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Profiling the nucleic acid-binding proteins (NABPs) during aging process is critical to elucidate its roles in biological systems as well as transcriptional and translational regulation. Here, we developed a comprehensive strategy to survey the NABPs of mouse immune organs by using single cell preparation and selective capture technology-based proteomics. Our approach provided a global view of tissue NABPs from different organs under normal physiological conditions with extraction specificity of 70 to 90%. Through quantitative proteomics analysis of mouse spleen and thymus at 1, 4, 12, 24, 48, and 72 weeks, we investigated the molecular features of aging-related NABPs. A total of 2674 proteins were quantified in all six stages, demonstrating distinct and time-specific expression pattern of NABPs. Thymus and spleen exhibited unique aging signatures, and differential proteins and pathways were enriched across the mouse lifespan. Three core modules and 16 hub proteins associated with aging were revealed through weighted gene correlation network analysis. Significant candidates were screened for immunoassay verification, and six hub proteins were confirmed. The integrated strategy pertains the capability to decipher the dynamic functions of NABPs in aging physiology and benefit further mechanism research., Competing Interests: Conflict of interest The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The human proteome comprises of all of the proteins produced by the sequences translated from the human genome with additional modifications in both sequence and function caused by nonsynonymous variants and posttranslational modifications including cleavage of the initial transcript into smaller peptides and polypeptides. The UniProtKB database (www.uniprot.org) is the world's leading high-quality, comprehensive and freely accessible resource of protein sequence and functional information and presents a summary of experimentally verified, or computationally predicted, functional information added by our expert biocuration team for each protein in the proteome. Researchers in the field of mass spectrometry-based proteomics both consume and add to the body of data available in UniProtKB, and this review highlights the information we provide to this community and the knowledge we in turn obtain from groups via deposition of large-scale datasets in public domain databases., Competing Interests: Conflict of interest The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Mycobacterium avium is one of the prominent disease-causing bacteria in humans. It causes lymphadenitis, chronic and extrapulmonary, and disseminated infections in adults, children, and immunocompromised patients. M. avium has ∼4500 predicted protein-coding regions on average, which can help discover several variants at the proteome level. Many of them are potentially associated with virulence; thus, identifying such proteins can be a helpful feature in developing panel-based theranostics. In line with such a long-term goal, we carried out an in-depth proteomic analysis of M. avium with both data-dependent and data-independent acquisition methods. Further, a set of proteogenomic investigations were carried out using (i) a protein database for Mycobacterium tuberculosis, (ii) an M. avium genome six-frame-translated database, and (iii) a variant protein database of M. avium. A search of mass spectrometry data against M. avium protein database resulted in identifying 2954 proteins. Further, proteogenomic analyses aided in identifying 1301 novel peptide sequences and correcting translation start sites for 15 proteins. Ultimately, we created a spectral library of M. avium proteins, including novel genome search-specific peptides and variant peptides detected in this study. We validated the spectral library by a data-independent acquisition of the M. avium proteome. Thus, we present an M. avium spectral library of 29,033 peptide precursors supported by 0.4 million fragment ions for further use by the biomedical community., Competing Interests: Conflict of interest The authors declare no competing interests., (Copyright © 2023. Published by Elsevier Inc.)

Coronavirus disease 2019 (COVID-19) is a highly contagious infection and threating the human lives in the world. The elevation of cytokines in blood is crucial to induce cytokine storm and immunosuppression in the transition of severity in COVID-19 patients. However, the comprehensive changes of serum proteins in COVID-19 patients throughout the SARS-CoV-2 infection is unknown. In this work, we developed a high-density antibody microarray and performed an in-depth proteomics analysis of serum samples collected from early COVID-19 ( n = 15) and influenza ( n = 13) patients. We identified a large set of differentially expressed proteins ( n = 132) that participate in a landscape of inflammation and immune signaling related to the SARS-CoV-2 infection. Furthermore, the significant correlations of neutrophil and lymphocyte with the CCL2 and CXCL10 mediated cytokine signaling pathways was identified. These information are valuable for the understanding of COVID-19 pathogenesis, identification of biomarkers and development of the optimal anti-inflammation therapy., Competing Interests: Conflict of interest—The authors declare that they have no conflicts of interest with the contents of this article., (© 2020 Hou et al.)

Recent efforts in gut microbiome studies have highlighted the importance of explicitly describing the ecological processes beyond correlative analysis. However, we are still at the early stage of understanding the organizational principles of the gut ecosystem, partially because of the limited information provided by currently used analytical tools in ecological modeling practices. Proteomics and metaproteomics can provide a number of insights for ecological studies, including biomass, matter and energy flow, and functional diversity. In this Mini Review, we discuss proteomics and metaproteomics-based experimental strategies that can contribute to studying the ecology, in particular at the mucosal-luminal interface (MLI) where the direct host-microbiome interaction happens. These strategies include isolation protocols for different MLI components, enrichment methods to obtain designated array of proteins, probing for specific pathways, and isotopic labeling for tracking nutrient flow. Integration of these technologies can generate spatiotemporal and site-specific biological information that supports mathematical modeling of the ecosystem at the MLI., Competing Interests: Conflict of interest—Authors declare no competing interests., (© 2020 Li and Figeys.)

Communication between individuals via molecules, termed chemosignaling, is widespread among animal and plant species. However, we lack knowledge on the specific functions of the substances involved for most systems. The femoral gland is an organ that secretes a waxy substance involved in chemical communication in lizards. Although the lipids and volatile substances secreted by the femoral glands have been investigated in several biochemical studies, the protein composition and functions of secretions remain completely unknown. Applying a proteomic approach, we provide the first attempt to comprehensively characterize the protein composition of femoral gland secretions from the Galápagos marine iguana. Using samples from several organs, the marine iguana proteome was assembled by next-generation sequencing and MS, resulting in 7513 proteins. Of these, 4305 proteins were present in the femoral gland, including keratins, small serum proteins, and fatty acid-binding proteins. Surprisingly, no proteins with discernible roles in partner recognition or inter-species communication could be identified. However, we did find several proteins with direct associations to the innate immune system, including lysozyme C, antileukoproteinase (ALP), pulmonary surfactant protein (SFTPD), and galectin (LGALS1) suggesting that the femoral glands function as an important barrier to infection. Furthermore, we report several novel anti-microbial peptides from the femoral glands that show similar action against Escherichia coli and Bacillus subtilis such as oncocin, a peptide known for its effectiveness against Gram-negative pathogens. This proteomics data set is a valuable resource for future functional protein analysis and demonstrates that femoral gland secretions also perform functions of the innate immune system., Competing Interests: Conflict of interest—Authors declare no competing interests., (© 2020 Tellkamp et al.)

Pathogenic mutations in the Leucine-rich repeat kinase 2 (LRRK2) are the predominant genetic cause of Parkinson's disease (PD). They increase its activity, resulting in augmented Rab10-Thr73 phosphorylation and conversely, LRRK2 inhibition decreases pRab10 levels. Currently, there is no assay to quantify pRab10 levels for drug target engagement or patient stratification. To meet this challenge, we developed an high accuracy and sensitivity targeted mass spectrometry (MS)-based assay for determining Rab10-Thr73 phosphorylation stoichiometry in human samples. It uses synthetic stable isotope-labeled (SIL) analogues for both phosphorylated and nonphosphorylated tryptic peptides surrounding Rab10-Thr73 to directly derive the percentage of Rab10 phosphorylation from attomole amounts of the endogenous phosphopeptide. The SIL and the endogenous phosphopeptides are separately admitted into an Orbitrap analyzer with the appropriate injection times. We test the reproducibility of our assay by determining Rab10-Thr73 phosphorylation stoichiometry in neutrophils of LRRK2 mutation carriers before and after LRRK2 inhibition. Compared with healthy controls, the PD predisposing mutation carriers LRRK2 G2019S and VPS35 D620N display 1.9-fold and 3.7-fold increased pRab10 levels, respectively. Our generic MS-based assay further establishes the relevance of pRab10 as a prognostic PD marker and is a powerful tool for determining LRRK2 inhibitor efficacy and for stratifying PD patients for LRRK2 inhibitor treatment., Competing Interests: Conflict of interest—The authors declare that they have no conflicts of interest with the contents of this article., (© 2020 Karayel et al.)

