Methods to study legionella transcriptome in vitro and in vivo.
Faucher, Sebastien P; Shuman, Howard A
2013-01-01
The study of transcriptome responses can provide insight into the regulatory pathways and genetic factors that contribute to a specific phenotype. For bacterial pathogens, it can identify putative new virulence systems and shed light on the mechanisms underlying the regulation of virulence factors. Microarrays have been previously used to study gene regulation in Legionella pneumophila. In the past few years a sharp reduction of the costs associated with microarray experiments together with the availability of relatively inexpensive custom-designed commercial microarrays has made microarray technology an accessible tool for the majority of researchers. Here we describe the methodologies to conduct microarray experiments from in vitro and in vivo samples.
Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco
2005-01-01
A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204
Bacterial identification and subtyping using DNA microarray and DNA sequencing.
Al-Khaldi, Sufian F; Mossoba, Magdi M; Allard, Marc M; Lienau, E Kurt; Brown, Eric D
2012-01-01
The era of fast and accurate discovery of biological sequence motifs in prokaryotic and eukaryotic cells is here. The co-evolution of direct genome sequencing and DNA microarray strategies not only will identify, isotype, and serotype pathogenic bacteria, but also it will aid in the discovery of new gene functions by detecting gene expressions in different diseases and environmental conditions. Microarray bacterial identification has made great advances in working with pure and mixed bacterial samples. The technological advances have moved beyond bacterial gene expression to include bacterial identification and isotyping. Application of new tools such as mid-infrared chemical imaging improves detection of hybridization in DNA microarrays. The research in this field is promising and future work will reveal the potential of infrared technology in bacterial identification. On the other hand, DNA sequencing by using 454 pyrosequencing is so cost effective that the promise of $1,000 per bacterial genome sequence is becoming a reality. Pyrosequencing technology is a simple to use technique that can produce accurate and quantitative analysis of DNA sequences with a great speed. The deposition of massive amounts of bacterial genomic information in databanks is creating fingerprint phylogenetic analysis that will ultimately replace several technologies such as Pulsed Field Gel Electrophoresis. In this chapter, we will review (1) the use of DNA microarray using fluorescence and infrared imaging detection for identification of pathogenic bacteria, and (2) use of pyrosequencing in DNA cluster analysis to fingerprint bacterial phylogenetic trees.
Comprehensive Census of Bacteria in Clean Rooms by Using DNA Microarray and Cloning Methods▿ †
La Duc, Myron T.; Osman, Shariff; Vaishampayan, Parag; Piceno, Yvette; Andersen, Gary; Spry, J. A.; Venkateswaran, Kasthuri
2009-01-01
A census of clean room surface-associated bacterial populations was derived from the results of both the cloning and sequencing of 16S rRNA genes and DNA microarray (PhyloChip) analyses. Samples from the Lockheed Martin Aeronautics Multiple Testing Facility (LMA-MTF), the Kennedy Space Center Payload Hazard and Servicing Facility (KSC-PHSF), and the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) clean rooms were collected during the various assembly phases of the Phoenix and Mars Science Laboratory (MSL) spacecraft. Clone library-derived analyses detected a larger bacterial diversity prior to the arrival of spacecraft hardware in these clean room facilities. PhyloChip results were in agreement with this trend but also unveiled the presence of anywhere from 9- to 70-fold more bacterial taxa than cloning approaches. Among the facilities sampled, the JPL-SAF (MSL mission) housed a significantly less diverse bacterial population than either the LMA-MTF or KSC-PHSF (Phoenix mission). Bacterial taxa known to thrive in arid conditions were frequently detected in MSL-associated JPL-SAF samples, whereas proteobacterial lineages dominated Phoenix-associated KSC-PHSF samples. Comprehensive bacterial censuses, such as that reported here, will help space-faring nations preemptively identify contaminant biomatter that may compromise extraterrestrial life detection experiments. The robust nature and high sensitivity of DNA microarray technologies should prove beneficial to a wide range of scientific, electronic, homeland security, medical, and pharmaceutical applications and to any other ventures with a vested interest in monitoring and controlling contamination in exceptionally clean environments. PMID:19700540
Comprehensive census of bacteria in clean rooms by using DNA microarray and cloning methods.
La Duc, Myron T; Osman, Shariff; Vaishampayan, Parag; Piceno, Yvette; Andersen, Gary; Spry, J A; Venkateswaran, Kasthuri
2009-10-01
A census of clean room surface-associated bacterial populations was derived from the results of both the cloning and sequencing of 16S rRNA genes and DNA microarray (PhyloChip) analyses. Samples from the Lockheed Martin Aeronautics Multiple Testing Facility (LMA-MTF), the Kennedy Space Center Payload Hazard and Servicing Facility (KSC-PHSF), and the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) clean rooms were collected during the various assembly phases of the Phoenix and Mars Science Laboratory (MSL) spacecraft. Clone library-derived analyses detected a larger bacterial diversity prior to the arrival of spacecraft hardware in these clean room facilities. PhyloChip results were in agreement with this trend but also unveiled the presence of anywhere from 9- to 70-fold more bacterial taxa than cloning approaches. Among the facilities sampled, the JPL-SAF (MSL mission) housed a significantly less diverse bacterial population than either the LMA-MTF or KSC-PHSF (Phoenix mission). Bacterial taxa known to thrive in arid conditions were frequently detected in MSL-associated JPL-SAF samples, whereas proteobacterial lineages dominated Phoenix-associated KSC-PHSF samples. Comprehensive bacterial censuses, such as that reported here, will help space-faring nations preemptively identify contaminant biomatter that may compromise extraterrestrial life detection experiments. The robust nature and high sensitivity of DNA microarray technologies should prove beneficial to a wide range of scientific, electronic, homeland security, medical, and pharmaceutical applications and to any other ventures with a vested interest in monitoring and controlling contamination in exceptionally clean environments.
Ranjbar, Reza; Behzadi, Payam; Najafi, Ali; Roudi, Raheleh
2017-01-01
A rapid, accurate, flexible and reliable diagnostic method may significantly decrease the costs of diagnosis and treatment. Designing an appropriate microarray chip reduces noises and probable biases in the final result. The aim of this study was to design and construct a DNA Microarray Chip for a rapid detection and identification of 10 important bacterial agents. In the present survey, 10 unique genomic regions relating to 10 pathogenic bacterial agents including Escherichia coli (E.coli), Shigella boydii, Sh.dysenteriae, Sh.flexneri, Sh.sonnei, Salmonella typhi, S.typhimurium, Brucella sp., Legionella pneumophila, and Vibrio cholera were selected for designing specific long oligo microarray probes. For this reason, the in-silico operations including utilization of the NCBI RefSeq database, Servers of PanSeq and Gview, AlleleID 7.7 and Oligo Analyzer 3.1 was done. On the other hand, the in-vitro part of the study comprised stages of robotic microarray chip probe spotting, bacterial DNAs extraction and DNA labeling, hybridization and microarray chip scanning. In wet lab section, different tools and apparatus such as Nexterion® Slide E, Qarray mini spotter, NimbleGen kit, TrayMix TM S4, and Innoscan 710 were used. A DNA microarray chip including 10 long oligo microarray probes was designed and constructed for detection and identification of 10 pathogenic bacteria. The DNA microarray chip was capable to identify all 10 bacterial agents tested simultaneously. The presence of a professional bioinformatician as a probe designer is needed to design appropriate multifunctional microarray probes to increase the accuracy of the outcomes.
Busti, Elena; Bordoni, Roberta; Castiglioni, Bianca; Monciardini, Paolo; Sosio, Margherita; Donadio, Stefano; Consolandi, Clarissa; Rossi Bernardi, Luigi; Battaglia, Cristina; De Bellis, Gianluca
2002-01-01
Background PCR amplification of bacterial 16S rRNA genes provides the most comprehensive and flexible means of sampling bacterial communities. Sequence analysis of these cloned fragments can provide a qualitative and quantitative insight of the microbial population under scrutiny although this approach is not suited to large-scale screenings. Other methods, such as denaturing gradient gel electrophoresis, heteroduplex or terminal restriction fragment analysis are rapid and therefore amenable to field-scale experiments. A very recent addition to these analytical tools is represented by microarray technology. Results Here we present our results using a Universal DNA Microarray approach as an analytical tool for bacterial discrimination. The proposed procedure is based on the properties of the DNA ligation reaction and requires the design of two probes specific for each target sequence. One oligo carries a fluorescent label and the other a unique sequence (cZipCode or complementary ZipCode) which identifies a ligation product. Ligated fragments, obtained in presence of a proper template (a PCR amplified fragment of the 16s rRNA gene) contain either the fluorescent label or the unique sequence and therefore are addressed to the location on the microarray where the ZipCode sequence has been spotted. Such an array is therefore "Universal" being unrelated to a specific molecular analysis. Here we present the design of probes specific for some groups of bacteria and their application to bacterial diagnostics. Conclusions The combined use of selective probes, ligation reaction and the Universal Array approach yielded an analytical procedure with a good power of discrimination among bacteria. PMID:12243651
Kalograiaki, Ioanna; Campanero-Rhodes, María A; Proverbio, Davide; Euba, Begoña; Garmendia, Junkal; Aastrup, Teodor; Solís, Dolores
2018-01-01
Bacterial surfaces are decorated with a diversity of carbohydrate structures that play important roles in the bacteria-host relationships. They may offer protection against host defense mechanisms, elicit strong antigenic responses, or serve as ligands for host receptors, including lectins of the innate immune system. Binding by these lectins may trigger defense responses or, alternatively, promote attachment, thereby enhancing infection. The outcome will depend on the particular bacterial surface landscape, which may substantially differ among species and strains. In this chapter, we describe two novel methods for exploring interactions directly on the bacterial surface, based on the generation of bacterial microarrays and quartz crystal microbalance (QCM) sensor chips. Bacterial microarrays enable profiling of accessible carbohydrate structures and screening of their recognition by host receptors, also providing information on binding avidity, while the QCM approach allows determination of binding affinity and kinetics. In both cases, the chief element is the use of entire bacterial cells, so that recognition of the bacterial glycan epitopes is explored in their natural environment. © 2018 Elsevier Inc. All rights reserved.
Parthasarathy, N; Saksena, R; Kováč, P; Deshazer, D; Peacock, S J; Wuthiekanun, V; Heine, H S; Friedlander, A M; Cote, C K; Welkos, S L; Adamovicz, J J; Bavari, S; Waag, D M
2008-11-03
We developed a microarray platform by immobilizing bacterial 'signature' carbohydrates onto epoxide modified glass slides. The carbohydrate microarray platform was probed with sera from non-melioidosis and melioidosis (Burkholderia pseudomallei) individuals. The platform was also probed with sera from rabbits vaccinated with Bacillus anthracis spores and Francisella tularensis bacteria. By employing this microarray platform, we were able to detect and differentiate B. pseudomallei, B. anthracis and F. tularensis antibodies in infected patients, and infected or vaccinated animals. These antibodies were absent in the sera of naïve test subjects. The advantages of the carbohydrate microarray technology over the traditional indirect hemagglutination and microagglutination tests for the serodiagnosis of melioidosis and tularemia are discussed. Furthermore, this array is a multiplex carbohydrate microarray for the detection of all three biothreat bacterial infections including melioidosis, anthrax and tularemia with one, multivalent device. The implication is that this technology could be expanded to include a wide array of infectious and biothreat agents.
Cooper, Moogega; La Duc, Myron T; Probst, Alexander; Vaishampayan, Parag; Stam, Christina; Benardini, James N; Piceno, Yvette M; Andersen, Gary L; Venkateswaran, Kasthuri
2011-08-01
A bacterial spore assay and a molecular DNA microarray method were compared for their ability to assess relative cleanliness in the context of bacterial abundance and diversity on spacecraft surfaces. Colony counts derived from the NASA standard spore assay were extremely low for spacecraft surfaces. However, the PhyloChip generation 3 (G3) DNA microarray resolved the genetic signatures of a highly diverse suite of microorganisms in the very same sample set. Samples completely devoid of cultivable spores were shown to harbor the DNA of more than 100 distinct microbial phylotypes. Furthermore, samples with higher numbers of cultivable spores did not necessarily give rise to a greater microbial diversity upon analysis with the DNA microarray. The findings of this study clearly demonstrated that there is not a statistically significant correlation between the cultivable spore counts obtained from a sample and the degree of bacterial diversity present. Based on these results, it can be stated that validated state-of-the-art molecular techniques, such as DNA microarrays, can be utilized in parallel with classical culture-based methods to further describe the cleanliness of spacecraft surfaces.
Parthasarathy, Narayanan; DeShazer, David; England, Marilyn; Waag, David M
2006-11-01
A polysaccharide microarray platform was prepared by immobilizing Burkholderia pseudomallei and Burkholderia mallei polysaccharides. This polysaccharide array was tested with success for detecting B. pseudomallei and B. mallei serum (human and animal) antibodies. The advantages of this microarray technology over the current serodiagnosis of the above bacterial infections were discussed.
Stannous Fluoride Effects on Gene Expression of Streptococcus mutans and Actinomyces viscosus.
Shi, Y; Li, R; White, D J; Biesbrock, A R
2018-02-01
A genome-wide transcriptional analysis was performed to elucidate the bacterial cellular response of Streptococcus mutans and Actinomyces viscosus to NaF and SnF 2 . The minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of SnF 2 were predetermined before microarray study. Gene expression profiling microarray experiments were carried out in the absence (control) and presence (experimental) of 10 ppm and 100 ppm Sn 2+ (in the form of SnF 2 ) and fluoride controls for 10-min exposures (4 biological replicates/treatment). These Sn 2+ levels and treatment time were chosen because they have been shown to slow bacterial growth of S. mutans (10 ppm) and A. viscosus (100 ppm) without affecting cell viability. All data generated by microarray experiments were analyzed with bioinformatics tools by applying the following criteria: 1) a q value should be ≤0.05, and 2) an absolute fold change in transcript level should be ≥1.5. Microarray results showed SnF 2 significantly inhibited several genes encoding enzymes of the galactose pathway upon a 10-min exposure versus a negative control: lacA and lacB (A and B subunits of the galactose-6-P isomerase), lacC (tagatose-6-P kinase), lacD (tagatose-1,6-bP adolase), galK (galactokinase), galT (galactose-1-phosphate uridylyltransferase), and galE (UDP-glucose 4-epimerase). A gene fruK encoding fructose-1-phosphate kinase in the fructose pathway was also significantly inhibited. Several genes encoding fructose/mannose-specific enzyme IIABC components in the phosphotransferase system (PTS) were also downregulated, as was ldh encoding lactate dehydrogenase, a key enzyme involved in lactic acid synthesis. SnF 2 downregulated the transcription of most key enzyme genes involved in the galactose pathway and also suppressed several key genes involved in the PTS, which transports sugars into the cell in the first step of glycolysis.
Assessing the cleanliness of surfaces: Innovative molecular approaches vs. standard spore assays
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cooper, M.; Duc, M.T. La; Probst, A.
2011-04-01
A bacterial spore assay and a molecular DNA microarray method were compared for their ability to assess relative cleanliness in the context of bacterial abundance and diversity on spacecraft surfaces. Colony counts derived from the NASA standard spore assay were extremely low for spacecraft surfaces. However, the PhyloChip generation 3 (G3) DNA microarray resolved the genetic signatures of a highly diverse suite of microorganisms in the very same sample set. Samples completely devoid of cultivable spores were shown to harbor the DNA of more than 100 distinct microbial phylotypes. Furthermore, samples with higher numbers of cultivable spores did not necessarilymore » give rise to a greater microbial diversity upon analysis with the DNA microarray. The findings of this study clearly demonstrated that there is not a statistically significant correlation between the cultivable spore counts obtained from a sample and the degree of bacterial diversity present. Based on these results, it can be stated that validated state-of-the-art molecular techniques, such as DNA microarrays, can be utilized in parallel with classical culture-based methods to further describe the cleanliness of spacecraft surfaces.« less
Analysis of sensitivity and rapid hybridization of a multiplexed Microbial Detection Microarray
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thissen, James B.; McLoughlin, Kevin; Gardner, Shea
Microarrays have proven to be useful in rapid detection of many viruses and bacteria. Pathogen detection microarrays have been used to diagnose viral and bacterial infections in clinical samples and to evaluate the safety of biological drug materials. A multiplexed version of the Lawrence Livermore Microbial Detection Array (LLMDA) was developed and evaluated with minimum detectable concentrations for pure unamplified DNA viruses, along with mixtures of viral and bacterial DNA subjected to different whole genome amplification protocols. In addition the performance of the array was tested when hybridization time was reduced from 17 h to 1 h. The LLMDA wasmore » able to detect unamplified vaccinia virus DNA at a concentration of 14 fM, or 100,000 genome copies in 12 μL of sample. With amplification, positive identification was made with only 100 genome copies of input material. When tested against human stool samples from patients with acute gastroenteritis, the microarray detected common gastroenteritis viral and bacterial infections such as rotavirus and E. coli. Accurate detection was found but with a 4-fold drop in sensitivity for a 1 h compared to a 17 h hybridization. The array detected 2 ng (equivalent concentration of 15.6 fM) of labeled DNA from a virus with 1 h hybridization without any amplification, and was able to identify the components of a mixture of viruses and bacteria at species and in some cases strain level resolution. Sensitivity improved by three orders of magnitude with random whole genome amplification prior to hybridization; for instance, the array detected a DNA virus with only 20 fg or 100 genome copies as input. This multiplexed microarray is an efficient tool to analyze clinical and environmental samples for the presence of multiple viral and bacterial pathogens rapidly.« less
Analysis of sensitivity and rapid hybridization of a multiplexed Microbial Detection Microarray
Thissen, James B.; McLoughlin, Kevin; Gardner, Shea; ...
2014-06-01
Microarrays have proven to be useful in rapid detection of many viruses and bacteria. Pathogen detection microarrays have been used to diagnose viral and bacterial infections in clinical samples and to evaluate the safety of biological drug materials. A multiplexed version of the Lawrence Livermore Microbial Detection Array (LLMDA) was developed and evaluated with minimum detectable concentrations for pure unamplified DNA viruses, along with mixtures of viral and bacterial DNA subjected to different whole genome amplification protocols. In addition the performance of the array was tested when hybridization time was reduced from 17 h to 1 h. The LLMDA wasmore » able to detect unamplified vaccinia virus DNA at a concentration of 14 fM, or 100,000 genome copies in 12 μL of sample. With amplification, positive identification was made with only 100 genome copies of input material. When tested against human stool samples from patients with acute gastroenteritis, the microarray detected common gastroenteritis viral and bacterial infections such as rotavirus and E. coli. Accurate detection was found but with a 4-fold drop in sensitivity for a 1 h compared to a 17 h hybridization. The array detected 2 ng (equivalent concentration of 15.6 fM) of labeled DNA from a virus with 1 h hybridization without any amplification, and was able to identify the components of a mixture of viruses and bacteria at species and in some cases strain level resolution. Sensitivity improved by three orders of magnitude with random whole genome amplification prior to hybridization; for instance, the array detected a DNA virus with only 20 fg or 100 genome copies as input. This multiplexed microarray is an efficient tool to analyze clinical and environmental samples for the presence of multiple viral and bacterial pathogens rapidly.« less
Sarmiento-Rubiano, Luz-Adriana; Berger, Bernard; Moine, Déborah; Zúñiga, Manuel; Pérez-Martínez, Gaspar; Yebra, María J
2010-09-17
Comparative genomic hybridization (CGH) constitutes a powerful tool for identification and characterization of bacterial strains. In this study we have applied this technique for the characterization of a number of Lactobacillus strains isolated from the intestinal content of rats fed with a diet supplemented with sorbitol. Phylogenetic analysis based on 16S rRNA gene, recA, pheS, pyrG and tuf sequences identified five bacterial strains isolated from the intestinal content of rats as belonging to the recently described Lactobacillus taiwanensis species. DNA-DNA hybridization experiments confirmed that these five strains are distinct but closely related to Lactobacillus johnsonii and Lactobacillus gasseri. A whole genome DNA microarray designed for the probiotic L. johnsonii strain NCC533 was used for CGH analysis of L. johnsonii ATCC 33200T, L. johnsonii BL261, L. gasseri ATCC 33323T and L. taiwanensis BL263. In these experiments, the fluorescence ratio distributions obtained with L. taiwanensis and L. gasseri showed characteristic inter-species profiles. The percentage of conserved L. johnsonii NCC533 genes was about 83% in the L. johnsonii strains comparisons and decreased to 51% and 47% for L. taiwanensis and L. gasseri, respectively. These results confirmed the separate status of L. taiwanensis from L. johnsonii at the level of species, and also that L. taiwanensis is closer to L. johnsonii than L. gasseri is to L. johnsonii. Conventional taxonomic analyses and microarray-based CGH analysis have been used for the identification and characterization of the newly species L. taiwanensis. The microarray-based CGH technology has been shown as a remarkable tool for the identification and fine discrimination between phylogenetically close species, and additionally provided insight into the adaptation of the strain L. taiwanensis BL263 to its ecological niche.
NASA Astrophysics Data System (ADS)
Bernardini, James Nicholas, III
An understanding of the microbiota within life support systems is essential for the prolonged presence of humans in space. This is because microbes may cause disease or induce biofouling and/or corrosion within spacecraft water systems. It is imperative that we develop effective high-throughput technologies for characterizing microbial populations that can eventually be used in the space environment. This dissertation describes testing and development of such methodologies, targeting both bacteria and viruses in water, and examines the bacterial and viral diversity within two spacecraft life support systems. The bacterial community of the International Space Station Internal Active Thermal Control System (IATCS) was examined using conventional culture-based and advanced molecular techniques including adenosine triphosphate (ATP) and Limulus Amebocyte Lysate (LAL) assays, direct microscopic examination, and analyses of 16S rRNA gene libraries from the community metagenome. The cultivable heterotrophs of the IATCS fluids ranged from below detection limit to 1.1x10 5/100 ml, and viable cells, measured by ATP, ranged from 1.4x10 3/100 ml to 7.7x105/100 ml. DNA extraction, cloning, sequencing, and bioinformatic analysis of the clones from 16S RNA gene libraries showed members of the firmicutes, alpha, beta, and gamma-proteobacteria to be present in the fluids. This persistent microbial bioburden and the presence of probable metal reducers, biofilm formers, and opportunistic pathogens illustrate the need for better characterization of bacterial communities present within spacecraft fluids. A new methodology was developed for detection of viruses in water using microarrays. Samples were concentrated by lyophilization, resuspended and filtered (0.22microm). Viral nucleic acids were then extracted, amplified, fluorescently labeled and hybridized onto a custom microarray with probes for ˜1000 known viruses. Numerous virus signatures were observed. Human Adenovirus C and Influenza A viruses were used to verify positive microarray hybridizations by quantitative polymerase chain reaction (PCR), reverse transcriptase PCR, and conventional PCR. Experiments were performed using municipal drinking water, IATCS fluids, and Shuttle drinking water. Thus, this dissertation describes what we believe is the first molecular analysis of the IATCS bacterial ecology and the first use and validation of a microarray-based assay for the detection of viral genetic signatures within drinking waters.
Chang, Ho-Won; Sung, Youlboong; Kim, Kyoung-Ho; Nam, Young-Do; Roh, Seong Woon; Kim, Min-Soo; Jeon, Che Ok; Bae, Jin-Woo
2008-08-15
A crucial problem in the use of previously developed genome-probing microarrays (GPM) has been the inability to use uncultivated bacterial genomes to take advantage of the high sensitivity and specificity of GPM in microbial detection and monitoring. We show here a method, digital multiple displacement amplification (MDA), to amplify and analyze various genomes obtained from single uncultivated bacterial cells. We used 15 genomes from key microbes involved in dichloromethane (DCM)-dechlorinating enrichment as microarray probes to uncover the bacterial population dynamics of samples without PCR amplification. Genomic DNA amplified from single cells originating from uncultured bacteria with 80.3-99.4% similarity to 16S rRNA genes of cultivated bacteria. The digital MDA-GPM method successfully monitored the dynamics of DCM-dechlorinating communities from different phases of enrichment status. Without a priori knowledge of microbial diversity, the digital MDA-GPM method could be designed to monitor most microbial populations in a given environmental sample.
BμG@Sbase—a microbial gene expression and comparative genomic database
Witney, Adam A.; Waldron, Denise E.; Brooks, Lucy A.; Tyler, Richard H.; Withers, Michael; Stoker, Neil G.; Wren, Brendan W.; Butcher, Philip D.; Hinds, Jason
2012-01-01
The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future. PMID:21948792
BμG@Sbase--a microbial gene expression and comparative genomic database.
Witney, Adam A; Waldron, Denise E; Brooks, Lucy A; Tyler, Richard H; Withers, Michael; Stoker, Neil G; Wren, Brendan W; Butcher, Philip D; Hinds, Jason
2012-01-01
The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future.
NASA Astrophysics Data System (ADS)
Vaishampayan, Parag; Osman, Shariff; Andersen, Gary; Venkateswaran, Kasthuri
2010-06-01
The bacterial diversity and comparative community structure of a clean room used for assembling the Phoenix spacecraft was characterized throughout the spacecraft assembly process by using 16S rRNA gene cloning/sequencing and DNA microarray (PhyloChip) technologies. Samples were collected from several locations of the clean room at three time points: before Phoenix's arrival (PHX-B), during hardware assembly (PHX-D), and after the spacecraft was removed for launch (PHX-A). Bacterial diversity comprised of all major bacterial phyla of PHX-B was found to be statistically different from PHX-D and PHX-A samples. Due to stringent cleaning and decontamination protocols during assembly, PHX-D bacterial diversity was dramatically reduced when compared to PHX-B and PHX-A samples. Comparative community analysis based on PhyloChip results revealed similar overall trends as were seen in clone libraries, but the high-density phylogenetic microarray detected larger diversity in all sampling events. The decrease in community complexity in PHX-D compared to PHX-B, and the subsequent recurrence of these organisms in PHX-A, speaks to the effectiveness of NASA cleaning protocols. However, the persistence of a subset of bacterial signatures throughout all spacecraft assembly phases underscores the need for continued refinement of sterilization technologies and the implementation of safeguards that monitor and inventory microbial contaminants.
Vaishampayan, Parag; Osman, Shariff; Andersen, Gary; Venkateswaran, Kasthuri
2010-06-01
The bacterial diversity and comparative community structure of a clean room used for assembling the Phoenix spacecraft was characterized throughout the spacecraft assembly process by using 16S rRNA gene cloning/sequencing and DNA microarray (PhyloChip) technologies. Samples were collected from several locations of the clean room at three time points: before Phoenix's arrival (PHX-B), during hardware assembly (PHX-D), and after the spacecraft was removed for launch (PHX-A). Bacterial diversity comprised of all major bacterial phyla of PHX-B was found to be statistically different from PHX-D and PHX-A samples. Due to stringent cleaning and decontamination protocols during assembly, PHX-D bacterial diversity was dramatically reduced when compared to PHX-B and PHX-A samples. Comparative community analysis based on PhyloChip results revealed similar overall trends as were seen in clone libraries, but the high-density phylogenetic microarray detected larger diversity in all sampling events. The decrease in community complexity in PHX-D compared to PHX-B, and the subsequent recurrence of these organisms in PHX-A, speaks to the effectiveness of NASA cleaning protocols. However, the persistence of a subset of bacterial signatures throughout all spacecraft assembly phases underscores the need for continued refinement of sterilization technologies and the implementation of safeguards that monitor and inventory microbial contaminants.
Shin, Hwa Hui; Seo, Jeong Hyun; Kim, Chang Sup; Hwang, Byeong Hee; Cha, Hyung Joon
2016-05-15
Life-threatening diarrheal cholera is usually caused by water or food contaminated with cholera toxin-producing Vibrio cholerae. For the prevention and surveillance of cholera, it is crucial to rapidly and precisely detect and identify the etiological causes, such as V. cholerae and/or its toxin. In the present work, we propose the use of a hybrid double biomolecular marker (DBM) microarray containing 16S rRNA-based DNA capture probe to genotypically identify V. cholerae and GM1 pentasaccharide capture probe to phenotypically detect cholera toxin. We employed a simple sample preparation method to directly obtain genomic DNA and secreted cholera toxin as target materials from bacterial cells. By utilizing the constructed DBM microarray and prepared samples, V. cholerae and cholera toxin were detected successfully, selectively, and simultaneously; the DBM microarray was able to analyze the pathogenicity of the identified V. cholerae regardless of whether the bacteria produces toxin. Therefore, our proposed DBM microarray is a new effective platform for identifying bacteria and analyzing bacterial pathogenicity simultaneously. Copyright © 2015 Elsevier B.V. All rights reserved.
Shi, Xiang Yang; Dumenyo, C Korsi; Hernandez-Martinez, Rufina; Azad, Hamid; Cooksey, Donald A
2007-11-01
Many virulence genes in plant bacterial pathogens are coordinately regulated by "global" regulatory genes. Conducting DNA microarray analysis of bacterial mutants of such genes, compared with the wild type, can help to refine the list of genes that may contribute to virulence in bacterial pathogens. The regulatory gene algU, with roles in stress response and regulation of the biosynthesis of the exopolysaccharide alginate in Pseudomonas aeruginosa and many other bacteria, has been extensively studied. The role of algU in Xylella fastidiosa, the cause of Pierce's disease of grapevines, was analyzed by mutation and whole-genome microarray analysis to define its involvement in aggregation, biofilm formation, and virulence. In this study, an algU::nptII mutant had reduced cell-cell aggregation, attachment, and biofilm formation and lower virulence in grapevines. Microarray analysis showed that 42 genes had significantly lower expression in the algU::nptII mutant than in the wild type. Among these are several genes that could contribute to cell aggregation and biofilm formation, as well as other physiological processes such as virulence, competition, and survival.
2012-01-01
Background Microbial anaerobic digestion (AD) is used as a waste treatment process to degrade complex organic compounds into methane. The archaeal and bacterial taxa involved in AD are well known, whereas composition of the fungal community in the process has been less studied. The present study aimed to reveal the composition of archaeal, bacterial and fungal communities in response to increasing organic loading in mesophilic and thermophilic AD processes by applying 454 amplicon sequencing technology. Furthermore, a DNA microarray method was evaluated in order to develop a tool for monitoring the microbiological status of AD. Results The 454 sequencing showed that the diversity and number of bacterial taxa decreased with increasing organic load, while archaeal i.e. methanogenic taxa remained more constant. The number and diversity of fungal taxa increased during the process and varied less in composition with process temperature than bacterial and archaeal taxa, even though the fungal diversity increased with temperature as well. Evaluation of the microarray using AD sample DNA showed correlation of signal intensities with sequence read numbers of corresponding target groups. The sensitivity of the test was found to be about 1%. Conclusions The fungal community survives in anoxic conditions and grows with increasing organic loading, suggesting that Fungi may contribute to the digestion by metabolising organic nutrients for bacterial and methanogenic groups. The microarray proof of principle tests suggest that the method has the potential for semiquantitative detection of target microbial groups given that comprehensive sequence data is available for probe design. PMID:22727142
Inoue, Daisuke; Hinoura, Takuji; Suzuki, Noriko; Pang, Junqin; Malla, Rabin; Shrestha, Sadhana; Chapagain, Saroj Kumar; Matsuzawa, Hiroaki; Nakamura, Takashi; Tanaka, Yasuhiro; Ike, Michihiko; Nishida, Kei; Sei, Kazunari
2015-01-01
Because of heavy dependence on groundwater for drinking water and other domestic use, microbial contamination of groundwater is a serious problem in the Kathmandu Valley, Nepal. This study investigated comprehensively the occurrence of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley by applying DNA microarray analysis targeting 941 pathogenic bacterial species/groups. Water quality measurements found significant coliform (fecal) contamination in 10 of the 11 investigated groundwater samples and significant nitrogen contamination in some samples. The results of DNA microarray analysis revealed the presence of 1-37 pathogen species/groups, including 1-27 biosafety level 2 ones, in 9 of the 11 groundwater samples. While the detected pathogens included several feces- and animal-related ones, those belonging to Legionella and Arthrobacter, which were considered not to be directly associated with feces, were detected prevalently. This study could provide a rough picture of overall pathogenic bacterial contamination in the Kathmandu Valley, and demonstrated the usefulness of DNA microarray analysis as a comprehensive screening tool of a wide variety of pathogenic bacteria.
NASA Astrophysics Data System (ADS)
Greef, Charles; Petropavlovskikh, Viatcheslav; Nilsen, Oyvind; Khattatov, Boris; Plam, Mikhail; Gardner, Patrick; Hall, John
2008-04-01
Small non-coding RNA sequences have recently been discovered as unique identifiers of certain bacterial species, raising the possibility that they can be used as highly specific Biowarfare Agent detection markers in automated field deployable integrated detection systems. Because they are present in high abundance they could allow genomic based bacterial species identification without the need for pre-assay amplification. Further, a direct detection method would obviate the need for chemical labeling, enabling a rapid, efficient, high sensitivity mechanism for bacterial detection. Surface Plasmon Resonance enhanced Common Path Interferometry (SPR-CPI) is a potentially market disruptive, high sensitivity dual technology that allows real-time direct multiplex measurement of biomolecule interactions, including small molecules, nucleic acids, proteins, and microbes. SPR-CPI measures differences in phase shift of reflected S and P polarized light under Total Internal Reflection (TIR) conditions at a surface, caused by changes in refractive index induced by biomolecular interactions within the evanescent field at the TIR interface. The measurement is performed on a microarray of discrete 2-dimensional areas functionalized with biomolecule capture reagents, allowing simultaneous measurement of up to 100 separate analytes. The optical beam encompasses the entire microarray, allowing a solid state detector system with no scanning requirement. Output consists of simultaneous voltage measurements proportional to the phase differences resulting from the refractive index changes from each microarray feature, and is automatically processed and displayed graphically or delivered to a decision making algorithm, enabling a fully automatic detection system capable of rapid detection and quantification of small nucleic acids at extremely sensitive levels. Proof-of-concept experiments on model systems and cell culture samples have demonstrated utility of the system, and efforts are in progress for full development and deployment of the device. The technology has broad applicability as a universal detection platform for BWA detection, medical diagnostics, and drug discovery research, and represents a new class of instrumentation as a rapid, high sensitivity, label-free methodology.
A microarray immunoassay for simultaneous detection of proteins and bacteria
NASA Technical Reports Server (NTRS)
Delehanty, James B.; Ligler, Frances S.
2002-01-01
We report the development and characterization of an antibody microarray biosensor for the rapid detection of both protein and bacterial analytes under flow conditions. Using a noncontact microarray printer, biotinylated capture antibodies were immobilized at discrete locations on the surface of an avidin-coated glass microscope slide. Preservation of capture antibody function during the deposition process was accomplished with the use of a low-salt buffer containing sucrose and bovine serum albumin. The slide was fitted with a six-channel flow module that conducted analyte-containing solutions over the array of capture antibody microspots. Detection of bound analyte was subsequently achieved using fluorescent tracer antibodies. The pattern of fluorescent complexes was interrogated using a scanning confocal microscope equipped with a 635-nm laser. This microarray system was employed to detect protein and bacterial analytes both individually and in samples containing mixtures of analytes. Assays were completed in 15 min, and detection of cholera toxin, staphylococcal enterotoxin B, ricin, and Bacillus globigii was demonstrated at levels as low as 8 ng/mL, 4 ng/mL, 10 ng/mL, and 6.2 x 10(4) cfu/mL, respectively. The assays presented here are very fast, as compared to previously published methods for measuring antibody-antigen interactions using microarrays (minutes versus hours).
Development of a Digital Microarray with Interferometric Reflectance Imaging
NASA Astrophysics Data System (ADS)
Sevenler, Derin
This dissertation describes a new type of molecular assay for nucleic acids and proteins. We call this technique a digital microarray since it is conceptually similar to conventional fluorescence microarrays, yet it performs enumerative ('digital') counting of the number captured molecules. Digital microarrays are approximately 10,000-fold more sensitive than fluorescence microarrays, yet maintain all of the strengths of the platform including low cost and high multiplexing (i.e., many different tests on the same sample simultaneously). Digital microarrays use gold nanorods to label the captured target molecules. Each gold nanorod on the array is individually detected based on its light scattering, with an interferometric microscopy technique called SP-IRIS. Our optimized high-throughput version of SP-IRIS is able to scan a typical array of 500 spots in less than 10 minutes. Digital DNA microarrays may have utility in applications where sequencing is prohibitively expensive or slow. As an example, we describe a digital microarray assay for gene expression markers of bacterial drug resistance.
2010-01-01
Background Comparative genomic hybridization (CGH) constitutes a powerful tool for identification and characterization of bacterial strains. In this study we have applied this technique for the characterization of a number of Lactobacillus strains isolated from the intestinal content of rats fed with a diet supplemented with sorbitol. Results Phylogenetic analysis based on 16S rRNA gene, recA, pheS, pyrG and tuf sequences identified five bacterial strains isolated from the intestinal content of rats as belonging to the recently described Lactobacillus taiwanensis species. DNA-DNA hybridization experiments confirmed that these five strains are distinct but closely related to Lactobacillus johnsonii and Lactobacillus gasseri. A whole genome DNA microarray designed for the probiotic L. johnsonii strain NCC533 was used for CGH analysis of L. johnsonii ATCC 33200T, L. johnsonii BL261, L. gasseri ATCC 33323T and L. taiwanensis BL263. In these experiments, the fluorescence ratio distributions obtained with L. taiwanensis and L. gasseri showed characteristic inter-species profiles. The percentage of conserved L. johnsonii NCC533 genes was about 83% in the L. johnsonii strains comparisons and decreased to 51% and 47% for L. taiwanensis and L. gasseri, respectively. These results confirmed the separate status of L. taiwanensis from L. johnsonii at the level of species, and also that L. taiwanensis is closer to L. johnsonii than L. gasseri is to L. johnsonii. Conclusion Conventional taxonomic analyses and microarray-based CGH analysis have been used for the identification and characterization of the newly species L. taiwanensis. The microarray-based CGH technology has been shown as a remarkable tool for the identification and fine discrimination between phylogenetically close species, and additionally provided insight into the adaptation of the strain L. taiwanensis BL263 to its ecological niche. PMID:20849602
Importing MAGE-ML format microarray data into BioConductor.
Durinck, Steffen; Allemeersch, Joke; Carey, Vincent J; Moreau, Yves; De Moor, Bart
2004-12-12
The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. http://www.bioconductor.org. Open Source.
Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.; DeSantis, Todd Z.; Gray, Michael A.; Zawada, David G.; Andersen, Gary L.
2013-01-01
Coral disease is a global problem. Diseases are typically named or described based on macroscopic changes, but broad signs of coral distress such as tissue loss or discoloration are unlikely to be specific to a particular pathogen. For example, there appear to be multiple diseases that manifest the rapid tissue loss that characterizes ‘white plague.’ PhyloChip™ G3 microarrays were used to compare the bacterial community composition of both healthy and white plague-like diseased corals. Samples of lobed star coral (Orbicella annularis, formerly of the genus Montastraea [1]) were collected from two geographically distinct areas, Dry Tortugas National Park and Virgin Islands National Park, to determine if there were biogeographic differences between the diseases. In fact, all diseased samples clustered together, however there was no consistent link to Aurantimonas coralicida, which has been described as the causative agent of white plague type II. The microarrays revealed a large amount of bacterial heterogeneity within the healthy corals and less diversity in the diseased corals. Gram-positive bacterial groups (Actinobacteria, Firmicutes) comprised a greater proportion of the operational taxonomic units (OTUs) unique to healthy samples. Diseased samples were enriched in OTUs from the families Corynebacteriaceae, Lachnospiraceae, Rhodobacteraceae, and Streptococcaceae. Much previous coral disease work has used clone libraries, which seem to be methodologically biased toward recovery of Gram-negative bacterial sequences and may therefore have missed the importance of Gram-positive groups. The PhyloChip™ data presented here provide a broader characterization of the bacterial community changes that occur within Orbicella annularis during the shift from a healthy to diseased state.
Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.; DeSantis, Todd Z.; Gray, Michael A.; Zawada, David G.; Andersen, Gary L.
2013-01-01
Coral disease is a global problem. Diseases are typically named or described based on macroscopic changes, but broad signs of coral distress such as tissue loss or discoloration are unlikely to be specific to a particular pathogen. For example, there appear to be multiple diseases that manifest the rapid tissue loss that characterizes ‘white plague.’ PhyloChip™ G3 microarrays were used to compare the bacterial community composition of both healthy and white plague-like diseased corals. Samples of lobed star coral (Orbicella annularis, formerly of the genus Montastraea [1]) were collected from two geographically distinct areas, Dry Tortugas National Park and Virgin Islands National Park, to determine if there were biogeographic differences between the diseases. In fact, all diseased samples clustered together, however there was no consistent link to Aurantimonas coralicida, which has been described as the causative agent of white plague type II. The microarrays revealed a large amount of bacterial heterogeneity within the healthy corals and less diversity in the diseased corals. Gram-positive bacterial groups (Actinobacteria, Firmicutes) comprised a greater proportion of the operational taxonomic units (OTUs) unique to healthy samples. Diseased samples were enriched in OTUs from the families Corynebacteriaceae, Lachnospiraceae, Rhodobacteraceae, and Streptococcaceae. Much previous coral disease work has used clone libraries, which seem to be methodologically biased toward recovery of Gram-negative bacterial sequences and may therefore have missed the importance of Gram-positive groups. The PhyloChip™data presented here provide a broader characterization of the bacterial community changes that occur within Orbicella annularis during the shift from a healthy to diseased state. PMID:24278181
Broad spectrum microarray for fingerprint-based bacterial species identification
2010-01-01
Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups. PMID:20163710
Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco
2006-01-01
We developed MicroGen, a multi-database Web based system for managing all the information characterizing spotted microarray experiments. It supports information gathering and storing according to the Minimum Information About Microarray Experiments (MIAME) standard. It also allows easy sharing of information and data among all multidisciplinary actors involved in spotted microarray experiments. PMID:17238488
NASA Astrophysics Data System (ADS)
Duan, Liang; Song, Yonghui; Xia, Siqing; Hermanowicz, Slawomir W.
2010-11-01
This study compared the whole composition of microbial communities in continuous-flow (MBR) and batch-fed (discontinuous) (MSBR) aerobic membrane bioreactors using high-density universal 16S rRNA Microarray. The array includes 506,944 probes targeted to 8935 clusters in 16S rRNA gene sequences. The Microarray results showed that both MBR and MSBR had high microbial diversity. 1126 and 1002 bacterial subfamilies were detected and can separate as 37 and 32 phyla in MBR and MSBR, respectively. Proteobacteria was the predominant phylum, 703 and 597 subfamilies were found in two systems, which constituted 62.4% and 59.6% of the whole bacteria. Gamma- and Alpha-were the dominant classes in Proteobacteria. It occupied 38.1% and 26.3%, 31.2% and 39.2% for MBR and MSBR, respectively. Bacteroidetes, Firmicutes and Actinobacteria were the subdominant groups, occupying around 9.4% and 7.6%, 6.1% and 6.5%, 6.0% and 9.0% of the total bacteria in two reactors. Some bacterial groups such as Acidobacteria, Chloroflexi, Cyanobacteria, Verrucomicrobia and Spirochaetes also found more than 15 subfamilies. All the results indicated that the MBR system had more bacteria community diversity than MSBR's. Moreover, it was very interested that MBR and MSBR had almost the same bacterial composition except Enterobacteriaceae. 63 OTUs of Enterobacteriaceae were detected in MBR, while just 10 OTUs were found in MSBR. That's one of the reasons leading to the difference of the bacterial diversity between two bioreactors.
Boltaña, Sebastian; Castellana, Barbara; Goetz, Giles; Tort, Lluis; Teles, Mariana; Mulero, Victor; Novoa, Beatriz; Figueras, Antonio; Goetz, Frederick W; Gallardo-Escarate, Cristian; Planas, Josep V; Mackenzie, Simon
2017-02-03
This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ) to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST) from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS) and peptidoglycan (PGN)). Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO) showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs), carrier proteins/membrane transport (approximately 15%), effectors/modulators and cell communication (approximately 11%), nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5%) and intracellular transducers/signal transduction (approximately 5%). Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ) that provides a platform enriched for the study of gene expression in S. aurata with an emphasis upon immunity and the immune response.
Friedrich, Torben; Rahmann, Sven; Weigel, Wilfried; Rabsch, Wolfgang; Fruth, Angelika; Ron, Eliora; Gunzer, Florian; Dandekar, Thomas; Hacker, Jörg; Müller, Tobias; Dobrindt, Ulrich
2010-10-21
The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes. Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.
Analysis of apple (Malus) responses to bacterial pathogens using an oligo microarray
USDA-ARS?s Scientific Manuscript database
Fire blight is a devastating disease of apple (Malus x domestica) caused by the bacterial pathogen Erwinia amylovora (Ea). When infiltrated into host leaves, Ea induces reactions similar to a hypersensitive response (HR). Type III (T3SS) associated effectors, especially DspA/E, are suspected to ha...
A biomimetic algorithm for the improved detection of microarray features
NASA Astrophysics Data System (ADS)
Nicolau, Dan V., Jr.; Nicolau, Dan V.; Maini, Philip K.
2007-02-01
One the major difficulties of microarray technology relate to the processing of large and - importantly - error-loaded images of the dots on the chip surface. Whatever the source of these errors, those obtained in the first stage of data acquisition - segmentation - are passed down to the subsequent processes, with deleterious results. As it has been demonstrated recently that biological systems have evolved algorithms that are mathematically efficient, this contribution attempts to test an algorithm that mimics a bacterial-"patented" algorithm for the search of available space and nutrients to find, "zero-in" and eventually delimitate the features existent on the microarray surface.
Liu, Jiabin; Behrens, Timothy W.; Kearney, John F.
2014-01-01
Marginal Zone (MZ) B cells play an important role in the clearance of blood-borne bacterial infections via rapid T-independent IgM responses. We have previously demonstrated that MZ B cells respond rapidly and robustly to bacterial particulates. To determine the MZ-specific genes that are expressed to allow for this response, MZ and Follicular (FO) B cells were sort-purified and analyzed via DNA microarray analysis. We identified 181 genes that were significantly different between the two B cell populations. 99 genes were more highly expressed in MZ B cells while 82 genes were more highly expressed in FO B cells. To further understand the molecular mechanisms by which MZ B cells respond so rapidly to bacterial challenge, idiotype positive and negative MZ B cells were sort-purified before (0 hour) or after (1 hour) i.v. immunization with heat killed Streptococcus pneumoniae, R36A, and analyzed via DNA microarray analysis. We identified genes specifically up regulated or down regulated at 1 hour following immunization in the idiotype positive MZ B cells. These results give insight into the gene expression pattern in resting MZ vs. FO B cells and the specific regulation of gene expression in antigen-specific MZ B cells following interaction with antigen. PMID:18453586
Peptidoglycan microarray as a novel tool to explore protein-ligand recognition.
Wang, Ning; Hirata, Akiyoshi; Nokihara, Kiyoshi; Fukase, Koichi; Fujimoto, Yukari
2016-11-04
Peptidoglycan is a giant bag-shaped molecule essential for bacterial cell shape and resistance to osmotic stresses. The activity of a large number of bacterial surface proteins involved in cell growth and division requires binding to this macromolecule. Recognition of peptidoglycan by immune effectors is also crucial for the establishment of the immune response against pathogens. The availability of pure and chemically defined peptidoglycan fragments is a major technical bottleneck that has precluded systematic studies of the mechanisms underpinning protein-mediated peptidoglycan recognition. Here, we report a microarray strategy suitable to carry out comprehensive studies to characterize proteins-peptidoglycan interactions. We describe a method to introduce a functional group on peptidoglycan fragments allowing their stable immobilization on amorphous carbon chip plates to minimize nonspecific binding. Such peptidoglycan microarrays were used with a model peptidoglycan binding protein-the human peptidoglycan recognition protein-S (hPGRP-S). We propose that this strategy could be implemented to carry out high-throughput analyses to study peptidoglycan binding proteins. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 422-429, 2016. © 2016 Wiley Periodicals, Inc.
Draghici, Sorin; Tarca, Adi L; Yu, Longfei; Ethier, Stephen; Romero, Roberto
2008-03-01
The BioArray Software Environment (BASE) is a very popular MIAME-compliant, web-based microarray data repository. However in BASE, like in most other microarray data repositories, the experiment annotation and raw data uploading can be very timeconsuming, especially for large microarray experiments. We developed KUTE (Karmanos Universal daTabase for microarray Experiments), as a plug-in for BASE 2.0 that addresses these issues. KUTE provides an automatic experiment annotation feature and a completely redesigned data work-flow that dramatically reduce the human-computer interaction time. For instance, in BASE 2.0 a typical Affymetrix experiment involving 100 arrays required 4 h 30 min of user interaction time forexperiment annotation, and 45 min for data upload/download. In contrast, for the same experiment, KUTE required only 28 min of user interaction time for experiment annotation, and 3.3 min for data upload/download. http://vortex.cs.wayne.edu/kute/index.html.
Dijkstra, Camelia E.; Larkin, Oliver J.; Anthony, Paul; Davey, Michael R.; Eaves, Laurence; Rees, Catherine E. D.; Hill, Richard J. A.
2011-01-01
Diamagnetic levitation is a technique that uses a strong, spatially varying magnetic field to reproduce aspects of weightlessness, on the Earth. We used a superconducting magnet to levitate growing bacterial cultures for up to 18 h, to determine the effect of diamagnetic levitation on all phases of the bacterial growth cycle. We find that diamagnetic levitation increases the rate of population growth in a liquid culture and reduces the sedimentation rate of the cells. Further experiments and microarray gene analysis show that the increase in growth rate is owing to enhanced oxygen availability. We also demonstrate that the magnetic field that levitates the cells also induces convective stirring in the liquid. We present a simple theoretical model, showing how the paramagnetic force on dissolved oxygen can cause convection during the aerobic phases of bacterial growth. We propose that this convection enhances oxygen availability by transporting oxygen around the liquid culture. Since this process results from the strong magnetic field, it is not present in other weightless environments, e.g. in Earth orbit. Hence, these results are of significance and timely to researchers considering the use of diamagnetic levitation to explore effects of weightlessness on living organisms and on physical phenomena. PMID:20667843
Dijkstra, Camelia E; Larkin, Oliver J; Anthony, Paul; Davey, Michael R; Eaves, Laurence; Rees, Catherine E D; Hill, Richard J A
2011-03-06
Diamagnetic levitation is a technique that uses a strong, spatially varying magnetic field to reproduce aspects of weightlessness, on the Earth. We used a superconducting magnet to levitate growing bacterial cultures for up to 18 h, to determine the effect of diamagnetic levitation on all phases of the bacterial growth cycle. We find that diamagnetic levitation increases the rate of population growth in a liquid culture and reduces the sedimentation rate of the cells. Further experiments and microarray gene analysis show that the increase in growth rate is owing to enhanced oxygen availability. We also demonstrate that the magnetic field that levitates the cells also induces convective stirring in the liquid. We present a simple theoretical model, showing how the paramagnetic force on dissolved oxygen can cause convection during the aerobic phases of bacterial growth. We propose that this convection enhances oxygen availability by transporting oxygen around the liquid culture. Since this process results from the strong magnetic field, it is not present in other weightless environments, e.g. in Earth orbit. Hence, these results are of significance and timely to researchers considering the use of diamagnetic levitation to explore effects of weightlessness on living organisms and on physical phenomena.
Burgarella, Sarah; Cattaneo, Dario; Pinciroli, Francesco; Masseroli, Marco
2005-12-01
Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results. We developed MicroGen, a web system for managing information and workflow in the production pipeline of spotted microarray experiments. It is constituted of a core multi-database system able to store all data completely characterizing different spotted microarray experiments according to the Minimum Information About Microarray Experiments (MIAME) standard, and of an intuitive and user-friendly web interface able to support the collaborative work required among multidisciplinary actors and roles involved in spotted microarray experiment production. MicroGen supports six types of user roles: the researcher who designs and requests the experiment, the spotting operator, the hybridisation operator, the image processing operator, the system administrator, and the generic public user who can access the unrestricted part of the system to get information about MicroGen services. MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production.
Split-plot microarray experiments: issues of design, power and sample size.
Tsai, Pi-Wen; Lee, Mei-Ling Ting
2005-01-01
This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.
ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.
Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B
2016-01-01
Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.
Soil microbial community successional patterns during forest ecosystem restoration.
Banning, Natasha C; Gleeson, Deirdre B; Grigg, Andrew H; Grant, Carl D; Andersen, Gary L; Brodie, Eoin L; Murphy, D V
2011-09-01
Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables.
Soil Microbial Community Successional Patterns during Forest Ecosystem Restoration ▿†
Banning, Natasha C.; Gleeson, Deirdre B.; Grigg, Andrew H.; Grant, Carl D.; Andersen, Gary L.; Brodie, Eoin L.; Murphy, D. V.
2011-01-01
Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables. PMID:21724890
DNA Microarray for Detection of Macrolide Resistance Genes
Cassone, Marco; D'Andrea, Marco M.; Iannelli, Francesco; Oggioni, Marco R.; Rossolini, Gian Maria; Pozzi, Gianni
2006-01-01
A DNA microarray was developed to detect bacterial genes conferring resistance to macrolides and related antibiotics. A database containing 65 nonredundant genes selected from publicly available DNA sequences was constructed and used to design 100 oligonucleotide probes that could specifically detect and discriminate all 65 genes. Probes were spotted on a glass slide, and the array was reacted with DNA templates extracted from 20 reference strains of eight different bacterial species (Streptococcus pneumoniae, Streptococcus pyogenes, Enterococcus faecalis, Enterococcus faecium, Staphylococcus aureus, Staphylococcus haemolyticus, Escherichia coli, and Bacteroides fragilis) known to harbor 29 different macrolide resistance genes. Hybridization results showed that probes reacted with, and only with, the expected DNA templates and allowed discovery of three unexpected genes, including msr(SA) in B. fragilis, an efflux gene that has not yet been described for gram-negative bacteria. PMID:16723563
Smith, Maria W.; Herfort, Lydie; Tyrol, Kaitlin; Suciu, Dominic; Campbell, Victoria; Crump, Byron C.; Peterson, Tawnya D.; Zuber, Peter; Baptista, Antonio M.; Simon, Holly M.
2010-01-01
Through their metabolic activities, microbial populations mediate the impact of high gradient regions on ecological function and productivity of the highly dynamic Columbia River coastal margin (CRCM). A 2226-probe oligonucleotide DNA microarray was developed to investigate expression patterns for microbial genes involved in nitrogen and carbon metabolism in the CRCM. Initial experiments with the environmental microarrays were directed toward validation of the platform and yielded high reproducibility in multiple tests. Bioinformatic and experimental validation also indicated that >85% of the microarray probes were specific for their corresponding target genes and for a few homologs within the same microbial family. The validated probe set was used to query gene expression responses by microbial assemblages to environmental variability. Sixty-four samples from the river, estuary, plume, and adjacent ocean were collected in different seasons and analyzed to correlate the measured variability in chemical, physical and biological water parameters to differences in global gene expression profiles. The method produced robust seasonal profiles corresponding to pre-freshet spring (April) and late summer (August). Overall relative gene expression was high in both seasons and was consistent with high microbial abundance measured by total RNA, heterotrophic bacterial production, and chlorophyll a. Both seasonal patterns involved large numbers of genes that were highly expressed relative to background, yet each produced very different gene expression profiles. April patterns revealed high differential gene expression in the coastal margin samples (estuary, plume and adjacent ocean) relative to freshwater, while little differential gene expression was observed along the river-to-ocean transition in August. Microbial gene expression profiles appeared to relate, in part, to seasonal differences in nutrient availability and potential resource competition. Furthermore, our results suggest that highly-active particle-attached microbiota in the Columbia River water column may perform dissimilatory nitrate reduction (both dentrification and DNRA) within anoxic particle microniches. PMID:20967204
Where statistics and molecular microarray experiments biology meet.
Kelmansky, Diana M
2013-01-01
This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed.
A new normalizing algorithm for BAC CGH arrays with quality control metrics.
Miecznikowski, Jeffrey C; Gaile, Daniel P; Liu, Song; Shepherd, Lori; Nowak, Norma
2011-01-01
The main focus in pin-tip (or print-tip) microarray analysis is determining which probes, genes, or oligonucleotides are differentially expressed. Specifically in array comparative genomic hybridization (aCGH) experiments, researchers search for chromosomal imbalances in the genome. To model this data, scientists apply statistical methods to the structure of the experiment and assume that the data consist of the signal plus random noise. In this paper we propose "SmoothArray", a new method to preprocess comparative genomic hybridization (CGH) bacterial artificial chromosome (BAC) arrays and we show the effects on a cancer dataset. As part of our R software package "aCGHplus," this freely available algorithm removes the variation due to the intensity effects, pin/print-tip, the spatial location on the microarray chip, and the relative location from the well plate. removal of this variation improves the downstream analysis and subsequent inferences made on the data. Further, we present measures to evaluate the quality of the dataset according to the arrayer pins, 384-well plates, plate rows, and plate columns. We compare our method against competing methods using several metrics to measure the biological signal. With this novel normalization algorithm and quality control measures, the user can improve their inferences on datasets and pinpoint problems that may arise in their BAC aCGH technology.
Design of microarray experiments for genetical genomics studies.
Bueno Filho, Júlio S S; Gilmour, Steven G; Rosa, Guilherme J M
2006-10-01
Microarray experiments have been used recently in genetical genomics studies, as an additional tool to understand the genetic mechanisms governing variation in complex traits, such as for estimating heritabilities of mRNA transcript abundances, for mapping expression quantitative trait loci, and for inferring regulatory networks controlling gene expression. Several articles on the design of microarray experiments discuss situations in which treatment effects are assumed fixed and without any structure. In the case of two-color microarray platforms, several authors have studied reference and circular designs. Here, we discuss the optimal design of microarray experiments whose goals refer to specific genetic questions. Some examples are used to illustrate the choice of a design for comparing fixed, structured treatments, such as genotypic groups. Experiments targeting single genes or chromosomic regions (such as with transgene research) or multiple epistatic loci (such as within a selective phenotyping context) are discussed. In addition, microarray experiments in which treatments refer to families or to subjects (within family structures or complex pedigrees) are presented. In these cases treatments are more appropriately considered to be random effects, with specific covariance structures, in which the genetic goals relate to the estimation of genetic variances and the heritability of transcriptional abundances.
Calibration and analysis of genome-based models for microbial ecology.
Louca, Stilianos; Doebeli, Michael
2015-10-16
Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.
Homogeneous versus heterogeneous probes for microbial ecological microarrays.
Bae, Jin-Woo; Park, Yong-Ha
2006-07-01
Microbial ecological microarrays have been developed for investigating the composition and functions of microorganism communities in environmental niches. These arrays include microbial identification microarrays, which use oligonucleotides, gene fragments or microbial genomes as probes. In this article, the advantages and disadvantages of each type of probe are reviewed. Oligonucleotide probes are currently useful for probing uncultivated bacteria that are not amenable to gene fragment probing, whereas the functional gene fragments amplified randomly from microbial genomes require phylogenetic and hierarchical categorization before use as microbial identification probes, despite their high resolution for both specificity and sensitivity. Until more bacteria are sequenced and gene fragment probes are thoroughly validated, heterogeneous bacterial genome probes will provide a simple, sensitive and quantitative tool for exploring the ecosystem structure.
Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun
2014-01-01
It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes. PMID:24185846
Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun; Cha, Hyung Joon
2014-01-01
It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes.
Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping
NASA Technical Reports Server (NTRS)
Royce, Thomas E.; Rozowsky, Joel S.; Bertone, Paul; Samanta, Manoj; Stolc, Viktor; Weissman, Sherman; Snyder, Michael; Gerstein, Mark
2005-01-01
Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.
Tackling the minority: sulfate-reducing bacteria in an archaea-dominated subsurface biofilm
Probst, Alexander J; Holman, Hoi-Ying N; DeSantis, Todd Z; Andersen, Gary L; Birarda, Giovanni; Bechtel, Hans A; Piceno, Yvette M; Sonnleitner, Maria; Venkateswaran, Kasthuri; Moissl-Eichinger, Christine
2013-01-01
Archaea are usually minor components of a microbial community and dominated by a large and diverse bacterial population. In contrast, the SM1 Euryarchaeon dominates a sulfidic aquifer by forming subsurface biofilms that contain a very minor bacterial fraction (5%). These unique biofilms are delivered in high biomass to the spring outflow that provides an outstanding window to the subsurface. Despite previous attempts to understand its natural role, the metabolic capacities of the SM1 Euryarchaeon remain mysterious to date. In this study, we focused on the minor bacterial fraction in order to obtain insights into the ecological function of the biofilm. We link phylogenetic diversity information with the spatial distribution of chemical and metabolic compounds by combining three different state-of-the-art methods: PhyloChip G3 DNA microarray technology, fluorescence in situ hybridization (FISH) and synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectromicroscopy. The results of PhyloChip and FISH technologies provide evidence for selective enrichment of sulfate-reducing bacteria, which was confirmed by the detection of bacterial dissimilatory sulfite reductase subunit B (dsrB) genes via quantitative PCR and sequence-based analyses. We further established a differentiation of archaeal and bacterial cells by SR-FTIR based on typical lipid and carbohydrate signatures, which demonstrated a co-localization of organic sulfate, carbonated mineral and bacterial signatures in the biofilm. All these results strongly indicate an involvement of the SM1 euryarchaeal biofilm in the global cycles of sulfur and carbon and support the hypothesis that sulfidic springs are important habitats for Earth's energy cycles. Moreover, these investigations of a bacterial minority in an Archaea-dominated environment are a remarkable example of the great power of combining highly sensitive microarrays with label-free infrared imaging. PMID:23178669
Urban aerosols harbor diverse and dynamic bacterial populations
Brodie, Eoin L.; DeSantis, Todd Z.; Parker, Jordan P. Moberg; Zubietta, Ingrid X.; Piceno, Yvette M.; Andersen, Gary L.
2007-01-01
Considering the importance of its potential implications for human health, agricultural productivity, and ecosystem stability, surprisingly little is known regarding the composition or dynamics of the atmosphere's microbial inhabitants. Using a custom high-density DNA microarray, we detected and monitored bacterial populations in two U.S. cities over 17 weeks. These urban aerosols contained at least 1,800 diverse bacterial types, a richness approaching that of some soil bacterial communities. We also reveal the consistent presence of bacterial families with pathogenic members including environmental relatives of select agents of bioterrorism significance. Finally, using multivariate regression techniques, we demonstrate that temporal and meteorological influences can be stronger factors than location in shaping the biological composition of the air we breathe. PMID:17182744
The MGED Ontology: a resource for semantics-based description of microarray experiments.
