DNA Microarray for Rapid Detection and Identification of Food and Water Borne Bacteria: From Dry to Wet Lab.

PubMed

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.

Broad spectrum microarray for fingerprint-based bacterial species identification

PubMed Central

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

High-throughput screening of T7 phage display and protein microarrays as a methodological approach for the identification of IgE-reactive components.

PubMed

San Segundo-Acosta, Pablo; Garranzo-Asensio, María; Oeo-Santos, Carmen; Montero-Calle, Ana; Quiralte, Joaquín; Cuesta-Herranz, Javier; Villalba, Mayte; Barderas, Rodrigo

2018-05-01

Olive pollen and yellow mustard seeds are major allergenic sources with high clinical relevance. To aid with the identification of IgE-reactive components, the development of sensitive methodological approaches is required. Here, we have combined T7 phage display and protein microarrays for the identification of allergenic peptides and mimotopes from olive pollen and mustard seeds. The identification of these allergenic sequences involved the construction and biopanning of T7 phage display libraries of mustard seeds and olive pollen using sera from allergic patients to both biological sources together with the construction of phage microarrays printed with 1536 monoclonal phages from the third/four rounds of biopanning. The screening of the phage microarrays with individual sera from allergic patients enabled the identification of 10 and 9 IgE-reactive unique amino acid sequences from olive pollen and mustard seeds, respectively. Five immunoreactive amino acid sequences displayed on phages were selected for their expression as His6-GST tag fusion proteins and validation. After immunological characterization, we assessed the IgE-reactivity of the constructs. Our results show that protein microarrays printed with T7 phages displaying peptides from allergenic sources might be used to identify allergenic components -peptides, proteins or mimotopes- through their screening with specific IgE antibodies from allergic patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Bacterial identification and subtyping using DNA microarray and DNA sequencing.

PubMed

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.

Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

PubMed Central

2012-01-01

Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

Development of a DNA microarray for species identification of quarantine aphids.

PubMed

Lee, Won Sun; Choi, Hwalran; Kang, Jinseok; Kim, Ji-Hoon; Lee, Si Hyeock; Lee, Seunghwan; Hwang, Seung Yong

2013-12-01

Aphid pests are being brought into Korea as a result of increased crop trading. Aphids exist on growth areas of plants, and thus plant growth is seriously affected by aphid pests. However, aphids are very small and have several sexual morphs and life stages, so it is difficult to identify species on the basis of morphological features. This problem was approached using DNA microarray technology. DNA targets of the cytochrome c oxidase subunit I gene were generated with a fluorescent dye-labelled primer and were hybridised onto a DNA microarray consisting of specific probes. After analysing the signal intensity of the specific probes, the unique patterns from the DNA microarray, consisting of 47 species-specific probes, were obtained to identify 23 aphid species. To confirm the accuracy of the developed DNA microarray, ten individual blind samples were used in blind trials, and the identifications were completely consistent with the sequencing data of all individual blind samples. A microarray has been developed to distinguish aphid species. DNA microarray technology provides a rapid, easy, cost-effective and accurate method for identifying aphid species for pest control management. © 2013 Society of Chemical Industry.

Comparison of DNA Microarray, Loop-Mediated Isothermal Amplification (LAMP) and Real-Time PCR with DNA Sequencing for Identification of Fusarium spp. Obtained from Patients with Hematologic Malignancies.

PubMed

de Souza, Marcela; Matsuzawa, Tetsuhiro; Sakai, Kanae; Muraosa, Yasunori; Lyra, Luzia; Busso-Lopes, Ariane Fidelis; Levin, Anna Sara Shafferman; Schreiber, Angélica Zaninelli; Mikami, Yuzuru; Gonoi, Tohoru; Kamei, Katsuhiko; Moretti, Maria Luiza; Trabasso, Plínio

2017-08-01

The performance of three molecular biology techniques, i.e., DNA microarray, loop-mediated isothermal amplification (LAMP), and real-time PCR were compared with DNA sequencing for properly identification of 20 isolates of Fusarium spp. obtained from blood stream as etiologic agent of invasive infections in patients with hematologic malignancies. DNA microarray, LAMP and real-time PCR identified 16 (80%) out of 20 samples as Fusarium solani species complex (FSSC) and four (20%) as Fusarium spp. The agreement among the techniques was 100%. LAMP exhibited 100% specificity, while DNA microarray, LAMP and real-time PCR showed 100% sensitivity. The three techniques had 100% agreement with DNA sequencing. Sixteen isolates were identified as FSSC by sequencing, being five Fusarium keratoplasticum, nine Fusarium petroliphilum and two Fusarium solani. On the other hand, sequencing identified four isolates as Fusarium non-solani species complex (FNSSC), being three isolates as Fusarium napiforme and one isolate as Fusarium oxysporum. Finally, LAMP proved to be faster and more accessible than DNA microarray and real-time PCR, since it does not require a thermocycler. Therefore, LAMP signalizes as emerging and promising methodology to be used in routine identification of Fusarium spp. among cases of invasive fungal infections.

A DNA microarray for identification of selected Korean birds based on mitochondrial cytochrome c oxidase I gene sequences.

PubMed

Chung, In-Hyuk; Yoo, Hye Sook; Eah, Jae-Yong; Yoon, Hyun-Kyu; Jung, Jin-Wook; Hwang, Seung Yong; Kim, Chang-Bae

2010-10-01

DNA barcoding with the gene encoding cytochrome c oxidase I (COI) in the mitochondrial genome has been proposed as a standard marker to identify and discover animal species. Some migratory wild birds are suspected of transmitting avian influenza and pose a threat to aircraft safety because of bird strikes. We have previously reported the COI gene sequences of 92 Korean bird species. In the present study, we developed a DNA microarray to identify 17 selected bird species on the basis of nucleotide diversity. We designed and synthesized 19 specific oligonucleotide probes; these probes were arrayed on a silylated glass slide. The length of the probes was 19-24 bps. The COI sequences amplified from the tissues of the selected birds were labeled with a fluorescent probe for microarray hybridization, and unique hybridization patterns were detected for each selected species. These patterns may be considered diagnostic patterns for species identification. This microarray system will provide a sensitive and a high-throughput method for identification of Korean birds.

Identification of differentially expressed genes and false discovery rate in microarray studies.

PubMed

Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

2007-04-01

To highlight the development in microarray data analysis for the identification of differentially expressed genes, particularly via control of false discovery rate. The emergence of high-throughput technology such as microarrays raises two fundamental statistical issues: multiplicity and sensitivity. We focus on the biological problem of identifying differentially expressed genes. First, multiplicity arises due to testing tens of thousands of hypotheses, rendering the standard P value meaningless. Second, known optimal single-test procedures such as the t-test perform poorly in the context of highly multiple tests. The standard approach of dealing with multiplicity is too conservative in the microarray context. The false discovery rate concept is fast becoming the key statistical assessment tool replacing the P value. We review the false discovery rate approach and argue that it is more sensible for microarray data. We also discuss some methods to take into account additional information from the microarrays to improve the false discovery rate. There is growing consensus on how to analyse microarray data using the false discovery rate framework in place of the classical P value. Further research is needed on the preprocessing of the raw data, such as the normalization step and filtering, and on finding the most sensitive test procedure.

16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia.

PubMed

Schönmann, Susan; Loy, Alexander; Wimmersberger, Céline; Sobek, Jens; Aquino, Catharine; Vandamme, Peter; Frey, Beat; Rehrauer, Hubert; Eberl, Leo

2009-04-01

For cultivation-independent and highly parallel analysis of members of the genus Burkholderia, an oligonucleotide microarray (phylochip) consisting of 131 hierarchically nested 16S rRNA gene-targeted oligonucleotide probes was developed. A novel primer pair was designed for selective amplification of a 1.3 kb 16S rRNA gene fragment of Burkholderia species prior to microarray analysis. The diagnostic performance of the microarray for identification and differentiation of Burkholderia species was tested with 44 reference strains of the genera Burkholderia, Pandoraea, Ralstonia and Limnobacter. Hybridization patterns based on presence/absence of probe signals were interpreted semi-automatically using the novel likelihood-based strategy of the web-tool Phylo- Detect. Eighty-eight per cent of the reference strains were correctly identified at the species level. The evaluated microarray was applied to investigate shifts in the Burkholderia community structure in acidic forest soil upon addition of cadmium, a condition that selected for Burkholderia species. The microarray results were in agreement with those obtained from phylogenetic analysis of Burkholderia 16S rRNA gene sequences recovered from the same cadmiumcontaminated soil, demonstrating the value of the Burkholderia phylochip for determinative and environmental studies.

Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

PubMed

Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

2005-05-18

To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

Identifying Fishes through DNA Barcodes and Microarrays.

PubMed

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.

Oligonucleotide microarray for the identification of potential mycotoxigenic fungi

PubMed Central

2010-01-01

Background Mycotoxins are secondary metabolites which are produced by numerous fungi and pose a continuous challenge to the safety and quality of food commodities in South Africa. These toxins have toxicologically relevant effects on humans and animals that eat contaminated foods. In this study, a diagnostic DNA microarray was developed for the identification of the most common food-borne fungi, as well as the genes leading to toxin production. Results A total of 40 potentially mycotoxigenic fungi isolated from different food commodities, as well as the genes that are involved in the mycotoxin synthetic pathways, were analyzed. For fungal identification, oligonucleotide probes were designed by exploiting the sequence variations of the elongation factor 1-alpha (EF-1 α) coding regions and the internal transcribed spacer (ITS) regions of the rRNA gene cassette. For the detection of fungi able to produce mycotoxins, oligonucleotide probes directed towards genes leading to toxin production from different fungal strains were identified in data available in the public domain. The probes selected for fungal identification and the probes specific for toxin producing genes were spotted onto microarray slides. Conclusions The diagnostic microarray developed can be used to identify single pure strains or cultures of potentially mycotoxigenic fungi as well as genes leading to toxin production in both laboratory samples and maize-derived foods offering an interesting potential for microbiological laboratories. PMID:20307326

Resequencing Pathogen Microarray (RPM) for prospective detection and identification of emergent pathogen strains and variants

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.

Homogeneous versus heterogeneous probes for microbial ecological microarrays.

PubMed

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.

Multi-Gene Detection and Identification of Mosquito-Borne RNA Viruses Using an Oligonucleotide Microarray

PubMed Central

Grubaugh, Nathan D.; McMenamy, Scott S.; Turell, Michael J.; Lee, John S.

2013-01-01

Background Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae), Alphavirus (Togaviridae), Orthobunyavirus (Bunyaviridae), and Phlebovirus (Bunyaviridae). Methodology/Principal Findings The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. Conclusions/Significance We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish public health priorities, detect disease outbreaks, and evaluate control programs. PMID:23967358

Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.

PubMed

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.

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

PubMed Central

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of data from experimental microarrays and simulation studies, the proposed model-based approach was shown to provide a more powerful result than the naïve approach and the hierarchical approach. Since our approach is model-based, it is very flexible and can easily handle different types of covariates. PMID:26964035

CLOFIBRATE-INDUCED GENE EXPRESSION CHANGES IN RAT LIVER: A CROSS-LABORATORY ANALYSIS USING MEMBRANE CDNA ARRAYS

EPA Science Inventory

Microarrays have the potential to significantly impact our ability to identify toxic hazards by the identification of mechanistically-relevant markers of toxicity. To be useful for risk assessment however, microarray data must be challenged to determine its reliability and inter...

IDENTIFICATION OF BIOLOGICALLY RELEVANT GENES USING A DATABASE OF RAT LIVER AND KIDNEY BASELINE GENE EXPRESSION

EPA Science Inventory

Microarray data from independent labs and studies can be compared to potentially identify toxicologically and biologically relevant genes. The Baseline Animal Database working group of HESI was formed to assess baseline gene expression from microarray data derived from control or...

Massively multiplexed microbial identification using resequencing DNA microarrays for outbreak investigation

NASA Astrophysics Data System (ADS)

Leski, T. A.; Ansumana, R.; Jimmy, D. H.; Bangura, U.; Malanoski, A. P.; Lin, B.; Stenger, D. A.

2011-06-01

Multiplexed microbial diagnostic assays are a promising method for detection and identification of pathogens causing syndromes characterized by nonspecific symptoms in which traditional differential diagnosis is difficult. Also such assays can play an important role in outbreak investigations and environmental screening for intentional or accidental release of biothreat agents, which requires simultaneous testing for hundreds of potential pathogens. The resequencing pathogen microarray (RPM) is an emerging technological platform, relying on a combination of massively multiplex PCR and high-density DNA microarrays for rapid detection and high-resolution identification of hundreds of infectious agents simultaneously. The RPM diagnostic system was deployed in Sierra Leone, West Africa in collaboration with Njala University and Mercy Hospital Research Laboratory located in Bo. We used the RPM-Flu microarray designed for broad-range detection of human respiratory pathogens, to investigate a suspected outbreak of avian influenza in a number of poultry farms in which significant mortality of chickens was observed. The microarray results were additionally confirmed by influenza specific real-time PCR. The results of the study excluded the possibility that the outbreak was caused by influenza, but implicated Klebsiella pneumoniae as a possible pathogen. The outcome of this feasibility study confirms that application of broad-spectrum detection platforms for outbreak investigation in low-resource locations is possible and allows for rapid discovery of the responsible agents, even in cases when different agents are suspected. This strategy enables quick and cost effective detection of low probability events such as outbreak of a rare disease or intentional release of a biothreat agent.

Prevalence, identification by a DNA microarray-based assay of human and food isolates Listeria spp. from Tunisia.

PubMed

Hmaïed, F; Helel, S; Le Berre, V; François, J-M; Leclercq, A; Lecuit, M; Smaoui, H; Kechrid, A; Boudabous, A; Barkallah, I

2014-02-01

We aimed at evaluating the prevalence of Listeria species isolated from food samples and characterizing food and human cases isolates. Between 2005 and 2007, one hundred food samples collected in the markets of Tunis were analysed in our study. Five strains of Listeria monocytogenes responsible for human listeriosis isolated in hospital of Tunis were included. Multiplex PCR serogrouping and pulsed field gel electrophoresis (PFGE) applying the enzyme AscI and ApaI were used for the characterization of isolates of L. monocytogenes. We have developed a rapid microarray-based assay to a reliable discrimination of species within the Listeria genus. The prevalence of Listeria spp. in food samples was estimated at 14% by using classical biochemical identification. Two samples were assigned to L. monocytogenes and 12 to L. innocua. DNA microarray allowed unambiguous identification of Listeria species. Our results obtained by microarray-based assay were in accordance with the biochemical identification. The two food L. monocytogenes isolates were assigned to the PCR serogroup IIa (serovar 1/2a). Whereas human L. monocytogenes isolates were of PCR serogroup IVb, (serovars 4b). These isolates present a high similarity in PFGE. Food L. monocytogenes isolates were classified into two different pulsotypes. These pulsotypes were different from that of the five strains responsible for the human cases. We confirmed the presence of Listeria spp. in variety of food samples in Tunis. Increased food and clinical surveillance must be taken into consideration in Tunisia to identify putative infections sources. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Performance Assessment of the CapitalBio Mycobacterium Identification Array System for Identification of Mycobacteria

PubMed Central

Liu, Jingbo; Yan, Zihe; Han, Min; Han, Zhijun; Jin, Lingjie; Zhao, Yanlin

2012-01-01

The CapitalBio Mycobacterium identification microarray system is a rapid system for the detection of Mycobacterium tuberculosis. The performance of this system was assessed with 24 reference strains, 486 Mycobacterium tuberculosis clinical isolates, and 40 clinical samples and then compared to the “gold standard” of DNA sequencing. The CapitalBio Mycobacterium identification microarray system showed highly concordant identification results of 100% and 98.4% for Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM), respectively. The sensitivity and specificity of the CapitalBio Mycobacterium identification array for identification of Mycobacterium tuberculosis isolates were 99.6% and 100%, respectively, for direct detection and identification of clinical samples, and the overall sensitivity was 52.5%. It was 100% for sputum, 16.7% for pleural fluid, and 10% for bronchoalveolar lavage fluid, respectively. The total assay was completed in 6 h, including DNA extraction, PCR, and hybridization. The results of this study confirm the utility of this system for the rapid identification of mycobacteria and suggest that the CapitalBio Mycobacterium identification array is a molecular diagnostic technique with high sensitivity and specificity that has the capacity to quickly identify most mycobacteria. PMID:22090408

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments

PubMed Central

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

Microarray-based identification of differentially expressed genes in extramammary Paget’s disease

PubMed Central

Lin, Jin-Ran; Liang, Jun; Zhang, Qiao-An; Huang, Qiong; Wang, Shang-Shang; Qin, Hai-Hong; Chen, Lian-Jun; Xu, Jin-Hua

2015-01-01

Extramammary Paget’s disease (EMPD) is a rare cutaneous malignancy accounting for approximately 1-2% of vulvar cancers. The rarity of this disease has caused difficulties in characterization and the molecular mechanism underlying EMPD development remains largely unclear. Here we used microarray analysis to identify differentially expressed genes in EMPD of the scrotum comparing with normal epithelium from healthy donors. Agilent single-channel microarray was used to compare the gene expression between 6 EMPD specimens and 6 normal scrotum epithelium samples. A total of 799 up-regulated genes and 723 down-regulated genes were identified in EMPD tissues. Real-time PCR was conducted to verify the differential expression of some representative genes, including ERBB4, TCF3, PAPSS2, PIK3R3, PRLR, SULT1A1, TCF7L1, and CREB3L4. Generally, the real-time PCR results were consistent with microarray data, and the expression of ERBB4, PRLR, TCF3, PIK3R3, SULT1A1, and TCF7L1 was significantly overexpressed in EMPD (P<0.05). Moreover, the overexpression of PRLR in EMPD, a receptor for the anterior pituitary hormone prolactin (PRL), was confirmed by immunohistochemistry. These data demonstrate that the differentially expressed genes from the microarray-based identification are tightly associated with EMPD occurrence. PMID:26221264

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping.

PubMed

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren; Nielsen, Morten

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.

Leptospiral outer membrane protein microarray, a novel approach to identification of host ligand-binding proteins.

PubMed

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.

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

PubMed Central

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope. PMID:28095436

The use of open source bioinformatics tools to dissect transcriptomic data.

PubMed

Nitsche, Benjamin M; Ram, Arthur F J; Meyer, Vera

2012-01-01

Microarrays are a valuable technology to study fungal physiology on a transcriptomic level. Various microarray platforms are available comprising both single and two channel arrays. Despite different technologies, preprocessing of microarray data generally includes quality control, background correction, normalization, and summarization of probe level data. Subsequently, depending on the experimental design, diverse statistical analysis can be performed, including the identification of differentially expressed genes and the construction of gene coexpression networks.We describe how Bioconductor, a collection of open source and open development packages for the statistical programming language R, can be used for dissecting microarray data. We provide fundamental details that facilitate the process of getting started with R and Bioconductor. Using two publicly available microarray datasets from Aspergillus niger, we give detailed protocols on how to identify differentially expressed genes and how to construct gene coexpression networks.

Chondrocyte channel transcriptomics

PubMed Central

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

FDA Escherichia coli Identification (FDA-ECID) Microarray: a Pangenome Molecular Toolbox for Serotyping, Virulence Profiling, Molecular Epidemiology, and Phylogeny

PubMed Central

Patel, Isha R.; Gangiredla, Jayanthi; Lacher, David W.; Mammel, Mark K.; Jackson, Scott A.; Lampel, Keith A.

2016-01-01

ABSTRACT Most Escherichia coli strains are nonpathogenic. However, for clinical diagnosis and food safety analysis, current identification methods for pathogenic E. coli either are time-consuming and/or provide limited information. Here, we utilized a custom DNA microarray with informative genetic features extracted from 368 sequence sets for rapid and high-throughput pathogen identification. The FDA Escherichia coli Identification (FDA-ECID) platform contains three sets of molecularly informative features that together stratify strain identification and relatedness. First, 53 known flagellin alleles, 103 alleles of wzx and wzy, and 5 alleles of wzm provide molecular serotyping utility. Second, 41,932 probe sets representing the pan-genome of E. coli provide strain-level gene content information. Third, approximately 125,000 single nucleotide polymorphisms (SNPs) of available whole-genome sequences (WGS) were distilled to 9,984 SNPs capable of recapitulating the E. coli phylogeny. We analyzed 103 diverse E. coli strains with available WGS data, including those associated with past foodborne illnesses, to determine robustness and accuracy. The array was able to accurately identify the molecular O and H serotypes, potentially correcting serological failures and providing better resolution for H-nontypeable/nonmotile phenotypes. In addition, molecular risk assessment was possible with key virulence marker identifications. Epidemiologically, each strain had a unique comparative genomic fingerprint that was extended to an additional 507 food and clinical isolates. Finally, a 99.7% phylogenetic concordance was established between microarray analysis and WGS using SNP-level data for advanced genome typing. Our study demonstrates FDA-ECID as a powerful tool for epidemiology and molecular risk assessment with the capacity to profile the global landscape and diversity of E. coli. IMPORTANCE This study describes a robust, state-of-the-art platform developed from available whole-genome sequences of E. coli and Shigella spp. by distilling useful signatures for epidemiology and molecular risk assessment into one assay. The FDA-ECID microarray contains features that enable comprehensive molecular serotyping and virulence profiling along with genome-scale genotyping and SNP analysis. Hence, it is a molecular toolbox that stratifies strain identification and pathogenic potential in the contexts of epidemiology and phylogeny. We applied this tool to strains from food, environmental, and clinical sources, resulting in significantly greater phylogenetic and strain-specific resolution than previously reported for available typing methods. PMID:27037122

Switching benchmarks in cancer of unknown primary: from autopsy to microarray.

PubMed

Pentheroudakis, George; Golfinopoulos, Vassilios; Pavlidis, Nicholas

2007-09-01

Cancer of unknown primary (CUP) is associated with unknown biology and dismal prognosis. Information on the primary site of origin is scant and has never been analysed. We systematically reviewed all published evidence on the CUP primary site identified by two different approaches, either autopsy or microarray gene expression profiling. Published reports on identification of CUP primary site by autopsy or microarray-based multigene expression platforms were retrieved and analysed for year of publication, primary site, patient age, gender, histology, rate of primary identification, manifestations and metastatic deposits, microarray chip technology, training and validation sets, mathematical modelling, classification accuracy and number of classifying genes. From 1944 to 2000, a total of 884 CUP patients (66% males) underwent autopsy in 12 studies after presenting with metastatic or systemic symptoms and succumbing to their disease. A primary was identified in 644 (73%) of them, mostly in the lung (27%), pancreas (24%), hepatobiliary tree (8%), kidneys (8%), bowel, genital system and stomach, as a small focus of adenocarcinoma or poorly differentiated carcinoma. An unpredictable systemic dissemination was evident with high frequency of lung (46%), nodal (35%), bone (17%), brain (16%) and uncommon (18%) deposits. Between the 1944-1980 and the 1980-2000 series, female representation increased, 'undetermined neoplasm' diagnosis became rarer, pancreatic primaries were found less often while colonic ones were identified more frequently. Four studies using microarray technology profiled more than 500 CUP cases using classifier set of genes (ranging from 10 to 495) and reported strikingly dissimilar frequencies of assigned primary sites (lung 11.5%, pancreas 12.5%, bowel 12%, breast 15%, hepatobiliary tree 8%, kidneys 6%, genital system 9%, bladder 5%) in 75-90% of the cases. Evolution in medical imaging technology, diet and lifestyle habits probably account for changing epidemiology of CUP primaries in autopsies. Discrepant assignment of primary sites by microarrays may be due to the presence of 'sanctuary sites' in autopsies, molecular misclassification and the postulated presence of a pro-metastatic genetic signature. In view of the absence of patient therapeutic or prognostic benefit with primary identification, gene expression profiling should be re-orientated towards unraveling the complex pathophysiology of metastases.

High-throughput identification of proteins with AMPylation using self-assembled human protein (NAPPA) microarrays.

PubMed

Yu, Xiaobo; LaBaer, Joshua

2015-05-01

AMPylation (adenylylation) has been recognized as an important post-translational modification that is used by pathogens to regulate host cellular proteins and their associated signaling pathways. AMPylation has potential functions in various cellular processes, and it is widely conserved across both prokaryotes and eukaryotes. However, despite the identification of many AMPylators, relatively few candidate substrates of AMPylation are known. This is changing with the recent development of a robust and reliable method for identifying new substrates using protein microarrays, which can markedly expand the list of potential substrates. Here we describe procedures for detecting AMPylated and auto-AMPylated proteins in a sensitive, high-throughput and nonradioactive manner. The approach uses high-density protein microarrays fabricated using nucleic acid programmable protein array (NAPPA) technology, which enables the highly successful display of fresh recombinant human proteins in situ. The modification of target proteins is determined via copper-catalyzed azide-alkyne cycloaddition (CuAAC). The assay can be accomplished within 11 h.

A Sol-gel Integrated Dual-readout Microarray Platform for Quantification and Identification of Prostate-specific Antigen.

PubMed

Lee, SangWook; Lee, Jong Hyun; Kwon, Hyuck Gi; Laurell, Thomas; Jeong, Ok Chan; Kim, Soyoun

2018-01-01

Here, we report a sol-gel integrated affinity microarray for on-chip matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) that enables capture and identification of prostate?specific antigen (PSA) in samples. An anti-PSA antibody (H117) was mixed with a sol?gel, and the mixture was spotted onto a porous silicon (pSi) surface without additional surface modifications. The antibody easily penetrates the sol-gel macropore fluidic network structure, making possible high affinities. To assess the capture affinity of the platform, we performed a direct assay using fluorescein isothiocyanate-labeled PSA. Pure PSA was subjected to on-chip MALDI-TOF-MS analysis, yielding three clear mass peptide peaks (m/z = 1272, 1407, and 1872). The sol-gel microarray platform enables dual readout of PSA both fluorometric and MALDI-TOF MS analysis in biological samples. Here we report a useful method for a means for discovery of biomarkers in complex body fluids.

The Microbial Detection Array Combined with Random Phi29-Amplification Used as a Diagnostic Tool for Virus Detection in Clinical Samples

PubMed Central

Erlandsson, Lena; Rosenstierne, Maiken W.; McLoughlin, Kevin; Jaing, Crystal; Fomsgaard, Anders

2011-01-01

A common technique used for sensitive and specific diagnostic virus detection in clinical samples is PCR that can identify one or several viruses in one assay. However, a diagnostic microarray containing probes for all human pathogens could replace hundreds of individual PCR-reactions and remove the need for a clear clinical hypothesis regarding a suspected pathogen. We have established such a diagnostic platform for random amplification and subsequent microarray identification of viral pathogens in clinical samples. We show that Phi29 polymerase-amplification of a diverse set of clinical samples generates enough viral material for successful identification by the Microbial Detection Array, demonstrating the potential of the microarray technique for broad-spectrum pathogen detection. We conclude that this method detects both DNA and RNA virus, present in the same sample, as well as differentiates between different virus subtypes. We propose this assay for diagnostic analysis of viruses in clinical samples. PMID:21853040

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

PubMed

Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of a DNA Microarray-Based Assay for the Detection of Sugar Beet Root Rot Pathogens.

PubMed

Liebe, Sebastian; Christ, Daniela S; Ehricht, Ralf; Varrelmann, Mark

2016-01-01

Sugar beet root rot diseases that occur during the cropping season or in storage are accompanied by high yield losses and a severe reduction of processing quality. The vast diversity of microorganism species involved in rot development requires molecular tools allowing simultaneous identification of many different targets. Therefore, a new microarray technology (ArrayTube) was applied in this study to improve diagnosis of sugar beet root rot diseases. Based on three marker genes (internal transcribed spacer, translation elongation factor 1 alpha, and 16S ribosomal DNA), 42 well-performing probes enabled the identification of prevalent field pathogens (e.g., Aphanomyces cochlioides), storage pathogens (e.g., Botrytis cinerea), and ubiquitous spoilage fungi (e.g., Penicillium expansum). All probes were proven for specificity with pure cultures from 73 microorganism species as well as for in planta detection of their target species using inoculated sugar beet tissue. Microarray-based identification of root rot pathogens in diseased field beets was successfully confirmed by classical detection methods. The high discriminatory potential was proven by Fusarium species differentiation based on a single nucleotide polymorphism. The results demonstrate that the ArrayTube constitute an innovative tool allowing a rapid and reliable detection of plant pathogens particularly when multiple microorganism species are present.

Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

PubMed Central

Schena, M; Shalon, D; Heller, R; Chai, A; Brown, P O; Davis, R W

1996-01-01

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. Images Fig. 1 Fig. 2 Fig. 3 PMID:8855227

ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles

PubMed Central

2009-01-01

Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286

Plant-pathogen interactions: what microarray tells about it?

PubMed

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.

Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

PubMed

Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

2016-04-01

Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

Identification of Escherichia coli O157 by Using a Novel Colorimetric Detection Method with DNA Microarrays

PubMed Central

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

Oligo Design: a computer program for development of probes for oligonucleotide microarrays.

PubMed

Herold, Keith E; Rasooly, Avraham

2003-12-01

Oligonucleotide microarrays have demonstrated potential for the analysis of gene expression, genotyping, and mutational analysis. Our work focuses primarily on the detection and identification of bacteria based on known short sequences of DNA. Oligo Design, the software described here, automates several design aspects that enable the improved selection of oligonucleotides for use with microarrays for these applications. Two major features of the program are: (i) a tiling algorithm for the design of short overlapping temperature-matched oligonucleotides of variable length, which are useful for the analysis of single nucleotide polymorphisms and (ii) a set of tools for the analysis of multiple alignments of gene families and related short DNA sequences, which allow for the identification of conserved DNA sequences for PCR primer selection and variable DNA sequences for the selection of unique probes for identification. Note that the program does not address the full genome perspective but, instead, is focused on the genetic analysis of short segments of DNA. The program is Internet-enabled and includes a built-in browser and the automated ability to download sequences from GenBank by specifying the GI number. The program also includes several utilities, including audio recital of a DNA sequence (useful for verifying sequences against a written document), a random sequence generator that provides insight into the relationship between melting temperature and GC content, and a PCR calculator.

Structured oligonucleotides for target indexing to allow single-vessel PCR amplification and solid support microarray hybridization

PubMed Central

Girard, Laurie D.; Boissinot, Karel; Peytavi, Régis; Boissinot, Maurice; Bergeron, Michel G.

2014-01-01

The combination of molecular diagnostic technologies is increasingly used to overcome limitations on sensitivity, specificity or multiplexing capabilities, and provide efficient lab-on-chip devices. Two such techniques, PCR amplification and microarray hybridization are used serially to take advantage of the high sensitivity and specificity of the former combined with high multiplexing capacities of the latter. These methods are usually performed in different buffers and reaction chambers. However, these elaborate methods have a high complexity cost related to reagent requirements, liquid storage and the number of reaction chambers to integrate into automated devices. Furthermore, microarray hybridizations have a sequence dependent efficiency not always predictable. In this work, we have developed the concept of a structured oligonucleotide probe which is activated by cleavage from polymerase exonuclease activity. This technology is called SCISSOHR for Structured Cleavage Induced Single-Stranded Oligonucleotide Hybridization Reaction. The SCISSOHR probes enable indexing the target sequence to a tag sequence. The SCISSOHR technology also allows the combination of nucleic acid amplification and microarray hybridization in a single vessel in presence of the PCR buffer only. The SCISSOHR technology uses an amplification probe that is irreversibly modified in presence of the target, releasing a single-stranded DNA tag for microarray hybridization. Each tag is composed of a 3-nucleotidesequence-dependent segment and a unique “target sequence-independent” 14-nucleotide segment allowing for optimal hybridization with minimal cross-hybridization. We evaluated the performance of five (5) PCR buffers to support microarray hybridization, compared to a conventional hybridization buffer. Finally, as a proof of concept, we developed a multiplexed assay for the amplification, detection, and identification of three (3) DNA targets. This new technology will facilitate the design of lab-on-chip microfluidic devices, while also reducing consumable costs. At term, it will allow the cost-effective automation of highly multiplexed assays for detection and identification of genetic targets. PMID:25489607

Structured oligonucleotides for target indexing to allow single-vessel PCR amplification and solid support microarray hybridization.

PubMed

Girard, Laurie D; Boissinot, Karel; Peytavi, Régis; Boissinot, Maurice; Bergeron, Michel G

2015-02-07

The combination of molecular diagnostic technologies is increasingly used to overcome limitations on sensitivity, specificity or multiplexing capabilities, and provide efficient lab-on-chip devices. Two such techniques, PCR amplification and microarray hybridization are used serially to take advantage of the high sensitivity and specificity of the former combined with high multiplexing capacities of the latter. These methods are usually performed in different buffers and reaction chambers. However, these elaborate methods have high complexity and cost related to reagent requirements, liquid storage and the number of reaction chambers to integrate into automated devices. Furthermore, microarray hybridizations have a sequence dependent efficiency not always predictable. In this work, we have developed the concept of a structured oligonucleotide probe which is activated by cleavage from polymerase exonuclease activity. This technology is called SCISSOHR for Structured Cleavage Induced Single-Stranded Oligonucleotide Hybridization Reaction. The SCISSOHR probes enable indexing the target sequence to a tag sequence. The SCISSOHR technology also allows the combination of nucleic acid amplification and microarray hybridization in a single vessel in presence of the PCR buffer only. The SCISSOHR technology uses an amplification probe that is irreversibly modified in presence of the target, releasing a single-stranded DNA tag for microarray hybridization. Each tag is composed of a 3-nucleotide sequence-dependent segment and a unique "target sequence-independent" 14-nucleotide segment allowing for optimal hybridization with minimal cross-hybridization. We evaluated the performance of five (5) PCR buffers to support microarray hybridization, compared to a conventional hybridization buffer. Finally, as a proof of concept, we developed a multiplexed assay for the amplification, detection, and identification of three (3) DNA targets. This new technology will facilitate the design of lab-on-chip microfluidic devices, while also reducing consumable costs. At term, it will allow the cost-effective automation of highly multiplexed assays for detection and identification of genetic targets.

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection inmore » archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.« less

Identification of candidate genes in osteoporosis by integrated microarray analysis.

PubMed

Li, J J; Wang, B Q; Fei, Q; Yang, Y; Li, D

2016-12-01

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594-601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1. © 2016 Fei et al.

A New Microarray Substrate for Ultra-Sensitive Genotyping of KRAS and BRAF Gene Variants in Colorectal Cancer

PubMed Central

Pinzani, Pamela; Mancini, Irene; Vinci, Serena; Chiari, Marcella; Orlando, Claudio; Cremonesi, Laura; Ferrari, Maurizio

2013-01-01

Molecular diagnostics of human cancers may increase accuracy in prognosis, facilitate the selection of the optimal therapeutic regimen, improve patient outcome, reduce costs of treatment and favour development of personalized approaches to patient care. Moreover sensitivity and specificity are fundamental characteristics of any diagnostic method. We developed a highly sensitive microarray for the detection of common KRAS and BRAF oncogenic mutations. In colorectal cancer, KRAS and BRAF mutations have been shown to identify a cluster of patients that does not respond to anti-EGFR therapies; the identification of these mutations is therefore clinically extremely important. To verify the technical characteristics of the microarray system for the correct identification of the KRAS mutational status at the two hotspot codons 12 and 13 and of the BRAFV600E mutation in colorectal tumor, we selected 75 samples previously characterized by conventional and CO-amplification at Lower Denaturation temperature-PCR (COLD-PCR) followed by High Resolution Melting analysis and direct sequencing. Among these samples, 60 were collected during surgery and immediately steeped in RNAlater while the 15 remainders were formalin-fixed and paraffin-embedded (FFPE) tissues. The detection limit of the proposed method was different for the 7 KRAS mutations tested and for the V600E BRAF mutation. In particular, the microarray system has been able to detect a minimum of about 0.01% of mutated alleles in a background of wild-type DNA. A blind validation displayed complete concordance of results. The excellent agreement of the results showed that the new microarray substrate is highly specific in assigning the correct genotype without any enrichment strategy. PMID:23536897

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Evolution of the MIDTAL microarray: the adaption and testing of oligonucleotide 18S and 28S rDNA probes and evaluation of subsequent microarray generations with Prymnesium spp. cultures and field samples.

PubMed

McCoy, Gary R; Touzet, Nicolas; Fleming, Gerard T A; Raine, Robin

2015-07-01

The toxic microalgal species Prymnesium parvum and Prymnesium polylepis are responsible for numerous fish kills causing economic stress on the aquaculture industry and, through the consumption of contaminated shellfish, can potentially impact on human health. Monitoring of toxic phytoplankton is traditionally carried out by light microscopy. However, molecular methods of identification and quantification are becoming more common place. This study documents the optimisation of the novel Microarrays for the Detection of Toxic Algae (MIDTAL) microarray from its initial stages to the final commercial version now available from Microbia Environnement (France). Existing oligonucleotide probes used in whole-cell fluorescent in situ hybridisation (FISH) for Prymnesium species from higher group probes to species-level probes were adapted and tested on the first-generation microarray. The combination and interaction of numerous other probes specific for a whole range of phytoplankton taxa also spotted on the chip surface caused high cross reactivity, resulting in false-positive results on the microarray. The probe sequences were extended for the subsequent second-generation microarray, and further adaptations of the hybridisation protocol and incubation temperatures significantly reduced false-positive readings from the first to the second-generation chip, thereby increasing the specificity of the MIDTAL microarray. Additional refinement of the subsequent third-generation microarray protocols with the addition of a poly-T amino linker to the 5' end of each probe further enhanced the microarray performance but also highlighted the importance of optimising RNA labelling efficiency when testing with natural seawater samples from Killary Harbour, Ireland.

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

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

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

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

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

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.

Development of a rapid microarray-based DNA subtyping assay for the alleles of Shiga toxins 1 and 2 of Escherichia coli.

PubMed

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.

Identification of testis-specific male contraceptive targets: insights from transcriptional profiling of the cycle of the rat seminiferous epithelium and purified testicular cells.

PubMed

Johnston, Daniel S; Jelinsky, Scott A; Zhi, Yu; Finger, Joshua N; Kopf, Gregory S; Wright, William W

2007-12-01

In an effort to identify novel targets for the development of nonhormonal male contraceptives, genome-wide transcriptional profiling of the rat testis was performed. Specifically, enzymatically purified spermatogonia plus early spermatocyctes, pachytene spermatocytes, round spermatids, and Sertoli cells was analyzed along with microdissected rat seminiferous tubules at stages I, II-III, IV-V, VI, VIIa,b, VIIc,d, VIII, IX- XI, XII, XIII-XIV of the cycle of the seminiferous epithelium using RAE 230_2.0 microarrays. The combined analysis of these studies identified 16,971 expressed probe sets on the array. How these expression data, combined with additional bioinformatic data analysis and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) analysis, led to the identification of 58 genes that have 1000-fold higher expression transcriptionally in the testis when compared to over 20 other nonreproductive tissues is described. The products of these genes may play important roles in testicular and/or sperm function, and further investigation on their utility as nonhormonal contraceptive targets is warranted. Moreover, these microarray data have been used to expedite the identification of a mutation in RIKEN cDNA 2410004F06 gene as likely being responsible for spermatogenic failure in a line of infertile mice generated by N-ethyl-N-nitrosourea (ENU) mutagenesis. The microarray data and the qRT-PCR data described are available in the Mammalian Reproductive Genetics database (http://mrg.genetics.washington.edu/).

MobilomeFINDER: web-based tools for in silico and experimental discovery of bacterial genomic islands

PubMed Central

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

MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation

PubMed Central

Zubakov, Dmitry; Boersma, Anton W. M.; Choi, Ying; van Kuijk, Patricia F.; Wiemer, Erik A. C.

2010-01-01

MicroRNAs (miRNAs) are non-protein coding molecules with important regulatory functions; many have tissue-specific expression patterns. Their very small size in principle makes them less prone to degradation processes, unlike messenger RNAs (mRNAs), which were previously proposed as molecular tools for forensic body fluid identification. To identify suitable miRNA markers for forensic body fluid identification, we first screened total RNA samples derived from saliva, semen, vaginal secretion, and venous and menstrual blood for the expression of 718 human miRNAs using a microarray platform. All body fluids could be easily distinguished from each other on the basis of complete array-based miRNA expression profiles. Results from quantitative reverse transcription PCR (RT-PCR; TaqMan) assays for microarray candidate markers confirmed strong over-expression in the targeting body fluid of several miRNAs for venous blood and several others for semen. However, no candidate markers from array experiments for other body fluids such as saliva, vaginal secretion, or menstrual blood could be confirmed by RT-PCR. Time-wise degradation of venous blood and semen stains for at least 1 year under lab conditions did not significantly affect the detection sensitivity of the identified miRNA markers. The detection limit of the TaqMan assays tested for selected venous blood and semen miRNA markers required only subpicogram amounts of total RNA per single RT-PCR test, which is considerably less than usually needed for reliable mRNA RT-PCR detection. We therefore propose the application of several stable miRNA markers for the forensic identification of blood stains and several others for semen stain identification, using commercially available TaqMan assays. Additional work remains necessary in search for suitable miRNA markers for other forensically relevant body fluids. Electronic supplementary material The online version of this article (doi:10.1007/s00414-009-0402-3) contains supplementary material, which is available to authorized users. PMID:20145944

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

PubMed Central

2012-01-01

Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. PMID:22276688

Analysis of mutations in oral poliovirus vaccine by hybridization with generic oligonucleotide microchips.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Proudnikov, D.; Kirillov, E.; Chumakov, K.

2000-01-01

This paper describes use of a new technology of hybridization with a micro-array of immobilized oligonucleotides for detection and quantification of neurovirulent mutants in Oral Poliovirus Vaccine (OPV). We used a micro-array consisting of three-dimensional gel-elements containing all possible hexamers (total of 4096 probes). Hybridization of fluorescently labelled viral cDNA samples with such microchips resulted in a pattern of spots that was registered and quantified by a computer-linked CCD camera, so that the sequence of the original cDNA could be deduced. The method could reliably identify single point mutations, since each of them affected fluorescence intensity of 12 micro-array elements.more » Micro-array hybridization of DNA mixtures with varying contents of point mutants demonstrated that the method can detect as little as 10% of revertants in a population of vaccine virus. This new technology should be useful for quality control of live viral vaccines, as well as for other applications requiring identification and quantification of point mutations.« less

Sequencing ebola and marburg viruses genomes using microarrays.

PubMed

Hardick, Justin; Woelfel, Roman; Gardner, Warren; Ibrahim, Sofi

2016-08-01

Periodic outbreaks of Ebola and Marburg hemorrhagic fevers have occurred in Africa over the past four decades with case fatality rates reaching as high as 90%. The latest Ebola outbreak in West Africa in 2014 raised concerns that these infections can spread across continents and pose serious health risks. Early and accurate identification of the causative agents is necessary to contain outbreaks. In this report, we describe sequencing-by-hybridization (SBH) technique using high density microarrays to identify Ebola and Marburg viruses. The microarrays were designed to interrogate the sequences of entire viral genomes, and were evaluated with three species of Ebolavirus (Reston, Sudan, and Zaire), and three strains of Marburgvirus (Angola, Musoke, and Ravn). The results showed that the consensus sequences generated with four or more hybridizations had 92.1-98.9% accuracy over 95-99% of the genomes. Additionally, with SBH microarrays it was possible to distinguish between different strains of the Lake Victoria Marburgvirus. J. Med. Virol. 88:1303-1308, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Efficient mutation identification in zebrafish by microarray capturing and next generation sequencing.

PubMed

Bontems, Franck; Baerlocher, Loic; Mehenni, Sabrina; Bahechar, Ilham; Farinelli, Laurent; Dosch, Roland

2011-02-18

Fish models like medaka, stickleback or zebrafish provide a valuable resource to study vertebrate genes. However, finding genetic variants e.g. mutations in the genome is still arduous. Here we used a combination of microarray capturing and next generation sequencing to identify the affected gene in the mozartkugelp11cv (mzlp11cv) mutant zebrafish. We discovered a 31-bp deletion in macf1 demonstrating the potential of this technique to efficiently isolate mutations in a vertebrate genome. Copyright © 2011 Elsevier Inc. All rights reserved.

Rapid Detection of Rare Deleterious Variants by Next Generation Sequencing with Optional Microarray SNP Genotype Data

PubMed Central

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

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

PubMed Central

2010-01-01

Background The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems'-level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log2- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets. PMID:20128918

Mapping of Epitopes Occurring in Bovine α(s1)-Casein Variants by Peptide Microarray Immunoassay.

PubMed

Lisson, Maria; Erhardt, Georg

2016-01-01

Immunoglobulin E epitope mapping of milk proteins reveals important information about their immunologic properties. Genetic variants of αS1-casein, one of the major allergens in bovine milk, are until now not considered when discussing the allergenic potential. Here we describe the complete procedure to assess the allergenicity of αS1-casein variants B and C, which are frequent in most breeds, starting from milk with identification and purification of casein variants by isoelectric focusing (IEF) and anion-exchange chromatography, followed by in vitro gastrointestinal digestion of the casein variants, identification of the resulting peptides by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), in silico analysis of the variant-specific peptides as allergenic epitopes, and determination of their IgE-binding properties by microarray immunoassay with cow's milk allergic human sera.

An approach for identification of unknown viruses using sequencing-by-hybridization.

PubMed

Katoski, Sarah E; Meyer, Hermann; Ibrahim, Sofi

2015-09-01

Accurate identification of biological threat agents, especially RNA viruses, in clinical or environmental samples can be challenging because the concentration of viral genomic material in a given sample is usually low, viral genomic RNA is liable to degradation, and RNA viruses are extremely diverse. A two-tiered approach was used for initial identification, then full genomic characterization of 199 RNA viruses belonging to virus families Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, and Togaviridae. A Sequencing-by-hybridization (SBH) microarray was used to tentatively identify a viral pathogen then, the identity is confirmed by guided next-generation sequencing (NGS). After optimization and evaluation of the SBH and NGS methodologies with various virus species and strains, the approach was used to test the ability to identify viruses in blinded samples. The SBH correctly identified two Ebola viruses in the blinded samples within 24 hr, and by using guided amplicon sequencing with 454 GS FLX, the identities of the viruses in both samples were confirmed. SBH provides at relatively low-cost screening of biological samples against a panel of viral pathogens that can be custom-designed on a microarray. Once the identity of virus is deduced from the highest hybridization signal on the SBH microarray, guided (amplicon) NGS sequencing can be used not only to confirm the identity of the virus but also to provide further information about the strain or isolate, including a potential genetic manipulation. This approach can be useful in situations where natural or deliberate biological threat incidents might occur and a rapid response is required. © 2015 Wiley Periodicals, Inc.

MIPHENO: Data normalization for high throughput metabolic analysis.

EPA Science Inventory

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...

Sequence specificity of single-stranded DNA-binding proteins: a novel DNA microarray approach

PubMed Central

Morgan, Hugh P.; Estibeiro, Peter; Wear, Martin A.; Max, Klaas E.A.; Heinemann, Udo; Cubeddu, Liza; Gallagher, Maurice P.; Sadler, Peter J.; Walkinshaw, Malcolm D.

2007-01-01

We have developed a novel DNA microarray-based approach for identification of the sequence-specificity of single-stranded nucleic-acid-binding proteins (SNABPs). For verification, we have shown that the major cold shock protein (CspB) from Bacillus subtilis binds with high affinity to pyrimidine-rich sequences, with a binding preference for the consensus sequence, 5′-GTCTTTG/T-3′. The sequence was modelled onto the known structure of CspB and a cytosine-binding pocket was identified, which explains the strong preference for a cytosine base at position 3. This microarray method offers a rapid high-throughput approach for determining the specificity and strength of ss DNA–protein interactions. Further screening of this newly emerging family of transcription factors will help provide an insight into their cellular function. PMID:17488853

Identification of new autoantigens for primary biliary cirrhosis using human proteome microarrays.

PubMed

Hu, Chao-Jun; Song, Guang; Huang, Wei; Liu, Guo-Zhen; Deng, Chui-Wen; Zeng, Hai-Pan; Wang, Li; Zhang, Feng-Chun; Zhang, Xuan; Jeong, Jun Seop; Blackshaw, Seth; Jiang, Li-Zhi; Zhu, Heng; Wu, Lin; Li, Yong-Zhe

2012-09-01

Primary biliary cirrhosis (PBC) is a chronic cholestatic liver disease of unknown etiology and is considered to be an autoimmune disease. Autoantibodies are important tools for accurate diagnosis of PBC. Here, we employed serum profiling analysis using a human proteome microarray composed of about 17,000 full-length unique proteins and identified 23 proteins that correlated with PBC. To validate these results, we fabricated a PBC-focused microarray with 21 of these newly identified candidates and nine additional known PBC antigens. By screening the PBC microarrays with additional cohorts of 191 PBC patients and 321 controls (43 autoimmune hepatitis, 55 hepatitis B virus, 31 hepatitis C virus, 48 rheumatoid arthritis, 45 systematic lupus erythematosus, 49 systemic sclerosis, and 50 healthy), six proteins were confirmed as novel PBC autoantigens with high sensitivities and specificities, including hexokinase-1 (isoforms I and II), Kelch-like protein 7, Kelch-like protein 12, zinc finger and BTB domain-containing protein 2, and eukaryotic translation initiation factor 2C, subunit 1. To facilitate clinical diagnosis, we developed ELISA for Kelch-like protein 12 and zinc finger and BTB domain-containing protein 2 and tested large cohorts (297 PBC and 637 control sera) to confirm the sensitivities and specificities observed in the microarray-based assays. In conclusion, our research showed that a strategy using high content protein microarray combined with a smaller but more focused protein microarray can effectively identify and validate novel PBC-specific autoantigens and has the capacity to be translated to clinical diagnosis by means of an ELISA-based method.

Ultrafiltration and Microarray for Detection of Microbial Source Tracking Marker and Pathogen Genes in Riverine and Marine Systems

PubMed Central

Li, Xiang; Harwood, Valerie J.; Nayak, Bina

2016-01-01

Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment. PMID:26729716

Oligonucleotide microarray for subtyping of influenza A viruses

NASA Astrophysics Data System (ADS)

Klotchenko, S. A.; Vasin, A. V.; Sandybaev, N. T.; Plotnikova, M. A.; Chervyakova, O. V.; Smirnova, E. A.; Kushnareva, E. V.; Strochkov, V. M.; Taylakova, E. T.; Egorov, V. V.; Koshemetov, J. K.; Kiselev, O. I.; Sansyzbay, A. R.

2012-02-01

Influenza is one of the most widespread respiratory viral diseases, infecting humans, horses, pigs, poultry and some other animal populations. Influenza A viruses (IAV) are classified into subtypes on the basis of the surface hemagglutinin (H1 to H16) and neuraminidase (N1 to N9) glycoproteins. The correct determination of IAV subtype is necessary for clinical and epidemiological studies. In this article we propose an oligonucleotide microarray for subtyping of IAV using universal one-step multisegment RT-PCR fluorescent labeling of viral gene segments. It showed to be an advanced approach for fast detection and identification of IAV.

Identification of Potential Chemical Carcinogens in Compendia of Gene Expression Profiles

EPA Science Inventory

Chemicals induce cancer through partially characterized adverse outcome pathways (AOPs) that include molecular initiating events (MIEs) and downstream key events (KEs). Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput form...

Clear cell papillary renal cell carcinoma: a chromosomal microarray analysis of two cases using a novel Molecular Inversion Probe (MIP) technology.

PubMed

Alexiev, Borislav A; Zou, Ying S

2014-12-01

Chromosomal microarray analysis using novel Molecular Inversion Probe (MIP) technology demonstrated 2,570 kb copy neutral LOH of 10q11.22 in two clear cell papillary renal cell carcinomas. In addition, one of the tumors had a big 29,784 kb deletion of 13q11-q14.2. There were two variants of unknown significance, a 2,509 kb gain of Xp22.33 and a 257 kb homozygous deletion of 8p11.22. The somatic mutation panel containing 74 mutations in nine genes did not reveal any mutations. Besides identification of submicroscopic duplications or deletions, SNP microarrays can reveal abnormal allelic imbalances including LOH and copy neutral LOH, which cannot be recognized by chromosome, FISH, and non-SNP microarray arrays. To the best of our knowledge, this is the first study demonstrating copy neutral LOH of 10q11.22 in clear cell papillary renal cell carcinomas using the new MIP SNP OncoScan FFPE Assay Kit on formalin-fixed paraffin-embedded tumor samples. Copyright © 2014 Elsevier GmbH. All rights reserved.

Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.

PubMed

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

Microarray labeling extension values: laboratory signatures for Affymetrix GeneChips

PubMed Central

Lee, Yun-Shien; Chen, Chun-Houh; Tsai, Chi-Neu; Tsai, Chia-Lung; Chao, Angel; Wang, Tzu-Hao

2009-01-01

Interlaboratory comparison of microarray data, even when using the same platform, imposes several challenges to scientists. RNA quality, RNA labeling efficiency, hybridization procedures and data-mining tools can all contribute variations in each laboratory. In Affymetrix GeneChips, about 11–20 different 25-mer oligonucleotides are used to measure the level of each transcript. Here, we report that ‘labeling extension values (LEVs)’, which are correlation coefficients between probe intensities and probe positions, are highly correlated with the gene expression levels (GEVs) on eukayotic Affymetrix microarray data. By analyzing LEVs and GEVs in the publicly available 2414 cel files of 20 Affymetrix microarray types covering 13 species, we found that correlations between LEVs and GEVs only exist in eukaryotic RNAs, but not in prokaryotic ones. Surprisingly, Affymetrix results of the same specimens that were analyzed in different laboratories could be clearly differentiated only by LEVs, leading to the identification of ‘laboratory signatures’. In the examined dataset, GSE10797, filtering out high-LEV genes did not compromise the discovery of biological processes that are constructed by differentially expressed genes. In conclusion, LEVs provide a new filtering parameter for microarray analysis of gene expression and it may improve the inter- and intralaboratory comparability of Affymetrix GeneChips data. PMID:19295132

Establishment and Application of a Visual DNA Microarray for the Detection of Food-borne Pathogens.

PubMed

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.

A Customized DNA Microarray for Microbial Source Tracking ...