Drug resistance is a major obstacle to curative cancer therapies, and increased understanding of the molecular events contributing to resistance would enable better prediction of therapy response, as well as contribute to new targets for combination therapy. Here we have analyzed the early molecular response to epidermal growth factor receptor (EGFR) inhibition using RNA sequencing data covering 13,486 genes and mass spectrometry data covering 10,138 proteins. This analysis revealed a massive response to EGFR inhibition already within the first 24 h, including significant regulation of hundreds of genes known to control downstream signaling, such as transcription factors, kinases, phosphatases and ubiquitin E3-ligases. Importantly, this response included upregulation of key genes in multiple oncogenic signaling pathways that promote proliferation and survival, such as ERBB3, FGFR2, JAK3, and BCL6, indicating an early adaptive response to EGFR inhibition. Using a library of more than 500 approved and experimental compounds in a combination therapy screen, we could show that several kinase inhibitors with targets including JAK3 and FGFR2 increased the response to EGFR inhibitors. Further, we investigated the functional impact of BCL6 upregulation in response to EGFR inhibition using siRNA-based silencing of BCL6. Proteomics profiling revealed that BCL6 inhibited transcription of multiple target genes including p53, resulting in reduced apoptosis which implicates BCL6 upregulation as a new EGFR inhibitor treatment escape mechanism. Finally, we demonstrate that combined treatment targeting both EGFR and BCL6 act synergistically in killing lung cancer cells. In conclusion, or data indicates that multiple different adaptive mechanisms may act in concert to blunt the cellular impact of EGFR inhibition, and we suggest BCL6 as a potential target for EGFR inhibitor-based combination therapy., Competing Interests: * The authors declare that they have no conflicts of interest with the contents of this article., (© 2020 Zhou Tran et al.)

Molecular mechanisms underlying sperm motility have not been fully explained, particularly in chickens. The objective was to identify seminal plasma proteins associated with chicken sperm motility by comparing the seminal plasma proteomic profile of roosters with low sperm motility (LSM, n = 4) and high sperm motility (HSM, n = 4). Using a label-free MS-based method, a total of 522 seminal plasma proteins were identified, including 386 (∼74%) previously reported and 136 novel ones. A total of 70 differentially abundant proteins were defined, including 48 more-abundant, 15 less-abundant, and seven proteins unique to the LSM group (specific proteins). Key secretory proteins like less-abundant adhesion G-protein coupled receptor G2 (ADGRG2) and more-abundant serine peptidase inhibitor Kazal-type 2 (SPINK2) in the LSM suggested that the corresponding secretory tissues played a crucial role in maintaining sperm motility. Majority (80%) of the more-abundant and five specific proteins were annotated to the cytoplasmic domain which might be a result of higher plasma membrane damage and acrosome dysfunction in LSM. Additionally, more-abundant mitochondrial proteins were detected in LSM seminal plasma associated with lower spermatozoa mitochondrial membrane potential (ΔΨm) and ATP concentrations. Further studies showed that the spermatozoa might be suffering from oxidative stress, as the amount of spermatozoa reactive oxygen species (ROS) were largely enhanced, seminal malondialdehyde (MDA) concentrations were increased, and the seminal plasma total antioxidant capacity (T-AOC) were decreased. Our study provides an additional catalogue of chicken seminal plasma proteome and supports the idea that seminal plasma could be as an indicator of spermatozoa physiology. More-abundant of acrosome, mitochondria and sperm cytoskeleton proteins in the seminal plasma could be a marker of sperm dysfunction and loss of motility. The degeneration of spermatozoa caused by the reduced seminal T-AOC and enhanced oxidative stress might be potential determinants of low sperm motility. These results could extend our understanding of sperm motility and sperm physiology regulation., Competing Interests: Conflict of interest—Authors declare no competing interests., (© 2020 Li et al.)

The onset of obesity-linked type 2 diabetes (T2D) is marked by an eventual failure in pancreatic β-cell function and mass that is no longer able to compensate for the inherent insulin resistance and increased metabolic load intrinsic to obesity. However, in a commonly used model of T2D, the db/db mouse, β-cells have an inbuilt adaptive flexibility enabling them to effectively adjust insulin production rates relative to the metabolic demand. Pancreatic β-cells from these animals have markedly reduced intracellular insulin stores, yet high rates of (pro)insulin secretion, together with a substantial increase in proinsulin biosynthesis highlighted by expanded rough endoplasmic reticulum and Golgi apparatus. However, when the metabolic overload and/or hyperglycemia is normalized, β-cells from db/db mice quickly restore their insulin stores and normalize secretory function. This demonstrates the β-cell's adaptive flexibility and indicates that therapeutic approaches applied to encourage β-cell rest are capable of restoring endogenous β-cell function. However, mechanisms that regulate β-cell adaptive flexibility are essentially unknown. To gain deeper mechanistic insight into the molecular events underlying β-cell adaptive flexibility in db/db β-cells, we conducted a combined proteomic and post-translational modification specific proteomic (PTMomics) approach on islets from db/db mice and wild-type controls (WT) with or without prior exposure to normal glucose levels. We identified differential modifications of proteins involved in redox homeostasis, protein refolding, K48-linked deubiquitination, mRNA/protein export, focal adhesion, ERK1/2 signaling, and renin-angiotensin-aldosterone signaling, as well as sialyltransferase activity, associated with β-cell adaptive flexibility. These proteins are all related to proinsulin biosynthesis and processing, maturation of insulin secretory granules, and vesicular trafficking-core pathways involved in the adaptation of insulin production to meet metabolic demand. Collectively, this study outlines a novel and comprehensive global PTMome signaling map that highlights important molecular mechanisms related to the adaptive flexibility of β-cell function, providing improved insight into disease pathogenesis of T2D., (© 2020 Kang et al.)

Anal squamous cell carcinoma is a rare tumor. Chemo-radiotherapy yields a 50% 3-year relapse-free survival rate in advanced anal cancer, so improved predictive markers and therapeutic options are needed. High-throughput proteomics and whole-exome sequencing were performed in 46 paraffin samples from anal squamous cell carcinoma patients. Hierarchical clustering was used to establish groups de novo Then, probabilistic graphical models were used to study the differences between groups of patients at the biological process level. A molecular classification into two groups of patients was established, one group with increased expression of proteins related to adhesion, T lymphocytes and glycolysis; and the other group with increased expression of proteins related to translation and ribosomes. The functional analysis by the probabilistic graphical model showed that these two groups presented differences in metabolism, mitochondria, translation, splicing and adhesion processes. Additionally, these groups showed different frequencies of genetic variants in some genes, such as ATM, SLFN11 and DST Finally, genetic and proteomic characteristics of these groups suggested the use of some possible targeted therapies, such as PARP inhibitors or immunotherapy., (© 2020 Trilla-Fuertes et al.)

Hmt1p is the predominant arginine methyltransferase in Saccharomyces cerevisiae Its substrate proteins are involved in transcription, transcriptional regulation, nucleocytoplasmic transport and RNA splicing. Hmt1p-catalyzed methylation can also modulate protein-protein interactions. Hmt1p is conserved from unicellular eukaryotes through to mammals where its ortholog, PRMT1, is lethal upon knockout. In yeast, however, the effect of knockout on the transcriptome and proteome has not been described. Transcriptome analysis revealed downregulation of phosphate-responsive genes in hmt1 Δ, including acid phosphatases PHO5 , PHO11 , and PHO12 , phosphate transporters PHO84 and PHO89 and the vacuolar transporter chaperone VTC3 Analysis of the hmt1 Δ proteome revealed decreased abundance of phosphate-associated proteins including phosphate transporter Pho84p, vacuolar alkaline phosphatase Pho8p, acid phosphatase Pho3p and subunits of the vacuolar transporter chaperone complex Vtc1p, Vtc3p and Vtc4p. Consistent with this, phosphate homeostasis was dysregulated in hmt1 Δ cells, showing decreased extracellular phosphatase levels and decreased total P i in phosphate-depleted medium. In vitro , we showed that transcription factor Pho4p can be methylated at Arg-241, which could explain phosphate dysregulation in hmt1 Δ if interplay exists with phosphorylation at Ser-242 or Ser-243, or if Arg-241 methylation affects the capacity of Pho4p to homodimerize or interact with Pho2p. However, the Arg-241 methylation site was not validated in vivo and the localization of a Pho4p-GFP fusion in hmt1 Δ was not different from wild type. To our knowledge, this is the first study to reveal an association between Hmt1p and phosphate homeostasis and one which suggests a regulatory link between S-adenosyl methionine and intracellular phosphate., (© 2018 Chia et al.)

