Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2010-06-01

SELDI-TOF-MS. Additional proteomic profiling studies using NMR- and MS-based metabonomics have been completed, and LC/MS based protein profiling using...Flight mass spectrometry (SELDI-TOF-MS). Changes in proteomic profiles will be confirmed and enhanced using NMR- and MS-based metabonomics , by Dr...performed using NMR- and MS-based metabonomics at Miami University, in the laboratory of Dr. Michael Kennedy. Initial spectra and profiles obtained show

Improving protein complex classification accuracy using amino acid composition profile.

PubMed

Huang, Chien-Hung; Chou, Szu-Yu; Ng, Ka-Lok

2013-09-01

Protein complex prediction approaches are based on the assumptions that complexes have dense protein-protein interactions and high functional similarity between their subunits. We investigated those assumptions by studying the subunits' interaction topology, sequence similarity and molecular function for human and yeast protein complexes. Inclusion of amino acids' physicochemical properties can provide better understanding of protein complex properties. Principal component analysis is carried out to determine the major features. Adopting amino acid composition profile information with the SVM classifier serves as an effective post-processing step for complexes classification. Improvement is based on primary sequence information only, which is easy to obtain. Copyright © 2013 Elsevier Ltd. All rights reserved.

Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

PubMed

Tamimi, Ahmad; Ashhab, Yaqoub; Tamimi, Hashem

2016-01-01

Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.

Evaluating two-dimensional electrophoresis profiles of the protein phaseolin as markers of genetic differentiation and seed protein quality in common bean (Phaseolus vulgaris L.).

PubMed

López-Pedrouso, María; Bernal, Javier; Franco, Daniel; Zapata, Carlos

2014-07-23

High-resolution two-dimensional electrophoresis (2-DE) profiles of the protein phaseolin, the major seed storage protein of common bean, display great number of spots with differentially glycosylated and phosphorylated α- and β-type polypeptides. This work aims to test whether these complex profiles can be useful markers of genetic differentiation and seed protein quality in bean populations. The 2-DE phaseolin profile and the amino acid composition were examined in bean seeds from 18 domesticated and wild accessions belonging to the Mesoamerican and Andean gene pools. We found that proteomic distances based on 2-DE profiles were successful in identifying the accessions belonging to each gene pool and outliers distantly related. In addition, accessions identified as outliers from proteomic distances showed the highest levels of methionine content, an essential amino acid deficient in bean seeds. These findings suggest that 2-DE phaseolin profiles provide valuable information with potential of being used in common bean genetic improvement.

The first decade of MALDI protein profiling: a lesson in translational biomarker research.

PubMed

Albrethsen, Jakob

2011-05-16

MALDI protein profiling has identified several important challenges in omics-based biomarker research. First, research into the analytical performance of a novel omics-platform of potential diagnostic impact must be carried out in a critical manner and according to common guidelines. Evaluation studies should be performed at an early time and preferably before massive advancement into explorative biomarker research. In particular, MALDI profiling underscores the need for an adequate understanding of the causal relationship between molecular abundance and the quantitative measure in multivariate biomarker research. Secondly, MALDI profiling has raised awareness of the significant risk of false-discovery in biomarker research due to several confounding factors, including sample processing and unspecific host-response to disease. Here, the experience from MALDI profiling supports that a central challenge in unbiased molecular profiling is to pinpoint the aberrations of clinical interest among potentially massive unspecific changes that can accompany disease. The lessons from the first decade of MALDI protein profiling are relevant for future efforts in advancing omics-based biomarker research beyond the laboratory setting and into clinical verification. Copyright © 2011 Elsevier B.V. All rights reserved.

Evolutionary profiles from the QR factorization of multiple sequence alignments

PubMed Central

Sethi, Anurag; O'Donoghue, Patrick; Luthey-Schulten, Zaida

2005-01-01

We present an algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of the homologous group. The method, based on the multidimensional QR factorization of numerically encoded multiple sequence alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. We observe a general trend that these smaller, more evolutionarily balanced profiles have comparable and, in many cases, better performance in database searches than conventional profiles containing hundreds of sequences, constructed in an iterative and computationally intensive procedure. For more diverse families or superfamilies, with sequence identity <30%, structural alignments, based purely on the geometry of the protein structures, provide better alignments than pure sequence-based methods. Merging the structure and sequence information allows the construction of accurate profiles for distantly related groups. These structure-based profiles outperformed other sequence-based methods for finding distant homologs and were used to identify a putative class II cysteinyl-tRNA synthetase (CysRS) in several archaea that eluded previous annotation studies. Phylogenetic analysis showed the putative class II CysRSs to be a monophyletic group and homology modeling revealed a constellation of active site residues similar to that in the known class I CysRS. PMID:15741270

A Click Chemistry-Based Proteomic Approach Reveals that 1,2,4-Trioxolane and Artemisinin Antimalarials Share a Common Protein Alkylation Profile.

PubMed

Ismail, Hanafy M; Barton, Victoria E; Panchana, Matthew; Charoensutthivarakul, Sitthivut; Biagini, Giancarlo A; Ward, Stephen A; O'Neill, Paul M

2016-05-23

In spite of the recent increase in endoperoxide antimalarials under development, it remains unclear if all these chemotypes share a common mechanism of action. This is important since it will influence cross-resistance risks between the different classes. Here we investigate this proposition using novel clickable 1,2,4-trioxolane activity based protein-profiling probes (ABPPs). ABPPs with potent antimalarial activity were able to alkylate protein target(s) within the asexual erythrocytic stage of Plasmodium falciparum (3D7). Importantly, comparison of the alkylation fingerprint with that generated from an artemisinin ABPP equivalent confirms a highly conserved alkylation profile, with both endoperoxide classes targeting proteins in the glycolytic, hemoglobin degradation, antioxidant defence, protein synthesis and protein stress pathways, essential biological processes for plasmodial survival. The alkylation signatures of the two chemotypes show significant overlap (ca. 90 %) both qualitatively and semi-quantitatively, suggesting a common mechanism of action that raises concerns about potential cross-resistance liabilities.

Characterising the muscle anabolic potential of dairy, meat and plant-based protein sources in older adults.

PubMed

Gorissen, Stefan H M; Witard, Oliver C

2018-02-01

The age-related loss of skeletal muscle mass and function is caused, at least in part, by a reduced muscle protein synthetic response to protein ingestion. The magnitude and duration of the postprandial muscle protein synthetic response to ingested protein is dependent on the quantity and quality of the protein consumed. This review characterises the anabolic properties of animal-derived and plant-based dietary protein sources in older adults. While approximately 60 % of dietary protein consumed worldwide is derived from plant sources, plant-based proteins generally exhibit lower digestibility, lower leucine content and deficiencies in certain essential amino acids such as lysine and methionine, which compromise the availability of a complete amino acid profile required for muscle protein synthesis. Based on currently available scientific evidence, animal-derived proteins may be considered more anabolic than plant-based protein sources. However, the production and consumption of animal-derived protein sources is associated with higher greenhouse gas emissions, while plant-based protein sources may be considered more environmentally sustainable. Theoretically, the lower anabolic capacity of plant-based proteins can be compensated for by ingesting a greater dose of protein or by combining various plant-based proteins to provide a more favourable amino acid profile. In addition, leucine co-ingestion can further augment the postprandial muscle protein synthetic response. Finally, prior exercise or n-3 fatty acid supplementation have been shown to sensitise skeletal muscle to the anabolic properties of dietary protein. Applying one or more of these strategies may support the maintenance of muscle mass with ageing when diets rich in plant-based protein are consumed.

Assigning protein functions by comparative genome analysis protein phylogenetic profiles

DOEpatents

Pellegrini, Matteo; Marcotte, Edward M.; Thompson, Michael J.; Eisenberg, David; Grothe, Robert; Yeates, Todd O.

2003-05-13

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Using distances between Top-n-gram and residue pairs for protein remote homology detection.

PubMed

Liu, Bin; Xu, Jinghao; Zou, Quan; Xu, Ruifeng; Wang, Xiaolong; Chen, Qingcai

2014-01-01

Protein remote homology detection is one of the central problems in bioinformatics, which is important for both basic research and practical application. Currently, discriminative methods based on Support Vector Machines (SVMs) achieve the state-of-the-art performance. Exploring feature vectors incorporating the position information of amino acids or other protein building blocks is a key step to improve the performance of the SVM-based methods. Two new methods for protein remote homology detection were proposed, called SVM-DR and SVM-DT. SVM-DR is a sequence-based method, in which the feature vector representation for protein is based on the distances between residue pairs. SVM-DT is a profile-based method, which considers the distances between Top-n-gram pairs. Top-n-gram can be viewed as a profile-based building block of proteins, which is calculated from the frequency profiles. These two methods are position dependent approaches incorporating the sequence-order information of protein sequences. Various experiments were conducted on a benchmark dataset containing 54 families and 23 superfamilies. Experimental results showed that these two new methods are very promising. Compared with the position independent methods, the performance improvement is obvious. Furthermore, the proposed methods can also provide useful insights for studying the features of protein families. The better performance of the proposed methods demonstrates that the position dependant approaches are efficient for protein remote homology detection. Another advantage of our methods arises from the explicit feature space representation, which can be used to analyze the characteristic features of protein families. The source code of SVM-DT and SVM-DR is available at http://bioinformatics.hitsz.edu.cn/DistanceSVM/index.jsp.

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles

PubMed Central

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G.; Gelly, Jean-Christophe

2016-01-01

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation —with Protein Blocks—, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the ‘Hard’ category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/. PMID:27319297

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles.

PubMed

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G; Gelly, Jean-Christophe

2016-06-20

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation -with Protein Blocks-, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the 'Hard' category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.

Similar protein expression profiles of ovarian and endometrial high-grade serous carcinomas.

PubMed

Hiramatsu, Kosuke; Yoshino, Kiyoshi; Serada, Satoshi; Yoshihara, Kosuke; Hori, Yumiko; Fujimoto, Minoru; Matsuzaki, Shinya; Egawa-Takata, Tomomi; Kobayashi, Eiji; Ueda, Yutaka; Morii, Eiichi; Enomoto, Takayuki; Naka, Tetsuji; Kimura, Tadashi

2016-03-01

Ovarian and endometrial high-grade serous carcinomas (HGSCs) have similar clinical and pathological characteristics; however, exhaustive protein expression profiling of these cancers has yet to be reported. We performed protein expression profiling on 14 cases of HGSCs (7 ovarian and 7 endometrial) and 18 endometrioid carcinomas (9 ovarian and 9 endometrial) using iTRAQ-based exhaustive and quantitative protein analysis. We identified 828 tumour-expressed proteins and evaluated the statistical similarity of protein expression profiles between ovarian and endometrial HGSCs using unsupervised hierarchical cluster analysis (P<0.01). Using 45 statistically highly expressed proteins in HGSCs, protein ontology analysis detected two enriched terms and proteins composing each term: IMP2 and MCM2. Immunohistochemical analyses confirmed the higher expression of IMP2 and MCM2 in ovarian and endometrial HGSCs as well as in tubal and peritoneal HGSCs than in endometrioid carcinomas (P<0.01). The knockdown of either IMP2 or MCM2 by siRNA interference significantly decreased the proliferation rate of ovarian HGSC cell line (P<0.01). We demonstrated the statistical similarity of the protein expression profiles of ovarian and endometrial HGSC beyond the organs. We suggest that increased IMP2 and MCM2 expression may underlie some of the rapid HGSC growth observed clinically.

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling*

PubMed Central

Larance, Mark; Kirkwood, Kathryn J.; Tinti, Michele; Brenes Murillo, Alejandro; Ferguson, Michael A. J.; Lamond, Angus I.

2016-01-01

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754). PMID:27114452

Plasma Protein Turnover Rates in Rats Using Stable Isotope Labeling, Global Proteomics, and Activity-Based Protein Profiling

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

Smith, Jordan Ned; Tyrrell, Kimberly J.; Hansen, Joshua R.

Protein turnover is important for general health on cellular and organism scales providing a strategy to replace old, damaged, or dysfunctional proteins. Protein turnover also informs of biomarker kinetics, as a better understanding of synthesis and degradation of proteins increases the clinical utility of biomarkers. Here, turnover rates of plasma proteins in rats were measured in vivo using a pulse-chase stable isotope labeling experiment. During the pulse, rats (n=5) were fed 13C6-labeled lysine (“heavy”) feed for 23 days to label proteins. During the chase, feed was changed to an unlabeled equivalent feed (“light”), and blood was repeatedly sampled from ratsmore » over 10 time points for 28 days. Plasma samples were digested with trypsin, and analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS). MaxQuant was used to identify peptides and proteins, and quantify heavy:light lysine ratios. A system of ordinary differential equations was used to calculate protein turnover rates. Using this approach, 273 proteins were identified, and turnover rates were quantified for 157 plasma proteins with half-lives ranging 0.3-103 days. For the ~70 most abundant proteins, variability in turnover rates among rats was low (median coefficient of variation: 0.09). Activity-based protein profiling was applied to pooled plasma samples to enrich serine hydrolases using a fluorophosphonate (FP2) activity-based probe. This enrichment resulted in turnover rates for an additional 17 proteins. This study is the first to measure global plasma protein turnover rates in rats in vivo, measure variability of protein turnover rates in any animal model, and utilize activity-based protein profiling for enhancing measurements of targeted, low-abundant proteins, such as those commonly used as biomarkers. Measured protein turnover rates will be important for understanding of the role of protein turnover in cellular and organism health as well as increasing the utility of protein biomarkers through better understanding of processes governing biomarker kinetics.« less

Phylo_dCor: distance correlation as a novel metric for phylogenetic profiling.

PubMed

Sferra, Gabriella; Fratini, Federica; Ponzi, Marta; Pizzi, Elisabetta

2017-09-05

Elaboration of powerful methods to predict functional and/or physical protein-protein interactions from genome sequence is one of the main tasks in the post-genomic era. Phylogenetic profiling allows the prediction of protein-protein interactions at a whole genome level in both Prokaryotes and Eukaryotes. For this reason it is considered one of the most promising methods. Here, we propose an improvement of phylogenetic profiling that enables handling of large genomic datasets and infer global protein-protein interactions. This method uses the distance correlation as a new measure of phylogenetic profile similarity. We constructed robust reference sets and developed Phylo-dCor, a parallelized version of the algorithm for calculating the distance correlation that makes it applicable to large genomic data. Using Saccharomyces cerevisiae and Escherichia coli genome datasets, we showed that Phylo-dCor outperforms phylogenetic profiling methods previously described based on the mutual information and Pearson's correlation as measures of profile similarity. In this work, we constructed and assessed robust reference sets and propose the distance correlation as a measure for comparing phylogenetic profiles. To make it applicable to large genomic data, we developed Phylo-dCor, a parallelized version of the algorithm for calculating the distance correlation. Two R scripts that can be run on a wide range of machines are available upon request.

Aureolib — A Proteome Signature Library: Towards an Understanding of Staphylococcus aureus Pathophysiology

PubMed Central

Pané-Farré, Jan; Kusch, Harald; Wolf, Carmen; Reiß, Swantje; Binh, Le Thi Nguyen; Albrecht, Dirk; Riedel, Katharina; Hecker, Michael; Engelmann, Susanne

2013-01-01

Gel-based proteomics is a powerful approach to study the physiology of Staphylococcus aureus under various growth restricting conditions. We analyzed 679 protein spots from a reference 2-dimensional gel of cytosolic proteins of S. aureus COL by mass spectrometry resulting in 521 different proteins. 4,692 time dependent protein synthesis profiles were generated by exposing S. aureus to nine infection-related stress and starvation stimuli (H2O2, diamide, paraquat, NO, fermentation, nitrate respiration, heat shock, puromycin, mupirocin). These expression profiles are stored in an online resource called Aureolib (http://www.aureolib.de). Moreover, information on target genes of 75 regulators and regulatory elements were included in the database. Cross-comparisons of this extensive data collection of protein synthesis profiles using the tools implemented in Aureolib lead to the identification of stress and starvation specific marker proteins. Altogether, 226 protein synthesis profiles showed induction ratios of 2.5-fold or higher under at least one of the tested conditions with 157 protein synthesis profiles specifically induced in response to a single stimulus. The respective proteins might serve as marker proteins for the corresponding stimulus. By contrast, proteins whose synthesis was increased or repressed in response to more than four stimuli are rather exceptional. The only protein that was induced by six stimuli is the universal stress protein SACOL1759. Most strikingly, cluster analyses of synthesis profiles of proteins differentially synthesized under at least one condition revealed only in rare cases a grouping that correlated with known regulon structures. The most prominent examples are the GapR, Rex, and CtsR regulon. In contrast, protein synthesis profiles of proteins belonging to the CodY and σB regulon are widely distributed. In summary, Aureolib is by far the most comprehensive protein expression database for S. aureus and provides an essential tool to decipher more complex adaptation processes in S. aureus during host pathogen interaction. PMID:23967085

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2008-12-01

Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences. In this paper, a novel building block of proteins called Top-n-grams is presented, which contains the evolutionary information extracted from the protein sequence frequency profiles. The protein sequence frequency profiles are calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into Top-n-grams. The protein sequences are transformed into fixed-dimension feature vectors by the occurrence times of each Top-n-gram. The training vectors are evaluated by SVM to train classifiers which are then used to classify the test protein sequences. We demonstrate that the prediction performance of remote homology detection and fold recognition can be improved by combining Top-n-grams and latent semantic analysis (LSA), which is an efficient feature extraction technique from natural language processing. When tested on superfamily and fold benchmarks, the method combining Top-n-grams and LSA gives significantly better results compared to related methods. The method based on Top-n-grams significantly outperforms the methods based on many other building blocks including N-grams, patterns, motifs and binary profiles. Therefore, Top-n-gram is a good building block of the protein sequences and can be widely used in many tasks of the computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the prediction of protein binding sites.

Comparative Activity-Based Flavin-Dependent Oxidase Profiling.

PubMed

Krysiak, Joanna; Breinbauer, Rolf

2017-01-01

Activity-based protein profiling (ABPP) has become a powerful chemoproteomic technology allowing for the dissection of complex ligand-protein interactions in their native cellular environment. One of the biggest challenges for ABPP is the extension of the proteome coverage. In this chapter a new ABPP strategy dedicated to monoamine oxidases (MAO) is presented. These enzymes are representative examples of flavin-dependent oxidases, playing a crucial role in the regulation of nervous system signaling.

Profiling charge complementarity and selectivity for binding at the protein surface.

PubMed

Sulea, Traian; Purisima, Enrico O

2003-05-01

A novel analysis and representation of the protein surface in terms of electrostatic binding complementarity and selectivity is presented. The charge optimization methodology is applied in a probe-based approach that simulates the binding process to the target protein. The molecular surface is color coded according to calculated optimal charge or according to charge selectivity, i.e., the binding cost of deviating from the optimal charge. The optimal charge profile depends on both the protein shape and charge distribution whereas the charge selectivity profile depends only on protein shape. High selectivity is concentrated in well-shaped concave pockets, whereas solvent-exposed convex regions are not charge selective. This suggests the synergy of charge and shape selectivity hot spots toward molecular selection and recognition, as well as the asymmetry of charge selectivity at the binding interface of biomolecular systems. The charge complementarity and selectivity profiles map relevant electrostatic properties in a readily interpretable way and encode information that is quite different from that visualized in the standard electrostatic potential map of unbound proteins.

Contribution of Fermentation Yeast to Final Amino Acid Profile in DDGS

USDA-ARS?s Scientific Manuscript database

One major factor affecting DDGS quality and market values is amino acid (AA) composition. DDGS proteins come from corn and yeast. Yet, the effect of fermentation yeast on DDGS protein quantity and quality (AA profile) has not been well documented. Based on literature review, there are at least 4 met...

Protein profiling in potato (Solanum tuberosum L.) leaf tissues by differential centrifugation.

PubMed

Lim, Sanghyun; Chisholm, Kenneth; Coffin, Robert H; Peters, Rick D; Al-Mughrabi, Khalil I; Wang-Pruski, Gefu; Pinto, Devanand M

2012-04-06

Foliar diseases, such as late blight, result in serious threats to potato production. As such, potato leaf tissue becomes an important substrate to study biological processes, such as plant defense responses to infection. Nonetheless, the potato leaf proteome remains poorly characterized. Here, we report protein profiling of potato leaf tissues using a modified differential centrifugation approach to separate the leaf tissues into cell wall and cytoplasmic fractions. This method helps to increase the number of identified proteins, including targeted putative cell wall proteins. The method allowed for the identification of 1484 nonredundant potato leaf proteins, of which 364 and 447 were reproducibly identified proteins in the cell wall and cytoplasmic fractions, respectively. Reproducibly identified proteins corresponded to over 70% of proteins identified in each replicate. A diverse range of proteins was identified based on their theoretical pI values, molecular masses, functional classification, and biological processes. Such a protein extraction method is effective for the establishment of a highly qualified proteome profile.

The Skeletal Muscle Anabolic Response to Plant- versus Animal-Based Protein Consumption.

PubMed

van Vliet, Stephan; Burd, Nicholas A; van Loon, Luc J C

2015-09-01

Clinical and consumer market interest is increasingly directed toward the use of plant-based proteins as dietary components aimed at preserving or increasing skeletal muscle mass. However, recent evidence suggests that the ingestion of the plant-based proteins in soy and wheat results in a lower muscle protein synthetic response when compared with several animal-based proteins. The possible lower anabolic properties of plant-based protein sources may be attributed to the lower digestibility of plant-based sources, in addition to greater splanchnic extraction and subsequent urea synthesis of plant protein-derived amino acids compared with animal-based proteins. The latter may be related to the relative lack of specific essential amino acids in plant- as opposed to animal-based proteins. Furthermore, most plant proteins have a relatively low leucine content, which may further reduce their anabolic properties when compared with animal proteins. However, few studies have actually assessed the postprandial muscle protein synthetic response to the ingestion of plant proteins, with soy and wheat protein being the primary sources studied. Despite the proposed lower anabolic properties of plant vs. animal proteins, various strategies may be applied to augment the anabolic properties of plant proteins. These may include the following: 1) fortification of plant-based protein sources with the amino acids methionine, lysine, and/or leucine; 2) selective breeding of plant sources to improve amino acid profiles; 3) consumption of greater amounts of plant-based protein sources; or 4) ingesting multiple protein sources to provide a more balanced amino acid profile. However, the efficacy of such dietary strategies on postprandial muscle protein synthesis remains to be studied. Future research comparing the anabolic properties of a variety of plant-based proteins should define the preferred protein sources to be used in nutritional interventions to support skeletal muscle mass gain or maintenance in both healthy and clinical populations. © 2015 American Society for Nutrition.

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Improvement in Protein Domain Identification Is Reached by Breaking Consensus, with the Agreement of Many Profiles and Domain Co-occurrence

PubMed Central

Bernardes, Juliana; Zaverucha, Gerson; Vaquero, Catherine; Carbone, Alessandra

2016-01-01

Traditional protein annotation methods describe known domains with probabilistic models representing consensus among homologous domain sequences. However, when relevant signals become too weak to be identified by a global consensus, attempts for annotation fail. Here we address the fundamental question of domain identification for highly divergent proteins. By using high performance computing, we demonstrate that the limits of state-of-the-art annotation methods can be bypassed. We design a new strategy based on the observation that many structural and functional protein constraints are not globally conserved through all species but might be locally conserved in separate clades. We propose a novel exploitation of the large amount of data available: 1. for each known protein domain, several probabilistic clade-centered models are constructed from a large and differentiated panel of homologous sequences, 2. a decision-making protocol combines outcomes obtained from multiple models, 3. a multi-criteria optimization algorithm finds the most likely protein architecture. The method is evaluated for domain and architecture prediction over several datasets and statistical testing hypotheses. Its performance is compared against HMMScan and HHblits, two widely used search methods based on sequence-profile and profile-profile comparison. Due to their closeness to actual protein sequences, clade-centered models are shown to be more specific and functionally predictive than the broadly used consensus models. Based on them, we improved annotation of Plasmodium falciparum protein sequences on a scale not previously possible. We successfully predict at least one domain for 72% of P. falciparum proteins against 63% achieved previously, corresponding to 30% of improvement over the total number of Pfam domain predictions on the whole genome. The method is applicable to any genome and opens new avenues to tackle evolutionary questions such as the reconstruction of ancient domain duplications, the reconstruction of the history of protein architectures, and the estimation of protein domain age. Website and software: http://www.lcqb.upmc.fr/CLADE. PMID:27472895

Prioritization of candidate disease genes by topological similarity between disease and protein diffusion profiles.

PubMed

Zhu, Jie; Qin, Yufang; Liu, Taigang; Wang, Jun; Zheng, Xiaoqi

2013-01-01

Identification of gene-phenotype relationships is a fundamental challenge in human health clinic. Based on the observation that genes causing the same or similar phenotypes tend to correlate with each other in the protein-protein interaction network, a lot of network-based approaches were proposed based on different underlying models. A recent comparative study showed that diffusion-based methods achieve the state-of-the-art predictive performance. In this paper, a new diffusion-based method was proposed to prioritize candidate disease genes. Diffusion profile of a disease was defined as the stationary distribution of candidate genes given a random walk with restart where similarities between phenotypes are incorporated. Then, candidate disease genes are prioritized by comparing their diffusion profiles with that of the disease. Finally, the effectiveness of our method was demonstrated through the leave-one-out cross-validation against control genes from artificial linkage intervals and randomly chosen genes. Comparative study showed that our method achieves improved performance compared to some classical diffusion-based methods. To further illustrate our method, we used our algorithm to predict new causing genes of 16 multifactorial diseases including Prostate cancer and Alzheimer's disease, and the top predictions were in good consistent with literature reports. Our study indicates that integration of multiple information sources, especially the phenotype similarity profile data, and introduction of global similarity measure between disease and gene diffusion profiles are helpful for prioritizing candidate disease genes. Programs and data are available upon request.

Relating drug–protein interaction network with drug side effects

PubMed Central

Mizutani, Sayaka; Pauwels, Edouard; Stoven, Véronique; Goto, Susumu; Yamanishi, Yoshihiro

2012-01-01

Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system–wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs. Results: We performed a large-scale analysis to extract correlated sets of targeted proteins and side effects, based on the co-occurrence of drugs in protein-binding profiles and side effect profiles, using sparse canonical correlation analysis. The analysis of 658 drugs with the two profiles for 1368 proteins and 1339 side effects led to the extraction of 80 correlated sets. Enrichment analyses using KEGG and Gene Ontology showed that most of the correlated sets were significantly enriched with proteins that are involved in the same biological pathways, even if their molecular functions are different. This allowed for a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. The extracted side effects can be regarded as possible phenotypic outcomes by drugs targeting the proteins that appear in the same correlated set. The proposed method is expected to be useful for predicting potential side effects of new drug candidate compounds based on their protein-binding profiles. Supplementary information: Datasets and all results are available at http://web.kuicr.kyoto-u.ac.jp/supp/smizutan/target-effect/. Availability: Software is available at the above supplementary website. Contact: yamanishi@bioreg.kyushu-u.ac.jp, or goto@kuicr.kyoto-u.ac.jp PMID:22962476

A new approach for rapid detection and typing of serum monoclonal components.

PubMed

Cacoub, P; Camproux, A C; Thiolières, J M; Assogba, U; Hausfater, P; Mallet, A; Foglietti, M J; Piette, J C; Bernard, M

2000-12-01

When used independently, none of the routine methods to explore serum monoclonal components (MC), including: serum protein electrophoresis (SPE), immunoelectrophoresis (IEP), kappa to lambda ratio (KLR) and immunofixation (IFE), provides a comprehensive quantitative and qualitative identification of the MC. In the past few years the concept of 'protein profile', based on immunonephelometric quantifications of serum proteins, has become widely used. It consists of a qualitative and quantitative graphic representation of numerous serum proteins including immunoglobulins. Aim of study was to develop a multidimensional model based exclusively on protein profiles labeled the protein profile prediction method (PPPM) to improve routine MC detection and typing. Serum samples from 127 hospitalized patients and 99 healthy blood donors were submitted to all of the following: SPE, IFE, KLR and a protein profile (which included IgM, IgA, IgG, kappa and lambda chain detections and quantification). The presence of a MC using IFE was chosen as the gold standard. Healthy donors and patients were randomly divided into two groups defined as testing and validation groups. A logistic model was designed based on the protein profiles of the testing group leading to the determination of a threshold value (called Z(r)) for MC detection. It was then tested to detect MC in the validation group. Using IFE, 73 MC were found in the 127 hospitalized patients. Using the threshold value for MC detection of Z(r)=1.86, the PPPM showed greater sensitivity (94.6%) in detecting a MC compared to either SPE (64.8%) or KLR (89.2%). This result was obtained without diminished specificity (80.8%). The association of SPE or KLR to PPPM did not significantly increase the sensitivity of the PPPM. In the validation group, for samples which had a high predictive probability of a MC using PPPM, the correct MC typing was identified in up to 77% of sera using PPPM only. These results may be interesting in helping to determine when supplementary IFE analysis is required to qualitatively analyze a MC. PPPM allows MC detection with great sensitivity. The immune protein profile dramatically increases the sensitivity of either SPE and/or KLR in detecting MC and may also allow heavy and light chain typing.

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

Specific identification of Bacillus anthracis strains

NASA Astrophysics Data System (ADS)

Krishnamurthy, Thaiya; Deshpande, Samir; Hewel, Johannes; Liu, Hongbin; Wick, Charles H.; Yates, John R., III

2007-01-01

Accurate identification of human pathogens is the initial vital step in treating the civilian terrorism victims and military personnel afflicted in biological threat situations. We have applied a powerful multi-dimensional protein identification technology (MudPIT) along with newly generated software termed Profiler to identify the sequences of specific proteins observed for few strains of Bacillus anthracis, a human pathogen. Software termed Profiler was created to initially screen the MudPIT data of B. anthracis strains and establish the observed proteins specific for its strains. A database was also generated using Profiler containing marker proteins of B. anthracis and its strains, which in turn could be used for detecting the organism and its corresponding strains in samples. Analysis of the unknowns by our methodology, combining MudPIT and Profiler, led to the accurate identification of the anthracis strains present in samples. Thus, a new approach for the identification of B. anthracis strains in unknown samples, based on the molecular mass and sequences of marker proteins, has been ascertained.

[FEATURES OF MASS-SPECTROMETRIC PROTEIN PROFILES OF STRAINS OF BRUCELLOSIS CAUSATIVE AGENT DURING PREPARATION OF CULTURE ON VARIOUS NUTRIENT MEDIA].

PubMed

Ulshina, D V; Kovalev, D A; Zhirov, A M; Zharinova, N V; Khudoleev, A A; Kogotkova, O I; Efremenko, V I; Evchenko, N I; Kulichenko, A N

2016-01-01

Carry out comparative analysis using time-of-flight mass-spectrometry with matrix laser desorption/ionization (MALDI-TOF MS) of protein profiles of brucellosis causative agents (Brucella melitensis Rev-1 and Brucella abortus 19BA), cultivated in various nutrient media: Albimi agar, brucellagar and erythrit-agar. Vaccine,strains: Brucella melitensis Rev-1 and Brucella abortus 19BA. Protein profiling in linear mode on Microflex "Bruker Daltonics" MALDI-TOF mass-spectrometer. A number of characteristic features of brucella mass-spectra was detected: in particular, preservation of the total qualitative composition of protein profiles of cultures and significant differences in the intensity of separate peaks depending on the nutrient medium used. Based on the analysis of the data obtained, use of Albimi agar as the nutrient medium for preparation of brucella culture samples for mass-spectrometric analysis was shown to be optimal.

Muscle Protein Profiles Used for Prediction of Texture of Farmed Salmon (Salmo salar L.).

PubMed

Ørnholt-Johansson, Gine; Frosch, Stina; Gudjónsdóttir, María; Wulff, Tune; Jessen, Flemming

2017-04-26

A soft texture is undesired in Atlantic salmon as it leads to downgrading and reduced yield, yet it is a factor for which the cause is not fully understood. This lack of understanding highlights the need for identifying the cause of the soft texture and developing solutions by which the processing industry can improve the yield. Changes in muscle protein profiles can occur both pre- and postharvest and constitute an overall characterization of the muscle properties including texture. The aim of this study was to investigate this relationship between specific muscle proteins and the texture of the salmon fillet. Samples for 2D-gel-based proteomics were taken from the fillet above the lateral line at the same position as where the texture had been measured. The resulting protein profiles were analyzed using multivariate data analysis. Sixteen proteins were found to correlate to the measured texture, showing that it is possible to predict peak force based on a small subset of proteins. Additionally, eight of the 16 proteins were identified by tandem mass spectrometry including serum albumin, dipeptidyl peptidase 3, heat shock protein 70, annexins, and a protein presumed to be a titin fragment. It is contemplated that the identification of these proteins and their significance for the measured texture will contribute to further understanding of the Atlantic salmon muscle texture.

Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study

PubMed Central

Weißenborn, Sandra; Walther, Dirk

2017-01-01

Despite many developed experimental and computational approaches, functional gene annotation remains challenging. With the rapidly growing number of sequenced genomes, the concept of phylogenetic profiling, which predicts functional links between genes that share a common co-occurrence pattern across different genomes, has gained renewed attention as it promises to annotate gene functions based on presence/absence calls alone. We applied phylogenetic profiling to the problem of metabolic pathway assignments of plant genes with a particular focus on secondary metabolism pathways. We determined phylogenetic profiles for 40,960 metabolic pathway enzyme genes with assigned EC numbers from 24 plant species based on sequence and pathway annotation data from KEGG and Ensembl Plants. For gene sequence family assignments, needed to determine the presence or absence of particular gene functions in the given plant species, we included data of all 39 species available at the Ensembl Plants database and established gene families based on pairwise sequence identities and annotation information. Aside from performing profiling comparisons, we used machine learning approaches to predict pathway associations from phylogenetic profiles alone. Selected metabolic pathways were indeed found to be composed of gene families of greater than expected phylogenetic profile similarity. This was particularly evident for primary metabolism pathways, whereas for secondary pathways, both the available annotation in different species as well as the abstraction of functional association via distinct pathways proved limiting. While phylogenetic profile similarity was generally not found to correlate with gene co-expression, direct physical interactions of proteins were reflected by a significantly increased profile similarity suggesting an application of phylogenetic profiling methods as a filtering step in the identification of protein-protein interactions. This feasibility study highlights the potential and challenges associated with phylogenetic profiling methods for the detection of functional relationships between genes as well as the need to enlarge the set of plant genes with proven secondary metabolism involvement as well as the limitations of distinct pathways as abstractions of relationships between genes. PMID:29163570

Differential identification of Candida species and other yeasts by analysis of (/sup 35/S)methionine-labeled polypeptide profiles

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

Shen, H.D.; Choo, K.B.; Tsai, W.C.

1988-12-01

This paper describes a scheme for differential identification of Candida species and other yeasts based on autoradiographic analysis of protein profiles of (/sup 35/S)methionine-labeled cellular proteins separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Using ATCC strains as references, protein profile analysis showed that different Candida and other yeast species produced distinctively different patterns. Good agreement in results obtained with this approach and with other conventional systems was observed. Being accurate and reproducible, this approach provides a basis for the development of an alternative method for the identification of yeasts isolated from clinical specimens.

Reconstruction of SAXS Profiles from Protein Structures

PubMed Central

Putnam, Daniel K.; Lowe, Edward W.

2013-01-01

Small angle X-ray scattering (SAXS) is used for low resolution structural characterization of proteins often in combination with other experimental techniques. After briefly reviewing the theory of SAXS we discuss computational methods based on 1) the Debye equation and 2) Spherical Harmonics to compute intensity profiles from a particular macromolecular structure. Further, we review how these formulas are parameterized for solvent density and hydration shell adjustment. Finally we introduce our solution to compute SAXS profiles utilizing GPU acceleration. PMID:24688746

Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.

PubMed

Wimmer, Helge; Gundacker, Nina C; Griss, Johannes; Haudek, Verena J; Stättner, Stefan; Mohr, Thomas; Zwickl, Hannes; Paulitschke, Verena; Baron, David M; Trittner, Wolfgang; Kubicek, Markus; Bayer, Editha; Slany, Astrid; Gerner, Christopher

2009-06-01

Interpretation of proteome data with a focus on biomarker discovery largely relies on comparative proteome analyses. Here, we introduce a database-assisted interpretation strategy based on proteome profiles of primary cells. Both 2-D-PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2-D gels of cytoplasmic fractions, we typically identify several hundred proteins. Using the same protein fractions, we usually identify more than thousand proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the proteins identified in the 2-D gels. Many characteristic differences in protein expression of different cells can thus be independently confirmed. Our self-designed SQL database (CPL/MUW - database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of protein identification data, which are based on MS, (ii) the detection of cell type-specific proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of proteome profiles obtained from human liver tissue and hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna-database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of proteome profiling experiments.

Mixed-mode ion exchange-based integrated proteomics technology for fast and deep plasma proteome profiling.

PubMed

Xue, Lu; Lin, Lin; Zhou, Wenbin; Chen, Wendong; Tang, Jun; Sun, Xiujie; Huang, Peiwu; Tian, Ruijun

2018-06-09

Plasma proteome profiling by LC-MS based proteomics has drawn great attention recently for biomarker discovery from blood liquid biopsy. Due to standard multi-step sample preparation could potentially cause plasma protein degradation and analysis variation, integrated proteomics sample preparation technologies became promising solution towards this end. Here, we developed a fully integrated proteomics sample preparation technology for both fast and deep plasma proteome profiling under its native pH. All the sample preparation steps, including protein digestion and two-dimensional fractionation by both mixed-mode ion exchange and high-pH reversed phase mechanism were integrated into one spintip device for the first time. The mixed-mode ion exchange beads design achieved the sample loading at neutral pH and protein digestion within 30 min. Potential sample loss and protein degradation by pH changing could be voided. 1 μL of plasma sample with depletion of high abundant proteins was processed by the developed technology with 12 equally distributed fractions and analyzed with 12 h of LC-MS gradient time, resulting in the identification of 862 proteins. The combination of the Mixed-mode-SISPROT and data-independent MS method achieved fast plasma proteome profiling in 2 h with high identification overlap and quantification precision for a proof-of-concept study of plasma samples from 5 healthy donors. We expect that the Mixed-mode-SISPROT become a generally applicable sample preparation technology for clinical oriented plasma proteome profiling. Copyright © 2018 Elsevier B.V. All rights reserved.

Profiling Charge Complementarity and Selectivity for Binding at the Protein Surface

PubMed Central

Sulea, Traian; Purisima, Enrico O.

2003-01-01

A novel analysis and representation of the protein surface in terms of electrostatic binding complementarity and selectivity is presented. The charge optimization methodology is applied in a probe-based approach that simulates the binding process to the target protein. The molecular surface is color coded according to calculated optimal charge or according to charge selectivity, i.e., the binding cost of deviating from the optimal charge. The optimal charge profile depends on both the protein shape and charge distribution whereas the charge selectivity profile depends only on protein shape. High selectivity is concentrated in well-shaped concave pockets, whereas solvent-exposed convex regions are not charge selective. This suggests the synergy of charge and shape selectivity hot spots toward molecular selection and recognition, as well as the asymmetry of charge selectivity at the binding interface of biomolecular systems. The charge complementarity and selectivity profiles map relevant electrostatic properties in a readily interpretable way and encode information that is quite different from that visualized in the standard electrostatic potential map of unbound proteins. PMID:12719221

Analysis of protein profiles in diabetic rat blood plasma that induced by alloxan

NASA Astrophysics Data System (ADS)

Hidayati, Dewi; Abdulgani, Nurlita; Setiyawan, Hengki; Trisnawati, Indah; Ashuri, Nova Maulidina; Sa'adah, Noor Nailis

2017-06-01

Proteomics is the study to identify the proteins involved in physiological metabolic pathway. The protein profiles of blood plasma from alloxan-induced diabetic rats has investigated using Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis (SDS-PAGE). Data were analyzed descriptively based on variations of the type and intensity of the protein. There were identified the similarity of protein variant between diabetic and control rats included ankyrin (200kDa), IgG (150kDa), nephrin (136 kDa), IDE (112 kDA), albumin (66 kDa), prealbumin (55 kDA), CICP (43 kDa), ApoA-V (39 kDa), GAPDH (35 kDa), C-RP (27,1 kDa), leptin (16 kDa) and apelin (13 kDa). However, the apelin profile at diabetic rats shows the higher intensity than control.

Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP).

PubMed

Ma, Hongyan; Delafield, Daniel G; Wang, Zhe; You, Jianlan; Wu, Si

2017-04-01

The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion. Graphical Abstract ᅟ.

Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP)

NASA Astrophysics Data System (ADS)

Ma, Hongyan; Delafield, Daniel G.; Wang, Zhe; You, Jianlan; Wu, Si

2017-04-01

The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion.

Urine protein profiling identified alpha-1-microglobulin and haptoglobin as biomarkers for early diagnosis of acute allograft rejection following kidney transplantation.

PubMed

Stubendorff, Beatrice; Finke, Stephanie; Walter, Martina; Kniemeyer, Olaf; von Eggeling, Ferdinand; Gruschwitz, Torsten; Steiner, Thomas; Ott, Undine; Wolf, Gunter; Wunderlich, Heiko; Junker, Kerstin

2014-12-01

Early diagnosis of acute rejection and effective immunosuppressive therapy lead to improvement in graft survival following kidney transplantation. In this study, we aimed to establish a urinary protein profile suitable to distinguish between patients with rejection and stable graft function and to predict acute rejection based on postoperatively collected urine samples. A further objective was to identify candidate proteins for the use as biomarkers in clinical practice. Urine samples of 116 kidney recipients were included. Rejection was proven by biopsy (n = 58), and stable transplant function was monitored for at least 2 years (n = 58). Postoperative urine samples were collected between 3rd and 10th day following transplantation. Urinary protein profiles were obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Protein identification and validation were performed using multiplex fluorescence 2DE, peptide mass fingerprinting and enzyme-linked immunosorbent assay. A protein profile including four mass peaks differentiated acute rejection from stable transplants at the time point of rejection and at the postoperative state with 73 % sensitivity and 88 % specificity. Alpha-1-microglobulin (A1MG) and Haptoglobin (Hp) were identified as putative rejection biomarkers. Protein levels were significantly higher in postoperative urine from patients with rejection (A1MG 29.13 vs. 22.06 μg/ml, p = 0.001; Hp 628.34 vs. 248.57 ng/ml, p = 0.003). The combination of both proteins enabled the diagnosis of early rejection with 85 % sensitivity and 80 % specificity. Protein profiling using mass spectrometry is suitable for noninvasive detection of rejection-specific changes following kidney transplantation. A specific protein profile enables the prediction of early acute allograft rejection in the immediate postoperative period. A1MG and Hp appear to be reliable rejection biomarkers.

HangOut: generating clean PSI-BLAST profiles for domains with long insertions.

PubMed

Kim, Bong-Hyun; Cong, Qian; Grishin, Nick V

2010-06-15

Profile-based similarity search is an essential step in structure-function studies of proteins. However, inclusion of non-homologous sequence segments into a profile causes its corruption and results in false positives. Profile corruption is common in multidomain proteins, and single domains with long insertions are a significant source of errors. We developed a procedure (HangOut) that, for a single domain with specified insertion position, cleans erroneously extended PSI-BLAST alignments to generate better profiles. HangOut is implemented in Python 2.3 and runs on all Unix-compatible platforms. The source code is available under the GNU GPL license at http://prodata.swmed.edu/HangOut/. Supplementary data are available at Bioinformatics online.

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

PubMed

Jiang, Li; Edwards, Stefan M; Thomsen, Bo; Workman, Christopher T; Guldbrandtsen, Bernt; Sørensen, Peter

2014-09-24

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.

Hierarchical Partitioning of Metazoan Protein Conservation Profiles Provides New Functional Insights

PubMed Central

Witztum, Jonathan; Persi, Erez; Horn, David; Pasmanik-Chor, Metsada; Chor, Benny

2014-01-01

The availability of many complete, annotated proteomes enables the systematic study of the relationships between protein conservation and functionality. We explore this question based solely on the presence or absence of protein homologues (a.k.a. conservation profiles). We study 18 metazoans, from two distinct points of view: the human's and the fly's. Using the GOrilla gene ontology (GO) analysis tool, we explore functional enrichment of the “universal proteins”, those with homologues in all 17 other species, and of the “non-universal proteins”. A large number of GO terms are strongly enriched in both human and fly universal proteins. Most of these functions are known to be essential. A smaller number of GO terms, exhibiting markedly different properties, are enriched in both human and fly non-universal proteins. We further explore the non-universal proteins, whose conservation profiles are consistent with the “tree of life” (TOL consistent), as well as the TOL inconsistent proteins. Finally, we applied Quantum Clustering to the conservation profiles of the TOL consistent proteins. Each cluster is strongly associated with one or a small number of specific monophyletic clades in the tree of life. The proteins in many of these clusters exhibit strong functional enrichment associated with the “life style” of the related clades. Most previous approaches for studying function and conservation are “bottom up”, studying protein families one by one, and separately assessing the conservation of each. By way of contrast, our approach is “top down”. We globally partition the set of all proteins hierarchically, as described above, and then identify protein families enriched within different subdivisions. While supporting previous findings, our approach also provides a tool for discovering novel relations between protein conservation profiles, functionality, and evolutionary history as represented by the tree of life. PMID:24594619

Application of activity-based protein profiling to study enzyme function in adipocytes.

PubMed

Galmozzi, Andrea; Dominguez, Eduardo; Cravatt, Benjamin F; Saez, Enrique

2014-01-01

Activity-based protein profiling (ABPP) is a chemical proteomics approach that utilizes small-molecule probes to determine the functional state of enzymes directly in native systems. ABPP probes selectively label active enzymes, but not their inactive forms, facilitating the characterization of changes in enzyme activity that occur without alterations in protein levels. ABPP can be a tool superior to conventional gene expression and proteomic profiling methods to discover new enzymes active in adipocytes and to detect differences in the activity of characterized enzymes that may be associated with disorders of adipose tissue function. ABPP probes have been developed that react selectively with most members of specific enzyme classes. Here, using as an example the serine hydrolase family that includes many enzymes with critical roles in adipocyte physiology, we describe methods to apply ABPP analysis to the study of adipocyte enzymatic pathways. © 2014 Elsevier Inc. All rights reserved.

PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

PubMed Central

Niu, Yulong; Liu, Chengcheng; Moghimyfiroozabad, Shayan; Yang, Yi

2017-01-01

Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/. PMID:28875072

Identification of discriminant proteins through antibody profiling, methods and apparatus for identifying an individual

DOEpatents

Apel, William A.; Thompson, Vicki S; Lacey, Jeffrey A.; Gentillon, Cynthia A.

2016-08-09

A method for determining a plurality of proteins for discriminating and positively identifying an individual based from a biological sample. The method may include profiling a biological sample from a plurality of individuals against a protein array including a plurality of proteins. The protein array may include proteins attached to a support in a preselected pattern such that locations of the proteins are known. The biological sample may be contacted with the protein array such that a portion of antibodies in the biological sample reacts with and binds to the proteins forming immune complexes. A statistical analysis method, such as discriminant analysis, may be performed to determine discriminating proteins for distinguishing individuals. Proteins of interest may be used to form a protein array. Such a protein array may be used, for example, to compare a forensic sample from an unknown source with a sample from a known source.

Identification of discriminant proteins through antibody profiling, methods and apparatus for identifying an individual

DOEpatents

Thompson, Vicki S; Lacey, Jeffrey A; Gentillon, Cynthia A; Apel, William A

2015-03-03

A method for determining a plurality of proteins for discriminating and positively identifying an individual based from a biological sample. The method may include profiling a biological sample from a plurality of individuals against a protein array including a plurality of proteins. The protein array may include proteins attached to a support in a preselected pattern such that locations of the proteins are known. The biological sample may be contacted with the protein array such that a portion of antibodies in the biological sample reacts with and binds to the proteins forming immune complexes. A statistical analysis method, such as discriminant analysis, may be performed to determine discriminating proteins for distinguishing individuals. Proteins of interest may be used to form a protein array. Such a protein array may be used, for example, to compare a forensic sample from an unknown source with a sample from a known source.

Proteomic profile of serum of pregnant women carring a fetus with Down syndrome using nano uplc Q-tof ms/ms technology.

PubMed

López Uriarte, Graciela Arelí; Burciaga Flores, Carlos Horacio; Torres de la Cruz, Víctor Manuel; Medina Aguado, María Magdalena; Gómez Puente, Viviana Maricela; Romero Gutiérrez, Liliana Nayeli; Martínez de Villarreal, Laura Elia

2018-06-01

Prenatal diagnosis of Down syndrome (DS) is based on the calculated risk of maternal age, biochemical and ultrasonographic markers and recently by cfDNA. Differences in proteomic profiles may give an opportunity to find new biomarkers. Characterize proteome of serum of mothers carrying DS fetus. Blood serum samples of three groups of women were obtained, (a) 10 non-pregnant, (b) 10 pregnant with healthy fetus by ultrasound evaluation, (c) nine pregnant with DS fetus. Sample preparation was as follows: Albumin/IgG depletion, desalting, and trypsin digestion; the process was performed in nanoUPLC MS/MS. Data analysis was made with Mass Lynx 4.1 and ProteinLynx Global Server 3.0, peptide and protein recognition by MASCOT algorithm and UNIPROT-Swissprot database. Each group showed different protein profiles. Some proteins were shared between groups. Only sera from pregnant women showed proteins related to immune and clot pathways. Mothers with DS fetus had 42 specific proteins. We found a different serum protein profile in mothers carrying DS fetuses that do not reflect expression of genes in the extra chromosome. Further studies will be necessary to establish the role of these proteins in aneuploid fetus and analyze their possible use as potential biomarkers.

Canola Proteins for Human Consumption: Extraction, Profile, and Functional Properties

PubMed Central

Tan, Siong H; Mailer, Rodney J; Blanchard, Christopher L; Agboola, Samson O

2011-01-01

Canola protein isolate has been suggested as an alternative to other proteins for human food use due to a balanced amino acid profile and potential functional properties such as emulsifying, foaming, and gelling abilities. This is, therefore, a review of the studies on the utilization of canola protein in human food, comprising the extraction processes for protein isolates and fractions, the molecular character of the extracted proteins, as well as their food functional properties. A majority of studies were based on proteins extracted from the meal using alkaline solution, presumably due to its high nitrogen yield, followed by those utilizing salt extraction combined with ultrafiltration. Characteristics of canola and its predecessor rapeseed protein fractions such as nitrogen yield, molecular weight profile, isoelectric point, solubility, and thermal properties have been reported and were found to be largely related to the extraction methods. However, very little research has been carried out on the hydrophobicity and structure profiles of the protein extracts that are highly relevant to a proper understanding of food functional properties. Alkaline extracts were generally not very suitable as functional ingredients and contradictory results about many of the measured properties of canola proteins, especially their emulsification tendencies, have also been documented. Further research into improved extraction methods is recommended, as is a more systematic approach to the measurement of desired food functional properties for valid comparison between studies. PMID:21535703

Analysis of Soluble Proteins in Natural Cordyceps sinensis from Different Producing Areas by Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis and Two-dimensional Electrophoresis

PubMed Central

Li, Chun-Hong; Zuo, Hua-Li; Zhang, Qian; Wang, Feng-Qin; Hu, Yuan-Jia; Qian, Zheng-Ming; Li, Wen-Jia; Xia, Zhi-Ning; Yang, Feng-Qing

2017-01-01

Background: As one of the bioactive components in Cordyceps sinensis (CS), proteins were rarely used as index components to study the correlation between the protein components and producing areas of natural CS. Objective: Protein components of 26 natural CS samples produced in Qinghai, Tibet, and Sichuan provinces were analyzed and compared to investigate the relationship among 26 different producing areas. Materials and Methods: Proteins from 26 different producing areas were extracted by Tris-HCl buffer with Triton X-100, and separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and two-dimensional electrophoresis (2-DE). Results: The SDS-PAGE results indicated that the number of protein bands and optical density curves of proteins in 26 CS samples was a bit different. However, the 2-DE results showed that the numbers and abundance of protein spots in protein profiles of 26 samples were obviously different and showed certain association with producing areas. Conclusions: Based on the expression values of matched protein spots, 26 batches of CS samples can be divided into two main categories (Tibet and Qinghai) by hierarchical cluster analysis. SUMMARY The number of protein bands and optical density curves of proteins in 26 Cordyceps sinensis samples were a bit different on the sodium dodecyl sulfate-polyacrylamide gel electrophoresis protein profilesNumbers and abundance of protein spots in protein profiles of 26 samples were obvious different on two-dimensional electrophoresis mapsTwenty-six different producing areas of natural Cordyceps sinensis samples were divided into two main categories (Tibet and Qinghai) by Hierarchical cluster analysis based on the values of matched protein spots. Abbreviations Used: SDS-PAGE: Sodium dodecyl sulfate polyacrylamide gel electrophoresis, 2-DE: Two-dimensional electrophoresis, Cordyceps sinensis: CS, TCMs: Traditional Chinese medicines PMID:28250651

Analysis of Soluble Proteins in Natural Cordyceps sinensis from Different Producing Areas by Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis and Two-dimensional Electrophoresis.

PubMed

Li, Chun-Hong; Zuo, Hua-Li; Zhang, Qian; Wang, Feng-Qin; Hu, Yuan-Jia; Qian, Zheng-Ming; Li, Wen-Jia; Xia, Zhi-Ning; Yang, Feng-Qing

2017-01-01

As one of the bioactive components in Cordyceps sinensis (CS), proteins were rarely used as index components to study the correlation between the protein components and producing areas of natural CS. Protein components of 26 natural CS samples produced in Qinghai, Tibet, and Sichuan provinces were analyzed and compared to investigate the relationship among 26 different producing areas. Proteins from 26 different producing areas were extracted by Tris-HCl buffer with Triton X-100, and separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and two-dimensional electrophoresis (2-DE). The SDS-PAGE results indicated that the number of protein bands and optical density curves of proteins in 26 CS samples was a bit different. However, the 2-DE results showed that the numbers and abundance of protein spots in protein profiles of 26 samples were obviously different and showed certain association with producing areas. Based on the expression values of matched protein spots, 26 batches of CS samples can be divided into two main categories (Tibet and Qinghai) by hierarchical cluster analysis. The number of protein bands and optical density curves of proteins in 26 Cordyceps sinensis samples were a bit different on the sodium dodecyl sulfate-polyacrylamide gel electrophoresis protein profilesNumbers and abundance of protein spots in protein profiles of 26 samples were obvious different on two-dimensional electrophoresis mapsTwenty-six different producing areas of natural Cordyceps sinensis samples were divided into two main categories (Tibet and Qinghai) by Hierarchical cluster analysis based on the values of matched protein spots. Abbreviations Used : SDS-PAGE: Sodium dodecyl sulfate polyacrylamide gel electrophoresis, 2-DE: Two-dimensional electrophoresis, Cordyceps sinensis : CS, TCMs: Traditional Chinese medicines.

Protein profiles of nasal lavage fluid from individuals with work-related upper airway symptoms associated with moldy and damp buildings.

PubMed

Wåhlén, K; Fornander, L; Olausson, P; Ydreborg, K; Flodin, U; Graff, P; Lindahl, M; Ghafouri, B

2016-10-01

Upper airway irritation is common among individuals working in moldy and damp buildings. The aim of this study was to investigate effects on the protein composition of the nasal lining fluid. The prevalence of symptoms in relation to work environment was examined in 37 individuals working in two damp buildings. Microbial growth was confirmed in one of the buildings. Nasal lavage fluid was collected from 29 of the exposed subjects and 13 controls, not working in a damp building. Protein profiles were investigated with a proteomic approach and evaluated by multivariate statistical models. Subjects from both workplaces reported upper airway and ocular symptoms. Based on protein profiles, symptomatic subjects in the two workplaces were discriminated from each other and separated from healthy controls. The groups differed in proteins involved in inflammation and host defense. Measurements of innate immunity proteins showed a significant increase in protein S100-A8 and decrease in SPLUNC1 in subjects from one workplace, while alpha-1-antitrypsin was elevated in subjects from the other workplace, compared with healthy controls. The results show that protein profiles in nasal lavage fluid can be used to monitor airway mucosal effects in personnel working in damp buildings and indicate that the profile may be separated when the dampness is associated with the presence of molds. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Ribosome profiling: a Hi-Def monitor for protein synthesis at the genome-wide scale

PubMed Central

Michel, Audrey M; Baranov, Pavel V

2013-01-01

Ribosome profiling or ribo-seq is a new technique that provides genome-wide information on protein synthesis (GWIPS) in vivo. It is based on the deep sequencing of ribosome protected mRNA fragments allowing the measurement of ribosome density along all RNA molecules present in the cell. At the same time, the high resolution of this technique allows detailed analysis of ribosome density on individual RNAs. Since its invention, the ribosome profiling technique has been utilized in a range of studies in both prokaryotic and eukaryotic organisms. Several studies have adapted and refined the original ribosome profiling protocol for studying specific aspects of translation. Ribosome profiling of initiating ribosomes has been used to map sites of translation initiation. These studies revealed the surprisingly complex organization of translation initiation sites in eukaryotes. Multiple initiation sites are responsible for the generation of N-terminally extended and truncated isoforms of known proteins as well as for the translation of numerous open reading frames (ORFs), upstream of protein coding ORFs. Ribosome profiling of elongating ribosomes has been used for measuring differential gene expression at the level of translation, the identification of novel protein coding genes and ribosome pausing. It has also provided data for developing quantitative models of translation. Although only a dozen or so ribosome profiling datasets have been published so far, they have already dramatically changed our understanding of translational control and have led to new hypotheses regarding the origin of protein coding genes. © 2013 John Wiley & Sons, Ltd. PMID:23696005

Benzoate-mediated changes on expression profile of soluble proteins in Serratia sp. DS001.

PubMed

Pandeeti, E V P; Chinnaboina, M R; Siddavattam, D

2009-05-01

To assess differences in protein expression profile associated with shift in carbon source from succinate to benzoate in Serratia sp. DS001 using a proteomics approach. A basic proteome map was generated for the soluble proteins extracted from Serratia sp. DS001 grown in succinate and benzoate. The differently and differentially expressed proteins were identified using ImageMaster 2D Platinum software (GE Healthcare). The identity of the proteins was determined by employing MS or MS/MS. Important enzymes such as Catechol 1,2 dioxygenase and transcriptional regulators that belong to the LysR superfamily were identified. Nearly 70 proteins were found to be differentially expressed when benzoate was used as carbon source. Based on the protein identity and degradation products generated from benzoate it is found that ortho pathway is operational in Serratia sp. DS001. Expression profile of the soluble proteins associated with shift in carbon source was mapped. The study also elucidates degradation pathway of benzoate in Serratia sp. DS001 by correlating the proteomics data with the catabolites of benzoate.

Proteomic Analysis of Whole Human Saliva Detects Enhanced Expression of Interleukin-1 Receptor Antagonist, Thioredoxin and Lipocalin-1 in Cigarette Smokers Compared to Non-Smokers

PubMed Central

Jessie, Kala; Pang, Wei Wei; Haji, Zubaidah; Rahim, Abdul; Hashim, Onn Haji

2010-01-01

A gel-based proteomics approach was used to screen for proteins of differential abundance between the saliva of smokers and those who had never smoked. Subjecting precipitated proteins from whole human saliva of healthy non-smokers to two-dimensional electrophoresis (2-DE) generated typical profiles comprising more than 50 proteins. While 35 of the proteins were previously established by other researchers, an additional 22 proteins were detected in the 2-DE saliva protein profiles generated in the present study. When the 2-DE profiles were compared to those obtained from subjects considered to be heavy cigarette smokers, three saliva proteins, including interleukin-1 receptor antagonist, thioredoxin and lipocalin-1, showed significant enhanced expression. The distribution patterns of lipocalin-1 isoforms were also different between cigarette smokers and non-smokers. The three saliva proteins have good potential to be used as biomarkers for the adverse effects of smoking and the risk for inflammatory and chronic diseases that are associated with it. PMID:21151451

Secretome profiling of primary human skeletal muscle cells.

PubMed

Hartwig, Sonja; Raschke, Silja; Knebel, Birgit; Scheler, Mika; Irmler, Martin; Passlack, Waltraud; Muller, Stefan; Hanisch, Franz-Georg; Franz, Thomas; Li, Xinping; Dicken, Hans-Dieter; Eckardt, Kristin; Beckers, Johannes; de Angelis, Martin Hrabe; Weigert, Cora; Häring, Hans-Ulrich; Al-Hasani, Hadi; Ouwens, D Margriet; Eckel, Jürgen; Kotzka, Jorg; Lehr, Stefan

2014-05-01

The skeletal muscle is a metabolically active tissue that secretes various proteins. These so-called myokines have been proposed to affect muscle physiology and to exert systemic effects on other tissues and organs. Yet, changes in the secretory profile may participate in the pathophysiology of metabolic diseases. The present study aimed at characterizing the secretome of differentiated primary human skeletal muscle cells (hSkMC) derived from healthy, adult donors combining three different mass spectrometry based non-targeted approaches as well as one antibody based method. This led to the identification of 548 non-redundant proteins in conditioned media from hSkmc. For 501 proteins, significant mRNA expression could be demonstrated. Applying stringent consecutive filtering using SignalP, SecretomeP and ER_retention signal databases, 305 proteins were assigned as potential myokines of which 12 proteins containing a secretory signal peptide were not previously described. This comprehensive profiling study of the human skeletal muscle secretome expands our knowledge of the composition of the human myokinome and may contribute to our understanding of the role of myokines in multiple biological processes. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

Proof of concept of a "greener" protein purification/enrichment method based on carboxylate-terminated carbosilane dendrimer-protein interactions.

PubMed

González-García, Estefanía; Maly, Marek; de la Mata, Francisco Javier; Gómez, Rafael; Marina, María Luisa; García, María Concepción

2016-11-01

Protein sample preparation is a critical and an unsustainable step since it involves the use of tedious methods that usually require high amount of solvents. The development of new materials offers additional opportunities in protein sample preparation. This work explores, for the first time, the potential application of carboxylate-terminated carbosilane dendrimers to the purification/enrichment of proteins. Studies on dendrimer binding to proteins, based on protein fluorescence intensity and emission wavelengths measurements, demonstrated the interaction between carboxylate-terminated carbosilane dendrimers and proteins at all tested pH levels. Interactions were greatly affected by the protein itself, pH, and dendrimer concentration and generation. Especially interesting was the interaction at acidic pH since it resulted in a significant protein precipitation. Dendrimer-protein interactions were modeled observing stable complexes for all proteins. Carboxylate-terminated carbosilane dendrimers at acidic pH were successfully used in the purification/enrichment of proteins extracted from a complex sample. Graphical Abstract Images showing the growing turbidity of solutions containing a mixture of proteins (lysozyme, myoglobin, and BSA) at different protein:dendrimer ratios (1:0, 1:1, 1:8, and 1:20) at acidic pH and SDS-PAGE profiles of the corresponsing supernatants. Comparison of SDS-PAGE profiles for the pellets obtained during the purification of proteins present in a complex sample using a conventional "no-clean" method based on acetone precipitation and the proposed "greener" method using carboxylate-terminated carbosilane dendrimer at a 1:20 protein:dendrimer ratio.

Multiplex single-molecule interaction profiling of DNA barcoded proteins

PubMed Central

Gu, Liangcai; Li, Chao; Aach, John; Hill, David E.; Vidal, Marc; Church, George M.

2014-01-01

In contrast with advances in massively parallel DNA sequencing1, high-throughput protein analyses2-4 are often limited by ensemble measurements, individual analyte purification and hence compromised quality and cost-effectiveness. Single-molecule (SM) protein detection achieved using optical methods5 is limited by the number of spectrally nonoverlapping chromophores. Here, we introduce a single molecular interaction-sequencing (SMI-Seq) technology for parallel protein interaction profiling leveraging SM advantages. DNA barcodes are attached to proteins collectively via ribosome display6 or individually via enzymatic conjugation. Barcoded proteins are assayed en masse in aqueous solution and subsequently immobilized in a polyacrylamide (PAA) thin film to construct a random SM array, where barcoding DNAs are amplified into in situ polymerase colonies (polonies)7 and analyzed by DNA sequencing. This method allows precise quantification of various proteins with a theoretical maximum array density of over one million polonies per square millimeter. Furthermore, protein interactions can be measured based on the statistics of colocalized polonies arising from barcoding DNAs of interacting proteins. Two demanding applications, G-protein coupled receptor (GPCR) and antibody binding profiling, were demonstrated. SMI-Seq enables “library vs. library” screening in a one-pot assay, simultaneously interrogating molecular binding affinity and specificity. PMID:25252978

Independent component analysis for the extraction of reliable protein signal profiles from MALDI-TOF mass spectra.

PubMed

Mantini, Dante; Petrucci, Francesca; Del Boccio, Piero; Pieragostino, Damiana; Di Nicola, Marta; Lugaresi, Alessandra; Federici, Giorgio; Sacchetta, Paolo; Di Ilio, Carmine; Urbani, Andrea

2008-01-01

Independent component analysis (ICA) is a signal processing technique that can be utilized to recover independent signals from a set of their linear mixtures. We propose ICA for the analysis of signals obtained from large proteomics investigations such as clinical multi-subject studies based on MALDI-TOF MS profiling. The method is validated on simulated and experimental data for demonstrating its capability of correctly extracting protein profiles from MALDI-TOF mass spectra. The comparison on peak detection with an open-source and two commercial methods shows its superior reliability in reducing the false discovery rate of protein peak masses. Moreover, the integration of ICA and statistical tests for detecting the differences in peak intensities between experimental groups allows to identify protein peaks that could be indicators of a diseased state. This data-driven approach demonstrates to be a promising tool for biomarker-discovery studies based on MALDI-TOF MS technology. The MATLAB implementation of the method described in the article and both simulated and experimental data are freely available at http://www.unich.it/proteomica/bioinf/.

Rosetta stone method for detecting protein function and protein-protein interactions from genome sequences

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Pellegrini, Matteo; Thompson, Michael J.; Yeates, Todd O.

2002-10-15

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Profiling plasma extracellular vesicle by pluronic block-copolymer based enrichment method unveils features associated with breast cancer aggression, metastasis and invasion

PubMed Central

Rosenow, Matthew; Xiao, Nick; Spetzler, David

2018-01-01

ABSTRACT Extracellular vesicle (EV)-based liquid biopsies have been proposed to be a readily obtainable biological substrate recently for both profiling and diagnostics purposes. Development of a fast and reliable preparation protocol to enrich such small particles could accelerate the discovery of informative, disease-related biomarkers. Though multiple EV enrichment protocols are available, in terms of efficiency, reproducibility and simplicity, precipitation-based methods are most amenable to studies with large numbers of subjects. However, the selectivity of the precipitation becomes critical. Here, we present a simple plasma EV enrichment protocol based on pluronic block copolymer. The enriched plasma EV was able to be verified by multiple platforms. Our results showed that the particles enriched from plasma by the copolymer were EV size vesicles with membrane structure; proteomic profiling showed that EV-related proteins were significantly enriched, while high-abundant plasma proteins were significantly reduced in comparison to other precipitation-based enrichment methods. Next-generation sequencing confirmed the existence of various RNA species that have been observed in EVs from previous studies. Small RNA sequencing showed enriched species compared to the corresponding plasma. Moreover, plasma EVs enriched from 20 advanced breast cancer patients and 20 age-matched non-cancer controls were profiled by semi-quantitative mass spectrometry. Protein features were further screened by EV proteomic profiles generated from four breast cancer cell lines, and then selected in cross-validation models. A total of 60 protein features that highly contributed in model prediction were identified. Interestingly, a large portion of these features were associated with breast cancer aggression, metastasis as well as invasion, consistent with the advanced clinical stage of the patients. In summary, we have developed a plasma EV enrichment method with improved precipitation selectivity and it might be suitable for larger-scale discovery studies. PMID:29696079

Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human.

PubMed

Li, Caixia; Tan, Xing Fei; Lim, Teck Kwang; Lin, Qingsong; Gong, Zhiyuan

2016-04-13

Omic approaches have been increasingly used in the zebrafish model for holistic understanding of molecular events and mechanisms of tissue functions. However, plasma is rarely used for omic profiling because of the technical challenges in collecting sufficient blood. In this study, we employed two mass spectrometric (MS) approaches for a comprehensive characterization of zebrafish plasma proteome, i.e. conventional shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS) for an overview study and quantitative SWATH (Sequential Window Acquisition of all THeoretical fragment-ion spectra) for comparison between genders. 959 proteins were identified in the shotgun profiling with estimated concentrations spanning almost five orders of magnitudes. Other than the presence of a few highly abundant female egg yolk precursor proteins (vitellogenins), the proteomic profiles of male and female plasmas were very similar in both number and abundance and there were basically no other highly gender-biased proteins. The types of plasma proteins based on IPA (Ingenuity Pathway Analysis) classification and tissue sources of production were also very similar. Furthermore, the zebrafish plasma proteome shares significant similarities with human plasma proteome, in particular in top abundant proteins including apolipoproteins and complements. Thus, the current study provided a valuable dataset for future evaluation of plasma proteins in zebrafish.

Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human

PubMed Central

Li, Caixia; Tan, Xing Fei; Lim, Teck Kwang; Lin, Qingsong; Gong, Zhiyuan

2016-01-01

Omic approaches have been increasingly used in the zebrafish model for holistic understanding of molecular events and mechanisms of tissue functions. However, plasma is rarely used for omic profiling because of the technical challenges in collecting sufficient blood. In this study, we employed two mass spectrometric (MS) approaches for a comprehensive characterization of zebrafish plasma proteome, i.e. conventional shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS) for an overview study and quantitative SWATH (Sequential Window Acquisition of all THeoretical fragment-ion spectra) for comparison between genders. 959 proteins were identified in the shotgun profiling with estimated concentrations spanning almost five orders of magnitudes. Other than the presence of a few highly abundant female egg yolk precursor proteins (vitellogenins), the proteomic profiles of male and female plasmas were very similar in both number and abundance and there were basically no other highly gender-biased proteins. The types of plasma proteins based on IPA (Ingenuity Pathway Analysis) classification and tissue sources of production were also very similar. Furthermore, the zebrafish plasma proteome shares significant similarities with human plasma proteome, in particular in top abundant proteins including apolipoproteins and complements. Thus, the current study provided a valuable dataset for future evaluation of plasma proteins in zebrafish. PMID:27071722

Phagonaute: A web-based interface for phage synteny browsing and protein function prediction.

PubMed

Delattre, Hadrien; Souiai, Oussema; Fagoonee, Khema; Guerois, Raphaël; Petit, Marie-Agnès

2016-09-01

Distant homology search tools are of great help to predict viral protein functions. However, due to the lack of profile databases dedicated to viruses, they can lack sensitivity. We constructed HMM profiles for more than 80,000 proteins from both phages and archaeal viruses, and performed all pairwise comparisons with HHsearch program. The whole resulting database can be explored through a user-friendly "Phagonaute" interface to help predict functions. Results are displayed together with their genetic context, to strengthen inferences based on remote homology. Beyond function prediction, this tool permits detections of co-occurrences, often indicative of proteins completing a task together, and observation of conserved patterns across large evolutionary distances. As a test, Herpes simplex virus I was added to Phagonaute, and 25% of its proteome matched to bacterial or archaeal viral protein counterparts. Phagonaute should therefore help virologists in their quest for protein functions and evolutionary relationships. Copyright © 2016 Elsevier Inc. All rights reserved.

Generation of miniaturized planar ecombinant antibody arrays using a microcantilever-based printer

NASA Astrophysics Data System (ADS)

Petersson, Linn; Berthet Duroure, Nathalie; Auger, Angèle; Dexlin-Mellby, Linda; Borrebaeck, Carl AK; Ait Ikhlef, Ali; Wingren, Christer

2014-07-01

Miniaturized (Ø 10 μm), multiplexed (>5-plex), and high-density (>100 000 spots cm-2) antibody arrays will play a key role in generating protein expression profiles in health and disease. However, producing such antibody arrays is challenging, and it is the type and range of available spotters which set the stage. This pilot study explored the use of a novel microspotting tool, BioplumeTM—consisting of an array of micromachined silicon cantilevers with integrated microfluidic channels—to produce miniaturized, multiplexed, and high-density planar recombinant antibody arrays for protein expression profiling which targets crude, directly labelled serum. The results demonstrated that 16-plex recombinant antibody arrays could be produced—based on miniaturized spot features (78.5 um2, Ø 10 μm) at a 7-125-times increased spot density (250 000 spots cm-2), interfaced with a fluorescent-based read-out. This prototype platform was found to display adequate reproducibility (spot-to-spot) and an assay sensitivity in the pM range. The feasibility of the array platform for serum protein profiling was outlined.

Genome-wide analysis and expression profiling of the Solanum tuberosum aquaporins.