Whetzel, Patricia L; Parkinson, Helen; Causton, Helen C; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Game, Laurence; Heiskanen, Mervi; Morrison, Norman; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Taylor, Chris; White, Joseph; Stoeckert, Christian J
2006-04-01
The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). Stoeckrt@pcbi.upenn.edu Supplementary data are available at Bioinformatics online.
Cruciani, Federica; Biagi, Elena; Severgnini, Marco; Consolandi, Clarissa; Calanni, Fiorella; Donders, Gilbert; Brigidi, Patrizia
2015-01-01
The healthy vaginal microbiota is generally dominated by lactobacilli that confer antimicrobial protection and play a crucial role in health. Bacterial vaginosis (BV) is the most prevalent lower genital tract infection in women in reproductive age and is characterized by a shift in the relative abundances of Lactobacillus spp. to a greater abundance of strictly anaerobic bacteria. In this study, we designed a new phylogenetic microarray-based tool (VaginArray) that includes 17 probe sets specific for the most representative bacterial groups of the human vaginal ecosystem. This tool was implemented using the ligase detection reaction-universal array (LDR-UA) approach. The entire probe set properly recognized the specific targets and showed an overall sensitivity of 6 to 12 ng per probe. The VaginArray was applied to assess the efficacy of rifaximin vaginal tablets for the treatment of BV, analyzing the vaginal bacterial communities of 22 BV-affected women treated with rifaximin vaginal tablets at a dosage of 25 mg/day for 5 days. Our results showed the ability of rifaximin to reduce the growth of various BV-related bacteria (Atopobium vaginae, Prevotella, Megasphaera, Mobiluncus, and Sneathia spp.), with the highest antibiotic susceptibility for A. vaginae and Sneathia spp. Moreover, we observed an increase of Lactobacillus crispatus levels in the subset of women who maintained remission after 1 month of therapy, opening new perspectives for the treatment of BV. PMID:25733514
Kostić, Tanja; Sessitsch, Angela
2011-01-01
Reliable and sensitive pathogen detection in clinical and environmental (including food and water) samples is of greatest importance for public health. Standard microbiological methods have several limitations and improved alternatives are needed. Most important requirements for reliable analysis include: (i) specificity; (ii) sensitivity; (iii) multiplexing potential; (iv) robustness; (v) speed; (vi) automation potential; and (vii) low cost. Microarray technology can, through its very nature, fulfill many of these requirements directly and the remaining challenges have been tackled. In this review, we attempt to compare performance characteristics of the microbial diagnostic microarrays developed for the detection and typing of food and water pathogens, and discuss limitations, points still to be addressed and issues specific for the analysis of food, water and environmental samples. PMID:27605332
NASA Astrophysics Data System (ADS)
Beazley, M. J.; Martinez, R.; Rajan, S.; Powell, J.; Piceno, Y.; Tom, L.; Andersen, G. L.; Hazen, T. C.; Van Nostrand, J. D.; Zhou, J.; Mortazavi, B.; Sobecky, P. A.
2011-12-01
Microbial community responses of an Alabama coastal salt marsh environment to the Deepwater Horizon oil spill were studied by 16S rRNA (PhyloChip) and functional gene (GeoChip) microarray-based analysis. Oil and tar balls associated with the oil spill arrived along the Alabama coast in June 2010. Marsh and inlet sediment samples collected in June, July, and September 2010 from a salt marsh ecosystem at Point Aux Pines Alabama were analyzed to determine if bacterial community structure changed as a result of oil perturbation. Sediment total petroleum hydrocarbon (TPH) concentrations ranged from below detection to 189 mg kg-1 and were randomly dispersed throughout the salt marsh sediments. Total DNA extracted from sediment and particulates were used for PhyloChip and GeoChip hybridization. A total of 4000 to 8000 operational taxonomic units (OTUs) were detected in marsh and inlet samples. Distinctive changes in the number of detectable OTUs were observed between June, July, and September 2010. Surficial inlet sediments demonstrated a significant increase in the total number of OTUs between June and September that correlated with TPH concentrations. The most significant increases in bacterial abundance were observed in the phyla Actinobacteria, Firmicutes, Gemmatimonadetes, Proteobacteria, and Verrucomicrobia. Bacterial richness in marsh sediments also correlated with TPH concentrations with significant changes primarily in Acidobacteria, Actinobacteria, Firmicutes, Fusobacteria, Nitrospirae, and Proteobacteria. GeoChip microarray analysis detected 5000 to 8300 functional genes in marsh and inlet samples. Surficial inlet sediments demonstrated distinctive increases in the number of detectable genes and gene signal intensities in July samples compared to June. Signal intensities increased (> 1.5-fold) in genes associated with petroleum degradation. Genes related to metal resistance, stress, and carbon cycling also demonstrated increases in oiled sediments. This study demonstrates the value of applying phylogenetic and functional gene microarray technology to characterize the extensive microbial diversity of marsh environments. Moreover, this technology provides significant insight into bacterial community responses to anthropogenic oil events.
Women's experiences receiving abnormal prenatal chromosomal microarray testing results.
Bernhardt, Barbara A; Soucier, Danielle; Hanson, Karen; Savage, Melissa S; Jackson, Laird; Wapner, Ronald J
2013-02-01
Genomic microarrays can detect copy-number variants not detectable by conventional cytogenetics. This technology is diffusing rapidly into prenatal settings even though the clinical implications of many copy-number variants are currently unknown. We conducted a qualitative pilot study to explore the experiences of women receiving abnormal results from prenatal microarray testing performed in a research setting. Participants were a subset of women participating in a multicenter prospective study "Prenatal Cytogenetic Diagnosis by Array-based Copy Number Analysis." Telephone interviews were conducted with 23 women receiving abnormal prenatal microarray results. We found that five key elements dominated the experiences of women who had received abnormal prenatal microarray results: an offer too good to pass up, blindsided by the results, uncertainty and unquantifiable risks, need for support, and toxic knowledge. As prenatal microarray testing is increasingly used, uncertain findings will be common, resulting in greater need for careful pre- and posttest counseling, and more education of and resources for providers so they can adequately support the women who are undergoing testing.
Yergeau, Etienne; Arbour, Mélanie; Brousseau, Roland; Juck, David; Lawrence, John R.; Masson, Luke; Whyte, Lyle G.; Greer, Charles W.
2009-01-01
High-Arctic soils have low nutrient availability, low moisture content, and very low temperatures and, as such, they pose a particular problem in terms of hydrocarbon bioremediation. An in-depth knowledge of the microbiology involved in this process is likely to be crucial to understand and optimize the factors most influencing bioremediation. Here, we compared two distinct large-scale field bioremediation experiments, located at the Canadian high-Arctic stations of Alert (ex situ approach) and Eureka (in situ approach). Bacterial community structure and function were assessed using microarrays targeting the 16S rRNA genes of bacteria found in cold environments and hydrocarbon degradation genes as well as quantitative reverse transcriptase PCR targeting key functional genes. The results indicated a large difference between sampling sites in terms of both soil microbiology and decontamination rates. A rapid reorganization of the bacterial community structure and functional potential as well as rapid increases in the expression of alkane monooxygenases and polyaromatic hydrocarbon-ring-hydroxylating dioxygenases were observed 1 month after the bioremediation treatment commenced in the Alert soils. In contrast, no clear changes in community structure were observed in Eureka soils, while key gene expression increased after a relatively long lag period (1 year). Such discrepancies are likely caused by differences in bioremediation treatments (i.e., ex situ versus in situ), weathering of the hydrocarbons, indigenous microbial communities, and environmental factors such as soil humidity and temperature. In addition, this study demonstrates the value of molecular tools for the monitoring of polar bacteria and their associated functions during bioremediation. PMID:19684169
Yamamoto, F; Yamamoto, M
2004-07-01
We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.
Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications
Scheler, Ott; Glynn, Barry; Parkel, Sven; Palta, Priit; Toome, Kadri; Kaplinski, Lauris; Remm, Maido; Maher, Majella; Kurg, Ants
2009-01-01
Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology. PMID:19445684
Studying modification of aminoglycoside antibiotics by resistance-causing enzymes via microarray.
Disney, Matthew D
2012-01-01
Widespread bacterial resistance to antibiotics is a significant public health concern. To remain a step ahead of evolving bacteria, new methods to study resistance to antibacterials and to uncover novel antibiotics that evade resistance are urgently needed. Herein, microarray-based methods that have been developed to study aminoglycoside modification by resistance-causing enzymes are reviewed. These arrays can also be used to study the binding of aminoglycoside antibiotics to a mimic of their therapeutic target, the rRNA aminoacyl site (A-site), and how modification by resistance-causing enzymes affects their abilities to bind RNA.
Qi, Z; Cao, H; Jiang, H; Zhao, J; Tang, Z
2016-01-01
To use microarrays to detect 11 selected bacteria in infected root canals, revealing bacterial combinations that are associated with clinical symptoms and signs of primary endodontic infections in a Chinese population. DNA was extracted from 90 samples collected from the root canals of teeth with primary endodontic infections in a Chinese population, and the 16S rRNA gene was amplified by polymerase chain reaction (PCR). The PCR products were hybridized to microarrays containing specific oligonucleotide probes targeting 11 species, and the arrays were screened with a confocal laser scanner. Pearson's chi-squared test and cluster analysis were performed to investigate the associations between the bacterial combinations and clinical symptoms and signs using SAS 8.02. Seventy-seven samples (86%) yielded at least one of the 11 target species. Parvimonas micra (56%), Porphyromonas endodontalis (51%), Tannerella forsythia (48%), Prevotella intermedia (44%) and Porphyromonas gingivalis (37%) were the most prevalent taxa and were often concomitant. The following positive associations were found between the bacterial combinations and clinical features: P. endodontalis and T. forsythia with abscess; P. gingivalis and P. micra with sinus tract; P. gingivalis and P. endodontalis or P. micra and P. endodontalis with abscess and sinus tract; and the combination of P. endodontalis, P. micra, T. forsythia and P. gingivalis with sinus tract (P < 0.05). Various combinations of P. micra, P. endodontalis, T. forsythia and P. gingivalis may contribute to abscesses or sinus tracts of endodontic origin with bacterial synergism in a Chinese population. © 2015 International Endodontic Journal. Published by John Wiley & Sons Ltd.
Shan, Jinyu; Clokie, Martha
2009-01-01
Bacteriophages manipulate bacterial gene expression in order to express their own genes or influence bacterial metabolism. Gene expression can be studied using real-time PCR or microarrays. Either technique requires the prior isolation of high quality RNA uncontaminated by the presence of genomic DNA. We outline the considerations necessary when working with bacteriophage infected bacterial cells. We also give an example of a protocol for extraction and quantification of high quality RNA from infected bacterial cells, using the marine cyanobacterium WH7803 and the phage S-PM2 as a case study. This protocol can be modified to extract RNA from the host/bacteriophage of interest.
DNA Microarrays for Aptamer Identification and Structural Characterization
2012-09-01
appropriate vector (which has a unique set of factors affecting cloning efficiency) and transformed into competent bacterial cells to spatially...818-822. 2) Tuerk, C. and Gold, L., “Systematic Evolution of Ligands by Exponential Enrichment: RNA Ligands to Bacteriophage T4 DNA Polymerase
Hilson, Pierre; Allemeersch, Joke; Altmann, Thomas; Aubourg, Sébastien; Avon, Alexandra; Beynon, Jim; Bhalerao, Rishikesh P.; Bitton, Frédérique; Caboche, Michel; Cannoot, Bernard; Chardakov, Vasil; Cognet-Holliger, Cécile; Colot, Vincent; Crowe, Mark; Darimont, Caroline; Durinck, Steffen; Eickhoff, Holger; de Longevialle, Andéol Falcon; Farmer, Edward E.; Grant, Murray; Kuiper, Martin T.R.; Lehrach, Hans; Léon, Céline; Leyva, Antonio; Lundeberg, Joakim; Lurin, Claire; Moreau, Yves; Nietfeld, Wilfried; Paz-Ares, Javier; Reymond, Philippe; Rouzé, Pierre; Sandberg, Goran; Segura, Maria Dolores; Serizet, Carine; Tabrett, Alexandra; Taconnat, Ludivine; Thareau, Vincent; Van Hummelen, Paul; Vercruysse, Steven; Vuylsteke, Marnik; Weingartner, Magdalena; Weisbeek, Peter J.; Wirta, Valtteri; Wittink, Floyd R.A.; Zabeau, Marc; Small, Ian
2004-01-01
Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics. PMID:15489341
Phelps, Jamie P; Dao, Philip; Jin, Hongfan; Rasochova, Lada
2007-02-01
Coat protein of the cowpea chlorotic mottle virus (CCMV), a plant bromovirus, has been expressed in a soluble form in a prokaryote, Pseudomonas fluorescens, and assembled into virus-like particles (VLPs) in vivo that were structurally similar to the native CCMV particles derived from plants. The CCMV VLPs were purified by PEG precipitation followed by separation on a sucrose density gradient and analyzed by size exclusion chromatography, UV spectrometry, and transmission electron microscopy. DNA microarray experiments revealed that the VLPs encapsulated very large numbers of different host RNAs in a non-specific manner. The development of a P. fluorescens expression system now enables production of CCMV VLPs by bacterial fermentation for use in pharmaceutical or nanotechnology applications.
An efficient method to identify differentially expressed genes in microarray experiments
Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin
2013-01-01
Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554
DOE Office of Scientific and Technical Information (OSTI.GOV)
Andersen, Gary L.; Dubinsky, Eric A.
Herein are described 1058 different bacterial taxa that were unique to either human, grazing mammal, or bird fecal wastes. These identified taxa can serve as specific identifier taxa for these sources in environmental waters. Two field tests in marine waters demonstrate the capacity of phylogenetic microarray analysis to track multiple sources with one test.
ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.
ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.
Marcatili, Paolo; Nielsen, Martin W; Sicheritz-Pontén, Thomas; Jensen, Tim K; Schafer-Nielsen, Claus; Boye, Mette; Nielsen, Morten; Klitgaard, Kirstine
2016-12-01
Polymicrobial infections represent a great challenge for the clarification of disease etiology and the development of comprehensive diagnostic or therapeutic tools, particularly for fastidious and difficult-to-cultivate bacteria. Using bovine digital dermatitis (DD) as a disease model, we introduce a novel strategy to study the pathogenesis of complex infections. The strategy combines meta-transcriptomics with high-density peptide-microarray technology to screen for in vivo-expressed microbial genes and the host antibody response at the site of infection. Bacterial expression patterns supported the assumption that treponemes were the major DD pathogens but also indicated the active involvement of other phyla (primarily Bacteroidetes). Bacterial genes involved in chemotaxis, flagellar synthesis and protection against oxidative and acidic stress were among the major factors defining the disease. The extraordinary diversity observed in bacterial expression, antigens and host antibody responses between individual cows pointed toward microbial variability as a hallmark of DD. Persistence of infection and DD reinfection in the same individual is common; thus, high microbial diversity may undermine the host's capacity to mount an efficient immune response and maintain immunological memory towards DD. The common antigenic markers identified here using a high-density peptide microarray address this issue and may be useful for future preventive measures against DD.
NASA Astrophysics Data System (ADS)
Vukanti, R. V.; Mintz, E. M.; Leff, L. G.
2005-05-01
Bacterial responses to environmental signals are multifactorial and are coupled to changes in gene expression. An understanding of bacterial responses to environmental conditions is possible using microarray expression analysis. In this study, the utility of microarrays for examining changes in gene expression in Escherichia coli under different environmental conditions was assessed. RNA was isolated, hybridized to Affymetrix E. coli Genome 2.0 chips and analyzed using Affymetrix GCOS and Genespring software. Major limiting factors were obtaining enough quality RNA (107-108 cells to get 10μg RNA)and accounting for differences in growth rates under different conditions. Stabilization of RNA prior to isolation and taking extreme precautions while handling RNA were crucial. In addition, use of this method in ecological studies is limited by availability and cost of commercial arrays; choice of primers for cDNA synthesis, reproducibility, complexity of results generated and need to validate findings. This method may be more widely applicable with the development of better approaches for RNA recovery from environmental samples and increased number of available strain-specific arrays. Diligent experimental design and verification of results with real-time PCR or northern blots is needed. Overall, there is a great potential for use of this technology to discover mechanisms underlying organisms' responses to environmental conditions.
Usadel, Björn; Nagel, Axel; Steinhauser, Dirk; Gibon, Yves; Bläsing, Oliver E; Redestig, Henning; Sreenivasulu, Nese; Krall, Leonard; Hannah, Matthew A; Poree, Fabien; Fernie, Alisdair R; Stitt, Mark
2006-12-18
Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs.PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis.PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at http://mapman.mpimp-golm.mpg.de/pageman/. PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.
Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.
Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein
2015-01-01
DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.
A database for the analysis of immunity genes in Drosophila: PADMA database.
Lee, Mark J; Mondal, Ariful; Small, Chiyedza; Paddibhatla, Indira; Kawaguchi, Akira; Govind, Shubha
2011-01-01
While microarray experiments generate voluminous data, discerning trends that support an existing or alternative paradigm is challenging. To synergize hypothesis building and testing, we designed the Pathogen Associated Drosophila MicroArray (PADMA) database for easy retrieval and comparison of microarray results from immunity-related experiments (www.padmadatabase.org). PADMA also allows biologists to upload their microarray-results and compare it with datasets housed within PADMA. We tested PADMA using a preliminary dataset from Ganaspis xanthopoda-infected fly larvae, and uncovered unexpected trends in gene expression, reshaping our hypothesis. Thus, the PADMA database will be a useful resource to fly researchers to evaluate, revise, and refine hypotheses.
In its Computational Toxicology Program, EPA/ORD proposes to integrate genomics and computational methods to provide a mechanistic basis for the prediction of toxicity of chemicals and the pathogenicity of microorganisms. The goal of microbiological water testing is to be able to...
USDA-ARS?s Scientific Manuscript database
Antimicrobial resistance in pathogenic bacteria is a major concern in human and animal health. The National Antimicrobial Resistance Monitoring System (NARMS) was designed by the CDC, FDA, and USDA to monitor antimicrobial resistance in the U.S. The Bacterial Epidemiology and Antimicrobial Resistanc...
Establishment and Application of a Visual DNA Microarray for the Detection of Food-borne Pathogens.
Li, Yongjin
2016-01-01
The accurate detection and identification of food-borne pathogenic microorganisms is critical for food safety nowadays. In the present work, a visual DNA microarray was established and applied to detect pathogens commonly found in food, including Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in food samples. Multiplex PCR (mPCR) was employed to simultaneously amplify specific gene fragments, fimY for Salmonella, ipaH for Shigella, iap for L. monocytogenes and ECs2841 for E. coli O157:H7, respectively. Biotinylated PCR amplicons annealed to the microarray probes were then reacted with a streptavidin-alkaline phosphatase conjugate and nitro blue tetrazolium/5-bromo-4-chloro-3'-indolylphosphate, p-toluidine salt (NBT/BCIP); the positive results were easily visualized as blue dots formatted on the microarray surface. The performance of a DNA microarray was tested against 14 representative collection strains and mock-contamination food samples. The combination of mPCR and a visual micro-plate chip specifically and sensitively detected Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in standard strains and food matrices with a sensitivity of ∼10(2) CFU/mL of bacterial culture. Thus, the developed method is advantageous because of its high throughput, cost-effectiveness and ease of use.
Experimental design for three-color and four-color gene expression microarrays.
Woo, Yong; Krueger, Winfried; Kaur, Anupinder; Churchill, Gary
2005-06-01
Three-color microarrays, compared with two-color microarrays, can increase design efficiency and power to detect differential expression without additional samples and arrays. Furthermore, three-color microarray technology is currently available at a reasonable cost. Despite the potential advantages, clear guidelines for designing and analyzing three-color experiments do not exist. We propose a three- and a four-color cyclic design (loop) and a complementary graphical representation to help design experiments that are balanced, efficient and robust to hybridization failures. In theory, three-color loop designs are more efficient than two-color loop designs. Experiments using both two- and three-color platforms were performed in parallel and their outputs were analyzed using linear mixed model analysis in R/MAANOVA. These results demonstrate that three-color experiments using the same number of samples (and fewer arrays) will perform as efficiently as two-color experiments. The improved efficiency of the design is somewhat offset by a reduced dynamic range and increased variability in the three-color experimental system. This result suggests that, with minor technological improvements, three-color microarrays using loop designs could detect differential expression more efficiently than two-color loop designs. http://www.jax.org/staff/churchill/labsite/software Multicolor cyclic design construction methods and examples along with additional results of the experiment are provided at http://www.jax.org/staff/churchill/labsite/pubs/yong.
Caryoscope: An Open Source Java application for viewing microarray data in a genomic context
Awad, Ihab AB; Rees, Christian A; Hernandez-Boussard, Tina; Ball, Catherine A; Sherlock, Gavin
2004-01-01
Background Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context. Results We have developed Caryoscope, which is an open source Java application for visualizing microarray data from array comparative genome hybridization experiments in a genomic context. Caryoscope can read General Feature Format files (GFF files), as well as comma- and tab-delimited files, that define the genomic positions of the microarray reporters for which data are obtained. The microarray data can be browsed using an interactive, zoomable interface, which helps users identify regions of chromosomal deletion or amplification. The graphical representation of the data can be exported in a number of graphic formats, including publication-quality formats such as PostScript. Conclusion Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context. PMID:15488149
Fish and chips: Various methodologies demonstrate utility of a 16,006-gene salmonid microarray
von Schalburg, Kristian R; Rise, Matthew L; Cooper, Glenn A; Brown, Gordon D; Gibbs, A Ross; Nelson, Colleen C; Davidson, William S; Koop, Ben F
2005-01-01
Background We have developed and fabricated a salmonid microarray containing cDNAs representing 16,006 genes. The genes spotted on the array have been stringently selected from Atlantic salmon and rainbow trout expressed sequence tag (EST) databases. The EST databases presently contain over 300,000 sequences from over 175 salmonid cDNA libraries derived from a wide variety of tissues and different developmental stages. In order to evaluate the utility of the microarray, a number of hybridization techniques and screening methods have been developed and tested. Results We have analyzed and evaluated the utility of a microarray containing 16,006 (16K) salmonid cDNAs in a variety of potential experimental settings. We quantified the amount of transcriptome binding that occurred in cross-species, organ complexity and intraspecific variation hybridization studies. We also developed a methodology to rapidly identify and confirm the contents of a bacterial artificial chromosome (BAC) library containing Atlantic salmon genomic DNA. Conclusion We validate and demonstrate the usefulness of the 16K microarray over a wide range of teleosts, even for transcriptome targets from species distantly related to salmonids. We show the potential of the use of the microarray in a variety of experimental settings through hybridization studies that examine the binding of targets derived from different organs and tissues. Intraspecific variation in transcriptome expression is evaluated and discussed. Finally, BAC hybridizations are demonstrated as a rapid and accurate means to identify gene content. PMID:16164747
Clustering-based spot segmentation of cDNA microarray images.
Uslan, Volkan; Bucak, Ihsan Ömür
2010-01-01
Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step that separates the spots from the background. The experiments show that fuzzy c-means have segmented spots of the microarray image more accurately than the k-means.
A perspective on microarrays: current applications, pitfalls, and potential uses
Jaluria, Pratik; Konstantopoulos, Konstantinos; Betenbaugh, Michael; Shiloach, Joseph
2007-01-01
With advances in robotics, computational capabilities, and the fabrication of high quality glass slides coinciding with increased genomic information being available on public databases, microarray technology is increasingly being used in laboratories around the world. In fact, fields as varied as: toxicology, evolutionary biology, drug development and production, disease characterization, diagnostics development, cellular physiology and stress responses, and forensics have benefiting from its use. However, for many researchers not familiar with microarrays, current articles and reviews often address neither the fundamental principles behind the technology nor the proper designing of experiments. Although, microarray technology is relatively simple, conceptually, its practice does require careful planning and detailed understanding of the limitations inherently present. Without these considerations, it can be exceedingly difficult to ascertain valuable information from microarray data. Therefore, this text aims to outline key features in microarray technology, paying particular attention to current applications as outlined in recent publications, experimental design, statistical methods, and potential uses. Furthermore, this review is not meant to be comprehensive, but rather substantive; highlighting important concepts and detailing steps necessary to conduct and interpret microarray experiments. Collectively, the information included in this text will highlight the versatility of microarray technology and provide a glimpse of what the future may hold. PMID:17254338
Yang, Yunfeng; Zhu, Mengxia; Wu, Liyou; Zhou, Jizhong
2008-09-16
Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories. Conflicting results have been reported with regard to the reliability of microarray results using this method. To explain it, we hypothesize that data processing is a critical element that impacts the data quality. Microarray experiments were performed in a gamma-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either with two labeled cDNA samples co-hybridized to the same array, or by employing Shewanella genomic DNA as a standard reference. Various data processing techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that data quality was significantly improved by imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses. These findings demonstrate that data processing significantly influences data quality, which provides an explanation for the conflicting evaluation in the literature. This work could serve as a guideline for microarray data analysis using genomic DNA as a standard reference.
USDA-ARS?s Scientific Manuscript database
The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...
Multiplex infectious disease microarrays: STAT serology on a drop of blood
NASA Astrophysics Data System (ADS)
Ewart, Tom; Tarnopolsky, Mark; Baker, Steve; Raha, Sandeep; Wong, Yuen-Yee; Ciebiera, Kathy
2009-06-01
New and resurgent viral and antibiotic-resistant bacterial diseases are being encountered worldwide. The US CDC now ranks hospital acquired infections among the top 10 leading causes of death in the US, costing $20 billion annually. Such nosocomial infections presently affect 5% - 10% of hospitalized patients leading to 2 million cases and 99,000 deaths annually. Until now, assays available to mount comprehensive surveillance of infectious disease exposure by biosecurity agencies and hospital infection control units have been too slow and too costly. In earlier clinical studies we have reported proteomic microarrays combining 13 autoimmune and 26 viral and bacterial pathogens that revealed correlations between autoimmune diseases and antecedent infections. In this work we have expanded the array to 40 viruses and bacteria and investigated a suspected role of human endogenous retroviruses in autoimmune neuropathies. Using scanning laser imaging, and fluorescence color multiplexing, serum IgG and IgM responses are measured concurrently on the same array, for 14 arrays (patient samples) per microscope slide in 15 minutes. Other advantages include internal calibration, 10 μL sample size, increased laboratory efficiency, and potential factor of 100 cost reduction.
Ou, Hong-Yu; He, Xinyi; Harrison, Ewan M.; Kulasekara, Bridget R.; Thani, Ali Bin; Kadioglu, Aras; Lory, Stephen; Hinton, Jay C. D.; Barer, Michael R.; Rajakumar, Kumar
2007-01-01
MobilomeFINDER (http://mml.sjtu.edu.cn/MobilomeFINDER) is an interactive online tool that facilitates bacterial genomic island or ‘mobile genome’ (mobilome) discovery; it integrates the ArrayOme and tRNAcc software packages. ArrayOme utilizes a microarray-derived comparative genomic hybridization input data set to generate ‘inferred contigs’ produced by merging adjacent genes classified as ‘present’. Collectively these ‘fragments’ represent a hypothetical ‘microarray-visualized genome (MVG)’. ArrayOme permits recognition of discordances between physical genome and MVG sizes, thereby enabling identification of strains rich in microarray-elusive novel genes. Individual tRNAcc tools facilitate automated identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites and other integration hotspots in closely related sequenced genomes. Accessory tools facilitate design of hotspot-flanking primers for in silico and/or wet-science-based interrogation of cognate loci in unsequenced strains and analysis of islands for features suggestive of foreign origins; island-specific and genome-contextual features are tabulated and represented in schematic and graphical forms. To date we have used MobilomeFINDER to analyse several Enterobacteriaceae, Pseudomonas aeruginosa and Streptococcus suis genomes. MobilomeFINDER enables high-throughput island identification and characterization through increased exploitation of emerging sequence data and PCR-based profiling of unsequenced test strains; subsequent targeted yeast recombination-based capture permits full-length sequencing and detailed functional studies of novel genomic islands. PMID:17537813
Questioning the utility of pooling samples in microarray experiments with cell lines.
Lusa, L; Cappelletti, V; Gariboldi, M; Ferrario, C; De Cecco, L; Reid, J F; Toffanin, S; Gallus, G; McShane, L M; Daidone, M G; Pierotti, M A
2006-01-01
We describe a microarray experiment using the MCF-7 breast cancer cell line in two different experimental conditions for which the same number of independent pools as the number of individual samples was hybridized on Affymetrix GeneChips. Unexpectedly, when using individual samples, the number of probe sets found to be differentially expressed between treated and untreated cells was about three times greater than that found using pools. These findings indicate that pooling samples in microarray experiments where the biological variability is expected to be small might not be helpful and could even decrease one's ability to identify differentially expressed genes.
Chondrocyte channel transcriptomics
Lewis, Rebecca; May, Hannah; Mobasheri, Ali; Barrett-Jolley, Richard
2013-01-01
To date, a range of ion channels have been identified in chondrocytes using a number of different techniques, predominantly electrophysiological and/or biomolecular; each of these has its advantages and disadvantages. Here we aim to compare and contrast the data available from biophysical and microarray experiments. This letter analyses recent transcriptomics datasets from chondrocytes, accessible from the European Bioinformatics Institute (EBI). We discuss whether such bioinformatic analysis of microarray datasets can potentially accelerate identification and discovery of ion channels in chondrocytes. The ion channels which appear most frequently across these microarray datasets are discussed, along with their possible functions. We discuss whether functional or protein data exist which support the microarray data. A microarray experiment comparing gene expression in osteoarthritis and healthy cartilage is also discussed and we verify the differential expression of 2 of these genes, namely the genes encoding large calcium-activated potassium (BK) and aquaporin channels. PMID:23995703
Microarray expression technology: from start to finish.
Elvidge, Gareth
2006-01-01
The recent introduction of new microarray expression technologies and the further development of established platforms ensure that the researcher is presented with a range of options for performing an experiment. Whilst this has opened up the possibilities for future applications, such as exon-specific arrays, increased sample throughput and 'chromatin immunoprecipitation (ChIP) on chip' experiments, the initial decision processes and experiment planning are made more difficult. This review will give an overview of the various technologies that are available to perform a microarray expression experiment, from the initial planning stages through to the final data analysis. Both practical aspects and data analysis options will be considered. The relative advantages and disadvantages will be discussed with insights provided for future directions of the technology.
Imaging combined autoimmune and infectious disease microarrays
NASA Astrophysics Data System (ADS)
Ewart, Tom; Raha, Sandeep; Kus, Dorothy; Tarnopolsky, Mark
2006-09-01
Bacterial and viral pathogens are implicated in many severe autoimmune diseases, acting through such mechanisms as molecular mimicry, and superantigen activation of T-cells. For example, Helicobacter pylori, well known cause of stomach ulcers and cancers, is also identified in ischaemic heart disease (mimicry of heat shock protein 65), autoimmune pancreatitis, systemic sclerosis, autoimmune thyroiditis (HLA DRB1*0301 allele susceptibility), and Crohn's disease. Successful antibiotic eradication of H.pylori often accompanies their remission. Yet current diagnostic devices, and test-limiting cost containment, impede recognition of the linkage, delaying both diagnosis and therapeutic intervention until the chronic debilitating stage. We designed a 15 minute low cost 39 antigen microarray assay, combining autoimmune, viral and bacterial antigens1. This enables point-of-care serodiagnosis and cost-effective narrowly targeted concurrent antibiotic and monoclonal anti-T-cell and anti-cytokine immunotherapy. Arrays of 26 pathogen and 13 autoimmune antigens with IgG and IgM dilution series were printed in triplicate on epoxysilane covalent binding slides with Teflon well masks. Sera diluted 1:20 were incubated 10 minutes, washed off, anti-IgG-Cy3 (green) and anti-IgM-Dy647 (red) were incubated for 5 minutes, washed off and the slide was read in an ArrayWoRx(e) scanning CCD imager (Applied Precision, Issaquah, WA). As a preliminary model for the combined infectious disease-autoimmune diagnostic microarray we surveyed 98 unidentified, outdated sera that were discarded after Hepatitis B antibody testing. In these, significant IgG or IgM autoantibody levels were found: dsDNA 5, ssDNA 11, Ro 2, RNP 7, SSB 4, gliadin 2, thyroglobulin 13 cases. Since control sera showed no autoantibodies, the high frequency of anti-DNA and anti-thyroglobulin antibodies found in infected sera lend increased support for linkage of infection to subsequent autoimmune disease. Expansion of the antigen set with synthetic peptide sequences should reveal the shared bacterial/human epitopes involved.
Ma, Chen; Chen, Feng; Zhang, Yifei; Sun, Xiangyu; Tong, Peiyuan; Si, Yan; Zheng, Shuguo
2015-01-01
Early childhood caries (ECC) has become a prevalent public health problem among Chinese preschool children. The bacterial microflora is considered to be an important factor in the formation and progress of dental caries. However, high-throughput and large-scale studies of the primary dentition are lacking. The present study aimed to compare oral microbial profiles between children with severe ECC (SECC) and caries-free children. Both saliva and supragingival plaque samples were obtained from children with SECC (n = 20) and caries-free children (n = 20) aged 3 to 4 years. The samples were assayed using the Human Oral Microbe Identification Microarray (HOMIM). A total of 379 bacterial species were detected in both the saliva and supragingival plaque samples from all children. Thirteen (including Streptococcus) and two (Streptococcus and Actinomyces) bacterial species in supragingival plaque and saliva, respectively, showed significant differences in prevalence between the two groups. Of these, the frequency of Streptococcus mutans detection was significantly higher in both saliva (p = 0.026) and plaque (p = 0.006) samples from the SECC group than in those from the caries-free group. The findings of our study revealed differences in the oral microbiota between the SECC and caries-free groups Several genera, including Streptococcus, Porphyromonas, and Actinomyces, are strongly associated with SECC and can be potential biomarkers of dental caries in the primary dentition.
Peter, Harald; Berggrav, Kathrine; Thomas, Peter; Pfeifer, Yvonne; Witte, Wolfgang; Templeton, Kate
2012-01-01
Klebsiella pneumoniae carbapenemases (KPCs) are considered a serious threat to antibiotic therapy, as they confer resistance to carbapenems, which are used to treat extended-spectrum beta-lactamase (ESBL)-producing bacteria. Here, we describe the development and evaluation of a DNA microarray for the detection and genotyping of KPC genes (blaKPC) within a 5-h period. To test the whole assay procedure (DNA extraction plus a DNA microarray assay) directly from clinical specimens, we compared two commercial DNA extraction kits (the QIAprep Spin miniprep kit [Qiagen] and the urine bacterial DNA isolation kit [Norgen]) for the direct DNA extraction from urine samples (dilution series spiked in human urine). Reliable single nucleotide polymorphism (SNP) typing was demonstrated using 1 × 105 CFU/ml urine for Escherichia coli (Qiagen and Norgen) and 80 CFU/ml urine, on average, for K. pneumoniae (Norgen). This study presents, for the first time, the combination of a new KPC microarray with commercial sample preparation for detecting and genotyping microbial pathogens directly from clinical specimens; this paves the way toward tests providing epidemiological and diagnostic data, enabling better antimicrobial stewardship. PMID:23035190
El Kaoutari, Abdessamad; Armougom, Fabrice; Leroy, Quentin; Vialettes, Bernard; Million, Matthieu; Raoult, Didier; Henrissat, Bernard
2013-01-01
Distal gut bacteria play a pivotal role in the digestion of dietary polysaccharides by producing a large number of carbohydrate-active enzymes (CAZymes) that the host otherwise does not produce. We report here the design of a custom microarray that we used to spot non-redundant DNA probes for more than 6,500 genes encoding glycoside hydrolases and lyases selected from 174 reference genomes from distal gut bacteria. The custom microarray was tested and validated by the hybridization of bacterial DNA extracted from the stool samples of lean, obese and anorexic individuals. Our results suggest that a microarray-based study can detect genes from low-abundance bacteria better than metagenomic-based studies. A striking example was the finding that a gene encoding a GH6-family cellulase was present in all subjects examined, whereas metagenomic studies have consistently failed to detect this gene in both human and animal gut microbiomes. In addition, an examination of eight stool samples allowed the identification of a corresponding CAZome core containing 46 families of glycoside hydrolases and polysaccharide lyases, which suggests the functional stability of the gut microbiota despite large taxonomical variations between individuals.
Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.
Zimmer, Daniel P; Paliy, Oleg; Thomas, Brian; Gyaneshwar, Prasad; Kustu, Sydney
2004-08-01
We have developed programs to facilitate analysis of microarray data in Escherichia coli. They fall into two categories: manipulation of microarray images and identification of known biological relationships among lists of genes. A program in the first category arranges spots from glass-slide DNA microarrays according to their position in the E. coli genome and displays them compactly in genome order. The resulting genome image is presented in a web browser with an image map that allows the user to identify genes in the reordered image. Another program in the first category aligns genome images from two or more experiments. These images assist in visualizing regions of the genome with common transcriptional control. Such regions include multigene operons and clusters of operons, which are easily identified as strings of adjacent, similarly colored spots. The images are also useful for assessing the overall quality of experiments. The second category of programs includes a database and a number of tools for displaying biological information about many E. coli genes simultaneously rather than one gene at a time, which facilitates identifying relationships among them. These programs have accelerated and enhanced our interpretation of results from E. coli DNA microarray experiments. Examples are given. Copyright 2004 Genetics Society of America
Kang, Seung-Hui; Park, Chan Hee; Jeung, Hei Cheul; Kim, Ki-Yeol; Rha, Sun Young; Chung, Hyun Cheol
2007-06-01
In array-CGH, various factors may act as variables influencing the result of experiments. Among them, Cot-1 DNA, which has been used as a repetitive sequence-blocking agent, may become an artifact-inducing factor in BAC array-CGH. To identify the effect of Cot-1 DNA on Microarray-CGH experiments, Cot-1 DNA was labeled directly and Microarray-CGH experiments were performed. The results confirmed that probes which hybridized more completely with Cot-1 DNA had a higher sequence similarity to the Alu element. Further, in the sex-mismatched Microarray-CGH experiments, the variation and intensity in the fluorescent signal were reduced in the high intensity probe group in which probes were better hybridized with Cot-1 DNA. Otherwise, those of the low intensity probe group showed no alterations regardless of Cot-1 DNA. These results confirmed by in silico methods that Cot-1 DNA could block repetitive sequences in gDNA and probes. In addition, it was confirmed biologically that the blocking effect of Cot-1 DNA could be presented via its repetitive sequences, especially Alu elements. Thus, in contrast to BAC-array CGH, the use of Cot-1 DNA is advantageous in controlling experimental variation in Microarray-CGH.
A meta-data based method for DNA microarray imputation.
Jörnsten, Rebecka; Ouyang, Ming; Wang, Hui-Yu
2007-03-29
DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting. We download all cDNA microarray data of Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans from the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones. Since downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available.
Szkola, A; Linares, E M; Worbs, S; Dorner, B G; Dietrich, R; Märtlbauer, E; Niessner, R; Seidel, M
2014-11-21
Simultaneous detection of small and large molecules on microarray immunoassays is a challenge that limits some applications in multiplex analysis. This is the case for biosecurity, where fast, cheap and reliable simultaneous detection of proteotoxins and small toxins is needed. Two highly relevant proteotoxins, ricin (60 kDa) and bacterial toxin staphylococcal enterotoxin B (SEB, 30 kDa) and the small phycotoxin saxitoxin (STX, 0.3 kDa) are potential biological warfare agents and require an analytical tool for simultaneous detection. Proteotoxins are successfully detected by sandwich immunoassays, whereas competitive immunoassays are more suitable for small toxins (<1 kDa). Based on this need, this work provides a novel and efficient solution based on anti-idiotypic antibodies for small molecules to combine both assay principles on one microarray. The biotoxin measurements are performed on a flow-through chemiluminescence microarray platform MCR3 in 18 minutes. The chemiluminescence signal was amplified by using a poly-horseradish peroxidase complex (polyHRP), resulting in low detection limits: 2.9 ± 3.1 μg L(-1) for ricin, 0.1 ± 0.1 μg L(-1) for SEB and 2.3 ± 1.7 μg L(-1) for STX. The developed multiplex system for the three biotoxins is completely novel, relevant in the context of biosecurity and establishes the basis for research on anti-idiotypic antibodies for microarray immunoassays.
NASA Technical Reports Server (NTRS)
Koizumi, Yoshikazu; Kelly, John J.; Nakagawa, Tatsunori; Urakawa, Hidetoshi; El-Fantroussi, Said; Al-Muzaini, Saleh; Fukui, Manabu; Urushigawa, Yoshikuni; Stahl, David A.
2002-01-01
A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis.
Koizumi, Yoshikazu; Kelly, John J.; Nakagawa, Tatsunori; Urakawa, Hidetoshi; El-Fantroussi, Saïd; Al-Muzaini, Saleh; Fukui, Manabu; Urushigawa, Yoshikuni; Stahl, David A.
2002-01-01
A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis. PMID:12088997
Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin
2009-12-15
Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may help to interpret new microarray data.
Bartonella quintana Deploys Host and Vector Temperature-Specific Transcriptomes
Previte, Domenic; Yoon, Kyong S.; Clark, J. Marshall; DeRisi, Joseph L.; Koehler, Jane E.
2013-01-01
The bacterial pathogen Bartonella quintana is passed between humans by body lice. B. quintana has adapted to both the human host and body louse vector niches, producing persistent infection with high titer bacterial loads in both the host (up to 105 colony-forming units [CFU]/ml) and vector (more than 108 CFU/ml). Using a novel custom microarray platform, we analyzed bacterial transcription at temperatures corresponding to the host (37°C) and vector (28°C), to probe for temperature-specific and growth phase-specific transcriptomes. We observed that transcription of 7% (93 genes) of the B. quintana genome is modified in response to change in growth phase, and that 5% (68 genes) of the genome is temperature-responsive. Among these transcriptional changes in response to temperature shift and growth phase was the induction of known B. quintana virulence genes and several previously unannotated genes. Hemin binding proteins, secretion systems, response regulators, and genes for invasion and cell attachment were prominent among the differentially-regulated B. quintana genes. This study represents the first analysis of global transcriptional responses by B. quintana. In addition, the in vivo experiments provide novel insight into the B. quintana transcriptional program within the body louse environment. These data and approaches will facilitate study of the adaptation mechanisms employed by Bartonella during the transition between human host and arthropod vector. PMID:23554923
NASA Astrophysics Data System (ADS)
Liu, Hai-Tao; Wen, Zhi-Yu; Xu, Yi; Shang, Zheng-Guo; Peng, Jin-Lan; Tian, Peng
2017-09-01
In this paper, an integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection was purposed based on microfluidic chips dielectrophoresis technique and electrochemical impedance detection principle. The microsystems include microfluidic chip, main control module, and drive and control module, and signal detection and processing modulet and result display unit. The main control module produce the work sequence of impedance detection system parts and achieve data communication functions, the drive and control circuit generate AC signal which amplitude and frequency adjustable, and it was applied on the foodborne pathogens impedance analysis microsystems to realize the capture enrichment and impedance detection. The signal detection and processing circuit translate the current signal into impendence of bacteria, and transfer to computer, the last detection result is displayed on the computer. The experiment sample was prepared by adding Escherichia coli standard sample into chicken sample solution, and the samples were tested on the dielectrophoresis chip capture enrichment and in-situ impedance detection microsystems with micro-array electrode microfluidic chips. The experiments show that the Escherichia coli detection limit of microsystems is 5 × 104 CFU/mL and the detection time is within 6 min in the optimization of voltage detection 10 V and detection frequency 500 KHz operating conditions. The integrated microfluidic analysis microsystems laid the solid foundation for rapid real-time in-situ detection of bacteria.
Microarray analyses reveal distinct roles for Rel proteins in the Drosophila immune response
Pal, Subhamoy; Wu, Junlin; Wu, Louisa P.
2007-01-01
The NF-κB group of transcription factors play an important role in mediating immune responses in organisms as diverse as insects and mammals. The fruit fly Drosophila melanogaster express three closely related NF-κB-like transcription factors: Dorsal, Dif, and Relish. To study their roles in vivo, we used microarrays to determine the effect of null mutations in individual Rel transcription factors on larval immune gene expression. Of the 188 genes that were significantly up-regulated in wildtype larvae upon bacterial challenge, overlapping but distinct groups of genes were affected in the Rel mutants. We also ectopically expressed Dorsal or Dif and used cDNA microarrays to determine the genes that were up-regulated in the presence of these transcription factors. This expression was sufficient to drive expression of some immune genes, suggesting redundancy in the regulation of these genes. Combining this data, we also identified novel genes that may be specific targets of Dif. PMID:17537510
Goel, Meenal; Verma, Abhishek; Gupta, Shalini
2018-07-15
Microarray technology to isolate living cells using external fields is a facile way to do phenotypic analysis at the cellular level. We have used alternating current dielectrophoresis (AC-DEP) to drive the assembly of live pathogenic Salmonella typhi (S.typhi) and Escherichia coli (E.coli) bacteria into miniaturized single cell microarrays. The effects of voltage and frequency were optimized to identify the conditions for maximum cell capture which gave an entrapment efficiency of 90% in 60 min. The chip was used for calibration-free estimation of cellular loads in binary mixtures and further applied for rapid and enhanced testing of cell viability in the presence of drug via impedance spectroscopy. Our results using a model antimicrobial sushi peptide showed that the cell viability could be tested down to 5 μg/mL drug concentration under an hour, thus establishing the utility of our system for ultrafast and sensitive detection. Copyright © 2018 Elsevier B.V. All rights reserved.
Characterization and simulation of cDNA microarray spots using a novel mathematical model
Kim, Hye Young; Lee, Seo Eun; Kim, Min Jung; Han, Jin Il; Kim, Bo Kyung; Lee, Yong Sung; Lee, Young Seek; Kim, Jin Hyuk
2007-01-01
Background The quality of cDNA microarray data is crucial for expanding its application to other research areas, such as the study of gene regulatory networks. Despite the fact that a number of algorithms have been suggested to increase the accuracy of microarray gene expression data, it is necessary to obtain reliable microarray images by improving wet-lab experiments. As the first step of a cDNA microarray experiment, spotting cDNA probes is critical to determining the quality of spot images. Results We developed a governing equation of cDNA deposition during evaporation of a drop in the microarray spotting process. The governing equation included four parameters: the surface site density on the support, the extrapolated equilibrium constant for the binding of cDNA molecules with surface sites on glass slides, the macromolecular interaction factor, and the volume constant of a drop of cDNA solution. We simulated cDNA deposition from the single model equation by varying the value of the parameters. The morphology of the resulting cDNA deposit can be classified into three types: a doughnut shape, a peak shape, and a volcano shape. The spot morphology can be changed into a flat shape by varying the experimental conditions while considering the parameters of the governing equation of cDNA deposition. The four parameters were estimated by fitting the governing equation to the real microarray images. With the results of the simulation and the parameter estimation, the phenomenon of the formation of cDNA deposits in each type was investigated. Conclusion This study explains how various spot shapes can exist and suggests which parameters are to be adjusted for obtaining a good spot. This system is able to explore the cDNA microarray spotting process in a predictable, manageable and descriptive manner. We hope it can provide a way to predict the incidents that can occur during a real cDNA microarray experiment, and produce useful data for several research applications involving cDNA microarrays. PMID:18096047
Firmicutes dominate the bacterial taxa within sugar-cane processing plants
Sharmin, Farhana; Wakelin, Steve; Huygens, Flavia; Hargreaves, Megan
2013-01-01
Sugar cane processing sites are characterised by high sugar/hemicellulose levels, available moisture and warm conditions, and are relatively unexplored unique microbial environments. The PhyloChip microarray was used to investigate bacterial diversity and community composition in three Australian sugar cane processing plants. These ecosystems were highly complex and dominated by four main Phyla, Firmicutes (the most dominant), followed by Proteobacteria, Bacteroidetes, and Chloroflexi. Significant variation (p < 0.05) in community structure occurred between samples collected from ‘floor dump sediment’, ‘cooling tower water’, and ‘bagasse leachate’. Many bacterial Classes contributed to these differences, however most were of low numerical abundance. Separation in community composition was also linked to Classes of Firmicutes, particularly Bacillales, Lactobacillales and Clostridiales, whose dominance is likely to be linked to their physiology as ‘lactic acid bacteria’, capable of fermenting the sugars present. This process may help displace other bacterial taxa, providing a competitive advantage for Firmicutes bacteria. PMID:24177592
The MGED ontology: a framework for describing functional genomics experiments.
Stoeckert, Christian J; Parkinson, Helen
2003-01-01
The Microarray Gene Expression Data (MGED) society was formed with an initial focus on experiments involving microarray technology. Despite the diversity of applications, there are common concepts used and a common need to capture experimental information in a standardized manner. In building the MGED ontology, it was recognized that it would be impractical to cover all the different types of experiments on all the different types of organisms by listing and defining all the types of organisms and their properties. Our solution was to create a framework for describing microarray experiments with an initial focus on the biological sample and its manipulation. For concepts that are common for many species, we could provide a manageable listing of controlled terms. For concepts that are species-specific or whose values cannot be readily listed, we created an 'OntologyEntry' concept that referenced an external resource. The MGED ontology is a work in progress that needs additional instances and particularly needs constraints to be added. The ontology currently covers the experimental sample and design, and we have begun capturing aspects of the microarrays themselves as well. The primary application of the ontology will be to develop forms for entering information into databases, and consequently allowing queries, taking advantage of the structure provided by the ontology. The application of an ontology of experimental conditions extends beyond microarray experiments and, as the scope of MGED includes other aspects of functional genomics, so too will the MGED ontology.
Profiling In Situ Microbial Community Structure with an Amplification Microarray
Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H.; Peacock, Aaron D.; Long, Philip E.
2013-01-01
The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO3−) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO3, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications. PMID:23160129
An Introduction to MAMA (Meta-Analysis of MicroArray data) System.
Zhang, Zhe; Fenstermacher, David
2005-01-01
Analyzing microarray data across multiple experiments has been proven advantageous. To support this kind of analysis, we are developing a software system called MAMA (Meta-Analysis of MicroArray data). MAMA utilizes a client-server architecture with a relational database on the server-side for the storage of microarray datasets collected from various resources. The client-side is an application running on the end user's computer that allows the user to manipulate microarray data and analytical results locally. MAMA implementation will integrate several analytical methods, including meta-analysis within an open-source framework offering other developers the flexibility to plug in additional statistical algorithms.
RDFBuilder: a tool to automatically build RDF-based interfaces for MAGE-OM microarray data sources.
Anguita, Alberto; Martin, Luis; Garcia-Remesal, Miguel; Maojo, Victor
2013-07-01
This paper presents RDFBuilder, a tool that enables RDF-based access to MAGE-ML-compliant microarray databases. We have developed a system that automatically transforms the MAGE-OM model and microarray data stored in the ArrayExpress database into RDF format. Additionally, the system automatically enables a SPARQL endpoint. This allows users to execute SPARQL queries for retrieving microarray data, either from specific experiments or from more than one experiment at a time. Our system optimizes response times by caching and reusing information from previous queries. In this paper, we describe our methods for achieving this transformation. We show that our approach is complementary to other existing initiatives, such as Bio2RDF, for accessing and retrieving data from the ArrayExpress database. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Implementation of mutual information and bayes theorem for classification microarray data
NASA Astrophysics Data System (ADS)
Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda
2018-03-01
Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.
Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick
2010-01-01
Antibodies microarrays are among the novel class of rapidly emerging proteomic technologies that will allow us to efficiently perform specific diagnosis and proteome analysis. Recombinant antibody fragments are especially suited for this approach but their stability is often a limiting factor. Camelids produce functional antibodies devoid of light chains (HCAbs) of which the single N-terminal domain is fully capable of antigen binding. When produced as an independent domain, these so-called single domain antibody fragments (sdAbs) have several advantages for biotechnological applications thanks to their unique properties of size (15 kDa), stability, solubility, and expression yield. These features should allow sdAbs to outperform other antibody formats in a number of applications, notably as capture molecule for antibody arrays. In this study, we have produced antibody microarrays using direct and oriented immobilization of sdAbs produced in crude bacterial lysates to generate proof-of-principle of a high-throughput compatible array design. Several sdAb immobilization strategies have been explored. Immobilization of in vivo biotinylated sdAbs by direct spotting of bacterial lysate on streptavidin and sandwich detection was developed to achieve high sensitivity and specificity, whereas immobilization of “multi-tagged” sdAbs via anti-tag antibodies and direct labeled sample detection strategy was optimized for the design of high-density antibody arrays for high-throughput proteomics and identification of potential biomarkers. PMID:20859568
Jałowiecki, Łukasz; Chojniak, Joanna; Dorgeloh, Elmar; Hegedusova, Berta; Ejhed, Helene; Magnér, Jörgen; Płaza, Grażyna
2017-11-01
The scope of the study was to apply Phenotype Biolog MicroArray (PM) technology to test the antibiotic sensitivity of the bacterial strains isolated from on-site wastewater treatment facilities. In the first step of the study, the percentage values of resistant bacteria from total heterotrophic bacteria growing on solid media supplemented with various antibiotics were determined. In the untreated wastewater, the average shares of kanamycin-, streptomycin-, and tetracycline-resistant bacteria were 53, 56, and 42%, respectively. Meanwhile, the shares of kanamycin-, streptomycin-, and tetracycline-resistant bacteria in the treated wastewater were 39, 33, and 29%, respectively. To evaluate the antibiotic susceptibility of the bacteria present in the wastewater, using the phenotype microarrays (PMs), the most common isolates from the treated wastewater were chosen: Serratia marcescens ss marcescens, Pseudomonas fluorescens, Stenotrophomonas maltophilia, Stenotrophomonas rhizophila, Microbacterium flavescens, Alcaligenes faecalis ss faecalis, Flavobacterium hydatis, Variovorax paradoxus, Acinetobacter johnsonii, and Aeromonas bestiarum. The strains were classified as multi-antibiotic-resistant bacteria. Most of them were resistant to more than 30 antibiotics from various chemical classes. Phenotype microarrays could be successfully used as an additional tool for evaluation of the multi-antibiotic resistance of environmental bacteria and in preliminary determination of the range of inhibition concentration.
Detection of pathogenic Vibrio spp. in shellfish by using multiplex PCR and DNA microarrays.
Panicker, Gitika; Call, Douglas R; Krug, Melissa J; Bej, Asim K
2004-12-01
This study describes the development of a gene-specific DNA microarray coupled with multiplex PCR for the comprehensive detection of pathogenic vibrios that are natural inhabitants of warm coastal waters and shellfish. Multiplex PCR with vvh and viuB for Vibrio vulnificus, with ompU, toxR, tcpI, and hlyA for V. cholerae, and with tlh, tdh, trh, and open reading frame 8 for V. parahaemolyticus helped to ensure that total and pathogenic strains, including subtypes of the three Vibrio spp., could be detected and discriminated. For DNA microarrays, oligonucleotide probes for these targeted genes were deposited onto epoxysilane-derivatized, 12-well, Teflon-masked slides by using a MicroGrid II arrayer. Amplified PCR products were hybridized to arrays at 50 degrees C and detected by using tyramide signal amplification with Alexa Fluor 546 fluorescent dye. Slides were imaged by using an arrayWoRx scanner. The detection sensitivity for pure cultures without enrichment was 10(2) to 10(3) CFU/ml, and the specificity was 100%. However, 5 h of sample enrichment followed by DNA extraction with Instagene matrix and multiplex PCR with microarray hybridization resulted in the detection of 1 CFU in 1 g of oyster tissue homogenate. Thus, enrichment of the bacterial pathogens permitted higher sensitivity in compliance with the Interstate Shellfish Sanitation Conference guideline. Application of the DNA microarray methodology to natural oysters revealed the presence of V. vulnificus (100%) and V. parahaemolyticus (83%). However, V. cholerae was not detected in natural oysters. An assay involving a combination of multiplex PCR and DNA microarray hybridization would help to ensure rapid and accurate detection of pathogenic vibrios in shellfish, thereby improving the microbiological safety of shellfish for consumers.
Detection of Pathogenic Vibrio spp. in Shellfish by Using Multiplex PCR and DNA Microarrays
Panicker, Gitika; Call, Douglas R.; Krug, Melissa J.; Bej, Asim K.
2004-01-01
This study describes the development of a gene-specific DNA microarray coupled with multiplex PCR for the comprehensive detection of pathogenic vibrios that are natural inhabitants of warm coastal waters and shellfish. Multiplex PCR with vvh and viuB for Vibrio vulnificus, with ompU, toxR, tcpI, and hlyA for V. cholerae, and with tlh, tdh, trh, and open reading frame 8 for V. parahaemolyticus helped to ensure that total and pathogenic strains, including subtypes of the three Vibrio spp., could be detected and discriminated. For DNA microarrays, oligonucleotide probes for these targeted genes were deposited onto epoxysilane-derivatized, 12-well, Teflon-masked slides by using a MicroGrid II arrayer. Amplified PCR products were hybridized to arrays at 50°C and detected by using tyramide signal amplification with Alexa Fluor 546 fluorescent dye. Slides were imaged by using an arrayWoRx scanner. The detection sensitivity for pure cultures without enrichment was 102 to 103 CFU/ml, and the specificity was 100%. However, 5 h of sample enrichment followed by DNA extraction with Instagene matrix and multiplex PCR with microarray hybridization resulted in the detection of 1 CFU in 1 g of oyster tissue homogenate. Thus, enrichment of the bacterial pathogens permitted higher sensitivity in compliance with the Interstate Shellfish Sanitation Conference guideline. Application of the DNA microarray methodology to natural oysters revealed the presence of V. vulnificus (100%) and V. parahaemolyticus (83%). However, V. cholerae was not detected in natural oysters. An assay involving a combination of multiplex PCR and DNA microarray hybridization would help to ensure rapid and accurate detection of pathogenic vibrios in shellfish, thereby improving the microbiological safety of shellfish for consumers. PMID:15574946
Deciphering the Function of New Gonococcal Vaccine Antigens Using Phenotypic Microarrays
Baarda, Benjamin I.; Emerson, Sarah; Proteau, Philip J.
2017-01-01
ABSTRACT The function and extracellular location of cell envelope proteins make them attractive candidates for developing vaccines against bacterial diseases, including challenging drug-resistant pathogens, such as Neisseria gonorrhoeae. A proteomics-driven reverse vaccinology approach has delivered multiple gonorrhea vaccine candidates; however, the biological functions of many of them remain to be elucidated. Herein, the functions of six gonorrhea vaccine candidates—NGO2121, NGO1985, NGO2054, NGO2111, NGO1205, and NGO1344—in cell envelope homeostasis were probed using phenotype microarrays under 1,056 conditions and a ΔbamE mutant (Δngo1780) as a reference of perturbed outer membrane integrity. Optimal growth conditions for an N. gonorrhoeae phenotype microarray assay in defined liquid medium were developed, which can be useful in other applications, including rapid and thorough antimicrobial susceptibility assessment. Our studies revealed 91 conditions having uniquely positive or negative effects on one of the examined mutants. A cluster analysis of 37 and 57 commonly beneficial and detrimental compounds, respectively, revealed three separate phenotype groups: NGO2121 and NGO1985; NGO1344 and BamE; and the trio of NGO1205, NGO2111, and NGO2054, with the last protein forming an independent branch of this cluster. Similar phenotypes were associated with loss of these vaccine candidates in the highly antibiotic-resistant WHO X strain. Based on their extensive sensitivity phenomes, NGO1985 and NGO2121 appear to be the most promising vaccine candidates. This study establishes the principle that phenotype microarrays can be successfully applied to a fastidious bacterial organism, such as N. gonorrhoeae. IMPORTANCE Innovative approaches are required to develop vaccines against prevalent and neglected sexually transmitted infections, such as gonorrhea. Herein, we have utilized phenotype microarrays in the first such investigation into Neisseria gonorrhoeae to probe the function of proteome-derived vaccine candidates in cell envelope homeostasis. Information gained from this screening can feed the vaccine candidate decision tree by providing insights into the roles these proteins play in membrane permeability, integrity, and overall N. gonorrhoeae physiology. The optimized screening protocol can be applied in investigations into the function of other hypothetical proteins of N. gonorrhoeae discovered in the expanding number of whole-genome sequences, in addition to revealing phenotypic differences between clinical and laboratory strains. PMID:28630127
Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.
Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Laegreid, Astrid
2007-10-18
The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.
Optimization of cDNA microarrays procedures using criteria that do not rely on external standards
Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Lægreid, Astrid
2007-01-01
Background The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. Results We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. Conclusion The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish. PMID:17949480
Zhang, Xiaomeng; Shao, Bin; Wu, Yangle; Qi, Ouyang
2013-01-01
One of the major objectives in systems biology is to understand the relation between the topological structures and the dynamics of biological regulatory networks. In this context, various mathematical tools have been developed to deduct structures of regulatory networks from microarray expression data. In general, from a single data set, one cannot deduct the whole network structure; additional expression data are usually needed. Thus how to design a microarray expression experiment in order to get the most information is a practical problem in systems biology. Here we propose three methods, namely, maximum distance method, trajectory entropy method, and sampling method, to derive the optimal initial conditions for experiments. The performance of these methods is tested and evaluated in three well-known regulatory networks (budding yeast cell cycle, fission yeast cell cycle, and E. coli. SOS network). Based on the evaluation, we propose an efficient strategy for the design of microarray expression experiments.
Schramm, Frédéric; Kern, Aurélie; Barthel, Cathy; Nadaud, Sophie; Meyer, Nicolas
2012-01-01
In Lyme borreliosis, the skin is the key site of bacterial inoculation by the infected tick, and of cutaneous manifestations, erythema migrans and acrodermatitis chronica atrophicans. We explored the role of fibroblasts, the resident cells of the dermis, in the development of the disease. Using microarray experiments, we compared the inflammation of fibroblasts induced by three strains of Borrelia burgdorferi sensu stricto isolated from different environments and stages of Lyme disease: N40 (tick), Pbre (erythema migrans) and 1408 (acrodermatitis chronica atrophicans). The three strains exhibited a similar profile of inflammation with strong induction of chemokines (CXCL1 and IL-8) and IL-6 cytokine mainly involved in the chemoattraction of immune cells. Molecules such as TNF-alpha and NF-κB factors, metalloproteinases (MMP-1, -3 and -12) and superoxide dismutase (SOD2), also described in inflammatory and cellular events, were up-regulated. In addition, we showed that tick salivary gland extracts induce a cytotoxic effect on fibroblasts and that OspC, essential in the transmission of Borrelia to the vertebrate host, was not responsible for the secretion of inflammatory molecules by fibroblasts. Tick saliva components could facilitate the early transmission of the disease to the site of injury creating a feeding pit. Later in the development of the disease, Borrelia would intensively multiply in the skin and further disseminate to distant organs. PMID:22768217
Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina
2006-06-01
Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.