The spread of methicillin-resistant Staphylococcus aureus (MRSA) in the community, hospitals and in livestock is mediated by highly diverse virulence factors that include secreted toxins, superantigens, enzymes and surface-associated adhesins allowing host adaptation and colonization. Here, we combined proteogenomics, secretome and phenotype analyses to compare the secreted virulence factors in selected S. aureus isolates of the dominant human- and livestock-associated genetic lineages CC8, CC22, and CC398. The proteogenomic comparison revealed 2181 core genes and 1306 accessory genes in 18 S. aureus isolates reflecting the high genome diversity. Using secretome analysis, we identified 869 secreted proteins with 538 commons in eight isolates of CC8, CC22, and CC398. These include 64 predicted extracellular and 37 cell surface proteins that account for 82.4% of total secretome abundance. Among the top 10 most abundantly secreted virulence factors are the major autolysins (Atl, IsaA, Sle1, SAUPAN006375000), lipases and lipoteichoic acid hydrolases (Lip, Geh, LtaS), cytolytic toxins (Hla, Hlb, PSMβ1) and proteases (SspB). The CC398 isolates showed lower secretion of cell wall proteins, but higher secretion of α- and β-hemolysins (Hla, Hlb) which correlated with an increased Agr activity and strong hemolysis. CC398 strains were further characterized by lower biofilm formation and staphyloxanthin levels because of decreased SigB activity. Overall, comparative secretome analyses revealed CC8- or CC22-specific enterotoxin and Spl protease secretion as well as Agr- and SigB-controlled differences in exotoxin and surface protein secretion between human-specific and zoonotic lineages of S. aureus ., (© 2018 Busche et al.)

Virtually all patients of the rare inflammatory eye disease birdshot chorioretinopathy (BSCR) carry the HLA-A*29:02 allele. BSCR is also associated with endoplasmic reticulum aminopeptidase 2 (ERAP2), an enzyme involved in processing HLA class I ligands, thus implicating the A*29:02 peptidome in this disease. To investigate the relationship between both risk factors we employed label-free quantitative mass spectrometry to characterize the effects of ERAP2 on the A*29:02-bound peptidome. An ERAP2-negative cell line was transduced with lentiviral constructs containing GFP-ERAP2 or GFP alone, and the A*29:02 peptidomes from both transduced cells were compared. A similar analysis was performed with two additional A*29:02-positive, ERAP1-concordant, cell lines expressing or not ERAP2. In both comparisons the presence of ERAP2 affected the following features of the A*29:02 peptidome: 1) Length, with increased amounts of peptides >9-mers, and 2) N-terminal residues, with less ERAP2-susceptible and more hydrophobic ones. The paradoxical effects on peptide length suggest that unproductive binding to ERAP2 might protect some peptides from ERAP1 over-trimming. The influence on N-terminal residues can be explained by a direct effect of ERAP2 on trimming, without ruling out and improved processing in concert with ERAP1. The alterations in the A*29:02 peptidome suggest that the association of ERAP2 with BSCR is through its effects on peptide processing. These differ from those on the ankylosing spondylitis-associated HLA-B*27. Thus, ERAP2 alters the peptidome of distinct HLA molecules as a function of their specific binding preferences, influencing different pathological outcomes in an allele-dependent way., (© 2018 Sanz-Bravo et al.)

Rapidly proliferating tumors are exposed to a hypoxic microenvironment because of their density, high metabolic consumption, and interruptions in blood flow because of immature angiogenesis. Cellular responses to hypoxia promote highly malignant and metastatic behavior, as well as a chemotherapy-resistant state. To better understand the complex relationships between hypoxic adaptations and cancer progression, we studied the dynamic proteome responses of glioblastoma cells exposed to hypoxia via an innovative approach: quantification of newly synthesized proteins using heavy stable-isotope arginine labeling combined with accurate assessment of cell replication by quantification of the light/heavy arginine ratio of peptides in histone H4. We found that hypoxia affects cancer cells in multiple intertwined ways: inflammation, typically with over-expressed glucose transporter (GLUT1), DUSP4/MKP2, and RelA proteins; a metabolic adaptation with overexpression of all glycolytic pathway enzymes for pyruvate/lactate synthesis; and the EMT (epithelial-mesenchymal transition) and cancer stem cell (CSC) renewal with characteristic morphological changes and mesenchymal/CSC protein expression profiles. For the first time, we identified the vitamin B 12 transporter protein TCN2, which is essential for one-carbon metabolism, as being significantly downregulated. Further, we found, by knockdown and overexpression experiments, that TCN2 plays an important role in controlling cancer cell transformation toward the highly aggressive mesenchymal/CSC stage; low expression of TCN2 has an effect similar to hypoxia, whereas high expression of TCN2 can reverse it. We conclude that hypoxia induces sequential metabolic responses of one-carbon metabolism in tumor cells. Our mass spectrometry data are available via ProteomeXchange with identifiers PXD005487 (TMT-labeling) and PXD007280 (label-free)., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)

Proteogenomics, i.e. comprehensive integration of genomics and proteomics data, is a powerful approach identifying novel protein biomarkers. This is especially the case for proteins that differ structurally between disease and control conditions. As tumor development is associated with aberrant splicing, we focus on this rich source of cancer specific biomarkers. To this end, we developed a proteogenomic pipeline, Splicify, which can detect differentially expressed protein isoforms. Splicify is based on integrating RNA massive parallel sequencing data and tandem mass spectrometry proteomics data to identify protein isoforms resulting from differential splicing between two conditions. Proof of concept was obtained by applying Splicify to RNA sequencing and mass spectrometry data obtained from colorectal cancer cell line SW480, before and after siRNA-mediated downmodulation of the splicing factors SF3B1 and SRSF1. These analyses revealed 2172 and 149 differentially expressed isoforms, respectively, with peptide confirmation upon knock-down of SF3B1 and SRSF1 compared with their controls. Splice variants identified included RAC1, OSBPL3, MKI67, and SYK. One additional sample was analyzed by PacBio Iso-Seq full-length transcript sequencing after SF3B1 downmodulation. This analysis verified the alternative splicing identified by Splicify and in addition identified novel splicing events that were not represented in the human reference genome annotation. Therefore, Splicify offers a validated proteogenomic data analysis pipeline for identification of disease specific protein biomarkers resulting from mRNA alternative splicing. Splicify is publicly available on GitHub (https://github.com/NKI-TGO/SPLICIFY) and suitable to address basic research questions using pre-clinical model systems as well as translational research questions using patient-derived samples, e.g. allowing to identify clinically relevant biomarkers., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)

Numerous aquatic invertebrates remain dormant for decades in a hydrated state as encysted embryos. In search for functional pathways associated with this form of dormancy, we used label-free quantitative proteomics to compare the proteomes of hydrated encysted dormant embryos (resting eggs; RE) with nondormant embryos (amictic eggs; AM) of the rotifer Brachionus plicatilis A total of 2631 proteins were identified in rotifer eggs. About 62% proteins showed higher abundance in AM relative to RE (Fold Change>3; p = 0.05). Proteins belonging to numerous putative functional pathways showed dramatic changes during dormancy. Most striking were changes in the mitochondria indicating an impeded metabolism. A comparison between the abundance of proteins and their corresponding transcript levels, revealed higher concordance for RE than for AM. Surprisingly, numerous highly abundant dormancy related proteins show corresponding high mRNA levels in metabolically inactive RE. As these mRNAs and proteins degrade at the time of exit from dormancy they may serve as a source of nucleotides and amino acids during the exit from dormancy. Because proteome analyses point to a similarity in functional pathways of hydrated RE and desiccated life forms, REs were dried. Similar hatching and reproductive rates were found for wet and dried REs, suggesting analogous pathways for long-term survival in wet or dry forms. Analysis by KEGG pathways revealed a few general strategies for dormancy, proposing an explanation for the low transcriptional similarity among dormancies across species, despite the resemblance in physiological phenotypes., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the leading cause of death among all infectious diseases. There are 11 eukaryotic-like serine/threonine protein kinases (STPKs) in Mtb, which are thought to play pivotal roles in cell growth, signal transduction and pathogenesis. However, their underlying mechanisms of action remain largely uncharacterized. In this study, using a Mtb proteome microarray, we have globally identified the binding proteins in Mtb for all of the STPKs, and constructed the first STPK protein interaction (KPI) map that includes 492 binding proteins and 1,027 interactions. Bioinformatics analysis showed that the interacting proteins reflect diverse functions, including roles in two-component system, transcription, protein degradation, and cell wall integrity. Functional investigations confirmed that PknG regulates cell wall integrity through key components of peptidoglycan (PG) biosynthesis, e.g. MurC. The global STPK-KPIs network constructed here is expected to serve as a rich resource for understanding the key signaling pathways in Mtb, thus facilitating drug development and effective control of Mtb., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)