PubMed

Venkatesh, Jelli; Yu, Jae-Woong; Park, Se Won

2013-12-01

Aquaporins belongs to the major intrinsic proteins involved in the transcellular membrane transport of water and other small solutes. A comprehensive genome-wide search for the homologues of Solanum tuberosum major intrinsic protein (MIP) revealed 41 full-length potato aquaporin genes. All potato aquaporins are grouped into five subfamilies; plasma membrane intrinsic proteins (PIPs), tonoplast intrinsic proteins (TIPs), NOD26-like intrinsic proteins (NIPs), small basic intrinsic proteins (SIPs) and x-intrinsic proteins (XIPs). Functional predictions based on the aromatic/arginine (ar/R) selectivity filters and Froger's positions showed a remarkable difference in substrate transport specificity among subfamilies. The expression pattern of potato aquaporins, examined by qPCR analysis, showed distinct expression profiles in various organs and tuber developmental stages. Furthermore, qPCR analysis of potato plantlets, subjected to various abiotic stresses revealed the marked effect of stresses on expression levels of aquaporins. Taken together, the expression profiles of aquaporins imply that aquaporins play important roles in plant growth and development, in addition to maintaining water homeostasis in response to environmental stresses. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Affinity proteomics within rare diseases: a BIO-NMD study for blood biomarkers of muscular dystrophies

PubMed Central

Ayoglu, Burcu; Chaouch, Amina; Lochmüller, Hanns; Politano, Luisa; Bertini, Enrico; Spitali, Pietro; Hiller, Monika; Niks, Eric H; Gualandi, Francesca; Pontén, Fredrik; Bushby, Kate; Aartsma-Rus, Annemieke; Schwartz, Elena; Le Priol, Yannick; Straub, Volker; Uhlén, Mathias; Cirak, Sebahattin; ‘t Hoen, Peter A C; Muntoni, Francesco; Ferlini, Alessandra; Schwenk, Jochen M; Nilsson, Peter; Al-Khalili Szigyarto, Cristina

2014-01-01

Despite the recent progress in the broad-scaled analysis of proteins in body fluids, there is still a lack in protein profiling approaches for biomarkers of rare diseases. Scarcity of samples is the main obstacle hindering attempts to apply discovery driven protein profiling in rare diseases. We addressed this challenge by combining samples collected within the BIO-NMD consortium from four geographically dispersed clinical sites to identify protein markers associated with muscular dystrophy using an antibody bead array platform with 384 antibodies. Based on concordance in statistical significance and confirmatory results obtained from analysis of both serum and plasma, we identified eleven proteins associated with muscular dystrophy, among which four proteins were elevated in blood from muscular dystrophy patients: carbonic anhydrase III (CA3) and myosin light chain 3 (MYL3), both specifically expressed in slow-twitch muscle fibers and mitochondrial malate dehydrogenase 2 (MDH2) and electron transfer flavoprotein A (ETFA). Using age-matched sub-cohorts, 9 protein profiles correlating with disease progression and severity were identified, which hold promise for the development of new clinical tools for management of dystrophinopathies. PMID:24920607

Proteomic and Epigenetic Analysis of Rice after Seed Spaceflight and Ground-Base Ion Radiations

NASA Astrophysics Data System (ADS)

Wang, Wei; Sun, Yeqing; Peng, Yuming; Zhao, Qian; Wen, Bin; Yang, Jun

Highly ionizing radiation (HZE) in space is considered as main factor causing biological effects to plant seeds. In previous work, we compared the proteomic profiles of rice plants growing after seed spaceflights to ground controls by two-dimensional difference gel electrophoresis (2-D DIGE) with mass spectrometry and found that the protein expression profiles were changed and differentially expressed proteins participated in most of the biological processes of rice. To further evaluate the dosage effects of space radiation and compare between low- and high-dose ion effects, we carried out three independent ground-base ionizing radiation experiments with different cumulative doses (low-dose range: 2~1000mGy, high-dose range: 2000~20000mGy) to rice seeds and performed proteomic analysis of seedlings. We found that protein expression profiles showed obvious boundaries between low- and high-dose radiation groups. Rates of differentially expressed proteins presented a dose-dependent effect, it reached the highest value at 2000mGy dosage point in all three radiation experiments coincidently; while proteins responded to low-dose radiations preferred to change their expressions at the minimum dosage (2mGy). Proteins participating in rice biological processes also responded differently between low- and high-dose radiations: proteins involved in energy metabolism and photosynthesis tended to be regulated after low-dose radiations while stress responding, protein folding and cell redox homeostasis related proteins preferred to change their expressions after high-dose radiations. By comparing the proteomic profiles between ground-base radiations and spaceflights, it was worth noting that ground-base low-dose ion radiation effects shared similar biological effects as space environment. In addition, we discovered that protein nucleoside diphosphate kinase 1 (NDPK1) showed obvious increased regulation after spaceflights and ion radiations. NDPK1 catalyzes nucleotide metabolism and is reported to be involved in DNA repair process. Its expression sensitivity and specificity were confirmed by RT-PCR and western blot analysis, indicating its potential to be used as space radiation biomarker. Space radiations might induce epigenetic effects on rice plants, especially changes of DNA methylation. Early results suggested that there were correlations between DNA methylation polymorphic and genomic mutation rates. In addition, the 5-methylcytosine located in coding gene’s promoter and exon regions could regulate gene expressions thus influence protein expressions. So whether there is correlation between genome DNA methylation changes and protein expression profile alterations caused by space radiation is worth for further investigation. Therefore we used the same rice samples treated by carbon ion radiation with different doses (0, 10, 20,100, 200, 1000, 2000, 5000, 20000mGy) and applied methylation sensitive amplification polymorphism (MSAP) for scanning genome DNA methylation changes. Interestingly, DNA methylation polymorphism rates also presented a dose-dependent effect and showed the same changing trend as rates of differentially expressed proteins. Whether there are correlations between epigenetic and proteomic effects of space radiation is worth for further investigation.

Evaluation of inter-day and inter-individual variability of tear peptide/protein profiles by MALDI-TOF MS analyses

PubMed Central

González, Nerea; Iloro, Ibon; Durán, Juan A.; Elortza, Félix

2012-01-01

Purpose To characterize the tear film peptidome and low molecular weight protein profiles of healthy control individuals, and to evaluate changes due to day-to-day and individual variation and tear collection methods, by using solid phase extraction coupled to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling. Methods The tear protein profiles of six healthy volunteers were analyzed over seven days and inter-day and inter-individual variability was evaluated. The bilaterality of tear film and the effect of tear collection methods on protein profiles were also analyzed in some of these patients. MALDI-TOF MS analyses were performed on tear samples purified by using a solid phase extraction (SPE) method based on C18 functionalized magnetic beads for peptide and low molecular weight protein enrichment, focusing spectra acquisition on the 1 to 20 kDa range. Spectra were analyzed using principal component analysis (PCA) with MultiExperiment Viewer (TMeV) software. Volunteers were examined in terms of tear production status (Schirmer I test), clinical assessment of palpebral lids and meibomian glands, and a subjective OSD questionnaire before tear collection by a glass micro-capillary. Results Analysis of peptides and proteins in the 1–20 kDa range showed no significant inter-day differences in tear samples collected from six healthy individuals during seven days of monitoring, but revealed subtle intrinsic inter-individual differences. Profile analyses of tears collected from the right and left eyes confirmed tear bilaterality in four healthy patients. The addition of physiologic serum for tear sample collection did not affect the peptide and small protein profiles with respect to the number of resolved peaks, but it did reduce the signal intensity of the peaks, and increased variability. Magnetic beads were found to be a suitable method for tear film purification for the profiling study. Conclusions No significant variability in tear peptide and protein profiles below 20 kDa was found in healthy controls over a seven day period, nor in right versus left eye profiles from the same individual. Subtle inter-individual differences can be observed upon tear profiling analysis and confirm intrinsic variability between control subjects. Addition of physiologic serum for tear collection affects the proteome and peptidome in terms of peak intensities, but not in the composition of the profiles themselves. This work shows that MALDI-TOF MS coupled with C18 magnetic beads is an effective and reproducible methodology for tear profiling studies in the clinical monitoring of patients. PMID:22736947

HHsvm: fast and accurate classification of profile–profile matches identified by HHsearch

PubMed Central

Dlakić, Mensur

2009-01-01

Motivation: Recently developed profile–profile methods rival structural comparisons in their ability to detect homology between distantly related proteins. Despite this tremendous progress, many genuine relationships between protein families cannot be recognized as comparisons of their profiles result in scores that are statistically insignificant. Results: Using known evolutionary relationships among protein superfamilies in SCOP database, support vector machines were trained on four sets of discriminatory features derived from the output of HHsearch. Upon validation, it was shown that the automatic classification of all profile–profile matches was superior to fixed threshold-based annotation in terms of sensitivity and specificity. The effectiveness of this approach was demonstrated by annotating several domains of unknown function from the Pfam database. Availability: Programs and scripts implementing the methods described in this manuscript are freely available from http://hhsvm.dlakiclab.org/. Contact: mdlakic@montana.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19773335

Electronegativity and intrinsic disorder of preeclampsia-related proteins.

PubMed

Polanco, Carlos; Castañón-González, Jorge Alberto; Uversky, Vladimir N; Buhse, Thomas; Samaniego Mendoza, José Lino; Calva, Juan J

2017-01-01

Preeclampsia, hemorrhage, and infection are the leading causes of maternal death in underdeveloped countries. Since several proteins associated with preeclampsia are known, we conducted a computational study which evaluated the commonness and potential functionality of intrinsic disorder of these proteins and also made an attempt to characterize their origin. The origin of the preeclampsia-related proteins was assessed with a supervised technique, a Polarity Index Method (PIM), which evaluates the electronegativity of proteins based solely on their sequence. The commonness of intrinsic disorder was evaluated using several disorder predictors from the PONDR family, the charge-hydropathy plot (CH-plot) and cumulative distribution function (CDF) analyses, and using the MobiDB web-based tool, whereas potential functionality of intrinsic disorder was studied with the D2P2 resource and ANCHOR predictor of disorder-based binding sites, and the STRING tool was used to build the interactivity networks of the preeclampsia-related proteins. Peculiarities of the PIM-derived polar profile of the group of preeclampsia-related proteins were then compared with profiles of a group of lipoproteins, antimicrobial peptides, angiogenesis-related proteins, and the intrinsically disordered proteins. Our results showed a high graphical correlation between preeclampsia proteins, lipoproteins, and the angiogenesis proteins. We also showed that many preeclampsia-related proteins contain numerous functional disordered regions. Therefore, these bioinformatics results led us to assume that the preeclampsia proteins are highly associated with the lipoproteins group, and that some preeclampsia-related proteins contain significant amounts of functional disorders.

Protein-based forensic identification using genetically variant peptides in human bone.

PubMed

Mason, Katelyn Elizabeth; Anex, Deon; Grey, Todd; Hart, Bradley; Parker, Glendon

2018-04-22

Bone tissue contains organic material that is useful for forensic investigations and may contain preserved endogenous protein that can persist in the environment for extended periods of time over a range of conditions. Single amino acid polymorphisms in these proteins reflect genetic information since they result from non-synonymous single nucleotide polymorphisms (SNPs) in DNA. Detection of genetically variant peptides (GVPs) - those peptides that contain amino acid polymorphisms - in digests of bone proteins allows for the corresponding SNP alleles to be inferred. Resulting genetic profiles can be used to calculate statistical measures of association between a bone sample and an individual. In this study proteomic analysis on rib cortical bone samples from 10 recently deceased individuals demonstrates this concept. A straight-forward acidic demineralization protocol yielded proteins that were digested with trypsin. Tryptic digests were analyzed by liquid chromatography mass spectrometry. A total of 1736 different proteins were identified across all resulting datasets. On average, individual samples contained 454±121 (x¯±σ) proteins. Thirty-five genetically variant peptides were identified from 15 observed proteins. Overall, 134 SNP inferences were made based on proteomically detected GVPs, which were confirmed by sequencing of subject DNA. Inferred individual SNP genetic profiles ranged in random match probability (RMP) from 1/6 to 1/42,472 when calculated with European population frequencies in the 1000 Genomes Project, Phase 3. Similarly, RMPs based on African population frequencies were calculated for each SNP genetic profile and likelihood ratios (LR) were obtained by dividing each European RMP by the corresponding African RMP. Resulting LR values ranged from 1.4 to 825 with a median value of 16. GVP markers offer a basis for the identification of compromised skeletal remains independent of the presence of DNA template. Published by Elsevier B.V.

Shotgun proteomics of plant plasma membrane and microdomain proteins using nano-LC-MS/MS.

PubMed

Takahashi, Daisuke; Li, Bin; Nakayama, Takato; Kawamura, Yukio; Uemura, Matsuo

2014-01-01

Shotgun proteomics allows the comprehensive analysis of proteins extracted from plant cells, subcellular organelles, and membranes. Previously, two-dimensional gel electrophoresis-based proteomics was used for mass spectrometric analysis of plasma membrane proteins. In order to get comprehensive proteome profiles of the plasma membrane including highly hydrophobic proteins with a number of transmembrane domains, a mass spectrometry-based shotgun proteomics method using nano-LC-MS/MS for proteins from the plasma membrane proteins and plasma membrane microdomain fraction is described. The results obtained are easily applicable to label-free protein semiquantification.

Analysis of the Human Prostate-Specific Proteome Defined by Transcriptomics and Antibody-Based Profiling Identifies TMEM79 and ACOXL as Two Putative, Diagnostic Markers in Prostate Cancer

PubMed Central

O'Hurley, Gillian; Busch, Christer; Fagerberg, Linn; Hallström, Björn M.; Stadler, Charlotte; Tolf, Anna; Lundberg, Emma; Schwenk, Jochen M.; Jirström, Karin; Bjartell, Anders; Gallagher, William M.; Uhlén, Mathias; Pontén, Fredrik

2015-01-01

To better understand prostate function and disease, it is important to define and explore the molecular constituents that signify the prostate gland. The aim of this study was to define the prostate specific transcriptome and proteome, in comparison to 26 other human tissues. Deep sequencing of mRNA (RNA-seq) and immunohistochemistry-based protein profiling were combined to identify prostate specific gene expression patterns and to explore tissue biomarkers for potential clinical use in prostate cancer diagnostics. We identified 203 genes with elevated expression in the prostate, 22 of which showed more than five-fold higher expression levels compared to all other tissue types. In addition to previously well-known proteins we identified two poorly characterized proteins, TMEM79 and ACOXL, with potential to differentiate between benign and cancerous prostatic glands in tissue biopsies. In conclusion, we have applied a genome-wide analysis to identify the prostate specific proteome using transcriptomics and antibody-based protein profiling to identify genes with elevated expression in the prostate. Our data provides a starting point for further functional studies to explore the molecular repertoire of normal and diseased prostate including potential prostate cancer markers such as TMEM79 and ACOXL. PMID:26237329

Effects of nutrient profiling and price changes based on NuVal® scores on food purchasing in an online experimental supermarket.

PubMed

Epstein, Leonard H; Finkelstein, Eric A; Katz, David L; Jankowiak, Noelle; Pudlewski, Corrin; Paluch, Rocco A

2016-08-01

The goal of the present study was to apply experimental economic methods in an online supermarket to examine the effects of nutrient profiling, and differential pricing based on the nutrient profile, on the overall diet quality, energy and macronutrients of the foods purchased, and diet cost. Participants were provided nutrient profiling scores or price adjustments based on nutrient profile scores while completing a hypothetical grocery shopping task. Prices of foods in the top 20 % of nutrient profiling scores were reduced (subsidized) by 25 % while those in the bottom 20 % of scores were increased (taxed) by 25 %. We evaluated the independent and interactive effects of nutrient profiling or price adjustments on overall diet quality of foods purchased as assessed by the NuVal® score, energy and macronutrients purchased and diet cost in a 2×2 factorial design. A large (>10 000 food items) online experimental supermarket in the USA. Seven hundred and eighty-one women. Providing nutrient profiling scores improved overall diet quality of foods purchased. Price changes were associated with an increase in protein purchased, an increase in energy cost, and reduced carbohydrate and protein costs. Price changes and nutrient profiling combined were associated with no unique benefits beyond price changes or nutrient profiling alone. Providing nutrient profile score increased overall NuVal® score without a reduction in energy purchased. Combining nutrient profiling and price changes did not show an overall benefit to diet quality and may be less useful than nutrient profiling alone to consumers who want to increase overall diet quality of foods purchased.

Determining protein function and interaction from genome analysis

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Thompson, Michael J.; Pellegrini, Matteo; Yeates, Todd O.

2004-08-03

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Mass Spectrometry Analysis of Spatial Protein Networks by Colocalization Analysis (COLA).

PubMed

Mardakheh, Faraz K

2017-01-01

A major challenge in systems biology is comprehensive mapping of protein interaction networks. Crucially, such interactions are often dynamic in nature, necessitating methods that can rapidly mine the interactome across varied conditions and treatments to reveal change in the interaction networks. Recently, we described a fast mass spectrometry-based method to reveal functional interactions in mammalian cells on a global scale, by revealing spatial colocalizations between proteins (COLA) (Mardakheh et al., Mol Biosyst 13:92-105, 2017). As protein localization and function are inherently linked, significant colocalization between two proteins is a strong indication for their functional interaction. COLA uses rapid complete subcellular fractionation, coupled with quantitative proteomics to generate a subcellular localization profile for each protein quantified by the mass spectrometer. Robust clustering is then applied to reveal significant similarities in protein localization profiles, indicative of colocalization.

Molecular typing of Vibrio parahaemolyticus isolated from seafood harvested along the south-west coast of India.

PubMed

Bhowmick, P P; Khushiramani, R; Raghunath, P; Karunasagar, I; Karunasagar, I

2008-02-01

Evaluation of protein profiling for typing Vibrio parahaemolyticus using 71 strains isolated from different seafood and comparison with other molecular typing techniques such as random amplified polymorphic DNA analysis (RAPD) and enterobacterial repetitive intergenic consensus sequence (ERIC)-PCR. Three molecular typing methods were used for the typing of 71 V. parahaemolyticus isolates from seafood. RAPD had a discriminatory index (DI) of 0.95, while ERIC-PCR showed a DI of 0.94. Though protein profiling had less discriminatory power, use of this method can be helpful in identifying new proteins which might have a role in establishment in the host or virulence of the organism. The use of protein profiling in combination with other established typing methods such as RAPD and ERIC-PCR generates useful information in the case of V. parahaemolyticus associated with seafood. The study demonstrates the usefulness of nucleic acid and protein-based studies in understanding the relationship between various isolates from seafood.

Amino acid profiles of rumen undegradable protein: a comparison between forages including cereal straws and alfalfa and their respective total mixed rations.

PubMed

Wang, B; Jiang, L S; Liu, J X

2018-06-01

Optimizing the amino acid (AA) profile of rumen undegradable protein (RUP) can positively affect the amount of milk protein. This study was conducted to improve knowledge regarding the AA profile of rumen undegradable protein from corn stover, rice straw and alfalfa hay as well as the total mixed ratio diets (TMR) based on one of them as forage source [forage-to-concentrate ratio of 45:55 (30% of corn stover (CS), 30% of rice straw (RS), 23% of alfalfa hay (AH) and dry matter basis)]. The other ingredients in the three TMR diets were similar. The RUP of all the forages and diets was estimated by incubation for 16 hr in the rumen of three ruminally cannulated lactating cows. All residues were corrected for microbial colonization, which was necessary in determining the AA composition of RUP from feed samples using in situ method. Compared with their original AA composition, the AA pattern of forages and forage-based diets changed drastically after rumen exposure. In addition, the extent of ruminal degradation of analysed AA was not constant among the forages. The greatest individual AA degradability of alfalfa hay and corn stover was Pro, but was His of rice straw. A remarkable difference was observed between microbial attachment corrected and uncorrected AA profiles of RUP, except for alfalfa hay and His in the three forages and TMR diets. The ruminal AA degradability of cereal straws was altered compared with alfalfa hay but not for the TMR diets. In summary, the AA composition of forages and TMR-based diets changed significantly after ruminal exposure, indicating that the original AA profiles of the feed cannot represent its AA composition of RUP. The AA profile of RUP and ruminal AA degradability for corn stover and rice straw contributed to missing information in the field. © 2017 Blackwell Verlag GmbH.

Surface Glycosylation Profiles of Urine Extracellular Vesicles

PubMed Central

Gerlach, Jared Q.; Krüger, Anja; Gallogly, Susan; Hanley, Shirley A.; Hogan, Marie C.; Ward, Christopher J.

2013-01-01

Urinary extracellular vesicles (uEVs) are released by cells throughout the nephron and contain biomolecules from their cells of origin. Although uEV-associated proteins and RNA have been studied in detail, little information exists regarding uEV glycosylation characteristics. Surface glycosylation profiling by flow cytometry and lectin microarray was applied to uEVs enriched from urine of healthy adults by ultracentrifugation and centrifugal filtration. The carbohydrate specificity of lectin microarray profiles was confirmed by competitive sugar inhibition and carbohydrate-specific enzyme hydrolysis. Glycosylation profiles of uEVs and purified Tamm Horsfall protein were compared. In both flow cytometry and lectin microarray assays, uEVs demonstrated surface binding, at low to moderate intensities, of a broad range of lectins whether prepared by ultracentrifugation or centrifugal filtration. In general, ultracentrifugation-prepared uEVs demonstrated higher lectin binding intensities than centrifugal filtration-prepared uEVs consistent with lesser amounts of co-purified non-vesicular proteins. The surface glycosylation profiles of uEVs showed little inter-individual variation and were distinct from those of Tamm Horsfall protein, which bound a limited number of lectins. In a pilot study, lectin microarray was used to compare uEVs from individuals with autosomal dominant polycystic kidney disease to those of age-matched controls. The lectin microarray profiles of polycystic kidney disease and healthy uEVs showed differences in binding intensity of 6/43 lectins. Our results reveal a complex surface glycosylation profile of uEVs that is accessible to lectin-based analysis following multiple uEV enrichment techniques, is distinct from co-purified Tamm Horsfall protein and may demonstrate disease-specific modifications. PMID:24069349

EvoDB: a database of evolutionary rate profiles, associated protein domains and phylogenetic trees for PFAM-A

PubMed Central

Ndhlovu, Andrew; Durand, Pierre M.; Hazelhurst, Scott

2015-01-01

The evolutionary rate at codon sites across protein-coding nucleotide sequences represents a valuable tier of information for aligning sequences, inferring homology and constructing phylogenetic profiles. However, a comprehensive resource for cataloguing the evolutionary rate at codon sites and their corresponding nucleotide and protein domain sequence alignments has not been developed. To address this gap in knowledge, EvoDB (an Evolutionary rates DataBase) was compiled. Nucleotide sequences and their corresponding protein domain data including the associated seed alignments from the PFAM-A (protein family) database were used to estimate evolutionary rate (ω = dN/dS) profiles at codon sites for each entry. EvoDB contains 98.83% of the gapped nucleotide sequence alignments and 97.1% of the evolutionary rate profiles for the corresponding information in PFAM-A. As the identification of codon sites under positive selection and their position in a sequence profile is usually the most sought after information for molecular evolutionary biologists, evolutionary rate profiles were determined under the M2a model using the CODEML algorithm in the PAML (Phylogenetic Analysis by Maximum Likelihood) suite of software. Validation of nucleotide sequences against amino acid data was implemented to ensure high data quality. EvoDB is a catalogue of the evolutionary rate profiles and provides the corresponding phylogenetic trees, PFAM-A alignments and annotated accession identifier data. In addition, the database can be explored and queried using known evolutionary rate profiles to identify domains under similar evolutionary constraints and pressures. EvoDB is a resource for evolutionary, phylogenetic studies and presents a tier of information untapped by current databases. Database URL: http://www.bioinf.wits.ac.za/software/fire/evodb PMID:26140928

EvoDB: a database of evolutionary rate profiles, associated protein domains and phylogenetic trees for PFAM-A.

PubMed

Ndhlovu, Andrew; Durand, Pierre M; Hazelhurst, Scott

2015-01-01

The evolutionary rate at codon sites across protein-coding nucleotide sequences represents a valuable tier of information for aligning sequences, inferring homology and constructing phylogenetic profiles. However, a comprehensive resource for cataloguing the evolutionary rate at codon sites and their corresponding nucleotide and protein domain sequence alignments has not been developed. To address this gap in knowledge, EvoDB (an Evolutionary rates DataBase) was compiled. Nucleotide sequences and their corresponding protein domain data including the associated seed alignments from the PFAM-A (protein family) database were used to estimate evolutionary rate (ω = dN/dS) profiles at codon sites for each entry. EvoDB contains 98.83% of the gapped nucleotide sequence alignments and 97.1% of the evolutionary rate profiles for the corresponding information in PFAM-A. As the identification of codon sites under positive selection and their position in a sequence profile is usually the most sought after information for molecular evolutionary biologists, evolutionary rate profiles were determined under the M2a model using the CODEML algorithm in the PAML (Phylogenetic Analysis by Maximum Likelihood) suite of software. Validation of nucleotide sequences against amino acid data was implemented to ensure high data quality. EvoDB is a catalogue of the evolutionary rate profiles and provides the corresponding phylogenetic trees, PFAM-A alignments and annotated accession identifier data. In addition, the database can be explored and queried using known evolutionary rate profiles to identify domains under similar evolutionary constraints and pressures. EvoDB is a resource for evolutionary, phylogenetic studies and presents a tier of information untapped by current databases. © The Author(s) 2015. Published by Oxford University Press.

Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

PubMed Central

Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

2011-01-01

Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

Protein Interaction Profile Sequencing (PIP-seq).

PubMed

Foley, Shawn W; Gregory, Brian D

2016-10-10

Every eukaryotic RNA transcript undergoes extensive post-transcriptional processing from the moment of transcription up through degradation. This regulation is performed by a distinct cohort of RNA-binding proteins which recognize their target transcript by both its primary sequence and secondary structure. Here, we describe protein interaction profile sequencing (PIP-seq), a technique that uses ribonuclease-based footprinting followed by high-throughput sequencing to globally assess both protein-bound RNA sequences and RNA secondary structure. PIP-seq utilizes single- and double-stranded RNA-specific nucleases in the absence of proteins to infer RNA secondary structure. These libraries are also compared to samples that undergo nuclease digestion in the presence of proteins in order to find enriched protein-bound sequences. Combined, these four libraries provide a comprehensive, transcriptome-wide view of RNA secondary structure and RNA protein interaction sites from a single experimental technique. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Affinity proteomic profiling of plasma for proteins associated to area-based mammographic breast density.

PubMed

Byström, Sanna; Eklund, Martin; Hong, Mun-Gwan; Fredolini, Claudia; Eriksson, Mikael; Czene, Kamila; Hall, Per; Schwenk, Jochen M; Gabrielson, Marike

2018-02-14

Mammographic breast density is one of the strongest risk factors for breast cancer, but molecular understanding of how breast density relates to cancer risk is less complete. Studies of proteins in blood plasma, possibly associated with mammographic density, are well-suited as these allow large-scale analyses and might shed light on the association between breast cancer and breast density. Plasma samples from 1329 women in the Swedish KARMA project, without prior history of breast cancer, were profiled with antibody suspension bead array (SBA) assays. Two sample sets comprising 729 and 600 women were screened by two different SBAs targeting a total number of 357 proteins. Protein targets were selected through searching the literature, for either being related to breast cancer or for being linked to the extracellular matrix. Association between proteins and absolute area-based breast density (AD) was assessed by quantile regression, adjusting for age and body mass index (BMI). Plasma profiling revealed linear association between 20 proteins and AD, concordant in the two sets of samples (p < 0.05). Plasma levels of seven proteins were positively associated and 13 proteins negatively associated with AD. For eleven of these proteins evidence for gene expression in breast tissue existed. Among these, ABCC11, TNFRSF10D, F11R and ERRF were positively associated with AD, and SHC1, CFLAR, ACOX2, ITGB6, RASSF1, FANCD2 and IRX5 were negatively associated with AD. Screening proteins in plasma indicates associations between breast density and processes of tissue homeostasis, DNA repair, cancer development and/or progression in breast cancer. Further validation and follow-up studies of the shortlisted protein candidates in independent cohorts will be needed to infer their role in breast density and its progression in premenopausal and postmenopausal women.

Quantitative proteomic view on secreted, cell surface-associated, and cytoplasmic proteins of the methicillin-resistant human pathogen Staphylococcus aureus under iron-limited conditions.

PubMed

Hempel, Kristina; Herbst, Florian-Alexander; Moche, Martin; Hecker, Michael; Becher, Dörte

2011-04-01

Staphylococcus aureus is capable of colonizing and infecting humans by its arsenal of surface-exposed and secreted proteins. Iron-limited conditions in mammalian body fluids serve as a major environmental signal to bacteria to express virulence determinants. Here we present a comprehensive, gel-free, and GeLC-MS/MS-based quantitative proteome profiling of S. aureus under this infection-relevant situation. (14)N(15)N metabolic labeling and three complementing approaches were combined for relative quantitative analyses of surface-associated proteins. The surface-exposed and secreted proteome profiling approaches comprise trypsin shaving, biotinylation, and precipitation of the supernatant. By analysis of the outer subproteomic and cytoplasmic protein fraction, 1210 proteins could be identified including 221 surface-associated proteins. Thus, access was enabled to 70% of the predicted cell wall-associated proteins, 80% of the predicted sortase substrates, two/thirds of lipoproteins and more than 50% of secreted and cytoplasmic proteins. For iron-deficiency, 158 surface-associated proteins were quantified. Twenty-nine proteins were found in altered amounts showing particularly surface-exposed proteins strongly induced, such as the iron-regulated surface determinant proteins IsdA, IsdB, IsdC and IsdD as well as lipid-anchored iron compound-binding proteins. The work presents a crucial subject for understanding S. aureus pathophysiology by the use of methods that allow quantitative surface proteome profiling.

Multiplexed Activity-based Protein Profiling of the Human Pathogen Aspergillus fumigatus Reveals Large Functional Changes upon Exposure to Human Serum

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

Wiedner, Susan D.; Burnum, Kristin E.; Pederson, Leeanna M.

2012-08-03

Environmental and metabolic adaptability is critical for survival of the fungal human pathogen Aspergillus fumigatus in the immunocompromised lung. We employed an activity-based protein profiling (ABPP) approach utilizing a new aryl vinyl sulfonate probe and a serine hydrolase probe combined with quantitative LC-MS based accurate mass and time (AMT) tag proteomics for the identification of functional pathway adaptation of A. fumigatus to environmental variability relevant to pulmonary Invasive Aspergillosis. When the fungal pathogen was grown with human serum, metabolism and energy processes were markedly decreased compared to no serum culture. Additionally, functional pathways associated with amino acid and protein biosynthesismore » were limited as the fungus scavenged from the serum to obtain essential nutrients. Our approach revealed significant metabolic adaptation by A. fumigatus, and provides direct insight into this pathogen’s ability to survive and proliferate.« less

ComplexQuant: high-throughput computational pipeline for the global quantitative analysis of endogenous soluble protein complexes using high resolution protein HPLC and precision label-free LC/MS/MS.

PubMed

Wan, Cuihong; Liu, Jian; Fong, Vincent; Lugowski, Andrew; Stoilova, Snejana; Bethune-Waddell, Dylan; Borgeson, Blake; Havugimana, Pierre C; Marcotte, Edward M; Emili, Andrew

2013-04-09

The experimental isolation and characterization of stable multi-protein complexes are essential to understanding the molecular systems biology of a cell. To this end, we have developed a high-throughput proteomic platform for the systematic identification of native protein complexes based on extensive fractionation of soluble protein extracts by multi-bed ion exchange high performance liquid chromatography (IEX-HPLC) combined with exhaustive label-free LC/MS/MS shotgun profiling. To support these studies, we have built a companion data analysis software pipeline, termed ComplexQuant. Proteins present in the hundreds of fractions typically collected per experiment are first identified by exhaustively interrogating MS/MS spectra using multiple database search engines within an integrative probabilistic framework, while accounting for possible post-translation modifications. Protein abundance is then measured across the fractions based on normalized total spectral counts and precursor ion intensities using a dedicated tool, PepQuant. This analysis allows co-complex membership to be inferred based on the similarity of extracted protein co-elution profiles. Each computational step has been optimized for processing large-scale biochemical fractionation datasets, and the reliability of the integrated pipeline has been benchmarked extensively. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2012 Elsevier B.V. All rights reserved.

Calling Biomarkers in Milk Using a Protein Microarray on Your Smartphone

PubMed Central

Ludwig, Susann K. J.; Tokarski, Christian; Lang, Stefan N.; van Ginkel, Leendert A.; Zhu, Hongying; Ozcan, Aydogan; Nielen, Michel W. F.

2015-01-01

Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay procedure, the 48 microspots were labelled with Quantum Dots (QD) depending on the protein biomarker levels in the sample. QD-fluorescence was subsequently detected by the smartphone camera under UV light excitation from LEDs embedded in a simple 3D-printed opto-mechanical smartphone attachment. The somewhat aberrant images obtained under such conditions, were corrected by newly developed Android-based software on the same smartphone, and protein biomarker profiles were calculated. The indirect detection of recombinant bovine somatotropin (rbST) in milk extracts based on altered biomarker profile of anti-rbST antibodies was selected as a real-life challenge. RbST-treated and untreated cows clearly showed reproducible treatment-dependent biomarker profiles in milk, in excellent agreement with results from a flow cytometer reference method. In a pilot experiment, anti-rbST antibody detection was multiplexed with the detection of another rbST-dependent biomarker, insulin-like growth factor 1 (IGF-1). Milk extract IGF-1 levels were found to be increased after rbST treatment and correlated with the results obtained from the reference method. These data clearly demonstrate the potential of the portable protein microarray concept towards simultaneous detection of multiple biomarkers. We envisage broad application of this ‘protein microarray on a smartphone’-concept for on-site testing, e.g., in food safety, environment and health monitoring. PMID:26308444

On the Regularities of the Polar Profiles of Proteins Related to Ebola Virus Infection and their Functional Domains.

PubMed

Polanco, Carlos; Samaniego Mendoza, José Lino; Buhse, Thomas; Uversky, Vladimir N; Bañuelos Chao, Ingrid Paola; Bañuelos Cedano, Marcela Angola; Tavera, Fernando Michel; Tavera, Daniel Michel; Falconi, Manuel; Ponce de León, Abelardo Vela

2018-03-06

The number of fatalities and economic losses caused by the Ebola virus infection across the planet culminated in the havoc that occurred between August and November 2014. However, little is known about the molecular protein profile of this devastating virus. This work represents a thorough bioinformatics analysis of the regularities of charge distribution (polar profiles) in two groups of proteins and their functional domains associated with Ebola virus disease: Ebola virus proteins and Human proteins interacting with Ebola virus. Our analysis reveals that a fragment exists in each of these proteins-one named the "functional domain"-with the polar profile similar to the polar profile of the protein that contains it. Each protein is formed by a group of short sub-sequences, where each fragment has a different and distinctive polar profile and where the polar profile between adjacent short sub-sequences changes orderly and gradually to coincide with the polar profile of the whole protein. When using the charge distribution as a metric, it was observed that it effectively discriminates the proteins from their functional domains. As a counterexample, the same test was applied to a set of synthetic proteins built for that purpose, revealing that any of the regularities reported here for the Ebola virus proteins and human proteins interacting with Ebola virus were not present in the synthetic proteins. Our results indicate that the polar profile of each protein studied and its corresponding functional domain are similar. Thus, when building each protein from its functional domai-adding one amino acid at a time and plotting each time its polar profile-it was observed that the resulting graphs can be divided into groups with similar polar profiles.

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

PubMed

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

PubMed Central

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components. PMID:29692857

Serum proteomic profiling for autism using magnetic bead-assisted matrix-assisted laser desorption ionization time-of-flight mass spectrometry: a pilot study.

PubMed

Chen, Yan-Ni; Du, Hui-Ying; Shi, Zhuo-Yue; He, Li; He, Yu-Ying; Wang, Duan

2018-01-24

The pathogenesis of autism spectrum disorders remains elusive and currently there are no diagnostic or predictive biomarkers in autism available. Proteomic profiling has been used in a wide range of neurodevelopmental disorder studies, which could produce deeper perceptions of the molecular bases behind certain disease and potentially becomes useful in discovering biomarkers in autism spectrum disorders. Serum samples were collected from autistic children about 3 years old in age (n = 32) and healthy controls (n = 20) in similar age and gender. The samples were identified specific proteins that are differentially expressed by magnetic bead-based pre-fractionation and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF-MS). Eight protein peaks were significantly different in autistic children from the healthy controls (P < 0.0001). The two peaks with the most significant differences were 6428 and 7758 Da in size. According to differences in serum protein profiles between the autistic children and healthy controls, this study identified a set of differentially expressed proteins those are significant for further evaluation and might function as biomarkers in autism.

Characterization of a PEGylated protein therapeutic by ion exchange chromatography with on-line detection by native ESI MS and MS/MS.

PubMed

Muneeruddin, K; Bobst, C E; Frenkel, R; Houde, D; Turyan, I; Sosic, Z; Kaltashov, I A

2017-01-16

Detailed profiling of both enzymatic (e.g., glycosylation) and non-enzymatic (e.g., oxidation and deamidation) post-translational modifications (PTMs) is frequently required for the quality assessment of protein-based drugs. Challenging as it is, this task is further complicated for the so-called second-generation biopharmaceuticals, which also contain "designer PTMs" introduced to either enhance their pharmacokinetic profiles (e.g., PEGylated proteins) or endow them with therapeutic activity (e.g., protein-drug conjugates). Such modifications of protein covalent structure can dramatically increase structural heterogeneity, making the very notion of "molecular mass" meaningless, as ions representing different glycoforms of a PEGylated protein may have nearly identical distributions of ionic current as a function of m/z, making their contributions to the mass spectrum impossible to distinguish. In this work we demonstrate that a combination of ion exchange chromatography (IXC) with on-line detection by electrospray ionization mass spectrometry (ESI MS) and methods of ion manipulation in the gas phase (limited charge reduction and collision-induced dissociation) allows meaningful structural information to be obtained on a structurally heterogeneous sample of PEGylated interferon β-1a. IXC profiling of the protein sample gives rise to a convoluted chromatogram with several partially resolved peaks which can represent both deamidation and different glycosylation patterns within the protein, as well as varying extent of PEGylation. Thus, profiling the protein with on-line IXC/ESI/MS/MS allows it to be characterized by providing information on three different types of PTMs (designer, enzymatic and non-enzymatic) within a single protein therapeutic.

Investigating the fate of activated sludge extracellular proteins in sludge digestion using sodium dodecyl sulfate polyacrylamide gel electrophoresis.

PubMed

Park, Chul; Helm, Richard F; Novak, John T

2008-12-01

The fate of activated sludge extracellular proteins in sludge digestion was investigated using three different cation-associated extraction methods and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Extraction methods used were the cation exchange resin (CER) method for extracting calcium (Ca2+) and magnesium (Mg2+), sulfide extraction for removing iron, and base treatment (pH 10.5) for dissolving aluminum. Extracellular polymeric substances extracted were then subjected to SDS-PAGE, and the resultant protein profiles were examined before and after sludge digestion. The SDS-PAGE results showed that three methods led to different SDS-PAGE profiles for both undigested and digested sludges. The results further revealed that CER-extracted proteins remained mainly undegraded in anaerobic digestion, but were degraded in aerobic digestion. While the fate of sulfide- and base-extracted proteins was not clear for aerobic digestion, their changes in anaerobic digestion were elucidated. Most sulfide-extracted proteins were removed by anaerobic digestion, while the increase in protein band intensity and diversity was observed for base-extracted proteins. These results suggest that activated sludge flocs contain different fractions of proteins that are distinguishable by their association with certain cations and that each fraction undergoes different fates in anaerobic and aerobic digestion. The proteins that were resistant to degradation and generated during anaerobic digestion were identified by liquid chromatography tandem mass spectrometry. Protein identification results and their putative roles in activated sludge and anaerobic digestion are discussed in this study.

PLIP: fully automated protein-ligand interaction profiler.

PubMed

Salentin, Sebastian; Schreiber, Sven; Haupt, V Joachim; Adasme, Melissa F; Schroeder, Michael

2015-07-01

The characterization of interactions in protein-ligand complexes is essential for research in structural bioinformatics, drug discovery and biology. However, comprehensive tools are not freely available to the research community. Here, we present the protein-ligand interaction profiler (PLIP), a novel web service for fully automated detection and visualization of relevant non-covalent protein-ligand contacts in 3D structures, freely available at projects.biotec.tu-dresden.de/plip-web. The input is either a Protein Data Bank structure, a protein or ligand name, or a custom protein-ligand complex (e.g. from docking). In contrast to other tools, the rule-based PLIP algorithm does not require any structure preparation. It returns a list of detected interactions on single atom level, covering seven interaction types (hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation interactions, salt bridges, water bridges and halogen bonds). PLIP stands out by offering publication-ready images, PyMOL session files to generate custom images and parsable result files to facilitate successive data processing. The full python source code is available for download on the website. PLIP's command-line mode allows for high-throughput interaction profiling. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective.

PubMed

Findeisen, Peter; Neumaier, Michael

2009-01-01

Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

Alchemical Free Energy Calculations for Nucleotide Mutations in Protein-DNA Complexes.

PubMed

Gapsys, Vytautas; de Groot, Bert L

2017-12-12

Nucleotide-sequence-dependent interactions between proteins and DNA are responsible for a wide range of gene regulatory functions. Accurate and generalizable methods to evaluate the strength of protein-DNA binding have long been sought. While numerous computational approaches have been developed, most of them require fitting parameters to experimental data to a certain degree, e.g., machine learning algorithms or knowledge-based statistical potentials. Molecular-dynamics-based free energy calculations offer a robust, system-independent, first-principles-based method to calculate free energy differences upon nucleotide mutation. We present an automated procedure to set up alchemical MD-based calculations to evaluate free energy changes occurring as the result of a nucleotide mutation in DNA. We used these methods to perform a large-scale mutation scan comprising 397 nucleotide mutation cases in 16 protein-DNA complexes. The obtained prediction accuracy reaches 5.6 kJ/mol average unsigned deviation from experiment with a correlation coefficient of 0.57 with respect to the experimentally measured free energies. Overall, the first-principles-based approach performed on par with the molecular modeling approaches Rosetta and FoldX. Subsequently, we utilized the MD-based free energy calculations to construct protein-DNA binding profiles for the zinc finger protein Zif268. The calculation results compare remarkably well with the experimentally determined binding profiles. The software automating the structure and topology setup for alchemical calculations is a part of the pmx package; the utilities have also been made available online at http://pmx.mpibpc.mpg.de/dna_webserver.html .

Integrated analysis of rice transcriptomic and metabolomic responses to elevated night temperatures identifies sensitivity- and tolerance-related profiles.

PubMed

Glaubitz, Ulrike; Li, Xia; Schaedel, Sandra; Erban, Alexander; Sulpice, Ronan; Kopka, Joachim; Hincha, Dirk K; Zuther, Ellen

2017-01-01

Transcript and metabolite profiling were performed on leaves from six rice cultivars under high night temperature (HNT) condition. Six genes were identified as central for HNT response encoding proteins involved in transcription regulation, signal transduction, protein-protein interactions, jasmonate response and the biosynthesis of secondary metabolites. Sensitive cultivars showed specific changes in transcript abundance including abiotic stress responses, changes of cell wall-related genes, of ABA signaling and secondary metabolism. Additionally, metabolite profiles revealed a highly activated TCA cycle under HNT and concomitantly increased levels in pathways branching off that could be corroborated by enzyme activity measurements. Integrated data analysis using clustering based on one-dimensional self-organizing maps identified two profiles highly correlated with HNT sensitivity. The sensitivity profile included genes of the functional bins abiotic stress, hormone metabolism, cell wall, signaling, redox state, transcription factors, secondary metabolites and defence genes. In the tolerance profile, similar bins were affected with slight differences in hormone metabolism and transcription factor responses. Metabolites of the two profiles revealed involvement of GABA signaling, thus providing a link to the TCA cycle status in sensitive cultivars and of myo-inositol as precursor for inositol phosphates linking jasmonate signaling to the HNT response specifically in tolerant cultivars. © 2016 John Wiley & Sons Ltd.

Poly(lactic-co-glycolic acid) devices: Production and applications for sustained protein delivery.

PubMed

Lee, Parker W; Pokorski, Jonathan K

2018-03-13

Injectable or implantable poly(lactic-co-glycolic acid) (PLGA) devices for the sustained delivery of proteins have been widely studied and utilized to overcome the necessity of repeated administrations for therapeutic proteins due to poor pharmacokinetic profiles of macromolecular therapies. These devices can come in the form of microparticles, implants, or patches depending on the disease state and route of administration. Furthermore, the release rate can be tuned from weeks to months by controlling the polymer composition, geometry of the device, or introducing additives during device fabrication. Slow-release devices have become a very powerful tool for modern medicine. Production of these devices has initially focused on emulsion-based methods, relying on phase separation to encapsulate proteins within polymeric microparticles. Process parameters and the effect of additives have been thoroughly researched to ensure protein stability during device manufacturing and to control the release profile. Continuous fluidic production methods have also been utilized to create protein-laden PLGA devices through spray drying and electrospray production. Thermal processing of PLGA with solid proteins is an emerging production method that allows for continuous, high-throughput manufacturing of PLGA/protein devices. Overall, polymeric materials for protein delivery remain an emerging field of research for the creation of single administration treatments for a wide variety of disease. This review describes, in detail, methods to make PLGA devices, comparing traditional emulsion-based methods to emerging methods to fabricate protein-laden devices. This article is categorized under: Biology-Inspired Nanomaterials > Protein and Virus-Based Structures Implantable Materials and Surgical Technologies > Nanomaterials and Implants Biology-Inspired Nanomaterials > Peptide-Based Structures. © 2018 Wiley Periodicals, Inc.

Recombinant Human Lysyl Oxidase-like 2 Secreted from Human Embryonic Kidney Cells Displays Complex and Acidic Glycans at All Three N-Linked Glycosylation Sites.

PubMed

Go, Eden P; Moon, Hee-Jung; Mure, Minae; Desaire, Heather

2018-05-04

Human lysyl oxidase-like 2 (hLOXL2), a glycoprotein implicated in tumor progression and organ fibrosis, is a molecular target for anticancer and antifibrosis treatment. This glycoprotein contains three predicted N-linked glycosylation sites; one is near the protein's active site, and at least one more is known to facilitate the protein's secretion. Because the glycosylation impacts the protein's biology, we sought to characterize the native, mammalian glycosylation profile and to determine how closely this profile is recapitulated when the protein is expressed in insect cells. All three glycosylation sites on the protein, expressed in human embryonic kidney (HEK) cells, were characterized individually using a mass spectrometry-based glycopeptide analysis workflow. These data were compared to the glycosylation profile of the same protein expressed in insect cells. We found that the producer cell type imparts a substantial influence on the glycosylation of this important protein. The more-relevant version, expressed in HEK cells, contains large, acidic glycoforms; these glycans are not generated in insect cells. The glycosylation differences likely have structural and functional consequences, and these data should be considered when generating protein for functional studies or for high-throughput screening campaigns.

Prediction of protein long-range contacts using an ensemble of genetic algorithm classifiers with sequence profile centers.

PubMed

Chen, Peng; Li, Jinyan

2010-05-17

Prediction of long-range inter-residue contacts is an important topic in bioinformatics research. It is helpful for determining protein structures, understanding protein foldings, and therefore advancing the annotation of protein functions. In this paper, we propose a novel ensemble of genetic algorithm classifiers (GaCs) to address the long-range contact prediction problem. Our method is based on the key idea called sequence profile centers (SPCs). Each SPC is the average sequence profiles of residue pairs belonging to the same contact class or non-contact class. GaCs train on multiple but different pairs of long-range contact data (positive data) and long-range non-contact data (negative data). The negative data sets, having roughly the same sizes as the positive ones, are constructed by random sampling over the original imbalanced negative data. As a result, about 21.5% long-range contacts are correctly predicted. We also found that the ensemble of GaCs indeed makes an accuracy improvement by around 5.6% over the single GaC. Classifiers with the use of sequence profile centers may advance the long-range contact prediction. In line with this approach, key structural features in proteins would be determined with high efficiency and accuracy.

Secretome profiles of immortalized dental follicle cells using iTRAQ-based proteomic analysis.

PubMed

Dou, Lei; Wu, Yan; Yan, Qifang; Wang, Jinhua; Zhang, Yan; Ji, Ping

2017-08-04

Secretomes produced by mesenchymal stromal cells (MSCs) were considered to be therapeutic potential. However, harvesting enough primary MSCs from tissue was time-consuming and costly, which impeded the application of MSCs secretomes. This study was to immortalize MSCs and compare the secretomes profile of immortalized and original MSCs. Human dental follicle cells (DFCs) were isolated and immortalized using pMPH86. The secretome profile of immortalized DFCs (iDFCs) was investigated and compared using iTRAQ labeling combined with mass spectrometry (MS) quantitative proteomics. The MS data was analyzed using ProteinPilotTM software, and then bioinformatic analysis of identified proteins was done. A total of 2092 secreted proteins were detected in conditioned media of iDFCs. Compared with primary DFCs, 253 differently expressed proteins were found in iDFCs secretome (142 up-regulated and 111 down-regulated). Intensive bioinformatic analysis revealed that the majority of secreted proteins were involved in cellular process, metabolic process, biological regulation, cellular component organization or biogenesis, immune system process, developmental process, response to stimulus and signaling. Proteomic profile of cell secretome wasn't largely affected after immortalization converted by this piggyBac immortalization system. The secretome of iDFCs may be a good candidate of primary DFCs for regenerative medicine.

Multiple biomarkers in molecular oncology. II. Molecular diagnostics applications in breast cancer management.

PubMed

Malinowski, Douglas P

2007-05-01

In recent years, the application of genomic and proteomic technologies to the problem of breast cancer prognosis and the prediction of therapy response have begun to yield encouraging results. Independent studies employing transcriptional profiling of primary breast cancer specimens using DNA microarrays have identified gene expression profiles that correlate with clinical outcome in primary breast biopsy specimens. Recent advances in microarray technology have demonstrated reproducibility, making clinical applications more achievable. In this regard, one such DNA microarray device based upon a 70-gene expression signature was recently cleared by the US FDA for application to breast cancer prognosis. These DNA microarrays often employ at least 70 gene targets for transcriptional profiling and prognostic assessment in breast cancer. The use of PCR-based methods utilizing a small subset of genes has recently demonstrated the ability to predict the clinical outcome in early-stage breast cancer. Furthermore, protein-based immunohistochemistry methods have progressed from using gene clusters and gene expression profiling to smaller subsets of expressed proteins to predict prognosis in early-stage breast cancer. Beyond prognostic applications, DNA microarray-based transcriptional profiling has demonstrated the ability to predict response to chemotherapy in early-stage breast cancer patients. In this review, recent advances in the use of multiple markers for prognosis of disease recurrence in early-stage breast cancer and the prediction of therapy response will be discussed.

Multivariate proteomic profiling identifies novel accessory proteins of coated vesicles

PubMed Central

Antrobus, Robin; Hirst, Jennifer; Bhumbra, Gary S.; Kozik, Patrycja; Jackson, Lauren P.; Sahlender, Daniela A.

2012-01-01

Despite recent advances in mass spectrometry, proteomic characterization of transport vesicles remains challenging. Here, we describe a multivariate proteomics approach to analyzing clathrin-coated vesicles (CCVs) from HeLa cells. siRNA knockdown of coat components and different fractionation protocols were used to obtain modified coated vesicle-enriched fractions, which were compared by stable isotope labeling of amino acids in cell culture (SILAC)-based quantitative mass spectrometry. 10 datasets were combined through principal component analysis into a “profiling” cluster analysis. Overall, 136 CCV-associated proteins were predicted, including 36 new proteins. The method identified >93% of established CCV coat proteins and assigned >91% correctly to intracellular or endocytic CCVs. Furthermore, the profiling analysis extends to less well characterized types of coated vesicles, and we identify and characterize the first AP-4 accessory protein, which we have named tepsin. Finally, our data explain how sequestration of TACC3 in cytosolic clathrin cages causes the severe mitotic defects observed in auxilin-depleted cells. The profiling approach can be adapted to address related cell and systems biological questions. PMID:22472443

Chemoproteomic profiling and discovery of protein electrophiles in human cells

NASA Astrophysics Data System (ADS)

Matthews, Megan L.; He, Lin; Horning, Benjamin D.; Olson, Erika J.; Correia, Bruno E.; Yates, John R.; Dawson, Philip E.; Cravatt, Benjamin F.

2017-03-01

Activity-based protein profiling (ABPP) serves as a chemical proteomic platform to discover and characterize functional amino acids in proteins on the basis of their enhanced reactivity towards small-molecule probes. This approach, to date, has mainly targeted nucleophilic functional groups, such as the side chains of serine and cysteine, using electrophilic probes. Here we show that 'reverse-polarity' (RP)-ABPP using clickable, nucleophilic hydrazine probes can capture and identify protein-bound electrophiles in cells. Using this approach, we demonstrate that the pyruvoyl cofactor of S-adenosyl-L-methionine decarboxylase (AMD1) is dynamically controlled by intracellular methionine concentrations. We also identify a heretofore unknown modification—an N-terminally bound glyoxylyl group—in the poorly characterized protein secernin-3. RP-ABPP thus provides a versatile method to monitor the metabolic regulation of electrophilic cofactors and discover novel types of electrophilic modifications on proteins in human cells.

Demonstration of protein-based human identification using the hair shaft proteome [Protein-based human identification: A proof of concept using the hair shaft proteome

DOE PAGES

Parker, Glendon J.; Leppert, Tami; Anex, Deon S.; ...

2016-09-07

Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 singlemore » nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects’ DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European–American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). Furthermore, this study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.« less

Demonstration of protein-based human identification using the hair shaft proteome [Protein-based human identification: A proof of concept using the hair shaft proteome

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

Parker, Glendon J.; Leppert, Tami; Anex, Deon S.

Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 singlemore » nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects’ DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European–American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). Furthermore, this study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.« less

Quantitative iTRAQ secretome analysis of Aspergillus niger reveals novel hydrolytic enzymes.

PubMed

Adav, Sunil S; Li, An A; Manavalan, Arulmani; Punt, Peter; Sze, Siu Kwan

2010-08-06

The natural lifestyle of Aspergillus niger made them more effective secretors of hydrolytic proteins and becomes critical when this species were exploited as hosts for the commercial secretion of heterologous proteins. The protein secretion profile of A. niger and its mutant at different pH was explored using iTRAQ-based quantitative proteomics approach coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). This study characterized 102 highly confident unique proteins in the secretome with zero false discovery rate based on decoy strategy. The iTRAQ technique identified and relatively quantified many hydrolyzing enzymes such as cellulases, hemicellulases, glycoside hydrolases, proteases, peroxidases, and protein translocating transporter proteins during fermentation. The enzymes have potential application in lignocellulosic biomass hydrolysis for biofuel production, for example, the cellulolytic and hemicellulolytic enzymes glucan 1,4-alpha-glucosidase, alpha-glucosidase C, endoglucanase, alpha l-arabinofuranosidase, beta-mannosidase, glycosyl hydrolase; proteases such as tripeptidyl-peptidase, aspergillopepsin, and other enzymes including cytochrome c oxidase, cytochrome c oxidase, glucose oxidase were highly expressed in A. niger and its mutant secretion. In addition, specific enzyme production can be stimulated by controlling pH of the culture medium. Our results showed comprehensive unique secretory protein profile of A. niger, its regulation at different pH, and the potential application of iTRAQ-based quantitative proteomics for the microbial secretome analysis.

Functional protease profiling for diagnosis of malignant disease.

PubMed

Findeisen, Peter; Neumaier, Michael

2012-01-01

Clinical proteomic profiling by mass spectrometry (MS) aims at uncovering specific alterations within mass profiles of clinical specimens that are of diagnostic value for the detection and classification of various diseases including cancer. However, despite substantial progress in the field, the clinical proteomic profiling approaches have not matured into routine diagnostic applications so far. Their limitations are mainly related to high-abundance proteins and their complex processing by a multitude of endogenous proteases thus making rigorous standardization difficult. MS is biased towards the detection of low-molecular-weight peptides. Specifically, in serum specimens, the particular fragments of proteolytically degraded proteins are amenable to MS analysis. Proteases are known to be involved in tumour progression and tumour-specific proteases are released into the blood stream presumably as a result of invasive progression and metastasis. Thus, the determination of protease activity in clinical specimens from patients with malignant disease can offer diagnostic and also therapeutic options. The identification of specific substrates for tumour proteases in complex biological samples is challenging, but proteomic screens for proteases/substrate interactions are currently experiencing impressive progress. Such proteomic screens include peptide-based libraries, differential isotope labelling in combination with MS, quantitative degradomic analysis of proteolytically generated neo-N-termini, monitoring the degradation of exogenous reporter peptides with MS, and activity-based protein profiling. In the present article, we summarize and discuss the current status of proteomic techniques to identify tumour-specific protease-substrate interactions for functional protease profiling. Thereby, we focus on the potential diagnostic use of the respective approaches. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of Potential Biomarkers for Rhegmatogenous Retinal Detachment Associated with Choroidal Detachment by Vitreous iTRAQ-Based Proteomic Profiling

PubMed Central

Wu, Zhifeng; Ding, Nannan; Yu, Mengxi; Wang, Ke; Luo, Shasha; Zou, Wenjun; Zhou, Ying; Yan, Biao; Jiang, Qin

2016-01-01

Rhegmatogenous retinal detachment associated with choroidal detachment (RRDCD) is a complicated and serious type of rhegmatogenous retinal detachment (RRD). In this study, we identified differentially expressed proteins in the vitreous humors of RRDCD and RRD using isobaric tags for relative and absolute quantitation (iTRAQ) combined with nano-liquid chromatography-electrospray ion trap-mass spectrometry-mass spectrometry (nano-LC-ESI-MS/MS) and bioinformatic analysis. Our result shows that 103 differentially expressed proteins, including 54 up-regulated and 49 down-regulated proteins were identified in RRDCD. Gene ontology (GO) analysis suggested that most of the differentially expressed proteins were extracellular．The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis suggested that proteins related to complement and coagulation cascades were significantly enriched. iTRAQ-based proteomic profiling reveals that complement and coagulation cascades and inflammation may play important roles in the pathogenesis of RRDCD. This study may provide novel insights into the pathogenesis of RRDCD and offer potential opportunities for the diagnosis and treatment of RRDCD. PMID:27941623

High-throughput profiling of nanoparticle-protein interactions by fluorescamine labeling.

PubMed

Ashby, Jonathan; Duan, Yaokai; Ligans, Erik; Tamsi, Michael; Zhong, Wenwan

2015-02-17

A rapid, high throughput fluorescence assay was designed to screen interactions between proteins and nanoparticles. The assay employs fluorescamine, a primary-amine specific fluorogenic dye, to label proteins. Because fluorescamine could specifically target the surface amines on proteins, a conformational change of the protein upon interaction with nanoparticles will result in a change in fluorescence. In the present study, the assay was applied to test the interactions between a selection of proteins and nanoparticles made of polystyrene, silica, or iron oxide. The particles were also different in their hydrodynamic diameter, synthesis procedure, or surface modification. Significant labeling differences were detected when the same protein incubated with different particles. Principal component analysis (PCA) on the collected fluorescence profiles revealed clear grouping effects of the particles based on their properties. The results prove that fluorescamine labeling is capable of detecting protein-nanoparticle interactions, and the resulting fluorescence profile is sensitive to differences in nanoparticle's physical properties. The assay can be carried out in a high-throughput manner, and is rapid with low operation cost. Thus, it is well suited for evaluating interactions between a larger number of proteins and nanoparticles. Such assessment can help to improve our understanding on the molecular basis that governs the biological behaviors of nanomaterials. It will also be useful for initial examination of the bioactivity and reproducibility of nanomaterials employed in biomedical fields.

Fourier-based classification of protein secondary structures.

PubMed

Shu, Jian-Jun; Yong, Kian Yan

2017-04-15

The correct prediction of protein secondary structures is one of the key issues in predicting the correct protein folded shape, which is used for determining gene function. Existing methods make use of amino acids properties as indices to classify protein secondary structures, but are faced with a significant number of misclassifications. The paper presents a technique for the classification of protein secondary structures based on protein "signal-plotting" and the use of the Fourier technique for digital signal processing. New indices are proposed to classify protein secondary structures by analyzing hydrophobicity profiles. The approach is simple and straightforward. Results show that the more types of protein secondary structures can be classified by means of these newly-proposed indices. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluating the efficacy of subcellular fractionation of blast cells using live cell labeling and 2D DIGE.

PubMed

Ho, Yin Ying; Penno, Megan; Perugini, Michelle; Lewis, Ian; Hoffmann, Peter

2012-01-01

Labeling of exposed cell surface proteins of live cells using CyDye DIGE fluor minimal dyes is an efficient strategy for cell surface proteome profiling and quantifying differentially expressed proteins in diseases. Here we describe a strategy to evaluate a two-step detergent-based protein fractionation method using live cell labeling followed by visualization of the fluorescently labeled cell surface proteins and fractionated proteins within a single 2D gel.

Evolutionary profiles derived from the QR factorization of multiple structural alignments gives an economy of information.

PubMed

O'Donoghue, Patrick; Luthey-Schulten, Zaida

2005-02-25

We present a new algorithm, based on the multidimensional QR factorization, to remove redundancy from a multiple structural alignment by choosing representative protein structures that best preserve the phylogenetic tree topology of the homologous group. The classical QR factorization with pivoting, developed as a fast numerical solution to eigenvalue and linear least-squares problems of the form Ax=b, was designed to re-order the columns of A by increasing linear dependence. Removing the most linear dependent columns from A leads to the formation of a minimal basis set which well spans the phase space of the problem at hand. By recasting the problem of redundancy in multiple structural alignments into this framework, in which the matrix A now describes the multiple alignment, we adapted the QR factorization to produce a minimal basis set of protein structures which best spans the evolutionary (phase) space. The non-redundant and representative profiles obtained from this procedure, termed evolutionary profiles, are shown in initial results to outperform well-tested profiles in homology detection searches over a large sequence database. A measure of structural similarity between homologous proteins, Q(H), is presented. By properly accounting for the effect and presence of gaps, a phylogenetic tree computed using this metric is shown to be congruent with the maximum-likelihood sequence-based phylogeny. The results indicate that evolutionary information is indeed recoverable from the comparative analysis of protein structure alone. Applications of the QR ordering and this structural similarity metric to analyze the evolution of structure among key, universally distributed proteins involved in translation, and to the selection of representatives from an ensemble of NMR structures are also discussed.

EFFECT OF HIGH-FAT DIETS SUPPLEMENTED WITH OKARA SOYBEAN BY-PRODUCT ON LIPID PROFILES OF PLASMA, LIVER AND FAECES IN SYRIAN HAMSTERS

USDA-ARS?s Scientific Manuscript database

The main components of okara, a by-product from soybean, is dietary fiber and protein. Both dietary fiber and protein can reduce plasma cholesterol. In this study we fed okara based diets with different amounts of fiber, protein and isoflavones to determine the most important component for choleste...

Prediction of protein-protein interaction network using a multi-objective optimization approach.

PubMed

Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

2016-06-01

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

The state of proteome profiling in the fungal genus Aspergillus.

PubMed

Kim, Yonghyun; Nandakumar, M P; Marten, Mark R

2008-03-01

Aspergilli are an important genus of filamentous fungi that contribute to a multibillion dollar industry. Since many fungal genome sequencing were recently completed, it would be advantageous to profile their proteome to better understand the fungal cell factory. Here, we review proteomic data generated for the Aspergilli in recent years. Thus far, a combined total of 28 cell surface, 102 secreted and 139 intracellular proteins have been identified based on 10 different studies on Aspergillus proteomics. A summary proteome map highlighting identified proteins in major metabolic pathway is presented.

Intact Cell MALDI-TOF MS on Sperm: A Molecular Test For Male Fertility Diagnosis.

PubMed

Soler, Laura; Labas, Valérie; Thélie, Aurore; Grasseau, Isabelle; Teixeira-Gomes, Ana-Paula; Blesbois, Elisabeth

2016-06-01

Currently, evaluation of sperm quality is primarily based on in vitro measures of sperm function such as motility, viability and/or acrosome reaction. However, results are often poorly correlated with fertility, and alternative diagnostic tools are therefore needed both in veterinary and human medicine. In a recent pilot study, we demonstrated that MS profiles from intact chicken sperm using MALDI-TOF profiles could detect significant differences between fertile/subfertile spermatozoa showing that such profiles could be useful for in vitro male fertility testing. In the present study, we performed larger standardized experimental procedures designed for the development of fertility- predictive mathematical models based on sperm cell MALDI-TOF MS profiles acquired through a fast, automated method. This intact cell MALDI-TOF MS-based method showed high diagnostic accuracy in identifying fertile/subfertile males in a large male population of known fertility from two distinct genetic lineages (meat and egg laying lines). We additionally identified 40% of the m/z peaks observed in sperm MS profiles through a top-down high-resolution protein identification analysis. This revealed that the MALDI-TOF MS spectra obtained from intact sperm cells contained a large proportion of protein degradation products, many implicated in important functional pathways in sperm such as energy metabolism, structure and movement. Proteins identified by our predictive model included diverse and important functional classes providing new insights into sperm function as it relates to fertility differences in this experimental system. Thus, in addition to the chicken model system developed here, with the use of appropriate models these methods should effectively translate to other animal taxa where similar tests for fertility are warranted. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Autonomous microfluidic sample preparation system for protein profile-based detection of aerosolized bacterial cells and spores.

PubMed

Stachowiak, Jeanne C; Shugard, Erin E; Mosier, Bruce P; Renzi, Ronald F; Caton, Pamela F; Ferko, Scott M; Van de Vreugde, James L; Yee, Daniel D; Haroldsen, Brent L; VanderNoot, Victoria A

2007-08-01

For domestic and military security, an autonomous system capable of continuously monitoring for airborne biothreat agents is necessary. At present, no system meets the requirements for size, speed, sensitivity, and selectivity to warn against and lead to the prevention of infection in field settings. We present a fully automated system for the detection of aerosolized bacterial biothreat agents such as Bacillus subtilis (surrogate for Bacillus anthracis) based on protein profiling by chip gel electrophoresis coupled with a microfluidic sample preparation system. Protein profiling has previously been demonstrated to differentiate between bacterial organisms. With the goal of reducing response time, multiple microfluidic component modules, including aerosol collection via a commercially available collector, concentration, thermochemical lysis, size exclusion chromatography, fluorescent labeling, and chip gel electrophoresis were integrated together to create an autonomous collection/sample preparation/analysis system. The cycle time for sample preparation was approximately 5 min, while total cycle time, including chip gel electrophoresis, was approximately 10 min. Sensitivity of the coupled system for the detection of B. subtilis spores was 16 agent-containing particles per liter of air, based on samples that were prepared to simulate those collected by wetted cyclone aerosol collector of approximately 80% efficiency operating for 7 min.

Gene expression profiling via LongSAGE in a non-model plant species: a case study in seeds of Brassica napus

PubMed Central

Obermeier, Christian; Hosseini, Bashir; Friedt, Wolfgang; Snowdon, Rod

2009-01-01

Background Serial analysis of gene expression (LongSAGE) was applied for gene expression profiling in seeds of oilseed rape (Brassica napus ssp. napus). The usefulness of this technique for detailed expression profiling in a non-model organism was demonstrated for the highly complex, neither fully sequenced nor annotated genome of B. napus by applying a tag-to-gene matching strategy based on Brassica ESTs and the annotated proteome of the closely related model crucifer A. thaliana. Results Transcripts from 3,094 genes were detected at two time-points of seed development, 23 days and 35 days after pollination (DAP). Differential expression showed a shift from gene expression involved in diverse developmental processes including cell proliferation and seed coat formation at 23 DAP to more focussed metabolic processes including storage protein accumulation and lipid deposition at 35 DAP. The most abundant transcripts at 23 DAP were coding for diverse protease inhibitor proteins and proteases, including cysteine proteases involved in seed coat formation and a number of lipid transfer proteins involved in embryo pattern formation. At 35 DAP, transcripts encoding napin, cruciferin and oleosin storage proteins were most abundant. Over both time-points, 18.6% of the detected genes were matched by Brassica ESTs identified by LongSAGE tags in antisense orientation. This suggests a strong involvement of antisense transcript expression in regulatory processes during B. napus seed development. Conclusion This study underlines the potential of transcript tagging approaches for gene expression profiling in Brassica crop species via EST matching to annotated A. thaliana genes. Limits of tag detection for low-abundance transcripts can today be overcome by ultra-high throughput sequencing approaches, so that tag-based gene expression profiling may soon become the method of choice for global expression profiling in non-model species. PMID:19575793

DEVELOPMENT OF PROTEIN PROFILE TECHNOLOGY TO EVALUATE ECOLOGICAL EFFECTS OF ENVIRONMENTAL CHEMICALS USING A SMALL FISH MODEL

EPA Science Inventory

The rationale for this research is: i) Protein expression changes with life stage, disease, tissue type and environmental stressors; ii) Technology allows rapid analysis of large numbers of proteins to provide protein expression profiles; iii) Protein profiles are used as specifi...

Replacing dietary nonessential amino acids with ammonia nitrogen does not alter amino acid profile of deposited protein in the carcass of growing pigs fed a diet deficient in nonessential amino acid nitrogen.

PubMed

Mansilla, W D; Htoo, J K; de Lange, C F M

2017-10-01

Amino acid usage for protein retention, and, consequently, the AA profile of retained protein, is the main factor for determining AA requirements in growing animals. The objective of the present study was to determine the effect of supplementing ammonia N on whole-body N retention and the AA profile of retained protein in growing pigs fed a diet deficient in nonessential AA (NEAA) N. In total, 48 barrows with a mean initial BW of 13.6 kg (SD 0.7) were used. At the beginning of the study, 8 pigs were euthanized for determination of initial protein mass. The remaining animals were individually housed and fed 1 of 5 dietary treatments. A common basal diet (95% of experimental diets) was formulated to meet the requirements for all essential AA (EAA) but to be deficient in NEAA N (CP = 8.01%). The basal diet was supplemented (5%) with cornstarch (negative control) or 2 N sources (ammonia or NEAA) at 2 levels each to supply 1.35 or 2.70% extra CP. The final standardized ileal digestible (SID) NEAA content in the high-NEAA-supplemented diet (positive control) was based on the NEAA profile of whole-body protein of 20-kg pigs, and it was expected to reduce the endogenous synthesis of NEAA. Pigs were fed at 3.0 times maintenance energy requirements for ME in 3 equal meals daily. At the end of a 3-wk period, pigs were euthanized and the carcass and visceral organs were weighed, frozen, and ground for determination of protein mass. From pigs in the initial, negative control, high-ammonia, and high-NEAA groups, AA contents in the carcass and pooled visceral organs were analyzed to determine the total and deposited protein AA profile, dietary EAA efficiencies, and minimal de novo synthesis of NEAA. Carcass weight and whole-body N retention linearly increased ( < 0.05) with N supplementation. The AA profile of protein and deposited protein in the carcass was not different ( > 0.10) between N sources, but Cys content increased ( < 0.05) with NEAA compared with ammonia in visceral organ protein and deposited protein. The dietary SID EAA efficiency for increasing EAA deposition in whole-body protein increased ( < 0.05) with N supplementation, but it was not different ( > 0.10) between N sources. The de novo synthesis of NEAA increased ( < 0.05) for ammonia compared with NEAA supplementation. In conclusion, adding ammonia as a N source to diets deficient in NEAA N increases whole-body N retention without affecting the carcass AA profile.

Comparative Proteomic Analysis of Whole-Gut Lavage Fluid and Pancreatic Juice Reveals a Less Invasive Method of Sampling Pancreatic Secretions

PubMed Central

Rocker, Jana M; Tan, Marcus C; Thompson, Lee W; Contreras, Carlo M; DiPalma, Jack A; Pannell, Lewis K

2016-01-01

OBJECTIVES: There are currently no reliable, non-invasive screening tests for pancreatic ductal adenocarcinoma. The fluid secreted from the pancreatic ductal system (“pancreatic juice”) has been well-studied as a potential source of cancer biomarkers. However, it is invasive to collect. We recently observed that the proteomic profile of intestinal effluent from the bowel in response to administration of an oral bowel preparation solution (also known as whole-gut lavage fluid, WGLF) contains large amounts of pancreas-derived proteins. We therefore hypothesized that the proteomic profile is similar to that of pancreatic juice. In this study, we compared the proteomic profiles of 77 patients undergoing routine colonoscopy with the profiles of 19 samples of pure pancreatic juice collected during surgery. METHODS: WGLF was collected from patients undergoing routine colonoscopy, and pancreatic juice was collected from patients undergoing pancreatic surgery. Protein was isolated from both samples using an optimized method and analyzed by LC-MS/MS. Identified proteins were compared between samples and groups to determine similarity of the two fluids. We then compared our results with literature reports of pancreatic juice-based studies to determine similarity. RESULTS: We found 104 proteins in our pancreatic juice samples, of which 90% were also found in our WGLF samples. The majority (67%) of the total proteins found in the WGLF were common to pancreatic juice, with intestine-specific proteins making up a smaller proportion. CONCLUSIONS: WGLF and pancreatic juice appear to have similar proteomic profiles. This supports the notion that WGLF is a non-invasive, surrogate bio-fluid for pancreatic juice. Further studies are required to further elucidate its role in the diagnosis of pancreatic cancer. PMID:27228405

Comparative analysis of inflamed and non-inflamed colon biopsies reveals strong proteomic inflammation profile in patients with ulcerative colitis

PubMed Central

2012-01-01

Background Accurate diagnostic and monitoring tools for ulcerative colitis (UC) are missing. Our aim was to describe the proteomic profile of UC and search for markers associated with disease exacerbation. Therefore, we aimed to characterize specific proteins associated with inflamed colon mucosa from patients with acute UC using mass spectrometry-based proteomic analysis. Methods Biopsies were sampled from rectum, sigmoid colon and left colonic flexure from twenty patients with active proctosigmoiditis and from four healthy controls for proteomics and histology. Proteomic profiles of whole colonic biopsies were characterized using 2D-gel electrophoresis, and peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was applied for identification of differently expressed protein spots. Results A total of 597 spots were annotated by image analysis and 222 of these had a statistically different protein level between inflamed and non-inflamed tissue in the patient group. Principal component analysis clearly grouped non-inflamed samples separately from the inflamed samples indicating that the proteomic signature of colon mucosa with acute UC is strong. Totally, 43 individual protein spots were identified, including proteins involved in energy metabolism (triosephosphate isomerase, glycerol-3-phosphate-dehydrogenase, alpha enolase and L-lactate dehydrogenase B-chain) and in oxidative stress (superoxide dismutase, thioredoxins and selenium binding protein). Conclusions A distinct proteomic profile of inflamed tissue in UC patients was found. Specific proteins involved in energy metabolism and oxidative stress were identified as potential candidate markers for UC. PMID:22726388

The sweet tooth of biopharmaceuticals: importance of recombinant protein glycosylation analysis.

