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Phosphorylation is a post-translational protein modification regulating most known cellular processes. While protein kinases constitute a large family of highly conserved enzymes, identification of active kinases is challenging due to a low abundance of some of these signaling molecules. Although chicken is the first agricultural animal to have a sequenced genome, annotation of the kinome, i.e., a complement of all protein kinases in the genome is limited. We used chemical probes consisting of ATP and ADP derivatives binding to specific lysine (Lys) residues within the ATP-binding pocket of kinases, combined with proteomics, to identify 267 peptides labeled with the ATP and ADP acyl derivatives and 188 corresponding chicken kinases in chicken spleen and liver. Our description of active chicken kinases and ATP binding sites will support future studies focused on identifying the role of this important class of enzymes in chicken health and disease. Significance Advances made in understanding chicken enzymes are critical for the improved knowledge of the regulatory pathways controlling physiological processes in chicken. Since protein phosphorylation controls multiple aspects of cell fate, it is often linked to pathological conditions, and understanding of the kinase expression in chicken is essential for future therapeutic approaches. We coupled proteomics and labeling with active-site probes binding to Lys residues within the ATP-binding pocket of kinases to identify 188 kinases and corresponding 267 peptides labeled with the ATP and ADP acyl derivatives in chicken spleen and liver. Results of the present study describing catalytically active kinases is a starting point for chemoproteomic-based interrogation of kinases in chicken exposed to different conditions. Kinases identified in this study are available through the Chickspress genome browser that has previously published mRNA, miRNA, and shotgun proteomics data.

Lauren A Bright,1 Wellesley Dittmar,1 Bindu Nanduri,2 Fiona M McCarthy,3 Nisma Mujahid,2 Lais RR Costa,2 Shane C Burgess,3 Cyprianna E Swiderski11Department of Clinical Sciences, College of Veterinary Medicine, Mississippi State University, Starkville, MS 39762, USA; 2Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, Starkville, MS 39762, USA; 3School of Animal Comparative and Biomedical Sciences, College of Agriculture and Life Sciences, University of Arizona, Tucson, AZ 85721, USABackground: Pasture-associated severe equine asthma is a warm season, environmentally-induced respiratory disease characterized by reversible airway obstruction, persistent and non-specific airway hyper-responsiveness, and chronic neutrophilic airway inflammation. During seasonal exacerbation, signs vary from mild to life-threatening episodes of wheezing, coughing, and chronic debilitating labored breathing.Purpose: In human asthma, neutrophilic airway inflammation is associated with more severe and steroid-refractory asthma phenotypes, highlighting a need to decipher the mechanistic basis of this disease characteristic. We hypothesize that the collective biological activities of proteins in bronchoalveolar lavage fluid (BALF) of horses with pasture-associated severe asthma predict changes in neutrophil functions that contribute to airway neutrophilic inflammation.Methods: Using shotgun proteomics, we identified 1,003 unique proteins in cell-free BALF from six horses experiencing asthma exacerbation and six control herdmates. Contributions of each protein to ten neutrophil functions were modeled using manual biocuration to determine each protein’s net effect on the respective neutrophil functions.Results: A total of 417 proteins were unique to asthmatic horses, 472 proteins were unique to control horses (p

To develop a reproducible tissue lysis method that retains enzyme function for activity-based protein profiling, we compared four different methods to obtain protein extracts from bovine lung tissue: focused ultrasonication, standard sonication, mortar & pestle method, and homogenization combined with standard sonication. Focused ultrasonication and mortar & pestle methods were sufficiently effective for activity-based profiling of deubiquitinases in tissue, and focused ultrasonication also had the fastest processing time. We used focused-ultrasonicator for subsequent activity-based proteomic analysis of deubiquitinases to test the compatibility of this method in sample preparation for activity-based chemical proteomics.

Bovine respiratory disease (BRD) is the most common economically important disease affecting cattle. For developing accurate diagnostics that can predict disease susceptibility/resistance and stratification, it is necessary to identify the molecular mechanisms that underlie BRD. To study the complex interactions among the bovine host and the multitude of viral and bacterial pathogens, as well as the environmental factors associated with BRD etiology, genome-scale high-throughput functional genomics methods such as microarrays, RNA-seq, and proteomics are helpful. In this review, we summarize the progress made in our understanding of BRD using functional genomics approaches. We also discuss some of the available bioinformatics resources for analyzing high-throughput data, in the context of biological pathways and molecular interactions. Although resources for studying host response to infection are available, the corresponding information is lacking for majority of BRD pathogens, impeding progress in identifying diagnostic signatures for BRD using functional genomics approaches.