Inactivating mutations in ARID1A, which encodes a subunit of the SWI/SNF chromatin-remodeling complex, are found in over half of ovarian clear cell carcinoma cases and more broadly across most types of cancers. To identify ARID1A-dependent changes in intracellular signaling pathways, we performed proteome analyses of isogenic ovarian clear cell carcinoma cell lines with or without ARID1A expression. Knockout of ARID1A in an ovarian clear cell carcinoma cell line with wild-type ARID1A, OVCA429, primarily resulted in downregulation of the mevalonate pathway, an important metabolic pathway involved in isoprenoid synthesis, cholesterol synthesis, and other downstream pathways. In a complementary experiment, expression of wild-type ARID1A in an ovarian clear cell carcinoma cell line containing mutated ARID1A, OVISE, affected the mevalonate pathway in a reciprocal manner. A striking aspect of these analyses was that, although only 5% of the detected proteome showed significant abundance changes, most proteins in the mevalonate pathway were coordinately affected by ARID1A status. There were generally corresponding changes when comparing the proteomics data to our previously published microarray data for ectopic expression of ARID1A in the OVISE cell line. However, ARID1A-dependent changes were not detected for genes within the mevalonate pathway. This discrepancy suggests that the mevalonate pathway is not regulated directly by ARID1A-mediated transcription and may be regulated post-transcriptionally. We conclude that ARID1A status indirectly influences the mevalonate pathway and probably influences other processes including glycogen metabolism and 14-3-3-mediated signaling. Further, our findings demonstrate that changes in mRNA levels are sometimes poor indicators of signaling pathways affected by gene manipulations in cancer cells., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable body of potential regulatory elements that impact hundreds of different biological processes important in eukaryotic biology and human health., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Cardiomyocytes undergo growth and remodeling in response to specific pathological or physiological conditions. In the former, myocardial growth is a risk factor for cardiac failure and faster protein synthesis is a major factor driving cardiomyocyte growth. Our goal was to quantify the rapid effects of different pro-hypertrophic stimuli on the synthesis of specific proteins in ARVC and to determine whether such effects are caused by alterations on mRNA abundance or the translation of specific mRNAs. Cardiomyocytes have very low rates of protein synthesis, posing a challenging problem in terms of studying changes in the synthesis of specific proteins, which also applies to other nondividing primary cells. To study the rates of accumulation of specific proteins in these cells, we developed an optimized version of the Quantitative Noncanonical Amino acid Tagging LC/MS proteomic method to label and selectively enrich newly synthesized proteins in these primary cells while eliminating the suppressive effects of pre-existing and highly abundant nonisotope-tagged polypeptides. Our data revealed that a classical pathologic (phenylephrine; PE) and the recently identified insulin stimulus that also contributes to the development of pathological cardiac hypertrophy (insulin), both increased the synthesis of proteins involved in, e.g. glycolysis, the Krebs cycle and beta-oxidation, and sarcomeric components. However, insulin increased synthesis of many metabolic enzymes to a greater extent than PE. Using a novel validation method, we confirmed that synthesis of selected candidates is indeed up-regulated by PE and insulin. Synthesis of all proteins studied was up-regulated by signaling through mammalian target of rapamycin complex 1 without changes in their mRNA levels, showing the key importance of translational control in the rapid effects of hypertrophic stimuli. Expression of PKM2 was up-regulated in rat hearts following TAC. This isoform possesses specific regulatory properties, so this finding indicates it may be involved in metabolic remodeling and also serve as a novel candidate biomarker. Levels of translation factor eEF1 also increased during TAC, likely contributing to faster cell mass accumulation. Interestingly those two candidates were not up-regulated in pregnancy or exercise induced CH, indicating PKM2 and eEF1 were pathological CH specific markers. We anticipate that the methodologies described here will be valuable for other researchers studying protein synthesis in primary cells., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Although the bioactive sphingolipid ceramide is an important cell signaling molecule, relatively few direct ceramide-interacting proteins are known. We used an approach combining yeast surface cDNA display and deep sequencing technology to identify novel proteins binding directly to ceramide. We identified 234 candidate ceramide-binding protein fragments and validated binding for 20. Most (17) bound selectively to ceramide, although a few (3) bound to other lipids as well. Several novel ceramide-binding domains were discovered, including the EF-hand calcium-binding motif, the heat shock chaperonin-binding motif STI1, the SCP2 sterol-binding domain, and the tetratricopeptide repeat region motif. Interestingly, four of the verified ceramide-binding proteins (HPCA, HPCAL1, NCS1, and VSNL1) and an additional three candidate ceramide-binding proteins (NCALD, HPCAL4, and KCNIP3) belong to the neuronal calcium sensor family of EF hand-containing proteins. We used mutagenesis to map the ceramide-binding site in HPCA and to create a mutant HPCA that does not bind to ceramide. We demonstrated selective binding to ceramide by mammalian cell-produced wild type but not mutant HPCA. Intriguingly, we also identified a fragment from prostaglandin D2synthase that binds preferentially to ceramide 1-phosphate. The wide variety of proteins and domains capable of binding to ceramide suggests that many of the signaling functions of ceramide may be regulated by direct binding to these proteins. Based on the deep sequencing data, we estimate that our yeast surface cDNA display library covers ∼60% of the human proteome and our selection/deep sequencing protocol can identify target-interacting protein fragments that are present at extremely low frequency in the starting library. Thus, the yeast surface cDNA display/deep sequencing approach is a rapid, comprehensive, and flexible method for the analysis of protein-ligand interactions, particularly for the study of non-protein ligands., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

We aimed to globally discover serum biomarkers for diagnosis of gastric cancer (GC). GC serum autoantibodies were discovered and validated using serum samples from independent patient cohorts encompassing 1,401 participants divided into three groups, i.e. healthy, GC patients, and GC-related disease group. To discover biomarkers for GC, the human proteome microarray was first applied to screen specific autoantibodies in a total of 87 serum samples from GC patients and healthy controls. Potential biomarkers were identified via a statistical analysis protocol. Targeted protein microarrays with only the potential biomarkers were constructed and used to validate the candidate biomarkers using 914 samples. To provide further validation, the abundance of autoantibodies specific to the biomarker candidates was analyzed using enzyme-linked immunosorbent assays. Receiver operating characteristic curves were generated to evaluate the diagnostic accuracy of the serum biomarkers. Finally, the efficacy of prognosis efficacy of the final four biomarkers was evaluated by analyzing the clinical records. The final panel of biomarkers consisting of COPS2, CTSF, NT5E, and TERF1 provides high diagnostic power, with 95% sensitivity and 92% specificity to differentiate GC patients from healthy individuals. Prognosis analysis showed that the panel could also serve as independent predictors of the overall GC patient survival. The panel of four serum biomarkers (COPS2, CTSF, NT5E, and TERF1) could serve as a noninvasive diagnostic index for GC, and the combination of them could potentially be used as a predictor of the overall GC survival rate., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Peptide intensities from mass spectra are increasingly used for relative quantitation of proteins in complex samples. However, numerous issues inherent to the mass spectrometry workflow turn quantitative proteomic data analysis into a crucial challenge. We and others have shown that modeling at the peptide level outperforms classical summarization-based approaches, which typically also discard a lot of proteins at the data preprocessing step. Peptide-based linear regression models, however, still suffer from unbalanced datasets due to missing peptide intensities, outlying peptide intensities and overfitting. Here, we further improve upon peptide-based models by three modular extensions: ridge regression, improved variance estimation by borrowing information across proteins with empirical Bayes and M-estimation with Huber weights. We illustrate our method on the CPTAC spike-in study and on a study comparing wild-type and ArgP knock-out Francisella tularensis proteomes. We show that the fold change estimates of our robust approach are more precise and more accurate than those from state-of-the-art summarization-based methods and peptide-based regression models, which leads to an improved sensitivity and specificity. We also demonstrate that ionization competition effects come already into play at very low spike-in concentrations and confirm that analyses with peptide-based regression methods on peptide intensity values aggregated by charge state and modification status (e.g. MaxQuant's peptides.txt file) are slightly superior to analyses on raw peptide intensity values (e.g. MaxQuant's evidence.txt file)., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Neurodegenerative diseases, such as Alzheimer's diseases (AD), are becoming more prevalent as the population ages. However, the mechanisms that lead to synapse destabilization and neuron death remain elusive. The advent of proteomics has allowed for high-throughput screening methods to search for biomarkers that could lead to early diagnosis and treatment and to identify alterations in the cellular proteome that could provide insight into disease etiology and possible treatment avenues. In this review, we have concentrated mainly on the findings that are related to how and whether proteomics studies have contributed to two aspects of AD research, the development of biomarkers for clinical diagnostics, and the recognition of proteins that can help elucidate the pathways leading to AD brain pathology. As a result of these studies, several candidate cerebrospinal fluid biomarkers are now available for further validation in different AD cohorts. Studies in AD brain and AD transgenic models support the notion that oxidative damage results in the alterations of metabolic enzymes and that mitochondrial dysfunction is central to AD neuropathology., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