PubMed

Lingg, Nico; Zhang, Peiqing; Song, Zhiwei; Bardor, Muriel

2012-12-01

Biopharmaceuticals currently represent the fastest growing sector of the pharmaceutical industry, mainly driven by a rapid expansion in the manufacture of recombinant protein-based drugs. Glycosylation is the most prominent post-translational modification occurring on these protein drugs. It constitutes one of the critical quality attributes that requires thorough analysis for optimal efficacy and safety. This review examines the functional importance of glycosylation of recombinant protein drugs, illustrated using three examples of protein biopharmaceuticals: IgG antibodies, erythropoietin and glucocerebrosidase. Current analytical methods are reviewed as solutions for qualitative and quantitative measurements of glycosylation to monitor quality target product profiles of recombinant glycoprotein drugs. Finally, we propose a framework for designing the quality target product profile of recombinant glycoproteins and planning workflow for glycosylation analysis with the selection of available analytical methods and tools. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cloning and expression profiling of odorant-binding proteins in the tarnished plant bug, Lygus lineolaris

USDA-ARS?s Scientific Manuscript database

In insects, the perception and discrimination of odorants requires the involvement of odorant binding proteins (OBPs). To gain a better molecular understanding of olfaction in the agronomic pest, Lygus lineolaris (tarnished plant bug), we used a transcriptomics-based approach to identify potential ...

A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

PubMed Central

Ye, Min; Nagar, Swati; Korzekwa, Ken

2015-01-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

PubMed

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Hyperforin: To Be or Not to Be an Activator of TRPC(6).

PubMed

Friedland, Kristina; Harteneck, Christian

2015-01-01

Meantime, it is well accepted that hyperforin, the chemical instable phloroglucinol derivative of Hypericum perforatum, St. John's wort, is the pharmacophore of St. John's wort extracts. With the decline of this scientific discussion, another controversial aspect has been arisen, the question regarding the underlying mechanism leading to the pharmacological profile of the plant extract used in therapy of depression. We will summarize the different concepts described for hyperforin's antidepressive activity. Starting with unspecific protein-independent mechanisms due to changes in pH, we will summarize data of protein-based concepts beginning with concepts based on involvement of a variety of proteins and will finally present concepts based on the modulation of a single protein.

Comprehensive mutagenesis of HIV-1 protease: a computational geometry approach.

PubMed

Masso, Majid; Vaisman, Iosif I

2003-05-30

A computational geometry technique based on Delaunay tessellation of protein structure, represented by C(alpha) atoms, is used to study effects of single residue mutations on sequence-structure compatibility in HIV-1 protease. Profiles of residue scores derived from the four-body statistical potential are constructed for all 1881 mutants of the HIV-1 protease monomer and compared with the profile of the wild-type protein. The profiles for an isolated monomer of HIV-1 protease and the identical monomer in a dimeric state with an inhibitor are analyzed to elucidate changes to structural stability. Protease residues shown to undergo the greatest impact are those forming the dimer interface and flap region, as well as those known to be involved in inhibitor binding.

Films based on soy protein-agar blends for wound dressing: Effect of different biopolymer proportions on the drug release rate and the physical and antibacterial properties of the films.

PubMed

Rivadeneira, Josefina; Audisio, M C; Gorustovich, Alejandro

2018-04-01

No single material can provide all requirements for wound dressings. Here, we evaluated the influence of different soy protein isolate and agar proportions (3:1, 1:1, and 1:3) in blend films on some of their physical-chemical and antibacterial properties to elucidate their potential as wound dressings. The films were synthesized by the gel casting method and ciprofloxacin hydrochloride was incorporated into the films. Films were characterized based on their surface morphology, water uptake ability, and weight loss profile. Also, the ciprofloxacin hydrochloride release kinetics was quantified spectrophotometrically. The antibacterial effect was evaluated against Staphylococcus aureus and Pseudomonas aeruginosa strains. The soy protein isolate-agar ratio affected the water uptake of the films and the release profile of ciprofloxacin hydrochloride but not the weight loss profile. The amount of drug released decreased near 80% because of the decrease in agar content in the films. The release kinetics of ciprofloxacin hydrochloride data best fitted to the Korsmeyer-Peppas model, suggesting that the mechanism of drug release was mainly of the diffusion type. All ciprofloxacin hydrochloride-releasing soy protein isolate-agar films strongly inhibited the cell viability of the bacterial strains studied. We concluded that water uptake and ciprofloxacin hydrochloride release can be controlled by changing the soy protein isolate-agar proportion. The proportions did not lead to changes in the antibacterial strength of the films.

Profiling and quantitative evaluation of three Nickel-Coated magnetic matrices for purification of recombinant proteins: lelpful hints for the optimized nanomagnetisable matrix preparation

PubMed Central

2011-01-01

Background Several materials are available in the market that work on the principle of protein magnetic fishing by their histidine (His) tags. Little information is available on their performance and it is often quoted that greatly improved purification of histidine-tagged proteins from crude extracts could be achieved. While some commercial magnetic matrices could be used successfully for purification of several His-tagged proteins, there are some which have been proved to operate just for a few extent of His-tagged proteins. Here, we address quantitative evaluation of three commercially available Nickel nanomagnetic beads for purification of two His-tagged proteins expressed in Escherichia coli and present helpful hints for optimized purification of such proteins and preparation of nanomagnetisable matrices. Results Marked differences in the performance of nanomagnetic matrices, principally on the basis of their specific binding capacity, recovery profile, the amount of imidazole needed for protein elution and the extent of target protein loss and purity were obtained. Based on the aforesaid criteria, one of these materials featured the best purification results (SiMAG/N-NTA/Nickel) for both proteins at the concentration of 4 mg/ml, while the other two (SiMAC-Nickel and SiMAG/CS-NTA/Nickel) did not work well with respect to specific binding capacity and recovery profile. Conclusions Taken together, functionality of different types of nanomagnetic matrices vary considerably. This variability may not only be dependent upon the structure and surface chemistry of the matrix which in turn determine the affinity of interaction, but, is also influenced to a lesser extent by the physical properties of the protein itself. Although the results of the present study may not be fully applied for all nanomagnetic matrices, but provide a framework which could be used to profiling and quantitative evaluation of other magnetisable matrices and also provide helpful hints for those researchers facing same challenge. PMID:21824404

Predicting turns in proteins with a unified model.

PubMed

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications.

Predicting Turns in Proteins with a Unified Model

PubMed Central

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Motivation Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. Results In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications. PMID:23144872

Low-molecular weight protein profiling of genetically modified maize using fast liquid chromatography electrospray ionization and time-of-flight mass spectrometry.

PubMed

Koc, Anna; Cañuelo, Ana; Garcia-Reyes, Juan F; Molina-Diaz, Antonio; Trojanowicz, Marek

2012-06-01

In this work, the use of liquid chromatography coupled to electrospray time-of-flight mass spectrometry (LC-TOFMS) has been evaluated for the profiling of relatively low-molecular weight protein species in both genetically modified (GM) and non-GM maize. The proposed approach consisted of a straightforward sample fractionation with different water and ethanol-based buffer solutions followed by separation and detection of the protein species using liquid chromatography with a small particle size (1.8 μm) C(18) column and electrospray-time-of-flight mass spectrometry detection in the positive ionization mode. The fractionation of maize reference material containing different content of transgenic material (from 0 to 5% GM) led to five different fractions (albumins, globulins, zeins, zein-like glutelins, and glutelins), all of them containing different protein species (from 2 to 52 different species in each fraction). Some relevant differences in the quantity and types of protein species were observed in the different fractions of the reference material (with different GM contents) tested, thus revealing the potential use of the proposed approach for fast protein profiling and to detect tentative GMO markers in maize. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

HFIP Extraction Followed by 2D CTAB/SDS-PAGE Separation: A New Methodology for Protein Identification from Tissue Sections after MALDI Mass Spectrometry Profiling for Personalized Medicine Research

PubMed Central

Longuespée, Rémi; Tastet, Christophe; Desmons, Annie; Kerdraon, Olivier; Day, Robert

2014-01-01

Abstract Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) and profiling technology have become the easiest methods for quickly accessing the protein composition of a tissue area. Unfortunately, the demand for the identification of these proteins remains unmet. To overcome this bottleneck, we combined several strategies to identify the proteins detected via MALDI profiling including on-tissue protein extraction using hexafluoroIsopropanol (1,1,1,3,3,3-hexafluoro-2-propanol, HFIP) coupled with two-dimensional cetyl trimethylammonium bromide/sodium dodecyl sulfate–polyacrylamide gel electrophoresis (2D CTAB/SDS-PAGE) for separation followed by trypsin digestion and MALDI-MS analyses for identification. This strategy was compared with an on-tissue bottom-up strategy that we previously developed. The data reflect the complementarity of the approaches. An increase in the number of specific proteins identified has been established. This approach demonstrates the potential of adapted extraction procedures and the combination of parallel identification approaches for personalized medicine applications. The anatomical context provides important insight into identifying biomarkers and may be considered a first step for tissue-based biomarker research, as well as the extemporaneous examination of biopsies during surgery. PMID:24841221

Examining post-translational modification-mediated protein–protein interactions using a chemical proteomics approach

PubMed Central

Li, Xiang; Foley, Emily A; Kawashima, Shigehiro A; Molloy, Kelly R; Li, Yinyin; Chait, Brian T; Kapoor, Tarun M

2013-01-01

Post-translational modifications (PTM) of proteins can control complex and dynamic cellular processes via regulating interactions between key proteins. To understand these regulatory mechanisms, it is critical that we can profile the PTM-dependent protein–protein interactions. However, identifying these interactions can be very difficult using available approaches, as PTMs can be dynamic and often mediate relatively weak protein–protein interactions. We have recently developed CLASPI (cross-linking-assisted and stable isotope labeling in cell culture-based protein identification), a chemical proteomics approach to examine protein–protein interactions mediated by methylation in human cell lysates. Here, we report three extensions of the CLASPI approach. First, we show that CLASPI can be used to analyze methylation-dependent protein–protein interactions in lysates of fission yeast, a genetically tractable model organism. For these studies, we examined trimethylated histone H3 lysine-9 (H3K9Me3)-dependent protein–protein interactions. Second, we demonstrate that CLASPI can be used to examine phosphorylation-dependent protein–protein interactions. In particular, we profile proteins recognizing phosphorylated histone H3 threonine-3 (H3T3-Phos), a mitotic histone “mark” appearing exclusively during cell division. Our approach identified survivin, the only known H3T3-Phos-binding protein, as well as other proteins, such as MCAK and KIF2A, that are likely to be involved in weak but selective interactions with this histone phosphorylation “mark”. Finally, we demonstrate that the CLASPI approach can be used to study the interplay between histone H3T3-Phos and trimethylation on the adjacent residue lysine 4 (H3K4Me3). Together, our findings indicate the CLASPI approach can be broadly applied to profile protein–protein interactions mediated by PTMs. PMID:23281010

High-resolution mapping of transcription factor binding sites on native chromatin

PubMed Central

Kasinathan, Sivakanthan; Orsi, Guillermo A.; Zentner, Gabriel E.; Ahmad, Kami; Henikoff, Steven

2014-01-01

Sequence-specific DNA-binding proteins including transcription factors (TFs) are key determinants of gene regulation and chromatin architecture. Formaldehyde cross-linking and sonication followed by Chromatin ImmunoPrecipitation (X-ChIP) is widely used for profiling of TF binding, but is limited by low resolution and poor specificity and sensitivity. We present a simple protocol that starts with micrococcal nuclease-digested uncross-linked chromatin and is followed by affinity purification of TFs and paired-end sequencing. The resulting ORGANIC (Occupied Regions of Genomes from Affinity-purified Naturally Isolated Chromatin) profiles of Saccharomyces cerevisiae Abf1 and Reb1 provide highly accurate base-pair resolution maps that are not biased toward accessible chromatin, and do not require input normalization. We also demonstrate the high specificity of our method when applied to larger genomes by profiling Drosophila melanogaster GAGA Factor and Pipsqueak. Our results suggest that ORGANIC profiling is a widely applicable high-resolution method for sensitive and specific profiling of direct protein-DNA interactions. PMID:24336359

Proteomic Analyses of Corneal Tissue Subjected to Alkali Exposure

PubMed Central

Parikh, Toral; Eisner, Natalie; Venugopalan, Praseeda; Yang, Qin; Lam, Byron L.

2011-01-01

Purpose. To determine whether exposure to alkaline chemicals results in predictable changes in corneal protein profile. To determine whether protein profile changes are indicative of severity and duration of alkali exposure. Methods. Enucleated bovine and porcine (n = 59 each) eyes were used for exposure to sodium, ammonium, and calcium hydroxide, respectively. Eyes were subjected to fluorescein staining, 5-bromo-2′-deoxy-uridine (BrdU) labeling. Excised cornea was subjected to protein extraction, spectrophotometric determination of protein amount, dynamic light scattering and SDS-PAGE profiling, mass spectrometric protein identification, and iTRAQ-labeled quantification. Select identified proteins were subjected to Western blot and immunohistochemical analyses. Results. Alkali exposure resulted in lower protein extractability from corneal tissue. Elevated aggregate formation was found with strong alkali exposure (sodium hydroxide>ammonium, calcium hydroxide), even with a short duration of exposure compared with controls. The protein yield after exposure varied as a function of postexposure time. Protein profiles changed because of alkali exposure. Concentration and strength of the alkali affected the profile change significantly. Mass spectrometry identified 15 proteins from different bands with relative quantification. Plexin D1 was identified for the first time in the cornea at a protein level that was further confirmed by Western blot and immunohistochemical analyses. Conclusions. Exposure to alkaline chemicals results in predictable and reproducible changes in corneal protein profile. Stronger alkali, longer durations, or both, of exposure resulted in lower yields and significant protein profile changes compared with controls. PMID:20861482

Distinct Protein Expression Profiles of Solid-Pseudopapillary Neoplasms of the Pancreas.

PubMed

Park, Minhee; Lim, Jong-Sun; Lee, Hyoung-Joo; Na, Keun; Lee, Min Jung; Kang, Chang Moo; Paik, Young-Ki; Kim, Hoguen

2015-08-07

Solid-pseudopapillary neoplasm (SPN) is an uncommon pancreatic tumor with mutation in CTNNB1 and distinct clinical and pathological features. We compared the proteomic profiles of SPN to mRNA expression. Pooled SPNs and pooled non-neoplastic pancreatic tissues were examined with high-resolution mass spectrometry. We identified 329 (150 up-regulated and 179 down-regulated) differentially expressed proteins in SPN. We identified 191 proteins (58.1% of the 329 dysregulated proteins) with the same expression tendencies in SPN based on mRNA data. Many overexpressed proteins were related to signaling pathways known to be activated in SPNs. We found that several proteins involved in Wnt signaling, including DKK4 and β-catenin, and proteins that bind β-catenin, such as FUS and NONO, were up-regulated in SPNs. Molecules involved in glycolysis, including PKM2, ENO2, and HK1, were overexpressed in accordance to their mRNA levels. In summary, SPN showed (1) distinct protein expression changes that correlated with mRNA expression, (2) overexpression of Wnt signaling proteins and proteins that bind directly to β-catenin, and (3) overexpression of proteins involved in metabolism. These findings may help develop early diagnostic biomarkers and molecular targets.

SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

PubMed

Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

2015-01-01

Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

Genetically Targeted Ratiometric and Activated pH Indicator Complexes (TRApHIC) for Receptor Trafficking.

PubMed

Perkins, Lydia A; Yan, Qi; Schmidt, Brigitte F; Kolodieznyi, Dmytro; Saurabh, Saumya; Larsen, Mads Breum; Watkins, Simon C; Kremer, Laura; Bruchez, Marcel P

2018-02-06

Fluorescent protein-based pH sensors are useful tools for measuring protein trafficking through pH changes associated with endo- and exocytosis. However, commonly used pH-sensing probes are ubiquitously expressed with their protein of interest throughout the cell, hindering our ability to focus on specific trafficking pools of proteins. We developed a family of excitation ratiometric, activatable pH responsive tandem dyes, consisting of a pH sensitive Cy3 donor linked to a fluorogenic malachite green acceptor. These cell-excluded dyes are targeted and activated upon binding to a genetically expressed fluorogen-activating protein and are suitable for selective labeling of surface proteins for analysis of endocytosis and recycling in live cells using both confocal and superresolution microscopy. Quantitative profiling of the endocytosis and recycling of tagged β2-adrenergic receptor (B2AR) at a single-vesicle level revealed differences among B2AR agonists, consistent with more detailed pharmacological profiling.

Protein-enhanced soups: a consumer-accepted food for increasing dietary protein provision among older adults.

PubMed

Donahue, Elizabeth; Crowe, Kristi Michele; Lawrence, Jeannine

2015-02-01

Protein-enhanced soups (PES) may improve protein intake among older adults. This study examined sensory attributes (aroma, texture, taste, and overall acceptability) and preferences of PES (chicken noodle and cheddar broccoli) compared with flavor-matched control soups (FCS) among older adults (≥65 years) and evaluated dietary profile changes of a standard menu based on the substitution of one PES serving/d for a standard soup. Modified paired preference tests and 5-point facial hedonic scales were administered to participants (n = 44). No significant differences in sensory attributes between either PES compared with FCS were identified, but significant gender- and age-related differences (p < 0.05) were observed. About Sixty-one percent of participants preferred protein-enhanced chicken noodle soup while only 38% preferred protein-enhanced cheddar broccoli soup to their respective FCS. Substituting one PES serving for one non-fortified soup serving per day resulted in significantly higher (p < 0.001) protein profile. Results suggest that all attributes of PES were consistent with sensory expectations and PES substitution could improve protein provision.

DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.

PubMed

Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan

2018-04-01

Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

Complexity in pH-Dependent Ribozyme Kinetics: Dark pKa Shifts and Wavy Rate-pH Profiles.

PubMed

Frankel, Erica A; Bevilacqua, Philip C

2018-02-06

Charged bases occur in RNA enzymes, or ribozymes, where they play key roles in catalysis. Cationic bases donate protons and perform electrostatic catalysis, while anionic bases accept protons. We previously published simulations of rate-pH profiles for ribozymes in terms of species plots for the general acid and general base that have been useful for understanding how ribozymes respond to pH. In that study, we did not consider interaction between the general acid and general base or interaction with other species on the RNA. Since that report, diverse small ribozyme classes have been discovered, many of which have charged nucleobases or metal ions in the active site that can either directly interact and participate in catalysis or indirectly interact as "influencers". Herein, we simulate experimental rate-pH profiles in terms of species plots in which reverse protonated charged nucleobases interact. These analyses uncover two surprising features of pH-dependent enzyme kinetics. (1) Cooperativity between the general acid and general base enhances population of the functional forms of a ribozyme and manifests itself as hidden or "dark" pK a shifts, real pK a shifts that accelerate the reaction but are not readily observed by standard experimental approaches, and (2) influencers favorably shift the pK a s of proton-transferring nucleobases and manifest themselves as "wavy" rate-pH profiles. We identify parallels with the protein enzyme literature, including reverse protonation and wavelike behavior, while pointing out that RNA is more prone to reverse protonation. The complexities uncovered, which arise from simple pairwise interactions, should aid deconvolution of complex rate-pH profiles for RNA and protein enzymes and suggest veiled catalytic devices for promoting catalysis that can be tested by experiment and calculation.

Differential proteomics study of platelets in asymptomatic constitutional macrothrombocytopenia: altered levels of cytoskeletal proteins.

PubMed

Karmakar, Shilpita; Saha, Sutapa; Banerjee, Debasis; Chakrabarti, Abhijit

2015-01-01

Harris platelet syndrome (HPS), also known as asymptomatic constitutional macrothrombocytopenia (ACMT), is an autosomal dominant platelet disorder characterized by mild-to-severe thrombocytopenia and giant platelets with normal platelet aggregation and absence of bleeding symptoms. We have attempted a comparative proteomics study for profiling of platelet proteins in healthy vs. pathological states to discover characteristic protein expression changes in macrothrombocytes and decipher the factors responsible for the functionally active yet morphologically distinct platelets. We have used 2-D gel-based protein separation techniques coupled with MALDI-ToF/ToF-based mass spectrometric identification and characterization of the proteins to investigate the differential proteome profiling of platelet proteins isolated from the peripheral blood samples of patients and normal volunteers. Our study revealed altered levels of actin-binding proteins such as myosin light chain, coactosin-like protein, actin-related protein 2/3 complex, and transgelin2 that hint toward the cytoskeletal changes necessary to maintain the structural and functional integrity of macrothrombocytes. We have also observed over expressed levels of peroxiredoxin2 that signifies the prevailing oxidative stress in these cells. Additionally, altered levels of protein disulfide isomerase and transthyretin provide insights into the measures adapted by the macrothrombocytes to maintain their normal functional activity. This first proteomics study of platelets from ACMT may provide an understanding of the structural stability and normal functioning of these platelets in spite of their large size. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

An ensemble approach to protein fold classification by integration of template-based assignment and support vector machine classifier.

PubMed

Xia, Jiaqi; Peng, Zhenling; Qi, Dawei; Mu, Hongbo; Yang, Jianyi

2017-03-15

Protein fold classification is a critical step in protein structure prediction. There are two possible ways to classify protein folds. One is through template-based fold assignment and the other is ab-initio prediction using machine learning algorithms. Combination of both solutions to improve the prediction accuracy was never explored before. We developed two algorithms, HH-fold and SVM-fold for protein fold classification. HH-fold is a template-based fold assignment algorithm using the HHsearch program. SVM-fold is a support vector machine-based ab-initio classification algorithm, in which a comprehensive set of features are extracted from three complementary sequence profiles. These two algorithms are then combined, resulting to the ensemble approach TA-fold. We performed a comprehensive assessment for the proposed methods by comparing with ab-initio methods and template-based threading methods on six benchmark datasets. An accuracy of 0.799 was achieved by TA-fold on the DD dataset that consists of proteins from 27 folds. This represents improvement of 5.4-11.7% over ab-initio methods. After updating this dataset to include more proteins in the same folds, the accuracy increased to 0.971. In addition, TA-fold achieved >0.9 accuracy on a large dataset consisting of 6451 proteins from 184 folds. Experiments on the LE dataset show that TA-fold consistently outperforms other threading methods at the family, superfamily and fold levels. The success of TA-fold is attributed to the combination of template-based fold assignment and ab-initio classification using features from complementary sequence profiles that contain rich evolution information. http://yanglab.nankai.edu.cn/TA-fold/. yangjy@nankai.edu.cn or mhb-506@163.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

(PS)2: protein structure prediction server version 3.0.

PubMed

Huang, Tsun-Tsao; Hwang, Jenn-Kang; Chen, Chu-Huang; Chu, Chih-Sheng; Lee, Chi-Wen; Chen, Chih-Chieh

2015-07-01

Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC-ESI-MS-MS.

PubMed

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R; Changelian, Armen; Laws, Edward R; Santagata, Sandro; Agar, Nathalie Y R; Van Berkel, Gary J

2015-08-01

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections, using a fully automated droplet-based liquid-microjunction surface-sampling-HPLC-ESI-MS-MS system for spatially resolved sampling, HPLC separation, and mass spectrometric detection. Excellent correlation was found between the protein distribution data obtained with this method and data obtained with matrix-assisted laser desorption/ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland. AVP was most abundant in the posterior pituitary gland region (neurohypophysis), and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH-secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH-secreting adenomas and in normal anterior adenohypophysis compared with non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis, as expected. This work reveals that a fully automated droplet-based liquid-microjunction surface-sampling system coupled to HPLC-ESI-MS-MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, including AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity, and specificity of this method support the potential of this basic technology, with further advancement, for assisting surgical decision-making. Graphical Abstract Mass spectrometry based profiling of hormones in human pituitary gland and tumor thin tissue sections.

Age and gender related changes of salivary total protein levels for forensic application.

PubMed

Bhuptani, D; Kumar, S; Vats, M; Sagav, R

2018-05-30

Saliva is one of the most commonly encountered biological fluids found at the crime scene. Forensic science including forensic odontology is focused on the positive identification of individuals. The salivary protein profiling can help in personalization by the changes associated with age throughout life and gender. These changes also seem to vary with the dietary habits, environmental factors and geographical areas. Thus, the aim of present study is to estimate these changes in salivary total protein concentration and profiling in individuals of Gujarat, India. The association of total protein concentration and protein content with the age, gender, tooth eruption, functions of the protein and its physiological significance are also intended for study in this population. One hundred unstimulated whole saliva samples from study subjects of Gujarat population were collected and grouped based on age and gender. Total protein concentration was determined by Bradford assay; also protein was separated and analyzed using Sodium dodecylsulphate polyacrylamide gel electrophoresis (SDS PAGE). T Test and ANOVA were used for statistical analysis. The concentration of Total Protein was found to be between 2-4 mg/ml. It showed a positive correlation with age and gender. It can be concluded more protein bands were prominently present in the adolescents group followed by children and lastly in the adults groups.More high (more than 80 kDa) and low (less than 30 kDa) molecular weight proteins are seen in children and adolescents than adults. SDS PAGE allowed identification and comparison of group variabilities in protein profiles. The total salivary protein showed an association between the parameters under this study which will aid in the individual identification in the field of forensics.

Proteomics profiling of interactome dynamics by colocalisation analysis (COLA).

PubMed

Mardakheh, Faraz K; Sailem, Heba Z; Kümper, Sandra; Tape, Christopher J; McCully, Ryan R; Paul, Angela; Anjomani-Virmouni, Sara; Jørgensen, Claus; Poulogiannis, George; Marshall, Christopher J; Bakal, Chris

2016-12-20

Localisation and protein function are intimately linked in eukaryotes, as proteins are localised to specific compartments where they come into proximity of other functionally relevant proteins. Significant co-localisation of two proteins can therefore be indicative of their functional association. We here present COLA, a proteomics based strategy coupled with a bioinformatics framework to detect protein-protein co-localisations on a global scale. COLA reveals functional interactions by matching proteins with significant similarity in their subcellular localisation signatures. The rapid nature of COLA allows mapping of interactome dynamics across different conditions or treatments with high precision.

Automated prediction of protein function and detection of functional sites from structure.

PubMed

Pazos, Florencio; Sternberg, Michael J E

2004-10-12

Current structural genomics projects are yielding structures for proteins whose functions are unknown. Accordingly, there is a pressing requirement for computational methods for function prediction. Here we present PHUNCTIONER, an automatic method for structure-based function prediction using automatically extracted functional sites (residues associated to functions). The method relates proteins with the same function through structural alignments and extracts 3D profiles of conserved residues. Functional features to train the method are extracted from the Gene Ontology (GO) database. The method extracts these features from the entire GO hierarchy and hence is applicable across the whole range of function specificity. 3D profiles associated with 121 GO annotations were extracted. We tested the power of the method both for the prediction of function and for the extraction of functional sites. The success of function prediction by our method was compared with the standard homology-based method. In the zone of low sequence similarity (approximately 15%), our method assigns the correct GO annotation in 90% of the protein structures considered, approximately 20% higher than inheritance of function from the closest homologue.

Semiconductor quantum dots as Förster resonance energy transfer donors for intracellularly-based biosensors

NASA Astrophysics Data System (ADS)

Field, Lauren D.; Walper, Scott A.; Susumu, Kimihiro; Oh, Eunkeu; Medintz, Igor L.; Delehanty, James B.

2017-02-01

Förster resonance energy transfer (FRET)-based assemblies currently comprise a significant portion of intracellularly based sensors. Although extremely useful, the fluorescent protein pairs typically utilized in such sensors are still plagued by many photophysical issues including significant direct acceptor excitation, small changes in FRET efficiency, and limited photostability. Luminescent semiconductor nanocrystals or quantum dots (QDs) are characterized by many unique optical properties including size-tunable photoluminescence, broad excitation profiles coupled to narrow emission profiles, and resistance to photobleaching, which can cumulatively overcome many of the issues associated with use of fluorescent protein FRET donors. Utilizing QDs for intracellular FRET-based sensing still requires significant development in many areas including materials optimization, bioconjugation, cellular delivery and assay design and implementation. We are currently developing several QD-based FRET sensors for various intracellular applications. These include sensors targeting intracellular proteolytic activity along with those based on theranostic nanodevices for monitoring drug release. The protease sensor is based on a unique design where an intracellularly expressed fluorescent acceptor protein substrate assembles onto a QD donor following microinjection, forming an active complex that can be monitored in live cells over time. In the theranostic configuration, the QD is conjugated to a carrier protein-drug analogue complex to visualize real-time intracellular release of the drug from its carrier in response to an external stimulus. The focus of this talk will be on the design, properties, photophysical characterization and cellular application of these sensor constructs.

Disparate Proteome Responses of Pathogenic and Non-pathogenic Aspergilli to Human Serum Measured by Activity-Based Protein Profiling (ABPP)

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

Wiedner, Susan D.; Ansong, Charles; Webb-Robertson, Bobbie-Jo M.

2013-07-01

Aspergillus fumigatus is the primary pathogen causing the devastating pulmonary disease Invasive Aspergillosis in immunocompromised individuals. Genomic analysis shows high synteny between A. fumigatus and closely related rarely pathogenic Neosartorya fischeri and Aspergillus clavatus genomes. To investigate the presence of unique or highly inducible protein reactivity in the pathogen, we applied activity-based protein profiling to compare protein reactivity of all three fungi over time in minimal media growth and in response to human serum. We found 350 probe-reactive proteins exclusive to A. fumigatus, including known virulence associated proteins, and 13 proteins associated with stress response exclusive to A. fumigatus culturemore » in serum. Though the fungi are highly orthologous, A. fumigatus has significantly more activity across varied biological process. Only 50% of expected orthologs of measured A. fumigatus reactive proteins were observed in N. fischeri and A. clavatus. Human serum induced processes uniquely or significantly represented in A. fumigatus include actin organization and assembly, transport, and fatty acid, cell membrane, and cell wall synthesis. Additionally, signaling proteins regulating vegetative growth, conidiation, and cell wall integrity, required for appropriate cellular response to external stimuli, had higher reactivity over time in A. fumigatus and N. fisheri, but not in A. clavatus. Together, we show that measured proteins and physiological processes identified solely or significantly over-represented in A. fumigatus reveal a unique adaptive response to human protein not found in closely related, but rarely aspergilli. These unique protein reactivity responses may reveal how A. fumigatus initiates pulmonary invasion leading to Invasive Aspergillosis.« less

Persistent human Borna disease virus infection modifies the acetylome of human oligodendroglia cells towards higher energy and transporter levels

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

Liu, Xia; Liu, Siwen; Chongqing Key Laboratory of Neurobiology, Chongqing Medical University, Chongqing 400016

2015-11-15

Background: Borna disease virus (BDV) is a neurotropic RNA virus persistently infecting mammalian hosts including humans. Lysine acetylation (Kac) is a key protein post-translational modification (PTM). The unexpectedly broad regulatory scope of Kac let us to profile the entire acetylome upon BDV infection. Methods: The acetylome was profiled through stable isotope labeling for cell culture (SILAC)-based quantitative proteomics. The quantifiable proteome was annotated using bioinformatics. Results: We identified and quantified 791 Kac sites in 473 Kac proteins in human BDV Hu-H1-infected and non-infected oligodendroglial (OL) cells. Bioinformatic analysis revealed that BDV infection alters the acetylation of metabolic proteins, membrane-associated proteinsmore » and transmembrane transporter activity, and affects the acetylation of several lysine acetyltransferases (KAT). Conclusions: Upon BDV persistence the OL acetylome is manipulated towards higher energy and transporter levels necessary for shuttling BDV proteins to and from nuclear replication sites. - Highlights: • We used SILAC-based proteomics to analyze the acetylome of BDV infected OL cells. • We quantified 791Kac sites in 473 proteins. • Bioinformatic analysis revealed altered acetylation of metabolic proteins et al. • BDV manipulates the OL acetylome towards higher energy and transporter levels. • BDV infection is associated with enriched phosphate-associated metabolic processes.« less

Sequential Extraction Results in Improved Proteome Profiling of Medicinal Plant Pinellia ternata Tubers, Which Contain Large Amounts of High-Abundance Proteins

PubMed Central

An, SuFang; Gong, FangPing; Wang, Wei

2012-01-01

Pinellia ternata tuber is one of the well-known Chinese traditional medicines. In order to understand the pharmacological properties of tuber proteins, it is necessary to perform proteome analysis of P. ternata tubers. However, a few high-abundance proteins (HAPs), mainly mannose-binding lectin (agglutinin), exist in aggregates of various sizes in the tubers and seriously interfere with proteome profiling by two-dimensional electrophoresis (2-DE). Therefore, selective depletion of these HAPs is a prerequisite for enhanced proteome analysis of P. ternata tubers. Based on differential protein solubility, we developed a novel protocol involving two sequential extractions for depletion of some HAPs and prefractionation of tuber proteins prior to 2-DE. The first extraction using 10% acetic acid selectively extracted acid-soluble HAPs and the second extraction using the SDS-containing buffer extracted remaining acid-insoluble proteins. After application of the protocol, 2-DE profiles of P. ternata tuber proteins were greatly improved and more protein spots were detected, especially low-abundance proteins. Moreover, the subunit composition of P. ternata lectin was analyzed by electrophoresis. Native lectin consists of two hydrogen-bonded subunits (11 kDa and 25 kDa) and the 11 kDa subunit was a glycoprotein. Subsequently, major HAPs in the tubers were analyzed by mass spectrometry, with nine protein spots being identified as lectin isoforms. The methodology was easy to perform and required no specialized apparatus. It would be useful for proteome analysis of other tuber plants of Araceae. PMID:23185632

Sequential extraction results in improved proteome profiling of medicinal plant Pinellia ternata tubers, which contain large amounts of high-abundance proteins.

PubMed

Wu, Xiaolin; Xiong, Erhui; An, Sufang; Gong, Fangping; Wang, Wei

2012-01-01

Pinellia ternata tuber is one of the well-known Chinese traditional medicines. In order to understand the pharmacological properties of tuber proteins, it is necessary to perform proteome analysis of P. ternata tubers. However, a few high-abundance proteins (HAPs), mainly mannose-binding lectin (agglutinin), exist in aggregates of various sizes in the tubers and seriously interfere with proteome profiling by two-dimensional electrophoresis (2-DE). Therefore, selective depletion of these HAPs is a prerequisite for enhanced proteome analysis of P. ternata tubers. Based on differential protein solubility, we developed a novel protocol involving two sequential extractions for depletion of some HAPs and prefractionation of tuber proteins prior to 2-DE. The first extraction using 10% acetic acid selectively extracted acid-soluble HAPs and the second extraction using the SDS-containing buffer extracted remaining acid-insoluble proteins. After application of the protocol, 2-DE profiles of P. ternata tuber proteins were greatly improved and more protein spots were detected, especially low-abundance proteins. Moreover, the subunit composition of P. ternata lectin was analyzed by electrophoresis. Native lectin consists of two hydrogen-bonded subunits (11 kDa and 25 kDa) and the 11 kDa subunit was a glycoprotein. Subsequently, major HAPs in the tubers were analyzed by mass spectrometry, with nine protein spots being identified as lectin isoforms. The methodology was easy to perform and required no specialized apparatus. It would be useful for proteome analysis of other tuber plants of Araceae.

Standardized Profiling of The Membrane-Enriched Proteome of Mouse Dorsal Root Ganglia (DRG) Provides Novel Insights Into Chronic Pain.

PubMed

Rouwette, Tom; Sondermann, Julia; Avenali, Luca; Gomez-Varela, David; Schmidt, Manuela

2016-06-01

Chronic pain is a complex disease with limited treatment options. Several profiling efforts have been employed with the aim to dissect its molecular underpinnings. However, generated results are often inconsistent and nonoverlapping, which is largely because of inherent technical constraints. Emerging data-independent acquisition (DIA)-mass spectrometry (MS) has the potential to provide unbiased, reproducible and quantitative proteome maps - a prerequisite for standardization among experiments. Here, we designed a DIA-based proteomics workflow to profile changes in the abundance of dorsal root ganglia (DRG) proteins in two mouse models of chronic pain, inflammatory and neuropathic. We generated a DRG-specific spectral library containing 3067 DRG proteins, which enables their standardized quantification by means of DIA-MS in any laboratory. Using this resource, we profiled 2526 DRG proteins in each biological replicate of both chronic pain models and respective controls with unprecedented reproducibility. We detected numerous differentially regulated proteins, the majority of which exhibited pain model-specificity. Our approach recapitulates known biology and discovers dozens of proteins that have not been characterized in the somatosensory system before. Functional validation experiments and analysis of mouse pain behaviors demonstrate that indeed meaningful protein alterations were discovered. These results illustrate how the application of DIA-MS can open new avenues to achieve the long-awaited standardization in the molecular dissection of pathologies of the somatosensory system. Therefore, our findings provide a valuable framework to qualitatively extend our understanding of chronic pain and somatosensation. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Stratification of co-evolving genomic groups using ranked phylogenetic profiles

PubMed Central

Freilich, Shiri; Goldovsky, Leon; Gottlieb, Assaf; Blanc, Eric; Tsoka, Sophia; Ouzounis, Christos A

2009-01-01

Background Previous methods of detecting the taxonomic origins of arbitrary sequence collections, with a significant impact to genome analysis and in particular metagenomics, have primarily focused on compositional features of genomes. The evolutionary patterns of phylogenetic distribution of genes or proteins, represented by phylogenetic profiles, provide an alternative approach for the detection of taxonomic origins, but typically suffer from low accuracy. Herein, we present rank-BLAST, a novel approach for the assignment of protein sequences into genomic groups of the same taxonomic origin, based on the ranking order of phylogenetic profiles of target genes or proteins across the reference database. Results The rank-BLAST approach is validated by computing the phylogenetic profiles of all sequences for five distinct microbial species of varying degrees of phylogenetic proximity, against a reference database of 243 fully sequenced genomes. The approach - a combination of sequence searches, statistical estimation and clustering - analyses the degree of sequence divergence between sets of protein sequences and allows the classification of protein sequences according to the species of origin with high accuracy, allowing taxonomic classification of 64% of the proteins studied. In most cases, a main cluster is detected, representing the corresponding species. Secondary, functionally distinct and species-specific clusters exhibit different patterns of phylogenetic distribution, thus flagging gene groups of interest. Detailed analyses of such cases are provided as examples. Conclusion Our results indicate that the rank-BLAST approach can capture the taxonomic origins of sequence collections in an accurate and efficient manner. The approach can be useful both for the analysis of genome evolution and the detection of species groups in metagenomics samples. PMID:19860884

Heat-induced Protein Structure and Subfractions in Relation to Protein Degradation Kinetics and Intestinal Availability in Dairy Cattle

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

Doiron, K.; Yu, P; McKinnon, J

2009-01-01

The objectives of this study were to reveal protein structures of feed tissues affected by heat processing at a cellular level, using the synchrotron-based Fourier transform infrared microspectroscopy as a novel approach, and quantify protein structure in relation to protein digestive kinetics and nutritive value in the rumen and intestine in dairy cattle. The parameters assessed included (1) protein structure a-helix to e-sheet ratio; (2) protein subfractions profiles; (3) protein degradation kinetics and effective degradability; (4) predicted nutrient supply using the intestinally absorbed protein supply (DVE)/degraded protein balance (OEB) system for dairy cattle. In this study, Vimy flaxseed protein wasmore » used as a model feed protein and was autoclave-heated at 120C for 20, 40, and 60 min in treatments T1, T2, and T3, respectively. The results showed that using the synchrotron-based Fourier transform infrared microspectroscopy revealed and identified the heat-induced protein structure changes. Heating at 120C for 40 and 60 min increased the protein structure a-helix to e-sheet ratio. There were linear effects of heating time on the ratio. The heating also changed chemical profiles, which showed soluble CP decreased upon heating with concomitant increases in nonprotein nitrogen, neutral, and acid detergent insoluble nitrogen. The protein subfractions with the greatest changes were PB1, which showed a dramatic reduction, and PB2, which showed a dramatic increase, demonstrating a decrease in overall protein degradability. In situ results showed a reduction in rumen-degradable protein and in rumen-degradable dry matter without differences between the treatments. Intestinal digestibility, determined using a 3-step in vitro procedure, showed no changes to rumen undegradable protein. Modeling results showed that heating increased total intestinally absorbable protein (feed DVE value) and decreased degraded protein balance (feed OEB value), but there were no differences between the treatments. There was a linear effect of heating time on the DVE and a cubic effect on the OEB value. Our results showed that heating changed chemical profiles, protein structure a-helix to e-sheet ratio, and protein subfractions; decreased rumen-degradable protein and rumen-degradable dry matter; and increased potential nutrient supply to dairy cattle. The protein structure a-helix to e-sheet ratio had a significant positive correlation with total intestinally absorbed protein supply and negative correlation with degraded protein balance.« less

Profiling the humoral immune response of acute and chronic Q fever by protein microarray.

PubMed

Vigil, Adam; Chen, Chen; Jain, Aarti; Nakajima-Sasaki, Rie; Jasinskas, Algimantas; Pablo, Jozelyn; Hendrix, Laura R; Samuel, James E; Felgner, Philip L

2011-10-01

Antigen profiling using comprehensive protein microarrays is a powerful tool for characterizing the humoral immune response to infectious pathogens. Coxiella burnetii is a CDC category B bioterrorist infectious agent with worldwide distribution. In order to assess the antibody repertoire of acute and chronic Q fever patients we have constructed a protein microarray containing 93% of the proteome of Coxiella burnetii, the causative agent of Q fever. Here we report the profile of the IgG and IgM seroreactivity in 25 acute Q fever patients in longitudinal samples. We found that both early and late time points of infection have a very consistent repertoire of IgM and IgG response, with a limited number of proteins undergoing increasing or decreasing seroreactivity. We also probed a large collection of acute and chronic Q fever patient samples and identified serological markers that can differentiate between the two disease states. In this comparative analysis we confirmed the identity of numerous IgG biomarkers of acute infection, identified novel IgG biomarkers for acute and chronic infections, and profiled for the first time the IgM antibody repertoire for both acute and chronic Q fever. Using these results we were able to devise a test that can distinguish acute from chronic Q fever. These results also provide a unique perspective on isotype switch and demonstrate the utility of protein microarrays for simultaneously examining the dynamic humoral immune response against thousands of proteins from a large number of patients. The results presented here identify novel seroreactive antigens for the development of recombinant protein-based diagnostics and subunit vaccines, and provide insight into the development of the antibody response.

Profiling the Native Specific Human Humoral Immune Response to Sudan Ebola Virus Strain Gulu by Chemiluminescence Enzyme-Linked Immunosorbent Assay

PubMed Central

Sobarzo, Ariel; Perelman, Eddie; Groseth, Allison; Dolnik, Olga; Becker, Stephan; Lutwama, Julius Julian; Dye, John M.; Yavelsky, Victoria; Marks, Robert S.

2012-01-01

Ebolavirus, a member of the family Filoviridae, causes high lethality in humans and nonhuman primates. Research focused on protection and therapy for Ebola virus infection has investigated the potential role of antibodies. Recent evidence suggests that antibodies can be effective in protection from lethal challenge with Ebola virus in nonhuman primates. However, despite these encouraging results, studies have not yet determined the optimal antibodies and composition of an antibody cocktail, if required, which might serve as a highly effective and efficient prophylactic. To better understand optimal antibodies and their targets, which might be important for protection from Ebola virus infection, we sought to determine the profile of viral protein-specific antibodies generated during a natural cycle of infection in humans. To this end, we characterized the profile of antibodies against individual viral proteins of Sudan Ebola virus (Gulu) in human survivors and nonsurvivors of the outbreak in Gulu, Uganda, in 2000-2001. We developed a unique chemiluminescence enzyme-linked immunosorbent assay (ELISA) for this purpose based on the full-length recombinant viral proteins NP, VP30, and VP40 and two recombinant forms of the viral glycoprotein (GP1-294 and GP1-649) of Sudan Ebola virus (Gulu). Screening results revealed that the greatest immunoreactivity was directed to the viral proteins NP and GP1-649, followed by VP40. Comparison of positive immunoreactivity between the viral proteins NP, GP1-649, and VP40 demonstrated a high correlation of immunoreactivity between these viral proteins, which is also linked with survival. Overall, our studies of the profile of immunorecognition of antibodies against four viral proteins of Sudan Ebola virus in human survivors may facilitate development of effective monoclonal antibody cocktails in the future. PMID:22993411

Genotoxicity Assessment of Drinking Water Disinfection Byproducts by DNA Damage and Repair Pathway Profiling Analysis.

PubMed

Lan, Jiaqi; Rahman, Sheikh Mokhlesur; Gou, Na; Jiang, Tao; Plewa, Micheal J; Alshawabkeh, Akram; Gu, April Z

2018-06-05

Genotoxicity is considered a major concern for drinking water disinfection byproducts (DBPs). Of over 700 DBPs identified to date, only a small number has been assessed with limited information for DBP genotoxicity mechanism(s). In this study, we evaluated genotoxicity of 20 regulated and unregulated DBPs applying a quantitative toxicogenomics approach. We used GFP-fused yeast strains that examine protein expression profiling of 38 proteins indicative of all known DNA damage and repair pathways. The toxicogenomics assay detected genotoxicity potential of these DBPs that is consistent with conventional genotoxicity assays end points. Furthermore, the high-resolution, real-time pathway activation and protein expression profiling, in combination with clustering analysis, revealed molecular level details in the genotoxicity mechanisms among different DBPs and enabled classification of DBPs based on their distinct DNA damage effects and repair mechanisms. Oxidative DNA damage and base alkylation were confirmed to be the main molecular mechanisms of DBP genotoxicity. Initial exploration of QSAR modeling using moleular genotoxicity end points (PELI) suggested that genotoxicity of DBPs in this study was correlated with topological and quantum chemical descriptors. This study presents a toxicogenomics-based assay for fast and efficient mechanistic genotoxicity screening and assessment of a large number of DBPs. The results help to fill in the knowledge gap in the understanding of the molecular mechanisms of DBP genotoxicity.

Exploiting genomic data to identify proteins involved in abalone reproduction.

PubMed

Mendoza-Porras, Omar; Botwright, Natasha A; McWilliam, Sean M; Cook, Mathew T; Harris, James O; Wijffels, Gene; Colgrave, Michelle L

2014-08-28

Aside from their critical role in reproduction, abalone gonads serve as an indicator of sexual maturity and energy balance, two key considerations for effective abalone culture. Temperate abalone farmers face issues with tank restocking with highly marketable abalone owing to inefficient spawning induction methods. The identification of key proteins in sexually mature abalone will serve as the foundation for a greater understanding of reproductive biology. Addressing this knowledge gap is the first step towards improving abalone aquaculture methods. Proteomic profiling of female and male gonads of greenlip abalone, Haliotis laevigata, was undertaken using liquid chromatography-mass spectrometry. Owing to the incomplete nature of abalone protein databases, in addition to searching against two publicly available databases, a custom database comprising genomic data was used. Overall, 162 and 110 proteins were identified in females and males respectively with 40 proteins common to both sexes. For proteins involved in sexual maturation, sperm and egg structure, motility, acrosomal reaction and fertilization, 23 were identified only in females, 18 only in males and 6 were common. Gene ontology analysis revealed clear differences between the female and male protein profiles reflecting a higher rate of protein synthesis in the ovary and higher metabolic activity in the testis. A comprehensive mass spectrometry-based analysis was performed to profile the abalone gonad proteome providing the foundation for future studies of reproduction in abalone. Key proteins involved in both reproduction and energy balance were identified. Genomic resources were utilised to build a database of molluscan proteins yielding >60% more protein identifications than in a standard workflow employing public protein databases. Copyright © 2014 Elsevier B.V. All rights reserved.

Pathophysiology and immunological profile of myasthenia gravis and its subgroups.

PubMed

Romi, Fredrik; Hong, Yu; Gilhus, Nils Erik

2017-12-01

Myasthenia gravis (MG) is an autoimmune antibody-mediated disease characterized by muscle weakness and fatigability. It is believed that the initial steps triggering humoral immunity in MG take place inside thymic tissue and thymoma. The immune response against one or several epitopes expressed on thymic tissue cells spills over to neuromuscular junction components sharing the same epitope causing humoral autoimmunity and antibody production. The main cause of MG is acetylcholine receptor antibodies. However, many other neuromuscular junction membrane protein targets, intracellular and extracellular proteins are suggested to participate in MG pathophysiology. MG should be divided into subgroups based on clinical presentation and immunology. This includes onset age, clinical characteristics, thymic pathology and antibody profile. The immunological profile of these subgroups is determined by the antibodies present. Copyright © 2017. Published by Elsevier Ltd.

The Human Pancreas Proteome Defined by Transcriptomics and Antibody-Based Profiling

PubMed Central

Fagerberg, Linn; Hallström, Björn M.; Schwenk, Jochen M.; Uhlén, Mathias; Korsgren, Olle; Lindskog, Cecilia

2014-01-01

The pancreas is composed of both exocrine glands and intermingled endocrine cells to execute its diverse functions, including enzyme production for digestion of nutrients and hormone secretion for regulation of blood glucose levels. To define the molecular constituents with elevated expression in the human pancreas, we employed a genome-wide RNA sequencing analysis of the human transcriptome to identify genes with elevated expression in the human pancreas. This quantitative transcriptomics data was combined with immunohistochemistry-based protein profiling to allow mapping of the corresponding proteins to different compartments and specific cell types within the pancreas down to the single cell level. Analysis of whole pancreas identified 146 genes with elevated expression levels, of which 47 revealed a particular higher expression as compared to the other analyzed tissue types, thus termed pancreas enriched. Extended analysis of in vitro isolated endocrine islets identified an additional set of 42 genes with elevated expression in these specialized cells. Although only 0.7% of all genes showed an elevated expression level in the pancreas, this fraction of transcripts, in most cases encoding secreted proteins, constituted 68% of the total mRNA in pancreas. This demonstrates the extreme specialization of the pancreas for production of secreted proteins. Among the elevated expression profiles, several previously not described proteins were identified, both in endocrine cells (CFC1, FAM159B, RBPJL and RGS9) and exocrine glandular cells (AQP12A, DPEP1, GATM and ERP27). In summary, we provide a global analysis of the pancreas transcriptome and proteome with a comprehensive list of genes and proteins with elevated expression in pancreas. This list represents an important starting point for further studies of the molecular repertoire of pancreatic cells and their relation to disease states or treatment effects. PMID:25546435

A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

PubMed

Ye, Min; Nagar, Swati; Korzekwa, Ken

2016-04-01

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Protein profiling of single epidermal cell types from Arabidopsis thaliana using surface-enhanced laser desorption and ionization technology.

PubMed

Ebert, Berit; Melle, Christian; Lieckfeldt, Elke; Zöller, Daniela; von Eggeling, Ferdinand; Fisahn, Joachim

2008-08-25

Here, we describe a novel approach for investigating differential protein expression within three epidermal cell types. In particular, 3000 single pavement, basal, and trichome cells from leaves of Arabidopsis thaliana were harvested by glass micro-capillaries. Subsequently, these single cell samples were joined to form pools of 100 individual cells and analyzed using the ProteinChip technology; SELDI: surface-enhanced laser desorption and ionization. As a result, numerous protein signals that were differentially expressed in the three epidermal cell types could be detected. One of these proteins was characterized by tryptical digestion and subsequent identification via tandem quadrupole-time of flight (Q-TOF) mass spectrometry. Down regulation of this sequenced small subunit precursor of ribulose-1,5 bisphosphate carboxylase(C) oxygenase(O) (RuBisCo) in trichome and basal cells indicates the sink status of these cell types that are located on the surface of A. thaliana source leaves. Based on the obtained protein profiles, we suggest a close functional relationship between basal and trichome cells at the protein level.

PCoM-DB Update: A Protein Co-Migration Database for Photosynthetic Organisms.

PubMed

Takabayashi, Atsushi; Takabayashi, Saeka; Takahashi, Kaori; Watanabe, Mai; Uchida, Hiroko; Murakami, Akio; Fujita, Tomomichi; Ikeuchi, Masahiko; Tanaka, Ayumi

2017-01-01

The identification of protein complexes is important for the understanding of protein structure and function and the regulation of cellular processes. We used blue-native PAGE and tandem mass spectrometry to identify protein complexes systematically, and built a web database, the protein co-migration database (PCoM-DB, http://pcomdb.lowtem.hokudai.ac.jp/proteins/top), to provide prediction tools for protein complexes. PCoM-DB provides migration profiles for any given protein of interest, and allows users to compare them with migration profiles of other proteins, showing the oligomeric states of proteins and thus identifying potential interaction partners. The initial version of PCoM-DB (launched in January 2013) included protein complex data for Synechocystis whole cells and Arabidopsis thaliana thylakoid membranes. Here we report PCoM-DB version 2.0, which includes new data sets and analytical tools. Additional data are included from whole cells of the pelagic marine picocyanobacterium Prochlorococcus marinus, the thermophilic cyanobacterium Thermosynechococcus elongatus, the unicellular green alga Chlamydomonas reinhardtii and the bryophyte Physcomitrella patens. The Arabidopsis protein data now include data for intact mitochondria, intact chloroplasts, chloroplast stroma and chloroplast envelopes. The new tools comprise a multiple-protein search form and a heat map viewer for protein migration profiles. Users can compare migration profiles of a protein of interest among different organelles or compare migration profiles among different proteins within the same sample. For Arabidopsis proteins, users can compare migration profiles of a protein of interest with putative homologous proteins from non-Arabidopsis organisms. The updated PCoM-DB will help researchers find novel protein complexes and estimate their evolutionary changes in the green lineage. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data.

PubMed

Adamczak, Rafal; Meller, Jarek

2016-12-28

Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions. uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust . uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.

Comparative Expression Profiling of Distinct T Cell Subsets Undergoing Oxidative Stress

PubMed Central

Lichtenfels, Rudolf; Mougiakakos, Dimitrios; Johansson, C. Christian; Dressler, Sven P.; Recktenwald, Christian V.; Kiessling, Rolf; Seliger, Barbara

2012-01-01

The clinical outcome of adoptive T cell transfer-based immunotherapies is often limited due to different escape mechanisms established by tumors in order to evade the hosts' immune system. The establishment of an immunosuppressive micromilieu by tumor cells along with distinct subsets of tumor-infiltrating lymphocytes is often associated with oxidative stress that can affect antigen-specific memory/effector cytotoxic T cells thereby substantially reducing their frequency and functional activation. Therefore, protection of tumor-reactive cytotoxic T lymphocytes from oxidative stress may enhance the anti-tumor-directed immune response. In order to better define the key pathways/proteins involved in the response to oxidative stress a comparative 2-DE-based proteome analysis of naïve CD45RA+ and their memory/effector CD45RO+ T cell counterparts in the presence and absence of low dose hydrogen peroxide (H2O2) was performed in this pilot study. Based on the profiling data of these T cell subpopulations under the various conditions, a series of differentially expressed spots were defined, members thereof identified by mass spectrometry and subsequently classified according to their cellular function and localization. Representative targets responding to oxidative stress including proteins involved in signaling pathways, in regulating the cellular redox status as well as in shaping/maintaining the structural cell integrity were independently verified at the transcript and protein level under the same conditions in both T cell subsets. In conclusion the resulting profiling data describe complex, oxidative stress-induced, but not strictly concordant changes within the respective expression profiles of CD45RA+ and CD45RO+ T cells. Some of the differentially expressed genes/proteins might be further exploited as potential targets toward modulating the redox capacity of the distinct lymphocyte subsets thereby providing the basis for further studies aiming at rendering them more resistant to tumor micromilieu-induced oxidative stress. PMID:22911781

Comparative bioinformatics analyses and profiling of lysosome-related organelle proteomes

NASA Astrophysics Data System (ADS)

Hu, Zhang-Zhi; Valencia, Julio C.; Huang, Hongzhan; Chi, An; Shabanowitz, Jeffrey; Hearing, Vincent J.; Appella, Ettore; Wu, Cathy

2007-01-01

Complete and accurate profiling of cellular organelle proteomes, while challenging, is important for the understanding of detailed cellular processes at the organelle level. Mass spectrometry technologies coupled with bioinformatics analysis provide an effective approach for protein identification and functional interpretation of organelle proteomes. In this study, we have compiled human organelle reference datasets from large-scale proteomic studies and protein databases for seven lysosome-related organelles (LROs), as well as the endoplasmic reticulum and mitochondria, for comparative organelle proteome analysis. Heterogeneous sources of human organelle proteins and rodent homologs are mapped to human UniProtKB protein entries based on ID and/or peptide mappings, followed by functional annotation and categorization using the iProXpress proteomic expression analysis system. Cataloging organelle proteomes allows close examination of both shared and unique proteins among various LROs and reveals their functional relevance. The proteomic comparisons show that LROs are a closely related family of organelles. The shared proteins indicate the dynamic and hybrid nature of LROs, while the unique transmembrane proteins may represent additional candidate marker proteins for LROs. This comparative analysis, therefore, provides a basis for hypothesis formulation and experimental validation of organelle proteins and their functional roles.

On the potential of using peculiarities of the protein intrinsic disorder distribution in mitochondrial cytochrome b to identify the source of animal meats

PubMed Central

Yacoub, Haitham A.; Sadek, Mahmoud A.; Uversky, Vladimir N.

2017-01-01

ABSTRACT This study was conducted to identify the source of animal meat based on the peculiarities of protein intrinsic disorder distribution in mitochondrial cytochrome b (mtCyt-b). The analysis revealed that animal and avian species can be discriminated based on the proportions of the two groups of residues, Leu+Ile, and Ser+Pro+Ala, in the amino acid sequences of their mtCyt-b. Although levels of the overall intrinsic disorder in mtCyt-b is not very high, the peculiarities of disorder distribution within the sequences of mtCyt-b from different species varies in a rather specific way. In fact, positions and intensities of disorder/flexibility “signals” in the corresponding disorder profiles are relatively unique for avian and animal species. Therefore, it is possible to devise a set of simple rules based on the peculiarities of disorder profiles of their mtCyt-b proteins to discriminate among species. This intrinsic disorder-based analysis represents a new technique that could be used to provide a promising solution for identification of the source of meats. PMID:28331777

Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome

PubMed Central

Leppert, Tami; Anex, Deon S.; Hilmer, Jonathan K.; Matsunami, Nori; Baird, Lisa; Stevens, Jeffery; Parsawar, Krishna; Durbin-Johnson, Blythe P.; Rocke, David M.; Nelson, Chad; Fairbanks, Daniel J.; Wilson, Andrew S.; Rice, Robert H.; Woodward, Scott R.; Bothner, Brian; Hart, Bradley R.; Leppert, Mark

2016-01-01

Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects’ DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European–American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). This study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts. PMID:27603779

A Transcriptome Meta-Analysis Proposes Novel Biological Roles for the Antifungal Protein AnAFP in Aspergillus niger

PubMed Central

Schäpe, Paul; Müller-Hagen, Dirk; Ouedraogo, Jean-Paul; Heiderich, Caroline; Jedamzick, Johanna; van den Hondel, Cees A.; Ram, Arthur F.; Meyer, Vera

2016-01-01

Understanding the genetic, molecular and evolutionary basis of cysteine-stabilized antifungal proteins (AFPs) from fungi is important for understanding whether their function is mainly defensive or associated with fungal growth and development. In the current study, a transcriptome meta-analysis of the Aspergillus niger γ-core protein AnAFP was performed to explore co-expressed genes and pathways, based on independent expression profiling microarrays covering 155 distinct cultivation conditions. This analysis uncovered that anafp displays a highly coordinated temporal and spatial transcriptional profile which is concomitant with key nutritional and developmental processes. Its expression profile coincides with early starvation response and parallels with genes involved in nutrient mobilization and autophagy. Using fluorescence- and luciferase reporter strains we demonstrated that the anafp promoter is active in highly vacuolated compartments and foraging hyphal cells during carbon starvation with CreA and FlbA, but not BrlA, as most likely regulators of anafp. A co-expression network analysis supported by luciferase-based reporter assays uncovered that anafp expression is embedded in several cellular processes including allorecognition, osmotic and oxidative stress survival, development, secondary metabolism and autophagy, and predicted StuA and VelC as additional regulators. The transcriptomic resources available for A. niger provide unparalleled resources to investigate the function of proteins. Our work illustrates how transcriptomic meta-analyses can lead to hypotheses regarding protein function and predict a role for AnAFP during slow growth, allorecognition, asexual development and nutrient recycling of A. niger and propose that it interacts with the autophagic machinery to enable these processes. PMID:27835655

A Transcriptome Meta-Analysis Proposes Novel Biological Roles for the Antifungal Protein AnAFP in Aspergillus niger.

PubMed

Paege, Norman; Jung, Sascha; Schäpe, Paul; Müller-Hagen, Dirk; Ouedraogo, Jean-Paul; Heiderich, Caroline; Jedamzick, Johanna; Nitsche, Benjamin M; van den Hondel, Cees A; Ram, Arthur F; Meyer, Vera

2016-01-01

Understanding the genetic, molecular and evolutionary basis of cysteine-stabilized antifungal proteins (AFPs) from fungi is important for understanding whether their function is mainly defensive or associated with fungal growth and development. In the current study, a transcriptome meta-analysis of the Aspergillus niger γ-core protein AnAFP was performed to explore co-expressed genes and pathways, based on independent expression profiling microarrays covering 155 distinct cultivation conditions. This analysis uncovered that anafp displays a highly coordinated temporal and spatial transcriptional profile which is concomitant with key nutritional and developmental processes. Its expression profile coincides with early starvation response and parallels with genes involved in nutrient mobilization and autophagy. Using fluorescence- and luciferase reporter strains we demonstrated that the anafp promoter is active in highly vacuolated compartments and foraging hyphal cells during carbon starvation with CreA and FlbA, but not BrlA, as most likely regulators of anafp. A co-expression network analysis supported by luciferase-based reporter assays uncovered that anafp expression is embedded in several cellular processes including allorecognition, osmotic and oxidative stress survival, development, secondary metabolism and autophagy, and predicted StuA and VelC as additional regulators. The transcriptomic resources available for A. niger provide unparalleled resources to investigate the function of proteins. Our work illustrates how transcriptomic meta-analyses can lead to hypotheses regarding protein function and predict a role for AnAFP during slow growth, allorecognition, asexual development and nutrient recycling of A. niger and propose that it interacts with the autophagic machinery to enable these processes.

HMMER Cut-off Threshold Tool (HMMERCTTER): Supervised classification of superfamily protein sequences with a reliable cut-off threshold.

PubMed

Pagnuco, Inti Anabela; Revuelta, María Victoria; Bondino, Hernán Gabriel; Brun, Marcel; Ten Have, Arjen

2018-01-01

Protein superfamilies can be divided into subfamilies of proteins with different functional characteristics. Their sequences can be classified hierarchically, which is part of sequence function assignation. Typically, there are no clear subfamily hallmarks that would allow pattern-based function assignation by which this task is mostly achieved based on the similarity principle. This is hampered by the lack of a score cut-off that is both sensitive and specific. HMMER Cut-off Threshold Tool (HMMERCTTER) adds a reliable cut-off threshold to the popular HMMER. Using a high quality superfamily phylogeny, it clusters a set of training sequences such that the cluster-specific HMMER profiles show cluster or subfamily member detection with 100% precision and recall (P&R), thereby generating a specific threshold as inclusion cut-off. Profiles and thresholds are then used as classifiers to screen a target dataset. Iterative inclusion of novel sequences to groups and the corresponding HMMER profiles results in high sensitivity while specificity is maintained by imposing 100% P&R self detection. In three presented case studies of protein superfamilies, classification of large datasets with 100% precision was achieved with over 95% recall. Limits and caveats are presented and explained. HMMERCTTER is a promising protein superfamily sequence classifier provided high quality training datasets are used. It provides a decision support system that aids in the difficult task of sequence function assignation in the twilight zone of sequence similarity. All relevant data and source codes are available from the Github repository at the following URL: https://github.com/BBCMdP/HMMERCTTER.

HMMER Cut-off Threshold Tool (HMMERCTTER): Supervised classification of superfamily protein sequences with a reliable cut-off threshold

PubMed Central

Pagnuco, Inti Anabela; Revuelta, María Victoria; Bondino, Hernán Gabriel; Brun, Marcel

2018-01-01

Background Protein superfamilies can be divided into subfamilies of proteins with different functional characteristics. Their sequences can be classified hierarchically, which is part of sequence function assignation. Typically, there are no clear subfamily hallmarks that would allow pattern-based function assignation by which this task is mostly achieved based on the similarity principle. This is hampered by the lack of a score cut-off that is both sensitive and specific. Results HMMER Cut-off Threshold Tool (HMMERCTTER) adds a reliable cut-off threshold to the popular HMMER. Using a high quality superfamily phylogeny, it clusters a set of training sequences such that the cluster-specific HMMER profiles show cluster or subfamily member detection with 100% precision and recall (P&R), thereby generating a specific threshold as inclusion cut-off. Profiles and thresholds are then used as classifiers to screen a target dataset. Iterative inclusion of novel sequences to groups and the corresponding HMMER profiles results in high sensitivity while specificity is maintained by imposing 100% P&R self detection. In three presented case studies of protein superfamilies, classification of large datasets with 100% precision was achieved with over 95% recall. Limits and caveats are presented and explained. Conclusions HMMERCTTER is a promising protein superfamily sequence classifier provided high quality training datasets are used. It provides a decision support system that aids in the difficult task of sequence function assignation in the twilight zone of sequence similarity. All relevant data and source codes are available from the Github repository at the following URL: https://github.com/BBCMdP/HMMERCTTER. PMID:29579071

Multiplexed salivary protein profiling for patients with respiratory diseases using fiber-optic bundles and fluorescent antibody-based microarrays.

PubMed

Nie, Shuai; Benito-Peña, Elena; Zhang, Huaibin; Wu, Yue; Walt, David R

2013-10-01

Over the past 40 years, the incidence and prevalence of respiratory diseases have increased significantly throughout the world, damaging economic productivity and challenging health care systems. Current diagnoses of different respiratory diseases generally involve invasive sampling methods such as induced sputum or bronchoalveolar lavage that are uncomfortable, or even painful, for the patient. In this paper, we present a platform incorporating fiber-optic bundles and antibody-based microarrays to perform multiplexed protein profiling of a panel of six salivary biomarkers for asthma and cystic fibrosis (CF) diagnosis. The platform utilizes an optical fiber bundle containing approximately 50,000 individual 4.5 μm diameter fibers that are chemically etched to create microwells in which modified microspheres decorated with monoclonal capture antibodies can be deposited. On the basis of a sandwich immunoassay format, the array quantifies human vascular endothelial growth factor (VEGF), interferon gamma-induced protein 10 (IP-10), interleukin-8 (IL-8), epidermal growth factor (EGF), matrix metalloproteinase 9 (MMP-9), and interleukin-1 beta (IL-1β) salivary biomarkers in the subpicomolar range. Saliva supernatants collected from 291 individuals (164 asthmatics, 71 CF patients, and 56 healthy controls (HC)) were analyzed on the platform to profile each group of patients using this six-analyte suite. It was found that four of the six proteins were observed to be significantly elevated (p < 0.01) in asthma and CF patients compared with HC. These results demonstrate the potential to use the multiplexed protein array platform for respiratory disease diagnosis.

Activity-Based Protein Profiling of Organophosphorus and Thiocarbamate Pesticides Reveals Multiple Serine Hydrolase Targets in Mouse Brain

PubMed Central

NOMURA, DANIEL K.; CASIDA, JOHN E.

2010-01-01

Organophosphorus (OP) and thiocarbamate (TC) agrochemicals are used worldwide as insecticides, herbicides, and fungicides, but their safety assessment in terms of potential off-targets remains incomplete. In this study, we used a chemoproteomic platform, termed activity-based protein profiling, to broadly define serine hydrolase targets in mouse brain of a panel of 29 OP and TC pesticides. Among the secondary targets identified, enzymes involved in degradation of endocannabinoid signaling lipids, monoacylglycerol lipase and fatty acid amide hydrolase, were inhibited by several OP and TC pesticides. Blockade of these two enzymes led to elevations in brain endocannabinoid levels and dysregulated brain arachidonate metabolism. Other secondary targets include enzymes thought to also play important roles in the nervous system and unannotated proteins. This study reveals a multitude of secondary targets for OP and TC pesticides and underscores the utility of chemoproteomic platforms in gaining insights into biochemical pathways that are perturbed by these toxicants. PMID:21341672

Quantitative Profiling of DNA Damage and Apoptotic Pathways in UV Damaged Cells Using PTMScan Direct

PubMed Central

Stokes, Matthew P.; Silva, Jeffrey C.; Jia, Xiaoying; Lee, Kimberly A.; Polakiewicz, Roberto D.; Comb, Michael J.

2013-01-01

Traditional methods for analysis of peptides using liquid chromatography and tandem mass spectrometry (LC-MS/MS) lack the specificity to comprehensively monitor specific biological processes due to the inherent duty cycle limitations of the MS instrument and the stochastic nature of the analytical platform. PTMScan Direct is a novel, antibody-based method that allows quantitative LC-MS/MS profiling of specific peptides from proteins that reside in the same signaling pathway. New PTMScan Direct reagents have been produced that target peptides from proteins involved in DNA Damage/Cell Cycle and Apoptosis/Autophagy pathways. Together, the reagents provide access to 438 sites on 237 proteins in these signaling cascades. These reagents have been used to profile the response to UV damage of DNA in human cell lines. UV damage was shown to activate canonical DNA damage response pathways through ATM/ATR-dependent signaling, stress response pathways and induce the initiation of apoptosis, as assessed by an increase in the abundance of peptides corresponding to cleaved, activated caspases. These data demonstrate the utility of PTMScan Direct as a multiplexed assay for profiling specific cellular responses to various stimuli, such as UV damage of DNA. PMID:23344034

Complementary Proteome and Transcriptome Profiling in Developing Grains of a Notched-Belly Rice Mutant Reveals Key Pathways Involved in Chalkiness Formation

PubMed Central

Lin, Zhaomiao; Wang, Zunxin; Zhang, Xincheng; Li, Ganghua; Wang, Shaohua; Ding, Yanfeng

2017-01-01

Rice grain chalkiness is a highly complex trait involved in multiple metabolic pathways and controlled by polygenes and growth conditions. To uncover novel aspects of chalkiness formation, we performed an integrated profiling of gene activity in the developing grains of a notched-belly rice mutant. Using exhaustive tandem mass spectrometry-based shotgun proteomics and whole-genome RNA sequencing to generate a nearly complete catalog of expressed mRNAs and proteins, we reliably identified 38,476 transcripts and 3,840 proteins. Comparison between the translucent part and chalky part of the notched-belly grains resulted in only a few differently express genes (240) and differently express proteins (363), thus making it possible to focus on ‘core’ genes or common pathways. Several novel key pathways were identified as of relevance to chalkiness formation, in particular the shift of C and N metabolism, the down-regulation of ribosomal proteins and the resulting low abundance of storage proteins especially the 13 kDa prolamin subunit, and the suppressed photosynthetic capacity in the pericarp of the chalky part. Further, genes and proteins as transporters for carbohydrates, amino acid/peptides, proteins, lipids and inorganic ions showed an increasing expression pattern in the chalky part of the notched-belly grains. Similarly, transcripts and proteins of receptors for auxin, ABA, ethylene and brassinosteroid were also up-regulated. In summary, this joint analysis of transcript and protein profiles provides a comprehensive reference map of gene activity regarding the physiological state in the chalky endosperm. PMID:28158863

Rapid identification and typing of Yersinia pestis and other Yersinia species by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry

PubMed Central

2010-01-01

Background Accurate identification is necessary to discriminate harmless environmental Yersinia species from the food-borne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis and from the group A bioterrorism plague agent Yersinia pestis. In order to circumvent the limitations of current phenotypic and PCR-based identification methods, we aimed to assess the usefulness of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) protein profiling for accurate and rapid identification of Yersinia species. As a first step, we built a database of 39 different Yersinia strains representing 12 different Yersinia species, including 13 Y. pestis isolates representative of the Antiqua, Medievalis and Orientalis biotypes. The organisms were deposited on the MALDI-TOF plate after appropriate ethanol-based inactivation, and a protein profile was obtained within 6 minutes for each of the Yersinia species. Results When compared with a 3,025-profile database, every Yersinia species yielded a unique protein profile and was unambiguously identified. In the second step of analysis, environmental and clinical isolates of Y. pestis (n = 2) and Y. enterocolitica (n = 11) were compared to the database and correctly identified. In particular, Y. pestis was unambiguously identified at the species level, and MALDI-TOF was able to successfully differentiate the three biotypes. Conclusion These data indicate that MALDI-TOF can be used as a rapid and accurate first-line method for the identification of Yersinia isolates. PMID:21073689

Rapid identification and typing of Yersinia pestis and other Yersinia species by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry.