EPA Pesticide Factsheets

It is estimated that more than 160, 000 miles of rivers and streams in the United States are impaired due to the presence of waterborne pathogens. These pathogens typically originate from human and other animal fecal pollution sources; therefore, a rapid microbial source tracking (MST) method is needed to facilitate water quality assessment and impaired water remediation. We report a novel qualitative DNA microarray technology consisting of 453 probes for the detection of general fecal and host-associated bacteria, viruses, antibiotic resistance, and other environmentally relevant genetic indicators. A novel data normalization and reduction approach is also presented to help alleviate false positives often associated with high-density microarray applications. To evaluate the performance of the approach, DNA and cDNA was isolated from swine, cattle, duck, goose and gull fecal reference samples, as well as soiled poultry liter and raw municipal sewage. Based on nonmetric multidimensional scaling analysis of results, findings suggest that the novel microarray approach may be useful for pathogen detection and identification of fecal contamination in recreational waters. The ability to simultaneously detect a large collection of environmentally important genetic indicators in a single test has the potential to provide water quality managers with a wide range of information in a short period of time. Future research is warranted to measure microarray performance i

Functional Analyses of NSF1 in Wine Yeast Using Interconnected Correlation Clustering and Molecular Analyses

PubMed Central

Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George

2013-01-01

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

An Efficient Microarray-Based Genotyping Platform for the Identification of Drug-Resistance Mutations in Majority and Minority Subpopulations of HIV-1 Quasispecies.

PubMed

Martín, Verónica; Perales, Celia; Fernández-Algar, María; Dos Santos, Helena G; Garrido, Patricia; Pernas, María; Parro, Víctor; Moreno, Miguel; García-Pérez, Javier; Alcamí, José; Torán, José Luis; Abia, David; Domingo, Esteban; Briones, Carlos

2016-01-01

The response of human immunodeficiency virus type 1 (HIV-1) quasispecies to antiretroviral therapy is influenced by the ensemble of mutants that composes the evolving population. Low-abundance subpopulations within HIV-1 quasispecies may determine the viral response to the administered drug combinations. However, routine sequencing assays available to clinical laboratories do not recognize HIV-1 minority variants representing less than 25% of the population. Although several alternative and more sensitive genotyping techniques have been developed, including next-generation sequencing (NGS) methods, they are usually very time consuming, expensive and require highly trained personnel, thus becoming unrealistic approaches in daily clinical practice. Here we describe the development and testing of a HIV-1 genotyping DNA microarray that detects and quantifies, in majority and minority viral subpopulations, relevant mutations and amino acid insertions in 42 codons of the pol gene associated with drug- and multidrug-resistance to protease (PR) and reverse transcriptase (RT) inhibitors. A customized bioinformatics protocol has been implemented to analyze the microarray hybridization data by including a new normalization procedure and a stepwise filtering algorithm, which resulted in the highly accurate (96.33%) detection of positive/negative signals. This microarray has been tested with 57 subtype B HIV-1 clinical samples extracted from multi-treated patients, showing an overall identification of 95.53% and 89.24% of the queried PR and RT codons, respectively, and enough sensitivity to detect minority subpopulations representing as low as 5-10% of the total quasispecies. The developed genotyping platform represents an efficient diagnostic and prognostic tool useful to personalize antiviral treatments in clinical practice.

CrossQuery: a web tool for easy associative querying of transcriptome data.

PubMed

Wagner, Toni U; Fischer, Andreas; Thoma, Eva C; Schartl, Manfred

2011-01-01

Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep-sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Microsoft Excel. CrossQuery enables researchers to quickly and freely work with transcriptome and microarray data sets requiring only minimal computer skills. Furthermore, CrossQuery allows growing association of multiple datasets as long as at least one common point of correlated information, such as transcript identification numbers or GO-terms, is shared between samples. For advanced users, the object-oriented plug-in and event-driven code design of both server-side and client-side scripts allow easy addition of new features, data sources and data types.

Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays

PubMed Central

Jin, Lian-Qun; Li, Jun-Wen; Wang, Sheng-Qi; Chao, Fu-Huan; Wang, Xin-Wei; Yuan, Zheng-Quan

2005-01-01

AIM: To detect the common intestinal pathogenic bacteria quickly and accurately. METHODS: A rapid (<3 h) experimental procedure was set up based upon the gene chip technology. Target genes were amplified and hybridized by oligonucleotide microarrays. RESULTS: One hundred and seventy strains of bacteria in pure culture belonging to 11 genera were successfully discriminated under comparatively same conditions, and a series of specific hybridization maps corresponding to each kind of bacteria were obtained. When this method was applied to 26 divided cultures, 25 (96.2%) were identified. CONCLUSION: Salmonella sp., Escherichia coli, Shigella sp., Listeria monocytogenes, Vibrio parahaemolyticus, Staphylococcus aureus, Proteus sp., Bacillus cereus, Vibrio cholerae, Enterococcus faecalis, Yersinia enterocolitica, and Campylobacter jejuni can be detected and identified by our microarrays. The accuracy, range, and discrimination power of this assay can be continually improved by adding further oligonucleotides to the arrays without any significant increase of complexity or cost. PMID:16437687

Nutrient control of gene expression in Drosophila: microarray analysis of starvation and sugar-dependent response

PubMed Central

Zinke, Ingo; Schütz, Christina S.; Katzenberger, Jörg D.; Bauer, Matthias; Pankratz, Michael J.

2002-01-01

We have identified genes regulated by starvation and sugar signals in Drosophila larvae using whole-genome microarrays. Based on expression profiles in the two nutrient conditions, they were organized into different categories that reflect distinct physiological pathways mediating sugar and fat metabolism, and cell growth. In the category of genes regulated in sugar-fed, but not in starved, animals, there is an upregulation of genes encoding key enzymes of the fat biosynthesis pathway and a downregulation of genes encoding lipases. The highest and earliest activated gene upon sugar ingestion is sugarbabe, a zinc finger protein that is induced in the gut and the fat body. Identification of potential targets using microarrays suggests that sugarbabe functions to repress genes involved in dietary fat breakdown and absorption. The current analysis provides a basis for studying the genetic mechanisms underlying nutrient signalling. PMID:12426388

Single molecule characterization of DNA binding and strand displacement reactions on lithographic DNA origami microarrays.

PubMed

Scheible, Max B; Pardatscher, Günther; Kuzyk, Anton; Simmel, Friedrich C

2014-03-12

The combination of molecular self-assembly based on the DNA origami technique with lithographic patterning enables the creation of hierarchically ordered nanosystems, in which single molecules are positioned at precise locations on multiple length scales. Based on a hybrid assembly protocol utilizing DNA self-assembly and electron-beam lithography on transparent glass substrates, we here demonstrate a DNA origami microarray, which is compatible with the requirements of single molecule fluorescence and super-resolution microscopy. The spatial arrangement allows for a simple and reliable identification of single molecule events and facilitates automated read-out and data analysis. As a specific application, we utilize the microarray to characterize the performance of DNA strand displacement reactions localized on the DNA origami structures. We find considerable variability within the array, which results both from structural variations and stochastic reaction dynamics prevalent at the single molecule level.

Characterization of a novel Lactobacillus species closely related to Lactobacillus johnsonii using a combination of molecular and comparative genomics methods.

PubMed

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.

Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

PubMed

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.

Identification of cell surface glycoprotein markers for glioblastoma-derived stem-like cells using a lectin microarray and LC-MS/MS approach

PubMed Central

He, Jintang; Liu, Yashu; Xie, Xiaolei; Zhu, Thant; Soules, Mary; DiMeco, Francesco; Vescovi, Angelo L.; Fan, Xing; Lubman, David M.

2010-01-01

Despite progress in the treatment of glioblastoma, more than 95% of patients suffering from this disease still die within two years. Recent findings support the belief that cancer stem-like cells are responsible for tumor formation and ongoing growth. Here a method combining lectin microarray and LC-MS/MS was used to discover the cell surface glycoprotein markers of a glioblastoma-derived stem-like cell line. Lectin microarray analysis of cell surface glycans showed that two galactose-specific lectins Trichosanthes kirilowii agglutinin (TKA) and Peanut agglutinin (PNA) could distinguish the stem-like glioblastoma neurosphere culture from a traditional adherent glioblastoma cell line. Agarose-bound TKA and PNA were used to capture the glycoproteins from the two cell cultures, which were analyzed by LC-MS/MS. The glycoproteins were quantified by spectral counting, resulting in the identification of 12 and 11 potential glycoprotein markers from the TKA and PNA captured fractions respectively. Almost all of these proteins were membrane proteins. Differential expression was verified by Western blotting analysis of 6 interesting proteins, including the up-regulated Receptor-type tyrosine-protein phosphatase zeta, Tenascin-C, Chondroitin sulfate proteoglycan NG2, Podocalyxin-like protein 1 and CD90, and the down-regulated CD44. An improved understanding of these proteins may be important for earlier diagnosis and better therapeutic targeting of glioblastoma. PMID:20235609

DNA Microarrays for Aptamer Identification and Structural Characterization

DTIC Science & Technology

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

Identification of Germ Plasm-Associated Transcripts by Microarray Analysis of Xenopus Vegetal Cortex RNA

PubMed Central

Cuykendall, Tawny N.; Houston, Douglas W.

2011-01-01

RNA localization is a common mechanism for regulating cell structure and function. Localized RNAs in Xenopus oocytes are critical for early development, including germline specification by the germ plasm. Despite the importance of these localized RNAs, only approximately 25 have been identified and fewer are functionally characterized. Using microarrays, we identified a large set of localized RNAs from the vegetal cortex. Overall, our results indicate a minimum of 275 localized RNAs in oocytes, or 2–3% of maternal transcripts, which are in general agreement with previous findings. We further validated vegetal localization for 24 candidates and further characterized three genes expressed in the germ plasm. We identified novel germ plasm expression for reticulon 3.1, exd2 (a novel exonuclease-domain encoding gene), and a putative noncoding RNA. Further analysis of these and other localized RNAs will likely identify new functions of germ plasm and facilitate the identification of cis-acting RNA localization elements. PMID:20503379

DNA microarray-based detection and identification of Burkholderia mallei, Burkholderia pseudomallei and Burkholderia spp.

PubMed

Schmoock, Gernot; Ehricht, Ralf; Melzer, Falk; Rassbach, Astrid; Scholz, Holger C; Neubauer, Heinrich; Sachse, Konrad; Mota, Rinaldo Aparecido; Saqib, Muhammad; Elschner, Mandy

2009-01-01

We developed a rapid oligonucleotide microarray assay based on genetic markers for the accurate identification and differentiation of Burkholderia (B.) mallei and Burkholderia pseudomallei, the agents of glanders and melioidosis, respectively. These two agents were clearly identified using at least 4 independent genetic markers including 16S rRNA gene, fliC, motB and also by novel species-specific target genes, identified by in silico sequence analysis. Specific hybridization signal profiles allowed the detection and differentiation of up to 10 further Burkholderia spp., including the closely related species Burkholderia thailandensis and Burkholderia-like agents, such as Burkholderia cepacia, Burkholderia cenocepacia, Burkholderia vietnamiensis, Burkholderia ambifaria, and Burkholderia gladioli, which are often associated with cystic fibrosis (CF) lung disease. The assay was developed using the easy-to-handle and economical ArrayTube (AT) platform. A representative strain panel comprising 44 B. mallei, 32 B. pseudomallei isolates, and various Burkholderia type strains were examined to validate the test. Assay specificity was determined by examination of 40 non-Burkholderia strains.

An Advanced Approach to Simultaneous Monitoring of Multiple Bacteria in Space

NASA Technical Reports Server (NTRS)

Eggers, M.

1998-01-01

The utility of a novel microarray-based microbial analyzer was demonstrated by the rapid detection, imaging, and identification of a mixture of microorganisms found in a waste water sample from the Lunar-Mars Life Support Test Project through the synergistic combination of: (1) judicious RNA probe selection via algorithms developed by University of Houston scientists; (2) tuned surface chemistries developed by Baylor College of Medicine scientists to facilitate hybridization of rRNA targets to DNA probes under very low salt conditions, thereby minimizing secondary structure; and (3) integration of the microarray printing and detection/imaging instrumentation by Genometrix to complete the quantitative analysis of microorganism mixtures.

Identification of Gender-specific Transcripts by Microarray in Gonad Tissue of Larval and Juvenile Xenopus tropicalis

EPA Science Inventory

Amphibian model species Xenopus tropicalis is currently being utilized by EPA in the development of a standardized in vivo reproductive toxicity assay. Perturbations to the hypothalamic-pituitary-gonadal axis from exposure to endocrine disrupting compounds during larval develop...

COMPARATIVE MICROARRAY EXPRESSION ANALYSIS OF SELECTED CANCER RELEVANT GENES IN HYPERTENSIVE RESISTANT VERSUS SUSCEPTIBLE RODENT STRAINS

EPA Science Inventory

Hypertension and cancer are prevalent diseases. Epidemiological studies suggest that hypertension may increase the long term risk of cancer. Identification of resistance and/or susceptibility genes using rodent models could provide important insights into the management and treat...

Statistical issues in signal extraction from microarrays

NASA Astrophysics Data System (ADS)

Bergemann, Tracy; Quiaoit, Filemon; Delrow, Jeffrey J.; Zhao, Lue Ping

2001-06-01

Microarray technologies are increasingly used in biomedical research to study genome-wide expression profiles in the post genomic era. Their popularity is largely due to their high throughput and economical affordability. For example, microarrays have been applied to studies of cell cycle, regulatory circuitry, cancer cell lines, tumor tissues, and drug discoveries. One obstacle facing the continued success of applying microarray technologies, however, is the random variaton present on microarrays: within signal spots, between spots and among chips. In addition, signals extracted by available software packages seem to vary significantly. Despite a variety of software packages, it appears that there are two major approaches to signal extraction. One approach is to focus on the identification of signal regions and hence estimation of signal levels above background levels. The other approach is to use the distribution of intensity values as a way of identifying relevant signals. Building upon both approaches, the objective of our work is to develop a method that is statistically rigorous and also efficient and robust. Statistical issues to be considered here include: (1) how to refine grid alignment so that the overall variation is minimized, (2) how to estimate the signal levels relative to the local background levels as well as the variance of this estimate, and (3) how to integrate red and green channel signals so that the ratio of interest is stable, simultaneously relaxing distributional assumptions.

Autonomous system for Web-based microarray image analysis.

PubMed

Bozinov, Daniel

2003-12-01

Software-based feature extraction from DNA microarray images still requires human intervention on various levels. Manual adjustment of grid and metagrid parameters, precise alignment of superimposed grid templates and gene spots, or simply identification of large-scale artifacts have to be performed beforehand to reliably analyze DNA signals and correctly quantify their expression values. Ideally, a Web-based system with input solely confined to a single microarray image and a data table as output containing measurements for all gene spots would directly transform raw image data into abstracted gene expression tables. Sophisticated algorithms with advanced procedures for iterative correction function can overcome imminent challenges in image processing. Herein is introduced an integrated software system with a Java-based interface on the client side that allows for decentralized access and furthermore enables the scientist to instantly employ the most updated software version at any given time. This software tool is extended from PixClust as used in Extractiff incorporated with Java Web Start deployment technology. Ultimately, this setup is destined for high-throughput pipelines in genome-wide medical diagnostics labs or microarray core facilities aimed at providing fully automated service to its users.

Development and validation of a microarray for the investigation of the CAZymes encoded by the human gut microbiome.

PubMed

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.

Methodological Challenges in Protein Microarray and Immunohistochemistry for the Discovery of Novel Autoantibodies in Paediatric Acute Disseminated Encephalomyelitis

PubMed Central

Peschl, Patrick; Ramberger, Melanie; Höftberger, Romana; Jöhrer, Karin; Baumann, Matthias; Rostásy, Kevin; Reindl, Markus

2017-01-01

Acute disseminated encephalomyelitis (ADEM) is a rare autoimmune-mediated demyelinating disease affecting mainly children and young adults. Differentiation to multiple sclerosis is not always possible, due to overlapping clinical symptoms and recurrent and multiphasic forms. Until now, immunoglobulins reactive to myelin oligodendrocyte glycoprotein (MOG antibodies) have been found in a subset of patients with ADEM. However, there are still patients lacking autoantibodies, necessitating the identification of new autoantibodies as biomarkers in those patients. Therefore, we aimed to identify novel autoantibody targets in ADEM patients. Sixteen ADEM patients (11 seronegative, 5 seropositive for MOG antibodies) were analysed for potential new biomarkers, using a protein microarray and immunohistochemistry on rat brain tissue to identify antibodies against intracellular and surface neuronal and glial antigens. Nine candidate antigens were identified in the protein microarray analysis in at least two patients per group. Immunohistochemistry on rat brain tissue did not reveal new target antigens. Although no new autoantibody targets could be found here, future studies should aim to identify new biomarkers for therapeutic and prognostic purposes. The microarray analysis and immunohistochemistry methods used here have several limitations, which should be considered in future searches for biomarkers. PMID:28327523

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

Identification of candidate genes involved in neuroblastoma progression by combining genomic and expression microarrays with survival data.

PubMed

Łastowska, M; Viprey, V; Santibanez-Koref, M; Wappler, I; Peters, H; Cullinane, C; Roberts, P; Hall, A G; Tweddle, D A; Pearson, A D J; Lewis, I; Burchill, S A; Jackson, M S

2007-11-22

Identifying genes, whose expression is consistently altered by chromosomal gains or losses, is an important step in defining genes of biological relevance in a wide variety of tumour types. However, additional criteria are needed to discriminate further among the large number of candidate genes identified. This is particularly true for neuroblastoma, where multiple genomic copy number changes of proven prognostic value exist. We have used Affymetrix microarrays and a combination of fluorescent in situ hybridization and single nucleotide polymorphism (SNP) microarrays to establish expression profiles and delineate copy number alterations in 30 primary neuroblastomas. Correlation of microarray data with patient survival and analysis of expression within rodent neuroblastoma cell lines were then used to define further genes likely to be involved in the disease process. Using this approach, we identify >1000 genes within eight recurrent genomic alterations (loss of 1p, 3p, 4p, 10q and 11q, 2p gain, 17q gain, and the MYCN amplicon) whose expression is consistently altered by copy number change. Of these, 84 correlate with patient survival, with the minimal regions of 17q gain and 4p loss being enriched significantly for such genes. These include genes involved in RNA and DNA metabolism, and apoptosis. Orthologues of all but one of these genes on 17q are overexpressed in rodent neuroblastoma cell lines. A significant excess of SNPs whose copy number correlates with survival is also observed on proximal 4p in stage 4 tumours, and we find that deletion of 4p is associated with improved outcome in an extended cohort of tumours. These results define the major impact of genomic copy number alterations upon transcription within neuroblastoma, and highlight genes on distal 17q and proximal 4p for downstream analyses. They also suggest that integration of discriminators, such as survival and comparative gene expression, with microarray data may be useful in the identification of critical genes within regions of loss or gain in many human cancers.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.

PubMed

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

PubMed Central

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

A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

PubMed Central

Zuckerman, Neta S.; Noam, Yair; Goldsmith, Andrea J.; Lee, Peter P.

2013-01-01

Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures - these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets. PMID:23990767

The importance of prenatal 3-dimensional sonography in a case of a segmental overgrowth syndrome with unclear chromosomal microarray results.

PubMed

Asoglu, Mehmet Resit; Higgs, Amanda; Esin, Sertac; Kaplan, Julie; Turan, Sifa

2018-06-01

PIK3CA-related overgrowth spectrum, caused by mosaic mutations in the PIK3CA gene, is associated with regional or generalized asymmetric overgrowth of the body or a body part in addition to other clinical findings. Three-dimensional ultrasonography (3-D US) has the capability to display structural abnormalities in soft tissues or other organs, thereby facilitating identification of segmental overgrowth lesions. We present a case suspected of having a segmental overgrowth disorder based on 3-D US, whose chromosomal microarray result was abnormal, but apparently was not the cause of the majority of the fetus's clinical features. © 2017 Wiley Periodicals, Inc.

Development of a Sensitive Microarray Platform for the Ranking of Galectin Inhibitors: Identification of a Selective Galectin-3 Inhibitor.

PubMed

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.

Evaluation of two outlier-detection-based methods for detecting tissue-selective genes from microarray data.

PubMed

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-05-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent's non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent's method is not suitable for ROKU.

Suppression subtractive hybridization as a tool to identify anthocyanin metabolism-related genes in apple skin.

PubMed

Ban, Yusuke; Moriguchi, Takaya

2010-01-01

The pigmentation of anthocyanins is one of the important determinants for consumer preference and marketability in horticultural crops such as fruits and flowers. To elucidate the mechanisms underlying the physiological process leading to the pigmentation of anthocyanins, identification of the genes differentially expressed in response to anthocyanin accumulation is a useful strategy. Currently, microarrays have been widely used to isolate differentially expressed genes. However, the use of microarrays is limited by its high cost of special apparatus and materials. Therefore, availability of microarrays is limited and does not come into common use at present. Suppression subtractive hybridization (SSH) is an alternative tool that has been widely used to identify differentially expressed genes due to its easy handling and relatively low cost. This chapter describes the procedures for SSH, including RNA extraction from polysaccharides and polyphenol-rich samples, poly(A)+ RNA purification, evaluation of subtraction efficiency, and differential screening using reverse northern in apple skin.

COLD-PCR and microarray: two independent highly sensitive approaches allowing the identification of fetal paternally inherited mutations in maternal plasma.

PubMed

Galbiati, Silvia; Monguzzi, Alessandra; Damin, Francesco; Soriani, Nadia; Passiu, Marianna; Castellani, Carlo; Natacci, Federica; Curcio, Cristina; Seia, Manuela; Lalatta, Faustina; Chiari, Marcella; Ferrari, Maurizio; Cremonesi, Laura

2016-07-01

Until now, non-invasive prenatal diagnosis of genetic diseases found only limited routine applications. In autosomal recessive diseases, it can be used to determine the carrier status of the fetus through the detection of a paternally inherited disease allele in cases where maternal and paternal mutated alleles differ. Conditions for non-invasive identification of fetal paternally inherited mutations in maternal plasma were developed by two independent approaches: coamplification at lower denaturation temperature-PCR (COLD-PCR) and highly sensitive microarrays. Assays were designed for identifying 14 mutations, 7 causing β-thalassaemia and 7 cystic fibrosis. In total, 87 non-invasive prenatal diagnoses were performed by COLD-PCR in 75 couples at risk for β-thalassaemia and 12 for cystic fibrosis. First, to identify the more appropriate methodology for the analysis of minority mutated fetal alleles in maternal plasma, both fast and full COLD-PCR protocols were developed for the most common Italian β-thalassaemia Cd39 and IVSI.110 mutations. In 5 out of 31 samples, no enrichment was obtained with the fast protocol, while full COLD-PCR provided the correct fetal genotypes. Thus, full COLD-PCR protocols were developed for all the remaining mutations and all analyses confirmed the fetal genotypes obtained by invasive prenatal diagnosis. Microarray analysis was performed on 40 samples from 28 couples at risk for β-thalassaemia and 12 for cystic fibrosis. Results were in complete concordance with those obtained by both COLD-PCR and invasive procedures. COLD-PCR and microarray approaches are not expensive, simple to handle, fast and can be easily set up in specialised clinical laboratories where prenatal diagnosis is routinely performed. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Use of homologous and heterologous gene expression profiling tools to characterize transcription dynamics during apple fruit maturation and ripening.

PubMed

Costa, Fabrizio; Alba, Rob; Schouten, Henk; Soglio, Valeria; Gianfranceschi, Luca; Serra, Sara; Musacchi, Stefano; Sansavini, Silviero; Costa, Guglielmo; Fei, Zhangjun; Giovannoni, James

2010-10-25

Fruit development, maturation and ripening consists of a complex series of biochemical and physiological changes that in climacteric fruits, including apple and tomato, are coordinated by the gaseous hormone ethylene. These changes lead to final fruit quality and understanding of the functional machinery underlying these processes is of both biological and practical importance. To date many reports have been made on the analysis of gene expression in apple. In this study we focused our investigation on the role of ethylene during apple maturation, specifically comparing transcriptomics of normal ripening with changes resulting from application of the hormone receptor competitor 1-methylcyclopropene. To gain insight into the molecular process regulating ripening in apple, and to compare to tomato (model species for ripening studies), we utilized both homologous and heterologous (tomato) microarray to profile transcriptome dynamics of genes involved in fruit development and ripening, emphasizing those which are ethylene regulated.The use of both types of microarrays facilitated transcriptome comparison between apple and tomato (for the later using data previously published and available at the TED: tomato expression database) and highlighted genes conserved during ripening of both species, which in turn represent a foundation for further comparative genomic studies. The cross-species analysis had the secondary aim of examining the efficiency of heterologous (specifically tomato) microarray hybridization for candidate gene identification as related to the ripening process. The resulting transcriptomics data revealed coordinated gene expression during fruit ripening of a subset of ripening-related and ethylene responsive genes, further facilitating the analysis of ethylene response during fruit maturation and ripening. Our combined strategy based on microarray hybridization enabled transcriptome characterization during normal climacteric apple ripening, as well as definition of ethylene-dependent transcriptome changes. Comparison with tomato fruit maturation and ethylene responsive transcriptome activity facilitated identification of putative conserved orthologous ripening-related genes, which serve as an initial set of candidates for assessing conservation of gene activity across genomes of fruit bearing plant species.

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Curation of microarray oligonucleotides and corresponding ESTs/cDNAs used for gene expression analysis in zebra finches.

PubMed

Lovell, Peter V; Huizinga, Nicole A; Getachew, Abel; Mees, Brianna; Friedrich, Samantha R; Wirthlin, Morgan; Mello, Claudio V

2018-05-18

Zebra finches are a major model organism for investigating mechanisms of vocal learning, a trait that enables spoken language in humans. The development of cDNA collections with expressed sequence tags (ESTs) and microarrays has allowed for extensive molecular characterizations of circuitry underlying vocal learning and production. However, poor database curation can lead to errors in transcriptome and bioinformatics analyses, limiting the impact of these resources. Here we used genomic alignments and synteny analysis for orthology verification to curate and reannotate ~ 35% of the oligonucleotides and corresponding ESTs/cDNAs that make-up Agilent microarrays for gene expression analysis in finches. We found that: (1) 5475 out of 43,084 oligos (a) failed to align to the zebra finch genome, (b) aligned to multiple loci, or (c) aligned to Chr_un only, and thus need to be flagged until a better genome assembly is available, or (d) reflect cloning artifacts; (2) Out of 9635 valid oligos examined further, 3120 were incorrectly named, including 1533 with no known orthologs; and (3) 2635 oligos required name update. The resulting curated dataset provides a reference for correcting gene identification errors in previous finch microarrays studies, and avoiding such errors in future studies.

Characterization of a novel Lactobacillus species closely related to Lactobacillus johnsonii using a combination of molecular and comparative genomics methods

PubMed Central

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

Identification of the TFII-I family target genes in the vertebrate genome.

PubMed

Chimge, Nyam-Osor; Makeyev, Aleksandr V; Ruddle, Frank H; Bayarsaihan, Dashzeveg

2008-07-01

GTF2I and GTF2IRD1 encode members of the TFII-I transcription factor family and are prime candidates in the Williams syndrome, a complex neurodevelopmental disorder. Our previous expression microarray studies implicated TFII-I proteins in the regulation of a number of genes critical in various aspects of cell physiology. Here, we combined bioinformatics and microarray results to identify TFII-I downstream targets in the vertebrate genome. These results were validated by chromatin immunoprecipitation and siRNA analysis. The collected evidence revealed the complexity of TFII-I-mediated processes that involve distinct regulatory networks. Altogether, these results lead to a better understanding of specific molecular events, some of which may be responsible for the Williams syndrome phenotype.

Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways

PubMed Central

Kaushik, Abhinav; Ali, Shakir; Gupta, Dinesh

2017-01-01

Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA. PMID:28084397

Use of photopolymerization for the rapid and cost-effective identification of Shiga toxin-producing Escherichia coli on DNA microarrays

USDA-ARS?s Scientific Manuscript database

Shiga toxin-producing Escherichia coli O157:H7 is a leading cause of foodborne illness worldwide. To evaluate better methods to rapidly detect and genotype E. coli O157 virulent strains, the present study explored the use of photopolymerization, a colorimetric and photoinduced signal amplification d...

Universal Detection and Identification of Avian Influenza Virus by Use of Resequencing Microarrays

DTIC Science & Technology

2009-04-01

For the RT step, primer LN was replaced by primer NLN (a random 9-mer with a linker se- quence). One picogram each of two internal controls (NAC1...samples (data not shown). These data indicated that most of the avian H5N1 samples identified were presumably sensitive to neuraminidase inhibitors

DNA microarrays for identifying fishes.

PubMed

Kochzius, M; Nölte, M; Weber, H; Silkenbeumer, N; Hjörleifsdottir, S; Hreggvidsson, G O; Marteinsson, V; Kappel, K; Planes, S; Tinti, F; Magoulas, A; Garcia Vazquez, E; Turan, C; Hervet, C; Campo Falgueras, D; Antoniou, A; Landi, M; Blohm, D

2008-01-01

In many cases marine organisms and especially their diverse developmental stages are difficult to identify by morphological characters. DNA-based identification methods offer an analytically powerful addition or even an alternative. In this study, a DNA microarray has been developed to be able to investigate its potential as a tool for the identification of fish species from European seas based on mitochondrial 16S rDNA sequences. Eleven commercially important fish species were selected for a first prototype. Oligonucleotide probes were designed based on the 16S rDNA sequences obtained from 230 individuals of 27 fish species. In addition, more than 1200 sequences of 380 species served as sequence background against which the specificity of the probes was tested in silico. Single target hybridisations with Cy5-labelled, PCR-amplified 16S rDNA fragments from each of the 11 species on microarrays containing the complete set of probes confirmed their suitability. True-positive, fluorescence signals obtained were at least one order of magnitude stronger than false-positive cross-hybridisations. Single nontarget hybridisations resulted in cross-hybridisation signals at approximately 27% of the cases tested, but all of them were at least one order of magnitude lower than true-positive signals. This study demonstrates that the 16S rDNA gene is suitable for designing oligonucleotide probes, which can be used to differentiate 11 fish species. These data are a solid basis for the second step to create a "Fish Chip" for approximately 50 fish species relevant in marine environmental and fisheries research, as well as control of fisheries products.

Application of Protein Microarrays for Multiplexed Detection of Antibodies to Tumor Antigens in Breast Cancer

PubMed Central

Anderson, Karen S.; Ramachandran, Niroshan; Wong, Jessica; Raphael, Jacob V.; Hainsworth, Eugenie; Demirkan, Gokhan; Cramer, Daniel; Aronzon, Diana; Hodi, F. Stephen; Harris, Lyndsay; Logvinenko, Tanya; LaBaer, Joshua

2012-01-01

There is strong preclinical evidence that cancer, including breast cancer, undergoes immune surveillance. This continual monitoring, by both the innate and the adaptive immune systems, recognizes changes in protein expression, mutation, folding, glycosylation, and degradation. Local immune responses to tumor antigens are amplified in draining lymph nodes, and then enter the systemic circulation. The antibody response to tumor antigens, such as p53 protein, are robust, stable, and easily detected in serum, may exist in greater concentrations than their cognate antigens, and are potential highly specific biomarkers for cancer. However, antibodies have limited sensitivities as single analytes, and differences in protein purification and assay characteristics have limited their clinical application. For example, p53 autoantibodies in the sera are highly specific for cancer patients, but are only detected in the sera of 10-20% of patients with breast cancer. Detection of p53 autoantibodies is dependent on tumor burden, p53 mutation, rapidly decreases with effective therapy, but is relatively independent of breast cancer subtype. Although antibodies to hundreds of other tumor antigens have been identified in the sera of breast cancer patients, very little is known about the specificity and clinical impact of the antibody immune repertoire to breast cancer. Recent advances in proteomic technologies have the potential for rapid identification of immune response signatures for breast cancer diagnosis and monitoring. We have adapted programmable protein microarrays for the specific detection of autoantibodies in breast cancer. Here, we present the first demonstration of the application of programmable protein microarray ELISAs for the rapid identification of breast cancer autoantibodies. PMID:18311903

Development of a miniaturized DNA microarray for identification of 66 virulence genes of Legionella pneumophila.

PubMed

Żak, Mariusz; Zaborowski, Piotr; Baczewska-Rej, Milena; Zasada, Aleksandra A; Matuszewska, Renata; Krogulska, Bożena

2011-12-20

For the last five years, Legionella sp. infections and legionnaire's disease in Poland have been receiving a lot of attention, because of the new regulations concerning microbiological quality of drinking water. This was the inspiration to search for and develop a new assay to identify many virulence genes of Legionella pneumophila to better understand their distribution in environmental and clinical strains. The method might be an invaluable help in infection risk assessment and in epidemiological investigations. The microarray is based on Array Tube technology. It contains 3 positive and 1 negative control. Target genes encode structural elements of T4SS, effector proteins and factors not related to T4SS. Probes were designed using OligoWiz software and data analyzed using IconoClust software. To isolate environmental and clinical strains, BAL samples and samples of hot water from different and independent hot water distribution systems of public utility buildings were collected. We have developed a miniaturized DNA microarray for identification of 66 virulence genes of L. pneumophila. The assay is specific to L. pneumophila sg 1 with sensitivity sufficient to perform the assay using DNA isolated from a single L. pneumophila colony. Seven environmental strains were analyzed. Two exhibited a hybridization pattern distinct from the reference strain. The method is time- and cost-effective. Initial studies have shown that genes encoding effector proteins may vary among environmental strains. Further studies might help to identify set of genes increasing the risk of clinical disease and to determine the pathogenic potential of environmental strains.

Chromosomal microarray analysis as the first-tier test for the identification of pathogenic copy number variants in chromosome 9 pericentric regions and its challenge.

PubMed

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.

BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.

PubMed

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.

Molecular biological identification of Babesia, Theileria, and Anaplasma species in cattle in Egypt using PCR assays, gene sequence analysis and a novel DNA microarray.

PubMed

El-Ashker, Maged; Hotzel, Helmut; Gwida, Mayada; El-Beskawy, Mohamed; Silaghi, Cornelia; Tomaso, Herbert

2015-01-30

In this preliminary study, a novel DNA microarray system was tested for the diagnosis of bovine piroplasmosis and anaplasmosis in comparison with microscopy and PCR assay results. In the Dakahlia Governorate, Egypt, 164 cattle were investigated for the presence of piroplasms and Anaplasma species. All investigated cattle were clinically examined. Blood samples were screened for the presence of blood parasites using microscopy and PCR assays. Seventy-one animals were acutely ill, whereas 93 were apparently healthy. In acutely ill cattle, Babesia/Theileria species (n=11) and Anaplasma marginale (n=10) were detected. Mixed infections with Babesia/Theileria spp. and A. marginale were present in two further cases. A. marginale infections were also detected in apparently healthy subjects (n=23). The results of PCR assays were confirmed by DNA sequencing. All samples that were positive by PCR for Babesia/Theileria spp. gave also positive results in the microarray analysis. The microarray chips identified Babesia bovis (n=12) and Babesia bigemina (n=2). Cattle with babesiosis were likely to have hemoglobinuria and nervous signs when compared to those with anaplasmosis that frequently had bloody feces. We conclude that clinical examination in combination with microscopy are still very useful in diagnosing acute cases of babesiosis and anaplasmosis, but a combination of molecular biological diagnostic assays will detect even asymptomatic carriers. In perspective, parallel detection of Babesia/Theileria spp. and A. marginale infections using a single microarray system will be a valuable improvement. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

A low density microarray method for the identification of human papillomavirus type 18 variants.

PubMed

Meza-Menchaca, Thuluz; Williams, John; Rodríguez-Estrada, Rocío B; García-Bravo, Aracely; Ramos-Ligonio, Ángel; López-Monteon, Aracely; Zepeda, Rossana C

2013-09-26

We describe a novel microarray based-method for the screening of oncogenic human papillomavirus 18 (HPV-18) molecular variants. Due to the fact that sequencing methodology may underestimate samples containing more than one variant we designed a specific and sensitive stacking DNA hybridization assay. This technology can be used to discriminate between three possible phylogenetic branches of HPV-18. Probes were attached covalently on glass slides and hybridized with single-stranded DNA targets. Prior to hybridization with the probes, the target strands were pre-annealed with the three auxiliary contiguous oligonucleotides flanking the target sequences. Screening HPV-18 positive cell lines and cervical samples were used to evaluate the performance of this HPV DNA microarray. Our results demonstrate that the HPV-18's variants hybridized specifically to probes, with no detection of unspecific signals. Specific probes successfully reveal detectable point mutations in these variants. The present DNA oligoarray system can be used as a reliable, sensitive and specific method for HPV-18 variant screening. Furthermore, this simple assay allows the use of inexpensive equipment, making it accessible in resource-poor settings.

A Low Density Microarray Method for the Identification of Human Papillomavirus Type 18 Variants

PubMed Central

Meza-Menchaca, Thuluz; Williams, John; Rodríguez-Estrada, Rocío B.; García-Bravo, Aracely; Ramos-Ligonio, Ángel; López-Monteon, Aracely; Zepeda, Rossana C.

2013-01-01

We describe a novel microarray based-method for the screening of oncogenic human papillomavirus 18 (HPV-18) molecular variants. Due to the fact that sequencing methodology may underestimate samples containing more than one variant we designed a specific and sensitive stacking DNA hybridization assay. This technology can be used to discriminate between three possible phylogenetic branches of HPV-18. Probes were attached covalently on glass slides and hybridized with single-stranded DNA targets. Prior to hybridization with the probes, the target strands were pre-annealed with the three auxiliary contiguous oligonucleotides flanking the target sequences. Screening HPV-18 positive cell lines and cervical samples were used to evaluate the performance of this HPV DNA microarray. Our results demonstrate that the HPV-18's variants hybridized specifically to probes, with no detection of unspecific signals. Specific probes successfully reveal detectable point mutations in these variants. The present DNA oligoarray system can be used as a reliable, sensitive and specific method for HPV-18 variant screening. Furthermore, this simple assay allows the use of inexpensive equipment, making it accessible in resource-poor settings. PMID:24077317

Development of oligonucleotide microarrays for simultaneous multi-species identification of Phellinus tree-pathogenic fungi.

PubMed

Tzean, Yuh; Shu, Po-Yao; Liou, Ruey-Fen; Tzean, Shean-Shong

2016-03-01

Polyporoid Phellinus fungi are ubiquitously present in the environment and play an important role in shaping forest ecology. Several species of Phellinus are notorious pathogens that can affect a broad variety of tree species in forest, plantation, orchard and urban habitats; however, current detection methods are overly complex and lack the sensitivity required to identify these pathogens at the species level in a timely fashion for effective infestation control. Here, we describe eight oligonucleotide microarray platforms for the simultaneous and specific detection of 17 important Phellinus species, using probes generated from the internal transcribed spacer regions unique to each species. The sensitivity, robustness and efficiency of this Phellinus microarray system was subsequently confirmed against template DNA from two key Phellinus species, as well as field samples collected from tree roots, trunks and surrounding soil. This system can provide early, specific and convenient detection of Phellinus species for forestry, arboriculture and quarantine inspection, and could potentially help to mitigate the environmental and economic impact of Phellinus-related diseases. © 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Microarray-based characterization of differential gene expression during vocal fold wound healing in rats

PubMed Central

Welham, Nathan V.; Ling, Changying; Dawson, John A.; Kendziorski, Christina; Thibeault, Susan L.; Yamashita, Masaru

2015-01-01

The vocal fold (VF) mucosa confers elegant biomechanical function for voice production but is susceptible to scar formation following injury. Current understanding of VF wound healing is hindered by a paucity of data and is therefore often generalized from research conducted in skin and other mucosal systems. Here, using a previously validated rat injury model, expression microarray technology and an empirical Bayes analysis approach, we generated a VF-specific transcriptome dataset to better capture the system-level complexity of wound healing in this specialized tissue. We measured differential gene expression at 3, 14 and 60 days post-injury compared to experimentally naïve controls, pursued functional enrichment analyses to refine and add greater biological definition to the previously proposed temporal phases of VF wound healing, and validated the expression and localization of a subset of previously unidentified repair- and regeneration-related genes at the protein level. Our microarray dataset is a resource for the wider research community and has the potential to stimulate new hypotheses and avenues of investigation, improve biological and mechanistic insight, and accelerate the identification of novel therapeutic targets. PMID:25592437

Evaluation of Two Outlier-Detection-Based Methods for Detecting Tissue-Selective Genes from Microarray Data

PubMed Central

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-01-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent’s non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent’s method is not suitable for ROKU. PMID:19936074

Identification of rat lung-specific microRNAs by micoRNA microarray: valuable discoveries for the facilitation of lung research.

PubMed

Wang, Yang; Weng, Tingting; Gou, Deming; Chen, Zhongming; Chintagari, Narendranath Reddy; Liu, Lin

2007-01-24

An important mechanism for gene regulation utilizes small non-coding RNAs called microRNAs (miRNAs). These small RNAs play important roles in tissue development, cell differentiation and proliferation, lipid and fat metabolism, stem cells, exocytosis, diseases and cancers. To date, relatively little is known about functions of miRNAs in the lung except lung cancer. In this study, we utilized a rat miRNA microarray containing 216 miRNA probes, printed in-house, to detect the expression of miRNAs in the rat lung compared to the rat heart, brain, liver, kidney and spleen. Statistical analysis using Significant Analysis of Microarray (SAM) and Tukey Honestly Significant Difference (HSD) revealed 2 miRNAs (miR-195 and miR-200c) expressed specifically in the lung and 9 miRNAs co-expressed in the lung and another organ. 12 selected miRNAs were verified by Northern blot analysis. The identified lung-specific miRNAs from this work will facilitate functional studies of miRNAs during normal physiological and pathophysiological processes of the lung.

Application of HLA-DRB1 genotyping by oligonucleotide micro-array technology in forensic medicine.

PubMed

Jiang, Bin; Li, Yao; Wu, Hai; He, Xianmin; Li, Chengtao; Li, Li; Tang, Rong; Xie, Yi; Mao, Yumin

2006-10-16

The human leukocyte antigen (HLA) system is known to be the most complex polymorphic system in the human genome. Among all of the HLA loci, HLA-DRB1 has the second largest number of alleles. The purpose of this study is to develop an oligonucleotide micro-array based HLA-DRB1 typing system for use in forensic identification, anthropology, tissue transplantation, and other genetic research fields. The system was developed by analyzing the HLA-DRB1 (DRB1) genotypes in 1198 unrelated healthy Chinese Han individuals originating from various parts of China and residing in Shanghai, China. Polymerase chain reaction (PCR) coupled with the oligonucleotide micro-array technology was used to detect and type HLA-DRB1 alleles of the sample individuals. The reliability, sensitivity, consistency and specificity were evaluated for use in forensic identification. Furthermore, a meta-analysis was carried out by comparing the allele frequencies of the HLA-DRB1 locus with those of other Chinese Han groups, Chinese minorities and other ethnic populations. All the DNA samples yielded a 273 bp amplification product, with no other amplification products in this length range. The minimum quantity of DNA detected by this method is 15 ng in a PCR reaction system of 25 microl. The population studied appeared to be not in Hardy-Weinberg equilibrium. Observed heterozygosity (Ho), expected heterozygosity (He), expected probability of exclusion (PE), polymorphic information content (PIC), and discrimination power (DP) of the HLA-DRB1 locus from the Shanghai Han ethnic group were evaluated to be 0.8022, 0.8870, 0.7741, 0.8771, 0.9750, respectively. A total of 25 HLA-DRB1 alleles were identified. HLA-DRB1*09XX, *04XX, *12XX and *15XX were the most frequent DRB1 alleles, which were observed in 58.76% of the sample. One hundred and sixteen genotypes were found. The five most frequent genotypes were: *04XX/*04XX (0.0626), *09XX/*09XX (0.0593), *04XX/*09XX (0.0551), *09XX/*15XX (0.0384) and *08XX/*12XX (0.0351). The meta-analysis showed that there were uniquely distributed features of DRB1 alleles among various ethnic populations and among the studied population groups from various regions with the same ethnic origin. An HLA-DRB1 genotyping system has been developed and established based on the oligonucleotide micro-array technology. The HLA-DRB1 typing of the Han population in Shanghai has revealed a relatively high heterogeneity. Information obtained in this study will be useful for medical and forensic applications as well as in anthropology research. Large-scale micro-array detection is highly accurate and reliable for DNA-based HLA-DRB1 genotyping. These results suggest that HLA-DRB1 DNA polymorphisms and the database of the Shanghai Han group have useful applications in processing forensic casework (as personal identification, paternity test), tracing population migration and genetic diagnosis.

Model-based variance-stabilizing transformation for Illumina microarray data.

PubMed

Lin, Simon M; Du, Pan; Huber, Wolfgang; Kibbe, Warren A

2008-02-01

Variance stabilization is a step in the preprocessing of microarray data that can greatly benefit the performance of subsequent statistical modeling and inference. Due to the often limited number of technical replicates for Affymetrix and cDNA arrays, achieving variance stabilization can be difficult. Although the Illumina microarray platform provides a larger number of technical replicates on each array (usually over 30 randomly distributed beads per probe), these replicates have not been leveraged in the current log2 data transformation process. We devised a variance-stabilizing transformation (VST) method that takes advantage of the technical replicates available on an Illumina microarray. We have compared VST with log2 and Variance-stabilizing normalization (VSN) by using the Kruglyak bead-level data (2006) and Barnes titration data (2005). The results of the Kruglyak data suggest that VST stabilizes variances of bead-replicates within an array. The results of the Barnes data show that VST can improve the detection of differentially expressed genes and reduce false-positive identifications. We conclude that although both VST and VSN are built upon the same model of measurement noise, VST stabilizes the variance better and more efficiently for the Illumina platform by leveraging the availability of a larger number of within-array replicates. The algorithms and Supplementary Data are included in the lumi package of Bioconductor, available at: www.bioconductor.org.

MMASS: an optimized array-based method for assessing CpG island methylation.

PubMed

Ibrahim, Ashraf E K; Thorne, Natalie P; Baird, Katie; Barbosa-Morais, Nuno L; Tavaré, Simon; Collins, V Peter; Wyllie, Andrew H; Arends, Mark J; Brenton, James D

2006-01-01

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation.

Identification of Prostate Cancer Prognostic Markers

DTIC Science & Technology

2016-10-01

Technologies). For this, the oxygen consumption rate (OCR) in the PC-3 control and ECI1-overexpressing clones was measured following their maintenance...carnitine Carnitine β-oxydation Etomoxir Page 25 of 31 Figure 10: Mitochondrial Respiration in ECI1-overexpressing PC-3 Clones. Oxygen Consumption rate... FISH ), prognostic markers, biomarkers, tissue microarrays, autophagy 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES

The Plasmodium falciparum Sexual Development Transcriptome: A Microarray Analysis using Ontology-Based Pattern Identification

DTIC Science & Technology

2005-06-17

ciparum. Mol Biochem Parasitol 1992;56(2):239–50. [56] Vinetz JM, Dave SK, Specht CA, et al. The chitinase PfCHT1 from the human malaria parasite Plasmodium...falciparum lacks proenzyme and chitin -binding domains and displays unique substrate prefer- ences. Proc Natl Acad Sci USA 1999;96(24):14061–6. [57

Animal Viruses Probe dataset (AVPDS) for microarray-based diagnosis and identification of viruses.

PubMed

Yadav, Brijesh S; Pokhriyal, Mayank; Vasishtha, Dinesh P; Sharma, Bhaskar

2014-03-01

AVPDS (Animal Viruses Probe dataset) is a dataset of virus-specific and conserve oligonucleotides for identification and diagnosis of viruses infecting animals. The current dataset contain 20,619 virus specific probes for 833 viruses and their subtypes and 3,988 conserved probes for 146 viral genera. Dataset of virus specific probe has been divided into two fields namely virus name and probe sequence. Similarly conserved probes for virus genera table have genus, and subgroup within genus name and probe sequence. The subgroup within genus is artificially divided subgroups with no taxonomic significance and contains probes which identifies viruses in that specific subgroup of the genus. Using this dataset we have successfully diagnosed the first case of Newcastle disease virus in sheep and reported a mixed infection of Bovine viral diarrhea and Bovine herpesvirus in cattle. These dataset also contains probes which cross reacts across species experimentally though computationally they meet specifications. These probes have been marked. We hope that this dataset will be useful in microarray-based detection of viruses. The dataset can be accessed through the link https://dl.dropboxusercontent.com/u/94060831/avpds/HOME.html.

Stress Sensors and Signal Transducers in Cyanobacteria

PubMed Central

Los, Dmitry A.; Zorina, Anna; Sinetova, Maria; Kryazhov, Sergey; Mironov, Kirill; Zinchenko, Vladislav V.

2010-01-01

In living cells, the perception of environmental stress and the subsequent transduction of stress signals are primary events in the acclimation to changes in the environment. Some molecular sensors and transducers of environmental stress cannot be identified by traditional and conventional methods. Based on genomic information, a systematic approach has been applied to the solution of this problem in cyanobacteria, involving mutagenesis of potential sensors and signal transducers in combination with DNA microarray analyses for the genome-wide expression of genes. Forty-five genes for the histidine kinases (Hiks), 12 genes for serine-threonine protein kinases (Spks), 42 genes for response regulators (Rres), seven genes for RNA polymerase sigma factors, and nearly 70 genes for transcription factors have been successfully inactivated by targeted mutagenesis in the unicellular cyanobacterium Synechocystis sp. PCC 6803. Screening of mutant libraries by genome-wide DNA microarray analysis under various stress and non-stress conditions has allowed identification of proteins that perceive and transduce signals of environmental stress. Here we summarize recent progress in the identification of sensory and regulatory systems, including Hiks, Rres, Spks, sigma factors, transcription factors, and the role of genomic DNA supercoiling in the regulation of the responses of cyanobacterial cells to various types of stress. PMID:22294932

[Genotyping of BRCA1, BRCA2 and CHEK2 germline mutations in Russian breast cancer patients using diagnostic biochips].

PubMed

Nasedkina, T V; Gromyko, O E; Emel'ianova, M A; Ignatova, E O; Kazubskaia, T P; Portnoĭ, S M; Zasedatelev, A S; Liubchenko, L N

2014-01-01

Germline mutations of BRCA1/2 genes cause the predisposition of their carriers to breast or/and ovary cancers (BC or/and OC) during the lifetime. Identification of these mutations is a basis of molecular diagnosis for BC susceptibility. Rapid genotyping technique using microarrays for identification of BRCA1 185delAG, 300T>G, 4153delA, 5382insC mutations and 4158 A>G sequence variant; BRCA2 695insT and 6174delT mutations; 1100delC mutation in CHEK2 gene was applied for 412 randomly collected breast cancer samples from the central region of European area of Russia. In 25 (6.0%) patients (6.0%) BC was associated with other tumours: OC, cervical cancer, colorectal cancer etc. BRCA1/2 and CHEK2 mutations were found in 33 (8.0%) BC patients. The most frequent mutation was BRCA1 5382insC, occurred in 16 (3.9%) BC patients, and CHEK2 1100delC, revealed in 7 (1.7%) BC patients. An application of diagnostic BC-microarray for genetic testing of BRCA1/2 and CHEK2 founder mutations has been discussed.

DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data

PubMed Central

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.

PubMed

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.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

PubMed Central

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

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

Development and utility of the FDA 'GutProbe' DNA microarray for identification, genotyping and metagenomic analysis of commercially available probiotics.

PubMed

Patro, J N; Ramachandran, P; Lewis, J L; Mammel, M K; Barnaba, T; Pfeiler, E A; Elkins, C A

2015-06-01

Lactic acid bacteria are beneficial microbes added to many food products and dietary supplements for their purported health benefits. Proper identification of bacteria is important to assess safety as well as proper product labelling. A custom microarray (FDA GutProbe) was developed to verify accurate labelling in commercial dietary supplements. Strain-specific attribution was achieved with GutProbe array which contains genes from the most commonly found species in probiotic supplements and food ingredients. Applied utility of the array was assessed with direct from product DNA hybridization to determine (i) if identification of multiple strains in one sample can be conducted and (ii) if any lot-to-lot variations exist with eight probiotics found on the US market. GutProbe is a useful tool in identifying a mixture of microbials in probiotics and did reveal some product variations. In addition, the array is able to identify lot-to-lot differences in these products. These strain level attribution may be useful for routine monitoring of batch variation as part of a 'Good Manufacturing Practices' process. The FDA GutProbe is an efficient and reliable platform to identify the presence of microbial ingredients and determining microbe differences in dietary supplements. The GutProbe is a fast, rapid method for direct community profiling or food matrix sampling. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Identification of microRNA-mRNA modules using microarray data.

PubMed

Jayaswal, Vivek; Lutherborrow, Mark; Ma, David D F; Yang, Yee H

2011-03-06

MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of miRNAs will further our knowledge of these networks. There is a many-to-many relationship between miRNAs and mRNAs because a single miRNA targets multiple mRNAs and a single mRNA is targeted by multiple miRNAs. However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs. We propose a two-step method for the identification of many-to-many relationships between miRNAs and mRNAs. In the first step, we obtain miRNA and mRNA clusters using a combination of miRNA-target mRNA prediction algorithms and microarray expression data. In the second step, we determine the associations between miRNA clusters and mRNA clusters based on changes in miRNA and mRNA expression profiles. We consider the miRNA-mRNA clusters with statistically significant associations to be potentially regulatory and, therefore, of biological interest. Our method reduces the interactions between several hundred miRNAs and several thousand mRNAs to a few miRNA-mRNA groups, thereby facilitating a more meaningful biological analysis and a more targeted experimental validation.

Detection of clonal evolution in hematopoietic malignancies by combining comparative genomic hybridization and single nucleotide polymorphism arrays.