NASA Astrophysics Data System (ADS)
Tibbetts, Clark; Lichanska, Agnieszka M.; Borsuk, Lisa A.; Weslowski, Brian; Morris, Leah M.; Lorence, Matthew C.; Schafer, Klaus O.; Campos, Joseph; Sene, Mohamadou; Myers, Christopher A.; Faix, Dennis; Blair, Patrick J.; Brown, Jason; Metzgar, David
2010-04-01
High-density resequencing microarrays support simultaneous detection and identification of multiple viral and bacterial pathogens. Because detection and identification using RPM is based upon multiple specimen-specific target pathogen gene sequences generated in the individual test, the test results enable both a differential diagnostic analysis and epidemiological tracking of detected pathogen strains and variants from one specimen to the next. The RPM assay enables detection and identification of pathogen sequences that share as little as 80% sequence similarity to prototype target gene sequences represented as detector tiles on the array. This capability enables the RPM to detect and identify previously unknown strains and variants of a detected pathogen, as in sentinel cases associated with an infectious disease outbreak. We illustrate this capability using assay results from testing influenza A virus vaccines configured with strains that were first defined years after the design of the RPM microarray. Results are also presented from RPM-Flu testing of three specimens independently confirmed to the positive for the 2009 Novel H1N1 outbreak strain of influenza virus.
USDA-ARS?s Scientific Manuscript database
Infection by Xanthomonas axonopodis pv. manihotis (Xam)of the model perennial range land weed leafy spurge was tested to see if Xam might serve a potential biological control agent for this invasive weed. Although leafy spurge was susceptible to Xam infection, it recovered with 21 days after inocula...
An Affymetrix Microarray Design for Microbial Genotyping
2009-10-01
sanguinis SK36 232 Streptococcus sanguinis HPT sanguinis 5 Streptococcus suis 05ZYH33 138 Streptococcus suis 98 HAH33 65 Streptococcus thermophilus...Rickettsia species, plasmids pBC16 and pLS1. Sequences representing bacterial toxins and antimicrobial resistance (e.g. antibiotic markers) were also...Also included were regions that were constant within a species but differed between species, virulence genes, and antibiotic resistance genes. 2.3
Wide screening of phage-displayed libraries identifies immune targets in planta.
Rioja, Cristina; Van Wees, Saskia C; Charlton, Keith A; Pieterse, Corné M J; Lorenzo, Oscar; García-Sánchez, Susana
2013-01-01
Microbe-Associated Molecular Patterns and virulence effectors are recognized by plants as a first step to mount a defence response against potential pathogens. This recognition involves a large family of extracellular membrane receptors and other immune proteins located in different sub-cellular compartments. We have used phage-display technology to express and select for Arabidopsis proteins able to bind bacterial pathogens. To rapidly identify microbe-bound phage, we developed a monitoring method based on microarrays. This combined strategy allowed for a genome-wide screening of plant proteins involved in pathogen perception. Two phage libraries for high-throughput selection were constructed from cDNA of plants infected with Pseudomonas aeruginosa PA14, or from combined samples of the virulent isolate DC3000 of Pseudomonas syringae pv. tomato and its avirulent variant avrRpt2. These three pathosystems represent different degrees in the specificity of plant-microbe interactions. Libraries cover up to 2 × 10(7) different plant transcripts that can be displayed as functional proteins on the surface of T7 bacteriophage. A number of these were selected in a bio-panning assay for binding to Pseudomonas cells. Among the selected clones we isolated the ethylene response factor ATERF-1, which was able to bind the three bacterial strains in competition assays. ATERF-1 was rapidly exported from the nucleus upon infiltration of either alive or heat-killed Pseudomonas. Moreover, aterf-1 mutants exhibited enhanced susceptibility to infection. These findings suggest that ATERF-1 contains a microbe-recognition domain with a role in plant defence. To identify other putative pathogen-binding proteins on a genome-wide scale, the copy number of selected-vs.-total clones was compared by hybridizing phage cDNAs with Arabidopsis microarrays. Microarray analysis revealed a set of 472 candidates with significant fold change. Within this set defence-related genes, including well-known targets of bacterial effectors, are over-represented. Other genes non-previously related to defence can be associated through this study with general or strain-specific recognition of Pseudomonas.
Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan
2014-06-15
The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.
Best practices for hybridization design in two-colour microarray analysis.
Knapen, Dries; Vergauwen, Lucia; Laukens, Kris; Blust, Ronny
2009-07-01
Two-colour microarrays are a popular platform of choice in gene expression studies. Because two different samples are hybridized on a single microarray, and several microarrays are usually needed in a given experiment, there are many possible ways to combine samples on different microarrays. The actual combination employed is commonly referred to as the 'hybridization design'. Different types of hybridization designs have been developed, all aimed at optimizing the experimental setup for the detection of differentially expressed genes while coping with technical noise. Here, we first provide an overview of the different classes of hybridization designs, discussing their advantages and limitations, and then we illustrate the current trends in the use of different hybridization design types in contemporary research.
Cao, H; Qi, Z; Jiang, H; Zhao, J; Liu, Z; Tang, Z
2012-08-01
To assess the prevalence of three black-pigmented bacterial species (Porphyromonas endodontalis, Porphyromonas gingivalis and Prevotella intermedia) using microarray technology in root canals of teeth associated with primary endodontic infections in a Chinese population. Microbial samples were taken from root canals of 80 teeth with pulp necrosis and primary endodontic infections in a Chinese population. DNA extracted from the samples was amplified by PCR with universal bacterial primers based on 16S rRNA gene sequences, and the products hybridized with the microarrays in which the specific oligonucleotide probes were added. The results of hybridization were screened by a confocal laser scanner. Pearson chi-square test and the two-sided Fisher exact test were used to analyse whether a significant association existed between the species and symptoms as well as in co-existence of two target organisms by a statistical software package (SAS 8.02). The 16S rRNA gene microarray detected at least one of the three test species in 76% of the study teeth. P. endodontalis, P. gingivalis and P. intermedia were found in 50%, 33% and 45%, respectively. A significant association was found in the presence of the pair P. endodontalis / P. gingivalis (P < 0.005). Both P. endodontalis (P <0.05) and P. gingivalis (P <0.005) had a statistically significant association with the presence of a sinus tract. The simultaneous presence of P. endodontalis and P. gingivalis was also associated with the presence of a sinus tract (P<0.005) and abscess formation (P<0.05). The three black-pigmented bacteria were prevalent in teeth with pulp necrosis and primary endodontic infections in a Chinese population. P. gingivalis and P. endodontalis were associated with the presence of sinus tract and abscess formation. © 2012 International Endodontic Journal.
Arnfinnsdottir, Nina Bjørk; Ottesen, Vegar; Lale, Rahmi; Sletmoen, Marit
2015-01-01
In this paper we demonstrate a procedure for preparing bacterial arrays that is fast, easy, and applicable in a standard molecular biology laboratory. Microcontact printing is used to deposit chemicals promoting bacterial adherence in predefined positions on glass surfaces coated with polymers known for their resistance to bacterial adhesion. Highly ordered arrays of immobilized bacteria were obtained using microcontact printed islands of polydopamine (PD) on glass surfaces coated with the antiadhesive polymer polyethylene glycol (PEG). On such PEG-coated glass surfaces, bacteria were attached to 97 to 100% of the PD islands, 21 to 62% of which were occupied by a single bacterium. A viability test revealed that 99% of the bacteria were alive following immobilization onto patterned surfaces. Time series imaging of bacteria on such arrays revealed that the attached bacteria both divided and expressed green fluorescent protein, both of which indicates that this method of patterning of bacteria is a suitable method for single-cell analysis.
Thermodynamically optimal whole-genome tiling microarray design and validation.
Cho, Hyejin; Chou, Hui-Hsien
2016-06-13
Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.
Li, Zhiguang; Kwekel, Joshua C; Chen, Tao
2012-01-01
Functional comparison across microarray platforms is used to assess the comparability or similarity of the biological relevance associated with the gene expression data generated by multiple microarray platforms. Comparisons at the functional level are very important considering that the ultimate purpose of microarray technology is to determine the biological meaning behind the gene expression changes under a specific condition, not just to generate a list of genes. Herein, we present a method named percentage of overlapping functions (POF) and illustrate how it is used to perform the functional comparison of microarray data generated across multiple platforms. This method facilitates the determination of functional differences or similarities in microarray data generated from multiple array platforms across all the functions that are presented on these platforms. This method can also be used to compare the functional differences or similarities between experiments, projects, or laboratories.
BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.
Angelini, Claudia; Cutillo, Luisa; De Canditiis, Daniela; Mutarelli, Margherita; Pensky, Marianna
2008-10-06
Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a biological process of interest. From methodological and computational point of view, analyzing high-dimensional time course microarray data requires very specific set of tools which are usually not included in standard software packages. Recently, the authors of this paper developed a fully Bayesian approach which allows one to identify differentially expressed genes in a 'one-sample' time-course microarray experiment, to rank them and to estimate their expression profiles. The method is based on explicit expressions for calculations and, hence, very computationally efficient. The software package BATS (Bayesian Analysis of Time Series) presented here implements the methodology described above. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles when at least 5-6 time points are available. The package has a user-friendly interface. BATS successfully manages various technical difficulties which arise in time-course microarray experiments, such as a small number of observations, non-uniform sampling intervals and replicated or missing data. BATS is a free user-friendly software for the analysis of both simulated and real microarray time course experiments. The software, the user manual and a brief illustrative example are freely available online at the BATS website: http://www.na.iac.cnr.it/bats.
Chun, Carlene K; Troll, Joshua V; Koroleva, Irina; Brown, Bartley; Manzella, Liliana; Snir, Einat; Almabrazi, Hakeem; Scheetz, Todd E; Bonaldo, Maria de Fatima; Casavant, Thomas L; Soares, M Bento; Ruby, Edward G; McFall-Ngai, Margaret J
2008-08-12
The light-organ symbiosis between the squid Euprymna scolopes and the luminous bacterium Vibrio fischeri offers the opportunity to decipher the hour-by-hour events that occur during the natural colonization of an animal's epithelial surface by its microbial partners. To determine the genetic basis of these events, a glass-slide microarray was used to characterize the light-organ transcriptome of juvenile squid in response to the initiation of symbiosis. Patterns of gene expression were compared between animals not exposed to the symbiont, exposed to the wild-type symbiont, or exposed to a mutant symbiont defective in either of two key characters of this association: bacterial luminescence or autoinducer (AI) production. Hundreds of genes were differentially regulated as a result of symbiosis initiation, and a hierarchy existed in the magnitude of the host's response to three symbiont features: bacterial presence > luminescence > AI production. Putative host receptors for bacterial surface molecules known to induce squid development are up-regulated by symbiont light production, suggesting that bioluminescence plays a key role in preparing the host for bacteria-induced development. Further, because the transcriptional response of tissues exposed to AI in the natural context (i.e., with the symbionts) differed from that to AI alone, the presence of the bacteria potentiates the role of quorum signals in symbiosis. Comparison of these microarray data with those from other symbioses, such as germ-free/conventionalized mice and zebrafish, revealed a set of shared genes that may represent a core set of ancient host responses conserved throughout animal evolution.
Chun, Carlene K.; Troll, Joshua V.; Koroleva, Irina; Brown, Bartley; Manzella, Liliana; Snir, Einat; Almabrazi, Hakeem; Scheetz, Todd E.; de Fatima Bonaldo, Maria; Casavant, Thomas L.; Soares, M. Bento; Ruby, Edward G.; McFall-Ngai, Margaret J.
2008-01-01
The light–organ symbiosis between the squid Euprymna scolopes and the luminous bacterium Vibrio fischeri offers the opportunity to decipher the hour-by-hour events that occur during the natural colonization of an animal's epithelial surface by its microbial partners. To determine the genetic basis of these events, a glass-slide microarray was used to characterize the light-organ transcriptome of juvenile squid in response to the initiation of symbiosis. Patterns of gene expression were compared between animals not exposed to the symbiont, exposed to the wild-type symbiont, or exposed to a mutant symbiont defective in either of two key characters of this association: bacterial luminescence or autoinducer (AI) production. Hundreds of genes were differentially regulated as a result of symbiosis initiation, and a hierarchy existed in the magnitude of the host's response to three symbiont features: bacterial presence > luminescence > AI production. Putative host receptors for bacterial surface molecules known to induce squid development are up-regulated by symbiont light production, suggesting that bioluminescence plays a key role in preparing the host for bacteria-induced development. Further, because the transcriptional response of tissues exposed to AI in the natural context (i.e., with the symbionts) differed from that to AI alone, the presence of the bacteria potentiates the role of quorum signals in symbiosis. Comparison of these microarray data with those from other symbioses, such as germ-free/conventionalized mice and zebrafish, revealed a set of shared genes that may represent a core set of ancient host responses conserved throughout animal evolution. PMID:18682555
Huang, Yvonne J.; Kim, Eugenia; Cox, Michael J.; Brodie, Eoin L.; Brown, Ron; Wiener-Kronish, Jeanine P.
2010-01-01
Abstract Acute exacerbations of chronic obstructive pulmonary disease (COPD) are a major source of morbidity and contribute significantly to healthcare costs. Although bacterial infections are implicated in nearly 50% of exacerbations, only a handful of pathogens have been consistently identified in COPD airways, primarily by culture-based methods, and the bacterial microbiota in acute exacerbations remains largely uncharacterized. The aim of this study was to comprehensively profile airway bacterial communities using a culture-independent microarray, the 16S rRNA PhyloChip, of a cohort of COPD patients requiring ventilatory support and antibiotic therapy for exacerbation-related respiratory failure. PhyloChip analysis revealed the presence of over 1,200 bacterial taxa representing 140 distinct families, many previously undetected in airway diseases; bacterial community composition was strongly influenced by the duration of intubation. A core community of 75 taxa was detected in all patients, many of which are known pathogens. Bacterial community diversity in COPD airways is substantially greater than previously recognized and includes a number of potential pathogens detected in the setting of antibiotic exposure. Comprehensive assessment of the COPD airway microbiota using high-throughput, culture-independent methods may prove key to understanding the relationships between airway bacterial colonization, acute exacerbation, and clinical outcomes in this and other chronic inflammatory airway diseases. PMID:20141328
Khan, Rishi L; Gonye, Gregory E; Gao, Guang; Schwaber, James S
2006-01-01
Background Using microarrays by co-hybridizing two samples labeled with different dyes enables differential gene expression measurements and comparisons across slides while controlling for within-slide variability. Typically one dye produces weaker signal intensities than the other often causing signals to be undetectable. In addition, undetectable spots represent a large problem for two-color microarray designs and most arrays contain at least 40% undetectable spots even when labeled with reference samples such as Stratagene's Universal Reference RNAs™. Results We introduce a novel universal reference sample that produces strong signal for all spots on the array, increasing the average fraction of detectable spots to 97%. Maximizing detectable spots on the reference image channel also decreases the variability of microarray data allowing for reliable detection of smaller differential gene expression changes. The reference sample is derived from sequence contained in the parental EST clone vector pT7T3D-Pac and is called vector RNA (vRNA). We show that vRNA can also be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This reference sample can be made inexpensively in large quantities as a renewable resource that is consistent across experiments. Conclusion Results of this study show that vRNA provides a useful universal reference that yields high signal for almost all spots on a microarray, reduces variation and allows for comparisons between experiments and laboratories. Further, it can be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This type of reference allows for detection of small changes in differential expression while reference designs in general allow for large-scale multivariate experimental designs. vRNA in combination with reference designs enable systems biology microarray experiments of small physiologically relevant changes. PMID:16677381
Equalizer reduces SNP bias in Affymetrix microarrays.
Quigley, David
2015-07-30
Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans. By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings. The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.
Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gregory Stephanopoulos
Transcriptional profiling experiments utilizing DNA microarrays to study the intracellular accumulation of PHB in Synechocystis has proved difficult in large part because strains that show significant differences in PHB which would justify global analysis of gene expression have not been isolated.
MeV+R: using MeV as a graphical user interface for Bioconductor applications in microarray analysis
Chu, Vu T; Gottardo, Raphael; Raftery, Adrian E; Bumgarner, Roger E; Yeung, Ka Yee
2008-01-01
We present MeV+R, an integration of the JAVA MultiExperiment Viewer program with Bioconductor packages. This integration of MultiExperiment Viewer and R is easily extensible to other R packages and provides users with point and click access to traditionally command line driven tools written in R. We demonstrate the ability to use MultiExperiment Viewer as a graphical user interface for Bioconductor applications in microarray data analysis by incorporating three Bioconductor packages, RAMA, BRIDGE and iterativeBMA. PMID:18652698
Advances in cell-free protein array methods.
Yu, Xiaobo; Petritis, Brianne; Duan, Hu; Xu, Danke; LaBaer, Joshua
2018-01-01
Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.
Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas
2016-09-19
Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.
Spot detection and image segmentation in DNA microarray data.
Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune
2005-01-01
Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.
Strand-specific transcriptome profiling with directly labeled RNA on genomic tiling microarrays
2011-01-01
Background With lower manufacturing cost, high spot density, and flexible probe design, genomic tiling microarrays are ideal for comprehensive transcriptome studies. Typically, transcriptome profiling using microarrays involves reverse transcription, which converts RNA to cDNA. The cDNA is then labeled and hybridized to the probes on the arrays, thus the RNA signals are detected indirectly. Reverse transcription is known to generate artifactual cDNA, in particular the synthesis of second-strand cDNA, leading to false discovery of antisense RNA. To address this issue, we have developed an effective method using RNA that is directly labeled, thus by-passing the cDNA generation. This paper describes this method and its application to the mapping of transcriptome profiles. Results RNA extracted from laboratory cultures of Porphyromonas gingivalis was fluorescently labeled with an alkylation reagent and hybridized directly to probes on genomic tiling microarrays specifically designed for this periodontal pathogen. The generated transcriptome profile was strand-specific and produced signals close to background level in most antisense regions of the genome. In contrast, high levels of signal were detected in the antisense regions when the hybridization was done with cDNA. Five antisense areas were tested with independent strand-specific RT-PCR and none to negligible amplification was detected, indicating that the strong antisense cDNA signals were experimental artifacts. Conclusions An efficient method was developed for mapping transcriptome profiles specific to both coding strands of a bacterial genome. This method chemically labels and uses extracted RNA directly in microarray hybridization. The generated transcriptome profile was free of cDNA artifactual signals. In addition, this method requires fewer processing steps and is potentially more sensitive in detecting small amount of RNA compared to conventional end-labeling methods due to the incorporation of more fluorescent molecules per RNA fragment. PMID:21235785
Pinne, Marija; Matsunaga, James; Haake, David A
2012-11-01
Leptospirosis is a zoonosis with worldwide distribution caused by pathogenic spirochetes belonging to the genus Leptospira. The leptospiral life cycle involves transmission via freshwater and colonization of the renal tubules of their reservoir hosts. Infection requires adherence to cell surfaces and extracellular matrix components of host tissues. These host-pathogen interactions involve outer membrane proteins (OMPs) expressed on the bacterial surface. In this study, we developed an Leptospira interrogans serovar Copenhageni strain Fiocruz L1-130 OMP microarray containing all predicted lipoproteins and transmembrane OMPs. A total of 401 leptospiral genes or their fragments were transcribed and translated in vitro and printed on nitrocellulose-coated glass slides. We investigated the potential of this protein microarray to screen for interactions between leptospiral OMPs and fibronectin (Fn). This approach resulted in the identification of the recently described fibronectin-binding protein, LIC10258 (MFn8, Lsa66), and 14 novel Fn-binding proteins, denoted Microarray Fn-binding proteins (MFns). We confirmed Fn binding of purified recombinant LIC11612 (MFn1), LIC10714 (MFn2), LIC11051 (MFn6), LIC11436 (MFn7), LIC10258 (MFn8, Lsa66), and LIC10537 (MFn9) by far-Western blot assays. Moreover, we obtained specific antibodies to MFn1, MFn7, MFn8 (Lsa66), and MFn9 and demonstrated that MFn1, MFn7, and MFn9 are expressed and surface exposed under in vitro growth conditions. Further, we demonstrated that MFn1, MFn4 (LIC12631, Sph2), and MFn7 enable leptospires to bind fibronectin when expressed in the saprophyte, Leptospira biflexa. Protein microarrays are valuable tools for high-throughput identification of novel host ligand-binding proteins that have the potential to play key roles in the virulence mechanisms of pathogens.
2015-07-27
University, Manassas, VA, USA, 4 PerkinElmer, Inc., Waltham, MA, USA Burkholderia is a diverse genus of gram-negative bacteria that causes high...Burkholderia spp. infections. Materials and Methods Bacterial Strains Bm ATCC 23344, NCTC 10247, NCTC 10229, NCTC 3708, NCTC 3709, 2002721278 (Burtnick...macrophage cell line RAW264.7 was obtained from ATCC (Manassas, VA). Cells were cultured in DMEM (Life Technologies) supplemented with 10% fetal
Microarrays for Undergraduate Classes
ERIC Educational Resources Information Center
Hancock, Dale; Nguyen, Lisa L.; Denyer, Gareth S.; Johnston, Jill M.
2006-01-01
A microarray experiment is presented that, in six laboratory sessions, takes undergraduate students from the tissue sample right through to data analysis. The model chosen, the murine erythroleukemia cell line, can be easily cultured in sufficient quantities for class use. Large changes in gene expression can be induced in these cells by…
Gu, Yunfu; D. Van Nostrand, Joy; Wu, Liyou; He, Zhili; Qin, Yujia; Zhao, Fang-Jie; Zhou, Jizhong
2017-01-01
To understand how soil microbial communities and arsenic (As) functional genes respond to soil arsenic (As) contamination, five soils contaminated with As at different levels were collected from diverse geographic locations, incubated for 54 days under flooded conditions, and examined by both MiSeq sequencing of 16S rRNA gene amplicons and functional gene microarray (GeoChip 4.0). The results showed that both bacterial community structure and As functional gene structure differed among geographical locations. The diversity of As functional genes correlated positively with the diversity of 16S rRNA genes (P< 0.05). Higher diversities of As functional genes and 16S rRNA genes were observed in the soils with higher available As. Soil pH, phosphate-extractable As, and amorphous Fe content were the most important factors in shaping the bacterial community structure and As transformation functional genes. Geographic location was also important in controlling both the bacterial community and As transformation functional potential. These findings provide insights into the variation of As transformation functional genes in soils contaminated with different levels of As at different geographic locations, and the impact of environmental As contamination on the soil bacterial community. PMID:28475654
Zhu, Yuerong; Zhu, Yuelin; Xu, Wei
2008-01-01
Background Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand. Results EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data. Conclusion EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from . PMID:18218103
Development and application of a microarray meter tool to optimize microarray experiments
Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary
2008-01-01
Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498
Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki
2010-06-01
Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.
Mining meiosis and gametogenesis with DNA microarrays.
Schlecht, Ulrich; Primig, Michael
2003-04-01
Gametogenesis is a key developmental process that involves complex transcriptional regulation of numerous genes including many that are conserved between unicellular eukaryotes and mammals. Recent expression-profiling experiments using microarrays have provided insight into the co-ordinated transcription of several hundred genes during mitotic growth and meiotic development in budding and fission yeast. Furthermore, microarray-based studies have identified numerous loci that are regulated during the cell cycle or expressed in a germ-cell specific manner in eukaryotic model systems like Caenorhabditis elegans, Mus musculus as well as Homo sapiens. The unprecedented amount of information produced by post-genome biology has spawned novel approaches to organizing biological knowledge using currently available information technology. This review outlines experiments that contribute to an emerging comprehensive picture of the molecular machinery governing sexual reproduction in eukaryotes.
Computational synchronization of microarray data with application to Plasmodium falciparum.
Zhao, Wei; Dauwels, Justin; Niles, Jacquin C; Cao, Jianshu
2012-06-21
Microarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data. We develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC. By analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions. This study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved in this process. Overall, these results indicate that further functional analysis of these additional putative protein kinases may reveal new insights into how the P. falciparum IDC is regulated.
2010-01-01
Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115
MiMiR – an integrated platform for microarray data sharing, mining and analysis
Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence
2008-01-01
Background Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies. PMID:18801157
MiMiR--an integrated platform for microarray data sharing, mining and analysis.
Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence
2008-09-18
Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.
Construction of a cDNA microarray derived from the ascidian Ciona intestinalis.
Azumi, Kaoru; Takahashi, Hiroki; Miki, Yasufumi; Fujie, Manabu; Usami, Takeshi; Ishikawa, Hisayoshi; Kitayama, Atsusi; Satou, Yutaka; Ueno, Naoto; Satoh, Nori
2003-10-01
A cDNA microarray was constructed from a basal chordate, the ascidian Ciona intestinalis. The draft genome of Ciona has been read and inferred to contain approximately 16,000 protein-coding genes, and cDNAs for transcripts of 13,464 genes have been characterized and compiled as the "Ciona intestinalis Gene Collection Release I". In the present study, we constructed a cDNA microarray of these 13,464 Ciona genes. A preliminary experiment with Cy3- and Cy5-labeled probes showed extensive differential gene expression between fertilized eggs and larvae. In addition, there was a good correlation between results obtained by the present microarray analysis and those from previous EST analyses. This first microarray of a large collection of Ciona intestinalis cDNA clones should facilitate the analysis of global gene expression and gene networks during the embryogenesis of basal chordates.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gentry, T.; Schadt, C.; Zhou, J.
Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. Thismore » review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.« less
Correcting for batch effects in case-control microbiome studies
Gibbons, Sean M.; Duvallet, Claire
2018-01-01
High-throughput data generation platforms, like mass-spectrometry, microarrays, and second-generation sequencing are susceptible to batch effects due to run-to-run variation in reagents, equipment, protocols, or personnel. Currently, batch correction methods are not commonly applied to microbiome sequencing datasets. In this paper, we compare different batch-correction methods applied to microbiome case-control studies. We introduce a model-free normalization procedure where features (i.e. bacterial taxa) in case samples are converted to percentiles of the equivalent features in control samples within a study prior to pooling data across studies. We look at how this percentile-normalization method compares to traditional meta-analysis methods for combining independent p-values and to limma and ComBat, widely used batch-correction models developed for RNA microarray data. Overall, we show that percentile-normalization is a simple, non-parametric approach for correcting batch effects and improving sensitivity in case-control meta-analyses. PMID:29684016
Evaluating concentration estimation errors in ELISA microarray experiments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Daly, Don S.; White, Amanda M.; Varnum, Susan M.
Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Althoughmore » propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.« less
A Java-based tool for the design of classification microarrays.
Meng, Da; Broschat, Shira L; Call, Douglas R
2008-08-04
Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.
EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments
Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A
2009-01-01
Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE3 provides a means for managing RNA samples and arrays during the hybridization process. EDGE3 is freely available for download at . PMID:19732451
Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A
2009-09-04
The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE(3) was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. EDGE(3) has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE(3) is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Here, we present EDGE(3), an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE(3) provides a means for managing RNA samples and arrays during the hybridization process. EDGE(3) is freely available for download at http://edge.oncology.wisc.edu/.
Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C
2014-08-04
Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.
Engineering Improvements in a Bacterial Therapeutic Delivery System for Breast Cancer
2009-09-01
curve is observed on the other platform (Supplementary Figure 2H). Although it is not the object of this article to explore a physical explanation for...light-directed oligonucleotide microarrays using a digital micromirror array.. Nat Biotechnol, 17(10), 974–978. [12] Matveeva, O. V., Shabalina, S. A...Rouillard, J. M., Whittam, T. S., Gulari, E., Tiedje, J. M., and Hashsham, S. A. (2006) On- chip non-equilibrium dissociation curves and dissociation
Qi, Yong; Xiong, Xiaolu; Wang, Xile; Duan, Changsong; Jia, Yinjun; Jiao, Jun; Gong, Wenping; Wen, Bohai
2013-01-01
Background Rickettsia heilongjiangensis, the agent of Far-Eastern spotted fever (FESF), is an obligate intracellular bacterium. The surface-exposed proteins (SEPs) of rickettsiae are involved in rickettsial adherence to and invasion of host cells, intracellular bacterial growth, and/or interaction with immune cells. They are also potential molecular candidates for the development of diagnostic reagents and vaccines against rickettsiosis. Methods R. heilongjiangensis SEPs were identified by biotin-streptavidin affinity purification and 2D electrophoreses coupled with ESI-MS/MS. Recombinant SEPs were probed with various sera to analyze their serological characteristics using a protein microarray and an enzyme-linked immune sorbent assay (ELISA). Results Twenty-five SEPs were identified, most of which were predicted to reside on the surface of R. heilongjiangensis cells. Bioinformatics analysis suggests that these proteins could be involved in bacterial pathogenesis. Eleven of the 25 SEPs were recognized as major seroreactive antigens by sera from R. heilongjiangensis-infected mice and FESF patients. Among the major seroreactive SEPs, microarray assays and/or ELISAs revealed that GroEL, OmpA-2, OmpB-3, PrsA, RplY, RpsB, SurA and YbgF had modest sensitivity and specificity for recognizing R. heilongjiangensis infection and/or spotted fever. Conclusions Many of the SEPs identified herein have potentially important roles in R. heilongjiangensis pathogenicity. Some of them have potential as serodiagnostic antigens or as subunit vaccine antigens against the disease. PMID:23894656
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brodie, Eoin L.; DeSantis, Todd Z.; Joyner, Dominique C.
2006-01-30
Reduction of soluble uranium U(VI) to less-soluble uraniumU(IV) is a promising approach to minimize migration from contaminatedaquifers. It is generally assumed that, under constant reducingconditions, U(IV) is stable and immobile; however, in a previous study,we documented reoxidation of U(IV) under continuous reducing conditions(Wan et al., Environ. Sci. Technol. 2005, 39:6162 6169). To determine ifchanges in microbial community composition were a factor in U(IV)reoxidation, we employed a high-density phylogenetic DNA microarray (16Smicroarray) containing 500,000 probes to monitor changes in bacterialpopulations during this remediation process. Comparison of the 16Smicroarray with clone libraries demonstrated successful detection andclassification of most clone groups. Analysis ofmore » the most dynamic groupsof 16S rRNA gene amplicons detected by the 16S microarray identified fiveclusters of bacterial subfamilies responding in a similar manner. Thisapproach demonstrated that amplicons of known metal-reducing bacteriasuch as Geothrix fermentans (confirmed by quantitative PCR) and thosewithin the Geobacteraceae were abundant during U(VI) reduction and didnot decline during the U(IV) reoxidation phase. Significantly, it appearsthat the observed reoxidation of uranium under reducing conditionsoccurred despite elevated microbial activity and the consistent presenceof metal-reducing bacteria. High-density phylogenetic microarraysconstitute a powerful tool, enabling the detection and monitoring of asubstantial portion of the microbial population in a routine, accurate,and reproducible manner.« less
Plant-pathogen interactions: what microarray tells about it?
Lodha, T D; Basak, J
2012-01-01
Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.
Modrák, Martin; Vohradský, Jiří
2018-04-13
Identifying regulons of sigma factors is a vital subtask of gene network inference. Integrating multiple sources of data is essential for correct identification of regulons and complete gene regulatory networks. Time series of expression data measured with microarrays or RNA-seq combined with static binding experiments (e.g., ChIP-seq) or literature mining may be used for inference of sigma factor regulatory networks. We introduce Genexpi: a tool to identify sigma factors by combining candidates obtained from ChIP experiments or literature mining with time-course gene expression data. While Genexpi can be used to infer other types of regulatory interactions, it was designed and validated on real biological data from bacterial regulons. In this paper, we put primary focus on CyGenexpi: a plugin integrating Genexpi with the Cytoscape software for ease of use. As a part of this effort, a plugin for handling time series data in Cytoscape called CyDataseries has been developed and made available. Genexpi is also available as a standalone command line tool and an R package. Genexpi is a useful part of gene network inference toolbox. It provides meaningful information about the composition of regulons and delivers biologically interpretable results.
Higashibata, Akira; Hashizume, Toko; Nemoto, Kanako; Higashitani, Nahoko; Etheridge, Timothy; Mori, Chihiro; Harada, Shunsuke; Sugimoto, Tomoko; Szewczyk, Nathaniel J; Baba, Shoji A; Mogami, Yoshihiro; Fukui, Keiji; Higashitani, Atsushi
2016-01-01
Although muscle atrophy is a serious problem during spaceflight, little is known about the sequence of molecular events leading to atrophy in response to microgravity. We carried out a spaceflight experiment using Caenorhabditis elegans onboard the Japanese Experiment Module of the International Space Station. Worms were synchronously cultured in liquid media with bacterial food for 4 days under microgravity or on a 1-G centrifuge. Worms were visually observed for health and movement and then frozen. Upon return, we analyzed global gene and protein expression using DNA microarrays and mass spectrometry. Body length and fat accumulation were also analyzed. We found that in worms grown from the L1 larval stage to adulthood under microgravity, both gene and protein expression levels for muscular thick filaments, cytoskeletal elements, and mitochondrial metabolic enzymes decreased relative to parallel cultures on the 1-G centrifuge (95% confidence interval (P⩽0.05)). In addition, altered movement and decreased body length and fat accumulation were observed in the microgravity-cultured worms relative to the 1-G cultured worms. These results suggest protein expression changes that may account for the progressive muscular atrophy observed in astronauts. PMID:28725720
ERIC Educational Resources Information Center
Bradford, William D.; Cahoon, Laty; Freel, Sara R.; Hoopes, Laura L. Mays; Eckdahl, Todd T.
2005-01-01
In order to engage their students in a core methodology of the new genomics era, an everincreasing number of faculty at primarily undergraduate institutions are gaining access to microarray technology. Their students are conducting successful microarray experiments designed to address a variety of interesting questions. A next step in these…
Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart
2017-05-01
Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.
Druart, Céline; Dewulf, Evelyne M; Cani, Patrice D; Neyrinck, Audrey M; Thissen, Jean-Paul; Delzenne, Nathalie M
2014-04-01
The aim of this human study was to assess the influence of prebiotic-induced gut microbiota modulation on PUFA-derived bacterial metabolites production. Therefore, we analyzed the circulating fatty acid profile including CLA/CLnA in obese women treated during 3 months with inulin-type fructan prebiotics. In these patients, we had already determined gut microbiota composition by phylogenetic microarray and qPCR analysis of 16S rDNA. Some PUFA-derived bacterial metabolites were detected in the serum of obese patients. Despite the prebiotic-induced modulation of gut microbiota, including changes in CLA/CLnA-producing bacteria, the treatment did not impact significantly on the circulating level of these metabolites. However, some PUFA-derived bacterial metabolites were positively correlated with specific fecal bacteria (Bifidobacterium spp., Eubacterium ventriosum and Lactobacillus spp.) and inversely correlated with serum cholesterol (total, LDL, HDL). These correlations suggest a potential beneficial effect of some of these metabolites but this remains to be confirmed by further investigation.
High-throughput Identification of Bacteria Repellent Polymers for Medical Devices
Wu, Mei; Hardman, Ailsa; Lilienkampf, Annamaria; Pernagallo, Salvatore; Blakely, Garry; Swann, David G.; Bradley, Mark; Gallagher, Maurice P.
2016-01-01
Medical devices are often associated with hospital-acquired infections, which place enormous strain on patients and the healthcare system as well as contributing to antimicrobial resistance. One possible avenue for the reduction of device-associated infections is the identification of bacteria-repellent polymer coatings for these devices, which would prevent bacterial binding at the initial attachment step. A method for the identification of such repellent polymers, based on the parallel screening of hundreds of polymers using a microarray, is described here. This high-throughput method resulted in the identification of a range of promising polymers that resisted binding of various clinically relevant bacterial species individually and also as multi-species communities. One polymer, PA13 (poly(methylmethacrylate-co-dimethylacrylamide)), demonstrated significant reduction in attachment of a number of hospital isolates when coated onto two commercially available central venous catheters. The method described could be applied to identify polymers for a wide range of applications in which modification of bacterial attachment is important. PMID:27842360
Thormar, Hans G; Gudmundsson, Bjarki; Eiriksdottir, Freyja; Kil, Siyoen; Gunnarsson, Gudmundur H; Magnusson, Magnus Karl; Hsu, Jason C; Jonsson, Jon J
2013-04-01
The causes of imprecision in microarray expression analysis are poorly understood, limiting the use of this technology in molecular diagnostics. Two-dimensional strandness-dependent electrophoresis (2D-SDE) separates nucleic acid molecules on the basis of length and strandness, i.e., double-stranded DNA (dsDNA), single-stranded DNA (ssDNA), and RNA·DNA hybrids. We used 2D-SDE to measure the efficiency of cDNA synthesis and its importance for the imprecision of an in vitro transcription-based microarray expression analysis. The relative amount of double-stranded cDNA formed in replicate experiments that used the same RNA sample template was highly variable, ranging between 0% and 72% of the total DNA. Microarray experiments showed an inverse relationship between the difference between sample pairs in probe variance and the relative amount of dsDNA. Approximately 15% of probes showed between-sample variation (P < 0.05) when the dsDNA percentage was between 12% and 35%. In contrast, only 3% of probes showed between-sample variation when the dsDNA percentage was 69% and 72%. Replication experiments of the 35% dsDNA and 72% dsDNA samples were used to separate sample variation from probe replication variation. The estimated SD of the sample-to-sample variation and of the probe replicates was lower in 72% dsDNA samples than in 35% dsDNA samples. Variation in the relative amount of double-stranded cDNA synthesized can be an important component of the imprecision in T7 RNA polymerase-based microarray expression analysis. © 2013 American Association for Clinical Chemistry
Barret, M; Frey-Klett, P; Boutin, M; Guillerm-Erckelboudt, A-Y; Martin, F; Guillot, L; Sarniguet, A
2009-01-01
In soil, some antagonistic rhizobacteria contribute to reduce root diseases caused by phytopathogenic fungi. Direct modes of action of these bacteria have been largely explored; however, commensal interaction also takes place between these microorganisms and little is known about the influence of filamentous fungi on bacteria. An in vitro confrontation bioassay between the pathogenic fungus Gaeumannomyces graminis var. tritici (Ggt) and the biocontrol bacterial strain Pseudomonas fluorescens Pf29Arp was set up to analyse bacterial transcriptional changes induced by the fungal mycelium at three time-points of the interaction before cell contact and up until contact. For this, a Pf29Arp shotgun DNA microarray was constructed. Specifity of Ggt effect was assessed in comparison with one of two other filamentous fungi, Laccaria bicolor and Magnaporthe grisea. During a commensal interaction, Ggt increased the growth rate of Pf29Arp. Before contact, Ggt induced bacterial genes involved in mycelium colonization. At contact, genes encoding protein of stress response and a patatin-like protein were up-regulated. Among all the bacterial genes identified, xseB was specifically up-regulated at contact by Ggt but down-regulated by the other fungi. Data showed that the bacterium sensed the presence of the fungus early, but the main gene alteration occurred during bacterial-fungal cell contact.
Predicting effects of climate change on the composition and function of soil microbial communities
NASA Astrophysics Data System (ADS)
Dubinsky, E.; Brodie, E.; Myint, C.; Ackerly, D.; van Nostrand, J.; Bird, J.; Zhou, J.; Andersen, G.; Firestone, M.
2008-12-01
Complex soil microbial communities regulate critical ecosystem processes that will be altered by climate change. A critical step towards predicting the impacts of climate change on terrestrial ecosystems is to determine the primary controllers of soil microbial community composition and function, and subsequently evaluate climate change scenarios that alter these controllers. We surveyed complex soil bacterial and archaeal communities across a range of climatic and edaphic conditions to identify critical controllers of soil microbial community composition in the field and then tested the resulting predictions using a 2-year manipulation of precipitation and temperature using mesocosms of California annual grasslands. Community DNA extracted from field soils sampled from six different ecosystems was assayed for bacterial and archaeal communities using high-density phylogenetic microarrays as well as functional gene arrays. Correlations among the relative abundances of thousands of microbial taxa and edaphic factors such as soil moisture and nutrient content provided a basis for predicting community responses to changing soil conditions. Communities of soil bacteria and archaea were strongly structured by single environmental predictors, particularly variables related to soil water. Bacteria in the Actinomycetales and Bacilli consistently demonstrated a strong negative response to increasing soil moisture, while taxa in a greater variety of lineages responded positively to increasing soil moisture. In the climate change experiment, overall bacterial community structure was impacted significantly by total precipitation but not by plant species. Changes in soil moisture due to decreased rainfall resulted in significant and predictable alterations in community structure. Over 70% of the bacterial taxa in common with the cross-ecosystem study responded as predicted to altered precipitation, with the most conserved response from Actinobacteria. The functional consequences of these predictable changes in community composition were measured with functional arrays that detect genes involved in the metabolism of carbon, nitrogen and other elements. The response of soil microbial communities to altered precipitation can be predicted from the distribution of microbial taxa across moisture gradients.
An object model and database for functional genomics.
Jones, Andrew; Hunt, Ela; Wastling, Jonathan M; Pizarro, Angel; Stoeckert, Christian J
2004-07-10
Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI-Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis. FGE-OM and the RAPAD schema are available from http://www.gusdb.org/fge.html, along with a set of more detailed diagrams. RAPAD can be accessed by registration at the site.
Deutsch, Eric W; Ball, Catherine A; Berman, Jules J; Bova, G Steven; Brazma, Alvis; Bumgarner, Roger E; Campbell, David; Causton, Helen C; Christiansen, Jeffrey H; Daian, Fabrice; Dauga, Delphine; Davidson, Duncan R; Gimenez, Gregory; Goo, Young Ah; Grimmond, Sean; Henrich, Thorsten; Herrmann, Bernhard G; Johnson, Michael H; Korb, Martin; Mills, Jason C; Oudes, Asa J; Parkinson, Helen E; Pascal, Laura E; Pollet, Nicolas; Quackenbush, John; Ramialison, Mirana; Ringwald, Martin; Salgado, David; Sansone, Susanna-Assunta; Sherlock, Gavin; Stoeckert, Christian J; Swedlow, Jason; Taylor, Ronald C; Walashek, Laura; Warford, Anthony; Wilkinson, David G; Zhou, Yi; Zon, Leonard I; Liu, Alvin Y; True, Lawrence D
2008-03-01
One purpose of the biomedical literature is to report results in sufficient detail that the methods of data collection and analysis can be independently replicated and verified. Here we present reporting guidelines for gene expression localization experiments: the minimum information specification for in situ hybridization and immunohistochemistry experiments (MISFISHIE). MISFISHIE is modeled after the Minimum Information About a Microarray Experiment (MIAME) specification for microarray experiments. Both guidelines define what information should be reported without dictating a format for encoding that information. MISFISHIE describes six types of information to be provided for each experiment: experimental design, biomaterials and treatments, reporters, staining, imaging data and image characterizations. This specification has benefited the consortium within which it was developed and is expected to benefit the wider research community. We welcome feedback from the scientific community to help improve our proposal.
Gomi, Kenji; Satoh, Masaru; Ozawa, Rika; Shinonaga, Yumi; Sanada, Sachiyo; Sasaki, Katsutomo; Matsumura, Masaya; Ohashi, Yuko; Kanno, Hiroo; Akimitsu, Kazuya; Takabayashi, Junji
2010-01-01
A pre-infestation of the white-backed planthopper (WBPH), Sogatella furcifera Horváth, conferred resistance to bacterial blight caused by Xanthomonas oryzae pv. oryzae (Xoo) in rice (Oryza sativa L.) under both laboratory and field conditions. The infestation of another planthopper species, the brown planthopper (BPH) Nilaparvata lugens Stål, did not significantly reduce the incidence of bacterial blight symptoms. A large-scale screening using a rice DNA microarray and quantitative RT-PCR revealed that WBPH infestation caused the upregulation of more defence-related genes than did BPH infestation. Hydroperoxide lyase 2 (OsHPL2), an enzyme for producing C(6) volatiles, was upregulated by WBPH infestation, but not by BPH infestation. One C(6) volatile, (E)-2-hexenal, accumulated in rice after WBPH infestation, but not after BPH infestation. A direct application of (E)-2-hexenal to a liquid culture of Xoo inhibited the growth of the bacterium. Furthermore, a vapour treatment of rice plants with (E)-2-hexenal induced resistance to bacterial blight. OsHPL2-overexpressing transgenic rice plants exhibited increased resistance to bacterial blight. Based on these data, we conclude that OsHPL2 and its derived (E)-2-hexenal play some role in WBPH-induced resistance in rice.
Kim, Jeong-Soon; Sagaram, Uma Shankar; Burns, Jacqueline K; Li, Jian-Liang; Wang, Nian
2009-01-01
Citrus greening or huanglongbing (HLB) is a devastating disease of citrus. HLB is associated with the phloem-limited fastidious prokaryotic alpha-proteobacterium 'Candidatus Liberibacter spp.' In this report, we used sweet orange (Citrus sinensis) leaf tissue infected with 'Ca. Liberibacter asiaticus' and compared this with healthy controls. Investigation of the host response was examined with citrus microarray hybridization based on 33,879 expressed sequence tag sequences from several citrus species and hybrids. The microarray analysis indicated that HLB infection significantly affected expression of 624 genes whose encoded proteins were categorized according to function. The categories included genes associated with sugar metabolism, plant defense, phytohormone, and cell wall metabolism, as well as 14 other gene categories. The anatomical analyses indicated that HLB bacterium infection caused phloem disruption, sucrose accumulation, and plugged sieve pores. The up-regulation of three key starch biosynthetic genes including ADP-glucose pyrophosphorylase, starch synthase, granule-bound starch synthase and starch debranching enzyme likely contributed to accumulation of starch in HLB-affected leaves. The HLB-associated phloem blockage resulted from the plugged sieve pores rather than the HLB bacterial aggregates since 'Ca. Liberibacter asiaticus' does not form aggregate in citrus. The up-regulation of pp2 gene is related to callose deposition to plug the sieve pores in HLB-affected plants.
Qin, Wanhai; Wang, Lei; Zhai, Ruidong; Ma, Qiuyue; Liu, Jianfang; Bao, Chuntong; Zhang, Hu; Sun, Changjiang; Feng, Xin; Gu, Jingmin; Du, Chongtao; Han, Wenyu; Langford, P R; Lei, Liancheng
2016-01-01
Actinobacillus pleuropneumoniae is an important pathogen that causes respiratory disease in pigs. Trimeric autotransporter adhesin (TAA) is a recently discovered bacterial virulence factor that mediates bacterial adhesion and colonization. Two TAA coding genes have been found in the genome of A. pleuropneumoniae strain 5b L20, but whether they contribute to bacterial pathogenicity is unclear. In this study, we used homologous recombination to construct a double-gene deletion mutant, ΔTAA, in which both TAA coding genes were deleted and used it in in vivo and in vitro studies to confirm that TAAs participate in bacterial auto-aggregation, biofilm formation, cell adhesion and virulence in mice. A microarray analysis was used to determine whether TAAs can regulate other A. pleuropneumoniae genes during interactions with porcine primary alveolar macrophages. The results showed that deletion of both TAA coding genes up-regulated 36 genes, including ene1514, hofB and tbpB2, and simultaneously down-regulated 36 genes, including lgt, murF and ftsY. These data illustrate that TAAs help to maintain full bacterial virulence both directly, through their bioactivity, and indirectly by regulating the bacterial type II and IV secretion systems and regulating the synthesis or secretion of virulence factors. This study not only enhances our understanding of the role of TAAs but also has significance for those studying A. pleuropneumoniae pathogenesis.
Methods to Assess the Direct Interaction of C. jejuni with Mucins.
Clyne, Marguerite; Duggan, Gina; Naughton, Julie; Bourke, Billy
2017-01-01
Studies of the interaction of bacteria with mucus-secreting cells can be complemented at a more mechanistic level by exploring the interaction of bacteria with purified mucins. Here we describe a far Western blotting approach to show how C. jejuni proteins separated by SDS PAGE and transferred to a membrane or slot blotted directly onto a membrane can be probed using biotinylated mucin. In addition we describe the use of novel mucin microarrays to assess bacterial interactions with mucins in a high-throughput manner.
Stochastic models for inferring genetic regulation from microarray gene expression data.
Tian, Tianhai
2010-03-01
Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information. 2009 Elsevier Ireland Ltd. All rights reserved.
Application of Immunosignatures for Diagnosis of Valley Fever
Navalkar, Krupa Arun; Johnston, Stephen Albert; Woodbury, Neal; Galgiani, John N.; Magee, D. Mitchell; Chicacz, Zbigniew
2014-01-01
Valley fever (VF) is difficult to diagnose, partly because the symptoms of VF are confounded with those of other community-acquired pneumonias. Confirmatory diagnostics detect IgM and IgG antibodies against coccidioidal antigens via immunodiffusion (ID). The false-negative rate can be as high as 50% to 70%, with 5% of symptomatic patients never showing detectable antibody levels. In this study, we tested whether the immunosignature diagnostic can resolve VF false negatives. An immunosignature is the pattern of antibody binding to random-sequence peptides on a peptide microarray. A 10,000-peptide microarray was first used to determine whether valley fever patients can be distinguished from 3 other cohorts with similar infections. After determining the VF-specific peptides, a small 96-peptide diagnostic array was created and tested. The performances of the 10,000-peptide array and the 96-peptide diagnostic array were compared to that of the ID diagnostic standard. The 10,000-peptide microarray classified the VF samples from the other 3 infections with 98% accuracy. It also classified VF false-negative patients with 100% sensitivity in a blinded test set versus 28% sensitivity for ID. The immunosignature microarray has potential for simultaneously distinguishing valley fever patients from those with other fungal or bacterial infections. The same 10,000-peptide array can diagnose VF false-negative patients with 100% sensitivity. The smaller 96-peptide diagnostic array was less specific for diagnosing false negatives. We conclude that the performance of the immunosignature diagnostic exceeds that of the existing standard, and the immunosignature can distinguish related infections and might be used in lieu of existing diagnostics. PMID:24964807
Emerging Use of Gene Expression Microarrays in Plant Physiology
Wullschleger, Stan D.; Difazio, Stephen P.
2003-01-01
Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less
Zhao, Yangyang; Qian, Guoliang; Chen, Yuan; Du, Liangcheng; Liu, Fengquan
2017-01-01
Lysobacter enzymogenes is a ubiquitous, beneficial, plant-associated bacterium emerging as a novel biological control agent. It has the potential to become a new source of antimicrobial secondary metabolites such as the Heat-Stable Antifungal Factor (HSAF), which is a broad-spectrum antimycotic with a novel mode of action. However, very little information about how L. enzymogenes detects and responds to fungi or oomycetes has been reported. An in vitro confrontation bioassay between the pathogenic oomycete Pythium aphanidermatum and the biocontrol bacterial strain L. enzymogenes OH11 was used to analyze the transcriptional changes in the bacteria that were induced by the oomycetes. Analysis was performed at three time points of the interaction, starting before inhibition zone formation until inhibition zone formation. A L. enzymogenes OH11 DNA microarray was constructed for the analysis. Microarray analysis indicated that a wide range of genes belonging to 14 diverse functions in L. enzymogenes were affected by P. aphanidermatum as critical antagonistic effects occurred. L. enzymogenes detected and responded to the presence of P. aphanidermatum early, but alteration of gene expression typically occurred after inhibition zone formation. The presence of P. aphanidermatum increased the twitching motility and HSAF production in L. enzymogenes. We also performed a contact interaction between L. enzymogenes and P. aphanidermatum, and found that HSAF played a critical role in the interaction. Our experiments demonstrated that L. enzymogenes displayed transcriptional and antagonistic responses to P. aphanidermatum in order to gain advantages in the competition with this oomycete. This study revealed new insights into the interactions between bacteria and oomycete. PMID:28634478
Zhao, Yangyang; Qian, Guoliang; Chen, Yuan; Du, Liangcheng; Liu, Fengquan
2017-01-01
Lysobacter enzymogenes is a ubiquitous, beneficial, plant-associated bacterium emerging as a novel biological control agent. It has the potential to become a new source of antimicrobial secondary metabolites such as the Heat-Stable Antifungal Factor (HSAF), which is a broad-spectrum antimycotic with a novel mode of action. However, very little information about how L. enzymogenes detects and responds to fungi or oomycetes has been reported. An in vitro confrontation bioassay between the pathogenic oomycete Pythium aphanidermatum and the biocontrol bacterial strain L. enzymogenes OH11 was used to analyze the transcriptional changes in the bacteria that were induced by the oomycetes. Analysis was performed at three time points of the interaction, starting before inhibition zone formation until inhibition zone formation. A L. enzymogenes OH11 DNA microarray was constructed for the analysis. Microarray analysis indicated that a wide range of genes belonging to 14 diverse functions in L. enzymogenes were affected by P. aphanidermatum as critical antagonistic effects occurred. L. enzymogenes detected and responded to the presence of P. aphanidermatum early, but alteration of gene expression typically occurred after inhibition zone formation. The presence of P. aphanidermatum increased the twitching motility and HSAF production in L. enzymogenes . We also performed a contact interaction between L. enzymogenes and P. aphanidermatum , and found that HSAF played a critical role in the interaction. Our experiments demonstrated that L. enzymogenes displayed transcriptional and antagonistic responses to P. aphanidermatum in order to gain advantages in the competition with this oomycete. This study revealed new insights into the interactions between bacteria and oomycete.
Immunological Targeting of Tumor Initiating Prostate Cancer Cells
2014-10-01
clinically using well-accepted immuno-competent animal models. 2) Keywords: Prostate Cancer, Lymphocyte, Vaccine, Antibody 3) Overall Project Summary...castrate animals . Task 1: Identify and verify antigenic targets from CAstrate Resistant Luminal Epithelial Cells (CRLEC) (months 1-16... animals per group will be processed to derive sufficient RNA for microarray analysis; the experiment will be repeated x 3. Microarray analysis will
Reuse of imputed data in microarray analysis increases imputation efficiency
Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su
2004-01-01
Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240
Geue, Lutz; Stieber, Bettina; Monecke, Stefan; Engelmann, Ines; Gunzer, Florian; Slickers, Peter; Braun, Sascha D; Ehricht, Ralf
2014-08-01
In this study, we developed a new rapid, economic, and automated microarray-based genotyping test for the standardized subtyping of Shiga toxins 1 and 2 of Escherichia coli. The microarrays from Alere Technologies can be used in two different formats, the ArrayTube and the ArrayStrip (which enables high-throughput testing in a 96-well format). One microarray chip harbors all the gene sequences necessary to distinguish between all Stx subtypes, facilitating the identification of single and multiple subtypes within a single isolate in one experiment. Specific software was developed to automatically analyze all data obtained from the microarray. The assay was validated with 21 Shiga toxin-producing E. coli (STEC) reference strains that were previously tested by the complete set of conventional subtyping PCRs. The microarray results showed 100% concordance with the PCR results. Essentially identical results were detected when the standard DNA extraction method was replaced by a time-saving heat lysis protocol. For further validation of the microarray, we identified the Stx subtypes or combinations of the subtypes in 446 STEC field isolates of human and animal origin. In summary, this oligonucleotide array represents an excellent diagnostic tool that provides some advantages over standard PCR-based subtyping. The number of the spotted probes on the microarrays can be increased by additional probes, such as for novel alleles, species markers, or resistance genes, should the need arise. Copyright © 2014, American Society for Microbiology. All Rights Reserved.
Estimation of gene induction enables a relevance-based ranking of gene sets.
Bartholomé, Kilian; Kreutz, Clemens; Timmer, Jens
2009-07-01
In order to handle and interpret the vast amounts of data produced by microarray experiments, the analysis of sets of genes with a common biological functionality has been shown to be advantageous compared to single gene analyses. Some statistical methods have been proposed to analyse the differential gene expression of gene sets in microarray experiments. However, most of these methods either require threshhold values to be chosen for the analysis, or they need some reference set for the determination of significance. We present a method that estimates the number of differentially expressed genes in a gene set without requiring a threshold value for significance of genes. The method is self-contained (i.e., it does not require a reference set for comparison). In contrast to other methods which are focused on significance, our approach emphasizes the relevance of the regulation of gene sets. The presented method measures the degree of regulation of a gene set and is a useful tool to compare the induction of different gene sets and place the results of microarray experiments into the biological context. An R-package is available.
Tra, Yolande V; Evans, Irene M
2010-01-01
BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.
WebArray: an online platform for microarray data analysis
Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng
2005-01-01
Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165
Evans, Irene M.
2010-01-01
BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954
Autoregressive-model-based missing value estimation for DNA microarray time series data.
Choong, Miew Keen; Charbit, Maurice; Yan, Hong
2009-01-01
Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goldfarb, K.C.; Karaoz, U.; Hanson, C.A.
2011-04-18
Soils are immensely diverse microbial habitats with thousands of co-existing bacterial, archaeal, and fungal species. Across broad spatial scales, factors such as pH and soil moisture appear to determine the diversity and structure of soil bacterial communities. Within any one site however, bacterial taxon diversity is high and factors maintaining this diversity are poorly resolved. Candidate factors include organic substrate availability and chemical recalcitrance, and given that they appear to structure bacterial communities at the phylum level, we examine whether these factors might structure bacterial communities at finer levels of taxonomic resolution. Analyzing 16S rRNA gene composition of nucleotide analog-labeledmore » DNA by PhyloChip microarrays, we compare relative growth rates on organic substrates of increasing chemical recalcitrance of >2,200 bacterial taxa across 43 divisions/phyla. Taxa that increase in relative abundance with labile organic substrates (i.e., glycine, sucrose) are numerous (>500), phylogenetically clustered, and occur predominantly in two phyla (Proteobacteria and Actinobacteria) including orders Actinomycetales, Enterobacteriales, Burkholderiales, Rhodocyclales, Alteromonadales, and Pseudomonadales. Taxa increasing in relative abundance with more chemically recalcitrant substrates (i.e., cellulose, lignin, or tannin-protein) are fewer (168) but more phylogenetically dispersed, occurring across eight phyla and including Clostridiales, Sphingomonadalaes, Desulfovibrionales. Just over 6% of detected taxa, including many Burkholderiales increase in relative abundance with both labile and chemically recalcitrant substrates. Estimates of median rRNA copy number per genome of responding taxa demonstrate that these patterns are broadly consistent with bacterial growth strategies. Taken together, these data suggest that changes in availability of intrinsically labile substrates may result in predictable shifts in soil bacterial composition.« less
Deutsch, Eric W; Ball, Catherine A; Berman, Jules J; Bova, G Steven; Brazma, Alvis; Bumgarner, Roger E; Campbell, David; Causton, Helen C; Christiansen, Jeffrey H; Daian, Fabrice; Dauga, Delphine; Davidson, Duncan R; Gimenez, Gregory; Goo, Young Ah; Grimmond, Sean; Henrich, Thorsten; Herrmann, Bernhard G; Johnson, Michael H; Korb, Martin; Mills, Jason C; Oudes, Asa J; Parkinson, Helen E; Pascal, Laura E; Pollet, Nicolas; Quackenbush, John; Ramialison, Mirana; Ringwald, Martin; Salgado, David; Sansone, Susanna-Assunta; Sherlock, Gavin; Stoeckert, Christian J; Swedlow, Jason; Taylor, Ronald C; Walashek, Laura; Warford, Anthony; Wilkinson, David G; Zhou, Yi; Zon, Leonard I; Liu, Alvin Y; True, Lawrence D
2015-01-01
One purpose of the biomedical literature is to report results in sufficient detail so that the methods of data collection and analysis can be independently replicated and verified. Here we present for consideration a minimum information specification for gene expression localization experiments, called the “Minimum Information Specification For In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE)”. It is modelled after the MIAME (Minimum Information About a Microarray Experiment) specification for microarray experiments. Data specifications like MIAME and MISFISHIE specify the information content without dictating a format for encoding that information. The MISFISHIE specification describes six types of information that should be provided for each experiment: Experimental Design, Biomaterials and Treatments, Reporters, Staining, Imaging Data, and Image Characterizations. This specification has benefited the consortium within which it was initially developed and is expected to benefit the wider research community. We welcome feedback from the scientific community to help improve our proposal. PMID:18327244
Mining microarray data at NCBI's Gene Expression Omnibus (GEO)*.
Barrett, Tanya; Edgar, Ron
2006-01-01
The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.
Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben
2017-06-06
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.
Yang, Chuanping; Wei, Hairong
2015-02-01
Microarray and RNA-seq experiments have become an important part of modern genomics and systems biology. Obtaining meaningful biological data from these experiments is an arduous task that demands close attention to many details. Negligence at any step can lead to gene expression data containing inadequate or composite information that is recalcitrant for pattern extraction. Therefore, it is imperative to carefully consider experimental design before launching a time-consuming and costly experiment. Contemporarily, most genomics experiments have two objectives: (1) to generate two or more groups of comparable data for identifying differentially expressed genes, gene families, biological processes, or metabolic pathways under experimental conditions; (2) to build local gene regulatory networks and identify hierarchically important regulators governing biological processes and pathways of interest. Since the first objective aims to identify the active molecular identities and the second provides a basis for understanding the underlying molecular mechanisms through inferring causality relationships mediated by treatment, an optimal experiment is to produce biologically relevant and extractable data to meet both objectives without substantially increasing the cost. This review discusses the major issues that researchers commonly face when embarking on microarray or RNA-seq experiments and summarizes important aspects of experimental design, which aim to help researchers deliberate how to generate gene expression profiles with low background noise but with more interaction to facilitate novel biological discoveries in modern plant genomics. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.
Ma, Liyuan; Li, Qian; Shen, Li; Feng, Xue; Xiao, Yunhua; Tao, Jiemeng; Liang, Yili; Yin, Huaqun; Liu, Xueduan
2016-10-01
Acidophilic microorganisms involved in uranium bioleaching are usually suppressed by dissolved fluoride ions, eventually leading to reduced leaching efficiency. However, little is known about the regulation mechanisms of microbial resistance to fluoride. In this study, the resistance of Acidithiobacillus ferrooxidans ATCC 23270 to fluoride was investigated by detecting bacterial growth fluctuations and ferrous or sulfur oxidation. To explore the regulation mechanism, a whole genome microarray was used to profile the genome-wide expression. The fluoride tolerance of A. ferrooxidans cultured in the presence of FeSO4 was better than that cultured with the S(0) substrate. The differentially expressed gene categories closely related to fluoride tolerance included those involved in energy metabolism, cellular processes, protein synthesis, transport, the cell envelope, and binding proteins. This study highlights that the cellular ferrous oxidation ability was enhanced at the lower fluoride concentrations. An overview of the cellular regulation mechanisms of extremophiles to fluoride resistance is discussed.