PubMed

Ayyadurai, Saravanan; Flaudrops, Christophe; Raoult, Didier; Drancourt, Michel

2010-11-12

Accurate identification is necessary to discriminate harmless environmental Yersinia species from the food-borne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis and from the group A bioterrorism plague agent Yersinia pestis. In order to circumvent the limitations of current phenotypic and PCR-based identification methods, we aimed to assess the usefulness of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) protein profiling for accurate and rapid identification of Yersinia species. As a first step, we built a database of 39 different Yersinia strains representing 12 different Yersinia species, including 13 Y. pestis isolates representative of the Antiqua, Medievalis and Orientalis biotypes. The organisms were deposited on the MALDI-TOF plate after appropriate ethanol-based inactivation, and a protein profile was obtained within 6 minutes for each of the Yersinia species. When compared with a 3,025-profile database, every Yersinia species yielded a unique protein profile and was unambiguously identified. In the second step of analysis, environmental and clinical isolates of Y. pestis (n = 2) and Y. enterocolitica (n = 11) were compared to the database and correctly identified. In particular, Y. pestis was unambiguously identified at the species level, and MALDI-TOF was able to successfully differentiate the three biotypes. These data indicate that MALDI-TOF can be used as a rapid and accurate first-line method for the identification of Yersinia isolates.

Profiling of Human Acquired Immunity Against the Salivary Proteins of Phlebotomus papatasi Reveals Clusters of Differential Immunoreactivity

PubMed Central

Geraci, Nicholas S.; Mukbel, Rami M.; Kemp, Michael T.; Wadsworth, Mariha N.; Lesho, Emil; Stayback, Gwen M.; Champion, Matthew M.; Bernard, Megan A.; Abo-Shehada, Mahmoud; Coutinho-Abreu, Iliano V.; Ramalho-Ortigão, Marcelo; Hanafi, Hanafi A.; Fawaz, Emadeldin Y.; El-Hossary, Shabaan S.; Wortmann, Glenn; Hoel, David F.; McDowell, Mary Ann

2014-01-01

Phlebotomus papatasi sand flies are among the primary vectors of Leishmania major parasites from Morocco to the Indian subcontinent and from southern Europe to central and eastern Africa. Antibody-based immunity to sand fly salivary gland proteins in human populations remains a complex contextual problem that is not yet fully understood. We profiled the immunoreactivities of plasma antibodies to sand fly salivary gland sonicates (SGSs) from 229 human blood donors residing in different regions of sand fly endemicity throughout Jordan and Egypt as well as 69 US military personnel, who were differentially exposed to P. papatasi bites and L. major infections in Iraq. Compared with plasma from control region donors, antibodies were significantly immunoreactive to five salivary proteins (12, 26, 30, 38, and 44 kDa) among Jordanian and Egyptian donors, with immunoglobulin G4 being the dominant anti-SGS isotype. US personnel were significantly immunoreactive to only two salivary proteins (38 and 14 kDa). Using k-means clustering, donors were segregated into four clusters distinguished by unique immunoreactivity profiles to varying combinations of the significantly immunogenic salivary proteins. SGS-induced cellular proliferation was diminished among donors residing in sand fly-endemic regions. These data provide a clearer picture of human immune responses to sand fly vector salivary constituents. PMID:24615125

Label-Free LC-MS Profiling of Skeletal Muscle Reveals Heart-Type Fatty Acid Binding Protein as a Candidate Biomarker of Aerobic Capacity.

PubMed

Malik, Zulezwan Ab; Cobley, James N; Morton, James P; Close, Graeme L; Edwards, Ben J; Koch, Lauren G; Britton, Steven L; Burniston, Jatin G

2013-12-01

Two-dimensional gel electrophoresis provides robust comparative analysis of skeletal muscle, but this technique is laborious and limited by its inability to resolve all proteins. In contrast, orthogonal separation by SDS-PAGE and reverse-phase liquid chromatography (RPLC) coupled to mass spectrometry (MS) affords deep mining of the muscle proteome, but differential analysis between samples is challenging due to the greater level of fractionation and the complexities of quantifying proteins based on the abundances of their tryptic peptides. Here we report simple, semi-automated and time efficient ( i.e ., 3 h per sample) proteome profiling of skeletal muscle by 1-dimensional RPLC electrospray ionisation tandem MS. Solei were analysed from rats (n = 5, in each group) bred as either high- or low-capacity runners (HCR and LCR, respectively) that exhibited a 6.4-fold difference (1,625 ± 112 m vs . 252 ± 43 m, p < 0.0001) in running capacity during a standardized treadmill test. Soluble muscle proteins were extracted, digested with trypsin and individual biological replicates (50 ng of tryptic peptides) subjected to LC-MS profiling. Proteins were identified by triplicate LC-MS/MS analysis of a pooled sample of each biological replicate. Differential expression profiling was performed on relative abundances (RA) of parent ions, which spanned three orders of magnitude. In total, 207 proteins were analysed, which encompassed almost all enzymes of the major metabolic pathways in skeletal muscle. The most abundant protein detected was type I myosin heavy chain (RA = 5,843 ± 897) and the least abundant protein detected was heat shock 70 kDa protein (RA = 2 ± 0.5). Sixteen proteins were significantly ( p < 0.05) more abundant in HCR muscle and hierarchal clustering of the profiling data highlighted two protein subgroups, which encompassed proteins associated with either the respiratory chain or fatty acid oxidation. Heart-type fatty acid binding protein (FABPH) was 1.54-fold ( p = 0.0064) more abundant in HCR than LCR soleus. This discovery was verified using selective reaction monitoring (SRM) of the y5 ion (551.21 m/z ) of the doubly-charged peptide SLGVGFATR (454.19 m/z ) of residues 23-31 of FABPH. SRM was conducted on technical replicates of each biological sample and exhibited a coefficient of variation of 20%. The abundance of FABPH measured by SRM was 2.84-fold greater ( p = 0.0095) in HCR muscle. In addition, SRM of FABPH was performed in vastus lateralis samples of young and elderly humans with different habitual activity levels (collected during a previous study) finding FABPH abundance was 2.23-fold greater ( p = 0.0396) in endurance-trained individuals regardless of differences in age. In summary, our findings in HCR/LCR rats provide protein-level confirmation for earlier transcriptome profiling work and show LC-MS is a viable means of profiling the abundance of almost all major metabolic enzymes of skeletal muscle in a highly parallel manner. Moreover, our approach is relatively more time efficient than techniques relying on orthogonal separations, and we demonstrate LC-MS profiling of the HCR/LCR selection model was able to highlight biomarkers that also exhibit differences in trained and untrained human muscle.

Cancer cell profiling by barcoding allows multiplexed protein analysis in fine-needle aspirates.

PubMed

Ullal, Adeeti V; Peterson, Vanessa; Agasti, Sarit S; Tuang, Suan; Juric, Dejan; Castro, Cesar M; Weissleder, Ralph

2014-01-15

Immunohistochemistry-based clinical diagnoses require invasive core biopsies and use a limited number of protein stains to identify and classify cancers. We introduce a technology that allows analysis of hundreds of proteins from minimally invasive fine-needle aspirates (FNAs), which contain much smaller numbers of cells than core biopsies. The method capitalizes on DNA-barcoded antibody sensing, where barcodes can be photocleaved and digitally detected without any amplification steps. After extensive benchmarking in cell lines, this method showed high reproducibility and achieved single-cell sensitivity. We used this approach to profile ~90 proteins in cells from FNAs and subsequently map patient heterogeneity at the protein level. Additionally, we demonstrate how the method could be used as a clinical tool to identify pathway responses to molecularly targeted drugs and to predict drug response in patient samples. This technique combines specificity with ease of use to offer a new tool for understanding human cancers and designing future clinical trials.

Cancer cell profiling by barcoding allows multiplexed protein analysis in fine needle aspirates

PubMed Central

Ullal, Adeeti V.; Peterson, Vanessa; Agasti, Sarit S.; Tuang, Suan; Juric, Dejan; Castro, Cesar M.; Weissleder, Ralph

2014-01-01

Immunohistochemistry-based clinical diagnoses require invasive core biopsies and use a limited number of protein stains to identify and classify cancers. Here, we introduce a technology that allows analysis of hundreds of proteins from minimally invasive fine needle aspirates (FNA), which contain much smaller numbers of cells than core biopsies. The method capitalizes on DNA-barcoded antibody sensing where barcodes can be photo-cleaved and digitally detected without any amplification steps. Following extensive benchmarking in cell lines, this method showed high reproducibility and achieved single cell sensitivity. We used this approach to profile ~90 proteins in cells from FNAs and subsequently map patient heterogeneity at the protein level. Additionally, we demonstrate how the method could be used as a clinical tool to identify pathway responses to molecularly targeted drugs and to predict drug response in patient samples. This technique combines specificity with ease of use to offer a new tool for understanding human cancers and designing future clinical trials. PMID:24431113

NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.

PubMed

Mao, Wusong; Cong, Peisheng; Wang, Zhiheng; Lu, Longjian; Zhu, Zhongliang; Li, Tonghua

2013-01-01

Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp.

Global PROTOMAP profiling to search for biomarkers of early-recurrent hepatocellular carcinoma.

PubMed

Taoka, Masato; Morofuji, Noriaki; Yamauchi, Yoshio; Ojima, Hidenori; Kubota, Daisuke; Terukina, Goro; Nobe, Yuko; Nakayama, Hiroshi; Takahashi, Nobuhiro; Kosuge, Tomoo; Isobe, Toshiaki; Kondo, Tadashi

2014-11-07

This study used global protein expression profiling to search for biomarkers to predict early recurrent hepatocellular carcinoma (HCC). HCC tissues surgically resected from patients with or without recurrence within 2 years (early recurrent) after surgery were compared with adjacent nontumor tissue and with normal liver tissue. We used the PROTOMAP strategy for comparative profiling, which integrates denaturing polyacrylamide gel electrophoresis migratory rates and high-resolution, semiquantitative mass-spectrometry-based identification of in-gel-digested tryptic peptides. PROTOMAP allows examination of global changes in the size, topography, and abundance of proteins in complex tissue samples. This approach identified 8438 unique proteins from 45 708 nonredundant peptides and generated a proteome-wide map of changes in expression and proteolytic events potentially induced by intrinsic apoptotic/necrotic pathways. In the early recurrent HCC tissue, 87 proteins were differentially expressed (≥20-fold) relative to the other tissues, 46 of which were up-regulated or specifically proteolyzed and 41 of which were down-regulated. This data set consisted of proteins that fell into various functional categories, including signal transduction and cell organization and, notably, the major catalytic pathways responsible for liver function, such as the urea cycle and detoxification metabolism. We found that aberrant proteolysis appeared to occur frequently during recurrence of HCC in several key signal transducers, including STAT1 and δ-catenin. Further investigation of these proteins will facilitate the development of novel clinical applications.

Identifying protein kinase target preferences using mass spectrometry

PubMed Central

Douglass, Jacqueline; Gunaratne, Ruwan; Bradford, Davis; Saeed, Fahad; Hoffert, Jason D.; Steinbach, Peter J.; Pisitkun, Trairak

2012-01-01

A general question in molecular physiology is how to identify candidate protein kinases corresponding to a known or hypothetical phosphorylation site in a protein of interest. It is generally recognized that the amino acid sequence surrounding the phosphorylation site provides information that is relevant to identification of the cognate protein kinase. Here, we present a mass spectrometry-based method for profiling the target specificity of a given protein kinase as well as a computational tool for the calculation and visualization of the target preferences. The mass spectrometry-based method identifies sites phosphorylated in response to in vitro incubation of protein mixtures with active recombinant protein kinases followed by standard phosphoproteomic methodologies. The computational tool, called “PhosphoLogo,” uses an information-theoretic algorithm to calculate position-specific amino acid preferences and anti-preferences from the mass-spectrometry data (http://helixweb.nih.gov/PhosphoLogo/). The method was tested using protein kinase A (catalytic subunit α), revealing the well-known preference for basic amino acids in positions −2 and −3 relative to the phosphorylated amino acid. It also provides evidence for a preference for amino acids with a branched aliphatic side chain in position +1, a finding compatible with known crystal structures of protein kinase A. The method was also employed to profile target preferences and anti-preferences for 15 additional protein kinases with potential roles in regulation of epithelial transport: CK2, p38, AKT1, SGK1, PKCδ, CaMK2δ, DAPK1, MAPKAPK2, PKD3, PIM1, OSR1, STK39/SPAK, GSK3β, Wnk1, and Wnk4. PMID:22723110

Protein and Older Persons.

PubMed

Bauer, Juergen M; Diekmann, Rebecca

2015-08-01

An optimal protein intake is important for the preservation of muscle mass, functionality, and quality of life in older persons. In recent years, new recommendations regarding the optimal intake of protein in this population have been published. Based on the available scientific literature, 1.0 to 1.2 g protein/kg body weight (BW)/d are recommended in healthy older adults. In certain disease states, a daily protein intake of more than 1.2 g/kg BW may be required. The distribution of protein intake over the day, the amount per meal, and the amino acid profile of proteins are also discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

UFO: a web server for ultra-fast functional profiling of whole genome protein sequences.

PubMed

Meinicke, Peter

2009-09-02

Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

Heterogeneity of proteins expressed by Brazilian Sporothrix schenckii isolates.

PubMed

Fernandes, Geisa Ferreira; Do Amaral, Cristiane Candida; Sasaki, Alexandre; Godoy, Patrício Martinez; De Camargo, Zoilo Pires

2009-12-01

The profiles of proteins present in the exoantigens of Brazilian Sporothrix schenckii isolates were studied and compared by electrophoresis (SDS-PAGE). Thirteen isolates from five different regions of Brazil (1,000 to 2,000 km apart) and ten from a more limited region (200 to 400 km apart within the state of São Paulo) were cultured in Sabouraud, M199 and minimum (MM) media. Qualitative and quantitative differences in the expression of proteins, which varied according to the medium and the isolate, were observed. Fractions with the same MW but varying in intensity were detected, as well as fractions present in 1 isolate but absent in others. Dendrograms were constructed and isolates grouped based on the fractions obtained, irrespective of the intensity. The results showed that Brazilian S. schenckii isolates express different protein profiles, a feature also present in isolates from a more restricted region. The exoantigens were found to have a maximum of 15 protein fractions, ranging in MW from 19-220 KDaltons depending on the medium used for the cultures. These data show the great heterogeneity of Brazilian S. schenckii protein expression.

Quantitative site-specific reactivity profiling of S-nitrosylation in mouse skeletal muscle using cysteinyl peptide enrichment coupled with mass spectrometry

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

Su, Dian; Shukla, Anil K.; Chen, Baowei

2013-04-01

S-nitrosylation (SNO) is an important reversible thiol oxidation event that has been increasingly recognized for its role in cell signaling. While many proteins susceptible to S-nitrosylation have been reported, site-specific identification of physiologically relevant SNO modifications remains an analytical challenge due to the low-abundance and labile nature of the modification. Herein we present further improvement and optimization of the recently reported, resin-assisted cysteinyl peptide enrichment protocol for SNO identification and the extension of this application to mouse skeletal muscle to identify specific sites sensitive to S-nitrosylation by quantitative reactivity profiling. The results of our data indicate that the protein- andmore » peptide-level enrichment protocols provide comparable specificity and coverage of SNO-peptide identifications. S-nitrosylation reactivity profiling was performed by quantitatively comparing the site-specific SNO modification levels in samples treated with S-nitrosoglutathione (GSNO), an NO donor, at two different physiologically relevant concentrations (i.e., 10 μM and 100 μM). The reactivity profiling experiments overall identified 489 SNO-modified cysteine sites from 197 proteins with the specificity of 95.2% at the unique-peptide-level based on the percentage of Cys-peptides. Among these sites, 260 sites from 135 proteins were observed with relatively high reactivity to S-nitrosylation; such SNO-sensitive sites are more likely to be physiologically relevant. Many of the SNO-sensitive proteins are preferentially localized in mitochondria, contractile fiber and actin cytoskeleton, suggesting the susceptibility of these subcellular compartments to redox regulation. Moreover, the SNO-sensitive proteins seem to be primarily involved in metabolic pathways, including TCA cycle, glycolysis/gluconeogenesis, glutathione metabolism, and fatty acid metabolism, suggesting the importance of redox regulation in muscle metabolism and insulin action.« less

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

PubMed

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

NASA Astrophysics Data System (ADS)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

Identification and Characterization of Memecylon Species Using Isozyme Profiling

PubMed Central

Bharathi, T. R.; Sekhar, Shailasree; Geetha, N.; Niranjana, S. R.; Prakash, H. S.

2017-01-01

Background: The protein/isozyme fingerprint is useful in differentiating the species and acts as a biochemical marker for identification and systematic studies of medicinal plant species. Objective: In the present study, protein and isozyme profiles for peroxidase, esterase, acid phosphatase, polyphenol oxidase, alcohol dehydrogenase, and alkaline phosphatase of five species of Memecylon (Melastomataceae), Memecylon umbellatum, Memecylon edule, Memecylon talbotianum, Memecylon malabaricum, and Memecylon wightii were investigated. Materials and Methods: Fresh leaves were used to prepare crude enzyme extract for analyzing the five enzymes isozyme variations. Separation of isozymes was carried out using polyacrylamide gel electrophoresis (PAGE) and the banding patterns of protein were scored. Pair-wise comparisons of genotypes, based on the presence or absence of unique and shared polymorphic products, were used to regenerate similarity coefficients. The similarity coefficients were then used to construct dendrograms, using the unweighted pair group method with arithmetic averages. Results: A total of 50 bands with various Rf values and molecular weight were obtained through PAGE analysis. Among the five Memecylon species, more number of bands was produced in M. wightii and less number of bands was observed in M. edule. The results of similarity indices grouped M. malabaricum and M. wightii in one cluster with 98% similarity and M. umbellatum, M. edule, and M. talbotianum are grouped in another cluster with 79% similarity showing close genetic similarities which is in accordance with the morphological identification of Memecylon species. Conclusion: The protein/isozyme fingerprint is useful in differentiating the species and acts as a biochemical marker for identification of Memecylon species. SUMMARY Biochemical characterization of Memecylon species was evaluated by SDS-PAGE of extracted protein and isozyme profiling on native PAGE.After electrophoresis, each gel was stained with specific stains. Genetic distance relationships were evaluated based on the banding patterns of protein on isozymes.Unique banding pattern of esterase, peroxidase, acid phosphatase, alcohol dehydrogenase and polyphenol oxidase are observed in all the five species of Memecylon, which represent the fingerprint of Memecylon species.SDS-PAGE and isozyme profiling of five Memecylon species revealed that M. malabaricum and M. wightii grouped in one cluster and M. umbellatum, M. edule and M. talbotianum grouped in another cluster showing close genetic similarities which is in accordance with the morphological identification of Memecylon species.This is the first report on the comparison of protein and isozyme profile of five different Memecylon species. Abbreviations Used: SDS-PAGE: Sodium docecyl sulfate polyacrylamide gel electrophoresis; NTSYS PC2: Numerical taxonomy system, version 2.2 for Windows XP, Vista, Win7, Win 8 and Win10 including 64 bit PMID:29263637

Absolute Quantification of Selected Proteins in the Human Osteoarthritic Secretome

PubMed Central

Peffers, Mandy J.; Beynon, Robert J.; Clegg, Peter D.

2013-01-01

Osteoarthritis (OA) is characterized by a loss of extracellular matrix which is driven by catabolic cytokines. Proteomic analysis of the OA cartilage secretome enables the global study of secreted proteins. These are an important class of molecules with roles in numerous pathological mechanisms. Although cartilage studies have identified profiles of secreted proteins, quantitative proteomics techniques have been implemented that would enable further biological questions to be addressed. To overcome this limitation, we used the secretome from human OA cartilage explants stimulated with IL-1β and compared proteins released into the media using a label-free LC-MS/MS-based strategy. We employed QconCAT technology to quantify specific proteins using selected reaction monitoring. A total of 252 proteins were identified, nine were differentially expressed by IL-1 β stimulation. Selected protein candidates were quantified in absolute amounts using QconCAT. These findings confirmed a significant reduction in TIMP-1 in the secretome following IL-1β stimulation. Label-free and QconCAT analysis produced equivocal results indicating no effect of cytokine stimulation on aggrecan, cartilage oligomeric matrix protein, fibromodulin, matrix metalloproteinases 1 and 3 or plasminogen release. This study enabled comparative protein profiling and absolute quantification of proteins involved in molecular pathways pertinent to understanding the pathogenesis of OA. PMID:24132152

Proteomic Profiling of De Novo Protein Synthesis in Starvation-Induced Autophagy Using Bioorthogonal Noncanonical Amino Acid Tagging.

PubMed

Zhang, J; Wang, J; Lee, Y-M; Lim, T-K; Lin, Q; Shen, H-M

2017-01-01

Autophagy is an intracellular degradation process activated by stress factors such as nutrient starvation to maintain cellular homeostasis. There is emerging evidence demonstrating that de novo protein synthesis is involved in the autophagic process. However, up-to-date characterizing of these de novo proteins is technically difficult. In this chapter, we describe a novel method to identify newly synthesized proteins during starvation-mediated autophagy by bioorthogonal noncanonical amino acid tagging (BONCAT), in conjunction with isobaric tagging for relative and absolute quantification (iTRAQ)-based quantitative proteomics. l-azidohomoalanine (AHA) is an analog of methionine, and it can be readily incorporated into the newly synthesized proteins. The AHA-containing proteins can be enriched with avidin beads after a "click" reaction between alkyne-bearing biotin and the azide moiety of AHA. The enriched proteins are then subjected to iTRAQ™ labeling for protein identification and quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). By using this technique, we have successfully profiled more than 700 proteins that are synthesized during starvation-induced autophagy. We believe that this approach is effective in identification of newly synthesized proteins in the process of autophagy and provides useful insights to the molecular mechanisms and biological functions of autophagy. © 2017 Elsevier Inc. All rights reserved.

Investigating the Importance of the Pocket-estimation Method in Pocket-based Approaches: An Illustration Using Pocket-ligand Classification.

PubMed

Caumes, Géraldine; Borrel, Alexandre; Abi Hussein, Hiba; Camproux, Anne-Claude; Regad, Leslie

2017-09-01

Small molecules interact with their protein target on surface cavities known as binding pockets. Pocket-based approaches are very useful in all of the phases of drug design. Their first step is estimating the binding pocket based on protein structure. The available pocket-estimation methods produce different pockets for the same target. The aim of this work is to investigate the effects of different pocket-estimation methods on the results of pocket-based approaches. We focused on the effect of three pocket-estimation methods on a pocket-ligand (PL) classification. This pocket-based approach is useful for understanding the correspondence between the pocket and ligand spaces and to develop pharmacological profiling models. We found pocket-estimation methods yield different binding pockets in terms of boundaries and properties. These differences are responsible for the variation in the PL classification results that can have an impact on the detected correspondence between pocket and ligand profiles. Thus, we highlighted the importance of the pocket-estimation method choice in pocket-based approaches. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Oral delivery of peptides and proteins using lipid-based drug delivery systems.

PubMed

Li, Ping; Nielsen, Hanne Mørck; Müllertz, Anette

2012-10-01

In order to successfully develop lipid-based drug delivery systems (DDS) for oral administration of peptides and proteins, it is important to gain an understanding of the colloid structures formed by these DDS, the mode of peptide and protein incorporation as well as the mechanism by which intestinal absorption of peptides and proteins is promoted. The present paper reviews the literature on lipid-based DDS, employed for oral delivery of peptides and proteins and highlights the mechanisms by which the different lipid-based carriers are expected to overcome the two most important barriers (extensive enzymatic degradation and poor transmucosal permeability). This paper also gives a clear-cut idea about advantages and drawbacks of using different lipidic colloidal carriers ((micro)emulsions, solid lipid core particles and liposomes) for oral delivery of peptides and proteins. Lipid-based DDS are safe and suitable for oral delivery of peptides and proteins. Significant progress has been made in this area with several technologies on clinical trials. However, a better understanding of the mechanism of action in vivo is needed in order to improve the design and development of lipid-based DDS with the desired bioavailability and therapeutic profile.

The Urinary Bladder Transcriptome and Proteome Defined by Transcriptomics and Antibody-Based Profiling

PubMed Central

Habuka, Masato; Fagerberg, Linn; Hallström, Björn M.; Pontén, Fredrik; Yamamoto, Tadashi; Uhlen, Mathias

2015-01-01

To understand functions and diseases of urinary bladder, it is important to define its molecular constituents and their roles in urinary bladder biology. Here, we performed genome-wide deep RNA sequencing analysis of human urinary bladder samples and identified genes up-regulated in the urinary bladder by comparing the transcriptome data to those of all other major human tissue types. 90 protein-coding genes were elevated in the urinary bladder, either with enhanced expression uniquely in the urinary bladder or elevated expression together with at least one other tissue (group enriched). We further examined the localization of these proteins by immunohistochemistry and tissue microarrays and 20 of these 90 proteins were localized to the whole urothelium with a majority not yet described in the context of the urinary bladder. Four additional proteins were found specifically in the umbrella cells (Uroplakin 1a, 2, 3a, and 3b), and three in the intermediate/basal cells (KRT17, PCP4L1 and ATP1A4). 61 of the 90 elevated genes have not been previously described in the context of urinary bladder and the corresponding proteins are interesting targets for more in-depth studies. In summary, an integrated omics approach using transcriptomics and antibody-based profiling has been used to define a comprehensive list of proteins elevated in the urinary bladder. PMID:26694548

Rapid Inhibition Profiling in Bacillus subtilis to Identify the Mechanism of Action of New Antimicrobials.

PubMed

Lamsa, Anne; Lopez-Garrido, Javier; Quach, Diana; Riley, Eammon P; Pogliano, Joe; Pogliano, Kit

2016-08-19

Increasing antimicrobial resistance has become a major public health crisis. New antimicrobials with novel mechanisms of action (MOA) are desperately needed. We previously developed a method, bacterial cytological profiling (BCP), which utilizes fluorescence microscopy to rapidly identify the MOA of antimicrobial compounds. BCP is based upon our discovery that cells treated with antibiotics affecting different metabolic pathways generate different cytological signatures, providing quantitative information that can be used to determine a compound's MOA. Here, we describe a system, rapid inhibition profiling (RIP), for creating cytological profiles of new antibiotic targets for which there are currently no chemical inhibitors. RIP consists of the fast, inducible degradation of a target protein followed by BCP. We demonstrate that degrading essential proteins in the major metabolic pathways for DNA replication, transcription, fatty acid biosynthesis, and peptidoglycan biogenesis in Bacillus subtilis rapidly produces cytological profiles closely matching that of antimicrobials targeting the same pathways. Additionally, RIP and antibiotics targeting different steps in fatty acid biosynthesis can be differentiated from each other. We utilize RIP and BCP to show that the antibacterial MOA of four nonsteroidal anti-inflammatory antibiotics differs from that proposed based on in vitro data. RIP is a versatile method that will extend our knowledge of phenotypes associated with inactivating essential bacterial enzymes and thereby allow for screening for molecules that inhibit novel essential targets.

Distinct changes in the proteome profile of endometrial tissues in polycystic ovary syndrome compared with healthy fertile women.

PubMed

Amjadi, Fatemehsadat; Mehdizadeh, Mehdi; Ashrafi, Mahnaz; Nasrabadi, Davood; Taleahmad, Sara; Mirzaei, Mehdi; Gupta, Vivek; Salekdeh, Ghasem Hosseini; Aflatoonian, Reza

2018-04-21

What is the molecular basis of infertility related to uterine dysfunction in women with polycystic ovary syndrome (PCOS)? In this study, differences in protein expression between PCOS and normal endometrium were identified using a proteomic approach based on two-dimensional electrophoresis (2-DE) coupled with mass spectrometry (MS). The proteome of endometrium were analysed during the proliferative (on day 2 or 3 before ovulation, n = 6) and luteal phases (on day 3-5 after ovulation, n = 6) from healthy women and PCOS patients (12-14 days after spontaneous bleeding, n = 12). The differentially expressed proteins were categorized based on the biological process using the DAVID bioinformatics resources. Over 803 reproducible protein spots were detected on gels, and 150 protein spots showed different intensities between PCOS and normal women during the proliferative and luteal phases. MS analysis detected 70 proteins out of 150 spots. For four of the 70 proteins, 14-3-3 protein, annexin A5, SERPINA1 and cathepsin D, 2-DE results were validated and localized by Western blot and immunohistochemistry, respectively, and their gene expression profiles were confirmed by real-time quantitative PCR. The obtained results corresponded to the proteomic analysis. The differentially expressed proteins identified are known to be involved in apoptosis, oxidative stress, inflammation and the cytoskeleton. The processes related to the differentially expressed proteins play important roles in fecundity and fecundability. The present study may reveal the cause of various endometrial aberrations as a limiting factor for achieving pregnancy in PCOS women. Copyright © 2018 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

hBfl-1/hNOXA Interaction Studies Provide New Insights on the Role of Bfl-1 in Cancer Cell Resistance and for the Design of Novel Anticancer Agents

PubMed Central

2016-01-01

Upregulation of antiapoptotic Bcl-2 proteins in certain tumors confers cancer cell resistance to chemotherapy or radiations. Members of the antiapoptotic Bcl-2 proteins, including Bcl-2, Mcl-1, Bcl-xL, Bcl-w, and Bfl-1, inhibit apoptosis by selectively binding to conserved α-helical regions, named BH3 domains, of pro-apoptotic proteins such as Bim, tBid, Bad, or NOXA. Five antiapoptotic proteins have been identified that interact with various selectivity with BH3 containing pro-apoptotic counterparts. Cancer cells present various and variable levels of these proteins, making the design of effective apoptosis based therapeutics challenging. Recently, BH3 profiling was introduced as a method to classify cancer cells based on their ability to resist apoptosis following exposure to selected BH3 peptides. However, these studies were based on binding affinities measured with model BH3 peptides and Bcl-2-proteins taken from mouse sequences. While the majority of these interactions are conserved between mice and humans, we found surprisingly that human NOXA binds to human Bfl-1 potently and covalently via conserved Cys residues, with over 2 orders of magnitude increased affinity over hMcl-1. Our data suggest that some assumptions of the original BH3 profiling need to be revisited and that perhaps further targeting efforts should be redirected toward Bfl-1, for which no suitable specific inhibitors or pharmacological tools have been reported. In this regard, we also describe the initial design and characterizations of novel covalent BH3-based agents that potently target Bfl-1. These molecules could provide a novel platform on which to design effective Bfl-1 targeting therapeutics. PMID:28026162

On the possibility of using polycrystalline material in the development of structure-based generic assays

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

Allaire, Marc, E-mail: allaire@bnl.gov; Moiseeva, Natalia; Botez, Cristian E.

The correlation coefficients calculated between raw powder diffraction profiles can be used to identify ligand-bound/unbound states of lysozyme. The discovery of ligands that bind specifically to a targeted protein benefits from the development of generic assays for high-throughput screening of a library of chemicals. Protein powder diffraction (PPD) has been proposed as a potential method for use as a structure-based assay for high-throughput screening applications. Building on this effort, powder samples of bound/unbound states of soluble hen-egg white lysozyme precipitated with sodium chloride were compared. The correlation coefficients calculated between the raw diffraction profiles were consistent with the known bindingmore » properties of the ligands and suggested that the PPD approach can be used even prior to a full description using stereochemically restrained Rietveld refinement.« less

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds.

PubMed

Feng, Yan; Mitchison, Timothy J; Bender, Andreas; Young, Daniel W; Tallarico, John A

2009-07-01

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

High-Resolution Free-Energy Landscape Analysis of α-Helical Protein Folding: HP35 and Its Double Mutant

PubMed Central

2013-01-01

The free-energy landscape can provide a quantitative description of folding dynamics, if determined as a function of an optimally chosen reaction coordinate. Here, we construct the optimal coordinate and the associated free-energy profile for all-helical proteins HP35 and its norleucine (Nle/Nle) double mutant, based on realistic equilibrium folding simulations [Piana et al. Proc. Natl. Acad. Sci. U.S.A.2012, 109, 17845]. From the obtained profiles, we directly determine such basic properties of folding dynamics as the configurations of the minima and transition states (TS), the formation of secondary structure and hydrophobic core during the folding process, the value of the pre-exponential factor and its relation to the transition path times, the relation between the autocorrelation times in TS and minima. We also present an investigation of the accuracy of the pre-exponential factor estimation based on the transition-path times. Four different estimations of the pre-exponential factor for both proteins give k0–1 values of approximately a few tens of nanoseconds. Our analysis gives detailed information about folding of the proteins and can serve as a rigorous common language for extensive comparison between experiment and simulation. PMID:24348206

High-Resolution Free-Energy Landscape Analysis of α-Helical Protein Folding: HP35 and Its Double Mutant.

PubMed

Banushkina, Polina V; Krivov, Sergei V

2013-12-10

The free-energy landscape can provide a quantitative description of folding dynamics, if determined as a function of an optimally chosen reaction coordinate. Here, we construct the optimal coordinate and the associated free-energy profile for all-helical proteins HP35 and its norleucine (Nle/Nle) double mutant, based on realistic equilibrium folding simulations [Piana et al. Proc. Natl. Acad. Sci. U.S.A. 2012 , 109 , 17845]. From the obtained profiles, we directly determine such basic properties of folding dynamics as the configurations of the minima and transition states (TS), the formation of secondary structure and hydrophobic core during the folding process, the value of the pre-exponential factor and its relation to the transition path times, the relation between the autocorrelation times in TS and minima. We also present an investigation of the accuracy of the pre-exponential factor estimation based on the transition-path times. Four different estimations of the pre-exponential factor for both proteins give k 0 -1 values of approximately a few tens of nanoseconds. Our analysis gives detailed information about folding of the proteins and can serve as a rigorous common language for extensive comparison between experiment and simulation.

Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle.

PubMed

Zhang, Kai; Tang, Chaohua; Liang, Xiaowei; Zhao, Qingyu; Zhang, Junmin

2018-01-10

Salbutamol, a selective β 2 -agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

An integrated microfluidic chip system for single-cell secretion profiling of rare circulating tumor cells.

PubMed

Deng, Yuliang; Zhang, Yu; Sun, Shuai; Wang, Zhihua; Wang, Minjiao; Yu, Beiqin; Czajkowsky, Daniel M; Liu, Bingya; Li, Yan; Wei, Wei; Shi, Qihui

2014-12-16

Genetic and transcriptional profiling, as well as surface marker identification of single circulating tumor cells (CTCs) have been demonstrated. However, quantitatively profiling of functional proteins at single CTC resolution has not yet been achieved, owing to the limited purity of the isolated CTC populations and a lack of single-cell proteomic approaches to handle and analyze rare CTCs. Here, we develop an integrated microfluidic system specifically designed for streamlining isolation, purification and single-cell secretomic profiling of CTCs from whole blood. Key to this platform is the use of photocleavable ssDNA-encoded antibody conjugates to enable a highly purified CTC population with <75 'contaminated' blood cells. An enhanced poly-L-lysine barcode pattern is created on the single-cell barcode chip for efficient capture rare CTC cells in microchambers for subsequent secreted protein profiling. This system was extensively evaluated and optimized with EpCAM-positive HCT116 cells seeded into whole blood. Patient blood samples were employed to assess the utility of the system for isolation, purification and single-cell secretion profiling of CTCs. The CTCs present in patient blood samples exhibit highly heterogeneous secretion profile of IL-8 and VEGF. The numbers of secreting CTCs are found not in accordance with CTC enumeration based on immunostaining in the parallel experiments.

An Integrated Microfluidic Chip System for Single-Cell Secretion Profiling of Rare Circulating Tumor Cells

PubMed Central

Deng, Yuliang; Zhang, Yu; Sun, Shuai; Wang, Zhihua; Wang, Minjiao; Yu, Beiqin; Czajkowsky, Daniel M.; Liu, Bingya; Li, Yan; Wei, Wei; Shi, Qihui

2014-01-01

Genetic and transcriptional profiling, as well as surface marker identification of single circulating tumor cells (CTCs) have been demonstrated. However, quantitatively profiling of functional proteins at single CTC resolution has not yet been achieved, owing to the limited purity of the isolated CTC populations and a lack of single-cell proteomic approaches to handle and analyze rare CTCs. Here, we develop an integrated microfluidic system specifically designed for streamlining isolation, purification and single-cell secretomic profiling of CTCs from whole blood. Key to this platform is the use of photocleavable ssDNA-encoded antibody conjugates to enable a highly purified CTC population with <75 ‘contaminated' blood cells. An enhanced poly-L-lysine barcode pattern is created on the single-cell barcode chip for efficient capture rare CTC cells in microchambers for subsequent secreted protein profiling. This system was extensively evaluated and optimized with EpCAM-positive HCT116 cells seeded into whole blood. Patient blood samples were employed to assess the utility of the system for isolation, purification and single-cell secretion profiling of CTCs. The CTCs present in patient blood samples exhibit highly heterogeneous secretion profile of IL-8 and VEGF. The numbers of secreting CTCs are found not in accordance with CTC enumeration based on immunostaining in the parallel experiments. PMID:25511131

Evaluating the protein coding potential of exonized transposable element sequences

PubMed Central

Piriyapongsa, Jittima; Rutledge, Mark T; Patel, Sanil; Borodovsky, Mark; Jordan, I King

2007-01-01

Background Transposable element (TE) sequences, once thought to be merely selfish or parasitic members of the genomic community, have been shown to contribute a wide variety of functional sequences to their host genomes. Analysis of complete genome sequences have turned up numerous cases where TE sequences have been incorporated as exons into mRNAs, and it is widely assumed that such 'exonized' TEs encode protein sequences. However, the extent to which TE-derived sequences actually encode proteins is unknown and a matter of some controversy. We have tried to address this outstanding issue from two perspectives: i-by evaluating ascertainment biases related to the search methods used to uncover TE-derived protein coding sequences (CDS) and ii-through a probabilistic codon-frequency based analysis of the protein coding potential of TE-derived exons. Results We compared the ability of three classes of sequence similarity search methods to detect TE-derived sequences among data sets of experimentally characterized proteins: 1-a profile-based hidden Markov model (HMM) approach, 2-BLAST methods and 3-RepeatMasker. Profile based methods are more sensitive and more selective than the other methods evaluated. However, the application of profile-based search methods to the detection of TE-derived sequences among well-curated experimentally characterized protein data sets did not turn up many more cases than had been previously detected and nowhere near as many cases as recent genome-wide searches have. We observed that the different search methods used were complementary in the sense that they yielded largely non-overlapping sets of hits and differed in their ability to recover known cases of TE-derived CDS. The probabilistic analysis of TE-derived exon sequences indicates that these sequences have low protein coding potential on average. In particular, non-autonomous TEs that do not encode protein sequences, such as Alu elements, are frequently exonized but unlikely to encode protein sequences. Conclusion The exaptation of the numerous TE sequences found in exons as bona fide protein coding sequences may prove to be far less common than has been suggested by the analysis of complete genomes. We hypothesize that many exonized TE sequences actually function as post-transcriptional regulators of gene expression, rather than coding sequences, which may act through a variety of double stranded RNA related regulatory pathways. Indeed, their relatively high copy numbers and similarity to sequences dispersed throughout the genome suggests that exonized TE sequences could serve as master regulators with a wide scope of regulatory influence. Reviewers: This article was reviewed by Itai Yanai, Kateryna D. Makova, Melissa Wilson (nominated by Kateryna D. Makova) and Cedric Feschotte (nominated by John M. Logsdon Jr.). PMID:18036258

Protein Structure and Function Prediction Using I-TASSER

PubMed Central

Yang, Jianyi; Zhang, Yang

2016-01-01

I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. PMID:26678386

Multiplexed quantitation of protein expression and phosphorylation based on functionalized soluble nanopolymers

PubMed Central

Pan, Li; Iliuk, Anton; Yu, Shuai; Geahlen, Robert L.; Tao, W. Andy

2012-01-01

We report here for the first time the multiplexed quantitation of phosphorylation and protein expression based on a functionalized soluble nanopolymer. The soluble nanopolymer, pIMAGO, is functionalized with Ti (IV) ions for chelating phosphoproteins in high specificity, and with infrared fluorescent tags for direct, multiplexed assays. The nanopolymer allows for direct competition for epitopes on proteins of interest, thus facilitating simultaneous detection of phosphorylation by pIMAGO and total protein amount by protein antibody in the same well of microplates. The new strategy has a great potential to measure cell signaling events by clearly distinguishing actual phosphorylation signals from protein expression changes, thus providing a powerful tool to accurately profile cellular signal transduction in healthy and disease cells. We anticipate broad applications of this new strategy in monitoring cellular signaling pathways and discovering new signaling events. PMID:23088311

ETMB-RBF: discrimination of metal-binding sites in electron transporters based on RBF networks with PSSM profiles and significant amino acid pairs.

PubMed

Ou, Yu-Yen; Chen, Shu-An; Wu, Sheng-Cheng

2013-01-01

Cellular respiration is the process by which cells obtain energy from glucose and is a very important biological process in living cell. As cells do cellular respiration, they need a pathway to store and transport electrons, the electron transport chain. The function of the electron transport chain is to produce a trans-membrane proton electrochemical gradient as a result of oxidation-reduction reactions. In these oxidation-reduction reactions in electron transport chains, metal ions play very important role as electron donor and acceptor. For example, Fe ions are in complex I and complex II, and Cu ions are in complex IV. Therefore, to identify metal-binding sites in electron transporters is an important issue in helping biologists better understand the workings of the electron transport chain. We propose a method based on Position Specific Scoring Matrix (PSSM) profiles and significant amino acid pairs to identify metal-binding residues in electron transport proteins. We have selected a non-redundant set of 55 metal-binding electron transport proteins as our dataset. The proposed method can predict metal-binding sites in electron transport proteins with an average 10-fold cross-validation accuracy of 93.2% and 93.1% for metal-binding cysteine and histidine, respectively. Compared with the general metal-binding predictor from A. Passerini et al., the proposed method can improve over 9% of sensitivity, and 14% specificity on the independent dataset in identifying metal-binding cysteines. The proposed method can also improve almost 76% sensitivity with same specificity in metal-binding histidine, and MCC is also improved from 0.28 to 0.88. We have developed a novel approach based on PSSM profiles and significant amino acid pairs for identifying metal-binding sites from electron transport proteins. The proposed approach achieved a significant improvement with independent test set of metal-binding electron transport proteins.

ETMB-RBF: Discrimination of Metal-Binding Sites in Electron Transporters Based on RBF Networks with PSSM Profiles and Significant Amino Acid Pairs

PubMed Central

Ou, Yu-Yen; Chen, Shu-An; Wu, Sheng-Cheng

2013-01-01

Background Cellular respiration is the process by which cells obtain energy from glucose and is a very important biological process in living cell. As cells do cellular respiration, they need a pathway to store and transport electrons, the electron transport chain. The function of the electron transport chain is to produce a trans-membrane proton electrochemical gradient as a result of oxidation–reduction reactions. In these oxidation–reduction reactions in electron transport chains, metal ions play very important role as electron donor and acceptor. For example, Fe ions are in complex I and complex II, and Cu ions are in complex IV. Therefore, to identify metal-binding sites in electron transporters is an important issue in helping biologists better understand the workings of the electron transport chain. Methods We propose a method based on Position Specific Scoring Matrix (PSSM) profiles and significant amino acid pairs to identify metal-binding residues in electron transport proteins. Results We have selected a non-redundant set of 55 metal-binding electron transport proteins as our dataset. The proposed method can predict metal-binding sites in electron transport proteins with an average 10-fold cross-validation accuracy of 93.2% and 93.1% for metal-binding cysteine and histidine, respectively. Compared with the general metal-binding predictor from A. Passerini et al., the proposed method can improve over 9% of sensitivity, and 14% specificity on the independent dataset in identifying metal-binding cysteines. The proposed method can also improve almost 76% sensitivity with same specificity in metal-binding histidine, and MCC is also improved from 0.28 to 0.88. Conclusions We have developed a novel approach based on PSSM profiles and significant amino acid pairs for identifying metal-binding sites from electron transport proteins. The proposed approach achieved a significant improvement with independent test set of metal-binding electron transport proteins. PMID:23405059

Insights into the immune manipulation mechanisms of pollen allergens by protein domain profiling.

PubMed

Patel, Seema; Rani, Aruna; Goyal, Arun

2017-10-01

Plant pollens are airborne allergens, as their inhalation causes immune activation, leading to rhinitis, conjunctivitis, sinusitis and oral allergy syndrome. A myriad of pollen proteins belonging to profilin, expansin, polygalacturonase, glucan endoglucosidase, pectin esterase, and lipid transfer protein class have been identified. In the present in silico study, the protein domains of fifteen pollen sequences were extracted from the UniProt database and submitted to the interactive web tool SMART (Simple Modular Architecture Research Tool), for finding the protein domain profiles. Analysis of the data based on custom-made scripts revealed the conservation of pathogenic domains such as OmpH, PROF, PreSET, Bet_v_1, Cpl-7 and GAS2. Further, the retention of critical domains like CHASE2, Galanin, Dak2, DALR_1, HAMP, PWI, EFh, Excalibur, CT, PbH1, HELICc, and Kelch in pollen proteins, much like cockroach allergens and lethal viruses (such as HIV, HCV, Ebola, Dengue and Zika) was observed. Based on the shared motifs in proteins of taxonomicall-ydispersed organisms, it can be hypothesized that allergens and pathogens manipulate the human immune system in a similar manner. Allergens, being inanimate, cannot replicate in human body, and are neutralized by immune system. But, when the allergens are unremitting, the immune system becomes persistently hyper-sensitized, creating an inflammatory milieu. This study is expected to contribute to the understanding of pollen allergenicity and pathogenicity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapid detection, classification and accurate alignment of up to a million or more related protein sequences.

PubMed

Neuwald, Andrew F

2009-08-01

The patterns of sequence similarity and divergence present within functionally diverse, evolutionarily related proteins contain implicit information about corresponding biochemical similarities and differences. A first step toward accessing such information is to statistically analyze these patterns, which, in turn, requires that one first identify and accurately align a very large set of protein sequences. Ideally, the set should include many distantly related, functionally divergent subgroups. Because it is extremely difficult, if not impossible for fully automated methods to align such sequences correctly, researchers often resort to manual curation based on detailed structural and biochemical information. However, multiply-aligning vast numbers of sequences in this way is clearly impractical. This problem is addressed using Multiply-Aligned Profiles for Global Alignment of Protein Sequences (MAPGAPS). The MAPGAPS program uses a set of multiply-aligned profiles both as a query to detect and classify related sequences and as a template to multiply-align the sequences. It relies on Karlin-Altschul statistics for sensitivity and on PSI-BLAST (and other) heuristics for speed. Using as input a carefully curated multiple-profile alignment for P-loop GTPases, MAPGAPS correctly aligned weakly conserved sequence motifs within 33 distantly related GTPases of known structure. By comparison, the sequence- and structurally based alignment methods hmmalign and PROMALS3D misaligned at least 11 and 23 of these regions, respectively. When applied to a dataset of 65 million protein sequences, MAPGAPS identified, classified and aligned (with comparable accuracy) nearly half a million putative P-loop GTPase sequences. A C++ implementation of MAPGAPS is available at http://mapgaps.igs.umaryland.edu. Supplementary data are available at Bioinformatics online.

Proteomic profiling of Pseudomonas aeruginosa AES-1R, PAO1 and PA14 reveals potential virulence determinants associated with a transmissible cystic fibrosis-associated strain

PubMed Central

2012-01-01

Background Pseudomonas aeruginosa is an opportunistic pathogen that is the major cause of morbidity and mortality in patients with cystic fibrosis (CF). While most CF patients are thought to acquire P. aeruginosa from the environment, person-person transmissible strains have been identified in CF clinics worldwide. The molecular basis for transmissibility and colonization of the CF lung remains poorly understood. Results A dual proteomics approach consisting of gel-based and gel-free comparisons were undertaken to analyse protein profiles in a transmissible, early (acute) isolate of the Australian epidemic strain 1 (AES-1R), the virulent burns/wound isolate PA14, and the poorly virulent, laboratory-associated strain PAO1. Over 1700 P. aeruginosa proteins were confidently identified. AES-1R protein profiles revealed elevated abundance of proteins associated with virulence and siderophore biosynthesis and acquisition, antibiotic resistance and lipopolysaccharide and fatty acid biosynthesis. The most abundant protein in AES-1R was confirmed as a previously hypothetical protein with sequence similarity to carbohydrate-binding proteins and database search revealed this gene is only found in the CF-associated strain PA2192. The link with CF infection may suggest that transmissible strains have acquired an ability to rapidly interact with host mucosal glycoproteins. Conclusions Our data suggest that AES-1R expresses higher levels of proteins, such as those involved in antibiotic resistance, iron acquisition and virulence that may provide a competitive advantage during early infection in the CF lung. Identification of novel proteins associated with transmissibility and acute infection may aid in deciphering new strategies for intervention to limit P. aeruginosa infections in CF patients. PMID:22264352

Proteomic profiling of Pseudomonas aeruginosa AES-1R, PAO1 and PA14 reveals potential virulence determinants associated with a transmissible cystic fibrosis-associated strain.

PubMed

Hare, Nathan J; Solis, Nestor; Harmer, Christopher; Marzook, N Bishara; Rose, Barbara; Harbour, Colin; Crossett, Ben; Manos, Jim; Cordwell, Stuart J

2012-01-22

Pseudomonas aeruginosa is an opportunistic pathogen that is the major cause of morbidity and mortality in patients with cystic fibrosis (CF). While most CF patients are thought to acquire P. aeruginosa from the environment, person-person transmissible strains have been identified in CF clinics worldwide. The molecular basis for transmissibility and colonization of the CF lung remains poorly understood. A dual proteomics approach consisting of gel-based and gel-free comparisons were undertaken to analyse protein profiles in a transmissible, early (acute) isolate of the Australian epidemic strain 1 (AES-1R), the virulent burns/wound isolate PA14, and the poorly virulent, laboratory-associated strain PAO1. Over 1700 P. aeruginosa proteins were confidently identified. AES-1R protein profiles revealed elevated abundance of proteins associated with virulence and siderophore biosynthesis and acquisition, antibiotic resistance and lipopolysaccharide and fatty acid biosynthesis. The most abundant protein in AES-1R was confirmed as a previously hypothetical protein with sequence similarity to carbohydrate-binding proteins and database search revealed this gene is only found in the CF-associated strain PA2192. The link with CF infection may suggest that transmissible strains have acquired an ability to rapidly interact with host mucosal glycoproteins. Our data suggest that AES-1R expresses higher levels of proteins, such as those involved in antibiotic resistance, iron acquisition and virulence that may provide a competitive advantage during early infection in the CF lung. Identification of novel proteins associated with transmissibility and acute infection may aid in deciphering new strategies for intervention to limit P. aeruginosa infections in CF patients.

Systematic Cell-Based Phenotyping of Missense Alleles Empowers Rare Variant Association Studies: A Case for LDLR and Myocardial Infarction

PubMed Central

Schuberth, Christian; Won, Hong-Hee; Blattmann, Peter; Joggerst-Thomalla, Brigitte; Theiss, Susanne; Asselta, Rosanna; Duga, Stefano; Merlini, Pier Angelica; Ardissino, Diego; Lander, Eric S.; Gabriel, Stacey; Rader, Daniel J.; Peloso, Gina M.; Kathiresan, Sekar; Runz, Heiko

2015-01-01

A fundamental challenge to contemporary genetics is to distinguish rare missense alleles that disrupt protein functions from the majority of alleles neutral on protein activities. High-throughput experimental tools to securely discriminate between disruptive and non-disruptive missense alleles are currently missing. Here we establish a scalable cell-based strategy to profile the biological effects and likely disease relevance of rare missense variants in vitro. We apply this strategy to systematically characterize missense alleles in the low-density lipoprotein receptor (LDLR) gene identified through exome sequencing of 3,235 individuals and exome-chip profiling of 39,186 individuals. Our strategy reliably identifies disruptive missense alleles, and disruptive-allele carriers have higher plasma LDL-cholesterol (LDL-C). Importantly, considering experimental data refined the risk of rare LDLR allele carriers from 4.5- to 25.3-fold for high LDL-C, and from 2.1- to 20-fold for early-onset myocardial infarction. Our study generates proof-of-concept that systematic functional variant profiling may empower rare variant-association studies by orders of magnitude. PMID:25647241

Extracting physicochemical features to predict protein secondary structure.

PubMed

Huang, Yin-Fu; Chen, Shu-Ying

2013-01-01

We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we train the SVM using the PSSM profiles generated from PSI-BLAST and the physicochemical features extracted from the CB513 data set. Finally, we use the filter to refine the predicted results from the trained SVM. For all the performance measures of our method, Q 3 reaches 79.52, SOV94 reaches 86.10, and SOV99 reaches 74.60; all the measures are higher than those of the SVMpsi method and the SVMfreq method. This validates that considering these physicochemical features in predicting protein secondary structure would exhibit better performances.

Extracting Physicochemical Features to Predict Protein Secondary Structure

PubMed Central

Chen, Shu-Ying

2013-01-01

We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we train the SVM using the PSSM profiles generated from PSI-BLAST and the physicochemical features extracted from the CB513 data set. Finally, we use the filter to refine the predicted results from the trained SVM. For all the performance measures of our method, Q 3 reaches 79.52, SOV94 reaches 86.10, and SOV99 reaches 74.60; all the measures are higher than those of the SVMpsi method and the SVMfreq method. This validates that considering these physicochemical features in predicting protein secondary structure would exhibit better performances. PMID:23766688

Impact of exposure to low concentrations of nitric oxide on protein profile in murine and human pancreatic islet cells

PubMed Central

Tapia-Limonchi, Rafael; Díaz, Irene; Cahuana, Gladys M; Bautista, Mario; Martín, Franz; Soria, Bernat; Tejedo, Juan R; Bedoya, Francisco J

2014-01-01

Homeostatic levels of nitric oxide (NO) protect efficiently against apoptotic death in both human and rodent pancreatic β cells, but the protein profile of this action remains to be determined. We have applied a 2 dimensional LC-MS-MALDI-TOF/TOF-based analysis to study the impact of protective NO in rat insulin-producing RINm5F cell line and in mouse and human pancreatic islets (HPI) exposed to serum deprivation condition. 24 proteins in RINm5F and 22 in HPI were identified to undergo changes in at least one experimental condition. These include stress response mitochondrial proteins (UQCRC2, VDAC1, ATP5C1, ATP5A1) in RINm5F cells and stress response endoplasmic reticulum proteins (HSPA5, PDIA6, VCP, GANAB) in HPI. In addition, metabolic and structural proteins, oxidoreductases and chaperones related with protein metabolism are also regulated by NO treatment. Network analysis of differentially expressed proteins shows their interaction in glucocorticoid receptor and NRF2-mediated oxidative stress response pathways and eNOS signaling. The results indicate that exposure to exogenous NO counteracts the impact of serum deprivation on pancreatic β cell proteome. Species differences in the proteins involved are apparent. PMID:25658244

The application of multiple reaction monitoring and multi-analyte profiling to HDL proteins

PubMed Central

2014-01-01

Background HDL carries a rich protein cargo and examining HDL protein composition promises to improve our understanding of its functions. Conventional mass spectrometry methods can be lengthy and difficult to extend to large populations. In addition, without prior enrichment of the sample, the ability of these methods to detect low abundance proteins is limited. Our objective was to develop a high-throughput approach to examine HDL protein composition applicable to diabetes and cardiovascular disease (CVD). Methods We optimized two multiplexed assays to examine HDL proteins using a quantitative immunoassay (Multi-Analyte Profiling- MAP) and mass spectrometric-based quantitative proteomics (Multiple Reaction Monitoring-MRM). We screened HDL proteins using human xMAP (90 protein panel) and MRM (56 protein panel). We extended the application of these two methods to HDL isolated from a group of participants with diabetes and prior cardiovascular events and a group of non-diabetic controls. Results We were able to quantitate 69 HDL proteins using MAP and 32 proteins using MRM. For several common proteins, the use of MRM and MAP was highly correlated (p < 0.01). Using MAP, several low abundance proteins implicated in atherosclerosis and inflammation were found on HDL. On the other hand, MRM allowed the examination of several HDL proteins not available by MAP. Conclusions MAP and MRM offer a sensitive and high-throughput approach to examine changes in HDL proteins in diabetes and CVD. This approach can be used to measure the presented HDL proteins in large clinical studies. PMID:24397693

An Update on ToxCast™

EPA Science Inventory

In its first phase, ToxCast™ is profiling over 300 well-characterized chemicals (primarily pesticides) in over 400 HTS endpoints. These endpoints include biochemical assays of protein function, cell-based transcriptional reporter assays, multi-cell interaction assays, transcripto...

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

PubMed

Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

2017-02-01

Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris

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

Zhang, Weiwen; Culley, David E.; Gritsenko, Marina A.

2006-11-03

ABSTRACT In the previous study, the whole-genome gene expression profiles of D. vulgaris in response to oxidative stress and heat shock were determined. The results showed 24-28% of the responsive genes were hypothetical proteins that have not been experimentally characterized or whose function can not be deduced by simple sequence comparison. To further explore the protecting mechanisms employed in D. vulgaris against the oxidative stress and heat shock, attempt was made in this study to infer functions of these hypothetical proteins by phylogenomic profiling along with detailed sequence comparison against various publicly available databases. By this approach we were abletomore » assign possible functions to 25 responsive hypothetical proteins. The findings included that DVU0725, induced by oxidative stress, may be involved in lipopolysaccharide biosynthesis, implying that the alternation of lipopolysaccharide on cell surface might service as a mechanism against oxidative stress in D. vulgaris. In addition, two responsive proteins, DVU0024 encoding a putative transcriptional regulator and DVU1670 encoding predicted redox protein, were sharing co-evolution atterns with rubrerythrin in Archaeoglobus fulgidus and Clostridium perfringens, respectively, implying that they might be part of the stress response and protective systems in D. vulgaris. The study demonstrated that phylogenomic profiling is a useful tool in interpretation of experimental genomics data, and also provided further insight on cellular response to oxidative stress and heat shock in D. vulgaris.« less

Effect of sprouted barley grain supplementation of an herbage-based or haylage-based diet on ruminal fermentation and methane output in continuous culture

USDA-ARS?s Scientific Manuscript database

A 4-unit dual-flow continuous culture fermentor system was used to assess the effect of supplementing 7-d sprouted barley (SB) or barley grain (BG) with an herbage-based or haylage-based diet on nutrient digestibility, volatile fatty acid (VFA) profiles, bacterial protein synthesis, and methane outp...

A transcriptome-based assessment of the astrocytic dystrophin-associated complex in the developing human brain.

PubMed

Simon, Matthew J; Murchison, Charles; Iliff, Jeffrey J

2018-02-01

Astrocytes play a critical role in regulating the interface between the cerebral vasculature and the central nervous system. Contributing to this is the astrocytic endfoot domain, a specialized structure that ensheathes the entirety of the vasculature and mediates signaling between endothelial cells, pericytes, and neurons. The astrocytic endfoot has been implicated as a critical element of the glymphatic pathway, and changes in protein expression profiles in this cellular domain are linked to Alzheimer's disease pathology. Despite this, basic physiological properties of this structure remain poorly understood including the developmental timing of its formation, and the protein components that localize there to mediate its functions. Here we use human transcriptome data from male and female subjects across several developmental stages and brain regions to characterize the gene expression profile of the dystrophin-associated complex (DAC), a known structural component of the astrocytic endfoot that supports perivascular localization of the astroglial water channel aquaporin-4. Transcriptomic profiling is also used to define genes exhibiting parallel expression profiles to DAC elements, generating a pool of candidate genes that encode gene products that may contribute to the physiological function of the perivascular astrocytic endfoot domain. We found that several genes encoding transporter proteins are transcriptionally associated with DAC genes. © 2017 Wiley Periodicals, Inc.

Profiling and characterization of sialylated N-glycans by 2D-HPLC (HIAX/PGC) with online orbitrap MS/MS and offline MSn.

PubMed

Hanneman, Andrew J S; Strand, James; Huang, Chi-Ting

2014-02-01

Glycosylation is a critical parameter used to evaluate protein quality and consistency. N-linked glycan profiling is fundamental to the support of biotherapeutic protein manufacturing from early stage process development through drug product commercialization. Sialylated glycans impact the serum half-life of receptor-Fc fusion proteins (RFPs), making their quality and consistency a concern during the production of fusion proteins. Here, we describe an analytical approach providing both quantitative profiling and in-depth mass spectrometry (MS)-based structural characterization of sialylated RFP N-glycans. Aiming to efficiently link routine comparability studies with detailed structural characterization, an integrated workflow was implemented employing fluorescence detection, online positive and negative ion tandem mass spectrometry (MS/MS), and offline static nanospray ionization-sequential mass spectrometry (NSI-MS(n)). For routine use, high-performance liquid chromatography profiling employs established fluorescence detection of 2-aminobenzoic acid derivatives (2AA) and hydrophilic interaction anion-exchange chromatography (HIAX) charge class separation. Further characterization of HIAX peak fractions is achieved by online (-) ion orbitrap MS/MS, offering the advantages of high mass accuracy and data-dependent MS/MS. As required, additional characterization uses porous graphitized carbon in the second chromatographic dimension to provide orthogonal (+) ion MS/MS spectra and buffer-free liquid chromatography peak eluants that are optimum for offline (+)/(-) NSI-MS(n) investigations to characterize low-abundance species and specific moieties including O-acetylation and sulfation. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) is a novel biomarker of myxofibrosarcoma invasion identified by global protein expression profiling.

PubMed

Kikuta, Kazutaka; Kubota, Daisuke; Yoshida, Akihiko; Qiao, Zhiwei; Morioka, Hideo; Nakamura, Masaya; Matsumoto, Morio; Chuman, Hirokazu; Kawai, Akira; Kondo, Tadashi

2017-09-01

Myxofibrosarcoma (MFS) is a mesenchymal malignancy characterized by frequent recurrence even after radical wide resection. To optimize therapy for MFS patients, we aimed to identify candidate tissue biomarkers of MFS invasion potential. Invasion characteristics of MFS were evaluated by magnetic resonance imaging and protein expression profiling of primary tumor tissues performed using two-dimensional difference gel electrophoresis (2D-DIGE). Protein expression profiles were compared between invasive and non-invasive tumors surgically resected from 11 patients. Among the 3453 protein spots observed, 59 demonstrated statistically significant difference in intensity (≥2-fold) between invasive and non-invasive tumors (p<0.01 by Wilkoxon test), and were identified by mass spectrometry as 47 individual proteins. Among them, we further focused on discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2), a receptor tyrosine kinase with aberrant expression in malignant tumors. Immunohistochemistry analysis of 21 additional MFS cases revealed that higher DCBLD2 expression was significantly associated with invasive properties of tumor cells. DCBLD2 sensitivity and specificity, and positive and negative predictive values for MFS invasion were 69.2%, 87.5%, 90%, and 63.6%, respectively. The expression level of DCBLD2 was consistent in different portions of tumor tissues. Thus, DCBLD2 expression can be a useful biomarker to evaluate invasive properties of MFS. Further validation studies based on multi-institutional collaboration and comprehensive analysis of DCBLD2 biological functions in MFS are required to confirm its prognostic utility for clinical application. Copyright © 2017 Elsevier B.V. All rights reserved.

Interactions of corn meal or molasses with a soybean-sunflower meal mix or flaxseed meal on production, milk fatty acids composition, and nutrient utilization in dairy cows fed grass hay-based diets

USDA-ARS?s Scientific Manuscript database

We investigated the interactions of molasses or corn meal [nonstructural carbohydrate (NSC) sources] with flaxseed meal or a soybean-sunflower meal protein mix [rumen-degradable protein (RDP) sources] on animal production, milk fatty acids profile, and nutrient utilization in organic Jersey cows fed...

Biosensor-based small molecule fragment screening with biolayer interferometry

NASA Astrophysics Data System (ADS)

Wartchow, Charles A.; Podlaski, Frank; Li, Shirley; Rowan, Karen; Zhang, Xiaolei; Mark, David; Huang, Kuo-Sen

2011-07-01

Biosensor-based fragment screening is a valuable tool in the drug discovery process. This method is advantageous over many biochemical methods because primary hits can be distinguished from non-specific or non-ideal interactions by examining binding profiles and responses, resulting in reduced false-positive rates. Biolayer interferometry (BLI), a technique that measures changes in an interference pattern generated from visible light reflected from an optical layer and a biolayer containing proteins of interest, is a relatively new method for monitoring small molecule interactions. The BLI format is based on a disposable sensor that is immersed in 96-well or 384-well plates. BLI has been validated for small molecule detection and fragment screening with model systems and well-characterized targets where affinity constants and binding profiles are generally similar to those obtained with surface plasmon resonsance (SPR). Screens with challenging targets involved in protein-protein interactions including BCL-2, JNK1, and eIF4E were performed with a fragment library of 6,500 compounds, and hit rates were compared for these targets. For eIF4E, a protein containing a PPI site and a nucleotide binding site, results from a BLI fragment screen were compared to results obtained in biochemical HTS screens. Overlapping hits were observed for the PPI site, and hits unique to the BLI screen were identified. Hit assessments with SPR and BLI are described.

LOCSVMPSI: a web server for subcellular localization of eukaryotic proteins using SVM and profile of PSI-BLAST

PubMed Central

Xie, Dan; Li, Ao; Wang, Minghui; Fan, Zhewen; Feng, Huanqing

2005-01-01

Subcellular location of a protein is one of the key functional characters as proteins must be localized correctly at the subcellular level to have normal biological function. In this paper, a novel method named LOCSVMPSI has been introduced, which is based on the support vector machine (SVM) and the position-specific scoring matrix generated from profiles of PSI-BLAST. With a jackknife test on the RH2427 data set, LOCSVMPSI achieved a high overall prediction accuracy of 90.2%, which is higher than the prediction results by SubLoc and ESLpred on this data set. In addition, prediction performance of LOCSVMPSI was evaluated with 5-fold cross validation test on the PK7579 data set and the prediction results were consistently better than the previous method based on several SVMs using composition of both amino acids and amino acid pairs. Further test on the SWISSPROT new-unique data set showed that LOCSVMPSI also performed better than some widely used prediction methods, such as PSORTII, TargetP and LOCnet. All these results indicate that LOCSVMPSI is a powerful tool for the prediction of eukaryotic protein subcellular localization. An online web server (current version is 1.3) based on this method has been developed and is freely available to both academic and commercial users, which can be accessed by at . PMID:15980436

Cassava (Manihot esculenta Krantz) genome harbors KNOX genes differentially expressed during storage root development.

PubMed

Guo, D; Li, H L; Tang, X; Peng, S Q

2014-12-18

In plants, homeodomain proteins play a critical role in regulating various aspects of plant growth and development. KNOX proteins are members of the homeodomain protein family. The KNOX transcription factors have been reported from Arabidopsis, rice, and other higher plants. The recent publication of the draft genome sequence of cassava (Manihot esculenta Krantz) has allowed a genome-wide search for M. esculenta KNOX (MeKNOX) transcription factors and the comparison of these positively identified proteins with their homologs in model plants. In the present study, we identified 12 MeKNOX genes in the cassava genome and grouped them into two distinct subfamilies based on their domain composition and phylogenetic analysis. Furthermore, semi-quantitative reverse transcription polymerase chain reaction analysis was performed to elucidate the expression profiles of these genes in different tissues and during various stages of root development. The analysis of MeKNOX expression profiles of indicated that 12 MeKNOX genes display differential expressions either in their transcript abundance or expression patterns.

Metal Ion-Induced Self-Assembly of a Multi-Responsive Block Copolypeptide into Well-Defined Nanocapsules.

PubMed

van Eldijk, Mark B; Schoonen, Lise; Cornelissen, Jeroen J L M; Nolte, Roeland J M; van Hest, Jan C M

2016-05-01

Protein cages are an interesting class of biomaterials with potential applications in bionanotechnology. Therefore, substantial effort is spent on the development of capsule-forming designer polypeptides with a tailor-made assembly profile. The expanded assembly profile of a triblock copolypeptide consisting of a metal ion chelating hexahistidine-tag, a stimulus-responsive elastin-like polypeptide block, and a pH-responsive morphology-controlling viral capsid protein is presented. The self-assembly of this multi-responsive protein-based block copolymer is triggered by the addition of divalent metal ions. This assembly process yields monodisperse nanocapsules with a 20 nm diameter composed of 60 polypeptides. The well-defined nanoparticles are the result of the emergent properties of all the blocks of the polypeptide. These results demonstrate the feasibility of hexahistidine-tags to function as supramolecular cross-linkers. Furthermore, their potential for the metal ion-mediated encapsulation of hexahistidine-tagged proteins is shown. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Glycosylation Benchmark Profile for HIV-1 Envelope Glycoprotein Production Based on Eleven Env Trimers

PubMed Central

Go, Eden P.; Ding, Haitao; Zhang, Shijian; Ringe, Rajesh P.; Nicely, Nathan; Hua, David; Steinbock, Robert T.; Golabek, Michael; Alin, James; Alam, S. Munir; Cupo, Albert; Haynes, Barton F.; Kappes, John C.; Moore, John P.; Sodroski, Joseph G.

2017-01-01

ABSTRACT HIV-1 envelope glycoprotein (Env) glycosylation is important because individual glycans are components of multiple broadly neutralizing antibody epitopes, while shielding other sites that might otherwise be immunogenic. The glycosylation on Env is influenced by a variety of factors, including the genotype of the protein, the cell line used for its expression, and the details of the construct design. Here, we used a mass spectrometry (MS)-based approach to map the complete glycosylation profile at every site in multiple HIV-1 Env trimers, accomplishing two goals. (i) We determined which glycosylation sites contain conserved glycan profiles across many trimeric Envs. (ii) We identified the variables that impact Env's glycosylation profile at sites with divergent glycosylation. Over half of the gp120 glycosylation sites on 11 different trimeric Envs have a conserved glycan profile, indicating that a native consensus glycosylation profile does indeed exist among trimers. We showed that some soluble gp120s and gp140s exhibit highly divergent glycosylation profiles compared to trimeric Env. We also assessed the impact of several variables on Env glycosylation: truncating the full-length Env; producing Env, instead of the more virologically relevant T lymphocytes, in CHO cells; and purifying Env with different chromatographic platforms, including nickel-nitrilotriacetic acid (Ni-NTA), 2G12, and PGT151 affinity. This report provides the first consensus glycosylation profile of Env trimers, which should serve as a useful benchmark for HIV-1 vaccine developers. This report also defines the sites where glycosylation may be impacted when Env trimers are truncated or produced in CHO cells. IMPORTANCE A protective HIV-1 vaccine will likely include a recombinant version of the viral envelope glycoprotein (Env). Env is highly glycosylated, and yet vaccine developers have lacked guidance on how to assess whether their immunogens have optimal glycosylation. The following important questions are still unanswered. (i) What is the “target” glycosylation profile, when the goal is to generate a natively glycosylated protein? (ii) What variables exert the greatest influence on Env glycosylation? We identified numerous sites on Env where the glycosylation profile does not deviate in 11 different Env trimers, and we investigated the impact on the divergent glycosylation profiles of changing the genotype of the Env sequence, the construct design, the purification method, and the producer cell type. The data presented here give vaccine developers a “glycosylation target” for their immunogens, and they show how protein production variables can impact Env glycosylation. PMID:28202756

Chromatography/Mass Spectrometry-Based Biomarkers in the Field of Obstructive Sleep Apnea

PubMed Central

Xu, Huajun; Zheng, Xiaojiao; Jia, Wei; Yin, Shankai

2015-01-01

Abstract Biomarker assessment is based on quantifying several proteins and metabolites. Recent developments in proteomics and metabolomics have enabled detection of these small molecules in biological samples and exploration of the underlying disease mechanisms in obstructive sleep apnea (OSA). This systemic review was performed to identify biomarkers, which were only detected by chromatography and/or mass spectrometry (MS) and to discuss the role of these biomarkers in the field of OSA. We systemically reviewed relevant articles from PubMed and EMBASE referring to proteins and metabolite profiles of biological samples in patients with OSA. The analytical platforms in this review were focused on chromatography and/or MS. In total, 30 studies evaluating biomarkers in patients with OSA using chromatography and/or MS methods were included. Numerous proteins and metabolites, including lipid profiles, adrenergic/dopaminergic biomarkers and derivatives, amino acids, oxidative stress biomarkers, and other micromolecules were identified in patients with OSA. Applying chromatography and/or MS methods to detect biomarkers helps develop an understanding of OSA mechanisms. More proteomic and metabolomic studies are warranted to develop potential diagnostic and clinical monitoring methods for OSA. PMID:26448002

Genetic characteristic of swamp buffalo (Bubalus bubalis) from Pampangan, South Sumatra based on blood protein profile

NASA Astrophysics Data System (ADS)

Windusari, Yuanita; Hanum, Laila; Wahyudi, Rizki

2017-11-01

Swamp buffalo (Bubalus bubalis) is an endemic species and one of the genetic wealth of South Sumatra with a distribution area in the district of Pampangan (OganIlir and OganOganIlir). Suspected inbreeding causes decreased phenotypic properties. Inbreeding among various swamp buffalo is certainly not only lower the qualities but also genotypes and phenotypes. It is of interest to determine kinship variants swamp buffaloes from Pampangan through the analysis of a blood protein profile. Blood protein profile of four variants swamps buffalo was studied by using five electrophoresis system i.e. pre-albumin (Palb), albumin (Alb), ceruloplasmin (Cp), transferrin (Tf) and transferrin post (Ptf). In this paper, it is obtained that there was no significant differences among the four variants of the buffaloes were used as a sample. Prealbumin has two alleles (Palb1 and Palb2), albumin has three alleles (Alba, AlbB, AlbC), ceruloplasmin has one allele (BPA), post-transferrin has one allele (PTFA) with an allele frequency 1.0000 at any time transferrin has two alleles (TFA and TFB) with the allele frequency of 0.7500 and 1.0000. Characteristics prealbumin (Palb), albumin (Alb), ceruloplasmin (Cp), and post-transferrin (P-tf) is monomorphic, while transferrin is polymorphic average heterozygosity values all loci (H) 0.1286. Based on average heterozygosity, the swamp buffalo (Bubalusbubalis) from Pampangan has low genetic variation and closest genetic relationship.