PubMed

Hartmann, Luise; Stephenson, Christine F; Verkamp, Stephanie R; Johnson, Krystal R; Burnworth, Bettina; Hammock, Kelle; Brodersen, Lisa Eidenschink; de Baca, Monica E; Wells, Denise A; Loken, Michael R; Zehentner, Barbara K

2014-12-01

Array comparative genomic hybridization (aCGH) has become a powerful tool for analyzing hematopoietic neoplasms and identifying genome-wide copy number changes in a single assay. aCGH also has superior resolution compared with fluorescence in situ hybridization (FISH) or conventional cytogenetics. Integration of single nucleotide polymorphism (SNP) probes with microarray analysis allows additional identification of acquired uniparental disomy, a copy neutral aberration with known potential to contribute to tumor pathogenesis. However, a limitation of microarray analysis has been the inability to detect clonal heterogeneity in a sample. This study comprised 16 samples (acute myeloid leukemia, myelodysplastic syndrome, chronic lymphocytic leukemia, plasma cell neoplasm) with complex cytogenetic features and evidence of clonal evolution. We used an integrated manual peak reassignment approach combining analysis of aCGH and SNP microarray data for characterization of subclonal abnormalities. We compared array findings with results obtained from conventional cytogenetic and FISH studies. Clonal heterogeneity was detected in 13 of 16 samples by microarray on the basis of log2 values. Use of the manual peak reassignment analysis approach improved resolution of the sample's clonal composition and genetic heterogeneity in 10 of 13 (77%) patients. Moreover, in 3 patients, clonal disease progression was revealed by array analysis that was not evident by cytogenetic or FISH studies. Genetic abnormalities originating from separate clonal subpopulations can be identified and further characterized by combining aCGH and SNP hybridization results from 1 integrated microarray chip by use of the manual peak reassignment technique. Its clinical utility in comparison to conventional cytogenetic or FISH studies is demonstrated. © 2014 American Association for Clinical Chemistry.

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

Identification of novel and known oocyte-specific genes using complementary DNA subtraction and microarray analysis in three different species.

PubMed

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.

Analysis of sensitivity and rapid hybridization of a multiplexed Microbial Detection Microarray

DOE PAGES

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

The Use of P63 Immunohistochemistry for the Identification of Squamous Cell Carcinoma of the Lung

PubMed Central

Conde, Esther; Angulo, Bárbara; Redondo, Pilar; Toldos, Oscar; García-García, Elena; Suárez-Gauthier, Ana; Rubio-Viqueira, Belén; Marrón, Carmen; García-Luján, Ricardo; Sánchez-Céspedes, Montse; López-Encuentra, Angel; Paz-Ares, Luis; López-Ríos, Fernando

2010-01-01

Introduction While some targeted agents should not be used in squamous cell carcinomas (SCCs), other agents might preferably target SCCs. In a previous microarray study, one of the top differentially expressed genes between adenocarcinomas (ACs) and SCCs is P63. It is a well-known marker of squamous differentiation, but surprisingly, its expression is not widely used for this purpose. Our goals in this study were (1) to further confirm our microarray data, (2) to analize the value of P63 immunohistochemistry (IHC) in reducing the number of large cell carcinoma (LCC) diagnoses in surgical specimens, and (3) to investigate the potential of P63 IHC to minimize the proportion of “carcinoma NOS (not otherwise specified)” in a prospective series of small tumor samples. Methods With these goals in mind, we studied (1) a tissue-microarray comprising 33 ACs and 99 SCCs on which we performed P63 IHC, (2) a series of 20 surgically resected LCCs studied for P63 and TTF-1 IHC, and (3) a prospective cohort of 66 small thoracic samples, including 32 carcinoma NOS, that were further classified by the result of P63 and TTF-1 IHC. Results The results in the three independent cohorts were as follows: (1) P63 IHC was differentially expressed in SCCs when compared to ACs (p<0.0001); (2) half of the 20 (50%) LCCs were positive for P63 and were reclassified as SCCs; and (3) all P63 positive cases (34%) were diagnosed as SCCs. Conclusions P63 IHC is useful for the identification of lung SCCs. PMID:20808915

Clofibrate-induced gene expression changes in rat liver: a cross-laboratory analysis using membrane cDNA arrays.

PubMed Central

Baker, Valerie A; Harries, Helen M; Waring, Jeff F; Duggan, Colette M; Ni, Hong A; Jolly, Robert A; Yoon, Lawrence W; De Souza, Angus T; Schmid, Judith E; Brown, Roger H; Ulrich, Roger G; Rockett, John C

2004-01-01

Microarrays have the potential to significantly impact our ability to identify toxic hazards by the identification of mechanistically relevant markers of toxicity. To be useful for risk assessment, however, microarray data must be challenged to determine reliability and interlaboratory reproducibility. As part of a series of studies conducted by the International Life Sciences Institute Health and Environmental Science Institute Technical Committee on the Application of Genomics to Mechanism-Based Risk Assessment, the biological response in rats to the hepatotoxin clofibrate was investigated. Animals were treated with high (250 mg/kg/day) or low (25 mg/kg/day) doses for 1, 3, or 7 days in two laboratories. Clinical chemistry parameters were measured, livers removed for histopathological assessment, and gene expression analysis was conducted using cDNA arrays. Expression changes in genes involved in fatty acid metabolism (e.g., acyl-CoA oxidase), cell proliferation (e.g., topoisomerase II-Alpha), and fatty acid oxidation (e.g., cytochrome P450 4A1), consistent with the mechanism of clofibrate hepatotoxicity, were detected. Observed differences in gene expression levels correlated with the level of biological response induced in the two in vivo studies. Generally, there was a high level of concordance between the gene expression profiles generated from pooled and individual RNA samples. Quantitative real-time polymerase chain reaction was used to confirm modulations for a number of peroxisome proliferator marker genes. Though the results indicate some variability in the quantitative nature of the microarray data, this appears due largely to differences in experimental and data analysis procedures used within each laboratory. In summary, this study demonstrates the potential for gene expression profiling to identify toxic hazards by the identification of mechanistically relevant markers of toxicity. PMID:15033592

Identification of significant features by the Global Mean Rank test.

PubMed

Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

2014-01-01

With the introduction of omics-technologies such as transcriptomics and proteomics, numerous methods for the reliable identification of significantly regulated features (genes, proteins, etc.) have been developed. Experimental practice requires these tests to successfully deal with conditions such as small numbers of replicates, missing values, non-normally distributed expression levels, and non-identical distributions of features. With the MeanRank test we aimed at developing a test that performs robustly under these conditions, while favorably scaling with the number of replicates. The test proposed here is a global one-sample location test, which is based on the mean ranks across replicates, and internally estimates and controls the false discovery rate. Furthermore, missing data is accounted for without the need of imputation. In extensive simulations comparing MeanRank to other frequently used methods, we found that it performs well with small and large numbers of replicates, feature dependent variance between replicates, and variable regulation across features on simulation data and a recent two-color microarray spike-in dataset. The tests were then used to identify significant changes in the phosphoproteomes of cancer cells induced by the kinase inhibitors erlotinib and 3-MB-PP1 in two independently published mass spectrometry-based studies. MeanRank outperformed the other global rank-based methods applied in this study. Compared to the popular Significance Analysis of Microarrays and Linear Models for Microarray methods, MeanRank performed similar or better. Furthermore, MeanRank exhibits more consistent behavior regarding the degree of regulation and is robust against the choice of preprocessing methods. MeanRank does not require any imputation of missing values, is easy to understand, and yields results that are easy to interpret. The software implementing the algorithm is freely available for academic and commercial use.

Use of the Escherichia coli Identification Microarray for Characterizing the Health Risks of Shiga Toxin-Producing Escherichia coli Isolated from Foods.

PubMed

Lacher, David W; Gangiredla, Jayanthi; Patel, Isha; Elkins, Christopher A; Feng, Peter C H

2016-10-01

More than 470 serotypes of Shiga toxin-producing Escherichia coli (STEC) have been identified, but not all cause severe illness in humans. Most STEC that cause severe diseases can adhere to epithelial cells, produce specific stx subtypes, and belong to certain serotypes; therefore, these traits appear to be critical STEC risk factors. However, testing for these traits is labor intensive, and serotyping is inadequate because of extensive variations among E. coli O and H antigen types. In the present study, the E. coli identification microarray, which tests for over 40,000 E. coli gene targets, was examined for its potential to quickly characterize STEC strains. Analysis of 47 E. coli isolates, including 31 STEC isolates, recovered from 39 foods revealed that the microarray effectively determined the presence or absence of adherence genes and identified the specific eae allele in 3 isolates. The array identified most of the stx subtypes carried by all the isolates but had some difficulties in discerning between stx 2a , stx 2c , and stx 2d because of the genetic similarities of these subtypes. The array determined the O and H types of 68 and 96% of the isolates, respectively, and although most serotypes were unremarkable, a few known pathogenic serotypes were also found. These selected STEC traits provided a scientific basis for assessing the potential health risks of STEC strains and also showed the importance of H typing in determining health risks. However, the diversity of the STEC group, the complexity of virulence mechanisms, and the variation in pathotypes among strains continue to pose challenges to assessing the potential of STEC strains to cause severe illness.

Evaluation of high throughput gene expression platforms using a genomic biomarker signature for prediction of skin sensitization.

PubMed

Forreryd, Andy; Johansson, Henrik; Albrekt, Ann-Sofie; Lindstedt, Malin

2014-05-16

Allergic contact dermatitis (ACD) develops upon exposure to certain chemical compounds termed skin sensitizers. To reduce the occurrence of skin sensitizers, chemicals are regularly screened for their capacity to induce sensitization. The recently developed Genomic Allergen Rapid Detection (GARD) assay is an in vitro alternative to animal testing for identification of skin sensitizers, classifying chemicals by evaluating transcriptional levels of a genomic biomarker signature. During assay development and biomarker identification, genome-wide expression analysis was applied using microarrays covering approximately 30,000 transcripts. However, the microarray platform suffers from drawbacks in terms of low sample throughput, high cost per sample and time consuming protocols and is a limiting factor for adaption of GARD into a routine assay for screening of potential sensitizers. With the purpose to simplify assay procedures, improve technical parameters and increase sample throughput, we assessed the performance of three high throughput gene expression platforms--nCounter®, BioMark HD™ and OpenArray®--and correlated their performance metrics against our previously generated microarray data. We measured the levels of 30 transcripts from the GARD biomarker signature across 48 samples. Detection sensitivity, reproducibility, correlations and overall structure of gene expression measurements were compared across platforms. Gene expression data from all of the evaluated platforms could be used to classify most of the sensitizers from non-sensitizers in the GARD assay. Results also showed high data quality and acceptable reproducibility for all platforms but only medium to poor correlations of expression measurements across platforms. In addition, evaluated platforms were superior to the microarray platform in terms of cost efficiency, simplicity of protocols and sample throughput. We evaluated the performance of three non-array based platforms using a limited set of transcripts from the GARD biomarker signature. We demonstrated that it was possible to achieve acceptable discriminatory power in terms of separation between sensitizers and non-sensitizers in the GARD assay while reducing assay costs, simplify assay procedures and increase sample throughput by using an alternative platform, providing a first step towards the goal to prepare GARD for formal validation and adaption of the assay for industrial screening of potential sensitizers.

Use of homologous and heterologous gene expression profiling tools to characterize transcription dynamics during apple fruit maturation and ripening

PubMed Central

2010-01-01

Background Fruit development, maturation and ripening consists of a complex series of biochemical and physiological changes that in climacteric fruits, including apple and tomato, are coordinated by the gaseous hormone ethylene. These changes lead to final fruit quality and understanding of the functional machinery underlying these processes is of both biological and practical importance. To date many reports have been made on the analysis of gene expression in apple. In this study we focused our investigation on the role of ethylene during apple maturation, specifically comparing transcriptomics of normal ripening with changes resulting from application of the hormone receptor competitor 1-Methylcyclopropene. Results To gain insight into the molecular process regulating ripening in apple, and to compare to tomato (model species for ripening studies), we utilized both homologous and heterologous (tomato) microarray to profile transcriptome dynamics of genes involved in fruit development and ripening, emphasizing those which are ethylene regulated. The use of both types of microarrays facilitated transcriptome comparison between apple and tomato (for the later using data previously published and available at the TED: tomato expression database) and highlighted genes conserved during ripening of both species, which in turn represent a foundation for further comparative genomic studies. The cross-species analysis had the secondary aim of examining the efficiency of heterologous (specifically tomato) microarray hybridization for candidate gene identification as related to the ripening process. The resulting transcriptomics data revealed coordinated gene expression during fruit ripening of a subset of ripening-related and ethylene responsive genes, further facilitating the analysis of ethylene response during fruit maturation and ripening. Conclusion Our combined strategy based on microarray hybridization enabled transcriptome characterization during normal climacteric apple ripening, as well as definition of ethylene-dependent transcriptome changes. Comparison with tomato fruit maturation and ethylene responsive transcriptome activity facilitated identification of putative conserved orthologous ripening-related genes, which serve as an initial set of candidates for assessing conservation of gene activity across genomes of fruit bearing plant species. PMID:20973957

Identification of drought-responsive genes in a drought-tolerant cotton (Gossypium hirsutum L.) cultivar under reduced irrigation field conditions and development of candidate gene markers for drought tolerance

USDA-ARS?s Scientific Manuscript database

Cotton productivity is affected by water deficit, and little is known about the molecular basis of drought tolerance in cotton. In this study, microarray analysis was conducted to identify drought-responsive genes in the third topmost leaves of the field-grown drought-tolerant cotton (Gossypium hirs...

Identification of Biomarkers Associated with the Healing of Chronic Wounds

DTIC Science & Technology

2015-11-01

The analysis of the wound fluid began with a broad survey tool Kinex™ Antibody Microarray (KAM) a single dye , non-competitive sample binding...signaling proteins. Lysate protein from each sample was covalently labeled with a fluorescent dye combination. Free dye molecules were then...patterned structures is controlled by varying their pattern geometry. The biodegradation of micro-patterned structures is modeled geometrically based on

Gene expression patterns of wood decay fungi Postia placenta and Phanerochaete chrysosporium are influenced by wood substrate composition during degradation

Treesearch

Oleksandr Skyba; Daniel Cullen; Carl J. Douglas; Shawn D. Mansfield

2016-01-01

Identification of the specific genes and enzymes involved in the fungal degradation of lignocellulosic biomass derived from feedstocks with various compositions is essential to the development of improved bioenergy processes. In order to elucidate the effect of substrate composition on gene expression in wood-rotting fungi, we employed microarrays based on the...

Identification of Prostate Cancer Prognostic Markers

DTIC Science & Technology

2015-10-01

downregulation of GABARAPL2, a gene located in a chromosomal region deleted in PCa metastases, showed increase in autophagy in a PCa cell line and reduced...alteration, chromosome gain and deletion, fluorescence in situ hybridization (FISH), prognostic markers, biomarkers, tissue microarrays, autophagy 16...TMA), colony formation assay, cell growth, autophagy . 3. ACCOMPLISHMENTS: What were the major goals of the project? The hypothesis of the project is

Comparative genomic characterization of citrus-associated Xylella fastidiosa strains.

PubMed

da Silva, Vivian S; Shida, Cláudio S; Rodrigues, Fabiana B; Ribeiro, Diógenes C D; de Souza, Alessandra A; Coletta-Filho, Helvécio D; Machado, Marcos A; Nunes, Luiz R; de Oliveira, Regina Costa

2007-12-21

The xylem-inhabiting bacterium Xylella fastidiosa (Xf) is the causal agent of Pierce's disease (PD) in vineyards and citrus variegated chlorosis (CVC) in orange trees. Both of these economically-devastating diseases are caused by distinct strains of this complex group of microorganisms, which has motivated researchers to conduct extensive genomic sequencing projects with Xf strains. This sequence information, along with other molecular tools, have been used to estimate the evolutionary history of the group and provide clues to understand the capacity of Xf to infect different hosts, causing a variety of symptoms. Nonetheless, although significant amounts of information have been generated from Xf strains, a large proportion of these efforts has concentrated on the study of North American strains, limiting our understanding about the genomic composition of South American strains - which is particularly important for CVC-associated strains. This paper describes the first genome-wide comparison among South American Xf strains, involving 6 distinct citrus-associated bacteria. Comparative analyses performed through a microarray-based approach allowed identification and characterization of large mobile genetic elements that seem to be exclusive to South American strains. Moreover, a large-scale sequencing effort, based on Suppressive Subtraction Hybridization (SSH), identified 290 new ORFs, distributed in 135 Groups of Orthologous Elements, throughout the genomes of these bacteria. Results from microarray-based comparisons provide further evidence concerning activity of horizontally transferred elements, reinforcing their importance as major mediators in the evolution of Xf. Moreover, the microarray-based genomic profiles showed similarity between Xf strains 9a5c and Fb7, which is unexpected, given the geographical and chronological differences associated with the isolation of these microorganisms. The newly identified ORFs, obtained by SSH, represent an approximately 10% increase in our current knowledge of the South American Xf gene pool and include new putative virulence factors, as well as novel potential markers for strain identification. Surprisingly, this list of novel elements include sequences previously believed to be unique to North American strains, pointing to the necessity of revising the list of specific markers that may be used for identification of distinct Xf strains.

Identification of Common Differentially Expressed Genes in Urinary Bladder Cancer

PubMed Central

Zaravinos, Apostolos; Lambrou, George I.; Boulalas, Ioannis; Delakas, Dimitris; Spandidos, Demetrios A.

2011-01-01

Background Current diagnosis and treatment of urinary bladder cancer (BC) has shown great progress with the utilization of microarrays. Purpose Our goal was to identify common differentially expressed (DE) genes among clinically relevant subclasses of BC using microarrays. Methodology/Principal Findings BC samples and controls, both experimental and publicly available datasets, were analyzed by whole genome microarrays. We grouped the samples according to their histology and defined the DE genes in each sample individually, as well as in each tumor group. A dual analysis strategy was followed. First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes. The experimental dataset identified 831 genes that were DE in all tumor samples, simultaneously. Moreover, 33 genes were up-regulated and 85 genes were down-regulated in all 10 BC samples compared to the 5 normal tissues, simultaneously. Hierarchical clustering partitioned tumor groups in accordance to their histology. K-means clustering of all genes and all samples, as well as clustering of tumor groups, presented 49 clusters. K-means clustering of common DE genes in all samples revealed 24 clusters. Genes manifested various differential patterns of expression, based on PCA. YY1 and NFκB were among the most common transcription factors that regulated the expression of the identified DE genes. Chromosome 1 contained 32 DE genes, followed by chromosomes 2 and 11, which contained 25 and 23 DE genes, respectively. Chromosome 21 had the least number of DE genes. GO analysis revealed the prevalence of transport and binding genes in the common down-regulated DE genes; the prevalence of RNA metabolism and processing genes in the up-regulated DE genes; as well as the prevalence of genes responsible for cell communication and signal transduction in the DE genes that were down-regulated in T1-Grade III tumors and up-regulated in T2/T3-Grade III tumors. Combination of samples from all microarray platforms revealed 17 common DE genes, (BMP4, CRYGD, DBH, GJB1, KRT83, MPZ, NHLH1, TACR3, ACTC1, MFAP4, SPARCL1, TAGLN, TPM2, CDC20, LHCGR, TM9SF1 and HCCS) 4 of which participate in numerous pathways. Conclusions/Significance The identification of the common DE genes among BC samples of different histology can provide further insight into the discovery of new putative markers. PMID:21483740

Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

PubMed

Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

2011-10-01

Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A new locally weighted K-means for cancer-aided microarray data analysis.

PubMed

Iam-On, Natthakan; Boongoen, Tossapon

2012-11-01

Cancer has been identified as the leading cause of death. It is predicted that around 20-26 million people will be diagnosed with cancer by 2020. With this alarming rate, there is an urgent need for a more effective methodology to understand, prevent and cure cancer. Microarray technology provides a useful basis of achieving this goal, with cluster analysis of gene expression data leading to the discrimination of patients, identification of possible tumor subtypes and individualized treatment. Amongst clustering techniques, k-means is normally chosen for its simplicity and efficiency. However, it does not account for the different importance of data attributes. This paper presents a new locally weighted extension of k-means, which has proven more accurate across many published datasets than the original and other extensions found in the literature.

Digital microarray analysis for digital artifact genomics

NASA Astrophysics Data System (ADS)

Jaenisch, Holger; Handley, James; Williams, Deborah

2013-06-01

We implement a Spatial Voting (SV) based analogy of microarray analysis for digital gene marker identification in malware code sections. We examine a famous set of malware formally analyzed by Mandiant and code named Advanced Persistent Threat (APT1). APT1 is a Chinese organization formed with specific intent to infiltrate and exploit US resources. Manidant provided a detailed behavior and sting analysis report for the 288 malware samples available. We performed an independent analysis using a new alternative to the traditional dynamic analysis and static analysis we call Spatial Analysis (SA). We perform unsupervised SA on the APT1 originating malware code sections and report our findings. We also show the results of SA performed on some members of the families associated by Manidant. We conclude that SV based SA is a practical fast alternative to dynamics analysis and static analysis.

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

Novel in silico technology in combination with microarrays: a state-of-the-art technology for allergy diagnosis and management?

PubMed

Melioli, Giovanni; Passalacqua, Giovanni; Canonica, Giorgio W

2014-12-01

'Allergen microarrays, in poly-sensitized allergic patients, represent a real value added in the accurate IgE profiling and in the identification of allergen(s) to administer for an effective allergen immunotherapy.' Allergen microarrays (AMA) were developed in the early 2000s to improve the diagnostic pathway of patients with allergic reactions. Nowadays, AMA are constituted by more than 100 different components (either purified or recombinant), representing genuine and cross-reacting molecules from plants and animals. The cost of the procedure had suggested its use as third-level diagnostics (following in vivo- and in vitro-specific IgE tests) in poly-sensitized patients. The complexity of the interpretation had inspired the development of in silico technologies to help clinicians in their work. Both machine learning techniques and expert systems are now available. In particular, an expert system that has been recently developed not only identifies positive and negative components but also lists dangerous components and classifies patients based on their potential responsiveness to allergen immunotherapy, on the basis of published algorithms. For these characteristics, AMA represents the state-of-the-art technology for allergy diagnosis in poly-sensitized patients.

Identification of intracellular proteins and signaling pathways in human endothelial cells regulated by angiotensin-(1-7).

PubMed

Meinert, Christian; Gembardt, Florian; Böhme, Ilka; Tetzner, Anja; Wieland, Thomas; Greenberg, Barry; Walther, Thomas

2016-01-01

The study aimed to identify proteins regulated by the cardiovascular protective peptide angiotensin-(1-7) and to determine potential intracellular signaling cascades. Human endothelial cells were stimulated with Ang-(1-7) for 1 h, 3 h, 6 h, and 9 h. Peptide effects on intracellular signaling were assessed via antibody microarray, containing antibodies against 725 proteins. Bioinformatics software was used to identify affected intracellular signaling pathways. Microarray data was verified exemplarily by Western blot, Real-Time RT-PCR, and immunohistochemical studies. The microarray identified 110 regulated proteins after 1 h, 119 after 3 h, 31 after 6 h, and 86 after 9 h Ang-(1-7) stimulation. Regulated proteins were associated with high significance to several metabolic pathways like “Molecular Mechanism of Cancer” and “p53 signaling” in a time dependent manner. Exemplarily, Western blots for the E3-type small ubiquitin-like modifier ligase PIAS2 confirmed the microarray data and displayed a decrease by more than 50% after Ang-(1-7) stimulation at 1 h and 3 h without affecting its mRNA. Immunohistochemical studies with PIAS2 in human endothelial cells showed a decrease in cytoplasmic PIAS2 after Ang-(1-7) treatment. The Ang-(1-7) mediated decrease of PIAS2 was reproduced in other endothelial cell types. The results suggest that angiotensin-(1-7) plays a role in metabolic pathways related to cell death and cell survival in human endothelial cells.

Prediction of transcriptional regulatory elements for plant hormone responses based on microarray data

PubMed Central

2011-01-01

Background Phytohormones organize plant development and environmental adaptation through cell-to-cell signal transduction, and their action involves transcriptional activation. Recent international efforts to establish and maintain public databases of Arabidopsis microarray data have enabled the utilization of this data in the analysis of various phytohormone responses, providing genome-wide identification of promoters targeted by phytohormones. Results We utilized such microarray data for prediction of cis-regulatory elements with an octamer-based approach. Our test prediction of a drought-responsive RD29A promoter with the aid of microarray data for response to drought, ABA and overexpression of DREB1A, a key regulator of cold and drought response, provided reasonable results that fit with the experimentally identified regulatory elements. With this succession, we expanded the prediction to various phytohormone responses, including those for abscisic acid, auxin, cytokinin, ethylene, brassinosteroid, jasmonic acid, and salicylic acid, as well as for hydrogen peroxide, drought and DREB1A overexpression. Totally 622 promoters that are activated by phytohormones were subjected to the prediction. In addition, we have assigned putative functions to 53 octamers of the Regulatory Element Group (REG) that have been extracted as position-dependent cis-regulatory elements with the aid of their feature of preferential appearance in the promoter region. Conclusions Our prediction of Arabidopsis cis-regulatory elements for phytohormone responses provides guidance for experimental analysis of promoters to reveal the basis of the transcriptional network of phytohormone responses. PMID:21349196

16S rRNA based microarray analysis of ten periodontal bacteria in patients with different forms of periodontitis.

PubMed

Topcuoglu, Nursen; Kulekci, Guven

2015-10-01

DNA microarray analysis is a computer based technology, that a reverse capture, which targets 10 periodontal bacteria (ParoCheck) is available for rapid semi-quantitative determination. The aim of this three-year retrospective study was to display the microarray analysis results for the subgingival biofilm samples taken from patient cases diagnosed with different forms of periodontitis. A total of 84 patients with generalized aggressive periodontitis (GAP,n:29), generalized chronic periodontitis (GCP, n:25), peri-implantitis (PI,n:14), localized aggressive periodontitis (LAP,n:8) and refractory chronic periodontitis (RP,n:8) were consecutively selected from the archives of the Oral Microbiological Diagnostic Laboratory. The subgingival biofilm samples were analyzed by the microarray-based identification of 10 selected species. All the tested species were detected in the samples. The red complex bacteria were the most prevalent with very high levels in all groups. Fusobacterium nucleatum was detected in all samples at high levels. The green and blue complex bacteria were less prevalent compared with red and orange complex, except Aggregatibacter actinomycetemcomitas was detected in all LAP group. Positive correlations were found within all the red complex bacteria and between red and orange complex bacteria especially in GCP and GAP groups. Parocheck enables to monitoring of periodontal pathogens in all forms of periodontal disease and can be alternative to other guiding and reliable microbiologic tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

Functions and Mechanisms of Sleep in Flies and Mammals

DTIC Science & Technology

2007-02-01

serotonin receptor likely to mediate the known interaction between the serotonergic Raphe nucleus and the LC (Htr1d). We have also confirmed the prior... Chemistry . His research focuses on mass spectrometry, a technique that will augment research on the mechanisms of sleep and complement microarray gene...labeling (ICAT, ITRAQ, etc); 8) MALDI and electrospray FTMS for the identification of small molecule structure ; 9) Gas phase reactions within the FTMS

EgoNet: identification of human disease ego-network modules

PubMed Central

2014-01-01

Background Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks. Results We present EgoNet, a novel method based on egocentric network-analysis techniques, to exhaustively search and prioritize disease subnetworks and gene markers from a large-scale biological network. When applied to a triple-negative breast cancer (TNBC) microarray dataset, the top selected modules contain both known gene markers in TNBC and novel candidates, such as RAD51 and DOK1, which play a central role in their respective ego-networks by connecting many differentially expressed genes. Conclusions Our results suggest that EgoNet, which is based on the ego network concept, allows the identification of novel biomarkers and provides a deeper understanding of their roles in complex diseases. PMID:24773628

Identification of lethal cluster of genes in the yeast transcription network

NASA Astrophysics Data System (ADS)

Rho, K.; Jeong, H.; Kahng, B.

2006-05-01

Identification of essential or lethal genes would be one of the ultimate goals in drug designs. Here we introduce an in silico method to select the cluster with a high population of lethal genes, called lethal cluster, through microarray assay. We construct a gene transcription network based on the microarray expression level. Links are added one by one in the descending order of the Pearson correlation coefficients between two genes. As the link density p increases, two meaningful link densities pm and ps are observed. At pm, which is smaller than the percolation threshold, the number of disconnected clusters is maximum, and the lethal genes are highly concentrated in a certain cluster that needs to be identified. Thus the deletion of all genes in that cluster could efficiently lead to a lethal inviable mutant. This lethal cluster can be identified by an in silico method. As p increases further beyond the percolation threshold, the power law behavior in the degree distribution of a giant cluster appears at ps. We measure the degree of each gene at ps. With the information pertaining to the degrees of each gene at ps, we return to the point pm and calculate the mean degree of genes of each cluster. We find that the lethal cluster has the largest mean degree.

Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

PubMed Central

Arias, Carlos Roberto; Yeh, Hsiang-Yuan; Soo, Von-Wun

2012-01-01

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well. PMID:22654636

IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN THE KIDNEYS OF GROWTH HORMONE TRANSGENIC MICE

PubMed Central

Coschigano, K.T.; Wetzel, A.N.; Obichere, N.; Sharma, A.; Lee, S.; Rasch, R.; Guigneaux, M.M.; Flyvbjerg, A.; Wood, T.G.; Kopchick, J.J.

2010-01-01

Objective Bovine growth hormone (bGH) transgenic mice develop severe kidney damage. This damage may be due, at least in part, to changes in gene expression. Identification of genes with altered expression in the bGH kidney may identify mechanisms leading to damage in this system that may also be relevant to other models of kidney damage. Design cDNA subtraction libraries, northern blot analyses, microarray analyses and real-time reverse transcription polymerase chain reaction (RT/PCR) assays were used to identify and verify specific genes exhibiting differential RNA expression between kidneys of bGH mice and their non-transgenic (NT) littermates. Results Immunoglobulins were the vast majority of genes identified by the cDNA subtractions and the microarray analyses as being up-regulated in bGH. Several glycoprotein genes and inflammation-related genes also showed increased RNA expression in the bGH kidney. In contrast, only a few genes were identified as being significantly down-regulated in the bGH kidney. The most notable decrease in RNA expression was for the gene encoding kidney androgen-regulated protein. Conclusions A number of genes were identified as being differentially expressed in the bGH kidney. Inclusion of two groups, immunoglobulins and inflammation-related genes, suggests a role of the immune system in bGH kidney damage. PMID:20655258

Identification and characterization of nuclear genes involved in photosynthesis in Populus

PubMed Central

2014-01-01

Background The gap between the real and potential photosynthetic rate under field conditions suggests that photosynthesis could potentially be improved. Nuclear genes provide possible targets for improving photosynthetic efficiency. Hence, genome-wide identification and characterization of the nuclear genes affecting photosynthetic traits in woody plants would provide key insights on genetic regulation of photosynthesis and identify candidate processes for improvement of photosynthesis. Results Using microarray and bulked segregant analysis strategies, we identified differentially expressed nuclear genes for photosynthesis traits in a segregating population of poplar. We identified 515 differentially expressed genes in this population (FC ≥ 2 or FC ≤ 0.5, P < 0.05), 163 up-regulated and 352 down-regulated. Real-time PCR expression analysis confirmed the microarray data. Singular Enrichment Analysis identified 48 significantly enriched GO terms for molecular functions (28), biological processes (18) and cell components (2). Furthermore, we selected six candidate genes for functional examination by a single-marker association approach, which demonstrated that 20 SNPs in five candidate genes significantly associated with photosynthetic traits, and the phenotypic variance explained by each SNP ranged from 2.3% to 12.6%. This revealed that regulation of photosynthesis by the nuclear genome mainly involves transport, metabolism and response to stimulus functions. Conclusions This study provides new genome-scale strategies for the discovery of potential candidate genes affecting photosynthesis in Populus, and for identification of the functions of genes involved in regulation of photosynthesis. This work also suggests that improving photosynthetic efficiency under field conditions will require the consideration of multiple factors, such as stress responses. PMID:24673936

Characterization of human septic sera induced gene expression modulation in human myocytes

PubMed Central

Hussein, Shaimaa; Michael, Paul; Brabant, Danielle; Omri, Abdelwahab; Narain, Ravin; Passi, Kalpdrum; Ramana, Chilakamarti V.; Parrillo, Joseph E.; Kumar, Anand; Parissenti, Amadeo; Kumar, Aseem

2009-01-01

To gain a better understanding of the gene expression changes that occurs during sepsis, we have performed a cDNA microarray study utilizing a tissue culture model that mimics human sepsis. This study utilized an in vitro model of cultured human fetal cardiac myocytes treated with 10% sera from septic patients or 10% sera from healthy volunteers. A 1700 cDNA expression microarray was used to compare the transcription profile from human cardiac myocytes treated with septic sera vs normal sera. Septic sera treatment of myocytes resulted in the down-regulation of 178 genes and the up-regulation of 4 genes. Our data indicate that septic sera induced cell cycle, metabolic, transcription factor and apoptotic gene expression changes in human myocytes. Identification and characterization of gene expression changes that occur during sepsis may lead to the development of novel therapeutics and diagnostics. PMID:19684886

Identification of embryonic pancreatic genes using Xenopus DNA microarrays.

PubMed

Hayata, Tadayoshi; Blitz, Ira L; Iwata, Nahoko; Cho, Ken W Y

2009-06-01

The pancreas is both an exocrine and endocrine endodermal organ involved in digestion and glucose homeostasis. During embryogenesis, the anlagen of the pancreas arise from dorsal and ventral evaginations of the foregut that later fuse to form a single organ. To better understand the molecular genetics of early pancreas development, we sought to isolate markers that are uniquely expressed in this tissue. Microarray analysis was performed comparing dissected pancreatic buds, liver buds, and the stomach region of tadpole stage Xenopus embryos. A total of 912 genes were found to be differentially expressed between these organs during early stages of organogenesis. K-means clustering analysis predicted 120 of these genes to be specifically enriched in the pancreas. Of these, we report on the novel expression patterns of 24 genes. Our analyses implicate the involvement of previously unsuspected signaling pathways during early pancreas development. Developmental Dynamics 238:1455-1466, 2009. (c) 2009 Wiley-Liss, Inc.

Gene expression profiling in respond to TBT exposure in small abalone Haliotis diversicolor.

PubMed

Jia, Xiwei; Zou, Zhihua; Wang, Guodong; Wang, Shuhong; Wang, Yilei; Zhang, Ziping

2011-10-01

In this study, we investigated the gene expression profiling of small abalone, Haliotis diversicolor by tributyltin (TBT) exposure using a cDNA microarray containing 2473 unique transcripts. Totally, 107 up-regulated genes and 41 down-regulated genes were found. For further investigation of candidate genes from microarray data and EST analysis, quantitative real-time PCR was performed at 6 h, 24 h, 48 h, 96 h and 192 h TBT exposure. 26 genes were found to be significantly differentially expressed in different time course, 3 of them were unknown. Some gene homologues like cellulose, endo-beta-1,4-glucanase, ferritin subunit 1 and thiolester containing protein II CG7052-PB might be the good biomarker candidate for TBT monitor. The identification of stress response genes and their expression profiles will permit detailed investigation of the defense responses of small abalone genes. Published by Elsevier Ltd.

Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

PubMed

Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

2006-07-01

Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

In-Silico Identification Of Micro-Loops In Myelodysplastic Syndromes

NASA Astrophysics Data System (ADS)

Beck, Dominik; Brandl, Miriam; Pham, Tuan D.; Chang, Chung-Che; Zhou, Xiaobo

2011-06-01

Micro-loops are regulatory network motifs that leverage transcriptional and posttranscriptional control to effectively regulate the transcriptome. In this paper a regulatory network for Myelodysplastic Syndromes (MDSs) was constructed from the literature and publicly available data sources. The network was filtered using data from deep-sequencing of small RNAs, exon and microarrays. Motif discovery showed that micro-loops might exist in MDS. We further used the identified micro-loops and performed basic network analysis to identify the known disease gene RUNX1/AML, as well as miRNA family hsa-mir-181. This suggested that the concept of micro-loops can be applied to enhance disease gene identification and biomarker discovery.

Met Nuclear Localization and Signaling in Breast Cancer

DTIC Science & Technology

2006-05-01

and in germinal regions of many tissues using 4 unique antibodies . Cell fractionation reveals a 60kDa band recognized by C-terminal Met antibodies ...cascades such as Gab1 , Grb2 and PI3K, leading to proliferation, scattering, increased motility, invasion and branching morphogenesis (reviewed in (2...Identification of Met antibodies for use on tissue microarray of normal and cancerous cells, Months 12-24 Task 2. Definition of the domain

Identification and Optimization of Classifier Genes from Multi-Class Earthworm Microarray Dataset

DTIC Science & Technology

2010-10-28

rapid and accurate diagnostic assays. A variety of toxicological effects have been associated with explosive compounds TNT and RDX. One important goal of...analyze toxicological mechanisms for two military- unique explosive compounds 2,4,6-trinitrotolune (TNT) and 1,3,5- trinitro-1,3,5-triazacyclohexane...also known as Royal Demolition eXplosive or RDX) [7,8]. These two compounds exhibit distinctive toxicological properties that are accompanied by

A microarray of ubiquitylated proteins for profiling deubiquitylase activity reveals the critical roles of both chain and substrate.

PubMed

Loch, Christian M; Strickler, James E

2012-11-01

Substrate ubiquitylation is a reversible process critical to cellular homeostasis that is often dysregulated in many human pathologies including cancer and neurodegeneration. Elucidating the mechanistic details of this pathway could unlock a large store of information useful to the design of diagnostic and therapeutic interventions. Proteomic approaches to the questions at hand have generally utilized mass spectrometry (MS), which has been successful in identifying both ubiquitylation substrates and profiling pan-cellular chain linkages, but is generally unable to connect the two. Interacting partners of the deubiquitylating enzymes (DUBs) have also been reported by MS, although substrates of catalytically competent DUBs generally cannot be. Where they have been used towards the study of ubiquitylation, protein microarrays have usually functioned as platforms for the identification of substrates for specific E3 ubiquitin ligases. Here, we report on the first use of protein microarrays to identify substrates of DUBs, and in so doing demonstrate the first example of microarray proteomics involving multiple (i.e., distinct, sequential and opposing) enzymatic activities. This technique demonstrates the selectivity of DUBs for both substrate and type (mono- versus poly-) of ubiquitylation. This work shows that the vast majority of DUBs are monoubiquitylated in vitro, and are incapable of removing this modification from themselves. This work also underscores the critical role of utilizing both ubiquitin chains and substrates when attempting to characterize DUBs. This article is part of a Special Issue entitled: Ubiquitin Drug Discovery and Diagnostics. Copyright © 2012 Elsevier B.V. All rights reserved.

OCaPPI-Db: an oligonucleotide probe database for pathogen identification through hybridization capture.

PubMed

Gasc, Cyrielle; Constantin, Antony; Jaziri, Faouzi; Peyret, Pierre

2017-01-01

The detection and identification of bacterial pathogens involved in acts of bio- and agroterrorism are essential to avoid pathogen dispersal in the environment and propagation within the population. Conventional molecular methods, such as PCR amplification, DNA microarrays or shotgun sequencing, are subject to various limitations when assessing environmental samples, which can lead to inaccurate findings. We developed a hybridization capture strategy that uses a set of oligonucleotide probes to target and enrich biomarkers of interest in environmental samples. Here, we present Oligonucleotide Capture Probes for Pathogen Identification Database (OCaPPI-Db), an online capture probe database containing a set of 1,685 oligonucleotide probes allowing for the detection and identification of 30 biothreat agents up to the species level. This probe set can be used in its entirety as a comprehensive diagnostic tool or can be restricted to a set of probes targeting a specific pathogen or virulence factor according to the user's needs. : http://ocappidb.uca.works. © The Author(s) 2017. Published by Oxford University Press.

High-throughput Identification of Bacteria Repellent Polymers for Medical Devices

PubMed Central

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

Expression profiling and pathway analysis of Krüppel-like factor 4 in mouse embryonic fibroblasts

PubMed Central

Hagos, Engda G; Ghaleb, Amr M; Kumar, Amrita; Neish, Andrew S; Yang, Vincent W

2011-01-01

Background: Krüppel-like factor 4 (KLF4) is a zinc-finger transcription factor with diverse regulatory functions in proliferation, differentiation, and development. KLF4 also plays a role in inflammation, tumorigenesis, and reprogramming of somatic cells to induced pluripotent stem (iPS) cells. To gain insight into the mechanisms by which KLF4 regulates these processes, we conducted DNA microarray analyses to identify differentially expressed genes in mouse embryonic fibroblasts (MEFs) wild type and null for Klf4. Methods: Expression profiles of fibroblasts isolated from mouse embryos wild type or null for the Klf4 alleles were examined by DNA microarrays. Differentially expressed genes were subjected to the Database for Annotation, Visualization and Integrated Discovery (DAVID). The microarray data were also interrogated with the Ingenuity Pathway Analysis (IPA) and Gene Set Enrichment Analysis (GSEA) for pathway identification. Results obtained from the microarray analysis were confirmed by Western blotting for select genes with biological relevance to determine the correlation between mRNA and protein levels. Results: One hundred and sixty three up-regulated and 88 down-regulated genes were identified that demonstrated a fold-change of at least 1.5 and a P-value < 0.05 in Klf4-null MEFs compared to wild type MEFs. Many of the up-regulated genes in Klf4-null MEFs encode proto-oncogenes, growth factors, extracellular matrix, and cell cycle activators. In contrast, genes encoding tumor suppressors and those involved in JAK-STAT signaling pathways are down-regulated in Klf4-null MEFs. IPA and GSEA also identified various pathways that are regulated by KLF4. Lastly, Western blotting of select target genes confirmed the changes revealed by microarray data. Conclusions: These data are not only consistent with previous functional studies of KLF4's role in tumor suppression and somatic cell reprogramming, but also revealed novel target genes that mediate KLF4's functions. PMID:21892412

An efficient pseudomedian filter for tiling microrrays.

PubMed

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

PubMed Central

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

Genomic Approach to Study Floral Development Genes in Rosa sp.

PubMed Central

Chauvet, Aurélie; Maene, Marion; Pécrix, Yann; Yang, Shu-Hua; Jeauffre, Julien; Thouroude, Tatiana; Boltz, Véronique; Martin-Magniette, Marie-Laure; Janczarski, Stéphane; Legeai, Fabrice; Renou, Jean-Pierre; Vergne, Philippe; Le Bris, Manuel; Foucher, Fabrice; Bendahmane, Mohammed

2011-01-01

Cultivated for centuries, the varieties of rose have been selected based on a number of flower traits. Understanding the genetic and molecular basis that contributes to these traits will impact on future improvements for this economically important ornamental plant. In this study, we used scanning electron microscopy and sections of meristems and flowers to establish a precise morphological calendar from early rose flower development stages to senescing flowers. Global gene expression was investigated from floral meristem initiation up to flower senescence in three rose genotypes exhibiting contrasted floral traits including continuous versus once flowering and simple versus double flower architecture, using a newly developed Affymetrix microarray (Rosa1_Affyarray) tool containing sequences representing 4765 unigenes expressed during flower development. Data analyses permitted the identification of genes associated with floral transition, floral organs initiation up to flower senescence. Quantitative real time PCR analyses validated the mRNA accumulation changes observed in microarray hybridizations for a selection of 24 genes expressed at either high or low levels. Our data describe the early flower development stages in Rosa sp, the production of a rose microarray and demonstrate its usefulness and reliability to study gene expression during extensive development phases, from the vegetative meristem to the senescent flower. PMID:22194838

Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

Implementation of spectral clustering with partitioning around medoids (PAM) algorithm on microarray data of carcinoma

NASA Astrophysics Data System (ADS)

Cahyaningrum, Rosalia D.; Bustamam, Alhadi; Siswantining, Titin

2017-03-01

Technology of microarray became one of the imperative tools in life science to observe the gene expression levels, one of which is the expression of the genes of people with carcinoma. Carcinoma is a cancer that forms in the epithelial tissue. These data can be analyzed such as the identification expressions hereditary gene and also build classifications that can be used to improve diagnosis of carcinoma. Microarray data usually served in large dimension that most methods require large computing time to do the grouping. Therefore, this study uses spectral clustering method which allows to work with any object for reduces dimension. Spectral clustering method is a method based on spectral decomposition of the matrix which is represented in the form of a graph. After the data dimensions are reduced, then the data are partitioned. One of the famous partition method is Partitioning Around Medoids (PAM) which is minimize the objective function with exchanges all the non-medoid points into medoid point iteratively until converge. Objectivity of this research is to implement methods spectral clustering and partitioning algorithm PAM to obtain groups of 7457 genes with carcinoma based on the similarity value. The result in this study is two groups of genes with carcinoma.

Microarray expression profiling identifies genes with altered expression in HDL-deficient mice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Callow, Matthew J.; Dudoit, Sandrine; Gong, Elaine L.

2000-05-05

Based on the assumption that severe alterations in the expression of genes known to be involved in HDL metabolism may affect the expression of other genes we screened an array of over 5000 mouse expressed sequence tags (ESTs) for altered gene expression in the livers of two lines of mice with dramatic decreases in HDL plasma concentrations. Labeled cDNA from livers of apolipoprotein AI (apo AI) knockout mice, Scavenger Receptor BI (SR-BI) transgenic mice and control mice were co-hybridized to microarrays. Two-sample t-statistics were used to identify genes with altered expression levels in the knockout or transgenic mice compared withmore » the control mice. In the SR-BI group we found 9 array elements representing at least 5 genes to be significantly altered on the basis of an adjusted p value of less than 0.05. In the apo AI knockout group 8 array elements representing 4 genes were altered compared with the control group (p < 0.05). Several of the genes identified in the SR-BI transgenic suggest altered sterol metabolism and oxidative processes. These studies illustrate the use of multiple-testing methods for the identification of genes with altered expression in replicated microarray experiments of apo AI knockout and SR-BI transgenic mice.« less

A Novel Pan-Flavivirus Detection and Identification Assay Based on RT-qPCR and Microarray

PubMed Central

Sachse, Konrad; Ziegler, Ute; Keller, Markus

2017-01-01

The genus Flavivirus includes arthropod-borne viruses responsible for a large number of infections in humans and economically important animals. While RT-PCR protocols for specific detection of most Flavivirus species are available, there has been also a demand for a broad-range Flavivirus assay covering all members of the genus. It is particularly challenging to balance specificity at genus level with equal sensitivity towards each target species. In the present study, a novel assay combining a SYBR Green-based RT-qPCR with a low-density DNA microarray has been developed. Validation experiments confirmed that the RT-qPCR exhibited roughly equal sensitivity of detection and quantification for all flaviviruses tested. These PCR products are subjected to hybridization on a microarray carrying 84 different oligonucleotide probes that represent all known Flavivirus species. This assay has been used as a screening and confirmation tool for Flavivirus presence in laboratory and field samples, and it performed successfully in international External Quality Assessment of NAT studies. Twenty-six Flavivirus strains were tested with the assay, showing equivalent or superior characteristics compared with the original or even with species-specific RT-PCRs. As an example, test results on West Nile virus detection in a panel of 340 mosquito pool samples from Greece are presented. PMID:28626758

PGD and aneuploidy screening for 24 chromosomes: advantages and disadvantages of competing platforms.

PubMed

Bisignano, A; Wells, D; Harton, G; Munné, S

2011-12-01

Diagnosis of embryos for chromosome abnormalities, i.e. aneuploidy screening, has been invigorated by the introduction of microarray-based testing methods allowing analysis of 24 chromosomes in one test. Recent data have been suggestive of increased implantation and pregnancy rates following microarray testing. Preimplantation genetic diagnosis for infertility aims to test for gross chromosome changes with the hope that identification and transfer of normal embryos will improve IVF outcomes. Testing by some methods, specifically single-nucleotide polymorphism (SNP) microarrays, allow for more information and potential insight into parental origin of aneuploidy and uniparental disomy. The usefulness and validity of reporting this information is flawed. Numerous papers have shown that the majority of meiotic errors occur in the egg, while mitotic errors in the embryo affect parental chromosomes at random. Potential mistakes made in assigning an error as meiotic or mitotic may lead to erroneous reporting of results with medical consequences. This study's data suggest that the bioinformatic cleaning used to 'fix' the miscalls that plague single-cell whole-genome amplification provides little improvement in the quality of useful data. Based on the information available, SNP-based aneuploidy screening suffers from a number of serious issues that must be resolved. Copyright © 2011 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Development of reversible jump Markov Chain Monte Carlo algorithm in the Bayesian mixture modeling for microarray data in Indonesia

NASA Astrophysics Data System (ADS)

Astuti, Ani Budi; Iriawan, Nur; Irhamah, Kuswanto, Heri

2017-12-01

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number.

Detection and genotyping of Entamoeba histolytica, Entamoeba dispar, Giardia lamblia, and Cryptosporidium parvum by oligonucleotide microarray.

PubMed

Wang, Zheng; Vora, Gary J; Stenger, David A

2004-07-01

Entamoeba histolytica, Giardia lamblia, and Cryptosporidium parvum are the most frequently identified protozoan parasites causing waterborne disease outbreaks. The morbidity and mortality associated with these intestinal parasitic infections warrant the development of rapid and accurate detection and genotyping methods to aid public health efforts aimed at preventing and controlling outbreaks. In this study, we describe the development of an oligonucleotide microarray capable of detecting and discriminating between E. histolytica, Entamoeba dispar, G. lamblia assemblages A and B, and C. parvum types 1 and 2 in a single assay. Unique hybridization patterns for each selected protozoan were generated by amplifying six to eight diagnostic sequences/organism by multiplex PCR; fluorescent labeling of the amplicons via primer extension; and subsequent hybridization to a set of genus-, species-, and subtype-specific covalently immobilized oligonucleotide probes. The profile-based specificity of this methodology not only permitted for the unequivocal identification of the six targeted species and subtypes, but also demonstrated its potential in identifying related species such as Cryptosporidium meleagridis and Cryptosporidium muris. In addition, sensitivity assays demonstrated lower detection limits of five trophozoites of G. lamblia. Taken together, the specificity and sensitivity of the microarray-based approach suggest that this methodology may provide a promising tool to detect and genotype protozoa from clinical and environmental samples.

Using Microarrays to Facilitate Positional Cloning: Identification of Tomosyn as an Inhibitor of Neurosecretion

PubMed Central

Dybbs, Michael; Ngai, John; Kaplan, Joshua M

2005-01-01

Forward genetic screens have been used as a powerful strategy to dissect complex biological pathways in many model systems. A significant limitation of this approach has been the time-consuming and costly process of positional cloning and molecular characterization of the mutations isolated in these screens. Here, the authors describe a strategy using microarray hybridizations to facilitate positional cloning. This method relies on the fact that premature stop codons (i.e., nonsense mutations) constitute a frequent class of mutations isolated in screens and that nonsense mutant messenger RNAs are efficiently degraded by the conserved nonsense-mediated decay pathway. They validate this strategy by identifying two previously uncharacterized mutations: (1) tom-1, a mutation found in a forward genetic screen for enhanced acetylcholine secretion in Caenorhabditis elegans, and (2) an apparently spontaneous mutation in the hif-1 transcription factor gene. They further demonstrate the broad applicability of this strategy using other known mutants in C. elegans, Arabidopsis, and mouse. Characterization of tom-1 mutants suggests that TOM-1, the C. elegans ortholog of mammalian tomosyn, functions as an endogenous inhibitor of neurotransmitter secretion. These results also suggest that microarray hybridizations have the potential to significantly reduce the time and effort required for positional cloning. PMID:16103915

Expression profiling of cardiovascular disease

PubMed Central

2004-01-01

Cardiovascular disease is the most important cause of morbidity and mortality in developed countries, causing twice as many deaths as cancer in the USA. The major cardiovascular diseases, including coronary artery disease (CAD), myocardial infarction (MI), congestive heart failure (CHF) and common congenital heart disease (CHD), are caused by multiple genetic and environmental factors, as well as the interactions between them. The underlying molecular pathogenic mechanisms for these disorders are still largely unknown, but gene expression may play a central role in the development and progression of cardiovascular disease. Microarrays are high-throughput genomic tools that allow the comparison of global expression changes in thousands of genes between normal and diseased cells/tissues. Microarrays have recently been applied to CAD/MI, CHF and CHD to profile changes in gene expression patterns in diseased and non-diseased patients. This same technology has also been used to characterise endothelial cells, vascular smooth muscle cells and inflammatory cells, with or without various treatments that mimic disease processes involved in CAD/MI. These studies have led to the identification of unique subsets of genes associated with specific diseases and disease processes. Ongoing microarray studies in the field will provide insights into the molecular mechanism of cardiovascular disease and may generate new diagnostic and therapeutic markers. PMID:15588496

Constitutional downregulation of SEMA5A expression in autism.

PubMed

Melin, M; Carlsson, B; Anckarsater, H; Rastam, M; Betancur, C; Isaksson, A; Gillberg, C; Dahl, N

2006-01-01

There is strong evidence for the importance of genetic factors in idiopathic autism. The results from independent twin and family studies suggest that the disorder is caused by the action of several genes, possibly acting epistatically. We have used cDNA microarray technology for the identification of constitutional changes in the gene expression profile associated with idiopathic autism. Samples were obtained and analyzed from 6 affected subjects belonging to multiplex autism families and from 6 healthy controls. We assessed the expression levels for approximately 7,700 genes by cDNA microarrays using mRNA derived from Epstein-Barr virus-transformed B lymphocytes. The microarray data were analyzed in order to identify up- or downregulation of specific genes. A common pattern with nine downregulated genes was identified among samples derived from individuals with autism when compared to controls. Four of these nine genes encode proteins involved in biological processes associated with brain function or the immune system, and are consequently considered as candidates for genes associated with autism. Quantitative real-time PCR confirms the downregulation of the gene encoding SEMA5A, a protein involved in axonal guidance. Epstein-Barr virus should be considered as a possible source for altered expression, but our consistent results make us suggest SEMA5A as a candidate gene in the etiology of idiopathic autism.