To date, the proteomic profiling of Müller cells, the dominant macroglia of the retina, has been hampered because of the absence of suitable enrichment methods. We established a novel protocol to isolate native, intact Müller cells from adult murine retinae at excellent purity which retain in situ morphology and are well suited for proteomic analyses. Two different strategies of sample preparation - an in StageTips (iST) and a subcellular fractionation approach including cell surface protein profiling were used for quantitative liquid chromatography-mass spectrometry (LC-MSMS) comparing Müller cell-enriched to depleted neuronal fractions. Pathway enrichment analyses on both data sets enabled us to identify Müller cell-specific functions which included focal adhesion kinase signaling, signal transduction mediated by calcium as second messenger, transmembrane neurotransmitter transport and antioxidant activity. Pathways associated with RNA processing, cellular respiration and phototransduction were enriched in the neuronal subpopulation. Proteomic results were validated for selected Müller cell genes by quantitative real time PCR, confirming the high expression levels of numerous members of the angiogenic and anti-inflammatory annexins and antioxidant enzymes (e.g. paraoxonase 2, peroxiredoxin 1, 4 and 6). Finally, the significant enrichment of antioxidant proteins in Müller cells was confirmed by measurements on vital retinal cells using the oxidative stress indicator CM-H2DCFDA. In contrast to photoreceptors or bipolar cells, Müller cells were most efficiently protected against H2O2-induced reactive oxygen species formation, which is in line with the protein repertoire identified in the proteomic profiling. Our novel approach to isolate intact glial cells from adult retina in combination with proteomic profiling enabled the identification of novel Müller glia specific proteins, which were validated as markers and for their functional impact in glial physiology. This provides the basis to allow the discovery of novel glial specializations and will enable us to elucidate the role of Müller cells in retinal pathologies - a topic still controversially discussed., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Gambogic acid (GA) is an anticancer agent in phase IIb clinical trial in China. In HeLa cells, GA inhibited cell proliferation, induced cell cycle arrest at G2/M phase and apoptosis, as showed by results of MTT assay and flow cytometric analysis. Possible target-related proteins of GA were searched using comparative proteomic analysis (2-DE) and nine proteins at early (3 h) stage together with nine proteins at late (24 h) stage were found. Vimentin was the only target-related protein found at both early and late stage. Results of both 2-DE analysis and Western blotting assay suggested cleavage of vimentin induced by GA. MS/MS analysis of cleaved vimentin peptides indicated possible cleavage sites of vimentin at or near ser51 and glu425. Results of targeted proteomic analysis showed that GA induced change in phosphorylation state of the vimentin head domain (aa51-64). Caspase inhibitors could not abrogate GA-induced cleavage of vimentin. Over-expression of vimentin ameliorated cytotoxicity of GA in HeLa cells. The GA-activated signal transduction, from p38 MAPK, heat shock protein 27 (HSP27), vimentin, dysfunction of cytoskeleton, to cell death, was predicted and then confirmed. Results of animal study showed that GA treatment inhibited tumor growth in HeLa tumor-bearing mice and cleavage of vimentin could be observed in tumor xenografts of GA-treated animals. Results of immunohistochemical staining also showed down-regulated vimentin level in tumor xenografts of GA-treated animals. Furthermore, compared with cytotoxicity of GA in HeLa cells, cytotoxicity of GA in MCF-7 cells with low level of vimentin was weaker whereas cytotoxicity of GA in MG-63 cells with high level of vimentin was stronger. These results indicated the important role of vimentin in the cytotoxicity of GA. The effects of GA on vimentin and other epithelial-to-mesenchymal transition (EMT) markers provided suggestion for better usage of GA in clinic., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Azoles are widely used antifungal drugs. This family of compounds includes triazoles, mostly used in the treatment of systemic infections, and imidazoles, such as clotrimazole, often used in the case of superficial infections. Candida glabrata is the second most common cause of candidemia worldwide and presents higher levels of intrinsic azole resistance when compared with Candida albicans, thus being an interesting subject for the study of azole resistance mechanisms in fungal pathogens.Since resistance often relies on the action of membrane transporters, including drug efflux pumps from the ATP-binding cassette family or from the Drug:H(+) antiporter (DHA)(1) family, an iTRAQ-based membrane proteomics analysis was performed to identify all the membrane-associated proteins whose abundance changes in C. glabrata cells exposed to the azole drug clotrimazole. Proteins found to have significant expression changes in this context were clustered into functional groups, namely: glucose metabolism, oxidative phosphorylation, mitochondrial import, ribosome components and translation machinery, lipid metabolism, multidrug resistance transporters, cell wall assembly, and stress response, comprising a total of 37 proteins. Among these, the DHA transporter CgTpo1_2 (ORF CAGL0E03674g) was identified as overexpressed in the C. glabrata membrane in response to clotrimazole. Functional characterization of this putative drug:H(+) antiporter, and of its homolog CgTpo1_1 (ORF CAGL0G03927g), allowed the identification of these proteins as localized to the plasma membrane and conferring azole drug resistance in this fungal pathogen by actively extruding the drug to the external medium. The cell wall protein CgGas1 was also shown to confer azole drug resistance through cell wall remodeling. Finally, the transcription factor CgPdr1 in the clotrimazole response was observed to control the expression of 20 of the identified proteins, thus highlighting the existence of additional unforeseen targets of this transcription factor, recognized as a major regulator of azole drug resistance in clinical isolates., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Omics analysis is a versatile approach for understanding the conservation and diversity of molecular systems across multiple taxa. In this study, we compared the proteome expression profiles of four yeast species (Saccharomyces cerevisiae, Saccharomyces mikatae, Kluyveromyces waltii, and Kluyveromyces lactis) grown on glucose- or glycerol-containing media. Conserved expression changes across all species were observed only for a small proportion of all proteins differentially expressed between the two growth conditions. Two Kluyveromyces species, both of which exhibited a high growth rate on glycerol, a nonfermentative carbon source, showed distinct species-specific expression profiles. In K. waltii grown on glycerol, proteins involved in the glyoxylate cycle and gluconeogenesis were expressed in high abundance. In K. lactis grown on glycerol, the expression of glycolytic and ethanol metabolic enzymes was unexpectedly low, whereas proteins involved in cytoplasmic translation, including ribosomal proteins and elongation factors, were highly expressed. These marked differences in the types of predominantly expressed proteins suggest that K. lactis optimizes the balance of proteome resource allocation between metabolism and protein synthesis giving priority to cellular growth. In S. cerevisiae, about 450 duplicate gene pairs were retained after whole-genome duplication. Intriguingly, we found that in the case of duplicates with conserved sequences, the total abundance of proteins encoded by a duplicate pair in S. cerevisiae was similar to that of protein encoded by nonduplicated ortholog in Kluyveromyces yeast. Given the frequency of haploinsufficiency, this observation suggests that conserved duplicate genes, even though minor cases of retained duplicates, do not exhibit a dosage effect in yeast, except for ribosomal proteins. Thus, comparative proteomic analyses across multiple species may reveal not only species-specific characteristics of metabolic processes under nonoptimal culture conditions but also provide valuable insights into intriguing biological principles, including the balance of proteome resource allocation and the role of gene duplication in evolutionary history., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Many species possess an endogenous circadian clock to synchronize internal physiology with an oscillating external environment. In plants, the circadian clock coordinates growth, metabolism and development over daily and seasonal time scales. Many proteins in the circadian network form oscillating complexes that temporally regulate myriad processes, including signal transduction, transcription, protein degradation and post-translational modification. In Arabidopsis thaliana, a tripartite complex composed of EARLY FLOWERING 4 (ELF4), EARLY FLOWERING 3 (ELF3), and LUX ARRHYTHMO (LUX), named the evening complex, modulates daily rhythms in gene expression and growth through transcriptional regulation. However, little is known about the physical interactions that connect the circadian system to other pathways. We used affinity purification and mass spectrometry (AP-MS) methods to identify proteins that associate with the evening complex in A. thaliana. New connections within the circadian network as well as to light signaling pathways were identified, including linkages between the evening complex, TIMING OF CAB EXPRESSION1 (TOC1), TIME FOR COFFEE (TIC), all phytochromes and TANDEM ZINC KNUCKLE/PLUS3 (TZP). Coupling genetic mutation with affinity purifications tested the roles of phytochrome B (phyB), EARLY FLOWERING 4, and EARLY FLOWERING 3 as nodes connecting the evening complex to clock and light signaling pathways. These experiments establish a hierarchical association between pathways and indicate direct and indirect interactions. Specifically, the results suggested that EARLY FLOWERING 3 and phytochrome B act as hubs connecting the clock and red light signaling pathways. Finally, we characterized a clade of associated nuclear kinases that regulate circadian rhythms, growth, and flowering in A. thaliana. Coupling mass spectrometry and genetics is a powerful method to rapidly and directly identify novel components and connections within and between complex signaling pathways., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Cancer is a very heterogeneous disease, and biological variability adds a further level of complexity, thus limiting the ability to identify new genes involved in cancer development. Oncogenes whose expression levels control cell aggressiveness are very useful for developing cellular models that permit differential expression screenings in isogenic contexts. HMGA1 protein has this unique property because it is a master regulator in breast cancer cells that control the transition from a nontumorigenic epithelial-like phenotype toward a highly aggressive mesenchymal-like one. The proteins extracted from HMGA1-silenced and control MDA-MB-231 cells were analyzed using label-free shotgun mass spectrometry. The differentially expressed proteins were cross-referenced with DNA microarray data obtained using the same cellular model and the overlapping genes were filtered for factors linked to poor prognosis in breast cancer gene expression meta-data sets, resulting in an HMGA1 protein signature composed of 21 members (HRS, HMGA1 reduced signature). This signature had a prognostic value (overall survival, relapse-free survival, and distant metastasis-free survival) in breast cancer. qRT-PCR, Western blot, and immunohistochemistry analyses validated the link of three members of this signature (KIFC1, LRRC59, and TRIP13) with HMGA1 expression levels both in vitro and in vivo and wound healing assays demonstrated that these three proteins are involved in modulating tumor cell motility. Combining proteomic and genomic data with the aid of bioinformatic tools, our results highlight the potential involvement in neoplastic transformation of a restricted list of factors with an as-yet-unexplored role in cancer. These factors are druggable targets that could be exploited for the development of new, targeted therapeutic approaches in triple-negative breast cancer., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