Cell- and Tissue-based Proteome Profiling and Dual Imaging of Apoptosis Markers with Probes Derived from Venetoclax and Idasanutlin.

PubMed

Li, Zhengqiu; Zhu, Dongsheng; Guo, Haijun; Chang, Yu; Ni, Yun; Li, Lin; Hao, Piliang; Xu, Yong; Ding, Ke

2018-05-16

Venetoclax (ABT-199) and idasanutlin (RG7388) are efficient anticancer drugs targeting two essential apoptosis markers, Bcl2 and MDM2, respectively. Recent studies have shown that the combination of these two drugs leads to remarkable enhancement of anticancer efficacy, both in vitro and in vivo. In an attempt to understand the mechanism of this synergistic effect, competitive affinity-based proteome profiling coupled with bioimaging was employed to characterize their protein targets in the same cancer cell line and tumor tissue. A series of protein hits, including ITPR1, GSR, RER1, PDIA3, Apoa1 and Tnfrsf17 were simultaneously identified by pull-down/LC-MS/MS with the two sets of affinity-based probes. Dual imaging was successfully carried out, simultaneously detecting Bcl2 and MDM2 expression in various cancer cells. This could facilitate the novel diagnostic and therapeutic strategies of dual targeting of Bcl2/MDM2. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model studies of diffusion-controlled (2-hydroxyethyl methacrylate) HEMA hydrogel membranes for controlled release of proteins

NASA Astrophysics Data System (ADS)

Appawu, Jennifer A. M.

This thesis project consisted of three main components that were connected by roots in chemical analysis for studies in tissue engineering. The first part focused on characterizing the structural parameters of synthetic cross-linked poly (2-hydroxyethyl methacrylate) (Poly(HEMA) hydrogel membranes to determine optimal formulations for clinical studies. Poly(HEMA) membranes were loaded with Keratincocyte Growth Factor (KGF) for controlled release studies. Protein loading and release kinetics were determined with fluorescence spectroscopy. The spatial distribution of a protein in the membrane was determined using Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS). The last part of the project focused on determining the biological effects of the polymer membranes in-vitro with a model cell line and a pilot in-vivo animal study. Based on the components completed in this project, five chapters are included in this dissertation document and are summarized below. A new protocol was developed using fluorescence spectroscopy that measured the rate of protein diffusion into cross-linked polymer membranes by measuring the change in the fluorescence intensity of the protein solution. This technique was also able to detect a conformational change that occurs within protein when KGF was imbibed within these cross-linked polymer membranes. ToF-SIMS chemical imaging and 3D depth profiling was used to determine the spatial distribution of KGF protein in frozen-hydrated HEMA hydrogel membranes. The 3D depth profiles showed that the KGF protein was aggregated in bright spots that indicated that KGF was not spatially homogenous on the surface and through the depth profiles. 3D depth profiles of the membranes studied at various times during release studies show that areas with aggregated proteins were retained during release, and at times with maximum release. The interpretation of the bright regions is that the KGf protein interacted with the cross-linked network of the hydrogel membranes, making it not available for release. The in-vitro biological experiments with the HaCaT cell line showed that the HEMA hydrogels were capable of sustaining cell viability, proliferation, and adhesion through cell adhesion and wounding experiments. The pilot in-vivo animal study also revealed that KGF protein had retained its pharmacological activity. The study also showed that the KGF protein enhanced the rate of wound closure.

ABC gene expression profiles have clinical importance and possibly form a new hallmark of cancer.

PubMed

Dvorak, Pavel; Pesta, Martin; Soucek, Pavel

2017-05-01

Adenosine triphosphate-binding cassette proteins constitute a large family of active transporters through extracellular and intracellular membranes. Increased drug efflux based on adenosine triphosphate-binding cassette protein activity is related to the development of cancer cell chemoresistance. Several articles have focused on adenosine triphosphate-binding cassette gene expression profiles (signatures), based on the expression of all 49 human adenosine triphosphate-binding cassette genes, in individual tumor types and reported connections to established clinicopathological features. The aim of this study was to test our theory about the existence of adenosine triphosphate-binding cassette gene expression profiles common to multiple types of tumors, which may modify tumor progression and provide clinically relevant information. Such general adenosine triphosphate-binding cassette profiles could constitute a new attribute of carcinogenesis. Our combined cohort consisted of tissues from 151 cancer patients-breast, colorectal, and pancreatic carcinomas. Standard protocols for RNA isolation and quantitative real-time polymerase chain reaction were followed. Gene expression data from individual tumor types as well as a merged tumor dataset were analyzed by bioinformatics tools. Several general adenosine triphosphate-binding cassette profiles, with differences in gene functions, were established and shown to have significant relations to clinicopathological features such as tumor size, histological grade, or clinical stage. Genes ABCC7, A3, A8, A12, and C8 prevailed among the most upregulated or downregulated ones. In conclusion, the results supported our theory about general adenosine triphosphate-binding cassette gene expression profiles and their importance for cancer on clinical as well as research levels. The presence of ABCC7 (official symbol CFTR) among the genes with key roles in the profiles supports the emerging evidence about its crucial role in various cancers. Graphical abstract.

Temporal expression profiling of plasma proteins reveals oxidative stress in early stages of Type 1 Diabetes progression

DOE PAGES

Liu, Chih-Wei; Bramer, Lisa; Webb-Robertson, Bobbie-Jo; ...

2017-10-07

We report that blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). To our knowledge, the current study represents the largest (> 2000 proteins measured)more » longitudinal expression profiles of human plasma proteome in T1D research. By applying statistical trend analysis on the temporal expression patterns between T1D and controls, and Benjamini-Hochberg procedure for multiple-testing correction, 13 protein groups were regarded as having statistically significant differences during the entire follow-up period. Moreover, 16 protein groups, which play pivotal roles in response to oxidative stress, have consistently abnormal expression trend before seroconversion to islet autoimmunity. Importantly, the expression trends of two key reactive oxygen species-decomposing enzymes, Catalase and Superoxide dismutase were verified independently by ELISA.« less

Temporal expression profiling of plasma proteins reveals oxidative stress in early stages of Type 1 Diabetes progression

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

Liu, Chih-Wei; Bramer, Lisa; Webb-Robertson, Bobbie-Jo

We report that blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). To our knowledge, the current study represents the largest (> 2000 proteins measured)more » longitudinal expression profiles of human plasma proteome in T1D research. By applying statistical trend analysis on the temporal expression patterns between T1D and controls, and Benjamini-Hochberg procedure for multiple-testing correction, 13 protein groups were regarded as having statistically significant differences during the entire follow-up period. Moreover, 16 protein groups, which play pivotal roles in response to oxidative stress, have consistently abnormal expression trend before seroconversion to islet autoimmunity. Importantly, the expression trends of two key reactive oxygen species-decomposing enzymes, Catalase and Superoxide dismutase were verified independently by ELISA.« less

Accurate optimization of amino acid form factors for computing small-angle X-ray scattering intensity of atomistic protein structures

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

Tong, Dudu; Yang, Sichun; Lu, Lanyuan

2016-06-20

Structure modellingviasmall-angle X-ray scattering (SAXS) data generally requires intensive computations of scattering intensity from any given biomolecular structure, where the accurate evaluation of SAXS profiles using coarse-grained (CG) methods is vital to improve computational efficiency. To date, most CG SAXS computing methods have been based on a single-bead-per-residue approximation but have neglected structural correlations between amino acids. To improve the accuracy of scattering calculations, accurate CG form factors of amino acids are now derived using a rigorous optimization strategy, termed electron-density matching (EDM), to best fit electron-density distributions of protein structures. This EDM method is compared with and tested againstmore » other CG SAXS computing methods, and the resulting CG SAXS profiles from EDM agree better with all-atom theoretical SAXS data. By including the protein hydration shell represented by explicit CG water molecules and the correction of protein excluded volume, the developed CG form factors also reproduce the selected experimental SAXS profiles with very small deviations. Taken together, these EDM-derived CG form factors present an accurate and efficient computational approach for SAXS computing, especially when higher molecular details (represented by theqrange of the SAXS data) become necessary for effective structure modelling.« less

In situ imaging and proteome profiling indicate andrographolide is a highly promiscuous compound

NASA Astrophysics Data System (ADS)

Li, Lin; Wijaya, Hadhi; Samanta, Sanjay; Lam, Yulin; Yao, Shao Q.

2015-06-01

Natural products represent an enormous source of pharmacologically useful compounds, and are often used as the starting point in modern drug discovery. Many biologically interesting natural products are however not being pursued as potential drug candidates, partly due to a lack of well-defined mechanism-of-action. Traditional in vitro methods for target identification of natural products based on affinity protein enrichment from crude cellular lysates cannot faithfully recapitulate protein-drug interactions in living cells. Reported herein are dual-purpose probes inspired by the natural product andrographolide, capable of both reaction-based, real-time bioimaging and in situ proteome profiling/target identification in live mammalian cells. Our results confirm that andrographolide is a highly promiscuous compound and engaged in covalent interactions with numerous previously unknown cellular targets in cell type-specific manner. We caution its potential therapeutic effects should be further investigated in detail.

Impact of Profiling Technologies in the Understanding of Recombinant Protein Production

NASA Astrophysics Data System (ADS)

Vijayendran, Chandran; Flaschel, Erwin

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

Size measuring techniques as tool to monitor pea proteins intramolecular crosslinking by transglutaminase treatment.

PubMed

Djoullah, Attaf; Krechiche, Ghali; Husson, Florence; Saurel, Rémi

2016-01-01

In this work, techniques for monitoring the intramolecular transglutaminase cross-links of pea proteins, based on protein size determination, were developed. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis profiles of transglutaminase-treated low concentration (0.01% w/w) pea albumin samples, compared to the untreated one (control), showed a higher electrophoretic migration of the major albumin fraction band (26 kDa), reflecting a decrease in protein size. This protein size decrease was confirmed, after DEAE column purification, by dynamic light scattering (DLS) where the hydrodynamic radius of treated samples appears to be reduced compared to the control one. Copyright © 2015 Elsevier Ltd. All rights reserved.

The effect of thermal processing on protein quality and free amino acid profile of Terminalia catappa (Indian Almond) seed.

PubMed

Adu, O B; Ogundeko, T O; Ogunrinola, O O; Saibu, G M; Elemo, B O

2015-07-01

The study examined the effect of various processing methods- boiling, drying and roasting- on the in vitro and in vivo protein digestibility and free amino acid profiles of Terminalia catappa seed. Moisture and crude protein of the various samples were determined. In vitro protein digestibility was determined after pepsin digestion. For the in vivo experiment, defatted T. catappa based diet was fed to 3 weeks old Wistar rats for 4 weeks and compared with animals maintained on casein based and nitrogen- free diets. The biological value (BV), net protein utilisation (NPU) and protein efficiency ratio (PER) of the diets were determined. Free amino acid composition was carried out using thin layer chromatography. Moisture was highest in the boiled T. catappa seed (8.30 ± 0.00 %). The raw, roasted and dried seeds had 5.55 ± 0.07, 3.88 ± 0.22 and 3.75 ± 0.07 % respectively. Crude protein was 19.19, 18.89, 17.62 and 16.36 % in the dried, roasted, boiled and raw seeds respectively. Roasted T. catappa seed had the highest in vitro protein digestibility with 37.52 %, while the dried, boiled and raw samples had digestibility values of 27.57, 27.07 and 24.45 % respectively. All nine essential amino acids were present in T. catappa in high concentrations except methionine and tryptophan. Glutamate was present in the highest concentration. Also, free amino acids were higher in the processed seeds compared to the raw seed. Animals fed T. catappa diet compared favourably with the casein group, thus indicating that the protein is of good quality.

Identification of an immunogenic protein of Actinobacillus seminis that is present in microvesicles

PubMed Central

2006-01-01

Abstract Actinobacillus seminis is a gram-negative bacterium of the Pasteurellaceae family that is involved in ovine epididymitis. Looking for a protein specific to this species, we determined the protein profile of subcellular fractions of A. seminis (American Type Culture Collection number 15768): proteins from the outer membrane (OMPs), inner membrane (IMPs), and cytoplasm (CPs). These profiles provide the first data, to our knowledge, regarding subcellular fractions of A. seminis. In the OMP fraction, we identified a protein with a molecular mass of 75 kDa that proved to be immunogenic and apparently specific for A. seminis. This conclusion was based on the reaction of hyperimmune serum of rabbits inoculated with whole cells of A. seminis that was tested against sonicated complete cells of reference strains and field isolates of Brucella ovis, Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni. No protein of these bacteria cross-reacted with the 75-kDa protein of A. seminis. Furthermore, when each type of hyperimmune serum was tested against the sonicated cells and each of the subcellular fractions of A. seminis, it did not recognize the A. seminis 75-kDa protein. We also isolated and identified this protein in microvesicles released to the culture supernatant. The results suggest that the 75-kDa protein could be used to establish a diagnostic test specific for ovine epididymitis caused by A. seminis. PMID:16548331

Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

PubMed

Wan, B; Yarbrough, J W; Schultz, T W

2008-01-01

This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

PubMed

Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S

2017-04-01

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Oxidative profiles of LDL and HDL isolated from women with preeclampsia.

PubMed

León-Reyes, G; Maida-Claros, R F; Urrutia-Medina, A X; Jorge-Galarza, E; Guzmán-Grenfell, A M; Fuentes-García, S; Medina-Navarro, R; Moreno-Eutimio, M A; Muñoz-Sánchez, J L; Hicks, J J; Torres-Ramos, Y D

2017-05-16

Oxidative stress causes biochemical changes in lipids and proteins; these changes can induce damage to the vascular endothelium and create maternal complications that are characteristic of preeclampsia. In this study, we evaluated the oxidative profile of lipoproteins isolated from women with preeclampsia. Thirty women diagnosed with preeclampsia and thirty women without preeclampsia were included in the study. Lipid-damage biomarkers, including conjugated dienes, lipohydroperoxides and malondialdehyde, were measured. The reduction of nitroblue tetrazolium, the formation of dityrosines, and the carbonylation of proteins were assessed as indicators of protein damage. The protective activity of HDL-c was evaluated by the paraoxonase-I activity present on the HDL-c particles. Serum lipid profiles were also quantified in both groups. Data were analysed using Student's t test and the Pearson correlation coefficient. Our results demonstrated in PE women evident oxidative changes in the lipids and proteins in HDL-c and LDL-c particles and the activity of the antioxidant enzyme PON-I decreased 59.9%. HDL-c exhibited self-defence, as demonstrated by the negative correlation between paraoxonase-I activity and the formation of lipohydroperoxides in HDL-c (r = -0.3755, p < 0.005). LDL-c and HDL-c isolated from women with preeclampsia show oxidative damage to lipids and proteins. We propose an oxidative profile based on the oxidation levels indicated by each of the markers used. We also found that paraoxonase-I is inactivated in the presence of lipohydroperoxides. Antioxidant support might be helpful to reduce oxidative stress in patients with preeclampsia. Further investigations are necessary to define the association between antioxidant activities and preeclampsia.

Effect of Heating Method on Alteration of Protein Molecular Structure in Flaxseed: Relationship with Changes in Protein Subfraction Profile and Digestion in Dairy Cows.

PubMed

Ahmad Khan, Nazir; Booker, Helen; Yu, Peiqiang

2015-02-04

This study evaluated the effect of heating methods on alteration of protein molecular structure in flaxseed (Linum usitatissimum L.) in relation to changes in protein subfraction profile and digestion in dairy cows. Seeds from two flaxseed varieties, sampled from two replicate plots at two locations, were evaluated. The seeds were either maintained in their raw state or heated in an air-draft oven (dry heating) or autoclave (moist heating) for 60 min at 120 °C or by microwave irradiation (MIR) for 5 min. Compared to raw seeds, moist heating decreased (P < 0.05) soluble protein (SP) content [56.5 ± 5.55 to 25.9 ± 6.16% crude protein (CP)] and increased (P < 0.05) rumen undegraded protein (RUP) content (36.0 ± 5.19 to 46.9 ± 2.72% CP) and intestinal digestibility of RUP (61.0 ± 2.28 to 63.8 ± 2.67% RUP). Dry heating did not alter (P > 0.05) the protein subfraction profile and rumen degradation kinetics, whereas MIR increased (P < 0.05) the RUP content from 36.0 ± 5.19 to 40.4 ± 4.67% CP. The MIR and dry heating did not alter (P > 0.05) the amide I to amide II ratio, but moist heating decreased (P < 0.05) both the amide I to amide II ratio and α-helix-to-β-sheet ratio. Regression equations based on protein molecular spectral intensities provided high prediction power for estimation of heat-induced changes in SP (R 2 = 0.62), RUP (R 2 = 0.71), and intestinal digestibility of RUP (R 2 = 0.72). Overall, heat-induced changes in protein nutritive value and digestion were strongly associated with heat-induced alteration in protein molecular structures.

LC-MS/MS Peptide Mapping with Automated Data Processing for Routine Profiling of N-Glycans in Immunoglobulins

NASA Astrophysics Data System (ADS)

Shah, Bhavana; Jiang, Xinzhao Grace; Chen, Louise; Zhang, Zhongqi

2014-06-01

Protein N-Glycan analysis is traditionally performed by high pH anion exchange chromatography (HPAEC), reversed phase liquid chromatography (RPLC), or hydrophilic interaction liquid chromatography (HILIC) on fluorescence-labeled glycans enzymatically released from the glycoprotein. These methods require time-consuming sample preparations and do not provide site-specific glycosylation information. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) peptide mapping is frequently used for protein structural characterization and, as a bonus, can potentially provide glycan profile on each individual glycosylation site. In this work, a recently developed glycopeptide fragmentation model was used for automated identification, based on their MS/MS, of N-glycopeptides from proteolytic digestion of monoclonal antibodies (mAbs). Experimental conditions were optimized to achieve accurate profiling of glycoforms. Glycan profiles obtained from LC-MS/MS peptide mapping were compared with those obtained from HPAEC, RPLC, and HILIC analyses of released glycans for several mAb molecules. Accuracy, reproducibility, and linearity of the LC-MS/MS peptide mapping method for glycan profiling were evaluated. The LC-MS/MS peptide mapping method with fully automated data analysis requires less sample preparation, provides site-specific information, and may serve as an alternative method for routine profiling of N-glycans on immunoglobulins as well as other glycoproteins with simple N-glycans.

Space Science

NASA Image and Video Library

2003-10-28

These gels were obtained by two-dimensional (2D) electrophoresis, in which proteins move different substances through a polyacrylamide gel matrix based on their molecular weight and total charge in an electric field. The gels illustrate principal investigator David Niesel’s findings that exposure to modeled microgravity results in some Streptoccoccus Pneumonia’s proteins being upregulated and others being downregulated. In 2D protein profiles of whole cell lysates of Streptoccoccus Pneumonia, 6,304 cultured under normal gravity (left), appear to be expressed at higher levels indicated with black circles. Red circles (right) indicate proteins that were grown under modeled microgravity in a high aspect ratio vessel HARV).

Chemical-genetic profile analysis of five inhibitory compounds in yeast.

PubMed

Alamgir, Md; Erukova, Veronika; Jessulat, Matthew; Azizi, Ali; Golshani, Ashkan

2010-08-06

Chemical-genetic profiling of inhibitory compounds can lead to identification of their modes of action. These profiles can help elucidate the complex interactions between small bioactive compounds and the cell machinery, and explain putative gene function(s). Colony size reduction was used to investigate the chemical-genetic profile of cycloheximide, 3-amino-1,2,4-triazole, paromomycin, streptomycin and neomycin in the yeast Saccharomyces cerevisiae. These compounds target the process of protein biosynthesis. More than 70,000 strains were analyzed from the array of gene deletion mutant yeast strains. As expected, the overall profiles of the tested compounds were similar, with deletions for genes involved in protein biosynthesis being the major category followed by metabolism. This implies that novel genes involved in protein biosynthesis could be identified from these profiles. Further investigations were carried out to assess the activity of three profiled genes in the process of protein biosynthesis using relative fitness of double mutants and other genetic assays. Chemical-genetic profiles provide insight into the molecular mechanism(s) of the examined compounds by elucidating their potential primary and secondary cellular target sites. Our follow-up investigations into the activity of three profiled genes in the process of protein biosynthesis provided further evidence concerning the usefulness of chemical-genetic analyses for annotating gene functions. We termed these genes TAE2, TAE3 and TAE4 for translation associated elements 2-4.

Proteomic Analysis of Interactions between a Deep-Sea Thermophilic Bacteriophage and Its Host at High Temperature ▿ †

PubMed Central

Wei, Dahai; Zhang, Xiaobo

2010-01-01

The virus-host interaction is essential to understanding the role that viruses play in ecological and geochemical processes in deep-sea vent ecosystems. Virus-induced changes in cellular gene expression and host physiology have been studied extensively. However, the molecular mechanism of interaction between a bacteriophage and its host at high temperature remains poorly understood. In the present study, the virus-induced gene expression profile of Geobacillus sp. E263, a thermophile isolated from a deep-sea hydrothermal ecosystem, was characterized. Based on proteomic analysis and random arbitrarily primed PCR (RAP-PCR) of Geobacillus sp. E263 cultured under non-bacteriophage GVE2 infection and GVE2 infection conditions, there were two types of protein/gene profiles in response to GVE2 infection. Twenty differentially expressed genes and proteins were revealed that could be grouped into 3 different categories based on cellular function, suggesting a coordinated response to infection. These differentially expressed genes and proteins were further confirmed by Northern blot analysis. To characterize the host proteins in response to virus infection, aspartate aminotransferase (AST) was inactivated to construct the AST mutant of Geobacillus sp. E263. The results showed that the AST protein was essential in virus infection. Thus, transcriptional and proteomic analyses and functional analysis revealed previously unknown host responses to deep-sea thermophilic virus infection. PMID:20015994

FIST: a sensory domain for diverse signal transduction pathways in prokaryotes and ubiquitin signaling in eukaryotes

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

Borziak, Kirill; Jouline, Igor B

2007-01-01

Motivation: Sensory domains that are conserved among Bacteria, Archaea and Eucarya are important detectors of common signals detected by living cells. Due to their high sequence divergence, sensory domains are difficult to identify. We systematically look for novel sensory domains using sensitive profile-based searches initi-ated with regions of signal transduction proteins where no known domains can be identified by current domain models. Results: Using profile searches followed by multiple sequence alignment, structure prediction, and domain architecture analysis, we have identified a novel sensory domain termed FIST, which is present in signal transduction proteins from Bacteria, Archaea and Eucarya. Remote similaritymore » to a known ligand-binding fold and chromosomal proximity of FIST-encoding genes to those coding for proteins involved in amino acid metabolism and transport suggest that FIST domains bind small ligands, such as amino acids.« less

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

PubMed

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O; Sperandio, Olivier

2010-03-05

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com.

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

PubMed Central

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O.; Sperandio, Olivier

2010-01-01

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com. PMID:20221258

The Utility of Nanopore Technology for Protein and Peptide Sensing.

PubMed

Robertson, Joseph W F; Reiner, Joseph E

2018-06-28

Resistive-pulse nanopore sensing enables label-free single-molecule analysis of a wide range of analytes. An increasing number of studies have demonstrated the feasibility and usefulness of nanopore sensing for protein and peptide characterization. Nanopores offer the potential to study a variety of protein-related phenomena that includes unfolding kinetics, differences in unfolding pathways, protein structure stability and free energy profiles of DNA-protein and RNA-protein binding. In addition to providing a tool for fundamental protein characterization, nanopores have also been used as highly selective protein detectors in various solution mixtures and conditions. This review highlights these and other developments in the area of nanopore-based protein and peptide detection. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Emory University: High-Throughput Protein-Protein Interaction Analysis for Hippo Pathway Profiling | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University used high-throughput protein-protein interaction (PPI) mapping for Hippo signaling pathway profiling to rapidly unveil promising PPIs as potential therapeutic targets and advance functional understanding of signaling circuitry in cells. Read the abstract.

Protein classification based on text document classification techniques.

PubMed

Cheng, Betty Yee Man; Carbonell, Jaime G; Klein-Seetharaman, Judith

2005-03-01

The need for accurate, automated protein classification methods continues to increase as advances in biotechnology uncover new proteins. G-protein coupled receptors (GPCRs) are a particularly difficult superfamily of proteins to classify due to extreme diversity among its members. Previous comparisons of BLAST, k-nearest neighbor (k-NN), hidden markov model (HMM) and support vector machine (SVM) using alignment-based features have suggested that classifiers at the complexity of SVM are needed to attain high accuracy. Here, analogous to document classification, we applied Decision Tree and Naive Bayes classifiers with chi-square feature selection on counts of n-grams (i.e. short peptide sequences of length n) to this classification task. Using the GPCR dataset and evaluation protocol from the previous study, the Naive Bayes classifier attained an accuracy of 93.0 and 92.4% in level I and level II subfamily classification respectively, while SVM has a reported accuracy of 88.4 and 86.3%. This is a 39.7 and 44.5% reduction in residual error for level I and level II subfamily classification, respectively. The Decision Tree, while inferior to SVM, outperforms HMM in both level I and level II subfamily classification. For those GPCR families whose profiles are stored in the Protein FAMilies database of alignments and HMMs (PFAM), our method performs comparably to a search against those profiles. Finally, our method can be generalized to other protein families by applying it to the superfamily of nuclear receptors with 94.5, 97.8 and 93.6% accuracy in family, level I and level II subfamily classification respectively. Copyright 2005 Wiley-Liss, Inc.

Protein profile of Lupinus texensis phloem sap exudates: searching for Fe- and Zn-containing proteins.

PubMed

Lattanzio, Giuseppe; Andaluz, Sofía; Matros, Andrea; Calvete, Juan José; Kehr, Julia; Abadía, Anunciación; Abadía, Javier; López-Millán, Ana-Flor

2013-08-01

The aim of this study was to obtain a comprehensive overview of the phloem sap protein profile of Lupinus texensis, with a special focus on proteins binding Fe and Zn. L. texensis was chosen as model plant given the simplicity to obtain exudates from sieve elements. Protein profiling by 2DE revealed 249 spots, and 54 of them were unambiguously identified by MALDI-MS and ESI-MS/MS. The largest number of identified protein species belongs to protein modification/turnover and general metabolism (19-21%), followed by redox homeostasis (9%) and defense and cell structural components (7%). This protein profile is similar to that reported in other plant species, suggesting that the phloem sap proteome is quite conserved. Staining of 2DE gels for Fe-containing proteins and affinity chromatography experiments revealed the presence of two low molecular weight Fe-binding proteins in phloem sap: a metallothionein-like protein type 2B identified in the Fe-affinity chromatography, and a second protein identified with both Fe staining methods. This protein species had a molecular weight of 13.5 kDa, a pI of 5.6 and 51% homology to a phloem-specific protein from Medicago truncatula. Zinc affinity chromatography revealed four Zn-binding proteins in phloem sap, one belonging to the dehydrin family and three Zn finger proteins. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The protein expression landscape of mitosis and meiosis in diploid budding yeast.

PubMed

Becker, Emmanuelle; Com, Emmanuelle; Lavigne, Régis; Guilleux, Marie-Hélène; Evrard, Bertrand; Pineau, Charles; Primig, Michael

2017-03-06

Saccharomyces cerevisiae is an established model organism for the molecular analysis of fundamental biological processes. The genomes of numerous strains have been sequenced, and the transcriptome and proteome ofmajor phases during the haploid and diploid yeast life cycle have been determined. However, much less is known about dynamic changes of the proteome when cells switch from mitotic growth to meiotic development. We report a quantitative protein profiling analysis of yeast cell division and differentiation based on mass spectrometry. Information about protein levels was integrated with strand-specific tiling array expression data. We identified a total of 2366 proteins in at least one condition, including 175 proteins showing a statistically significant>5-fold change across the sample set, and 136 proteins detectable in sporulating but not respiring cells. We correlate protein expression patterns with biological processes and molecular function by Gene Ontology term enrichment, chemoprofiling, transcription interference and the formation of double stranded RNAs by overlapping sense/antisense transcripts. Our work provides initial quantitative insight into protein expression in diploid respiring and differentiating yeast cells. Critically, it associates developmentally regulated induction of antisense long noncoding RNAs and double stranded RNAs with fluctuating protein concentrations during growth and development. This integrated genomics analysis helps better understand how the transcriptome and the proteome correlate in diploid yeast cells undergoing mitotic growth in the presence of acetate (respiration) versus meiotic differentiation (Meiosis I and II). The study (i) provides quantitative expression data for 2366 proteins and their cognate mRNAs in at least one sample, (ii) shows strongly fluctuating protein levels during growth and differentiation for 175 cases, and (iii) identifies 136 proteins absent in mitotic but present in meiotic yeast cells. We have integrated protein profiling data using mass spectrometry with tiling array RNA profiling data and information on double-stranded RNAs (dsRNAs) by overlapping sense/antisense transcripts from an RNA-Sequencing experiment. This work therefore provides quantitative insight into protein expression during cell division and development and associates changing protein levels with developmental stage specific induction of antisense transcripts and the formation of dsRNAs. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative profiling of O-glycans by electrospray ionization- and matrix-assisted laser desorption ionization-time-of-flight-mass spectrometry after in-gel derivatization with isotope-coded 1-phenyl-3-methyl-5-pyrazolone.

PubMed

Sić, Siniša; Maier, Norbert M; Rizzi, Andreas M

2016-09-07

The potential and benefits of isotope-coded labeling in the context of MS-based glycan profiling are evaluated focusing on the analysis of O-glycans. For this purpose, a derivatization strategy using d0/d5-1-phenyl-3-methyl-5-pyrazolone (PMP) is employed, allowing O-glycan release and derivatization to be achieved in one single step. The paper demonstrates that this release and derivatization reaction can be carried out also in-gel with only marginal loss in sensitivity compared to in-solution derivatization. Such an effective in-gel reaction allows one to extend this release/labeling method also to glycoprotein/glycoform samples pre-separated by gel-electrophoresis without the need of extracting the proteins/digested peptides from the gel. With highly O-glycosylated proteins (e.g. mucins) LODs in the range of 0.4 μg glycoprotein (100 fmol) loaded onto the electrophoresis gel can be attained, with minor glycosylated proteins (like IgAs, FVII, FIX) the LODs were in the range of 80-100 μg (250 pmol-1.5 nmol) glycoprotein loaded onto the gel. As second aspect, the potential of isotope coded labeling as internal standardization strategy for the reliable determination of quantitative glycan profiles via MALDI-MS is investigated. Towards this goal, a number of established and emerging MALDI matrices were tested for PMP-glycan quantitation, and their performance is compared with that of ESI-based measurements. The crystalline matrix 2,6-dihydroxyacetophenone (DHAP) and the ionic liquid matrix N,N-diisopropyl-ethyl-ammonium 2,4,6-trihydroxyacetophenone (DIEA-THAP) showed potential for MALDI-based quantitation of PMP-labeled O-glycans. We also provide a comprehensive overview on the performance of MS-based glycan quantitation approaches by comparing sensitivity, LOD, accuracy and repeatability data obtained with RP-HPLC-ESI-MS, stand-alone nano-ESI-MS with a spray-nozzle chip, and MALDI-MS. Finally, the suitability of the isotope-coded PMP labeling strategy for O-glycan profiling of biological important proteins is demonstrated by comparative analysis of IgA immunoglobulins and two coagulation factors. Copyright © 2016 Elsevier B.V. All rights reserved.

Integrated analysis of long noncoding RNA and mRNA expression profile in children with obesity by microarray analysis.

PubMed

Liu, Yuesheng; Ji, Yuqiang; Li, Min; Wang, Min; Yi, Xiaoqing; Yin, Chunyan; Wang, Sisi; Zhang, Meizhen; Zhao, Zhao; Xiao, Yanfeng

2018-06-08

Long noncoding RNAs (lncRNAs) have an important role in adipose tissue function and energy metabolism homeostasis, and abnormalities may lead to obesity. To investigate whether lncRNAs are involved in childhood obesity, we investigated the differential expression profile of lncRNAs in obese children compared with non-obese children. A total number of 1268 differentially expressed lncRNAs and 1085 differentially expressed mRNAs were identified. Gene Ontology (GO) and pathway analysis revealed that these lncRNAs were involved in varied biological processes, including the inflammatory response, lipid metabolic process, osteoclast differentiation and fatty acid metabolism. In addition, the lncRNA-mRNA co-expression network and the protein-protein interaction (PPI) network were constructed to identify hub regulatory lncRNAs and genes based on the microarray expression profiles. This study for the first time identifies an expression profile of differentially expressed lncRNAs in obese children and indicated hub lncRNA RP11-20G13.3 attenuated adipogenesis of preadipocytes, which is conducive to the search for new diagnostic and therapeutic strategies of childhood obesity.

The grafting of universal T-helper epitopes enhances immunogenicity of HIV-1 Tat concurrently improving its safety profile.

PubMed

Kashi, Venkatesh P; Jacob, Rajesh A; Shamanna, Raghavendra A; Menon, Malini; Balasiddaiah, Anangi; Varghese, Rebu K; Bachu, Mahesh; Ranga, Udaykumar

2014-01-01

Extracellular Tat (eTat) plays an important role in HIV-1 pathogenesis. The presence of anti-Tat antibodies is negatively correlated with disease progression, hence making Tat a potential vaccine candidate. The cytotoxicity and moderate immunogenicity of Tat however remain impediments for developing Tat-based vaccines. Here, we report a novel strategy to concurrently enhance the immunogenicity and safety profile of Tat. The grafting of universal helper T-lymphocyte (HTL) epitopes, Pan DR Epitope (PADRE) and Pol711 into the cysteine rich domain (CRD) and the basic domain (BD) abolished the transactivation potential of the Tat protein. The HTL-Tat proteins elicited a significantly higher titer of antibodies as compared to the wild-type Tat in BALB/c mice. While the N-terminal epitope remained immunodominant in HTL-Tat immunizations, an additional epitope in exon-2 was recognized with comparable magnitude suggesting a broader immune recognition. Additionally, the HTL-Tat proteins induced cross-reactive antibodies of high avidity that efficiently neutralized exogenous Tat, thus blocking the activation of a Tat-defective provirus. With advantages such as presentation of multiple B-cell epitopes, enhanced antibody response and importantly, transactivation-deficient Tat protein, this approach has potential application for the generation of Tat-based HIV/AIDS vaccines.

Whey versus soy protein diets and renal status in rats.

PubMed

Aparicio, Virginia A; Nebot, Elena; Tassi, Mohamed; Camiletti-Moirón, Daniel; Sanchez-Gonzalez, Cristina; Porres, Jesús M; Aranda, Pilar

2014-09-01

Different dietary protein sources can promote different renal statuses. We examined the effects of whey protein (WP) and soy protein (SP) intake on plasma, urinary, and morphological renal parameters in rats. One hundred and twenty Wistar rats were randomly distributed into 2 experimental groups fed with either WP or SP diets over 12 weeks. These diets were based on commercial WP or SP isolates. The urinary calcium content was higher in the WP diet compared to the SP diet group (P<.001) whereas the urinary citrate level was lower (P<.001). The urinary pH was more acidic in the WP diet group compared to the SP diet group (P<.001); however, no differences were observed between the groups for any of the renal morphological parameters analyzed (all, P>.05) or other plasma renal markers such as albumin or urea concentrations. The increase of acid and urinary calcium and the lower urinary citrate level observed in the WP diet group could increase the incidence of nephrolithiasis compared to the SP diet group. Despite the WP showed poorer acid-base profile, no significant morphological renal changes were observed. These results suggest that the use of SP instead of WP appears to promote a more alkaline plasma and urinary profile, with their consequent renal advantages.

Structure-based drug design for G protein-coupled receptors.

PubMed

Congreve, Miles; Dias, João M; Marshall, Fiona H

2014-01-01

Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed. © 2014 Elsevier B.V. All rights reserved.

Advances in organic polymer-based monolithic column technology for high-resolution liquid chromatography-mass spectrometry profiling of antibodies, intact proteins, oligonucleotides, and peptides.

PubMed

Eeltink, Sebastiaan; Wouters, Sam; Dores-Sousa, José Luís; Svec, Frantisek

2017-05-19

This review focuses on the preparation of organic polymer-based monolithic stationary phases and their application in the separation of biomolecules, including antibodies, intact proteins and protein isoforms, oligonucleotides, and protein digests. Column and material properties, and the optimization of the macropore structure towards kinetic performance are also discussed. State-of-the-art liquid chromatography-mass spectrometry biomolecule separations are reviewed and practical aspects such as ion-pairing agent selection and carryover are presented. Finally, advances in comprehensive two-dimensional LC separations using monolithic columns, in particular ion-exchange×reversed-phase and reversed-phase×reversed-phase LC separations conducted at high and low pH, are shown. Copyright © 2017 Elsevier B.V. All rights reserved.

Super-Chelators for Advanced Protein Labeling in Living Cells.

PubMed

Gatterdam, Karl; Joest, Eike F; Dietz, Marina S; Heilemann, Mike; Tampé, Robert

2018-05-14

Live-cell labeling, super-resolution microscopy, single-molecule applications, protein localization, or chemically induced assembly are emerging approaches, which require specific and very small interaction pairs. The minimal disturbance of protein function is essential to derive unbiased insights into cellular processes. Herein, we define a new class of hexavalent N-nitrilotriacetic acid (hexaNTA) chelators, displaying the highest affinity and stability of all NTA-based small interaction pairs described so far. Coupled to bright organic fluorophores with fine-tuned photophysical properties, the super-chelator probes were delivered into human cells by chemically gated nanopores. These super-chelators permit kinetic profiling, multiplexed labeling of His 6 - and His 12 -tagged proteins as well as single-molecule-based super-resolution imaging. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protein extraction and gel-based separation methods to analyze responses to pathogens in carnation (Dianthus caryophyllus L).

PubMed

Ardila, Harold Duban; Fernández, Raquel González; Higuera, Blanca Ligia; Redondo, Inmaculada; Martínez, Sixta Tulia

2014-01-01

We are currently using a 2-DE-based proteomics approach to study plant responses to pathogenic fungi by using the carnation (Dianthus caryophyllus L)-Fusarium oxysporum f. sp. dianthi pathosystem. It is clear that the protocols for the first stages of a standard proteomics workflow must be optimized to each biological system and objectives of the research. The optimization procedure for the extraction and separation of proteins by 1-DE and 2-DE in the indicated system is reported. This strategy can be extrapolated to other plant-pathogen interaction systems in order to perform an evaluation of the changes in the host protein profile caused by the pathogen and to identify proteins which, at early stages, are involved or implicated in the plant defense response.

CABS-flex: server for fast simulation of protein structure fluctuations

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2013-01-01

The CABS-flex server (http://biocomp.chem.uw.edu.pl/CABSflex) implements CABS-model–based protocol for the fast simulations of near-native dynamics of globular proteins. In this application, the CABS model was shown to be a computationally efficient alternative to all-atom molecular dynamics—a classical simulation approach. The simulation method has been validated on a large set of molecular dynamics simulation data. Using a single input (user-provided file in PDB format), the CABS-flex server outputs an ensemble of protein models (in all-atom PDB format) reflecting the flexibility of the input structure, together with the accompanying analysis (residue mean-square-fluctuation profile and others). The ensemble of predicted models can be used in structure-based studies of protein functions and interactions. PMID:23658222

CABS-flex: Server for fast simulation of protein structure fluctuations.

PubMed

Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2013-07-01

The CABS-flex server (http://biocomp.chem.uw.edu.pl/CABSflex) implements CABS-model-based protocol for the fast simulations of near-native dynamics of globular proteins. In this application, the CABS model was shown to be a computationally efficient alternative to all-atom molecular dynamics--a classical simulation approach. The simulation method has been validated on a large set of molecular dynamics simulation data. Using a single input (user-provided file in PDB format), the CABS-flex server outputs an ensemble of protein models (in all-atom PDB format) reflecting the flexibility of the input structure, together with the accompanying analysis (residue mean-square-fluctuation profile and others). The ensemble of predicted models can be used in structure-based studies of protein functions and interactions.

Molecular classification of fatty liver by high-throughput profiling of protein post-translational modifications.

PubMed

Urasaki, Yasuyo; Fiscus, Ronald R; Le, Thuc T

2016-04-01

We describe an alternative approach to classifying fatty liver by profiling protein post-translational modifications (PTMs) with high-throughput capillary isoelectric focusing (cIEF) immunoassays. Four strains of mice were studied, with fatty livers induced by different causes, such as ageing, genetic mutation, acute drug usage, and high-fat diet. Nutrient-sensitive PTMs of a panel of 12 liver metabolic and signalling proteins were simultaneously evaluated with cIEF immunoassays, using nanograms of total cellular protein per assay. Changes to liver protein acetylation, phosphorylation, and O-N-acetylglucosamine glycosylation were quantified and compared between normal and diseased states. Fatty liver tissues could be distinguished from one another by distinctive protein PTM profiles. Fatty liver is currently classified by morphological assessment of lipid droplets, without identifying the underlying molecular causes. In contrast, high-throughput profiling of protein PTMs has the potential to provide molecular classification of fatty liver. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Structure-Templated Predictions of Novel Protein Interactions from Sequence Information

PubMed Central

Betel, Doron; Breitkreuz, Kevin E; Isserlin, Ruth; Dewar-Darch, Danielle; Tyers, Mike; Hogue, Christopher W. V

2007-01-01

The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain–motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information. PMID:17892321

Synthesis and Evaluation of a Novel Adenosine-Ribose Probe for Global-Scale Profiling of Nucleoside and Nucleotide-Binding Proteins

PubMed Central

Mahajan, Shikha; Manetsch, Roman; Merkler, David J.; Stevens Jr., Stanley M.

2015-01-01

Proteomics is a powerful approach used for investigating the complex molecular mechanisms of disease pathogenesis and progression. An important challenge in modern protein profiling approaches involves targeting of specific protein activities in order to identify altered molecular processes associated with disease pathophysiology. Adenosine-binding proteins represent an important subset of the proteome where aberrant expression or activity changes of these proteins have been implicated in numerous human diseases. Herein, we describe an affinity-based approach for the enrichment of adenosine-binding proteins from a complex cell proteome. A novel N 6-biotinylated-8-azido-adenosine probe (AdoR probe) was synthesized, which contains a reactive group that forms a covalent bond with the target proteins, as well as a biotin tag for affinity enrichment using avidin chromatography. Probe specificity was confirmed with protein standards prior to further evaluation in a complex protein mixture consisting of a lysate derived from mouse neuroblastoma N18TG2 cells. Protein identification and relative quantitation using mass spectrometry allowed for the identification of small variations in abundance of nucleoside- and nucleotide-binding proteins in these samples where a significant enrichment of AdoR-binding proteins in the labeled proteome from the neuroblastoma cells was observed. The results from this study demonstrate the utility of this method to enrich for nucleoside- and nucleotide-binding proteins in a complex protein mixture, pointing towards a unique set of proteins that can be examined in the context of further understanding mechanisms of disease, or fundamental biological processes in general. PMID:25671571

Profile of bovine proteins in retained and normally expelled placenta in dairy cows.

PubMed

Kankofer, M; Wawrzykowski, J; Hoedemaker, M

2014-04-01

Tissue-specific protein profile is determined by its function, structure, intensity of metabolism and usefulness. This profile remains under hormonal control. Any disturbance in the general metabolism may be reflected in changes in both protein quantity and quality. These changes can be of low or high specificity, and some can be used as clinical markers of pathological conditions. The aim of this study was to describe and to compare the protein profile of caruncle and foetal villi of bovine placenta that was either properly released or retained. Placental tissues were collected from healthy cows, divided into releasing and retaining foetal membranes, homogenized and subjected to 1D and 2D electrophoresis. Computer-aided analysis of gel images showed essential qualitative and quantitative alterations in protein profile between tissues that were properly released and retained. Alterations concerned both the number of fractions and spots as well as the intensity of staining. This preliminary study provides a general overview of the differences in the protein profile between released and retained foetal membranes. It may allow for selecting the group of proteins or single molecules, which should be further analysed in detail as possible markers differentiating the retention of foetal membranes in cows from placentas that were released spontaneously. The continuation of the study for the identification of particular spots detected in 2D gels is necessary. © 2013 Blackwell Verlag GmbH.

Comparative structure-function characterization of the saposin-like domains from potato, barley, cardoon and Arabidopsis aspartic proteases.

PubMed

Bryksa, Brian C; Grahame, Douglas A; Yada, Rickey Y

2017-05-01

The present study characterized the aspartic protease saposin-like domains of four plant species, Solanum tuberosum (potato), Hordeum vulgare L. (barley), Cynara cardunculus L. (cardoon; artichoke thistle) and Arabidopsis thaliana, in terms of bilayer disruption and fusion, and structure pH-dependence. Comparison of the recombinant saposin-like domains revealed that each induced leakage of bilayer vesicles composed of a simple phospholipid mixture with relative rates Arabidopsis>barley>cardoon>potato. When compared for leakage of bilayer composed of a vacuole-like phospholipid mixture, leakage was approximately five times higher for potato saposin-like domain compared to the others. In terms of fusogenic activity, distinctions between particle size profiles were noted among the four proteins, particularly for potato saposin-like domain. Bilayer fusion assays in reducing conditions resulted in altered fusion profiles except in the case of cardoon saposin-like domain which was virtually unchanged. Secondary structure profiles were similar across all four proteins under different pH conditions, although cardoon saposin-like domain appeared to have higher overall helix structure. Furthermore, increases in Trp emission upon protein-bilayer interactions suggested that protein structure rearrangements equilibrated with half-times ranging from 52 to 120s, with cardoon saposin-like domain significantly slower than the other three species. Overall, the present findings serve as a foundation for future studies seeking to delineate protein structural features and motifs in protein-bilayer interactions based upon variability in plant aspartic protease saposin-like domain structures. Copyright © 2017 Elsevier B.V. All rights reserved.

Template-based protein structure modeling using the RaptorX web server.

PubMed

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2012-07-19

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world.

Template-based protein structure modeling using the RaptorX web server

PubMed Central

Källberg, Morten; Wang, Haipeng; Wang, Sheng; Peng, Jian; Wang, Zhiyong; Lu, Hui; Xu, Jinbo

2016-01-01

A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX ~35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed ~6,000 sequences submitted by ~1,600 users from around the world. PMID:22814390

Preliminary study on plasma proteins in pregnant and non-pregnant female dogs.

PubMed

Szczubiał, Marek; Wawrzykowski, Jacek; Dąbrowski, Roman; Krawczyk, Magdalena; Kankofer, Marta

2017-07-15

In this study, we used a combined approach based on 2-dimensional electrophoresis (2-DE), difference in gel electrophoresis (DIGE), and mass spectrometry (MS) to identify the plasma protein composition in pregnant female dogs and compared it with non-pregnant female dogs. We used the plasma samples obtained from four female dogs during I, II, and III thirds of pregnancy, three days after parturition, as well as from four non-pregnant female dogs in diestrus phase. Analysis of 2-DE gel image exhibited of 249 protein spots. The intensity of staining of 35 spots differed significantly (P < 0.05) between the non-pregnant and pregnant female dogs. We used matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI TOF MS) to identify 47 spots corresponding to 52 different proteins. Five identified protein spots, including zinc finger BED domain-containing protein 5, hemoglobin subunit beta-2, integrator complex subunit 7, apolipoprotein A-I, and glutamyl aminopeptidase were differentially presented in the plasma of pregnant and non-pregnant female dogs. To the best of our knowledge, this is the first report on the plasma protein profile of pregnant and non-pregnant female dogs. In this study, we identified proteins that have not been previously identified in dogs. Our findings showed that numerous protein spots were differentially presented in the plasma of female dogs during normal pregnancy. Although we identified only a limited number of differentially presented proteins, our study demonstrated that the plasma protein profile changed during pregnancy in female dogs, which suggests its importance in maintaining pregnancy. Further studies are necessary to define complete plasma protein profile of pregnant female dogs and to identify all proteins that are differentially presented in the pregnant animals compared with the non-pregnant ones. In addition, studies are warranted to explain the role of those proteins in maintaining the pregnancy and their usefulness in detection of early pregnancy. Furthermore, our results indicated that DIGE technique is useful in the comparison of samples originated from different states and time points in dogs. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative Protein Profiling of Intraphagosomal Expressed Proteins of Mycobacterium bovis BCG.

PubMed

Singhal, Neelja; Kumar, Manish; Sharma, Divakar; Bisht, Deepa

2016-01-01

BCG, the only available vaccine against tuberculosis affords a variable protection which wanes with time. In this study we have analyzed and compared the proteins which are expressed differentially during broth-culture and intraphagosomal growth of M.bovis BCG. Eight proteins which showed increased expression during the intraphagosomal growth were identified by MALDI-TOF/MS. These were - a precursor of alanine and proline-rich secreted protein apa, isoforms of malate dehydrogenase, large subunit alpha (Alpha-ETF) of electron transfer flavoprotein, immunogenic protein MPB64 precursor, UPF0036 protein, and two proteins with unknown function. Based on these findings we speculate that higher expression of these proteins has a probable role in intracellular survival, adaptation and/or immunoprotective effect of BCG. Further, these proteins might also be used as gene expression markers for endosome trafficking events of BCG.

RT-LAMP assay: an alternative approach for profiling of bovine heat shock protein 70 gene in PBMC cultured model.

PubMed

Sengar, Gyanendra Singh; Deb, Rajib; Raja, T V; Singh, Umesh; Kant, Rajiv; Bhanuprakash, V; Alyethodi, R R; Kumar, Sushil; Verma, Preetam; Chakraborty, Soumendu; Alex, Rani; Singh, Rani

2017-07-01

The purpose of this study is to develop a novel Reverse Transcriptase Loop-mediated isothermal amplification (RT-LAMP) based assay for in vitro profiling of heat shock protein 70 (Hsp70) in bovine peripheral blood mononuclear cell (PBMC) culture model utilizing the absorbance level of magnesium pyrophosphate-a by-product of LAMP reaction. A set of bovine Hsp70 specific RT-LAMP primers were designed to detect the differential absorbance level of magnesium pyrophosphate by-product which signifies the degree of Hsp70 amplification from cDNA of thermally induced cultured cells at different recovery periods. The study revealed significant (P < 0.05) correlation between absorbance level and the fold change of Hsp70 transcripts at different kinetic intervals of heat stress recovery in bovine PBMC cell culture models. RT-LAMP based absorbance assay can be used as an indicator to measure the degree of bovine Hsp70 transcripts produced during thermal stress and can be used as an alternative to the traditional Real time PCR assay. Developed RT-LAMP assay can be used as a cost-effective method for profiling of bovine HSP70 gene.

Comparison of identification methods for oral asaccharolytic Eubacterium species.

PubMed

Wade, W G; Slayne, M A; Aldred, M J

1990-12-01

Thirty one strains of oral, asaccharolytic Eubacterium spp. and the type strains of E. brachy, E. nodatum and E. timidum were subjected to three identification techniques--protein-profile analysis, determination of metabolic end-products, and the API ATB32A identification kit. Five clusters were obtained from numerical analysis of protein profiles and excellent correlations were seen with the other two methods. Protein profiles alone allowed unequivocal identification.

Unparalleled sample treatment throughput for proteomics workflows relying on ultrasonic energy.

PubMed

Jorge, Susana; Araújo, J E; Pimentel-Santos, F M; Branco, Jaime C; Santos, Hugo M; Lodeiro, Carlos; Capelo, J L

2018-02-01

We report on the new microplate horn ultrasonic device as a powerful tool to speed proteomics workflows with unparalleled throughput. 96 complex proteomes were digested at the same time in 4min. Variables such as ultrasonication time, ultrasonication amplitude, and protein to enzyme ratio were optimized. The "classic" method relying on overnight protein digestion (12h) and the sonoreactor-based method were also employed for comparative purposes. We found the protein digestion efficiency homogeneously distributed in the entire microplate horn surface using the following conditions: 4min sonication time and 25% amplitude. Using this approach, patients with lymphoma and myeloma were classified using principal component analysis and a 2D gel-mass spectrometry based approach. Furthermore, we demonstrate the excellent performance by using MALDI-mass spectrometry based profiling as a fast way to classify patients with rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Finally, the speed and simplicity of this method were demonstrated by clustering 90 patients with knee osteoarthritis disease (30), with a prosthesis (30, control group) and healthy individuals (30) with no history of joint disease. Overall, the new approach allows profiling a disease in just one week while allows to match the minimalism rules as outlined by Halls. Copyright © 2017 Elsevier B.V. All rights reserved.

Ranking the selectivity of PubChem screening hits by activity-based protein profiling: MMP13 as a case study.

PubMed

Nakai, Ryuichiro; Salisbury, Cleo M; Rosen, Hugh; Cravatt, Benjamin F

2009-02-01

High-throughput screening (HTS) has become an integral part of academic and industrial efforts aimed at developing new chemical probes and drugs. These screens typically generate several 'hits', or lead active compounds, that must be prioritized for follow-up medicinal chemistry studies. Among primary considerations for ranking lead compounds is selectivity for the intended target, especially among mechanistically related proteins. Here, we show how the chemical proteomic technology activity-based protein profiling (ABPP) can serve as a universal assay to rank HTS hits based on their selectivity across many members of an enzyme superfamily. As a case study, four metalloproteinase-13 (MMP13) inhibitors of similar potency originating from a publically supported HTS and reported in PubChem were tested by ABPP for selectivity against a panel of 27 diverse metalloproteases. The inhibitors could be readily separated into two groups: (1) those that were active against several metalloproteases and (2) those that showed high selectivity for MMP13. The latter set of inhibitors was thereby designated as more suitable for future medicinal chemistry optimization. We anticipate that ABPP will find general utility as a platform to rank the selectivity of lead compounds emerging from HTS assays for a wide variety of enzymes.

Multiplexed profiling of GPCR activities by combining split TEV assays and EXT-based barcoded readouts.

PubMed

Galinski, Sabrina; Wichert, Sven P; Rossner, Moritz J; Wehr, Michael C

2018-05-25

G protein-coupled receptors (GPCRs) are the largest class of cell surface receptors and are implicated in the physiological regulation of many biological processes. The high diversity of GPCRs and their physiological functions make them primary targets for therapeutic drugs. For the generation of novel compounds, however, selectivity towards a given target is a critical issue in drug development as structural similarities between members of GPCR subfamilies exist. Therefore, the activities of multiple GPCRs that are both closely and distantly related to assess compound selectivity need to be tested simultaneously. Here, we present a cell-based multiplexed GPCR activity assay, termed GPCRprofiler, which uses a β-arrestin recruitment strategy and combines split TEV protein-protein interaction and EXT-based barcode technologies. This approach enables simultaneous measurements of receptor activities of multiple GPCR-ligand combinations by applying massively parallelized reporter assays. In proof-of-principle experiments covering 19 different GPCRs, both the specificity of endogenous agonists and the polypharmacological effects of two known antipsychotics on GPCR activities were demonstrated. Technically, normalization of barcode reporters across individual assays allows quantitative pharmacological assays in a parallelized manner. In summary, the GPCRprofiler technique constitutes a flexible and scalable approach, which enables simultaneous profiling of compound actions on multiple receptor activities in living cells.

Plasma Exosome Profiling of Cancer Patients by a Next Generation Systems Biology Approach.

PubMed

Domenyuk, Valeriy; Zhong, Zhenyu; Stark, Adam; Xiao, Nianqing; O'Neill, Heather A; Wei, Xixi; Wang, Jie; Tinder, Teresa T; Tonapi, Sonal; Duncan, Janet; Hornung, Tassilo; Hunter, Andrew; Miglarese, Mark R; Schorr, Joachim; Halbert, David D; Quackenbush, John; Poste, George; Berry, Donald A; Mayer, Günter; Famulok, Michael; Spetzler, David

2017-02-20

Technologies capable of characterizing the full breadth of cellular systems need to be able to measure millions of proteins, isoforms, and complexes simultaneously. We describe an approach that fulfils this criterion: Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT). ADAPT employs an enriched library of single-stranded oligodeoxynucleotides (ssODNs) to profile complex biological samples, thus achieving an unprecedented coverage of system-wide, native biomolecules. We used ADAPT as a highly specific profiling tool that distinguishes women with or without breast cancer based on circulating exosomes in their blood. To develop ADAPT, we enriched a library of ~10 11 ssODNs for those associating with exosomes from breast cancer patients or controls. The resulting 10 6 enriched ssODNs were then profiled against plasma from independent groups of healthy and breast cancer-positive women. ssODN-mediated affinity purification and mass spectrometry identified low-abundance exosome-associated proteins and protein complexes, some with known significance in both normal homeostasis and disease. Sequencing of the recovered ssODNs provided quantitative measures that were used to build highly accurate multi-analyte signatures for patient classification. Probing plasma from 500 subjects with a smaller subset of 2000 resynthesized ssODNs stratified healthy, breast biopsy-negative, and -positive women. An AUC of 0.73 was obtained when comparing healthy donors with biopsy-positive patients.

Plasma Exosome Profiling of Cancer Patients by a Next Generation Systems Biology Approach

PubMed Central

Domenyuk, Valeriy; Zhong, Zhenyu; Stark, Adam; Xiao, Nianqing; O’Neill, Heather A.; Wei, Xixi; Wang, Jie; Tinder, Teresa T.; Tonapi, Sonal; Duncan, Janet; Hornung, Tassilo; Hunter, Andrew; Miglarese, Mark R.; Schorr, Joachim; Halbert, David D.; Quackenbush, John; Poste, George; Berry, Donald A.; Mayer, Günter; Famulok, Michael; Spetzler, David

2017-01-01

Technologies capable of characterizing the full breadth of cellular systems need to be able to measure millions of proteins, isoforms, and complexes simultaneously. We describe an approach that fulfils this criterion: Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT). ADAPT employs an enriched library of single-stranded oligodeoxynucleotides (ssODNs) to profile complex biological samples, thus achieving an unprecedented coverage of system-wide, native biomolecules. We used ADAPT as a highly specific profiling tool that distinguishes women with or without breast cancer based on circulating exosomes in their blood. To develop ADAPT, we enriched a library of ~1011 ssODNs for those associating with exosomes from breast cancer patients or controls. The resulting 106 enriched ssODNs were then profiled against plasma from independent groups of healthy and breast cancer-positive women. ssODN-mediated affinity purification and mass spectrometry identified low-abundance exosome-associated proteins and protein complexes, some with known significance in both normal homeostasis and disease. Sequencing of the recovered ssODNs provided quantitative measures that were used to build highly accurate multi-analyte signatures for patient classification. Probing plasma from 500 subjects with a smaller subset of 2000 resynthesized ssODNs stratified healthy, breast biopsy-negative, and -positive women. An AUC of 0.73 was obtained when comparing healthy donors with biopsy-positive patients. PMID:28218293

SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition

PubMed Central

Melvin, Iain; Ie, Eugene; Kuang, Rui; Weston, Jason; Stafford, William Noble; Leslie, Christina

2007-01-01

Background Predicting a protein's structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing new representations for protein sequences, called string kernels, for use with support vector machine (SVM) classifiers. However, while some of these approaches exhibit state-of-the-art performance at the binary protein classification problem, i.e. discriminating between a particular protein class and all other classes, few of these studies have addressed the real problem of multi-class superfamily or fold recognition. Moreover, there are only limited software tools and systems for SVM-based protein classification available to the bioinformatics community. Results We present a new multi-class SVM-based protein fold and superfamily recognition system and web server called SVM-Fold, which can be found at . Our system uses an efficient implementation of a state-of-the-art string kernel for sequence profiles, called the profile kernel, where the underlying feature representation is a histogram of inexact matching k-mer frequencies. We also employ a novel machine learning approach to solve the difficult multi-class problem of classifying a sequence of amino acids into one of many known protein structural classes. Binary one-vs-the-rest SVM classifiers that are trained to recognize individual structural classes yield prediction scores that are not comparable, so that standard "one-vs-all" classification fails to perform well. Moreover, SVMs for classes at different levels of the protein structural hierarchy may make useful predictions, but one-vs-all does not try to combine these multiple predictions. To deal with these problems, our method learns relative weights between one-vs-the-rest classifiers and encodes information about the protein structural hierarchy for multi-class prediction. In large-scale benchmark results based on the SCOP database, our code weighting approach significantly improves on the standard one-vs-all method for both the superfamily and fold prediction in the remote homology setting and on the fold recognition problem. Moreover, our code weight learning algorithm strongly outperforms nearest-neighbor methods based on PSI-BLAST in terms of prediction accuracy on every structure classification problem we consider. Conclusion By combining state-of-the-art SVM kernel methods with a novel multi-class algorithm, the SVM-Fold system delivers efficient and accurate protein fold and superfamily recognition. PMID:17570145

Deciphering Phosphotyrosine-Dependent Signaling Networks in Cancer by SH2 Profiling

PubMed Central

Machida, Kazuya; Khenkhar, Malik

2012-01-01

It has been a decade since the introduction of SH2 profiling, a modular domain-based molecular diagnostics tool. This review covers the original concept of SH2 profiling, different analytical platforms, and their applications, from the detailed analysis of single proteins to broad screening in translational research. Illustrated by practical examples, we discuss the uniqueness and advantages of the approach as well as its limitations and challenges. We provide guidance for basic researchers and oncologists who may consider SH2 profiling in their respective cancer research, especially for those focusing on tyrosine phosphoproteomics. SH2 profiling can serve as an alternative phosphoproteomics tool to dissect aberrant tyrosine kinase pathways responsible for individual malignancies, with the goal of facilitating personalized diagnostics for the treatment of cancer. PMID:23226573

Identification and substrate prediction of new Fragaria x ananassa aquaporins and expression in different tissues and during strawberry fruit development.

PubMed

Merlaen, Britt; De Keyser, Ellen; Van Labeke, Marie-Christine

2018-01-01

The newly identified aquaporin coding sequences presented here pave the way for further insights into the plant-water relations in the commercial strawberry ( Fragaria x ananassa ). Aquaporins are water channel proteins that allow water to cross (intra)cellular membranes. In Fragaria x ananassa , few of them have been identified hitherto, hampering the exploration of the water transport regulation at cellular level. Here, we present new aquaporin coding sequences belonging to different subclasses: plasma membrane intrinsic proteins subtype 1 and subtype 2 (PIP1 and PIP2) and tonoplast intrinsic proteins (TIP). The classification is based on phylogenetic analysis and is confirmed by the presence of conserved residues. Substrate-specific signature sequences (SSSSs) and specificity-determining positions (SDPs) predict the substrate specificity of each new aquaporin. Expression profiling in leaves, petioles and developing fruits reveals distinct patterns, even within the same (sub)class. Expression profiles range from leaf-specific expression over constitutive expression to fruit-specific expression. Both upregulation and downregulation during fruit ripening occur. Substrate specificity and expression profiles suggest that functional specialization exists among aquaporins belonging to a different but also to the same (sub)class.

Lysine-based polycation:heparin coacervate for controlled protein delivery.

PubMed

Johnson, Noah Ray; Ambe, Trisha; Wang, Yadong

2014-01-01

Polycations have good potential as carriers of proteins and genetic material. However, poor control over the release rate and safety issues currently limit their use as delivery vehicles. Here we introduce a new lysine-based polycation, poly(ethylene lysinylaspartate diglyceride) (PELD), which exhibits high cytocompatibility. PELD self-assembles with the biological polyanion heparin into a coacervate that incorporates proteins with high loading efficiency. Coacervates of varying surface charge were obtained by simple alteration of the PELD:heparin ratio and resulted in diverse release profiles of the model protein bovine serum albumin. Therefore, coacervate charge represents a direct means of control over release rate and duration. The PELD coacervate also rapidly adsorbed onto a porous polymeric scaffold, demonstrating potential use in tissue engineering applications. This coacervate represents a safe and tunable protein delivery system for biomedical applications. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

GTA: a game theoretic approach to identifying cancer subnetwork markers.

PubMed

Farahmand, S; Goliaei, S; Ansari-Pour, N; Razaghi-Moghadam, Z

2016-03-01

The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

PubMed Central

Cui, Jian; Liu, Jinghua; Li, Yuhua; Shi, Tieliu

2011-01-01

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome. PMID:21297957

ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data.

PubMed

Minas, Giorgos; Momiji, Hiroshi; Jenkins, Dafyd J; Costa, Maria J; Rand, David A; Finkenstädt, Bärbel

2017-06-26

Given the development of high-throughput experimental techniques, an increasing number of whole genome transcription profiling time series data sets, with good temporal resolution, are becoming available to researchers. The ReTrOS toolbox (Reconstructing Transcription Open Software) provides MATLAB-based implementations of two related methods, namely ReTrOS-Smooth and ReTrOS-Switch, for reconstructing the temporal transcriptional activity profile of a gene from given mRNA expression time series or protein reporter time series. The methods are based on fitting a differential equation model incorporating the processes of transcription, translation and degradation. The toolbox provides a framework for model fitting along with statistical analyses of the model with a graphical interface and model visualisation. We highlight several applications of the toolbox, including the reconstruction of the temporal cascade of transcriptional activity inferred from mRNA expression data and protein reporter data in the core circadian clock in Arabidopsis thaliana, and how such reconstructed transcription profiles can be used to study the effects of different cell lines and conditions. The ReTrOS toolbox allows users to analyse gene and/or protein expression time series where, with appropriate formulation of prior information about a minimum of kinetic parameters, in particular rates of degradation, users are able to infer timings of changes in transcriptional activity. Data from any organism and obtained from a range of technologies can be used as input due to the flexible and generic nature of the model and implementation. The output from this software provides a useful analysis of time series data and can be incorporated into further modelling approaches or in hypothesis generation.

A population pharmacokinetic model of valproic acid in pediatric patients with epilepsy: a non-linear pharmacokinetic model based on protein-binding saturation.

PubMed

Ding, Junjie; Wang, Yi; Lin, Weiwei; Wang, Changlian; Zhao, Limei; Li, Xingang; Zhao, Zhigang; Miao, Liyan; Jiao, Zheng

2015-03-01

Valproic acid (VPA) follows a non-linear pharmacokinetic profile in terms of protein-binding saturation. The total daily dose regarding VPA clearance is a simple power function, which may partially explain the non-linearity of the pharmacokinetic profile; however, it may be confounded by the therapeutic drug monitoring effect. The aim of this study was to develop a population pharmacokinetic model for VPA based on protein-binding saturation in pediatric patients with epilepsy. A total of 1,107 VPA serum trough concentrations at steady state were collected from 902 epileptic pediatric patients aged from 3 weeks to 14 years at three hospitals. The population pharmacokinetic model was developed using NONMEM(®) software. The ability of three candidate models (the simple power exponent model, the dose-dependent maximum effect [DDE] model, and the protein-binding model) to describe the non-linear pharmacokinetic profile of VPA was investigated, and potential covariates were screened using a stepwise approach. Bootstrap, normalized prediction distribution errors and external evaluations from two independent studies were performed to determine the stability and predictive performance of the candidate models. The age-dependent exponent model described the effects of body weight and age on the clearance well. Co-medication with carbamazepine was identified as a significant covariate. The DDE model best fitted the aim of this study, although there were no obvious differences in the predictive performances. The condition number was less than 500, and the precision of the parameter estimates was less than 30 %, indicating stability and validity of the final model. The DDE model successfully described the non-linear pharmacokinetics of VPA. Furthermore, the proposed population pharmacokinetic model of VPA can be used to design rational dosage regimens to achieve desirable serum concentrations.

Discovering semantic features in the literature: a foundation for building functional associations

PubMed Central

Chagoyen, Monica; Carmona-Saez, Pedro; Shatkay, Hagit; Carazo, Jose M; Pascual-Montano, Alberto

2006-01-01

Background Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research. Results We present a method to create literature profiles for large sets of genes or proteins based on common semantic features extracted from a corpus of relevant documents. These profiles can be used to establish pair-wise similarities among genes, utilized in gene/protein classification or can be even combined with experimental measurements. Semantic features can be used by researchers to facilitate the understanding of the commonalities indicated by experimental results. Our approach is based on non-negative matrix factorization (NMF), a machine-learning algorithm for data analysis, capable of identifying local patterns that characterize a subset of the data. The literature is thus used to establish putative relationships among subsets of genes or proteins and to provide coherent justification for this clustering into subsets. We demonstrate the utility of the method by applying it to two independent and vastly different sets of genes. Conclusion The presented method can create literature profiles from documents relevant to sets of genes. The representation of genes as additive linear combinations of semantic features allows for the exploration of functional associations as well as for clustering, suggesting a valuable methodology for the validation and interpretation of high-throughput experimental data. PMID:16438716

Comparative analyses of industrial-scale human platelet lysate preparations.

PubMed

Pierce, Jan; Benedetti, Eric; Preslar, Amber; Jacobson, Pam; Jin, Ping; Stroncek, David F; Reems, Jo-Anna

2017-12-01

Efforts are underway to eliminate fetal bovine serum from mammalian cell cultures for clinical use. An emerging, viable replacement option for fetal bovine serum is human platelet lysate (PL) as either a plasma-based or serum-based product. Nine industrial-scale, serum-based PL manufacturing runs (i.e., lots) were performed, consisting of an average ± standard deviation volume of 24.6 ± 2.2 liters of pooled, platelet-rich plasma units that were obtained from apheresis donors. Manufactured lots were compared by evaluating various biochemical and functional test results. Comprehensive cytokine profiles of PL lots and product stability tests were performed. Global gene expression profiles of mesenchymal stromal cells (MSCs) cultured with plasma-based or serum-based PL were compared to MSCs cultured with fetal bovine serum. Electrolyte and protein levels were relatively consistent among all serum-based PL lots, with only slight variations in glucose and calcium levels. All nine lots were as good as or better than fetal bovine serum in expanding MSCs. Serum-based PL stored at -80°C remained stable over 2 years. Quantitative cytokine arrays showed similarities as well as dissimilarities in the proteins present in serum-based PL. Greater differences in MSC gene expression profiles were attributable to the starting cell source rather than with the use of either PL or fetal bovine serum as a culture supplement. Using a large-scale, standardized method, lot-to-lot variations were noted for industrial-scale preparations of serum-based PL products. However, all lots performed as well as or better than fetal bovine serum in supporting MSC growth. Together, these data indicate that off-the-shelf PL is a feasible substitute for fetal bovine serum in MSC cultures. © 2017 AABB.

Proteomics profiling of interactome dynamics by colocalisation analysis (COLA)† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6mb00701e Click here for additional data file. Click here for additional data file.

PubMed Central

Sailem, Heba Z.; Kümper, Sandra; Tape, Christopher J.; McCully, Ryan R.; Paul, Angela; Anjomani-Virmouni, Sara; Jørgensen, Claus; Poulogiannis, George; Marshall, Christopher J.

2017-01-01

Localisation and protein function are intimately linked in eukaryotes, as proteins are localised to specific compartments where they come into proximity of other functionally relevant proteins. Significant co-localisation of two proteins can therefore be indicative of their functional association. We here present COLA, a proteomics based strategy coupled with a bioinformatics framework to detect protein–protein co-localisations on a global scale. COLA reveals functional interactions by matching proteins with significant similarity in their subcellular localisation signatures. The rapid nature of COLA allows mapping of interactome dynamics across different conditions or treatments with high precision. PMID:27824369

NHS-Esters As Versatile Reactivity-Based Probes for Mapping Proteome-Wide Ligandable Hotspots.

PubMed

Ward, Carl C; Kleinman, Jordan I; Nomura, Daniel K

2017-06-16

Most of the proteome is considered undruggable, oftentimes hindering translational efforts for drug discovery. Identifying previously unknown druggable hotspots in proteins would enable strategies for pharmacologically interrogating these sites with small molecules. Activity-based protein profiling (ABPP) has arisen as a powerful chemoproteomic strategy that uses reactivity-based chemical probes to map reactive, functional, and ligandable hotspots in complex proteomes, which has enabled inhibitor discovery against various therapeutic protein targets. Here, we report an alkyne-functionalized N-hydroxysuccinimide-ester (NHS-ester) as a versatile reactivity-based probe for mapping the reactivity of a wide range of nucleophilic ligandable hotspots, including lysines, serines, threonines, and tyrosines, encompassing active sites, allosteric sites, post-translational modification sites, protein interaction sites, and previously uncharacterized potential binding sites. Surprisingly, we also show that fragment-based NHS-ester ligands can be made to confer selectivity for specific lysine hotspots on specific targets including Dpyd, Aldh2, and Gstt1. We thus put forth NHS-esters as promising reactivity-based probes and chemical scaffolds for covalent ligand discovery.

Systematic Evaluation of the Use of Human Plasma and Serum for Mass-Spectrometry-Based Shotgun Proteomics.

PubMed

Lan, Jiayi; Núñez Galindo, Antonio; Doecke, James; Fowler, Christopher; Martins, Ralph N; Rainey-Smith, Stephanie R; Cominetti, Ornella; Dayon, Loïc

2018-04-06

Over the last two decades, EDTA-plasma has been used as the preferred sample matrix for human blood proteomic profiling. Serum has also been employed widely. Only a few studies have assessed the difference and relevance of the proteome profiles obtained from plasma samples, such as EDTA-plasma or lithium-heparin-plasma, and serum. A more complete evaluation of the use of EDTA-plasma, heparin-plasma, and serum would greatly expand the comprehensiveness of shotgun proteomics of blood samples. In this study, we evaluated the use of heparin-plasma with respect to EDTA-plasma and serum to profile blood proteomes using a scalable automated proteomic pipeline (ASAP 2 ). The use of plasma and serum for mass-spectrometry-based shotgun proteomics was first tested with commercial pooled samples. The proteome coverage consistency and the quantitative performance were compared. Furthermore, protein measurements in EDTA-plasma and heparin-plasma samples were comparatively studied using matched sample pairs from 20 individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study. We identified 442 proteins in common between EDTA-plasma and heparin-plasma samples. Overall agreement of the relative protein quantification between the sample pairs demonstrated that shotgun proteomics using workflows such as the ASAP 2 is suitable in analyzing heparin-plasma and that such sample type may be considered in large-scale clinical research studies. Moreover, the partial proteome coverage overlaps (e.g., ∼70%) showed that measures from heparin-plasma could be complementary to those obtained from EDTA-plasma.

mPUMA: a computational approach to microbiota analysis by de novo assembly of operational taxonomic units based on protein-coding barcode sequences.