Constitutional downregulation of SEMA5A expression in autism

PubMed Central

Melin, Malin; Carlsson, Birgit; Anckarsäter, Henrik; Rastam, Maria; Betancur, Catalina; Isaksson, Anders; Gillberg, Christopher; Dahl, Niklas

2006-01-01

There is strong evidence for the importance of genetic factors in idiopathic autism. The results from independent twin and family studies suggest that the disorder is caused by the action of several genes, possibly acting epistatically. We have used cDNA microarray technology for the identification of constitutional changes in the gene expression profile associated with idiopathic autism. Samples were obtained and analyzed from six affected subjects belonging to multiplex autism families and from six healthy controls. We assessed the expression levels for approximately 7,700 genes by cDNA microarrays using mRNA derived from Epstein Barr virus (EBV)-transformed B-lymphocytes. The microarray data was analyzed in order to identify up- or down-regulation of specific genes. A common pattern with nine down-regulated genes was identified among samples derived from individuals with autism when compared to controls. Four of these nine genes encode proteins involved in biological processes associated with brain function or the immune system, and are consequently considered as candidates for genes associated with autism. Quantitative realtime PCR confirms the down-regulation of the gene encoding SEMA5A, a protein involved in axonal guidance. EBV should be considered as a possible source for altered expression but our consistent results make us suggest SEMA5A a candidate gene in the etiology of idiopathic autism. PMID:17028446

Understanding the molecular aspects of oriental obesity pattern differentiation using DNA microarray.

PubMed

Hong, Sun Woo; Yoo, Jae-Wook; Bose, Shambhunath; Park, Jung-Hyun; Han, Kyungsun; Kim, Soyoun; Lim, Chi-Yeon; Kim, Hojun; Lee, Dong-Ki

2015-10-19

Human constitution, the fundamental basis of oriental medicine, is categorized into different patterns for a particular disease according to the physical, physiological, and clinical characteristics of the individuals. Obesity, a condition of metabolic disorder, is classified according to six patterns in oriental medicine, as follows: spleen deficiency syndrome, phlegm fluid syndrome, yang deficiency syndrome (YDS), food accumulation syndrome (FAS), liver depression syndrome (LDS), and blood stasis syndrome. In oriental medicine, identification of the disease pattern for individual obese patients is performed on the basis of differentiation in obesity syndrome index and, accordingly, personalized treatment is provided to the patients. The aim of the current study was to understand the obesity patterns in oriental medicine from the genomic point of view via determining the gene expression signature of obese patients using peripheral blood mononuclear cells as the samples. The study was conducted in 23 South Korean obese subjects (19 female and four male) with BMI ≥25 kg/m(2). Identification of oriental obesity pattern was based on the software-guided evaluation of the responses of the subjects to a questionnaire developed by the Korean Institute of Oriental Medicine. The expression profiles of genes were determined using DNA microarray and the level of transcription of genes of interest was further evaluated using quantitative real-time PCR (qRT-PCR). Gene clustering analysis of the microarray data from the FAS, LDS, and YDS subjects exhibited disease pattern-specific upregulation of expression of several genes in a particular cluster. Further analysis of transcription of selected genes using qRT-PCR led to identification of specific genes, including prostaglandin endoperoxide synthase 2, G0/G1 switch 2, carcinoembryonic antigen-related cell adhesion molecule 3, cystein-serine-rich nuclear protein 1, and interleukin 8 receptor, alpha which were highly expressed in LDS obesity constitution. Our current study can be considered as a valuable contribution to the understanding of possible explanation for obesity pattern differentiation in oriental medicine. Further studies can address a novel possibility that the genomic and oriental empirical approaches can be combined and implemented in systematic and synergistic development of personalized medicine. This clinical trial was registered in Clinical Research Information Service of Korea National Institute of Health ( https://cris.nih.go.kr/cris/index.jsp ). KCT0000387.

Genomic resources in fruit plants: an assessment of current status.

PubMed

Rai, Manoj K; Shekhawat, N S

2015-01-01

The availability of many genomic resources such as genome sequences, functional genomics resources including microarrays and RNA-seq, sufficient numbers of molecular markers, express sequence tags (ESTs) and high-density genetic maps is causing a rapid acceleration of genetics and genomic research of many fruit plants. This is leading to an increase in our knowledge of the genes that are linked to many horticultural and agronomically important traits. Recently, some progress has also been made on the identification and functional analysis of miRNAs in some fruit plants. This is one of the most active research fields in plant sciences. The last decade has witnessed development of genomic resources in many fruit plants such as apple, banana, citrus, grapes, papaya, pears, strawberry etc.; however, many of them are still not being exploited. Furthermore, owing to lack of resources, infrastructure and research facilities in many lesser-developed countries, development of genomic resources in many underutilized or less-studied fruit crops, which grow in these countries, is limited. Thus, research emphasis should be given to those fruit crops for which genomic resources are relatively scarce. The development of genomic databases of these less-studied fruit crops will enable biotechnologists to identify target genes that underlie key horticultural and agronomical traits. This review presents an overview of the current status of the development of genomic resources in fruit plants with the main emphasis being on genome sequencing, EST resources, functional genomics resources including microarray and RNA-seq, identification of quantitative trait loci and construction of genetic maps as well as efforts made on the identification and functional analysis of miRNAs in fruit plants.

Genome-wide microarray analysis leads to identification of genes in response to herbicide, metribuzin in wheat leaves.

PubMed

Pilcher, Whitney; Zandkamiri, Hana; Arceneaux, Kelly; Harrison, Stephen; Baisakh, Niranjan

2017-01-01

Herbicides are an important component of weed management in wheat, particularly in the southeastern US where weeds actively compete with wheat throughout the winter for nutrients and reduce tillering and ultimately the yield of the crop. Some wheat varieties are sensitive to metribuzin, a low-cost non-selective herbicide, leading to leaf chlorosis, stand loss, and decreased yield. Knowledge of the genetics of herbicide tolerance in wheat is very limited and most new varieties have not been screened for metribuzin tolerance. The identification of genes associated with metribuzin tolerance will lead to the development of molecular markers for use in screening breeding lines for metribuzin tolerance. AGS 2035 and AGS 2060 were identified as resistant and sensitive to metribuzin in several previous field screening experiments as well as controlled condition screening of nine varieties in the present study. Genome-wide transcriptome profiling of the genes in AGS 2035 and AGS 2060 through microarray analysis identified 169 and 127 genes to be significantly (2-fold, P>0.01) up- and down-regulated, respectively in response to metribuzin. Functional annotation revealed that genes involved in cell wall biosynthesis, photosynthesis and sucrose metabolism were highly responsive to metribuzin application. (Semi)quantitative RT-PCR of seven selected differentially expressed genes (DEGs) indicated that a gene coding for alkaline alpha-galactosidase 2 (AAG2) was specifically expressed in resistant varieties only after one and two weeks of metribuzin application. Integration of the DEGs into our ongoing mapping effort and identification of the genes within the QTL region showing significant association with resistance in future will aid in development of functional markers for metribuzin resistance.

Clustering of Staphylococcus aureus bovine mastitis strains from regions of Central-Eastern Poland based on their biochemical and genetic characteristics.

PubMed

Puacz, E; Ilczyszyn, W M; Kosecka, M; Buda, A; Dudziak, W; Polakowska, K; Panz, T; Białecka, A; Kasprowicz, A; Lisowski, A; Krukowski, H; Cuteri, V; Międzobrodzki, J

2015-01-01

Staphylococcus aureus strains were isolated from mastitic milk of cows with infected mammary glands. The animals were living in 12 different farms near Lublin, in Central-Eastern Poland. A biochemical identification method based on enzymatic assay was performed, followed by haemolytic and proteolytic tests. PCR-RFLP targeted on the gap gene allowed the genetic identification of strains at the species level and verified phenotypic identification results. A molecular typing method using triplex PCR was performed to recognize the genetic similarity of the analyzed strains. DNA microarray hybridization (StaphyType, Alere Technologies) was used for detection of antibiotic resistance and virulence associated markers. The results obtained indicate high genetic similarity in strains isolated from the same sites. High genetic similarities were also detected between strains isolated from cows from different farms of the same region. A slightly lower similarity was noted however, in strains from various regions indicating that the strains are herd specific and that the cow's infections caused by S. aureus were of a clonal character. In 21 representative isolates selected for DNA-microarray testing, only fosfomycin (fosB) and penicillin resistance markers (blaZ, blaI, blaR) were detected. The presence of genes coding for haemolysins (lukF, lukS, hlgA, hla, hld, hlb), proteases (aur, sspA, sspB, sspP), enterotoxins (entA, entD, entG, entI, entJ, entM, entN, entO, entR, entU, egc-cluster), adhesins (icaA, icaC, icaD, bbp, clfA, clfB, fib, fnbA, map, vwb) or immune evasion proteins (scn, chp, sak) was common and, with exceptions, matched triplex PCR-defined clusters.

DNA Microarray-Based Identification of Genes Controlled by Autoinducer 2-Stimulated Quorum Sensing in Escherichia Coli

DTIC Science & Technology

2001-09-01

and pathogenicity in Erwinia carotovora (rsmA) (12). Additionally, csrA has been documented to affect cell size and surface properties, which is in...machinery to cell wall 13.1 b1502 Putative adhesin; similar to FimH protein 13.0 tap Methyl-accepting chemotaxis protein IV, peptide sensor receptor...oxohexanoyl)-L-homoserine lactone 5246 DELISA ET AL. J. BACTERIOL. regulates carbapenem antibiotic production in Erwinia carotovora . Biochem. J. 288:997

Development of a Genome-Proxy Microarray for Profiling Marine Microbial Communities and its Application to a Time Series in Monterey Bay, California

DTIC Science & Technology

2008-09-01

community representation. 12 survey a complex microbial community. Community DNA or rRNA extracted from a sample may require amplification before...restricted to cultivated clades, since not only do many clades have sufficient database representation due to 16S environmental surveys , but such...well developed for standard and comprehensive surveys . Depending on the population being targeted and the identification method, FCM can be a

Single-feature polymorphism discovery in the barley transcriptome

PubMed Central

Rostoks, Nils; Borevitz, Justin O; Hedley, Peter E; Russell, Joanne; Mudie, Sharon; Morris, Jenny; Cardle, Linda; Marshall, David F; Waugh, Robbie

2005-01-01

A probe-level model for analysis of GeneChip gene-expression data is presented which identified more than 10,000 single-feature polymorphisms (SFP) between two barley genotypes. The method has good sensitivity, as 67% of known single-nucleotide polymorphisms (SNP) were called as SFPs. This method is applicable to all oligonucleotide microarray data, accounts for SNP effects in gene-expression data and represents an efficient and versatile approach for highly parallel marker identification in large genomes. PMID:15960806

Application of Broad-Spectrum Resequencing Microarray for Genotyping Rhabdoviruses▿

PubMed Central

Dacheux, Laurent; Berthet, Nicolas; Dissard, Gabriel; Holmes, Edward C.; Delmas, Olivier; Larrous, Florence; Guigon, Ghislaine; Dickinson, Philip; Faye, Ousmane; Sall, Amadou A.; Old, Iain G.; Kong, Katherine; Kennedy, Giulia C.; Manuguerra, Jean-Claude; Cole, Stewart T.; Caro, Valérie; Gessain, Antoine; Bourhy, Hervé

2010-01-01

The rapid and accurate identification of pathogens is critical in the control of infectious disease. To this end, we analyzed the capacity for viral detection and identification of a newly described high-density resequencing microarray (RMA), termed PathogenID, which was designed for multiple pathogen detection using database similarity searching. We focused on one of the largest and most diverse viral families described to date, the family Rhabdoviridae. We demonstrate that this approach has the potential to identify both known and related viruses for which precise sequence information is unavailable. In particular, we demonstrate that a strategy based on consensus sequence determination for analysis of RMA output data enabled successful detection of viruses exhibiting up to 26% nucleotide divergence with the closest sequence tiled on the array. Using clinical specimens obtained from rabid patients and animals, this method also shows a high species level concordance with standard reference assays, indicating that it is amenable for the development of diagnostic assays. Finally, 12 animal rhabdoviruses which were currently unclassified, unassigned, or assigned as tentative species within the family Rhabdoviridae were successfully detected. These new data allowed an unprecedented phylogenetic analysis of 106 rhabdoviruses and further suggest that the principles and methodology developed here may be used for the broad-spectrum surveillance and the broader-scale investigation of biodiversity in the viral world. PMID:20610710

Identification and expression analysis of cold and freezing stress responsive genes of Brassica oleracea.

PubMed

Ahmed, Nasar Uddin; Jung, Hee-Jeong; Park, Jong-In; Cho, Yong-Gu; Hur, Yoonkang; Nou, Ill-Sup

2015-01-10

Cold and freezing stress is a major environmental constraint to the production of Brassica crops. Enhancement of tolerance by exploiting cold and freezing tolerance related genes offers the most efficient approach to address this problem. Cold-induced transcriptional profiling is a promising approach to the identification of potential genes related to cold and freezing stress tolerance. In this study, 99 highly expressed genes were identified from a whole genome microarray dataset of Brassica rapa. Blast search analysis of the Brassica oleracea database revealed the corresponding homologous genes. To validate their expression, pre-selected cold tolerant and susceptible cabbage lines were analyzed. Out of 99 BoCRGs, 43 were differentially expressed in response to varying degrees of cold and freezing stress in the contrasting cabbage lines. Among the differentially expressed genes, 18 were highly up-regulated in the tolerant lines, which is consistent with their microarray expression. Additionally, 12 BoCRGs were expressed differentially after cold stress treatment in two contrasting cabbage lines, and BoCRG54, 56, 59, 62, 70, 72 and 99 were predicted to be involved in cold regulatory pathways. Taken together, the cold-responsive genes identified in this study provide additional direction for elucidating the regulatory network of low temperature stress tolerance and developing cold and freezing stress resistant Brassica crops. Copyright © 2014 Elsevier B.V. All rights reserved.

Mutation Spectrum of the ABCA4 Gene in a Greek Cohort with Stargardt Disease: Identification of Novel Mutations and Evidence of Three Prevalent Mutated Alleles

PubMed Central

Vassiliki, Kokkinou; George, Koutsodontis; Polixeni, Stamatiou; Christoforos, Giatzakis; Minas, Aslanides Ioannis; Stavrenia, Koukoula; Ioannis, Datseris

2018-01-01

Aim To evaluate the frequency and pattern of disease-associated mutations of ABCA4 gene among Greek patients with presumed Stargardt disease (STGD1). Materials and Methods A total of 59 patients were analyzed for ABCA4 mutations using the ABCR400 microarray and PCR-based sequencing of all coding exons and flanking intronic regions. MLPA analysis as well as sequencing of two regions in introns 30 and 36 reported earlier to harbor deep intronic disease-associated variants was used in 4 selected cases. Results An overall detection rate of at least one mutant allele was achieved in 52 of the 59 patients (88.1%). Direct sequencing improved significantly the complete characterization rate, that is, identification of two mutations compared to the microarray analysis (93.1% versus 50%). In total, 40 distinct potentially disease-causing variants of the ABCA4 gene were detected, including six previously unreported potentially pathogenic variants. Among the disease-causing variants, in this cohort, the most frequent was c.5714+5G>A representing 16.1%, while p.Gly1961Glu and p.Leu541Pro represented 15.2% and 8.5%, respectively. Conclusions By using a combination of methods, we completely molecularly diagnosed 48 of the 59 patients studied. In addition, we identified six previously unreported, potentially pathogenic ABCA4 mutations. PMID:29854428

Integrating Microarray Data and GRNs.

PubMed

Koumakis, L; Potamias, G; Tsiknakis, M; Zervakis, M; Moustakis, V

2016-01-01

With the completion of the Human Genome Project and the emergence of high-throughput technologies, a vast amount of molecular and biological data are being produced. Two of the most important and significant data sources come from microarray gene-expression experiments and respective databanks (e,g., Gene Expression Omnibus-GEO (http://www.ncbi.nlm.nih.gov/geo)), and from molecular pathways and Gene Regulatory Networks (GRNs) stored and curated in public (e.g., Kyoto Encyclopedia of Genes and Genomes-KEGG (http://www.genome.jp/kegg/pathway.html), Reactome (http://www.reactome.org/ReactomeGWT/entrypoint.html)) as well as in commercial repositories (e.g., Ingenuity IPA (http://www.ingenuity.com/products/ipa)). The association of these two sources aims to give new insight in disease understanding and reveal new molecular targets in the treatment of specific phenotypes.Three major research lines and respective efforts that try to utilize and combine data from both of these sources could be identified, namely: (1) de novo reconstruction of GRNs, (2) identification of Gene-signatures, and (3) identification of differentially expressed GRN functional paths (i.e., sub-GRN paths that distinguish between different phenotypes). In this chapter, we give an overview of the existing methods that support the different types of gene-expression and GRN integration with a focus on methodologies that aim to identify phenotype-discriminant GRNs or subnetworks, and we also present our methodology.

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

PubMed Central

2013-01-01

Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

Application of an oligonucleotide microarray-based nano-amplification technique for the detection of fungal pathogens.

PubMed

Lu, Weiping; Gu, Dayong; Chen, Xingyun; Xiong, Renping; Liu, Ping; Yang, Nan; Zhou, Yuanguo

2010-10-01

The traditional techniques for diagnosis of invasive fungal infections in the clinical microbiology laboratory need improvement. These techniques are prone to delay results due to their time-consuming process, or result in misidentification of the fungus due to low sensitivity or low specificity. The aim of this study was to develop a method for the rapid detection and identification of fungal pathogens. The internal transcribed spacer two fragments of fungal ribosomal DNA were amplified using a polymerase chain reaction for all samples. Next, the products were hybridized with the probes immobilized on the surface of a microarray. These species-specific probes were designed to detect nine different clinical pathogenic fungi including Candida albicans, Candida tropocalis, Candida glabrata, Candida parapsilosis, Candida krusei, Candida lusitaniae, Candida guilliermondii, Candida keyfr, and Cryptococcus neoformans. The hybridizing signals were enhanced with gold nanoparticles and silver deposition, and detected using a flatbed scanner or visually. Fifty-nine strains of fungal pathogens, including standard and clinically isolated strains, were correctly identified by this method. The sensitivity of the assay for Candida albicans was 10 cells/mL. Ten cultures from clinical specimens and 12 clinical samples spiked with fungi were also identified correctly. This technique offers a reliable alternative to conventional methods for the detection and identification of fungal pathogens. It has higher efficiency, specificity and sensitivity compared with other methods commonly used in the clinical laboratory.

Identification of Novel Tissue-Specific Genes by Analysis of Microarray Databases: A Human and Mouse Model

PubMed Central

Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon

2013-01-01

Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331

Identification of genes modulated in rheumatoid arthritis using complementary DNA microarray analysis of lymphoblastoid B cell lines from disease-discordant monozygotic twins.

PubMed

Haas, Christian S; Creighton, Chad J; Pi, Xiujun; Maine, Ira; Koch, Alisa E; Haines, G Kenneth; Ling, Song; Chinnaiyan, Arul M; Holoshitz, Joseph

2006-07-01

To identify disease-specific gene expression profiles in patients with rheumatoid arthritis (RA), using complementary DNA (cDNA) microarray analyses on lymphoblastoid B cell lines (LCLs) derived from RA-discordant monozygotic (MZ) twins. The cDNA was prepared from LCLs derived from the peripheral blood of 11 pairs of RA-discordant MZ twins. The RA twin cDNA was labeled with cy5 fluorescent dye, and the cDNA of the healthy co-twin was labeled with cy3. To determine relative expression profiles, cDNA from each twin pair was combined and hybridized on 20,000-element microarray chips. Immunohistochemistry and real-time polymerase chain reaction were used to detect the expression of selected gene products in synovial tissue from patients with RA compared with patients with osteoarthritis and normal healthy controls. In RA twin LCLs compared with healthy co-twin LCLs, 1,163 transcripts were significantly differentially expressed. Of these, 747 were overexpressed and 416 were underexpressed. Gene ontology analysis revealed many genes known to play a role in apoptosis, angiogenesis, proteolysis, and signaling. The 3 most significantly overexpressed genes were laeverin (a novel enzyme with sequence homology to CD13), 11beta-hydroxysteroid dehydrogenase type 2 (a steroid pathway enzyme), and cysteine-rich, angiogenic inducer 61 (a known angiogenic factor). The products of these genes, heretofore uncharacterized in RA, were all abundantly expressed in RA synovial tissues. Microarray cDNA analysis of peripheral blood-derived LCLs from well-controlled patient populations is a useful tool to detect RA-relevant genes and could help in identifying novel therapeutic targets.

The CD117 immunohistochemistry tissue microarray survey for quality assurance and interlaboratory comparison: a College of American Pathologists Cell Markers Committee Study.

PubMed

Dorfman, David M; Bui, Marilyn M; Tubbs, Raymond R; Hsi, Eric D; Fitzgibbons, Patrick L; Linden, Michael D; Rickert, Robert R; Roche, Patrick C

2006-06-01

We have developed tissue microarray-based surveys to allow laboratories to compare their performance in staining predictive immunohistochemical markers, including proto-oncogene CD117 (c-kit), which is characteristically expressed in gastrointestinal stromal tumors (GISTs). GISTs exhibit activating mutations in the c-kit proto-oncogene, which render them amenable to treatment with imatinib mesylate. Consequently, correct identification of c-Kit expression is important for the diagnosis and treatment of GISTs. To analyze CD117 immunohistochemical staining performance by a large number of clinical laboratories. A mechanical device was used to construct tissue microarrays consisting of 3 x 1-mm cores of 10 tumor samples, which can be used to generate hundreds of tissue sections from the arrayed cases, suitable for large-scale interlaboratory comparison of immunohistochemical staining. An initial survey of 63 laboratories and a second survey of 90 laboratories, performed in 2004 and 2005, exhibited >81% concordance for 7 of 10 cores, including all 4 GIST cases, which were immunoreactive for CD117 with >95% staining concordance. Three of the cores achieved less than 81% concordance of results, possibly due to the presence of foci of necrosis in one core and CD117-positive mast cells in 2 cores of CD117-negative neoplasms. There was good performance among a large number of laboratories performing CD117 immunohistochemical staining, with consistently higher concordance of results for CD117-positive GIST cases than for nonimmunoreactive cases. Tissue microarrays for CD117 and other predictive markers should be useful for interlaboratory comparisons, quality assurance, and education of participants regarding staining nuances such as the expression of CKIT by nonneoplastic mast cells.

DNA microarray analyses reveal a post-irradiation differential time-dependent gene expression profile in yeast cells exposed to X-rays and gamma-rays.

PubMed

Kimura, Shinzo; Ishidou, Emi; Kurita, Sakiko; Suzuki, Yoshiteru; Shibato, Junko; Rakwal, Randeep; Iwahashi, Hitoshi

2006-07-21

Ionizing radiation (IR) is the most enigmatic of genotoxic stress inducers in our environment that has been around from the eons of time. IR is generally considered harmful, and has been the subject of numerous studies, mostly looking at the DNA damaging effects in cells and the repair mechanisms therein. Moreover, few studies have focused on large-scale identification of cellular responses to IR, and to this end, we describe here an initial study on the transcriptional responses of the unicellular genome model, yeast (Saccharomyces cerevisiae strain S288C), by cDNA microarray. The effect of two different IR, X-rays, and gamma (gamma)-rays, was investigated by irradiating the yeast cells cultured in YPD medium with 50 Gy doses of X- and gamma-rays, followed by resuspension of the cells in YPD for time-course experiments. The samples were collected for microarray analysis at 20, 40, and 80 min after irradiation. Microarray analysis revealed a time-course transcriptional profile of changed gene expressions. Up-regulated genes belonged to the functional categories mainly related to cell cycle and DNA processing, cell rescue defense and virulence, protein and cell fate, and metabolism (X- and gamma-rays). Similarly, for X- and gamma-rays, the down-regulated genes belonged to mostly transcription and protein synthesis, cell cycle and DNA processing, control of cellular organization, cell fate, and C-compound and carbohydrate metabolism categories, respectively. This study provides for the first time a snapshot of the genome-wide mRNA expression profiles in X- and gamma-ray post-irradiated yeast cells and comparatively interprets/discusses the changed gene functional categories as effects of these two radiations vis-à-vis their energy levels.

Genome analysis of Legionella pneumophila strains using a mixed-genome microarray.

PubMed

Euser, Sjoerd M; Nagelkerke, Nico J; Schuren, Frank; Jansen, Ruud; Den Boer, Jeroen W

2012-01-01

Legionella, the causative agent for Legionnaires' disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data. Microarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in The Netherlands in the period 2002-2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental. Four genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment.

MicroRNA-integrated and network-embedded gene selection with diffusion distance.

PubMed

Huang, Di; Zhou, Xiaobo; Lyon, Christopher J; Hsueh, Willa A; Wong, Stephen T C

2010-10-29

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways.

Histological staining methods preparatory to laser capture microdissection significantly affect the integrity of the cellular RNA.

PubMed

Wang, Hongyang; Owens, James D; Shih, Joanna H; Li, Ming-Chung; Bonner, Robert F; Mushinski, J Frederic

2006-04-27

Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays. The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases. RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts.

Histological staining methods preparatory to laser capture microdissection significantly affect the integrity of the cellular RNA

PubMed Central

Wang, Hongyang; Owens, James D; Shih, Joanna H; Li, Ming-Chung; Bonner, Robert F; Mushinski, J Frederic

2006-01-01

Background Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays. Results The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases. Conclusion RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts. PMID:16643667

cDNA microarrays as a tool for identification of biomineralization proteins in the coccolithophorid Emiliania huxleyi (Haptophyta).

PubMed

Quinn, Patrick; Bowers, Robert M; Zhang, Xiaoyu; Wahlund, Thomas M; Fanelli, Michael A; Olszova, Daniela; Read, Betsy A

2006-08-01

Marine unicellular coccolithophore algae produce species-specific calcite scales otherwise known as coccoliths. While the coccoliths and their elaborate architecture have attracted the attention of investigators from various scientific disciplines, our knowledge of the underpinnings of the process of biomineralization in this alga is still in its infancy. The processes of calcification and coccolithogenesis are highly regulated and likely to be complex, requiring coordinated expression of many genes and pathways. In this study, we have employed cDNA microarrays to investigate changes in gene expression associated with biomineralization in the most abundant coccolithophorid, Emiliania huxleyi. Expression profiling of cultures grown under calcifying and noncalcifying conditions has been carried out using cDNA microarrays corresponding to approximately 2,300 expressed sequence tags. A total of 127 significantly up- or down-regulated transcripts were identified using a P value of 0.01 and a change of >2.0-fold. Real-time reverse transcriptase PCR was used to test the overall validity of the microarray data, as well as the relevance of many of the proteins predicted to be associated with biomineralization, including a novel gamma-class carbonic anhydrase (A. R. Soto, H. Zheng, D. Shoemaker, J. Rodriguez, B. A. Read, and T. M. Wahlund, Appl. Environ. Microbiol. 72:5500-5511, 2006). Differentially regulated genes include those related to cellular metabolism, ion channels, transport proteins, vesicular trafficking, and cell signaling. The putative function of the vast majority of candidate transcripts could not be defined. Nonetheless, the data described herein represent profiles of the transcription changes associated with biomineralization-related pathways in E. huxleyi and have identified novel and potentially useful targets for more detailed analysis.

cDNA Microarrays as a Tool for Identification of Biomineralization Proteins in the Coccolithophorid Emiliania huxleyi (Haptophyta)

PubMed Central

Quinn, Patrick; Bowers, Robert M.; Zhang, Xiaoyu; Wahlund, Thomas M.; Fanelli, Michael A.; Olszova, Daniela; Read, Betsy A.

2006-01-01

Marine unicellular coccolithophore algae produce species-specific calcite scales otherwise known as coccoliths. While the coccoliths and their elaborate architecture have attracted the attention of investigators from various scientific disciplines, our knowledge of the underpinnings of the process of biomineralization in this alga is still in its infancy. The processes of calcification and coccolithogenesis are highly regulated and likely to be complex, requiring coordinated expression of many genes and pathways. In this study, we have employed cDNA microarrays to investigate changes in gene expression associated with biomineralization in the most abundant coccolithophorid, Emiliania huxleyi. Expression profiling of cultures grown under calcifying and noncalcifying conditions has been carried out using cDNA microarrays corresponding to approximately 2,300 expressed sequence tags. A total of 127 significantly up- or down-regulated transcripts were identified using a P value of 0.01 and a change of >2.0-fold. Real-time reverse transcriptase PCR was used to test the overall validity of the microarray data, as well as the relevance of many of the proteins predicted to be associated with biomineralization, including a novel gamma-class carbonic anhydrase (A. R. Soto, H. Zheng, D. Shoemaker, J. Rodriguez, B. A. Read, and T. M. Wahlund, Appl. Environ. Microbiol. 72:5500-5511, 2006). Differentially regulated genes include those related to cellular metabolism, ion channels, transport proteins, vesicular trafficking, and cell signaling. The putative function of the vast majority of candidate transcripts could not be defined. Nonetheless, the data described herein represent profiles of the transcription changes associated with biomineralization-related pathways in E. huxleyi and have identified novel and potentially useful targets for more detailed analysis. PMID:16885305

The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison

PubMed Central

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

Identification of Early Response Genes in Human Peripheral Leukocytes Infected with Orientia tsutsugamushi: The Emergent of a Unique Gene Expression Profile for Diagnosis of O. tsutsugamush Infection

DTIC Science & Technology

2010-01-01

dynein to move from the cell periphery to the microtubule organizing center [22]. Therefore, the initial interactions between host and intracellular...used to study host-pathogen interactions , mainly by identifying genes from pathogens that may be involved in pathogenecity and by surveying the scope...toward understanding the host-Orientia tsutsugamushi interaction at the molecular level, we used human cDNA microarray technology to examine in detail

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

Identification and validation of vesicant therapeutic targets using a high, throughput siRNA screening approach

DTIC Science & Technology

2014-12-24

toxlet.2011.04.007 Rogers JV, Choi YW, Kiser RC et al (2004) Microarray analysis of gene expression in murine skin exposed to sulfur mustard. J Bio...Chemotactic factors released in culture by intact developing and healing skin lesions produced in rabbits by the irritant sulfur mustard. Inflam- mation 21(2...Project ID Number CBM.CUTOC.04.10. RC 00114. ABSTRACT See reprint. 15. SUBJECT TERMS sulfur mustard, cutaneous injury, siRNA, high-throughput screening

Strategies for cell manipulation and skeletal tissue engineering using high-throughput polymer blend formulation and microarray techniques.

PubMed

Khan, Ferdous; Tare, Rahul S; Kanczler, Janos M; Oreffo, Richard O C; Bradley, Mark

2010-03-01

A combination of high-throughput material formulation and microarray techniques were synergistically applied for the efficient analysis of the biological functionality of 135 binary polymer blends. This allowed the identification of cell-compatible biopolymers permissive for human skeletal stem cell growth in both in vitro and in vivo applications. The blended polymeric materials were developed from commercially available, inexpensive and well characterised biodegradable polymers, which on their own lacked both the structural requirements of a scaffold material and, critically, the ability to facilitate cell growth. Blends identified here proved excellent templates for cell attachment, and in addition, a number of blends displayed remarkable bone-like architecture and facilitated bone regeneration by providing 3D biomimetic scaffolds for skeletal cell growth and osteogenic differentiation. This study demonstrates a unique strategy to generate and identify innovative materials with widespread application in cell biology as well as offering a new reparative platform strategy applicable to skeletal tissues. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Gene regulatory network identification from the yeast cell cycle based on a neuro-fuzzy system.

PubMed

Wang, B H; Lim, J W; Lim, J S

2016-08-30

Many studies exist for reconstructing gene regulatory networks (GRNs). In this paper, we propose a method based on an advanced neuro-fuzzy system, for gene regulatory network reconstruction from microarray time-series data. This approach uses a neural network with a weighted fuzzy function to model the relationships between genes. Fuzzy rules, which determine the regulators of genes, are very simplified through this method. Additionally, a regulator selection procedure is proposed, which extracts the exact dynamic relationship between genes, using the information obtained from the weighted fuzzy function. Time-series related features are extracted from the original data to employ the characteristics of temporal data that are useful for accurate GRN reconstruction. The microarray dataset of the yeast cell cycle was used for our study. We measured the mean squared prediction error for the efficiency of the proposed approach and evaluated the accuracy in terms of precision, sensitivity, and F-score. The proposed method outperformed the other existing approaches.

High-throughput multiplex HLA-typing by ligase detection reaction (LDR) and universal array (UA) approach.

PubMed

Consolandi, Clarissa

2009-01-01

One major goal of genetic research is to understand the role of genetic variation in living systems. In humans, by far the most common type of such variation involves differences in single DNA nucleotides, and is thus termed single nucleotide polymorphism (SNP). The need for improvement in throughput and reliability of traditional techniques makes it necessary to develop new technologies. Thus the past few years have witnessed an extraordinary surge of interest in DNA microarray technology. This new technology offers the first great hope for providing a systematic way to explore the genome. It permits a very rapid analysis of thousands genes for the purpose of gene discovery, sequencing, mapping, expression, and polymorphism detection. We generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. In particular, we set up a universal array approach in combination with a PCR-LDR (polymerase chain reaction-ligation detection reaction) strategy for allele identification in the HLA gene.

Fast gene ontology based clustering for microarray experiments.

PubMed

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.

Identification of consensus biomarkers for predicting non-genotoxic hepatocarcinogens

PubMed Central

Huang, Shan-Han; Tung, Chun-Wei

2017-01-01

The assessment of non-genotoxic hepatocarcinogens (NGHCs) is currently relying on two-year rodent bioassays. Toxicogenomics biomarkers provide a potential alternative method for the prioritization of NGHCs that could be useful for risk assessment. However, previous studies using inconsistently classified chemicals as the training set and a single microarray dataset concluded no consensus biomarkers. In this study, 4 consensus biomarkers of A2m, Ca3, Cxcl1, and Cyp8b1 were identified from four large-scale microarray datasets of the one-day single maximum tolerated dose and a large set of chemicals without inconsistent classifications. Machine learning techniques were subsequently applied to develop prediction models for NGHCs. The final bagging decision tree models were constructed with an average AUC performance of 0.803 for an independent test. A set of 16 chemicals with controversial classifications were reclassified according to the consensus biomarkers. The developed prediction models and identified consensus biomarkers are expected to be potential alternative methods for prioritization of NGHCs for further experimental validation. PMID:28117354

Microarray evaluation of gene expression profiles in inflamed and healthy human dental pulp: the role of IL1beta and CD40 in pulp inflammation.

PubMed

Gatta, V; Zizzari, V L; Dd ' Amico, V; Salini, L; D' Aurora, M; Franchi, S; Antonucci, I; Sberna, M T; Gherlone, E; Stuppia, L; Tetè, S

2012-01-01

Dental pulp undergoes a number of changes passing from healthy status to inflammation due to deep decay. These changes are regulated by several genes resulting differently expressed in inflamed and healthy dental pulp, and the knowledge of the processes underlying this differential expression is of great relevance in the identification of the pathogenesis of the disease. In this study, the gene expression profile of inflamed and healthy dental pulps were compared by microarray analysis, and data obtained were analyzed by Ingenuity Pathway Analysis (IPA) software. This analysis allows to focus on a variety of genes, typically expressed in inflamed tissues. The comparison analysis showed an increased expression of several genes in inflamed pulp, among which IL1β and CD40 resulted of particular interest. These results indicate that gene expression profile of human dental pulp in different physiological and pathological conditions may become an useful tool for improving our knowledge about processes regulating pulp inflammation.

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning. Analysis of Space Grown Arabidopsis with Microarray Data from GeneLab: Identification of Genes Important in Vascular Patterning

NASA Technical Reports Server (NTRS)

Weitzel, A. J.; Wyatt, S. E.; Parsons-Wingerter, P.

2016-01-01

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photo-assimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be up-regulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS (Auxin-Regulated Gene Involved in Organ Size)-like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm up-regulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

Extracellular vesicles from Paracoccidioides pathogenic species transport polysaccharide and expose ligands for DC-SIGN receptors

DOE PAGES

da Silva, Roberta Peres; Heiss, Christian; Black, Ian; ...

2015-09-21

Extracellular vesicles (EVs) mediate non-conventional transport of molecules across the fungal cell wall. We aimed at describing the carbohydrate composition and surface carbohydrate epitopes of EVs isolated from the pathogenic fungi Paracoccidioides brasiliensis and P. lutzii using standard procedures. Total EV carbohydrates were ethanol-precipitated from preparations depleted of lipids and proteins, then analyzed by chemical degradation, gas chromatography-mass spectrometry, nuclear magnetic resonance and size-exclusion chromatography. EV glycosyl residues of Glc, Man, and Gal comprised most probably two major components: a high molecular mass 4,6-α-glucan and a galactofuranosylmannan, possibly an oligomer, bearing a 2-α-Manp main chain linked to β-Galf (1,3) andmore » α-Manp (1,6) end units. The results also suggested the presence of small amounts of a (1→6)- Manp polymer, (1→3)-glucan and (1→6)-glucan. Glycan microarrays allowed identification of EV surface lectin(s), while plant lectin microarray profiling revealed terminal Man and GlcNAc residues exposed at the EVs surface. Mammalian lectin microarray profiling showed that DC-SIGN receptors recognized surface carbohydrate in Paracoccidioides EVs. Our results suggest that oligosaccharides, cytoplasmic storage, and cell wall polysaccharides can be exported in fungal EVs, which also expose surface PAMPs and lectins. As a result, the role of these newly identified components in the interaction with the host remains to be unraveled.« less

Identification of Antigenic Glycans from Schistosoma mansoni by Using a Shotgun Egg Glycan Microarray.

PubMed

Mickum, Megan L; Prasanphanich, Nina Salinger; Song, Xuezheng; Dorabawila, Nelum; Mandalasi, Msano; Lasanajak, Yi; Luyai, Anthony; Secor, W Evan; Wilkins, Patricia P; Van Die, Irma; Smith, David F; Nyame, A Kwame; Cummings, Richard D; Rivera-Marrero, Carlos A

2016-05-01

Infection of mammals by the parasitic helminth Schistosoma mansoni induces antibodies to glycan antigens in worms and eggs, but the differential nature of the immune response among infected mammals is poorly understood. To better define these responses, we used a shotgun glycomics approach in which N-glycans from schistosome egg glycoproteins were prepared, derivatized, separated, and used to generate an egg shotgun glycan microarray. This array was interrogated with sera from infected mice, rhesus monkeys, and humans and with glycan-binding proteins and antibodies to gather information about the structures of antigenic glycans, which also were analyzed by mass spectrometry. A major glycan antigen targeted by IgG from different infected species is the FLDNF epitope [Fucα3GalNAcβ4(Fucα3)GlcNAc-R], which is also recognized by the IgG monoclonal antibody F2D2. The FLDNF antigen is expressed by all life stages of the parasite in mammalian hosts, and F2D2 can kill schistosomula in vitro in a complement-dependent manner. Different antisera also recognized other glycan determinants, including core β-xylose and highly fucosylated glycans. Thus, the natural shotgun glycan microarray of schistosome eggs is useful in identifying antigenic glycans and in developing new anti-glycan reagents that may have diagnostic applications and contribute to developing new vaccines against schistosomiasis. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Combined analysis of transcriptome and proteome data as a tool for the identification of candidate biomarkers in renal cell carcinoma

PubMed Central

Seliger, Barbara; Dressler, Sven P.; Wang, Ena; Kellner, Roland; Recktenwald, Christian V.; Lottspeich, Friedrich; Marincola, Francesco M.; Baumgärtner, Maja; Atkins, Derek; Lichtenfels, Rudolf

2012-01-01

Results obtained from expression profilings of renal cell carcinoma using different “ome”-based approaches and comprehensive data analysis demonstrated that proteome-based technologies and cDNA microarray analyses complement each other during the discovery phase for disease-related candidate biomarkers. The integration of the respective data revealed the uniqueness and complementarities of the different technologies. While comparative cDNA microarray analyses though restricted to upregulated targets largely revealed genes involved in controlling gene/protein expression (19%) and signal transduction processes (13%), proteomics/PROTEOMEX-defined candidate biomarkers include enzymes of the cellular metabolism (36%), transport proteins (12%) and cell motility/structural molecules (10%). Candidate biomarkers defined by proteomics and PROTEOMEX are frequently shared, whereas the sharing rate between cDNA microarray and proteome-based profilings is limited. Putative candidate biomarkers provide insights into their cellular (dys)function and their diagnostic/prognostic value but still warrant further validation in larger patient numbers. Based on the fact that merely 3 candidate biomarkers were shared by all applied technologies, namely annexin A4, tubulin alpha-1A chain and ubiquitin carboxyl-terminal hydrolase L1 the analysis at a single hierarchical level of biological regulation seems to provide only limited results thus emphasizing the importance and benefit of performing rather combinatorial screenings which can complement the standard clinical predictors. PMID:19235166

Identification of Antigenic Glycans from Schistosoma mansoni by Using a Shotgun Egg Glycan Microarray

PubMed Central

Mickum, Megan L.; Prasanphanich, Nina Salinger; Song, Xuezheng; Dorabawila, Nelum; Mandalasi, Msano; Lasanajak, Yi; Luyai, Anthony; Secor, W. Evan; Wilkins, Patricia P.; Van Die, Irma; Smith, David F.; Nyame, A. Kwame

2016-01-01

Infection of mammals by the parasitic helminth Schistosoma mansoni induces antibodies to glycan antigens in worms and eggs, but the differential nature of the immune response among infected mammals is poorly understood. To better define these responses, we used a shotgun glycomics approach in which N-glycans from schistosome egg glycoproteins were prepared, derivatized, separated, and used to generate an egg shotgun glycan microarray. This array was interrogated with sera from infected mice, rhesus monkeys, and humans and with glycan-binding proteins and antibodies to gather information about the structures of antigenic glycans, which also were analyzed by mass spectrometry. A major glycan antigen targeted by IgG from different infected species is the FLDNF epitope [Fucα3GalNAcβ4(Fucα3)GlcNAc-R], which is also recognized by the IgG monoclonal antibody F2D2. The FLDNF antigen is expressed by all life stages of the parasite in mammalian hosts, and F2D2 can kill schistosomula in vitro in a complement-dependent manner. Different antisera also recognized other glycan determinants, including core β-xylose and highly fucosylated glycans. Thus, the natural shotgun glycan microarray of schistosome eggs is useful in identifying antigenic glycans and in developing new anti-glycan reagents that may have diagnostic applications and contribute to developing new vaccines against schistosomiasis. PMID:26883596

Antibody Microarray for E. coli O157:H7 and Shiga Toxin in Microtiter Plates.

PubMed

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.

Extracellular vesicles from Paracoccidioides pathogenic species transport polysaccharide and expose ligands for DC-SIGN receptors

DOE Office of Scientific and Technical Information (OSTI.GOV)

da Silva, Roberta Peres; Heiss, Christian; Black, Ian

Extracellular vesicles (EVs) mediate non-conventional transport of molecules across the fungal cell wall. We aimed at describing the carbohydrate composition and surface carbohydrate epitopes of EVs isolated from the pathogenic fungi Paracoccidioides brasiliensis and P. lutzii using standard procedures. Total EV carbohydrates were ethanol-precipitated from preparations depleted of lipids and proteins, then analyzed by chemical degradation, gas chromatography-mass spectrometry, nuclear magnetic resonance and size-exclusion chromatography. EV glycosyl residues of Glc, Man, and Gal comprised most probably two major components: a high molecular mass 4,6-α-glucan and a galactofuranosylmannan, possibly an oligomer, bearing a 2-α-Manp main chain linked to β-Galf (1,3) andmore » α-Manp (1,6) end units. The results also suggested the presence of small amounts of a (1→6)- Manp polymer, (1→3)-glucan and (1→6)-glucan. Glycan microarrays allowed identification of EV surface lectin(s), while plant lectin microarray profiling revealed terminal Man and GlcNAc residues exposed at the EVs surface. Mammalian lectin microarray profiling showed that DC-SIGN receptors recognized surface carbohydrate in Paracoccidioides EVs. Our results suggest that oligosaccharides, cytoplasmic storage, and cell wall polysaccharides can be exported in fungal EVs, which also expose surface PAMPs and lectins. As a result, the role of these newly identified components in the interaction with the host remains to be unraveled.« less

Molecular probes and microarrays for the detection of toxic algae in the genera Dinophysis and Phalacroma (Dinophyta).

PubMed

Edvardsen, Bente; Dittami, Simon M; Groben, René; Brubak, Sissel; Escalera, Laura; Rodríguez, Francisco; Reguera, Beatriz; Chen, Jixin; Medlin, Linda K

2013-10-01

Dinophysis and Phalacroma species containing diarrheic shellfish toxins and pectenotoxins occur in coastal temperate waters all year round and prevent the harvesting of mussels during several months each year in regions in Europe, Chile, Japan, and New Zealand. Toxicity varies among morphologically similar species, and a precise identification is needed for early warning systems. Molecular techniques using ribosomal DNA sequences offer a means to identify and detect precisely the potentially toxic species. We designed molecular probes targeting the 18S rDNA at the family and genus levels for Dinophysis and Phalacroma and at the species level for Dinophysis acuminata, Dinophysis acuta, and Dinophysis norvegica, the most commonly occurring, potentially toxic species of these genera in Western European waters. Dot blot hybridizations with polymerase chain reaction (PCR)-amplified rDNA from 17 microalgae were used to demonstrate probe specificity. The probes were modified along with other published fluorescence in situ hybridization and PCR probes and tested for a microarray platform within the MIDTAL project ( http://www.midtal.com ). The microarray was applied to field samples from Norway and Spain and compared to microscopic cell counts. These probes may be useful for early warning systems and monitoring and can also be used in population dynamic studies to distinguish species and life cycle stages, such as cysts, and their distribution in time and space.

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

Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

PubMed Central

2012-01-01

Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process. PMID:23256600

KIRMES: kernel-based identification of regulatory modules in euchromatic sequences.

PubMed

Schultheiss, Sebastian J; Busch, Wolfgang; Lohmann, Jan U; Kohlbacher, Oliver; Rätsch, Gunnar

2009-08-15

Understanding transcriptional regulation is one of the main challenges in computational biology. An important problem is the identification of transcription factor (TF) binding sites in promoter regions of potential TF target genes. It is typically approached by position weight matrix-based motif identification algorithms using Gibbs sampling, or heuristics to extend seed oligos. Such algorithms succeed in identifying single, relatively well-conserved binding sites, but tend to fail when it comes to the identification of combinations of several degenerate binding sites, as those often found in cis-regulatory modules. We propose a new algorithm that combines the benefits of existing motif finding with the ones of support vector machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana, we were able to show that the newly developed strategy significantly improves the recognition of TF targets. The python source code (open source-licensed under GPL), the data for the experiments and a Galaxy-based web service are available at http://www.fml.mpg.de/raetsch/suppl/kirmes/.

Current genetic methodologies in the identification of disaster victims and in forensic analysis.

PubMed

Ziętkiewicz, Ewa; Witt, Magdalena; Daca, Patrycja; Zebracka-Gala, Jadwiga; Goniewicz, Mariusz; Jarząb, Barbara; Witt, Michał

2012-02-01

This review presents the basic problems and currently available molecular techniques used for genetic profiling in disaster victim identification (DVI). The environmental conditions of a mass disaster often result in severe fragmentation, decomposition and intermixing of the remains of victims. In such cases, traditional identification based on the anthropological and physical characteristics of the victims is frequently inconclusive. This is the reason why DNA profiling became the gold standard for victim identification in mass-casualty incidents (MCIs) or any forensic cases where human remains are highly fragmented and/or degraded beyond recognition. The review provides general information about the sources of genetic material for DNA profiling, the genetic markers routinely used during genetic profiling (STR markers, mtDNA and single-nucleotide polymorphisms [SNP]) and the basic statistical approaches used in DNA-based disaster victim identification. Automated technological platforms that allow the simultaneous analysis of a multitude of genetic markers used in genetic identification (oligonucleotide microarray techniques and next-generation sequencing) are also presented. Forensic and population databases containing information on human variability, routinely used for statistical analyses, are discussed. The final part of this review is focused on recent developments, which offer particularly promising tools for forensic applications (mRNA analysis, transcriptome variation in individuals/populations and genetic profiling of specific cells separated from mixtures).

Gene expression profile of blood cells for the prediction of delayed cerebral ischemia after intracranial aneurysm rupture: a pilot study in humans.

PubMed

Baumann, Antoine; Devaux, Yvan; Audibert, Gérard; Zhang, Lu; Bracard, Serge; Colnat-Coulbois, Sophie; Klein, Olivier; Zannad, Faiez; Charpentier, Claire; Longrois, Dan; Mertes, Paul-Michel

2013-01-01

Delayed cerebral ischemia (DCI) is a potentially devastating complication after intracranial aneurysm rupture and its mechanisms remain poorly elucidated. Early identification of the patients prone to developing DCI after rupture may represent a major breakthrough in its prevention and treatment. The single gene approach of DCI has demonstrated interest in humans. We hypothesized that whole genome expression profile of blood cells may be useful for better comprehension and prediction of aneurysmal DCI. Over a 35-month period, 218 patients with aneurysm rupture were included in this study. DCI was defined as the occurrence of a new delayed neurological deficit occurring within 2 weeks after aneurysm rupture with evidence of ischemia either on perfusion-diffusion MRI, CT angiography or CT perfusion imaging, or with cerebral angiography. DCI patients were matched against controls based on 4 out of 5 criteria (age, sex, Fisher grade, aneurysm location and smoking status). Genome-wide expression analysis of blood cells obtained at admission was performed by microarrays. Transcriptomic analysis was performed using long oligonucleotide microarrays representing 25,000 genes. Quantitative PCR: 1 µg of total RNA extracted was reverse-transcribed, and the resulting cDNA was diluted 10-fold before performing quantitative PCR. Microarray data were first analyzed by 'Significance Analysis of Microarrays' software which includes the Benjamini correction for multiple testing. In a second step, microarray data fold change was compared using a two-tailed, paired t test. Analysis of receiver-operating characteristic (ROC) curves and the area under the ROC curves were used for prediction analysis. Logistic regression models were used to investigate the additive value of multiple biomarkers. A total of 16 patients demonstrated DCI. Significance Analysis of Microarrays software failed to retrieve significant genes, most probably because of the heterogeneity of the patients included in the microarray experiments and the small size of the DCI population sample. Standard two-tailed paired t test and C-statistic revealed significant associations between gene expression and the occurrence of DCI: in particular, the expression of neuroregulin 1 was 1.6-fold upregulated in patients with DCI (p = 0.01) and predicted DCI with an area under the ROC curve of 0.96. Logistic regression analyses revealed a significant association between neuroregulin 1 and DCI (odds ratio 1.46, 95% confidence interval 1.02-2.09, p = 0.02). This pilot study suggests that blood cells may be a reservoir of prognostic biomarkers of DCI in patients with intracranial aneurysm rupture. Despite an evident lack of power, this study elicited neuroregulin 1, a vasoreactivity-, inflammation- and angiogenesis-related gene, as a possible candidate predictor of DCI. Larger cohort studies are needed but genome-wide microarray-based studies are promising research tools for the understanding of DCI after intracranial aneurysm rupture. © 2013 S. Karger AG, Basel.

Serum reactome induced by Bordetella pertussis infection and Pertussis vaccines: qualitative differences in serum antibody recognition patterns revealed by peptide microarray analysis.

PubMed

Valentini, Davide; Ferrara, Giovanni; Advani, Reza; Hallander, Hans O; Maeurer, Markus J

2015-07-01

Pertussis (whooping cough) remains a public health problem despite extensive vaccination strategies. Better understanding of the host-pathogen interaction and the detailed B. pertussis (Bp) target recognition pattern will help in guided vaccine design. We characterized the specific epitope antigen recognition profiles of serum antibodies ('the reactome') induced by whooping cough and B. pertussis (Bp) vaccines from a case-control study conducted in 1996 in infants enrolled in a Bp vaccine trial in Sweden (Gustafsson, NEJM, 1996, 334, 349-355). Sera from children with whooping cough, vaccinated with Diphtheria Tetanus Pertussis (DTP) whole-cell (wc), acellular 5 (DPTa5), or with the 2 component (a2) vaccines and from infants receiving only DT (n=10 for each group) were tested with high-content peptide microarrays containing 17 Bp proteins displayed as linear (n=3175) peptide stretches. Slides were incubated with serum and peptide-IgG complexes detected with Cy5-labeled goat anti-human IgG and analyzed using a GenePix 4000B microarray scanner, followed by statistical analysis, using PAM (Prediction Analysis for Microarrays) and the identification of uniquely recognized peptide epitopes. 367/3,085 (11.9%) peptides were recognized in 10/10 sera from children with whooping cough, 239 (7.7%) in DTPwc, 259 (8.4%) in DTPa5, 105 (3.4%) DTPa2, 179 (5.8%) in the DT groups. Recognition of strongly recognized peptides was similar between whooping cough and DPTwc, but statistically different between whooping cough vs. DTPa5 (p<0.05), DTPa2 and DT (p<0.001 vs. both) vaccines. 6/3,085 and 2/3,085 peptides were exclusively recognized in (10/10) sera from children with whooping cough and DTPa2 vaccination, respectively. DTPwc resembles more closely the whooping cough reactome as compared to acellular vaccines. We could identify a unique recognition signature common for each vaccination group (10/10 children). Peptide microarray technology allows detection of subtle differences in epitope signature responses and may help to guide rational vaccine development by the objective description of a clinically relevant immune response that confers protection against infectious pathogens.

TIPMaP: a web server to establish transcript isoform profiles from reliable microarray probes.

PubMed

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.

Identification of microRNAs with regulatory potential using a matched microRNA-mRNA time-course data.

PubMed

Jayaswal, Vivek; Lutherborrow, Mark; Ma, David D F; Hwa Yang, Yee

2009-05-01

Over the past decade, a class of small RNA molecules called microRNAs (miRNAs) has been shown to regulate gene expression at the post-transcription stage. While early work focused on the identification of miRNAs using a combination of experimental and computational techniques, subsequent studies have focused on identification of miRNA-target mRNA pairs as each miRNA can have hundreds of mRNA targets. The experimental validation of some miRNAs as oncogenic has provided further motivation for research in this area. In this article we propose an odds-ratio (OR) statistic for identification of regulatory miRNAs. It is based on integrative analysis of matched miRNA and mRNA time-course microarray data. The OR-statistic was used for (i) identification of miRNAs with regulatory potential, (ii) identification of miRNA-target mRNA pairs and (iii) identification of time lags between changes in miRNA expression and those of its target mRNAs. We applied the OR-statistic to a cancer data set and identified a small set of miRNAs that were negatively correlated to mRNAs. A literature survey revealed that some of the miRNAs that were predicted to be regulatory, were indeed oncogenic or tumor suppressors. Finally, some of the predicted miRNA targets have been shown to be experimentally valid.