Bovine herpesvirus (BoHV) type 1 is an important agricultural pathogen that infects cattle and other ruminants worldwide. Acute infection of the oro-respiratory tract leads to immune suppression and allows commensal bacteria to infect an otherwise healthy lower respiratory tract. This condition is known as the Bovine Respiratory Disease (BRD). BoHV-1 latently infects the host for life and periodical stress events re-initiate BRD, translating into high morbidity and large economic losses. To gain a better understanding of the biology of BoHV-1 and the disease it causes, we elucidated the protein composition of extracellular virions using liquid chromatography-mass spectrometry analysis. We detected 33 viral proteins, including the expected proteins of the nucleocapsid and envelope as well as other regulatory proteins present in the viral tegument. In addition to viral proteins, we have also identified packaged proteins of host origin. This constitutes the first proteomic characterization of the BoHV virion.

Listeria monocytogenes is a Gram-positive, foodborne pathogen responsible for approximately 28% of all food-related deaths each year in the United States. L. monocytogenes infections are linked to the consumption of minimally processed ready-to-eat (RTE) products such as cheese, deli meats, and cold-smoked finfish products. L. monocytogenes is resistant to stresses commonly encountered in the food-processing environment, including low pH, high salinity, oxygen content, and various temperatures. The purpose of this study was to determine if cells habituated at low temperatures would result in cross-protective effects against osmotic stress. We found that cells exposed to refrigerated temperatures prior to a mild salt stress treatment had increased survival in NaCl concentrations of 3%. Additionally, the longer the cells were pre-exposed to cold temperatures, the greater the increase in survival in 3% NaCl. A proteomics analysis was performed in triplicate in order to elucidate mechanisms involved in cold-stress induced cross protection against osmotic stress. Proteins involved in maintenance of the cell wall and cellular processes, such as penicillin binding proteins and osmolyte transporters, and processes involving amino acid metabolism, such as osmolyte synthesis, transport, and lipid biosynthesis, had the greatest increase in expression when cells were exposed to cold temperatures prior to salt. By gaining a better understanding of how this pathogen adapts physiologically to various environmental conditions, improvements can be made in detection and mitigation strategies.

Social play is the most characteristic form of social interaction which is necessary for adolescents to develop proper cognitive, emotional, and social competency. The information available on neural substrates and the mechanism involved in social play is limited. This study characterized social play by proteomic and transcriptional profiling studies. Social play was performed on male Sprague Dawley rats on postnatal day 38 and protein and gene expression in the amygdala was determined following behavioral testing. The proteomic analysis led to the identification of 170 differentially expressed proteins (p ≤ 0.05) with 67 upregulated and 103 downregulated proteins. The transcriptomic analysis led to the identification of 188 genes (FDR ≤ 0.05) with 55 upregulated and 133 downregulated genes. DAVID analysis of gene/protein expression data revealed that social play altered GABAergic signaling, glutamatergic signaling, and G-protein coupled receptor (GPCR) signaling. These data suggest that the synaptic levels of GABA and glutamate increased during play. Ingenuity Pathway Analysis (IPA) confirmed these alterations. IPA also revealed that differentially expressed genes/proteins in our data had significant over representation of neurotransmitter signaling systems, including the opioid, serotonin, and dopamine systems, suggesting that play alters the systems involved in the regulation of reward. In addition, corticotropin-releasing hormone signaling was altered indicating that an increased level of stress occurs during play. Overall, our data suggest that increased inhibitory GPCR signaling in these neurotransmitter pathways occurs following social play as a physiological response to regulate the induced level of reward and stress and to maintain the excitatory-inhibitory balance in the neurotransmitter systems.

The equine genome sequence enables the use of high-throughput genomic technologies in equine research, but accurate identification of expressed gene products and interpreting their biological relevance require additional structural and functional genome annotation. Here, we employ the equine genome sequence to identify predicted and known proteins using proteomics and model these proteins into biological pathways, identifying 582 proteins in normal cell-free equine bronchoalveolar lavage fluid (BALF). We improved structural and functional annotation by directly confirming the in vivo expression of 558 (96%) proteins, which were computationally predicted previously, and adding Gene Ontology (GO) annotations for 174 proteins, 108 of which lacked functional annotation. Bronchoalveolar lavage is commonly used to investigate equine respiratory disease, leading us to model the associated proteome and its biological functions. Modelling of protein functions using Ingenuity Pathway Analysis identified carbohydrate metabolism, cell-to-cell signalling, cellular function, inflammatory response, organ morphology, lipid metabolism and cellular movement as key biological processes in normal equine BALF. Comparative modelling of protein functions in normal cell-free bronchoalveolar lavage proteomes from horse, human, and mouse, performed by grouping GO terms sharing common ancestor terms, confirms conservation of functions across species. Ninety-one of 92 human GO categories and 105 of 109 mouse GO categories were conserved in the horse. Our approach confirms the utility of the equine genome sequence to characterize protein networks without antibodies or mRNA quantification, highlights the need for continued structural and functional annotation of the equine genome and provides a framework for equine researchers to aid in the annotation effort.