PubMed

Links, Matthew G; Chaban, Bonnie; Hemmingsen, Sean M; Muirhead, Kevin; Hill, Janet E

2013-08-15

Formation of operational taxonomic units (OTU) is a common approach to data aggregation in microbial ecology studies based on amplification and sequencing of individual gene targets. The de novo assembly of OTU sequences has been recently demonstrated as an alternative to widely used clustering methods, providing robust information from experimental data alone, without any reliance on an external reference database. Here we introduce mPUMA (microbial Profiling Using Metagenomic Assembly, http://mpuma.sourceforge.net), a software package for identification and analysis of protein-coding barcode sequence data. It was developed originally for Cpn60 universal target sequences (also known as GroEL or Hsp60). Using an unattended process that is independent of external reference sequences, mPUMA forms OTUs by DNA sequence assembly and is capable of tracking OTU abundance. mPUMA processes microbial profiles both in terms of the direct DNA sequence as well as in the translated amino acid sequence for protein coding barcodes. By forming OTUs and calculating abundance through an assembly approach, mPUMA is capable of generating inputs for several popular microbiota analysis tools. Using SFF data from sequencing of a synthetic community of Cpn60 sequences derived from the human vaginal microbiome, we demonstrate that mPUMA can faithfully reconstruct all expected OTU sequences and produce compositional profiles consistent with actual community structure. mPUMA enables analysis of microbial communities while empowering the discovery of novel organisms through OTU assembly.

Trauma-associated Human Neutrophil Alterations Revealed by Comparative Proteomics Profiling

PubMed Central

Zhou, Jian-Ying; Krovvidi, Ravi K.; Gao, Yuqian; Gao, Hong; Petritis, Brianne O.; De, Asit; Miller-Graziano, Carol; Bankey, Paul E.; Petyuk, Vladislav A.; Nicora, Carrie D.; Clauss, Therese R; Moore, Ronald J.; Shi, Tujin; Brown, Joseph N.; Kaushal, Amit; Xiao, Wenzhong; Davis, Ronald W.; Maier, Ronald V.; Tompkins, Ronald G.; Qian, Wei-Jun; Camp, David G.; Smith, Richard D.

2013-01-01

PURPOSE Polymorphonuclear neutrophils (PMNs) play an important role in mediating the innate immune response after severe traumatic injury; however, the cellular proteome response to traumatic condition is still largely unknown. EXPERIMENTAL DESIGN We applied 2D-LC-MS/MS based shotgun proteomics to perform comparative proteome profiling of human PMNs from severe trauma patients and healthy controls. RESULTS A total of 197 out of ~2500 proteins (being identified with at least two peptides) were observed with significant abundance changes following the injury. The proteomics data were further compared with transcriptomics data for the same genes obtained from an independent patient cohort. The comparison showed that the protein abundance changes for the majority of proteins were consistent with the mRNA abundance changes in terms of directions of changes. Moreover, increased protein secretion was suggested as one of the mechanisms contributing to the observed discrepancy between protein and mRNA abundance changes. Functional analyses of the altered proteins showed that many of these proteins were involved in immune response, protein biosynthesis, protein transport, NRF2-mediated oxidative stress response, the ubiquitin-proteasome system, and apoptosis pathways. CONCLUSIONS AND CLINICAL RELEVANCE Our data suggest increased neutrophil activation and inhibited neutrophil apoptosis in response to trauma. The study not only reveals an overall picture of functional neutrophil response to trauma at the proteome level, but also provides a rich proteomics data resource of trauma-associated changes in the neutrophil that will be valuable for further studies of the functions of individual proteins in PMNs. PMID:23589343

Transport of Proteins through Nanopores

NASA Astrophysics Data System (ADS)

Luan, Binquan

In biological cells, a malfunctioned protein (such as misfolded or damaged) is degraded by a protease in which an unfoldase actively drags the protein into a nanopore-like structure and then a peptidase cuts the linearized protein into small fragments (i.e. a recycling process). Mimicking this biological process, many experimental studies have focused on the transport of proteins through a biological protein pore or a synthetic solid-state nanopore. Potentially, the nanopore-based sensors can provide a platform for interrogating proteins that might be disease-related or be targeted by a new drug molecule. The single-profile of a protein chain inside an extremely small nanopore might even permit the sequencing of the protein. Here, through all-atom molecular dynamics simulations, I will show various types of protein transport through a nanopore and reveal the nanoscale mechanics/energetics that plays an important role governing the protein transport.

Genome-wide profiling of DNA-binding proteins using barcode-based multiplex Solexa sequencing.

PubMed

Raghav, Sunil Kumar; Deplancke, Bart

2012-01-01

Chromatin immunoprecipitation (ChIP) is a commonly used technique to detect the in vivo binding of proteins to DNA. ChIP is now routinely paired to microarray analysis (ChIP-chip) or next-generation sequencing (ChIP-Seq) to profile the DNA occupancy of proteins of interest on a genome-wide level. Because ChIP-chip introduces several biases, most notably due to the use of a fixed number of probes, ChIP-Seq has quickly become the method of choice as, depending on the sequencing depth, it is more sensitive, quantitative, and provides a greater binding site location resolution. With the ever increasing number of reads that can be generated per sequencing run, it has now become possible to analyze several samples simultaneously while maintaining sufficient sequence coverage, thus significantly reducing the cost per ChIP-Seq experiment. In this chapter, we provide a step-by-step guide on how to perform multiplexed ChIP-Seq analyses. As a proof-of-concept, we focus on the genome-wide profiling of RNA Polymerase II as measuring its DNA occupancy at different stages of any biological process can provide insights into the gene regulatory mechanisms involved. However, the protocol can also be used to perform multiplexed ChIP-Seq analyses of other DNA-binding proteins such as chromatin modifiers and transcription factors.

Effects of Microgravity on Streptoccoccus Pneumonia

NASA Technical Reports Server (NTRS)

2003-01-01

These gels were obtained by two-dimensional (2D) electrophoresis, in which proteins move different substances through a polyacrylamide gel matrix based on their molecular weight and total charge in an electric field. The gels illustrate principal investigator David Niesel's findings that exposure to modeled microgravity results in some Streptoccoccus Pneumonia's proteins being upregulated and others being downregulated. In 2D protein profiles of whole cell lysates of Streptoccoccus Pneumonia, 6,304 cultured under normal gravity (left), appear to be expressed at higher levels indicated with black circles. Red circles (right) indicate proteins that were grown under modeled microgravity in a high aspect ratio vessel HARV).

A low-complexity add-on score for protein remote homology search with COMER.

PubMed

Margelevicius, Mindaugas

2018-06-15

Protein sequence alignment forms the basis for comparative modeling, the most reliable approach to protein structure prediction, among many other applications. Alignment between sequence families, or profile-profile alignment, represents one of the most, if not the most, sensitive means for homology detection but still necessitates improvement. We aim at improving the quality of profile-profile alignments and the sensitivity induced by them by refining profile-profile substitution scores. We have developed a new score that represents an additional component of profile-profile substitution scores. A comprehensive evaluation shows that the new add-on score statistically significantly improves both the sensitivity and the alignment quality of the COMER method. We discuss why the score leads to the improvement and its almost optimal computational complexity that makes it easily implementable in any profile-profile alignment method. An implementation of the add-on score in the open-source COMER software and data are available at https://sourceforge.net/projects/comer. The COMER software is also available on Github at https://github.com/minmarg/comer and as a Docker image (minmar/comer). Supplementary data are available at Bioinformatics online.

ProfileGrids: a sequence alignment visualization paradigm that avoids the limitations of Sequence Logos.

PubMed

Roca, Alberto I

2014-01-01

The 2013 BioVis Contest provided an opportunity to evaluate different paradigms for visualizing protein multiple sequence alignments. Such data sets are becoming extremely large and thus taxing current visualization paradigms. Sequence Logos represent consensus sequences but have limitations for protein alignments. As an alternative, ProfileGrids are a new protein sequence alignment visualization paradigm that represents an alignment as a color-coded matrix of the residue frequency occurring at every homologous position in the aligned protein family. The JProfileGrid software program was used to analyze the BioVis contest data sets to generate figures for comparison with the Sequence Logo reference images. The ProfileGrid representation allows for the clear and effective analysis of protein multiple sequence alignments. This includes both a general overview of the conservation and diversity sequence patterns as well as the interactive ability to query the details of the protein residue distributions in the alignment. The JProfileGrid software is free and available from http://www.ProfileGrid.org.

Comparative and network-based proteomic analysis of low dose ethanol- and lipopolysaccharide-induced macrophages.

PubMed

Kamal, Abu Hena M; Fessler, Michael B; Chowdhury, Saiful M

2018-01-01

Macrophages are specialized phagocytes that play an essential role in inflammation, immunity, and tissue repair. Profiling the global proteomic response of macrophages to microbial molecules such as bacterial lipopolysaccharide is key to understanding fundamental mechanisms of inflammatory disease. Ethanol is a widely abused substance that has complex effects on inflammation. Reports have indicated that ethanol can activate or inhibit the lipopolysaccharide receptor, Toll-like Receptor 4, in different settings, with important consequences for liver and neurologic inflammation, but the underlying mechanisms are poorly understood. To profile the sequential effect of low dose ethanol and lipopolysaccharide on macrophages, a gel-free proteomic technique was applied to RAW 264.7 macrophages. Five hundred four differentially expressed proteins were identified and quantified with high confidence using ≥ 5 peptide spectral matches. Among these, 319 proteins were shared across all treatment conditions, and 69 proteins were exclusively identified in ethanol-treated or lipopolysaccharide-stimulated cells. The interactive impact of ethanol and lipopolysaccharide on the macrophage proteome was evaluated using bioinformatics tools, enabling identification of differentially responsive proteins, protein interaction networks, disease- and function-based networks, canonical pathways, and upstream regulators. Five candidate protein coding genes (PGM2, ISYNA1, PARP1, and PSAP) were further validated by qRT-PCR that mostly related to glucose metabolism and fatty acid synthesis pathways. Taken together, this study describes for the first time at a systems level the interaction between ethanol and lipopolysaccharide in the proteomic programming of macrophages, and offers new mechanistic insights into the biology that may underlie the impact of ethanol on infectious and inflammatory disease in humans.

Kinetic insulation as an effective mechanism for achieving pathway specificity in intracellular signaling networks

PubMed Central

Behar, Marcelo; Dohlman, Henrik G.; Elston, Timothy C.

2007-01-01

Intracellular signaling pathways that share common components often elicit distinct physiological responses. In most cases, the biochemical mechanisms responsible for this signal specificity remain poorly understood. Protein scaffolds and cross-inhibition have been proposed as strategies to prevent unwanted cross-talk. Here, we report a mechanism for signal specificity termed “kinetic insulation.” In this approach signals are selectively transmitted through the appropriate pathway based on their temporal profile. In particular, we demonstrate how pathway architectures downstream of a common component can be designed to efficiently separate transient signals from signals that increase slowly over time. Furthermore, we demonstrate that upstream signaling proteins can generate the appropriate input to the common pathway component regardless of the temporal profile of the external stimulus. Our results suggest that multilevel signaling cascades may have evolved to modulate the temporal profile of pathway activity so that stimulus information can be efficiently encoded and transmitted while ensuring signal specificity. PMID:17913886

Proteomic analysis of the seed development in Jatropha curcas: from carbon flux to the lipid accumulation.

PubMed

Liu, Hui; Wang, Cuiping; Komatsu, Setsuko; He, Mingxia; Liu, Gongshe; Shen, Shihua

2013-10-08

To characterize the metabolic signatures of lipid accumulation in Jatropha curcas seeds, comparative proteomic technique was employed to profile protein changes during the seed development. Temporal changes in comparative proteome were examined using gels-based proteomic technique at six developmental stages for lipid accumulation. And 104 differentially expressed proteins were identified by MALDI-TOF/TOF tandem mass spectrometry. These protein species were classified into 10 functional categories, and the results demonstrated that protein species related to energy and metabolism were notably accumulated and involved in the carbon flux to lipid accumulation that occurs primarily from early to late stage in seed development. Glycolysis and oxidative pentose phosphate pathways were the major pathways of producing carbon flux, and the glucose-6-phosphate and triose-phosphate are the major carbon source for fatty acid synthesis. Lipid analysis revealed that fatty acid accumulation initiated 25days after flowering at the late stage of seed development of J. curcas. Furthermore, C16:0 was initially synthesized as the precursor for the elongation to C18:1 and C18:2 in the developing seeds of J. curcas. Together, the metabolic signatures on protein changes in seed development provide profound knowledge and perspective insights into understanding lipid network in J. curcas. Due to the abundant oil content in seeds, Jatropha curcas seeds are being considered as the ideal materials for biodiesel. Although several studies had carried out the transcriptomic project to study the genes expression profiles in seed development of J. curcas, these ESTs hadn't been confirmed by qRT-PCR. Yet, the seed development of J. curcas had been described for a pool of developing seeds instead of being characterized systematically. Moreover, cellular metabolic events are also controlled by protein-protein interactions, posttranslational protein modifications, and enzymatic activities which cannot be described by transcriptional profiling approaches alone. In this study, within the overall objective of profiling differential protein abundance in developing J. curcas seeds, we provide a setting of physiological data with dynamic proteomic and qRT-PCR analysis to characterize the metabolic pathways and the relationship between mRNA and protein patterns from early stage to seed filling during the seed development of J. curcas. The construction of J. curcas seed development proteome profiles will significantly increase our understanding of the process of seed development and provide a foundation to examine the dynamic changes of the metabolic network during seed development process and certainly suggest some clues to improve the lipid content of J. curcas seeds. © 2013. Published by Elsevier B.V. All rights reserved.

GlycoPP: A Webserver for Prediction of N- and O-Glycosites in Prokaryotic Protein Sequences

PubMed Central

Chauhan, Jagat S.; Bhat, Adil H.; Raghava, Gajendra P. S.; Rao, Alka

2012-01-01

Glycosylation is one of the most abundant post-translational modifications (PTMs) required for various structure/function modulations of proteins in a living cell. Although elucidated recently in prokaryotes, this type of PTM is present across all three domains of life. In prokaryotes, two types of protein glycan linkages are more widespread namely, N- linked, where a glycan moiety is attached to the amide group of Asn, and O- linked, where a glycan moiety is attached to the hydroxyl group of Ser/Thr/Tyr. For their biologically ubiquitous nature, significance, and technology applications, the study of prokaryotic glycoproteins is a fast emerging area of research. Here we describe new Support Vector Machine (SVM) based algorithms (models) developed for predicting glycosylated-residues (glycosites) with high accuracy in prokaryotic protein sequences. The models are based on binary profile of patterns, composition profile of patterns, and position-specific scoring matrix profile of patterns as training features. The study employ an extensive dataset of 107 N-linked and 116 O-linked glycosites extracted from 59 experimentally characterized glycoproteins of prokaryotes. This dataset includes validated N-glycosites from phyla Crenarchaeota, Euryarchaeota (domain Archaea), Proteobacteria (domain Bacteria) and validated O-glycosites from phyla Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria (domain Bacteria). In view of the current understanding that glycosylation occurs on folded proteins in bacteria, hybrid models have been developed using information on predicted secondary structures and accessible surface area in various combinations with training features. Using these models, N-glycosites and O-glycosites could be predicted with an accuracy of 82.71% (MCC 0.65) and 73.71% (MCC 0.48), respectively. An evaluation of the best performing models with 28 independent prokaryotic glycoproteins confirms the suitability of these models in predicting N- and O-glycosites in potential glycoproteins from aforementioned organisms, with reasonably high confidence. A web server GlycoPP, implementing these models is available freely at http:/www.imtech.res.in/raghava/glycopp/. PMID:22808107

Comprehensive proteomic profiles of mouse AApoAII amyloid fibrils provide insights into the involvement of lipoproteins in the pathology of amyloidosis.

PubMed

Miyahara, Hiroki; Sawashita, Jinko; Ishikawa, Eri; Yang, Mu; Ding, Xin; Liu, Yingye; Hachiya, Naomi; Kametani, Fuyuki; Yazaki, Masahide; Mori, Masayuki; Higuchi, Keiichi

2018-02-10

Amyloidosis is a disorder characterized by extracellular fibrillar deposits of misfolded proteins. The amyloid deposits commonly contain several non-fibrillar proteins as amyloid-associated proteins, but their roles in amyloidosis pathology are still unknown. In mouse senile amyloidosis, apolipoprotein A-II (ApoA-II) forms extracellular amyloid fibril (AApoAII) deposits with other proteins (AApoAII-associated proteins) in many organs. We previously reported that R1.P1-Apoa2 c mice provide a reproducible model of AApoAII amyloidosis. In order to investigate the sequential alterations of AApoAII-associated protein, we performed a proteomic analysis of amyloid fibrils extracted from mouse liver tissues that contained different levels of AApoAII deposition. We identified 6 AApoAII-associated proteins that constituted 20 of the top-ranked proteins in mice with severe AApoAII deposition. Although the amount of AApoAII-associated proteins increased with the progression of amyloidosis, the relative abundance of AApoAII-associated proteins changed little throughout the progression of amyloidosis. On the other hand, plasma levels of these proteins showed dramatic changes during the progression of amyloidosis. In addition, we confirmed that AApoAII-associated proteins were significantly associated with lipid metabolism based on functional enrichment analysis, and lipids were co-deposited with AApoAII fibrils from early stages of development of amyloidosis. Thus, these results demonstrate that lipoproteins are involved in AApoAII amyloidosis pathology. This study presented proteomic profiles of AApoAII amyloidosis during disease progression and it revealed co-deposition of lipids with AApoAII deposits based on functional analyses. The relative abundance of AApoAII-associated proteins in the amyloid fibril fractions did not change over the course of development of AApoAII amyloidosis pathology. However, their concentrations in plasma changed dramatically with progression of the disease. Interestingly, several AApoAII-associated proteins have been found as constituents of lipid-rich lesions of other degenerative diseases, such as atherosclerosis and age-related macular degeneration. The common protein components among these diseases with lipid-rich deposits could be accounted for by a lipoprotein retention model. Copyright © 2017 Elsevier B.V. All rights reserved.

Network-based function prediction and interactomics: the case for metabolic enzymes.

PubMed

Janga, S C; Díaz-Mejía, J Javier; Moreno-Hagelsieb, G

2011-01-01

As sequencing technologies increase in power, determining the functions of unknown proteins encoded by the DNA sequences so produced becomes a major challenge. Functional annotation is commonly done on the basis of amino-acid sequence similarity alone. Long after sequence similarity becomes undetectable by pair-wise comparison, profile-based identification of homologs can often succeed due to the conservation of position-specific patterns, important for a protein's three dimensional folding and function. Nevertheless, prediction of protein function from homology-driven approaches is not without problems. Homologous proteins might evolve different functions and the power of homology detection has already started to reach its maximum. Computational methods for inferring protein function, which exploit the context of a protein in cellular networks, have come to be built on top of homology-based approaches. These network-based functional inference techniques provide both a first hand hint into a proteins' functional role and offer complementary insights to traditional methods for understanding the function of uncharacterized proteins. Most recent network-based approaches aim to integrate diverse kinds of functional interactions to boost both coverage and confidence level. These techniques not only promise to solve the moonlighting aspect of proteins by annotating proteins with multiple functions, but also increase our understanding on the interplay between different functional classes in a cell. In this article we review the state of the art in network-based function prediction and describe some of the underlying difficulties and successes. Given the volume of high-throughput data that is being reported the time is ripe to employ these network-based approaches, which can be used to unravel the functions of the uncharacterized proteins accumulating in the genomic databases. © 2010 Elsevier Inc. All rights reserved.

HAMAP in 2013, new developments in the protein family classification and annotation system

PubMed Central

Pedruzzi, Ivo; Rivoire, Catherine; Auchincloss, Andrea H.; Coudert, Elisabeth; Keller, Guillaume; de Castro, Edouard; Baratin, Delphine; Cuche, Béatrice A.; Bougueleret, Lydie; Poux, Sylvain; Redaschi, Nicole; Xenarios, Ioannis; Bridge, Alan

2013-01-01

HAMAP (High-quality Automated and Manual Annotation of Proteins—available at http://hamap.expasy.org/) is a system for the classification and annotation of protein sequences. It consists of a collection of manually curated family profiles for protein classification, and associated annotation rules that specify annotations that apply to family members. HAMAP was originally developed to support the manual curation of UniProtKB/Swiss-Prot records describing microbial proteins. Here we describe new developments in HAMAP, including the extension of HAMAP to eukaryotic proteins, the use of HAMAP in the automated annotation of UniProtKB/TrEMBL, providing high-quality annotation for millions of protein sequences, and the future integration of HAMAP into a unified system for UniProtKB annotation, UniRule. HAMAP is continuously updated by expert curators with new family profiles and annotation rules as new protein families are characterized. The collection of HAMAP family classification profiles and annotation rules can be browsed and viewed on the HAMAP website, which also provides an interface to scan user sequences against HAMAP profiles. PMID:23193261

Profiling of 3696 Nuclear Receptor-Coregulator Interactions: A Resource for Biological and Clinical Discovery.

PubMed

Broekema, Marjoleine F; Hollman, Danielle A A; Koppen, Arjen; van den Ham, Henk-Jan; Melchers, Diana; Pijnenburg, Dirk; Ruijtenbeek, Rob; van Mil, Saskia W C; Houtman, René; Kalkhoven, Eric

2018-06-01

Nuclear receptors (NRs) are ligand-inducible transcription factors that play critical roles in metazoan development, reproduction, and physiology and therefore are implicated in a broad range of pathologies. The transcriptional activity of NRs critically depends on their interaction(s) with transcriptional coregulator proteins, including coactivators and corepressors. Short leucine-rich peptide motifs in these proteins (LxxLL in coactivators and LxxxIxxxL in corepressors) are essential and sufficient for NR binding. With 350 different coregulator proteins identified to date and with many coregulators containing multiple interaction motifs, an enormous combinatorial potential is present for selective NR-mediated gene regulation. However, NR-coregulator interactions have often been determined experimentally on a one-to-one basis across diverse experimental conditions. In addition, NR-coregulator interactions are difficult to predict because the molecular determinants that govern specificity are not well established. Therefore, many biologically and clinically relevant NR-coregulator interactions may remain to be discovered. Here, we present a comprehensive overview of 3696 NR-coregulator interactions by systematically characterizing the binding of 24 nuclear receptors with 154 coregulator peptides. We identified unique ligand-dependent NR-coregulator interaction profiles for each NR, confirming many well-established NR-coregulator interactions. Hierarchical clustering based on the NR-coregulator interaction profiles largely recapitulates the classification of NR subfamilies based on the primary amino acid sequences of the ligand-binding domains, indicating that amino acid sequence is an important, although not the only, molecular determinant in directing and fine-tuning NR-coregulator interactions. This NR-coregulator peptide interactome provides an open data resource for future biological and clinical discovery as well as NR-based drug design.

PANDA: Protein function prediction using domain architecture and affinity propagation.

PubMed

Wang, Zheng; Zhao, Chenguang; Wang, Yiheng; Sun, Zheng; Wang, Nan

2018-02-22

We developed PANDA (Propagation of Affinity and Domain Architecture) to predict protein functions in the format of Gene Ontology (GO) terms. PANDA at first executes profile-profile alignment algorithm to search against PfamA, KOG, COG, and SwissProt databases, and then launches PSI-BLAST against UniProt for homologue search. PANDA integrates a domain architecture inference algorithm based on the Bayesian statistics that calculates the probability of having a GO term. All the candidate GO terms are pooled and filtered based on Z-score. After that, the remaining GO terms are clustered using an affinity propagation algorithm based on the GO directed acyclic graph, followed by a second round of filtering on the clusters of GO terms. We benchmarked the performance of all the baseline predictors PANDA integrates and also for every pooling and filtering step of PANDA. It can be found that PANDA achieves better performances in terms of area under the curve for precision and recall compared to the baseline predictors. PANDA can be accessed from http://dna.cs.miami.edu/PANDA/ .

Multiplexed Activity-based Protein Profiling of the Human Pathogen Aspergillus fumigatus Reveals Large Functional Changes upon Exposure to Human Serum*

PubMed Central

Wiedner, Susan D.; Burnum, Kristin E.; Pederson, LeeAnna M.; Anderson, Lindsey N.; Fortuin, Suereta; Chauvigné-Hines, Lacie M.; Shukla, Anil K.; Ansong, Charles; Panisko, Ellen A.; Smith, Richard D.; Wright, Aaron T.

2012-01-01

Environmental adaptability is critical for survival of the fungal human pathogen Aspergillus fumigatus in the immunocompromised host lung. We hypothesized that exposure of the fungal pathogen to human serum would lead to significant alterations to the organism's physiology, including metabolic activity and stress response. Shifts in functional pathway and corresponding enzyme reactivity of A. fumigatus upon exposure to the human host may represent much needed prognostic indicators of fungal infection. To address this, we employed a multiplexed activity-based protein profiling (ABPP) approach coupled to quantitative mass spectrometry-based proteomics to measure broad enzyme reactivity of the fungus cultured with and without human serum. ABPP showed a shift from aerobic respiration to ethanol fermentation and utilization over time in the presence of human serum, which was not observed in serum-free culture. Our approach provides direct insight into this pathogen's ability to survive, adapt, and proliferate. Additionally, our multiplexed ABPP approach captured a broad swath of enzyme reactivity and functional pathways and provides a method for rapid assessment of the A. fumigatus response to external stimuli. PMID:22865858

Multiplexed activity-based protein profiling of the human pathogen Aspergillus fumigatus reveals large functional changes upon exposure to human serum.

PubMed

Wiedner, Susan D; Burnum, Kristin E; Pederson, LeeAnna M; Anderson, Lindsey N; Fortuin, Suereta; Chauvigné-Hines, Lacie M; Shukla, Anil K; Ansong, Charles; Panisko, Ellen A; Smith, Richard D; Wright, Aaron T

2012-09-28

Environmental adaptability is critical for survival of the fungal human pathogen Aspergillus fumigatus in the immunocompromised host lung. We hypothesized that exposure of the fungal pathogen to human serum would lead to significant alterations to the organism's physiology, including metabolic activity and stress response. Shifts in functional pathway and corresponding enzyme reactivity of A. fumigatus upon exposure to the human host may represent much needed prognostic indicators of fungal infection. To address this, we employed a multiplexed activity-based protein profiling (ABPP) approach coupled to quantitative mass spectrometry-based proteomics to measure broad enzyme reactivity of the fungus cultured with and without human serum. ABPP showed a shift from aerobic respiration to ethanol fermentation and utilization over time in the presence of human serum, which was not observed in serum-free culture. Our approach provides direct insight into this pathogen's ability to survive, adapt, and proliferate. Additionally, our multiplexed ABPP approach captured a broad swath of enzyme reactivity and functional pathways and provides a method for rapid assessment of the A. fumigatus response to external stimuli.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding.

PubMed

Shahi, Payam; Kim, Samuel C; Haliburton, John R; Gartner, Zev J; Abate, Adam R

2017-03-14

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

NASA Astrophysics Data System (ADS)

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-03-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

PubMed Central

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-01-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing. PMID:28290550

Secretome of Aspergillus oryzae in Shaoxing rice wine koji.

PubMed

Zhang, Bo; Guan, Zheng-Bing; Cao, Yu; Xie, Guang-Fa; Lu, Jian

2012-04-16

Shaoxing rice wine is the most famous and representative Chinese rice wine. Aspergillus oryzae SU16 is used in the manufacture of koji, the Shaoxing rice wine starter culture. In the current study, a comprehensive analysis of the secretome profile of A. oryzae SU16 in Shaoxing rice wine koji was performed for the first time. The proteomic analysis for the identification of the secretory proteins was done using two-dimensional electrophoresis combined with matrix-assisted laser desorption/ionization-tandem time of flight mass spectrometry based on the annotated A. oryzae genome sequence. A total of 41 unique proteins were identified from the secretome. These proteins included 17 extracellular proteins following the classical secretory pathway, and 10 extracellular proteins putatively secreted by the non-classical secretory pathway. The present secretome profile greatly differed from previous reports on A. oryzae growing in other solid-state nutrient sources. Several new secretory or putative secretory proteins were also found. These proteomic data will significantly aid the advancement of research on the secretome of A. oryzae, especially in solid-state cultures, and in elucidating the production process mechanism of Shaoxing rice wine koji. The findings may promote the technological development and innovation of the Shaoxing rice wine industry. Copyright © 2012 Elsevier B.V. All rights reserved.

Differences of protein profile before and after orthodontic treatment

NASA Astrophysics Data System (ADS)

Nasri, Farah Amirah Mohd; Wahab, Rohaya Megat Abdul; Karsani, Saiful Anuar; Ariffin, Shahrul Hisham Zainal

2016-11-01

Mechanical forces in orthodontic treatment used to treat malocclusion can cause inflamed gingival tissue and the process of tooth movement may resorb dental root. Root resorption is an iatrogenic effect of orthodontic treatment but it can be monitored using protein biomarker. This study aims to investigate the differences of protein profile before and after orthodontic treatment using different staining methods. Human gingival crevicular fluid and saliva were collected from orthodontic patients before and after treatment. Protein profile were observed using SDS-PAGE. Our study shows down regulation of proteins after 3 months of treatment. Hence, there are potential values from this study to aid in investigation for specific biomarkers for root resorption.

Investigating Molecular Structures of Bio-Fuel and Bio-Oil Seeds as Predictors To Estimate Protein Bioavailability for Ruminants by Advanced Nondestructive Vibrational Molecular Spectroscopy.

PubMed

Ban, Yajing; L Prates, Luciana; Yu, Peiqiang

2017-10-18

This study was conducted to (1) determine protein and carbohydrate molecular structure profiles and (2) quantify the relationship between structural features and protein bioavailability of newly developed carinata and canola seeds for dairy cows by using Fourier transform infrared molecular spectroscopy. Results showed similarity in protein structural makeup within the entire protein structural region between carinata and canola seeds. The highest area ratios related to structural CHO, total CHO, and cellulosic compounds were obtained for carinata seeds. Carinata and canola seeds showed similar carbohydrate and protein molecular structures by multivariate analyses. Carbohydrate molecular structure profiles were highly correlated to protein rumen degradation and intestinal digestion characteristics. In conclusion, the molecular spectroscopy can detect inherent structural characteristics in carinata and canola seeds in which carbohydrate-relative structural features are related to protein metabolism and utilization. Protein and carbohydrate spectral profiles could be used as predictors of rumen protein bioavailability in cows.

Differential protein partitioning within the herpesvirus tegument and envelope underlies a complex and variable virion architecture

PubMed Central

Bohannon, Kevin Patrick; Jun, Yonggun; Gross, Steven P.; Smith, Gregory Allan

2013-01-01

The herpesvirus virion is a multilayered structure consisting of a DNA-filled capsid, tegument, and envelope. Detailed reconstructions of the capsid are possible based on its icosahedral symmetry, but the surrounding tegument and envelope layers lack regular architecture. To circumvent limitations of symmetry-based ultrastructural reconstruction methods, a fluorescence approach was developed using single-particle imaging combined with displacement measurements at nanoscale resolution. An analysis of 11 tegument and envelope proteins defined the composition and plasticity of symmetric and asymmetric elements of the virion architecture. The resulting virion protein map ascribes molecular composition to density profiles previously acquired by traditional ultrastructural methods, and provides a way forward to examine the dynamics of the virion architecture during infection. PMID:23569236

Differential protein partitioning within the herpesvirus tegument and envelope underlies a complex and variable virion architecture.

PubMed

Bohannon, Kevin Patrick; Jun, Yonggun; Gross, Steven P; Smith, Gregory Allan

2013-04-23

The herpesvirus virion is a multilayered structure consisting of a DNA-filled capsid, tegument, and envelope. Detailed reconstructions of the capsid are possible based on its icosahedral symmetry, but the surrounding tegument and envelope layers lack regular architecture. To circumvent limitations of symmetry-based ultrastructural reconstruction methods, a fluorescence approach was developed using single-particle imaging combined with displacement measurements at nanoscale resolution. An analysis of 11 tegument and envelope proteins defined the composition and plasticity of symmetric and asymmetric elements of the virion architecture. The resulting virion protein map ascribes molecular composition to density profiles previously acquired by traditional ultrastructural methods, and provides a way forward to examine the dynamics of the virion architecture during infection.

Dense module enumeration in biological networks

NASA Astrophysics Data System (ADS)

Tsuda, Koji; Georgii, Elisabeth

2009-12-01

Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.

Insights into salicylic acid responses in cucumber (Cucumis sativus L.) cotyledons based on a comparative proteomic analysis.

PubMed

Hao, J H; Dong, C J; Zhang, Z G; Wang, X L; Shang, Q M

2012-05-01

To investigate the response of cucumber seedlings to exogenous salicylic acid (SA) and gain a better understanding of SA action mechanism, we generated a proteomic profile of cucumber (Cucumis sativus L.) cotyledons treated with exogenous SA. Analysis of 1500 protein spots from each gel revealed 63 differentially expressed proteins, 59 of which were identified successfully. Of the identified proteins, 97% matched cucumber proteins using a whole cucumber protein database based on the newly completed genome established by our laboratory. The identified proteins were involved in various cellular responses and metabolic processes, including antioxidative reactions, cell defense, photosynthesis, carbohydrate metabolism, respiration and energy homeostasis, protein folding and biosynthesis. The two largest functional categories included proteins involved in antioxidative reactions (23.7%) and photosynthesis (18.6%). Furthermore, the SA-responsive protein interaction network revealed 13 key proteins, suggesting that the expression changes of these proteins could be critical for SA-induced resistance. An analysis of these changes suggested that SA-induced resistance and seedling growth might be regulated in part through pathways involving antioxidative reactions and photosynthesis. © 2012 Elsevier Ireland Ltd. All rights reserved.

Fluorescence-based Western blotting for quantitation of protein biomarkers in clinical samples.

PubMed

Zellner, Maria; Babeluk, Rita; Diestinger, Michael; Pirchegger, Petra; Skeledzic, Senada; Oehler, Rudolf

2008-09-01

Since most high throughput techniques used in biomarker discovery are very time and cost intensive, highly specific and quantitative analytical alternative application methods are needed for the routine analysis. Conventional Western blotting allows detection of specific proteins to the level of single isotypes while its quantitative accuracy is rather limited. We report a novel and improved quantitative Western blotting method. The use of fluorescently labelled secondary antibodies strongly extends the dynamic range of the quantitation and improves the correlation with the protein amount (r=0.997). By an additional fluorescent staining of all proteins immediately after their transfer to the blot membrane, it is possible to visualise simultaneously the antibody binding and the total protein profile. This allows for an accurate correction for protein load. Applying this normalisation it could be demonstrated that fluorescence-based Western blotting is able to reproduce a quantitative analysis of two specific proteins in blood platelet samples from 44 subjects with different diseases as initially conducted by 2D-DIGE. These results show that the proposed fluorescence-based Western blotting is an adequate application technique for biomarker quantitation and suggest possibilities of employment that go far beyond.

Two different protein expression profiles of oral squamous cell carcinoma analyzed by immunoprecipitation high-performance liquid chromatography.

PubMed

Kim, Soung Min; Jeong, Dasul; Kim, Min Keun; Lee, Sang Shin; Lee, Suk Keun

2017-08-08

Oral squamous cell carcinoma (OSCC) is one of the most dangerous cancers in the body, producing serious complications with individual behaviors. Many different pathogenetic factors are involved in the carcinogenesis of OSCC. Cancer cells derived from oral keratinocytes can produce different carcinogenic signaling pathways through differences in protein expression, but their protein expression profiles cannot be easily explored with ordinary detection methods. The present study compared the protein expression profiles between two different types of OSCCs, which were analyzed through immunoprecipitation high-performance liquid chromatography (IP-HPLC). Two types of squamous cell carcinoma (SCC) occurred in a mandibular (SCC-1) and maxillary gingiva (SCC-2), but their clinical features and progression were quite different from each other. SCC-1 showed a large gingival ulceration with severe halitosis and extensive bony destruction, while SCC-2 showed a relatively small papillary gingival swelling but rapidly grew to form a large submucosal mass, followed by early cervical lymph node metastasis. In the histological observation, SCC-1 was relatively well differentiated with a severe inflammatory reaction, while SCC-2 showed severely infiltrative growth of each cancer islets accompanied with a mild inflammatory reaction. IP-HPLC analysis revealed contrary protein expression profiles analyzed by 72 different oncogenic proteins. SCC-1 showed more cellular apoptosis and invasive growth than SCC-2 through increased expression of caspases, MMPs, p53 signaling, FAS signaling, TGF-β1 signaling, and angiogenesis factors, while SCC-2 showed more cellular growth and survival than SCC-1 through the increased expression of proliferating factors, RAS signaling, eIF5A signaling, WNT signaling, and survivin. The increased trends of cellular apoptosis and invasiveness in the protein expression profiles of SCC-1 were implicative of its extensive gingival ulceration and bony destruction, while the increased trends of cellular proliferation and survival in the protein profile of SCC-2 were implicative of its rapid growing tumor mass and early lymph node metastasis. These analyses of the essential oncogenic protein expression profiles in OSCC provide important information for genetic counseling or customized gene therapy in cancer treatment. Therefore, protein expression profile analysis through IP-HPLC is helpful not only for the molecular genetic diagnosis of cancer but also in identifying target molecules for customized gene therapy in near future.

pH-selective mutagenesis of protein-protein interfaces: in silico design of therapeutic antibodies with prolonged half-life.

PubMed

Spassov, Velin Z; Yan, Lisa

2013-04-01

Understanding the effects of mutation on pH-dependent protein binding affinity is important in protein design, especially in the area of protein therapeutics. We propose a novel method for fast in silico mutagenesis of protein-protein complexes to calculate the effect of mutation as a function of pH. The free energy differences between the wild type and mutants are evaluated from a molecular mechanics model, combined with calculations of the equilibria of proton binding. The predicted pH-dependent energy profiles demonstrate excellent agreement with experimentally measured pH-dependency of the effect of mutations on the dissociation constants for the complex of turkey ovomucoid third domain (OMTKY3) and proteinase B. The virtual scanning mutagenesis identifies all hotspots responsible for pH-dependent binding of immunoglobulin G (IgG) to neonatal Fc receptor (FcRn) and the results support the current understanding of the salvage mechanism of the antibody by FcRn based on pH-selective binding. The method can be used to select mutations that change the pH-dependent binding profiles of proteins and guide the time consuming and expensive protein engineering experiments. As an application of this method, we propose a computational strategy to search for mutations that can alter the pH-dependent binding behavior of IgG to FcRn with the aim of improving the half-life of therapeutic antibodies in the target organism. Copyright © 2013 Wiley Periodicals, Inc.

Identification of hidden relationships from the coupling of hydrophobic cluster analysis and domain architecture information.

PubMed

Faure, Guilhem; Callebaut, Isabelle

2013-07-15

Describing domain architecture is a critical step in the functional characterization of proteins. However, some orphan domains do not match any profile stored in dedicated domain databases and are thereby difficult to analyze. We present here an original novel approach, called TREMOLO-HCA, for the analysis of orphan domain sequences and inspired from our experience in the use of Hydrophobic Cluster Analysis (HCA). Hidden relationships between protein sequences can be more easily identified from the PSI-BLAST results, using information on domain architecture, HCA plots and the conservation degree of amino acids that may participate in the protein core. This can lead to reveal remote relationships with known families of domains, as illustrated here with the identification of a hidden Tudor tandem in the human BAHCC1 protein and a hidden ET domain in the Saccharomyces cerevisiae Taf14p and human AF9 proteins. The results obtained in such a way are consistent with those provided by HHPRED, based on pairwise comparisons of HHMs. Our approach can, however, be applied even in absence of domain profiles or known 3D structures for the identification of novel families of domains. It can also be used in a reverse way for refining domain profiles, by starting from known protein domain families and identifying highly divergent members, hitherto considered as orphan. We provide a possible integration of this approach in an open TREMOLO-HCA package, which is fully implemented in python v2.7 and is available on request. Instructions are available at http://www.impmc.upmc.fr/∼callebau/tremolohca.html. isabelle.callebaut@impmc.upmc.fr Supplementary Data are available at Bioinformatics online.

SH2 Domain Histochemistry.

PubMed

Buhs, Sophia; Nollau, Peter

2017-01-01

Among posttranslational modifications, the phosphorylation of tyrosine residues is a key modification in cell signaling. Because of its biological importance, characterization of the cellular state of tyrosine phosphorylation is of great interest. Based on the unique properties of endogenously expressed SH2 domains recognizing tyrosine phosphorylated signaling proteins with high specificity we have developed an alternative approach, coined SH2 profiling, enabling us to decipher complex patterns of tyrosine phosphorylation in various normal and cancerous tissues. So far, SH2 profiling has largely been applied for the analysis of protein extracts with the limitation that information on spatial distribution and intensity of tyrosine phosphorylation within a tissue is lost. Here, we describe a novel SH2 domain based strategy for differential characterization of the state of tyrosine phosphorylation in formaldehyde-fixed and paraffin-embedded tissues. This approach demonstrates that SH2 domains may serve as very valuable tools for the analysis of the differential state of tyrosine phosphorylation in primary tissues fixed and processed under conditions frequently applied by routine pathology laboratories.

NMR-based metabolomics reveals the metabolite profiles of Vibrio parahaemolyticus under ferric iron stimulation.

PubMed

Zhou, Jun; Lu, Chenyang; Zhang, Dijun; Ma, Chennv; Su, Xiurong

2017-08-01

Vibrio parahaemolyticus is a halophilic bacterium endemic to coastal areas, and its pathogenicity has caused widespread seafood poisoning. In our previous research, the protein expression of V. parahaemolyticus in Fe 3+ medium was determined using isobaric tags for relative and absolute quantitation (iTRAQ). Here, nuclear magnetic resonance (NMR) was used to detect changes in the V. parahaemolyticus metabolome. NMR spectra were obtained using methanol-water extracts of intracellular metabolites from V. parahaemolyticus under various culture conditions, and 62 metabolites were identified, including serine, arginine, alanine, ornithine, tryptophan, glutamine, malate, NAD + , NADP + , oxypurinol, xanthosine, dCTP, uracil, thymine, hypoxanthine, and betaine. Among these, 21 metabolites were up-regulated after the stimulation of the cells by ferric iron, and 9 metabolites were down-regulated. These metabolites are involved in amino acid and protein synthesis, energy metabolism, DNA and RNA synthesis and osmolality. Based on these results, we conclude that Fe 3+ influences the metabolite profiles of V. parahaemolyticus.

Advancing understanding of microbial bioenergy conversion processes by activity-based protein profiling

DOE PAGES

Liu, Yun; Fredrickson, James K.; Sadler, Natalie C.; ...

2015-09-25

Here, the development of renewable biofuels is a global priority, but success will require novel technologies that greatly improve our understanding of microbial systems biology. An approach with great promise in enabling functional characterization of microbes is activity-based protein profiling (ABPP), which employs chemical probes to directly measure enzyme function in discrete enzyme classes in vivo and/or in vitro, thereby facilitating the rapid discovery of new biocatalysts and enabling much improved biofuel production platforms. We review general design strategies in ABPP, and highlight recent advances that are or could be pivotal to biofuels processes including applications of ABPP to cellulosicmore » bioethanol, biodiesel, and phototrophic production of hydrocarbons. We also examine the key challenges and opportunities of ABPP in renewable biofuels research. The integration of ABPP with molecular and systems biology approaches will shed new insight on the catalytic and regulatory mechanisms of functional enzymes and their synergistic effects in the field of biofuels production.« less

Functional proteomics outlines the complexity of breast cancer molecular subtypes.

PubMed

Gámez-Pozo, Angelo; Trilla-Fuertes, Lucía; Berges-Soria, Julia; Selevsek, Nathalie; López-Vacas, Rocío; Díaz-Almirón, Mariana; Nanni, Paolo; Arevalillo, Jorge M; Navarro, Hilario; Grossmann, Jonas; Gayá Moreno, Francisco; Gómez Rioja, Rubén; Prado-Vázquez, Guillermo; Zapater-Moros, Andrea; Main, Paloma; Feliú, Jaime; Martínez Del Prado, Purificación; Zamora, Pilar; Ciruelos, Eva; Espinosa, Enrique; Fresno Vara, Juan Ángel

2017-08-30

Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score.

Mean of the typical decoding rates: a new translation efficiency index based on the analysis of ribosome profiling data.

PubMed

Dana, Alexandra; Tuller, Tamir

2014-12-01

Gene translation modeling and prediction is a fundamental problem that has numerous biomedical implementations. In this work we present a novel, user-friendly tool/index for calculating the mean of the typical decoding rates that enables predicting translation elongation efficiency of protein coding genes for different tissue types, developmental stages, and experimental conditions. The suggested translation efficiency index is based on the analysis of the organism's ribosome profiling data. This index could be used for example to predict changes in translation elongation efficiency of lowly expressed genes that usually have relatively low and/or biased ribosomal densities and protein levels measurements, or can be used for example for predicting translation efficiency of new genetically engineered genes. We demonstrate the usability of this index via the analysis of six organisms in different tissues and developmental stages. Distributable cross platform application and guideline are available for download at: http://www.cs.tau.ac.il/~tamirtul/MTDR/MTDR_Install.html. Copyright © 2015 Dana and Tuller.

Investigation of protein folding by coarse-grained molecular dynamics with the UNRES force field.

PubMed

Maisuradze, Gia G; Senet, Patrick; Czaplewski, Cezary; Liwo, Adam; Scheraga, Harold A

2010-04-08

Coarse-grained molecular dynamics simulations offer a dramatic extension of the time-scale of simulations compared to all-atom approaches. In this article, we describe the use of the physics-based united-residue (UNRES) force field, developed in our laboratory, in protein-structure simulations. We demonstrate that this force field offers about a 4000-times extension of the simulation time scale; this feature arises both from averaging out the fast-moving degrees of freedom and reduction of the cost of energy and force calculations compared to all-atom approaches with explicit solvent. With massively parallel computers, microsecond folding simulation times of proteins containing about 1000 residues can be obtained in days. A straightforward application of canonical UNRES/MD simulations, demonstrated with the example of the N-terminal part of the B-domain of staphylococcal protein A (PDB code: 1BDD, a three-alpha-helix bundle), discerns the folding mechanism and determines kinetic parameters by parallel simulations of several hundred or more trajectories. Use of generalized-ensemble techniques, of which the multiplexed replica exchange method proved to be the most effective, enables us to compute thermodynamics of folding and carry out fully physics-based prediction of protein structure, in which the predicted structure is determined as a mean over the most populated ensemble below the folding-transition temperature. By using principal component analysis of the UNRES folding trajectories of the formin-binding protein WW domain (PDB code: 1E0L; a three-stranded antiparallel beta-sheet) and 1BDD, we identified representative structures along the folding pathways and demonstrated that only a few (low-indexed) principal components can capture the main structural features of a protein-folding trajectory; the potentials of mean force calculated along these essential modes exhibit multiple minima, as opposed to those along the remaining modes that are unimodal. In addition, a comparison between the structures that are representative of the minima in the free-energy profile along the essential collective coordinates of protein folding (computed by principal component analysis) and the free-energy profile projected along the virtual-bond dihedral angles gamma of the backbone revealed the key residues involved in the transitions between the different basins of the folding free-energy profile, in agreement with existing experimental data for 1E0L .

Clr4 specificity and catalytic activity beyond H3K9 methylation.

PubMed

Kusevic, Denis; Kudithipudi, Srikanth; Iglesias, Nahid; Moazed, Danesh; Jeltsch, Albert

2017-04-01

In fission yeast, the catalytic activity of the protein lysine methyltransferase (PKMT) Clr4, the sole homolog of the mammalian SUV39H1 and SUV39H2 enzymes, majorly contributes to the formation of heterochromatin. The enzyme introduces histone 3 lysine 9 (H3K9) di- and tri-methylation, a central heterochromatic histone modification, and later it was also found to methylate the Mlo3 protein, which has a role in heterochromatin formation as well. Herein, we have investigated the substrate specificity of Clr4 using custom made mutational scanning peptide arrays. Our data show, that Clr4 recognizes an RK core motif, showing high preference for R8. In addition, it exhibits specific contacts at the S10, T11, G12 and G13 positions of the H3 peptide recognizing an R-K-SKRT-TCS-G sequence. Based on the specificity profile and in vitro methyltransferase assay targeted searches, 11 putative methylation sites in S. pombe proteins were identified from reported Clr4 interacting proteins including Mlo3. Peptide methylation was observed on Mlo3 and 7 novel target sites with strongest methylation signals on Spbc28F2.11 (HMG box-containing protein) at lysine 292 and Hrp3 (Chromodomain ATP-dep DNA helicase) at lysine 89. These data suggest that Clr4 has additional methylation substrates and it will be important to study the biological function of these novel methylation events. Furthermore, the specificity profile of Clr4 has been used to develop a quantitative method to compare and cluster specificity profiles of PKMTs. It shows that the specificity profile of Clr4 is most similar to that of the SUV39H2 enzyme, one of its human homologs. This approach will be helpful in the comparison of the recognition profiles of other families of PKMTs as well. Copyright © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

Background-free, high sensitivity staining of proteins in one- and two-dimensional sodium dodecyl sulfate-polyacrylamide gels using a luminescent ruthenium complex.

PubMed

Berggren, K; Chernokalskaya, E; Steinberg, T H; Kemper, C; Lopez, M F; Diwu, Z; Haugland, R P; Patton, W F

2000-07-01

SYPRO Ruby dye is a permanent stain comprised of ruthenium as part of an organic complex that interacts noncovalently with proteins. SYPRO Ruby Protein Gel Stain provides a sensitive, gentle, fluorescence-based method for detecting proteins in one-dimensional and two-dimensional sodium dodecyl sulfate-polyacrylamide gels. Proteins are fixed, stained from 3h to overnight and then rinsed in deionized water or dilute methanol/acetic acid solution for 30 min. The stain can be visualized using a wide range of excitation sources commonly used in image analysis systems including a 302 nm UV-B transilluminator, 473 nm second harmonic generation (SHG) laser, 488 nm argon-ion laser, 532 nm yttrium-aluminum-garnet (YAG) laser, xenon arc lamp, blue fluorescent light bulb or blue light-emitting diode (LED). The sensitivity of SYPRO Ruby Protein Gel Stain is superior to colloidal Coomassie Brilliant Blue (CBB) stain or monobromobimane labeling and comparable with the highest sensitivity silver or zinc-imidazole staining procedures available. The linear dynamic range of SYPRO Ruby Protein Gel stain extends over three orders of magnitude, which is vastly superior to silver, zinc-imidazole, monobromobimane and CBB stain. The fluorescent stain does not contain superfluous chemicals (formaldehyde, glutaraldehyde, Tween-20) that frequently interfere with peptide identification in mass spectrometry. While peptide mass profiles are severely altered in protein samples prelabeled with monobromobimane, successful identification of proteins by peptide mass profiling using matrix-assisted laser desorption/ionization mass spectrometry was easily performed after protein detection with SYPRO Ruby Protein Gel stain.

Single-Cell, Multiplexed Protein Detection of Rare Tumor Cells Based on a Beads-on-Barcode Antibody Microarray.

PubMed

Yang, Liu; Wang, Zhihua; Deng, Yuliang; Li, Yan; Wei, Wei; Shi, Qihui

2016-11-15

Circulating tumor cells (CTCs) shed from tumor sites and represent the molecular characteristics of the tumor. Besides genetic and transcriptional characterization, it is important to profile a panel of proteins with single-cell precision for resolving CTCs' phenotype, organ-of-origin, and drug targets. We describe a new technology that enables profiling multiple protein markers of extraordinarily rare tumor cells at the single-cell level. This technology integrates a microchip consisting of 15000 60 pL-sized microwells and a novel beads-on-barcode antibody microarray (BOBarray). The BOBarray allows for multiplexed protein detection by assigning two independent identifiers (bead size and fluorescent color) of the beads to each protein. Four bead sizes (1.75, 3, 4.5, and 6 μm) and three colors (blue, green, and yellow) are utilized to encode up to 12 different proteins. The miniaturized BOBarray can fit an array of 60 pL-sized microwells that isolate single cells for cell lysis and the subsequent detection of protein markers. An enclosed 60 pL-sized microchamber defines a high concentration of proteins released from lysed single cells, leading to single-cell resolution of protein detection. The protein markers assayed in this study include organ-specific markers and drug targets that help to characterize the organ-of-origin and drug targets of isolated rare tumor cells from blood samples. This new approach enables handling a very small number of cells and achieves single-cell, multiplexed protein detection without loss of rare but clinically important tumor cells.

iTRAQ-based quantitative protein expression profiling and MRM verification of markers in type 2 diabetes.

PubMed

Kaur, Prabhjit; Rizk, Nasser M; Ibrahim, Sereen; Younes, Noura; Uppal, Arushi; Dennis, Kevin; Karve, Tejaswita; Blakeslee, Kenneth; Kwagyan, John; Zirie, Mahmoud; Ressom, Habtom W; Cheema, Amrita K

2012-11-02

The pathogenesis of Type 2 diabetes mellitus (T2DM) is complex owing to molecular heterogeneity in the afflicted population. Current diagnostic methods rely on blood glucose measurements, which are noninformative with respect to progression of the disease to other associated pathologies. Thus, predicting the risk and development of T2DM-related complications, such as cardiovascular disease, remains a major challenge. We have used a combination of quantitative methods for characterization of circulating serum biomarkers of T2DM using a cohort of nondiabetic control subjects (n = 76) and patients diagnosed with T2DM (n = 106). In this case-control study, the samples were randomly divided as training and validation data sets. In the first step, iTRAQ (isobaric tagging for relative and absolute quantification) based protein expression profiling was performed for identification of proteins displaying a significant differential expression in the two study groups. Five of these protein markers were selected for validation using multiple reaction-monitoring mass spectrometry (MRM-MS) and further confirmed with Western blot and QPCR analysis. Functional pathway analysis identified perturbations in lipid and small molecule metabolism as well as pathways that lead to disruption of glucose homeostasis and blood coagulation. These putative biomarkers may be clinically useful for subset stratification of T2DM patients as well as for the development of novel therapeutics targeting the specific pathology.

Proteomics and pathway analysis of N-glycosylated mammary gland proteins in response to Escherichia coli mastitis in cattle.

PubMed

Yang, Yongxin; Shen, Weijun; Zhao, Xiaowei; Zhao, Huiling; Huang, Dongwei; Cheng, Guanglong

2014-06-01

The aim of this study was to investigate the N-linked glycosylated protein profile of mammary tissue from healthy cows and cows with mastitis due to Escherichia coli, in order to understand the molecular mechanisms of the host response to mastitis. N-glycopeptides were enriched with a lectin mixture and identified through high-accuracy mass spectrometry. A total of 551 N-glycosylation sites, corresponding to 294 proteins, were identified in the mammary tissues of healthy cows; these glycoproteins were categorised into three functional groups and clustered into 11 specific pathways. A total of 511 N-glycosylation sites, corresponding to 283 glycosylated proteins, were detected in the mammary tissues of cows with E. coli mastitis. There were differences in N-glycosylation sites in 98 proteins in the mammary tissues of healthy cows and cows with mastitis due to E. coli. Most proteins with altered glycosylation were those involved in responses to stress, cell adhesion and the immune response, and were assigned to five specific pathways based on their gene ontology annotation. The results from this study show that the glycosylated protein profile in the mammary tissues of healthy and mastitic cows are different, and altered glycoproteins are associated with several pathways, including the lysosome and O-glycan biosynthesis pathways. Copyright © 2014. Published by Elsevier Ltd.

Cassava root membrane proteome reveals activities during storage root maturation.

PubMed

Naconsie, Maliwan; Lertpanyasampatha, Manassawe; Viboonjun, Unchera; Netrphan, Supatcharee; Kuwano, Masayoshi; Ogasawara, Naotake; Narangajavana, Jarunya

2016-01-01

Cassava (Manihot esculenta Crantz) is one of the most important crops of Thailand. Its storage roots are used as food, feed, starch production, and be the important source for biofuel and biodegradable plastic production. Despite the importance of cassava storage roots, little is known about the mechanisms involved in their formation. This present study has focused on comparison of the expression profiles of cassava root proteome at various developmental stages using two-dimensional gel electrophoresis and LC-MS/MS. Based on an anatomical study using Toluidine Blue, the secondary growth was confirmed to be essential during the development of cassava storage root. To investigate biochemical processes occurring during storage root maturation, soluble and membrane proteins were isolated from storage roots harvested from 3-, 6-, 9-, and 12-month-old cassava plants. The proteins with differential expression pattern were analysed and identified to be associated with 8 functional groups: protein folding and degradation, energy, metabolism, secondary metabolism, stress response, transport facilitation, cytoskeleton, and unclassified function. The expression profiling of membrane proteins revealed the proteins involved in protein folding and degradation, energy, and cell structure were highly expressed during early stages of development. Integration of these data along with the information available in genome and transcriptome databases is critical to expand knowledge obtained solely from the field of proteomics. Possible role of identified proteins were discussed in relation with the activities during storage root maturation in cassava.

Ancient thioredoxins evolved to modern-day stability-function requirement by altering native state ensemble.

PubMed

Modi, Tushar; Huihui, Jonathan; Ghosh, Kingshuk; Ozkan, S Banu

2018-06-19

Thioredoxins (THRXs)-small globular proteins that reduce other proteins-are ubiquitous in all forms of life, from Archaea to mammals. Although ancestral thioredoxins share sequential and structural similarity with the modern-day (extant) homologues, they exhibit significantly different functional activity and stability. We investigate this puzzle by comparative studies of their (ancient and modern-day THRXs') native state ensemble, as quantified by the dynamic flexibility index (DFI), a metric for the relative resilience of an amino acid to perturbations in the rest of the protein. Clustering proteins using DFI profiles strongly resemble an alternative classification scheme based on their activity and stability. The DFI profiles of the extant proteins are substantially different around the α3, α4 helices and catalytic regions. Likewise, allosteric coupling of the active site with the rest of the protein is different between ancient and extant THRXs, possibly explaining the decreased catalytic activity at low pH with evolution. At a global level, we note that the population of low-flexibility (called hinges) and high-flexibility sites increases with evolution. The heterogeneity (quantified by the variance) in DFI distribution increases with the decrease in the melting temperature typically associated with the evolution of ancient proteins to their modern-day counterparts.This article is part of a discussion meeting issue 'Allostery and molecular machines'. © 2018 The Author(s).

Profiling the Serum Protein Corona of Fibrillar Human Islet Amyloid Polypeptide.

PubMed

Pilkington, Emily H; Gustafsson, Ove J R; Xing, Yanting; Hernandez-Fernaud, Juan; Zampronio, Cleidi; Kakinen, Aleksandr; Faridi, Ava; Ding, Feng; Wilson, Paul; Ke, Pu Chun; Davis, Thomas P

2018-05-16

Amyloids may be regarded as native nanomaterials that form in the presence of complex protein mixtures. By drawing an analogy with the physicochemical properties of nanoparticles in biological fluids, we hypothesized that amyloids should form a protein corona in vivo that would imbue the underlying amyloid with a modified biological identity. To explore this hypothesis, we characterized the protein corona of human islet amyloid polypeptide (IAPP) fibrils in fetal bovine serum using two complementary methodologies developed herein: quartz crystal microbalance and "centrifugal capture", coupled with nanoliquid chromatography tandem mass spectroscopy. Clear evidence for a significant protein corona was obtained. No trends were identified for amyloid corona proteins based on their physicochemical properties, whereas strong binding with IAPP fibrils occurred for linear proteins or multidomain proteins with structural plasticity. Proteomic analysis identified amyloid-enriched proteins that are known to play significant roles in mediating cellular machinery and processing, potentially leading to pathological outcomes and therapeutic targets.

Amino Acid Profiles in Term and Preterm Human Milk through Lactation: A Systematic Review

PubMed Central

Zhang, Zhiying; Adelman, Alicia S.; Rai, Deshanie; Boettcher, Julia; Lőnnerdal, Bo

2013-01-01

Amino acid profile is a key aspect of human milk (HM) protein quality. We report a systematic review of total amino acid (TAA) and free amino acid (FAA) profiles, in term and preterm HM derived from 13 and 19 countries, respectively. Of the 83 studies that were critically reviewed, 26 studies with 3774 subjects were summarized for TAA profiles, while 22 studies with 4747 subjects were reviewed for FAA. Effects of gestational age, lactation stage, and geographical region were analyzed by Analysis of Variance. Data on total nitrogen (TN) and TAA composition revealed general inter-study consistency, whereas FAA concentrations varied among studies. TN and all TAA declined in the first two months of lactation and then remained relatively unchanged. In contrast, the FAA glutamic acid and glutamine increased, peaked around three to six months, and then declined. Some significant differences were observed for TAA and FAA, based on gestational age and region. Most regional TAA and FAA data were derived from Asia and Europe, while information from Africa was scant. This systematic review represents a useful evaluation of the amino acid composition of human milk, which is valuable for the assessment of protein quality of breast milk substitutes. PMID:24288022

Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells.

PubMed

Zhu, Ying; Piehowski, Paul D; Zhao, Rui; Chen, Jing; Shen, Yufeng; Moore, Ronald J; Shukla, Anil K; Petyuk, Vladislav A; Campbell-Thompson, Martha; Mathews, Clayton E; Smith, Richard D; Qian, Wei-Jun; Kelly, Ryan T

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

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

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui

Nanoscale or single cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (Nanodroplet Processing in One pot for Trace Samples) platform as a major advance in overall sensitivity. NanoPOTS dramatically enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive LC-MS, nanoPOTS allows identification of ~1500 to ~3,000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runsmore » algorithm of MaxQuant, >3000 proteins were consistently identified from as few as 10 cells. Furthermore, we demonstrate robust quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

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

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Graph Based Study of Allergen Cross-Reactivity of Plant Lipid Transfer Proteins (LTPs) Using Microarray in a Multicenter Study

PubMed Central

Palacín, Arantxa; Gómez-Casado, Cristina; Rivas, Luis A.; Aguirre, Jacobo; Tordesillas, Leticia; Bartra, Joan; Blanco, Carlos; Carrillo, Teresa; Cuesta-Herranz, Javier; de Frutos, Consolación; Álvarez-Eire, Genoveva García; Fernández, Francisco J.; Gamboa, Pedro; Muñoz, Rosa; Sánchez-Monge, Rosa; Sirvent, Sofía; Torres, María J.; Varela-Losada, Susana; Rodríguez, Rosalía; Parro, Victor; Blanca, Miguel; Salcedo, Gabriel; Díaz-Perales, Araceli

2012-01-01

The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens. PMID:23272072

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

DOE PAGES

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui; ...

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Exposure to an extremely low-frequency electromagnetic field only slightly modifies the proteome of Chromobacterium violaceumATCC 12472.

PubMed

Baraúna, Rafael A; Santos, Agenor V; Graças, Diego A; Santos, Daniel M; Ghilardi, Rubens; Pimenta, Adriano M C; Carepo, Marta S P; Schneider, Maria P C; Silva, Artur

2015-05-01

Several studies of the physiological responses of different organisms exposed to extremely low-frequency electromagnetic fields (ELF-EMF) have been described. In this work, we report the minimal effects of in situ exposure to ELF-EMF on the global protein expression of Chromobacterium violaceum using a gel-based proteomic approach. The protein expression profile was only slightly altered, with five differentially expressed proteins detected in the exposed cultures; two of these proteins (DNA-binding stress protein, Dps, and alcohol dehydrogenase) were identified by MS/MS. The enhanced expression of Dps possibly helped to prevent physical damage to DNA. Although small, the changes in protein expression observed here were probably beneficial in helping the bacteria to adapt to the stress generated by the electromagnetic field.

Conformational changes in proteins recovered from jumbo squid (Dosidicus gigas) muscle through pH shift washing treatments.

PubMed

Cortés-Ruiz, Juan A; Pacheco-Aguilar, Ramón; Ramírez-Suárez, Juan C; Lugo-Sánchez, Maria E; García-Orozco, Karina D; Sotelo-Mundo, Rogerio R; Peña-Ramos, Aida

2016-04-01

Conformational and thermal-rheological properties of acidic (APC) and neutral (NPC) protein concentrates were evaluated and compared to those of squid (Dosidicus gigas) muscle proteins (SM). Surface hydrophobicity, sulfhydryl status, secondary structure profile, differential scanning calorimetry and oscillatory dynamic rheology were used to evaluate the effect of treatments on protein properties. Acidic condition during the washing process (APC) promoted structural and conformational changes in the protein present in the concentrate produced. These changes were enhanced during the heat setting of the corresponding sol. Results demonstrate that washing squid muscle under the proposed acidic conditions is a feasible technological alternative for squid-based surimi production improving its yield and gel-forming ability. Copyright © 2015. Published by Elsevier Ltd.

On a Molecular Basis, Investigate Association of Molecular Structure with Bioactive Compounds, Anti-Nutritional Factors and Chemical and Nutrient Profiles of Canola Seeds and Co-Products from Canola Processing: Comparison Crusher Plants within Canada and within China as well as between Canada and China.

PubMed

Gomaa, Walaa M S; Mosaad, Gamal M; Yu, Peiqiang

2018-04-21

The objectives of this study were to: (1) Use molecular spectroscopy as a novel technique to quantify protein molecular structures in relation to its chemical profiles and bioenergy values in oil-seeds and co-products from bio-oil processing. (2) Determine and compare: (a) protein molecular structure using Fourier transform infrared (FT/IR-ATR) molecular spectroscopy technique; (b) bioactive compounds, anti-nutritional factors, and chemical composition; and (c) bioenergy values in oil seeds (canola seeds), co-products (meal or pellets) from bio-oil processing plants in Canada in comparison with China. (3) Determine the relationship between protein molecular structural features and nutrient profiles in oil-seeds and co-products from bio-oil processing. Our results showed the possibility to characterize protein molecular structure using FT/IR molecular spectroscopy. Processing induced changes between oil seeds and co-products were found in the chemical, bioenergy profiles and protein molecular structure. However, no strong correlation was found between the chemical and nutrient profiles of oil seeds (canola seeds) and their protein molecular structure. On the other hand, co-products were strongly correlated with protein molecular structure in the chemical profile and bioenergy values. Generally, comparisons of oil seeds (canola seeds) and co-products (meal or pellets) in Canada, in China, and between Canada and China indicated the presence of variations among different crusher plants and bio-oil processing products.

Classification of Phylogenetic Profiles for Protein Function Prediction: An SVM Approach

NASA Astrophysics Data System (ADS)

Kotaru, Appala Raju; Joshi, Ramesh C.

Predicting the function of an uncharacterized protein is a major challenge in post-genomic era due to problems complexity and scale. Having knowledge of protein function is a crucial link in the development of new drugs, better crops, and even the development of biochemicals such as biofuels. Recently numerous high-throughput experimental procedures have been invented to investigate the mechanisms leading to the accomplishment of a protein’s function and Phylogenetic profile is one of them. Phylogenetic profile is a way of representing a protein which encodes evolutionary history of proteins. In this paper we proposed a method for classification of phylogenetic profiles using supervised machine learning method, support vector machine classification along with radial basis function as kernel for identifying functionally linked proteins. We experimentally evaluated the performance of the classifier with the linear kernel, polynomial kernel and compared the results with the existing tree kernel. In our study we have used proteins of the budding yeast saccharomyces cerevisiae genome. We generated the phylogenetic profiles of 2465 yeast genes and for our study we used the functional annotations that are available in the MIPS database. Our experiments show that the performance of the radial basis kernel is similar to polynomial kernel is some functional classes together are better than linear, tree kernel and over all radial basis kernel outperformed the polynomial kernel, linear kernel and tree kernel. In analyzing these results we show that it will be feasible to make use of SVM classifier with radial basis function as kernel to predict the gene functionality using phylogenetic profiles.

Application of Large-Scale Aptamer-Based Proteomic Profiling to Planned Myocardial Infarctions.

PubMed

Jacob, Jaison; Ngo, Debby; Finkel, Nancy; Pitts, Rebecca; Gleim, Scott; Benson, Mark D; Keyes, Michelle J; Farrell, Laurie A; Morgan, Thomas; Jennings, Lori L; Gerszten, Robert E

2018-03-20

Emerging proteomic technologies using novel affinity-based reagents allow for efficient multiplexing with high-sample throughput. To identify early biomarkers of myocardial injury, we recently applied an aptamer-based proteomic profiling platform that measures 1129 proteins to samples from patients undergoing septal alcohol ablation for hypertrophic cardiomyopathy, a human model of planned myocardial injury. Here, we examined the scalability of this approach using a markedly expanded platform to study a far broader range of human proteins in the context of myocardial injury. We applied a highly multiplexed, expanded proteomic technique that uses single-stranded DNA aptamers to assay 4783 human proteins (4137 distinct human gene targets) to derivation and validation cohorts of planned myocardial injury, individuals with spontaneous myocardial infarction, and at-risk controls. We found 376 target proteins that significantly changed in the blood after planned myocardial injury in a derivation cohort (n=20; P <1.05E-05, 1-way repeated measures analysis of variance, Bonferroni threshold). Two hundred forty-seven of these proteins were validated in an independent planned myocardial injury cohort (n=15; P <1.33E-04, 1-way repeated measures analysis of variance); >90% were directionally consistent and reached nominal significance in the validation cohort. Among the validated proteins that were increased within 1 hour after planned myocardial injury, 29 were also elevated in patients with spontaneous myocardial infarction (n=63; P <6.17E-04). Many of the novel markers identified in our study are intracellular proteins not previously identified in the peripheral circulation or have functional roles relevant to myocardial injury. For example, the cardiac LIM protein, cysteine- and glycine-rich protein 3, is thought to mediate cardiac mechanotransduction and stress responses, whereas the mitochondrial ATP synthase F 0 subunit component is a vasoactive peptide on its release from cells. Last, we performed aptamer-affinity enrichment coupled with mass spectrometry to technically verify aptamer specificity for a subset of the new biomarkers. Our results demonstrate the feasibility of large-scale aptamer multiplexing at a level that has not previously been reported and with sample throughput that greatly exceeds other existing proteomic methods. The expanded aptamer-based proteomic platform provides a unique opportunity for biomarker and pathway discovery after myocardial injury. © 2017 American Heart Association, Inc.

Identification of widespread adenosine nucleotide binding in Mycobacterium tuberculosis

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

Ansong, Charles; Ortega, Corrie; Payne, Samuel H.

The annotation of protein function is almost completely performed by in silico approaches. However, computational prediction of protein function is frequently incomplete and error prone. In Mycobacterium tuberculosis (Mtb), ~25% of all genes have no predicted function and are annotated as hypothetical proteins. This lack of functional information severely limits our understanding of Mtb pathogenicity. Current tools for experimental functional annotation are limited and often do not scale to entire protein families. Here, we report a generally applicable chemical biology platform to functionally annotate bacterial proteins by combining activity-based protein profiling (ABPP) and quantitative LC-MS-based proteomics. As an example ofmore » this approach for high-throughput protein functional validation and discovery, we experimentally annotate the families of ATP-binding proteins in Mtb. Our data experimentally validate prior in silico predictions of >250 ATPases and adenosine nucleotide-binding proteins, and reveal 73 hypothetical proteins as novel ATP-binding proteins. We identify adenosine cofactor interactions with many hypothetical proteins containing a diversity of unrelated sequences, providing a new and expanded view of adenosine nucleotide binding in Mtb. Furthermore, many of these hypothetical proteins are both unique to Mycobacteria and essential for infection, suggesting specialized functions in mycobacterial physiology and pathogenicity. Thus, we provide a generally applicable approach for high throughput protein function discovery and validation, and highlight several ways in which application of activity-based proteomics data can improve the quality of functional annotations to facilitate novel biological insights.« less

Global Analysis of Viral Infection in an Archaeal Model System

PubMed Central

Maaty, Walid S.; Steffens, Joseph D.; Heinemann, Joshua; Ortmann, Alice C.; Reeves, Benjamin D.; Biswas, Swapan K.; Dratz, Edward A.; Grieco, Paul A.; Young, Mark J.; Bothner, Brian

2012-01-01

The origin and evolutionary relationship of viruses is poorly understood. This makes archaeal virus-host systems of particular interest because the hosts generally root near the base of phylogenetic trees, while some of the viruses have clear structural similarities to those that infect prokaryotic and eukaryotic cells. Despite the advantageous position for use in evolutionary studies, little is known about archaeal viruses or how they interact with their hosts, compared to viruses of bacteria and eukaryotes. In addition, many archaeal viruses have been isolated from extreme environments and present a unique opportunity for elucidating factors that are important for existence at the extremes. In this article we focus on virus-host interactions using a proteomics approach to study Sulfolobus Turreted Icosahedral Virus (STIV) infection of Sulfolobus solfataricus P2. Using cultures grown from the ATCC cell stock, a single cycle of STIV infection was sampled six times over a 72 h period. More than 700 proteins were identified throughout the course of the experiments. Seventy one host proteins were found to change their concentration by nearly twofold (p < 0.05) with 40 becoming more abundant and 31 less abundant. The modulated proteins represent 30 different cell pathways and 14 clusters of orthologous groups. 2D gel analysis showed that changes in post-translational modifications were a common feature of the affected proteins. The results from these studies showed that the prokaryotic antiviral adaptive immune system CRISPR-associated proteins (CAS proteins) were regulated in response to the virus infection. It was found that regulated proteins come from mRNAs with a shorter than average half-life. In addition, activity-based protein profiling (ABPP) profiling on 2D-gels showed caspase, hydrolase, and tyrosine phosphatase enzyme activity labeling at the protein isoform level. Together, this data provides a more detailed global view of archaeal cellular responses to viral infection, demonstrates the power of quantitative two-dimensional differential gel electrophoresis and ABPP using 2D gel compatible fluorescent dyes. PMID:23233852

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

DOE PAGES

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R.; ...