Jiménez-Guerrero, Irene; Acosta-Jurado, Sebastián; Navarro-Gómez, Pilar; López-Baena, Francisco Javier; Ollero, Francisco Javier
2017-01-01
Simultaneous quantification of transcripts of the whole bacterial genome allows the analysis of the global transcriptional response under changing conditions. RNA-seq and microarrays are the most used techniques to measure these transcriptomic changes, and both complement each other in transcriptome profiling. In this review, we exhaustively compiled the symbiosis-related transcriptomic reports (microarrays and RNA sequencing) carried out hitherto in rhizobia. This review is specially focused on transcriptomic changes that takes place when five rhizobial species, Bradyrhizobium japonicum (=diazoefficiens) USDA 110, Rhizobium leguminosarum biovar viciae 3841, Rhizobium tropici CIAT 899, Sinorhizobium (=Ensifer) meliloti 1021 and S. fredii HH103, recognize inducing flavonoids, plant-exuded phenolic compounds that activate the biosynthesis and export of Nod factors (NF) in all analysed rhizobia. Interestingly, our global transcriptomic comparison also indicates that each rhizobial species possesses its own arsenal of molecular weapons accompanying the set of NF in order to establish a successful interaction with host legumes. PMID:29267254
Ko, Kwan Soo; Park, Sulhee; Oh, Won Sup; Suh, Ji-Yoeun; Oh, Taejeong; Ahn, Sungwhan; Chun, Jongsik; Song, Jae-Hoon
2006-02-28
The global pattern of growth-dependent gene expres-sion in Streptococcus pneumoniae strains was evalu-ated using a high-density DNA microarray. Total RNAs obtained from an avirulent S. pneumoniae strain R6 and a virulent strain AMC96-6 were used to compare the expression patterns at seven time points (2.5, 3.5, 4.5, 5.5, 6.0, 6.5, and 8.0 h). The expression profile of strain R6 changed between log and station-ary growth (the Log-Stat switch). There were clear differences between the growth-dependent gene ex-pression profiles of the virulent and avirulent pneumo-coccal strains in 367 of 1,112 genes. Transcripts of genes associated with bacterial competence and capsular polysaccharide formation, as well as clpP and cbpA, were higher in the virulent strain. Our data suggest that late log or early stationary phase may be the most virulent phase of S. pneumoniae.
Goodman, Corey W.; Major, Heather J.; Walls, William D.; Sheffield, Val C.; Casavant, Thomas L.; Darbro, Benjamin W.
2016-01-01
Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. PMID:25595567
DNA microarrays: a powerful genomic tool for biomedical and clinical research
Trevino, Victor; Falciani, Francesco; Barrera-Saldaña, Hugo A.
2007-01-01
Among the many benefits of the Human Genome Project are new and powerful tools such as the genome-wide hybridization devices referred as microarrays. Initially designed to measure gene transcriptional levels, microarray technologies are now used for comparing other genome features among individuals and their tissues and cells. Results provide valuable information on disease subcategories, disease prognosis, and treatment outcome. Likewise, reveal differences in genetic makeup, regulatory mechanisms and subtle variations are approaching the era of personalized medicine. To understand this powerful tool, its versatility and how it is dramatically changing the molecular approach to biomedical and clinical research, this review describes the technology, its applications, a didactic step-by-step review of a typical microarray protocol, and a real experiment. Finally, it calls the attention of the medical community to integrate multidisciplinary teams, to take advantage of this technology and its expanding applications that in a slide reveals our genetic inheritance and destiny. PMID:17660860
Improved microarray methods for profiling the yeast knockout strain collection
Yuan, Daniel S.; Pan, Xuewen; Ooi, Siew Loon; Peyser, Brian D.; Spencer, Forrest A.; Irizarry, Rafael A.; Boeke, Jef D.
2005-01-01
A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3–6% and 15–18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens. PMID:15994458
Clustering approaches to identifying gene expression patterns from DNA microarray data.
Do, Jin Hwan; Choi, Dong-Kug
2008-04-30
The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.
Hayeems, R Z; Babul-Hirji, R; Hoang, N; Weksberg, R; Shuman, C
2016-04-01
Advances in genome-based microarray and sequencing technologies hold tremendous promise for understanding, better-managing and/or preventing disease and disease-related risk. Chromosome microarray technology (array based comparative genomic hybridization [aCGH]) is widely utilized in pediatric care to inform diagnostic etiology and medical management. Less clear is how parents experience and perceive the value of this technology. This study explored parents' experiences with aCGH in the pediatric setting, focusing on how they make meaning of various types of test results. We conducted in-person or telephone-based semi-structured interviews with parents of 21 children who underwent aCGH testing in 2010. Transcripts were coded and analyzed thematically according to the principles of interpretive description. We learned that parents expect genomic tests to be of personal use; their experiences with aCGH results characterize this use as intrinsic in the test's ability to provide a much sought-after answer for their child's condition, and instrumental in its ability to guide care, access to services, and family planning. In addition, parents experience uncertainty regardless of whether aCGH results are of pathogenic, uncertain, or benign significance; this triggers frustration, fear, and hope. Findings reported herein better characterize the notion of personal utility and highlight the pervasive nature of uncertainty in the context of genomic testing. Empiric research that links pre-test counseling content and psychosocial outcomes is warranted to optimize patient care.
Szatmári, Ágnes; Zvara, Ágnes; Móricz, Ágnes M.; Besenyei, Eszter; Szabó, Erika; Ott, Péter G.; Puskás, László G.; Bozsó, Zoltán
2014-01-01
Background Pattern Triggered Immunity (PTI) or Basal Resistance (BR) is a potent, symptomless form of plant resistance. Upon inoculation of a plant with non-pathogens or pathogenicity-mutant bacteria, the induced PTI will prevent bacterial proliferation. Developed PTI is also able to protect the plant from disease or HR (Hypersensitive Response) after a challenging infection with pathogenic bacteria. Our aim was to reveal those PTI-related genes of tobacco (Nicotiana tabacum) that could possibly play a role in the protection of the plant from disease. Methodology/Principal Findings Leaves were infiltrated with Pseudomonas syringae pv. syringae hrcC- mutant bacteria to induce PTI, and samples were taken 6 and 48 hours later. Subtraction Suppressive Hybridization (SSH) resulted in 156 PTI-activated genes. A cDNA microarray was generated from the SSH clone library. Analysis of hybridization data showed that in the early (6 hpi) phase of PTI, among others, genes of peroxidases, signalling elements, heat shock proteins and secondary metabolites were upregulated, while at the late phase (48 hpi) the group of proteolysis genes was newly activated. Microarray data were verified by real time RT-PCR analysis. Almost all members of the phenyl-propanoid pathway (PPP) possibly leading to lignin biosynthesis were activated. Specific inhibition of cinnamic-acid-4-hydroxylase (C4H), rate limiting enzyme of the PPP, decreased the strength of PTI - as shown by the HR-inhibition and electrolyte leakage tests. Quantification of cinnamate and p-coumarate by thin-layer chromatography (TLC)-densitometry supported specific changes in the levels of these metabolites upon elicitation of PTI. Conclusions/Significance We believe to provide first report on PTI-related changes in the levels of these PPP metabolites. Results implicated an actual role of the upregulation of the phenylpropanoid pathway in the inhibition of bacterial pathogenic activity during PTI. PMID:25101956
Grenville-Briggs, Laura J; Stansfield, Ian
2011-01-01
This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate active learning through experience of current research methods in bioinformatics and functional genomics. They seek to closely mimic a realistic research environment, and require the students first to propose research hypotheses, then test those hypotheses using specific sections of the microarray dataset. The complexity of the microarray data provides students with the freedom to propose their own unique hypotheses, tested using appropriate sections of the microarray data. This research latitude was highly regarded by students and is a strength of this practical. In addition, the focus on DNA damage by radiation and mutagenic chemicals allows them to place their results in a human medical context, and successfully sparks broad interest in the subject material. In evaluation, 79% of students scored the practical workshops on a five-point scale as 4 or 5 (totally effective) for student learning. More broadly, the general use of microarray data as a "student research playground" is also discussed. Copyright © 2011 Wiley Periodicals, Inc.
ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses
Stokes, Todd H; Torrance, JT; Li, Henry; Wang, May D
2008-01-01
Background A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers (Semantic Agents) such as Google to further enhance data discovery. Conclusions Microarray data and meta information in ArrayWiki are distributed and visualized using a novel and compact data storage format, BioPNG. Also, they are open to the research community for curation, modification, and contribution. By making a small investment of time to learn the syntax and structure common to all sites running MediaWiki software, domain scientists and practioners can all contribute to make better use of microarray technologies in research and medical practices. ArrayWiki is available at . PMID:18541053
Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; Haaland, D. M.; Timlin, J. A.; Elbourne, L. D. H.; Palenik, B.; Paulsen, I. T.
2009-01-01
Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition. PMID:19404483
Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; ...
2009-01-01
Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in partmore » to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.« less
Antibody Microarray for E. coli O157:H7 and Shiga Toxin in Microtiter Plates.
Gehring, Andrew G; Brewster, Jeffrey D; He, Yiping; Irwin, Peter L; Paoli, George C; Simons, Tawana; Tu, Shu-I; Uknalis, Joseph
2015-12-04
Antibody microarray is a powerful analytical technique because of its inherent ability to simultaneously discriminate and measure numerous analytes, therefore making the technique conducive to both the multiplexed detection and identification of bacterial analytes (i.e., whole cells, as well as associated metabolites and/or toxins). We developed a sandwich fluorescent immunoassay combined with a high-throughput, multiwell plate microarray detection format. Inexpensive polystyrene plates were employed containing passively adsorbed, array-printed capture antibodies. During sample reaction, centrifugation was the only strategy found to significantly improve capture, and hence detection, of bacteria (pathogenic Escherichia coli O157:H7) to planar capture surfaces containing printed antibodies. Whereas several other sample incubation techniques (e.g., static vs. agitation) had minimal effect. Immobilized bacteria were labeled with a red-orange-fluorescent dye (Alexa Fluor 555) conjugated antibody to allow for quantitative detection of the captured bacteria with a laser scanner. Shiga toxin 1 (Stx1) could be simultaneously detected along with the cells, but none of the agitation techniques employed during incubation improved detection of the relatively small biomolecule. Under optimal conditions, the assay had demonstrated limits of detection of ~5.8 × 10⁵ cells/mL and 110 ng/mL for E. coli O157:H7 and Stx1, respectively, in a ~75 min total assay time.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sheppod, Timothy; Satterfield, Brent; Hukari, Kyle W.
2006-10-01
The advancement of DNA cloning has significantly augmented the potential threat of a focused bioweapon assault, such as a terrorist attack. With current DNA cloning techniques, toxin genes from the most dangerous (but environmentally labile) bacterial or viral organism can now be selected and inserted into robust organism to produce an infinite number of deadly chimeric bioweapons. In order to neutralize such a threat, accurate detection of the expressed toxin genes, rather than classification on strain or genealogical decent of these organisms, is critical. The development of a high-throughput microarray approach will enable the detection of unknowns chimeric bioweapons. Themore » development of a high-throughput microarray approach will enable the detection of unknown bioweapons. We have developed a unique microfluidic approach to capture and concentrate these threat genes (mRNA's) upto a 30 fold concentration. These captured oligonucleotides can then be used to synthesize in situ oligonucleotide copies (cDNA probes) of the captured genes. An integrated microfluidic architecture will enable us to control flows of reagents, perform clean-up steps and finally elute nanoliter volumes of synthesized oligonucleotides probes. The integrated approach has enabled a process where chimeric or conventional bioweapons can rapidly be identified based on their toxic function, rather than being restricted to information that may not identify the critical nature of the threat.« less
Zhang, Hongtao; Palma, Angelina S; Zhang, Yibing; Childs, Robert A; Liu, Yan; Mitchell, Daniel A; Guidolin, Leticia S; Weigel, Wilfried; Mulloy, Barbara; Ciocchini, Andrés E; Feizi, Ten; Chai, Wengang
2016-01-01
The β1,2-glucans produced by bacteria are important in invasion, survival and immunomodulation in infected hosts be they mammals or plants. However, there has been a lack of information on proteins which recognize these molecules. This is partly due to the extremely limited availability of the sequence-defined oligosaccharides and derived probes for use in the study of their interactions. Here we have used the cyclic β1,2-glucan (CβG) of the bacterial pathogen Brucella abortus, after removal of succinyl side chains, to prepare linearized oligosaccharides which were used to generate microarrays. We describe optimized conditions for partial depolymerization of the cyclic glucan by acid hydrolysis and conversion of the β1,2-gluco-oligosaccharides, with degrees of polymerization 2–13, to neoglycolipids for the purpose of generating microarrays. By microarray analyses, we show that the C-type lectin receptor DC-SIGNR, like the closely related DC-SIGN we investigated earlier, binds to the β1,2-gluco-oligosaccharides, as does the soluble immune effector serum mannose-binding protein. Exploratory studies with DC-SIGN are suggestive of the recognition also of the intact CβG by this receptor. These findings open the way to unravelling mechanisms of immunomodulation mediated by β1,2-glucans in mammalian systems. PMID:27053576
Chronic kidney disease, uremic milieu, and its effects on gut bacterial microbiota dysbiosis.
Chaves, Lee D; McSkimming, Daniel I; Bryniarski, Mark A; Honan, Amanda M; Abyad, Sham; Thomas, Shruthi A; Wells, Steven; Buck, Michael J; Sun, Yijun; Genco, Robert J; Quigg, Richard J; Yacoub, Rabi
2018-04-25
Several lines of evidence suggest that gut bacterial microbiota is altered in patients with chronic kidney disease (CKD), though the mechanism of which this dysbiosis takes place is not well understood. Recent studies delineated changes in gut microbiota in both CKD patients and experimental animal models using microarray chips. We present 16S ribosomal RNA gene sequencing of both stool pellets and small bowel contents of C57Bl/6J mice that underwent a remnant kidney model, and establish that changes in microbiota take place in the early gastrointestinal track. Increased intestinal urea concertation has been hypothesized as a leading contributor for dysbiotic changes in CKD. We show that urea transporters UT-A and UT-B mRNA are both expressed throughout the whole gastrointestinal track. The noted increase in intestinal urea concentration appears to be independent of urea transporters' expression. Urea supplementation in drinking water resulted in alteration in bacterial gut microbiota that is quite different than that seen in CKD. This indicates that increased intestinal urea concentration might not fully explain the CKD associated dysbiosis.
Ancient pathogen DNA in archaeological samples detected with a Microbial Detection Array.
Devault, Alison M; McLoughlin, Kevin; Jaing, Crystal; Gardner, Shea; Porter, Teresita M; Enk, Jacob M; Thissen, James; Allen, Jonathan; Borucki, Monica; DeWitte, Sharon N; Dhody, Anna N; Poinar, Hendrik N
2014-03-06
Ancient human remains of paleopathological interest typically contain highly degraded DNA in which pathogenic taxa are often minority components, making sequence-based metagenomic characterization costly. Microarrays may hold a potential solution to these challenges, offering a rapid, affordable, and highly informative snapshot of microbial diversity in complex samples without the lengthy analysis and/or high cost associated with high-throughput sequencing. Their versatility is well established for modern clinical specimens, but they have yet to be applied to ancient remains. Here we report bacterial profiles of archaeological and historical human remains using the Lawrence Livermore Microbial Detection Array (LLMDA). The array successfully identified previously-verified bacterial human pathogens, including Vibrio cholerae (cholera) in a 19th century intestinal specimen and Yersinia pestis ("Black Death" plague) in a medieval tooth, which represented only minute fractions (0.03% and 0.08% alignable high-throughput shotgun sequencing reads) of their respective DNA content. This demonstrates that the LLMDA can identify primary and/or co-infecting bacterial pathogens in ancient samples, thereby serving as a rapid and inexpensive paleopathological screening tool to study health across both space and time.
Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray
2010-01-01
Background Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. Conclusion All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues. PMID:20964859
Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray.
Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte
2010-10-21
Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues.
CRISPR/Cas9: From Genome Engineering to Cancer Drug Discovery
Luo, Ji
2016-01-01
Advances in translational research are often driven by new technologies. The advent of microarrays, next-generation sequencing, proteomics and RNA interference (RNAi) have led to breakthroughs in our understanding of the mechanisms of cancer and the discovery of new cancer drug targets. The discovery of the bacterial clustered regularly interspaced palindromic repeat (CRISPR) system and its subsequent adaptation as a tool for mammalian genome engineering has opened up new avenues for functional genomics studies. This review will focus on the utility of CRISPR in the context of cancer drug target discovery. PMID:28603775
Novel techniques and findings in the study of plant microbiota: search for plant probiotics.
Berlec, Aleš
2012-09-01
Plants live in intimate relationships with numerous microorganisms present inside or outside plant tissues. The plant exterior provides two distinct ecosystems, the rhizosphere (below ground) and the phyllosphere (above ground), both populated by microbial communities. Most studies on plant microbiota deal with pathogens or mutualists. This review focuses on plant commensal bacteria, which could represent a rich source of bacteria beneficial to plants, alternatively termed plant probiotics. Plant commensal bacteria have been addressed only recently with culture-independent studies. These use next-generation sequencing, DNA microarray technologies and proteomics to decipher microbial community composition and function. Diverse bacterial populations are described in both rhizosphere and phyllosphere of different plants. The microorganisms can emerge from neighboring environmental ecosystems at random; however their survival is regulated by the plant. Influences from the environment, such as pesticides, farming practice and atmosphere, also affect the composition of microbial communities. Apart from community composition studies, some functional studies have also been performed. These include identification of broad-substrate surface receptors and methanol utilization enzymes by the proteomic approach, as well as identification of bacterial species that are important mediators of disease-suppressive soil phenomenon. Experience from more advanced human microbial studies could provide useful information and is discussed in the context of methodology and common trends. Administration of microbial mixtures of whole communities, rather than individual species, is highlighted and should be considered in future agricultural applications. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Mining Microarray Data at NCBI’s Gene Expression Omnibus (GEO)*
Barrett, Tanya; Edgar, Ron
2006-01-01
Summary The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo. PMID:16888359
Nicholson, Wayne L; Moeller, Ralf; Horneck, Gerda
2012-05-01
Because of their ubiquity and resistance to spacecraft decontamination, bacterial spores are considered likely potential forward contaminants on robotic missions to Mars. Thus, it is important to understand their global responses to long-term exposure to space or martian environments. As part of the PROTECT experiment, spores of B. subtilis 168 were exposed to real space conditions and to simulated martian conditions for 559 days in low-Earth orbit mounted on the EXPOSE-E exposure platform outside the European Columbus module on the International Space Station. Upon return, spores were germinated, total RNA extracted, fluorescently labeled, and used to probe a custom Bacillus subtilis microarray to identify genes preferentially activated or repressed relative to ground control spores. Increased transcript levels were detected for a number of stress-related regulons responding to DNA damage (SOS response, SPβ prophage induction), protein damage (CtsR/Clp system), oxidative stress (PerR regulon), and cell envelope stress (SigV regulon). Spores exposed to space demonstrated a much broader and more severe stress response than spores exposed to simulated martian conditions. The results are discussed in the context of planetary protection for a hypothetical journey of potential forward contaminant spores from Earth to Mars and their subsequent residence on Mars.
Kudo, Toru; Sasaki, Yohei; Terashima, Shin; Matsuda-Imai, Noriko; Takano, Tomoyuki; Saito, Misa; Kanno, Maasa; Ozaki, Soichi; Suwabe, Keita; Suzuki, Go; Watanabe, Masao; Matsuoka, Makoto; Takayama, Seiji; Yano, Kentaro
2016-10-13
In quantitative gene expression analysis, normalization using a reference gene as an internal control is frequently performed for appropriate interpretation of the results. Efforts have been devoted to exploring superior novel reference genes using microarray transcriptomic data and to evaluating commonly used reference genes by targeting analysis. However, because the number of specifically detectable genes is totally dependent on probe design in the microarray analysis, exploration using microarray data may miss some of the best choices for the reference genes. Recently emerging RNA sequencing (RNA-seq) provides an ideal resource for comprehensive exploration of reference genes since this method is capable of detecting all expressed genes, in principle including even unknown genes. We report the results of a comprehensive exploration of reference genes using public RNA-seq data from plants such as Arabidopsis thaliana (Arabidopsis), Glycine max (soybean), Solanum lycopersicum (tomato) and Oryza sativa (rice). To select reference genes suitable for the broadest experimental conditions possible, candidates were surveyed by the following four steps: (1) evaluation of the basal expression level of each gene in each experiment; (2) evaluation of the expression stability of each gene in each experiment; (3) evaluation of the expression stability of each gene across the experiments; and (4) selection of top-ranked genes, after ranking according to the number of experiments in which the gene was expressed stably. Employing this procedure, 13, 10, 12 and 21 top candidates for reference genes were proposed in Arabidopsis, soybean, tomato and rice, respectively. Microarray expression data confirmed that the expression of the proposed reference genes under broad experimental conditions was more stable than that of commonly used reference genes. These novel reference genes will be useful for analyzing gene expression profiles across experiments carried out under various experimental conditions.
Evaluation of microarray data normalization procedures using spike-in experiments
Rydén, Patrik; Andersson, Henrik; Landfors, Mattias; Näslund, Linda; Hartmanová, Blanka; Noppa, Laila; Sjöstedt, Anders
2006-01-01
Background Recently, a large number of methods for the analysis of microarray data have been proposed but there are few comparisons of their relative performances. By using so-called spike-in experiments, it is possible to characterize the analyzed data and thereby enable comparisons of different analysis methods. Results A spike-in experiment using eight in-house produced arrays was used to evaluate established and novel methods for filtration, background adjustment, scanning, channel adjustment, and censoring. The S-plus package EDMA, a stand-alone tool providing characterization of analyzed cDNA-microarray data obtained from spike-in experiments, was developed and used to evaluate 252 normalization methods. For all analyses, the sensitivities at low false positive rates were observed together with estimates of the overall bias and the standard deviation. In general, there was a trade-off between the ability of the analyses to identify differentially expressed genes (i.e. the analyses' sensitivities) and their ability to provide unbiased estimators of the desired ratios. Virtually all analysis underestimated the magnitude of the regulations; often less than 50% of the true regulations were observed. Moreover, the bias depended on the underlying mRNA-concentration; low concentration resulted in high bias. Many of the analyses had relatively low sensitivities, but analyses that used either the constrained model (i.e. a procedure that combines data from several scans) or partial filtration (a novel method for treating data from so-called not-found spots) had with few exceptions high sensitivities. These methods gave considerable higher sensitivities than some commonly used analysis methods. Conclusion The use of spike-in experiments is a powerful approach for evaluating microarray preprocessing procedures. Analyzed data are characterized by properties of the observed log-ratios and the analysis' ability to detect differentially expressed genes. If bias is not a major problem; we recommend the use of either the CM-procedure or partial filtration. PMID:16774679
Mahajan, Prashant; Kuppermann, Nathan; Suarez, Nicolas; Mejias, Asuncion; Casper, Charlie; Dean, J Michael; Ramilo, Octavio
2015-01-01
To develop the infrastructure and demonstrate the feasibility of conducting microarray-based RNA transcriptional profile analyses for the diagnosis of serious bacterial infections in febrile infants 60 days and younger in a multicenter pediatric emergency research network. We designed a prospective multicenter cohort study with the aim of enrolling more than 4000 febrile infants 60 days and younger. To ensure success of conducting complex genomic studies in emergency department (ED) settings, we established an infrastructure within the Pediatric Emergency Care Applied Research Network, including 21 sites, to evaluate RNA transcriptional profiles in young febrile infants. We developed a comprehensive manual of operations and trained site investigators to obtain and process blood samples for RNA extraction and genomic analyses. We created standard operating procedures for blood sample collection, processing, storage, shipping, and analyses. We planned to prospectively identify, enroll, and collect 1 mL blood samples for genomic analyses from eligible patients to identify logistical issues with study procedures. Finally, we planned to batch blood samples and determined RNA quantity and quality at the central microarray laboratory and organized data analysis with the Pediatric Emergency Care Applied Research Network data coordinating center. Below we report on establishment of the infrastructure and the feasibility success in the first year based on the enrollment of a limited number of patients. We successfully established the infrastructure at 21 EDs. Over the first 5 months we enrolled 79% (74 of 94) of eligible febrile infants. We were able to obtain and ship 1 mL of blood from 74% (55 of 74) of enrolled participants, with at least 1 sample per participating ED. The 55 samples were shipped and evaluated at the microarray laboratory, and 95% (52 of 55) of blood samples were of adequate quality and contained sufficient RNA for expression analysis. It is possible to create a robust infrastructure to conduct genomic studies in young febrile infants in the context of a multicenter pediatric ED research setting. The sufficient quantity and high quality of RNA obtained suggests that whole blood transcriptional profile analysis for the diagnostic evaluation of young febrile infants can be successfully performed in this setting.
Grote, Lauren; Myers, Melanie; Lovell, Anne; Saal, Howard; Sund, Kristen Lipscomb
2014-01-01
SNP microarrays are capable of detecting regions of homozygosity (ROH) which can suggest parental relatedness. This study was designed to describe pre- and post-test counseling practices of genetics professionals regarding ROH, explore perceived comfort and ethical concerns in the follow-up of such results, demonstrate awareness of laws surrounding duty to report consanguinity and incest, and allow respondents to share their personal experiences with results suggesting a parental relationship. A 35 question survey was administered to 240 genetic counselors and geneticists who had ordered or counseled for SNP microarray. The results are presented using descriptive statistics. There was variation in both pre- and post-test counseling practices of genetics professionals. Twenty-five percent of respondents reported pre-test counseling that ROH can indicate parental relatedness. The most commonly reported ethical concern was disclosure of findings suggesting parental relatedness to parents of the patient; only 48.4% reported disclosing parental relatedness when indicated. Fifty-seven percent felt comfortable receiving results suggesting parental consanguinity while 17% felt comfortable receiving results suggesting parental incest. Twenty percent of respondents were extremely/moderately familiar with the laws about duty to report incest. Personal experiences in post-test counseling included both parental acknowledgement and denial of relatedness. This study highlights the differences in genetics professionals' pre- and post-test counseling practices, comfort, and experiences surrounding parental relatedness suggested by SNP microarray results. It identifies a need for professional organizations to offer guidance to genetics professionals about how to respond to and counsel for molecular results suggesting parental consanguinity or incest. © 2013 Wiley Periodicals, Inc.
Goodman, Corey W; Major, Heather J; Walls, William D; Sheffield, Val C; Casavant, Thomas L; Darbro, Benjamin W
2015-04-01
Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. Copyright © 2015 Elsevier Inc. All rights reserved.
Molecular Signatures of Nicotinoid-Pathogen Synergy in the Termite Gut
Sen, Ruchira; Raychoudhury, Rhitoban; Cai, Yunpeng; Sun, Yijun; Lietze, Verena-Ulrike; Peterson, Brittany F.; Scharf, Michael E.; Boucias, Drion G.
2015-01-01
Previous studies in lower termites revealed unexpected synergies between nicotinoid insecticides and fungal entomopathogens. The present study investigated molecular mechanisms of nicotinoid-pathogen synergy in the lower termite Reticulitermes flavipes, using the nicotinoid, imidacloprid, in combination with fungal and bacterial entomopathogens. Particular focus was placed on metatranscriptome composition and microbial dynamics in the symbiont-rich termite gut, which houses diverse mixes of protists and bacteria. cDNA microarrays containing a mix of host and protist symbiont oligonucleotides were used to simultaneously assess termite and protist gene expression. Five treatments were compared that included single challenges with sublethal doses of fungi (Metharizium anisopliae), bacteria (Serratia marcescens) or imidacloprid, and dual challenges with fungi + imidacloprid or bacteria + imidacloprid. Our findings point towards protist dysbiosis and compromised social behavior, rather than suppression of stereotypical immune defense mechanisms, as the dominant factors underlying nicotinoid-pathogen synergy in termites. Also, greater impacts observed for the fungal pathogen than for the bacterial pathogen suggest that the rich bacterial symbiont community in the R. flavipes gut (>5000 species-level phylotypes) exists in an ecological balance that effectively excludes exogenous bacterial pathogens. These findings significantly advance our understanding of antimicrobial defenses in this important eusocial insect group, as well as provide novel insights into how nicotinoids can exert deleterious effects on social insect colonies. PMID:25837376
Identifying Fishes through DNA Barcodes and Microarrays.
Kochzius, Marc; Seidel, Christian; Antoniou, Aglaia; Botla, Sandeep Kumar; Campo, Daniel; Cariani, Alessia; Vazquez, Eva Garcia; Hauschild, Janet; Hervet, Caroline; Hjörleifsdottir, Sigridur; Hreggvidsson, Gudmundur; Kappel, Kristina; Landi, Monica; Magoulas, Antonios; Marteinsson, Viggo; Nölte, Manfred; Planes, Serge; Tinti, Fausto; Turan, Cemal; Venugopal, Moleyur N; Weber, Hannes; Blohm, Dietmar
2010-09-07
International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S), cytochrome b (cyt b), and cytochrome oxidase subunit I (COI) for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ) phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90%) renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.
DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data
Glez-Peña, Daniel; Álvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino
2009-01-01
Background Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. Results DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. Conclusion DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on these contributions GENECBR, a successful tool for cancer diagnosis using microarray datasets, has recently been released. PMID:19178723
DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data.
Glez-Peña, Daniel; Alvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino
2009-01-29
Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on these contributions GENECBR, a successful tool for cancer diagnosis using microarray datasets, has recently been released.
Retrieving relevant time-course experiments: a study on Arabidopsis microarrays.
Şener, Duygu Dede; Oğul, Hasan
2016-06-01
Understanding time-course regulation of genes in response to a stimulus is a major concern in current systems biology. The problem is usually approached by computational methods to model the gene behaviour or its networked interactions with the others by a set of latent parameters. The model parameters can be estimated through a meta-analysis of available data obtained from other relevant experiments. The key question here is how to find the relevant experiments which are potentially useful in analysing current data. In this study, the authors address this problem in the context of time-course gene expression experiments from an information retrieval perspective. To this end, they introduce a computational framework that takes a time-course experiment as a query and reports a list of relevant experiments retrieved from a given repository. These retrieved experiments can then be used to associate the environmental factors of query experiment with the findings previously reported. The model is tested using a set of time-course Arabidopsis microarrays. The experimental results show that relevant experiments can be successfully retrieved based on content similarity.
Spaceflight Alters Bacterial Gene Expression and Virulence and Reveals Role for Global Regulator Hfq
NASA Technical Reports Server (NTRS)
Wilson, J. W.; Ott, C. M.; zuBentrup, K. Honer; Ramamurthy R.; Quick, L.; Porwollik, S.; Cheng, P.; McClellan, M.; Tsaprailis, G.; Radabaugh, T.;
2007-01-01
A comprehensive analysis of both the molecular genetic and phenotypic responses of any organism to the spaceflight environment has never been accomplished due to significant technological and logistical hurdles. Moreover, the effects of spaceflight on microbial pathogenicity and associated infectious disease risks have not been studied. The bacterial pathogen Salmonella typhimurium was grown aboard Space Shuttle mission STS-115 and compared to identical ground control cultures. Global microarray and proteomic analyses revealed 167 transcripts and 73 proteins changed expression with the conserved RNA-binding protein Hfq identified as a likely global regulator involved in the response to this environment. Hfq involvement was confirmed with a ground based microgravity culture model. Spaceflight samples exhibited enhanced virulence in a murine infection model and extracellular matrix accumulation consistent with a biofilm. Strategies to target Hfq and related regulators could potentially decrease infectious disease risks during spaceflight missions and provide novel therapeutic options on Earth.
Oral microbiota species in acute apical endodontic abscesses.
George, Noelle; Flamiatos, Erin; Kawasaki, Kellie; Kim, Namgu; Carriere, Charles; Phan, Brian; Joseph, Raphael; Strauss, Shay; Kohli, Richie; Choi, Dongseok; Baumgartner, J Craig; Sedgley, Christine; Maier, Tom; Machida, Curtis A
2016-01-01
Acute apical abscesses are serious endodontic diseases resulting from pulpal infection with opportunistic oral microorganisms. The objective of this study was to identify and compare the oral microbiota in patients (N=18) exhibiting acute apical abscesses, originating from the demographic region in Portland, Oregon. The study hypothesis is that abscesses obtained from this demographic region may contain unique microorganisms not identified in specimens from other regions. Endodontic abscesses were sampled from patients at the Oregon Health & Science University (OHSU) School of Dentistry. DNA from abscess specimens was subjected to polymerase chain reaction amplification using 16S rRNA gene-specific primers and Cy3-dCTP labeling. Labeled DNA was then applied to microbial microarrays (280 species) generated by the Human Oral Microbial Identification Microarray Laboratory (Forsyth Institute, Cambridge, MA). The most prevalent microorganisms, found across multiple abscess specimens, include Fusobacterium nucleatum, Parvimonas micra, Megasphaera species clone CS025, Prevotella multisaccharivorax, Atopobium rimae, and Porphyromonas endodontalis. The most abundant microorganisms, found in highest numbers within individual abscesses, include F. nucleatum, P. micra, Streptococcus Cluster III, Solobacterium moorei, Streptococcus constellatus, and Porphyromonas endodontalis. Strong bacterial associations were identified between Prevotella multisaccharivorax, Acidaminococcaceae species clone DM071, Megasphaera species clone CS025, Actinomyces species clone EP053, and Streptococcus cristatus (all with Spearman coefficients >0.9). Cultivable and uncultivable bacterial species have been identified in endodontic abscesses obtained from the Portland, Oregon demographic region, and taxa identifications correlated well with other published studies, with the exception of Treponema and Streptococcus cristae, which were not commonly identified in endodontic abscesses between the demographic region in Portland, Oregon and other regions.
Atack, John M; Srikhanta, Yogitha N; Djoko, Karrera Y; Welch, Jessica P; Hasri, Norain H M; Steichen, Christopher T; Vanden Hoven, Rachel N; Grimmond, Sean M; Othman, Dk Seti Maimonah Pg; Kappler, Ulrike; Apicella, Michael A; Jennings, Michael P; Edwards, Jennifer L; McEwan, Alastair G
2013-06-01
NtrYX is a sensor-histidine kinase/response regulator two-component system that has had limited characterization in a small number of Alphaproteobacteria. Phylogenetic analysis of the response regulator NtrX showed that this two-component system is extensively distributed across the bacterial domain, and it is present in a variety of Betaproteobacteria, including the human pathogen Neisseria gonorrhoeae. Microarray analysis revealed that the expression of several components of the respiratory chain was reduced in an N. gonorrhoeae ntrX mutant compared to that in the isogenic wild-type (WT) strain 1291. These included the cytochrome c oxidase subunit (ccoP), nitrite reductase (aniA), and nitric oxide reductase (norB). Enzyme activity assays showed decreased cytochrome oxidase and nitrite reductase activities in the ntrX mutant, consistent with microarray data. N. gonorrhoeae ntrX mutants had reduced capacity to survive inside primary cervical cells compared to the wild type, and although they retained the ability to form a biofilm, they exhibited reduced survival within the biofilm compared to wild-type cells, as indicated by LIVE/DEAD staining. Analyses of an ntrX mutant in a representative alphaproteobacterium, Rhodobacter capsulatus, showed that cytochrome oxidase activity was also reduced compared to that in the wild-type strain SB1003. Taken together, these data provide evidence that the NtrYX two-component system may be a key regulator in the expression of respiratory enzymes and, in particular, cytochrome c oxidase, across a wide range of proteobacteria, including a variety of bacterial pathogens.
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Sioson, Allan A; Mane, Shrinivasrao P; Li, Pinghua; Sha, Wei; Heath, Lenwood S; Bohnert, Hans J; Grene, Ruth
2006-01-01
Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity. PMID:16626497
Watson, Christopher M.; Crinnion, Laura A.; Gurgel‐Gianetti, Juliana; Harrison, Sally M.; Daly, Catherine; Antanavicuite, Agne; Lascelles, Carolina; Markham, Alexander F.; Pena, Sergio D. J.; Bonthron, David T.
2015-01-01
ABSTRACT Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease‐causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome‐wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution. PMID:26037133
Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.
Rivera, Robert; Wang, Jie; Yu, Xiaobo; Demirkan, Gokhan; Hopper, Marika; Bian, Xiaofang; Tahsin, Tasnia; Magee, D Mitchell; Qiu, Ji; LaBaer, Joshua; Wallstrom, Garrick
2017-11-03
In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.
Integrative missing value estimation for microarray data.
Hu, Jianjun; Li, Haifeng; Waterman, Michael S; Zhou, Xianghong Jasmine
2006-10-12
Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. We present the integrative Missing Value Estimation method (iMISS) by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS) imputation algorithm by up to 15% improvement in our benchmark tests. We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.
Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild
2009-07-01
Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.
A proposed metric for assessing the measurement quality of individual microarrays
Kim, Kyoungmi; Page, Grier P; Beasley, T Mark; Barnes, Stephen; Scheirer, Katherine E; Allison, David B
2006-01-01
Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements. PMID:16430768
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, C.H.; Sercu, B.; Van De Werhorst, L.C.
2010-03-01
Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring. Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomicmore » units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and a-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC:A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies. This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health.« less
Wu, Cindy H.; Sercu, Bram; Van De Werfhorst, Laurie C.; Wong, Jakk; DeSantis, Todd Z.; Brodie, Eoin L.; Hazen, Terry C.; Holden, Patricia A.; Andersen, Gary L.
2010-01-01
Background Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring. Methodology/Principal Findings Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomic units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and α-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC∶A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies. Conclusions/Significance This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health. PMID:20585654
The XBabelPhish MAGE-ML and XML translator.
Maier, Don; Wymore, Farrell; Sherlock, Gavin; Ball, Catherine A
2008-01-18
MAGE-ML has been promoted as a standard format for describing microarray experiments and the data they produce. Two characteristics of the MAGE-ML format compromise its use as a universal standard: First, MAGE-ML files are exceptionally large - too large to be easily read by most people, and often too large to be read by most software programs. Second, the MAGE-ML standard permits many ways of representing the same information. As a result, different producers of MAGE-ML create different documents describing the same experiment and its data. Recognizing all the variants is an unwieldy software engineering task, resulting in software packages that can read and process MAGE-ML from some, but not all producers. This Tower of MAGE-ML Babel bars the unencumbered exchange of microarray experiment descriptions couched in MAGE-ML. We have developed XBabelPhish - an XQuery-based technology for translating one MAGE-ML variant into another. XBabelPhish's use is not restricted to translating MAGE-ML documents. It can transform XML files independent of their DTD, XML schema, or semantic content. Moreover, it is designed to work on very large (> 200 Mb.) files, which are common in the world of MAGE-ML. XBabelPhish provides a way to inter-translate MAGE-ML variants for improved interchange of microarray experiment information. More generally, it can be used to transform most XML files, including very large ones that exceed the capacity of most XML tools.
NASA Astrophysics Data System (ADS)
Leonard, Heidi; Holtzman, Liran; Haimov, Yuri; Weizman, Daniel; Kashi, Yechezkel; Nativ, Ofer; Halachmi, Sarel; Segal, Ester
2018-02-01
We have developed a rapid phenotypic antimicrobial susceptibility testing (AST) in which photonic 2D silicon microarrays are employed as both the optical transducer element and as a preferable solid-liquid interface for bacterial colonization. We harness the intrinsic ability of the micro-architectures to relay optical phase-shift reflectometric interference spectroscopic measurements (termed PRISM) and incorporate it into a platform for culture-free, label-free tracking of bacterial accumulation, proliferation, and death. This assay employs microfluidic channels interfaced with PRISM chips and is carried out in a two-stage process, namely bacteria seeding and antibiotic incubation. Bacteria proliferation within the microtopologies results in an increase in refractive index of the medium, yielding an increase in optical path difference, while cell death or bacteriostatic activity results in decreasing or unchanged values. The optical responses of bacteria to various concentrations of relevant antibiotics have been tracked in real time, allowing for accurate determination of the minimum inhibitory concentration (MIC) values within 2-3 hours. We further extended this work to analyze antibiotic susceptibilities of clinical isolates and direct urine samples derived from patients at neighboring hospitals in newly designed, disposable microfluidic devices. This has opened the door to the observation of unique bacterial behaviors, as we can evaluate bacterial adhesion, growth, and antibiotic resistance on different microarchitectures, different surface chemistries, and even different strains. Motility, charge, and biofilm abilities have been explored for their effect of bacterial adhesion to the microstructures as we further develop our method of rapid, label-free AST for full clinical application.
Applying dynamic Bayesian networks to perturbed gene expression data.
Dojer, Norbert; Gambin, Anna; Mizera, Andrzej; Wilczyński, Bartek; Tiuryn, Jerzy
2006-05-08
A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics, allowing to deal with the stochastic aspects of gene expressions and noisy measurements in a natural way, Bayesian networks appear attractive in the field of inferring gene interactions structure from microarray experiments data. However, the basic formalism has some disadvantages, e.g. it is sometimes hard to distinguish between the origin and the target of an interaction. Two kinds of microarray experiments yield data particularly rich in information regarding the direction of interactions: time series and perturbation experiments. In order to correctly handle them, the basic formalism must be modified. For example, dynamic Bayesian networks (DBN) apply to time series microarray data. To our knowledge the DBN technique has not been applied in the context of perturbation experiments. We extend the framework of dynamic Bayesian networks in order to incorporate perturbations. Moreover, an exact algorithm for inferring an optimal network is proposed and a discretization method specialized for time series data from perturbation experiments is introduced. We apply our procedure to realistic simulations data. The results are compared with those obtained by standard DBN learning techniques. Moreover, the advantages of using exact learning algorithm instead of heuristic methods are analyzed. We show that the quality of inferred networks dramatically improves when using data from perturbation experiments. We also conclude that the exact algorithm should be used when it is possible, i.e. when considered set of genes is small enough.
MADGE: scalable distributed data management software for cDNA microarrays.
McIndoe, Richard A; Lanzen, Aaron; Hurtz, Kimberly
2003-01-01
The human genome project and the development of new high-throughput technologies have created unparalleled opportunities to study the mechanism of diseases, monitor the disease progression and evaluate effective therapies. Gene expression profiling is a critical tool to accomplish these goals. The use of nucleic acid microarrays to assess the gene expression of thousands of genes simultaneously has seen phenomenal growth over the past five years. Although commercial sources of microarrays exist, investigators wanting more flexibility in the genes represented on the array will turn to in-house production. The creation and use of cDNA microarrays is a complicated process that generates an enormous amount of information. Effective data management of this information is essential to efficiently access, analyze, troubleshoot and evaluate the microarray experiments. We have developed a distributable software package designed to track and store the various pieces of data generated by a cDNA microarray facility. This includes the clone collection storage data, annotation data, workflow queues, microarray data, data repositories, sample submission information, and project/investigator information. This application was designed using a 3-tier client server model. The data access layer (1st tier) contains the relational database system tuned to support a large number of transactions. The data services layer (2nd tier) is a distributed COM server with full database transaction support. The application layer (3rd tier) is an internet based user interface that contains both client and server side code for dynamic interactions with the user. This software is freely available to academic institutions and non-profit organizations at http://www.genomics.mcg.edu/niddkbtc.
Salehi, Reza; Tsoi, Stephen C M; Colazo, Marcos G; Ambrose, Divakar J; Robert, Claude; Dyck, Michael K
2017-01-30
Early embryonic loss is a large contributor to infertility in cattle. Moreover, bovine becomes an interesting model to study human preimplantation embryo development due to their similar developmental process. Although genetic factors are known to affect early embryonic development, the discovery of such factors has been a serious challenge. Microarray technology allows quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. One of the main decisions that have to be made when planning a microarray experiment is whether to use a one- or two-color approach. Two-color design increases technical replication, minimizes variability, improves sensitivity and accuracy as well as allows having loop designs, defining the common reference samples. Although microarray is a powerful biological tool, there are potential pitfalls that can attenuate its power. Hence, in this technical paper we demonstrate an optimized protocol for RNA extraction, amplification, labeling, hybridization of the labeled amplified RNA to the array, array scanning and data analysis using the two-color analysis strategy.
Metadata management and semantics in microarray repositories.
Kocabaş, F; Can, T; Baykal, N
2011-12-01
The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework.
Cross species analysis of microarray expression data
Lu, Yong; Huggins, Peter; Bar-Joseph, Ziv
2009-01-01
Motivation: Many biological systems operate in a similar manner across a large number of species or conditions. Cross-species analysis of sequence and interaction data is often applied to determine the function of new genes. In contrast to these static measurements, microarrays measure the dynamic, condition-specific response of complex biological systems. The recent exponential growth in microarray expression datasets allows researchers to combine expression experiments from multiple species to identify genes that are not only conserved in sequence but also operated in a similar way in the different species studied. Results: In this review we discuss the computational and technical challenges associated with these studies, the approaches that have been developed to address these challenges and the advantages of cross-species analysis of microarray data. We show how successful application of these methods lead to insights that cannot be obtained when analyzing data from a single species. We also highlight current open problems and discuss possible ways to address them. Contact: zivbj@cs.cmu.edu PMID:19357096
Clustering gene expression data based on predicted differential effects of GV interaction.
Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu
2005-02-01
Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.
Wilkins, Ella J; Archibald, Alison D; Sahhar, Margaret A; White, Susan M
2016-11-01
Chromosomal microarray is an increasingly utilized diagnostic test, particularly in the pediatric setting. However, the clinical significance of copy number variants detected by this technology is not always understood, creating uncertainties in interpreting and communicating results. The aim of this study was to explore parents' experiences of an uncertain microarray result for their child. This research utilized a qualitative approach with a phenomenological methodology. Semi-structured interviews were conducted with nine parents of eight children who received an uncertain microarray result for their child, either a 16p11.2 microdeletion or 15q13.3 microdeletion. Interviews were transcribed verbatim and thematic analysis was used to identify themes within the data. Participants were unprepared for the abnormal test result. They had a complex perception of the extent of their child's condition and a mixed understanding of the clinical relevance of the result, but were accepting of the limitations of medical knowledge, and appeared to have adapted to the result. The test result was empowering for parents in terms of access to medical and educational services; however, they articulated significant unmet support needs. Participants expressed hope for the future, in particular that more information would become available over time. This research has demonstrated that parents of children who have an uncertain microarray result appeared to adapt to uncertainty and limited availability of information and valued honesty and empathic ongoing support from health professionals. Genetic health professionals are well positioned to provide such support and aid patients' and families' adaptation to their situation as well as promote empowerment. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
High quality epoxysilane substrate for clinical multiplex serodiagnostic proteomic microarrays
NASA Astrophysics Data System (ADS)
Ewart, Tom; Carmichael, Stuart; Lea, Peter
2005-09-01
Polylysine and aminopropylsilane treated glass comprised the majority of substrates employed in first generation genetic microarray substrates. Second generation single stranded long oligo libraries with amino termini provided for controlled terminal specific attachment, and rationally designed unique sequence libraries with normalized melting temperatures. These libraries benefit from active covalent coupling surfaces such as Epoxysilane. The latter's oxime ring shows versatile reactivity with amino-, thiol- and hydroxyl- groups thus encompassing small molecule, oligo and proteomic microarray applications. Batch-to-batch production uniformity supports entry of the Epoxysilane process into clinical diagnostics. We carried out multiple print runs of 21 clinically relevant bacterial and viral antigens at optimized concentrations, plus human IgG and IgM standards in triplicate on multiple batches of Epoxysilane substrates. A set of 45 patient sera were assayed in a 35 minute protocol using 10 microliters per array in a capillary-fill format (15 minute serum incubation, wash, 15 minute incubation with Cy3-labeled anti-hIgG plus Dy647-labeled anti-hIgM, final wash). The LOD (3 SD above background) was better than 1 microgram/ml for IgG, and standard curves were regular and monotonically increasing over the range 0 to 1000 micrograms/ml. Ninety-five percent of the CVs for the standards were under 10%, and 90% percent of CVs for antigen responses were under 10% across all batches of Epoxysilane and print runs. In addition, where SDs are larger than expected, microarray images may be readily reviewed for quality control purposes and pin misprints quickly identified. In order to determine the influence of stirring on sensitivity and speed of the microarray assay, we printed 10 common ToRCH antigens (H. pylori, T. gondii, Rubella, Rubeola, C. trachomatis, Herpes 1 and 2, CMV, C. jejuni, and EBV) in Epoxysilane-activated slide-wells. Anti-IgG-Cy3 direct binding to printed IgG calibration spots could be detected (3 x LOD) above background at 100 pg/ml (0.13 femtomoles sample content) in a 10 minute incubation. The LOD for detection of serum anti-H. pylori antibody level was 9 ng/ml in the same incubation time.
Mathematics make microbes beautiful, beneficial, and bountiful.
Jungck, John R
2012-01-01
Microbiology is a rich area for visualizing the importance of mathematics in terms of designing experiments, data mining, testing hypotheses, and visualizing relationships. Historically, Nobel Prizes have acknowledged the close interplay between mathematics and microbiology in such examples as the fluctuation test and mutation rates using Poisson statistics by Luria and Delbrück and the use of graph theory of polyhedra by Caspar and Klug. More and more contemporary microbiology journals feature mathematical models, computational algorithms and heuristics, and multidimensional visualizations. While revolutions in research have driven these initiatives, a commensurate effort needs to be made to incorporate much more mathematics into the professional preparation of microbiologists. In order not to be daunting to many educators, a Bloom-like "Taxonomy of Quantitative Reasoning" is shared with explicit examples of microbiological activities for engaging students in (a) counting, measuring, calculating using image analysis of bacterial colonies and viral infections on variegated leaves, measurement of fractal dimensions of beautiful colony morphologies, and counting vertices, edges, and faces on viral capsids and using graph theory to understand self assembly; (b) graphing, mapping, ordering by applying linear, exponential, and logistic growth models of public health and sanitation problems, revisiting Snow's epidemiological map of cholera with computational geometry, and using interval graphs to do complementation mapping, deletion mapping, food webs, and microarray heatmaps; (c) problem solving by doing gene mapping and experimental design, and applying Boolean algebra to gene regulation of operons; (d) analysis of the "Bacterial Bonanza" of microbial sequence and genomic data using bioinformatics and phylogenetics; (e) hypothesis testing-again with phylogenetic trees and use of Poisson statistics and the Luria-Delbrück fluctuation test; and (f) modeling of biodiversity by using game theory, of epidemics with algebraic models, bacterial motion by using motion picture analysis and fluid mechanics of motility in multiple dimensions through the physics of "Life at Low Reynolds Numbers," and pattern formation of quorum sensing bacterial populations. Through a developmental model for preprofessional education that emphasizes the beauty, utility, and diversity of microbiological systems, we hope to foster creativity as well as mathematically rigorous reasoning. Copyright © 2012 Elsevier Inc. All rights reserved.
Chakraborty, Smarajit; Mizusaki, Hideaki; Kenney, Linda J.
2015-01-01
In bacteria, one paradigm for signal transduction is the two-component regulatory system, consisting of a sensor kinase (usually a membrane protein) and a response regulator (usually a DNA binding protein). The EnvZ/OmpR two-component system responds to osmotic stress and regulates expression of outer membrane proteins. In Salmonella, EnvZ/OmpR also controls expression of another two-component system SsrA/B, which is located on Salmonella Pathogenicity Island (SPI) 2. SPI-2 encodes a type III secretion system, which functions as a nanomachine to inject bacterial effector proteins into eukaryotic cells. During the intracellular phase of infection, Salmonella switches from assembling type III secretion system structural components to secreting effectors into the macrophage cytoplasm, enabling Salmonella to replicate in the phagocytic vacuole. Major questions remain regarding how bacteria survive the acidified vacuole and how acidification affects bacterial secretion. We previously reported that EnvZ sensed cytoplasmic signals rather than extracellular ones, as intracellular osmolytes altered the dynamics of a 17-amino-acid region flanking the phosphorylated histidine. We reasoned that the Salmonella cytoplasm might acidify in the macrophage vacuole to activate OmpR-dependent transcription of SPI-2 genes. To address these questions, we employed a DNA-based FRET biosensor (“I-switch”) to measure bacterial cytoplasmic pH and immunofluorescence to monitor effector secretion during infection. Surprisingly, we observed a rapid drop in bacterial cytoplasmic pH upon phagocytosis that was not predicted by current models. Cytoplasmic acidification was completely dependent on the OmpR response regulator, but did not require known OmpR-regulated genes such as ompC, ompF, or ssaC (SPI-2). Microarray analysis highlighted the cadC/BA operon, and additional experiments confirmed that it was repressed by OmpR. Acidification was blocked in the ompR null background in a Cad-dependent manner. Acid-dependent activation of OmpR stimulated type III secretion; blocking acidification resulted in a neutralized cytoplasm that was defective for SPI-2 secretion. Based upon these findings, we propose that Salmonella infection involves an acid-dependent secretion process in which the translocon SseB moves away from the bacterial cell surface as it associates with the vacuolar membrane, driving the secretion of SPI-2 effectors such as SseJ. New steps in the SPI-2 secretion process are proposed. PMID:25875623
Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian
2017-01-01
In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.
Duan, Fenghai; Xu, Ye
2017-01-01
To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis. In total, 1640 probe sets (genes) were reliably identified to have turning points along with the age at diagnosis in their expression profiling, of which 927 expressed lower after turning points and 713 expressed higher after the turning points. K-means clustered them into 3 groups with turning points centering at 54, 62.5, and 72, respectively. The pathway analysis showed that the identified genes were actively involved in various cancer-related functions or networks. In this article, we applied the nonparametric multivariate adaptive splines method to a publicly available gene expression data and successfully identified genes with expressions varying before and after breast cancer diagnosis.
arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays
Menten, Björn; Pattyn, Filip; De Preter, Katleen; Robbrecht, Piet; Michels, Evi; Buysse, Karen; Mortier, Geert; De Paepe, Anne; van Vooren, Steven; Vermeesch, Joris; Moreau, Yves; De Moor, Bart; Vermeulen, Stefan; Speleman, Frank; Vandesompele, Jo
2005-01-01
Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at . PMID:15910681
Framework for Parallel Preprocessing of Microarray Data Using Hadoop
2018-01-01
Nowadays, microarray technology has become one of the popular ways to study gene expression and diagnosis of disease. National Center for Biology Information (NCBI) hosts public databases containing large volumes of biological data required to be preprocessed, since they carry high levels of noise and bias. Robust Multiarray Average (RMA) is one of the standard and popular methods that is utilized to preprocess the data and remove the noises. Most of the preprocessing algorithms are time-consuming and not able to handle a large number of datasets with thousands of experiments. Parallel processing can be used to address the above-mentioned issues. Hadoop is a well-known and ideal distributed file system framework that provides a parallel environment to run the experiment. In this research, for the first time, the capability of Hadoop and statistical power of R have been leveraged to parallelize the available preprocessing algorithm called RMA to efficiently process microarray data. The experiment has been run on cluster containing 5 nodes, while each node has 16 cores and 16 GB memory. It compares efficiency and the performance of parallelized RMA using Hadoop with parallelized RMA using affyPara package as well as sequential RMA. The result shows the speed-up rate of the proposed approach outperforms the sequential approach and affyPara approach. PMID:29796018
Yokoi, Takahide; Kaku, Yoshiko; Suzuki, Hiroyuki; Ohta, Masayuki; Ikuta, Hajime; Isaka, Kazuichi; Sumino, Tatsuo; Wagatsuma, Masako
2007-08-01
To investigate uncharacterized microbial communities, a custom DNA microarray named 'FloraArray' was developed for screening specific probes that would represent the characteristics of a microbial community. The array was prepared by spotting 2000 plasmid DNAs from a genomic shotgun library of a sludge sample on a DNA microarray. By comparative hybridization of the array with two different samples of genomic DNA, one from the activated sludge and the other from a nonactivated sludge sample of an anaerobic ammonium oxidation (anammox) bacterial community, specific spots were visualized as a definite fluctuating profile in an MA (differential intensity ratio vs. spot intensity) plot. About 300 spots of the array accounted for the candidate probes to represent anammox reaction of the activated sludge. After sequence analysis of the probes and examination of the results of blastn searches against the reported anammox reference sequence, complete matches were found for 161 probes (58.3%) and >90% matches were found for 242 probes (87.1%). These results demonstrate that 'FloraArray' could be a useful tool for screening specific DNA molecules of unknown microbial communities.
Microarray Analysis of Microbiota of Gingival Lesions in Noma Patients
Huyghe, Antoine; François, Patrice; Mombelli, Andrea; Tangomo, Manuela; Girard, Myriam; Baratti-Mayer, Denise; Bolivar, Ignacio; Pittet, Didier; Schrenzel, Jacques
2013-01-01
Noma (cancrum oris) is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG) lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma. PMID:24086784
Choi, Young-Jun; Fuchs, Jeremy F.; Mayhew, George F.; Yu, Helen E.; Christensen, Bruce M.
2012-01-01
Hemocytes are integral components of mosquito immune mechanisms such as phagocytosis, melanization, and production of antimicrobial peptides. However, our understanding of hemocyte-specific molecular processes and their contribution to shaping the host immune response remains limited. To better understand the immunophysiological features distinctive of hemocytes, we conducted genome-wide analysis of hemocyte-enriched transcripts, and examined how tissue-enriched expression patterns change with the immune status of the host. Our microarray data indicate that the hemocyte-enriched trascriptome is dynamic and context-dependent. Analysis of transcripts enriched after bacterial challenge in circulating hemocytes with respect to carcass added a dimension to evaluating infection-responsive genes and immune-related gene families. We resolved patterns of transcriptional change unique to hemocytes from those that are likely shared by other immune responsive tissues, and identified clusters of genes preferentially induced in hemocytes, likely reflecting their involvement in cell type specific functions. In addition, the study revealed conserved hemocyte-enriched molecular repertoires which might be implicated in core hemocyte function by cross-species meta-analysis of microarray expression data from Anopheles gambiae and Drosophila melanogaster. PMID:22796331
NASA Technical Reports Server (NTRS)
Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.
2002-01-01
The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.
Elkins, C A; Kotewicz, M L; Jackson, S A; Lacher, D W; Abu-Ali, G S; Patel, I R
2013-01-01
Modern risk control and food safety practices involving food-borne bacterial pathogens are benefiting from new genomic technologies for rapid, yet highly specific, strain characterisations. Within the United States Food and Drug Administration (USFDA) Center for Food Safety and Applied Nutrition (CFSAN), optical genome mapping and DNA microarray genotyping have been used for several years to quickly assess genomic architecture and gene content, respectively, for outbreak strain subtyping and to enhance retrospective trace-back analyses. The application and relative utility of each method varies with outbreak scenario and the suspect pathogen, with comparative analytical power enhanced by database scale and depth. Integration of these two technologies allows high-resolution scrutiny of the genomic landscapes of enteric food-borne pathogens with notable examples including Shiga toxin-producing Escherichia coli (STEC) and Salmonella enterica serovars from a variety of food commodities. Moreover, the recent application of whole genome sequencing technologies to food-borne pathogen outbreaks and surveillance has enhanced resolution to the single nucleotide scale. This new wealth of sequence data will support more refined next-generation custom microarray designs, targeted re-sequencing and "genomic signature recognition" approaches involving a combination of genes and single nucleotide polymorphism detection to distil strain-specific fingerprinting to a minimised scale. This paper examines the utility of microarrays and optical mapping in analysing outbreaks, reviews best practices and the limits of these technologies for pathogen differentiation, and it considers future integration with whole genome sequencing efforts.
Escorihuela, Jorge; Bañuls, María José; García Castelló, Javier; Toccafondo, Veronica; García-Rupérez, Jaime; Puchades, Rosa; Maquieira, Ángel
2012-12-01
Methodology for the functionalization of silicon-based materials employed for the development of photonic label-free nanobiosensors is reported. The studied functionalization based on organosilane chemistry allowed the direct attachment of biomolecules in a single step, maintaining their bioavailability. Using this immobilization approach in probe microarrays, successful specific detection of bacterial DNA is achieved, reaching hybridization sensitivities of 10 pM. The utility of the immobilization approach for the functionalization of label-free nanobiosensors based on photonic crystals and ring resonators was demonstrated using bovine serum albumin (BSA)/anti-BSA as a model system.
Ecology and genomics of Bacillus subtilis.
Earl, Ashlee M; Losick, Richard; Kolter, Roberto
2008-06-01
Bacillus subtilis is a remarkably diverse bacterial species that is capable of growth within many environments. Recent microarray-based comparative genomic analyses have revealed that members of this species also exhibit considerable genomic diversity. The identification of strain-specific genes might explain how B. subtilis has become so broadly adapted. The goal of identifying ecologically adaptive genes could soon be realized with the imminent release of several new B. subtilis genome sequences. As we embark upon this exciting new era of B. subtilis comparative genomics we review what is currently known about the ecology and evolution of this species.
Effect of Microgravity on Sinorhizobium meliloti: Initial Results from the SyNRGE Experiment
NASA Technical Reports Server (NTRS)
Roberts, Michael S.; Stutte, Gary W.
2011-01-01
SyNRGE (Symbiotic Nodulation in a Reduced Gravity Environment) was a sortie mission on STS-135 in the Biological Research in Canisters (BRIe) hardware to study the effect of microgravity on a plant-microbe symbiosis resulting in biological nitrogen fixation. Medicago truncatula, a model species of the legume family, was innoculated with its bacterial symbiont, Sinorhizobium meliloti, to observe early events associated with infection and nodulation in Petri Dish Fixation Units (PDFUs). Two sets of experiments were conducted in orbit and in 24-hour delayed ground controls. Experiment one was designed to determine if S. meliloti infect M. truncatula and initiate physiological changes associated with nodule formation. Roots of five-day-old M. truncatula cultivar Jemalong A17 (Enodll::gus) were innoculated 24 hr before launch with either S. meliloti strain 1021 or strain ABS7 and integrated into BRIC-PDFU hardware placed in a 4 C Cold Bag for launch on Atlantis. Innoculated plants and uninoculated controls were maintained in the dark at ambient temperature in the middeck of STS-135 for 11 days before fixation in RNA/ate/M by crew activation of the PDFU. Experiment two was designed to determine if microgravity altered the process of bacterial infection and host plant nodule formation. Seeds of two M. truncatula cultivar Jemalong A17 lines, the Enodll::gus used in experiment 1, and SUNN, a super-nodulating mutant of A17, were germinated on orbit for 11 days in the middeck cabin and returned to Earth alive inside of BRIC-PDFU's at 4 C S. meliloti strains 1021 and ABS7 were cultivated separately in broth culture on orbit and also returned to Earth alive. After landing, flight- and ground-grown plants and bacteria were transferred from BRIC-PDFU's into Nunc(TradeMark) 4-well plates for reciprocity crosses. Rates of plant growth and nodule development on Buffered Nodulation Medium (lacking nitrogen) were measured for 14 days. Bacteria cultivated in microgravity in the presence or absence of M. truncatula were characterized by phenotype microarray (PM) analysis of over 1,000 phenotypes including the utilization of carbon, nitrogen, phosphate, and sulfur sources; growth stimulation/inhibition by nutrients, osmolytes, and metabolic inhibitors; and antibiotic susceptibility. (Research supported by NASA ESMD/Advance Capabilities Division grant NNX10AR0
Engelmann, Brett W
2017-01-01
The Src Homology 2 (SH2) domain family primarily recognizes phosphorylated tyrosine (pY) containing peptide motifs. The relative affinity preferences among competing SH2 domains for phosphopeptide ligands define "specificity space," and underpins many functional pY mediated interactions within signaling networks. The degree of promiscuity exhibited and the dynamic range of affinities supported by individual domains or phosphopeptides is best resolved by a carefully executed and controlled quantitative high-throughput experiment. Here, I describe the fabrication and application of a cellulose-peptide conjugate microarray (CPCMA) platform to the quantitative analysis of SH2 domain specificity space. Included herein are instructions for optimal experimental design with special attention paid to common sources of systematic error, phosphopeptide SPOT synthesis, microarray fabrication, analyte titrations, data capture, and analysis.