Listeria monocytogenes is a gram-positive, food-borne pathogen that causes disease in both humans and animals. There are three major genetic lineages of L. monocytogenes and 13 serovars. To further our understanding of the differences that exist between different genetic lineages/serovars of L. monocytogenes , we analyzed the global protein expression of the serotype 1/2a strain EGD and the serotype 4b strain F2365 during early-stationary-phase growth at 37°C. Using multidimensional protein identification technology with electrospray ionization tandem mass spectrometry, we identified 1,754 proteins from EGD and 1,427 proteins from F2365, of which 1,077 were common to both. Analysis of proteins that had significantly altered expression between strains revealed potential biological differences between these two L. monocytogenes strains. In particular, the strains differed in expression of proteins involved in cell wall physiology and flagellar biosynthesis, as well as DNA repair proteins and stress response proteins.

The complete annotation of the cattle genome allows reliable protein identification by tandem mass spectrometry (MS 2 ) and greatly facilitates proteomics. Previously, we reported that differential detergent fractionation (DDF) analysis of bovine monocytes reveals proteins related to antigen pattern recognition, uptake and presentation to immunocompetent lymphocytes. Here we have identified 47 bovine proteins, involved in immune function of professional antigen-presenting cells (APC) that have been significantly altered after cytopathic (cp) Bovine Viral Diarrhea Virus (BVDV) infection. In particular, proteins related to immune responses such as cell adhesion, apoptosis, antigen uptake, processing and presentation, acute phase response proteins, MHC class I- and II-related proteins and other molecules involved in immune function of professional antigen presentation have been significantly altered after BVDV infection. Our data suggest that cp BVDV, while promoting monocyte activation and differentiation, is inhibiting their antigen presentation to immunocompetent T cells, thus resulting in the uncontrolled inflammation mediated by activated macrophages, enhanced viral spread, and impaired anti-viral defense mechanisms in the host.

Using a proteomics approach, we evaluated the effect of cytopathic (cp), and non-cytopathic (ncp) bovine viral diarrhea viruses (BVDV) on the expression of protein kinases and related proteins in bovine monocytes. Proteins were isolated from membrane and cytosolic fractions with the differential detergent fractionation (DDF) method and identified with 2D-LC ESI MS2. Of approximately 10,000 proteins identified, 378 proteins had homology with known protein kinases or related proteins. Eighteen proteins involved in cell differentiation and activation, migration, anti-viral mechanisms (interferon/apoptosis), biosynthesis, sugar metabolism and oncogenic transformation were significantly altered in BVDV-infected monocytes compared to the uninfected controls. Six proteins, mostly related to cell migration, anti-viral mechanisms, sugar metabolism and possibly tumor resistance were differentially expressed between the ncp and cp BVDV-infected monocytes. Particularly, the expression of the receptor of activated C kinase (RACK), of pyridoxal kinase (PK), diacyglycerol kinase (DGK) and Brutons tyrosine kinase (BTK) was decreased in monocytes infected with cp BVDV compared to ncp BVDV, possibly contributing to the cytopathic effect of the virus. This and other findings are discussed in view of the possible role the identified proteins play in the development of viral infection and oncogenic transformation of cells.

Understanding the growth of bacterial pathogens in a micronutrient restricted host environment can identify potential virulence proteins that help overcome this nutritional barrier to productive infection. In this study, we investigated the pneumococcal protein expression response to iron limitation using an in vitro model. We identified S. pneumoniae TIGR4 proteins by 2-D LC ESI MS/MS and determined significant changes in protein expression in response to iron restriction using computer-intensive random resampling methods. Differential protein expression was studied in the context of a S. pneumoniae TIGR4 protein interaction network using Pathway Studio. Our analysis showed that pneumococcal iron restriction response was marked by increased expression of known virulence factors like PsaA. It involved changes in the expression of stress response, and phase variation and biofilm formation proteins. The net effect of changes in all these biological processes could increase the virulence of S. pneumoniae TIGR4 during in vivo infection.