An Integrated Lab-on-Chip for Rapid Identification and Simultaneous Differentiation of Tropical Pathogens

PubMed Central

Sato, Mitsuharu; Watthanaworawit, Wanitda; Ling, Clare L.; Mauduit, Marjorie; Malleret, Benoît; Grüner, Anne-Charlotte; Tan, Rosemary; Nosten, François H.; Snounou, Georges; Rénia, Laurent; Ng, Lisa F. P.

2014-01-01

Tropical pathogens often cause febrile illnesses in humans and are responsible for considerable morbidity and mortality. The similarities in clinical symptoms provoked by these pathogens make diagnosis difficult. Thus, early, rapid and accurate diagnosis will be crucial in patient management and in the control of these diseases. In this study, a microfluidic lab-on-chip integrating multiplex molecular amplification and DNA microarray hybridization was developed for simultaneous detection and species differentiation of 26 globally important tropical pathogens. The analytical performance of the lab-on-chip for each pathogen ranged from 102 to 103 DNA or RNA copies. Assay performance was further verified with human whole blood spiked with Plasmodium falciparum and Chikungunya virus that yielded a range of detection from 200 to 4×105 parasites, and from 250 to 4×107 PFU respectively. This lab-on-chip was subsequently assessed and evaluated using 170 retrospective patient specimens in Singapore and Thailand. The lab-on-chip had a detection sensitivity of 83.1% and a specificity of 100% for P. falciparum; a sensitivity of 91.3% and a specificity of 99.3% for P. vivax; a positive 90.0% agreement and a specificity of 100% for Chikungunya virus; and a positive 85.0% agreement and a specificity of 100% for Dengue virus serotype 3 with reference methods conducted on the samples. Results suggested the practicality of an amplification microarray-based approach in a field setting for high-throughput detection and identification of tropical pathogens. PMID:25078474

Identification of Gene Networks Associated with Acute Myeloid Leukemia by Comparative Molecular Methylation and Expression Profiling

PubMed Central

Dellett, Margaret; O’Hagan, Kathleen Ann; Colyer, Hilary Ann Alexandra; Mills, Ken I.

2010-01-01

Around 80% of acute myeloid leukemia (AML) patients achieve a complete remission, however many will relapse and ultimately die of their disease. The association between karyotype and prognosis has been studied extensively and identified patient cohorts as having favourable [e.g. t(8; 21), inv (16)/t(16; 16), t(15; 17)], intermediate [e.g. cytogenetically normal (NK-AML)] or adverse risk [e.g. complex karyotypes]. Previous studies have shown that gene expression profiling signatures can classify the sub-types of AML, although few reports have shown a similar feature by using methylation markers. The global methylation patterns in 19 diagnostic AML samples were investigated using the Methylated CpG Island Amplification Microarray (MCAM) method and CpG island microarrays containing 12,000 CpG sites. The first analysis, comparing favourable and intermediate cytogenetic risk groups, revealed significantly differentially methylated CpG sites (594 CpG islands) between the two subgroups. Mutations in the NPM1 gene occur at a high frequency (40%) within the NK-AML subgroup and are associated with a more favourable prognosis in these patients. A second analysis comparing the NPM1 mutant and wild-type research study subjects again identified distinct methylation profiles between these two subgroups. Network and pathway analysis revealed possible molecular mechanisms associated with the different risk and/or mutation sub-groups. This may result in a better classification of the risk groups, improved monitoring targets, or the identification of novel molecular therapies. PMID:24179384

Recombinant blood group proteins for use in antibody screening and identification tests.

PubMed

Seltsam, Axel; Blasczyk, Rainer

2009-11-01

The present review elucidates the potentials of recombinant blood group proteins (BGPs) for red blood cell (RBC) antibody detection and identification in pretransfusion testing and the achievements in this field so far. Many BGPs have been eukaryotically and prokaryotically expressed in sufficient quantity and quality for RBC antibody testing. Recombinant BGPs can be incorporated in soluble protein reagents or solid-phase assays such as ELISA, color-coded microsphere and protein microarray chip-based techniques. Because novel recombinant protein-based assays use single antigens, a positive reaction of a serum with the recombinant protein directly indicates the presence and specificity of the target antibody. Inversely, conventional RBC-based assays use panels of human RBCs carrying a huge number of blood group antigens at the same time and require negative reactions of samples with antigen-negative cells for indirect determination of antibody specificity. Because of their capacity for single-step, direct RBC antibody determination, recombinant protein-based assays may greatly facilitate and accelerate the identification of common and rare RBC antibodies.

Review of methods used for identification of biothreat agents in environmental protection and human health aspects.

PubMed

Mirski, Tomasz; Bartoszcze, Michał; Bielawska-Drózd, Agata; Cieślik, Piotr; Michalski, Aleksander J; Niemcewicz, Marcin; Kocik, Janusz; Chomiczewski, Krzysztof

2014-01-01

Modern threats of bioterrorism force the need to develop methods for rapid and accurate identification of dangerous biological agents. Currently, there are many types of methods used in this field of studies that are based on immunological or genetic techniques, or constitute a combination of both methods (immuno-genetic). There are also methods that have been developed on the basis of physical and chemical properties of the analytes. Each group of these analytical assays can be further divided into conventional methods (e.g. simple antigen-antibody reactions, classical PCR, real-time PCR), and modern technologies (e.g. microarray technology, aptamers, phosphors, etc.). Nanodiagnostics constitute another group of methods that utilize the objects at a nanoscale (below 100 nm). There are also integrated and automated diagnostic systems, which combine different methods and allow simultaneous sampling, extraction of genetic material and detection and identification of the analyte using genetic, as well as immunological techniques.

Identification of New Serum Biomarkers for Early Breast Cancer Diagnosis and Prognosis Using Lipid Microarrays

DTIC Science & Technology

2008-09-01

specific for asialo-GM1 bound specifically to GM1, but not to the closely related gangliosides GM1 or GM2 (Fig. 2). Monoclonal antibodies raised...against GD3 specifically bound GD3, but not to asialo-GM1, GM1 and GM2 (Fig. 2). The secondary antibodies did not show reactivity against lipids (data not...fluorescent intensity on different membranes. Asialo GM1 GM1 GM2 GD3 Fig 2. Lipids on the PVDF membrane can be detected by specific

Identification of New Serum Biomarkers for Early Breast Cancer Diagnosis and Prognosis Using Lipid Microarrays

DTIC Science & Technology

2007-09-01

specific for asialo-GM1 bound specifically to GM1, but not to the closely related gangliosides GM1 or GM2 (Fig. 2). Monoclonal antibodies raised against...GD3 specifically bound GD3, but not to asialo-GM1, GM1 and GM2 (Fig. 2). The secondary antibodies did not show reactivity against lipids (data not...fluorescent intensity on different membranes. Asialo GM1 GM1 GM2 GD3 Fig 2. Lipids on the PVDF membrane can be detected by specific antibodies

Unraveling transcriptional control and cis-regulatory codes using the software suite GeneACT

PubMed Central

Cheung, Tom Hiu; Kwan, Yin Lam; Hamady, Micah; Liu, Xuedong

2006-01-01

Deciphering gene regulatory networks requires the systematic identification of functional cis-acting regulatory elements. We present a suite of web-based bioinformatics tools, called GeneACT , that can rapidly detect evolutionarily conserved transcription factor binding sites or microRNA target sites that are either unique or over-represented in differentially expressed genes from DNA microarray data. GeneACT provides graphic visualization and extraction of common regulatory sequence elements in the promoters and 3'-untranslated regions that are conserved across multiple mammalian species. PMID:17064417

FindGDPs: fast identification of primers for labeling microbial transcriptomes for DNA microarray analysis

PubMed Central

Blick, Robert J.; Revel, Andrew T.; Hansen, Eric J.

2008-01-01

Summary FindGDPs is a program that uses a greedy algorithm to quickly identify a set of genome-directed primers that specifically anneal to all of the open reading frames in a genome and that do not exhibit full-length complementarity to the members of another user-supplied set of nucleotide sequences. Availability The program code is distributed under the GNU General Public License at http://www8.utsouthwestern.edu/utsw/cda/dept131456/files/159331.html Contact eric.hansen@utsouthwestern.edu PMID:15593406

Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays

PubMed Central

Popescu, Sorina C.; Popescu, George V.; Bachan, Shawn; Zhang, Zimei; Seay, Montrell; Gerstein, Mark; Snyder, Michael; Dinesh-Kumar, S. P.

2007-01-01

Calmodulins (CaMs) are the most ubiquitous calcium sensors in eukaryotes. A number of CaM-binding proteins have been identified through classical methods, and many proteins have been predicted to bind CaMs based on their structural homology with known targets. However, multicellular organisms typically contain many CaM-like (CML) proteins, and a global identification of their targets and specificity of interaction is lacking. In an effort to develop a platform for large-scale analysis of proteins in plants we have developed a protein microarray and used it to study the global analysis of CaM/CML interactions. An Arabidopsis thaliana expression collection containing 1,133 ORFs was generated and used to produce proteins with an optimized medium-throughput plant-based expression system. Protein microarrays were prepared and screened with several CaMs/CMLs. A large number of previously known and novel CaM/CML targets were identified, including transcription factors, receptor and intracellular protein kinases, F-box proteins, RNA-binding proteins, and proteins of unknown function. Multiple CaM/CML proteins bound many binding partners, but the majority of targets were specific to one or a few CaMs/CMLs indicating that different CaM family members function through different targets. Based on our analyses, the emergent CaM/CML interactome is more extensive than previously predicted. Our results suggest that calcium functions through distinct CaM/CML proteins to regulate a wide range of targets and cellular activities. PMID:17360592

Early markers of reperfusion injury after liver transplantation: association with primary dysfunction.

PubMed

Bruns, Helge; Heil, Jan; Schultze, Daniel; Al Saeedi, Mohammed; Schemmer, Peter

2015-06-01

In patients with end-stage liver disease, liver transplantation is the only available curative treatment. Although the outcome and quality of life in the patients have improved over the past decades, primary dys- or nonfunction (PDF/PNF) can occur. Early detection of PDF and PNF is crucial and could lead to individual therapies. This study was designed to identify early markers of reperfusion injury and PDF in liver biopsies taken during the first hour after reperfusion. Biopsies from donor livers were prospectively taken as a routine during the first hour after reperfusion. Recipient data, transaminases and outcome were routinely monitored. In total, 10 biopsy specimens taken from patients with 90-day mortality and PDF, and patients with long-term survival but without PDF were used for DNA microarrays. Markers that were significantly up- or down-regulated in the microarray were verified using quantitative real-time PCR. Age, indications and labMELD score were similar in both groups. Peak-transaminases during the first week after transplantation were significantly different in the two groups. In total, 20 differentially regulated markers that correlated to PDF were identified using microarray analysis and verified with quantitative real-time PCR. The markers identified in this study could predict PDF at a very early time point and might point to interventions that ameliorate reperfusion injury and thus prevent PDF. Identification of patients and organs at risk might lead to individualized therapies and could ultimately improve outcome.

Resequencing microarray probe design for typing genetically diverse viruses: human rhinoviruses and enteroviruses

PubMed Central

Wang, Zheng; Malanoski, Anthony P; Lin, Baochuan; Kidd, Carolyn; Long, Nina C; Blaney, Kate M; Thach, Dzung C; Tibbetts, Clark; Stenger, David A

2008-01-01

Background Febrile respiratory illness (FRI) has a high impact on public health and global economics and poses a difficult challenge for differential diagnosis. A particular issue is the detection of genetically diverse pathogens, i.e. human rhinoviruses (HRV) and enteroviruses (HEV) which are frequent causes of FRI. Resequencing Pathogen Microarray technology has demonstrated potential for differential diagnosis of several respiratory pathogens simultaneously, but a high confidence design method to select probes for genetically diverse viruses is lacking. Results Using HRV and HEV as test cases, we assess a general design strategy for detecting and serotyping genetically diverse viruses. A minimal number of probe sequences (26 for HRV and 13 for HEV), which were potentially capable of detecting all serotypes of HRV and HEV, were determined and implemented on the Resequencing Pathogen Microarray RPM-Flu v.30/31 (Tessarae RPM-Flu). The specificities of designed probes were validated using 34 HRV and 28 HEV strains. All strains were successfully detected and identified at least to species level. 33 HRV strains and 16 HEV strains could be further differentiated to serotype level. Conclusion This study provides a fundamental evaluation of simultaneous detection and differential identification of genetically diverse RNA viruses with a minimal number of prototype sequences. The results demonstrated that the newly designed RPM-Flu v.30/31 can provide comprehensive and specific analysis of HRV and HEV samples which implicates that this design strategy will be applicable for other genetically diverse viruses. PMID:19046445

From High-Throughput Microarray-Based Screening to Clinical Application: The Development of a Second Generation Multigene Test for Breast Cancer Prognosis

PubMed Central

Brase, Jan C.; Kronenwett, Ralf; Petry, Christoph; Denkert, Carsten; Schmidt, Marcus

2013-01-01

Several multigene tests have been developed for breast cancer patients to predict the individual risk of recurrence. Most of the first generation tests rely on proliferation-associated genes and are commonly carried out in central reference laboratories. Here, we describe the development of a second generation multigene assay, the EndoPredict test, a prognostic multigene expression test for estrogen receptor (ER) positive, human epidermal growth factor receptor (HER2) negative (ER+/HER2−) breast cancer patients. The EndoPredict gene signature was initially established in a large high-throughput microarray-based screening study. The key steps for biomarker identification are discussed in detail, in comparison to the establishment of other multigene signatures. After biomarker selection, genes and algorithms were transferred to a diagnostic platform (reverse transcription quantitative PCR (RT-qPCR)) to allow for assaying formalin-fixed, paraffin-embedded (FFPE) samples. A comprehensive analytical validation was performed and a prospective proficiency testing study with seven pathological laboratories finally proved that EndoPredict can be reliably used in the decentralized setting. Three independent large clinical validation studies (n = 2,257) demonstrated that EndoPredict offers independent prognostic information beyond current clinicopathological parameters and clinical guidelines. The review article summarizes several important steps that should be considered for the development process of a second generation multigene test and offers a means for transferring a microarray signature from the research laboratory to clinical practice. PMID:27605191

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

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.

nuID: a universal naming scheme of oligonucleotides for Illumina, Affymetrix, and other microarrays

PubMed Central

Du, Pan; Kibbe, Warren A; Lin, Simon M

2007-01-01

Background Oligonucleotide probes that are sequence identical may have different identifiers between manufacturers and even between different versions of the same company's microarray; and sometimes the same identifier is reused and represents a completely different oligonucleotide, resulting in ambiguity and potentially mis-identification of the genes hybridizing to that probe. Results We have devised a unique, non-degenerate encoding scheme that can be used as a universal representation to identify an oligonucleotide across manufacturers. We have named the encoded representation 'nuID', for nucleotide universal identifier. Inspired by the fact that the raw sequence of the oligonucleotide is the true definition of identity for a probe, the encoding algorithm uniquely and non-degenerately transforms the sequence itself into a compact identifier (a lossless compression). In addition, we added a redundancy check (checksum) to validate the integrity of the identifier. These two steps, encoding plus checksum, result in an nuID, which is a unique, non-degenerate, permanent, robust and efficient representation of the probe sequence. For commercial applications that require the sequence identity to be confidential, we have an encryption schema for nuID. We demonstrate the utility of nuIDs for the annotation of Illumina microarrays, and we believe it has universal applicability as a source-independent naming convention for oligomers. Reviewers This article was reviewed by Itai Yanai, Rong Chen (nominated by Mark Gerstein), and Gregory Schuler (nominated by David Lipman). PMID:17540033

Next-generation sequencing for endocrine cancers: Recent advances and challenges.

PubMed

Suresh, Padmanaban S; Venkatesh, Thejaswini; Tsutsumi, Rie; Shetty, Abhishek

2017-05-01

Contemporary molecular biology research tools have enriched numerous areas of biomedical research that address challenging diseases, including endocrine cancers (pituitary, thyroid, parathyroid, adrenal, testicular, ovarian, and neuroendocrine cancers). These tools have placed several intriguing clues before the scientific community. Endocrine cancers pose a major challenge in health care and research despite considerable attempts by researchers to understand their etiology. Microarray analyses have provided gene signatures from many cells, tissues, and organs that can differentiate healthy states from diseased ones, and even show patterns that correlate with stages of a disease. Microarray data can also elucidate the responses of endocrine tumors to therapeutic treatments. The rapid progress in next-generation sequencing methods has overcome many of the initial challenges of these technologies, and their advantages over microarray techniques have enabled them to emerge as valuable aids for clinical research applications (prognosis, identification of drug targets, etc.). A comprehensive review describing the recent advances in next-generation sequencing methods and their application in the evaluation of endocrine and endocrine-related cancers is lacking. The main purpose of this review is to illustrate the concepts that collectively constitute our current view of the possibilities offered by next-generation sequencing technological platforms, challenges to relevant applications, and perspectives on the future of clinical genetic testing of patients with endocrine tumors. We focus on recent discoveries in the use of next-generation sequencing methods for clinical diagnosis of endocrine tumors in patients and conclude with a discussion on persisting challenges and future objectives.

Identification of Differentially Expressed IGFBP5-Related Genes in Breast Cancer Tumor Tissues Using cDNA Microarray Experiments.

PubMed

Akkiprik, Mustafa; Peker, İrem; Özmen, Tolga; Amuran, Gökçe Güllü; Güllüoğlu, Bahadır M; Kaya, Handan; Özer, Ayşe

2015-11-10

IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray analysis revealed that a total of 186 genes were differentially expressed in breast cancer compared with normal breast tissues. Of the 186 genes, 169 genes were downregulated and 17 genes were upregulated in the tumor samples. KEGG pathway analyses showed that protein digestion and absorption, focal adhesion, salivary secretion, drug metabolism-cytochrome P450, and phenylalanine metabolism pathways are involved. Among these DEGs, the prominent top two genes (MMP11 and COL1A1) which potentially correlated with IGFBP5 were selected for validation using real time RT-qPCR. Only COL1A1 expression showed a consistent upregulation with IGFBP5 expression and COL1A1 and MMP11 were significantly positively correlated. We concluded that the discovery of coordinately expressed genes related with IGFBP5 might contribute to understanding of the molecular mechanism of the function of IGFBP5 in breast cancer. Further functional studies on DEGs and association with IGFBP5 may identify novel biomarkers for clinical applications in breast cancer.

Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases

PubMed Central

Puffenberger, Erik G.; Jinks, Robert N.; Sougnez, Carrie; Cibulskis, Kristian; Willert, Rebecca A.; Achilly, Nathan P.; Cassidy, Ryan P.; Fiorentini, Christopher J.; Heiken, Kory F.; Lawrence, Johnny J.; Mahoney, Molly H.; Miller, Christopher J.; Nair, Devika T.; Politi, Kristin A.; Worcester, Kimberly N.; Setton, Roni A.; DiPiazza, Rosa; Sherman, Eric A.; Eastman, James T.; Francklyn, Christopher; Robey-Bond, Susan; Rider, Nicholas L.; Gabriel, Stacey; Morton, D. Holmes; Strauss, Kevin A.

2012-01-01

The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean = 4.4 Mb) that contain many genes (mean = 79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data. PMID:22279524

Identification of genomic aberrations in hemangioblastoma by droplet digital PCR and SNP microarray highlights novel candidate genes and pathways for pathogenesis.

PubMed

Mehrian-Shai, Ruty; Yalon, Michal; Moshe, Itai; Barshack, Iris; Nass, Dvorah; Jacob, Jasmine; Dor, Chen; Reichardt, Juergen K V; Constantini, Shlomi; Toren, Amos

2016-01-14

The genetic mechanisms underlying hemangioblastoma development are still largely unknown. We used high-resolution single nucleotide polymorphism microarrays and droplet digital PCR analysis to detect copy number variations (CNVs) in total of 45 hemangioblastoma tumors. We identified 94 CNVs with a median of 18 CNVs per sample. The most frequently gained regions were on chromosomes 1 (p36.32) and 7 (p11.2). These regions contain the EGFR and PRDM16 genes. Recurrent losses were located at chromosome 12 (q24.13), which includes the gene PTPN11. Our findings provide the first high-resolution genome-wide view of chromosomal changes in hemangioblastoma and identify 23 candidate genes: EGFR, PRDM16, PTPN11, HOXD11, HOXD13, FLT3, PTCH, FGFR1, FOXP1, GPC3, HOXC13, HOXC11, MKL1, CHEK2, IRF4, GPHN, IKZF1, RB1, HOXA9, and micro RNA, such as hsa-mir-196a-2 for hemangioblastoma pathogenesis. Furthermore, our data implicate that cell proliferation and angiogenesis promoting pathways may be involved in the molecular pathogenesis of hemangioblastoma.

Transcriptomic profiling as a screening tool to detect trenbolone treatment in beef cattle.

PubMed

Pegolo, S; Cannizzo, F T; Biolatti, B; Castagnaro, M; Bargelloni, L

2014-06-01

The effects of steroid hormone implants containing trenbolone alone (Finaplix-H), combined with 17β-oestradiol (17β-E; Revalor-H), or with 17β-E and dexamethasone (Revalor-H plus dexamethasone per os) on the bovine muscle transcriptome were examined by DNA-microarray. Overall, large sets of genes were shown to be modulated by the different growth promoters (GPs) and the regulated pathways and biological processes were mostly shared among the treatment groups. Using the Prediction Analysis of Microarray program, GP-treated animals were accurately identified by a small number of predictive genes. A meta-analysis approach was also carried out for the Revalor group to potentially increase the robustness of class prediction analysis. After data pre-processing, a high level of accuracy (90%) was obtained in the classification of samples, using 105 predictive gene markers. Transcriptomics could thus help in the identification of indirect biomarkers for anabolic treatment in beef cattle to be applied for the screening of muscle samples collected after slaughtering. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modular synthesis of N-glycans and arrays for the hetero-ligand binding analysis of HIV antibodies

NASA Astrophysics Data System (ADS)

Shivatare, Sachin S.; Chang, Shih-Huang; Tsai, Tsung-I.; Tseng, Susan Yu; Shivatare, Vidya S.; Lin, Yih-Shyan; Cheng, Yang-Yu; Ren, Chien-Tai; Lee, Chang-Chun David; Pawar, Sujeet; Tsai, Charng-Sheng; Shih, Hao-Wei; Zeng, Yi-Fang; Liang, Chi-Hui; Kwong, Peter D.; Burton, Dennis R.; Wu, Chung-Yi; Wong, Chi-Huey

2016-04-01

A new class of broadly neutralizing antibodies (bNAbs) from HIV donors has been reported to target the glycans on gp120—a glycoprotein found on the surface of the virus envelope—thus renewing hope of developing carbohydrate-based HIV vaccines. However, the version of gp120 used in previous studies was not from human T cells and so the glycosylation pattern could be somewhat different to that found in the native system. Moreover, some antibodies recognized two different glycans simultaneously and this cannot be detected with the commonly used glycan microarrays on glass slides. Here, we have developed a glycan microarray on an aluminium-oxide-coated glass slide containing a diverse set of glycans, including homo- and mixed N-glycans (high-mannose, hybrid and complex types) that were prepared by modular chemo-enzymatic methods to detect the presence of hetero-glycan binding behaviours. This new approach allows rapid screening and identification of optimal glycans recognized by neutralizing antibodies, and could speed up the development of HIV-1 vaccines targeting cell surface glycans.

Two-color Dye-swap DNA Microarray approach toward confident gene expression profiling in PMCAO mouse model for ischemia-related and PACAP38-influenced genes

PubMed Central

Hori, Motohide; Shibato, Junko; Nakamachi, Tomoya; Rakwal, Randeep; Ogawa, Tetsuo; Shioda, Seiji; Numazawa, Satoshi

2015-01-01

Toward twin goals of identifying molecular factors in brain injured by ischemic stroke, and the effects of neuropeptide pituitary adenylate-cyclase activating polypeptide (PACAP) on the ischemic brain, we have established the permanent middle cerebral artery occlusion (PMCAO) mouse model and utilized the Agilent mouse whole genome 4 × 44 K DNA chip. PACAP38 (1 pmol) injection was given intracerebroventrically in comparison to a control saline (0.9% NaCl) injection, to screen genes responsive to PACAP38. Two sets of tissues were prepared, whole hemispheres (ischemic and non-ischemic) and infract core and penumbra regions at 6 and 24 h. In this study, we have detailed the experimental design and protocol used therein and explained the quality controls for the use of total RNA in the downstream DNA microarray experiment utilizing a two-color dye-swap approach for stringent and confident gene identification published in a series of papers by Hori and coworkers (Hori et al., 2012–2015). PMID:26484166

Polymerization Behavior and Polymer Properties of Eosin-Mediated Surface Modification Reactions.

PubMed

Avens, Heather J; Randle, Thomas James; Bowman, Christopher N

2008-10-17

Surface modification by surface-mediated polymerization necessitates control of the grafted polymer film thicknesses to achieve the desired property changes. Here, a microarray format is used to assess a range of reaction conditions and formulations rapidly in regards to the film thicknesses achieved and the polymerization behavior. Monomer formulations initiated by eosin conjugates with varying concentrations of poly(ethylene glycol) diacrylate (PEGDA), N-methyldiethanolamine (MDEA), and 1-vinyl-2-pyrrolidone (VP) were evaluated. Acrylamide with MDEA or ascorbic acid as a coinitiator was also investigated. The best formulation was found to be 40 wt% acrylamide with MDEA which yielded four to eight fold thicker films (maximum polymer thickness increased from 180 nm to 1420 nm) and generated visible films from 5-fold lower eosin surface densities (2.8 vs. 14 eosins/µm(2)) compared to a corresponding PEGDA formulation. Using a microarray format to assess multiple initiator surface densities enabled facile identification of a monomer formulation that yields the desired polymer properties and polymerization behavior across the requisite range of initiator surface densities.

Polymerization Behavior and Polymer Properties of Eosin-Mediated Surface Modification Reactions

PubMed Central

Avens, Heather J.; Randle, Thomas James; Bowman, Christopher N.

2008-01-01

Surface modification by surface-mediated polymerization necessitates control of the grafted polymer film thicknesses to achieve the desired property changes. Here, a microarray format is used to assess a range of reaction conditions and formulations rapidly in regards to the film thicknesses achieved and the polymerization behavior. Monomer formulations initiated by eosin conjugates with varying concentrations of poly(ethylene glycol) diacrylate (PEGDA), N-methyldiethanolamine (MDEA), and 1-vinyl-2-pyrrolidone (VP) were evaluated. Acrylamide with MDEA or ascorbic acid as a coinitiator was also investigated. The best formulation was found to be 40 wt% acrylamide with MDEA which yielded four to eight fold thicker films (maximum polymer thickness increased from 180 nm to 1420 nm) and generated visible films from 5-fold lower eosin surface densities (2.8 vs. 14 eosins/µm2) compared to a corresponding PEGDA formulation. Using a microarray format to assess multiple initiator surface densities enabled facile identification of a monomer formulation that yields the desired polymer properties and polymerization behavior across the requisite range of initiator surface densities. PMID:19838291

Detection systems for carbapenemase gene identification should include the SME serine carbapenemase.

PubMed

Bush, Karen; Pannell, Megan; Lock, John L; Queenan, Anne Marie; Jorgensen, James H; Lee, Ryan M; Lewis, James S; Jarrett, Deidre

2013-01-01

Carbapenemase detection has become a major problem in hospitals that encounter outbreaks of infections caused by carbapenem-resistant Gram-negative bacteria. Rapid detection systems have been reported using multiplex PCR analyses and DNA microarray assays. Major carbapenemases that are detected by these systems include the KPC and OXA serine carbapenemases, and the IMP, VIM and NDM families of metallo-β-lactamases. However, increasing numbers of the SME serine carbapenemase are being reported from Serratia marcescens, especially from North and South America. These organisms differ from many of the other carbapenemase-producing pathogens in that they are generally susceptible to the expanded-spectrum cephalosporins ceftazidime and cefepime while retaining resistance to almost all other β-lactam antibiotics. Thus, multiplex PCR assays or DNA microarray testing of carbapenem-resistant S. marcescens isolates should include analyses for production of the SME carbapenemase. Confirmation of the presence of this enzyme may provide reassurance that oxyimino-cephalosporins can be considered for treatment of infections caused by these carbapenem-resistant pathogens. Copyright © 2012 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression.

PubMed

Catto, James W F; Abbod, Maysam F; Wild, Peter J; Linkens, Derek A; Pilarsky, Christian; Rehman, Ishtiaq; Rosario, Derek J; Denzinger, Stefan; Burger, Maximilian; Stoehr, Robert; Knuechel, Ruth; Hartmann, Arndt; Hamdy, Freddie C

2010-03-01

New methods for identifying bladder cancer (BCa) progression are required. Gene expression microarrays can reveal insights into disease biology and identify novel biomarkers. However, these experiments produce large datasets that are difficult to interpret. To develop a novel method of microarray analysis combining two forms of artificial intelligence (AI): neurofuzzy modelling (NFM) and artificial neural networks (ANN) and validate it in a BCa cohort. We used AI and statistical analyses to identify progression-related genes in a microarray dataset (n=66 tumours, n=2800 genes). The AI-selected genes were then investigated in a second cohort (n=262 tumours) using immunohistochemistry. We compared the accuracy of AI and statistical approaches to identify tumour progression. AI identified 11 progression-associated genes (odds ratio [OR]: 0.70; 95% confidence interval [CI], 0.56-0.87; p=0.0004), and these were more discriminate than genes chosen using statistical analyses (OR: 1.24; 95% CI, 0.96-1.60; p=0.09). The expression of six AI-selected genes (LIG3, FAS, KRT18, ICAM1, DSG2, and BRCA2) was determined using commercial antibodies and successfully identified tumour progression (concordance index: 0.66; log-rank test: p=0.01). AI-selected genes were more discriminate than pathologic criteria at determining progression (Cox multivariate analysis: p=0.01). Limitations include the use of statistical correlation to identify 200 genes for AI analysis and that we did not compare regression identified genes with immunohistochemistry. AI and statistical analyses use different techniques of inference to determine gene-phenotype associations and identify distinct prognostic gene signatures that are equally valid. We have identified a prognostic gene signature whose members reflect a variety of carcinogenic pathways that could identify progression in non-muscle-invasive BCa. 2009 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Differential Adipose Tissue Gene Expression Profiles in Abacavir Treated Patients That May Contribute to the Understanding of Cardiovascular Risk: A Microarray Study

PubMed Central

Shahmanesh, Mohsen; Phillips, Kenneth; Boothby, Meg; Tomlinson, Jeremy W.

2015-01-01

Objective To compare changes in gene expression by microarray from subcutaneous adipose tissue from HIV treatment naïve patients treated with efavirenz based regimens containing abacavir (ABC), tenofovir (TDF) or zidovidine (AZT). Design Subcutaneous fat biopsies were obtained before, at 6- and 18–24-months after treatment, and from HIV negative controls. Groups were age, ethnicity, weight, biochemical profile, and pre-treatment CD4 count matched. Microarray data was generated using the Agilent Whole Human Genome Microarray. Identification of differentially expressed genes and genomic response pathways was performed using limma and gene set enrichment analysis. Results There were significant divergences between ABC and the other two groups 6 months after treatment in genes controlling cell adhesion and environmental information processing, with some convergence at 18–24 months. Compared to controls the ABC group, but not AZT or TDF showed enrichment of genes controlling adherence junction, at 6 months and 18–24 months (adjusted p<0.05) and focal adhesions and tight junction at 6 months (p<0.5). Genes controlling leukocyte transendothelial migration (p<0.05) and ECM-receptor interactions (p = 0.04) were over-expressed in ABC compared to TDF and AZT at 6 months but not at 18–24 months. Enrichment of pathways and individual genes controlling cell adhesion and environmental information processing were specifically dysregulated in the ABC group in comparison with other treatments. There was little difference between AZT and TDF. Conclusion After initiating treatment, there is divergence in the expression of genes controlling cell adhesion and environmental information processing between ABC and both TDF and AZT in subcutaneous adipose tissue. If similar changes are also taking place in other tissues including the coronary vasculature they may contribute to the increased risk of cardiovascular events reported in patients recently started on abacavir-containing regimens. PMID:25617630

Identification of reference genes for quantitative expression analysis using large-scale RNA-seq data of Arabidopsis thaliana and model crop plants.

PubMed

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.

Identification of Biomarkers of Response to IFNg during Endotoxin Tolerance: Application to Septic Shock

PubMed Central

Allantaz-Frager, Florence; Turrel-Davin, Fanny; Venet, Fabienne; Monnin, Cécile; De Saint Jean, Amélie; Barbalat, Véronique; Cerrato, Elisabeth; Pachot, Alexandre; Lepape, Alain; Monneret, Guillaume

2013-01-01

The rapid development in septic patients of features of marked immunosuppression associated with increased risk of nosocomial infections and mortality represents the rational for the initiation of immune targeted treatments in sepsis. However, as there is no clinical sign of immune dysfunctions, the current challenge is to develop biomarkers that will help clinicians identify the patients that would benefit from immunotherapy and monitor its efficacy. Using an in vitro model of endotoxin tolerance (ET), a pivotal feature of sepsis-induced immunosuppression in monocytes, we identified using gene expression profiling by microarray a panel of transcripts associated with the development of ET which expression was restored after immunostimulation with interferon-gamma (IFN-γ). These results were confirmed by qRT-PCR. Importantly, this short-list of markers was further evaluated in patients. Of these transcripts, six (TNFAIP6, FCN1, CXCL10, GBP1, CXCL5 and PID1) were differentially expressed in septic patients’ blood compared to healthy blood upon ex vivo LPS stimulation and were restored by IFN-γ. In this study, by combining a microarray approach in an in vitro model and a validation in clinical samples, we identified a panel of six new transcripts that could be used for the identification of septic patients eligible for IFNg therapy. Along with the previously identified markers TNFa, IL10 and HLA-DRA, the potential value of these markers should now be evaluated in a larger cohort of patients. Upon favorable results, they could serve as stratification tools prior to immunostimulatory treatment and to monitor drug efficacy. PMID:23874546

Identification of biomarkers of response to IFNg during endotoxin tolerance: application to septic shock.

PubMed

Allantaz-Frager, Florence; Turrel-Davin, Fanny; Venet, Fabienne; Monnin, Cécile; De Saint Jean, Amélie; Barbalat, Véronique; Cerrato, Elisabeth; Pachot, Alexandre; Lepape, Alain; Monneret, Guillaume

2013-01-01

The rapid development in septic patients of features of marked immunosuppression associated with increased risk of nosocomial infections and mortality represents the rational for the initiation of immune targeted treatments in sepsis. However, as there is no clinical sign of immune dysfunctions, the current challenge is to develop biomarkers that will help clinicians identify the patients that would benefit from immunotherapy and monitor its efficacy. Using an in vitro model of endotoxin tolerance (ET), a pivotal feature of sepsis-induced immunosuppression in monocytes, we identified using gene expression profiling by microarray a panel of transcripts associated with the development of ET which expression was restored after immunostimulation with interferon-gamma (IFN-γ). These results were confirmed by qRT-PCR. Importantly, this short-list of markers was further evaluated in patients. Of these transcripts, six (TNFAIP6, FCN1, CXCL10, GBP1, CXCL5 and PID1) were differentially expressed in septic patients' blood compared to healthy blood upon ex vivo LPS stimulation and were restored by IFN-γ. In this study, by combining a microarray approach in an in vitro model and a validation in clinical samples, we identified a panel of six new transcripts that could be used for the identification of septic patients eligible for IFNg therapy. Along with the previously identified markers TNFa, IL10 and HLA-DRA, the potential value of these markers should now be evaluated in a larger cohort of patients. Upon favorable results, they could serve as stratification tools prior to immunostimulatory treatment and to monitor drug efficacy.

Oral microbiota species in acute apical endodontic abscesses.

PubMed

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.

Identification of candidate biomarkers with cancer-specific glycosylation in the tissue and serum of endometrioid ovarian cancer patients by glycoproteomic analysis

PubMed Central

Abbott, Karen L.; Lim, Jae-Min; Wells, Lance; Benigno, Benedict B.; McDonald, John F.; Pierce, Michael

2016-01-01

Epithelial ovarian cancer is diagnosed less than 25% of the time when the cancer is confined to the ovary, leading to 5-year survival rates of less than 30%. Therefore, there is an urgent need for early diagnostics for ovarian cancer. Our study using glycotranscriptome comparative analysis of endometrioid ovarian cancer tissue and normal ovarian tissue led to the identification of distinct differences in the transcripts of a restricted set of glycosyltransferases involved in N-linked glycosylation. Utilizing lectins that bind to glycan structures predicted to show changes, we observed differences in lectin-bound glycoproteins consistent with some of the transcript differences. In this study, we have extended our observations by the use of selected lectins to perform a targeted glycoproteomic analysis of ovarian cancer and normal ovarian tissues. Our results have identified several glycoproteins that display tumor-specific glycosylation changes. We have verified these glycosylation changes on glycoproteins from tissue using immunoprecipitation followed by lectin blot detection. The glycoproteins that were verified were then analyzed further using existing microarray data obtained from benign ovarian adenomas, borderline ovarian adenocarcinomas, and malignant ovarian adenocarcinomas. The verified glycoproteins found to be expressed above control levels in the microarray data sets were then screened for tumor-specific glycan modifications in serum from ovarian cancer patients. Results obtained from two of these glycoprotein markers, periostin and thrombospondin, have confirmed that tumor-specific glycan changes can be used to distinguish ovarian cancer patient serum from normal serum. PMID:19953551

Identification of a novel set of genes reflecting different in vivo invasive patterns of human GBM cells.

PubMed

Monticone, Massimiliano; Daga, Antonio; Candiani, Simona; Romeo, Francesco; Mirisola, Valentina; Viaggi, Silvia; Melloni, Ilaria; Pedemonte, Simona; Zona, Gianluigi; Giaretti, Walter; Pfeffer, Ulrich; Castagnola, Patrizio

2012-08-17

Most patients affected by Glioblastoma multiforme (GBM, grade IV glioma) experience a recurrence of the disease because of the spreading of tumor cells beyond surgical boundaries. Unveiling mechanisms causing this process is a logic goal to impair the killing capacity of GBM cells by molecular targeting.We noticed that our long-term GBM cultures, established from different patients, may display two categories/types of growth behavior in an orthotopic xenograft model: expansion of the tumor mass and formation of tumor branches/nodules (nodular like, NL-type) or highly diffuse single tumor cell infiltration (HD-type). We determined by DNA microarrays the gene expression profiles of three NL-type and three HD-type long-term GBM cultures. Subsequently, individual genes with different expression levels between the two groups were identified using Significance Analysis of Microarrays (SAM). Real time RT-PCR, immunofluorescence and immunoblot analyses, were performed for a selected subgroup of regulated gene products to confirm the results obtained by the expression analysis. Here, we report the identification of a set of 34 differentially expressed genes in the two types of GBM cultures. Twenty-three of these genes encode for proteins localized to the plasma membrane and 9 of these for proteins are involved in the process of cell adhesion. This study suggests the participation in the diffuse infiltrative/invasive process of GBM cells within the CNS of a novel set of genes coding for membrane-associated proteins, which should be thus susceptible to an inhibition strategy by specific targeting.Massimiliano Monticone and Antonio Daga contributed equally to this work.

Gene expression profiles in rainbow trout, Onchorynchus mykiss, exposed to a simple chemical mixture.

PubMed

Hook, Sharon E; Skillman, Ann D; Gopalan, Banu; Small, Jack A; Schultz, Irvin R

2008-03-01

Among proposed uses for microarrays in environmental toxiciology is the identification of key contributors to toxicity within a mixture. However, it remains uncertain whether the transcriptomic profiles resulting from exposure to a mixture have patterns of altered gene expression that contain identifiable contributions from each toxicant component. We exposed isogenic rainbow trout Onchorynchus mykiss, to sublethal levels of ethynylestradiol, 2,2,4,4-tetrabromodiphenyl ether, and chromium VI or to a mixture of all three toxicants Fluorescently labeled complementary DNA (cDNA) were generated and hybridized against a commercially available Salmonid array spotted with 16,000 cDNAs. Data were analyzed using analysis of variance (p<0.05) with a Benjamani-Hochberg multiple test correction (Genespring [Agilent] software package) to identify up and downregulated genes. Gene clustering patterns that can be used as "expression signatures" were determined using hierarchical cluster analysis. The gene ontology terms associated with significantly altered genes were also used to identify functional groups that were associated with toxicant exposure. Cross-ontological analytics approach was used to assign functional annotations to genes with "unknown" function. Our analysis indicates that transcriptomic profiles resulting from the mixture exposure resemble those of the individual contaminant exposures, but are not a simple additive list. However, patterns of altered genes representative of each component of the mixture are clearly discernible, and the functional classes of genes altered represent the individual components of the mixture. These findings indicate that the use of microarrays to identify transcriptomic profiles may aid in the identification of key stressors within a chemical mixture, ultimately improving environmental assessment.

Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays

PubMed Central

2011-01-01

Background Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs. Results In this study, we introduce a novel method referred to as the wavelet-based identification of focal genomic aberrations (WIFA). The use of the wavelet analysis, because it is a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in broadly aberrant regions. The proposed method integrates multiple cancer samples so that it enables the detection of the consistent aberrations across multiple samples. We then apply this method to glioblastoma multiforme and lung cancer data sets from the SNP microarray platform. Through this process, we confirm the ability to detect previously known cancer related genes from both cancer types with high accuracy. Also, the application of this approach to a lung cancer data set identifies focal amplification regions that contain known oncogenes, though these regions are not reported using a recent CNAs detecting algorithm GISTIC: SMAD7 (chr18q21.1) and FGF10 (chr5p12). Conclusions Our results suggest that WIFA can be used to reveal cancer related genes in various cancer data sets. PMID:21569311

Importing MAGE-ML format microarray data into BioConductor.

PubMed

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.

Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

PubMed

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.

A technological update of molecular diagnostics for infectious diseases

PubMed Central

Liu, Yu-Tsueng

2008-01-01

Identification of a causative pathogen is essential for the choice of treatment for most infectious diseases. Many FDA approved molecular assays; usually more sensitive and specific compared to traditional tests, have been developed in the last decade. A new trend of high throughput and multiplexing assays are emerging thanks to technological developments for the human genome sequencing project. The applications of microarray and ultra high throughput sequencing technologies for diagnostic microbiology are reviewed. The race for the $1000 genome technology by 2014 will have a profound impact in diagnosis and treatment of infectious diseases in the near future. PMID:18782035

Ecology and genomics of Bacillus subtilis.

PubMed

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.

Identification of rice genes associated with cosmic-ray response via co-expression gene network analysis.

PubMed

Hwang, Sun-Goo; Kim, Dong Sub; Hwang, Jung Eun; Han, A-Reum; Jang, Cheol Seong

2014-05-15

In order to better understand the biological systems that are affected in response to cosmic ray (CR), we conducted weighted gene co-expression network analysis using the module detection method. By using the Pearson's correlation coefficient (PCC) value, we evaluated complex gene-gene functional interactions between 680 CR-responsive probes from integrated microarray data sets, which included large-scale transcriptional profiling of 1000 microarray samples. These probes were divided into 6 distinct modules that contained 20 enriched gene ontology (GO) functions, such as oxidoreductase activity, hydrolase activity, and response to stimulus and stress. In particular, modules 1 and 2 commonly showed enriched annotation categories such as oxidoreductase activity, including enriched cis-regulatory elements known as ROS-specific regulators. These results suggest that the ROS-mediated irradiation response pathway is affected by CR in modules 1 and 2. We found 243 ionizing radiation (IR)-responsive probes that exhibited similarities in expression patterns in various irradiation microarray data sets. The expression patterns of 6 randomly selected IR-responsive genes were evaluated by quantitative reverse transcription polymerase chain reaction following treatment with CR, gamma rays (GR), and ion beam (IB); similar patterns were observed among these genes under these 3 treatments. Moreover, we constructed subnetworks of IR-responsive genes and evaluated the expression levels of their neighboring genes following GR treatment; similar patterns were observed among them. These results of network-based analyses might provide a clue to understanding the complex biological system related to the CR response in plants. Copyright © 2014 Elsevier B.V. All rights reserved.

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

PubMed Central

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

Elucidation of the effect of brain cortex tetrapeptide Cortagen on gene expression in mouse heart by microarray.

PubMed

Anisimov, Sergey V; Khavinson, Vladimir Kh; Anisimov, Vladimir N

2004-01-01

Aging is associated with significant alterations in gene expression in numerous organs and tissues. Anti-aging therapy with peptide bioregulators holds much promise for the correction of age-associated changes, making a screening for their molecular targets in tissues an important question of modern gerontology. The synthetic tetrapeptide Cortagen (Ala-Glu-Asp-Pro) was obtained by directed synthesis based on amino acid analysis of natural brain cortex peptide preparation Cortexin. In humans, Cortagen demonstrated a pronounced therapeutic effect upon the structural and functional posttraumatic recovery of peripheral nerve tissue. Importantly, other effects were also observed in cardiovascular and cerebrovascular parameters. Based on these latter observations, we hypothesized that acute course of Cortagen treatment, large-scale transcriptome analysis, and identification of transcripts with altered expression in heart would facilitate our understanding of the mechanisms responsible for this peptide biological effects. We therefore analyzed the expression of 15,247 transcripts in the heart of female 6-months CBA mice receiving injections of Cortagen for 5 consecutive days was studied by cDNA microarrays. Comparative analysis of cDNA microarray hybridisation with heart samples from control and experimental group revealed 234 clones (1,53% of the total number of clones) with significant changes of expression that matched 110 known genes belonging to various functional categories. Maximum up- and down-regulation was +5.42 and -2.86, respectively. Intercomparison of changes in cardiac expression profile induced by synthetic peptides (Cortagen, Vilon, Epitalon) and pineal peptide hormone melatonin revealed both common and specific effects of Cortagen upon gene expression in heart.

Joint mapping of genes and conditions via multidimensional unfolding analysis

PubMed Central

Van Deun, Katrijn; Marchal, Kathleen; Heiser, Willem J; Engelen, Kristof; Van Mechelen, Iven

2007-01-01

Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data. PMID:17550582

Global Microarray Analysis of Carbohydrate Use in Alkaliphilic Hemicellulolytic Bacterium Bacillus sp. N16-5

PubMed Central

Song, Yajian; Xue, Yanfen; Ma, Yanhe

2013-01-01

The alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5 has a broad substrate spectrum and exhibits the capacity to utilize complex carbohydrates such as galactomannan, xylan, and pectin. In the monosaccharide mixture, sequential utilization by Bacillus sp. N16-5 was observed. Glucose appeared to be its preferential monosaccharide, followed by fructose, mannose, arabinose, xylose, and galactose. Global transcription profiles of the strain were determined separately for growth on six monosaccharides (glucose, fructose, mannose, galactose, arabinose, and xylose) and four polysaccharides (galactomannan, xylan, pectin, and sodium carboxymethylcellulose) using one-color microarrays. Numerous genes potentially related to polysaccharide degradation, sugar transport, and monosaccharide metabolism were found to respond to a specific substrate. Putative gene clusters for different carbohydrates were identified according to transcriptional patterns and genome annotation. Identification and analysis of these gene clusters contributed to pathway reconstruction for carbohydrate utilization in Bacillus sp. N16-5. Several genes encoding putative sugar transporters were highly expressed during growth on specific sugars, suggesting their functional roles. Two phosphoenolpyruvate-dependent phosphotransferase systems were identified as candidate transporters for mannose and fructose, and a major facilitator superfamily transporter was identified as a candidate transporter for arabinose and xylose. Five carbohydrate uptake transporter 1 family ATP-binding cassette transporters were predicted to participate in the uptake of hemicellulose and pectin degradation products. Collectively, microarray data improved the pathway reconstruction involved in carbohydrate utilization of Bacillus sp. N16-5 and revealed that the organism precisely regulates gene transcription in response to fluctuations in energy resources. PMID:23326578

Characterization of QKI gene expression, genetics, and epigenetics in suicide victims with major depressive disorder.

PubMed

Klempan, Timothy A; Ernst, Carl; Deleva, Vesselina; Labonte, Benoit; Turecki, Gustavo

2009-11-01

A number of studies have suggested deficits in myelination and glial gene expression in different psychiatric disorders. We examined the brain expression and genetic/epigenetic regulation of QKI, an oligodendrocyte-specific RNA binding protein important for cell development and myelination. The microarray-based expression of QKI was evaluated in cortical and subcortical brain regions from suicide victims with a diagnosis of major depression (n = 16) and control subjects (n = 13). These findings were also assessed with a real-time (quantitative polymerase chain reaction [qPCR]) approach, with QKI protein levels evaluated through immunoblotting. Identification of a QKI promoter sequence was then used to examine genetic and epigenetic variation at the QKI locus. The messenger RNA (mRNA) levels of multiple transcripts of QKI were evaluated on Affymetrix microarrays, revealing significant reductions in 11 cortical regions and the hippocampus and amygdala of suicide victims compared with control subjects. Microarray findings were confirmed by qPCR, and reduced expression of QKI protein was identified in orbitofrontal cortex. Analysis of promoter variation and methylation state in a subset of individuals did not identify differences at the genetic or epigenetic level between depressed suicide victims and control subjects. The observation of consistent reductions in multiple isoforms of QKI mRNA in depressed suicide victims supports the growing body of evidence for a role of myelination-related deficits in the etiology of psychiatric disorders. A specific role of QKI in this process is implied by its reduced expression and known interactions with genes involved in oligodendrocyte determination; however, QKI gene variation responsible for these changes remains to be identified.

Design and verification of a pangenome microarray oligonucleotide probe set for Dehalococcoides spp.

PubMed

Hug, Laura A; Salehi, Maryam; Nuin, Paulo; Tillier, Elisabeth R; Edwards, Elizabeth A

2011-08-01

Dehalococcoides spp. are an industrially relevant group of Chloroflexi bacteria capable of reductively dechlorinating contaminants in groundwater environments. Existing Dehalococcoides genomes revealed a high level of sequence identity within this group, including 98 to 100% 16S rRNA sequence identity between strains with diverse substrate specificities. Common molecular techniques for identification of microbial populations are often not applicable for distinguishing Dehalococcoides strains. Here we describe an oligonucleotide microarray probe set designed based on clustered Dehalococcoides genes from five different sources (strain DET195, CBDB1, BAV1, and VS genomes and the KB-1 metagenome). This "pangenome" probe set provides coverage of core Dehalococcoides genes as well as strain-specific genes while optimizing the potential for hybridization to closely related, previously unknown Dehalococcoides strains. The pangenome probe set was compared to probe sets designed independently for each of the five Dehalococcoides strains. The pangenome probe set demonstrated better predictability and higher detection of Dehalococcoides genes than strain-specific probe sets on nontarget strains with <99% average nucleotide identity. An in silico analysis of the expected probe hybridization against the recently released Dehalococcoides strain GT genome and additional KB-1 metagenome sequence data indicated that the pangenome probe set performs more robustly than the combined strain-specific probe sets in the detection of genes not included in the original design. The pangenome probe set represents a highly specific, universal tool for the detection and characterization of Dehalococcoides from contaminated sites. It has the potential to become a common platform for Dehalococcoides-focused research, allowing meaningful comparisons between microarray experiments regardless of the strain examined.

cDNA microarray reveals the alterations of cytoskeleton-related genes in osteoblast under high magneto-gravitational environment.

PubMed

Qian, Airong; Di, Shengmeng; Gao, Xiang; Zhang, Wei; Tian, Zongcheng; Li, Jingbao; Hu, Lifang; Yang, Pengfei; Yin, Dachuan; Shang, Peng

2009-07-01

The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has been widely applied in many fields. In this study, a special designed superconducting magnet, which can produce three apparent gravity levels (0, 1, and 2 g), namely high magneto-gravitational environment (HMGE), was used to simulate space gravity environment. The effects of HMGE on osteoblast gene expression profile were investigated by microarray. Genes sensitive to diamagnetic levitation environment (0 g), gravity changes, and high magnetic field changes were sorted on the basis of typical cell functions. Cytoskeleton, as an intracellular load-bearing structure, plays an important role in gravity perception. Therefore, 13 cytoskeleton-related genes were chosen according to the results of microarray analysis, and the expressions of these genes were found to be altered under HMGE by real-time PCR. Based on the PCR results, the expressions of WASF2 (WAS protein family, member 2), WIPF1 (WAS/WASL interacting protein family, member 1), paxillin, and talin 1 were further identified by western blot assay. Results indicated that WASF2 and WIPF1 were more sensitive to altered gravity levels, and talin 1 and paxillin were sensitive to both magnetic field and gravity changes. Our findings demonstrated that HMGE can affect osteoblast gene expression profile and cytoskeleton-related genes expression. The identification of mechanosensitive genes may enhance our understandings to the mechanism of bone loss induced by microgravity and may provide some potential targets for preventing and treating bone loss or osteoporosis.

EFEMP1 as a novel DNA methylation marker for prostate cancer: array-based DNA methylation and expression profiling.

PubMed

Kim, Yong-June; Yoon, Hyung-Yoon; Kim, Seon-Kyu; Kim, Young-Won; Kim, Eun-Jung; Kim, Isaac Yi; Kim, Wun-Jae

2011-07-01

Abnormal DNA methylation is associated with many human cancers. The aim of the present study was to identify novel methylation markers in prostate cancer (PCa) by microarray analysis and to test whether these markers could discriminate normal and PCa cells. Microarray-based DNA methylation and gene expression profiling was carried out using a panel of PCa cell lines and a control normal prostate cell line. The methylation status of candidate genes in prostate cell lines was confirmed by real-time reverse transcriptase-PCR, bisulfite sequencing analysis, and treatment with a demethylation agent. DNA methylation and gene expression analysis in 203 human prostate specimens, including 106 PCa and 97 benign prostate hyperplasia (BPH), were carried out. Further validation using microarray gene expression data from the Gene Expression Omnibus (GEO) was carried out. Epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) was identified as a lead candidate methylation marker for PCa. The gene expression level of EFEMP1 was significantly higher in tissue samples from patients with BPH than in those with PCa (P < 0.001). The sensitivity and specificity of EFEMP1 methylation status in discriminating between PCa and BPH reached 95.3% (101 of 106) and 86.6% (84 of 97), respectively. From the GEO data set, we confirmed that the expression level of EFEMP1 was significantly different between PCa and BPH. Genome-wide characterization of DNA methylation profiles enabled the identification of EFEMP1 aberrant methylation patterns in PCa. EFEMP1 might be a useful indicator for the detection of PCa.