The endogenous mechanisms contributing to tissue survival following myocardial infarction are not fully understood. We investigated the alterations in the mitochondrial proteome after ischemia-reperfusion (I/R) and its possible implications on cell survival. Mitochondrial proteomic analysis of cardiac tissue from an in vivo porcine I/R model found that surviving tissue in the peri-infarct border zone showed increased expression of several proteins. Notably, these included subunits of the mitochondrial pyruvate carrier (MPC), namely MPC1 and MPC2. Western blot, immunohistochemistry, and mRNA analysis corroborated the elevated expression of MPC in the surviving tissue. Furthermore, MPC1 and MPC2 protein levels were found to be markedly elevated in the myocardium of ischemic cardiomyopathy patients. These findings led to the hypothesis that increased MPC expression is cardioprotective due to enhancement of mitochondrial pyruvate uptake in the energy-starved heart following I/R. To test this, isolated mouse hearts perfused with a modified Krebs buffer (containing glucose, pyruvate, and octanoate as metabolic substrates) were subjected to I/R with or without the MPC transport inhibitor UK5099. UK5099 increased myocardial infarction and attenuated post-ischemic recovery of left ventricular end-diastolic pressure. However, aerobically perfused control hearts that were exposed to UK5099 did not modulate contractile function, although pyruvate uptake was blocked as evidenced by increased cytosolic lactate and pyruvate levels. Our findings indicate that increased expression of MPC leads to enhanced uptake and utilization of pyruvate during I/R. We propose this as a putative endogenous mechanism that promotes myocardial survival to limit infarct size., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Protein kinases are an important class of enzymes involved in the phosphorylation of their targets, which regulate key cellular processes and are typically mediated by a specificity for certain residues around the target phospho-acceptor residue. While efforts have been made to identify such specificities, only ∼30% of human kinases have a significant number of known binding sites. We describe a computational method that utilizes functional interaction data and phosphorylation data to predict specificities of kinases. We applied this method to human kinases to predict substrate preferences for 57% of all known kinases and show that we are able to reconstruct well-known specificities. We used an in vitro mass spectrometry approach to validate four understudied kinases and show that predicted models closely resemble true specificities. We show that this method can be applied to different organisms and can be extended to other phospho-recognition domains. Applying this approach to different types of posttranslational modifications (PTMs) and binding domains could uncover specificities of understudied PTM recognition domains and provide significant insight into the mechanisms of signaling networks., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Proteogenomic re-annotation and mRNA splicing information can lead to the discovery of various protein forms for eukaryotic model organisms like rat. However, detection of novel proteoforms using mass spectrometry proteomics data remains a formidable challenge. We developed EuGenoSuite, an open source multiple algorithmic proteomic search tool and utilized it in our in-house integrated transcriptomic-proteomic pipeline to facilitate automated proteogenomic analysis. Using four proteogenomic pipelines (integrated transcriptomic-proteomic, Peppy, Enosi, and ProteoAnnotator) on publicly available RNA-sequence and MS proteomics data, we discovered 363 novel peptides in rat brain microglia representing novel proteoforms for 249 gene loci in the rat genome. These novel peptides aided in the discovery of novel exons, translation of annotated untranslated regions, pseudogenes, and splice variants for various loci; many of which have known disease associations, including neurological disorders like schizophrenia, amyotrophic lateral sclerosis, etc. Novel isoforms were also discovered for genes implicated in cardiovascular diseases and breast cancer for which rats are considered model organisms. Our integrative multi-omics data analysis not only enables the discovery of new proteoforms but also generates an improved reference for human disease studies in the rat model., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Understanding molecular mechanisms underlying plant salinity tolerance provides valuable knowledgebase for effective crop improvement through genetic engineering. Current proteomic technologies, which support reliable and high-throughput analyses, have been broadly used for exploring sophisticated molecular networks in plants. In the current study, we compared phosphoproteomic and proteomic changes in roots of different soybean seedlings of a salt-tolerant cultivar (Wenfeng07) and a salt-sensitive cultivar (Union85140) induced by salt stress. The root samples of Wenfeng07 and Union85140 at three-trifoliate stage were collected at 0 h, 0.5 h, 1 h, 4 h, 12 h, 24 h, and 48 h after been treated with 150 mm NaCl. LC-MS/MS based phosphoproteomic analysis of these samples identified a total of 2692 phosphoproteins and 5509 phosphorylation sites. Of these, 2344 phosphoproteins containing 3744 phosphorylation sites were quantitatively analyzed. Our results showed that 1163 phosphorylation sites were differentially phosphorylated in the two compared cultivars. Among them, 10 MYB/MYB transcription factor like proteins were identified with fluctuating phosphorylation modifications at different time points, indicating that their crucial roles in regulating flavonol accumulation might be mediated by phosphorylated modifications. In addition, the protein expression profiles of these two cultivars were compared using LC MS/MS based shotgun proteomic analysis, and expression pattern of all the 89 differentially expressed proteins were independently confirmed by qRT-PCR. Interestingly, the enzymes involved in chalcone metabolic pathway exhibited positive correlations with salt tolerance. We confirmed the functional relevance of chalcone synthase, chalcone isomerase, and cytochrome P450 monooxygenase genes using soybean composites and Arabidopsis thaliana mutants, and found that their salt tolerance were positively regulated by chalcone synthase, but was negatively regulated by chalcone isomerase and cytochrome P450 monooxygenase. A novel salt tolerance pathway involving chalcone metabolism, mostly mediated by phosphorylated MYB transcription factors, was proposed based on our findings. (The mass spectrometry raw data are available via ProteomeXchange with identifier PXD002856)., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the "peptide-to-protein" inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0-30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in a ∼60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding eight times more identifications of 0-30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Citreoviridin, one of toxic mycotoxins derived from fungal species, can suppress lung cancer cell growth by inhibiting the activity of ectopic ATP synthase, but has limited effect on normal cells. However, the mechanism of citreoviridin triggering dynamic molecular responses in cancer cells remains unclear. Here, we performed temporal phosphoproteomics to elucidate the dynamic changes after citreoviridin treatment in cells and xenograft model. We identified a total of 829 phosphoproteins and demonstrated that citreoviridin treatment affects protein folding, cell cycle, and cytoskeleton function. Furthermore, response network constructed by mathematical modeling shows the relationship between the phosphorylated heat shock protein 90 β and mitogen-activated protein kinase signaling pathway. This work describes that citreoviridin suppresses cancer cell growth and mitogen-activated protein kinase/extracellular signal-regulated kinase signaling by site-specific dephosphorylation of HSP90AB1 on Serine 255 and provides perspectives in cancer therapeutic strategies., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but this requires accurate and robust tools. Here, we develop a state of the art quantitative mass spectrometric pipeline to characterize formalin-fixed paraffin-embedded tissues of patients with closely related subtypes of diffuse large B-cell lymphoma. We combined a super-SILAC approach with label-free quantification (hybrid LFQ) to address situations where the protein is absent in the super-SILAC standard but present in the patient samples. Shotgun proteomic analysis on a quadrupole Orbitrap quantified almost 9,000 tumor proteins in 20 patients. The quantitative accuracy of our approach allowed the segregation of diffuse large B-cell lymphoma patients according to their cell of origin using both their global protein expression patterns and the 55-protein signature obtained previously from patient-derived cell lines (Deeb, S. J., D'Souza, R. C., Cox, J., Schmidt-Supprian, M., and Mann, M. (2012) Mol. Cell. Proteomics 11, 77-89). Expression levels of individual segregation-driving proteins as well as categories such as extracellular matrix proteins behaved consistently with known trends between the subtypes. We used machine learning (support vector machines) to extract candidate proteins with the highest segregating power. A panel of four proteins (PALD1, MME, TNFAIP8, and TBC1D4) is predicted to classify patients with low error rates. Highly ranked proteins from the support vector analysis revealed differential expression of core signaling molecules between the subtypes, elucidating aspects of their pathobiology., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Tamoxifen, an estrogen receptor-α (ER) antagonist, is an important agent for the treatment of breast cancer. However, this therapy is complicated by the fact that a substantial number of patients exhibit either de novo or acquired resistance. To characterize the signaling mechanisms underlying this resistance, we treated the MCF7 breast cancer cell line with tamoxifen for over six months and showed that this cell line acquired resistance to tamoxifen in vitro and in vivo. We performed SILAC-based quantitative phosphoproteomic profiling on the tamoxifen resistant and vehicle-treated sensitive cell lines to quantify the phosphorylation alterations associated with tamoxifen resistance. From >5600 unique phosphopeptides identified, 1529 peptides exhibited hyperphosphorylation and 409 peptides showed hypophosphorylation in the tamoxifen resistant cells. Gene set enrichment analysis revealed that focal adhesion pathway was one of the most enriched signaling pathways activated in tamoxifen resistant cells. Significantly, we showed that the focal adhesion kinase FAK2 was not only hyperphosphorylated but also transcriptionally up-regulated in tamoxifen resistant cells. FAK2 suppression by specific siRNA knockdown or a small molecule inhibitor repressed cellular proliferation in vitro and tumor formation in vivo. More importantly, our survival analysis revealed that high expression of FAK2 is significantly associated with shorter metastasis-free survival in estrogen receptor-positive breast cancer patients treated with tamoxifen. Our studies suggest that FAK2 is a potential therapeutic target for the management of hormone-refractory breast cancers., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Legumes form a symbiosis with rhizobia in which the plant provides an energy source to the rhizobia bacteria that it uses to fix atmospheric nitrogen. This nitrogen is provided to the legume plant, allowing it to grow without the addition of nitrogen fertilizer. As part of the symbiosis, the bacteria in the infected cells of a new root organ, the nodule, are surrounded by a plant-derived membrane, the symbiosome membrane, which becomes the interface between the symbionts. Fractions containing the symbiosome membrane (SM) and material from the lumen of the symbiosome (peribacteroid space or PBS) were isolated from soybean root nodules and analyzed using nongel proteomic techniques. Bicarbonate stripping and chloroform-methanol extraction of isolated SM were used to reduce complexity of the samples and enrich for hydrophobic integral membrane proteins. One hundred and ninety-seven proteins were identified as components of the SM, with an additional fifteen proteins identified from peripheral membrane and PBS protein fractions. Proteins involved in a range of cellular processes such as metabolism, protein folding and degradation, membrane trafficking, and solute transport were identified. These included a number of proteins previously localized to the SM, such as aquaglyceroporin nodulin 26, sulfate transporters, remorin, and Rab7 homologs. Among the proteome were a number of putative transporters for compounds such as sulfate, calcium, hydrogen ions, peptide/dicarboxylate, and nitrate, as well as transporters for which the substrate is not easy to predict. Analysis of the promoter activity for six genes encoding putative SM proteins showed nodule specific expression, with five showing expression only in infected cells. Localization of two proteins was confirmed using GFP-fusion experiments. The data have been deposited to the ProteomeXchange with identifier PXD001132. This proteome will provide a rich resource for the study of the legume-rhizobium symbiosis., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Voltage-gated sodium channels (Nav1.1-Nav1.9) are responsible for the initiation and propagation of action potentials in neurons, controlling firing patterns, synaptic transmission and plasticity of the brain circuit. Yet, it is the protein-protein interactions of the macromolecular complex that exert diverse modulatory actions on the channel, dictating its ultimate functional outcome. Despite the fundamental role of Nav channels in the brain, information on its proteome is still lacking. Here we used affinity purification from crude membrane extracts of whole brain followed by quantitative high-resolution mass spectrometry to resolve the identity of Nav1.2 protein interactors. Of the identified putative protein interactors, fibroblast growth factor 12 (FGF12), a member of the nonsecreted intracellular FGF family, exhibited 30-fold enrichment in Nav1.2 purifications compared with other identified proteins. Using confocal microscopy, we visualized native FGF12 in the brain tissue and confirmed that FGF12 forms a complex with Nav1.2 channels at the axonal initial segment, the subcellular specialized domain of neurons required for action potential initiation. Co-immunoprecipitation studies in a heterologous expression system validate Nav1.2 and FGF12 as interactors, whereas patch-clamp electrophysiology reveals that FGF12 acts synergistically with CaMKII, a known kinase regulator of Nav channels, to modulate Nav1.2-encoded currents. In the presence of CaMKII inhibitors we found that FGF12 produces a bidirectional shift in the voltage-dependence of activation (more depolarized) and the steady-state inactivation (more hyperpolarized) of Nav1.2, increasing the channel availability. Although providing the first characterization of the Nav1.2 CNS proteome, we identify FGF12 as a new functionally relevant interactor. Our studies will provide invaluable information to parse out the molecular determinant underlying neuronal excitability and plasticity, and extending the relevance of iFGFs signaling in the normal and diseased brain., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Macrophages operate at the forefront of innate immunity and their discrimination of foreign versus "self" particles is critical for a number of responses including efficient pathogen killing, antigen presentation, and cytokine induction. In order to efficiently destroy the particles and detect potential threats, macrophages express an array of receptors to sense and phagocytose prey particles. In this study, we accurately quantified a proteomic time-course of isolated phagosomes from murine bone marrow-derived macrophages induced by particles conjugated to seven different ligands representing pathogen-associated molecular patterns, immune opsonins or apoptotic cell markers. We identified a clear functional differentiation over the three timepoints and detected subtle differences between certain ligand-phagosomes, indicating that triggering of receptors through a single ligand type has mild, but distinct, effects on phagosome proteome and function. Moreover, our data shows that uptake of phosphatidylserine-coated beads induces an active repression of NF-κB immune responses upon Toll-like receptor (TLR)-activation by recruitment of anti-inflammatory regulators to the phagosome. This data shows for the first time a systematic time-course analysis of bone marrow-derived macrophages phagosomes and how phagosome fate is regulated by the receptors triggered for phagocytosis., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Current therapies for prostate cancer include antiandrogens, inhibitory ligands of the androgen receptor, which repress androgen-stimulated growth. These include the selective androgen receptor modulators cyproterone acetate and hydroxyflutamide and the complete antagonist bicalutamide. Their activity is partly dictated by the presence of androgen receptor mutations, which are commonly detected in patients who relapse while receiving antiandrogens, i.e. in castrate-resistant prostate cancer. To characterize the early proteomic response to these antiandrogens we used the LNCaP prostate cancer cell line, which harbors the androgen receptor mutation most commonly detected in castrate-resistant tumors (T877A), analyzing alterations in the proteome, and comparing these to the effect of these therapeutics upon androgen receptor activity and cell proliferation. The majority are regulated post-transcriptionally, possibly via nongenomic androgen receptor signaling. Differences detected between the exposure groups demonstrate subtle changes in the biological response to each specific ligand, suggesting a spectrum of agonistic and antagonistic effects dependent on the ligand used. Analysis of the crystal structures of the AR in the presence of cyproterone acetate, hydroxyflutamide, and DHT identified important differences in the orientation of key residues located in the AF-2 and BF-3 protein interaction surfaces. This further implies that although there is commonality in the growth responses between androgens and those antiandrogens that stimulate growth in the presence of a mutation, there may also be influential differences in the growth pathways stimulated by the different ligands. This therefore has implications for prostate cancer treatment because tumors may respond differently dependent upon which mutation is present and which ligand is activating growth, also for the design of selective androgen receptor modulators, which aim to elicit differential proteomic responses dependent upon cellular context., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