Although protein ubiquitination has been shown to regulate multiple processes during host response to Salmonella enterica serovar Typhimurium infection, specific functions of host deubiquitinating enzymes remain unknown in this bacterial infection. By using chemical proteomics approach, in which deubiquitinating enzymes were labeled by an active-site probe and analyzed by quantitative proteomics, we identified novel deubiquitinases in chicken macrophages based on their reactivity with the probe. Also, we detected down-regulation of UCH-L3, and USP4 as well as up-regulation of USP5 and UCH-L5 deubiquitinating enzymes in macrophages infected with Salmonella Typhimurium. We showed that decrease in either UCH-L5 activity, or in UCH-L5 protein amount in chicken and human macrophages infected or stimulated with LPS/nigericin, led to decreased IL-1β release. These data point towards a putative role of UCH-L5 in inflammasome regulation during Salmonella infection. Because inflammasome activation is important in innate resistance to these bacteria, one would expect that naturally occurring or therapeutically induced alteration in UCH-L5 activation would influence disease outcome and could represent a target for new therapeutic approaches.

Background A systems toxicology investigation comparing and integrating transcriptomic and proteomic results was conducted to develop holistic effects characterizations for the wildlife bird model, Northern bobwhite (Colinus virginianus) dosed with the explosives degradation product 2-amino-4,6-dinitrotoluene (2A-DNT). A subchronic 60d toxicology bioassay was leveraged where both sexes were dosed via daily gavage with 0, 3, 14, or 30 mg/kg-d 2A-DNT. Effects on global transcript expression were investigated in liver and kidney tissue using custom microarrays for C. virginianus in both sexes at all doses, while effects on proteome expression were investigated in liver for both sexes and kidney in males, at 30 mg/kg-d. Results As expected, transcript expression was not directly indicative of protein expression in response to 2A-DNT. However, a high degree of correspondence was observed among gene and protein expression when investigating higher-order functional responses including statistically enriched gene networks and canonical pathways, especially when connected to toxicological outcomes of 2A-DNT exposure. Analysis of networks statistically enriched for both transcripts and proteins demonstrated common responses including inhibition of programmed cell death and arrest of cell cycle in liver tissues at 2A-DNT doses that caused liver necrosis and death in females. Additionally, both transcript and protein expression in liver tissue was indicative of induced phase I and II xenobiotic metabolism potentially as a mechanism to detoxify and excrete 2A-DNT. Nuclear signaling assays, transcript expression and protein expression each implicated peroxisome proliferator-activated receptor (PPAR) nuclear signaling as a primary molecular target in the 2A-DNT exposure with significant downstream enrichment of PPAR-regulated pathways including lipid metabolic pathways and gluconeogenesis suggesting impaired bioenergetic potential. Conclusion Although the differential expression of transcripts and proteins was largely unique, the consensus of functional pathways and gene networks enriched among transcriptomic and proteomic datasets provided the identification of many critical metabolic functions underlying 2A-DNT toxicity as well as impaired PPAR signaling, a key molecular initiating event known to be affected in di- and trinitrotoluene exposures. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1798-4) contains supplementary material, which is available to authorized users.

Lysine acetylation is a reversible, dynamic protein modification regulated by lysine acetyltransferases and deacetylases. Recent advances in high-throughput proteomics have greatly contributed to the success of global analysis of lysine acetylation. A large number of proteins of diverse biological functions have been shown to be acetylated in several reports in human cells, E.coli, and dicot plants. However, the extent of lysine acetylation in non-histone proteins remains largely unknown in monocots, particularly in the cereal crops. Here we report the mass spectrometric examination of lysine acetylation in rice (Oryza sativa). We identified 60 lysine acetylated sites on 44 proteins of diverse biological functions. Immunoblot studies further validated the presence of a large number of acetylated non-histone proteins. Examination of the amino acid composition revealed substantial amino acid bias around the acetylation sites and the amino acid preference is conserved among different organisms. Gene ontology analysis demonstrates that lysine acetylation occurs in diverse cytoplasmic, chloroplast and mitochondrial proteins in addition to the histone modifications. Our results suggest that lysine acetylation might constitute a regulatory mechanism for many proteins, including both histones and non-histone proteins of diverse biological functions.