Differential gene expression of wheat progeny with contrasting levels of transpiration efficiency.

PubMed

Xue, Gang-Ping; McIntyre, C Lynne; Chapman, Scott; Bower, Neil I; Way, Heather; Reverter, Antonio; Clarke, Bryan; Shorter, Ray

2006-08-01

High water use efficiency or transpiration efficiency (TE) in wheat is a desirable physiological trait for increasing grain yield under water-limited environments. The identification of genes associated with this trait would facilitate the selection for genotypes with higher TE using molecular markers. We performed an expression profiling (microarray) analysis of approximately 16,000 unique wheat ESTs to identify genes that were differentially expressed between wheat progeny lines with contrasting TE levels from a cross between Quarrion (high TE) and Genaro 81 (low TE). We also conducted a second microarray analysis to identify genes responsive to drought stress in wheat leaves. Ninety-three genes that were differentially expressed between high and low TE progeny lines were identified. One fifth of these genes were markedly responsive to drought stress. Several potential growth-related regulatory genes, which were down-regulated by drought, were expressed at a higher level in the high TE lines than the low TE lines and are potentially associated with a biomass production component of the Quarrion-derived high TE trait. Eighteen of the TE differentially expressed genes were further analysed using quantitative RT-PCR on a separate set of plant samples from those used for microarray analysis. The expression levels of 11 of the 18 genes were positively correlated with the high TE trait, measured as carbon isotope discrimination (Delta(13)C). These data indicate that some of these TE differentially expressed genes are candidates for investigating processes that underlie the high TE trait or for use as expression quantitative trait loci (eQTLs) for TE.

Efficacy of a novel PCR- and microarray-based method in diagnosis of a prosthetic joint infection

PubMed Central

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

Identification of genes associated with the long-gut-persistence phenotype of the probiotic Lactobacillus johnsonii strain NCC533 using a combination of genomics and transcriptome analysis.

PubMed

Denou, Emmanuel; Pridmore, Raymond David; Berger, Bernard; Panoff, Jean-Michel; Arigoni, Fabrizio; Brüssow, Harald

2008-05-01

Lactobacillus johnsonii strains NCC533 and ATCC 33200 (the type strain of this species) differed significantly in gut residence time (12 versus 5 days) after oral feeding to mice. Genes affecting the long gut residence time of the probiotic strain NCC533 were targeted for analysis. We hypothesized that genes specific for this strain, which are expressed during passage of the bacterium through the gut, affect the phenotype. When the DNA of the type strain was hybridized against a microarray of the sequenced NCC533 strain, we identified 233 genes that were specific for the long-gut-persistence isolate. Whole-genome transcription analysis of the NCC533 strain using the microarray format identified 174 genes that were strongly and consistently expressed in the jejunum of mice monocolonized with this strain. Fusion of the two microarray data sets identified three gene loci that were both expressed in vivo and specific to the long-gut-persistence isolate. The identified genes included LJ1027 and LJ1028, two glycosyltransferase genes in the exopolysaccharide synthesis operon; LJ1654 to LJ1656, encoding a sugar phosphotransferase system (PTS) transporter annotated as mannose PTS; and LJ1680, whose product shares 30% amino acid identity with immunoglobulin A proteases from pathogenic bacteria. Knockout mutants were tested in vivo. The experiments revealed that deletion of LJ1654 to LJ1656 and LJ1680 decreased the gut residence time, while a mutant with a deleted exopolysaccharide biosynthesis cluster had a slightly increased residence time.

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

PubMed

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.

2008 Microarray Research Group (MARG Survey): Sensing the State of Microarray Technology

EPA Science Inventory

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...

THE ABRF-MARG MICROARRAY SURVEY 2004: TAKING THE PULSE OF THE MICROARRAY FIELD

EPA Science Inventory

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…

Parallel, confocal, and complete spectrum imager for fluorescent detection of high-density microarray

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.

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

Identification of Quantitative Trait Loci (QTL) and Candidate Genes for Cadmium Tolerance in Populus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Induri, Brahma R; Ellis, Danielle R; Slavov, Gancho

2012-01-01

Knowledge of genetic variation in response of Populus to heavy metals like cadmium (Cd) is an important step in understanding the underlying mechanisms of tolerance. In this study, a pseudo-backcross pedigree of Populus trichocarpa and Populus deltoides was characterized for Cd exposure. The pedigree showed significant variation for Cd tolerance thus enabling the identification of relatively tolerant and susceptible genotypes for intensive characterization. A total of 16 QTLs at logarithm of odds (LOD) ratio > 2.5, were found to be associated with total dry weight, its components, and root volume. Four major QTLs for total dry weight were mapped tomore » different linkage groups in control (LG III) and Cd conditions (LG XVI) and had opposite allelic effects on Cd tolerance, suggesting that these genomic regions were differentially controlled. The phenotypic variation explained by Cd QTL for all traits under study varied from 5.9% to 11.6% and averaged 8.2% across all QTL. Leaf Cd contents also showed significant variation suggesting the phytoextraction potential of Populus genotypes, though heritability of this trait was low (0.22). A whole-genome microarray study was conducted by using two genotypes with extreme responses for Cd tolerance in the above study and differentially expressed genes were identified. Candidate genes including CAD2 (CADMIUM SENSITIVE 2), HMA5 (HEAVY METAL ATPase5), ATGTST1 (Arabidopsis thaliana Glutathione S-Transferase1), ATGPX6 (Glutathione peroxidase 6), and ATMRP 14 (Arabidopsis thaliana Multidrug Resistance associated Protein 14) were identified from QTL intervals and microarray study. Functional characterization of these candidate genes could enhance phytoremediation capabilities of Populus.« less

Oral microbiota species in acute apical endodontic abscesses

PubMed Central

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

Biomarkers of acute respiratory allergen exposure: Screening for sensitization potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pucheu-Haston, Cherie M., E-mail: Pucheu-Haston.Cherie@epa.go; Copeland, Lisa B.; Vallanat, Beena

2010-04-15

Effective hazard screening will require the development of high-throughput or in vitro assays for the identification of potential sensitizers. The goal of this preliminary study was to identify potential biomarkers that differentiate the response to allergens vs non-allergens following an acute exposure in naive individuals. Female BALB/c mice received a single intratracheal aspiration exposure to Metarhizium anisopliae crude antigen (MACA) or bovine serum albumin (BSA) in Hank's Balanced Salt Solution (HBSS) or HBSS alone. Mice were terminated after 1, 3, 6, 12, 18 and 24 h. Bronchoalveolar lavage fluid (BALF) was evaluated to determine total and differential cellularity, total proteinmore » concentration and LDH activity. RNA was isolated from lung tissue for microarray analysis and qRT-PCR. MACA administration induced a rapid increase in BALF neutrophils, lymphocytes, eosinophils and total protein compared to BSA or HBSS. Microarray analysis demonstrated differential expression of genes involved in cytokine production, signaling, inflammatory cell recruitment, adhesion and activation in 3 and 12 h MACA-treated samples compared to BSA or HBSS. Further analyses allowed identification of approx 100 candidate biomarker genes. Eleven genes were selected for further assessment by qRT-PCR. Of these, 6 demonstrated persistently increased expression (Ccl17, Ccl22, Ccl7, Cxcl10, Cxcl2, Saa1), while C3ar1 increased from 6-24 h. In conclusion, a single respiratory exposure of mice to an allergenic mold extract induces an inflammatory response which is distinct in phenotype and gene transcription from the response to a control protein. Further validation of these biomarkers with additional allergens and irritants is needed. These biomarkers may facilitate improvements in screening methods.« less

Global transcriptomic profiling using small volumes of whole blood: a cost-effective method for translational genomic biomarker identification in small animals.

PubMed

Fricano, Meagan M; Ditewig, Amy C; Jung, Paul M; Liguori, Michael J; Blomme, Eric A G; Yang, Yi

2011-01-01

Blood is an ideal tissue for the identification of novel genomic biomarkers for toxicity or efficacy. However, using blood for transcriptomic profiling presents significant technical challenges due to the transcriptomic changes induced by ex vivo handling and the interference of highly abundant globin mRNA. Most whole blood RNA stabilization and isolation methods also require significant volumes of blood, limiting their effective use in small animal species, such as rodents. To overcome these challenges, a QIAzol-based RNA stabilization and isolation method (QSI) was developed to isolate sufficient amounts of high quality total RNA from 25 to 500 μL of rat whole blood. The method was compared to the standard PAXgene Blood RNA System using blood collected from rats exposed to saline or lipopolysaccharide (LPS). The QSI method yielded an average of 54 ng total RNA per μL of rat whole blood with an average RNA Integrity Number (RIN) of 9, a performance comparable with the standard PAXgene method. Total RNA samples were further processed using the NuGEN Ovation Whole Blood Solution system and cDNA was hybridized to Affymetrix Rat Genome 230 2.0 Arrays. The microarray QC parameters using RNA isolated with the QSI method were within the acceptable range for microarray analysis. The transcriptomic profiles were highly correlated with those using RNA isolated with the PAXgene method and were consistent with expected LPS-induced inflammatory responses. The present study demonstrated that the QSI method coupled with NuGEN Ovation Whole Blood Solution system is cost-effective and particularly suitable for transcriptomic profiling of minimal volumes of whole blood, typical of those obtained with small animal species.

Mapping of transcription factor binding regions in mammalian cells by ChIP: Comparison of array- and sequencing-based technologies

PubMed Central

Euskirchen, Ghia M.; Rozowsky, Joel S.; Wei, Chia-Lin; Lee, Wah Heng; Zhang, Zhengdong D.; Hartman, Stephen; Emanuelsson, Olof; Stolc, Viktor; Weissman, Sherman; Gerstein, Mark B.; Ruan, Yijun; Snyder, Michael

2007-01-01

Recent progress in mapping transcription factor (TF) binding regions can largely be credited to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for mapping TF binding regions in mammalian cells using two different ChIP schemes: ChIP with DNA microarray analysis (ChIP-chip) and ChIP with DNA sequencing (ChIP-PET). We first investigated parameters central to obtaining robust ChIP-chip data sets by analyzing STAT1 targets in the ENCODE regions of the human genome, and then compared ChIP-chip to ChIP-PET. We devised methods for scoring and comparing results among various tiling arrays and examined parameters such as DNA microarray format, oligonucleotide length, hybridization conditions, and the use of competitor Cot-1 DNA. The best performance was achieved with high-density oligonucleotide arrays, oligonucleotides ≥50 bases (b), the presence of competitor Cot-1 DNA and hybridizations conducted in microfluidics stations. When target identification was evaluated as a function of array number, 80%–86% of targets were identified with three or more arrays. Comparison of ChIP-chip with ChIP-PET revealed strong agreement for the highest ranked targets with less overlap for the low ranked targets. With advantages and disadvantages unique to each approach, we found that ChIP-chip and ChIP-PET are frequently complementary in their relative abilities to detect STAT1 targets for the lower ranked targets; each method detected validated targets that were missed by the other method. The most comprehensive list of STAT1 binding regions is obtained by merging results from ChIP-chip and ChIP-sequencing. Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies. PMID:17568005

Analysis of High-Throughput ELISA Microarray Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis

PubMed Central

Nie, Hongyi; Liu, Xiaoyan; Pan, Jiao; Li, Wenfeng; Li, Zhiguo; Zhang, Shaowu; Chen, Shenglu; Miao, Xiaoqing; Zheng, Nenggan; Su, Songkun

2017-01-01

Abstract China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production. PMID:28981563

Assignment by Negative-Ion Electrospray Tandem Mass Spectrometry of the Tetrasaccharide Backbones of Monosialylated Glycans Released from Bovine Brain Gangliosides

NASA Astrophysics Data System (ADS)

Chai, Wengang; Zhang, Yibing; Mauri, Laura; Ciampa, Maria G.; Mulloy, Barbara; Sonnino, Sandro; Feizi, Ten

2018-05-01

Gangliosides, as plasma membrane-associated sialylated glycolipids, are antigenic structures and they serve as ligands for adhesion proteins of pathogens, for toxins of bacteria, and for endogenous proteins of the host. The detectability by carbohydrate-binding proteins of glycan antigens and ligands on glycolipids can be influenced by the differing lipid moieties. To investigate glycan sequences of gangliosides as recognition structures, we have underway a program of work to develop a "gangliome" microarray consisting of isolated natural gangliosides and neoglycolipids (NGLs) derived from glycans released from them, and each linked to the same lipid molecule for arraying and comparative microarray binding analyses. Here, in the first phase of our studies, we describe a strategy for high-sensitivity assignment of the tetrasaccharide backbones and application to identification of eight of monosialylated glycans released from bovine brain gangliosides. This approach is based on negative-ion electrospray mass spectrometry with collision-induced dissociation (ESI-CID-MS/MS) of the desialylated glycans. Using this strategy, we have the data on backbone regions of four minor components among the monosialo-ganglioside-derived glycans; these are of the ganglio-, lacto-, and neolacto-series.

Identification of novel target genes involved in Indian Fanconi anemia patients using microarray.

PubMed

Shyamsunder, Pavithra; Ganesh, Kripa S; Vidyasekar, Prasanna; Mohan, Sheila; Verma, Rama Shanker

2013-12-01

Fanconi anemia (FA) is a genetic disorder characterized by progressive bone marrow failure and a predisposition to cancers. Mutations have been documented in 15 FA genes that participate in the FA-BRCA DNA repair pathway, a fundamental pathway in the development of the disease and the presentation of its characteristic symptoms. Certain symptoms such as oxygen sensitivity, hematological abnormalities and impaired immunity suggest that FA proteins could participate in or independently control other pathways as well. In this study, we identified 9 DNA repair genes that were down regulated in a genome wide analysis of 6 Indian Fanconi anemia patients. Functional clustering of a total of 233 dysregulated genes identified key biological processes that included regulation of transcription, DNA repair, cell cycle and chromosomal organization. Microarray data revealed the down regulation of ATXN3, ARID4A and ETS-1, which were validated by RTPCR in a subsequent sample set of 9 Indian FA patients. Here we report for the first time a gene expression profile of Fanconi anemia patients from the Indian population and a pool of genes that might aid in the acquisition and progression of the FA phenotype. © 2013 Elsevier B.V. All rights reserved.

Diagnosis of Familial Wolf-Hirschhorn Syndrome due to a Paternal Cryptic Chromosomal Rearrangement by Conventional and Molecular Cytogenetic Techniques

PubMed Central

Venegas-Vega, Carlos A.; Zepeda, Luis M.; Garduño-Zarazúa, Luz M.; Berumen, Jaime; Kofman, Susana; Cervantes, Alicia

2013-01-01

The use of conventional cytogenetic techniques in combination with fluorescent in situ hybridization (FISH) and single-nucleotide polymorphism (SNP) microarrays is necessary for the identification of cryptic rearrangements in the diagnosis of chromosomal syndromes. We report two siblings, a boy of 9 years and 9 months of age and his 7-years- and 5-month-old sister, with the classic Wolf-Hirschhorn syndrome (WHS) phenotype. Using high-resolution GTG- and NOR-banding karyotypes, as well as FISH analysis, we characterized a pure 4p deletion in both sibs and a balanced rearrangement in their father, consisting in an insertion of 4p material within a nucleolar organizing region of chromosome 15. Copy number variant (CNV) analysis using SNP arrays showed that both siblings have a similar size of 4p deletion (~6.5 Mb). Our results strongly support the need for conventional cytogenetic and FISH analysis, as well as high-density microarray mapping for the optimal characterization of the genetic imbalance in patients with WHS; parents must always be studied for recognizing cryptic balanced chromosomal rearrangements for an adequate genetic counseling. PMID:23484094

Mitochondrial dysfunction, oxidative stress and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson’s disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, Mark H.; Qian, Weijun; Wang, Haixing

2008-02-10

The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson disease (PD) are not completely understood. Here we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 85 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA following neurotoxin treatment. The combined protein and gene list providesmore » a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response and apoptosis. Additionally, codon usage and miRNAs may play an important role in translational control in the striatum. These results constitute one of the largest datasets integrating protein and transcript changes for these neurotoxin models with many similar endpoint phenotypes but distinct mechanisms.« less

Hazard characterization and identification of a former ammunition site using microarrays, bioassays, and chemical analysis.

PubMed

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.

A framework to identify gene expression profiles in a model of inflammation induced by lipopolysaccharide after treatment with thalidomide

PubMed Central

2012-01-01

Background Thalidomide is an anti-inflammatory and anti-angiogenic drug currently used for the treatment of several diseases, including erythema nodosum leprosum, which occurs in patients with lepromatous leprosy. In this research, we use DNA microarray analysis to identify the impact of thalidomide on gene expression responses in human cells after lipopolysaccharide (LPS) stimulation. We employed a two-stage framework. Initially, we identified 1584 altered genes in response to LPS. Modulation of this set of genes was then analyzed in the LPS stimulated cells treated with thalidomide. Results We identified 64 genes with altered expression induced by thalidomide using the rank product method. In addition, the lists of up-regulated and down-regulated genes were investigated by means of bioinformatics functional analysis, which allowed for the identification of biological processes affected by thalidomide. Confirmatory analysis was done in five of the identified genes using real time PCR. Conclusions The results showed some genes that can further our understanding of the biological mechanisms in the action of thalidomide. Of the five genes evaluated with real time PCR, three were down regulated and two were up regulated confirming the initial results of the microarray analysis. PMID:22695124

Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data.

PubMed

Shah, M; Marchand, M; Corbeil, J

2012-01-01

One of the objectives of designing feature selection learning algorithms is to obtain classifiers that depend on a small number of attributes and have verifiable future performance guarantees. There are few, if any, approaches that successfully address the two goals simultaneously. To the best of our knowledge, such algorithms that give theoretical bounds on the future performance have not been proposed so far in the context of the classification of gene expression data. In this work, we investigate the premise of learning a conjunction (or disjunction) of decision stumps in Occam's Razor, Sample Compression, and PAC-Bayes learning settings for identifying a small subset of attributes that can be used to perform reliable classification tasks. We apply the proposed approaches for gene identification from DNA microarray data and compare our results to those of the well-known successful approaches proposed for the task. We show that our algorithm not only finds hypotheses with a much smaller number of genes while giving competitive classification accuracy but also having tight risk guarantees on future performance, unlike other approaches. The proposed approaches are general and extensible in terms of both designing novel algorithms and application to other domains.

Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis.

PubMed

Nie, Hongyi; Liu, Xiaoyan; Pan, Jiao; Li, Wenfeng; Li, Zhiguo; Zhang, Shaowu; Chen, Shenglu; Miao, Xiaoqing; Zheng, Nenggan; Su, Songkun

2017-01-01

China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production.

Myogenin, AP2β, NOS-1, and HMGA2 are surrogate markers of fusion status in rhabdomyosarcoma: a report from the soft tissue sarcoma committee of the children's oncology group.

PubMed

Rudzinski, Erin R; Anderson, James R; Lyden, Elizabeth R; Bridge, Julia A; Barr, Frederic G; Gastier-Foster, Julie M; Bachmeyer, Karen; Skapek, Stephen X; Hawkins, Douglas S; Teot, Lisa A; Parham, David M

2014-05-01

Pediatric rhabdomyosarcoma (RMS) is traditionally classified on the basis of the histologic appearance into alveolar (ARMS) and embryonal (ERMS) subtypes. The majority of ARMS contain a PAX3-FOXO1 or PAX7-FOXO1 gene fusion, but about 20% do not. Intergroup Rhabdomyosarcoma Study stage-matched and group-matched ARMS typically behaves more aggressively than ERMS, but recent studies have shown that it is, in fact, the fusion status that drives the outcome for RMS. Gene expression microarray data indicate that several genes discriminate between fusion-positive and fusion-negative RMS with high specificity. Using tissue microarrays containing a series of both ARMS and ERMS, we identified a panel of 4 immunohistochemical markers-myogenin, AP2β, NOS-1, and HMGA2-which can be used as surrogate markers of fusion status in RMS. These antibodies provide an alternative to molecular methods for identification of fusion-positive RMS, particularly in cases in which there is scant or poor-quality material. In addition, these antibodies may be useful in fusion-negative ARMS as an indicator that a variant gene fusion may be present.

MotifMark: Finding regulatory motifs in DNA sequences.

PubMed

Hassanzadeh, Hamid Reza; Kolhe, Pushkar; Isbell, Charles L; Wang, May D

2017-07-01

The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding sites and the specificity of target proteins in binding to these regions are two important steps in understanding the mechanisms of these biological activities. A number of high-throughput technologies have recently emerged that try to quantify the affinity between proteins and DNA motifs. Despite their success, these technologies have their own limitations and fall short in precise characterization of motifs, and as a result, require further downstream analysis to extract useful and interpretable information from a haystack of noisy and inaccurate data. Here we propose MotifMark, a new algorithm based on graph theory and machine learning, that can find binding sites on candidate probes and rank their specificity in regard to the underlying transcription factor. We developed a pipeline to analyze experimental data derived from compact universal protein binding microarrays and benchmarked it against two of the most accurate motif search methods. Our results indicate that MotifMark can be a viable alternative technique for prediction of motif from protein binding microarrays and possibly other related high-throughput techniques.

ChIP-chip.

PubMed

Kim, Tae Hoon; Dekker, Job

2018-05-01

ChIP-chip can be used to analyze protein-DNA interactions in a region-wide and genome-wide manner. DNA microarrays contain PCR products or oligonucleotide probes that are designed to represent genomic sequences. Identification of genomic sites that interact with a specific protein is based on competitive hybridization of the ChIP-enriched DNA and the input DNA to DNA microarrays. The ChIP-chip protocol can be divided into two main sections: Amplification of ChIP DNA and hybridization of ChIP DNA to arrays. A large amount of DNA is required to hybridize to DNA arrays, and hybridization to a set of multiple commercial arrays that represent the entire human genome requires two rounds of PCR amplifications. The relative hybridization intensity of ChIP DNA and that of the input DNA is used to determine whether the probe sequence is a potential site of protein-DNA interaction. Resolution of actual genomic sites bound by the protein is dependent on the size of the chromatin and on the genomic distance between the probes on the array. As with expression profiling using gene chips, ChIP-chip experiments require multiple replicates for reliable statistical measure of protein-DNA interactions. © 2018 Cold Spring Harbor Laboratory Press.

Loss of Cytoplasmic CDK1 Predicts Poor Survival in Human Lung Cancer and Confers Chemotherapeutic Resistance

PubMed Central

Zhang, Chunyu; Elkahloun, Abdel G.; Robertson, Matthew; Gills, Joell J.; Tsurutani, Junji; Shih, Joanna H.; Fukuoka, Junya; Hollander, M. Christine; Harris, Curtis C.; Travis, William D.; Jen, Jin; Dennis, Phillip A.

2011-01-01

The dismal lethality of lung cancer is due to late stage at diagnosis and inherent therapeutic resistance. The incorporation of targeted therapies has modestly improved clinical outcomes, but the identification of new targets could further improve clinical outcomes by guiding stratification of poor-risk early stage patients and individualizing therapeutic choices. We hypothesized that a sequential, combined microarray approach would be valuable to identify and validate new targets in lung cancer. We profiled gene expression signatures during lung epithelial cell immortalization and transformation, and showed that genes involved in mitosis were progressively enhanced in carcinogenesis. 28 genes were validated by immunoblotting and 4 genes were further evaluated in non-small cell lung cancer tissue microarrays. Although CDK1 was highly expressed in tumor tissues, its loss from the cytoplasm unexpectedly predicted poor survival and conferred resistance to chemotherapy in multiple cell lines, especially microtubule-directed agents. An analysis of expression of CDK1 and CDK1-associated genes in the NCI60 cell line database confirmed the broad association of these genes with chemotherapeutic responsiveness. These results have implications for personalizing lung cancer therapy and highlight the potential of combined approaches for biomarker discovery. PMID:21887332

The low-abundance transcriptome reveals novel biomarkers, specific intracellular pathways and targetable genes associated with advanced gastric cancer.

PubMed

Bizama, Carolina; Benavente, Felipe; Salvatierra, Edgardo; Gutiérrez-Moraga, Ana; Espinoza, Jaime A; Fernández, Elmer A; Roa, Iván; Mazzolini, Guillermo; Sagredo, Eduardo A; Gidekel, Manuel; Podhajcer, Osvaldo L

2014-02-15

Studies on the low-abundance transcriptome are of paramount importance for identifying the intimate mechanisms of tumor progression that can lead to novel therapies. The aim of the present study was to identify novel markers and targetable genes and pathways in advanced human gastric cancer through analyses of the low-abundance transcriptome. The procedure involved an initial subtractive hybridization step, followed by global gene expression analysis using microarrays. We observed profound differences, both at the single gene and gene ontology levels, between the low-abundance transcriptome and the whole transcriptome. Analysis of the low-abundance transcriptome led to the identification and validation by tissue microarrays of novel biomarkers, such as LAMA3 and TTN; moreover, we identified cancer type-specific intracellular pathways and targetable genes, such as IRS2, IL17, IFNγ, VEGF-C, WISP1, FZD5 and CTBP1 that were not detectable by whole transcriptome analyses. We also demonstrated that knocking down the expression of CTBP1 sensitized gastric cancer cells to mainstay chemotherapeutic drugs. We conclude that the analysis of the low-abundance transcriptome provides useful insights into the molecular basis and treatment of cancer. © 2013 UICC.

High resolution time course analysis of gene expression from the liver and pituitary

PubMed Central

Hughes, Michael E.; DiTacchio, Luciano; Hayes, Kevin; Pullivarthy, Sandhya R.; Panda, Satchidananda; Hogenesch, John

2009-01-01

In both the suprachiasmatic nucleus and peripheral tissues, the circadian oscillator drives rhythmic transcription of downstream target genes. Recently, a number of studies have used DNA microarrays to systematically identify oscillating transcripts in plants, fruit flies, rats and mice. These studies have identified several dozen to many hundred rhythmically expressed genes by sampling tissues every four hours for one, two, or more days. To extend this work, we have performed DNA microarray analysis on RNA derived from the mouse pituitary sampled every hour for two days. COSOPT and Fisher's G-test were employed at a false-discovery rate less than 5% to identify more than 250 genes in the pituitary that oscillate with a 24-hour period length. We found that increasing the frequency of sampling across the circadian day dramatically increased the statistical power of both COSOPT and Fisher's G-test, resulting in considerably more high-confidence identifications of rhythmic transcripts than previously described. Finally, to extend the utility of these data sets, a web-based resource has been constructed at http://wasabi.itmat.upenn.edu/circa/mouse that is freely available to the research community. PMID:18419295

Intra-Platform Repeatability and Inter-Platform Comparability of MicroRNA Microarray Technology

PubMed Central

Sato, Fumiaki; Tsuchiya, Soken; Terasawa, Kazuya; Tsujimoto, Gozoh

2009-01-01

Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems. PMID:19436744

Living Cell Microarrays: An Overview of Concepts

PubMed Central

Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

2016-01-01

Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. PMID:27600077

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.

Identification of differentially-expressed genes potentially implicated in drought response in pitaya (Hylocereus undatus) by suppression subtractive hybridization and cDNA microarray analysis.

PubMed

Fan, Qing-Jie; Yan, Feng-Xia; Qiao, Guang; Zhang, Bing-Xue; Wen, Xiao-Peng

2014-01-01

Drought is one of the most severe threats to the growth, development and yield of plant. In order to unravel the molecular basis underlying the high tolerance of pitaya (Hylocereus undatus) to drought stress, suppression subtractive hybridization (SSH) and cDNA microarray approaches were firstly combined to identify the potential important or novel genes involved in the plant responses to drought stress. The forward (drought over drought-free) and reverse (drought-free over drought) suppression subtractive cDNA libraries were constructed using in vitro shoots of cultivar 'Zihonglong' exposed to drought stress and drought-free (control). A total of 2112 clones, among which half were from either forward or reverse SSH library, were randomly picked up to construct a pitaya cDNA microarray. Microarray analysis was carried out to verify the expression fluctuations of this set of clones upon drought treatment compared with the controls. A total of 309 expressed sequence tags (ESTs), 153 from forward library and 156 from reverse library, were obtained, and 138 unique ESTs were identified after sequencing by clustering and blast analyses, which included genes that had been previously reported as responsive to water stress as well as some functionally unknown genes. Thirty six genes were mapped to 47 KEGG pathways, including carbohydrate metabolism, lipid metabolism, energy metabolism, nucleotide metabolism, and amino acid metabolism of pitaya. Expression analysis of the selected ESTs by reverse transcriptase polymerase chain reaction (RT-PCR) corroborated the results of differential screening. Moreover, time-course expression patterns of these selected ESTs further confirmed that they were closely responsive to drought treatment. Among the differentially expressed genes (DEGs), many are related to stress tolerances including drought tolerance. Thereby, the mechanism of drought tolerance of this pitaya genotype is a very complex physiological and biochemical process, in which multiple metabolism pathways and many genes were implicated. The data gained herein provide an insight into the mechanism underlying the drought stress tolerance of pitaya, as well as may facilitate the screening of candidate genes for drought tolerance. © 2013 Elsevier B.V. All rights reserved.

Eureka-DMA: an easy-to-operate graphical user interface for fast comprehensive investigation and analysis of DNA microarray data.

PubMed

Abelson, Sagi

2014-02-24

In the past decade, the field of molecular biology has become increasingly quantitative; rapid development of new technologies enables researchers to investigate and address fundamental issues quickly and in an efficient manner which were once impossible. Among these technologies, DNA microarray provides methodology for many applications such as gene discovery, diseases diagnosis, drug development and toxicological research and it has been used increasingly since it first emerged. Multiple tools have been developed to interpret the high-throughput data produced by microarrays. However, many times, less consideration has been given to the fact that an extensive and effective interpretation requires close interplay between the bioinformaticians who analyze the data and the biologists who generate it. To bridge this gap and to simplify the usability of such tools we developed Eureka-DMA - an easy-to-operate graphical user interface that allows bioinformaticians and bench-biologists alike to initiate analyses as well as to investigate the data produced by DNA microarrays. In this paper, we describe Eureka-DMA, a user-friendly software that comprises a set of methods for the interpretation of gene expression arrays. Eureka-DMA includes methods for the identification of genes with differential expression between conditions; it searches for enriched pathways and gene ontology terms and combines them with other relevant features. It thus enables the full understanding of the data for following testing as well as generating new hypotheses. Here we show two analyses, demonstrating examples of how Eureka-DMA can be used and its capability to produce relevant and reliable results. We have integrated several elementary expression analysis tools to provide a unified interface for their implementation. Eureka-DMA's simple graphical user interface provides effective and efficient framework in which the investigator has the full set of tools for the visualization and interpretation of the data with the option of exporting the analysis results for later use in other platforms. Eureka-DMA is freely available for academic users and can be downloaded at http://blue-meduza.org/Eureka-DMA.

Immunohistochemistry is a reliable screening tool for identification of ALK rearrangement in non-small-cell lung carcinoma and is antibody dependent.

PubMed

Conklin, Chris M J; Craddock, Kenneth J; Have, Cherry; Laskin, Janessa; Couture, Christian; Ionescu, Diana N

2013-01-01

Fluorescence in situ hybridization (FISH) is the standard procedure for the detection of anaplastic lymphoma receptor tyrosine kinase (ALK) rearrangement in non-small-cell lung carcinoma (NSCLC) but is expensive and time consuming. We tested three antibodies to ALK, using various detection systems, and hypothesized that ALK immunohistochemistry (IHC) may represent a cost-effective and efficient means of screening for ALK rearrangement in NSCLC. We screened 377 stage I or II NSCLC cases in a tissue microarray by FISH and IHC (5A4 [Leica Biosystems Newcastle Ltd, Newcastle upon Tyne, UYnited Kingdom] by Nichirei's N-Histofine ALK detection kit [Nichirei Biosciences inc., Tokyo, Japan], 5A4 by Novocastra with ADVANCE [Dako Canada inc., Burlington, Ontario, Canada], D5F3 by Cell Signaling Technology with ADVANCE [Cell Signalling Technologies inc., Danvers, MA], and DAKO clone ALK1 with FLEX [Dako Canada inc., Burlington, Ontario, Canada] and ADVANCE). IHC was scored as 0, 1+, 2+, or 3+. Possibly positive or positive cases were further analyzed by IHC and FISH on whole section. Tissue microarray results were available on 377 cases by IHC and 273 cases by FISH. Eleven cases were positive or possibly positive by either IHC or FISH, and three cases were positive or possibly positive by both methods. Three cases were ALK-positive by FISH on whole section validation. There was no correlation between semiquantitative IHC score (1+, 2+, 3+) and ALK rearrangement by FISH. D5F3 (Cell Signaling by ADVANCE) and 5A4 (Novocastra by ADVANCE) showed the greatest combination of sensitivity (100%) and specificity (87.5% for 5A4 by Novocastra and 75% for D5F3 by Cell Signaling), and produced no false-negative results. IHC is a reliable screening tool for identification of ALK rearrangement in NSCLC and is antibody dependent. D5F3 (Cell Signaling) and 5A4 (Novocastra) can be used with FISH for identification of IHC-positive cases to reduce screening costs.

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

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.

The Effect of Gestational Age on Angiogenic Gene Expression in the Rat Placenta

PubMed Central

Vaswani, Kanchan; Hum, Melissa Wen-Ching; Chan, Hsiu-Wen; Ryan, Jennifer; Wood-Bradley, Ryan J.; Nitert, Marloes Dekker; Mitchell, Murray D.; Armitage, James A.; Rice, Gregory E.

2013-01-01

The placenta plays a central role in determining the outcome of pregnancy. It undergoes changes during gestation as the fetus develops and as demands for energy substrate transfer and gas exchange increase. The molecular mechanisms that coordinate these changes have yet to be fully elucidated. The study performed a large scale screen of the transcriptome of the rat placenta throughout mid-late gestation (E14.25–E20) with emphasis on characterizing gestational age associated changes in the expression of genes invoved in angiogenic pathways. Sprague Dawley dams were sacrificed at E14.25, E15.25, E17.25 and E20 (n = 6 per group) and RNA was isolated from one placenta per dam. Changes in placental gene expression were identifed using Illumina Rat Ref-12 Expression BeadChip Microarrays. Differentially expressed genes (>2-fold change, <1% false discovery rate, FDR) were functionally categorised by gene ontology pathway analysis. A subset of differentially expressed genes identified by microarrays were confirmed using Real-Time qPCR. The expression of thirty one genes involved in the angiogenic pathway was shown to change over time, using microarray analysis (22 genes displayed increased and 9 gene decreased expression). Five genes (4 up regulated: Cd36, Mmp14, Rhob and Angpt4 and 1 down regulated: Foxm1) involved in angiogenesis and blood vessel morphogenesis were subjected to further validation. qPCR confirmed late gestational increased expression of Cd36, Mmp14, Rhob and Angpt4 and a decrease in expression of Foxm1 before labour onset (P<0.0001). The observed acute, pre-labour changes in the expression of the 31 genes during gestation warrant further investigation to elucidate their role in pregnancy. PMID:24391823

A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

PubMed Central

Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol; Scalcinati, Gionata; Fagerberg, Linn; Uhlén, Matthias; Nielsen, Jens

2012-01-01

RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data. PMID:22965124

Clinical significance of rare copy number variations in epilepsy: a case-control survey using microarray-based comparative genomic hybridization.

PubMed

Striano, Pasquale; Coppola, Antonietta; Paravidino, Roberta; Malacarne, Michela; Gimelli, Stefania; Robbiano, Angela; Traverso, Monica; Pezzella, Marianna; Belcastro, Vincenzo; Bianchi, Amedeo; Elia, Maurizio; Falace, Antonio; Gazzerro, Elisabetta; Ferlazzo, Edoardo; Freri, Elena; Galasso, Roberta; Gobbi, Giuseppe; Molinatto, Cristina; Cavani, Simona; Zuffardi, Orsetta; Striano, Salvatore; Ferrero, Giovanni Battista; Silengo, Margherita; Cavaliere, Maria Luigia; Benelli, Matteo; Magi, Alberto; Piccione, Maria; Dagna Bricarelli, Franca; Coviello, Domenico A; Fichera, Marco; Minetti, Carlo; Zara, Federico

2012-03-01

To perform an extensive search for genomic rearrangements by microarray-based comparative genomic hybridization in patients with epilepsy. Prospective cohort study. Epilepsy centers in Italy. Two hundred seventy-nine patients with unexplained epilepsy, 265 individuals with nonsyndromic mental retardation but no epilepsy, and 246 healthy control subjects were screened by microarray-based comparative genomic hybridization. Identification of copy number variations (CNVs) and gene enrichment. Rare CNVs occurred in 26 patients (9.3%) and 16 healthy control subjects (6.5%) (P = .26). The CNVs identified in patients were larger (P = .03) and showed higher gene content (P = .02) than those in control subjects. The CNVs larger than 1 megabase (P = .002) and including more than 10 genes (P = .005) occurred more frequently in patients than in control subjects. Nine patients (34.6%) among those harboring rare CNVs showed rearrangements associated with emerging microdeletion or microduplication syndromes. Mental retardation and neuropsychiatric features were associated with rare CNVs (P = .004), whereas epilepsy type was not. The CNV rate in patients with epilepsy and mental retardation or neuropsychiatric features is not different from that observed in patients with mental retardation only. Moreover, significant enrichment of genes involved in ion transport was observed within CNVs identified in patients with epilepsy. Patients with epilepsy show a significantly increased burden of large, rare, gene-rich CNVs, particularly when associated with mental retardation and neuropsychiatric features. The limited overlap between CNVs observed in the epilepsy group and those observed in the group with mental retardation only as well as the involvement of specific (ion channel) genes indicate a specific association between the identified CNVs and epilepsy. Screening for CNVs should be performed for diagnostic purposes preferentially in patients with epilepsy and mental retardation or neuropsychiatric features.

A Discovery Resource of Rare Copy Number Variations in Individuals with Autism Spectrum Disorder

PubMed Central

Prasad, Aparna; Merico, Daniele; Thiruvahindrapuram, Bhooma; Wei, John; Lionel, Anath C.; Sato, Daisuke; Rickaby, Jessica; Lu, Chao; Szatmari, Peter; Roberts, Wendy; Fernandez, Bridget A.; Marshall, Christian R.; Hatchwell, Eli; Eis, Peggy S.; Scherer, Stephen W.

2012-01-01

The identification of rare inherited and de novo copy number variations (CNVs) in human subjects has proven a productive approach to highlight risk genes for autism spectrum disorder (ASD). A variety of microarrays are available to detect CNVs, including single-nucleotide polymorphism (SNP) arrays and comparative genomic hybridization (CGH) arrays. Here, we examine a cohort of 696 unrelated ASD cases using a high-resolution one-million feature CGH microarray, the majority of which were previously genotyped with SNP arrays. Our objective was to discover new CNVs in ASD cases that were not detected by SNP microarray analysis and to delineate novel ASD risk loci via combined analysis of CGH and SNP array data sets on the ASD cohort and CGH data on an additional 1000 control samples. Of the 615 ASD cases analyzed on both SNP and CGH arrays, we found that 13,572 of 21,346 (64%) of the CNVs were exclusively detected by the CGH array. Several of the CGH-specific CNVs are rare in population frequency and impact previously reported ASD genes (e.g., NRXN1, GRM8, DPYD), as well as novel ASD candidate genes (e.g., CIB2, DAPP1, SAE1), and all were inherited except for a de novo CNV in the GPHN gene. A functional enrichment test of gene-sets in ASD cases over controls revealed nucleotide metabolism as a potential novel pathway involved in ASD, which includes several candidate genes for follow-up (e.g., DPYD, UPB1, UPP1, TYMP). Finally, this extensively phenotyped and genotyped ASD clinical cohort serves as an invaluable resource for the next step of genome sequencing for complete genetic variation detection. PMID:23275889

Automated detection and quantitation of bacterial RNA by using electrical microarrays.

PubMed

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.

Non-Small-Cell Lung Cancer Molecular Signatures Recapitulate Lung Developmental Pathways

PubMed Central

Borczuk, Alain C.; Gorenstein, Lyall; Walter, Kristin L.; Assaad, Adel A.; Wang, Liqun; Powell, Charles A.

2003-01-01

Current paradigms hold that lung carcinomas arise from pleuripotent stem cells capable of differentiation into one or several histological types. These paradigms suggest lung tumor cell ontogeny is determined by consequences of gene expression that recapitulate events important in embryonic lung development. Using oligonucleotide microarrays, we acquired gene profiles from 32 microdissected non-small-cell lung tumors. We determined the 100 top-ranked marker genes for adenocarcinoma, squamous cell, large cell, and carcinoid using nearest neighbor analysis. Results were validated by immunostaining for 11 selected proteins using a tissue microarray representing 80 tumors. Gene expression data of lung development were accessed from a publicly available dataset generated with the murine Mu11k genome microarray. Self-organized mapping identified two temporally distinct clusters of murine orthologues. Supervised clustering of lung development data showed large-cell carcinoma gene orthologues were in a cluster expressed in pseudoglandular and canalicular stages whereas adenocarcinoma homologues were predominantly in a cluster expressed later in the terminal sac and alveolar stages of murine lung development. Representative large-cell genes (E2F3, MYBL2, HDAC2, CDK4, PCNA) are expressed in the nucleus and are associated with cell cycle and proliferation. In contrast, adenocarcinoma genes are associated with lung-specific transcription pathways (SFTPB, TTF-1), cell adhesion, and signal transduction. In sum, non-small-cell lung tumors histology gene profiles suggest mechanisms relevant to ontogeny and clinical course. Adenocarcinoma genes are associated with differentiation and glandular formation whereas large-cell genes are associated with proliferation and differentiation arrest. The identification of developmentally regulated pathways active in tumorigenesis provides insights into lung carcinogenesis and suggests early steps may differ according to the eventual tumor morphology. PMID:14578194

H1N1 viral proteome peptide microarray predicts individuals at risk for H1N1 infection and segregates infection versus Pandemrix® vaccination

PubMed Central

Ambati, Aditya; Valentini, Davide; Montomoli, Emanuele; Lapini, Guilia; Biuso, Fabrizio; Wenschuh, Holger; Magalhaes, Isabelle; Maeurer, Markus

2015-01-01

A high content peptide microarray containing the entire influenza A virus [A/California/08/2009(H1N1)] proteome and haemagglutinin proteins from 12 other influenza A subtypes, including the haemagglutinin from the [A/South Carolina/1/1918(H1N1)] strain, was used to gauge serum IgG epitope signatures before and after Pandemrix® vaccination or H1N1 infection in a Swedish cohort during the pandemic influenza season 2009. A very narrow pattern of pandemic flu-specific IgG epitope recognition was observed in the serum from individuals who later contracted H1N1 infection. Moreover, the pandemic influenza infection generated IgG reactivity to two adjacent epitopes of the neuraminidase protein. The differential serum IgG recognition was focused on haemagglutinin 1 (H1) and restricted to classical antigenic sites (Cb) in both the vaccinated controls and individuals with flu infections. We further identified a novel epitope VEPGDKITFEATGNL on the Ca antigenic site (251–265) of the pandemic flu haemagglutinin, which was exclusively recognized in serum from individuals with previous vaccinations and never in serum from individuals with H1N1 infection (confirmed by RNA PCR analysis from nasal swabs). This epitope was mapped to the receptor-binding domain of the influenza haemagglutinin and could serve as a correlate of immune protection in the context of pandemic flu. The study shows that unbiased epitope mapping using peptide microarray technology leads to the identification of biologically and clinically relevant target structures. Most significantly an H1N1 infection induced a different footprint of IgG epitope recognition patterns compared with the pandemic H1N1 vaccine. PMID:25639813

The Changing Role of the Clinical Microbiology Laboratory in Defining Resistance in Gram-negatives.

PubMed

Endimiani, Andrea; Jacobs, Michael R

2016-06-01

The evolution of resistance in Gram-negatives has challenged the clinical microbiology laboratory to implement new methods for their detection. Multidrug-resistant strains present major challenges to conventional and new detection methods. More rapid pathogen identification and antimicrobial susceptibility testing have been developed for use directly on specimens, including fluorescence in situ hybridization tests, automated polymerase chain reaction systems, microarrays, mass spectroscopy, next-generation sequencing, and microfluidics. Review of these methods shows the advances that have been made in rapid detection of resistance in cultures, but limited progress in direct detection from specimens. Copyright © 2016 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Xiaoling

My research is on the synergistic regulation of PAI-1 by EGF and TGF-β. The mechanism of synergistic regulation of PAI-1 by EGF and TGF-β are addressed. Methods are described for effective identification of RNA accessible sites for antisense oligodexoxynucleotides (ODNs) and siRNA. In this study effective AS-ODN sequences for both Lcn2 and Bcl2 were identified by in vitro tiled microarray studies. Our results suggest that hybridization of ODN arrays to a target mRNA under physiological conditions might be used as a rapid and reliable in vitro method to accurately identify targets on mRNA molecules for effective antisense and potential siRNAmore » activity in vivo.« less

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

PubMed

Li, Chunquan; Han, Junwei; Yao, Qianlan; Zou, Chendan; Xu, Yanjun; Zhang, Chunlong; Shang, Desi; Zhou, Lingyun; Zou, Chaoxia; Sun, Zeguo; Li, Jing; Zhang, Yunpeng; Yang, Haixiu; Gao, Xu; Li, Xia

2013-05-01

Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.

Pathogen detection in milk samples by ligation detection reaction-mediated universal array method.

PubMed

Cremonesi, P; Pisoni, G; Severgnini, M; Consolandi, C; Moroni, P; Raschetti, M; Castiglioni, B

2009-07-01

This paper describes a new DNA chip, based on the use of a ligation detection reaction coupled to a universal array, developed to detect and analyze, directly from milk samples, microbial pathogens known to cause bovine, ovine, and caprine mastitis or to be responsible for foodborne intoxication or infection, or both. Probes were designed for the identification of 15 different bacterial groups: Staphylococcus aureus, Streptococcus agalactiae, nonaureus staphylococci, Streptococcus bovis, Streptococcus equi, Streptococcus canis, Streptococcus dysgalactiae, Streptococcus parauberis, Streptococcus uberis, Streptococcus pyogenes, Mycoplasma spp., Salmonella spp., Bacillus spp., Campylobacter spp., and Escherichia coli and related species. These groups were identified based on the 16S rRNA gene. For microarray validation, 22 strains from the American Type Culture Collection or other culture collections and 50 milk samples were tested. The results demonstrated high specificity, with sensitivity as low as 6 fmol. Moreover, the ligation detection reaction-universal array assay allowed for the identification of Mycoplasma spp. in a few hours, avoiding the long incubation times of traditional microbiological identification methods. The universal array described here is a versatile tool able to identify milk pathogens efficiently and rapidly.

cDNA microarray analysis of esophageal cancer: discoveries and prospects.

PubMed

Shimada, Yutaka; Sato, Fumiaki; Shimizu, Kazuharu; Tsujimoto, Gozoh; Tsukada, Kazuhiro

2009-07-01

Recent progress in molecular biology has revealed many genetic and epigenetic alterations that are involved in the development and progression of esophageal cancer. Microarray analysis has also revealed several genetic networks that are involved in esophageal cancer. However, clinical application of microarray techniques and use of microarray data have not yet occurred. In this review, we focus on the recent developments and problems with microarray analysis of esophageal cancer.

Manufacturing of microarrays.

PubMed

Petersen, David W; Kawasaki, Ernest S

2007-01-01

DNA microarray technology has become a powerful tool in the arsenal of the molecular biologist. Capitalizing on high precision robotics and the wealth of DNA sequences annotated from the genomes of a large number of organisms, the manufacture of microarrays is now possible for the average academic laboratory with the funds and motivation. Microarray production requires attention to both biological and physical resources, including DNA libraries, robotics, and qualified personnel. While the fabrication of microarrays is a very labor-intensive process, production of quality microarrays individually tailored on a project-by-project basis will help researchers shed light on future scientific questions.

The Longhorn Array Database (LAD): An Open-Source, MIAME compliant implementation of the Stanford Microarray Database (SMD)

PubMed Central

Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R

2003-01-01

Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. PMID:12930545

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

PubMed Central

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

A Java-based tool for the design of classification microarrays.

PubMed

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.

THE ABRF MARG MICROARRAY SURVEY 2005: TAKING THE PULSE ON THE MICROARRAY FIELD

EPA Science Inventory

Over the past several years microarray technology has evolved into a critical component of any discovery based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a pr...

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.

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%.

Protein microarray with horseradish peroxidase chemiluminescence for quantification of serum α-fetoprotein.

PubMed

Zhao, Yuanshun; Zhang, Yonghong; Lin, Dongdong; Li, Kang; Yin, Chengzeng; Liu, Xiuhong; Jin, Boxun; Sun, Libo; Liu, Jinhua; Zhang, Aiying; Li, Ning

2015-10-01

To develop and evaluate a protein microarray assay with horseradish peroxidase (HRP) chemiluminescence for quantification of α-fetoprotein (AFP) in serum from patients with hepatocellular carcinoma (HCC). A protein microarray assay for AFP was developed. Serum was collected from patients with HCC and healthy control subjects. AFP was quantified using protein microarray and enzyme-linked immunosorbent assay (ELISA). Serum AFP concentrations determined via protein microarray were positively correlated (r = 0.973) with those determined via ELISA in patients with HCC (n = 60) and healthy control subjects (n = 30). Protein microarray showed 80% sensitivity and 100% specificity for HCC diagnosis. ELISA had 83.3% sensitivity and 100% specificity. Protein microarray effectively distinguished between patients with HCC and healthy control subjects (area under ROC curve 0.974; 95% CI 0.000, 1.000). Protein microarray is a rapid, simple and low-cost alternative to ELISA for detecting AFP in human serum. © The Author(s) 2015.

Automated detection system of single nucleotide polymorphisms using two kinds of functional magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Liu, Hongna; Li, Song; Wang, Zhifei; Li, Zhiyang; Deng, Yan; Wang, Hua; Shi, Zhiyang; He, Nongyue

2008-11-01

Single nucleotide polymorphisms (SNPs) comprise the most abundant source of genetic variation in the human genome wide codominant SNPs identification. Therefore, large-scale codominant SNPs identification, especially for those associated with complex diseases, has induced the need for completely high-throughput and automated SNP genotyping method. Herein, we present an automated detection system of SNPs based on two kinds of functional magnetic nanoparticles (MNPs) and dual-color hybridization. The amido-modified MNPs (NH 2-MNPs) modified with APTES were used for DNA extraction from whole blood directly by electrostatic reaction, and followed by PCR, was successfully performed. Furthermore, biotinylated PCR products were captured on the streptavidin-coated MNPs (SA-MNPs) and interrogated by hybridization with a pair of dual-color probes to determine SNP, then the genotype of each sample can be simultaneously identified by scanning the microarray printed with the denatured fluorescent probes. This system provided a rapid, sensitive and highly versatile automated procedure that will greatly facilitate the analysis of different known SNPs in human genome.

Avatar DNA Nanohybrid System in Chip-on-a-Phone

NASA Astrophysics Data System (ADS)

Park, Dae-Hwan; Han, Chang Jo; Shul, Yong-Gun; Choy, Jin-Ho

2014-05-01

Long admired for informational role and recognition function in multidisciplinary science, DNA nanohybrids have been emerging as ideal materials for molecular nanotechnology and genetic information code. Here, we designed an optical machine-readable DNA icon on microarray, Avatar DNA, for automatic identification and data capture such as Quick Response and ColorZip codes. Avatar icon is made of telepathic DNA-DNA hybrids inscribed on chips, which can be identified by camera of smartphone with application software. Information encoded in base-sequences can be accessed by connecting an off-line icon to an on-line web-server network to provide message, index, or URL from database library. Avatar DNA is then converged with nano-bio-info-cogno science: each building block stands for inorganic nanosheets, nucleotides, digits, and pixels. This convergence could address item-level identification that strengthens supply-chain security for drug counterfeits. It can, therefore, provide molecular-level vision through mobile network to coordinate and integrate data management channels for visual detection and recording.

Avatar DNA Nanohybrid System in Chip-on-a-Phone

PubMed Central

Park, Dae-Hwan; Han, Chang Jo; Shul, Yong-Gun; Choy, Jin-Ho

2014-01-01

Long admired for informational role and recognition function in multidisciplinary science, DNA nanohybrids have been emerging as ideal materials for molecular nanotechnology and genetic information code. Here, we designed an optical machine-readable DNA icon on microarray, Avatar DNA, for automatic identification and data capture such as Quick Response and ColorZip codes. Avatar icon is made of telepathic DNA-DNA hybrids inscribed on chips, which can be identified by camera of smartphone with application software. Information encoded in base-sequences can be accessed by connecting an off-line icon to an on-line web-server network to provide message, index, or URL from database library. Avatar DNA is then converged with nano-bio-info-cogno science: each building block stands for inorganic nanosheets, nucleotides, digits, and pixels. This convergence could address item-level identification that strengthens supply-chain security for drug counterfeits. It can, therefore, provide molecular-level vision through mobile network to coordinate and integrate data management channels for visual detection and recording. PMID:24824876

[Pharmacogenomics in neuro-oncology].

PubMed

Riese-Jorda, H H; Baez, J M

Chemotherapy protocols for treatment of brain tumors use toxic molecules for killing cancer cells in a similar way that protocols for treating other cancers. Therefore, secondary effects and poor response are the major handicaps. Technological developments based on pharmacogenomics and pharmacoproteomics will predict response and toxicity giving rise to a personalized medicine. However, there are only few studies that correlate chemotherapeutical molecules for brain tumor treatment and prediction of response and toxicity. The development of new technologies based on high-density microarrays allows the progressive identification of genes whose presence will predict the efficacy of therapeutic protocols. Once identified, specific equipments based on low-density arrays will detect exclusively in an easy and fast way the presence of genes in order to predict patient's response and avoid toxicity. Other more sophisticated techniques at present still at an experimental step based on proteomics as MALDI (Matrix-Assisted Laser Desorption Ionization) and SELDI (Surface-Enhanced Laser Desorption Ionization) will allow the identification of proteins that could predict response and toxicity.