The data-independent acquisition (DIA) approach has recently been introduced as a novel mass spectrometric method that promises to combine the high content aspect of shotgun proteomics with the reproducibility and precision of selected reaction monitoring. Here, we evaluate, whether SWATH-MS type DIA effectively translates into a better protein profiling as compared with the established shotgun proteomics. We implemented a novel DIA method on the widely used Orbitrap platform and used retention-time-normalized (iRT) spectral libraries for targeted data extraction using Spectronaut. We call this combination hyper reaction monitoring (HRM). Using a controlled sample set, we show that HRM outperformed shotgun proteomics both in the number of consistently identified peptides across multiple measurements and quantification of differentially abundant proteins. The reproducibility of HRM in peptide detection was above 98%, resulting in quasi complete data sets compared with 49% of shotgun proteomics. Utilizing HRM, we profiled acetaminophen (APAP)(1)-treated three-dimensional human liver microtissues. An early onset of relevant proteome changes was revealed at subtoxic doses of APAP. Further, we detected and quantified for the first time human NAPQI-protein adducts that might be relevant for the toxicity of APAP. The adducts were identified on four mitochondrial oxidative stress related proteins (GATM, PARK7, PRDX6, and VDAC2) and two other proteins (ANXA2 and FTCD). Our findings imply that DIA should be the preferred method for quantitative protein profiling., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Complex phosphorylation-dependent signaling networks underlie the coordination of cellular growth and division. In the fission yeast Schizosaccharomyces pombe, the Dual specificity tyrosine-(Y)-phosphorylation regulated kinase (DYRK) family protein kinase Pom1 regulates cell cycle progression through the mitotic inducer Cdr2 and controls cell polarity through unknown targets. Here, we sought to determine the phosphorylation targets of Pom1 kinase activity by SILAC-based phosphoproteomics. We defined a set of high-confidence Pom1 targets that were enriched for cytoskeletal and cell growth functions. Cdr2 was the only cell cycle target of Pom1 kinase activity that we identified in cells. Mutation of Pom1-dependent phosphorylation sites in the C terminus of Cdr2 inhibited mitotic entry but did not impair Cdr2 localization. In addition, we found that Pom1 phosphorylated multiple substrates that function in polarized cell growth, including Tea4, Mod5, Pal1, the Rho GAP Rga7, and the Arf GEF Syt22. Purified Pom1 phosphorylated these cell polarity targets in vitro, confirming that they are direct substrates of Pom1 kinase activity and likely contribute to regulation of polarized growth by Pom1. Our study demonstrates that Pom1 acts in a linear pathway to control cell cycle progression while regulating a complex network of cell growth targets., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