Shauna A Trichler,1,* Sandra C Bulla,1,* Nandita Mahajan,1 Kari V Lunsford,2 Ken Pendarvis,3 Bindu Nanduri,4,5 Fiona M McCarthy,3 Camilo Bulla1 1Department of Pathobiology and Population Medicine, 2Department of Clinical Sciences and Animal Health Center, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS, 3Department of Veterinary Science and Microbiology, University of Arizona, Tucson, AZ, 4Department of Biological Sciences, College of Veterinary Medicine, Mississippi State University, Mississippi State, MS, 5Institute for Genomics, Biocomputing and Biotechnology, Starkville, MS, USA *These authors contributed equally to this work Abstract: During platelet development, proteins necessary for the many functional roles of the platelet are stored within cytoplasmic granules. Platelets have also been shown to take up and store many plasma proteins into granules. This makes the platelet a potential novel source of biomarkers for many disease states. Approaches to sample preparation for proteomic studies for biomarkers search vary. Compared with traditional two-dimensional polyacrylamide gel electrophoresis systems, nonelectrophoretic proteomics methods that employ offline protein fractionation methods such as the differential detergent fractionation method have clear advantages. Here we report a proteomic survey of the canine platelet proteome using differential detergent fractionation coupled with mass spectrometry and functional modeling of the canine platelet proteins identified. A total of 5,974 unique proteins were identified from platelets, of which only 298 (5%) had previous experimental evidence of in vivo expression. The use of offline prefractionation of canine proteins by differential detergent fractionation resulted in greater proteome coverage as compared with previous reports. This initial study contributes to a broader understanding of canine platelet biology and aids functional research, identification of potential treatment targets and biomarkers, and sets a new standard for the resting platelet proteome. Keywords: proteome, differential detergent fractionation, dog, functional analysis, protein

Listeria monocytogenes is a food-borne pathogen responsible for the disease listeriosis. The infectious process depends on survival in the high bile-salt conditions encountered throughout the gastrointestinal tract, including the gallbladder. However, it is not clear how bile-salt resistance mechanisms are induced, especially under physiologically relevant conditions. This study sought to determine how the L. monocytogenes strains EGDe (serovar 1/2a), F2365 (serovar 4a) and HCC23 (serovar 4b) respond to bile salts under anaerobic conditions. Changes in the expressed proteome were analysed using multidimensional protein identification technology coupled with electrospray ionization tandem mass spectrometry. In general, the response to bile salts among the strains tested involved significant alterations in the presence of cell-wall-associated proteins, DNA repair proteins, protein folding chaperones and oxidative stress-response proteins. Strain viability correlated with an initial osmotic stress response, yet continued survival for EGDe and F2365 involved different mechanisms. Specifically, proteins associated with biofilm formation in EGDe and transmembrane efflux pumps in F2365 were expressed, suggesting that variations exist in how virulent strains respond and adapt to high bile-salt environments. These results indicate that the bile-salt response varies among these serovars and that further research is needed to elucidate how the response to bile salts correlates with colonization potential in vivo.

Listeria monocytogenes is able to survive and proliferate within macrophages. In the current study, the ability of three L. monocytogenes strains (serovar 1/2a strain EGDe, serovar 4b strain F2365, and serovar 4a strain HCC23) to proliferate in the murine macrophage cell line J774.1 was analyzed. We found that the avirulent strain HCC23 was able to initiate an infection but could not establish prolonged infection within the macrophages. By contrast, strains EGDe and F2365 proliferated within macrophages for at least 7 h. We further analyzed these strains by comparing their protein expression profiles at 0 h, 3 h, and 5 h post-infection using multidimensional protein identification technology coupled with electrospray ionization tandem mass spectrometry. Our results indicated that similar metabolic and cell wall associated proteins were expressed by all three strains at 3 h post-infection. However, increased expression of stress response and DNA repair proteins was associated with the ability to proliferate in macrophages at 5 h post-infection. By comparing the protein expression patterns of these three L. monocytogenes strains during intracellular growth in macrophages, we were able to detect biological differences that may determine the ability of L. monocytogenes to survive in macrophages.

Oligotropha carboxidovorans OM5 T. (DSM 1227, ATCC 49405) is a chemolithoautotrophic bacterium able to utilize CO and H(2) to derive energy for fixation of CO(2). Thus, it is capable of growth using syngas, which is a mixture of varying amounts of CO and H(2) generated by organic waste gasification. O. carboxidovorans is capable also of heterotrophic growth in standard bacteriologic media. Here we characterize how the O. carboxidovorans proteome adapts to different lifestyles of chemolithoautotrophy and heterotrophy. Fatty acid methyl ester (FAME) analysis of O. carboxidovorans grown with acetate or with syngas showed that the bacterium changes membrane fatty acid composition. Quantitative shotgun proteomic analysis of O. carboxidovorans grown in the presence of acetate and syngas showed production of proteins encoded on the megaplasmid for assimilating CO and H(2) as well as proteins encoded on the chromosome that might have contributed to fatty acid and acetate metabolism. We found that adaptation to chemolithoautotrophic growth involved adaptations in cell envelope, oxidative homeostasis, and metabolic pathways such as glyoxylate shunt and amino acid/cofactor biosynthetic enzymes.