Identification of apoptosis-related PLZF target genes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernardo, Maria Victoria; Yelo, Estefania; Gimeno, Lourdes

2007-07-27

The PLZF gene encodes a BTB/POZ-zinc finger-type transcription factor, involved in physiological development, proliferation, differentiation, and apoptosis. In this paper, we investigate proliferation, survival, and gene expression regulation in stable clones from the human haematopoietic K562, DG75, and Jurkat cell lines with inducible expression of PLZF. In Jurkat cells, but not in K562 and DG75 cells, PLZF induced growth suppression and apoptosis in a cell density-dependent manner. Deletion of the BTB/POZ domain of PLZF abrogated growth suppression and apoptosis. PLZF was expressed with a nuclear speckled pattern distinctively in the full-length PLZF-expressing Jurkat clones, suggesting that the nuclear speckled localizationmore » is required for PLZF-induced apoptosis. By microarray analysis, we identified that the apoptosis-inducer TP53INP1, ID1, and ID3 genes were upregulated, and the apoptosis-inhibitor TERT gene was downregulated. The identification of apoptosis-related PLZF target genes may have biological and clinical relevance in cancer typified by altered PLZF expression.« less

ROKU: a novel method for identification of tissue-specific genes.

PubMed

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-06-12

One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes.

Current status and future perspectives on molecular and serological methods in diagnostic mycology.

PubMed

Lau, Anna; Chen, Sharon; Sleiman, Sue; Sorrell, Tania

2009-11-01

Invasive fungal infections are an important cause of infectious morbidity. Nonculture-based methods are increasingly used for rapid, accurate diagnosis to improve patient outcomes. New and existing DNA amplification platforms have high sensitivity and specificity for direct detection and identification of fungi in clinical specimens. Since laboratories are increasingly reliant on DNA sequencing for fungal identification, measures to improve sequence interpretation should support validation of reference isolates and quality control in public gene repositories. Novel technologies (e.g., isothermal and PNA FISH methods), platforms enabling high-throughput analyses (e.g., DNA microarrays and Luminex xMAP) and/or commercial PCR assays warrant further evaluation for routine diagnostic use. Notwithstanding the advantages of molecular tests, serological assays remain clinically useful for patient management. The serum Aspergillus galactomannan test has been incorporated into diagnostic algorithms of invasive aspergillosis. Both the galactomannan and the serum beta-D-glucan test have value for diagnosing infection and monitoring therapeutic response.

The Microarray Revolution: Perspectives from Educators

ERIC Educational Resources Information Center

Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

2004-01-01

In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

Recent progress in making protein microarray through BioLP

NASA Astrophysics Data System (ADS)

Yang, Rusong; Wei, Lian; Feng, Ying; Li, Xiujian; Zhou, Quan

2017-02-01

Biological laser printing (BioLP) is a promising biomaterial printing technique. It has the advantage of high resolution, high bioactivity, high printing frequency and small transported liquid amount. In this paper, a set of BioLP device is design and made, and protein microarrays are printed by this device. It's found that both laser intensity and fluid layer thickness have an influence on the microarrays acquired. Besides, two kinds of the fluid layer coating methods are compared, and the results show that blade coating method is better than well-coating method in BioLP. A microarray of 0.76pL protein microarray and a "NUDT" patterned microarray are printed to testify the printing ability of BioLP.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

EPA Science Inventory

The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray

PubMed Central

Ramirez, Lisa S.; Wang, Jun

2016-01-01

Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this report, we renovate the antibody microarray technology by using a novel approach for manufacturing and by introducing new features. The fabrication of our high-density antibody microarray is accomplished through perpendicularly oriented flow-patterning of single stranded DNAs and subsequent conversion mediated by DNA-antibody conjugates. This protocol outlines the critical steps in flow-patterning DNA, producing and purifying DNA-antibody conjugates, and assessing the quality of the fabricated microarray. The uniformity and sensitivity are comparable with conventional microarrays, while our microarray fabrication does not require the assistance of an array printer and can be performed in most research laboratories. The other major advantage is that the size of our microarray units is 10 times smaller than that of printed arrays, offering the unique capability of analyzing functional proteins from single cells when interfacing with generic microchip designs. This barcode technology can be widely employed in biomarker detection, cell signaling studies, tissue engineering, and a variety of clinical applications. PMID:26780370

Microarray platform for omics analysis

NASA Astrophysics Data System (ADS)

Mecklenburg, Michael; Xie, Bin

2001-09-01

Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

On-Chip Synthesis of Protein Microarrays from DNA Microarrays Via Coupled In Vitro Transcription and Translation for Surface Plasmon Resonance Imaging Biosensor Applications

PubMed Central

Seefeld, Ting H.; Halpern, Aaron R.; Corn, Robert M.

2012-01-01

Protein microarrays are fabricated from double-stranded DNA (dsDNA) microarrays by a one-step, multiplexed enzymatic synthesis in an on-chip microfluidic format and then employed for antibody biosensing measurements with surface plasmon resonance imaging (SPRI). A microarray of dsDNA elements (denoted as generator elements) that encode either a His-tagged green fluorescent protein (GFP) or a His-tagged luciferase protein is utilized to create multiple copies of messenger RNA (mRNA) in a surface RNA polymerase reaction; the mRNA transcripts are then translated into proteins by cell-free protein synthesis in a microfluidic format. The His-tagged proteins diffuse to adjacent Cu(II)-NTA microarray elements (denoted as detector elements) and are specifically adsorbed. The net result is the on-chip, cell-free synthesis of a protein microarray that can be used immediately for SPRI protein biosensing. The dual element format greatly reduces any interference from the nonspecific adsorption of enzyme or proteins. SPRI measurements for the detection of the antibodies anti-GFP and anti-luciferase were used to verify the formation of the protein microarray. This convenient on-chip protein microarray fabrication method can be implemented for multiplexed SPRI biosensing measurements in both clinical and research applications. PMID:22793370

Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

PubMed

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.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma.

PubMed

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong; Li, Ning

2016-12-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC ( n = 65) and healthy control subjects ( n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma

PubMed Central

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong

2016-01-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC (n = 65) and healthy control subjects (n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC. PMID:27885040

Genotyping microarray: Mutation screening in Spanish families with autosomal dominant retinitis pigmentosa

PubMed Central

García-Hoyos, María; Cortón, Marta; Ávila-Fernández, Almudena; Riveiro-Álvarez, Rosa; Giménez, Ascensión; Hernan, Inma; Carballo, Miguel; Ayuso, Carmen

2012-01-01

Purpose Presently, 22 genes have been described in association with autosomal dominant retinitis pigmentosa (adRP); however, they explain only 50% of all cases, making genetic diagnosis of this disease difficult and costly. The aim of this study was to evaluate a specific genotyping microarray for its application to the molecular diagnosis of adRP in Spanish patients. Methods We analyzed 139 unrelated Spanish families with adRP. Samples were studied by using a genotyping microarray (adRP). All mutations found were further confirmed with automatic sequencing. Rhodopsin (RHO) sequencing was performed in all negative samples for the genotyping microarray. Results The adRP genotyping microarray detected the mutation associated with the disease in 20 of the 139 families with adRP. As in other populations, RHO was found to be the most frequently mutated gene in these families (7.9% of the microarray genotyped families). The rate of false positives (microarray results not confirmed with sequencing) and false negatives (mutations in RHO detected with sequencing but not with the genotyping microarray) were established, and high levels of analytical sensitivity (95%) and specificity (100%) were found. Diagnostic accuracy was 15.1%. Conclusions The adRP genotyping microarray is a quick, cost-efficient first step in the molecular diagnosis of Spanish patients with adRP. PMID:22736939

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies.

PubMed

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-09-20

High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option.GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike.

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

PubMed Central

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-01-01

Background High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike. PMID:16987406

Alterations in TNF- and IL-related gene expression in space-flown WI38 human fibroblasts

NASA Technical Reports Server (NTRS)

Semov, Alexandre; Semova, Nathalia; Lacelle, Chantale; Marcotte, Richard; Petroulakis, Emmanuel; Proestou, Gregory; Wang, Eugenia

2002-01-01

Spaceflight, just like aging, causes profound changes in musculoskeletal parameters, which result in decreased bone density and muscular weakness. As these conditions decrease our ability to conduct long-term manned space missions, and increase bone frailty in the elderly, the identification of genes responsible for the apparition of these physiological changes will be of great benefit. Thus, we developed and implemented a new microarray approach to investigate the changes in normal WI38 human fibroblast gene expression that arise as a consequence of space flight. Using our microarray, we identified changes in the level of expression of 10 genes, belonging to either the tumor necrosis factor- (TNF) or interleukin- (IL) related gene families in fibroblasts when WI38 cells exposed to microgravity during the STS-93 Space Shuttle mission were compared with ground controls. The genes included two ligands from the TNF superfamily, TWEAK and TNFSF15; two TNF receptor-associated proteins, NSMAF and PTPN13; three TNF-inducible genes, ABC50, PTX3, and SCYA13; TNF-alpha converting enzyme, IL-1 receptor antagonist, and IL-15 receptor alpha chain. Most of these are involved in either the regulation of bone density, and as such the development of spaceflight osteopenia, or in the development of proinflammatory status.

Exploring new packaging and delivery options for the immunization supply chain.

PubMed

Zehrung, Darin; Jarrahian, Courtney; Giersing, Birgitte; Kristensen, Debra

2017-04-19

A variety of vaccine packaging and delivery technologies may benefit the immunization supply chain. These include alternative primary packaging, such as blow-fill-seal polymer containers, and novel delivery technologies, such intradermal delivery devices, microarray patches, and sublingual formulations of vaccines, and others in development. The potential timeline to availability of these technologies varies and depends on their stage of development and the type of data necessary to achieve licensure. Some new delivery devices are anticipated to be introduced in 2017, such as intradermal devices for delivery of inactivated poliovirus vaccine to stretch vaccine supplies due to a supply limitation. Other new technologies requiring vaccine reformulation, such as microarray patches and sublingual vaccines, may become available in the long term (2021 and beyond). Development of many new technologies requires partnership between vaccine and technology manufacturers and identification of the applicable regulatory pathway. Interaction with public-sector stakeholders early on (through engagement with forums such as the World Health Organization's Immunization Practices Advisory Committee Delivery Technologies Working Group) is important to ensure suitability for immunization program use. Key considerations for programmatic suitability of a new vaccine, packaging, and delivery device include cold chain volume, costs, and health impact. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Microarray analysis of Arabidopsis WRKY33 mutants in response to the necrotrophic fungus Botrytis cinerea

PubMed Central

Sham, Arjun; Moustafa, Khaled; Al-Shamisi, Shamma; Alyan, Sofyan; Iratni, Rabah

2017-01-01

The WRKY33 transcription factor was reported for resistance to the necrotrophic fungus Botrytis cinerea. Using microarray-based analysis, we compared Arabidopsis WRKY33 overexpressing lines and wrky33 mutant that showed altered susceptibility to B. cinerea with their corresponding wild-type plants. In the wild-type, about 1660 genes (7% of the transcriptome) were induced and 1054 genes (5% of the transcriptome) were repressed at least twofold at early stages of inoculation with B. cinerea, confirming previous data of the contribution of these genes in B. cinerea resistance. In Arabidopsis wild-type plant infected with B. cinerea, the expressions of the differentially expressed genes encoding for proteins and metabolites involved in pathogen defense and non-defense responses, seem to be dependent on a functional WRKY33 gene. The expression profile of 12-oxo-phytodienoic acid- and phytoprostane A1-treated Arabidopsis plants in response to B. cinerea revealed that cyclopentenones can also modulate WRKY33 regulation upon inoculation with B. cinerea. These results support the role of electrophilic oxylipins in mediating plant responses to B. cinerea infection through the TGA transcription factor. Future directions toward the identification of the molecular components in cyclopentenone signaling will elucidate the novel oxylipin signal transduction pathways in plant defense. PMID:28207847

SLEPR: A Sample-Level Enrichment-Based Pathway Ranking Method — Seeking Biological Themes through Pathway-Level Consistency

PubMed Central

Yi, Ming; Stephens, Robert M.

2008-01-01

Analysis of microarray and other high throughput data often involves identification of genes consistently up or down-regulated across samples as the first step in extraction of biological meaning. This gene-level paradigm can be limited as a result of valid sample fluctuations and biological complexities. In this report, we describe a novel method, SLEPR, which eliminates this limitation by relying on pathway-level consistencies. Our method first selects the sample-level differentiated genes from each individual sample, capturing genes missed by other analysis methods, ascertains the enrichment levels of associated pathways from each of those lists, and then ranks annotated pathways based on the consistency of enrichment levels of individual samples from both sample classes. As a proof of concept, we have used this method to analyze three public microarray datasets with a direct comparison with the GSEA method, one of the most popular pathway-level analysis methods in the field. We found that our method was able to reproduce the earlier observations with significant improvements in depth of coverage for validated or expected biological themes, but also produced additional insights that make biological sense. This new method extends existing analyses approaches and facilitates integration of different types of HTP data. PMID:18818771

Analysis of transcriptional responses in the mouse dorsal striatum following acute 3,4-methylenedioxymethamphetamine (ecstasy): identification of extracellular signal-regulated kinase-controlled genes

PubMed Central

Salzmann, Julie; Canestrelli, Corinne; Noble, Florence; Marie-Claire, Cynthia

2006-01-01

3,4-methylenedioxymethamphetamine (MDMA, ecstasy), a widely used recreational drug with psychoactive properties, induces both serotonin (5-HT) and dopamine (DA) release in the brain. However, little is known about its intracellular effects. We previously showed that MDMA rewarding effects in mice were dependent upon ERK activation and that dorsal striatum was a critical region for mediating ERK-dependent Egr1 MDMA-induced transcription. Here, we extend these findings by showing that MDMA is indeed able to activate ERK within this structure. To identify genes regulated by acute MDMA in the mice dorsal striatum, and selectively controlled by this kinase, we performed microarray experiments by using a selective inhibitor of ERK activation, SL327. Of the ~24,000 genes from the microarray, 27 showed altered expression after exposure to MDMA, and among these, 59% were partially or totally inhibited by SL327 pretreatment. Our results showed that the genes regulated by MDMA encode proteins that belong to transcription factors family, signalling pathways (phosphatases, cytoskeleton regulation), and synaptic functions. These early changes, and especially those controlled by ERK activation might play significant roles in the expression of many of the behaviours that occur following MDMA taking. PMID:16289835

Identification of the Key Genes and Pathways in Esophageal Carcinoma.

PubMed

Su, Peng; Wen, Shiwang; Zhang, Yuefeng; Li, Yong; Xu, Yanzhao; Zhu, Yonggang; Lv, Huilai; Zhang, Fan; Wang, Mingbo; Tian, Ziqiang

2016-01-01

Objective . Esophageal carcinoma (EC) is a frequently common malignancy of gastrointestinal cancer in the world. This study aims to screen key genes and pathways in EC and elucidate the mechanism of it. Methods . 5 microarray datasets of EC were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) were screened by bioinformatics analysis. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network construction were performed to obtain the biological roles of DEGs in EC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression level of DEGs in EC. Results . A total of 1955 genes were filtered as DEGs in EC. The upregulated genes were significantly enriched in cell cycle and the downregulated genes significantly enriched in Endocytosis. PPI network displayed CDK4 and CCT3 were hub proteins in the network. The expression level of 8 dysregulated DEGs including CDK4, CCT3, THSD4, SIM2, MYBL2, CENPF, CDCA3, and CDKN3 was validated in EC compared to adjacent nontumor tissues and the results were matched with the microarray analysis. Conclusion . The significantly DEGs including CDK4, CCT3, THSD4, and SIM2 may play key roles in tumorigenesis and development of EC involved in cell cycle and Endocytosis.

Microarrays--new possibilities for detecting biological factors hazardous for humans and animals, and for use in environmental protection.

PubMed

Mirski, Tomasz; Bartoszcze, Michał; Bielawska-Drózd, Agata; Gryko, Romuald; Kocik, Janusz; Niemcewicz, Marcin; Chomiczewski, Krzysztof

2016-01-01

Both the known biological agents that cause infectious diseases, as well as modified (ABF-Advanced Biological Factors) or new, emerging agents pose a significant diagnostic problem using previously applied methods, both classical, as well as based on molecular biology methods. The latter, such as PCR and real-time PCR, have significant limitations, both quantitative (low capacity), and qualitative (limited number of targets). The article discusses the results of studies on using the microarray method for the identification of viruses (e.g. Orthopoxvirus group, noroviruses, influenza A and B viruses, rhino- and enteroviruses responsible for the FRI (Febrile Respiratory Illness), European bunyaviruses, and SARS-causing viruses), and bacteria (Mycobacterium spp., Yersinia spp., Campylobacter spp., Streptococcus pneumoniae, Salmonella typhi, Salmonella enterica, Staphylococcus aureus, Neisseria meningitidis, Clostridium difficile , Helicobacter pylori), including multiple antibiotic-resistant strains. The method allows for the serotyping and genotyping of bacteria, and is useful in the diagnosis of genetically modified agents. It allows the testing of thousands of genes in one experiment. In addition to diagnosis, it is applicable for gene expression studies, analysis of the function of genes, microorganisms virulence, and allows the detection of even single mutations. The possibility of its operational application in epidemiological surveillance, and in the detection of disease outbreak agents is demonstrated.

Identification of differentially expressed genes affecting hair and cashmere growth in the Laiwu black goat by microarray.

PubMed

Zhao, Jinshan; Li, Hegang; Liu, Kaidong; Zhang, Baoxun; Li, Peipei; He, Jianning; Cheng, Ming; De, Wei; Liu, Jifeng; Zhao, Yaofeng; Yang, Lihua; Liu, Nan

2016-10-01

Goats are an important source of fibers. In the present study microarray technology was used to investigate the potential genes primarily involved in hair and cashmere growth in the Laiwu black goat. A total of 655 genes differentially expressed in body (hair‑growing) and groin (hairless) skin were identified, and their potential association with hair and cashmere growth was analyzed. The majority of genes associated with hair growth regulation could be assigned to intracellular, intracellular organelle, membrane‑bound vesicle, cytoplasmic vesicle, pattern binding, heparin binding, polysaccharide binding, glycosaminoglycan binding and cytoplasmic membrane‑bound vesicle categories. Numerous genes upregulated in body compared with groin skin contained common motifs for nuclear factor 1A, Yi, E2 factor (E2F) and cyclic adenosine monophosphate response element binding (CREB)/CREBβ binding sites in their promoter region. The promoter region of certain genes downregulated in body compared with groin skin contained three common regions with LF‑A1, Yi, E2F, Collier/Olfactory‑1/early B‑cell factor 1, peroxisome proliferator‑activated receptor α or U sites. Thus, the present study identified molecules in the cashmere‑bearing skin area of the Laiwu black goat, which may contribute to hair and cashmere traits.

Gene expression profiling to characterize sediment toxicity – a pilot study using Caenorhabditis elegans whole genome microarrays

PubMed Central

Menzel, Ralph; Swain, Suresh C; Hoess, Sebastian; Claus, Evelyn; Menzel, Stefanie; Steinberg, Christian EW; Reifferscheid, Georg; Stürzenbaum, Stephen R

2009-01-01

Background Traditionally, toxicity of river sediments is assessed using whole sediment tests with benthic organisms. The challenge, however, is the differentiation between multiple effects caused by complex contaminant mixtures and the unspecific toxicity endpoints such as survival, growth or reproduction. The use of gene expression profiling facilitates the identification of transcriptional changes at the molecular level that are specific to the bio-available fraction of pollutants. Results In this pilot study, we exposed the nematode Caenorhabditis elegans to three sediments of German rivers with varying (low, medium and high) levels of heavy metal and organic contamination. Beside chemical analysis, three standard bioassays were performed: reproduction of C. elegans, genotoxicity (Comet assay) and endocrine disruption (YES test). Gene expression was profiled using a whole genome DNA-microarray approach to identify overrepresented functional gene categories and derived cellular processes. Disaccharide and glycogen metabolism were found to be affected, whereas further functional pathways, such as oxidative phosphorylation, ribosome biogenesis, metabolism of xenobiotics, aging and several developmental processes were found to be differentially regulated only in response to the most contaminated sediment. Conclusion This study demonstrates how ecotoxicogenomics can identify transcriptional responses in complex mixture scenarios to distinguish different samples of river sediments. PMID:19366437

Myeloid leukemia factor-1 is a novel modulator of neonatal rat cardiomyocyte proliferation.

PubMed

Rangrez, Ashraf Yusuf; Pott, Jost; Kluge, Annika; Frauen, Robert; Stiebeling, Katharina; Hoppe, Phillip; Sossalla, Samuel; Frey, Norbert; Frank, Derk

2017-04-01

The present study focuses on the identification of the gene expression profile of neonatal rat cardiomyocytes (NRVCMs) after dynamic mechanical stretch through microarrays of RNA isolated from cells stretched for 2, 6 or 24h. In this analysis, myeloid leukemia factor-1 (MLF1) was found to be significantly downregulated during the course of stretch. We found that MLF1 is highly expressed in the heart, however, its cardiac function is unknown yet. In line with microarray data, MLF1 was profoundly downregulated in in vivo mouse models of cardiomyopathy, and also significantly reduced in the hearts of human patients with dilated cardiomyopathy. Our data indicates that the overexpression of MLF1 in NRVCMs inhibited cell proliferation while augmenting apoptosis. Conversely, knockdown of MLF1 protected NRVCMs from apoptosis and promoted cell proliferation. Moreover, we found that knockdown of MLF1 protected NRVCMs from hypoxia-induced cell death. The observed accelerated apoptosis is attributed to the activation of caspase-3/-7/PARP-dependent apoptotic signaling and upregulation of p53. Most interestingly, MLF1 knockdown significantly upregulated the expression of D cyclins suggesting its possible role in cyclin-dependent cell proliferation. Taken together, we, for the first time, identified an important role for MLF1 in NRVCM proliferation. Copyright © 2017 Elsevier B.V. All rights reserved.

Analyzing Kernel Matrices for the Identification of Differentially Expressed Genes

PubMed Central

Xia, Xiao-Lei; Xing, Huanlai; Liu, Xueqin

2013-01-01

One of the most important applications of microarray data is the class prediction of biological samples. For this purpose, statistical tests have often been applied to identify the differentially expressed genes (DEGs), followed by the employment of the state-of-the-art learning machines including the Support Vector Machines (SVM) in particular. The SVM is a typical sample-based classifier whose performance comes down to how discriminant samples are. However, DEGs identified by statistical tests are not guaranteed to result in a training dataset composed of discriminant samples. To tackle this problem, a novel gene ranking method namely the Kernel Matrix Gene Selection (KMGS) is proposed. The rationale of the method, which roots in the fundamental ideas of the SVM algorithm, is described. The notion of ''the separability of a sample'' which is estimated by performing -like statistics on each column of the kernel matrix, is first introduced. The separability of a classification problem is then measured, from which the significance of a specific gene is deduced. Also described is a method of Kernel Matrix Sequential Forward Selection (KMSFS) which shares the KMGS method's essential ideas but proceeds in a greedy manner. On three public microarray datasets, our proposed algorithms achieved noticeably competitive performance in terms of the B.632+ error rate. PMID:24349110

Identification of a transcriptional signature for the wound healing continuum

PubMed Central

Peake, Matthew A; Caley, Mathew; Giles, Peter J; Wall, Ivan; Enoch, Stuart; Davies, Lindsay C; Kipling, David; Thomas, David W; Stephens, Phil

2014-01-01

There is a spectrum/continuum of adult human wound healing outcomes ranging from the enhanced (nearly scarless) healing observed in oral mucosa to scarring within skin and the nonhealing of chronic skin wounds. Central to these outcomes is the role of the fibroblast. Global gene expression profiling utilizing microarrays is starting to give insight into the role of such cells during the healing process, but no studies to date have produced a gene signature for this wound healing continuum. Microarray analysis of adult oral mucosal fibroblast (OMF), normal skin fibroblast (NF), and chronic wound fibroblast (CWF) at 0 and 6 hours post-serum stimulation was performed. Genes whose expression increases following serum exposure in the order OMF < NF < CWF are candidates for a negative/impaired healing phenotype (the dysfunctional healing group), whereas genes with the converse pattern are potentially associated with a positive/preferential healing phenotype (the enhanced healing group). Sixty-six genes in the enhanced healing group and 38 genes in the dysfunctional healing group were identified. Overrepresentation analysis revealed pathways directly and indirectly associated with wound healing and aging and additional categories associated with differentiation, development, and morphogenesis. Knowledge of this wound healing continuum gene signature may in turn assist in the therapeutic assessment/treatment of a patient's wounds. PMID:24844339

Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

PubMed

Bhanot, Gyan; Alexe, Gabriela; Levine, Arnold J; Stolovitzky, Gustavo

2005-01-01

A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines the results of several machine learning tools trained on raw and pattern data to produce an accurate meta-classifier. We illustrate and validate our method by applying it to gene expression datasets: the oligonucleotide HuGeneFL microarray dataset of Shipp et al. (www.genome.wi.mit.du/MPR/lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our pattern-based meta-classification technique achieves higher predictive accuracies than each of the individual classifiers , is robust against data perturbations and provides subsets of related predictive genes. Our techniques predict that combinations of some genes in the p53 pathway are highly predictive of phenotype. In particular, we find that in 80% of DLBCL cases the mRNA level of at least one of the three genes p53, PLK1 and CDK2 is elevated, while in 80% of FL cases, the mRNA level of at most one of them is elevated.

Fabrication of molecularly imprinted polymer microarray on a chip by mid-infrared laser pulse initiated polymerisation.

PubMed

Henry, Olivier Y F; Piletsky, Sergey A; Cullen, David C

2008-07-15

The possibility to assess several functional polymeric materials in parallel in a microchip format could find a wide range of applications in sensing, combinatorial and high-throughput screening. However several factors, inherent to the nature of material polymerisation have limited such development. We here report an innovative fabrication approach for the elaboration of polymer microarrays bearing polymer dots typically 300 microm in diameter fabricated in situ on a glass cover slip via CO(2) laser pulse initiated polymerisation, as well as initial results on the identification of a suitable monomer composition for the molecular imprinting of dansyl-L-phenylalanine as a proof-of-concept example. A combination of methacrylic acid and 2-vinylpyridine showed the largest affinity to dansyl-L-phenylalanine which agreed with the existing literature and the results were further confirmed by HPLC. Finally, a sensor chip bearing both non-imprinted as well as imprinted polymers was also prepared in order to prove the suitability of this fabrication approach for the elaboration of MIP based sensors. The assay consisted in a simple dip-and-read step and the sensing system was able to discriminate between the l and d enantiomers of dansylphenylalanine with an imprinting factor of 1.6.

Methods for genotyping verotoxin-producing Escherichia coli.

PubMed

Karama, M; Gyles, C L

2010-12-01

Verotoxin-producing Escherichia coli (VTEC) is annually incriminated in more than 100,000 cases of enteric foodborne human disease and in losses amounting to $US 2.5 billion every year. A number of genotyping methods have been developed to track VTEC infections and determine diversity and evolutionary relationships among these microorganisms. These methods have facilitated monitoring and surveillance of foodborne VTEC outbreaks and early identification of outbreaks or clusters of outbreaks. Pulsed-field gel electrophoresis (PFGE) has been used extensively to track and differentiate VTEC because of its high discriminatory power, reproducibility and ease of standardization. Multiple-locus variable-number tandem-repeats analysis (MLVA) and microarrays are the latest genotyping methods that have been applied to discriminate VTEC. MLVA, a simpler and less expensive method, is proving to have a discriminatory power comparable to that of PFGE. Microarrays are successfully being applied to differentiate VTEC and make inferences on genome diversification. Novel methods that are being evaluated for subtyping VTEC include the detection of single nucleotide polymorphisms and optical mapping. This review discusses the principles, applications, advantages and disadvantages of genotyping methods that have been used to differentiate VTEC strains. These methods have been mainly used to differentiate strains of O157:H7 VTEC and to a lesser extent non-O157 VTEC. © 2009 Blackwell Verlag GmbH.

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

PubMed

Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Microarrays in brain research: the good, the bad and the ugly.

PubMed

Mirnics, K

2001-06-01

Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role

Simplified Identification of mRNA or DNA in Whole Cells

NASA Technical Reports Server (NTRS)

Almeida, Eduardo; Kadambi, Geeta

2007-01-01

A recently invented method of detecting a selected messenger ribonucleic acid (mRNA) or deoxyribonucleic acid (DNA) sequence offers two important advantages over prior such methods: it is simpler and can be implemented by means of compact equipment. The simplification and miniaturization achieved by this invention are such that this method is suitable for use outside laboratories, in field settings in which space and power supplies may be limited. The present method is based partly on hybridization of nucleic acid, which is a powerful technique for detection of specific complementary nucleic acid sequences and is increasingly being used for detection of changes in gene expression in microarrays containing thousands of gene probes.

Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

PubMed

Mathur, Sunil; Sadana, Ajit

2015-12-01

We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

PubMed

Saito, Kazuki; Hirai, Masami Y; Yonekura-Sakakibara, Keiko

2008-01-01

Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

PubMed

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.

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

PubMed Central

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Plastic Polymers for Efficient DNA Microarray Hybridization: Application to Microbiological Diagnostics▿

PubMed Central

Zhao, Zhengshan; Peytavi, Régis; Diaz-Quijada, Gerardo A.; Picard, Francois J.; Huletsky, Ann; Leblanc, Éric; Frenette, Johanne; Boivin, Guy; Veres, Teodor; Dumoulin, Michel M.; Bergeron, Michel G.

2008-01-01

Fabrication of microarray devices using traditional glass slides is not easily adaptable to integration into microfluidic systems. There is thus a need for the development of polymeric materials showing a high hybridization signal-to-background ratio, enabling sensitive detection of microbial pathogens. We have developed such plastic supports suitable for highly sensitive DNA microarray hybridizations. The proof of concept of this microarray technology was done through the detection of four human respiratory viruses that were amplified and labeled with a fluorescent dye via a sensitive reverse transcriptase PCR (RT-PCR) assay. The performance of the microarray hybridization with plastic supports made of PMMA [poly(methylmethacrylate)]-VSUVT or Zeonor 1060R was compared to that with high-quality glass slide microarrays by using both passive and microfluidic hybridization systems. Specific hybridization signal-to-background ratios comparable to that obtained with high-quality commercial glass slides were achieved with both polymeric substrates. Microarray hybridizations demonstrated an analytical sensitivity equivalent to approximately 100 viral genome copies per RT-PCR, which is at least 100-fold higher than the sensitivities of previously reported DNA hybridizations on plastic supports. Testing of these plastic polymers using a microfluidic microarray hybridization platform also showed results that were comparable to those with glass supports. In conclusion, PMMA-VSUVT and Zeonor 1060R are both suitable for highly sensitive microarray hybridizations. PMID:18784318

Development and application of a microarray meter tool to optimize microarray experiments

PubMed Central

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

A Web-Based Multi-Database System Supporting Distributed Collaborative Management and Sharing of Microarray Experiment Information

PubMed Central

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

Polysaccharide Microarray Technology for the Detection of Burkholderia Pseudomallei and Burkholderia Mallei Antibodies

DTIC Science & Technology

2006-04-27

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... Polysaccharide microarrays; Burkholderia pseudomallei; Burkholderia mallei; Glanders; Melioidosis1. Introduction There has been a great deal of emphasis on the

Microarray-integrated optoelectrofluidic immunoassay system

PubMed Central

Han, Dongsik

2016-01-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection. PMID:27190571

Microarray-integrated optoelectrofluidic immunoassay system.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-05-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

Advances in cell-free protein array methods.

PubMed

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.

Carbohydrate Microarray Technology Applied to High-Throughput Mapping of Plant Cell Wall Glycans Using Comprehensive Microarray Polymer Profiling (CoMPP).

PubMed

Kračun, Stjepan Krešimir; Fangel, Jonatan Ulrik; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Vidal-Melgosa, Silvia; Willats, William George Tycho

2017-01-01

Cell walls are an important feature of plant cells and a major component of the plant glycome. They have both structural and physiological functions and are critical for plant growth and development. The diversity and complexity of these structures demand advanced high-throughput techniques to answer questions about their structure, functions and roles in both fundamental and applied scientific fields. Microarray technology provides both the high-throughput and the feasibility aspects required to meet that demand. In this chapter, some of the most recent microarray-based techniques relating to plant cell walls are described together with an overview of related contemporary techniques applied to carbohydrate microarrays and their general potential in glycoscience. A detailed experimental procedure for high-throughput mapping of plant cell wall glycans using the comprehensive microarray polymer profiling (CoMPP) technique is included in the chapter and provides a good example of both the robust and high-throughput nature of microarrays as well as their applicability to plant glycomics.

Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, S; Jaing, C

2012-03-27

The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interimmore » report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.« less

Strategies for the Identification and Tracking of Cronobacter Species: An Opportunistic Pathogen of Concern to Neonatal Health

PubMed Central

Yan, Qiongqiong; Fanning, Séamus

2015-01-01

Cronobacter species are emerging opportunistic food-borne pathogens, which consists of seven species, including C. sakazakii, C. malonaticus, C. muytjensii, C. turicensis, C. dublinensis, C. universalis, and C. condimenti. The organism can cause severe clinical infections, including necrotizing enterocolitis, septicemia, and meningitis, predominately among neonates <4 weeks of age. Cronobacter species can be isolated from various foods and their surrounding environments; however, powdered infant formula (PIF) is the most frequently implicated food source linked with Cronobacter infection. This review aims to provide a summary of laboratory-based strategies that can be used to identify and trace Cronobacter species. The identification of Cronobacter species using conventional culture method and immuno-based detection protocols were first presented. The molecular detection and identification at genus-, and species-level along with molecular-based serogroup approaches are also described, followed by the molecular sub-typing methods, in particular pulsed-field gel electrophoresis and multi-locus sequence typing. Next generation sequence approaches, including whole genome sequencing, DNA microarray, and high-throughput whole-transcriptome sequencing, are also highlighted. Appropriate application of these strategies would contribute to reduce the risk of Cronobacter contamination in PIF and production environments, thereby improving food safety and protecting public health. PMID:26000266

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways

PubMed Central

Li, Chunquan; Han, Junwei; Yao, Qianlan; Zou, Chendan; Xu, Yanjun; Zhang, Chunlong; Shang, Desi; Zhou, Lingyun; Zou, Chaoxia; Sun, Zeguo; Li, Jing; Zhang, Yunpeng; Yang, Haixiu; Gao, Xu; Li, Xia

2013-01-01

Various ‘omics’ technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways. PMID:23482392

A genome-wide 20 K citrus microarray for gene expression analysis

PubMed Central

Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

2008-01-01

Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in citrus globular embryos. PMID:18598343

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.

PubMed

Rai, Muhammad Farooq; Tycksen, Eric D; Sandell, Linda J; Brophy, Robert H

2018-01-01

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Assessing the impact of Benzo[a]pyrene on Marine Mussels: Application of a novel targeted low density microarray complementing classical biomarker responses

PubMed Central

Sforzini, Susanna; Arlt, Volker M.; Barranger, Audrey; Dallas, Lorna J.; Oliveri, Caterina; Aminot, Yann; Pacchioni, Beniamina; Millino, Caterina; Lanfranchi, Gerolamo; Readman, James W.; Moore, Michael N.; Viarengo, Aldo; Jha, Awadhesh N.

2017-01-01

Despite the increasing use of mussels in environmental monitoring and ecotoxicological studies, their genomes and gene functions have not been thoroughly explored. Several cDNA microarrays were recently proposed for Mytilus spp., but putatively identified partial transcripts have rendered the generation of robust transcriptional responses difficult in terms of pathway identification. We developed a new low density oligonucleotide microarray with 465 probes covering the same number of genes. Target genes were selected to cover most of the well-known biological processes in the stress response documented over the last decade in bivalve species at the cellular and tissue levels. Our new ‘STressREsponse Microarray’ (STREM) platform consists of eight sub-arrays with three replicates for each target in each sub-array. To assess the potential use of the new array, we tested the effect of the ubiquitous environmental pollutant benzo[a]pyrene (B[a]P) at 5, 50, and 100 μg/L on two target tissues, the gills and digestive gland, of Mytilus galloprovincialis exposed invivo for three days. Bioaccumulation of B[a]P was also determined demonstrating exposure in both tissues. In addition to the well-known effects of B[a]P on DNA metabolism and oxidative stress, the new array data provided clues about the implication of other biological processes, such as cytoskeleton, immune response, adhesion to substrate, and mitochondrial activities. Transcriptional data were confirmed using qRT-PCR. We further investigated cellular functions and possible alterations related to biological processes highlighted by the microarray data using oxidative stress biomarkers (Lipofuscin content) and the assessment of genotoxicity. DNA damage, as measured by the alkaline comet assay, increased as a function of dose.DNA adducts measurements using 32P-postlabeling method also showed the presence of bulky DNA adducts (i.e. dG-N2-BPDE). Lipofiscin content increased significantly in B[a]P exposed mussels. Immunohistochemical analysis of tubulin and actin showed changes in cytoskeleton organisation. Our results adopting an integrated approach confirmed that the combination of newly developed transcriptomic approcah, classical biomarkers along with chemical analysis of water and tissue samples should be considered for environmental bioimonitoring and ecotoxicological studies to obtain holistic information to assess the impact of contaminants on the biota. PMID:28651000

The effect of column purification on cDNA indirect labelling for microarrays

PubMed Central

Molas, M Lia; Kiss, John Z

2007-01-01

Background The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. Results We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Conclusion Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays. PMID:17597522

The effect of column purification on cDNA indirect labelling for microarrays.

PubMed

Molas, M Lia; Kiss, John Z

2007-06-27

The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays.

The Glycan Microarray Story from Construction to Applications.

PubMed

Hyun, Ji Young; Pai, Jaeyoung; Shin, Injae

2017-04-18

Not only are glycan-mediated binding processes in cells and organisms essential for a wide range of physiological processes, but they are also implicated in various pathological processes. As a result, elucidation of glycan-associated biomolecular interactions and their consequences is of great importance in basic biological research and biomedical applications. In 2002, we and others were the first to utilize glycan microarrays in efforts aimed at the rapid analysis of glycan-associated recognition events. Because they contain a number of glycans immobilized in a dense and orderly manner on a solid surface, glycan microarrays enable multiple parallel analyses of glycan-protein binding events while utilizing only small amounts of glycan samples. Therefore, this microarray technology has become a leading edge tool in studies aimed at elucidating roles played by glycans and glycan binding proteins in biological systems. In this Account, we summarize our efforts on the construction of glycan microarrays and their applications in studies of glycan-associated interactions. Immobilization strategies of functionalized and unmodified glycans on derivatized glass surfaces are described. Although others have developed immobilization techniques, our efforts have focused on improving the efficiencies and operational simplicity of microarray construction. The microarray-based technology has been most extensively used for rapid analysis of the glycan binding properties of proteins. In addition, glycan microarrays have been employed to determine glycan-protein interactions quantitatively, detect pathogens, and rapidly assess substrate specificities of carbohydrate-processing enzymes. More recently, the microarrays have been employed to identify functional glycans that elicit cell surface lectin-mediated cellular responses. Owing to these efforts, it is now possible to use glycan microarrays to expand the understanding of roles played by glycans and glycan binding proteins in biological systems.

Two-Dimensional VO2 Mesoporous Microarrays for High-Performance Supercapacitor

NASA Astrophysics Data System (ADS)

Fan, Yuqi; Ouyang, Delong; Li, Bao-Wen; Dang, Feng; Ren, Zongming

2018-05-01

Two-dimensional (2D) mesoporous VO2 microarrays have been prepared using an organic-inorganic liquid interface. The units of microarrays consist of needle-like VO2 particles with a mesoporous structure, in which crack-like pores with a pore size of about 2 nm and depth of 20-100 nm are distributed on the particle surface. The liquid interface acts as a template for the formation of the 2D microarrays, as identified from the kinetic observation. Due to the mesoporous structure of the units and high conductivity of the microarray, such 2D VO2 microarrays exhibit a high specific capacitance of 265 F/g at 1 A/g and excellent rate capability (182 F/g at 10 A/g) and cycling stability, suggesting the effect of unique microstructure for improving the electrochemical performance.

CNVs affecting cancer predisposing genes (CPGs) detected as incidental findings in routine germline diagnostic chromosomal microarray (CMA) testing.

PubMed

Innes, Josie; Reali, Lisa; Clayton-Smith, Jill; Hall, Georgina; Lim, Derek Hk; Burghel, George J; French, Kim; Khan, Unzela; Walker, Daniel; Lalloo, Fiona; Evans, D Gareth R; McMullan, Dominic; Maher, Eamonn R; Woodward, Emma R

2018-02-01

Identification of CNVs through chromosomal microarray (CMA) testing is the first-line investigation in individuals with learning difficulties/congenital abnormalities. Although recognised that CMA testing may identify CNVs encompassing a cancer predisposition gene (CPG), limited information is available on the frequency and nature of such results. We investigated CNV gains and losses affecting 39 CPGs in 3366 pilot index case individuals undergoing CMA testing, and then studied an extended cohort (n=10 454) for CNV losses at 105 CPGs and CNV gains at 9 proto-oncogenes implicated in inherited cancer susceptibility. In the pilot cohort, 31/3366 (0.92%) individuals had a CNV involving one or more of 16/39 CPGs. 30/31 CNVs involved a tumour suppressor gene (TSG), and 1/30 a proto-oncogene (gain of MET ). BMPR1A , TSC2 and TMEM127 were affected in multiple cases. In the second stage analysis, 49/10 454 (0.47%) individuals in the extended cohort had 50 CNVs involving 24/105 CPGs. 43/50 CNVs involved a TSG and 7/50 a proto-oncogene (4 gains, 3 deletions). The most frequently involved genes, FLCN (n=10) and SDHA (n=7), map to the Smith-Magenis and cri-du-chat regions, respectively. Incidental identification of a CNV involving a CPG is not rare and poses challenges for future cancer risk estimation. Prospective data collection from CPG-CNV cohorts ascertained incidentally and through syndromic presentations is required to determine the risks posed by specific CNVs. In particular, ascertainment and investigation of adults with CPG-CNVs and adults with learning disability and cancer, could provide important information to guide clinical management and surveillance. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Microarray and network-based identification of functional modules and pathways of active tuberculosis.

PubMed

Bian, Zhong-Rui; Yin, Juan; Sun, Wen; Lin, Dian-Jie

2017-04-01

Diagnose of active tuberculosis (TB) is challenging and treatment response is also difficult to efficiently monitor. The aim of this study was to use an integrated analysis of microarray and network-based method to the samples from publically available datasets to obtain a diagnostic module set and pathways in active TB. Towards this goal, background protein-protein interactions (PPI) network was generated based on global PPI information and gene expression data, following by identification of differential expression network (DEN) from the background PPI network. Then, ego genes were extracted according to the degree features in DEN. Next, module collection was conducted by ego gene expansion based on EgoNet algorithm. After that, differential expression of modules between active TB and controls was evaluated using random permutation test. Finally, biological significance of differential modules was detected by pathways enrichment analysis based on Reactome database, and Fisher's exact test was implemented to extract differential pathways for active TB. Totally, 47 ego genes and 47 candidate modules were identified from the DEN. By setting the cutoff-criteria of gene size >5 and classification accuracy ≥0.9, 7 ego modules (Module 4, Module 7, Module 9, Module 19, Module 25, Module 38 and Module 43) were extracted, and all of them had the statistical significance between active TB and controls. Then, Fisher's exact test was conducted to capture differential pathways for active TB. Interestingly, genes in Module 4, Module 25, Module 38, and Module 43 were enriched in the same pathway, formation of a pool of free 40S subunits. Significant pathway for Module 7 and Module 9 was eukaryotic translation termination, and for Module 19 was nonsense mediated decay enhanced by the exon junction complex (EJC). Accordingly, differential modules and pathways might be potential biomarkers for treating active TB, and provide valuable clues for better understanding of molecular mechanism of active TB. Copyright © 2017 Elsevier Ltd. All rights reserved.

A comprehensive hybridization model allows whole HERV transcriptome profiling using high density microarray.

PubMed

Becker, Jérémie; Pérot, Philippe; Cheynet, Valérie; Oriol, Guy; Mugnier, Nathalie; Mommert, Marine; Tabone, Olivier; Textoris, Julien; Veyrieras, Jean-Baptiste; Mallet, François

2017-04-08

Human endogenous retroviruses (HERVs) have received much attention for their implications in the etiology of many human diseases and their profound effect on evolution. Notably, recent studies have highlighted associations between HERVs expression and cancers (Yu et al., Int J Mol Med 32, 2013), autoimmunity (Balada et al., Int Rev Immunol 29:351-370, 2010) and neurological (Christensen, J Neuroimmune Pharmacol 5:326-335, 2010) conditions. Their repetitive nature makes their study particularly challenging, where expression studies have largely focused on individual loci (De Parseval et al., J Virol 77:10414-10422, 2003) or general trends within families (Forsman et al., J Virol Methods 129:16-30, 2005; Seifarth et al., J Virol 79:341-352, 2005; Pichon et al., Nucleic Acids Res 34:e46, 2006). To refine our understanding of HERVs activity, we introduce here a new microarray, HERV-V3. This work was made possible by the careful detection and annotation of genomic HERV/MaLR sequences as well as the development of a new hybridization model, allowing the optimization of probe performances and the control of cross-reactions. RESULTS: HERV-V3 offers an almost complete coverage of HERVs and their ancestors (mammalian apparent LTR-retrotransposons, MaLRs) at the locus level along with four other repertoires (active LINE-1 elements, lncRNA, a selection of 1559 human genes and common infectious viruses). We demonstrate that HERV-V3 analytical performances are comparable with commercial Affymetrix arrays, and that for a selection of tissue/pathological specific loci, the patterns of expression measured on HERV-V3 is consistent with those reported in the literature. Given its large HERVs/MaLRs coverage and additional repertoires, HERV-V3 opens the door to multiple applications such as enhancers and alternative promoters identification, biomarkers identification as well as the characterization of genes and HERVs/MaLRs modulation caused by viral infection.

The Rice B-Box Zinc Finger Gene Family: Genomic Identification, Characterization, Expression Profiling and Diurnal Analysis

PubMed Central

Huang, Jianyan; Zhao, Xiaobo; Weng, Xiaoyu; Wang, Lei; Xie, Weibo

2012-01-01

Background The B-box (BBX) -containing proteins are a class of zinc finger proteins that contain one or two B-box domains and play important roles in plant growth and development. The Arabidopsis BBX gene family has recently been re-identified and renamed. However, there has not been a genome-wide survey of the rice BBX (OsBBX) gene family until now. Methodology/Principal Findings In this study, we identified 30 rice BBX genes through a comprehensive bioinformatics analysis. Each gene was assigned a uniform nomenclature. We described the chromosome localizations, gene structures, protein domains, phylogenetic relationship, whole life-cycle expression profile and diurnal expression patterns of the OsBBX family members. Based on the phylogeny and domain constitution, the OsBBX gene family was classified into five subfamilies. The gene duplication analysis revealed that only chromosomal segmental duplication contributed to the expansion of the OsBBX gene family. The expression profile of the OsBBX genes was analyzed by Affymetrix GeneChip microarrays throughout the entire life-cycle of rice cultivar Zhenshan 97 (ZS97). In addition, microarray analysis was performed to obtain the expression patterns of these genes under light/dark conditions and after three phytohormone treatments. This analysis revealed that the expression patterns of the OsBBX genes could be classified into eight groups. Eight genes were regulated under the light/dark treatments, and eleven genes showed differential expression under at least one phytohormone treatment. Moreover, we verified the diurnal expression of the OsBBX genes using the data obtained from the Diurnal Project and qPCR analysis, and the results indicated that many of these genes had a diurnal expression pattern. Conclusions/Significance The combination of the genome-wide identification and the expression and diurnal analysis of the OsBBX gene family should facilitate additional functional studies of the OsBBX genes. PMID:23118960

Expressed sequence tag analysis of adult human lens for the NEIBank Project: over 2000 non-redundant transcripts, novel genes and splice variants.

PubMed

Wistow, Graeme; Bernstein, Steven L; Wyatt, M Keith; Behal, Amita; Touchman, Jeffrey W; Bouffard, Gerald; Smith, Don; Peterson, Katherine

2002-06-15

To explore the expression profile of the human lens and to provide a resource for microarray studies, expressed sequence tag (EST) analysis has been performed on cDNA libraries from adult lenses. A cDNA library was constructed from two adult (40 year old) human lenses. Over two thousand clones were sequenced from the unamplified, un-normalized library. The library was then normalized and a further 2200 sequences were obtained. All the data were analyzed using GRIST (GRouping and Identification of Sequence Tags), a procedure for gene identification and clustering. The lens library (by) contains a low percentage of non-mRNA contaminants and a high fraction (over 75%) of apparently full length cDNA clones. Approximately 2000 reads from the unamplified library yields 810 clusters, potentially representing individual genes expressed in the lens. After normalization, the content of crystallins and other abundant cDNAs is markedly reduced and a similar number of reads from this library (fs) yields 1455 unique groups of which only two thirds correspond to named genes in GenBank. Among the most abundant cDNAs is one for a novel gene related to glutamine synthetase, which was designated "lengsin" (LGS). Analyses of ESTs also reveal examples of alternative transcripts, including a major alternative splice form for the lens specific membrane protein MP19. Variant forms for other transcripts, including those encoding the apoptosis inhibitor Livin and the armadillo repeat protein ARVCF, are also described. The lens cDNA libraries are a resource for gene discovery, full length cDNAs for functional studies and microarrays. The discovery of an abundant, novel transcript, lengsin, and a major novel splice form of MP19 reflect the utility of unamplified libraries constructed from dissected tissue. Many novel transcripts and splice forms are represented, some of which may be candidates for genetic diseases.

BoolFilter: an R package for estimation and identification of partially-observed Boolean dynamical systems.

PubMed

Mcclenny, Levi D; Imani, Mahdi; Braga-Neto, Ulisses M

2017-11-25

Gene regulatory networks govern the function of key cellular processes, such as control of the cell cycle, response to stress, DNA repair mechanisms, and more. Boolean networks have been used successfully in modeling gene regulatory networks. In the Boolean network model, the transcriptional state of each gene is represented by 0 (inactive) or 1 (active), and the relationship among genes is represented by logical gates updated at discrete time points. However, the Boolean gene states are never observed directly, but only indirectly and incompletely through noisy measurements based on expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays. The Partially-Observed Boolean Dynamical System (POBDS) signal model is distinct from other deterministic and stochastic Boolean network models in removing the requirement of a directly observable Boolean state vector and allowing uncertainty in the measurement process, addressing the scenario encountered in practice in transcriptomic analysis. BoolFilter is an R package that implements the POBDS model and associated algorithms for state and parameter estimation. It allows the user to estimate the Boolean states, network topology, and measurement parameters from time series of transcriptomic data using exact and approximated (particle) filters, as well as simulate the transcriptomic data for a given Boolean network model. Some of its infrastructure, such as the network interface, is the same as in the previously published R package for Boolean Networks BoolNet, which enhances compatibility and user accessibility to the new package. We introduce the R package BoolFilter for Partially-Observed Boolean Dynamical Systems (POBDS). The BoolFilter package provides a useful toolbox for the bioinformatics community, with state-of-the-art algorithms for simulation of time series transcriptomic data as well as the inverse process of system identification from data obtained with various expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays.

Clustering-based spot segmentation of cDNA microarray images.

PubMed

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

PubMed Central

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

A Platform for Combined DNA and Protein Microarrays Based on Total Internal Reflection Fluorescence

PubMed Central

Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

2012-01-01

We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax. PMID:22438738

Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach.

PubMed

Motakis, E S; Nason, G P; Fryzlewicz, P; Rutter, G A

2006-10-15

Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar-Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being 'distribution-free' in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data. DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results. The R package of the Data-Driven Haar-Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.

Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

PubMed Central

Biyani, Manish; Ichiki, Takanori

2015-01-01

Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era. PMID:27600226

HTSFinder: Powerful Pipeline of DNA Signature Discovery by Parallel and Distributed Computing

PubMed Central

Karimi, Ramin; Hajdu, Andras

2016-01-01

Comprehensive effort for low-cost sequencing in the past few years has led to the growth of complete genome databases. In parallel with this effort, a strong need, fast and cost-effective methods and applications have been developed to accelerate sequence analysis. Identification is the very first step of this task. Due to the difficulties, high costs, and computational challenges of alignment-based approaches, an alternative universal identification method is highly required. Like an alignment-free approach, DNA signatures have provided new opportunities for the rapid identification of species. In this paper, we present an effective pipeline HTSFinder (high-throughput signature finder) with a corresponding k-mer generator GkmerG (genome k-mers generator). Using this pipeline, we determine the frequency of k-mers from the available complete genome databases for the detection of extensive DNA signatures in a reasonably short time. Our application can detect both unique and common signatures in the arbitrarily selected target and nontarget databases. Hadoop and MapReduce as parallel and distributed computing tools with commodity hardware are used in this pipeline. This approach brings the power of high-performance computing into the ordinary desktop personal computers for discovering DNA signatures in large databases such as bacterial genome. A considerable number of detected unique and common DNA signatures of the target database bring the opportunities to improve the identification process not only for polymerase chain reaction and microarray assays but also for more complex scenarios such as metagenomics and next-generation sequencing analysis. PMID:26884678

HTSFinder: Powerful Pipeline of DNA Signature Discovery by Parallel and Distributed Computing.

PubMed

Karimi, Ramin; Hajdu, Andras

2016-01-01

Comprehensive effort for low-cost sequencing in the past few years has led to the growth of complete genome databases. In parallel with this effort, a strong need, fast and cost-effective methods and applications have been developed to accelerate sequence analysis. Identification is the very first step of this task. Due to the difficulties, high costs, and computational challenges of alignment-based approaches, an alternative universal identification method is highly required. Like an alignment-free approach, DNA signatures have provided new opportunities for the rapid identification of species. In this paper, we present an effective pipeline HTSFinder (high-throughput signature finder) with a corresponding k-mer generator GkmerG (genome k-mers generator). Using this pipeline, we determine the frequency of k-mers from the available complete genome databases for the detection of extensive DNA signatures in a reasonably short time. Our application can detect both unique and common signatures in the arbitrarily selected target and nontarget databases. Hadoop and MapReduce as parallel and distributed computing tools with commodity hardware are used in this pipeline. This approach brings the power of high-performance computing into the ordinary desktop personal computers for discovering DNA signatures in large databases such as bacterial genome. A considerable number of detected unique and common DNA signatures of the target database bring the opportunities to improve the identification process not only for polymerase chain reaction and microarray assays but also for more complex scenarios such as metagenomics and next-generation sequencing analysis.