Shen, Congcong; Shi, Yu; Ni, Yingying; Deng, Ye; Van Nostrand, Joy D; He, Zhili; Zhou, Jizhong; Chu, Haiyan
2016-01-01
The elevational and latitudinal diversity patterns of microbial taxa have attracted great attention in the past decade. Recently, the distribution of functional attributes has been in the spotlight. Here, we report a study profiling soil microbial communities along an elevation gradient (500-2200 m) on Changbai Mountain. Using a comprehensive functional gene microarray (GeoChip 5.0), we found that microbial functional gene richness exhibited a dramatic increase at the treeline ecotone, but the bacterial taxonomic and phylogenetic diversity based on 16S rRNA gene sequencing did not exhibit such a similar trend. However, the β-diversity (compositional dissimilarity among sites) pattern for both bacterial taxa and functional genes was similar, showing significant elevational distance-decay patterns which presented increased dissimilarity with elevation. The bacterial taxonomic diversity/structure was strongly influenced by soil pH, while the functional gene diversity/structure was significantly correlated with soil dissolved organic carbon (DOC). This finding highlights that soil DOC may be a good predictor in determining the elevational distribution of microbial functional genes. The finding of significant shifts in functional gene diversity at the treeline ecotone could also provide valuable information for predicting the responses of microbial functions to climate change.
Molecular diagnosis of bloodstream infections: planning to (physically) reach the bedside.
Leggieri, N; Rida, A; François, P; Schrenzel, Jacques
2010-08-01
Faster identification of infecting microorganisms and treatment options is a first-ranking priority in the infectious disease area, in order to prevent inappropriate treatment and overuse of broad-spectrum antibiotics. Standard bacterial identification is intrinsically time-consuming, and very recently there has been a burst in the number of commercially available nonphenotype-based techniques and in the documentation of a possible clinical impact of these techniques. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is now a standard diagnostic procedure on cultures and hold promises on spiked blood. Meanwhile, commercial PCR-based techniques have improved with the use of bacterial DNA enrichment methods, the diversity of amplicon analysis techniques (melting curve analysis, microarrays, gel electrophoresis, sequencing and analysis by mass spectrometry) leading to the ability to challenge bacterial culture as the gold standard for providing earlier diagnosis with a better 'clinical' sensitivity and additional prognostic information. Laboratory practice has already changed with MALDI-TOF MS, but a change in clinical practice, driven by emergent nucleic acid-based techniques, will need the demonstration of real-life applicability as well as robust clinical-impact-oriented studies.
Martínez, Isidoro; Oliveros, Juan C.; Cuesta, Isabel; de la Barrera, Jorge; Ausina, Vicente; Casals, Cristina; de Lorenzo, Alba; García, Ernesto; García-Fojeda, Belén; Garmendia, Junkal; González-Nicolau, Mar; Lacoma, Alicia; Menéndez, Margarita; Moranta, David; Nieto, Amelia; Ortín, Juan; Pérez-González, Alicia; Prat, Cristina; Ramos-Sevillano, Elisa; Regueiro, Verónica; Rodriguez-Frandsen, Ariel; Solís, Dolores; Yuste, José; Bengoechea, José A.; Melero, José A.
2017-01-01
Lower respiratory tract infections are among the top five leading causes of human death. Fighting these infections is therefore a world health priority. Searching for induced alterations in host gene expression shared by several relevant respiratory pathogens represents an alternative to identify new targets for wide-range host-oriented therapeutics. With this aim, alveolar macrophages were independently infected with three unrelated bacterial (Streptococcus pneumoniae, Klebsiella pneumoniae, and Staphylococcus aureus) and two dissimilar viral (respiratory syncytial virus and influenza A virus) respiratory pathogens, all of them highly relevant for human health. Cells were also activated with bacterial lipopolysaccharide (LPS) as a prototypical pathogen-associated molecular pattern. Patterns of differentially expressed cellular genes shared by the indicated pathogens were searched by microarray analysis. Most of the commonly up-regulated host genes were related to the innate immune response and/or apoptosis, with Toll-like, RIG-I-like and NOD-like receptors among the top 10 signaling pathways with over-expressed genes. These results identify new potential broad-spectrum targets to fight the important human infections caused by the bacteria and viruses studied here. PMID:28298903
Chavan, Shweta S; Bauer, Michael A; Peterson, Erich A; Heuck, Christoph J; Johann, Donald J
2013-01-01
Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.
Jensen, Michael L.; Thymann, Thomas; Cilieborg, Malene S.; Lykke, Mikkel; Mølbak, Lars; Jensen, Bent B.; Schmidt, Mette; Kelly, Denise; Mulder, Imke; Burrin, Douglas G.
2013-01-01
Preterm birth, bacterial colonization, and formula feeding predispose to necrotizing enterocolitis (NEC). Antibiotics are commonly administered to prevent sepsis in preterm infants, but it is not known whether this affects intestinal immunity and NEC resistance. We hypothesized that broad-spectrum antibiotic treatment improves NEC resistance and intestinal structure, function, and immunity in neonates. Caesarean-delivered preterm pigs were fed 3 days of parenteral nutrition followed by 2 days of enteral formula. Immediately after birth, they were assigned to receive either antibiotics (oral and parenteral doses of gentamycin, ampicillin, and metronidazole, ANTI, n = 11) or saline in the control group (CON, n = 13), given twice daily. NEC lesions and intestinal structure, function, microbiology, and immunity markers were recorded. None of the ANTI but 85% of the CON pigs developed NEC lesions by day 5 (0/11 vs. 11/13, P < 0.05). ANTI pigs had higher intestinal villi (+60%), digestive enzyme activities (+53–73%), and goblet cell densities (+110%) and lower myeloperoxidase (−51%) and colonic microbial density (105 vs. 1010 colony-forming units, all P < 0.05). Microarray transcriptomics showed strong downregulation of genes related to inflammation and innate immune response to microbiota and marked upregulation of genes related to amino acid metabolism, in particular threonine, glucose transport systems, and cell cycle in 5-day-old ANTI pigs. In a follow-up experiment, 5 days of antibiotics prevented NEC at least until day 10. Neonatal prophylactic antibiotics effectively reduced gut bacterial load, prevented NEC, intestinal atrophy, dysfunction, and inflammation and enhanced expression of genes related to gut metabolism and immunity in preterm pigs. PMID:24157972
Lee, Joseph C; Stiles, David; Lu, Jun; Cam, Margaret C
2007-01-01
Background Microarrays are a popular tool used in experiments to measure gene expression levels. Improving the reproducibility of microarray results produced by different chips from various manufacturers is important to create comparable and combinable experimental results. Alternative splicing has been cited as a possible cause of differences in expression measurements across platforms, though no study to this point has been conducted to show its influence in cross-platform differences. Results Using probe sequence data, a new microarray probe/transcript annotation was created based on the AceView Aug05 release that allowed for the categorization of genes based on their expression measurements' susceptibility to alternative splicing differences across microarray platforms. Examining gene expression data from multiple platforms in light of the new categorization, genes unsusceptible to alternative splicing differences showed higher signal agreement than those genes most susceptible to alternative splicing differences. The analysis gave rise to a different probe-level visualization method that can highlight probe differences according to transcript specificity. Conclusion The results highlight the need for detailed probe annotation at the transcriptome level. The presence of alternative splicing within a given sample can affect gene expression measurements and is a contributing factor to overall technical differences across platforms. PMID:17708771
Brodsky, Leonid; Leontovich, Andrei; Shtutman, Michael; Feinstein, Elena
2004-01-01
Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides’ areas characterized by an abnormal concentration of low/high differential expression values, which we define as ‘patterns of differentials’. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile’s quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis. PMID:14999086
Imholte, Gregory; Gottardo, Raphael
2017-01-01
Summary The peptide microarray immunoassay simultaneously screens sample serum against thousands of peptides, determining the presence of antibodies bound to array probes. Peptide microarrays tiling immunogenic regions of pathogens (e.g. envelope proteins of a virus) are an important high throughput tool for querying and mapping antibody binding. Because of the assay’s many steps, from probe synthesis to incubation, peptide microarray data can be noisy with extreme outliers. In addition, subjects may produce different antibody profiles in response to an identical vaccine stimulus or infection, due to variability among subjects’ immune systems. We present a robust Bayesian hierarchical model for peptide microarray experiments, pepBayes, to estimate the probability of antibody response for each subject/peptide combination. Heavy-tailed error distributions accommodate outliers and extreme responses, and tailored random effect terms automatically incorporate technical effects prevalent in the assay. We apply our model to two vaccine trial datasets to demonstrate model performance. Our approach enjoys high sensitivity and specificity when detecting vaccine induced antibody responses. A simulation study shows an adaptive thresholding classification method has appropriate false discovery rate control with high sensitivity, and receiver operating characteristics generated on vaccine trial data suggest that pepBayes clearly separates responses from non-responses. PMID:27061097
Mothers' appreciation of chromosomal microarray analysis for autism spectrum disorder.
Giarelli, Ellen; Reiff, Marian
2015-10-01
The aim of this study was to examine mothers' experiences with chromosomal microarray analysis (CMA) for a child with autism spectrum disorder (ASD). This is a descriptive qualitative study using thematic content analysis of in-depth interview with 48 mothers of children who had genetic testing for ASD. The principal theme, "something is missing," included missing knowledge about genetics, information on use of the results, explanations of the relevance to the diagnosis, and relevance to life-long care. Two subordinate themes were (a) disappreciation of the helpfulness of scientific information to explain the diagnosis, and (b) returning to personal experience for interpretation. The test "appreciated" in value when results could be linked to the phenotype. © 2015, Wiley Periodicals, Inc.
Translating standards into practice - one Semantic Web API for Gene Expression.
Deus, Helena F; Prud'hommeaux, Eric; Miller, Michael; Zhao, Jun; Malone, James; Adamusiak, Tomasz; McCusker, Jim; Das, Sudeshna; Rocca Serra, Philippe; Fox, Ronan; Marshall, M Scott
2012-08-01
Sharing and describing experimental results unambiguously with sufficient detail to enable replication of results is a fundamental tenet of scientific research. In today's cluttered world of "-omics" sciences, data standards and standardized use of terminologies and ontologies for biomedical informatics play an important role in reporting high-throughput experiment results in formats that can be interpreted by both researchers and analytical tools. Increasing adoption of Semantic Web and Linked Data technologies for the integration of heterogeneous and distributed health care and life sciences (HCLSs) datasets has made the reuse of standards even more pressing; dynamic semantic query federation can be used for integrative bioinformatics when ontologies and identifiers are reused across data instances. We present here a methodology to integrate the results and experimental context of three different representations of microarray-based transcriptomic experiments: the Gene Expression Atlas, the W3C BioRDF task force approach to reporting Provenance of Microarray Experiments, and the HSCI blood genomics project. Our approach does not attempt to improve the expressivity of existing standards for genomics but, instead, to enable integration of existing datasets published from microarray-based transcriptomic experiments. SPARQL Construct is used to create a posteriori mappings of concepts and properties and linking rules that match entities based on query constraints. We discuss how our integrative approach can encourage reuse of the Experimental Factor Ontology (EFO) and the Ontology for Biomedical Investigations (OBIs) for the reporting of experimental context and results of gene expression studies. Copyright © 2012 Elsevier Inc. All rights reserved.
Methods for processing microarray data.
Ares, Manuel
2014-02-01
Quality control must be maintained at every step of a microarray experiment, from RNA isolation through statistical evaluation. Here we provide suggestions for analyzing microarray data. Because the utility of the results depends directly on the design of the experiment, the first critical step is to ensure that the experiment can be properly analyzed and interpreted. What is the biological question? What is the best way to perform the experiment? How many replicates will be required to obtain the desired statistical resolution? Next, the samples must be prepared, pass quality controls for integrity and representation, and be hybridized and scanned. Also, slides with defects, missing data, high background, or weak signal must be rejected. Data from individual slides must be normalized and combined so that the data are as free of systematic bias as possible. The third phase is to apply statistical filters and tests to the data to determine genes (1) expressed above background, (2) whose expression level changes in different samples, and (3) whose RNA-processing patterns or protein associations change. Next, a subset of the data should be validated by an alternative method, such as reverse transcription-polymerase chain reaction (RT-PCR). Provided that this endorses the general conclusions of the array analysis, gene sets whose expression, splicing, polyadenylation, protein binding, etc. change in different samples can be classified with respect to function, sequence motif properties, as well as other categories to extract hypotheses for their biological roles and regulatory logic.
Reboiro-Jato, Miguel; Arrais, Joel P; Oliveira, José Luis; Fdez-Riverola, Florentino
2014-01-30
The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools. geneCommittee is a web-based interactive tool for routinely evaluating the discriminative classification power of custom hypothesis in the form of biologically relevant gene sets. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. Provided with a straightforward and intuitive interface, geneCommittee is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research. geneCommittee allows the enrichment of microarrays raw data with gene functional annotations, producing integrated datasets that simplify the construction of better discriminative hypothesis, and allows the creation of a set of complementary classifiers. The trained committees can then be used for clinical research and diagnosis. Full documentation including common use cases and guided analysis workflows is freely available at http://sing.ei.uvigo.es/GC/.
Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent
2009-01-01
Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a STARNET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at , and does not require user registration. PMID:19828039
Roder, Cornelia; Arif, Chatchanit; Daniels, Camille; Weil, Ernesto; Voolstra, Christian R
2014-01-01
Coral diseases are characterized by microbial community shifts in coral mucus and tissue, but causes and consequences of these changes are vaguely understood due to the complexity and dynamics of coral-associated bacteria. We used 16S rRNA gene microarrays to assay differences in bacterial assemblages of healthy and diseased colonies displaying White Plague Disease (WPD) signs from two closely related Caribbean coral species, Orbicella faveolata and Orbicella franksi. Analysis of differentially abundant operational taxonomic units (OTUs) revealed strong differences between healthy and diseased specimens, but not between coral species. A subsequent comparison to data from two Indo-Pacific coral species (Pavona duerdeni and Porites lutea) revealed distinct microbial community patterns associated with ocean basin, coral species and health state. Coral species were clearly separated by site, but also, the relatedness of the underlying bacterial community structures resembled the phylogenetic relationship of the coral hosts. In diseased samples, bacterial richness increased and putatively opportunistic bacteria were consistently more abundant highlighting the role of opportunistic conditions in structuring microbial community patterns during disease. Our comparative analysis shows that it is possible to derive conserved bacterial footprints of diseased coral holobionts that might help in identifying key bacterial species related to the underlying etiopathology. Furthermore, our data demonstrate that similar-appearing disease phenotypes produce microbial community patterns that are consistent over coral species and oceans, irrespective of the putative underlying pathogen. Consequently, profiling coral diseases by microbial community structure over multiple coral species might allow the development of a comparative disease framework that can inform on cause and relatedness of coral diseases. PMID:24350609
Kraiselburd, Ivana; Daurelio, Lucas D.; Tondo, María Laura; Merelo, Paz; Cortadi, Adriana A.; Talón, Manuel; Tadeo, Francisco R.; Orellano, Elena G.
2013-01-01
Pathogens interaction with a host plant starts a set of immune responses that result in complex changes in gene expression and plant physiology. Light is an important modulator of plant defense response and recent studies have evidenced the novel influence of this environmental stimulus in the virulence of several bacterial pathogens. Xanthomonas citri subsp. citri is the bacterium responsible for citrus canker disease, which affects most citrus cultivars. The ability of this bacterium to colonize host plants is influenced by bacterial blue-light sensing through a LOV-domain protein and disease symptoms are considerably altered upon deletion of this protein. In this work we aimed to unravel the role of this photoreceptor during the bacterial counteraction of plant immune responses leading to citrus canker development. We performed a transcriptomic analysis in Citrus sinensis leaves inoculated with the wild type X. citri subsp. citri and with a mutant strain lacking the LOV protein by a cDNA microarray and evaluated the differentially regulated genes corresponding to specific biological processes. A down-regulation of photosynthesis-related genes (together with a corresponding decrease in photosynthesis rates) was observed upon bacterial infection, this effect being more pronounced in plants infected with the lov-mutant bacterial strain. Infection with this strain was also accompanied with the up-regulation of several secondary metabolism- and defense response-related genes. Moreover, we found that relevant plant physiological alterations triggered by pathogen attack such as cell wall fortification and tissue disruption were amplified during the lov-mutant strain infection. These results suggest the participation of the LOV-domain protein from X. citri subsp. citri in the bacterial counteraction of host plant defense response, contributing in this way to disease development. PMID:24260514
Weighted analysis of paired microarray experiments.
Kristiansson, Erik; Sjögren, Anders; Rudemo, Mats; Nerman, Olle
2005-01-01
In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.
Wang, Yuwei; Yang, Chun; He, Yonglin; Zhan, Xingxing; Xu, Lei
2016-08-01
Tuberculosis is a major challenge to global public health. However, the Bacille Calmette‑Guérin (BCG), the only vaccine available against tuberculosis, has been questioned for the low protective effect. The present study used the mouse gene intracellular pathogen resistance I (Ipr1) gene to alter the current BCG vaccine and evaluated its immunity effect against tuberculosis. This study also investigated the intrinsic relationships of Ipr1 and innate immunity. The reformed BCG (BCGi) carrying the Ipr1 gene was constructed. The mice were intranasally challenged with the M. tuberculosis H37Rv strain after vaccination with BCGi. Protection efficacy of the vaccine was assessed by the organ coefficient, bacterial load and pathological changes in the lung. The differential expression of 113 immune‑related genes between BCGi and BCG groups were detected by an oligo microarray. According to the results of organ coefficient, bacterial load and pathological changes in the organization, BCGi had been shown to have stronger protective effects against M. tuberculosis than BCG. The oligo microarray and reverse transcription‑quantitative polymerase chain reaction further revealed that the Ipr1 gene could upregulate the expression of 13 genes, including a >3‑fold increase in Toll‑like receptor (TLR)4 and 10‑fold increase in surfactant protein D (sftpd). The two genes not only participate in innate immunity against pathogens, but also are closely interrelated. Ipr1 could activate the TLR4 and sftpd signaling pathway and improve the innate immunity against tuberculosis, therefore Ipr1 modified BCG may be a candidate vaccine against M. tuberculosis.
Oral microbiota species in acute apical endodontic abscesses
George, Noelle; Flamiatos, Erin; Kawasaki, Kellie; Kim, Namgu; Carriere, Charles; Phan, Brian; Joseph, Raphael; Strauss, Shay; Kohli, Richie; Choi, Dongseok; Craig Baumgartner, J.; Sedgley, Christine; Maier, Tom; Machida, Curtis A.
2016-01-01
Background and objectives Acute apical abscesses are serious endodontic diseases resulting from pulpal infection with opportunistic oral microorganisms. The objective of this study was to identify and compare the oral microbiota in patients (N=18) exhibiting acute apical abscesses, originating from the demographic region in Portland, Oregon. The study hypothesis is that abscesses obtained from this demographic region may contain unique microorganisms not identified in specimens from other regions. Design Endodontic abscesses were sampled from patients at the Oregon Health & Science University (OHSU) School of Dentistry. DNA from abscess specimens was subjected to polymerase chain reaction amplification using 16S rRNA gene-specific primers and Cy3-dCTP labeling. Labeled DNA was then applied to microbial microarrays (280 species) generated by the Human Oral Microbial Identification Microarray Laboratory (Forsyth Institute, Cambridge, MA). Results The most prevalent microorganisms, found across multiple abscess specimens, include Fusobacterium nucleatum, Parvimonas micra, Megasphaera species clone CS025, Prevotella multisaccharivorax, Atopobium rimae, and Porphyromonas endodontalis. The most abundant microorganisms, found in highest numbers within individual abscesses, include F. nucleatum, P. micra, Streptococcus Cluster III, Solobacterium moorei, Streptococcus constellatus, and Porphyromonas endodontalis. Strong bacterial associations were identified between Prevotella multisaccharivorax, Acidaminococcaceae species clone DM071, Megasphaera species clone CS025, Actinomyces species clone EP053, and Streptococcus cristatus (all with Spearman coefficients >0.9). Conclusions Cultivable and uncultivable bacterial species have been identified in endodontic abscesses obtained from the Portland, Oregon demographic region, and taxa identifications correlated well with other published studies, with the exception of Treponema and Streptococcus cristae, which were not commonly identified in endodontic abscesses between the demographic region in Portland, Oregon and other regions. PMID:26983837
Koide, Tie; Zaini, Paulo A; Moreira, Leandro M; Vêncio, Ricardo Z N; Matsukuma, Adriana Y; Durham, Alan M; Teixeira, Diva C; El-Dorry, Hamza; Monteiro, Patrícia B; da Silva, Ana Claudia R; Verjovski-Almeida, Sergio; da Silva, Aline M; Gomes, Suely L
2004-08-01
Xylella fastidiosa is a phytopathogenic bacterium that causes serious diseases in a wide range of economically important crops. Despite extensive comparative analyses of genome sequences of Xylella pathogenic strains from different plant hosts, nonpathogenic strains have not been studied. In this report, we show that X. fastidiosa strain J1a12, associated with citrus variegated chlorosis (CVC), is nonpathogenic when injected into citrus and tobacco plants. Furthermore, a DNA microarray-based comparison of J1a12 with 9a5c, a CVC strain that is highly pathogenic and had its genome completely sequenced, revealed that 14 coding sequences of strain 9a5c are absent or highly divergent in strain J1a12. Among them, we found an arginase and a fimbrial adhesin precursor of type III pilus, which were confirmed to be absent in the nonpathogenic strain by PCR and DNA sequencing. The absence of arginase can be correlated to the inability of J1a12 to multiply in host plants. This enzyme has been recently shown to act as a bacterial survival mechanism by down-regulating host nitric oxide production. The lack of the adhesin precursor gene is in accordance with the less aggregated phenotype observed for J1a12 cells growing in vitro. Thus, the absence of both genes can be associated with the failure of the J1a12 strain to establish and spread in citrus and tobacco plants. These results provide the first detailed comparison between a nonpathogenic strain and a pathogenic strain of X. fastidiosa, constituting an important step towards understanding the molecular basis of the disease.
Koide, Tie; Zaini, Paulo A.; Moreira, Leandro M.; Vêncio, Ricardo Z. N.; Matsukuma, Adriana Y.; Durham, Alan M.; Teixeira, Diva C.; El-Dorry, Hamza; Monteiro, Patrícia B.; da Silva, Ana Claudia R.; Verjovski-Almeida, Sergio; da Silva, Aline M.; Gomes, Suely L.
2004-01-01
Xylella fastidiosa is a phytopathogenic bacterium that causes serious diseases in a wide range of economically important crops. Despite extensive comparative analyses of genome sequences of Xylella pathogenic strains from different plant hosts, nonpathogenic strains have not been studied. In this report, we show that X. fastidiosa strain J1a12, associated with citrus variegated chlorosis (CVC), is nonpathogenic when injected into citrus and tobacco plants. Furthermore, a DNA microarray-based comparison of J1a12 with 9a5c, a CVC strain that is highly pathogenic and had its genome completely sequenced, revealed that 14 coding sequences of strain 9a5c are absent or highly divergent in strain J1a12. Among them, we found an arginase and a fimbrial adhesin precursor of type III pilus, which were confirmed to be absent in the nonpathogenic strain by PCR and DNA sequencing. The absence of arginase can be correlated to the inability of J1a12 to multiply in host plants. This enzyme has been recently shown to act as a bacterial survival mechanism by down-regulating host nitric oxide production. The lack of the adhesin precursor gene is in accordance with the less aggregated phenotype observed for J1a12 cells growing in vitro. Thus, the absence of both genes can be associated with the failure of the J1a12 strain to establish and spread in citrus and tobacco plants. These results provide the first detailed comparison between a nonpathogenic strain and a pathogenic strain of X. fastidiosa, constituting an important step towards understanding the molecular basis of the disease. PMID:15292146
Microbiome Analysis of Stool Samples from African Americans with Colon Polyps
Brim, Hassan; Yooseph, Shibu; Zoetendal, Erwin G.; Lee, Edward; Torralbo, Manolito; Laiyemo, Adeyinka O.; Shokrani, Babak; Nelson, Karen; Ashktorab, Hassan
2013-01-01
Background Colonic polyps are common tumors occurring in ~50% of Western populations with ~10% risk of malignant progression. Dietary agents have been considered the primary environmental exposure to promote colorectal cancer (CRC) development. However, the colonic mucosa is permanently in contact with the microbiota and its metabolic products including toxins that also have the potential to trigger oncogenic transformation. Aim To analyze fecal DNA for microbiota composition and functional potential in African Americans with pre-neoplastic lesions. Materials & Methods We analyzed the bacterial composition of stool samples from 6 healthy individuals and 6 patients with colon polyps using 16S ribosomal RNA-based phylogenetic microarray; the Human intestinal Tract Chip (HITChip) and 16S rRNA gene barcoded 454 pyrosequencing. The functional potential was determined by sequence-based metagenomics using 454 pyrosequencing. Results Fecal microbiota profiling of samples from the healthy and polyp patients using both a phylogenetic microarraying (HITChip) and barcoded 454 pyrosequencing generated similar results. A distinction between both sets of samples was only obtained when the analysis was performed at the sub-genus level. Most of the species leading to the dissociation were from the Bacteroides group. The metagenomic analysis did not reveal major differences in bacterial gene prevalence/abundances between the two groups even when the analysis and comparisons were restricted to available Bacteroides genomes. Conclusion This study reveals that at the pre-neoplastic stages, there is a trend showing microbiota changes between healthy and colon polyp patients at the sub-genus level. These differences were not reflected at the genome/functions levels. Bacteria and associated functions within the Bacteroides group need to be further analyzed and dissected to pinpoint potential actors in the early colon oncogenic transformation in a large sample size. PMID:24376500
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thomassen, Mads; Skov, Vibe; Eiriksdottir, Freyja
2006-06-16
The quality of DNA microarray based gene expression data relies on the reproducibility of several steps in a microarray experiment. We have developed a spotted genome wide microarray chip with oligonucleotides printed in duplicate in order to minimise undesirable biases, thereby optimising detection of true differential expression. The validation study design consisted of an assessment of the microarray chip performance using the MessageAmp and FairPlay labelling kits. Intraclass correlation coefficient (ICC) was used to demonstrate that MessageAmp was significantly more reproducible than FairPlay. Further examinations with MessageAmp revealed the applicability of the system. The linear range of the chips wasmore » three orders of magnitude, the precision was high, as 95% of measurements deviated less than 1.24-fold from the expected value, and the coefficient of variation for relative expression was 13.6%. Relative quantitation was more reproducible than absolute quantitation and substantial reduction of variance was attained with duplicate spotting. An analysis of variance (ANOVA) demonstrated no significant day-to-day variation.« less
Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R.; del Río-Navarro, Blanca E.; Mendoza-Vargas, Alfredo; Sánchez, Filiberto
2017-01-01
Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. PMID:29230367
DigOut: viewing differential expression genes as outliers.
Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan
2010-12-01
With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.
Methylation oligonucleotide microarray: a novel tool to analyze methylation patterns
NASA Astrophysics Data System (ADS)
Hou, Peng; Ji, Meiju; He, Nongyao; Lu, Zuhong
2003-04-01
A new technique to analyze methylation patterns in several adjacent CpG sites was developed and reported here. We selected a 336bp segment of the 5"-untranslated region and the first exon of the p16Ink4a gene, which include the most densely packed CpG fragment of the islands containing 32 CpG dinucleotides, as the investigated target. The probes that include all types of methylation patterns were designed to fabricate a DNA microarray to determine the methylation patterns of seven adjacent CpG dinucleotides sites. High accuracy and reproducibility were observed in several parallel experiments. The results led us to the conclusion that the methylation oligonucleotide microarray can be applied as a novel and powerful tool to map methylation patterns and changes in multiple CpG island loci in a variety of tumors.
Impact of Whole Body Irradiation on the Intestinal Microbiome- Considerations for Space Flight
NASA Astrophysics Data System (ADS)
Karouia, Fathi; Santos, Orlando; Valdivia-Silva, Julio E.; Jones, Jeffrey; Greenberger, Joel S.; Epperly, Michael W.
Human space travelers experience a unique environment that affects homeostasis and physiologic adaptation. Spaceflight-related changes have been reported in the musculo-skeletal, cardiovascular, neurovestibular, endocrine, and immune systems to just name a few. However, to date, radiation exposure is one of the main limiting factors for long duration space exploration missions and especially a mission to Mars. Over the past few years through advances in technology, the characterization of the microbiome has revealed a large and complex community of microorganisms living in symbiosis with the human host. However, heterogeneity of the intestinal microbial spectrum in humans has been associated with a variety of diseases and susceptibility to infectious and toxic agents. Limited information is known about the influence of space environment in general and radiation in particular on the microbiome. Furthermore, multiple spaceflight and simulated microgravity experiments have shown changes in phenotypic microbial characteristics such as microbial growth, morphology, metabolism, genetic transfer, antibiotic and stress susceptibility, and an increase in virulence factors. We now report a study of the bacterial composition of the intestine in C57BL/6NTAC mice and the types of microbes entering the body at two time points after the LD 50/30 dose of total body irradiation using microarray-based assay, G3 PhyloChip 16S rRNA, and bioinformatics methods. Bacteria and archaea taxon richness was determined at the genus level and ranged from 2 to 107 and 0 to 3 respectively. As expected, pre-exposure blood samples exhibited less bacterial and archaeal genus richness compared to all other samples. However, the study shows a significant shift in the mouse gut microbial speciation in several bacterial families, with increases in the Turicibacteraceae and Enterobacteriaceae and decreases in the Lachnospiraceae and Ruminococcaceae families. The findings most relevant to occupational human exposure, would likely relate to the increase in populations of Enterobacteriaceae, as multiple species within this family are known to produce disease in humans, including abscess formation, bacteremia, sepsis, disseminated toxins and even death. Therefore studies on the impact of the space environment and space radiation in particular on the astronaut’s microbiome composition and pathogeneicity in addition to the development of countermeasures are important steps in order to decrease risks associated with astronaut’s health and mission integrity.
Gene Expression Analysis: Teaching Students to Do 30,000 Experiments at Once with Microarray
ERIC Educational Resources Information Center
Carvalho, Felicia I.; Johns, Christopher; Gillespie, Marc E.
2012-01-01
Genome scale experiments routinely produce large data sets that require computational analysis, yet there are few student-based labs that illustrate the design and execution of these experiments. In order for students to understand and participate in the genomic world, teaching labs must be available where students generate and analyze large data…
Reverse engineering biological networks :applications in immune responses to bio-toxins.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martino, Anthony A.; Sinclair, Michael B.; Davidson, George S.
Our aim is to determine the network of events, or the regulatory network, that defines an immune response to a bio-toxin. As a model system, we are studying T cell regulatory network triggered through tyrosine kinase receptor activation using a combination of pathway stimulation and time-series microarray experiments. Our approach is composed of five steps (1) microarray experiments and data error analysis, (2) data clustering, (3) data smoothing and discretization, (4) network reverse engineering, and (5) network dynamics analysis and fingerprint identification. The technological outcome of this study is a suite of experimental protocols and computational tools that reverse engineermore » regulatory networks provided gene expression data. The practical biological outcome of this work is an immune response fingerprint in terms of gene expression levels. Inferring regulatory networks from microarray data is a new field of investigation that is no more than five years old. To the best of our knowledge, this work is the first attempt that integrates experiments, error analyses, data clustering, inference, and network analysis to solve a practical problem. Our systematic approach of counting, enumeration, and sampling networks matching experimental data is new to the field of network reverse engineering. The resulting mathematical analyses and computational tools lead to new results on their own and should be useful to others who analyze and infer networks.« less
Structure of the human gastric bacterial community in relation to Helicobacter pylori status.
Maldonado-Contreras, Ana; Goldfarb, Kate C; Godoy-Vitorino, Filipa; Karaoz, Ulas; Contreras, Mónica; Blaser, Martin J; Brodie, Eoin L; Dominguez-Bello, Maria G
2011-04-01
The human stomach is naturally colonized by Helicobacter pylori, which, when present, dominates the gastric bacterial community. In this study, we aimed to characterize the structure of the bacterial community in the stomach of patients of differing H. pylori status. We used a high-density 16S rRNA gene microarray (PhyloChip, Affymetrix, Inc.) to hybridize 16S rRNA gene amplicons from gastric biopsy DNA of 10 rural Amerindian patients from Amazonas, Venezuela, and of two immigrants to the United States (from South Asia and Africa, respectively). H. pylori status was determined by PCR amplification of H. pylori glmM from gastric biopsy samples. Of the 12 patients, 8 (6 of the 10 Amerindians and the 2 non-Amerindians) were H. pylori glmM positive. Regardless of H. pylori status, the PhyloChip detected Helicobacteriaceae DNA in all patients, although with lower relative abundance in patients who were glmM negative. The G2-chip taxonomy analysis of PhyloChip data indicated the presence of 44 bacterial phyla (of which 16 are unclassified by the Taxonomic Outline of the Bacteria and Archaea taxonomy) in a highly uneven community dominated by only four phyla: Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. Positive H. pylori status was associated with increased relative abundance of non-Helicobacter bacteria from the Proteobacteria, Spirochetes and Acidobacteria, and with decreased abundance of Actinobacteria, Bacteroidetes and Firmicutes. The PhyloChip detected richness of low abundance phyla, and showed marked differences in the structure of the gastric bacterial community according to H. pylori status.
Structure of the human gastric bacterial community in relation to Helicobacter pylori status
Maldonado-Contreras, Ana; Goldfarb, Kate C; Godoy-Vitorino, Filipa; Karaoz, Ulas; Contreras, Mónica; Blaser, Martin J; Brodie, Eoin L; Dominguez-Bello, Maria G
2011-01-01
The human stomach is naturally colonized by Helicobacter pylori, which, when present, dominates the gastric bacterial community. In this study, we aimed to characterize the structure of the bacterial community in the stomach of patients of differing H. pylori status. We used a high-density 16S rRNA gene microarray (PhyloChip, Affymetrix, Inc.) to hybridize 16S rRNA gene amplicons from gastric biopsy DNA of 10 rural Amerindian patients from Amazonas, Venezuela, and of two immigrants to the United States (from South Asia and Africa, respectively). H. pylori status was determined by PCR amplification of H. pylori glmM from gastric biopsy samples. Of the 12 patients, 8 (6 of the 10 Amerindians and the 2 non-Amerindians) were H. pylori glmM positive. Regardless of H. pylori status, the PhyloChip detected Helicobacteriaceae DNA in all patients, although with lower relative abundance in patients who were glmM negative. The G2-chip taxonomy analysis of PhyloChip data indicated the presence of 44 bacterial phyla (of which 16 are unclassified by the Taxonomic Outline of the Bacteria and Archaea taxonomy) in a highly uneven community dominated by only four phyla: Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. Positive H. pylori status was associated with increased relative abundance of non-Helicobacter bacteria from the Proteobacteria, Spirochetes and Acidobacteria, and with decreased abundance of Actinobacteria, Bacteroidetes and Firmicutes. The PhyloChip detected richness of low abundance phyla, and showed marked differences in the structure of the gastric bacterial community according to H. pylori status. PMID:20927139
GenePublisher: Automated analysis of DNA microarray data.
Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, Thomas; Friis, Carsten
2003-07-01
GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with a specification of the data. The server performs normalization, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user.
Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne
2005-04-15
The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.
Wilson, J. W.; Ott, C. M.; zu Bentrup, K. Höner; Ramamurthy, R.; Quick, L.; Porwollik, S.; Cheng, P.; McClelland, M.; Tsaprailis, G.; Radabaugh, T.; Hunt, A.; Fernandez, D.; Richter, E.; Shah, M.; Kilcoyne, M.; Joshi, L.; Nelman-Gonzalez, M.; Hing, S.; Parra, M.; Dumars, P.; Norwood, K.; Bober, R.; Devich, J.; Ruggles, A.; Goulart, C.; Rupert, M.; Stodieck, L.; Stafford, P.; Catella, L.; Schurr, M. J.; Buchanan, K.; Morici, L.; McCracken, J.; Allen, P.; Baker-Coleman, C.; Hammond, T.; Vogel, J.; Nelson, R.; Pierson, D. L.; Stefanyshyn-Piper, H. M.; Nickerson, C. A.
2007-01-01
A comprehensive analysis of both the molecular genetic and phenotypic responses of any organism to the space flight environment has never been accomplished because of significant technological and logistical hurdles. Moreover, the effects of space flight on microbial pathogenicity and associated infectious disease risks have not been studied. The bacterial pathogen Salmonella typhimurium was grown aboard Space Shuttle mission STS-115 and compared with identical ground control cultures. Global microarray and proteomic analyses revealed that 167 transcripts and 73 proteins changed expression with the conserved RNA-binding protein Hfq identified as a likely global regulator involved in the response to this environment. Hfq involvement was confirmed with a ground-based microgravity culture model. Space flight samples exhibited enhanced virulence in a murine infection model and extracellular matrix accumulation consistent with a biofilm. Strategies to target Hfq and related regulators could potentially decrease infectious disease risks during space flight missions and provide novel therapeutic options on Earth. PMID:17901201
Microfluidic system for the identification of bacterial pathogens causing urinary tract infections
NASA Astrophysics Data System (ADS)
Becker, Holger; Hlawatsch, Nadine; Haraldsson, Tommy; van der Wijngaart, Wouter; Lind, Anders; Malhotra-Kumar, Surbi; Turlej-Rogacka, Agata; Goossens, Herman
2015-03-01
Urinary tract infections (UTIs) are among the most common bacterial infections and pose a significant healthcare burden. The growing trend in antibiotic resistance makes it mandatory to develop diagnostic kits which allow not only the determination of a pathogen but also the antibiotic resistances. We have developed a microfluidic cartridge which takes a direct urine sample, extracts the DNA, performs an amplification using batch-PCR and flows the sample over a microarray which is printed into a microchannel for fluorescence detection. The cartridge is injection-molded out of COP and contains a set of two-component injection-molded rotary valves to switch between input and to isolate the PCR chamber during thermocycling. The hybridization probes were spotted directly onto a functionalized section of the outlet microchannel. We have been able to successfully perform PCR of E.coli in urine in this chip and perform a fluorescence detection of PCR products. An upgraded design of the cartridge contains the buffers and reagents in blisters stored on the chip.
Duan, Liang; Song, Yonghui; Xia, Siqing; Hermanowicz, Slawomir W
2013-12-01
This study investigated the nitrifying bacterial community in membrane bioreactor (MBR) at short solids retention times (SRTs) of 3, 5 and 10 days. The denaturing gradient gel electrophoresis results showed that different types of ammonia-oxidizing bacteria (AOB) can survive at different operating conditions. The diversity of AOB increased as the SRT increased. The real-time PCR results showed that the amoA gene concentrations were similar when MBRs were stabilized, and it can be a good indicator of stabilized nitrification. The results of clone library indicated that Nitrosomonas was the dominant group of AOB in three reactors. The microarray results showed that Nitrospira was the dominant group of nitrite-oxidizing bacteria (NOB) in the system. All groups of AOB and NOB except Nitrosolobus and Nitrococcus were found in MBR, indicated that the nitrifying bacterial community structure was more complicated. The combination of some molecular tools can provide more information of microbial communities. Copyright © 2013 Elsevier Ltd. All rights reserved.
Variation of gene expression in Bacillus subtilis samples of fermentation replicates.
Zhou, Ying; Yu, Wen-Bang; Ye, Bang-Ce
2011-06-01
The application of comprehensive gene expression profiling technologies to compare wild and mutated microorganism samples or to assess molecular differences between various treatments has been widely used. However, little is known about the normal variation of gene expression in microorganisms. In this study, an Agilent customized microarray representing 4,106 genes was used to quantify transcript levels of five-repeated flasks to assess normal variation in Bacillus subtilis gene expression. CV analysis and analysis of variance were employed to investigate the normal variance of genes and the components of variance, respectively. The results showed that above 80% of the total variation was caused by biological variance. For the 12 replicates, 451 of 4,106 genes exhibited variance with CV values over 10%. The functional category enrichment analysis demonstrated that these variable genes were mainly involved in cell type differentiation, cell type localization, cell cycle and DNA processing, and spore or cyst coat. Using power analysis, the minimal biological replicate number for a B. subtilis microarray experiment was determined to be six. The results contribute to the definition of the baseline level of variability in B. subtilis gene expression and emphasize the importance of replicate microarray experiments.
Recursive feature selection with significant variables of support vectors.
Tsai, Chen-An; Huang, Chien-Hsun; Chang, Ching-Wei; Chen, Chun-Houh
2012-01-01
The development of DNA microarray makes researchers screen thousands of genes simultaneously and it also helps determine high- and low-expression level genes in normal and disease tissues. Selecting relevant genes for cancer classification is an important issue. Most of the gene selection methods use univariate ranking criteria and arbitrarily choose a threshold to choose genes. However, the parameter setting may not be compatible to the selected classification algorithms. In this paper, we propose a new gene selection method (SVM-t) based on the use of t-statistics embedded in support vector machine. We compared the performance to two similar SVM-based methods: SVM recursive feature elimination (SVMRFE) and recursive support vector machine (RSVM). The three methods were compared based on extensive simulation experiments and analyses of two published microarray datasets. In the simulation experiments, we found that the proposed method is more robust in selecting informative genes than SVMRFE and RSVM and capable to attain good classification performance when the variations of informative and noninformative genes are different. In the analysis of two microarray datasets, the proposed method yields better performance in identifying fewer genes with good prediction accuracy, compared to SVMRFE and RSVM.
SATRAT: Staphylococcus aureus transcript regulatory network analysis tool.
Gopal, Tamilselvi; Nagarajan, Vijayaraj; Elasri, Mohamed O
2015-01-01
Staphylococcus aureus is a commensal organism that primarily colonizes the nose of healthy individuals. S. aureus causes a spectrum of infections that range from skin and soft-tissue infections to fatal invasive diseases. S. aureus uses a large number of virulence factors that are regulated in a coordinated fashion. The complex regulatory mechanisms have been investigated in numerous high-throughput experiments. Access to this data is critical to studying this pathogen. Previously, we developed a compilation of microarray experimental data to enable researchers to search, browse, compare, and contrast transcript profiles. We have substantially updated this database and have built a novel exploratory tool-SATRAT-the S. aureus transcript regulatory network analysis tool, based on the updated database. This tool is capable of performing deep searches using a query and generating an interactive regulatory network based on associations among the regulators of any query gene. We believe this integrated regulatory network analysis tool would help researchers explore the missing links and identify novel pathways that regulate virulence in S. aureus. Also, the data model and the network generation code used to build this resource is open sourced, enabling researchers to build similar resources for other bacterial systems.
Fernádez-Morales, Flavio H; Duarte, Julio E; Samitier-Martí, Josep
2008-12-01
This paper describes the modeling and experimental verification of a castellated microelectrode array intended to handle biocells, based on common dielectrophoresis. The proposed microsystem was developed employing platinum electrodes deposited by lift-off, silicon micromachining, and photoresin patterning techniques. Having fabricated the microdevice it was tested employing Escherichia coli as bioparticle model. Positive dielectrophoresis could be verified with the selected cells for frequencies above 100 kHz, and electrohydrodynamic effects were observed as the dominant phenomena when working at lower frequencies. As a result, negative dielectrophoresis could not be observed because its occurrence overlaps with electrohydrodynamic effects; i.e. the viscous drag force acting on the particles is greater than the dielectrophoretic force at frequencies where negative dielectrophoresis should occur. The experiments illustrate the convenience of this kind of microdevices to micro handling biological objects, opening the possibility for using these microarrays with other bioparticles. Additionally, liquid motion as a result of electrohydrodynamic effects must be taken into account when designing bioparticle micromanipulators, and could be used as mechanism to clean the electrode surfaces, that is one of the most important problems related to this kind of devices.
Mansourian, Robert; Mutch, David M; Antille, Nicolas; Aubert, Jerome; Fogel, Paul; Le Goff, Jean-Marc; Moulin, Julie; Petrov, Anton; Rytz, Andreas; Voegel, Johannes J; Roberts, Matthew-Alan
2004-11-01
Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. The GEA code for R software is freely available upon request to authors.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hatazawa, Yukino; Research Fellow of Japan Society for the Promotion of Science, Tokyo; Minami, Kimiko
The expression of the transcriptional coactivator PGC1α is increased in skeletal muscles during exercise. Previously, we showed that increased PGC1α leads to prolonged exercise performance (the duration for which running can be continued) and, at the same time, increases the expression of branched-chain amino acid (BCAA) metabolism-related enzymes and genes that are involved in supplying substrates for the TCA cycle. We recently created mice with PGC1α knockout specifically in the skeletal muscles (PGC1α KO mice), which show decreased mitochondrial content. In this study, global gene expression (microarray) analysis was performed in the skeletal muscles of PGC1α KO mice compared withmore » that of wild-type control mice. As a result, decreased expression of genes involved in the TCA cycle, oxidative phosphorylation, and BCAA metabolism were observed. Compared with previously obtained microarray data on PGC1α-overexpressing transgenic mice, each gene showed the completely opposite direction of expression change. Bioinformatic analysis of the promoter region of genes with decreased expression in PGC1α KO mice predicted the involvement of several transcription factors, including a nuclear receptor, ERR, in their regulation. As PGC1α KO microarray data in this study show opposing findings to the PGC1α transgenic data, a loss-of-function experiment, as well as a gain-of-function experiment, revealed PGC1α’s function in the oxidative energy metabolism of skeletal muscles. - Highlights: • Microarray analysis was performed in the skeletal muscle of PGC1α KO mice. • Expression of genes in the oxidative energy metabolism was decreased. • Bioinformatic analysis of promoter region of the genes predicted involvement of ERR. • PGC1α KO microarray data in this study show the mirror image of transgenic data.« less
An efficient pseudomedian filter for tiling microrrays.
Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B
2007-06-07
Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at http://tiling.gersteinlab.org/pseudomedian/.
An efficient pseudomedian filter for tiling microrrays
Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B
2007-01-01
Background Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. Results We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Conclusion Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at . PMID:17555595
Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.
2002-01-01
The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 × g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies. PMID:12370447
Impact of developmental lead exposure on splenic factors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kasten-Jolly, Jane, E-mail: kjolly@wadsworth.or; Heo, Yong, E-mail: yheo@cu.ac.k; Lawrence, David A., E-mail: david.lawrence@wadsworth.or
2010-09-01
Lead (Pb) is known to alter the functions of numerous organ systems, including the hematopoietic and immune systems. Pb can induce anemia and can lower host resistance to bacterial and viral infections. The anemia is due to Pb's inhibition of hemoglobin synthesis and Pb's induction of membrane changes, leading to early erythrocyte senescence. Pb also increases B-cell activation/proliferation and skews T-cell help (Th) toward Th2 subset generation. The specific mechanisms for many of the Pb effects are, as yet, not completely understood. Therefore, we performed gene expression analysis, via microarray, on RNA from the spleens of developmentally Pb-exposed mice, inmore » order to gain further insight into these Pb effects. Splenic RNA microarray analysis indicated strong up-regulation of genes coding for proteolytic enzymes, lipases, amylase, and RNaseA. The data also showed that Pb affected the expression of many genes associated with innate immunity. Analysis of the microarray results via GeneSifter software indicated that Pb increased apoptosis, B-cell differentiation, and Th2 development. Direct up-regulation by Pb of expression of the gene encoding the heme-regulated inhibitor (HRI) suggested that Pb can decrease erythropoiesis by blocking globin mRNA translation. Pb's high elevation of digestive/catabolizing enzymes could generate immunogenic self peptides. With Pb's potential to induce new self-peptides and to enhance the expression of caspases, cytokines, and other immunomodulators, further evaluation of Pb's involvement in autoimmune phenomena, especially Th2-mediated autoantibody production, and alteration of organ system activities is warranted.« less
Wang, Jia-Chi; Boyar, Fatih Z
2016-01-01
Chromosomal microarray analysis (CMA) has been recommended and practiced routinely in the large reference laboratories of U.S.A. as the first-tier test for the postnatal evaluation of individuals with intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies. Using CMA as a diagnostic tool and without a routine setting of fluorescence in situ hybridization with labeled bacterial artificial chromosome probes (BAC-FISH) in the large reference laboratories becomes a challenge in the characterization of chromosome 9 pericentric region. This region has a very complex genomic structure and contains a variety of heterochromatic and euchromatic polymorphic variants. These variants were usually studied by G-banding, C-banding and BAC-FISH analysis. Chromosomal microarray analysis (CMA) was not recommended since it may lead to false positive results. Here, we presented a cohort of four cases, in which high-resolution CMA was used as the first-tier test or simultaneously with G-banding analysis on the proband to identify pathogenic copy number variants (CNVs) in the whole genome. CMA revealed large pathogenic CNVs from chromosome 9 in 3 cases which also revealed different G-banding patterns between the two chromosome 9 homologues. Although we demonstrated that high-resolution CMA played an important role in the identification of pathogenic copy number variants in chromosome 9 pericentric regions, the lack of BAC-FISH analysis or other useful tools renders significant challenges in the characterization of chromosome 9 pericentric regions. None; it is not a clinical trial, and the cases were retrospectively collected and analyzed.
Efficacy of a novel PCR- and microarray-based method in diagnosis of a prosthetic joint infection
2014-01-01
Background and purpose Polymerase chain reaction (PCR) methods enable detection and species identification of many pathogens. We assessed the efficacy of a new PCR and microarray-based platform for detection of bacteria in prosthetic joint infections (PJIs). Methods This prospective study involved 61 suspected PJIs in hip and knee prostheses and 20 negative controls. 142 samples were analyzed by Prove-it Bone and Joint assay. The laboratory staff conducting the Prove-it analysis were not aware of the results of microbiological culture and clinical findings. The results of the analysis were compared with diagnosis of PJIs defined according to the Musculoskeletal Infection Society (MSIS) criteria and with the results of microbiological culture. Results 38 of 61 suspected PJIs met the definition of PJI according to the MSIS criteria. Of the 38 patients, the PCR detected bacteria in 31 whereas bacterial culture was positive in 28 patients. 15 of the PJI patients were undergoing antimicrobial treatment as the samples for analysis were obtained. When antimicrobial treatment had lasted 4 days or more, PCR detected bacteria in 6 of the 9 patients, but positive cultures were noted in only 2 of the 9 patients. All PCR results for the controls were negative. Of the 61 suspected PJIs, there were false-positive PCR results in 6 cases. Interpretation The Prove-it assay was helpful in PJI diagnostics during ongoing antimicrobial treatment. Without preceding treatment with antimicrobials, PCR and microarray-based assay did not appear to give any additional information over culture. PMID:24564748
Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification
Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid
2015-01-01
This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003
Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.
Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid
2015-01-01
This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.
Ontology-based, Tissue MicroArray oriented, image centered tissue bank
Viti, Federica; Merelli, Ivan; Caprera, Andrea; Lazzari, Barbara; Stella, Alessandra; Milanesi, Luciano
2008-01-01
Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes. PMID:18460177
Ma, Chuang; Wang, Xiangfeng
2012-09-01
One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.
Ma, Chuang; Wang, Xiangfeng
2012-01-01
One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655
Favela-Hernández, Juan Manuel J; Clemente-Soto, Aldo F; Balderas-Rentería, Isaías; Garza-González, Elvira; Camacho-Corona, María del Rayo
2015-07-08
Bacterial infections represent one of the main threats to global public health. One of the major causative agents associated with high morbidity and mortality infections in hospitals worldwide is methicillin-resistant Staphylococcus aureus. Therefore, there is a need to develop new antibacterial agents to treat these infections, and natural products are a rich source of them. In previous studies, we reported that lignan 3'-demethoxy-6-O-demethylisoguaiacin, isolated and characterized from Larrea tridentate, showed the best activity towards methicillin-resistant S. aureus. Thus, the aim of this study was to determine the potential molecular mechanism of the antibacterial activity of 3'-demethoxy-6-O-demethylisoguaiacin against methicillin-resistant S. aureus using microarray technology. Results of microarray genome expression were validated by real-time polymerase chain reaction (RT-PCR). The genetic profile expression results showed that lignan 3'-demethoxy-6-O-demethylisoguaiacin had activity on cell membrane affecting proteins of the ATP-binding cassette (ABC) transport system causing bacteria death. This molecular mechanism is not present in any antibacterial commercial drug and could be a new target for the development of novel antibacterial agents.
Favela-Hernández, Juan Manuel J; Clemente-Soto, Aldo F; Balderas-Rentería, Isaías; Garza-González, Elvira; Camacho-Corona, María Del Rayo
2015-07-08
Bacterial infections represent one of the main threats to global public health. One of the major causative agents associated with high morbidity and mortality infections in hospitals worldwide is methicillin-resistant Staphylococcus aureus. Therefore, there is a need to develop new antibacterial agents to treat these infections, and natural products are a rich source of them. In previous studies, we reported that lignan 3'-demethoxy-6-O-demethylisoguaiacin, isolated and characterized from Larrea tridentate, showed the best activity towards methicillin-resistant S. aureus. Thus, the aim of this study was to determine the potential molecular mechanism of the antibacterial activity of 3'-demethoxy-6-O-demethylisoguaiacin against methicillin-resistant S. aureus using microarray technology. Results of microarray genome expression were validated by real-time polymerase chain reaction (RT-PCR). The genetic profile expression results showed that lignan 3'-demethoxy-6-O-demethylisoguaiacin had activity on cell membrane affecting proteins of the ATP-binding cassette (ABC) transport system causing bacteria death. This molecular mechanism is not present in any antibacterial commercial drug and could be a new target for the development of novel antibacterial agents.
Eisentraeger, Adolf; Reifferscheid, Georg; Dardenne, Freddy; Blust, Ronny; Schofer, Andrea
2007-04-01
More than 100,000 tons of 2,4,6-trinitrotoluene were produced at the former ammunition site Werk Tanne in Clausthal-Zellerfeld, Germany. The production of explosives and consequent detonation in approximately 1944 by the Allies caused great pollution in this area. Four soil samples and three water samples were taken from this site and characterized by applying chemical-analytical methods and several bioassays. Ecotoxicological test systems, such as the algal growth inhibition assay with Desmodesmus subspicatus, and genotoxicity tests, such as the umu and NM2009 tests, were performed. Also applied were the Ames test, according to International Organization for Standardization 16240, and an Ames fluctuation test. The toxic mode of action was examined using bacterial gene profiling assays with a battery of Escherichia coli strains and with the human liver cell line hepG2 using the PIQOR Toxicology cDNA microarray. Additionally, the molecular mechanism of 2,4,6-trinitrotoluene in hepG2 cells was analyzed. The present assessment indicates a danger of pollutant leaching for the soil-groundwater path. A possible impact for human health is discussed, because the groundwater in this area serves as drinking water.
Isolation of Microarray-Grade Total RNA, MicroRNA, and DNA from a Single PAXgene Blood RNA Tube
Kruhøffer, Mogens; Dyrskjøt, Lars; Voss, Thorsten; Lindberg, Raija L.P.; Wyrich, Ralf; Thykjaer, Thomas; Orntoft, Torben F.
2007-01-01
We have developed a procedure for isolation of microRNA and genomic DNA in addition to total RNA from whole blood stabilized in PAXgene Blood RNA tubes. The procedure is based on automatic extraction on a BioRobot MDx and includes isolation of DNA from a fraction of the stabilized blood and recovery of small RNA species that are otherwise lost. The procedure presented here is suitable for large-scale experiments and is amenable to further automation. Procured total RNA and DNA was tested using Affymetrix Expression and single-nucleotide polymorphism GeneChips, respectively, and isolated microRNA was tested using spotted locked nucleic acid-based microarrays. We conclude that the yield and quality of total RNA, microRNA, and DNA from a single PAXgene blood RNA tube is sufficient for downstream microarray analysis. PMID:17690207
Finding Groups in Gene Expression Data
2005-01-01
The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large-scale, high-throughput investigations of gene activity and have thus provided the data analyst with a distinctive, high-dimensional field of study. Many questions in this field relate to finding subgroups of data profiles which are very similar. A popular type of exploratory tool for finding subgroups is cluster analysis, and many different flavors of algorithms have been used and indeed tailored for microarray data. Cluster analysis, however, implies a partitioning of the entire data set, and this does not always match the objective. Sometimes pattern discovery or bump hunting tools are more appropriate. This paper reviews these various tools for finding interesting subgroups. PMID:16046827
Workflows for microarray data processing in the Kepler environment.
Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark
2012-05-17
Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R/BioConductor scripting approaches to pipeline design. Finally, we suggest that microarray data processing task workflows may provide a basis for future example-based comparison of different workflow systems. We provide a set of tools and complete workflows for microarray data analysis in the Kepler environment, which has the advantages of offering graphical, clear display of conceptual steps and parameters and the ability to easily integrate other resources such as remote data and web services.
Naiser, Thomas; Ehler, Oliver; Kayser, Jona; Mai, Timo; Michel, Wolfgang; Ott, Albrecht
2008-01-01
Background The high binding specificity of short 10 to 30 mer oligonucleotide probes enables single base mismatch (MM) discrimination and thus provides the basis for genotyping and resequencing microarray applications. Recent experiments indicate that the underlying principles governing DNA microarray hybridization – and in particular MM discrimination – are not completely understood. Microarrays usually address complex mixtures of DNA targets. In order to reduce the level of complexity and to study the problem of surface-based hybridization with point defects in more detail, we performed array based hybridization experiments in well controlled and simple situations. Results We performed microarray hybridization experiments with short 16 to 40 mer target and probe lengths (in situations without competitive hybridization) in order to systematically investigate the impact of point-mutations – varying defect type and position – on the oligonucleotide duplex binding affinity. The influence of single base bulges and single base MMs depends predominantly on position – it is largest in the middle of the strand. The position-dependent influence of base bulges is very similar to that of single base MMs, however certain bulges give rise to an unexpectedly high binding affinity. Besides the defect (MM or bulge) type, which is the second contribution in importance to hybridization affinity, there is also a sequence dependence, which extends beyond the defect next-neighbor and which is difficult to quantify. Direct comparison between binding affinities of DNA/DNA and RNA/DNA duplexes shows, that RNA/DNA purine-purine MMs are more discriminating than corresponding DNA/DNA MMs. In DNA/DNA MM discrimination the affected base pair (C·G vs. A·T) is the pertinent parameter. We attribute these differences to the different structures of the duplexes (A vs. B form). Conclusion We have shown that DNA microarrays can resolve even subtle changes in hybridization affinity for simple target mixtures. We have further shown that the impact of point defects on oligonucleotide stability can be broken down to a hierarchy of effects. In order to explain our observations we propose DNA molecular dynamics – in form of zipping of the oligonucleotide duplex – to play an important role. PMID:18477387
Insight into the bacterial gut microbiome of the North American moose (Alces alces)
2012-01-01
Background The work presented here provides the first intensive insight into the bacterial populations in the digestive tract of the North American moose (Alces alces). Eight free-range moose on natural pasture were sampled, producing eight rumen samples and six colon samples. Second generation (G2) PhyloChips were used to determine the presence of hundreds of operational taxonomic units (OTUs), representing multiple closely related species/strains (>97% identity), found in the rumen and colon of the moose. Results A total of 789 unique OTUs were used for analysis, which passed the fluorescence and the positive fraction thresholds. There were 73 OTUs, representing 21 bacterial families, which were found exclusively in the rumen samples: Lachnospiraceae, Prevotellaceae and several unclassified families, whereas there were 71 OTUs, representing 22 bacterial families, which were found exclusively in the colon samples: Clostridiaceae, Enterobacteriaceae and several unclassified families. Overall, there were 164 OTUs that were found in 100% of the samples. The Firmicutes were the most dominant bacteria phylum in both the rumen and the colon. Microarray data available at ArrayExpress, accession number E-MEXP-3721. Conclusions Using PhyloTrac and UniFrac computer software, samples clustered into two distinct groups: rumen and colon, confirming that the rumen and colon are distinct environments. There was an apparent correlation of age to cluster, which will be validated by a larger sample size in future studies, but there were no detectable trends based upon gender. PMID:22992344
Brinkman, Cassandra L; Schmidt-Malan, Suzannah M; Karau, Melissa J; Greenwood-Quaintance, Kerryl; Hassett, Daniel J; Mandrekar, Jayawant N; Patel, Robin
2016-01-01
Bacterial biofilms may form on indwelling medical devices such as prosthetic joints, heart valves and catheters, causing challenging-to-treat infections. We have previously described the 'electricidal effect', in which bacterial biofilms are decreased following exposure to direct electrical current. Herein, we sought to determine if the decreased bacterial quantities are due to detachment of biofilms or cell death and to investigate the role that reactive oxygen species (ROS) play in the observed effect. Using confocal and electron microscopy and flow cytometry, we found that direct current (DC) leads to cell death and changes in the architecture of biofilms formed by Gram-positive and Gram-negative bacteria. Reactive oxygen species (ROS) appear to play a role in DC-associated cell death, as there was an increase in ROS-production by Staphylococcus aureus and Staphylococcus epidermidis biofilms following exposure to DC. An increase in the production of ROS response enzymes catalase and superoxide dismutase (SOD) was observed for S. aureus, S. epidermidis and Pseudomonas aeruginosa biofilms following exposure to DC. Additionally, biofilms were protected from cell death when supplemented with antioxidants and oxidant scavengers, including catalase, mannitol and Tempol. Knocking out SOD (sodAB) in P. aeruginosa led to an enhanced DC effect. Microarray analysis of P. aeruginosa PAO1 showed transcriptional changes in genes related to the stress response and cell death. In conclusion, the electricidal effect results in death of bacteria in biofilms, mediated, at least in part, by production of ROS.