The utility of a genome sequence in biological research depends entirely on the comprehensive description of all of its functional elements. Analysis of genome sequences is still predominantly gene-centric (i.e., identifying gene models/open reading frames). In this article, we describe a proteomics-based method for identifying open reading frames that are missed by computational algorithms. Mass spectrometry-based identification of peptides and proteins from biological samples provide evidence for the expression of the genome sequence at the protein level. This proteogenomic annotation method combines computationally predicted ORFs and the genome sequence with proteomics to identify novel gene models. We also describe our proteogenomic mapping pipeline - a set of computational tools that automate the proteogenomic annotation work flow. This pipeline is available for download at www.agbase.msstate.edu/tools/ .

The utility of a genome sequence in biological research depends entirely on the comprehensive description of all of its functional elements. Analysis of genome sequences is still predominantly gene-centric (i.e., identifying gene models/open reading frames). In this article, we describe a proteomics-based method for identifying open reading frames that are missed by computational algorithms. Mass spectrometry-based identification of peptides and proteins from biological samples provide evidence for the expression of the genome sequence at the protein level. This proteogenomic annotation method combines computationally predicted ORFs and the genome sequence with proteomics to identify novel gene models. We also describe our proteogenomic mapping pipeline - a set of computational tools that automate the proteogenomic annotation work flow. This pipeline is available for download at www.agbase.msstate.edu/tools/ .

Experimental identification of expressed proteins by proteomics constitutes the most reliable approach to identify genomic location and structure of protein-coding genes and substantially complements computational genome annotation. Channel catfish herpesvirus (CCV) is a simple comparative model for understanding herpesvirus biology and the evolution of the Herpesviridae. The canonical CCV genome has 76 predicted ORF and only 12 of these have been confirmed experimentally. We describe a modification of a statistical method, which assigns significance measures, q-values, to peptide identifications based on 2-D LC ESI MS/MS, real-decoy database searches and SEQUEST XCorr and DeltaC(n) scores. We used this approach to identify CCV proteins expressed during its replication in cell culture, to determine protein composition of mature virions and, consequently, to refine the canonical CCV genome annotation. To complement trypsin, we used partial proteinase K digestion, which yielded greater proteome coverage. At FDR

Background When proteins are subjected to proteolytic digestion and analyzed by mass spectrometry using a method such as 2D LC MS/MS, only a portion of the proteotypic peptides associated with each protein will be observed. The ability to predict which peptides can and cannot potentially be observed for a particular experimental dataset has several important applications in proteomics research including calculation of peptide coverage in terms of potentially detectable peptides, systems biology analysis of data sets, and protein quantification. Results We have developed a methodology for constructing artificial neural networks that can be used to predict which peptides are potentially observable for a given set of experimental, instrumental, and analytical conditions for 2D LC MS/MS (a.k.a Multidimensional Protein Identification Technology [MudPIT]) datasets. Neural network classifiers constructed using this procedure for two MudPIT datasets exhibit 10-fold cross validation accuracy of about 80%. We show that a classifier constructed for one dataset has poor predictive performance with the other dataset, thus demonstrating the need for dataset specific classifiers. Classification results with each dataset are used to compute informative percent amino acid coverage statistics for each protein in terms of the predicted detectable peptides in addition to the percent coverage of the complete sequence. We also demonstrate the utility of predicted peptide observability for systems analysis to help determine if proteins that were expected but not observed generate sufficient peptides for detection. Conclusion Classifiers that accurately predict the likelihood of detecting proteotypic peptides by mass spectrometry provide proteomics researchers with powerful new approaches for data analysis. We demonstrate that the procedure we have developed for building a classifier based on an individual experimental data set results in classifiers with accuracy comparable to those reported in the literature based on large training sets collected from multiple experiments. Our approach allows the researcher to construct a classifier that is specific for the experimental, instrument, and analytical conditions of a single experiment and amenable to local, condition-specific, implementation. The resulting classifiers have application in a number of areas such as determination of peptide coverage for protein identification, pathway analysis, and protein quantification.