The fatal neurodegenerative disorders amyotrophic lateral sclerosis and spinal muscular atrophy are, respectively, the most common motoneuron disease and genetic cause of infant death. Various in vitro model systems have been established to investigate motoneuron disease mechanisms, in particular immortalized cell lines and primary neurons. Using quantitative mass-spectrometry-based proteomics, we compared the proteomes of primary motoneurons to motoneuron-like cell lines NSC-34 and N2a, as well as to non-neuronal control cells, at a depth of 10,000 proteins. We used this resource to evaluate the suitability of murine in vitro model systems for cell biological and biochemical analysis of motoneuron disease mechanisms. Individual protein and pathway analysis indicated substantial differences between motoneuron-like cell lines and primary motoneurons, especially for proteins involved in differentiation, cytoskeleton, and receptor signaling, whereas common metabolic pathways were more similar. The proteins associated with amyotrophic lateral sclerosis also showed distinct differences between cell lines and primary motoneurons, providing a molecular basis for understanding fundamental alterations between cell lines and neurons with respect to neuronal pathways with relevance for disease mechanisms. Our study provides a proteomics resource for motoneuron research and presents a paradigm of how mass-spectrometry-based proteomics can be used to evaluate disease model systems., (© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.)

To improve ethanol production directly from CO2 in photosynthetic cyanobacterial systems, one key issue that needs to be addressed is the low ethanol tolerance of cyanobacterial cells. Our previous proteomic and transcriptomic analyses found that several regulatory proteins were up-regulated by exogenous ethanol in Synechocystis sp. PCC6803. In this study, through tolerance analysis of the gene disruption mutants of the up-regulated regulatory genes, we uncovered that one transcriptional regulator, Sll0794, was related directly to ethanol tolerance in Synechocystis. Using a quantitative iTRAQ-LC-MS/MS proteomics approach coupled with quantitative real-time reverse transcription-PCR (RT-qPCR), we further determined the possible regulatory network of Sll0794. The proteomic analysis showed that in the Δsll0794 mutant grown under ethanol stress a total of 54 and 87 unique proteins were down- and up-regulated, respectively. In addition, electrophoretic mobility shift assays demonstrated that the Sll0794 transcriptional regulator was able to bind directly to the upstream regions of sll1514, slr1512, and slr1838, which encode a 16.6 kDa small heat shock protein, a putative sodium-dependent bicarbonate transporter and a carbon dioxide concentrating mechanism protein CcmK, respectively. The study provided a proteomic description of the putative ethanol-tolerance network regulated by the sll0794 gene, and revealed new insights on the ethanol-tolerance regulatory mechanism in Synechocystis. As the first regulatory protein discovered related to ethanol tolerance, the gene may serve as a valuable target for transcription machinery engineering to further improve ethanol tolerance in Synechocystis. All MS data have been deposited in the ProteomeXchange with identifier PXD001266 (http://proteomecentral.proteomexchange.org/dataset/PXD001266)., (© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.)

Overwintering plants are capable of exhibiting high levels of cold tolerance, which is acquired through the process of cold acclimation (CA). In contrast to CA, the acquired freezing tolerance is rapidly reduced during cold de-acclimation (DA) and plants resume growth after sensing warm temperatures. In order to better understand plant growth and development, and to aid in the breeding of cold-tolerant plants, it is important to decipher the functional mechanisms of the DA process. In this study, we performed comparative transcriptomic and proteomic analyses during CA and DA. As revealed by shotgun proteomics, we identified 3987 peptides originating from 1569 unique proteins and the corresponding mRNAs were analyzed. Among the 1569 genes, 658 genes were specifically induced at the transcriptional level during the process of cold acclimation. In order to investigate the relationship between mRNA and the corresponding protein expression pattern, a Pearson correlation was analyzed. Interestingly, 199 genes showed a positive correlation of mRNA and protein expression pattern, indicating that both their transcription and translation occurred during CA. However, 226 genes showed a negative correlation of mRNA and protein expression pattern, indicating that their mRNAs were transcribed during CA and were stored for the subsequent DA step. Under this scenario, those proteins were specifically increased during DA without additional transcription of mRNA. In order to confirm the negative correlation of mRNA and protein expression patterns, qRT-PCR and western blot analyses were performed. Mitochondrial malate dehydrogenase 1 (mMDH1) exhibited a negative correlation of mRNA and protein levels, which was characterized by CA-specific mRNA induction and protein accumulation specifically during DA. These data indicate that the expression of specific mRNAs and subsequent accumulation of corresponding proteins are not always in accordance under low temperature stress conditions in plants., (© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.)

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that, with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian Proteoform Quantification model (BP-Quant)(1) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern or the existence of multiple overexpressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab® and R packages., (© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.)