Schüler, Susann; Wenz, Ingrid; Wiederanders, B; Slickers, P; Ehricht, R
2006-06-12
Recent developments in DNA microarray technology led to a variety of open and closed devices and systems including high and low density microarrays for high-throughput screening applications as well as microarrays of lower density for specific diagnostic purposes. Beside predefined microarrays for specific applications manufacturers offer the production of custom-designed microarrays adapted to customers' wishes. Array based assays demand complex procedures including several steps for sample preparation (RNA extraction, amplification and sample labelling), hybridization and detection, thus leading to a high variability between several approaches and resulting in the necessity of extensive standardization and normalization procedures. In the present work a custom designed human proteinase DNA microarray of lower density in ArrayTube format was established. This highly economic open platform only requires standard laboratory equipment and allows the study of the molecular regulation of cell behaviour by proteinases. We established a procedure for sample preparation and hybridization and verified the array based gene expression profile by quantitative real-time PCR (QRT-PCR). Moreover, we compared the results with the well established Affymetrix microarray. By application of standard labelling procedures with e.g. Klenow fragment exo-, single primer amplification (SPA) or In Vitro Transcription (IVT) we noticed a loss of signal conservation for some genes. To overcome this problem we developed a protocol in accordance with the SPA protocol, in which we included target specific primers designed individually for each spotted oligomer. Here we present a complete array based assay in which only the specific transcripts of interest are amplified in parallel and in a linear manner. The array represents a proof of principle which can be adapted to other species as well. As the designed protocol for amplifying mRNA starts from as little as 100 ng total RNA, it presents an alternative method for detecting even low expressed genes by microarray experiments in a highly reproducible and sensitive manner. Preservation of signal integrity is demonstrated out by QRT-PCR measurements. The little amounts of total RNA necessary for the analyses make this method applicable for investigations with limited material as in clinical samples from, for example, organ or tumour biopsies. Those are arguments in favour of the high potential of our assay compared to established procedures for amplification within the field of diagnostic expression profiling. Nevertheless, the screening character of microarray data must be mentioned, and independent methods should verify the results.
Gómez, Marta; Moles, Laura; Espinosa-Martos, Irene; Bustos, Gerardo; de Vos, Willem M.; Rodríguez, Juan M.; Fuentes, Susana
2017-01-01
An abnormal colonization pattern of the preterm gut may affect immune maturation and exert a long-term influence on the intestinal bacterial composition and host health. However, follow-up studies assessing the evolution of the fecal microbiota of infants that were born preterm are very scarce. In this work, the bacterial compositions of fecal samples, obtained from sixteen 2-year-old infants were evaluated using a phylogenetic microarray; subsequently, the results were compared with those obtained in a previous study from samples of meconium and feces collected from the same infants while they stayed in the neonatal intensive care unit (NICU). In parallel, the concentration of a wide range of cytokines, chemokines, growth factors and immunoglobulins were determined in meconium and fecal samples. Globally, a higher bacterial diversity and a lower interindividual variability were observed in 2-year-olds’ feces, when compared to the samples obtained during their first days of life. Hospital-associated fecal bacteria, that were dominant during the NICU stay, seemed to be replaced, two years later, by genera, which are usually predominant in the healthy adult microbiome. The immune profile of the meconium and fecal samples differed, depending on the sampling time, showing different immune maturation statuses of the gut. PMID:29186903
Shen, Congcong; Shi, Yu; Ni, Yingying; Deng, Ye; Van Nostrand, Joy D.; He, Zhili; Zhou, Jizhong; Chu, Haiyan
2016-01-01
The elevational and latitudinal diversity patterns of microbial taxa have attracted great attention in the past decade. Recently, the distribution of functional attributes has been in the spotlight. Here, we report a study profiling soil microbial communities along an elevation gradient (500–2200 m) on Changbai Mountain. Using a comprehensive functional gene microarray (GeoChip 5.0), we found that microbial functional gene richness exhibited a dramatic increase at the treeline ecotone, but the bacterial taxonomic and phylogenetic diversity based on 16S rRNA gene sequencing did not exhibit such a similar trend. However, the β-diversity (compositional dissimilarity among sites) pattern for both bacterial taxa and functional genes was similar, showing significant elevational distance-decay patterns which presented increased dissimilarity with elevation. The bacterial taxonomic diversity/structure was strongly influenced by soil pH, while the functional gene diversity/structure was significantly correlated with soil dissolved organic carbon (DOC). This finding highlights that soil DOC may be a good predictor in determining the elevational distribution of microbial functional genes. The finding of significant shifts in functional gene diversity at the treeline ecotone could also provide valuable information for predicting the responses of microbial functions to climate change. PMID:27524983
Recent developments in detection and enumeration of waterborne bacteria: a retrospective minireview.
Deshmukh, Rehan A; Joshi, Kopal; Bhand, Sunil; Roy, Utpal
2016-12-01
Waterborne diseases have emerged as global health problems and their rapid and sensitive detection in environmental water samples is of great importance. Bacterial identification and enumeration in water samples is significant as it helps to maintain safe drinking water for public consumption. Culture-based methods are laborious, time-consuming, and yield false-positive results, whereas viable but nonculturable (VBNCs) microorganisms cannot be recovered. Hence, numerous methods have been developed for rapid detection and quantification of waterborne pathogenic bacteria in water. These rapid methods can be classified into nucleic acid-based, immunology-based, and biosensor-based detection methods. This review summarizes the principle and current state of rapid methods for the monitoring and detection of waterborne bacterial pathogens. Rapid methods outlined are polymerase chain reaction (PCR), digital droplet PCR, real-time PCR, multiplex PCR, DNA microarray, Next-generation sequencing (pyrosequencing, Illumina technology and genomics), and fluorescence in situ hybridization that are categorized as nucleic acid-based methods. Enzyme-linked immunosorbent assay (ELISA) and immunofluorescence are classified into immunology-based methods. Optical, electrochemical, and mass-based biosensors are grouped into biosensor-based methods. Overall, these methods are sensitive, specific, time-effective, and important in prevention and diagnosis of waterborne bacterial diseases. © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.
Fogaça, Andréa C; Zaini, Paulo A; Wulff, Nelson A; da Silva, Patrícia I P; Fázio, Marcos A; Miranda, Antônio; Daffre, Sirlei; da Silva, Aline M
2010-05-01
In the xylem vessels of susceptible hosts, such as citrus trees, Xylella fastidiosa forms biofilm-like colonies that can block water transport, which appears to correlate to disease symptoms. Besides aiding host colonization, bacterial biofilms play an important role in resistance against antimicrobial agents, for instance antimicrobial peptides (AMPs). Here, we show that gomesin, a potent AMP from a tarantula spider, modulates X. fastidiosa gene expression profile upon 60 min of treatment with a sublethal concentration. DNA microarray hybridizations revealed that among the upregulated coding sequences, some are related to biofilm production. In addition, we show that the biofilm formed by gomesin-treated bacteria is thicker than that formed by nontreated cells or cells exposed to streptomycin. We have also observed that the treatment of X. fastidiosa with a sublethal concentration of gomesin before inoculation in tobacco plants correlates with a reduction in foliar symptoms, an effect possibly due to the trapping of bacterial cells to fewer xylem vessels, given the enhancement in biofilm production. These results warrant further investigation of how X. fastidiosa would respond to the AMPs produced by citrus endophytes and by the insect vector, leading to a better understanding of the mechanism of action of these molecules on bacterial virulence.
Galectins are human milk glycan receptors
Noll, Alexander J; Gourdine, Jean-Philippe; Yu, Ying; Lasanajak, Yi; Smith, David F; Cummings, Richard D
2016-01-01
The biological recognition of human milk glycans (HMGs) is poorly understood. Because HMGs are rich in galactose we explored whether they might interact with human galectins, which bind galactose-containing glycans and are highly expressed in epithelial cells and other cell types. We screened a number of human galectins for their binding to HMGs on a shotgun glycan microarray consisting of 247 HMGs derived from human milk, as well as to a defined HMG microarray. Recombinant human galectins (hGal)-1, -3, -4, -7, -8 and -9 bound selectively to glycans, with each galectin recognizing a relatively unique binding motif; by contrast hGal-2 did not recognize HMGs, but did bind to the human blood group A Type 2 determinants on other microarrays. Unlike other galectins, hGal-7 preferentially bound to glycans expressing a terminal Type 1 (Galβ1-3GlcNAc) sequence, a motif that had eluded detection on non-HMG glycan microarrays. Interactions with HMGs were confirmed in a solution setting by isothermal titration microcalorimetry and hapten inhibition experiments. These results demonstrate that galectins selectively bind to HMGs and suggest the possibility that galectin–HMG interactions may play a role in infant immunity. PMID:26747425
Estimating differential expression from multiple indicators
Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik
2014-01-01
Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062
Kitchen, Robert R; Sabine, Vicky S; Simen, Arthur A; Dixon, J Michael; Bartlett, John M S; Sims, Andrew H
2011-12-01
Systematic processing noise, which includes batch effects, is very common in microarray experiments but is often ignored despite its potential to confound or compromise experimental results. Compromised results are most likely when re-analysing or integrating datasets from public repositories due to the different conditions under which each dataset is generated. To better understand the relative noise-contributions of various factors in experimental-design, we assessed several Illumina and Affymetrix datasets for technical variation between replicate hybridisations of Universal Human Reference (UHRR) and individual or pooled breast-tumour RNA. A varying degree of systematic noise was observed in each of the datasets, however in all cases the relative amount of variation between standard control RNA replicates was found to be greatest at earlier points in the sample-preparation workflow. For example, 40.6% of the total variation in reported expressions were attributed to replicate extractions, compared to 13.9% due to amplification/labelling and 10.8% between replicate hybridisations. Deliberate probe-wise batch-correction methods were effective in reducing the magnitude of this variation, although the level of improvement was dependent on the sources of noise included in the model. Systematic noise introduced at the chip, run, and experiment levels of a combined Illumina dataset were found to be highly dependent upon the experimental design. Both UHRR and pools of RNA, which were derived from the samples of interest, modelled technical variation well although the pools were significantly better correlated (4% average improvement) and better emulated the effects of systematic noise, over all probes, than the UHRRs. The effect of this noise was not uniform over all probes, with low GC-content probes found to be more vulnerable to batch variation than probes with a higher GC-content. The magnitude of systematic processing noise in a microarray experiment is variable across probes and experiments, however it is generally the case that procedures earlier in the sample-preparation workflow are liable to introduce the most noise. Careful experimental design is important to protect against noise, detailed meta-data should always be provided, and diagnostic procedures should be routinely performed prior to downstream analyses for the detection of bias in microarray studies.
2011-01-01
Background Systematic processing noise, which includes batch effects, is very common in microarray experiments but is often ignored despite its potential to confound or compromise experimental results. Compromised results are most likely when re-analysing or integrating datasets from public repositories due to the different conditions under which each dataset is generated. To better understand the relative noise-contributions of various factors in experimental-design, we assessed several Illumina and Affymetrix datasets for technical variation between replicate hybridisations of Universal Human Reference (UHRR) and individual or pooled breast-tumour RNA. Results A varying degree of systematic noise was observed in each of the datasets, however in all cases the relative amount of variation between standard control RNA replicates was found to be greatest at earlier points in the sample-preparation workflow. For example, 40.6% of the total variation in reported expressions were attributed to replicate extractions, compared to 13.9% due to amplification/labelling and 10.8% between replicate hybridisations. Deliberate probe-wise batch-correction methods were effective in reducing the magnitude of this variation, although the level of improvement was dependent on the sources of noise included in the model. Systematic noise introduced at the chip, run, and experiment levels of a combined Illumina dataset were found to be highly dependant upon the experimental design. Both UHRR and pools of RNA, which were derived from the samples of interest, modelled technical variation well although the pools were significantly better correlated (4% average improvement) and better emulated the effects of systematic noise, over all probes, than the UHRRs. The effect of this noise was not uniform over all probes, with low GC-content probes found to be more vulnerable to batch variation than probes with a higher GC-content. Conclusions The magnitude of systematic processing noise in a microarray experiment is variable across probes and experiments, however it is generally the case that procedures earlier in the sample-preparation workflow are liable to introduce the most noise. Careful experimental design is important to protect against noise, detailed meta-data should always be provided, and diagnostic procedures should be routinely performed prior to downstream analyses for the detection of bias in microarray studies. PMID:22133085
Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W
2007-12-21
Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences.
Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W
2007-01-01
Background Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Results Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. Conclusion The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences. PMID:18154678
Enhanced Microbial Detection Capabilities by a Rapid Portable Instrument
NASA Technical Reports Server (NTRS)
Morris, Heather; Monaco, Lisa; Wainwright, Norm; Steele, Andrew; Damon, Michael; Schenk, Alison; Stimpson, Eric; Maule, Jake; Effinger, Michael
2010-01-01
We present data describing a progression of continuing technology development - from expanding the detection capabilities of the current PTS unit to re-outfitting the instrument with a protein microarray increasing the number of detectable compounds. To illustrate the adaptability of the cartridge format, on-orbit operations data from the ISS demonstrate the detection of the fungal cell wall compound beta-glucan using applicable LOCAD-PTS cartridges. LOCAD-PTS is a handheld device consisting of a spectrophotometer, an onboard pumping mechanism, and data storage capabilities. A suite of interchangeable cartridges lined with four distinct capillaries allow a hydrated sample to mix with necessary reagents in the channels before being pumped to the optical well for spectrophotometric analysis. The reagents housed in one type of cartridge trigger a reaction based on the Limulus Amebocyte Lysate (LAL) assay, which results in the release of paranitroaniline dye. The dye is measured using a 395 nm filter. The LAL assay detects the Gram-negative bacterial cell wall molecule, endotoxin or lipopolysaccharide (LPS). The more dye released, the greater the concentration of endotoxin in the sample. Sampling, quantitative analysis, and data retrieval require less than 20 minutes. This is significantly faster than standard culture-based methods, which require at least a 24 hour incubation period.Using modified cartridges, we demonstrate the detection of Gram negative bacteria with protein microarray technology. Additionally, we provide data from multiple field tests where both standard and advanced PTS technologies were used. These tests investigate the transfer of target microbial molecules from one surface to another. Collectively, these data demonstrate that the new cartridges expand the number of compounds detected by LOCAD-PTS, while maintaining the rapid, in situ analysis characteristic of the instrument. The unit provides relevant data for verifying sterile sample collection protocols, which are critical for conducting accurate scientific experiments during future missions to the Moon and Mars.
Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.; DeSantis, Todd Z.; Gray, Michael A.; Andersen, Gary L.
2014-01-01
Coral disease is one of the major causes of reef degradation. Dark Spot Syndrome (DSS) was described in the early 1990's as brown or purple amorphous areas of tissue on a coral and has since become one of the most prevalent diseases reported on Caribbean reefs. It has been identified in a number of coral species, but there is debate as to whether it is in fact the same disease in different corals. Further, it is questioned whether these macroscopic signs are in fact diagnostic of an infectious disease at all. The most commonly affected species in the Caribbean is the massive starlet coral Siderastrea siderea. We sampled this species in two locations, Dry Tortugas National Park and Virgin Islands National Park. Tissue biopsies were collected from both healthy colonies and those with dark spot lesions. Microbial-community DNA was extracted from coral samples (mucus, tissue, and skeleton), amplified using bacterial-specific primers, and applied to PhyloChip G3 microarrays to examine the bacterial diversity associated with this coral. Samples were also screened for the presence of a fungal ribotype that has recently been implicated as a causative agent of DSS in another coral species, but the amplifications were unsuccessful. S. siderea samples did not cluster consistently based on health state (i.e., normal versus dark spot). Various bacteria, including Cyanobacteria and Vibrios, were observed to have increased relative abundance in the discolored tissue, but the patterns were not consistent across all DSS samples. Overall, our findings do not support the hypothesis that DSS in S. siderea is linked to a bacterial pathogen or pathogens. This dataset provides the most comprehensive overview to date of the bacterial community associated with the scleractinian coral S. siderea.
Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.; ...
2014-10-07
Coral disease is one of the major causes of reef degradation. Dark Spot Syndrome (DSS) was described in the early 1990's as brown or purple amorphous areas of tissue on a coral and has since become one of the most prevalent diseases reported on Caribbean reefs. It has been identified in a number of coral species, but there is debate as to whether it is in fact the same disease in different corals. Further, it is questioned whether these macroscopic signs are in fact diagnostic of an infectious disease at all. The most commonly affected species in the Caribbean ismore » the massive starlet coral Siderastrea siderea. We sampled this species in two locations, Dry Tortugas National Park and Virgin Islands National Park. Tissue biopsies were collected from both healthy colonies and those with dark spot lesions. Microbial-community DNA was extracted from coral samples (mucus, tissue, and skeleton), amplified using bacterial-specific primers, and applied to PhyloChip G3 microarrays to examine the bacterial diversity associated with this coral. Samples were also screened for the presence of a fungal ribotype that has recently been implicated as a causative agent of DSS in another coral species, but the amplifications were unsuccessful. S. siderea samples did not cluster consistently based on health state (i.e., normal versus dark spot). Various bacteria, including Cyanobacteria and Vibrios, were observed to have increased relative abundance in the discolored tissue, but the patterns were not consistent across all DSS samples. Overall, our findings do not support the hypothesis that DSS in S. siderea is linked to a bacterial pathogen or pathogens. This dataset provides the most comprehensive overview to date of the bacterial community associated with the scleractinian coral S. siderea.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.
Coral disease is one of the major causes of reef degradation. Dark Spot Syndrome (DSS) was described in the early 1990's as brown or purple amorphous areas of tissue on a coral and has since become one of the most prevalent diseases reported on Caribbean reefs. It has been identified in a number of coral species, but there is debate as to whether it is in fact the same disease in different corals. Further, it is questioned whether these macroscopic signs are in fact diagnostic of an infectious disease at all. The most commonly affected species in the Caribbean ismore » the massive starlet coral Siderastrea siderea. We sampled this species in two locations, Dry Tortugas National Park and Virgin Islands National Park. Tissue biopsies were collected from both healthy colonies and those with dark spot lesions. Microbial-community DNA was extracted from coral samples (mucus, tissue, and skeleton), amplified using bacterial-specific primers, and applied to PhyloChip G3 microarrays to examine the bacterial diversity associated with this coral. Samples were also screened for the presence of a fungal ribotype that has recently been implicated as a causative agent of DSS in another coral species, but the amplifications were unsuccessful. S. siderea samples did not cluster consistently based on health state (i.e., normal versus dark spot). Various bacteria, including Cyanobacteria and Vibrios, were observed to have increased relative abundance in the discolored tissue, but the patterns were not consistent across all DSS samples. Overall, our findings do not support the hypothesis that DSS in S. siderea is linked to a bacterial pathogen or pathogens. This dataset provides the most comprehensive overview to date of the bacterial community associated with the scleractinian coral S. siderea.« less
Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.; DeSantis, Todd Z.; Gray, Michael A.; Andersen, Gary L.
2014-01-01
Coral disease is one of the major causes of reef degradation. Dark Spot Syndrome (DSS) was described in the early 1990's as brown or purple amorphous areas of tissue on a coral and has since become one of the most prevalent diseases reported on Caribbean reefs. It has been identified in a number of coral species, but there is debate as to whether it is in fact the same disease in different corals. Further, it is questioned whether these macroscopic signs are in fact diagnostic of an infectious disease at all. The most commonly affected species in the Caribbean is the massive starlet coral Siderastrea siderea. We sampled this species in two locations, Dry Tortugas National Park and Virgin Islands National Park. Tissue biopsies were collected from both healthy colonies and those with dark spot lesions. Microbial-community DNA was extracted from coral samples (mucus, tissue, and skeleton), amplified using bacterial-specific primers, and applied to PhyloChip G3 microarrays to examine the bacterial diversity associated with this coral. Samples were also screened for the presence of a fungal ribotype that has recently been implicated as a causative agent of DSS in another coral species, but the amplifications were unsuccessful. S. siderea samples did not cluster consistently based on health state (i.e., normal versus dark spot). Various bacteria, including Cyanobacteria and Vibrios, were observed to have increased relative abundance in the discolored tissue, but the patterns were not consistent across all DSS samples. Overall, our findings do not support the hypothesis that DSS in S. siderea is linked to a bacterial pathogen or pathogens. This dataset provides the most comprehensive overview to date of the bacterial community associated with the scleractinian coral S. siderea. PMID:25289937
Ni, Ming; Ye, Fuqiang; Zhu, Juanjuan; Li, Zongwei; Yang, Shuai; Yang, Bite; Han, Lu; Wu, Yongge; Chen, Ying; Li, Fei; Wang, Shengqi; Bo, Xiaochen
2014-12-01
Numerous public microarray datasets are valuable resources for the scientific communities. Several online tools have made great steps to use these data by querying related datasets with users' own gene signatures or expression profiles. However, dataset annotation and result exhibition still need to be improved. ExpTreeDB is a database that allows for queries on human and mouse microarray experiments from Gene Expression Omnibus with gene signatures or profiles. Compared with similar applications, ExpTreeDB pays more attention to dataset annotations and result visualization. We introduced a multiple-level annotation system to depict and organize original experiments. For example, a tamoxifen-treated cell line experiment is hierarchically annotated as 'agent→drug→estrogen receptor antagonist→tamoxifen'. Consequently, retrieved results are exhibited by an interactive tree-structured graphics, which provide an overview for related experiments and might enlighten users on key items of interest. The database is freely available at http://biotech.bmi.ac.cn/ExpTreeDB. Web site is implemented in Perl, PHP, R, MySQL and Apache. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
2011-01-01
Background Although many biological databases are applying semantic web technologies, meaningful biological hypothesis testing cannot be easily achieved. Database-driven high throughput genomic hypothesis testing requires both of the capabilities of obtaining semantically relevant experimental data and of performing relevant statistical testing for the retrieved data. Tissue Microarray (TMA) data are semantically rich and contains many biologically important hypotheses waiting for high throughput conclusions. Methods An application-specific ontology was developed for managing TMA and DNA microarray databases by semantic web technologies. Data were represented as Resource Description Framework (RDF) according to the framework of the ontology. Applications for hypothesis testing (Xperanto-RDF) for TMA data were designed and implemented by (1) formulating the syntactic and semantic structures of the hypotheses derived from TMA experiments, (2) formulating SPARQLs to reflect the semantic structures of the hypotheses, and (3) performing statistical test with the result sets returned by the SPARQLs. Results When a user designs a hypothesis in Xperanto-RDF and submits it, the hypothesis can be tested against TMA experimental data stored in Xperanto-RDF. When we evaluated four previously validated hypotheses as an illustration, all the hypotheses were supported by Xperanto-RDF. Conclusions We demonstrated the utility of high throughput biological hypothesis testing. We believe that preliminary investigation before performing highly controlled experiment can be benefited. PMID:21342584
Schwartz, S; Kohan, M; Pasion, R; Papenhausen, P R; Platt, L D
2018-02-01
Screening via noninvasive prenatal testing (NIPT) involving the analysis of cell-free DNA (cfDNA) from plasma has become readily available to screen for chromosomal and DNA aberrations through maternal blood. This report reviews a laboratory's experience with follow-up of positive NIPT screens for microdeletions. Patients that were screened positive by NIPT for a microdeletion involving 1p, 4p, 5p, 15q, or 22q who underwent diagnostic studies by either chorionic villus sampling or amniocentesis were evaluated. The overall positive predictive value for 349 patients was 9.2%. When a microdeletion was confirmed, 39.3% of the cases had additional abnormal microarray findings. Unrelated abnormal microarray findings were detected in 11.8% of the patients in whom the screen positive microdeletion was not confirmed. Stretches of homozygosity in the microdeletion were frequently associated with a false positive cfDNA microdeletion result. Overall, this report reveals that while cfDNA analysis will screen for microdeletions, the positive predictive value is low; in our series it is 9.2%. Therefore, the patient should be counseled accordingly. Confirmatory diagnostic microarray studies are imperative because of the high percentage of false positives and the frequent additional abnormalities not delineated by cfDNA analysis. © 2018 John Wiley & Sons, Ltd.
[DNA microarray reveals changes in gene expression of endothelial cells under shear stress].
Cheng, Min; Zhang, Wensheng; Chen, Huaiqing; Wu, Wenchao; Huang, Hua
2004-04-01
cDNA microarray technology is used as a powerful tool for rapid, comprehensive, and quantitative analysis of gene profiles of cultured human umbilical vein endothelial cells(HUVECs) in the normal static group and the shear stressed (4.20 dyne/cm2, 2 h) group. The total RNA from normal static cultured HUVECs was labeled by Cy3-dCTP, and total RNA of HUVECs from the paired shear stressed experiment was labeled by Cy5-dCTP. The expression ratios reported are the average from the two separate experiments. After bioinformatics analysis, we identified a total of 108 genes (approximately 0.026%) revealing differential expression. Of these 53 genes expressions were up-regulated, the most enhanced ones being human homolog of yeast IPP isomerase, human low density lipoprotein receptor gene, Squalene epoxidase gene, 7-dehydrocholesterol reductase, and 55 were down-regulated, the most decreased ones being heat shock 70 kD protein 1, TCB gene encoding cytosolic thyroid hormone-binding protein in HUVECs exposed to low shear stress. These results indicate that the cDNA microarray technique is effective in screening the differentially expressed genes in endothelial cells induced by various experimental conditions and the data may serve as stimuli to further researches.
Dye bias correction in dual-labeled cDNA microarray gene expression measurements.
Rosenzweig, Barry A; Pine, P Scott; Domon, Olen E; Morris, Suzanne M; Chen, James J; Sistare, Frank D
2004-01-01
A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to gene-specific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias. PMID:15033598
Casel, Pierrot; Moreews, François; Lagarrigue, Sandrine; Klopp, Christophe
2009-07-16
Microarray is a powerful technology enabling to monitor tens of thousands of genes in a single experiment. Most microarrays are now using oligo-sets. The design of the oligo-nucleotides is time consuming and error prone. Genome wide microarray oligo-sets are designed using as large a set of transcripts as possible in order to monitor as many genes as possible. Depending on the genome sequencing state and on the assembly state the knowledge of the existing transcripts can be very different. This knowledge evolves with the different genome builds and gene builds. Once the design is done the microarrays are often used for several years. The biologists working in EADGENE expressed the need of up-to-dated annotation files for the oligo-sets they share including information about the orthologous genes of model species, the Gene Ontology, the corresponding pathways and the chromosomal location. The results of SigReannot on a chicken micro-array used in the EADGENE project compared to the initial annotations show that 23% of the oligo-nucleotide gene annotations were not confirmed, 2% were modified and 1% were added. The interest of this up-to-date annotation procedure is demonstrated through the analysis of real data previously published. SigReannot uses the oligo-nucleotide design procedure criteria to validate the probe-gene link and the Ensembl transcripts as reference for annotation. It therefore produces a high quality annotation based on reference gene sets.
Kitchen, Robert R; Sabine, Vicky S; Sims, Andrew H; Macaskill, E Jane; Renshaw, Lorna; Thomas, Jeremy S; van Hemert, Jano I; Dixon, J Michael; Bartlett, John M S
2010-02-24
Microarray technology is a popular means of producing whole genome transcriptional profiles, however high cost and scarcity of mRNA has led many studies to be conducted based on the analysis of single samples. We exploit the design of the Illumina platform, specifically multiple arrays on each chip, to evaluate intra-experiment technical variation using repeated hybridisations of universal human reference RNA (UHRR) and duplicate hybridisations of primary breast tumour samples from a clinical study. A clear batch-specific bias was detected in the measured expressions of both the UHRR and clinical samples. This bias was found to persist following standard microarray normalisation techniques. However, when mean-centering or empirical Bayes batch-correction methods (ComBat) were applied to the data, inter-batch variation in the UHRR and clinical samples were greatly reduced. Correlation between replicate UHRR samples improved by two orders of magnitude following batch-correction using ComBat (ranging from 0.9833-0.9991 to 0.9997-0.9999) and increased the consistency of the gene-lists from the duplicate clinical samples, from 11.6% in quantile normalised data to 66.4% in batch-corrected data. The use of UHRR as an inter-batch calibrator provided a small additional benefit when used in conjunction with ComBat, further increasing the agreement between the two gene-lists, up to 74.1%. In the interests of practicalities and cost, these results suggest that single samples can generate reliable data, but only after careful compensation for technical bias in the experiment. We recommend that investigators appreciate the propensity for such variation in the design stages of a microarray experiment and that the use of suitable correction methods become routine during the statistical analysis of the data.
2010-01-01
Background Microarray technology is a popular means of producing whole genome transcriptional profiles, however high cost and scarcity of mRNA has led many studies to be conducted based on the analysis of single samples. We exploit the design of the Illumina platform, specifically multiple arrays on each chip, to evaluate intra-experiment technical variation using repeated hybridisations of universal human reference RNA (UHRR) and duplicate hybridisations of primary breast tumour samples from a clinical study. Results A clear batch-specific bias was detected in the measured expressions of both the UHRR and clinical samples. This bias was found to persist following standard microarray normalisation techniques. However, when mean-centering or empirical Bayes batch-correction methods (ComBat) were applied to the data, inter-batch variation in the UHRR and clinical samples were greatly reduced. Correlation between replicate UHRR samples improved by two orders of magnitude following batch-correction using ComBat (ranging from 0.9833-0.9991 to 0.9997-0.9999) and increased the consistency of the gene-lists from the duplicate clinical samples, from 11.6% in quantile normalised data to 66.4% in batch-corrected data. The use of UHRR as an inter-batch calibrator provided a small additional benefit when used in conjunction with ComBat, further increasing the agreement between the two gene-lists, up to 74.1%. Conclusion In the interests of practicalities and cost, these results suggest that single samples can generate reliable data, but only after careful compensation for technical bias in the experiment. We recommend that investigators appreciate the propensity for such variation in the design stages of a microarray experiment and that the use of suitable correction methods become routine during the statistical analysis of the data. PMID:20181233
Microarray missing data imputation based on a set theoretic framework and biological knowledge.
Gan, Xiangchao; Liew, Alan Wee-Chung; Yan, Hong
2006-01-01
Gene expressions measured using microarrays usually suffer from the missing value problem. However, in many data analysis methods, a complete data matrix is required. Although existing missing value imputation algorithms have shown good performance to deal with missing values, they also have their limitations. For example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by global structure. In addition, these algorithms do not take into account any biological constraint in their imputation. In this paper, we propose a set theoretic framework based on projection onto convex sets (POCS) for missing data imputation. POCS allows us to incorporate different types of a priori knowledge about missing values into the estimation process. The main idea of POCS is to formulate every piece of prior knowledge into a corresponding convex set and then use a convergence-guaranteed iterative procedure to obtain a solution in the intersection of all these sets. In this work, we design several convex sets, taking into consideration the biological characteristic of the data: the first set mainly exploit the local correlation structure among genes in microarray data, while the second set captures the global correlation structure among arrays. The third set (actually a series of sets) exploits the biological phenomenon of synchronization loss in microarray experiments. In cyclic systems, synchronization loss is a common phenomenon and we construct a series of sets based on this phenomenon for our POCS imputation algorithm. Experiments show that our algorithm can achieve a significant reduction of error compared to the KNNimpute, SVDimpute and LSimpute methods.
Bilardi, Jade E.; Walker, Sandra; Temple-Smith, Meredith; McNair, Ruth; Mooney-Somers, Julie; Bellhouse, Clare; Fairley, Christopher K.; Chen, Marcus Y.; Bradshaw, Catriona
2013-01-01
Background Bacterial vaginosis is a common vaginal infection, causing an abnormal vaginal discharge and/or odour in up to 50% of sufferers. Recurrence is common following recommended treatment. There are limited data on women’s experience of bacterial vaginosis, and the impact on their self-esteem, sexual relationships and quality of life. The aim of this study was to explore the experiences and impact of recurrent bacterial vaginosis on women. Methods A social constructionist approach was chosen as the framework for the study. Thirty five women with male and/or female partners participated in semi-structured interviews face-to-face or by telephone about their experience of recurrent bacterial vaginosis. Results Recurrent bacterial vaginosis impacted on women to varying degrees, with some women reporting it had little impact on their lives but most reporting it had a moderate to severe impact. The degree to which it impacted on women physically, emotionally, sexually and socially often depended on the frequency of episodes and severity of symptoms. Women commonly reported that symptoms of bacterial vaginosis made them feel embarrassed, ashamed, ‘dirty’ and very concerned others may detect their malodour and abnormal discharge. The biggest impact of recurrent bacterial vaginosis was on women’s self-esteem and sex lives, with women regularly avoiding sexual activity, in particular oral sex, as they were too embarrassed and self-conscious of their symptoms to engage in these activities. Women often felt confused about why they were experiencing recurrent bacterial vaginosis and frustrated at their lack of control over recurrence. Conclusion Women’s experience of recurrent bacterial vaginosis varied broadly and significantly in this study. Some women reported little impact on their lives but most reported a moderate to severe impact, mainly on their self-esteem and sex life. Further support and acknowledgement of these impacts are required when managing women with recurrent bacterial vaginosis. PMID:24040236
Bilardi, Jade E; Walker, Sandra; Temple-Smith, Meredith; McNair, Ruth; Mooney-Somers, Julie; Bellhouse, Clare; Fairley, Christopher K; Chen, Marcus Y; Bradshaw, Catriona
2013-01-01
Bacterial vaginosis is a common vaginal infection, causing an abnormal vaginal discharge and/or odour in up to 50% of sufferers. Recurrence is common following recommended treatment. There are limited data on women's experience of bacterial vaginosis, and the impact on their self-esteem, sexual relationships and quality of life. The aim of this study was to explore the experiences and impact of recurrent bacterial vaginosis on women. A social constructionist approach was chosen as the framework for the study. Thirty five women with male and/or female partners participated in semi-structured interviews face-to-face or by telephone about their experience of recurrent bacterial vaginosis. Recurrent bacterial vaginosis impacted on women to varying degrees, with some women reporting it had little impact on their lives but most reporting it had a moderate to severe impact. The degree to which it impacted on women physically, emotionally, sexually and socially often depended on the frequency of episodes and severity of symptoms. Women commonly reported that symptoms of bacterial vaginosis made them feel embarrassed, ashamed, 'dirty' and very concerned others may detect their malodour and abnormal discharge. The biggest impact of recurrent bacterial vaginosis was on women's self-esteem and sex lives, with women regularly avoiding sexual activity, in particular oral sex, as they were too embarrassed and self-conscious of their symptoms to engage in these activities. Women often felt confused about why they were experiencing recurrent bacterial vaginosis and frustrated at their lack of control over recurrence. Women's experience of recurrent bacterial vaginosis varied broadly and significantly in this study. Some women reported little impact on their lives but most reported a moderate to severe impact, mainly on their self-esteem and sex life. Further support and acknowledgement of these impacts are required when managing women with recurrent bacterial vaginosis.
Automated detection and quantitation of bacterial RNA by using electrical microarrays.
Elsholz, B; Wörl, R; Blohm, L; Albers, J; Feucht, H; Grunwald, T; Jürgen, B; Schweder, T; Hintsche, Rainer
2006-07-15
Low-density electrical 16S rRNA specific oligonucleotide microarrays and an automated analysis system have been developed for the identification and quantitation of pathogens. The pathogens are Escherichia coli, Pseudomonas aeruginosa, Enterococcus faecalis, Staphylococcus aureus, and Staphylococcus epidermidis, which are typically involved in urinary tract infections. Interdigitated gold array electrodes (IDA-electrodes), which have structures in the nanometer range, have been used for very sensitive analysis. Thiol-modified oligonucleotides are immobilized on the gold IDA as capture probes. They mediate the specific recognition of the target 16S rRNA by hybridization. Additionally three unlabeled oligonucleotides are hybridized in close proximity to the capturing site. They are supporting molecules, because they improve the RNA hybridization at the capturing site. A biotin labeled detector oligonucleotide is also allowed to hybridize to the captured RNA sequence. The biotin labels enable the binding of avidin alkaline phophatase conjugates. The phosphatase liberates the electrochemical mediator p-aminophenol from its electrically inactive phosphate derivative. The electrical signals were generated by amperometric redox cycling and detected by a unique multipotentiostat. The read out signals of the microarray are position specific current and change over time in proportion to the analyte concentration. If two additional biotins are introduced into the affinity binding complex via the supporting oligonucleotides, the sensitivity of the assays increase more than 60%. The limit of detection of Escherichia coli total RNA has been determined to be 0.5 ng/microL. The control of fluidics for variable assay formats as well as the multichannel electrical read out and data handling have all been fully automated. The fast and easy procedure does not require any amplification of the targeted nucleic acids by PCR.
Lipid Microarray Biosensor for Biotoxin Detection.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Singh, Anup K.; Throckmorton, Daniel J.; Moran-Mirabal, Jose C.
2006-05-01
We present the use of micron-sized lipid domains, patterned onto planar substrates and within microfluidic channels, to assay the binding of bacterial toxins via total internal reflection fluorescence microscopy (TIRFM). The lipid domains were patterned using a polymer lift-off technique and consisted of ganglioside-populated DSPC:cholesterol supported lipid bilayers (SLBs). Lipid patterns were formed on the substrates by vesicle fusion followed by polymer lift-off, which revealed micron-sized SLBs containing either ganglioside GT1b or GM1. The ganglioside-populated SLB arrays were then exposed to either Cholera toxin subunit B (CTB) or Tetanus toxin fragment C (TTC). Binding was assayed on planar substrates bymore » TIRFM down to 1 nM concentration for CTB and 100 nM for TTC. Apparent binding constants extracted from three different models applied to the binding curves suggest that binding of a protein to a lipid-based receptor is strongly affected by the lipid composition of the SLB and by the substrate on which the bilayer is formed. Patterning of SLBs inside microfluidic channels also allowed the preparation of lipid domains with different compositions on a single device. Arrays within microfluidic channels were used to achieve segregation and selective binding from a binary mixture of the toxin fragments in one device. The binding and segregation within the microfluidic channels was assayed with epifluorescence as proof of concept. We propose that the method used for patterning the lipid microarrays on planar substrates and within microfluidic channels can be easily adapted to proteins or nucleic acids and can be used for biosensor applications and cell stimulation assays under different flow conditions. KEYWORDS. Microarray, ganglioside, polymer lift-off, cholera toxin, tetanus toxin, TIRFM, binding constant.4« less
Segmental Duplications and Copy-Number Variation in the Human Genome
Sharp, Andrew J. ; Locke, Devin P. ; McGrath, Sean D. ; Cheng, Ze ; Bailey, Jeffrey A. ; Vallente, Rhea U. ; Pertz, Lisa M. ; Clark, Royden A. ; Schwartz, Stuart ; Segraves, Rick ; Oseroff, Vanessa V. ; Albertson, Donna G. ; Pinkel, Daniel ; Eichler, Evan E.
2005-01-01
The human genome contains numerous blocks of highly homologous duplicated sequence. This higher-order architecture provides a substrate for recombination and recurrent chromosomal rearrangement associated with genomic disease. However, an assessment of the role of segmental duplications in normal variation has not yet been made. On the basis of the duplication architecture of the human genome, we defined a set of 130 potential rearrangement hotspots and constructed a targeted bacterial artificial chromosome (BAC) microarray (with 2,194 BACs) to assess copy-number variation in these regions by array comparative genomic hybridization. Using our segmental duplication BAC microarray, we screened a panel of 47 normal individuals, who represented populations from four continents, and we identified 119 regions of copy-number polymorphism (CNP), 73 of which were previously unreported. We observed an equal frequency of duplications and deletions, as well as a 4-fold enrichment of CNPs within hotspot regions, compared with control BACs (P < .000001), which suggests that segmental duplications are a major catalyst of large-scale variation in the human genome. Importantly, segmental duplications themselves were also significantly enriched >4-fold within regions of CNP. Almost without exception, CNPs were not confined to a single population, suggesting that these either are recurrent events, having occurred independently in multiple founders, or were present in early human populations. Our study demonstrates that segmental duplications define hotspots of chromosomal rearrangement, likely acting as mediators of normal variation as well as genomic disease, and it suggests that the consideration of genomic architecture can significantly improve the ascertainment of large-scale rearrangements. Our specialized segmental duplication BAC microarray and associated database of structural polymorphisms will provide an important resource for the future characterization of human genomic disorders. PMID:15918152
Archaeal viruses--novel, diverse and enigmatic.
Peng, Xu; Garrett, Roger A; She, QunXin
2012-05-01
Recent research has revealed a remarkable diversity of viruses in archaeal-rich environments where spindles, spheres, filaments and rods are common, together with other exceptional morphotypes never recorded previously. Moreover, their double-stranded DNA genomes carry very few genes exhibiting homology to those of bacterial and eukaryal viruses. Studies on viral life cycles are still at a preliminary stage but important insights are being gained especially from microarray analyses of viral transcripts for a few model virus-host systems. Recently, evidence has been presented for some exceptional archaeal-specific mechanisms for extra-cellular morphological development of virions and for their cellular extrusion. Here we summarise some of the recent developments in this rapidly developing and exciting research area.
Responses of Baltic Sea Ice and Open-Water Natural Bacterial Communities to Salinity Change
Kaartokallio, Hermanni; Laamanen, Maria; Sivonen, Kaarina
2005-01-01
To investigate the responses of Baltic Sea wintertime bacterial communities to changing salinity (5 to 26 practical salinity units), an experimental study was conducted. Bacterial communities of Baltic seawater and sea ice from a coastal site in southwest Finland were used in two batch culture experiments run for 17 or 18 days at 0°C. Bacterial abundance, cell volume, and leucine and thymidine incorporation were measured during the experiments. The bacterial community structure was assessed using denaturing gradient gel electrophoresis (DGGE) of PCR-amplified partial 16S rRNA genes with sequencing of DGGE bands from initial communities and communities of day 10 or 13 of the experiment. The sea ice-derived bacterial community was metabolically more active than the open-water community at the start of the experiment. Ice-derived bacterial communities were able to adapt to salinity change with smaller effects on physiology and community structure, whereas in the open-water bacterial communities, the bacterial cell volume evolution, bacterial abundance, and community structure responses indicated the presence of salinity stress. The closest relatives for all eight partial 16S rRNA gene sequences obtained were either organisms found in polar sea ice and other cold habitats or those found in summertime Baltic seawater. All sequences except one were associated with the α- and γ-proteobacteria or the Cytophaga-Flavobacterium-Bacteroides group. The overall physiological and community structure responses were parallel in ice-derived and open-water bacterial assemblages, which points to a linkage between community structure and physiology. These results support previous assumptions of the role of salinity fluctuation as a major selective factor shaping the sea ice bacterial community structure. PMID:16085826
Biofilm Community Diversity after Exposure to 0.4% Stannous Fluoride Gels
Reilly, Cavan; Rasmussen, Karin; Selberg, Tieg; Stevens, Justin; Jones, Robert S.
2015-01-01
Aims To test the effect of %0.4 stannous fluoride (SnF2) glycerin based gels on the bacterial ecology in both a clinical observational study and in vitro polymicobial biofilm model. Methods and Results The influence of stannous fluoride (0.4% SnF2) gels on bacteria was tested in both an observational study in children 6-12 years of age (n=20) and an in vitro biofilm model system. The plaque derived multi-species bacterial biofilm model was based on clinical bacterial strains derived directly from the clinical study. Potential changes in the plaque ecology were determined through the Human Oral Microbial Identification Microarray-HOMIM (n=10). The semiquantitative data resulting from this system were analyzed with cumulative logit models for each bacterial strain and Bonferroni adjustments were employed to correct for multiple hypothesis testing. Both hierarchical biclustering and principal components analysis were used to graphically assess reproducibility within subjects over time. Mixed effects models were used to examine changes in plaque scores and numbers of bacterial strains found in the various conditions. Conclusions Both the observational clinical study and the biofilm model showed that short-term use of 0.4% SnF2 gel has little effect on the bacterial plaque ecology. The amount of plaque accumulation on a subject's teeth, which was measured by plaque index scores failed to show statistical significant changes over the two baselines or after treatment (p=0.9928). The in vitro results were similar when examining the effect of 0.4% SnF2 gels on biofilm adherence through a crystal violet assay (p= 0.1157). Significance and Impact of the Study The bacteria within the dental biofilms showed resilience in maintaining the overall community diversity after exposure to 0.4% Stannous Fluoride Gels. The study supports that the immediate benefits of using these gels each night to manage caries in children may be strictly from fluoride ions inhibiting tooth demineralization. PMID:25263195
Variations of oral microbiota are associated with pancreatic diseases including pancreatic cancer
Farrell, James J; Zhang, Lei; Zhou, Hui; Chia, David; Elashoff, David; Akin, David; Paster, Bruce J; Joshipura, Kaumudi; Wong, David T W
2012-01-01
Objective The associations between oral diseases and increased risk of pancreatic cancer have been reported in several prospective cohort studies. In this study, we measured variations of salivary microbiota and evaluated their potential associations with pancreatic cancer and chronic pancreatitis. Methods This study was divided into three phases: (1) microbial profiling using the Human Oral Microbe Identification Microarray to investigate salivary microbiota variation between 10 resectable patients with pancreatic cancer and 10 matched healthy controls, (2) identification and verification of bacterial candidates by real-time quantitative PCR (qPCR) and (3) validation of bacterial candidates by qPCR on an independent cohort of 28 resectable pancreatic cancer, 28 matched healthy control and 27 chronic pancreatitis samples. Results Comprehensive comparison of the salivary microbiota between patients with pancreatic cancer and healthy control subjects revealed a significant variation of salivary microflora. Thirty-one bacterial species/clusters were increased in the saliva of patients with pancreatic cancer (n=10) in comparison to those of the healthy controls (n=10), whereas 25 bacterial species/clusters were decreased. Two out of six bacterial candidates (Neisseria elongata and Streptococcus mitis) were validated using the independent samples, showing significant variation (p<0.05, qPCR) between patients with pancreatic cancer and controls (n=56). Additionally, two bacteria (Granulicatella adiacens and S mitis) showed significant variation (p<0.05, qPCR) between chronic pancreatitis samples and controls (n=55). The combination of two bacterial biomarkers (N elongata and S mitis) yielded a receiver operating characteristic plot area under the curve value of 0.90 (95% CI 0.78 to 0.96, p<0.0001) with a 96.4% sensitivity and 82.1% specificity in distinguishing patients with pancreatic cancer from healthy subjects. Conclusions The authors observed associations between variations of patients’ salivary microbiota with pancreatic cancer and chronic pancreatitis. This report also provides proof of salivary microbiota as an informative source for discovering non-invasive biomarkers of systemic diseases. PMID:21994333
Korves, T M; Piceno, Y M; Tom, L M; Desantis, T Z; Jones, B W; Andersen, G L; Hwang, G M
2013-02-01
Air travel can rapidly transport infectious diseases globally. To facilitate the design of biosensors for infectious organisms in commercial aircraft, we characterized bacterial diversity in aircraft air. Samples from 61 aircraft high-efficiency particulate air (HEPA) filters were analyzed with a custom microarray of 16S rRNA gene sequences (PhyloChip), representing bacterial lineages. A total of 606 subfamilies from 41 phyla were detected. The most abundant bacterial subfamilies included bacteria associated with humans, especially skin, gastrointestinal and respiratory tracts, and with water and soil habitats. Operational taxonomic units that contain important human pathogens as well as their close, more benign relatives were detected. When compared to 43 samples of urban outdoor air, aircraft samples differed in composition, with higher relative abundance of Firmicutes and Gammaproteobacteria lineages in aircraft samples, and higher relative abundance of Actinobacteria and Betaproteobacteria lineages in outdoor air samples. In addition, aircraft and outdoor air samples differed in the incidence of taxa containing human pathogens. Overall, these results demonstrate that HEPA filter samples can be used to deeply characterize bacterial diversity in aircraft air and suggest that the presence of close relatives of certain pathogens must be taken into account in probe design for aircraft biosensors. A biosensor that could be deployed in commercial aircraft would be required to function at an extremely low false alarm rate, making an understanding of microbial background important. This study reveals a diverse bacterial background present on aircraft, including bacteria closely related to pathogens of public health concern. Furthermore, this aircraft background is different from outdoor air, suggesting different probes may be needed to detect airborne contaminants to achieve minimal false alarm rates. This study also indicates that aircraft HEPA filters could be used with other molecular techniques to further characterize background bacteria and in investigations in the wake of a disease outbreak. © 2012 John Wiley & Sons A/S.
NCBI GEO: mining tens of millions of expression profiles--database and tools update.
Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Edgar, Ron
2007-01-01
The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely disseminates microarray and other forms of high-throughput data generated by the scientific community. The database has a minimum information about a microarray experiment (MIAME)-compliant infrastructure that captures fully annotated raw and processed data. Several data deposit options and formats are supported, including web forms, spreadsheets, XML and Simple Omnibus Format in Text (SOFT). In addition to data storage, a collection of user-friendly web-based interfaces and applications are available to help users effectively explore, visualize and download the thousands of experiments and tens of millions of gene expression patterns stored in GEO. This paper provides a summary of the GEO database structure and user facilities, and describes recent enhancements to database design, performance, submission format options, data query and retrieval utilities. GEO is accessible at http://www.ncbi.nlm.nih.gov/geo/
Ikeda, Akemi; Kojima-Aikawa, Kyoko; Taniguchi, Naoyuki; Varón Silva, Daniel; Feizi, Ten; Seeberger, Peter H.; Yamaguchi, Yoshiki
2018-01-01
ZG16p is a soluble mammalian lectin that interacts with mannose and heparan sulfate. Here we describe detailed analyses of the interactions of human ZG16p with mycobacterial phosphatidylinositol mannosides (PIMs), using glycan microarray and NMR. Pathogen-related glycan microarray analysis identified phosphatidylinositol mono- and di-mannosides (PIM1 and PIM2) as novel ligand candidates of ZG16p. Saturation Transfer Difference (STD) NMR and transferred NOE experiments with chemically synthesized PIM glycans indicate that PIMs preferentially interacts with ZG16p using the mannose residues. Binding site of PIMs is identified by chemical shift perturbation experiments using uniformly 15N-labeled ZG16p. NMR results with docking simulations suggest a binding mode of ZG16p and PIM glycan, which would help to consider the physiological role of ZG16p. PMID:25919894
MSL: A Measure to Evaluate Three-dimensional Patterns in Gene Expression Data
Gutiérrez-Avilés, David; Rubio-Escudero, Cristina
2015-01-01
Microarray technology is highly used in biological research environments due to its ability to monitor the RNA concentration levels. The analysis of the data generated represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior. Biclustering relaxes the constraints for grouping, allowing genes to be evaluated only under a subset of the conditions. Triclustering appears for the analysis of longitudinal experiments in which the genes are evaluated under certain conditions at several time points. These triclusters provide hidden information in the form of behavior patterns from temporal experiments with microarrays relating subsets of genes, experimental conditions, and time points. We present an evaluation measure for triclusters called Multi Slope Measure, based on the similarity among the angles of the slopes formed by each profile formed by the genes, conditions, and times of the tricluster. PMID:26124630
Brockmann-Gretza, Olaf; Kalinowski, Jörn
2006-01-01
Background The stringent response is the initial reaction of microorganisms to nutritional stress. During stringent response the small nucleotides (p)ppGpp act as global regulators and reprogram bacterial transcription. In this work, the genetic network controlled by the stringent response was characterized in the amino acid-producing Corynebacterium glutamicum. Results The transcriptome of a C. glutamicum rel gene deletion mutant, unable to synthesize (p)ppGpp and to induce the stringent response, was compared with that of its rel-proficient parent strain by microarray analysis. A total of 357 genes were found to be transcribed differentially in the rel-deficient mutant strain. In a second experiment, the stringent response was induced by addition of DL-serine hydroxamate (SHX) in early exponential growth phase. The time point of the maximal effect on transcription was determined by real-time RT-PCR using the histidine and serine biosynthetic genes. Transcription of all of these genes reached a maximum at 10 minutes after SHX addition. Microarray experiments were performed comparing the transcriptomes of SHX-induced cultures of the rel-proficient strain and the rel mutant. The differentially expressed genes were grouped into three classes. Class A comprises genes which are differentially regulated only in the presence of an intact rel gene. This class includes the non-essential sigma factor gene sigB which was upregulated and a large number of genes involved in nitrogen metabolism which were downregulated. Class B comprises genes which were differentially regulated in response to SHX in both strains, independent of the rel gene. A large number of genes encoding ribosomal proteins fall into this class, all being downregulated. Class C comprises genes which were differentially regulated in response to SHX only in the rel mutant. This class includes genes encoding putative stress proteins and global transcriptional regulators that might be responsible for the complex transcriptional patterns detected in the rel mutant when compared directly with its rel-proficient parent strain. Conclusion In C. glutamicum the stringent response enfolds a fast answer to an induced amino acid starvation on the transcriptome level. It also showed some significant differences to the transcriptional reactions occuring in Escherichia coli and Bacillus subtilis. Notable are the rel-dependent regulation of the nitrogen metabolism genes and the rel-independent regulation of the genes encoding ribosomal proteins. PMID:16961923
TIPMaP: a web server to establish transcript isoform profiles from reliable microarray probes.
Chitturi, Neelima; Balagannavar, Govindkumar; Chandrashekar, Darshan S; Abinaya, Sadashivam; Srini, Vasan S; Acharya, Kshitish K
2013-12-27
Standard 3' Affymetrix gene expression arrays have contributed a significantly higher volume of existing gene expression data than other microarray platforms. These arrays were designed to identify differentially expressed genes, but not their alternatively spliced transcript forms. No resource can currently identify expression pattern of specific mRNA forms using these microarray data, even though it is possible to do this. We report a web server for expression profiling of alternatively spliced transcripts using microarray data sets from 31 standard 3' Affymetrix arrays for human, mouse and rat species. The tool has been experimentally validated for mRNAs transcribed or not-detected in a human disease condition (non-obstructive azoospermia, a male infertility condition). About 4000 gene expression datasets were downloaded from a public repository. 'Good probes' with complete coverage and identity to latest reference transcript sequences were first identified. Using them, 'Transcript specific probe-clusters' were derived for each platform and used to identify expression status of possible transcripts. The web server can lead the user to datasets corresponding to specific tissues, conditions via identifiers of the microarray studies or hybridizations, keywords, official gene symbols or reference transcript identifiers. It can identify, in the tissues and conditions of interest, about 40% of known transcripts as 'transcribed', 'not-detected' or 'differentially regulated'. Corresponding additional information for probes, genes, transcripts and proteins can be viewed too. We identified the expression of transcripts in a specific clinical condition and validated a few of these transcripts by experiments (using reverse transcription followed by polymerase chain reaction). The experimental observations indicated higher agreements with the web server results, than contradictions. The tool is accessible at http://resource.ibab.ac.in/TIPMaP. The newly developed online tool forms a reliable means for identification of alternatively spliced transcript-isoforms that may be differentially expressed in various tissues, cell types or physiological conditions. Thus, by making better use of existing data, TIPMaP avoids the dependence on precious tissue-samples, in experiments with a goal to establish expression profiles of alternative splice forms--at least in some cases.
Goetghebuer, Lise; Servais, Pierre; George, Isabelle F
2017-05-01
Microbial communities play a key role in water self-purification. They are primary drivers of biogenic element cycles and ecosystem processes. However, these communities remain largely uncharacterized. In order to understand the diversity-heterotrophic activity relationship facing sole carbon sources, we assembled a synthetic community composed of 20 'typical' freshwater bacterial species mainly isolated from the Zenne River (Belgium). The carbon source utilization profiles of each individual strain and of the mixed community were measured in Biolog Phenotype MicroArrays PM1 and PM2A microplates that allowed testing 190 different carbon sources. Our results strongly suggest interactions occurring between our planktonic strains as our synthetic community showed metabolic properties that were not displayed by its single components. Finally, the catabolic performances of the synthetic community and a natural community from the same sampling site were compared. The synthetic community behaved like the natural one and was therefore representative of the latter in regard to carbon source consumption. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Wang, Hong-Yan; Lin, Li; Tan, Li-Si; Yu, Hui-Yuan; Cheng, Jya-Wei; Pan, Ya-Ping
2017-02-17
Wound-related infection remains a major challenge for health professionals. One disadvantage in conventional antibiotics is their inability to penetrate biofilms, the main protective strategy for bacteria to evade irradiation. Previously, we have shown that synthetic antimicrobial peptides could inhibit bacterial biofilms formation. In this study, we first delineated how Nal-P-113, a novel antimicrobial peptide, exerted its inhibitory effects on Porphyromonas gingivalis W83 biofilms formation at a low concentration. Secondly, we performed gene expression profiling and validated that Nal-P-113 at a low dose significantly down-regulated genes related to mobile and extrachromosomal element functions, transport and binding proteins in Porphyromonas gingivalis W83. These findings suggest that Nal-P-113 at low dose is sufficient to inhibit the formation of biofilms although Porphyromonas gingivalis W83 may maintain its survival in the oral cavity. The newly discovered molecular pathways may add the knowledge of developing a new strategy to target bacterial infections in combination with current first-line treatment in periodontitis.
Dielectrophoretic manipulation and separation of microparticles using microarray dot electrodes.
Yafouz, Bashar; Kadri, Nahrizul Adib; Ibrahim, Fatimah
2014-04-03
This paper introduces a dielectrophoretic system for the manipulation and separation of microparticles. The system is composed of five layers and utilizes microarray dot electrodes. We validated our system by conducting size-dependent manipulation and separation experiments on 1, 5 and 15 μm polystyrene particles. Our findings confirm the capability of the proposed device to rapidly and efficiently manipulate and separate microparticles of various dimensions, utilizing positive and negative dielectrophoresis (DEP) effects. Larger size particles were repelled and concentrated in the center of the dot by negative DEP, while the smaller sizes were attracted and collected by the edge of the dot by positive DEP.
Sequence verification as quality-control step for production of cDNA microarrays.
Taylor, E; Cogdell, D; Coombes, K; Hu, L; Ramdas, L; Tabor, A; Hamilton, S; Zhang, W
2001-07-01
To generate cDNA arrays in our core laboratory, we amplified about 2300 PCR products from a human, sequence-verified cDNA clone library. As a quality-control step, we sequenced the PCR products immediately before printing. The sequence information was used to search the GenBank database to confirm the identities. Although these clones were previously sequence verified by the company, we found that only 79% of the clones matched the original database after handling. Our experience strongly indicates the necessity to sequence verify the clones at the final stage before printing on microarray slides and to modify the gene list accordingly.
Comparative transcriptional profiling of human Merkel cells and Merkel cell carcinoma.
Mouchet, Nicolas; Coquart, Nolwenn; Lebonvallet, Nicolas; Le Gall-Ianotto, Christelle; Mogha, Ariane; Fautrel, Alain; Boulais, Nicholas; Dréno, Brigitte; Martin, Ludovic; Hu, Weiguo; Galibert, Marie-Dominique; Misery, Laurent
2014-12-01
Merkel cell carcinoma is believed to be derived from Merkel cells after infection by Merkel cell polyomavirus (MCPyV) and other poorly understood events. Transcriptional profiling using cDNA microarrays was performed on cells from MCPy-negative and MCPy-positive Merkel cell carcinomas and isolated normal Merkel cells. This microarray revealed numerous significantly upregulated genes and some downregulated genes. The extensive list of genes that were identified in these experiments provides a large body of potentially valuable information of Merkel cell carcinoma carcinogenesis and could represent a source of potential targets for cancer therapy. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Spotting effect in microarray experiments
Mary-Huard, Tristan; Daudin, Jean-Jacques; Robin, Stéphane; Bitton, Frédérique; Cabannes, Eric; Hilson, Pierre
2004-01-01
Background Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio) and intensity across the array. Results Using the variogram, a geostatistical tool, we characterized the observed variability, called here the spotting effect because it most probably arises during steps in the array printing procedure. Conclusions The spotting effect is not appropriately corrected by current normalization methods, even by those addressing spatial variability. Importantly, the spotting effect may alter differential and clustering analysis. PMID:15151695
Microarray Meta-Analysis of RNA-Binding Protein Functions in Alternative Polyadenylation
Hu, Wenchao; Liu, Yuting; Yan, Jun
2014-01-01
Alternative polyadenylation (APA) is a post-transcriptional mechanism to generate diverse mRNA transcripts with different 3′UTRs from the same gene. In this study, we systematically searched for the APA events with differential expression in public mouse microarray data. Hundreds of genes with over-represented differential APA events and the corresponding experiments were identified. We further revealed that global APA differential expression occurred prevalently in tissues such as brain comparing to peripheral tissues, and biological processes such as development, differentiation and immune responses. Interestingly, we also observed widespread differential APA events in RNA-binding protein (RBP) genes such as Rbm3, Eif4e2 and Elavl1. Given the fact that RBPs are considered as the main regulators of differential APA expression, we constructed a co-expression network between APAs and RBPs using the microarray data. Further incorporation of CLIP-seq data of selected RBPs showed that Nova2 represses and Mbnl1 promotes the polyadenylation of closest poly(A) sites respectively. Altogether, our study is the first microarray meta-analysis in a mammal on the regulation of APA by RBPs that integrated massive mRNA expression data under a wide-range of biological conditions. Finally, we present our results as a comprehensive resource in an online website for the research community. PMID:24622240
Karsten, Stanislav L.; Van Deerlin, Vivianna M. D.; Sabatti, Chiara; Gill, Lisa H.; Geschwind, Daniel H.
2002-01-01
Archival formalin-fixed, paraffin-embedded and ethanol-fixed tissues represent a potentially invaluable resource for gene expression analysis, as they are the most widely available material for studies of human disease. Little data are available evaluating whether RNA obtained from fixed (archival) tissues could produce reliable and reproducible microarray expression data. Here we compare the use of RNA isolated from human archival tissues fixed in ethanol and formalin to frozen tissue in cDNA microarray experiments. Since an additional factor that can limit the utility of archival tissue is the often small quantities available, we also evaluate the use of the tyramide signal amplification method (TSA), which allows the use of small amounts of RNA. Detailed analysis indicates that TSA provides a consistent and reproducible signal amplification method for cDNA microarray analysis, across both arrays and the genes tested. Analysis of this method also highlights the importance of performing non-linear channel normalization and dye switching. Furthermore, archived, fixed specimens can perform well, but not surprisingly, produce more variable results than frozen tissues. Consistent results are more easily obtainable using ethanol-fixed tissues, whereas formalin-fixed tissue does not typically provide a useful substrate for cDNA synthesis and labeling. PMID:11788730
BioconductorBuntu: a Linux distribution that implements a web-based DNA microarray analysis server.
Geeleher, Paul; Morris, Dermot; Hinde, John P; Golden, Aaron
2009-06-01
BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets. BioconductorBuntu is available for download under a creative commons license along with additional documentation and a tutorial from (http://bioinf.nuigalway.ie).
Customizing chemotherapy for colon cancer: the potential of gene expression profiling.