Background Effective and economical methods for quantitative analysis of high throughput mass spectrometry data are essential to meet the goals of directly identifying, characterizing, and quantifying proteins from a particular cell state. Multidimensional Protein Identification Technology (MudPIT) is a common approach used in protein identification. Two types of methods are used to detect differential protein expression in MudPIT experiments: those involving stable isotope labelling and the so-called label-free methods. Label-free methods are based on the relationship between protein abundance and sampling statistics such as peptide count, spectral count, probabilistic peptide identification scores, and sum of peptide Sequest XCorr scores (ΣXCorr). Although a number of label-free methods for protein quantification have been described in the literature, there are few publicly available tools that implement these methods. We describe ProtQuant, a Java-based tool for label-free protein quantification that uses the previously published ΣXCorr method for quantification and includes an improved method for handling missing data. Results ProtQuant was designed for ease of use and portability for the bench scientist. It implements the ΣXCorr method for label free protein quantification from MudPIT datasets. ProtQuant has a graphical user interface, accepts multiple file formats, is not limited by the size of the input files, and can process any number of replicates and any number of treatments. In addition,ProtQuant implements a new method for dealing with missing values for peptide scores used for quantification. The new algorithm, called ΣXCorr*, uses "below threshold" peptide scores to provide meaningful non-zero values for missing data points. We demonstrate that ΣXCorr* produces an average reduction in false positive identifications of differential expression of 25% compared to ΣXCorr. Conclusion ProtQuant is a tool for protein quantification built for multi-platform use with an intuitive user interface. ProtQuant efficiently and uniquely performs label-free quantification of protein datasets produced with Sequest and provides the user with facilities for data management and analysis. Importantly, ProtQuant is available as a self-installing executable for the Windows environment used by many bench scientists.

Germinal vesicle (GV) breakdown is fundamental for maturation of fully grown, developmentally competent, mammalian oocytes. Bidirectional communication between oocytes and surrounding cumulus cells (CC) is essential for maturation of a competent oocyte. However, neither the factors involved in this communication nor the mechanisms of their actions are well defined. Here, we define the proteomes of GV oocytes and their surrounding CC, including membrane proteins, using proteomics in a bovine model. We found that 4395 proteins were expressed in the CC and 1092 proteins were expressed in oocytes. Further, 858 proteins were common to both the CC and the oocytes. This first comprehensive proteome analysis of bovine oocytes and CC not only provides a foundation for signaling and cell physiology at the GV stage of oocyte development, but are also valuable for comparative studies of other stages of oocyte development at the molecular level. Furthermore, some of these proteins may represent molecular biomarkers for developmental potential of oocytes.

Here we identify, using nonelectrophoretic proteomics, effects of subminimum inhibitory concentrations (subMIC) of two antibiotic preparations, chlortetracycline (CTC), and chlortetracycline-sulfamethazine (CTC + SMZ), on protein expression in the bovine respiratory pathogen Mannheimia haemolytica. The M. haemolytica genome is currently in draft form, and annotation is incomplete. Relying on the principle of gene sequence conservation across species, we used annotated genomes from closely related species to identify, confirm, and functionally annotate 495 M. haemolytica proteins. To conduct quantitative comparative proteomics, we developed a protein quantitation method based on the cross correlation function of the SEQUEST algorithm. When M. haemolytica was cultivated in the presence of 1/4 MIC of CTC and CTC + SMZ, expression of proteins involved in energy production, nucleotide metabolism, translation, and the bacterial stress response (chaperones) were affected. The most notable subMIC effect was a significant decrease in the expression of leukotoxin A, which is an important M. haemolytica virulence factor. Reduction in leukotoxin expression could be one of the molecular mechanisms responsible for the efficacy of these antibiotics against bovine respiratory disease.

Copper (II) oxide (CuO) nanoparticles (NP) are widely used in industry and medicine. In our study we evaluated the response of BEAS-2B human lung cells to CuO NP, using Stable isotope labeling by amino acids in cell culture (SILAC)-based proteomics and phosphoproteomics. Pathway modeling of the protein differential expression showed that CuO NP affect proteins relevant in cellular function and maintenance, protein synthesis, cell death and survival, cell cycle and cell morphology. Some of the signaling pathways represented by BEAS-2B proteins responsive to the NP included mTOR signaling, protein ubiquitination pathway, actin cytoskeleton signaling and epithelial adherens junction signaling. Follow-up experiments showed that CuO NP altered actin cytoskeleton, protein phosphorylation and protein ubiquitination level.