2015-06-18

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland.more » AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.« less

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

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

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R.

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland.more » AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.« less

An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis

PubMed Central

Brender, Jeffrey R.; Czajka, Jeff; Marsh, David; Gray, Felicia; Cierpicki, Tomasz; Zhang, Yang

2013-01-01

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality. PMID:24204234

Artemisinin activity-based probes identify multiple molecular targets within the asexual stage of the malaria parasites Plasmodium falciparum 3D7

PubMed Central

Ismail, Hanafy M.; Barton, Victoria; Phanchana, Matthew; Charoensutthivarakul, Sitthivut; Wong, Michael H. L.; Hemingway, Janet; Biagini, Giancarlo A.; O’Neill, Paul M.; Ward, Stephen A.

2016-01-01

The artemisinin (ART)-based antimalarials have contributed significantly to reducing global malaria deaths over the past decade, but we still do not know how they kill parasites. To gain greater insight into the potential mechanisms of ART drug action, we developed a suite of ART activity-based protein profiling probes to identify parasite protein drug targets in situ. Probes were designed to retain biological activity and alkylate the molecular target(s) of Plasmodium falciparum 3D7 parasites in situ. Proteins tagged with the ART probe can then be isolated using click chemistry before identification by liquid chromatography–MS/MS. Using these probes, we define an ART proteome that shows alkylated targets in the glycolytic, hemoglobin degradation, antioxidant defense, and protein synthesis pathways, processes essential for parasite survival. This work reveals the pleiotropic nature of the biological functions targeted by this important class of antimalarial drugs. PMID:26858419

Major surfome and secretome profile of Streptococcus agalactiae from Nile tilapia (Oreochromis niloticus): Insight into vaccine development.

PubMed

Li, Wei; Wang, Hai-Qing; He, Run-Zhen; Li, Yan-Wei; Su, You-Lu; Li, An-Xing

2016-08-01

Streptococcus agalactiae is a major piscine pathogen that is responsible for huge economic losses to the aquaculture industry. Safe recombinant vaccines, based on a small number of antigenic proteins, are emerging as the most attractive, cost-effective solution against S. agalactiae. The proteins of S. agalactiae exposed to the environment, including surface proteins and secretory proteins, are important targets for the immune system and they are likely to be good vaccine candidates. To obtain a precise profile of its surface proteins, S. agalactiae strain THN0901, which was isolated from tilapia (Oreochromis niloticus), was treated with proteinase K to cleave surface-exposed proteins, which were identified by liquid chromatography-tandem spectrometry (LC-MS/MS). Forty surface-associated proteins were identified, including ten proteins containing cell wall-anchoring motifs, eight lipoproteins, eleven membrane proteins, seven secretory proteins, three cytoplasmic proteins, and one unknown protein. In addition, culture supernatant proteins of S. agalactiae were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and all of the Coomassie-stained bands were subsequently identified by LC-MS/MS. A total of twenty-six extracellular proteins were identified, including eleven secretory proteins, seven cell wall proteins, three membrane proteins, two cytoplasmic proteins and three unknown proteins. Of these, six highly expressed surface-associated and secretory proteins are putative to be vaccine candidate of piscine S. agalactiae. Moreover, immunogenic secreted protein, a highly expressed protein screened from the secretome in the present study, was demonstrated to induce high antibody titer in tilapia, and it conferred protection against S. agalactiae, as evidenced by the relative percent survival (RPS) 48.61± 8.45%. The data reported here narrow the scope of screening protective antigens, and provide guidance in the development of a novel vaccine against piscine S. agalactiae. Copyright © 2016 Elsevier Ltd. All rights reserved.

Enhancing the Pharmacokinetic Profile of Protein-Based Drugs

DTIC Science & Technology

2014-06-12

policy or decision, unless so designated by other documentation. 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O...activated carrier. The reactions were deglycosylated, desalted by ZipTip, and submitted for MALDI-TOF MS analysis. The 0 equivalent control reaction

Label-free quantitative proteomic analysis of human plasma-derived microvesicles to find protein signatures of abdominal aortic aneurysms.

PubMed

Martinez-Pinna, Roxana; Gonzalez de Peredo, Anne; Monsarrat, Bernard; Burlet-Schiltz, Odile; Martin-Ventura, Jose Luis

2014-08-01

To find potential biomarkers of abdominal aortic aneurysms (AAA), we performed a differential proteomic study based on human plasma-derived microvesicles. Exosomes and microparticles isolated from plasma of AAA patients and control subjects (n = 10 each group) were analyzed by a label-free quantitative MS-based strategy. Homemade and publicly available software packages have been used for MS data analysis. The application of two kinds of bioinformatic tools allowed us to find differential protein profiles from AAA patients. Some of these proteins found by the two analysis methods belong to main pathological mechanisms of AAA such as oxidative stress, immune-inflammation, and thrombosis. Data analysis from label-free MS-based experiments requires the use of sophisticated bioinformatic approaches to perform quantitative studies from complex protein mixtures. The application of two of these bioinformatic tools provided us a preliminary list of differential proteins found in plasma-derived microvesicles not previously associated to AAA, which could help us to understand the pathological mechanisms related to this disease. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A chemogenomic analysis of the human proteome: application to enzyme families.

PubMed

Bernasconi, Paul; Chen, Min; Galasinski, Scott; Popa-Burke, Ioana; Bobasheva, Anna; Coudurier, Louis; Birkos, Steve; Hallam, Rhonda; Janzen, William P

2007-10-01

Sequence-based phylogenies (SBP) are well-established tools for describing relationships between proteins. They have been used extensively to predict the behavior and sensitivity toward inhibitors of enzymes within a family. The utility of this approach diminishes when comparing proteins with little sequence homology. Even within an enzyme family, SBPs must be complemented by an orthogonal method that is independent of sequence to better predict enzymatic behavior. A chemogenomic approach is demonstrated here that uses the inhibition profile of a 130,000 diverse molecule library to uncover relationships within a set of enzymes. The profile is used to construct a semimetric additive distance matrix. This matrix, in turn, defines a sequence-independent phylogeny (SIP). The method was applied to 97 enzymes (kinases, proteases, and phosphatases). SIP does not use structural information from the molecules used for establishing the profile, thus providing a more heuristic method than the current approaches, which require knowledge of the specific inhibitor's structure. Within enzyme families, SIP shows a good overall correlation with SBP. More interestingly, SIP uncovers distances within families that are not recognizable by sequence-based methods. In addition, SIP allows the determination of distance between enzymes with no sequence homology, thus uncovering novel relationships not predicted by SBP. This chemogenomic approach, used in conjunction with SBP, should prove to be a powerful tool for choosing target combinations for drug discovery programs as well as for guiding the selection of profiling and liability targets.

Mass spectrometry-based proteomic analysis of human liver cytochrome(s) P450

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

Shrivas, Kamlesh; Mindaye, Samuel T.; Getie-Kebtie, Melkamu

2013-02-15

The major objective of personalized medicine is to select optimized drug therapies and to a large degree such mission is determined by the expression profiles of cytochrome(s) P450 (CYP). Accordingly, a proteomic case study in personalized medicine is provided by the superfamily of cytochromes P450. Our knowledge about CYP isozyme expression on a protein level is very limited and based exclusively on DNA/mRNA derived data. Such information is not sufficient because transcription and translation events do not lead to correlated levels of expressed proteins. Here we report expression profiles of CYPs in human liver obtained by mass spectrometry (MS)-based proteomicmore » approach. We analyzed 32 samples of human liver microsomes (HLM) of different sexes, ages and ethnicity along with samples of recombinant human CYPs. We have experimentally confirmed that each CYP isozyme can be effectively differentiated by their unique isozyme-specific tryptic peptide(s). Trypsin digestion patterns for almost 30 human CYP isozymes were established. Those findings should assist in selecting tryptic peptides suitable for MS-based quantitation. The data obtained demonstrate remarkable differences in CYP expression profiles. CYP2E1, CYP2C8 and CYP4A11 were the only isozymes found in all HLM samples. Female and pediatric HLM samples revealed much more diverse spectrum of expressed CYPs isozymes compared to male HLM. We have confirmed expression of a number of “rare” CYP (CYP2J2, CYP4B1, CYP4V2, CYP4F3, CYP4F11, CYP8B1, CYP19A1, CYP24A1 and CYP27A1) and obtained first direct experimental data showing expression of such CYPs as CYP2F1, CYP2S1, CYP2W1, CYP4A22, CYP4X1, and CYP26A1 on a protein level. - Highlights: ► First detailed proteomic analysis of CYP isozymes expression in human liver ► Trypsin digestion patterns for almost 30 human CYP isozymes established ► The data obtained demonstrate remarkable differences in CYP expression profiles. ► Female HLM samples revealed more diverse spectrum of CYP isozymes than male. ► First data showing expression of 2F1, 2S1, 2W1, 4A22, 4X1, 26A1 on a protein level.« less

The limits of protein sequence comparison?

PubMed Central

Pearson, William R; Sierk, Michael L

2010-01-01

Modern sequence alignment algorithms are used routinely to identify homologous proteins, proteins that share a common ancestor. Homologous proteins always share similar structures and often have similar functions. Over the past 20 years, sequence comparison has become both more sensitive, largely because of profile-based methods, and more reliable, because of more accurate statistical estimates. As sequence and structure databases become larger, and comparison methods become more powerful, reliable statistical estimates will become even more important for distinguishing similarities that are due to homology from those that are due to analogy (convergence). The newest sequence alignment methods are more sensitive than older methods, but more accurate statistical estimates are needed for their full power to be realized. PMID:15919194

ProfileGrids: a sequence alignment visualization paradigm that avoids the limitations of Sequence Logos

PubMed Central

2014-01-01

Background The 2013 BioVis Contest provided an opportunity to evaluate different paradigms for visualizing protein multiple sequence alignments. Such data sets are becoming extremely large and thus taxing current visualization paradigms. Sequence Logos represent consensus sequences but have limitations for protein alignments. As an alternative, ProfileGrids are a new protein sequence alignment visualization paradigm that represents an alignment as a color-coded matrix of the residue frequency occurring at every homologous position in the aligned protein family. Results The JProfileGrid software program was used to analyze the BioVis contest data sets to generate figures for comparison with the Sequence Logo reference images. Conclusions The ProfileGrid representation allows for the clear and effective analysis of protein multiple sequence alignments. This includes both a general overview of the conservation and diversity sequence patterns as well as the interactive ability to query the details of the protein residue distributions in the alignment. The JProfileGrid software is free and available from http://www.ProfileGrid.org. PMID:25237393

Association of protein structure, protein and carbohydrate subfractions with bioenergy profiles and biodegradation functions in modeled forage

NASA Astrophysics Data System (ADS)

Ji, Cuiying; Zhang, Xuewei; Yu, Peiqiang

2016-03-01

The objectives of this study were to detect unique aspects and association of forage protein inherent structure, biological compounds, protein and carbohydrate subfractions, bioenergy profiles, and biodegradation features. In this study, common available alfalfa hay from two different sourced-origins (FSO vs. CSO) was used as a modeled forage for inherent structure profile, bioenergy, biodegradation and their association between their structure and bio-functions. The molecular spectral profiles were determined using non-invasive molecular spectroscopy. The parameters included: protein structure amide I group, amide II group and their ratios; protein subfractions (PA1, PA2, PB1, PB2, PC); carbohydrate fractions (CA1, CA2, CA3, CA4, CB1, CB2, CC); biodegradable and undegradable fractions of protein (RDPA2, RDPB1, RDPB2, RDP; RUPA2 RUPB1, RUPB2, RUPC, RUP); biodegradable and undegradable fractions of carbohydrate (RDCA4, RDCB1, RDCB2, RDCB3, RDCHO; RUCA4, RUCB1; RUCB2; RUCB3 RUCC, RUCHO) and bioenergy profiles (tdNDF, tdFA, tdCP, tdNFC, TDN1 ×, DE3 ×, ME3 ×, NEL3 ×; NEm, NEg). The results show differences in protein and carbohydrate (CHO) subfractions in the moderately degradable true protein fraction (PB1: 502 vs. 420 g/kg CP, P = 0.09), slowly degraded true protein fraction (PB2: 45 vs. 96 g/kg CP, P = 0.02), moderately degradable CHO fraction (CB2: 283 vs. 223 g/kg CHO, P = 0.06) and slowly degraded CHO fraction (CB3: 369 vs. 408 g/kg CHO) between the two sourced origins. As to biodegradable (RD) fractions of protein and CHO in rumen, there were differences in RD of PB1 (417 vs. 349 g/kg CP, P = 0.09), RD of PB2 (29 vs. 62 g/kg CP, P = 0.02), RD of CB2 (251 vs. 198 g/kg DM, P = 0.06), RD of CB3 (236 vs. 261 g/kg CHO, P = 0.08). As to bioenergy profile, there were differences in total digestible nutrient (TDN: 551 vs. 537 g/kg DM, P = 0.06), and metabolic bioenergy (P = 0.095). As to protein molecular structure, there were differences in protein structure 1st and 2nd amide groups (P < 0.10), but no difference in the 1st to 2nd amide group intensity ratios (P > 0.05). These results indicate that the sourced-origins and the internal molecular structure profiles affected biological functions, nutrient bioavailability and biodegradation.

Medium pH in submerged cultivation modulates differences in the intracellular protein profile of Fusarium oxysporum.

PubMed

da Rosa-Garzon, Nathália Gonsales; Laure, Hélen Julie; Souza-Motta, Cristina Maria de; Rosa, José César; Cabral, Hamilton

2017-08-09

Fusarium oxysporum is a filamentous fungus that damages a wide range of plants and thus causes severe crop losses. In fungal pathogens, the genes and proteins involved in virulence are known to be controlled by environmental pH. Here, we report the influence of culture-medium pH (5, 6, 7, and 8) on the production of degradative enzymes involved in the pathogenesis of F. oxysporum URM 7401 and on the 2D-electrophoresis profile of intracellular proteins in this fungus. F. oxysporum URM 7401 was grown in acidic, neutral, and alkaline culture media in a submerged bioprocess. After 96 hr, the crude extract was processed to enzyme activity assays, while the intracellular proteins were obtained from mycelium and analyzed using 2D electrophoresis and mass spectrometry. We note that the diversity of secreted enzymes was changed quantitatively in different culture-medium pH. Also, the highest accumulated biomass and the intracellular protein profile of F. oxysporum URM 7401 indicate an increase in metabolism in neutral-alkaline conditions. The differential profiles of secreted enzymes and intracellular proteins under the evaluated conditions indicate that the global protein content in F. oxysporum URM 7401 is modulated by extracellular pH.

Interaction of silver nanoparticles with proteins: a characteristic protein concentration dependent profile of SPR signal.

PubMed

Banerjee, Victor; Das, K P

2013-11-01

Silver nanoparticles are finding increasing applications in biological systems, for example as antimicrobial agents and potential candidates for control drug release systems. In all such applications, silver nanoparticles interact with proteins and other biomolecules. Hence, the study of such interactions is of considerable importance. While BSA has been extensively used as a model protein for the study of interaction with the silver nanoparticles, studies using other proteins are rather limited. The interaction of silver nanoparticles with light leads to collective oscillation of the conducting electrons giving rise to surface plasmon resonance (SPR). Here, we have studied the protein concentration dependence of the SPR band profiles for a number of proteins. We found that for all the proteins, with increase in concentration, the SPR band intensity initially decreased, reaching minima and then increased again leading to a characteristic "dip and rise" pattern. Minimum point of the pattern appeared to be related to the isoelectric point of the proteins. Detailed dynamic light scattering and transmission electron microscopy studies revealed that the consistency of SPR profile was dependent on the average particle size and state of association of the silver nanoparticles with the change in the protein concentration. Fluorescence spectroscopic studies showed the binding constants of the proteins with the silver nanoparticles were in the nano molar range with more than one nanoparticle binding to protein molecule. Structural studies demonstrate that protein retains its native-like structure on the nanoparticle surface unless the molar ratio of silver nanoparticles to protein exceeds 10. Our study reveals that nature of the protein concentration dependent profile of SPR signal is a general phenomena and mostly independent of the size and structure of the proteins. Copyright © 2013 Elsevier B.V. All rights reserved.

Multiplexed Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry Quantification of Cancer Signaling Proteins

PubMed Central

Chen, Yi; Fisher, Kate J.; Lloyd, Mark; Wood, Elizabeth R.; Coppola, Domenico; Siegel, Erin; Shibata, David; Chen, Yian A.; Koomen, John M.

2017-01-01

Quantitative evaluation of protein expression across multiple cancer-related signaling pathways (e.g. Wnt/β-catenin, TGF-β, receptor tyrosine kinases (RTK), MAP kinases, NF-κB, and apoptosis) in tumor tissues may enable the development of a molecular profile for each individual tumor that can aid in the selection of appropriate targeted cancer therapies. Here, we describe the development of a broadly applicable protocol to develop and implement quantitative mass spectrometry assays using cell line models and frozen tissue specimens from colon cancer patients. Cell lines are used to develop peptide-based assays for protein quantification, which are incorporated into a method based on SDS-PAGE protein fractionation, in-gel digestion, and liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM/MS). This analytical platform is then applied to frozen tumor tissues. This protocol can be broadly applied to the study of human disease using multiplexed LC-MRM assays. PMID:28808993

Unraveling the proteomic profile of mice testis during the initiation of meiosis.

PubMed

Shao, Binbin; Guo, Yueshuai; Wang, Lei; Zhou, Quan; Gao, Tingting; Zheng, Bo; Zheng, Haoyu; Zhou, Tao; Zhou, Zuomin; Guo, Xuejiang; Huang, Xiaoyan; Sha, Jiahao

2015-04-29

In mice, once primordial germ cells (PGCs) are generated, they continue to proliferate and migrate to eventually reach the future gonads. They initiate sexual differentiation after their colonization of the gonads. During this process, retinoic acid (RA) induces meiosis in the female germ cells, which proceeds to the diplotene stage of meiotic prophase I, whereas the male germ cells initiate growth arrest. After birth, meiosis is initiated in mice spermatogonia by their conversion to preleptotene spermatocytes. There are evidences showing the roles of RA in the regulation of spermatogonial differentiation and meiosis initiation. However, it is still not well known on what responds to RA and how RA signaling engages meiosis. Thus, we constructed a proteomic profile of proteins associated with meiosis onset during testis development in mouse and identified 104 differentially expressed proteins (≥1.5 folds). Bioinformatic analysis showed proteins functioning in specific cell processes. The expression patterns of five selected proteins were verified via Western blot, of which we found that Tfrc gene was RA responsive, with a RA responsive element, and could be up regulated by RA in spermatogonial stem cell (SSC) line. Taken together, the results provide an important reference profile for further functional study of meiosis initiation. Spermatogenesis involves mitosis of spermatogonia, meiosis of spermatocytes and spermiogenesis, in which meiosis is a unique event to germ cells, and not in the somatic cells. Till now, the detailed molecular mechanisms of the transition from mitosis to meiosis are still not elucidated. With high-throughput proteomic technology, it is now possible to systemically identify proteins possibly involved. With TMT-6plex based quantification, we identified 104 proteins differentially between testes without meiosis (day 8.5) and those that were meiosis initiated (day 10.5). And a well-known protein essential for meiosis initiation, stra8, was identified to be differentially expressed in the study. And bioinformatic analysis and functional studies revealed several proteins regulated by retinoic acid, a chemical known to regulate the meiosis initiation. Thus, this quantitative proteomic approach can identify meiosis initiation regulating proteins, and further functional studies of these proteins will help elucidate the mechanisms of meiosis initiation. Copyright © 2015. Published by Elsevier B.V.

Classification of Ancient Mammal Individuals Using Dental Pulp MALDI-TOF MS Peptide Profiling

PubMed Central

Tran, Thi-Nguyen-Ny; Aboudharam, Gérard; Gardeisen, Armelle; Davoust, Bernard; Bocquet-Appel, Jean-Pierre; Flaudrops, Christophe; Belghazi, Maya; Raoult, Didier; Drancourt, Michel

2011-01-01

Background The classification of ancient animal corpses at the species level remains a challenging task for forensic scientists and anthropologists. Severe damage and mixed, tiny pieces originating from several skeletons may render morphological classification virtually impossible. Standard approaches are based on sequencing mitochondrial and nuclear targets. Methodology/Principal Findings We present a method that can accurately classify mammalian species using dental pulp and mass spectrometry peptide profiling. Our work was organized into three successive steps. First, after extracting proteins from the dental pulp collected from 37 modern individuals representing 13 mammalian species, trypsin-digested peptides were used for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis. The resulting peptide profiles accurately classified every individual at the species level in agreement with parallel cytochrome b gene sequencing gold standard. Second, using a 279–modern spectrum database, we blindly classified 33 of 37 teeth collected in 37 modern individuals (89.1%). Third, we classified 10 of 18 teeth (56%) collected in 15 ancient individuals representing five mammal species including human, from five burial sites dating back 8,500 years. Further comparison with an upgraded database comprising ancient specimen profiles yielded 100% classification in ancient teeth. Peptide sequencing yield 4 and 16 different non-keratin proteins including collagen (alpha-1 type I and alpha-2 type I) in human ancient and modern dental pulp, respectively. Conclusions/Significance Mass spectrometry peptide profiling of the dental pulp is a new approach that can be added to the arsenal of species classification tools for forensics and anthropology as a complementary method to DNA sequencing. The dental pulp is a new source for collagen and other proteins for the species classification of modern and ancient mammal individuals. PMID:21364886

Multilineage potential and proteomic profiling of human dental stem cells derived from a single donor

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

Patil, Rajreddy; Kumar, B. Mohana; Lee, Won-Jae

Dental tissues provide an alternative autologous source of mesenchymal stem cells (MSCs) for regenerative medicine. In this study, we isolated human dental MSCs of follicle, pulp and papilla tissue from a single donor tooth after impacted third molar extraction by excluding the individual differences. We then compared the morphology, proliferation rate, expression of MSC-specific and pluripotency markers, and in vitro differentiation ability into osteoblasts, adipocytes, chondrocytes and functional hepatocyte-like cells (HLCs). Finally, we analyzed the protein expression profiles of undifferentiated dental MSCs using 2DE coupled with MALDI-TOF-MS. Three types of dental MSCs largely shared similar morphology, proliferation potential, expression ofmore » surface markers and pluripotent transcription factors, and differentiation ability into osteoblasts, adipocytes, and chondrocytes. Upon hepatogenic induction, all MSCs were transdifferentiated into functional HLCs, and acquired hepatocyte functions by showing their ability for glycogen storage and urea production. Based on the proteome profiling results, we identified nineteen proteins either found commonly or differentially expressed among the three types of dental MSCs. In conclusion, three kinds of dental MSCs from a single donor tooth possessed largely similar cellular properties and multilineage potential. Further, these dental MSCs had similar proteomic profiles, suggesting their interchangeable applications for basic research and call therapy. - Highlights: • Isolated and characterized three types of human dental MSCs from a single donor. • MSCs of dental follicle, pulp and papilla had largely similar biological properties. • All MSCs were capable of transdifferentiating into functional hepatocyte-like cells. • 2DE proteomics with MALDI-TOF/MS identified 19 proteins in three types of MSCs. • Similar proteomic profiles suggest interchangeable applications of dental MSCs.« less

Lipid remodeling and an altered membrane-associated proteome may drive the differential effects of EPA and DHA treatment on skeletal muscle glucose uptake and protein accretion.

PubMed

Jeromson, Stewart; Mackenzie, Ivor; Doherty, Mary K; Whitfield, Phillip D; Bell, Gordon; Dick, James; Shaw, Andy; Rao, Francesco V; Ashcroft, Stephen P; Philp, Andrew; Galloway, Stuart D R; Gallagher, Iain; Hamilton, D Lee

2018-06-01

In striated muscle, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have differential effects on the metabolism of glucose and differential effects on the metabolism of protein. We have shown that, despite similar incorporation, treatment of C 2 C 12 myotubes (CM) with EPA but not DHA improves glucose uptake and protein accretion. We hypothesized that these differential effects of EPA and DHA may be due to divergent shifts in lipidomic profiles leading to altered proteomic profiles. We therefore carried out an assessment of the impact of treating CM with EPA and DHA on lipidomic and proteomic profiles. Fatty acid methyl esters (FAME) analysis revealed that both EPA and DHA led to similar but substantials changes in fatty acid profiles with the exception of arachidonic acid, which was decreased only by DHA, and docosapentanoic acid (DPA), which was increased only by EPA treatment. Global lipidomic analysis showed that EPA and DHA induced large alterations in the cellular lipid profiles and in particular, the phospholipid classes. Subsequent targeted analysis confirmed that the most differentially regulated species were phosphatidylcholines and phosphatidylethanolamines containing long-chain fatty acids with five (EPA treatment) or six (DHA treatment) double bonds. As these are typically membrane-associated lipid species we hypothesized that these treatments differentially altered the membrane-associated proteome. Stable isotope labeling by amino acids in cell culture (SILAC)-based proteomics of the membrane fraction revealed significant divergence in the effects of EPA and DHA on the membrane-associated proteome. We conclude that the EPA-specific increase in polyunsaturated long-chain fatty acids in the phospholipid fraction is associated with an altered membrane-associated proteome and these may be critical events in the metabolic remodeling induced by EPA treatment.

A robust mass spectrometry method for rapid profiling of erythrocyte ghost membrane proteomes.

PubMed

Fye, Haddy K S; Mrosso, Paul; Bruce, Lesley; Thézénas, Marie-Laëtitia; Davis, Simon; Fischer, Roman; Rwegasira, Gration L; Makani, Julie; Kessler, Benedikt M

2018-01-01

Red blood cell (RBC) physiology is directly linked to many human disorders associated with low tissue oxygen levels or anemia including chronic obstructive pulmonary disease, congenital heart disease, sleep apnea and sickle cell anemia. Parasites such as Plasmodium spp. and phylum Apicomplexa directly target RBCs, and surface molecules within the RBC membrane are critical for pathogen interactions. Proteomics of RBC membrane 'ghost' fractions has therefore been of considerable interest, but protocols described to date are either suboptimal or too extensive to be applicable to a larger set of clinical cohorts. Here, we describe an optimised erythrocyte isolation protocol from blood, tested for various storage conditions and explored using different fractionation conditions for isolating ghost RBC membranes. Liquid chromatography mass spectrometry (LC-MS) analysis on a Q-Exactive Orbitrap instrument was used to profile proteins isolated from the comparative conditions. Data analysis was run on the MASCOT and MaxQuant platforms to assess their scope and diversity. The results obtained demonstrate a robust method for membrane enrichment enabling consistent MS based characterisation of > 900 RBC membrane proteins in single LC-MS/MS analyses. Non-detergent based membrane solubilisation methods using the tissue and supernatant fractions of isolated ghost membranes are shown to offer effective haemoglobin removal as well as diverse recovery including erythrocyte membrane proteins of high and low abundance. The methods described in this manuscript propose a medium to high throughput framework for membrane proteome profiling by LC-MS of potential applicability to larger clinical cohorts in a variety of disease contexts.

Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213

PubMed Central

2012-01-01

Background Computational methods for structural gene annotation have propelled gene discovery but face certain drawbacks with regards to prokaryotic genome annotation. Identification of transcriptional start sites, demarcating overlapping gene boundaries, and identifying regulatory elements such as small RNA are not accurate using these approaches. In this study, we re-visit the structural annotation of Mannheimia haemolytica PHL213, a bovine respiratory disease pathogen. M. haemolytica is one of the causative agents of bovine respiratory disease that results in about $3 billion annual losses to the cattle industry. We used RNA-Seq and analyzed the data using freely-available computational methods and resources. The aim was to identify previously unannotated regions of the genome using RNA-Seq based expression profile to complement the existing annotation of this pathogen. Results Using the Illumina Genome Analyzer, we generated 9,055,826 reads (average length ~76 bp) and aligned them to the reference genome using Bowtie. The transcribed regions were analyzed using SAMTOOLS and custom Perl scripts in conjunction with BLAST searches and available gene annotation information. The single nucleotide resolution map enabled the identification of 14 novel protein coding regions as well as 44 potential novel sRNA. The basal transcription profile revealed that 2,506 of the 2,837 annotated regions were expressed in vitro, at 95.25% coverage, representing all broad functional gene categories in the genome. The expression profile also helped identify 518 potential operon structures involving 1,086 co-expressed pairs. We also identified 11 proteins with mutated/alternate start codons. Conclusions The application of RNA-Seq based transcriptome profiling to structural gene annotation helped correct existing annotation errors and identify potential novel protein coding regions and sRNA. We used computational tools to predict regulatory elements such as promoters and terminators associated with the novel expressed regions for further characterization of these novel functional elements. Our study complements the existing structural annotation of Mannheimia haemolytica PHL213 based on experimental evidence. Given the role of sRNA in virulence gene regulation and stress response, potential novel sRNA described in this study can form the framework for future studies to determine the role of sRNA, if any, in M. haemolytica pathogenesis. PMID:23046475

The overnight effect of dietary energy balance on postprandial plasma free amino acid (PFAA) profiles in Japanese adult men.

PubMed

Nishioka, Manabu; Imaizumi, Akira; Ando, Toshihiko; Tochikubo, Osamu

2013-01-01

The plasma free amino acid (PFAA) profile is affected by various nutritional conditions, such as the dietary energy balance. Regarding the clinical use of PFAA profiling, it is of concern that differences in food ingestion patterns may generate systematic errors in a plasma amino acid profile and constitute a confounding factor in assessment. In this study, the overnight impact of the dietary energy balance on the postprandial plasma amino acid profile was investigated to elucidate in particular the effects of high protein meals typical in Japanese cuisine. We conducted diet-controlled, crossover trials in eleven healthy male volunteers aged 40-61 y. They consumed either a normal meal (meal N) or high protein meal (meal H) at dinner. Forearm venous blood was collected, and plasma amino acid concentrations were measured before dinner and the next morning. We found that a high protein meal in the evening that contained 40% energy would significantly increase the PFAA concentration the next morning, even more than 12 hours after the meal. Among amino acids, the most significant difference was observed in the branched-chain amino acids (BCAAs) and in some urea-cycle related compounds. If the subject consumed the high protein diet at dinner, the PFAA profile after overnight fasting might be still affected by the meal even 12 hours after the meal, suggesting that the PFAA profile does not reflect the subject's health condition, but rather the acute effect of high protein ingestion.

The Overnight Effect of Dietary Energy Balance on Postprandial Plasma Free Amino Acid (PFAA) Profiles in Japanese Adult Men

PubMed Central

Nishioka, Manabu; Imaizumi, Akira; Ando, Toshihiko; Tochikubo, Osamu

2013-01-01

The plasma free amino acid (PFAA) profile is affected by various nutritional conditions, such as the dietary energy balance. Regarding the clinical use of PFAA profiling, it is of concern that differences in food ingestion patterns may generate systematic errors in a plasma amino acid profile and constitute a confounding factor in assessment. In this study, the overnight impact of the dietary energy balance on the postprandial plasma amino acid profile was investigated to elucidate in particular the effects of high protein meals typical in Japanese cuisine. We conducted diet-controlled, crossover trials in eleven healthy male volunteers aged 40–61 y. They consumed either a normal meal (meal N) or high protein meal (meal H) at dinner. Forearm venous blood was collected, and plasma amino acid concentrations were measured before dinner and the next morning. We found that a high protein meal in the evening that contained 40% energy would significantly increase the PFAA concentration the next morning, even more than 12 hours after the meal. Among amino acids, the most significant difference was observed in the branched-chain amino acids (BCAAs) and in some urea-cycle related compounds. If the subject consumed the high protein diet at dinner, the PFAA profile after overnight fasting might be still affected by the meal even 12 hours after the meal, suggesting that the PFAA profile does not reflect the subject's health condition, but rather the acute effect of high protein ingestion. PMID:23667542

Activity Based Protein Profiling Leads to Identification of Novel Protein Targets for Nerve Agent VX.

PubMed

Carmany, Dan; Walz, Andrew J; Hsu, Fu-Lian; Benton, Bernard; Burnett, David; Gibbons, Jennifer; Noort, Daan; Glaros, Trevor; Sekowski, Jennifer W

2017-04-17

Organophosphorus (OP) nerve agents continue to be a threat at home and abroad during the war against terrorism. Human exposure to nerve agents such as VX results in a cascade of toxic effects relative to the exposure level including ocular miosis, excessive secretions, convulsions, seizures, and death. The primary mechanism behind these overt symptoms is the disruption of cholinergic pathways. While much is known about the primary toxicity mechanisms of nerve agents, there remains a paucity of information regarding impacts on other pathways and systemic effects. These are important for establishing a comprehensive understanding of the toxic mechanisms of OP nerve agents. To identify novel proteins that interact with VX, and that may give insight into these other mechanisms, we used activity-based protein profiling (ABPP) employing a novel VX-probe on lysates from rat heart, liver, kidney, diaphragm, and brain tissue. By making use of a biotin linked VX-probe, proteins covalently bound by the probe were isolated and enriched using streptavidin beads. The proteins were then digested, labeled with isobarically distinct tandem mass tag (TMT) labels, and analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Quantitative analysis identified 132 bound proteins, with many proteins found in multiple tissues. As with previously published ABPP OP work, monoacylglycerol lipase associated proteins and fatty acid amide hydrolase (FAAH) were shown to be targets of VX. In addition to these two and other predicted neurotransmitter-related proteins, a number of proteins involved with energy metabolism were identified. Four of these enzymes, mitochondrial isocitrate dehydrogenase 2 (IDH2), isocitrate dehydrogenase 3 (IDH3), malate dehydrogenase (MDH), and succinyl CoA (SCS) ligase, were assayed for VX inhibition. Only IDH2 NADP+ activity was shown to be inhibited directly. This result is consistent with other work reporting animals exposed to OP compounds exhibit reduced IDH activity. Though clearly a secondary mechanism for toxicity, this is the first time VX has been shown to directly interfere with energy metabolism. Taken together, the ABPP work described here suggests the discovery of novel protein-agent interactions, which could be useful for the development of novel diagnostics or potential adjuvant therapeutics.

Protein profile in HBx transfected cells: a comparative iTRAQ-coupled 2D LC-MS/MS analysis.

PubMed

Feng, Huixing; Li, Xi; Niu, Dandan; Chen, Wei Ning

2010-06-16

The x protein of HBV (HBx) has been involved in the development of hepatocellular carcinoma (HCC), with a possible link to individual genotypes. Nevertheless, the underlying mechanism remains obscure. In this study, we aim to identify the HBx-induced protein profile in HepG2 cells by LC-MS/MS proteomics analysis. Our results indicated that proteins were differentially expressed in HepG2 cells transfected by HBx of various genotypes. Proteins associated with cytoskeleton were found to be either up-regulated (MACF1, HMGB1, Annexin A2) or down-regulated (Lamin A/C). These may in turn result in the decrease of focal adhesion and increase of cell migration in response to HBx. Levels of other cellular proteins with reported impact on the function of extracellular matrix (ECM) proteins and cell migration, including Ca(2+)-binding proteins (S100A11, S100A6, and S100A4) and proteasome protein (PSMA3), were affected by HBx. The differential protein profile identified in this study was also supported by our functional assay which indicated that cell migration was enhanced by HBx. Our preliminary study provided a new platform to establish a comprehensive cellular protein profile by LC-MS/MS proteomics analysis. Further downstream functional assays, including our reported cell migration assay, should provide new insights in the association between HCC and HBx. Copyright 2009 Elsevier B.V. All rights reserved.

New serum biomarkers for detection of tuberculosis using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Liu, Ji-Yan; Jin, Lei; Zhao, Meng-Yuan; Zhang, Xin; Liu, Chi-Bo; Zhang, Yu-Xiang; Li, Fu-Jian; Zhou, Jian-Min; Wang, Hua-Jun; Li, Ji-Cheng

2011-10-01

New technologies for the early detection of tuberculosis (TB) are urgently needed. Pathological changes within an organ might be reflected in proteomic patterns in serum. The aim of the present study was to screen for the potential protein biomarkers in serum for the diagnosis of TB using proteomic fingerprint technology. Proteomic fingerprint technology combining protein chips with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) was used to profile the serum proteins from 50 patients with TB, 25 patients with lung disease other than TB, and 25 healthy volunteers. The protein fingerprint expression of all the serum samples and the resulting profiles between TB and control groups were analyzed with the Biomarker Wizard system. A total of 30 discriminating m/z peaks were detected that were related to TB (p<0.01). The model of biomarkers constructed by the Biomarker Patterns Software based on the three biomarkers (2024, 8007, and 8598 Da) generated excellent separation between the TB and control groups. The sensitivity was 84.0% and the specificity was 86.0%. Blind test data indicated a sensitivity of 80.0% and a specificity of 84.2%. The data suggested a potential application of SELDI-TOF MS as an effective technology to profile serum proteome, and with pattern analysis, a diagnostic model comprising three potential biomarkers was indicated to differentiate people with TB and healthy controls rapidly and precisely.

Genomic and Expression Profiling of Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis Patients

DTIC Science & Technology

2005-05-01

3.2042 3164754 GAB1 GRB2-associated binding protein 1 Hs.80720 3.2026 3.58551 CAV2 Caveolin 2 Hs.212332 3.2012 2.83580 FLJ20481 Hypothetical protein...Development of in situ hybridization probes. - Testing antibodies by immunohistochemistry. REPORTABLE OUTCOMES: So far we have been in data acquisition...collaborator Dr. Torsten Nielsen at the University of British Columbia has been successful in finding an antibody against all forms of TLE (based on our gene

fRMSDPred: Predicting Local RMSD Between Structural Fragments Using Sequence Information

DTIC Science & Technology

2007-04-04

machine learning approaches for estimating the RMSD value of a pair of protein fragments. These estimated fragment-level RMSD values can be used to construct the alignment, assess the quality of an alignment, and identify high-quality alignment segments. We present algorithms to solve this fragment-level RMSD prediction problem using a supervised learning framework based on support vector regression and classification that incorporates protein profiles, predicted secondary structure, effective information encoding schemes, and novel second-order pairwise exponential kernel

Effect of an ozone injury-retardant chemical on isozyme profiles from alfalfa callus in vitro

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

Rier, J.P.; Sood, V.K.; Whitaker, A.

1983-01-01

Plant ozone injury retardant (EDU or ethylenediurea) at 1.0 ppm inhibited growth of callus of alfalfa cultivars Williamsburg (ozone-sensitive) and MSB-CW5An2(ozone-insensitive) germplasm of Medicago sative. The presence of EDU(0.1 ppm) in growth medium increased the number of protein and peroxidase isozyme bands in alfalfa cultivar stem callus and ozone modified their intensities. Protein profiles of MSB stem callus from media containing EDU or exposed to ozone were unchanged. Marked differences were observed between the peroxidase profiles of ozonated and control ozone-insensitive stem callus from media containing EDU. Protein profiles of ozonated ozone-insensitive leaf callus differed slightly from controls.

Structural phylogeny by profile extraction and multiple superimposition using electrostatic congruence as a discriminator

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

Chakraborty, Sandeep; Rao, Basuthkar J.; Baker, Nathan A.

2013-04-01

Phylogenetic analysis of proteins using multiple sequence alignment (MSA) assumes an underlying evolutionary relationship in these proteins which occasionally remains undetected due to considerable sequence divergence. Structural alignment programs have been developed to unravel such fuzzy relationships. However, none of these structure based methods have used electrostatic properties to discriminate between spatially equivalent residues. We present a methodology for MSA of a set of related proteins with known structures using electrostatic properties as an additional discriminator (STEEP). STEEP first extracts a profile, then generates a multiple structural superimposition providing a consolidated spatial framework for comparing residues and finally emits themore » MSA. Residues that are aligned differently by including or excluding electrostatic properties can be targeted by directed evolution experiments to transform the enzymatic properties of one protein into another. We have compared STEEP results to those obtained from a MSA program (ClustalW) and a structural alignment method (MUSTANG) for chymotrypsin serine proteases. Subsequently, we used PhyML to generate phylogenetic trees for the serine and metallo-β-lactamase superfamilies from the STEEP generated MSA, and corroborated the accepted relationships in these superfamilies. We have observed that STEEP acts as a functional classifier when electrostatic congruence is used as a discriminator, and thus identifies potential targets for directed evolution experiments. In summary, STEEP is unique among phylogenetic methods for its ability to use electrostatic congruence to specify mutations that might be the source of the functional divergence in a protein family. Based on our results, we also hypothesize that the active site and its close vicinity contains enough information to infer the correct phylogeny for related proteins.« less

MALDI-TOF Mass Spectrometry Enables a Comprehensive and Fast Analysis of Dynamics and Qualities of Stress Responses of Lactobacillus paracasei subsp. paracasei F19

PubMed Central

Schott, Ann-Sophie; Behr, Jürgen; Quinn, Jennifer; Vogel, Rudi F.

2016-01-01

Lactic acid bacteria (LAB) are widely used as starter cultures in the manufacture of foods. Upon preparation, these cultures undergo various stresses resulting in losses of survival and fitness. In order to find conditions for the subsequent identification of proteomic biomarkers and their exploitation for preconditioning of strains, we subjected Lactobacillus (Lb.) paracasei subsp. paracasei TMW 1.1434 (F19) to different stress qualities (osmotic stress, oxidative stress, temperature stress, pH stress and starvation stress). We analysed the dynamics of its stress responses based on the expression of stress proteins using MALDI-TOF mass spectrometry (MS), which has so far been used for species identification. Exploiting the methodology of accumulating protein expression profiles by MALDI-TOF MS followed by the statistical evaluation with cluster analysis and discriminant analysis of principle components (DAPC), it was possible to monitor the expression of low molecular weight stress proteins, identify a specific time point when the expression of stress proteins reached its maximum, and statistically differentiate types of adaptive responses into groups. Above the specific result for F19 and its stress response, these results demonstrate the discriminatory power of MALDI-TOF MS to characterize even dynamics of stress responses of bacteria and enable a knowledge-based focus on the laborious identification of biomarkers and stress proteins. To our knowledge, the implementation of MALDI-TOF MS protein profiling for the fast and comprehensive analysis of various stress responses is new to the field of bacterial stress responses. Consequently, we generally propose MALDI-TOF MS as an easy and quick method to characterize responses of microbes to different environmental conditions, to focus efforts of more elaborate approaches on time points and dynamics of stress responses. PMID:27783652

A study on maize proteins as a potential new tablet excipient.

PubMed

Georget, Dominique M R; Barker, Susan A; Belton, Peter S

2008-06-01

This investigation has examined the use of zein proteins from maize as the major component in oral controlled-release tablets, such formulations often being required to improve patient compliance. Tablets containing ground zein proteins, calcium hydrogen orthophosphate, polyvinyl pyrrolidone, theophylline and magnesium stearate were produced by wet granulation and compression on a single station tablet press and were compared to directly compressed tablets based on zein proteins, calcium hydrogen orthophosphate and theophylline. Non invasive techniques such as Fourier Transform infrared spectroscopy and Fourier Transform Raman spectroscopy were employed to investigate any changes in the secondary structure of zein proteins during tablet production. Random coils, alpha helices and beta sheets predominated and their relative content remained unaffected during grinding, wet granulation and compression, indicating that formulations based on zeins will be robust, i.e. insensitive to minor changes in the production conditions. Drug release from the tablets was studied using a standard pharmacopoeial dissolution test. Dissolution profiles in water, 0.1M HCl (pH=1) and phosphate buffer (pH=6.8) show that only a limited amount of theophylline was released after 4.5h, suggesting that zein proteins could act as a potential vehicle for oral controlled drug release. Analysis of the theophylline release profiles using the Peppas and Sahlin model reveals that diffusion and polymer relaxation occurred in acidic (pH=1) and buffered (pH=6.8) conditions for wet granulated tablets, whereas diffusion was predominant in directly compressed tablets. In conclusion, the present study has shown that zeins can be successfully used as a pharmaceutical excipient, and in particular as a matrix in monolithic controlled release tablets.

Hydrogel droplet microarrays with trapped antibody-functionalized beads for multiplexed protein analysis.

PubMed

Li, Huiyan; Leulmi, Rym Feriel; Juncker, David

2011-02-07

Antibody microarrays are a powerful tool for rapid, multiplexed profiling of proteins. 3D microarray substrates have been developed to improve binding capacity, assay sensitivity, and mass transport, however, they often rely on photopolymers which are difficult to manufacture and have a small pore size that limits mass transport and demands long incubation time. Here, we present a novel 3D antibody microarray format based on the entrapment of antibody-coated microbeads within alginate droplets that were spotted onto a glass slide using an inkjet. Owing to the low concentration of alginate used, the gels were highly porous to proteins, and together with the 3D architecture helped enhance mass transport during the assays. The spotting parameters were optimized for the attachment of the alginate to the substrate. Beads with 0.2 µm, 0.5 µm and 1 µm diameter were tested and 1 µm beads were selected based on their superior retention within the hydrogel. The beads were found to be distributed within the entire volume of the gel droplet using confocal microscopy. The assay time and the concentration of beads in the gels were investigated for maximal binding signal using one-step immunoassays. As a proof of concept, six proteins including cytokines (TNFα, IL-8 and MIP/CCL4), breast cancer biomarkers (CEA and HER2) and one cancer-related protein (ENG) were profiled in multiplex using sandwich assays down to pg mL(-1) concentrations with 1 h incubation without agitation in both buffer solutions and 10% serum. These results illustrate the potential of beads-in-gel microarrays for highly sensitive and multiplexed protein analysis.

MoRFPred-plus: Computational Identification of MoRFs in Protein Sequences using Physicochemical Properties and HMM profiles.

PubMed

Sharma, Ronesh; Bayarjargal, Maitsetseg; Tsunoda, Tatsuhiko; Patil, Ashwini; Sharma, Alok

2018-01-21

Intrinsically Disordered Proteins (IDPs) lack stable tertiary structure and they actively participate in performing various biological functions. These IDPs expose short binding regions called Molecular Recognition Features (MoRFs) that permit interaction with structured protein regions. Upon interaction they undergo a disorder-to-order transition as a result of which their functionality arises. Predicting these MoRFs in disordered protein sequences is a challenging task. In this study, we present MoRFpred-plus, an improved predictor over our previous proposed predictor to identify MoRFs in disordered protein sequences. Two separate independent propensity scores are computed via incorporating physicochemical properties and HMM profiles, these scores are combined to predict final MoRF propensity score for a given residue. The first score reflects the characteristics of a query residue to be part of MoRF region based on the composition and similarity of assumed MoRF and flank regions. The second score reflects the characteristics of a query residue to be part of MoRF region based on the properties of flanks associated around the given residue in the query protein sequence. The propensity scores are processed and common averaging is applied to generate the final prediction score of MoRFpred-plus. Performance of the proposed predictor is compared with available MoRF predictors, MoRFchibi, MoRFpred, and ANCHOR. Using previously collected training and test sets used to evaluate the mentioned predictors, the proposed predictor outperforms these predictors and generates lower false positive rate. In addition, MoRFpred-plus is a downloadable predictor, which makes it useful as it can be used as input to other computational tools. https://github.com/roneshsharma/MoRFpred-plus/wiki/MoRFpred-plus:-Download. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparative and network-based proteomic analysis of low dose ethanol- and lipopolysaccharide-induced macrophages

PubMed Central

Kamal, Abu Hena M.; Fessler, Michael B.

2018-01-01

Macrophages are specialized phagocytes that play an essential role in inflammation, immunity, and tissue repair. Profiling the global proteomic response of macrophages to microbial molecules such as bacterial lipopolysaccharide is key to understanding fundamental mechanisms of inflammatory disease. Ethanol is a widely abused substance that has complex effects on inflammation. Reports have indicated that ethanol can activate or inhibit the lipopolysaccharide receptor, Toll-like Receptor 4, in different settings, with important consequences for liver and neurologic inflammation, but the underlying mechanisms are poorly understood. To profile the sequential effect of low dose ethanol and lipopolysaccharide on macrophages, a gel-free proteomic technique was applied to RAW 264.7 macrophages. Five hundred four differentially expressed proteins were identified and quantified with high confidence using ≥ 5 peptide spectral matches. Among these, 319 proteins were shared across all treatment conditions, and 69 proteins were exclusively identified in ethanol-treated or lipopolysaccharide-stimulated cells. The interactive impact of ethanol and lipopolysaccharide on the macrophage proteome was evaluated using bioinformatics tools, enabling identification of differentially responsive proteins, protein interaction networks, disease- and function-based networks, canonical pathways, and upstream regulators. Five candidate protein coding genes (PGM2, ISYNA1, PARP1, and PSAP) were further validated by qRT-PCR that mostly related to glucose metabolism and fatty acid synthesis pathways. Taken together, this study describes for the first time at a systems level the interaction between ethanol and lipopolysaccharide in the proteomic programming of macrophages, and offers new mechanistic insights into the biology that may underlie the impact of ethanol on infectious and inflammatory disease in humans. PMID:29481576

Combining genomic and proteomic approaches for epigenetics research

PubMed Central

Han, Yumiao; Garcia, Benjamin A

2014-01-01

Epigenetics is the study of changes in gene expression or cellular phenotype that do not change the DNA sequence. In this review, current methods, both genomic and proteomic, associated with epigenetics research are discussed. Among them, chromatin immunoprecipitation (ChIP) followed by sequencing and other ChIP-based techniques are powerful techniques for genome-wide profiling of DNA-binding proteins, histone post-translational modifications or nucleosome positions. However, mass spectrometry-based proteomics is increasingly being used in functional biological studies and has proved to be an indispensable tool to characterize histone modifications, as well as DNA–protein and protein–protein interactions. With the development of genomic and proteomic approaches, combination of ChIP and mass spectrometry has the potential to expand our knowledge of epigenetics research to a higher level. PMID:23895656

WIWS: a protein structure bioinformatics Web service collection.

PubMed

Hekkelman, M L; Te Beek, T A H; Pettifer, S R; Thorne, D; Attwood, T K; Vriend, G

2010-07-01

The WHAT IF molecular-modelling and drug design program is widely distributed in the world of protein structure bioinformatics. Although originally designed as an interactive application, its highly modular design and inbuilt control language have recently enabled its deployment as a collection of programmatically accessible web services. We report here a collection of WHAT IF-based protein structure bioinformatics web services: these relate to structure quality, the use of symmetry in crystal structures, structure correction and optimization, adding hydrogens and optimizing hydrogen bonds and a series of geometric calculations. The freely accessible web services are based on the industry standard WS-I profile and the EMBRACE technical guidelines, and are available via both REST and SOAP paradigms. The web services run on a dedicated computational cluster; their function and availability is monitored daily.

Metabolic Profile as a Potential Modifier of Long-Term Radiation Effects on Peripheral Lymphocyte Subsets in Atomic Bomb Survivors.

PubMed

Yoshida, Kengo; Nakashima, Eiji; Kyoizumi, Seishi; Hakoda, Masayuki; Hayashi, Tomonori; Hida, Ayumi; Ohishi, Waka; Kusunoki, Yoichiro

2016-09-01

Immune system impairments reflected by the composition and function of circulating lymphocytes are still observed in atomic bomb survivors, and metabolic abnormalities including altered blood triglyceride and cholesterol levels have also been detected in such survivors. Based on closely related features of immune and metabolic profiles of individuals, we investigated the hypothesis that long-term effects of radiation exposure on lymphocyte subsets might be modified by metabolic profiles in 3,113 atomic bomb survivors who participated in health examinations at the Radiation Effect Research Foundation, Hiroshima and Nagasaki, in 2000-2002. The lymphocyte subsets analyzed involved T-, B- and NK-cell subsets, and their percentages in the lymphocyte fraction were assessed using flow cytometry. Health examinations included metabolic indicators, body mass index, serum levels of total cholesterol, high-density lipoprotein cholesterol, C-reactive protein and hemoglobin A1c, as well as diabetes and fatty liver diagnoses. Standard regression analyses indicated that several metabolic indicators of obesity/related disease, particularly high-density lipoprotein cholesterol levels, were positively associated with type-1 helper T- and B-cell percentages but were inversely associated with naïve CD4 T and NK cells. A regression analysis adjusted for high-density lipoprotein cholesterol revealed a radiation dose relationship with increasing NK-cell percentage. Additionally, an interaction effect was suggested between radiation dose and C-reactive protein on B-cell percentage with a negative coefficient of the interaction term. Collectively, these findings suggest that radiation exposure and subsequent metabolic profile changes, potentially in relationship to obesity-related inflammation, lead to such long-term alterations in lymphocyte subset composition. Because this study is based on cross-sectional and exploratory analyses, the implications regarding radiation exposure, metabolic profiles and circulating lymphocytes warrant future longitudinal and molecular mechanistic studies.

Host-pathogen interactions: A cholera surveillance system

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

Wright, Aaron T.

2016-02-22

Bacterial pathogen-secreted proteases may play a key role in inhibiting a potentially widespread host-pathogen interaction. Activity-based protein profiling enabled the identification of a major Vibrio cholerae serine protease that limits the ability of a host-derived intestinal lectin to bind to the bacterial pathogen in vivo.

Isolation and chemical analysis of nanoparticles from English ivy (Hedera helix L.)

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

Lenaghan, Scott C; Burris, Jason N; Chourey, Karuna

It was discovered that adventitious roots of English ivy secreted a high strength adhesive containing uniform nanoparticles. These nanoparticles were hypothesized to be organic in nature. Subsequent studies have revealed several applications for these nanoparticles, but their chemical composition remained unknown. Here, we describe an isolation procedure to obtain gram quantities of ivy nanoparticles from adventitious roots. In addition, ultraviolet/visible (UV/Vis) spectroscopy, inductively coupled plasma mass spectrometry (ICP-MS), elemental analysis, fourier transform infrared spectroscopy (FTIR), and gel electrophoresis were conducted to identify the chemical nature of the ivy nanoparticles. Based on this comprehensive analysis, we conclude that the ivy nanoparticlesmore » are proteinaceous consisting of 51.77% carbon, 4.72% nitrogen, and 0.32% sulfur, without the presence of metals. Liquid chromatography tandem mass spectrometry (LC-MS/MS) based protein profiling revealed the presence of at least 6 proteins, including heat shock proteins and other large molecular weight proteins. Identification of these protein candidates will facilitate gene discovery and bioproduction of ivy nanoparticles.« less

Profiling of integral membrane proteins and their post translational modifications using high-resolution mass spectrometry.

PubMed

Souda, Puneet; Ryan, Christopher M; Cramer, William A; Whitelegge, Julian

2011-12-01

Integral membrane proteins pose challenges to traditional proteomics approaches due to unique physicochemical properties including hydrophobic transmembrane domains that limit solubility in aqueous solvents. A well resolved intact protein molecular mass profile defines a protein's native covalent state including post-translational modifications, and is thus a vital measurement toward full structure determination. Both soluble loop regions and transmembrane regions potentially contain post-translational modifications that must be characterized if the covalent primary structure of a membrane protein is to be defined. This goal has been achieved using electrospray-ionization mass spectrometry (ESI-MS) with low-resolution mass analyzers for intact protein profiling, and high-resolution instruments for top-down experiments, toward complete covalent primary structure information. In top-down, the intact protein profile is supplemented by gas-phase fragmentation of the intact protein, including its transmembrane regions, using collisionally activated and/or electron-capture dissociation (CAD/ECD) to yield sequence-dependent high-resolution MS information. Dedicated liquid chromatography systems with aqueous/organic solvent mixtures were developed allowing us to demonstrate that polytopic integral membrane proteins are amenable to ESI-MS analysis, including top-down measurements. Covalent post-translational modifications are localized regardless of their position in transmembrane domains. Top-down measurements provide a more detail oriented high-resolution description of post-transcriptional and post-translational diversity for enhanced understanding beyond genomic translation. Copyright © 2011 Elsevier Inc. All rights reserved.

High Concentrations of Atmospheric Ammonia Induce Alterations in the Hepatic Proteome of Broilers (Gallus gallus): An iTRAQ-Based Quantitative Proteomic Analysis

PubMed Central

Zhang, Jize; Li, Cong; Tang, Xiangfang; Lu, Qingping; Sa, Renna; Zhang, Hongfu

2015-01-01

With the development of the poultry industry, ammonia, as a main contaminant in the air, is causing increasing problems with broiler health. To date, most studies of ammonia toxicity have focused on the nervous system and the gastrointestinal tract in mammals. However, few detailed studies have been conducted on the hepatic response to ammonia toxicity in poultry. The molecular mechanisms that underlie these effects remain unclear. In the present study, our group applied isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomic analysis to investigate changes in the protein profile change in hepatic tissue of broilers exposed to high concentrations of atmospheric ammonia, with the goal of characterizing the molecular mechanisms of chronic liver injury from exposure to high ambient levels of ammonia. Overall, 30 differentially expressed proteins that are involved in nutrient metabolism (energy, lipid, and amino acid), immune response, transcriptional and translational regulation, stress response, and detoxification were identified. In particular, two of these proteins, beta-1 galactosidase (GLB1) and a kinase (PRKA) anchor protein 8-like (AKAP8 L), were previously suggested to be potential biomarkers of chronic liver injury. In addition to the changes in the protein profile, serum parameters and histochemical analyses of hepatic tissue also showed extensive hepatic damage in ammonia-exposed broilers. Altogether, these findings suggest that longtime exposure to high concentrations of atmospheric ammonia can trigger chronic hepatic injury in broilers via different mechanisms, providing new information that can be used for intervention using nutritional strategies in the future. PMID:25901992

Transcription Factor NRF2 as a Therapeutic Target for Chronic Diseases: A Systems Medicine Approach.

PubMed

Cuadrado, Antonio; Manda, Gina; Hassan, Ahmed; Alcaraz, María José; Barbas, Coral; Daiber, Andreas; Ghezzi, Pietro; León, Rafael; López, Manuela G; Oliva, Baldo; Pajares, Marta; Rojo, Ana I; Robledinos-Antón, Natalia; Valverde, Angela M; Guney, Emre; Schmidt, Harald H H W

2018-04-01

Systems medicine has a mechanism-based rather than a symptom- or organ-based approach to disease and identifies therapeutic targets in a nonhypothesis-driven manner. In this work, we apply this to transcription factor nuclear factor (erythroid-derived 2)-like 2 (NRF2) by cross-validating its position in a protein-protein interaction network (the NRF2 interactome) functionally linked to cytoprotection in low-grade stress, chronic inflammation, metabolic alterations, and reactive oxygen species formation. Multiscale network analysis of these molecular profiles suggests alterations of NRF2 expression and activity as a common mechanism in a subnetwork of diseases (the NRF2 diseasome). This network joins apparently heterogeneous phenotypes such as autoimmune, respiratory, digestive, cardiovascular, metabolic, and neurodegenerative diseases, along with cancer. Importantly, this approach matches and confirms in silico several applications for NRF2-modulating drugs validated in vivo at different phases of clinical development. Pharmacologically, their profile is as diverse as electrophilic dimethyl fumarate, synthetic triterpenoids like bardoxolone methyl and sulforaphane, protein-protein or DNA-protein interaction inhibitors, and even registered drugs such as metformin and statins, which activate NRF2 and may be repurposed for indications within the NRF2 cluster of disease phenotypes. Thus, NRF2 represents one of the first targets fully embraced by classic and systems medicine approaches to facilitate both drug development and drug repurposing by focusing on a set of disease phenotypes that appear to be mechanistically linked. The resulting NRF2 drugome may therefore rapidly advance several surprising clinical options for this subset of chronic diseases. Copyright © 2018 by The Author(s).

Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.

PubMed

Chen, Jin-Qiu; Wakefield, Lalage M; Goldstein, David J

2015-06-06

There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

Gene expression profiling during asexual development of the late blight pathogen Phytophthora infestans reveals a highly dynamic transcriptome.

PubMed

Judelson, Howard S; Ah-Fong, Audrey M V; Aux, George; Avrova, Anna O; Bruce, Catherine; Cakir, Cahid; da Cunha, Luis; Grenville-Briggs, Laura; Latijnhouwers, Maita; Ligterink, Wilco; Meijer, Harold J G; Roberts, Samuel; Thurber, Carrie S; Whisson, Stephen C; Birch, Paul R J; Govers, Francine; Kamoun, Sophien; van West, Pieter; Windass, John

2008-04-01

Much of the pathogenic success of Phytophthora infestans, the potato and tomato late blight agent, relies on its ability to generate from mycelia large amounts of sporangia, which release zoospores that encyst and form infection structures. To better understand these stages, Affymetrix GeneChips based on 15,650 unigenes were designed and used to profile the life cycle. Approximately half of P. infestans genes were found to exhibit significant differential expression between developmental transitions, with approximately (1)/(10) being stage-specific and most changes occurring during zoosporogenesis. Quantitative reverse-transcription polymerase chain reaction assays confirmed the robustness of the array results and showed that similar patterns of differential expression were obtained regardless of whether hyphae were from laboratory media or infected tomato. Differentially expressed genes encode potential cellular regulators, especially protein kinases; metabolic enzymes such as those involved in glycolysis, gluconeogenesis, or the biosynthesis of amino acids or lipids; regulators of DNA synthesis; structural proteins, including predicted flagellar proteins; and pathogenicity factors, including cell-wall-degrading enzymes, RXLR effector proteins, and enzymes protecting against plant defense responses. Curiously, some stage-specific transcripts do not appear to encode functional proteins. These findings reveal many new aspects of oomycete biology, as well as potential targets for crop protection chemicals.

Variations on cardiovascular risk factors in metabolic syndrome after consume of a citrus-based juice.

PubMed

Mulero, Juana; Bernabé, Juana; Cerdá, Begoña; García-Viguera, Cristina; Moreno, Diego A; Albaladejo, Maria Dolores; Avilés, Francisco; Parra, Soledad; Abellán, José; Zafrilla, Pilar

2012-06-01

Inflammation and oxidative stress plays a critical role in cardiovascular disease and metabolic syndrome often occurs with these two variables. The aim of the study is to estimate variations on cardiovascular risk factors in Metabolic Syndrome patients after consume of a citrus-based juice compared with control groups. The study comprised 20 healthy subjects and 33 patients with Metabolic Syndrome. 18 patients consume daily 300 mL of a citrus-based juice during 6 month and 15 patients consume 300 mL of a placebo beverage. The control group consumes a citrus-based juice. Before, at fourth month and at sixth month after treatment the following parameters were determined: lipid profile, oxidized LDL, C-Reactive Protein and Homocysteine. The study was carried out in accordance with the Helsinki Declaration, and the Ethical Committee of the San Antonio Catholic University and approved the protocol (6 November 2006, register number: 1424). After six months of citrus-based juice consuming, there is significant differences at 95% confidence in oxidized LDL, C-Reactive Protein, and Homocysteine in Metabolic Syndrome patients who consume citrus-based juice. We have not found significant differences in other groups. Consume of citrus-based juice improve lipid profile and inflammation markers in Metabolic Syndrome patients. Copyright © 2011 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

The influence of high glucose on the Cip/Kip family expression profiles in HRECs.

PubMed

Tian, Jingyi; Ma, Hongjie; Luo, Yan; Hu, Andina; Lin, Shaofen; Li, Tao; Guo, Kai; Li, Jing; Cai, Meng; Tang, Shibo

2013-12-01

Neovascularization is the main characteristic of the proliferative stage of diabetic retinopathy. It has been proven that cell cycle regulation is involved in angiogenesis. The cell cycle regulators, Cip/Kip protein family, belong to the cyclin-dependent kinase inhibitors, are versatile proteins, and except for their function in cell cycle regulation, they also participate in transcription, apoptosis and migration. The expression profiles of the Cip/Kip family in human retina microvascular endothelial cells (HRECs) under normal or high glucose conditions has not been described before. This study was undertaken to determine the expression profiles of the Cip/Kip family proteins, e.g., proteins which are influenced by high glucose and in what manner. Western blot and immunofluorescence analyses were used to investigate the protein expression profiles. Only p21(cip1) and p27(kip1) were detected in HRECs, and they were located in the nucleus. P21(cip1) protein abundance was higher than p27(kip1) in HRECs. Incubation of HRECs in medium containing 30 mM D-glucose for 48 h resulted in downregulation of p21(cip1) protein expression, but had no influence on p27(kip1) protein levels or p21(cip1) mRNA abundance. These results were accompanied by cell cycle G1 phase exit and a lower cell survival rate. Our data show for the first time that high glucose changes the Cip/Kip family expression profiles in HRECs, which may be the foundation for the investigation of the role of the Cip/Kip family in the pathogenesis of diabetic retinopathy.

Nutritional Evaluation of Australian Microalgae as Potential Human Health Supplements

PubMed Central

Kent, Megan; Welladsen, Heather M.; Mangott, Arnold; Li, Yan

2015-01-01

This study investigated the biochemical suitability of Australian native microalgal species Scenedesmus sp., Nannochloropsis sp., Dunaliella sp., and a chlorophytic polyculture as nutritional supplements for human health. The four microalgal cultures were harvested during exponential growth, lyophilized, and analysed for proximate composition (moisture, ash, lipid, carbohydrates, and protein), pigments, and amino acid and fatty acid profiles. The resulting nutritional value, based on biochemical composition, was compared to commercial Spirulina and Chlorella products. The Australian native microalgae exhibited similar, and in several cases superior, organic nutritional properties relative to the assessed commercial products, with biochemical profiles rich in high-quality protein, nutritious polyunsaturated fats (such as α-linolenic acid, arachidonic acid, and eicosapentaenoic acid), and antioxidant pigments. These findings indicate that the microalgae assessed have great potential as multi-nutrient human health supplements. PMID:25723496

Differential Protein Expression Profiles in Glaucomatous Trabecular Meshwork: An Evaluation Study on a Small Primary Open Angle Glaucoma Population.

PubMed

Micera, Alessandra; Quaranta, Luciano; Esposito, Graziana; Floriani, Irene; Pocobelli, Augusto; Saccà, Sergio Claudio; Riva, Ivano; Manni, Gianluca; Oddone, Francesco

2016-02-01

Primary open angle glaucoma (POAG) is a progressive optic neuropathy characterized by impaired aqueous outflow and extensive remodeling in the trabecular meshwork (TM). The aim of this study was to characterize and compare the expression patterns of selected proteins belonging to the tissue remodeling, inflammation and growth factor pathways in ex vivo glaucomatous and post-mortem TMs using protein-array analysis. TM specimens were collected from 63 white subjects, including 40 patients with glaucoma and 23 controls. Forty POAG TMs were collected at the time of surgery and 23 post-mortem specimens were from non-glaucomatous donor sclerocorneal tissues. Protein profiles were evaluated using a chip-based array consisting of 60 literature-selected antibodies. A different expression of some factors was observed in POAG TMs with respect to post-mortem specimens, either in abundance (interleukin [IL]10, IL6, IL5, IL7, IL12, IL3, macrophage inflammatory protein [MIP]1δ/α, vascular endothelial growth factor [VEGF], transforming growth factor beta 1 [TGFβ1], soluble tumor necrosis factor receptor I [sTNFRI]) or in scarcity (IL16, IL18, intercellular adhesion molecule 3 [ICAM3], matrix metalloproteinase-7 [MMP7], tissue inhibitor of metalloproteinase 1 [TIMP1]). MMP2, MMP7, TGFβ1, and VEGF expressions were confirmed by Western blot, zymography, and polymerase chain reaction. No difference in protein profile expression was detected between glaucomatous subtypes. The analysis of this small TM population highlighted some proteins linked to POAG, some previously reported and others of new detection (IL7, MIPs, sTNFαRI). A larger POAG population is required to select promising disease-associated biomarker candidates. This study was partially supported by the Fondazione Roma, the Italian Ministry of Health and the "National 5xMille 2010 tax donation to IRCCS-G.B. Bietti Foundation".

Nasal protein profiles in work-related asthma caused by different exposures.

PubMed

Suojalehto, H; Lindström, I; Wolff, H; Puustinen, A

2018-03-01

The mechanisms of work-related asthma (WRA) are incompletely delineated. Nasal cell samples may be informative about processes in the lower airways. Our aim was to determine the nasal protein expression profiles of WRA caused by different kind of exposures. We collected nasal brush samples from 82 nonsmoking participants, including healthy controls and WRA patients exposed to (i) protein allergens, (ii) isocyanates and (iii) welding fumes the day after relevant exposure. The proteome changes in samples were analysed by two-dimensional difference gel electrophoresis, and the differentially regulated proteins found were identified by mass spectrometry. Immunological comparison was carried out using Western blot. We detected an average of 2500 spots per protein gel. Altogether, 228 protein spots were chosen for identification, yielding 77 different proteins. Compared to the controls, exposure to protein allergens had the largest effects on the proteome. Hierarchical clustering revealed that protein allergen- and isocyanate-related asthma had similar profiles, whereas asthma related to welding fumes differed. The highly overrepresented functional categories in the asthma groups were defence response, protease inhibitor activity, inflammatory and calcium signalling, complement activation and cellular response to oxidative stress. Immunological analysis confirmed the found abundance differences in galectin 10 and protein S100-A9 between the groups. Work-related asthma patients exposed to protein allergens and isocyanates elicit similar nasal proteome responses and the profiles of welders and healthy controls were alike. Revealed biological activities of the protein expression changes are associated with allergic inflammation and asthma. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

Manipulating fatty acid biosynthesis in microalgae for biofuel through protein-protein interactions.

PubMed

Blatti, Jillian L; Beld, Joris; Behnke, Craig A; Mendez, Michael; Mayfield, Stephen P; Burkart, Michael D

2012-01-01

Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes.

Manipulating Fatty Acid Biosynthesis in Microalgae for Biofuel through Protein-Protein Interactions

PubMed Central

Blatti, Jillian L.; Beld, Joris; Behnke, Craig A.; Mendez, Michael; Mayfield, Stephen P.; Burkart, Michael D.

2012-01-01

Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes. PMID:23028438

Exposure to an extremely low-frequency electromagnetic field only slightly modifies the proteome of Chromobacterium violaceumATCC 12472

PubMed Central

Baraúna, Rafael A.; Santos, Agenor V.; Graças, Diego A.; Santos, Daniel M.; Ghilardi, Rubens; Pimenta, Adriano M. C.; Carepo, Marta S. P.; Schneider, Maria P.C.; Silva, Artur

2015-01-01

Several studies of the physiological responses of different organisms exposed to extremely low-frequency electromagnetic fields (ELF-EMF) have been described. In this work, we report the minimal effects of in situ exposure to ELF-EMF on the global protein expression of Chromobacterium violaceum using a gel-based proteomic approach. The protein expression profile was only slightly altered, with five differentially expressed proteins detected in the exposed cultures; two of these proteins (DNA-binding stress protein, Dps, and alcohol dehydrogenase) were identified by MS/MS. The enhanced expression of Dps possibly helped to prevent physical damage to DNA. Although small, the changes in protein expression observed here were probably beneficial in helping the bacteria to adapt to the stress generated by the electromagnetic field. PMID:26273227

Genomewide Function Conservation and Phylogeny in the Herpesviridae

PubMed Central

Albà, M. Mar; Das, Rhiju; Orengo, Christine A.; Kellam, Paul

2001-01-01

The Herpesviridae are a large group of well-characterized double-stranded DNA viruses for which many complete genome sequences have been determined. We have extracted protein sequences from all predicted open reading frames of 19 herpesvirus genomes. Sequence comparison and protein sequence clustering methods have been used to construct herpesvirus protein homologous families. This resulted in 1692 proteins being clustered into 243 multiprotein families and 196 singleton proteins. Predicted functions were assigned to each homologous family based on genome annotation and published data and each family classified into seven broad functional groups. Phylogenetic profiles were constructed for each herpesvirus from the homologous protein families and used to determine conserved functions and genomewide phylogenetic trees. These trees agreed with molecular-sequence-derived trees and allowed greater insight into the phylogeny of ungulate and murine gammaherpesviruses. PMID:11156614

Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.

PubMed

Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong

2015-01-01

In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.

Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue.

PubMed

Kislinger, Thomas; Gramolini, Anthony O; MacLennan, David H; Emili, Andrew

2005-08-01

An optimized analytical expression profiling strategy based on gel-free multidimensional protein identification technology (MudPIT) is reported for the systematic investigation of biochemical (mal)-adaptations associated with healthy and diseased heart tissue. Enhanced shotgun proteomic detection coverage and improved biological inference is achieved by pre-fractionation of excised mouse cardiac muscle into subcellular components, with each organellar fraction investigated exhaustively using multiple repeat MudPIT analyses. Functional-enrichment, high-confidence identification, and relative quantification of hundreds of organelle- and tissue-specific proteins are achieved readily, including detection of low abundance transcriptional regulators, signaling factors, and proteins linked to cardiac disease. Important technical issues relating to data validation, including minimization of artifacts stemming from biased under-sampling and spurious false discovery, together with suggestions for further fine-tuning of sample preparation, are discussed. A framework for follow-up bioinformatic examination, pattern recognition, and data mining is also presented in the context of a stringent application of MudPIT for probing fundamental aspects of heart muscle physiology as well as the discovery of perturbations associated with heart failure.

Proteomics reveals the effects of sustained weight loss on the human plasma proteome.