Mariadason, John M; Arango, Diego; Augenlicht, Leonard H
2004-06-01
The value of gene expression profiling, or microarray analysis, for the classification and prognosis of multiple forms of cancer is now clearly established. For colon cancer, expression profiling can readily discriminate between normal and tumor tissue, and to some extent between tumors of different histopathological stage and prognosis. While a definitive in vivo study demonstrating the potential of this methodology for predicting response to chemotherapy is presently lacking, the ability of microarrays to distinguish other subtleties of colon cancer phenotype, as well as recent in vitro proof-of-principle experiments utilizing colon cancer cell lines, illustrate the potential of this methodology for predicting the probability of response to specific chemotherapeutic agents. This review discusses some of the recent advances in the use of microarray analysis for understanding and distinguishing colon cancer subtypes, and attempts to identify challenges that need to be overcome in order to achieve the goal of using gene expression profiling for customizing chemotherapy in colon cancer.
Dion, Johann; Advedissian, Tamara; Storozhylova, Nataliya; Dahbi, Samir; Lambert, Annie; Deshayes, Frédérique; Viguier, Mireille; Tellier, Charles; Poirier, Françoise; Téletchéa, Stéphane; Dussouy, Christophe; Tateno, Hiroaki; Hirabayashi, Jun; Grandjean, Cyrille
2017-12-14
Glycan microarrays are useful tools for lectin glycan profiling. The use of a glycan microarray based on evanescent-field fluorescence detection was herein further extended to the screening of lectin inhibitors in competitive experiments. The efficacy of this approach was tested with 2/3'-mono- and 2,3'-diaromatic type II lactosamine derivatives and galectins as targets and was validated by comparison with fluorescence anisotropy proposed as an orthogonal protein interaction measurement technique. We showed that subtle differences in the architecture of the inhibitor could be sensed that pointed out the preference of galectin-3 for 2'-arylamido derivatives over ureas, thioureas, and amines and that of galectin-7 for derivatives bearing an α substituent at the anomeric position of glucosamine. We eventually identified a diaromatic oxazoline as a highly specific inhibitor of galectin-3 versus galectin-1 and galectin-7. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Gene Expression Omnibus (GEO): Microarray data storage, submission, retrieval, and analysis
Barrett, Tanya
2006-01-01
The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely distributes high-throughput molecular abundance data, predominantly gene expression data generated by DNA microarray technology. The database has a flexible design that can handle diverse styles of both unprocessed and processed data in a MIAME- (Minimum Information About a Microarray Experiment) supportive infrastructure that promotes fully annotated submissions. GEO currently stores about a billion individual gene expression measurements, derived from over 100 organisms, submitted by over 1,500 laboratories, addressing a wide range of biological phenomena. To maximize the utility of these data, several user-friendly Web-based interfaces and applications have been implemented that enable effective exploration, query, and visualization of these data, at the level of individual genes or entire studies. This chapter describes how the data are stored, submission procedures, and mechanisms for data retrieval and query. GEO is publicly accessible at http://www.ncbi.nlm.nih.gov/projects/geo/. PMID:16939800
English, Sangeeta B.; Shih, Shou-Ching; Ramoni, Marco F.; Smith, Lois E.; Butte, Atul J.
2014-01-01
Though genome-wide technologies, such as microarrays, are widely used, data from these methods are considered noisy; there is still varied success in downstream biological validation. We report a method that increases the likelihood of successfully validating microarray findings using real time RT-PCR, including genes at low expression levels and with small differences. We use a Bayesian network to identify the most relevant sources of noise based on the successes and failures in validation for an initial set of selected genes, and then improve our subsequent selection of genes for validation based on eliminating these sources of noise. The network displays the significant sources of noise in an experiment, and scores the likelihood of validation for every gene. We show how the method can significantly increase validation success rates. In conclusion, in this study, we have successfully added a new automated step to determine the contributory sources of noise that determine successful or unsuccessful downstream biological validation. PMID:18790084
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jaing, C; Gardner, S
The goal of this project is to develop forensic genotyping assays for select agent viruses, enhancing the current capabilities for the viral bioforensics and law enforcement community. We used a multipronged approach combining bioinformatics analysis, PCR-enriched samples, microarrays and TaqMan assays to develop high resolution and cost effective genotyping methods for strain level forensic discrimination of viruses. We have leveraged substantial experience and efficiency gained through year 1 on software development, SNP discovery, TaqMan signature design and phylogenetic signature mapping to scale up the development of forensics signatures in year 2. In this report, we have summarized the whole genomemore » wide SNP analysis and microarray probe design for forensics characterization of South American hemorrhagic fever viruses, tick-borne encephalitis viruses and henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus and Japanese encephalitis virus.« less
A Characterization of the Oral Microbiome in Allogeneic Stem Cell Transplant Patients
Ames, Nancy J.; Sulima, Pawel; Ngo, Thoi; Barb, Jennifer; Munson, Peter J.; Paster, Bruce J.; Hart, Thomas C.
2012-01-01
Background The mouth is a complex biological structure inhabited by diverse bacterial communities. The purpose of this study is to describe the effects of allogeneic stem cell transplantation on the oral microbiota and to examine differences among those patients who acquired respiratory complications after transplantation. Methodology/Principal Findings All patients were consented at the National Institutes of Health, Clinical Center. Bacterial DNA was analyzed from patients' oral specimens using the Human Oral Microbe Identification Microarray. The specimens were collected from four oral sites in 45 allogeneic transplantation patients. Specimens were collected at baseline prior to transplantation, after transplantation at the nadir of the neutrophil count and after myeloid engraftment. If respiratory signs and symptoms developed, additional specimens were obtained. Patients were followed for 100 days post transplantation. Eleven patients' specimens were subjected to further statistical analysis. Many common bacterial genera, such as Streptococcus, Veillonella, Gemella, Granulicatella and Camplyobacter were identified as being present before and after transplantation. Five of 11 patients developed respiratory complications following transplantation and there was preliminary evidence that the oral microbiome changed in their oral specimens. Cluster analysis and principal component analysis revealed this change in the oral microbiota. Conclusions/Significance After allogeneic transplantation, the oral bacterial community's response to a new immune system was not apparent and many of the most common core oral taxa remained unaffected. However, the oral microbiome was affected in patients who developed respiratory signs and symptoms after transplantation. The association related to the change in the oral microbiota and respiratory complications after transplantation will be validated by future studies using high throughput molecular methods. PMID:23144704
Brinkman, Cassandra L.; Schmidt-Malan, Suzannah M.; Karau, Melissa J.; Greenwood-Quaintance, Kerryl; Hassett, Daniel J.; Mandrekar, Jayawant N.
2016-01-01
Bacterial biofilms may form on indwelling medical devices such as prosthetic joints, heart valves and catheters, causing challenging-to-treat infections. We have previously described the ‘electricidal effect’, in which bacterial biofilms are decreased following exposure to direct electrical current. Herein, we sought to determine if the decreased bacterial quantities are due to detachment of biofilms or cell death and to investigate the role that reactive oxygen species (ROS) play in the observed effect. Using confocal and electron microscopy and flow cytometry, we found that direct current (DC) leads to cell death and changes in the architecture of biofilms formed by Gram-positive and Gram-negative bacteria. Reactive oxygen species (ROS) appear to play a role in DC-associated cell death, as there was an increase in ROS-production by Staphylococcus aureus and Staphylococcus epidermidis biofilms following exposure to DC. An increase in the production of ROS response enzymes catalase and superoxide dismutase (SOD) was observed for S. aureus, S. epidermidis and Pseudomonas aeruginosa biofilms following exposure to DC. Additionally, biofilms were protected from cell death when supplemented with antioxidants and oxidant scavengers, including catalase, mannitol and Tempol. Knocking out SOD (sodAB) in P. aeruginosa led to an enhanced DC effect. Microarray analysis of P. aeruginosa PAO1 showed transcriptional changes in genes related to the stress response and cell death. In conclusion, the electricidal effect results in death of bacteria in biofilms, mediated, at least in part, by production of ROS. PMID:27992529
Characterization of Trapped Lignin-Degrading Microbes in Tropical Forest Soil
DeAngelis, Kristen M.; Allgaier, Martin; Chavarria, Yaucin; Fortney, Julian L.; Hugenholtz, Phillip; Simmons, Blake; Sublette, Kerry; Silver, Whendee L.; Hazen, Terry C.
2011-01-01
Lignin is often the most difficult portion of plant biomass to degrade, with fungi generally thought to dominate during late stage decomposition. Lignin in feedstock plant material represents a barrier to more efficient plant biomass conversion and can also hinder enzymatic access to cellulose, which is critical for biofuels production. Tropical rain forest soils in Puerto Rico are characterized by frequent anoxic conditions and fluctuating redox, suggesting the presence of lignin-degrading organisms and mechanisms that are different from known fungal decomposers and oxygen-dependent enzyme activities. We explored microbial lignin-degraders by burying bio-traps containing lignin-amended and unamended biosep beads in the soil for 1, 4, 13 and 30 weeks. At each time point, phenol oxidase and peroxidase enzyme activity was found to be elevated in the lignin-amended versus the unamended beads, while cellulolytic enzyme activities were significantly depressed in lignin-amended beads. Quantitative PCR of bacterial communities showed more bacterial colonization in the lignin-amended compared to the unamended beads after one and four weeks, suggesting that the lignin supported increased bacterial abundance. The microbial community was analyzed by small subunit 16S ribosomal RNA genes using microarray (PhyloChip) and by high-throughput amplicon pyrosequencing based on universal primers targeting bacterial, archaeal, and eukaryotic communities. Community trends were significantly affected by time and the presence of lignin on the beads. Lignin-amended beads have higher relative abundances of representatives from the phyla Actinobacteria, Firmicutes, Acidobacteria and Proteobacteria compared to unamended beads. This study suggests that in low and fluctuating redox soils, bacteria could play a role in anaerobic lignin decomposition. PMID:21559391
Transcriptional Response of Nitrifying Communities to Wetting of Dry Soil
Firestone, Mary K.
2013-01-01
The first rainfall following a severe dry period provides an abrupt water potential change that is both an acute physiological stress and a defined stimulus for the reawakening of soil microbial communities. We followed the responses of indigenous communities of ammonia-oxidizing bacteria, ammonia-oxidizing archaea, and nitrite-oxidizing bacteria to the addition of water to laboratory incubations of soils taken from two California annual grasslands following a typically dry Mediterranean summer. By quantifying transcripts for a subunit of bacterial and archaeal ammonia monooxygenases (amoA) and a bacterial nitrite oxidoreductase (nxrA) in soil from 15 min to 72 h after water addition, we identified transcriptional response patterns for each of these three groups of nitrifiers. An increase in quantity of bacterial amoA transcripts was detectable within 1 h of wet-up and continued until the size of the ammonium pool began to decrease, reflecting a possible role of transcription in upregulation of nitrification after drought-induced stasis. In one soil, the pulse of amoA transcription lasted for less than 24 h, demonstrating the transience of transcriptional pools and the tight coupling of transcription to the local soil environment. Analysis of 16S rRNA using a high-density microarray suggested that nitrite-oxidizing Nitrobacter spp. respond in tandem with ammonia-oxidizing bacteria while nitrite-oxidizing Nitrospina spp. and Nitrospira bacteria may not. Archaeal ammonia oxidizers may respond slightly later than bacterial ammonia oxidizers but may maintain elevated transcription longer. Despite months of desiccation-induced inactivation, we found rapid transcriptional response by all three groups of soil nitrifiers. PMID:23524666
Hidayat, M F H; Milne, T; Cullinan, M P; Seymour, G J
2018-06-01
The salivary transcriptome may present as a readily available and non-invasive source of potential biomarkers. The development of chronic periodontitis is determined by individual patient susceptibility; hence, the aim of this study was to determine the potential of the salivary transcriptome as a biomarker of disease susceptibility using chronic periodontitis as an example. Using an Oragene ® RNA kit, the total RNA was purified from the saliva of 10 patients with chronic periodontitis and 10 patients without chronic periodontitis. The quantity and quality of the total RNA was determined, and a measure of gene expression via cDNA was undertaken using the Affymetrix microarray system. The microarray profiling result was further validated by real-time quantitative polymerase chain reaction. Spectrophotometric analysis showed the total RNA purified from each participant ranged from 0.92 μg/500 μL to 62.85 μg/500 μL. There was great variability in the quantity of total RNA obtained from the 2 groups in the study with a mean of 10.21 ± 12.71 μg/500 μL for the periodontitis group and 15.97 ± 23.47 μg/500 μL for the control group. Further the RNA purity (based on the A 260 /A 280 ratio) for the majority of participants (9 periodontitis and 6 controls) were within the acceptable limits for downstream analysis (2.0 ± 0.1). The study samples, showed 2 distinct bands at 23S (3800 bp) and 16S (1500 bp) characteristic of bacterial rRNA. Preliminary microarray analysis was performed for 4 samples (P2, P6, H5 and H9). The percentage of genes present in each of the 4 samples was not consistent with about 1.8%-18.7% of genes being detected. Quantitative real-time polymerase chain reaction confirmed that the total RNA purified from each sample was mainly bacterial RNA (Uni 16S) with minimal human mRNA. This study showed that minimal amounts of human RNA were able to be isolated from the saliva of patients with periodontitis as well as controls. Further work is required to enhance the extraction process of human mRNA from saliva if the salivary transcriptome is to be used in determining individual patient susceptibility. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Pozhitkov, Alex E; Noble, Peter A; Bryk, Jarosław; Tautz, Diethard
2014-01-01
Although microarrays are analysis tools in biomedical research, they are known to yield noisy output that usually requires experimental confirmation. To tackle this problem, many studies have developed rules for optimizing probe design and devised complex statistical tools to analyze the output. However, less emphasis has been placed on systematically identifying the noise component as part of the experimental procedure. One source of noise is the variance in probe binding, which can be assessed by replicating array probes. The second source is poor probe performance, which can be assessed by calibrating the array based on a dilution series of target molecules. Using model experiments for copy number variation and gene expression measurements, we investigate here a revised design for microarray experiments that addresses both of these sources of variance. Two custom arrays were used to evaluate the revised design: one based on 25 mer probes from an Affymetrix design and the other based on 60 mer probes from an Agilent design. To assess experimental variance in probe binding, all probes were replicated ten times. To assess probe performance, the probes were calibrated using a dilution series of target molecules and the signal response was fitted to an adsorption model. We found that significant variance of the signal could be controlled by averaging across probes and removing probes that are nonresponsive or poorly responsive in the calibration experiment. Taking this into account, one can obtain a more reliable signal with the added option of obtaining absolute rather than relative measurements. The assessment of technical variance within the experiments, combined with the calibration of probes allows to remove poorly responding probes and yields more reliable signals for the remaining ones. Once an array is properly calibrated, absolute quantification of signals becomes straight forward, alleviating the need for normalization and reference hybridizations.
NASA Astrophysics Data System (ADS)
Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew
Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed that the device identified influenza A hemagglutinin and neuraminidase subtypes and sequenced portions of both genes, demonstrating the potential of integrated microfluidic and microarray technology for multiple virus detection. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluidic handling steps and allows microarray-based DNA analysis in a rapid and automated fashion.
MIPHENO: Data normalization for high throughput metabolic analysis.
High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course...
Ma, Y; Dai, X; Hong, T; Munk, G B; Libera, M
2016-12-19
Despite their many advantages and successes, molecular beacon (MB) hybridization probes have not been extensively used in microarray formats because of the complicating probe-substrate interactions that increase the background intensity. We have previously shown that tethering to surface-patterned microgels is an effective means for localizing MB probes to specific surface locations in a microarray format while simultaneously maintaining them in as water-like an environment as possible and minimizing probe-surface interactions. Here we extend this approach to include both real-time detection together with integrated NASBA amplification. We fabricate small (∼250 μm × 250 μm) simplex, duplex, and five-plex assays with microarray spots of controllable size (∼20 μm diameter), position, and shape to detect bacteria and fungi in a bloodstream-infection model. The targets, primers, and microgel-tethered probes can be combined in a single isothermal reaction chamber with no post-amplification labelling. We extract total RNA from clinical blood samples and differentiate between Gram-positive and Gram-negative bloodstream infection in a duplex assay to detect RNA- amplicons. The sensitivity based on our current protocols in a simplex assay to detect specific ribosomal RNA sequences within total RNA extracted from S. aureus and E. coli cultures corresponds to tens of bacteria per ml. We furthermore show that the platform can detect RNA- amplicons from synthetic target DNA with 1 fM sensitivity in sample volumes that contain about 12 000 DNA molecules. These experiments demonstrate an alternative approach that can enable rapid and real-time microarray-based molecular diagnostics.
Dynamic, electronically switchable surfaces for membrane protein microarrays.
Tang, C S; Dusseiller, M; Makohliso, S; Heuschkel, M; Sharma, S; Keller, B; Vörös, J
2006-02-01
Microarray technology is a powerful tool that provides a high throughput of bioanalytical information within a single experiment. These miniaturized and parallelized binding assays are highly sensitive and have found widespread popularity especially during the genomic era. However, as drug diagnostics studies are often targeted at membrane proteins, the current arraying technologies are ill-equipped to handle the fragile nature of the protein molecules. In addition, to understand the complex structure and functions of proteins, different strategies to immobilize the probe molecules selectively onto a platform for protein microarray are required. We propose a novel approach to create a (membrane) protein microarray by using an indium tin oxide (ITO) microelectrode array with an electronic multiplexing capability. A polycationic, protein- and vesicle-resistant copolymer, poly(l-lysine)-grafted-poly(ethylene glycol) (PLL-g-PEG), is exposed to and adsorbed uniformly onto the microelectrode array, as a passivating adlayer. An electronic stimulation is then applied onto the individual ITO microelectrodes resulting in the localized release of the polymer thus revealing a bare ITO surface. Different polymer and biological moieties are specifically immobilized onto the activated ITO microelectrodes while the other regions remain protein-resistant as they are unaffected by the induced electrical potential. The desorption process of the PLL-g-PEG is observed to be highly selective, rapid, and reversible without compromising on the integrity and performance of the conductive ITO microelectrodes. As such, we have successfully created a stable and heterogeneous microarray of biomolecules by using selective electronic addressing on ITO microelectrodes. Both pharmaceutical diagnostics and biomedical technology are expected to benefit directly from this unique method.
Calling Biomarkers in Milk Using a Protein Microarray on Your Smartphone
Ludwig, Susann K. J.; Tokarski, Christian; Lang, Stefan N.; van Ginkel, Leendert A.; Zhu, Hongying; Ozcan, Aydogan; Nielen, Michel W. F.
2015-01-01
Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay procedure, the 48 microspots were labelled with Quantum Dots (QD) depending on the protein biomarker levels in the sample. QD-fluorescence was subsequently detected by the smartphone camera under UV light excitation from LEDs embedded in a simple 3D-printed opto-mechanical smartphone attachment. The somewhat aberrant images obtained under such conditions, were corrected by newly developed Android-based software on the same smartphone, and protein biomarker profiles were calculated. The indirect detection of recombinant bovine somatotropin (rbST) in milk extracts based on altered biomarker profile of anti-rbST antibodies was selected as a real-life challenge. RbST-treated and untreated cows clearly showed reproducible treatment-dependent biomarker profiles in milk, in excellent agreement with results from a flow cytometer reference method. In a pilot experiment, anti-rbST antibody detection was multiplexed with the detection of another rbST-dependent biomarker, insulin-like growth factor 1 (IGF-1). Milk extract IGF-1 levels were found to be increased after rbST treatment and correlated with the results obtained from the reference method. These data clearly demonstrate the potential of the portable protein microarray concept towards simultaneous detection of multiple biomarkers. We envisage broad application of this ‘protein microarray on a smartphone’-concept for on-site testing, e.g., in food safety, environment and health monitoring. PMID:26308444
Systematic Omics Analysis Review (SOAR) Tool to Support Risk Assessment
McConnell, Emma R.; Bell, Shannon M.; Cote, Ila; Wang, Rong-Lin; Perkins, Edward J.; Garcia-Reyero, Natàlia; Gong, Ping; Burgoon, Lyle D.
2014-01-01
Environmental health risk assessors are challenged to understand and incorporate new data streams as the field of toxicology continues to adopt new molecular and systems biology technologies. Systematic screening reviews can help risk assessors and assessment teams determine which studies to consider for inclusion in a human health assessment. A tool for systematic reviews should be standardized and transparent in order to consistently determine which studies meet minimum quality criteria prior to performing in-depth analyses of the data. The Systematic Omics Analysis Review (SOAR) tool is focused on assisting risk assessment support teams in performing systematic reviews of transcriptomic studies. SOAR is a spreadsheet tool of 35 objective questions developed by domain experts, focused on transcriptomic microarray studies, and including four main topics: test system, test substance, experimental design, and microarray data. The tool will be used as a guide to identify studies that meet basic published quality criteria, such as those defined by the Minimum Information About a Microarray Experiment standard and the Toxicological Data Reliability Assessment Tool. Seven scientists were recruited to test the tool by using it to independently rate 15 published manuscripts that study chemical exposures with microarrays. Using their feedback, questions were weighted based on importance of the information and a suitability cutoff was set for each of the four topic sections. The final validation resulted in 100% agreement between the users on four separate manuscripts, showing that the SOAR tool may be used to facilitate the standardized and transparent screening of microarray literature for environmental human health risk assessment. PMID:25531884
Extraction and labeling methods for microarrays using small amounts of plant tissue.
Stimpson, Alexander J; Pereira, Rhea S; Kiss, John Z; Correll, Melanie J
2009-03-01
Procedures were developed to maximize the yield of high-quality RNA from small amounts of plant biomass for microarrays. Two disruption techniques (bead milling and pestle and mortar) were compared for the yield and the quality of RNA extracted from 1-week-old Arabidopsis thaliana seedlings (approximately 0.5-30 mg total biomass). The pestle and mortar method of extraction showed enhanced RNA quality at the smaller biomass samples compared with the bead milling technique, although the quality in the bead milling could be improved with additional cooling steps. The RNA extracted from the pestle and mortar technique was further tested to determine if the small quantity of RNA (500 ng-7 microg) was appropriate for microarray analyses. A new method of low-quantity RNA labeling for microarrays (NuGEN Technologies, Inc.) was used on five 7-day-old seedlings (approximately 2.5 mg fresh weight total) of Arabidopsis that were grown in the dark and exposed to 1 h of red light or continued dark. Microarray analyses were performed on a small plant sample (five seedlings; approximately 2.5 mg) using these methods and compared with extractions performed with larger biomass samples (approximately 500 roots). Many well-known light-regulated genes between the small plant samples and the larger biomass samples overlapped in expression changes, and the relative expression levels of selected genes were confirmed with quantitative real-time polymerase chain reaction, suggesting that these methods can be used for plant experiments where the biomass is extremely limited (i.e. spaceflight studies).
Malenke, J R; Milash, B; Miller, A W; Dearing, M D
2013-07-01
Massively parallel sequencing has enabled the creation of novel, in-depth genetic tools for nonmodel, ecologically important organisms. We present the de novo transcriptome sequencing, analysis and microarray development for a vertebrate herbivore, the woodrat (Neotoma spp.). This genus is of ecological and evolutionary interest, especially with respect to ingestion and hepatic metabolism of potentially toxic plant secondary compounds. We generated a liver transcriptome of the desert woodrat (Neotoma lepida) using the Roche 454 platform. The assembled contigs were well annotated using rodent references (99.7% annotation), and biotransformation function was reflected in the gene ontology. The transcriptome was used to develop a custom microarray (eArray, Agilent). We tested the microarray with three experiments: one across species with similar habitat (thus, dietary) niches, one across species with different habitat niches and one across populations within a species. The resulting one-colour arrays had high technical and biological quality. Probes designed from the woodrat transcriptome performed significantly better than functionally similar probes from the Norway rat (Rattus norvegicus). There were a multitude of expression differences across the woodrat treatments, many of which related to biotransformation processes and activities. The pattern and function of the differences indicate shared ecological pressures, and not merely phylogenetic distance, play an important role in shaping gene expression profiles of woodrat species and populations. The quality and functionality of the woodrat transcriptome and custom microarray suggest these tools will be valuable for expanding the scope of herbivore biology, as well as the exploration of conceptual topics in ecology. © 2013 John Wiley & Sons Ltd.
2014-01-01
Background Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN architectures. Results In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database of transcriptional interactions. We used data from Arabidopsis thaliana root samples to show that the transcriptional regulatory networks derived from this database successfully recover previously identified root transcriptional modules and to propose new transcription factors for the SHORT ROOT/SCARECROW and PLETHORA pathways. We further show that these networks are a powerful tool to integrate and analyze high-throughput expression data, as exemplified by our analysis of a SHORT ROOT induction time-course microarray dataset, and are a reliable source for the prediction of novel root gene functions. In particular, we used our database to predict novel genes involved in root secondary cell-wall synthesis and identified the MADS-box TF XAL1/AGL12 as an unexpected participant in this process. Conclusions This study demonstrates that network inference using carefully curated microarray data yields reliable TRN architectures. In contrast to previous efforts to obtain root TRNs, that have focused on particular functional modules or tissues, our root transcriptional interactions provide an overview of the transcriptional pathways present in Arabidopsis thaliana roots and will likely yield a plethora of novel hypotheses to be tested experimentally. PMID:24739361
Linking microarray reporters with protein functions.
Gaj, Stan; van Erk, Arie; van Haaften, Rachel I M; Evelo, Chris T A
2007-09-26
The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.
Card, Roderick; Vaughan, Kelly; Bagnall, Mary; Spiropoulos, John; Cooley, William; Strickland, Tony; Davies, Rob; Anjum, Muna F.
2016-01-01
Salmonella enterica is a foodborne zoonotic pathogen of significant public health concern. We have characterized the virulence and antimicrobial resistance gene content of 95 Salmonella isolates from 11 serovars by DNA microarray recovered from UK livestock or imported meat. Genes encoding resistance to sulphonamides (sul1, sul2), tetracycline [tet(A), tet(B)], streptomycin (strA, strB), aminoglycoside (aadA1, aadA2), beta-lactam (blaTEM), and trimethoprim (dfrA17) were common. Virulence gene content differed between serovars; S. Typhimurium formed two subclades based on virulence plasmid presence. Thirteen isolates were selected by their virulence profile for pathotyping using the Galleria mellonella pathogenesis model. Infection with a chicken invasive S. Enteritidis or S. Gallinarum isolate, a multidrug resistant S. Kentucky, or a S. Typhimurium DT104 isolate resulted in high mortality of the larvae; notably presence of the virulence plasmid in S. Typhimurium was not associated with increased larvae mortality. Histopathological examination showed that infection caused severe damage to the Galleria gut structure. Enumeration of intracellular bacteria in the larvae 24 h post-infection showed increases of up to 7 log above the initial inoculum and transmission electron microscopy (TEM) showed bacterial replication in the haemolymph. TEM also revealed the presence of vacuoles containing bacteria in the haemocytes, similar to Salmonella containing vacuoles observed in mammalian macrophages; although there was no evidence from our work of bacterial replication within vacuoles. This work shows that microarrays can be used for rapid virulence genotyping of S. enterica and that the Galleria animal model replicates some aspects of Salmonella infection in mammals. These procedures can be used to help inform on the pathogenicity of isolates that may be antibiotic resistant and have scope to aid the assessment of their potential public and animal health risk. PMID:27199965
Ota, Koki; Kikuchi, Yuichiro; Imamura, Kentaro; Kita, Daichi; Yoshikawa, Kouki; Saito, Atsushi; Ishihara, Kazuyuki
2017-02-01
Extracytoplasmic function (ECF) sigma factors play an important role in the bacterial response to various environmental stresses. Porphyromonas gingivalis, a prominent etiological agent in human periodontitis, possesses six putative ECF sigma factors. So far, information is limited on the ECF sigma factor, PGN_0319. The aim of this study was to investigate the role of PGN_0319 (SigCH) of P. gingivalis, focusing on the regulation of hmuY and hmuR, which encode outer-membrane proteins involved in hemin utilization, and cdhR, a transcriptional regulator of hmuYR. First, we evaluated the gene expression profile of the sigCH mutant by DNA microarray. Among the genes with altered expression levels, those involved in hemin utilization were downregulated in the sigCH mutant. To verify the microarray data, quantitative reverse transcription PCR analysis was performed. The RNA samples used were obtained from bacterial cells grown to early-log phase, in which sigCH expression in the wild type was significantly higher than that in mid-log and late-log phases. The expression levels of hmuY, hmuR, and cdhR were significantly decreased in the sigCH mutant compared to wild type. Transcription of these genes was restored in a sigCH complemented strain. Compared to the wild type, the sigCH mutant showed reduced growth in log phase under hemin-limiting conditions. Electrophoretic mobility shift assays showed that recombinant SigCH protein bound to the promoter region of hmuY and cdhR. These results suggest that SigCH plays an important role in the early growth of P. gingivalis, and directly regulates cdhR and hmuYR, thereby playing a potential role in the mechanisms of hemin utilization by P. gingivalis. Copyright © 2016 Elsevier Ltd. All rights reserved.
Serotyping of Streptococcus pneumoniae Based on Capsular Genes Polymorphisms
Raymond, Frédéric; Boucher, Nancy; Allary, Robin; Robitaille, Lynda; Lefebvre, Brigitte; Tremblay, Cécile
2013-01-01
Streptococcus pneumoniae serotype epidemiology is essential since serotype replacement is a concern when introducing new polysaccharide-conjugate vaccines. A novel PCR-based automated microarray assay was developed to assist in the tracking of the serotypes. Autolysin, pneumolysin and eight genes located in the capsular operon were amplified using multiplex PCR. This step was followed by a tagged fluorescent primer extension step targeting serotype-specific polymorphisms. The tagged primers were then hybridized to a microarray. Results were exported to an expert system to identify capsular serotypes. The assay was validated on 166 cultured S. pneumoniae samples from 63 different serotypes as determined by the Quellung method. We show that typing only 12 polymorphisms located in the capsular operon allows the identification at the serotype level of 22 serotypes and the assignation of 24 other serotypes to a subgroup of serotypes. Overall, 126 samples (75.9%) were correctly serotyped, 14 were assigned to a member of the same serogroup, 8 rare serotypes were erroneously serotyped, and 18 gave negative serotyping results. Most of the discrepancies involved rare serotypes or serotypes that are difficult to discriminate using a DNA-based approach, for example 6A and 6B. The assay was also tested on clinical specimens including 43 cerebrospinal fluid samples from patients with meningitis and 59 nasopharyngeal aspirates from bacterial pneumonia patients. Overall, 89% of specimens positive for pneumolysin were serotyped, demonstrating that this method does not require culture to serotype clinical specimens. The assay showed no cross-reactivity for 24 relevant bacterial species found in these types of samples. The limit of detection for serotyping and S. pneumoniae detection was 100 genome equivalent per reaction. This automated assay is amenable to clinical testing and does not require any culturing of the samples. The assay will be useful for the evaluation of serotype prevalence changes after new conjugate vaccines introduction. PMID:24086706
Ho, Yu-Hsuan; Shah, Pramod; Chen, Yi-Wen; Chen, Chien-Sheng
2016-01-01
Antimicrobial peptides (AMPs) act either through membrane lysis or by attacking intracellular targets. Intracellular targeting AMPs are a resource for antimicrobial agent development. Several AMPs have been identified as intracellular targeting peptides; however, the intracellular targets of many of these peptides remain unknown. In the present study, we used an Escherichia coli proteome microarray to systematically identify the protein targets of three intracellular targeting AMPs: bactenecin 7 (Bac7), a hybrid of pleurocidin and dermaseptin (P-Der), and proline-arginine-rich peptide (PR-39). In addition, we also included the data of lactoferricin B (LfcinB) from our previous study for a more comprehensive analysis. We analyzed the unique protein hits of each AMP in the Kyoto Encyclopedia of Genes and Genomes. The results indicated that Bac7 targets purine metabolism and histidine kinase, LfcinB attacks the transcription-related activities and several cellular carbohydrate biosynthetic processes, P-Der affects several catabolic processes of small molecules, and PR-39 preferentially recognizes proteins involved in RNA- and folate-metabolism-related cellular processes. Moreover, both Bac7 and LfcinB target purine metabolism, whereas LfcinB and PR-39 target lipopolysaccharide biosynthesis. This suggested that LfcinB and Bac7 as well as LfcinB and PR-39 have a synergistic effect on antimicrobial activity, which was validated through antimicrobial assays. Furthermore, common hits of all four AMPs indicated that all of them target arginine decarboxylase, which is a crucial enzyme for Escherichia coli survival in extremely acidic environments. Thus, these AMPs may display greater inhibition to bacterial growth in extremely acidic environments. We have also confirmed this finding in bacterial growth inhibition assays. In conclusion, this comprehensive identification and systematic analysis of intracellular targeting AMPs reveals crucial insights into the intracellular mechanisms of the action of AMPs. PMID:26902206
Ho, Yu-Hsuan; Shah, Pramod; Chen, Yi-Wen; Chen, Chien-Sheng
2016-06-01
Antimicrobial peptides (AMPs) act either through membrane lysis or by attacking intracellular targets. Intracellular targeting AMPs are a resource for antimicrobial agent development. Several AMPs have been identified as intracellular targeting peptides; however, the intracellular targets of many of these peptides remain unknown. In the present study, we used an Escherichia coli proteome microarray to systematically identify the protein targets of three intracellular targeting AMPs: bactenecin 7 (Bac7), a hybrid of pleurocidin and dermaseptin (P-Der), and proline-arginine-rich peptide (PR-39). In addition, we also included the data of lactoferricin B (LfcinB) from our previous study for a more comprehensive analysis. We analyzed the unique protein hits of each AMP in the Kyoto Encyclopedia of Genes and Genomes. The results indicated that Bac7 targets purine metabolism and histidine kinase, LfcinB attacks the transcription-related activities and several cellular carbohydrate biosynthetic processes, P-Der affects several catabolic processes of small molecules, and PR-39 preferentially recognizes proteins involved in RNA- and folate-metabolism-related cellular processes. Moreover, both Bac7 and LfcinB target purine metabolism, whereas LfcinB and PR-39 target lipopolysaccharide biosynthesis. This suggested that LfcinB and Bac7 as well as LfcinB and PR-39 have a synergistic effect on antimicrobial activity, which was validated through antimicrobial assays. Furthermore, common hits of all four AMPs indicated that all of them target arginine decarboxylase, which is a crucial enzyme for Escherichia coli survival in extremely acidic environments. Thus, these AMPs may display greater inhibition to bacterial growth in extremely acidic environments. We have also confirmed this finding in bacterial growth inhibition assays. In conclusion, this comprehensive identification and systematic analysis of intracellular targeting AMPs reveals crucial insights into the intracellular mechanisms of the action of AMPs. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nelson, T.A.; Holmes, S.; Alekseyenko, A.V.
Irritable bowel syndrome (IBS) is a chronic, episodic gastrointestinal disorder that is prevalent in a significant fraction of western human populations; and changes in the microbiota of the large bowel have been implicated in the pathology of the disease. Using a novel comprehensive, high-density DNA microarray (PhyloChip) we performed a phylogenetic analysis of the microbial community of the large bowel in a rat model in which intracolonic acetic acid in neonates was used to induce long lasting colonic hypersensitivity and decreased stool water content and frequency, representing the equivalent of human constipation-predominant IBS. Our results revealed a significantly increased compositionalmore » difference in the microbial communities in rats with neonatal irritation as compared with controls. Even more striking was the dramatic change in the ratio of Firmicutes relative to Bacteroidetes, where neonatally irritated rats were enriched more with Bacteroidetes and also contained a different composition of species within this phylum. Our study also revealed differences at the level of bacterial families and species. The PhyloChip is a useful and convenient method to study enteric microflora. Further, this rat model system may be a useful experimental platform to study the causes and consequences of changes in microbial community composition associated with IBS.« less
Zhang, Haifang; Zhang, Xiaolei; Yan, Meiying; Pang, Bo; Kan, Biao; Xu, Huaxi; Huang, Xinxiang
2011-12-15
To determine the genotype of Salmonella enterica serovar Typhi (S. Typhi) strains in China and analyze their genetic diversity. We collected S. Typhi strains from 1959 to 2006 in five highly endemic Chinese provinces and chose 40 representative strains. Multilocus sequence typing was used to determine the genotypes or sequence types (ST) and microarray-based comparative genomic hybridization (M-CGH) to investigate the differences in gene content among these strains. Forty representative S. Typhi strains belonged to 4 sequence types (ST1, ST2, ST890, and ST892). The predominant S. Typhi genotype (31/40) was ST2 and it had a diverse geographic distribution. We discovered two novel STs - ST890 and ST892. M-CGH showed that 69 genes in these two novel STs were divergent from S. Typhi Ty2, which belongs to ST1. In addition, 5 representative Typhi strains of ST2 isolated from Guizhou province showed differences in divergent genes. We determined two novel sequence types, ST890 and ST892, and found that ST2 was the most prevalent genotype of S. Typhi in China. Genetic diversity was present even within a highly clonal bacterial population.
Yu, Xiaobo; Woolery, Andrew R.; Luong, Phi; Hao, Yi Heng; Grammel, Markus; Westcott, Nathan; Park, Jin; Wang, Jie; Bian, Xiaofang; Demirkan, Gokhan; Hang, Howard C.; Orth, Kim; LaBaer, Joshua
2014-01-01
AMPylation (adenylylation) is a recently discovered mechanism employed by infectious bacteria to regulate host cell signaling. However, despite significant effort, only a few host targets have been identified, limiting our understanding of how these pathogens exploit this mechanism to control host cells. Accordingly, we developed a novel nonradioactive AMPylation screening platform using high-density cell-free protein microarrays displaying human proteins produced by human translational machinery. We screened 10,000 unique human proteins with Vibrio parahaemolyticus VopS and Histophilus somni IbpAFic2, and identified many new AMPylation substrates. Two of these, Rac2, and Rac3, were confirmed in vivo as bona fide substrates during infection with Vibrio parahaemolyticus. We also mapped the site of AMPylation of a non-GTPase substrate, LyGDI, to threonine 51, in a region regulated by Src kinase, and demonstrated that AMPylation prevented its phosphorylation by Src. Our results greatly expanded the repertoire of potential host substrates for bacterial AMPylators, determined their recognition motif, and revealed the first pathogen-host interaction AMPylation network. This approach can be extended to identify novel substrates of AMPylators with different domains or in different species and readily adapted for other post-translational modifications. PMID:25073739
Time-dependent Translational Response of E. coli to Excess Zn(II)
Easton, J. Allen; Thompson, Peter; Crowder, Michael W.
2006-01-01
Zinc homeostasis is not well understood beyond methods of import and export. In order to better understand zinc homeostasis in Escherichia coli by identifying Zn(ii)-responsive proteins, a proteomic approach was taken. Through the use of two-dimensional gel electrophoresis, we were able to show that the levels of OmpF, AspC, YcdO, Eno, and CysE increased after 30 min of Zn(ii) stress, while the levels of Tig, TufA, SelA, and LeuC decreased relative to non-stressed controls. After 4 h of Zn(ii) stress, the levels of three proteins (DnaK, YeaU, and Mdh) were found to be up-regulated, while the levels of seven amino acid importers (HisJ, ArgT, LivJ, DppA, OppA, RbsB, and GinH) were found to be decreased. None of these proteins had been reported to be up- or down-regulated in any previously published cDNA microarray experiments. This result raises questions about the validity of cDNA arrays when they are used to make assumptions concerning protein levels within bacterial cells. These data also suggest that time is a factor when characterizing how the E. coli proteome responds to Zn(ii) stress. PMID:17122063
Jakobsen, Tim Holm; Bragason, Steinn Kristinn; Phipps, Richard Kerry; Christensen, Louise Dahl; van Gennip, Maria; Alhede, Morten; Skindersoe, Mette; Larsen, Thomas Ostenfeld; Høiby, Niels; Bjarnsholt, Thomas
2012-01-01
Foods with health-promoting effects beyond nutritional values have been gaining increasing research focus in recent years, although not much has been published on this subject in relation to bacterial infections. With respect to treatment, a novel antimicrobial strategy, which is expected to transcend problems with selective pressures for antibiotic resistance, is to interrupt bacterial communication, also known as quorum sensing (QS), by means of signal antagonists, the so-called QS inhibitors (QSIs). Furthermore, QSI agents offer a potential solution to the deficiencies associated with use of traditional antibiotics to treat infections caused by bacterial biofilms and multidrug-resistant bacteria. Several QSIs of natural origin have been identified, and in this study, several common food products and plants were extracted and screened for QSI activity in an attempt to isolate and characterize previously unknown QSI compounds active against the common opportunistic pathogen Pseudomonas aeruginosa. Several extracts displayed activity, but horseradish exhibited the highest activity. Chromatographic separation led to the isolation of a potent QSI compound that was identified by liquid chromatography-diode array detector-mass spectrometry (LC-DAD-MS) and nuclear magnetic resonance (NMR) spectroscopy as iberin—an isothiocyanate produced by many members of the Brassicaceae family. Real-time PCR (RT-PCR) and DNA microarray studies showed that iberin specifically blocks expression of QS-regulated genes in P. aeruginosa. PMID:22286987
Biofilm community diversity after exposure to 0·4% stannous fluoride gels.
Reilly, C; Rasmussen, K; Selberg, T; Stevens, J; Jones, R S
2014-12-01
To test the effect of 0·4% stannous fluoride (SnF2 ) glycerine-based gels on specific portions of the bacterial community in both a clinical observational study and in vitro multispecies plaque-derived (MSPD) biofilm model. Potential changes to specific portions of the bacterial community were determined through the Human Oral Microbial Identification Microarray (HOMIM). Both the observational clinical study and the biofilm model showed that short-term use of 0·4% SnF2 gel has little effect on the bacterial community depicted by hierarchical cluster analysis. The amount of plaque accumulation on a subject's teeth, which was measured by plaque index scores, failed to show statistical significant changes over the two baselines or after treatment (P = 0·9928). The in vitro results were similar when examining the effect of 0·4% SnF2 gels on biofilm adherence through a crystal violet assay (P = 0·1157). The bacteria within the dental biofilms showed resilience in maintaining the overall community diversity after exposure to 0·4% SnF2 topical gels. The study supports that the immediate benefits of using 0·4% SnF2 gels in children may be strictly from fluoride ions inhibiting tooth demineralization rather than delivering substantial antimicrobial effects. © 2014 The Society for Applied Microbiology.
NASA Astrophysics Data System (ADS)
Ghosh, S. B.; Bhattacharya, K.; Nayak, S.; Mukherjee, P.; Salaskar, D.; Kale, S. P.
2015-09-01
Definitive identification of microorganisms, including pathogenic and non-pathogenic bacteria, is extremely important for a wide variety of applications including food safety, environmental studies, bio-terrorism threats, microbial forensics, criminal investigations and above all disease diagnosis. Although extremely powerful techniques such as those based on PCR and microarrays exist, they require sophisticated laboratory facilities along with elaborate sample preparation by trained researchers. Among different spectroscopic techniques, FTIR was used in the 1980s and 90s for bacterial identification. In the present study five species of Bacillus were isolated from the aerobic predigester chamber of Nisargruna Biogas Plant (NBP) and were identified to the species level by biochemical and molecular biological (16S ribosomal DNA sequence) methods. Those organisms were further checked by solid state spectroscopic absorbance measurements using a wide range of electromagnetic radiation (wavelength 200 nm to 25,000 nm) encompassing UV, visible, near Infrared and Infrared regions. UV-Vis and NIR spectroscopy was performed on dried bacterial cell suspension on silicon wafer in specular mode while FTIR was performed on KBr pellets containing the bacterial cells. Consistent and reproducible species specific spectra were obtained and sensitivity up to a level of 1000 cells was observed in FTIR with a DTGS detector. This clearly shows the potential of solid state spectroscopic techniques for simple, easy to implement, reliable and sensitive detection of bacteria from environmental samples.
Díez, Lorena; Solopova, Ana; Fernández-Pérez, Rocío; González, Miriam; Tenorio, Carmen; Kuipers, Oscar P; Ruiz-Larrea, Fernanda
2017-09-18
This paper describes the molecular response of Lactococcus lactis NZ9700 to ethanol. This strain is a well-known nisin producer and a lactic acid bacteria (LAB) model strain. Global transcriptome profiling using DNA microarrays demonstrated a bacterial adaptive response to the presence of 2% ethanol in the culture broth and differential expression of 67 genes. The highest up-regulation was detected for those genes involved in arginine degradation through the arginine deiminase (ADI) pathway (20-40 fold up-regulation). The metabolic responses to ethanol of wild type L. lactis strains were studied and compared to those of regulator-deletion mutants MG∆argR and MG∆ahrC. The results showed that in the presence of 2% ethanol those strains with an active ADI pathway reached higher growth rates when arginine was available in the culture broth than in absence of arginine. In a chemically defined medium strains with an active ADI pathway consumed arginine and produced ornithine in the presence of 2% ethanol, hence corroborating that arginine catabolism is involved in the bacterial response to ethanol. This is the first study of the L. lactis response to ethanol stress to demonstrate the relevance of arginine catabolism for bacterial adaptation and survival in an ethanol containing medium. Copyright © 2017 Elsevier B.V. All rights reserved.
Molecular complexity of successive bacterial epidemics deconvoluted by comparative pathogenomics.
Beres, Stephen B; Carroll, Ronan K; Shea, Patrick R; Sitkiewicz, Izabela; Martinez-Gutierrez, Juan Carlos; Low, Donald E; McGeer, Allison; Willey, Barbara M; Green, Karen; Tyrrell, Gregory J; Goldman, Thomas D; Feldgarden, Michael; Birren, Bruce W; Fofanov, Yuriy; Boos, John; Wheaton, William D; Honisch, Christiane; Musser, James M
2010-03-02
Understanding the fine-structure molecular architecture of bacterial epidemics has been a long-sought goal of infectious disease research. We used short-read-length DNA sequencing coupled with mass spectroscopy analysis of SNPs to study the molecular pathogenomics of three successive epidemics of invasive infections involving 344 serotype M3 group A Streptococcus in Ontario, Canada. Sequencing the genome of 95 strains from the three epidemics, coupled with analysis of 280 biallelic SNPs in all 344 strains, revealed an unexpectedly complex population structure composed of a dynamic mixture of distinct clonally related complexes. We discovered that each epidemic is dominated by micro- and macrobursts of multiple emergent clones, some with distinct strain genotype-patient phenotype relationships. On average, strains were differentiated from one another by only 49 SNPs and 11 insertion-deletion events (indels) in the core genome. Ten percent of SNPs are strain specific; that is, each strain has a unique genome sequence. We identified nonrandom temporal-spatial patterns of strain distribution within and between the epidemic peaks. The extensive full-genome data permitted us to identify genes with significantly increased rates of nonsynonymous (amino acid-altering) nucleotide polymorphisms, thereby providing clues about selective forces operative in the host. Comparative expression microarray analysis revealed that closely related strains differentiated by seemingly modest genetic changes can have significantly divergent transcriptomes. We conclude that enhanced understanding of bacterial epidemics requires a deep-sequencing, geographically centric, comparative pathogenomics strategy.
Park, Ju Yeon; Kang, Beom Ryong; Ryu, Choong-Min; Anderson, Anne J; Kim, Young Cheol
2018-05-01
The Gac/Rsm network regulates, at the transcriptional level, many beneficial traits in biocontrol-active pseudomonads. In this study, we used Phenotype MicroArrays, followed by specific growth studies and mutational analysis, to understand how catabolism is regulated by this sensor kinase system in the biocontrol isolate Pseudomonas chlororaphis O6. The growth of a gacS mutant was decreased significantly relative to that of the wild-type on ornithine and arginine, and on the precursor of these amino acids, N-acetyl-l-glutamic acid. The gacS mutant also showed reduced production of polyamines. Expression of the genes encoding arginine decarboxylase (speA) and ornithine decarboxylases (speC) was controlled at the transcriptional level by the GacS sensor of P. chlororaphis O6. Polyamine production was reduced in the speC mutant, and was eliminated in the speAspeC mutant. The addition of exogenous polyamines to the speAspeC mutant restored the in vitro growth inhibition of two fungal pathogens, as well as the secretion of three biological control-related factors: pyrrolnitrin, protease and siderophore. These results extend our knowledge of the regulation by the Gac/Rsm network in a biocontrol pseudomonad to include polyamine synthesis. Collectively, our studies demonstrate that bacterial polyamines act as important regulators of bacterial cell growth and biocontrol potential. © 2017 BSPP AND JOHN WILEY & SONS LTD.
Soil-borne microbial functional structure across different land uses.
Kuramae, Eiko E; Zhou, Jizhong Z; Kowalchuk, George A; van Veen, Johannes A
2014-01-01
Land use change alters the structure and composition of microbial communities. However, the links between environmental factors and microbial functions are not well understood. Here we interrogated the functional structure of soil microbial communities across different land uses. In a multivariate regression tree analysis of soil physicochemical properties and genes detected by functional microarrays, the main factor that explained the different microbial community functional structures was C : N ratio. C : N ratio showed a significant positive correlation with clay and soil pH. Fields with low C : N ratio had an overrepresentation of genes for carbon degradation, carbon fixation, metal reductase, and organic remediation categories, while fields with high C : N ratio had an overrepresentation of genes encoding dissimilatory sulfate reductase, methane oxidation, nitrification, and nitrogen fixation. The most abundant genes related to carbon degradation comprised bacterial and fungal cellulases; bacterial and fungal chitinases; fungal laccases; and bacterial, fungal, and oomycete polygalacturonases. The high number of genes related to organic remediation was probably driven by high phosphate content, while the high number of genes for nitrification was probably explained by high total nitrogen content. The functional gene diversity found in different soils did not group the sites accordingly to land management. Rather, the soil factors, C : N ratio, phosphate, and total N, were the main factors driving the differences in functional genes across the fields examined.
Pichon, Christophe; du Merle, Laurence; Caliot, Marie Elise; Trieu-Cuot, Patrick; Le Bouguénec, Chantal
2012-04-01
Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli.
Pichon, Christophe; du Merle, Laurence; Caliot, Marie Elise; Trieu-Cuot, Patrick; Le Bouguénec, Chantal
2012-01-01
Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli. PMID:22139924
Reconstructing the temporal ordering of biological samples using microarray data.
Magwene, Paul M; Lizardi, Paul; Kim, Junhyong
2003-05-01
Accurate time series for biological processes are difficult to estimate due to problems of synchronization, temporal sampling and rate heterogeneity. Methods are needed that can utilize multi-dimensional data, such as those resulting from DNA microarray experiments, in order to reconstruct time series from unordered or poorly ordered sets of observations. We present a set of algorithms for estimating temporal orderings from unordered sets of sample elements. The techniques we describe are based on modifications of a minimum-spanning tree calculated from a weighted, undirected graph. We demonstrate the efficacy of our approach by applying these techniques to an artificial data set as well as several gene expression data sets derived from DNA microarray experiments. In addition to estimating orderings, the techniques we describe also provide useful heuristics for assessing relevant properties of sample datasets such as noise and sampling intensity, and we show how a data structure called a PQ-tree can be used to represent uncertainty in a reconstructed ordering. Academic implementations of the ordering algorithms are available as source code (in the programming language Python) on our web site, along with documentation on their use. The artificial 'jelly roll' data set upon which the algorithm was tested is also available from this web site. The publicly available gene expression data may be found at http://genome-www.stanford.edu/cellcycle/ and http://caulobacter.stanford.edu/CellCycle/.
Jiang, Ming-Ming; Mai, Zhi-Tao; Wan, Shan-Zhi; Chi, Yu-Min; Zhang, Xin; Sun, Bao-Hua; Di, Qing-Guo
2018-04-01
Circular RNAs (circRNAs) are a novel class of non-protein-coding RNA. Emerging evidence indicates that circRNAs participate in the regulation of many pathophysiological processes. This study aims to explore the expression profiles and pathological effects of circRNAs in non-small cell lung cancer (NSCLC). Human circRNAs microarray analysis was performed to screen the expression profile of circRNAs in NSCLC tissue. Expressions of circRNA and miRNA in NSCLC tissues and cells were quantified by qRTPCR. Functional experiments were performed to investigate the biological functions of circRNA, including CCK-8 assay, colony formation assay, transwell assay and xenograft in vivo assay. Human circRNAs microarray revealed a total 957 abnormally expressed circRNAs (> twofold, P < 0.05) in NSCLC tissue compared with adjacent normal tissue. In further studies, hsa_circ_0007385 was significantly up regulated in NSCLC tissue and cells. In vitro experiments with hsa_circ_0007385 knockdown resulted in significant suppression of the proliferation, migration and invasion of NSCLC cells. In vivo xenograft assay using hsa_circ_0007385 knockdown, significantly reduced tumor growth. Bioinformatics analysis and luciferase reporter assay verified the potential target miR-181, suggesting a possible regulatory pathway for hsa_circ_0007385. In summary, results suggest hsa_circ_0007385 plays a role in NSCLC tumorigenesis, providing a potential therapeutic target for NSCLC.
Hirakawa, Ikumi; Miyagawa, Shinichi; Katsu, Yoshinao; Kagami, Yoshihiro; Tatarazako, Norihisa; Kobayashi, Tohru; Kusano, Teruhiko; Mizutani, Takeshi; Ogino, Yukiko; Takeuchi, Takashi; Ohta, Yasuhiko; Iguchi, Taisen
2012-05-01
The occurrence of oocytes in the testis (testis-ova) of several fish species is often associated with exposure of estrogenic chemicals. However, induction mechanisms of the testis-ova remain to be elucidated. To develop marker genes for detecting testis-ova in the testis, adult male medaka were exposed to nominal concentration of 100 ng L(-1) of 17α-ethinylestradiol (EE2) for 3-5 weeks, and 800 ng estradiol benzoate (EB) for 3 weeks (experiment I), and a measured concentration of 20 ng L(-1) EE2 for 1-6 weeks (experiment II). Histological analysis was performed for the testis, and microarray analyses were performed for the testis, liver and brain. Microarray analysis in the estrogen-exposed medaka liver showed vitellogenin and choriogenin as estrogen responsive genes. Testis-ova were induced in the testis after 4 weeks of exposure to 100 ng L(-1) EE2, 3 weeks of exposure to 800 ng EB, and 6 weeks of exposure to 20 ng L(-1) EE2. Microarray analysis of estrogen-exposed testes revealed up-regulation of genes related to zona pellucida (ZP) and the oocytes marker gene, 42Sp50. Using quantitative RT-PCR we confirmed that Zpc5 gene can be used as a marker for the detection of testis-ova in male medaka. Copyright © 2011 Elsevier Ltd. All rights reserved.
2013-01-01
Background Hybridization based assays and capture systems depend on the specificity of hybridization between a probe and its intended target. A common guideline in the construction of DNA microarrays, for instance, is that avoiding complementary stretches of more than 15 nucleic acids in a 50 or 60-mer probe will eliminate sequence specific cross-hybridization reactions. Here we present a study of the behavior of partially matched oligonucleotide pairs with complementary stretches starting well below this threshold complementarity length – in silico, in solution, and at the microarray surface. The modeled behavior of pairs of oligonucleotide probes and their targets suggests that even a complementary stretch of sequence 12 nt in length would give rise to specific cross-hybridization. We designed a set of binding partners to a 50-mer oligonucleotide containing complementary stretches from 6 nt to 21 nt in length. Results Solution melting experiments demonstrate that stable partial duplexes can form when only 12 bp of complementary sequence are present; surface hybridization experiments confirm that a signal close in magnitude to full-strength signal can be obtained from hybridization of a 12 bp duplex within a 50mer oligonucleotide. Conclusions Microarray and other molecular capture strategies that rely on a 15 nt lower complementarity bound for eliminating specific cross-hybridization may not be sufficiently conservative. PMID:23445545
Lim, Hye-Sun; Ha, Hyekyung; Shin, Hyeun-Kyoo; Jeong, Soo-Jin
2015-09-01
Saussurea lappa has been reported to possess anti-atopic properties. In this study, we have confirmed the S. lappa's anti-atopic properties in Nc/Nga mice and investigated the candidate gene related with its properties using microarray. We determined the target gene using real time PCR in in vitro experiment. S. lappa showed the significant reduction in atopic dermatitis (AD) score and immunoglobulin E compared with the AD induced Nc/Nga mice. In the results of microarray using back skin obtained from animals, we found that S. lappa's properties are closely associated with cytokine-cytokine receptor interaction and the JAK-STAT signaling pathway. Consistent with the microarray data, real-time RT-PCR confirmed these modulation at the mRNA level in skin tissues from S. lappa-treated mice. Among these genes, PI3Kca and IL20Rβ were significantly downregulated by S. lappa treatment in Nc/Nga mouse model. In in vitro experiment using HaCaT cells, we found that the S. lappa components, including alantolactone, caryophyllene, costic acid, costunolide and dehydrocostus lactone significantly decreased the expression of PI3Kca but not IL20Rβ in vitro. Therefore, our study suggests that PI3Kca-related signaling is closely related with the protective effects of S. lappa against the development of atopic-dermatitis.
2013-01-01
Background The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. Results A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. Conclusions This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An overview on the genes related with the immune system on R. decussatus transcriptome is also reported. PMID:24168212
Leite, Ricardo B; Milan, Massimo; Coppe, Alessandro; Bortoluzzi, Stefania; dos Anjos, António; Reinhardt, Richard; Saavedra, Carlos; Patarnello, Tomaso; Cancela, M Leonor; Bargelloni, Luca
2013-10-29
The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An overview on the genes related with the immune system on R. decussatus transcriptome is also reported.
2009-01-01
Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical. Conclusion Feature variability can have a strong impact on breast cancer signature composition, as well as the classification of individual patient samples. We therefore strongly recommend that feature variability is considered in analyzing data from microarray breast cancer expression profiling experiments. PMID:19941644
McArt, Darragh G.; Dunne, Philip D.; Blayney, Jaine K.; Salto-Tellez, Manuel; Van Schaeybroeck, Sandra; Hamilton, Peter W.; Zhang, Shu-Dong
2013-01-01
The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. PMID:23840550
COMPARISON OF COMPARATIVE GENOMIC HYBRIDIZATIONS TECHNOLOGIES ACROSS MICROARRAY PLATFORMS
Comparative Genomic Hybridization (CGH) measures DNA copy number differences between a reference genome and a test genome. The DNA samples are differentially labeled and hybridized to an immobilized substrate. In early CGH experiments, the DNA targets were hybridized to metaphase...
Lønborg, Christian; Nieto-Cid, Mar; Hernando-Morales, Victor; Hernández-Ruiz, Marta; Teira, Eva; Álvarez-Salgado, Xosé Antón
2016-05-01
The impact of solar radiation on dissolved organic matter (DOM) derived from 3 different sources (seawater, eelgrass leaves and river water) and the effect on the bacterial carbon cycling and diversity were investigated. Seawater with DOM from the sources was first either kept in the dark or exposed to sunlight (4 days), after which a bacterial inoculum was added and incubated for 4 additional days. Sunlight exposure reduced the coloured DOM and carbon signals, which was followed by a production of inorganic nutrients. Bacterial carbon cycling was higher in the dark compared with the light treatment in seawater and river samples, while higher levels were found in the sunlight-exposed eelgrass experiment. Sunlight pre-exposure stimulated the bacterial growth efficiency in the seawater experiments, while no impact was found in the other experiments. We suggest that these responses are connected to differences in substrate composition and the production of free radicals. The bacterial community that developed in the dark and sunlight pre-treated samples differed in the seawater and river experiments. Our findings suggest that impact of sunlight exposure on the bacterial carbon transfer and diversity depends on the DOM source and on the sunlight-induced production of inorganic nutrients. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Jani, Andrea J.; Briggs, Cheryl J.
2014-01-01
Symbiotic microbial communities may interact with infectious pathogens sharing a common host. The microbiome may limit pathogen infection or, conversely, an invading pathogen can disturb the microbiome. Documentation of such relationships during naturally occurring disease outbreaks is rare, and identifying causal links from field observations is difficult. This study documented the effects of an amphibian skin pathogen of global conservation concern [the chytrid fungus Batrachochytrium dendrobatidis (Bd)] on the skin-associated bacterial microbiome of the endangered frog, Rana sierrae, using a combination of population surveys and laboratory experiments. We examined covariation of pathogen infection and bacterial microbiome composition in wild frogs, demonstrating a strong and consistent correlation between Bd infection load and bacterial community composition in multiple R. sierrae populations. Despite the correlation between Bd infection load and bacterial community composition, we observed 100% mortality of postmetamorphic frogs during a Bd epizootic, suggesting that the relationship between Bd and bacterial communities was not linked to variation in resistance to mortal disease and that Bd infection altered bacterial communities. In a controlled experiment, Bd infection significantly altered the R. sierrae microbiome, demonstrating a causal relationship. The response of microbial communities to Bd infection was remarkably consistent: Several bacterial taxa showed the same response to Bd infection across multiple field populations and the laboratory experiment, indicating a somewhat predictable interaction between Bd and the microbiome. The laboratory experiment demonstrates that Bd infection causes changes to amphibian skin bacterial communities, whereas the laboratory and field results together strongly support Bd disturbance as a driver of bacterial community change during natural disease dynamics. PMID:25385615
Bacterial Transport in Heterogeneous Porous Media: Laboratory and Field Experiments
NASA Astrophysics Data System (ADS)
Fuller, M. E.
2001-12-01
A fully instrumented research site for examining field-scale bacterial transport has been established on the eastern shore of Virginia. Studies employing intact sediment cores from the South Oyster site have been performed to examine the effects of physical and chemical heterogeneity, to derive transport parameters, and to aid in the selection of bacterial strains for use in field experiments. A variety of innovative methods for tracking bacteria were developed and evaluated under both laboratory and field conditions, providing the tools to detect target cell concentrations in groundwater down to <20 cells/ml, and to perform real-time monitoring in the field. Comprehensive modeling efforts have provided a framework for the layout and instrumentation of the field site, and have aided in the design and interpretation of field-scale bacterial transport experiments. Field transport experiments were conducted in both aerobic and an anoxic flow cells to determine the effects of physical and chemical heterogeneity on field-scale bacterial transport. The results of this research not only contribute to the development of more effective bioremediation strategies, but also have implications for a better understanding of bacterial movement in the subsurface as it relates to public health microbiology and general microbial ecology.
Alshamlan, Hala; Badr, Ghada; Alohali, Yousef
2015-01-01
An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028
Swimley, Michelle S.; Taylor, Amber W.; Dawson, Erica D.