Background High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the high speed of experimental data generation and to aid in structural genome annotation, experimentally observed peptides need to be mapped back to their source genome location quickly and exactly. Previously, the tools to do this have been limited to custom scripts designed by individual research groups to analyze their own data, are generally not widely available, and do not scale well with large eukaryotic genomes. Results The Proteogenomic Mapping Tool includes a Java implementation of the Aho-Corasick string searching algorithm which takes as input standardized file types and rapidly searches experimentally observed peptides against a given genome translated in all 6 reading frames for exact matches. The Java implementation allows the application to scale well with larger eukaryotic genomes while providing cross-platform functionality. Conclusions The Proteogenomic Mapping Tool provides a standalone application for mapping peptides back to their source genome on a number of operating system platforms with standard desktop computer hardware and executes very rapidly for a variety of datasets. Allowing the selection of different genetic codes for different organisms allows researchers to easily customize the tool to their own research interests and is recommended for anyone working to structurally annotate genomes using MS derived proteomics data.

Background Mass spectrometry-based protein identification methods are fundamental to proteomics. Biological experiments are usually performed in replicates and proteomic analyses generate huge datasets which need to be integrated and quantitatively analyzed. The Sequest™ search algorithm is a commonly used algorithm for identifying peptides and proteins from two dimensional liquid chromatography electrospray ionization tandem mass spectrometry (2-D LC ESI MS2) data. A number of proteomic pipelines that facilitate high throughput 'post data acquisition analysis' are described in the literature. However, these pipelines need to be updated to accommodate the rapidly evolving data analysis methods. Here, we describe a proteomic data analysis pipeline that specifically addresses two main issues pertinent to protein identification and differential expression analysis: 1) estimation of the probability of peptide and protein identifications and 2) non-parametric statistics for protein differential expression analysis. Our proteomic analysis workflow analyzes replicate datasets from a single experimental paradigm to generate a list of identified proteins with their probabilities and significant changes in protein expression using parametric and non-parametric statistics. Results The input for our workflow is Bioworks™ 3.2 Sequest (or a later version, including cluster) output in XML format. We use a decoy database approach to assign probability to peptide identifications. The user has the option to select "quality thresholds" on peptide identifications based on the P value. We also estimate probability for protein identification. Proteins identified with peptides at a user-specified threshold value from biological experiments are grouped as either control or treatment for further analysis in ProtQuant. ProtQuant utilizes a parametric (ANOVA) method, for calculating differences in protein expression based on the quantitative measure ΣXcorr. Alternatively ProtQuant output can be further processed using non-parametric Monte-Carlo resampling statistics to calculate P values for differential expression. Correction for multiple testing of ANOVA and resampling P values is done using Benjamini and Hochberg's method. The results of these statistical analyses are then combined into a single output file containing a comprehensive protein list with probabilities and differential expression analysis, associated P values, and resampling statistics. Conclusion For biologists carrying out proteomics by mass spectrometry, our workflow facilitates automated, easy to use analyses of Bioworks (3.2 or later versions) data. All the methods used in the workflow are peer-reviewed and as such the results of our workflow are compliant with proteomic data submission guidelines to public proteomic data repositories including PRIDE. Our workflow is a necessary intermediate step that is required to link proteomics data to biological knowledge for generating testable hypotheses.

Background The identification of non-coding transcripts in human, mouse, and Escherichia coli has revealed their widespread occurrence and functional importance in both eukaryotic and prokaryotic life. In prokaryotes, studies have shown that non-coding transcripts participate in a broad range of cellular functions like gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Streptococcus pneumoniae (pneumococcus), an obligate human respiratory pathogen responsible for significant worldwide morbidity and mortality. Tiling microarrays enable genome wide mRNA profiling as well as identification of novel transcripts at a high-resolution. Results Here, we describe a high-resolution transcription map of the S. pneumoniae clinical isolate TIGR4 using genomic tiling arrays. Our results indicate that approximately 66% of the genome is expressed under our experimental conditions. We identified a total of 50 non-coding small RNAs (sRNAs) from the intergenic regions, of which 36 had no predicted function. Half of the identified sRNA sequences were found to be unique to S. pneumoniae genome. We identified eight overrepresented sequence motifs among sRNA sequences that correspond to sRNAs in different functional categories. Tiling arrays also identified approximately 202 operon structures in the genome. Conclusions In summary, the pneumococcal operon structures and novel sRNAs identified in this study enhance our understanding of the complexity and extent of the pneumococcal 'expressed' genome. Furthermore, the results of this study open up new avenues of research for understanding the complex RNA regulatory network governing S. pneumoniae physiology and virulence.