PubMed

Geyer, Philipp E; Wewer Albrechtsen, Nicolai J; Tyanova, Stefka; Grassl, Niklas; Iepsen, Eva W; Lundgren, Julie; Madsbad, Sten; Holst, Jens J; Torekov, Signe S; Mann, Matthias

2016-12-22

Sustained weight loss is a preferred intervention in a wide range of metabolic conditions, but the effects on an individual's health state remain ill-defined. Here, we investigate the plasma proteomes of a cohort of 43 obese individuals that had undergone 8 weeks of 12% body weight loss followed by a year of weight maintenance. Using mass spectrometry-based plasma proteome profiling, we measured 1,294 plasma proteomes. Longitudinal monitoring of the cohort revealed individual-specific protein levels with wide-ranging effects of losing weight on the plasma proteome reflected in 93 significantly affected proteins. The adipocyte-secreted SERPINF1 and apolipoprotein APOF1 were most significantly regulated with fold changes of -16% and +37%, respectively (P < 10 -13 ), and the entire apolipoprotein family showed characteristic differential regulation. Clinical laboratory parameters are reflected in the plasma proteome, and eight plasma proteins correlated better with insulin resistance than the known marker adiponectin. Nearly all study participants benefited from weight loss regarding a ten-protein inflammation panel defined from the proteomics data. We conclude that plasma proteome profiling broadly evaluates and monitors intervention in metabolic diseases. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

Label-free proteomic analysis of intestinal mucosa proteins in common carp (Cyprinus carpio) infected with Aeromonas hydrophila.

PubMed

Di, Guilan; Li, Hui; Zhang, Chao; Zhao, Yanjing; Zhou, Chuanjiang; Naeem, Sajid; Li, Li; Kong, Xianghui

2017-07-01

Outbreaks of infectious diseases in common carp Cyprinus carpio, a major cultured fish in northern regions of China, constantly result in significant economic losses. Until now, information proteomic on immune defence remains limited. In the present study, a profile of intestinal mucosa immune response in Cyprinus carpio was investigated after 0, 12, 36 and 84 h after challenging tissues with Aeromonas hydrophila at a concentration of 1.4 × 10 8  CFU/mL. Proteomic profiles in different samples were compared using label-free quantitative proteomic approach. Based on MASCOT database search, 1149 proteins were identified in samples after normalisation of proteins. Treated groups 1 (T1) and 2 (T2) were first clustered together and then clustered with control (C group). The distance between C and treated group 3 (T3) represented the maxima according to hierarchical cluster analysis. Therefore, comparative analysis between C and T3 was selected in the following analysis. A total of 115 proteins with differential abundance were detected to show conspicuous expressing variances. A total of 52 up-regulated proteins and 63 down-regulated proteins were detected in T3. Gene ontology analysis showed that identified up-regulated differentially expressed proteins in T3 were mainly localised in the hemoglobin complex, and down-regulated proteins in T3 were mainly localised in the major histocompatibility complex II protein complex. Forty-six proteins of differential abundance (40% of 115) were involved in immune response, with 17 up-regulated and 29 down-regulated proteins detected in T3. This study is the first to report proteome response of carp intestinal mucosa against A. hydrophila infection; information obtained contribute to understanding defence mechanisms of carp intestinal mucosa. Copyright © 2017 Elsevier Ltd. All rights reserved.

Large-scale inference of protein tissue origin in gram-positive sepsis plasma using quantitative targeted proteomics

PubMed Central

Malmström, Erik; Kilsgård, Ola; Hauri, Simon; Smeds, Emanuel; Herwald, Heiko; Malmström, Lars; Malmström, Johan

2016-01-01

The plasma proteome is highly dynamic and variable, composed of proteins derived from surrounding tissues and cells. To investigate the complex processes that control the composition of the plasma proteome, we developed a mass spectrometry-based proteomics strategy to infer the origin of proteins detected in murine plasma. The strategy relies on the construction of a comprehensive protein tissue atlas from cells and highly vascularized organs using shotgun mass spectrometry. The protein tissue atlas was transformed to a spectral library for highly reproducible quantification of tissue-specific proteins directly in plasma using SWATH-like data-independent mass spectrometry analysis. We show that the method can determine drastic changes of tissue-specific protein profiles in blood plasma from mouse animal models with sepsis. The strategy can be extended to several other species advancing our understanding of the complex processes that contribute to the plasma proteome dynamics. PMID:26732734

Life and death of proteins: a case study of glucose-starved Staphylococcus aureus.

PubMed

Michalik, Stephan; Bernhardt, Jörg; Otto, Andreas; Moche, Martin; Becher, Dörte; Meyer, Hanna; Lalk, Michael; Schurmann, Claudia; Schlüter, Rabea; Kock, Holger; Gerth, Ulf; Hecker, Michael

2012-09-01

The cellular amount of proteins not only depends on synthesis but also on degradation. Here, we expand the understanding of differential protein levels by complementing synthesis data with a proteome-wide, mass spectrometry-based stable isotope labeling with amino acids in cell culture analysis of protein degradation in the human pathogen Staphylococcus aureus during glucose starvation. Monitoring protein stability profiles in a wild type and an isogenic clpP protease mutant revealed that 1) proteolysis mainly affected proteins with vegetative functions, anabolic and selected catabolic enzymes, whereas the expression of TCA cycle and gluconeogenesis enzymes increased; 2) most proteins were prone to aggregation in the clpP mutant; 3) the absence of ClpP correlated with protein denaturation and oxidative stress responses, deregulation of virulence factors and a CodY repression. We suggest that degradation of redundant, inactive proteins disintegrated from functional complexes and thereby amenable to proteolytic attack is a fundamental cellular process in all organisms to regain nutrients and guarantee protein homeostasis.

Life and Death of Proteins: A Case Study of Glucose-starved Staphylococcus aureus*

PubMed Central

Michalik, Stephan; Bernhardt, Jörg; Otto, Andreas; Moche, Martin; Becher, Dörte; Meyer, Hanna; Lalk, Michael; Schurmann, Claudia; Schlüter, Rabea; Kock, Holger; Gerth, Ulf; Hecker, Michael

2012-01-01

The cellular amount of proteins not only depends on synthesis but also on degradation. Here, we expand the understanding of differential protein levels by complementing synthesis data with a proteome-wide, mass spectrometry-based stable isotope labeling with amino acids in cell culture analysis of protein degradation in the human pathogen Staphylococcus aureus during glucose starvation. Monitoring protein stability profiles in a wild type and an isogenic clpP protease mutant revealed that 1) proteolysis mainly affected proteins with vegetative functions, anabolic and selected catabolic enzymes, whereas the expression of TCA cycle and gluconeogenesis enzymes increased; 2) most proteins were prone to aggregation in the clpP mutant; 3) the absence of ClpP correlated with protein denaturation and oxidative stress responses, deregulation of virulence factors and a CodY repression. We suggest that degradation of redundant, inactive proteins disintegrated from functional complexes and thereby amenable to proteolytic attack is a fundamental cellular process in all organisms to regain nutrients and guarantee protein homeostasis. PMID:22556279

Computational Prediction and Validation of BAHD1 as a Novel Molecule for Ulcerative Colitis

NASA Astrophysics Data System (ADS)

Zhu, Huatuo; Wan, Xingyong; Li, Jing; Han, Lu; Bo, Xiaochen; Chen, Wenguo; Lu, Chao; Shen, Zhe; Xu, Chenfu; Chen, Lihua; Yu, Chaohui; Xu, Guoqiang

2015-07-01

Ulcerative colitis (UC) is a common inflammatory bowel disease (IBD) producing intestinal inflammation and tissue damage. The precise aetiology of UC remains unknown. In this study, we applied a rank-based expression profile comparative algorithm, gene set enrichment analysis (GSEA), to evaluate the expression profiles of UC patients and small interfering RNA (siRNA)-perturbed cells to predict proteins that might be essential in UC from publicly available expression profiles. We used quantitative PCR (qPCR) to characterize the expression levels of those genes predicted to be the most important for UC in dextran sodium sulphate (DSS)-induced colitic mice. We found that bromo-adjacent homology domain (BAHD1), a novel heterochromatinization factor in vertebrates, was the most downregulated gene. We further validated a potential role of BAHD1 as a regulatory factor for inflammation through the TNF signalling pathway in vitro. Our findings indicate that computational approaches leveraging public gene expression data can be used to infer potential genes or proteins for diseases, and BAHD1 might act as an indispensable factor in regulating the cellular inflammatory response in UC.

Appetite control and biomarkers of satiety with vegetarian (soy) and meat-based high-protein diets for weight loss in obese men: a randomized crossover trial.

PubMed

Neacsu, Madalina; Fyfe, Claire; Horgan, Graham; Johnstone, Alexandra M

2014-08-01

There is limited evidence with regard to the effect of different sources of protein on appetite during weight loss. Vegetarian and meat-based high-protein diets may have contrasting effects on appetite and biomarkers of protein-induced satiety. The aim was to assess appetite response to meat or vegetarian high-protein weight-loss (HPWL) diets in obese men to monitor plasma amino acid profile and gut peptide response as potential satiety biomarkers. Twenty obese [body mass index (in kg/m²): 34.8] men participated in a dietary intervention study. After 3 d of a maintenance diet, they were provided in a crossover design with either a vegetarian HPWL (Soy-HPWL) or a meat-based HPWL (Meat-HPWL) diet for 2 wk. Both diets comprised 30% protein, 30% fat, and 40% carbohydrate, provided to measured resting metabolic rate. Body weight and the motivation to eat were measured daily. Plasma satiety biomarkers were collected during a test-meal challenge (5 h) at the end of each diet period. Over the 2 wk, subjects lost, on average, 2.41 and 2.27 kg with consumption of the Soy- and Meat-HPWL diets, respectively [P = 0.352; SE of the difference (SED): 0.1]. ANOVA confirmed that subjectively rated hunger (P = 0.569; SED: 3.8), fullness (P = 0.404; SED: 4.1), desire to eat (P = 0.356; SED: 3.7), preservation of lean body mass (P = 0.334; SED: 0.2), and loss of percentage fat mass (P = 0.179; SED: 0.2) did not differ between the 2 HPWL diets. There were differences in absolute concentrations of ghrelin and peptide YY between the 2 HPWL diets, although the response as net area under the curve was not different. Appetite control and weight loss were similar for both HPWL diets. Gut hormone profile was similar between the diets, which suggests that vegetarian diets can be as effective as meat-based diets for appetite control during weight loss. © 2014 American Society for Nutrition.

Identification of anticitrullinated protein antibody reactivities in a subset of anti-CCP-negative rheumatoid arthritis: association with cigarette smoking and HLA-DRB1 ‘shared epitope’ alleles

PubMed Central

Wagner, Catriona A; Sokolove, Jeremy; Lahey, Lauren J; Bengtsson, Camilla; Saevarsdottir, Saedis; Alfredsson, Lars; Delanoy, Michelle; Lindstrom, Tamsin M; Walker, Roger P; Bromberg, Reuven; Chandra, Piyanka E; Binder, Steven R; Klareskog, Lars; Robinson, William H

2015-01-01

Introduction A hallmark of rheumatoid arthritis (RA) is the development of autoantibodies targeting proteins that contain citrulline. Anticitrullinated protein antibodies (ACPAs) are currently detected by the commercial cyclic citrullinated peptide (CCP) assay, which uses a mix of cyclised citrullinated peptides as an artificial mimic of the true antigen(s). To increase the sensitivity of ACPA detection and dissect ACPA specificities, we developed a multiplex assay that profiles ACPAs by measuring their reactivity to the citrullinated peptides and proteins derived from RA joint tissue. Methods We created a bead-based, citrullinated antigen array to profile ACPAs. This custom array contains 16 citrullinated peptides and proteins detected in RA synovial tissues. We used the array to profile ACPAs in sera from a cohort of patients with RA and other non-inflammatory arthritides, as well as sera from an independent cohort of RA patients for whom data were available on carriage of HLA-DRB1 ‘shared epitope’ (SE) alleles and history of cigarette smoking. Results Our multiplex assay showed that at least 10% of RA patients who tested negative in the commercial CCP assay possessed ACPAs. Carriage of HLA-DRB1 SE alleles and a history of cigarette smoking were associated with an increase in ACPA reactivity—in anti-CCP+ RA and in a subset of anti-CCP− RA. Conclusions Our multiplex assay can identify ACPA-positive RA patients missed by the commercial CCP assay, thus enabling greater diagnostic sensitivity. Further, our findings suggest that cigarette smoking and possession of HLA-DRB1 SE alleles contribute to the development of ACPAs in anti-CCP− RA. PMID:24297382

Circulating proteins as predictors of incident heart failure in the elderly.

PubMed

Stenemo, Markus; Nowak, Christoph; Byberg, Liisa; Sundström, Johan; Giedraitis, Vilmantas; Lind, Lars; Ingelsson, Erik; Fall, Tove; Ärnlöv, Johan

2018-01-01

To identify novel risk markers for incident heart failure using proteomic profiling of 80 proteins previously associated with cardiovascular pathology. Proteomic profiling (proximity extension assay) was performed in two community-based prospective cohorts of elderly individuals without heart failure at baseline: the Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS, n = 901, median age 70.2 (interquartile range 70.0-70.3) years, 80 events]; and the Uppsala Longitudinal Study of Adult Men [ULSAM, n = 685, median age 77.8 (interquartile range 76.9-78.1) years, 90 events]. Twenty-nine proteins were associated with incident heart failure in the discovery cohort PIVUS after adjustment for age and sex, and correction for multiple testing. Eighteen associations replicated in ULSAM. In pooled analysis of both cohorts, higher levels of nine proteins were associated with incident heart failure after adjustment for established risk factors: growth differentiation factor 15 (GDF-15), T-cell immunoglobulin and mucin domain 1 (TIM-1), tumour necrosis factor-related apoptosis-inducing ligand receptor 2 (TRAIL-R2), spondin-1 (SPON1), matrix metalloproteinase-12 (MMP-12), follistatin (FS), urokinase-type plasminogen activator surface receptor (U-PAR), osteoprotegerin (OPG), and suppression of tumorigenicity 2 (ST2). Of these, GDF-15, U-PAR, MMP-12, TRAIL-R2, SPON1 and FS were associated with worsened echocardiographic left ventricular systolic function at baseline, while only TIM-1 was positively associated with worsened diastolic function (P < 0.02 for all). Proteomic profiling identified several novel associations between proteins involved in apoptosis, inflammation, matrix remodelling, and fibrinolysis with incident heart failure in elderly individuals. Our results encourage additional studies investigating the underlying mechanisms and the clinical utility of our findings. © 2017 The Authors. European Journal of Heart Failure © 2017 European Society of Cardiology.

Effect of Daily Exposure to an Isolated Soy Protein Supplement on Body Composition, Energy and Macronutrient Intake, Bone Formation Markers, and Lipid Profile in Children in Colombia.

PubMed

Mejía, Wilson; Córdoba, Diana; Durán, Paola; Chacón, Yersson; Rosselli, Diego

2018-01-16

A soy protein-based supplement may optimize bone health, support physical growth, and stimulate bone formation. This study aimed to assess the effect of a daily soy protein supplement (SPS) on nutritional status, bone formation markers, lipid profile, and daily energy and macronutrient intake in children. One hundred seven participants (62 girls), ages 2 to 9, started the study and were randomly assigned to lunch fruit juice with (n = 57, intervention group) or without (n = 50, control group) addition of 45 g (230 Kcal) of a commercial SPS during 12 months; 84 children (51 girls, 33 boys) completed the study (45 and 39 intervention and control, respectively). Nutritional assessment included anthropometry and nutrient intakes; initial and final blood samples were taken; insulin-like growth factor-I (IGF-I), osteocalcin, bone specific alkaline phosphatase (BAP), insulin-like growth factor binding protein-3 (IGFBP-3), cholesterol, triglycerides, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) were analyzed. Statistically significant changes (p < .05) in body mass index and weight for age Z scores were observed between groups while changes in body composition were not. Changes in energy, total protein, and carbohydrate intakes were significantly higher in the intervention group (p < .01). Calorie intake changes were statistically significant between groups (p < .001), and BAP decreased in both groups, with values within normal ranges. Osteocalcin, IGFBP-3, and lipid profile were not different between groups. IGF-I levels and IGF/IGFBP-3 ratio increased significantly in both groups. In conclusion, changes in macronutrient and energy intake and nutritional status in the intervention group compared to control group may ensure harmonious and adequate bone health and development.

Proteomic profiling of the rat cerebral cortex in sleep and waking.

PubMed

Cirelli, C; Pfister-Genskow, M; McCarthy, D; Woodbury, R; Tononi, G

2009-09-01

Transcriptomic studies have shown that hundreds of genes change their expression levels across the sleep/waking cycle, and found that waking-related and sleep-related mRNAs belong to different functional categories. Proteins, however, rather than DNA or RNA, carry out most of the cellular functions, and direct measurements of protein levels and activity are required to assess the effects of behavioral states on the overall functional state of the cell. Here we used surface-enhanced laser desorption-ionization (SELDI), followed by time-of-flight mass spectrometry, to obtain a large-scale profiling of the proteins in the rat cerebral cortex whose expression is affected by sleep, spontaneous waking, short (6 hours) and long (7 days) sleep deprivation. Each of the 94 cortical samples was profiled in duplicate on 4 different ProteinChip Array surfaces using 2 different matrix molecules. Overall, 1055 protein peaks were consistently detected in cortical samples and 15 candidate biomarkers were selected for identification based on significant changes in multiple conditions (conjunction analysis): 8 "sleep" peaks, 4 "waking" peaks, and 4 "long sleep deprivation" peaks. Four candidate biomarkers were purified and positively identified. The 3353 Da candidate sleep marker was identified as the 30 amino acid C-terminal fragment of rat histone H4. This region encompasses the osteogenic growth peptide, but a possible link between sleep and this peptide remains highly speculative. Two peaks associated with short and long sleep deprivation were identified as hemoglobin alpha1/2 and beta, respectively, while another peak associated with long sleep deprivation was identified as cytochrome C. The upregulation of hemoglobins and cytochrome C may be part of a cellular stress response triggered by even short periods of sleep loss.

Secretome profile analysis of multidrug-resistant, monodrug-resistant and drug-susceptible Mycobacterium tuberculosis.

PubMed

Putim, Chanyanuch; Phaonakrop, Narumon; Jaresitthikunchai, Janthima; Gamngoen, Ratikorn; Tragoolpua, Khajornsak; Intorasoot, Sorasak; Anukool, Usanee; Tharincharoen, Chayada Sitthidet; Phunpae, Ponrut; Tayapiwatana, Chatchai; Kasinrerk, Watchara; Roytrakul, Sittiruk; Butr-Indr, Bordin

2018-03-01

The emergence of drug-resistant tuberculosis has generated great concern in the control of tuberculosis and HIV/TB patients have established severe complications that are difficult to treat. Although, the gold standard of drug-susceptibility testing is highly accurate and efficient, it is time-consuming. Diagnostic biomarkers are, therefore, necessary in discriminating between infection from drug-resistant and drug-susceptible strains. One strategy that aids to effectively control tuberculosis is understanding the function of secreting proteins that mycobacteria use to manipulate the host cellular defenses. In this study, culture filtrate proteins from Mycobacterium tuberculosis H37Rv, isoniazid-resistant, rifampicin-resistant and multidrug-resistant strains were gathered and profiled by shotgun-proteomics technique. Mass spectrometric analysis of the secreted proteome identified several proteins, of which 837, 892, 838 and 850 were found in M. tuberculosis H37Rv, isoniazid-resistant, rifampicin-resistant and multidrug-resistant strains, respectively. These proteins have been implicated in various cellular processes, including biological adhesion, biological regulation, developmental process, immune system process localization, cellular process, cellular component organization or biogenesis, metabolic process, and response to stimulus. Analysis based on STITCH database predicted the interaction of DNA topoisomerase I, 3-oxoacyl-(acyl-carrier protein) reductase, ESAT-6-like protein, putative prophage phiRv2 integrase, and 3-phosphoshikimate 1-carboxyvinyltransferase with isoniazid, rifampicin, pyrazinamide, ethambutol and streptomycin, suggesting putative roles in controlling the anti-tuberculosis ability. However, several proteins with no interaction with all first-line anti-tuberculosis drugs might be used as markers for mycobacterial identification.

Urine Sample Preparation in 96-Well Filter Plates for Quantitative Clinical Proteomics

PubMed Central

2015-01-01

Urine is an important, noninvasively collected body fluid source for the diagnosis and prognosis of human diseases. Liquid chromatography mass spectrometry (LC-MS) based shotgun proteomics has evolved as a sensitive and informative technique to discover candidate disease biomarkers from urine specimens. Filter-aided sample preparation (FASP) generates peptide samples from protein mixtures of cell lysate or body fluid origin. Here, we describe a FASP method adapted to 96-well filter plates, named 96FASP. Soluble urine concentrates containing ∼10 μg of total protein were processed by 96FASP and LC-MS resulting in 700–900 protein identifications at a 1% false discovery rate (FDR). The experimental repeatability, as assessed by label-free quantification and Pearson correlation analysis for shared proteins among replicates, was high (R ≥ 0.97). Application to urinary pellet lysates which is of particular interest in the context of urinary tract infection analysis was also demonstrated. On average, 1700 proteins (±398) were identified in five experiments. In a pilot study using 96FASP for analysis of eight soluble urine samples, we demonstrated that protein profiles of technical replicates invariably clustered; the protein profiles for distinct urine donors were very different from each other. Robust, highly parallel methods to generate peptide mixtures from urine and other body fluids are critical to increase cost-effectiveness in clinical proteomics projects. This 96FASP method has potential to become a gold standard for high-throughput quantitative clinical proteomics. PMID:24797144

Electrophoretic characterisation of the outer membrane proteins of Yersinia pestis isolated in north-east Brazil.

PubMed Central

Abath, F. G.; Almeida, A. M.; Ferreira, L. C.

1989-01-01

The outer membrane proteins of 38 Yersinia pestis isolates from all known plague foci of north-east Brazil were analysed by SDS-PAGE. Approximately 20 bands were consistently found in all strains analysed and 11 were selected for comparative studies. Although qualitative differences among the electrophoretic profiles of outer membrane proteins of wild Y. pestis isolates were not observed, quantitative alterations were clearly noted for most of these proteins. No particular quantitative alteration of the electrophoretic profile of outer membrane proteins could be associated with the period of isolation and geographic origin of the isolates. The 64 kDa outer membrane protein was significantly expressed in higher amounts among Y. pestis strains isolated from a recent plague outbreak. The possible use of electrophoretic profiles of outer membrane proteins of wild Y. pestis isolates as a tool for epidemiological studies and for the analysis of virulence determinants is discussed. Images Fig. 2 PMID:2606164

Diversity in Protein Profiles of Individual Calcium Oxalate Kidney Stones

PubMed Central

Okumura, Nobuaki; Tsujihata, Masao; Momohara, Chikahiro; Yoshioka, Iwao; Suto, Kouzou; Nonomura, Norio; Okuyama, Akihiko; Takao, Toshifumi

2013-01-01

Calcium oxalate kidney stones contain low amounts of proteins, some of which have been implicated in progression or prevention of kidney stone formation. To gain insights into the pathophysiology of urolithiasis, we have characterized protein components of calcium oxalate kidney stones by proteomic approaches. Proteins extracted from kidney stones showed highly heterogeneous migration patterns in gel electrophoresis as reported. This was likely to be mainly due to proteolytic degradation and protein-protein crosslinking of Tamm-Horsfall protein and prothrombin. Protein profiles of calcium oxalate kidney stones were obtained by in-solution protease digestion followed by nanoLC-MALDI-tandem mass spectrometry, which resulted in identification of a total of 92 proteins in stones from 9 urolithiasis patients. Further analysis showed that protein species and their relative amounts were highly variable among individual stones. Although proteins such as prothrombin, osteopontin, calgranulin A and calgranulin B were found in most stones tested, some samples had high contents of prothrombin and osteopontin, while others had high contents of calgranulins. In addition, calgranulin-rich stones had various neutrophil-enriched proteins such as myeloperoxidase and lactotransferrin. These proteomic profiles of individual kidney stones suggest that multiple systems composed of different groups of proteins including leucocyte-derived ones are differently involved in pathogenesis of individual kidney stones depending on situations. PMID:23874695

Nutritional and anti-nutritional potential of three accessions of itching bean (Mucuna pruriens (L.) DC var. pruriens): an under-utilized tribal pulse.

PubMed

Kala, Balasubiramanian Kamatchi; Mohan, Veerabahu Ramasamy

2010-08-01

Three accessions of the under-utilized legume itching bean (Mucuna pruriens var. pruriens) were analysed for proximate composition, mineral profiles, vitamins (niacin and ascorbic acid), fatty acid profiles, amino acid profiles of total seed protein, in vitro protein digestibility and certain anti-nutritional factors. All three accessions of M. pruriens var. pruriens contained higher amounts of crude protein and crude lipid when compared with most of the commonly consumed pulses. The fatty acid profiles revealed that the seed lipids contained a higher concentration of palmitic acid and linoleic acids. Amino acid profiles of M. pruriens var. pruriens revealed that the seed protein contained relatively higher levels of certain essential amino acids compared with the FAO/WHO requirement pattern. The investigated seeds are rich in minerals such as potassium, calcium, magnesium, phosphorus, iron and manganese. Anti nutritional substances such as total free phenolics, tannins, 3,4-dihydroxyphenylalanine, phytic acid, hydrogen cyanide, trypsin inhibitor activity, oligosaccharides and phytohaemagglutinating activity were investigated. The anti-nutritional fatty acid, behenic acid, also was detected in the present study.

Analysis of the low-molecular weight protein profile of egg-white and its changes during early chicken embryological development.

PubMed

Fang, Jun; Ma, Mei H; Qiu, Ning; Wu, Xiao; Jin, Yong G

2012-01-01

Many low-molecular weight (LMW) proteins in egg-white are potentially bioactive, but the mass range and number of these are not yet fully characterized. The aim of the present study was to map the LMW protein profile in egg-white and provide the basis for further understanding of the physiological function of these proteins. For this purpose, six time points (days 0, 1, 2, 3, 4, 5 of incubation) were selected in an attempt to delineate the LMW proteomic profile in egg-white and its changes during early chicken embryological development. Samples were pretreated using gel chromatography techniques prior to analysis by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). Protein search focused on the mass range m/z 1,000 to 8,000. One hundred and fourteen mass signal peaks of LMW proteins ranging from m/z 1,035.88 to 7,112.91 were detected at all six time points. The observed changes in the LMW protein profile during development were highly dynamic. Eighty six novel mass signal peaks of LMW proteins were generated during incubation, the origin of which could be assigned to the high-molecular weight protein fractions.The list of egg-white LMW proteins provided in this paper is by far the most comprehensive and is intended to serve as a starting point for the isolation and functional characterization of interesting LMW proteins which may play a crucial role in early embryo nutrition and immunity.

Effect of an ozone injury retardant chemical on isozyme profiles from alfalfa callus in vitro

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

Rier, J.P. Jr.; Sood, V.K.; Whitaker, A.

1983-01-01

Plant ozone injury retardant N-(2-(2-oxo-1-imidazolidinyl)-ethyl)-N'-phenylurea (EDU or ethylenediurea) at 1.0 ppm inhibited growth of callus of alfalfa cultivars Williamsburg (ozone-sensitive) and MSB-CW5An2 (ozone-insensitive) germplasm of Medicago sativa. The presence of EDU (0.1 ppm)in the growth medium increased the number of protein and peroxidase isozyme bands in alfalfa cultivar Williamsburg stem callus and ozone modified their intensities. Protein profiles of MSB stem callus from media containing EDU or exposed to ozone were unchanged. Marked differences were observed between the peroxidase profiles of ozonated and control ozone-insensitive stem callus from media containing EDU. Protein profiles of ozonated ozone-sensitive leaf callus differed slightlymore » from controls. The peroxidase profile of ozonated ozone-sensitive leaf callus was not altered when its growth medium contained EDU, but when it was absent, changes were observed in these profiles.« less

Transition Pathway and Its Free-Energy Profile: A Protocol for Protein Folding Simulations

PubMed Central

Lee, In-Ho; Kim, Seung-Yeon; Lee, Jooyoung

2013-01-01

We propose a protocol that provides a systematic definition of reaction coordinate and related free-energy profile as the function of temperature for the protein-folding simulation. First, using action-derived molecular dynamics (ADMD), we investigate the dynamic folding pathway model of a protein between a fixed extended conformation and a compact conformation. We choose the pathway model to be the reaction coordinate, and the folding and unfolding processes are characterized by the ADMD step index, in contrast to the common a priori reaction coordinate as used in conventional studies. Second, we calculate free-energy profile as the function of temperature, by employing the replica-exchange molecular dynamics (REMD) method. The current method provides efficient exploration of conformational space and proper characterization of protein folding/unfolding dynamics from/to an arbitrary extended conformation. We demonstrate that combination of the two simulation methods, ADMD and REMD, provides understanding on molecular conformational changes in proteins. The protocol is tested on a small protein, penta-peptide of met-enkephalin. For the neuropeptide met-enkephalin system, folded, extended, and intermediate sates are well-defined through the free-energy profile over the reaction coordinate. Results are consistent with those in the literature. PMID:23917881

Three-Dimensional Biologically Relevant Spectrum (BRS-3D): Shape Similarity Profile Based on PDB Ligands as Molecular Descriptors.

PubMed

Hu, Ben; Kuang, Zheng-Kun; Feng, Shi-Yu; Wang, Dong; He, Song-Bing; Kong, De-Xin

2016-11-17

The crystallized ligands in the Protein Data Bank (PDB) can be treated as the inverse shapes of the active sites of corresponding proteins. Therefore, the shape similarity between a molecule and PDB ligands indicated the possibility of the molecule to bind with the targets. In this paper, we proposed a shape similarity profile that can be used as a molecular descriptor for ligand-based virtual screening. First, through three-dimensional (3D) structural clustering, 300 diverse ligands were extracted from the druggable protein-ligand database, sc-PDB. Then, each of the molecules under scrutiny was flexibly superimposed onto the 300 ligands. Superimpositions were scored by shape overlap and property similarity, producing a 300 dimensional similarity array termed the "Three-Dimensional Biologically Relevant Spectrum (BRS-3D)". Finally, quantitative or discriminant models were developed with the 300 dimensional descriptor using machine learning methods (support vector machine). The effectiveness of this approach was evaluated using 42 benchmark data sets from the G protein-coupled receptor (GPCR) ligand library and the GPCR decoy database (GLL/GDD). We compared the performance of BRS-3D with other 2D and 3D state-of-the-art molecular descriptors. The results showed that models built with BRS-3D performed best for most GLL/GDD data sets. We also applied BRS-3D in histone deacetylase 1 inhibitors screening and GPCR subtype selectivity prediction. The advantages and disadvantages of this approach are discussed.

SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures.

PubMed

Suresh, V; Parthasarathy, S

2014-01-01

We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.

Expression of small leucine-rich extracellular matrix proteoglycans biglycan and lumican reveals oral lichen planus malignant potential.

PubMed

Lončar-Brzak, Božana; Klobučar, Marko; Veliki-Dalić, Irena; Sabol, Ivan; Kraljević Pavelić, Sandra; Krušlin, Božo; Mravak-Stipetić, Marinka

2018-03-01

The aim of this study was to examine molecular alterations on the protein level in lesions of oral lichen planus (OLP), oral squamous cell carcinoma (OSCC) and healthy mucosa. Global protein profiling methods based on liquid chromatography coupled to mass spectrometry (LC-MS) were used, with a special emphasis on evaluation of deregulated extracellular matrix molecules expression, as well as on analyses of IG2F and IGFR2 expression in healthy mucosa, OLP and OSCC tissues by comparative semi-quantitative immunohistochemistry. Mass spectrometry-based proteomics profiling of healthy mucosa, OLP and OSCC tissues (and accompanied histologically unaltered tissues, respectively) identified 55 extracellular matrix proteins. Twenty among identified proteins were common to all groups of samples. Expression of small leucine-rich extracellular matrix proteoglycans lumican and biglycan was found both in OSCC and OLP and they were validated by Western blot analysis as putative biomarkers. A significant increase (p < 0.05) of biglycan expression in OLP-AT group was determined in comparison with OLP-T group, while lumican showed significant up-regulation (p < 0.05) in OLP-T and OSCC-T groups vs. adjacent and control tissue groups. Biglycan expression was only determined in OSCC-AT group. Immunohistochemical analysis of IGF2 and IG2FR expression revealed no significant difference among groups of samples. Biglycan and lumican were identified as important pathogenesis biomarkers of OLP that point to its malignant potential.

Structural and metabolic transitions of C4 leaf development and differentiation defined by microscopy and quantitative proteomics in maize.

PubMed

Majeran, Wojciech; Friso, Giulia; Ponnala, Lalit; Connolly, Brian; Huang, Mingshu; Reidel, Edwin; Zhang, Cankui; Asakura, Yukari; Bhuiyan, Nazmul H; Sun, Qi; Turgeon, Robert; van Wijk, Klaas J

2010-11-01

C(4) grasses, such as maize (Zea mays), have high photosynthetic efficiency through combined biochemical and structural adaptations. C(4) photosynthesis is established along the developmental axis of the leaf blade, leading from an undifferentiated leaf base just above the ligule into highly specialized mesophyll cells (MCs) and bundle sheath cells (BSCs) at the tip. To resolve the kinetics of maize leaf development and C(4) differentiation and to obtain a systems-level understanding of maize leaf formation, the accumulation profiles of proteomes of the leaf and the isolated BSCs with their vascular bundle along the developmental gradient were determined using large-scale mass spectrometry. This was complemented by extensive qualitative and quantitative microscopy analysis of structural features (e.g., Kranz anatomy, plasmodesmata, cell wall, and organelles). More than 4300 proteins were identified and functionally annotated. Developmental protein accumulation profiles and hierarchical cluster analysis then determined the kinetics of organelle biogenesis, formation of cellular structures, metabolism, and coexpression patterns. Two main expression clusters were observed, each divided in subclusters, suggesting that a limited number of developmental regulatory networks organize concerted protein accumulation along the leaf gradient. The coexpression with BSC and MC markers provided strong candidates for further analysis of C(4) specialization, in particular transporters and biogenesis factors. Based on the integrated information, we describe five developmental transitions that provide a conceptual and practical template for further analysis. An online protein expression viewer is provided through the Plant Proteome Database.

Proteomic profiling of early degenerative retina of RCS rats.

PubMed

Zhu, Zhi-Hong; Fu, Yan; Weng, Chuan-Huang; Zhao, Cong-Jian; Yin, Zheng-Qin

2017-01-01

To identify the underlying cellular and molecular changes in retinitis pigmentosa (RP). Label-free quantification-based proteomics analysis, with its advantages of being more economic and consisting of simpler procedures, has been used with increasing frequency in modern biological research. Dystrophic RCS rats, the first laboratory animal model for the study of RP, possess a similar pathological course as human beings with the diseases. Thus, we employed a comparative proteomics analysis approach for in-depth proteome profiling of retinas from dystrophic RCS rats and non-dystrophic congenic controls through Linear Trap Quadrupole - orbitrap MS/MS, to identify the significant differentially expressed proteins (DEPs). Bioinformatics analyses, including Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation and upstream regulatory analysis, were then performed on these retina proteins. Finally, a Western blotting experiment was carried out to verify the difference in the abundance of transcript factor E2F1. In this study, we identified a total of 2375 protein groups from the retinal protein samples of RCS rats and non-dystrophic congenic controls. Four hundred thirty-four significantly DEPs were selected by Student's t -test. Based on the results of the bioinformatics analysis, we identified mitochondrial dysfunction and transcription factor E2F1 as the key initiation factors in early retinal degenerative process. We showed that the mitochondrial dysfunction and the transcription factor E2F1 substantially contribute to the disease etiology of RP. The results provide a new potential therapeutic approach for this retinal degenerative disease.

Profiling of integral membrane proteins and their post translational modifications using high-resolution mass spectrometry

PubMed Central

Souda, Puneet; Ryan, Christopher M.; Cramer, William A.; Whitelegge, Julian

2011-01-01

Integral membrane proteins pose challenges to traditional proteomics approaches due to unique physicochemical properties including hydrophobic transmembrane domains that limit solubility in aqueous solvents. A well resolved intact protein molecular mass profile defines a protein’s native covalent state including post-translational modifications, and is thus a vital measurement toward full structure determination. Both soluble loop regions and transmembrane regions potentially contain post-translational modifications that must be characterized if the covalent primary structure of a membrane protein is to be defined. This goal has been achieved using electrospray-ionization mass spectrometry (ESI-MS) with low-resolution mass analyzers for intact protein profiling, and high-resolution instruments for top-down experiments, toward complete covalent primary structure information. In top-down, the intact protein profile is supplemented by gas-phase fragmentation of the intact protein, including its transmembrane regions, using collisionally activated and/or electroncapture dissociation (CAD/ECD) to yield sequence-dependent high-resolution MS information. Dedicated liquid chromatography systems with aqueous/organic solvent mixtures were developed allowing us to demonstrate that polytopic integral membrane proteins are amenable to ESI-MS analysis, including top-down measurements. Covalent post-translational modifications are localized regardless of their position in transmembrane domains. Top-down measurements provide a more detail oriented high-resolution description of post-transcriptional and post-translational diversity for enhanced understanding beyond genomic translation. PMID:21982782

Postprandial lipemia detects the effect of soy protein on cardiovascular disease risk compared with the fasting lipid profile.

PubMed

Santo, Antonio S; Santo, Ariana M; Browne, Richard W; Burton, Harold; Leddy, John J; Horvath, Steven M; Horvath, Peter J

2010-12-01

Studies examining the effect of soy protein on cardiovascular disease (CVD) risk factors have not taken advantage of the postprandial state as an adjunct to the fasting lipid profile. The American Heart Association has acknowledged the efficacy of soy protein in reducing CVD risk factors to be limited. We hypothesized that the postprandial state would be more sensitive to any favorable changes associated with consuming soy protein compared with the fasting lipid profile. Furthermore, the presence of isoflavones in soy would enhance this effect. Thirty sedentary males aged 18-30 years were randomly assigned to milk protein (Milk), isoflavone-poor soy (Soy-), or isoflavone-rich soy (Soy+). Usual diets were supplemented with 25 g/day of protein for 28 days. Serum samples were collected before and after supplementation in a fasted state and postprandially at 30, 60, 120, 240, and 360 min after a high-fat, 1,000 kcal shake. Triacylglycerol (TAG), total cholesterol, non-esterified fatty acids, apolipoproteins B-100 and A-I and glucose concentrations were quantified. Fasting concentrations were not different after any protein supplementation. Postprandial TAG and TAG AUC increased after Soy-consumption supporting the postprandial state as a more sensitive indicator of soy ingestion effects on CVD risk factors compared with the fasting lipid profile. Furthermore, the absence of isoflavones in soy protein may have deleterious consequences on purported cardio-protective effects.

Bioorthogonal chemistry: applications in activity-based protein profiling.

PubMed

Willems, Lianne I; van der Linden, Wouter A; Li, Nan; Li, Kah-Yee; Liu, Nora; Hoogendoorn, Sascha; van der Marel, Gijs A; Florea, Bogdan I; Overkleeft, Herman S

2011-09-20

The close interaction between organic chemistry and biology goes back to the late 18th century, when the modern natural sciences began to take shape. After synthetic organic chemistry arose as a discipline, organic chemists almost immediately began to pursue the synthesis of naturally occurring compounds, thereby contributing to the understanding of their functions in biological processes. Research in those days was often remarkably interdisciplinary; in fact, it constituted chemical biology research before the phrase even existed. For example, histological dyes, both of an organic and inorganic nature, were developed and applied by independent researchers (Gram and Golgi) with the aim of visualizing cellular substructures (the bacterial cell wall and the Golgi apparatus). Over the years, as knowledge within the various fields of the natural sciences deepened, research disciplines drifted apart, becoming rather monodisciplinary. In these years, broadly ranging from the end of World War II to about the 1980s, organic chemistry continued to impact life sciences research, but contributions were of a more indirect nature. As an example, the development of the polymerase chain reaction, from which molecular biology and genetics research have greatly profited, was partly predicated on the availability of synthetic oligonucleotides. These molecules first became available in the late 1960s, the result of organic chemists pursuing the synthesis of DNA oligomers primarily because of the synthetic challenges involved. Today, academic natural sciences research is again becoming more interdisciplinary, and sometimes even multidisciplinary. What was termed "chemical biology" by Stuart Schreiber at the end of the last century can be roughly described as the use of intellectually chemical approaches to shed light on processes that are fundamentally rooted in biology. Chemical tools and techniques that are developed for biological studies in the exciting and rapidly evolving field of chemical biology research include contributions from many areas of the multifaceted discipline of chemistry, and particularly from organic chemistry. Researchers apply knowledge inherent to organic chemistry, such as reactivity and selectivity, to the manipulation of specific biomolecules in biological samples (cell extracts, living cells, and sometimes even animal models) to gain insight into the biological phenomena in which these molecules participate. In this Account, we highlight some of the recent developments in chemical biology research driven by organic chemistry, with a focus on bioorthogonal chemistry in relation to activity-based protein profiling. The rigorous demands of bioorthogonality have not yet been realized in a truly bioorthogonal reagent pair, but remarkable progress has afforded a range of tangible contributions to chemical biology research. Activity-based protein profiling, which aims to obtain information on the workings of a protein (or protein family) within the larger context of the full biological system, has in particular benefited from these advances. Both activity-based protein profiling and bioorthogonal chemistry have been around for approximately 15 years, and about 8 years ago the two fields very profitably intersected. We expect that each discipline, both separately and in concert, will continue to make important contributions to chemical biology research. © 2011 American Chemical Society

Quantitative proteomic analysis of whey proteins in the colostrum and mature milk of yak (Bos grunniens).

PubMed

Yang, Yongxin; Zhao, Xiaowei; Yu, Shumin; Cao, Suizhong

2015-02-01

Yak (Bos grunniens) is an important natural resource in mountainous regions. To date, few studies have addressed the differences in the protein profiles of yak colostrum and milk. We used quantitative proteomics to compare the protein profiles of whey from yak colostrum and milk. Milk samples were collected from 21 yaks after calving (1 and 28 d). Whey protein profiles were generated through isobaric tag for relative and absolute quantification (iTRAQ)-labelled proteomics. We identified 183 proteins in milk whey; of these, the expression levels of 86 proteins differed significantly between the whey from colostrum and milk. Haemoglobin expression showed the greatest change; its levels were significantly higher in the whey from colostrum than in mature milk whey. Functional analysis revealed that many of the differentially expressed proteins were associated with biological regulation and response to stimuli. Further, eight differentially expressed proteins involved in the complement and coagulation cascade pathway were enriched in milk whey. These findings add to the general understanding of the protein composition of yak milk, suggest potential functions of the differentially expressed proteins, and provide novel information on the role of colostral components in calf survival. © 2014 Society of Chemical Industry.

Multiplex single-molecule interaction profiling of DNA-barcoded proteins.

PubMed

Gu, Liangcai; Li, Chao; Aach, John; Hill, David E; Vidal, Marc; Church, George M

2014-11-27

In contrast with advances in massively parallel DNA sequencing, high-throughput protein analyses are often limited by ensemble measurements, individual analyte purification and hence compromised quality and cost-effectiveness. Single-molecule protein detection using optical methods is limited by the number of spectrally non-overlapping chromophores. Here we introduce a single-molecular-interaction sequencing (SMI-seq) technology for parallel protein interaction profiling leveraging single-molecule advantages. DNA barcodes are attached to proteins collectively via ribosome display or individually via enzymatic conjugation. Barcoded proteins are assayed en masse in aqueous solution and subsequently immobilized in a polyacrylamide thin film to construct a random single-molecule array, where barcoding DNAs are amplified into in situ polymerase colonies (polonies) and analysed by DNA sequencing. This method allows precise quantification of various proteins with a theoretical maximum array density of over one million polonies per square millimetre. Furthermore, protein interactions can be measured on the basis of the statistics of colocalized polonies arising from barcoding DNAs of interacting proteins. Two demanding applications, G-protein coupled receptor and antibody-binding profiling, are demonstrated. SMI-seq enables 'library versus library' screening in a one-pot assay, simultaneously interrogating molecular binding affinity and specificity.

Exploring Polypharmacology Using a ROCS-Based Target Fishing Approach

DTIC Science & Technology

2012-01-01

target representatives. Target profiles were then generated for a given query molecule by computing maximal shape/ chemistry overlap between the query...molecule and the drug sets assigned to each protein target. The overlap was computed using the program ROCS (Rapid Overlay of Chemical Structures ). We...approaches in off-target prediction has been reviewed.9,10 Many structure -based target fishing (SBTF) approaches, such as INVDOCK11 and Target Fishing Dock

Proteomic Phenotyping of Novosphingobium nitrogenifigens Reveals a Robust Capacity for Simultaneous Nitrogen Fixation, Polyhydroxyalkanoate Production, and Resistance to Reactive Oxygen Species

PubMed Central

Strabala, Timothy J.; Peng, Lifeng; Rawson, Pisana; Lloyd-Jones, Gareth; Jordan, T. William

2012-01-01

Novosphingobium nitrogenifigens Y88T (Y88) is a free-living, diazotrophic Alphaproteobacterium, capable of producing 80% of its biomass as the biopolymer polyhydroxybutyrate (PHB). We explored the potential utility of this species as a polyhydroxybutyrate production strain, correlating the effects of glucose, nitrogen availability, dissolved oxygen concentration, and extracellular pH with polyhydroxybutyrate production and changes in the Y88 proteomic profile. Using two-dimensional differential in-gel electrophoresis and tandem mass spectrometry, we identified 217 unique proteins from six growth conditions. We observed reproducible, characteristic proteomic signatures for each of the physiological states we examined. We identified proteins that changed in abundance in correlation with either nitrogen fixation, dissolved oxygen concentration, or acidification of the growth medium. The proteins that correlated with nitrogen fixation were identified either as known nitrogen fixation proteins or as novel proteins that we predict play roles in aspects of nitrogen fixation based on their proteomic profiles. In contrast, the proteins involved in central carbon and polyhydroxybutyrate metabolism were constitutively abundant, consistent with the constitutive polyhydroxybutyrate production that we observed in this species. Three proteins with roles in detoxification of reactive oxygen species were identified in this obligate aerobe. The most abundant protein in all experiments was a polyhydroxyalkanoate granule-associated protein, phasin. The full-length isoform of this protein has a long, intrinsically disordered Ala/Pro/Lys-rich N-terminal segment, a feature that appears to be unique to sphingomonad phasins. The data suggest that Y88 has potential as a PHB production strain due to its aerobic tolerance and metabolic orientation toward polyhydroxybutyrate accumulation, even in low-nitrogen growth medium. PMID:22582058

Characterization of celiac disease related oat proteins: bases for the development of high quality oat varieties suitable for celiac patients.

PubMed

Giménez, María J; Real, Ana; García-Molina, M Dolores; Sousa, Carolina; Barro, Francisco

2017-02-17

Some studies have suggested that the immunogenicity of oats depends on the cultivar. RP-HPLC has been proposed as a useful technique to select varieties of oats with reduced immunogenicity. The aim of this study was to identify both the avenin protein patterns associated with low gluten content and the available variability for the development of new non-toxic oat cultivars. The peaks of alcohol-soluble avenins of a collection of landraces and cultivars of oats have been characterized based on the RP-HPLC elution times. The immunotoxicity of oat varieties for patients with celiac disease (CD) has been tested using a competitive ELISA based on G12 monoclonal antibody. The oat lines show, on average, seven avenin peaks giving profiles with certain similarities. Based on this similarity, most of the accessions have been grouped into avenin patterns. The variability of RP-HPLC profiles of the collection is great, but not sufficient to uniquely identify the different varieties of the set. Overall, the immunogenicity of the collection is less than 20 ppm. However, there is a different distribution of toxicity ranges between the different peak patterns. We conclude that the RP-HPLC technique is useful to establish groups of varieties differing in degree of toxicity for CD patients.

Characterization of celiac disease related oat proteins: bases for the development of high quality oat varieties suitable for celiac patients

PubMed Central

Giménez, María J.; Real, Ana; García-Molina, M. Dolores; Sousa, Carolina; Barro, Francisco

2017-01-01

Some studies have suggested that the immunogenicity of oats depends on the cultivar. RP-HPLC has been proposed as a useful technique to select varieties of oats with reduced immunogenicity. The aim of this study was to identify both the avenin protein patterns associated with low gluten content and the available variability for the development of new non-toxic oat cultivars. The peaks of alcohol-soluble avenins of a collection of landraces and cultivars of oats have been characterized based on the RP-HPLC elution times. The immunotoxicity of oat varieties for patients with celiac disease (CD) has been tested using a competitive ELISA based on G12 monoclonal antibody. The oat lines show, on average, seven avenin peaks giving profiles with certain similarities. Based on this similarity, most of the accessions have been grouped into avenin patterns. The variability of RP-HPLC profiles of the collection is great, but not sufficient to uniquely identify the different varieties of the set. Overall, the immunogenicity of the collection is less than 20 ppm. However, there is a different distribution of toxicity ranges between the different peak patterns. We conclude that the RP-HPLC technique is useful to establish groups of varieties differing in degree of toxicity for CD patients. PMID:28209962

Objective Diagnosis of Cervical Cancer by Tissue Protein Profile Analysis

NASA Astrophysics Data System (ADS)

Patil, Ajeetkumar; Bhat, Sujatha; Rai, Lavanya; Kartha, V. B.; Chidangil, Santhosh

2011-07-01

Protein profiles of homogenized normal cervical tissue samples from hysterectomy subjects and cancerous cervical tissues from biopsy samples collected from patients with different stages of cervical cancer were recorded using High Performance Liquid Chromatography coupled with Laser Induced Fluorescence (HPLC-LIF). The Protein profiles were subjected to Principle Component Analysis to derive statistically significant parameters. Diagnosis of sample types were carried out by matching three parameters—scores of factors, squared residuals, and Mahalanobis Distance. ROC and Youden's Index curves for calibration standards were used for objective estimation of the optimum threshold for decision making and performance.

Small RNA fragments in complex culture media cause alterations in protein profiles of three species of bacteria.

PubMed

Pavankumar, Asalapuram R; Ayyappasamy, Sudalaiyadum Perumal; Sankaran, Krishnan

2012-03-01

Efforts to delineate the basis for variations in protein profiles of different membrane fractions from various bacterial pathogens led to the finding that even the same medium [e.g., Luria Bertani (LB) broth] purchased from different commercial sources generates remarkably dissimilar protein profiles despite similar growth characteristics. Given the pervasive roles small RNAs play in regulating gene expression, we inquired if these source-specific differences due to media arise from disparities in the presence of small RNAs. Indeed, LB media components from two different commercial suppliers contained varying, yet significant, amounts of 10-80 bp small RNAs. Removal of small RNA from LB using RNaseA during media preparation resulted in significant changes in bacterial protein expression profiles. Our studies underscore the fact that seemingly identical growth media can lead to dramatic alterations in protein expression patterns, highlighting the importance of utilizing media free of small RNA during bacteriological studies. Finally, these results raise the intriguing possibility that similar pools of small RNAs in the environment can influence bacterial adaptation.

Comparison of Haemophilus parasuis reference strains and field isolates by using random amplified polymorphic DNA and protein profiles

PubMed Central

2012-01-01

Background Haemophilus parasuis is the causative agent of Glässer’s disease and is a pathogen of swine in high-health status herds. Reports on serotyping of field strains from outbreaks describe that approximately 30% of them are nontypeable and therefore cannot be traced. Molecular typing methods have been used as alternatives to serotyping. This study was done to compare random amplified polymorphic DNA (RAPD) profiles and whole cell protein (WCP) lysate profiles as methods for distinguishing H. parasuis reference strains and field isolates. Results The DNA and WCP lysate profiles of 15 reference strains and 31 field isolates of H. parasuis were analyzed using the Dice and neighbor joining algorithms. The results revealed unique and reproducible DNA and protein profiles among the reference strains and field isolates studied. Simpson’s index of diversity showed significant discrimination between isolates when three 10mer primers were combined for the RAPD method and also when both the RAPD and WCP lysate typing methods were combined. Conclusions The RAPD profiles seen among the reference strains and field isolates did not appear to change over time which may reflect a lack of DNA mutations in the genes of the samples. The recent field isolates had different WCP lysate profiles than the reference strains, possibly because the number of passages of the type strains may affect their protein expression. PMID:22703293

Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function

PubMed Central

Tian, Weidong; Zhang, Lan V; Taşan, Murat; Gibbons, Francis D; King, Oliver D; Park, Julie; Wunderlich, Zeba; Cherry, J Michael; Roth, Frederick P

2008-01-01

Background: Learning the function of genes is a major goal of computational genomics. Methods for inferring gene function have typically fallen into two categories: 'guilt-by-profiling', which exploits correlation between function and other gene characteristics; and 'guilt-by-association', which transfers function from one gene to another via biological relationships. Results: We have developed a strategy ('Funckenstein') that performs guilt-by-profiling and guilt-by-association and combines the results. Using a benchmark set of functional categories and input data for protein-coding genes in Saccharomyces cerevisiae, Funckenstein was compared with a previous combined strategy. Subsequently, we applied Funckenstein to 2,455 Gene Ontology terms. In the process, we developed 2,455 guilt-by-profiling classifiers based on 8,848 gene characteristics and 12 functional linkage graphs based on 23 biological relationships. Conclusion: Funckenstein outperforms a previous combined strategy using a common benchmark dataset. The combination of 'guilt-by-profiling' and 'guilt-by-association' gave significant improvement over the component classifiers, showing the greatest synergy for the most specific functions. Performance was evaluated by cross-validation and by literature examination of the top-scoring novel predictions. These quantitative predictions should help prioritize experimental study of yeast gene functions. PMID:18613951

A Metabolic Probe-Enabled Strategy Reveals Uptake and Protein Targets of Polyunsaturated Aldehydes in the Diatom Phaeodactylum tricornutum

PubMed Central

Wolfram, Stefanie; Wielsch, Natalie; Hupfer, Yvonne; Mönch, Bettina; Lu-Walther, Hui-Wen; Heintzmann, Rainer; Werz, Oliver; Svatoš, Aleš; Pohnert, Georg

2015-01-01

Diatoms are unicellular algae of crucial importance as they belong to the main primary producers in aquatic ecosystems. Several diatom species produce polyunsaturated aldehydes (PUAs) that have been made responsible for chemically mediated interactions in the plankton. PUA-effects include chemical defense by reducing the reproductive success of grazing copepods, allelochemical activity by interfering with the growth of competing phytoplankton and cell to cell signaling. We applied a PUA-derived molecular probe, based on the biologically highly active 2,4-decadienal, with the aim to reveal protein targets of PUAs and affected metabolic pathways. By using fluorescence microscopy, we observed a substantial uptake of the PUA probe into cells of the diatom Phaeodactylum tricornutum in comparison to the uptake of a structurally closely related control probe based on a saturated aldehyde. The specific uptake motivated a chemoproteomic approach to generate a qualitative inventory of proteins covalently targeted by the α,β,γ,δ-unsaturated aldehyde structure element. Activity-based protein profiling revealed selective covalent modification of target proteins by the PUA probe. Analysis of the labeled proteins gave insights into putative affected molecular functions and biological processes such as photosynthesis including ATP generation and catalytic activity in the Calvin cycle or the pentose phosphate pathway. The mechanism of action of PUAs involves covalent reactions with proteins that may result in protein dysfunction and interference of involved pathways. PMID:26496085

Different protein profile in amniotic fluid with nervous system malformations by surface-enhanced laser desorption-ionization/time-of-flight mass spectrometry (SELDI-TOF-MS) technology.

PubMed

Ma, Zhe; Liu, Cun; Deng, Biping; Dong, Shaogang; Tao, Guowei; Zhan, Xinfeng; Wang, Chuner; Liu, Shaoping; Qu, Xun

2010-12-01

To detect the distinct proteins in amniotic fluid (AF) between nervous system malformations fetuses and normal fetuses. Surface-enhanced laser desorption-ionization/time-of-flight mass spectrometry was used to characterize AF peptides in AF between nervous system malformations fetuses and normal fetuses. WCX2 protein chips were used to characterize AF peptides in AF. Protein chips were examined in a PBSIIC protein reader, the protein profiling was collected by ProteinChip software version 3.1 (Ciphergen Biosystems, Fremont, CA, USA) and analyzed by Biomarker Wizard software (Ciphergen Biosystems). Nine distinct proteins were identified in AF between nervous system malformations fetuses and normal fetuses. Compared with the control group, three proteins with m/z 4967.5 Da, 5258.0 Da, and 11,717.0 Da were down-regulated, and six proteins with m/z 2540.4 Da, 3107.1 Da, 3396.8 Da, 4590.965 Da, 5589.2 Da and 6429.4 Da up-regulated in nervous system malformations fetuses. The results suggest that there are distinct proteins in protein profiling of AF between nervous system malformations fetuses and normal fetuses. © 2010 The Authors. Journal of Obstetrics and Gynaecology Research © 2010 Japan Society of Obstetrics and Gynecology.

A comparison of the human and mouse protein corona profiles of functionalized SiO2 nanocarriers.

PubMed

Solorio-Rodríguez, A; Escamilla-Rivera, V; Uribe-Ramírez, M; Chagolla, A; Winkler, R; García-Cuellar, C M; De Vizcaya-Ruiz, A

2017-09-21

Nanoparticles are a promising cancer therapy for their use as drug carriers given their versatile functionalization with polyethylene glycol and proteins that can be recognized by overexpressed receptors in tumor cells. However, it has been suggested that in biological fluids, proteins cover nanoparticles, which gives the proteins a biological identity that could be responsible for unexpected biological responses: the so-called protein corona. A relevant biological event that is usually ignored in protein-corona formation is the interspecies differences in protein binding, which can be involved in the discrepancies observed in preclinical studies and the nanoparticle safety and efficiency. Hence, the aim of this study was to determine the differences between human and mouse plasma protein corona profiles in an active therapy model using silicon dioxide nanoparticles (SiO 2 nanoparticles) functionalized with polyethylene glycol and transferrin. Functionalized SiO 2 nanoparticles were made with a primary particle size of 25 nm and a transferrin content of 50 μg mg -1 of nanoparticles and were PEGylated with a cross-linker. The proteomic analysis by nanoliquid chromatography tandem-mass spectrometry (nanoLC-MS/MS) showed interspecies differences. The most abundant proteins found in the human protein corona profile were immunoglobulins, actin cytoplasmic 1, hemoglobin subunit beta, serotransferrin, ficolin-3, complement C3, and apolipoprotein A-1. Meanwhile, the mouse protein corona adsorbed the serine protease inhibitor A3K, serotransferrin, alpha-1-antitrypsin 1-2, hemoglobin subunit beta, and fibrinogen gamma and beta chains. These protein-corona profile differences in the functionalized SiO 2 nanoparticles indicate that biological responses observed in in vivo models could not be translated to clinical use and must be considered in the interpretation of preclinical trials in order to design more efficient and safer nanomedicines.

LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise.

PubMed

Mantini, Dante; Petrucci, Francesca; Pieragostino, Damiana; Del Boccio, Piero; Di Nicola, Marta; Di Ilio, Carmine; Federici, Giorgio; Sacchetta, Paolo; Comani, Silvia; Urbani, Andrea

2007-03-26

Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational method for the detection of protein peaks from linear-mode MALDI-TOF data is proposed. LIMPIC is based on novel techniques for background noise reduction and baseline removal. Peak detection is performed considering the presence of a non-homogeneous noise level in the mass spectrum. A comparison of the peaks collected from multiple spectra is used to classify them on the basis of a detection rate parameter, and hence to separate the protein signals from other disturbances. LIMPIC preprocessing proves to be superior than other classical preprocessing techniques, allowing for a reliable decomposition of the background noise and the baseline drift from the MALDI-TOF mass spectra. It provides lower coefficient of variation associated with the peak intensity, improving the reliability of the information that can be extracted from single spectra. Our results show that LIMPIC peak-picking is effective even in low protein concentration regimes. The analytical comparison with commercial and freeware peak-picking algorithms demonstrates its superior performances in terms of sensitivity and specificity, both on in-vitro purified protein samples and human plasma samples. The quantitative information on the peak intensity extracted with LIMPIC could be used for the recognition of significant protein profiles by means of advanced statistic tools: LIMPIC might be valuable in the perspective of biomarker discovery.

Quantitative Fluorescence Studies in Living Cells: Extending Fluorescence Fluctuation Spectroscopy to Peripheral Membrane Proteins

NASA Astrophysics Data System (ADS)

Smith, Elizabeth Myhra

The interactions of peripheral membrane proteins with both membrane lipids and proteins are vital for many cellular processes including membrane trafficking, cellular signaling, and cell growth/regulation. Building accurate biophysical models of these processes requires quantitative characterization of the behavior of peripheral membrane proteins, yet methods to quantify their interactions inside living cells are very limited. Because peripheral membrane proteins usually exist both in membrane-bound and cytoplasmic forms, the separation of these two populations is a key challenge. This thesis aims at addressing this challenge by extending fluorescence fluctuation spectroscopy (FFS) to simultaneously measure the oligomeric state of peripheral membrane proteins in the cytoplasm and at the plasma membrane. We developed a new method based on z-scan FFS that accounts for the fluorescence contributions from cytoplasmic and membrane layers by incorporating a fluorescence intensity z-scan through the cell. H-Ras-EGFP served as a model system to demonstrate the feasibility of the technique. The resolvability and stability of z-scanning was determined as well as the oligomeric state of H-Ras-EGFP at the plasma membrane and in the cytoplasm. Further, we successfully characterized the binding affinity of a variety of proteins to the plasma membrane by quantitative analysis of the z-scan fluorescence intensity profile. This analysis method, which we refer to as z-scan fluorescence profile deconvoution, was further used in combination with dual-color competition studies to determine the lipid specificity of protein binding. Finally, we applied z-scan FFS to provide insight into the early assembly steps of the HTLV-1 retrovirus.

Proteomic profiling and identification of immunodominant spore antigens of Bacillus anthracis, Bacillus cereus, and Bacillus thuringiensis.

PubMed

Delvecchio, Vito G; Connolly, Joseph P; Alefantis, Timothy G; Walz, Alexander; Quan, Marian A; Patra, Guy; Ashton, John M; Whittington, Jessica T; Chafin, Ryan D; Liang, Xudong; Grewal, Paul; Khan, Akbar S; Mujer, Cesar V

2006-09-01

Differentially expressed and immunogenic spore proteins of the Bacillus cereus group of bacteria, which includes Bacillus anthracis, Bacillus cereus, and Bacillus thuringiensis, were identified. Comparative proteomic profiling of their spore proteins distinguished the three species from each other as well as the virulent from the avirulent strains. A total of 458 proteins encoded by 232 open reading frames were identified by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry analysis for all the species. A number of highly expressed proteins, including elongation factor Tu (EF-Tu), elongation factor G, 60-kDa chaperonin, enolase, pyruvate dehydrogenase complex, and others exist as charge variants on two-dimensional gels. These charge variants have similar masses but different isoelectric points. The majority of identified proteins have cellular roles associated with energy production, carbohydrate transport and metabolism, amino acid transport and metabolism, posttranslational modifications, and translation. Novel vaccine candidate proteins were identified using B. anthracis polyclonal antisera from humans postinfected with cutaneous anthrax. Fifteen immunoreactive proteins were identified in B. anthracis spores, whereas 7, 14, and 7 immunoreactive proteins were identified for B. cereus and in the virulent and avirulent strains of B. thuringiensis spores, respectively. Some of the immunodominant antigens include charge variants of EF-Tu, glyceraldehyde-3-phosphate dehydrogenase, dihydrolipoamide acetyltransferase, Delta-1-pyrroline-5-carboxylate dehydrogenase, and a dihydrolipoamide dehydrogenase. Alanine racemase and neutral protease were uniquely immunogenic to B. anthracis. Comparative analysis of the spore immunome will be of significance for further nucleic acid- and immuno-based detection systems as well as next-generation vaccine development.

Proteomic Profiling and Identification of Immunodominant Spore Antigens of Bacillus anthracis, Bacillus cereus, and Bacillus thuringiensis‡

PubMed Central

DelVecchio, Vito G.; Connolly, Joseph P.; Alefantis, Timothy G.; Walz, Alexander; Quan, Marian A.; Patra, Guy; Ashton, John M.; Whittington, Jessica T.; Chafin, Ryan D.; Liang, Xudong; Grewal, Paul; Khan, Akbar S.; Mujer, Cesar V.

2006-01-01

Differentially expressed and immunogenic spore proteins of the Bacillus cereus group of bacteria, which includes Bacillus anthracis, Bacillus cereus, and Bacillus thuringiensis, were identified. Comparative proteomic profiling of their spore proteins distinguished the three species from each other as well as the virulent from the avirulent strains. A total of 458 proteins encoded by 232 open reading frames were identified by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry analysis for all the species. A number of highly expressed proteins, including elongation factor Tu (EF-Tu), elongation factor G, 60-kDa chaperonin, enolase, pyruvate dehydrogenase complex, and others exist as charge variants on two-dimensional gels. These charge variants have similar masses but different isoelectric points. The majority of identified proteins have cellular roles associated with energy production, carbohydrate transport and metabolism, amino acid transport and metabolism, posttranslational modifications, and translation. Novel vaccine candidate proteins were identified using B. anthracis polyclonal antisera from humans postinfected with cutaneous anthrax. Fifteen immunoreactive proteins were identified in B. anthracis spores, whereas 7, 14, and 7 immunoreactive proteins were identified for B. cereus and in the virulent and avirulent strains of B. thuringiensis spores, respectively. Some of the immunodominant antigens include charge variants of EF-Tu, glyceraldehyde-3-phosphate dehydrogenase, dihydrolipoamide acetyltransferase, Δ-1-pyrroline-5-carboxylate dehydrogenase, and a dihydrolipoamide dehydrogenase. Alanine racemase and neutral protease were uniquely immunogenic to B. anthracis. Comparative analysis of the spore immunome will be of significance for further nucleic acid- and immuno-based detection systems as well as next-generation vaccine development. PMID:16957262

Spiking of serum specimens with exogenous reporter peptides for mass spectrometry based protease profiling as diagnostic tool.

PubMed

Findeisen, Peter; Peccerella, Teresa; Post, Stefan; Wenz, Frederik; Neumaier, Michael

2008-04-01

Serum is a difficult matrix for the identification of biomarkers by mass spectrometry (MS). This is due to high-abundance proteins and their complex processing by a multitude of endogenous proteases making rigorous standardisation difficult. Here, we have investigated the use of defined exogenous reporter peptides as substrates for disease-specific proteases with respect to improved standardisation and disease classification accuracy. A recombinant N-terminal fragment of the Adenomatous Polyposis Coli (APC) protein was digested with trypsin to yield a peptide mixture for subsequent Reporter Peptide Spiking (RPS) of serum. Different preanalytical handling of serum samples was simulated by storage of serum samples for up to 6 h at ambient temperature, followed by RPS, further incubation under standardised conditions and testing for stability of protease-generated MS profiles. To demonstrate the superior classification accuracy achieved by RPS, a pilot profiling experiment was performed using serum specimens from pancreatic cancer patients (n = 50) and healthy controls (n = 50). After RPS six different peak categories could be defined, two of which (categories C and D) are modulated by endogenous proteases. These latter are relevant for improved classification accuracy as shown by enhanced disease-specific classification from 78% to 87% in unspiked and spiked samples, respectively. Peaks of these categories presented with unchanged signal intensities regardless of preanalytical conditions. The use of RPS generally improved the signal intensities of protease-generated peptide peaks. RPS circumvents preanalytical variabilities and improves classification accuracies. Our approach will be helpful to introduce MS-based proteomic profiling into routine laboratory testing.

Mitochondrial genome sequence and expression profiling for the legume pod borer Maruca vitrata (Lepidoptera: Crambidae)

USDA-ARS?s Scientific Manuscript database

We report on the assembly of the 14,146 base pairs (bp) near complete mitochondrial sequencing of the legume pod borer (LPB), Maruca vitrata (Lepidoptera: Crambidae), which was used to estimate divergence and relationships within the lepidopteran lineage. Arrangement and orientation of 13 protein c...

Functionomics of NCC mutations in Gitelman syndrome using a novel mammalian cell-based activity assay.

PubMed

Valdez-Flores, Marco A; Vargas-Poussou, Rosa; Verkaart, Sjoerd; Tutakhel, Omar A Z; Valdez-Ortiz, Angel; Blanchard, Anne; Treard, Cyrielle; Hoenderop, Joost G J; Bindels, René J M; Jeleń, Sabina

2016-12-01

Gitelman syndrome (GS) is an autosomal recessive salt-wasting tubular disorder resulting from loss-of-function mutations in the thiazide-sensitive NaCl cotransporter (NCC). Functional analysis of these mutations has been limited to the use of Xenopus laevis oocytes. The aim of the present study was, therefore, to analyze the functional consequences of NCC mutations in a mammalian cell-based assay, followed by analysis of mutated NCC protein expression as well as glycosylation and phosphorylation profiles using human embryonic kidney (HEK) 293 cells. NCC activity was assessed with a novel assay based on thiazide-sensitive iodide uptake in HEK293 cells expressing wild-type or mutant NCC (N59I, R83W, I360T, C421Y, G463R, G731R, L859P, or R861C). All mutations caused a significantly lower NCC activity. Immunoblot analysis of the HEK293 cells revealed that 1) all NCC mutants have decreased NCC protein expression; 2) mutant N59I, R83W, I360T, C421Y, G463R, and L859P have decreased NCC abundance at the plasma membrane; 3) mutants C421Y and L859P display impaired NCC glycosylation; and 4) mutants N59I, R83W, C421Y, C731R, and L859P show affected NCC phosphorylation. In conclusion, we developed a mammalian cell-based assay in which NCC activity assessment together with a profiling of mutated protein processing aid our understanding of the pathogenic mechanism of the NCC mutations. Copyright © 2016 the American Physiological Society.

The DIMA web resource--exploring the protein domain network.

PubMed

Pagel, Philipp; Oesterheld, Matthias; Stümpflen, Volker; Frishman, Dmitrij

2006-04-15

Conserved domains represent essential building blocks of most known proteins. Owing to their role as modular components carrying out specific functions they form a network based both on functional relations and direct physical interactions. We have previously shown that domain interaction networks provide substantially novel information with respect to networks built on full-length protein chains. In this work we present a comprehensive web resource for exploring the Domain Interaction MAp (DIMA), interactively. The tool aims at integration of multiple data sources and prediction techniques, two of which have been implemented so far: domain phylogenetic profiling and experimentally demonstrated domain contacts from known three-dimensional structures. A powerful yet simple user interface enables the user to compute, visualize, navigate and download domain networks based on specific search criteria. http://mips.gsf.de/genre/proj/dima

Genetic differences in the serum proteome of horses, donkeys and mules are detectable by protein profiling.

PubMed

Henze, Andrea; Aumer, Franziska; Grabner, Arthur; Raila, Jens; Schweigert, Florian J

2011-10-01

Although horses and donkeys belong to the same genus, their genetic characteristics probably result in specific proteomes and post-translational modifications (PTM) of proteins. Since PTM can alter protein properties, specific PTM may contribute to species-specific characteristics. Therefore, the aim of the present study was to analyse differences in serum protein profiles of horses and donkeys as well as mules, which combine the genetic backgrounds of both species. Additionally, changes in PTM of the protein transthyretin (TTR) were analysed. Serum protein profiles of each species (five animals per species) were determined using strong anion exchanger ProteinChips® (Bio-Rad, Munich, Germany) in combination with surface-enhanced laser desorption ionisation-time of flight MS. The PTM of TTR were analysed subsequently by immunoprecipitation in combination with matrix-assisted laser desorption ionisation-time of flight MS. Protein profiling revealed species-specific differences in the proteome, with some protein peaks present in all three species as well as protein peaks that were unique for donkeys and mules, horses and mules or for horses alone. The molecular weight of TTR of horses and donkeys differed by 30 Da, and both species revealed several modified forms of TTR besides the native form. The mass spectra of mules represented a merging of TTR spectra of horses and donkeys. In summary, the present study indicated that there are substantial differences in the proteome of horses and donkeys. Additionally, the results probably indicate that the proteome of mules reveal a higher similarity to donkeys than to horses.

Protein profiles associated with survival in lung adenocarcinoma

PubMed Central

Chen, Guoan; Gharib, Tarek G; Wang, Hong; Huang, Chiang-Ching; Kuick, Rork; Thomas, Dafydd G.; Shedden, Kerby A.; Misek, David E.; Taylor, Jeremy M. G.; Giordano, Thomas J.; Kardia, Sharon L. R.; Iannettoni, Mark D.; Yee, John; Hogg, Philip J.; Orringer, Mark B.; Hanash, Samir M.; Beer, David G.

2003-01-01

Morphologic assessment of lung tumors is informative but insufficient to adequately predict patient outcome. We previously identified transcriptional profiles that predict patient survival, and here we identify proteins associated with patient survival in lung adenocarcinoma. A total of 682 individual protein spots were quantified in 90 lung adenocarcinomas by using quantitative two-dimensional polyacrylamide gel electrophoresis analysis. A leave-one-out cross-validation procedure using the top 20 survival-associated proteins identified by Cox modeling indicated that protein profiles as a whole can predict survival in stage I tumor patients (P = 0.01). Thirty-three of 46 survival-associated proteins were identified by using mass spectrometry. Expression of 12 candidate proteins was confirmed as tumor-derived with immunohistochemical analysis and tissue microarrays. Oligonucleotide microarray results from both the same tumors and from an independent study showed mRNAs associated with survival for 11 of 27 encoded genes. Combined analysis of protein and mRNA data revealed 11 components of the glycolysis pathway as associated with poor survival. Among these candidates, phosphoglycerate kinase 1 was associated with survival in the protein study, in both mRNA studies and in an independent validation set of 117 adenocarcinomas and squamous lung tumors using tissue microarrays. Elevated levels of phosphoglycerate kinase 1 in the serum were also significantly correlated with poor outcome in a validation set of 107 patients with lung adenocarcinomas using ELISA analysis. These studies identify new prognostic biomarkers and indicate that protein expression profiles can predict the outcome of patients with early-stage lung cancer. PMID:14573703