2011-01-01
Abstract Shiga toxin–producing Escherichia coli O157 is a leading cause of foodborne illness worldwide. To evaluate better methods to rapidly detect and genotype E. coli O157 strains, the present study evaluated the use of ampliPHOX, a novel colorimetric detection method based on photopolymerization, for pathogen identification with DNA microarrays. A low-density DNA oligonucleotide microarray was designed to target stx1 and stx2 genes encoding Shiga toxin production, the eae gene coding for adherence membrane protein, and the per gene encoding the O157-antigen perosamine synthetase. Results from the validation experiments demonstrated that the use of ampliPHOX allowed the accurate genotyping of the tested E. coli strains, and positive hybridization signals were observed for only probes targeting virulence genes present in the reference strains. Quantification showed that the average signal-to-noise ratio values ranged from 47.73 ± 7.12 to 76.71 ± 8.33, whereas average signal-to-noise ratio values below 2.5 were determined for probes where no polymer was formed due to lack of specific hybridization. Sensitivity tests demonstrated that the sensitivity threshold for E. coli O157 detection was 100–1000 CFU/mL. Thus, the use of DNA microarrays in combination with photopolymerization allowed the rapid and accurate genotyping of E. coli O157 strains. PMID:21288130
High throughput gene expression profiling: a molecular approach to integrative physiology
Liang, Mingyu; Cowley, Allen W; Greene, Andrew S
2004-01-01
Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions. PMID:14678487
Alshamlan, Hala; Badr, Ghada; Alohali, Yousef
2015-01-01
An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.
An expression database for roots of the model legume Medicago truncatula under salt stress
2009-01-01
Background Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. Description The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. Conclusion MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/. PMID:19906315
An expression database for roots of the model legume Medicago truncatula under salt stress.
Li, Daofeng; Su, Zhen; Dong, Jiangli; Wang, Tao
2009-11-11
Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/.
Sule, Preeti; Horne, Shelley M.; Logue, Catherine M.; Prüß, Birgit M.
2011-01-01
To understand the continuous problems that Escherichia coli O157:H7 causes as food pathogen, this study assessed global gene regulation in bacteria growing on meat. Since FlhD/FlhC of E. coli K-12 laboratory strains was previously established as a major control point in transducing signals from the environment to several cellular processes, this study compared the expression pattern of an E. coli O157:H7 parent strain to that of its isogenic flhC mutant. This was done with bacteria that had been grown on meat. Microarray experiments revealed 287 putative targets of FlhC. Real-time PCR was performed as an alternative estimate of transcription and confirmed microarray data for 13 out of 15 genes tested (87%). The confirmed genes are representative of cellular functions, such as central metabolism, cell division, biofilm formation, and pathogenicity. An additional 13 genes from the same cellular functions that had not been hypothesized as being regulated by FlhC by the microarray experiment were tested with real-time PCR and also exhibited higher expression levels in the flhC mutant than in the parent strain. Physiological experiments were performed and confirmed that FlhC reduced the cell division rate, the amount of biofilm biomass, and pathogenicity in a chicken embryo lethality model. Altogether, this study provides valuable insight into the complex regulatory network of the pathogen that enables its survival under various environmental conditions. This information may be used to develop strategies that could be used to reduce the number of cells or pathogenicity of E. coli O157:H7 on meat by interfering with the signal transduction pathways. PMID:21498760
Transcriptomic responses to wounding: meta-analysis of gene expression microarray data.
Sass, Piotr Andrzej; Dąbrowski, Michał; Charzyńska, Agata; Sachadyn, Paweł
2017-11-07
A vast amount of microarray data on transcriptomic response to injury has been collected so far. We designed the analysis in order to identify the genes displaying significant changes in expression after wounding in different organisms and tissues. This meta-analysis is the first study to compare gene expression profiles in response to wounding in as different tissues as heart, liver, skin, bones, and spinal cord, and species, including rat, mouse and human. We collected available microarray transcriptomic profiles obtained from different tissue injury experiments and selected the genes showing a minimum twofold change in expression in response to wounding in prevailing number of experiments for each of five wound healing stages we distinguished: haemostasis & early inflammation, inflammation, early repair, late repair and remodelling. During the initial phases after wounding, haemostasis & early inflammation and inflammation, the transcriptomic responses showed little consistency between different tissues and experiments. For the later phases, wound repair and remodelling, we identified a number of genes displaying similar transcriptional responses in all examined tissues. As revealed by ontological analyses, activation of certain pathways was rather specific for selected phases of wound healing, such as e.g. responses to vitamin D pronounced during inflammation. Conversely, we observed induction of genes encoding inflammatory agents and extracellular matrix proteins in all wound healing phases. Further, we selected several genes differentially upregulated throughout different stages of wound response, including established factors of wound healing in addition to those previously unreported in this context such as PTPRC and AQP4. We found that transcriptomic responses to wounding showed similar traits in a diverse selection of tissues including skin, muscles, internal organs and nervous system. Notably, we distinguished transcriptional induction of inflammatory genes not only in the initial response to wounding, but also later, during wound repair and tissue remodelling.
Holloway, Andrew J; Oshlack, Alicia; Diyagama, Dileepa S; Bowtell, David DL; Smyth, Gordon K
2006-01-01
Background Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguously evaluate precision and sensitivity for these technologies on a whole-array basis. Results A methodology is described for evaluating the precision and sensitivity of whole-genome gene expression technologies such as microarrays. The method consists of an easy-to-construct titration series of RNA samples and an associated statistical analysis using non-linear regression. The method evaluates the precision and responsiveness of each microarray platform on a whole-array basis, i.e., using all the probes, without the need to match probes across platforms. An experiment is conducted to assess and compare four widely used microarray platforms. All four platforms are shown to have satisfactory precision but the commercial platforms are superior for resolving differential expression for genes at lower expression levels. The effective precision of the two-color platforms is improved by allowing for probe-specific dye-effects in the statistical model. The methodology is used to compare three data extraction algorithms for the Affymetrix platforms, demonstrating poor performance for the commonly used proprietary algorithm relative to the other algorithms. For probes which can be matched across platforms, the cross-platform variability is decomposed into within-platform and between-platform components, showing that platform disagreement is almost entirely systematic rather than due to measurement variability. Conclusion The results demonstrate good precision and sensitivity for all the platforms, but highlight the need for improved probe annotation. They quantify the extent to which cross-platform measures can be expected to be less accurate than within-platform comparisons for predicting disease progression or outcome. PMID:17118209
Vallée, Maud; Gravel, Catherine; Palin, Marie-France; Reghenas, Hélène; Stothard, Paul; Wishart, David S; Sirard, Marc-André
2005-07-01
The main objective of the present study was to identify novel oocyte-specific genes in three different species: bovine, mouse, and Xenopus laevis. To achieve this goal, two powerful technologies were combined: a polymerase chain reaction (PCR)-based cDNA subtraction, and cDNA microarrays. Three subtractive libraries consisting of 3456 clones were established and enriched for oocyte-specific transcripts. Sequencing analysis of the positive insert-containing clones resulted in the following classification: 53% of the clones corresponded to known cDNAs, 26% were classified as uncharacterized cDNAs, and a final 9% were classified as novel sequences. All these clones were used for cDNA microarray preparation. Results from these microarray analyses revealed that in addition to already known oocyte-specific genes, such as GDF9, BMP15, and ZP, known genes with unknown function in the oocyte were identified, such as a MLF1-interacting protein (MLF1IP), B-cell translocation gene 4 (BTG4), and phosphotyrosine-binding protein (xPTB). Furthermore, 15 novel oocyte-specific genes were validated by reverse transcription-PCR to confirm their preferential expression in the oocyte compared to somatic tissues. The results obtained in the present study confirmed that microarray analysis is a robust technique to identify true positives from the suppressive subtractive hybridization experiment. Furthermore, obtaining oocyte-specific genes from three species simultaneously allowed us to look at important genes that are conserved across species. Further characterization of these novel oocyte-specific genes will lead to a better understanding of the molecular mechanisms related to the unique functions found in the oocyte.
Linking microarray reporters with protein functions
Gaj, Stan; van Erk, Arie; van Haaften, Rachel IM; Evelo, Chris TA
2007-01-01
Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/. PMID:17897448
Global gene expression analysis of the heat shock response in the phytopathogen Xylella fastidiosa.
Koide, Tie; Vêncio, Ricardo Z N; Gomes, Suely L
2006-08-01
Xylella fastidiosa is a phytopathogenic bacterium that is responsible for diseases in many economically important crops. Although different strains have been studied, little is known about X. fastidiosa stress responses. One of the better characterized stress responses in bacteria is the heat shock response, which induces the expression of specific genes to prevent protein misfolding and aggregation and to promote degradation of the irreversibly denatured polypeptides. To investigate X. fastidiosa genes involved in the heat shock response, we performed a whole-genome microarray analysis in a time course experiment. Globally, 261 genes were induced (9.7%) and 222 genes were repressed (8.3%). The expression profiles of the differentially expressed genes were grouped, and their expression patterns were validated by quantitative reverse transcription-PCR experiments. We determined the transcription start sites of six heat shock-inducible genes and analyzed their promoter regions, which allowed us to propose a putative consensus for sigma(32) promoters in Xylella and to suggest additional genes as putative members of this regulon. Besides the induction of classical heat shock protein genes, we observed the up-regulation of virulence-associated genes such as vapD and of genes for hemagglutinins, hemolysin, and xylan-degrading enzymes, which may indicate the importance of heat stress to bacterial pathogenesis. In addition, we observed the repression of genes related to fimbriae, aerobic respiration, and protein biosynthesis and the induction of genes related to the extracytoplasmic stress response and some phage-related genes, revealing the complex network of genes that work together in response to heat shock.
Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu
2012-06-08
Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eric E. Roden
2009-07-08
This report summarizes research conducted in conjunction with a project entitled “Integrated Nucleic Acid System for In-Field Monitoring of Microbial Community Dynamics and Metabolic Activity”, which was funded through the Integrative Studies Element of the former NABIR Program (now the Environmental Remediation Sciences Program) within the Office of Biological and Environmental Research. Dr. Darrell Chandler (originally at Argonne National Laboratory, now with Akonni Biosystems) was the overall PI/PD for the project. The overall project goals were to (1) apply a model iron-reducer and sulfate-reducer microarray and instrumentation systems to sediment and groundwater samples from the Scheibe et al. FRC Areamore » 2 field site, UMTRA sediments, and other DOE contaminated sites; (2) continue development and expansion of a 16S rRNA/rDNA¬-targeted probe suite for microbial community dynamics as new sequences are obtained from DOE-relevant sites; and (3) address the fundamental molecular biology and analytical chemistry associated with the extraction, purification and analysis of functional genes and mRNA in environmental samples. Work on the UW subproject focused on conducting detailed batch and semicontinuous culture reactor experiments with uranium-contaminated FRC Area 2 sediment. The reactor experiments were designed to provide coherent geochemical and microbiological data in support of microarray analyses of microbial communities in Area 2 sediments undergoing biostimulation with ethanol. A total of four major experiments were conducted (one batch and three semicontinuous culture), three of which (the batch and two semicontinuous culture) provided samples for DNA microarray analysis. A variety of other molecular analyses (clone libraries, 16S PhyloChip, RT-PCR, and T-RFLP) were conducted on parallel samples from the various experiments in order to provide independent information on microbial community response to biostimulation.« less
Characterization of Trapped Lignin-Degrading Microbes in Tropical Forest Soil
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeAngelis, Kristen M.; Allgaier, Martin; Chavarria, Yaucin
2011-04-29
Lignin is often the most difficult portion of plant biomass to degrade, with fungi generally thought to dominate during late stage decomposition. Lignin in feedstock plant material represents a barrier to more efficient plant biomass conversion and can also hinder enzymatic access to cellulose, which is critical for biofuels production. Tropical rain forest soils in Puerto Rico are characterized by frequent anoxic conditions and fluctuating redox, suggesting the presence of lignin-degrading organisms and mechanisms that are different from known fungal decomposers and oxygen-dependent enzyme activities. We explored microbial lignin-degraders by burying bio-traps containing lignin-amended and unamended biosep beads in themore » soil for 1, 4, 13 and 30 weeks. At each time point, phenol oxidase and peroxidase enzyme activity was found to be elevated in the lignin-amended versus the unamended beads, while cellulolytic enzyme activities were significantly depressed in lignin-amended beads. Quantitative PCR of bacterial communities showed more bacterial colonization in the lignin-amended compared to the unamended beads after one and four weeks, suggesting that the lignin supported increased bacterial abundance. The microbial community was analyzed by small subunit 16S ribosomal RNA genes using microarray (PhyloChip) and by high-throughput amplicon pyrosequencing based on universal primers targeting bacterial, archaeal, and eukaryotic communities. Community trends were significantly affected by time and the presence of lignin on the beads. Lignin-amended beads have higher relative abundances of representatives from the phyla Actinobacteria, Firmicutes, Acidobacteria and Proteobacteria compared to unamended beads. This study suggests that in low and fluctuating redox soils, bacteria could play a role in anaerobic lignin decomposition.« less
Characterization of trapped lignin-degrading microbes in tropical forest soil
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeAngelis, K.M.; Allgaier, M.; Chavarria, Y.
2011-03-01
Lignin is often the most difficult portion of plant biomass to degrade, with fungi generally thought to dominate during late stage decomposition. Lignin in feedstock plant material represents a barrier to more efficient plant biomass conversion and can also hinder enzymatic access to cellulose, which is critical for biofuels production. Tropical rain forest soils in Puerto Rico are characterized by frequent anoxic conditions and fluctuating redox, suggesting the presence of lignin-degrading organisms and mechanisms that are different from known fungal decomposers and oxygen-dependent enzyme activities. We explored microbial lignin-degraders by burying bio-traps containing lignin-amended and unamended biosep beads in themore » soil for 1, 4, 13 and 30 weeks. At each time point, phenol oxidase and peroxidase enzyme activity was found to be elevated in the lignin-amended versus the unamended beads, while cellulolytic enzyme activities were significantly depressed in lignin-amended beads. Quantitative PCR of bacterial communities showed more bacterial colonization in the lignin-amended compared to the unamended beads after one and four weeks, suggesting that the lignin supported increased bacterial abundance. The microbial community was analyzed by small subunit 16S ribosomal RNA genes using microarray (PhyloChip) and by high-throughput amplicon pyrosequencing based on universal primers targeting bacterial, archaeal, and eukaryotic communities. Community trends were significantly affected by time and the presence of lignin on the beads. Lignin-amended beads have higher relative abundances of representatives from the phyla Actinobacteria, Firmicutes, Acidobacteria and Proteobacteria compared to unamended beads. This study suggests that in low and fluctuating redox soils, bacteria could play a role in anaerobic lignin decomposition.« less
Characterization of Trapped Lignin-Degrading Microbes in Tropical Forest Soil
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeAngelis, Kristen; Allgaier, Martin; Chavarria, Yaucin
2011-07-14
Lignin is often the most difficult portion of plant biomass to degrade, with fungi generally thought to dominate during late stage decomposition. Lignin in feedstock plant material represents a barrier to more efficient plant biomass conversion and can also hinder enzymatic access to cellulose, which is critical for biofuels production. Tropical rain forest soils in Puerto Rico are characterized by frequent anoxic conditions and fluctuating redox, suggesting the presence of lignin-degrading organisms and mechanisms that are different from known fungal decomposers and oxygen-dependent enzyme activities. We explored microbial lignin-degraders by burying bio-traps containing lignin-amended and unamended biosep beads in themore » soil for 1, 4, 13 and 30 weeks. At each time point, phenol oxidase and peroxidase enzyme activity was found to be elevated in the lignin-amended versus the unamended beads, while cellulolytic enzyme activities were significantly depressed in lignin-amended beads. Quantitative PCR of bacterial communities showed more bacterial colonization in the lignin-amended compared to the unamended beads after one and four weeks, suggesting that the lignin supported increased bacterial abundance. The microbial community was analyzed by small subunit 16S ribosomal RNA genes using microarray (PhyloChip) and by high-throughput amplicon pyrosequencing based on universal primers targeting bacterial, archaeal, and eukaryotic communities. Community trends were significantly affected by time and the presence of lignin on the beads. Lignin-amended beads have higher relative abundances of representatives from the phyla Actinobacteria, Firmicutes, Acidobacteria and Proteobacteria compared to unamended beads. This study suggests that in low and fluctuating redox soils, bacteria could play a role in anaerobic lignin decomposition.« less
2009-01-01
Background The maintenance of internal pH in bacterial cells is challenged by natural stress conditions, during host infection or in biotechnological production processes. Comprehensive transcriptomic and proteomic analyses has been conducted in several bacterial model systems, yet questions remain as to the mechanisms of pH homeostasis. Results Here we present the comprehensive analysis of pH homeostasis in C. glutamicum, a bacterium of industrial importance. At pH values between 6 and 9 effective maintenance of the internal pH at 7.5 ± 0.5 pH units was found. By DNA microarray analyses differential mRNA patterns were identified. The expression profiles were validated and extended by 1D-LC-ESI-MS/MS based quantification of soluble and membrane proteins. Regulators involved were identified and thereby participation of numerous signaling modules in pH response was found. The functional analysis revealed for the first time the occurrence of oxidative stress in C. glutamicum cells at neutral and low pH conditions accompanied by activation of the iron starvation response. Intracellular metabolite pool analysis unraveled inhibition of the TCA and other pathways at low pH. Methionine and cysteine synthesis were found to be activated via the McbR regulator, cysteine accumulation was observed and addition of cysteine was shown to be toxic under acidic conditions. Conclusions Novel limitations for C. glutamicum at non-optimal pH values were identified by a comprehensive analysis on the level of the transcriptome, proteome, and metabolome indicating a functional link between pH acclimatization, oxidative stress, iron homeostasis, and metabolic alterations. The results offer new insights into bacterial stress physiology and new starting points for bacterial strain design or pathogen defense. PMID:20025733
ArrayInitiative - a tool that simplifies creating custom Affymetrix CDFs
2011-01-01
Background Probes on a microarray represent a frozen view of a genome and are quickly outdated when new sequencing studies extend our knowledge, resulting in significant measurement error when analyzing any microarray experiment. There are several bioinformatics approaches to improve probe assignments, but without in-house programming expertise, standardizing these custom array specifications as a usable file (e.g. as Affymetrix CDFs) is difficult, owing mostly to the complexity of the specification file format. However, without correctly standardized files there is a significant barrier for testing competing analysis approaches since this file is one of the required inputs for many commonly used algorithms. The need to test combinations of probe assignments and analysis algorithms led us to develop ArrayInitiative, a tool for creating and managing custom array specifications. Results ArrayInitiative is a standalone, cross-platform, rich client desktop application for creating correctly formatted, custom versions of manufacturer-provided (default) array specifications, requiring only minimal knowledge of the array specification rules and file formats. Users can import default array specifications, import probe sequences for a default array specification, design and import a custom array specification, export any array specification to multiple output formats, export the probe sequences for any array specification and browse high-level information about the microarray, such as version and number of probes. The initial release of ArrayInitiative supports the Affymetrix 3' IVT expression arrays we currently analyze, but as an open source application, we hope that others will contribute modules for other platforms. Conclusions ArrayInitiative allows researchers to create new array specifications, in a standard format, based upon their own requirements. This makes it easier to test competing design and analysis strategies that depend on probe definitions. Since the custom array specifications are easily exported to the manufacturer's standard format, researchers can analyze these customized microarray experiments using established software tools, such as those available in Bioconductor. PMID:21548938
Wang, Wenyu; Liu, Yang; Hao, Jingcan; Zheng, Shuyu; Wen, Yan; Xiao, Xiao; He, Awen; Fan, Qianrui; Zhang, Feng; Liu, Ruiyu
2016-10-10
Hip cartilage destruction is consistently observed in the non-traumatic osteonecrosis of femoral head (NOFH) and accelerates its bone necrosis. The molecular mechanism underlying the cartilage damage of NOFH remains elusive. In this study, we conducted a systematically comparative study of gene expression profiles between NOFH and osteoarthritis (OA). Hip articular cartilage specimens were collected from 12 NOFH patients and 12 controls with traumatic femoral neck fracture for microarray (n=4) and quantitative real-time PCR validation experiments (n=8). Gene expression profiling of articular cartilage was performed using Agilent Human 4×44K Microarray chip. The accuracy of microarray experiment was further validated by qRT-PCR. Gene expression results of OA hip cartilage were derived from previously published study. Significance Analysis of Microarrays (SAM) software was applied for identifying differently expressed genes. Gene ontology (GO) and pathway enrichment analysis were conducted by Gene Set Enrichment Analysis software and DAVID tool, respectively. Totally, 27 differently expressed genes were identified for NOFH. Comparing the gene expression profiles of NOFH cartilage and OA cartilage detected 8 common differently expressed genes, including COL5A1, OGN, ANGPTL4, CRIP1, NFIL3, METRNL, ID2 and STEAP1. GO comparative analysis identified 10 common significant GO terms, mainly implicated in apoptosis and development process. Pathway comparative analysis observed that ECM-receptor interaction pathway and focal adhesion pathway were enriched in the differently expressed genes of both NOFH and hip OA. In conclusion, we identified a set of differently expressed genes, GO and pathways for NOFH articular destruction, some of which were also involved in the hip OA. Our study results may help to reveal the pathogenetic similarities and differences of cartilage damage of NOFH and hip OA. Copyright © 2016 Elsevier B.V. All rights reserved.
NCBI GEO: archive for high-throughput functional genomic data.
Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Edgar, Ron
2009-01-01
The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as 'Minimum Information About a Microarray Experiment' (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.
NCBI GEO: mining millions of expression profiles--database and tools.
Barrett, Tanya; Suzek, Tugba O; Troup, Dennis B; Wilhite, Stephen E; Ngau, Wing-Chi; Ledoux, Pierre; Rudnev, Dmitry; Lash, Alex E; Fujibuchi, Wataru; Edgar, Ron
2005-01-01
The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
Overcoming confounded controls in the analysis of gene expression data from microarray experiments.
Bhattacharya, Soumyaroop; Long, Dang; Lyons-Weiler, James
2003-01-01
A potential limitation of data from microarray experiments exists when improper control samples are used. In cancer research, comparisons of tumour expression profiles to those from normal samples is challenging due to tissue heterogeneity (mixed cell populations). A specific example exists in a published colon cancer dataset, in which tissue heterogeneity was reported among the normal samples. In this paper, we show how to overcome or avoid the problem of using normal samples that do not derive from the same tissue of origin as the tumour. We advocate an exploratory unsupervised bootstrap analysis that can reveal unexpected and undesired, but strongly supported, clusters of samples that reflect tissue differences instead of tumour versus normal differences. All of the algorithms used in the analysis, including the maximum difference subset algorithm, unsupervised bootstrap analysis, pooled variance t-test for finding differentially expressed genes and the jackknife to reduce false positives, are incorporated into our online Gene Expression Data Analyzer ( http:// bioinformatics.upmc.edu/GE2/GEDA.html ).
Linear model for fast background subtraction in oligonucleotide microarrays.
Kroll, K Myriam; Barkema, Gerard T; Carlon, Enrico
2009-11-16
One important preprocessing step in the analysis of microarray data is background subtraction. In high-density oligonucleotide arrays this is recognized as a crucial step for the global performance of the data analysis from raw intensities to expression values. We propose here an algorithm for background estimation based on a model in which the cost function is quadratic in a set of fitting parameters such that minimization can be performed through linear algebra. The model incorporates two effects: 1) Correlated intensities between neighboring features in the chip and 2) sequence-dependent affinities for non-specific hybridization fitted by an extended nearest-neighbor model. The algorithm has been tested on 360 GeneChips from publicly available data of recent expression experiments. The algorithm is fast and accurate. Strong correlations between the fitted values for different experiments as well as between the free-energy parameters and their counterparts in aqueous solution indicate that the model captures a significant part of the underlying physical chemistry.
Fast gene ontology based clustering for microarray experiments.
Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa
2008-11-21
Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.
Probabilistic segmentation and intensity estimation for microarray images.
Gottardo, Raphael; Besag, Julian; Stephens, Matthew; Murua, Alejandro
2006-01-01
We describe a probabilistic approach to simultaneous image segmentation and intensity estimation for complementary DNA microarray experiments. The approach overcomes several limitations of existing methods. In particular, it (a) uses a flexible Markov random field approach to segmentation that allows for a wider range of spot shapes than existing methods, including relatively common 'doughnut-shaped' spots; (b) models the image directly as background plus hybridization intensity, and estimates the two quantities simultaneously, avoiding the common logical error that estimates of foreground may be less than those of the corresponding background if the two are estimated separately; and (c) uses a probabilistic modeling approach to simultaneously perform segmentation and intensity estimation, and to compute spot quality measures. We describe two approaches to parameter estimation: a fast algorithm, based on the expectation-maximization and the iterated conditional modes algorithms, and a fully Bayesian framework. These approaches produce comparable results, and both appear to offer some advantages over other methods. We use an HIV experiment to compare our approach to two commercial software products: Spot and Arrayvision.
Kerr, Kathleen F; Serikawa, Kyle A; Wei, Caimiao; Peters, Mette A; Bumgarner, Roger E
2007-01-01
The reference design is a practical and popular choice for microarray studies using two-color platforms. In the reference design, the reference RNA uses half of all array resources, leading investigators to ask: What is the best reference RNA? We propose a novel method for evaluating reference RNAs and present the results of an experiment that was specially designed to evaluate three common choices of reference RNA. We found no compelling evidence in favor of any particular reference. In particular, a commercial reference showed no advantage in our data. Our experimental design also enabled a new way to test the effectiveness of pre-processing methods for two-color arrays. Our results favor using intensity normalization and foregoing background subtraction. Finally, we evaluate the sensitivity and specificity of data quality filters, and we propose a new filter that can be applied to any experimental design and does not rely on replicate hybridizations.
RNA sequencing: current and prospective uses in metabolic research.
Vikman, Petter; Fadista, Joao; Oskolkov, Nikolay
2014-10-01
Previous global RNA analysis was restricted to known transcripts in species with a defined transcriptome. Next generation sequencing has transformed transcriptomics by making it possible to analyse expressed genes with an exon level resolution from any tissue in any species without any a priori knowledge of which genes that are being expressed, splice patterns or their nucleotide sequence. In addition, RNA sequencing is a more sensitive technique compared with microarrays with a larger dynamic range, and it also allows for investigation of imprinting and allele-specific expression. This can be done for a cost that is able to compete with that of a microarray, making RNA sequencing a technique available to most researchers. Therefore RNA sequencing has recently become the state of the art with regards to large-scale RNA investigations and has to a large extent replaced microarrays. The only drawback is the large data amounts produced, which together with the complexity of the data can make a researcher spend far more time on analysis than performing the actual experiment. © 2014 Society for Endocrinology.
Development of an electro-responsive platform for the controlled transfection of mammalian cells
NASA Astrophysics Data System (ADS)
Hook, Andrew L.; Thissen, Helmut W.; Hayes, Jason P.; Voelcker, Nicolas H.
2005-02-01
The recent development of living microarrays as novel tools for the analysis of gene expression in an in-situ environment promises to unravel gene function within living organisms. In order to significantly enhance microarray performance, we are working towards electro-responsive DNA transfection chips. This study focuses on the control of DNA adsorption and desorption by appropriate surface modification of highly doped p++ silicon. Silicon was modified by plasma polymerisation of allylamine (ALAPP), a non-toxic surface that sustains cell growth. Subsequent high surface density grafting of poly(ethylene oxide) formed a layer resistant to biomolecule adsorption and cell attachment. Spatially controlled excimer laser ablation of the surface produced micron resolution patterns of re-exposed plasma polymer whilst the rest of the surface remained non-fouling. We observed electro-stimulated preferential adsorption of DNA to the ALAPP surface and subsequent desorption by the application of a negative bias. Cell culture experiments with HEK 293 cells demonstrated efficient and controlled transfection of cells using the expression of green fluorescent protein as a reporter. Thus, these chemically patterned surfaces are promising platforms for use as living microarrays.
SoFoCles: feature filtering for microarray classification based on gene ontology.
Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A
2010-02-01
Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Katika, Madhumohan R.; Department of Health Risk Analysis and Toxicology, Maastricht University; Netherlands Toxicogenomics Centre
Deoxynivalenol (DON) or vomitoxin is a commonly encountered type-B trichothecene mycotoxin, produced by Fusarium species predominantly found in cereals and grains. DON is known to exert toxic effects on the gastrointestinal, reproductive and neuroendocrine systems, and particularly on the immune system. Depending on dose and exposure time, it can either stimulate or suppress immune function. The main objective of this study was to obtain a deeper insight into DON-induced effects on lymphoid cells. For this, we exposed the human T-lymphocyte cell line Jurkat and human peripheral blood mononuclear cells (PBMCs) to various concentrations of DON for various times and examinedmore » gene expression changes by DNA microarray analysis. Jurkat cells were exposed to 0.25 and 0.5 μM DON for 3, 6 and 24 h. Biological interpretation of the microarray data indicated that DON affects various processes in these cells: It upregulates genes involved in ribosome structure and function, RNA/protein synthesis and processing, endoplasmic reticulum (ER) stress, calcium-mediated signaling, mitochondrial function, oxidative stress, the NFAT and NF-κB/TNF-α pathways, T cell activation and apoptosis. The effects of DON on the expression of genes involved in ER stress, NFAT activation and apoptosis were confirmed by qRT-PCR. Other biochemical experiments confirmed that DON activates calcium-dependent proteins such as calcineurin and M-calpain that are known to be involved in T cell activation and apoptosis. Induction of T cell activation was also confirmed by demonstrating that DON activates NFATC1 and induces its translocation from the cytoplasm to the nucleus. For the gene expression profiling of PBMCs, cells were exposed to 2 and 4 μM DON for 6 and 24 h. Comparison of the Jurkat microarray data with those obtained with PBMCs showed that most of the processes affected by DON in the Jurkat cell line were also affected in the PBMCs. -- Highlights: ► The human T cell line Jurkat and human PBMCs were exposed to DON. ► Whole-genome microarray experiments were performed. ► Microarray data indicates that DON affects ribosome and RNA/protein synthesis. ► DON treatment induces ER stress, calcium mediated signaling, NFAT and NF-κB. ► Exposure to DON induces T cell activation, oxidative stress and apoptosis.« less
caCORRECT2: Improving the accuracy and reliability of microarray data in the presence of artifacts
2011-01-01
Background In previous work, we reported the development of caCORRECT, a novel microarray quality control system built to identify and correct spatial artifacts commonly found on Affymetrix arrays. We have made recent improvements to caCORRECT, including the development of a model-based data-replacement strategy and integration with typical microarray workflows via caCORRECT's web portal and caBIG grid services. In this report, we demonstrate that caCORRECT improves the reproducibility and reliability of experimental results across several common Affymetrix microarray platforms. caCORRECT represents an advance over state-of-art quality control methods such as Harshlighting, and acts to improve gene expression calculation techniques such as PLIER, RMA and MAS5.0, because it incorporates spatial information into outlier detection as well as outlier information into probe normalization. The ability of caCORRECT to recover accurate gene expressions from low quality probe intensity data is assessed using a combination of real and synthetic artifacts with PCR follow-up confirmation and the affycomp spike in data. The caCORRECT tool can be accessed at the website: http://cacorrect.bme.gatech.edu. Results We demonstrate that (1) caCORRECT's artifact-aware normalization avoids the undesirable global data warping that happens when any damaged chips are processed without caCORRECT; (2) When used upstream of RMA, PLIER, or MAS5.0, the data imputation of caCORRECT generally improves the accuracy of microarray gene expression in the presence of artifacts more than using Harshlighting or not using any quality control; (3) Biomarkers selected from artifactual microarray data which have undergone the quality control procedures of caCORRECT are more likely to be reliable, as shown by both spike in and PCR validation experiments. Finally, we present a case study of the use of caCORRECT to reliably identify biomarkers for renal cell carcinoma, yielding two diagnostic biomarkers with potential clinical utility, PRKAB1 and NNMT. Conclusions caCORRECT is shown to improve the accuracy of gene expression, and the reproducibility of experimental results in clinical application. This study suggests that caCORRECT will be useful to clean up possible artifacts in new as well as archived microarray data. PMID:21957981
2012-01-01
Background DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin. Results For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform. Conclusions To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These two factors are sequence dependent and have a large impact on probe intensity. The results presented here provide novel insight into the effect of probe synthesis errors on Affymetrix microarrays; furthermore, the algorithms developed in this work provide useful tools for the analysis of cross-hybridization, probe synthesis efficiency, fragmentation, wash stringency, temperature, and salt concentration on microarray intensities. PMID:23270536
2011-01-01
Background Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. Results The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. Conclusion We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research. PMID:21208403
DNA microarray unravels rapid changes in transcriptome of MK-801 treated rat brain
Kobayashi, Yuka; Kulikova, Sofya P; Shibato, Junko; Rakwal, Randeep; Satoh, Hiroyuki; Pinault, Didier; Masuo, Yoshinori
2015-01-01
AIM: To investigate the impact of MK-801 on gene expression patterns genome wide in rat brain regions. METHODS: Rats were treated with an intraperitoneal injection of MK-801 [0.08 (low-dose) and 0.16 (high-dose) mg/kg] or NaCl (vehicle control). In a first series of experiment, the frontoparietal electrocorticogram was recorded 15 min before and 60 min after injection. In a second series of experiments, the whole brain of each animal was rapidly removed at 40 min post-injection, and different regions were separated: amygdala, cerebral cortex, hippocampus, hypothalamus, midbrain and ventral striatum on ice followed by DNA microarray (4 × 44 K whole rat genome chip) analysis. RESULTS: Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline gamma frequency (30-80 Hz) oscillations in the frontoparietal electroencephalogram. DNA microarray analysis showed the largest number (up- and down- regulations) of gene expressions in the cerebral cortex (378), midbrain (376), hippocampus (375), ventral striatum (353), amygdala (301), and hypothalamus (201) under low-dose (0.08 mg/kg) of MK-801. Under high-dose (0.16 mg/kg), ventral striatum (811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region. CONCLUSION: Acute MK-801 treatment increases synchrony of baseline gamma oscillations, and causes very early changes in gene expressions in six individual rat brain regions, a first report. PMID:26629322
Privat, Isabelle; Bardil, Amélie; Gomez, Aureliano Bombarely; Severac, Dany; Dantec, Christelle; Fuentes, Ivanna; Mueller, Lukas; Joët, Thierry; Pot, David; Foucrier, Séverine; Dussert, Stéphane; Leroy, Thierry; Journot, Laurent; de Kochko, Alexandre; Campa, Claudine; Combes, Marie-Christine; Lashermes, Philippe; Bertrand, Benoit
2011-01-05
Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research.
2008 Microarray Research Group (MARG Survey): Sensing the State of Microarray Technology
Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution and transformation, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. Th...
ERIC Educational Resources Information Center
Sheng, Xiumei; Xu, Shungao; Lu, Renyun; Isaac, Dadzie; Zhang, Xueyi; Zhang, Haifang; Wang, Huifang; Qiao, Zheng; Huang, Xinxiang
2014-01-01
Scientific experiments are indispensable parts of Biochemistry and Molecular Biology. In this study, a comprehensive Biochemistry and Molecular Biology experiment about "Salmonella enterica" serovar Typhi Flagellar phase variation has been designed. It consisted of three parts, namely, inducement of bacterial Flagellar phase variation,…
An Ribonuclease T2 Family Protein Modulates Acinetobacter baumannii Abiotic Surface Colonization
Jacobs, Anna C.; Blanchard, Catlyn E.; Catherman, Seana C.; Dunman, Paul M.; Murata, Yoshihiko
2014-01-01
Acinetobacter baumannii is an emerging bacterial pathogen of considerable medical concern. The organism's transmission and ability to cause disease has been associated with its propensity to colonize and form biofilms on abiotic surfaces in health care settings. To better understand the genetic determinants that affect biomaterial attachment, we performed a transposon mutagenesis analysis of abiotic surface-colonization using A. baumannii strain 98-37-09. Disruption of an RNase T2 family gene was found to limit the organism's ability to colonize polystyrene, polypropylene, glass, and stainless steel surfaces. DNA microarray analyses revealed that in comparison to wild type and complemented cells, the RNase T2 family mutant exhibited reduced expression of 29 genes, 15 of which are predicted to be associated with bacterial attachment and surface-associated motility. Motility assays confirmed that RNase T2 mutant displays a severe motility defect. Taken together, our results indicate that the RNase T2 family protein identified in this study is a positive regulator of A. baumannii's ability to colonize inanimate surfaces and motility. Moreover, the enzyme may be an effective target for the intervention of biomaterial colonization, and consequently limit the organism's transmission within the hospital setting. PMID:24489668
Toward a Genome-Wide Systems Biology Analysis of Host-Pathogen Interactions in Group A Streptococcus
Musser, James M.; DeLeo, Frank R.
2005-01-01
Genome-wide analysis of microbial pathogens and molecular pathogenesis processes has become an area of considerable activity in the last 5 years. These studies have been made possible by several advances, including completion of the human genome sequence, publication of genome sequences for many human pathogens, development of microarray technology and high-throughput proteomics, and maturation of bioinformatics. Despite these advances, relatively little effort has been expended in the bacterial pathogenesis arena to develop and use integrated research platforms in a systems biology approach to enhance our understanding of disease processes. This review discusses progress made in exploiting an integrated genome-wide research platform to gain new knowledge about how the human bacterial pathogen group A Streptococcus causes disease. Results of these studies have provided many new avenues for basic pathogenesis research and translational research focused on development of an efficacious human vaccine and novel therapeutics. One goal in summarizing this line of study is to bring exciting new findings to the attention of the investigative pathology community. In addition, we hope the review will stimulate investigators to consider using analogous approaches for analysis of the molecular pathogenesis of other microbes. PMID:16314461
Promyelocytic Leukemia Protein (PML) Controls Listeria monocytogenes Infection
Ribet, David; Lallemand-Breitenbach, Valérie; Ferhi, Omar; Nahori, Marie-Anne; Varet, Hugo
2017-01-01
ABSTRACT The promyelocytic leukemia protein (PML) is the main organizer of stress-responsive subnuclear structures called PML nuclear bodies. These structures recruit multiple interactors and modulate their abundance or their posttranslational modifications, notably by the SUMO ubiquitin-like modifiers. The involvement of PML in antiviral responses is well established. In contrast, the role of PML in bacterial infection remains poorly characterized. Here, we show that PML restricts infection by the pathogenic bacterium Listeria monocytogenes but not by Salmonella enterica serovar Typhimurium. During infection, PML undergoes oxidation-mediated multimerization, associates with the nuclear matrix, and becomes de-SUMOylated due to the pore-forming activity of the Listeria toxin listeriolysin O (LLO). These events trigger an antibacterial response that is not observed during in vitro infection by an LLO-defective Listeria mutant, but which can be phenocopied by specific induction of PML de-SUMOylation. Using transcriptomic and proteomic microarrays, we also characterized a network of immunity genes and cytokines, which are regulated by PML in response to Listeria infection but independently from the listeriolysin O toxin. Our study thus highlights two mechanistically distinct complementary roles of PML in host responses against bacterial infection. PMID:28074026
Yergeau, Etienne; Bokhorst, Stef; Kang, Sanghoon; Zhou, Jizhong; Greer, Charles W; Aerts, Rien; Kowalchuk, George A
2012-01-01
Because of severe abiotic limitations, Antarctic soils represent simplified systems, where microorganisms are the principal drivers of nutrient cycling. This relative simplicity makes these ecosystems particularly vulnerable to perturbations, like global warming, and the Antarctic Peninsula is among the most rapidly warming regions on the planet. However, the consequences of the ongoing warming of Antarctica on microorganisms and the processes they mediate are unknown. Here, using 16S rRNA gene pyrosequencing and qPCR, we report highly consistent responses in microbial communities across disparate sub-Antarctic and Antarctic environments in response to 3 years of experimental field warming (+0.5 to 2 °C). Specifically, we found significant increases in the abundance of fungi and bacteria and in the Alphaproteobacteria-to-Acidobacteria ratio, which could result in an increase in soil respiration. Furthermore, shifts toward generalist bacterial communities following warming weakened the linkage between the bacterial taxonomic and functional richness. GeoChip microarray analyses also revealed significant warming effects on functional communities, specifically in the N-cycling microorganisms. Our results demonstrate that soil microorganisms across a range of sub-Antarctic and Antarctic environments can respond consistently and rapidly to increasing temperatures. PMID:21938020
Kumaresan, Deepak; Stralis-Pavese, Nancy; Abell, Guy C J; Bodrossy, Levente; Murrell, J Colin
2011-10-01
Aggregates of different sizes and stability in soil create a composite of ecological niches differing in terms of physico-chemical and structural characteristics. The aim of this study was to identify, using DNA-SIP and mRNA-based microarray analysis, whether shifts in activity and community composition of methanotrophs occur when ecological niches created by soil structure are physically perturbed. Landfill cover soil was subject to three treatments termed: 'control' (minimal structural disruption), 'sieved' (sieved soil using 2 mm mesh) and 'ground' (grinding using mortar and pestle). 'Sieved' and 'ground' soil treatments exhibited higher methane oxidation potentials compared with the 'control' soil treatment. Analysis of the active community composition revealed an effect of physical disruption on active methanotrophs. Type I methanotrophs were the most active methanotrophs in 'sieved' and 'ground' soil treatments, whereas both Type I and Type II methanotrophs were active in the 'control' soil treatment. The result emphasize that changes to a particular ecological niche may not result in an immediate change to the active bacterial composition and change in composition will depend on the ability of the bacterial communities to respond to the perturbation. © 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.
Consequences of reductive evolution for gene expression in an obligate endosymbiont.
Wilcox, Jennifer L; Dunbar, Helen E; Wolfinger, Russell D; Moran, Nancy A
2003-06-01
The smallest cellular genomes are found in obligate symbiotic and pathogenic bacteria living within eukaryotic hosts. In comparison with large genomes of free-living relatives, these reduced genomes are rearranged and have lost most regulatory elements. To test whether reduced bacterial genomes incur reduced regulatory capacities, we used full-genome microarrays to evaluate transcriptional response to environmental stress in Buchnera aphidicola, the obligate endosymbiont of aphids. The 580 genes of the B. aphidicola genome represent a subset of the 4500 genes known from the related organism, Escherichia coli. Although over 20 orthologues of E. coli heat stress (HS) genes are retained by B. aphidicola, only five were differentially expressed after near-lethal heat stress treatments, and only modest shifts were observed. Analyses of upstream regulatory regions revealed loss or degradation of most HS (sigma32) promoters. Genomic rearrangements downstream of an intact HS promoter yielded upregulation of a functionally unrelated and an inactivated gene. Reanalyses of comparable experimental array data for E. coli and Bacillus subtilis revealed that genome-wide differential expression was significantly lower in B. aphidicola. Our demonstration of a diminished stress response validates reports of temperature sensitivity in B. aphidicola and suggests that this reduced bacterial genome exhibits transcriptional inflexibility.
Hou, Z; Fink, R C; Black, E P; Sugawara, M; Zhang, Z; Diez-Gonzalez, F; Sadowsky, M J
2012-11-01
The objective of this study was to examine transcriptional changes in Escherichia coli when the bacterium was growing in the lettuce rhizoshpere. A combination of microarray analyses, colonization assays and confocal microscopy was used to gain a more complete understanding of bacterial genes involved in the colonization and growth of E. coli K12 in the lettuce root rhizosphere using a novel hydroponic assay system. After 3 days of interaction with lettuce roots, E. coli genes involved in protein synthesis, stress responses and attachment were up-regulated. Mutants in curli production (crl, csgA) and flagella synthesis (fliN) had a reduced capacity to attach to roots as determined by bacterial counts and by confocal laser scanning microscopy. This study indicates that E. coli K12 has the capability to colonize lettuce roots by using attachment genes and can readily adapt to the rhizosphere of lettuce plants. Results of this study show curli production and biofilm modulation genes are important for rhizosphere colonization and may provide useful targets to disrupt this process. Further studies using pathogenic strains will provide additional information about lettuce-E. coli interactions. © 2012 The Authors Journal of Applied Microbiology © 2012 The Society for Applied Microbiology.
THE ABRF-MARG MICROARRAY SURVEY 2004: TAKING THE PULSE OF THE MICROARRAY FIELD
Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. The goal of the surve...
Contributions to Statistical Problems Related to Microarray Data
ERIC Educational Resources Information Center
Hong, Feng
2009-01-01
Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…
NASA Astrophysics Data System (ADS)
Bogdanov, Valery L.; Boyce-Jacino, Michael
1999-05-01
Confined arrays of biochemical probes deposited on a solid support surface (analytical microarray or 'chip') provide an opportunity to analysis multiple reactions simultaneously. Microarrays are increasingly used in genetics, medicine and environment scanning as research and analytical instruments. A power of microarray technology comes from its parallelism which grows with array miniaturization, minimization of reagent volume per reaction site and reaction multiplexing. An optical detector of microarray signals should combine high sensitivity, spatial and spectral resolution. Additionally, low-cost and a high processing rate are needed to transfer microarray technology into biomedical practice. We designed an imager that provides confocal and complete spectrum detection of entire fluorescently-labeled microarray in parallel. Imager uses microlens array, non-slit spectral decomposer, and high- sensitive detector (cooled CCD). Two imaging channels provide a simultaneous detection of localization, integrated and spectral intensities for each reaction site in microarray. A dimensional matching between microarray and imager's optics eliminates all in moving parts in instrumentation, enabling highly informative, fast and low-cost microarray detection. We report theory of confocal hyperspectral imaging with microlenses array and experimental data for implementation of developed imager to detect fluorescently labeled microarray with a density approximately 103 sites per cm2.
Lubiprostone ameliorates the cystic fibrosis mouse intestinal phenotype.
De Lisle, Robert C; Mueller, Racquel; Roach, Eileen
2010-09-15
Cystic fibrosis (CF) is caused by mutations in the CFTR gene that impair the function of CFTR, a cAMP-regulated anion channel. In the small intestine loss of CFTR function creates a dehydrated, acidic luminal environment which is believed to cause an accumulation of mucus, a phenotype characteristic of CF. CF mice have small intestinal bacterial overgrowth, an altered innate immune response, and impaired intestinal transit. We investigated whether lubiprostone, which can activate the CLC2 Cl- channel, would improve the intestinal phenotype in CF mice. Cftr(tm1UNC) (CF) and wildtype (WT) littermate mice on the C57BL/6J background were used. Lubiprostone (10 μg/kg-day) was administered by gavage for two weeks. Mucus accumulation was estimated from crypt lumen widths in periodic acid-Schiff base, Alcian blue stained sections. Luminal bacterial load was measured by qPCR for the bacterial 16S gene. Gastric emptying and small intestinal transit in fasted mice were assessed using gavaged rhodamine dextran. Gene expression was evaluated by Affymetrix Mouse430 2.0 microarray and qRT-PCR. Crypt width in control CF mice was 700% that of WT mice (P < 0.001). Lubiprostone did not affect WT crypt width but, unexpectedly, increased CF crypt width 22% (P = 0.001). Lubiprostone increased bacterial load in WT mice to 490% of WT control levels (P = 0.008). Conversely, lubiprostone decreased bacterial overgrowth in CF mice by 60% (P = 0.005). Lubiprostone increased gastric emptying at 20 min postgavage in both WT (P < 0.001) and CF mice (P < 0.001). Lubiprostone enhanced small intestinal transit in WT mice (P = 0.024) but not in CF mice (P = 0.377). Among other innate immune markers, expression of mast cell genes was elevated 4-to 40-fold in the CF intestine as compared to WT, and lubiprostone treatment of CF mice decreased expression to WT control levels. These results indicate that lubiprostone has some benefits for the CF intestinal phenotype, especially on bacterial overgrowth and the innate immune response. The unexpected observation of increased mucus accumulation in the crypts of lubiprostone-treated CF mice suggests the possibility that lubiprostone increases mucus secretion.
Lubiprostone ameliorates the cystic fibrosis mouse intestinal phenotype
2010-01-01
Background Cystic fibrosis (CF) is caused by mutations in the CFTR gene that impair the function of CFTR, a cAMP-regulated anion channel. In the small intestine loss of CFTR function creates a dehydrated, acidic luminal environment which is believed to cause an accumulation of mucus, a phenotype characteristic of CF. CF mice have small intestinal bacterial overgrowth, an altered innate immune response, and impaired intestinal transit. We investigated whether lubiprostone, which can activate the CLC2 Cl- channel, would improve the intestinal phenotype in CF mice. Methods Cftrtm1UNC (CF) and wildtype (WT) littermate mice on the C57BL/6J background were used. Lubiprostone (10 μg/kg-day) was administered by gavage for two weeks. Mucus accumulation was estimated from crypt lumen widths in periodic acid-Schiff base, Alcian blue stained sections. Luminal bacterial load was measured by qPCR for the bacterial 16S gene. Gastric emptying and small intestinal transit in fasted mice were assessed using gavaged rhodamine dextran. Gene expression was evaluated by Affymetrix Mouse430 2.0 microarray and qRT-PCR. Results Crypt width in control CF mice was 700% that of WT mice (P < 0.001). Lubiprostone did not affect WT crypt width but, unexpectedly, increased CF crypt width 22% (P = 0.001). Lubiprostone increased bacterial load in WT mice to 490% of WT control levels (P = 0.008). Conversely, lubiprostone decreased bacterial overgrowth in CF mice by 60% (P = 0.005). Lubiprostone increased gastric emptying at 20 min postgavage in both WT (P < 0.001) and CF mice (P < 0.001). Lubiprostone enhanced small intestinal transit in WT mice (P = 0.024) but not in CF mice (P = 0.377). Among other innate immune markers, expression of mast cell genes was elevated 4-to 40-fold in the CF intestine as compared to WT, and lubiprostone treatment of CF mice decreased expression to WT control levels. Conclusions These results indicate that lubiprostone has some benefits for the CF intestinal phenotype, especially on bacterial overgrowth and the innate immune response. The unexpected observation of increased mucus accumulation in the crypts of lubiprostone-treated CF mice suggests the possibility that lubiprostone increases mucus secretion. PMID:20843337
Wong, Hector R; Cvijanovich, Natalie Z; Hall, Mark; Allen, Geoffrey L; Thomas, Neal J; Freishtat, Robert J; Anas, Nick; Meyer, Keith; Checchia, Paul A; Lin, Richard; Bigham, Michael T; Sen, Anita; Nowak, Jeffrey; Quasney, Michael; Henricksen, Jared W; Chopra, Arun; Banschbach, Sharon; Beckman, Eileen; Harmon, Kelli; Lahni, Patrick; Shanley, Thomas P
2012-10-29
Differentiating between sterile inflammation and bacterial infection in critically ill patients with fever and other signs of the systemic inflammatory response syndrome (SIRS) remains a clinical challenge. The objective of our study was to mine an existing genome-wide expression database for the discovery of candidate diagnostic biomarkers to predict the presence of bacterial infection in critically ill children. Genome-wide expression data were compared between patients with SIRS having negative bacterial cultures (n = 21) and patients with sepsis having positive bacterial cultures (n = 60). Differentially expressed genes were subjected to a leave-one-out cross-validation (LOOCV) procedure to predict SIRS or sepsis classes. Serum concentrations of interleukin-27 (IL-27) and procalcitonin (PCT) were compared between 101 patients with SIRS and 130 patients with sepsis. All data represent the first 24 hours of meeting criteria for either SIRS or sepsis. Two hundred twenty one gene probes were differentially regulated between patients with SIRS and patients with sepsis. The LOOCV procedure correctly predicted 86% of the SIRS and sepsis classes, and Epstein-Barr virus-induced gene 3 (EBI3) had the highest predictive strength. Computer-assisted image analyses of gene-expression mosaics were able to predict infection with a specificity of 90% and a positive predictive value of 94%. Because EBI3 is a subunit of the heterodimeric cytokine, IL-27, we tested the ability of serum IL-27 protein concentrations to predict infection. At a cut-point value of ≥5 ng/ml, serum IL-27 protein concentrations predicted infection with a specificity and a positive predictive value of >90%, and the overall performance of IL-27 was generally better than that of PCT. A decision tree combining IL-27 and PCT improved overall predictive capacity compared with that of either biomarker alone. Genome-wide expression analysis has provided the foundation for the identification of IL-27 as a novel candidate diagnostic biomarker for predicting bacterial infection in critically ill children. Additional studies will be required to test further the diagnostic performance of IL-27. The microarray data reported in this article have been deposited in the Gene Expression Omnibus under accession number GSE4607.
Hernandez-Sanabria, Emma; Slomka, Vera; Herrero, Esteban R.; Kerckhof, Frederiek-Maarten; Zaidel, Lynette; Teughels, Wim; Boon, Nico
2017-01-01
Understanding the driving forces behind the shifts in the ecological balance of the oral microbiota will become essential for the future management and treatment of periodontitis. As the use of competitive approaches for modulating bacterial outgrowth is unexplored in the oral ecosystem, our study aimed to investigate both the associations among groups of functional compounds and the impact of individual substrates on selected members of the oral microbiome. We employed the Phenotype Microarray high-throughput technology to analyse the microbial cellular phenotypes of 15 oral bacteria. Multivariate statistical analysis was used to detect respiratory activity triggers and to assess similar metabolic activities. Carbon and nitrogen were relevant for the respiration of health-associated bacteria, explaining competitive interactions when grown in biofilms. Carbon, nitrogen, and peptides tended to decrease the respiratory activity of all pathobionts, but not significantly. None of the evaluated compounds significantly increased activity of pathobionts at both 24 and 48 h. Additionally, metabolite requirements of pathobionts were dissimilar, suggesting that collective modulation of their respiratory activity may be challenging. Flow cytometry indicated that the metabolic activity detected in the Biolog plates may not be a direct result of the number of bacterial cells. In addition, damage to the cell membrane may not influence overall respiratory activity. Our methodology confirmed previously reported competitive and collaborative interactions among bacterial groups, which could be used either as marker of health status or as targets for modulation of the oral environment. PMID:28638806
Metabolic sensor governing bacterial virulence in Staphylococcus aureus.
Ding, Yue; Liu, Xing; Chen, Feifei; Di, Hongxia; Xu, Bin; Zhou, Lu; Deng, Xin; Wu, Min; Yang, Cai-Guang; Lan, Lefu
2014-11-18
An effective metabolism is essential to all living organisms, including the important human pathogen Staphylococcus aureus. To establish successful infection, S. aureus must scavenge nutrients and coordinate its metabolism for proliferation. Meanwhile, it also must produce an array of virulence factors to interfere with host defenses. However, the ways in which S. aureus ties its metabolic state to its virulence regulation remain largely unknown. Here we show that citrate, the first intermediate of the tricarboxylic acid (TCA) cycle, binds to and activates the catabolite control protein E (CcpE) of S. aureus. Using structural and site-directed mutagenesis studies, we demonstrate that two arginine residues (Arg145 and Arg256) within the putative inducer-binding cavity of CcpE are important for its allosteric activation by citrate. Microarray analysis reveals that CcpE tunes the expression of 126 genes that comprise about 4.7% of the S. aureus genome. Intriguingly, although CcpE is a major positive regulator of the TCA-cycle activity, its regulon consists predominantly of genes involved in the pathogenesis of S. aureus. Moreover, inactivation of CcpE results in increased staphyloxanthin production, improved ability to acquire iron, increased resistance to whole-blood-mediated killing, and enhanced bacterial virulence in a mouse model of systemic infection. This study reveals CcpE as an important metabolic sensor that allows S. aureus to sense and adjust its metabolic state and subsequently to coordinate the expression of virulence factors and bacterial virulence.
Field, Erin K.; D'Imperio, Seth; Miller, Amber R.; VanEngelen, Michael R.; Gerlach, Robin; Lee, Brady D.; Apel, William A.; Peyton, Brent M.
2010-01-01
Low-level-radioactive-waste (low-level-waste) sites, including those at various U.S. Department of Energy sites, frequently contain cellulosic waste in the form of paper towels, cardboard boxes, or wood contaminated with heavy metals and radionuclides such as chromium and uranium. To understand how the soil microbial community is influenced by the presence of cellulosic waste products, multiple soil samples were obtained from a nonradioactive model low-level-waste test pit at the Idaho National Laboratory. Samples were analyzed using 16S rRNA gene clone libraries and 16S rRNA gene microarray (PhyloChip) analyses. Both methods revealed changes in the bacterial community structure with depth. In all samples, the PhyloChip detected significantly more operational taxonomic units, and therefore relative diversity, than the clone libraries. Diversity indices suggest that diversity is lowest in the fill and fill-waste interface (FW) layers and greater in the wood waste and waste-clay interface layers. Principal-coordinate analysis and lineage-specific analysis determined that the Bacteroidetes and Actinobacteria phyla account for most of the significant differences observed between the layers. The decreased diversity in the FW layer and increased members of families containing known cellulose-degrading microorganisms suggest that the FW layer is an enrichment environment for these organisms. These results suggest that the presence of the cellulosic material significantly influences the bacterial community structure in a stratified soil system. PMID:20305022
Ghosh, S B; Bhattacharya, K; Nayak, S; Mukherjee, P; Salaskar, D; Kale, S P
2015-09-05
Definitive identification of microorganisms, including pathogenic and non-pathogenic bacteria, is extremely important for a wide variety of applications including food safety, environmental studies, bio-terrorism threats, microbial forensics, criminal investigations and above all disease diagnosis. Although extremely powerful techniques such as those based on PCR and microarrays exist, they require sophisticated laboratory facilities along with elaborate sample preparation by trained researchers. Among different spectroscopic techniques, FTIR was used in the 1980s and 90s for bacterial identification. In the present study five species of Bacillus were isolated from the aerobic predigester chamber of Nisargruna Biogas Plant (NBP) and were identified to the species level by biochemical and molecular biological (16S ribosomal DNA sequence) methods. Those organisms were further checked by solid state spectroscopic absorbance measurements using a wide range of electromagnetic radiation (wavelength 200 nm to 25,000 nm) encompassing UV, visible, near Infrared and Infrared regions. UV-Vis and NIR spectroscopy was performed on dried bacterial cell suspension on silicon wafer in specular mode while FTIR was performed on KBr pellets containing the bacterial cells. Consistent and reproducible species specific spectra were obtained and sensitivity up to a level of 1000 cells was observed in FTIR with a DTGS detector. This clearly shows the potential of solid state spectroscopic techniques for simple, easy to implement, reliable and sensitive detection of bacteria from environmental samples. Copyright © 2015 Elsevier B.V. All rights reserved.
Prideaux, Lani; Kang, Seungha; Wagner, Josef; Buckley, Michael; Mahar, Jackie E; De Cruz, Peter; Wen, Zhonghui; Chen, Liping; Xia, Bing; van Langenberg, Daniel R; Lockett, Trevor; Ng, Siew C; Sung, Joseph J Y; Desmond, Paul; McSweeney, Chris; Morrison, Mark; Kirkwood, Carl D; Kamm, Michael A
2013-12-01
The gut microbiota is central to health and disorders such as inflammatory bowel disease. Differences in microbiota related to geography and ethnicity may hold the key to recent changes in the incidence of microbiota-related disorders. Gut mucosal microbiota was analyzed in 190 samples from 87 Caucasian and Chinese subjects, from Australia and Hong Kong, comprising 22 patients with Crohn's disease, 30 patients with ulcerative colitis, 29 healthy controls, and 6 healthy relatives of patients with Crohn's disease. Bacterial 16S rRNA microarray and 454 pyrosequencing were performed. The microbiota was diverse in health, regardless of ethnicity or geography (operational taxonomic unit number and Shannon diversity index). Ethnicity and geography, however, did affect microbial composition. Crohn's disease resulted in reduced bacterial diversity, regardless of ethnicity or geography, and was the strongest determinant of composition. In ulcerative colitis, diversity was reduced in Chinese subjects only, suggesting that ethnicity is a determinant of bacterial diversity, whereas composition was determined by disease and ethnicity. Specific phylotypes were different between health and disease. Chinese patients with inflammatory bowel disease more often than healthy Chinese tended to have had a Western diet in childhood, in the East and West. The healthy microbiota is diverse but compositionally affected by geographical and ethnic factors. The microbiota is substantially altered in inflammatory bowel disease, but ethnicity may also play an important role. This may be key to the changing epidemiology in developing countries, and emigrants to the West.
Sinha, Ranjita; Gupta, Aarti; Senthil-Kumar, Muthappa
2017-01-01
Chickpea (Cicer arietinum); the second largest legume grown worldwide is prone to drought and various pathogen infections. These drought and pathogen stresses often occur concurrently in the field conditions. However, the molecular events in response to that are largely unknown. The present study examines the transcriptome dynamics in chickpea plants exposed to a combination of water-deficit stress and Ralstonia solanacearum infection. R. solanacearum is a potential wilt disease causing pathogen in chickpea. Drought stressed chickpea plants were infected with this pathogen and the plants were allowed to experience progressive drought with 2 and 4 days of R. solanacearum infection called short duration stress (SD stresses) and long duration stress (LD stresses), respectively. Our study showed that R. solanacearum multiplication decreased under SD-combined stress compared to SD-pathogen but there was no significant change in LD-combined stress compared to LD-pathogen. The microarray analysis during these conditions showed that 821 and 1039 differentially expressed genes (DEGs) were unique to SD- and LD-combined stresses, respectively, when compared with individual stress conditions. Three and fifteen genes were common among all the SD-stress treatments and LD-stress treatments, respectively. Genes involved in secondary cell wall biosynthesis, alkaloid biosynthesis, defense related proteins, and osmo-protectants were up-regulated during combined stress. The expression of genes involved in lignin and cellulose biosynthesis were specifically up-regulated in SD-combined, LD-combined, and LD-pathogen stress. A close transcriptomic association of LD-pathogen stress with SD-combined stress was observed in this study which indicates that R. solanacearum infection also exerts drought stress along with pathogen stress thus mimics combined stress effect. Furthermore the expression profiling of candidate genes using real-time quantitative PCR validated the microarray data. The study showed that down-regulation of defense-related genes during LD-combined stress resulted in an increased bacterial multiplication as compared to SD-combined stress. Overall, our study highlights a sub-set of DEGs uniquely expressed in response to combined stress, which serve as potential candidates for further functional characterization to delineate the molecular response of the plant to concurrent drought-pathogen stress. PMID:28382041
NASA Astrophysics Data System (ADS)
Reicher, Naama; Segev, Lior; Rudich, Yinon
2018-01-01
The WeIzmann Supercooled Droplets Observation on Microarray (WISDOM) is a new setup for studying ice nucleation in an array of monodisperse droplets for atmospheric implications. WISDOM combines microfluidics techniques for droplets production and a cryo-optic stage for observation and characterization of freezing events of individual droplets. This setup is designed to explore heterogeneous ice nucleation in the immersion freezing mode, down to the homogeneous freezing of water (235 K) in various cooling rates (typically 0.1-10 K min-1). It can also be used for studying homogeneous freezing of aqueous solutions in colder temperatures. Frozen fraction, ice nucleation active surface site densities and freezing kinetics can be obtained from WISDOM measurements for hundreds of individual droplets in a single freezing experiment. Calibration experiments using eutectic solutions and previously studied materials are described. WISDOM also allows repeatable cycles of cooling and heating for the same array of droplets. This paper describes the WISDOM setup, its temperature calibration, validation experiments and measurement uncertainties. Finally, application of WISDOM to study the ice nucleating particle (INP) properties of size-selected ambient Saharan dust particles is presented.