An Introduction to MAMA (Meta-Analysis of MicroArray data) System.

PubMed

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.

Methods to study legionella transcriptome in vitro and in vivo.

PubMed

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.

GeneXplorer: an interactive web application for microarray data visualization and analysis.

PubMed

Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin

2004-10-01

When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

Fluorescence-based bioassays for the detection and evaluation of food materials.

PubMed

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-10-13

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials.

Fluorescence-Based Bioassays for the Detection and Evaluation of Food Materials

PubMed Central

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-01-01

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials. PMID:26473869

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

PubMed

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.

Microfluidic microarray systems and methods thereof

DOEpatents

West, Jay A. A. [Castro Valley, CA; Hukari, Kyle W [San Ramon, CA; Hux, Gary A [Tracy, CA

2009-04-28

Disclosed are systems that include a manifold in fluid communication with a microfluidic chip having a microarray, an illuminator, and a detector in optical communication with the microarray. Methods for using these systems for biological detection are also disclosed.

cDNA Microarray Screening in Food Safety

PubMed Central

ROY, SASHWATI; SEN, CHANDAN K

2009-01-01

The cDNA microarray technology and related bioinformatics tools presents a wide range of novel application opportunities. The technology may be productively applied to address food safety. In this mini-review article, we present an update highlighting the late breaking discoveries that demonstrate the vitality of cDNA microarray technology as a tool to analyze food safety with reference to microbial pathogens and genetically modified foods. In order to bring the microarray technology to mainstream food safety, it is important to develop robust user-friendly tools that may be applied in a field setting. In addition, there needs to be a standardized process for regulatory agencies to interpret and act upon microarray-based data. The cDNA microarray approach is an emergent technology in diagnostics. Its values lie in being able to provide complimentary molecular insight when employed in addition to traditional tests for food safety, as part of a more comprehensive battery of tests. PMID:16466843

Functional comparison of microarray data across multiple platforms using the method of percentage of overlapping functions.

PubMed

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.

ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

PubMed

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.

Profiling In Situ Microbial Community Structure with an Amplification Microarray

PubMed Central

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

PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA

EPA Science Inventory

Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...

DNA Microarray-based Ecotoxicological Biomarker Discovery in a Small Fish Model Species

EPA Science Inventory

This paper addresses several issues critical to use of zebrafish oligonucleotide microarrays for computational toxicology research on endocrine disrupting chemicals using small fish models, and more generally, the use of microarrays in aquatic toxicology.

IMPROVING THE RELIABILITY OF MICROARRAYS FOR TOXICOLOGY RESEARCH: A COLLABORATIVE APPROACH

EPA Science Inventory

Microarray-based gene expression profiling is a critical tool to identify molecular biomarkers of specific chemical stressors. Although current microarray technologies have progressed from their infancy, biological and technical repeatability and reliability are often still limit...

Identification of novel autoantibodies in type 1 diabetic patients using a high-density protein microarray.

PubMed

Koo, Bo Kyung; Chae, Sehyun; Kim, Kristine M; Kang, Min Jueng; Kim, Eunhee G; Kwak, Soo Heon; Jung, Hye Seung; Cho, Young Min; Choi, Sung Hee; Park, Young Joo; Shin, Choong Ho; Jang, Hak C; Shin, Chan Soo; Hwang, Daehee; Yi, Eugene C; Park, Kyong Soo

2014-09-01

Autoantibodies can facilitate diagnostic and therapeutic means for type 1 diabetes (T1DM). We profiled autoantibodies from serum samples of 16 T1DM patients, 16 type 2 diabetic (T2DM) patients, and 27 healthy control subjects with normal glucose tolerance (NGT) by using protein microarrays containing 9,480 proteins. Two novel autoantibodies, anti-EEF1A1 and anti-UBE2L3, were selected from microarrays followed by immunofluorescence staining of pancreas. We then tested the validity of the candidates by ELISA in two independent test cohorts: 1) 95 adults with T1DM, 49 with T2DM, 11 with latent autoimmune diabetes in adults (LADA), 20 with Graves disease, and 66 with NGT and 2) 33 children with T1DM and 34 healthy children. Concentrations of these autoantibodies were significantly higher in T1DM patients than in NGT and T2DM subjects (P < 0.01), which was also confirmed in the test cohort of children (P < 0.05). Prevalence of anti-EEF1A1 and anti-UBE2L3 antibodies was 29.5% and 35.8% in T1DM, respectively. Of note, 40.9% of T1DM patients who lack anti-GAD antibodies (GADA) had anti-EEF1A1 and/or anti-UBE2L3 antibodies. These were also detected in patients with fulminant T1DM but not LADA. Our approach identified autoantibodies that can provide a new dimension of information indicative of T1DM independent of GADA and new insights into diagnosis and classification of T1DM. © 2014 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Genome‐Wide MicroRNA and Gene Analysis of Mesenchymal Stem Cell Chondrogenesis Identifies an Essential Role and Multiple Targets for miR‐140‐5p

PubMed Central

Tselepi, Maria; Gómez, Rodolfo; Woods, Steven; Hui, Wang; Smith, Graham R.; Shanley, Daryl P.; Clark, Ian M.; Young, David A.

2015-01-01

Abstract microRNAs (miRNAs) are abundantly expressed in development where they are critical determinants of cell differentiation and phenotype. Accordingly miRNAs are essential for normal skeletal development and chondrogenesis in particular. However, the question of which miRNAs are specific to the chondrocyte phenotype has not been fully addressed. Using microarray analysis of miRNA expression during mesenchymal stem cell chondrogenic differentiation and detailed examination of the role of essential differentiation factors, such as SOX9, TGF‐β, and the cell condensation phase, we characterize the repertoire of specific miRNAs involved in chondrocyte development, highlighting in particular miR‐140 and miR‐455. Further with the use of mRNA microarray data we integrate miRNA expression and mRNA expression during chondrogenesis to underline the particular importance of miR‐140, especially the ‐5p strand. We provide a detailed identification and validation of direct targets of miR‐140‐5p in both chondrogenesis and adult chondrocytes with the use of microarray and 3′UTR analysis. This emphasizes the diverse array of targets and pathways regulated by miR‐140‐5p. We are also able to confirm previous experimentally identified targets but, additionally, identify a novel positive regulation of the Wnt signaling pathway by miR‐140‐5p. Wnt signaling has a complex role in chondrogenesis and skeletal development and these findings illustrate a previously unidentified role for miR‐140‐5p in regulation of Wnt signaling in these processes. Together these developments further highlight the role of miRNAs during chondrogenesis to improve our understanding of chondrocyte development and guide cartilage tissue engineering. Stem Cells 2015;33:3266–3280 PMID:26175215

An extended data mining method for identifying differentially expressed assay-specific signatures in functional genomic studies.

PubMed

Rollins, Derrick K; Teh, Ailing

2010-12-17

Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA) has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and compared to a current approach on the basis of false discovery rate (FDR) and statistical power (SP) which is the ability to correctly identify important genes. This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based. Both test statistics were found to be effective as evaluated in three case studies: (i) exposing E. coli cells to two different ethanol levels; (ii) application of myostatin to two groups of mice; and (iii) a simulated data study derived from the properties of (ii). The proposed method (PM) effectively identified critical genes in these studies based on comparison with the current method (CM). The simulation study supports higher identification accuracy for PM over CM for both proposed test statistics when the gene variance is constant and for one of the test statistics when the gene variance is non-constant. PM compares quite favorably to CM in terms of lower FDR and much higher SP. Thus, PM can be quite effective in producing accurate signatures from large microarray data sets for differential expression between assays groups identified in a preliminary step of the PCA procedure and is, therefore, recommended for use in these applications.

Discovering monotonic stemness marker genes from time-series stem cell microarray data.

PubMed

Wang, Hsei-Wei; Sun, Hsing-Jen; Chang, Ting-Yu; Lo, Hung-Hao; Cheng, Wei-Chung; Tseng, George C; Lin, Chin-Teng; Chang, Shing-Jyh; Pal, Nikhil; Chung, I-Fang

2015-01-01

Identification of genes with ascending or descending monotonic expression patterns over time or stages of stem cells is an important issue in time-series microarray data analysis. We propose a method named Monotonic Feature Selector (MFSelector) based on a concept of total discriminating error (DEtotal) to identify monotonic genes. MFSelector considers various time stages in stage order (i.e., Stage One vs. other stages, Stages One and Two vs. remaining stages and so on) and computes DEtotal of each gene. MFSelector can successfully identify genes with monotonic characteristics. We have demonstrated the effectiveness of MFSelector on two synthetic data sets and two stem cell differentiation data sets: embryonic stem cell neurogenesis (ESCN) and embryonic stem cell vasculogenesis (ESCV) data sets. We have also performed extensive quantitative comparisons of the three monotonic gene selection approaches. Some of the monotonic marker genes such as OCT4, NANOG, BLBP, discovered from the ESCN dataset exhibit consistent behavior with that reported in other studies. The role of monotonic genes found by MFSelector in either stemness or differentiation is validated using information obtained from Gene Ontology analysis and other literature. We justify and demonstrate that descending genes are involved in the proliferation or self-renewal activity of stem cells, while ascending genes are involved in differentiation of stem cells into variant cell lineages. We have developed a novel system, easy to use even with no pre-existing knowledge, to identify gene sets with monotonic expression patterns in multi-stage as well as in time-series genomics matrices. The case studies on ESCN and ESCV have helped to get a better understanding of stemness and differentiation. The novel monotonic marker genes discovered from a data set are found to exhibit consistent behavior in another independent data set, demonstrating the utility of the proposed method. The MFSelector R function and data sets can be downloaded from: http://microarray.ym.edu.tw/tools/MFSelector/.

Genomic resources for Myzus persicae: EST sequencing, SNP identification, and microarray design

PubMed Central

Ramsey, John S; Wilson, Alex CC; de Vos, Martin; Sun, Qi; Tamborindeguy, Cecilia; Winfield, Agnese; Malloch, Gaynor; Smith, Dawn M; Fenton, Brian; Gray, Stewart M; Jander, Georg

2007-01-01

Background The green peach aphid, Myzus persicae (Sulzer), is a world-wide insect pest capable of infesting more than 40 plant families, including many crop species. However, despite the significant damage inflicted by M. persicae in agricultural systems through direct feeding damage and by its ability to transmit plant viruses, limited genomic information is available for this species. Results Sequencing of 16 M. persicae cDNA libraries generated 26,669 expressed sequence tags (ESTs). Aphids for library construction were raised on Arabidopsis thaliana, Nicotiana benthamiana, Brassica oleracea, B. napus, and Physalis floridana (with and without Potato leafroll virus infection). The M. persicae cDNA libraries include ones made from sexual and asexual whole aphids, guts, heads, and salivary glands. In silico comparison of cDNA libraries identified aphid genes with tissue-specific expression patterns, and gene expression that is induced by feeding on Nicotiana benthamiana. Furthermore, 2423 genes that are novel to science and potentially aphid-specific were identified. Comparison of cDNA data from three aphid lineages identified single nucleotide polymorphisms that can be used as genetic markers and, in some cases, may represent functional differences in the protein products. In particular, non-conservative amino acid substitutions in a highly expressed gut protease may be of adaptive significance for M. persicae feeding on different host plants. The Agilent eArray platform was used to design an M. persicae oligonucleotide microarray representing over 10,000 unique genes. Conclusion New genomic resources have been developed for M. persicae, an agriculturally important insect pest. These include previously unknown sequence data, a collection of expressed genes, molecular markers, and a DNA microarray that can be used to study aphid gene expression. These resources will help elucidate the adaptations that allow M. persicae to develop compatible interactions with its host plants, complementing ongoing work illuminating plant molecular responses to phloem-feeding insects. PMID:18021414

Expression Profile of Genes during Resistance Reversal in a Temephos Selected Strain of the Dengue Vector, Aedes aegypti

PubMed Central

Strode, Clare; de Melo-Santos, Maria; Magalhães, Tereza; Araújo, Ana; Ayres, Contancia

2012-01-01

Background The mosquito Aedes aegypti is one of the most important disease vectors because it transmits two major arboviruses, dengue and yellow fever, which cause significant global morbidity and mortality. Chemical insecticides form the cornerstone of vector control. The organophosphate temephos a larvicide recommended by WHO for controlling Ae. aegypti, however, resistance to this compound has been reported in many countries, including Brazil. Methodology/Principal Findings The aim of this study was to identify genes implicated in metabolic resistance in an Ae. aegypti temephos resistant strain, named RecR, through microarray analysis. We utilized a custom ‘Ae. aegypti detox chip’ and validated microarray data through RT-PCR comparing susceptible and resistant individuals. In addition, we analyzed gene expression in 4th instar larvae from a reversed susceptible strain (RecRev), exposed and unexposed to temephos. The results obtained revealed a set of 13 and 6 genes significantly over expressed in resistant adult mosquitoes and larvae, respectively. One of these genes, the cytochrome P450 CYP6N12, was up-regulated in both stages. RT-PCR confirmed the microarray results and, additionally, showed no difference in gene expression between temephos exposed and unexposed RecRev mosquitoes. This suggested that the differences in the transcript profiles among the strains are heritable due to a selection process and are not caused by immediate insecticide exposure. Reversal of temephos resistance was demonstrated and, importantly, there was a positive correlation between a decrease in the resistance ratio and an accompanying decrease in the expression levels of previously over expressed genes. Some of the genes identified here have also been implicated in metabolic resistance in other mosquito species and insecticide resistant populations of Ae. aegypti. Conclusions/Significance The identification of gene expression signatures associated to insecticide resistance and their suppression could greatly aid the development of improved strategies of vector control. PMID:22870187

Substrate analysis of the Pneumocystis carinii protein kinases PcCbk1 and PcSte20 using yeast proteome microarrays provides a novel method for Pneumocystis signalling biology.

PubMed

Kottom, Theodore J; Limper, Andrew H

2011-10-01

Pneumocystis carinii (Pc) undergoes morphological transitions between cysts and trophic forms. We have previously described two Pc serine/threonine kinases, termed PcCbk1 and PcSte20, with PcSte20 belonging to a family of kinases involved in yeast mating, while PcCbk1 is a member of a group of protein kinases involved in regulation of cell cycle, shape, and proliferation. As Pc remains genetically intractable, knowledge on specific substrates phosphorylated by these kinases remains limited. Utilizing the phylogenetic relatedness of Pc to Saccharomyces cerevisiae, we interrogated a yeast proteome microarray containing >4000 purified protein based peptides, leading to the identification of 18 potential PcCbk1 and 15 PcSte20 substrates (Z-score > 3.0). A number of these potential protein substrates are involved in bud site selection, polarized growth, and response to mating α factor and pseudohyphal and invasive growth. Full-length open reading frames suggested by the PcCbk1 and PcSte20 protoarrays were amplified and expressed. These five proteins were used as substrates for PcCbk1 or PcSte20, with each being highly phosphorylated by the respective kinase. Finally, to demonstrate the utility of this method to identify novel PcCbk1 and PcSte20 substrates, we analysed DNA sequence data from the partially complete Pc genome database and detected partial sequence information of potential PcCbk1 kinase substrates PcPxl1 and PcInt1. We additionally identified the potential PcSte20 kinase substrate PcBdf2. Full-length Pc substrates were cloned and expressed in yeast, and shown to be phosphorylated by the respective Pc kinases. In conclusion, the yeast protein microarray represents a novel crossover technique for identifying unique potential Pc kinase substrates. Copyright © 2011 John Wiley & Sons, Ltd.

Short non-coding RNAs as bacteria species identifiers detected by surface plasmon resonance enhanced common path interferometry

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.

SOLID3: a multiplex antibody microarray-based optical sensor instrument for in situ life detection in planetary exploration.

PubMed

Parro, Víctor; de Diego-Castilla, Graciela; Rodríguez-Manfredi, José A; Rivas, Luis A; Blanco-López, Yolanda; Sebastián, Eduardo; Romeral, Julio; Compostizo, Carlos; Herrero, Pedro L; García-Marín, Adolfo; Moreno-Paz, Mercedes; García-Villadangos, Miriam; Cruz-Gil, Patricia; Peinado, Verónica; Martín-Soler, Javier; Pérez-Mercader, Juan; Gómez-Elvira, Javier

2011-01-01

The search for unequivocal signs of life on other planetary bodies is one of the major challenges for astrobiology. The failure to detect organic molecules on the surface of Mars by measuring volatile compounds after sample heating, together with the new knowledge of martian soil chemistry, has prompted the astrobiological community to develop new methods and technologies. Based on protein microarray technology, we have designed and built a series of instruments called SOLID (for "Signs Of LIfe Detector") for automatic in situ detection and identification of substances or analytes from liquid and solid samples (soil, sediments, or powder). Here, we present the SOLID3 instrument, which is able to perform both sandwich and competitive immunoassays and consists of two separate functional units: a Sample Preparation Unit (SPU) for 10 different extractions by ultrasonication and a Sample Analysis Unit (SAU) for fluorescent immunoassays. The SAU consists of five different flow cells, with an antibody microarray in each one (2000 spots). It is also equipped with an exclusive optical package and a charge-coupled device (CCD) for fluorescent detection. We demonstrated the performance of SOLID3 in the detection of a broad range of molecular-sized compounds, which range from peptides and proteins to whole cells and spores, with sensitivities at 1-2 ppb (ng mL⁻¹) for biomolecules and 10⁴ to 10³ spores per milliliter. We report its application in the detection of acidophilic microorganisms in the Río Tinto Mars analogue and report the absence of substantial negative effects on the immunoassay in the presence of 50 mM perchlorate (20 times higher than that found at the Phoenix landing site). Our SOLID instrument concept is an excellent option with which to detect biomolecules because it avoids the high-temperature treatments that may destroy organic matter in the presence of martian oxidants.

Chromosomal microarray analysis of Bulgarian patients with epilepsy and intellectual disability.

PubMed

Peycheva, Valentina; Kamenarova, Kunka; Ivanova, Neviana; Stamatov, Dimitar; Avdjieva-Tzavella, Daniela; Alexandrova, Iliana; Zhelyazkova, Sashka; Pacheva, Iliana; Dimova, Petya; Ivanov, Ivan; Litvinenko, Ivan; Bozhinova, Veneta; Tournev, Ivailo; Simeonov, Emil; Mitev, Vanyo; Jordanova, Albena; Kaneva, Radka

2018-08-15

High resolution chromosomal microarray analysis (CMA) has facilitated the identification of small chromosomal rearrangements throughout the genome, associated with various neurodevelopmental phenotypes, including ID/DD. Recently, it became evident that intellectual disability (ID)/developmental delay (DD) can occur with associated co-morbidities like epileptic seizures, autism and additional congenital anomalies. These observations require whole genome approach in order to detect the genetic causes of these complex disorders. In this study, we examined 92 patients of Bulgarian origin at age between 1 and 22 years with ID, generalized epilepsy, autistic signs and congenital anomalies. CMA was carried out using SurePrint G3 Human CGH Microarray Kit, 4 × 180 K and SurePrint G3 Unrestricted CGH ISCA v2, 4 × 180 K oligo platforms. Referral indications for selection of the patients were the presence of generalized refractory seizures disorders and co-morbid ID. Clearly pathogenic copy number variations (CNVs) were detected in eight patients (8.7%) from our cohort. Additionally, possibly pathogenic rearrangements of unclear clinical significance were detected in six individuals (6.5%), which make for an overall diagnostic yield of 15.2% among our cohort of patients. We report here the patients with clearly pathogenic CNVs, discuss the potential causality of the possibly pathogenic CNVs and make genotype - phenotype correlations. One novel possibly pathogenic heterozygous deletion in 15q22.31 region was detected in a case with ID/DD. Additionally, whole APBA2 gene duplication in 15q13.1 was found in three generations of a family with epilepsy, ID and psychiatric abnormalities. The results from this study allow us to define the genetic diagnosis in a subset of Bulgarian patients and improve the genetic counseling of the affected families. To our knowledge, this is the first aCGH evaluation of a Bulgarian cohort of children with epilepsy and ID so far. Copyright © 2018 Elsevier B.V. All rights reserved.

A parallel implementation of the network identification by multiple regression (NIR) algorithm to reverse-engineer regulatory gene networks.

PubMed

Gregoretti, Francesco; Belcastro, Vincenzo; di Bernardo, Diego; Oliva, Gennaro

2010-04-21

The reverse engineering of gene regulatory networks using gene expression profile data has become crucial to gain novel biological knowledge. Large amounts of data that need to be analyzed are currently being produced due to advances in microarray technologies. Using current reverse engineering algorithms to analyze large data sets can be very computational-intensive. These emerging computational requirements can be met using parallel computing techniques. It has been shown that the Network Identification by multiple Regression (NIR) algorithm performs better than the other ready-to-use reverse engineering software. However it cannot be used with large networks with thousands of nodes--as is the case in biological networks--due to the high time and space complexity. In this work we overcome this limitation by designing and developing a parallel version of the NIR algorithm. The new implementation of the algorithm reaches a very good accuracy even for large gene networks, improving our understanding of the gene regulatory networks that is crucial for a wide range of biomedical applications.

Identification of methyllysine peptides binding to chromobox protein homolog 6 chromodomain in the human proteome.

PubMed

Li, Nan; Stein, Richard S L; He, Wei; Komives, Elizabeth; Wang, Wei

2013-10-01

Methylation is one of the important post-translational modifications that play critical roles in regulating protein functions. Proteomic identification of this post-translational modification and understanding how it affects protein activity remain great challenges. We tackled this problem from the aspect of methylation mediating protein-protein interaction. Using the chromodomain of human chromobox protein homolog 6 as a model system, we developed a systematic approach that integrates structure modeling, bioinformatics analysis, and peptide microarray experiments to identify lysine residues that are methylated and recognized by the chromodomain in the human proteome. Given the important role of chromobox protein homolog 6 as a reader of histone modifications, it was interesting to find that the majority of its interacting partners identified via this approach function in chromatin remodeling and transcriptional regulation. Our study not only illustrates a novel angle for identifying methyllysines on a proteome-wide scale and elucidating their potential roles in regulating protein function, but also suggests possible strategies for engineering the chromodomain-peptide interface to enhance the recognition of and manipulate the signal transduction mediated by such interactions.

Combinatorial peptide libraries and biometric score matrices permit the quantitative analysis of specific and degenerate interactions between clonotypic TCR and MHC peptide ligands.

PubMed

Zhao, Y; Gran, B; Pinilla, C; Markovic-Plese, S; Hemmer, B; Tzou, A; Whitney, L W; Biddison, W E; Martin, R; Simon, R

2001-08-15

The interaction of TCRs with MHC peptide ligands can be highly flexible, so that many different peptides are recognized by the same TCR in the context of a single restriction element. We provide a quantitative description of such interactions, which allows the identification of T cell epitopes and molecular mimics. The response of T cell clones to positional scanning synthetic combinatorial libraries is analyzed with a mathematical approach that is based on a model of independent contribution of individual amino acids to peptide Ag recognition. This biometric analysis compares the information derived from these libraries composed of trillions of decapeptides with all the millions of decapeptides contained in a protein database to rank and predict the most stimulatory peptides for a given T cell clone. We demonstrate the predictive power of the novel strategy and show that, together with gene expression profiling by cDNA microarrays, it leads to the identification of novel candidate autoantigens in the inflammatory autoimmune disease, multiple sclerosis.

ROKU: a novel method for identification of tissue-specific genes

PubMed Central

Kadota, Koji; Ye, Jiazhen; Nakai, Yuji; Terada, Tohru; Shimizu, Kentaro

2006-01-01

Background One of the important goals of microarray research is the identification of genes whose expression is considerably higher or lower in some tissues than in others. We would like to have ways of identifying such tissue-specific genes. Results We describe a method, ROKU, which selects tissue-specific patterns from gene expression data for many tissues and thousands of genes. ROKU ranks genes according to their overall tissue specificity using Shannon entropy and detects tissues specific to each gene if any exist using an outlier detection method. We evaluated the capacity for the detection of various specific expression patterns using synthetic and real data. We observed that ROKU was superior to a conventional entropy-based method in its ability to rank genes according to overall tissue specificity and to detect genes whose expression pattern are specific only to objective tissues. Conclusion ROKU is useful for the detection of various tissue-specific expression patterns. The framework is also directly applicable to the selection of diagnostic markers for molecular classification of multiple classes. PMID:16764735

The opportunities and challenges of large-scale molecular approaches to songbird neurobiology

PubMed Central

Mello, C.V.; Clayton, D.F.

2014-01-01

High-through put methods for analyzing genome structure and function are having a large impact in song-bird neurobiology. Methods include genome sequencing and annotation, comparative genomics, DNA microarrays and transcriptomics, and the development of a brain atlas of gene expression. Key emerging findings include the identification of complex transcriptional programs active during singing, the robust brain expression of non-coding RNAs, evidence of profound variations in gene expression across brain regions, and the identification of molecular specializations within song production and learning circuits. Current challenges include the statistical analysis of large datasets, effective genome curations, the efficient localization of gene expression changes to specific neuronal circuits and cells, and the dissection of behavioral and environmental factors that influence brain gene expression. The field requires efficient methods for comparisons with organisms like chicken, which offer important anatomical, functional and behavioral contrasts. As sequencing costs plummet, opportunities emerge for comparative approaches that may help reveal evolutionary transitions contributing to vocal learning, social behavior and other properties that make songbirds such compelling research subjects. PMID:25280907

Genome-wide identification, classification, and expression analysis of the arabinogalactan protein gene family in rice (Oryza sativa L.)

PubMed Central

Zhao, Jie

2010-01-01

Arabinogalactan proteins (AGPs) comprise a family of hydroxyproline-rich glycoproteins that are implicated in plant growth and development. In this study, 69 AGPs are identified from the rice genome, including 13 classical AGPs, 15 arabinogalactan (AG) peptides, three non-classical AGPs, three early nodulin-like AGPs (eNod-like AGPs), eight non-specific lipid transfer protein-like AGPs (nsLTP-like AGPs), and 27 fasciclin-like AGPs (FLAs). The results from expressed sequence tags, microarrays, and massively parallel signature sequencing tags are used to analyse the expression of AGP-encoding genes, which is confirmed by real-time PCR. The results reveal that several rice AGP-encoding genes are predominantly expressed in anthers and display differential expression patterns in response to abscisic acid, gibberellic acid, and abiotic stresses. Based on the results obtained from this analysis, an attempt has been made to link the protein structures and expression patterns of rice AGP-encoding genes to their functions. Taken together, the genome-wide identification and expression analysis of the rice AGP gene family might facilitate further functional studies of rice AGPs. PMID:20423940

Direct labeling of serum proteins by fluorescent dye for antibody microarray.

PubMed

Klimushina, M V; Gumanova, N G; Metelskaya, V A

2017-05-06

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

Transfection microarray and the applications.

PubMed

Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun

2009-05-01

Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.

A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

PubMed Central

Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-ce

2016-01-01

Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. PMID:27364157

EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

PubMed Central

Barton, G; Abbott, J; Chiba, N; Huang, DW; Huang, Y; Krznaric, M; Mack-Smith, J; Saleem, A; Sherman, BT; Tiwari, B; Tomlinson, C; Aitman, T; Darlington, J; Game, L; Sternberg, MJE; Butcher, SA

2008-01-01

Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data management and analysis tasks through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume. PMID:19032776

Identification of an Efficient Gene Expression Panel for Glioblastoma Classification

PubMed Central

Zelaya, Ivette; Laks, Dan R.; Zhao, Yining; Kawaguchi, Riki; Gao, Fuying; Kornblum, Harley I.; Coppola, Giovanni

2016-01-01

We present here a novel genetic algorithm-based random forest (GARF) modeling technique that enables a reduction in the complexity of large gene disease signatures to highly accurate, greatly simplified gene panels. When applied to 803 glioblastoma multiforme samples, this method allowed the 840-gene Verhaak et al. gene panel (the standard in the field) to be reduced to a 48-gene classifier, while retaining 90.91% classification accuracy, and outperforming the best available alternative methods. Additionally, using this approach we produced a 32-gene panel which allows for better consistency between RNA-seq and microarray-based classifications, improving cross-platform classification retention from 69.67% to 86.07%. A webpage producing these classifications is available at http://simplegbm.semel.ucla.edu. PMID:27855170

A review of current and future molecular diagnostic tests for use in the microbiology laboratory.

PubMed

Jannes, Geert; De Vos, Daniel

2006-01-01

Nucleic acid-based diagnostics gradually are replacing or complementing culture-based, biochemical, and immunological assays in routine microbiology laboratories. Similar to conventional tests, the first-generation deoxyribonucleic acid assays determined only a single analyte. Recent improvements in detection technologies have paved the way for the development of multiparameter assays using macroarrays or micro-arrays, while the introduction of closed-tube real-time polymerase chain reaction systems has resulted in the development of rapid microbial diagnostics with a reduced contamination risk. The use of these new molecular technologies is not restricted to detection and identification of microbial pathogens but also can be used for genotyping, allowing one to determine antibiotic resistance or to perform microbial fingerprinting.

Delineation of Two Clinically and Molecularly Distinct Subgroups of Posterior Fossa Ependymoma

PubMed Central

Witt, Hendrik; Mack, Stephen C.; Ryzhova, Marina; Bender, Sebastian; Sill, Martin; Isserlin, Ruth; Benner, Axel; Hielscher, Thomas; Milde, Till; Remke, Marc; Jones, David T.W.; Northcott, Paul A.; Garzia, Livia; Bertrand, Kelsey C.; Wittmann, Andrea; Yao, Yuan; Roberts, Stephen S.; Massimi, Luca; Van Meter, Tim; Weiss, William A.; Gupta, Nalin; Grajkowska, Wiesia; Lach, Boleslaw; Cho, Yoon-Jae; von Deimling, Andreas; Kulozik, Andreas E.; Witt, Olaf; Bader, Gary D.; Hawkins, Cynthia E.; Tabori, Uri; Guha, Abhijit; Rutka, James T.; Lichter, Peter; Korshunov, Andrey

2014-01-01

Summary Despite the histological similarity of ependymomas from throughout the neuroaxis, the disease likely comprises multiple independent entities, each with a distinct molecular pathogenesis. Transcriptional profiling of two large independent cohorts of ependymoma reveals the existence of two demographically, transcriptionally, genetically, and clinically distinct groups of posterior fossa (PF) ependymomas. Group A patients are younger, have laterally located tumors with a balanced genome, and are much more likely to exhibit recurrence, metastasis at recurrence, and death compared with Group B patients. Identification and optimization of immunohistochemical (IHC) markers for PF ependymoma subgroups allowed validation of our findings on a third independent cohort, using a human ependymoma tissue microarray, and provides a tool for prospective prognostication and stratification of PF ependymoma patients. PMID:21840481

eSensor®: A Microarray Technology Based on Electrochemical Detection of Nucleic Acids and Its Application to Cystic Fibrosis Carrier Screening

NASA Astrophysics Data System (ADS)

Reed, Michael R.; Coty, William A.

We have developed a test for identification of carriers for cystic fibrosis using the eSensor® DNA detection technology. Oligonucleotide probes are deposited within self-assembled monolayers on gold electrodes arrayed upon printed circuit boards. These probes allow sequence-specific capture of amplicons containing a panel of mutation sites associated with cystic fibrosis. DNA targets are detected and mutations genotyped using a “sandwich” assay methodology employing electrochemical detection of ferrocene-labeled oligonucleotides for discrimination of carrier and non-carrier alleles. Performance of the cystic fibrosis application demonstrates sufficient accuracy and reliability for clinical diagnostic use, and the procedure can be performed by trained medical technologists available in the hospital laboratory.

THE MAQC PROJECT: ESTABLISHING QC METRICS AND THRESHOLDS FOR MICROARRAY QUALITY CONTROL

EPA Science Inventory

Microarrays represent a core technology in pharmacogenomics and toxicogenomics; however, before this technology can successfully and reliably be applied in clinical practice and regulatory decision-making, standards and quality measures need to be developed. The Microarray Qualit...

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

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

Ossification of the posterior longitudinal ligament related genes identification using microarray gene expression profiling and bioinformatics analysis.

PubMed

He, Hailong; Mao, Lingzhou; Xu, Peng; Xi, Yanhai; Xu, Ning; Xue, Mingtao; Yu, Jiangming; Ye, Xiaojian

2014-01-10

Ossification of the posterior longitudinal ligament (OPLL) is a kind of disease with physical barriers and neurological disorders. The objective of this study was to explore the differentially expressed genes (DEGs) in OPLL patient ligament cells and identify the target sites for the prevention and treatment of OPLL in clinic. Gene expression data GSE5464 was downloaded from Gene Expression Omnibus; then DEGs were screened by limma package in R language, and changed functions and pathways of OPLL cells compared to normal cells were identified by DAVID (The Database for Annotation, Visualization and Integrated Discovery); finally, an interaction network of DEGs was constructed by string. A total of 1536 DEGs were screened, with 31 down-regulated and 1505 up-regulated genes. Response to wounding function and Toll-like receptor signaling pathway may involve in the development of OPLL. Genes, such as PDGFB, PRDX2 may involve in OPLL through response to wounding function. Toll-like receptor signaling pathway enriched genes such as TLR1, TLR5, and TLR7 may involve in spine cord injury in OPLL. PIK3R1 was the hub gene in the network of DEGs with the highest degree; INSR was one of the most closely related genes of it. OPLL related genes screened by microarray gene expression profiling and bioinformatics analysis may be helpful for elucidating the mechanism of OPLL. © 2013.

Identification of Cell Cycle-regulated Genes in Fission YeastD⃞

PubMed Central

Peng, Xu; Karuturi, R. Krishna Murthy; Miller, Lance D.; Lin, Kui; Jia, Yonghui; Kondu, Pinar; Wang, Long; Wong, Lim-Soon; Liu, Edison T.; Balasubramanian, Mohan K.; Liu, Jianhua

2005-01-01

Cell cycle progression is both regulated and accompanied by periodic changes in the expression levels of a large number of genes. To investigate cell cycle-regulated transcriptional programs in the fission yeast Schizosaccharomyces pombe, we developed a whole-genome oligonucleotide-based DNA microarray. Microarray analysis of both wild-type and cdc25 mutant cell cultures was performed to identify transcripts whose levels oscillated during the cell cycle. Using an unsupervised algorithm, we identified 747 genes that met the criteria for cell cycle-regulated expression. Peaks of gene expression were found to be distributed throughout the entire cell cycle. Furthermore, we found that four promoter motifs exhibited strong association with cell cycle phase-specific expression. Examination of the regulation of MCB motif-containing genes through the perturbation of DNA synthesis control/MCB-binding factor (DSC/MBF)-mediated transcription in arrested synchronous cdc10 mutant cell cultures revealed a subset of functional targets of the DSC/MBF transcription factor complex, as well as certain gene promoter requirements. Finally, we compared our data with those for the budding yeast Saccharomyces cerevisiae and found ∼140 genes that are cell cycle regulated in both yeasts, suggesting that these genes may play an evolutionarily conserved role in regulation of cell cycle-specific processes. Our complete data sets are available at http://giscompute.gis.a-star.edu.sg/~gisljh/CDC. PMID:15616197

Microbial Profiling of Combat Wound Infection through Detection Microarray and Next-Generation Sequencing

PubMed Central

Allen, Jonathan E.; Brown, Trevor S.; Gardner, Shea N.; McLoughlin, Kevin S.; Forsberg, Jonathan A.; Kirkup, Benjamin C.; Chromy, Brett A.; Luciw, Paul A.; Elster, Eric A.

2014-01-01

Combat wound healing and resolution are highly affected by the resident microbial flora. We therefore sought to achieve comprehensive detection of microbial populations in wounds using novel genomic technologies and bioinformatics analyses. We employed a microarray capable of detecting all sequenced pathogens for interrogation of 124 wound samples from extremity injuries in combat-injured U.S. service members. A subset of samples was also processed via next-generation sequencing and metagenomic analysis. Array analysis detected microbial targets in 51% of all wound samples, with Acinetobacter baumannii being the most frequently detected species. Multiple Pseudomonas species were also detected in tissue biopsy specimens. Detection of the Acinetobacter plasmid pRAY correlated significantly with wound failure, while detection of enteric-associated bacteria was associated significantly with successful healing. Whole-genome sequencing revealed broad microbial biodiversity between samples. The total wound bioburden did not associate significantly with wound outcome, although temporal shifts were observed over the course of treatment. Given that standard microbiological methods do not detect the full range of microbes in each wound, these data emphasize the importance of supplementation with molecular techniques for thorough characterization of wound-associated microbes. Future application of genomic protocols for assessing microbial content could allow application of specialized care through early and rapid identification and management of critical patterns in wound bioburden. PMID:24829242

DNA Modification Study of Major Depressive Disorder: Beyond Locus-by-Locus Comparisons

PubMed Central

Oh, Gabriel; Wang, Sun-Chong; Pal, Mrinal; Chen, Zheng Fei; Khare, Tarang; Tochigi, Mamoru; Ng, Catherine; Yang, Yeqing A.; Kwan, Andrew; Kaminsky, Zachary A.; Mill, Jonathan; Gunasinghe, Cerisse; Tackett, Jennifer L.; Gottesman, Irving I.; Willemsen, Gonneke; de Geus, Eco J.C.; Vink, Jacqueline M.; Slagboom, P. Eline; Wray, Naomi R.; Heath, Andrew C.; Montgomery, Grant W.; Turecki, Gustavo; Martin, Nicholas G.; Boomsma, Dorret I.; McGuffin, Peter; Kustra, Rafal; Petronis, Art

2014-01-01

Background Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. Methods We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. Results In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Conclusions Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations. PMID:25108803

Identification of PblB mediating galactose-specific adhesion in a successful Streptococcus pneumoniae clone

PubMed Central

Hsieh, Yu-Chia; Lin, Tzu-Lung; Lin, Che-Ming; Wang, Jin-Town

2015-01-01

The pneumococcal genome is variable and there are minimal data on the influence of the accessory genome on phenotype. Pneumococcal serotype 14 sequence type (ST) 46 had been the most prevalent clone causing pneumonia in children in Taiwan. A microarray was constructed using the genomic DNA of a clinical strain (NTUH-P15) of serotype 14 ST46. Using DNA hybridization, genomic variations in NTUH-P15 were compared to those of 3 control strains. Microarray analysis identified 7 genomic regions that had significant increases in hybridization signals in the NTUH-P15 strain compared to control strains. One of these regions encoded PblB, a phage-encoded virulence factor implicated (in Streptococcus mitis) in infective endocarditis. The isogenic pblB mutant decreased adherence to A549 human lung epithelial cell compared to wild-type NTUH-P15 strain (P = 0.01). Complementation with pblB restored the adherence. PblB is predicted to contain a galactose-binding domain-like region. Preincubation of NTUH-P15 with D-galactose resulted in decreases of adherence to A549 cell in a dose-dependent manner. Challenge of mice with NTUH-P15, isogenic pblB mutant and pblB complementation strains determined that PblB was required for bacterial persistence in the nasopharynx and lung. PblB, as an adhesin mediating the galactose-specific adhesion activity of pneumococci, promote pneumococcal clonal success. PMID:26193794

DNA modification study of major depressive disorder: beyond locus-by-locus comparisons.

PubMed

Oh, Gabriel; Wang, Sun-Chong; Pal, Mrinal; Chen, Zheng Fei; Khare, Tarang; Tochigi, Mamoru; Ng, Catherine; Yang, Yeqing A; Kwan, Andrew; Kaminsky, Zachary A; Mill, Jonathan; Gunasinghe, Cerisse; Tackett, Jennifer L; Gottesman, Irving I; Willemsen, Gonneke; de Geus, Eco J C; Vink, Jacqueline M; Slagboom, P Eline; Wray, Naomi R; Heath, Andrew C; Montgomery, Grant W; Turecki, Gustavo; Martin, Nicholas G; Boomsma, Dorret I; McGuffin, Peter; Kustra, Rafal; Petronis, Art

2015-02-01

Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations. Copyright © 2015 Society of Biological Psychiatry. All rights reserved.

Identification, occurrence, and validation of DRE and ABRE Cis-regulatory motifs in the promoter regions of genes of Arabidopsis thaliana.

PubMed

Mishra, Sonal; Shukla, Aparna; Upadhyay, Swati; Sanchita; Sharma, Pooja; Singh, Seema; Phukan, Ujjal J; Meena, Abha; Khan, Feroz; Tripathi, Vineeta; Shukla, Rakesh Kumar; Shrama, Ashok

2014-04-01

Plants posses a complex co-regulatory network which helps them to elicit a response under diverse adverse conditions. We used an in silico approach to identify the genes with both DRE and ABRE motifs in their promoter regions in Arabidopsis thaliana. Our results showed that Arabidopsis contains a set of 2,052 genes with ABRE and DRE motifs in their promoter regions. Approximately 72% or more of the total predicted 2,052 genes had a gap distance of less than 400 bp between DRE and ABRE motifs. For positional orientation of the DRE and ABRE motifs, we found that the DR form (one in direct and the other one in reverse orientation) was more prevalent than other forms. These predicted 2,052 genes include 155 transcription factors. Using microarray data from The Arabidopsis Information Resource (TAIR) database, we present 44 transcription factors out of 155 which are upregulated by more than twofold in response to osmotic stress and ABA treatment. Fifty-one transcripts from the one predicted above were validated using semiquantitative expression analysis to support the microarray data in TAIR. Taken together, we report a set of genes containing both DRE and ABRE motifs in their promoter regions in A. thaliana, which can be useful to understand the role of ABA under osmotic stress condition. © 2013 Institute of Botany, Chinese Academy of Sciences.

Identification of a single nucleotide polymorphism indicative of high risk in acute myocardial infarction

PubMed Central

Shalia, Kavita; Saranath, Dhananjaya; Rayar, Jaipreet; Shah, Vinod K.; Mashru, Manoj R.; Soneji, Surendra L.

2017-01-01

Background & objectives: Acute myocardial infarction (AMI) is a major health concern in India. The aim of the study was to identify single nucleotide polymorphisms (SNPs) associated with AMI in patients using dedicated chip and validating the identified SNPs on custom-designed chips using high-throughput microarray analysis. Methods: In pilot phase, 48 AMI patients and 48 healthy controls were screened for SNPs using human CVD55K BeadChip with 48,472 SNP probes on Illumina high-throughput microarray platform. The identified SNPs were validated by genotyping additional 160 patients and 179 controls using custom-made Illumina VeraCode GoldenGate Genotyping Assay. Analysis was carried out using PLINK software. Results: From the pilot phase, 98 SNPs present on 94 genes were identified with increased risk of AMI (odds ratio of 1.84-8.85, P=0.04861-0.003337). Five of these SNPs demonstrated association with AMI in the validation phase (P<0.05). Among these, one SNP rs9978223 on interferon gamma receptor 2 [IFNGR2, interferon (IFN)-gamma transducer 1] gene showed a significant association (P=0.00021) with AMI below Bonferroni corrected P value (P=0.00061). IFNGR2 is the second subunit of the receptor for IFN-gamma, an important cytokine in inflammatory reactions. Interpretation & conclusions: The study identified an SNP rs9978223 on IFNGR2 gene, associated with increased risk in AMI patient from India. PMID:29434065

Identification of neuron-related genes for cell therapy of neurological disorders by network analysis.

PubMed

Su, Li-Ning; Song, Xiao-Qing; Wei, Hui-Ping; Yin, Hai-Feng

Bone mesenchymal stem cells (BMSCs) differentiated into neurons have been widely proposed for use in cell therapy of many neurological disorders. It is therefore important to understand the molecular mechanisms underlying this differentiation. We screened differentially expressed genes between immature neural tissues and untreated BMSCs to identify the genes responsible for neuronal differentiation from BMSCs. GSE68243 gene microarray data of rat BMSCs and GSE18860 gene microarray data of rat neurons were received from the Gene Expression Omnibus database. Transcriptome Analysis Console software showed that 1248 genes were up-regulated and 1273 were down-regulated in neurons compared with BMSCs. Gene Ontology functional enrichment, protein-protein interaction networks, functional modules, and hub genes were analyzed using DAVID, STRING 10, BiNGO tool, and Network Analyzer software, revealing that nine hub genes, Nrcam, Sema3a, Mapk8, Dlg4, Slit1, Creb1, Ntrk2, Cntn2, and Pax6, may play a pivotal role in neuronal differentiation from BMSCs. Seven genes, Dcx, Nrcam, sema3a, Cntn2, Slit1, Ephb1, and Pax6, were shown to be hub nodes within the neuronal development network, while six genes, Fgf2, Tgfβ1, Vegfa, Serpine1, Il6, and Stat1, appeared to play an important role in suppressing neuronal differentiation. However, additional studies are required to confirm these results.

Molecular impact of juvenile hormone agonists on neonatal Daphnia magna.

PubMed

Toyota, Kenji; Kato, Yasuhiko; Miyakawa, Hitoshi; Yatsu, Ryohei; Mizutani, Takeshi; Ogino, Yukiko; Miyagawa, Shinichi; Watanabe, Hajime; Nishide, Hiroyo; Uchiyama, Ikuo; Tatarazako, Norihisa; Iguchi, Taisen

2014-05-01

Daphnia magna has been used extensively to evaluate organism- and population-level responses to pollutants in acute toxicity and reproductive toxicity tests. We have previously reported that exposure to juvenile hormone (JH) agonists results in a reduction of reproductive function and production of male offspring in a cyclic parthenogenesis, D. magna. Recent advances in molecular techniques have provided tools to understand better the responses to pollutants in aquatic organisms, including D. magna. DNA microarray was used to evaluate gene expression profiles of neonatal daphnids exposed to JH agonists: methoprene (125, 250 and 500 ppb), fenoxycarb (0.5, 1 and 2 ppb) and epofenonane (50, 100 and 200 ppb). Exposure to these JH analogs resulted in chemical-specific patterns of gene expression. The heat map analyses based on hierarchical clustering revealed a similar pattern between treatments with a high dose of methoprene and with epofenonane. In contrast, treatment with low to middle doses of methoprene resulted in similar profiles to fenoxycarb treatments. Hemoglobin and JH epoxide hydrolase genes were clustered as JH-responsive genes. These data suggest that fenoxycarb has high activity as a JH agonist, methoprene shows high toxicity and epofenonane works through a different mechanism compared with other JH analogs, agreeing with data of previously reported toxicity tests. In conclusion, D. magna DNA microarray is useful for the classification of JH analogs and identification of JH-responsive genes. Copyright © 2013 John Wiley & Sons, Ltd.

Identification of copy number variations associated with congenital heart disease by chromosomal microarray analysis and next-generation sequencing.

PubMed

Zhu, Xiangyu; Li, Jie; Ru, Tong; Wang, Yaping; Xu, Yan; Yang, Ying; Wu, Xing; Cram, David S; Hu, Yali

2016-04-01

To determine the type and frequency of pathogenic chromosomal abnormalities in fetuses diagnosed with congenital heart disease (CHD) using chromosomal microarray analysis (CMA) and validate next-generation sequencing as an alternative diagnostic method. Chromosomal aneuploidies and submicroscopic copy number variations (CNVs) were identified in amniocytes DNA samples from CHD fetuses using high-resolution CMA and copy number variation sequencing (CNV-Seq). Overall, 21 of 115 CHD fetuses (18.3%) referred for CMA had a pathogenic chromosomal anomaly. In six of 73 fetuses (8.2%) with an isolated CHD, CMA identified two cases of DiGeorge syndrome, and one case each of 1q21.1 microdeletion, 16p11.2 microdeletion and Angelman/Prader Willi syndromes, and 22q11.21 microduplication syndrome. In 12 of 42 fetuses (28.6%) with CHD and additional structural abnormalities, CMA identified eight whole or partial trisomies (19.0%), five CNVs (11.9%) associated with DiGeorge, Wolf-Hirschhorn, Miller-Dieker, Cri du Chat and Blepharophimosis, Ptosis, and Epicanthus Inversus syndromes and four other rare pathogenic CNVs (9.5%). Overall, there was a 100% diagnostic concordance between CMA and CNV-Seq for detecting all 21 pathogenic chromosomal abnormalities associated with CHD. CMA and CNV-Seq are reliable and accurate prenatal techniques for identifying pathogenic fetal chromosomal abnormalities associated with cardiac defects. © 2016 John Wiley & Sons, Ltd. © 2016 John Wiley & Sons, Ltd.

Sparse representation and Bayesian detection of genome copy number alterations from microarray data.

PubMed

Pique-Regi, Roger; Monso-Varona, Jordi; Ortega, Antonio; Seeger, Robert C; Triche, Timothy J; Asgharzadeh, Shahab

2008-02-01

Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) that are associated with the development and behavior of tumors. Advances in microarray technology have allowed for greater resolution in detection of DNA copy number changes (amplifications or deletions) across the genome. However, the increase in number of measured signals and accompanying noise from the array probes present a challenge in accurate and fast identification of breakpoints that define CNA. This article proposes a novel detection technique that exploits the use of piece wise constant (PWC) vectors to represent genome copy number and sparse Bayesian learning (SBL) to detect CNA breakpoints. First, a compact linear algebra representation for the genome copy number is developed from normalized probe intensities. Second, SBL is applied and optimized to infer locations where copy number changes occur. Third, a backward elimination (BE) procedure is used to rank the inferred breakpoints; and a cut-off point can be efficiently adjusted in this procedure to control for the false discovery rate (FDR). The performance of our algorithm is evaluated using simulated and real genome datasets and compared to other existing techniques. Our approach achieves the highest accuracy and lowest FDR while improving computational speed by several orders of magnitude. The proposed algorithm has been developed into a free standing software application (GADA, Genome Alteration Detection Algorithm). http://biron.usc.edu/~piquereg/GADA

Enhanced identification and biological validation of differential gene expression via Illumina whole-genome expression arrays through the use of the model-based background correction methodology

PubMed Central

Ding, Liang-Hao; Xie, Yang; Park, Seongmi; Xiao, Guanghua; Story, Michael D.

2008-01-01

Despite the tremendous growth of microarray usage in scientific studies, there is a lack of standards for background correction methodologies, especially in single-color microarray platforms. Traditional background subtraction methods often generate negative signals and thus cause large amounts of data loss. Hence, some researchers prefer to avoid background corrections, which typically result in the underestimation of differential expression. Here, by utilizing nonspecific negative control features integrated into Illumina whole genome expression arrays, we have developed a method of model-based background correction for BeadArrays (MBCB). We compared the MBCB with a method adapted from the Affymetrix robust multi-array analysis algorithm and with no background subtraction, using a mouse acute myeloid leukemia (AML) dataset. We demonstrated that differential expression ratios obtained by using the MBCB had the best correlation with quantitative RT–PCR. MBCB also achieved better sensitivity in detecting differentially expressed genes with biological significance. For example, we demonstrated that the differential regulation of Tnfr2, Ikk and NF-kappaB, the death receptor pathway, in the AML samples, could only be detected by using data after MBCB implementation. We conclude that MBCB is a robust background correction method that will lead to more precise determination of gene expression and better biological interpretation of Illumina BeadArray data. PMID:18450815

Biomarker selection and classification of "-omics" data using a two-step bayes classification framework.

PubMed

Assawamakin, Anunchai; Prueksaaroon, Supakit; Kulawonganunchai, Supasak; Shaw, Philip James; Varavithya, Vara; Ruangrajitpakorn, Taneth; Tongsima, Sissades

2013-01-01

Identification of suitable biomarkers for accurate prediction of phenotypic outcomes is a goal for personalized medicine. However, current machine learning approaches are either too complex or perform poorly. Here, a novel two-step machine-learning framework is presented to address this need. First, a Naïve Bayes estimator is used to rank features from which the top-ranked will most likely contain the most informative features for prediction of the underlying biological classes. The top-ranked features are then used in a Hidden Naïve Bayes classifier to construct a classification prediction model from these filtered attributes. In order to obtain the minimum set of the most informative biomarkers, the bottom-ranked features are successively removed from the Naïve Bayes-filtered feature list one at a time, and the classification accuracy of the Hidden Naïve Bayes classifier is checked for each pruned feature set. The performance of the proposed two-step Bayes classification framework was tested on different types of -omics datasets including gene expression microarray, single nucleotide polymorphism microarray (SNParray), and surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) proteomic data. The proposed two-step Bayes classification framework was equal to and, in some cases, outperformed other classification methods in terms of prediction accuracy, minimum number of classification markers, and computational time.

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

SIMULATION AND VISUALIZATION OF FLOW PATTERN IN MICROARRAYS FOR LIQUID PHASE OLIGONUCLEOTIDE AND PEPTIDE SYNTHESIS

PubMed Central

O-Charoen, Sirimon; Srivannavit, Onnop; Gulari, Erdogan

2008-01-01

Microfluidic microarrays have been developed for economical and rapid parallel synthesis of oligonucleotide and peptide libraries. For a synthesis system to be reproducible and uniform, it is crucial to have a uniform reagent delivery throughout the system. Computational fluid dynamics (CFD) is used to model and simulate the microfluidic microarrays to study geometrical effects on flow patterns. By proper design geometry, flow uniformity could be obtained in every microreactor in the microarrays. PMID:17480053

The application of DNA microarrays in gene expression analysis.

PubMed

van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

2000-03-31

DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

Sandwich ELISA Microarrays: Generating Reliable and Reproducible Assays for High-Throughput Screens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonzalez, Rachel M.; Varnum, Susan M.; Zangar, Richard C.

The sandwich ELISA microarray is a powerful screening tool in biomarker discovery and validation due to its ability to simultaneously probe for multiple proteins in a miniaturized assay. The technical challenges of generating and processing the arrays are numerous. However, careful attention to possible pitfalls in the development of your antibody microarray assay can overcome these challenges. In this chapter, we describe in detail the steps that are involved in generating a reliable and reproducible sandwich ELISA microarray assay.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.