Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

Writers and readers of H3K9me2 form distinct protein networks during the cell cycle that include candidates for H3K9 mimicry

Histone H3 lysine 9 methylation (H3K9me), which is written by the Euchromatic Histone Lysine Methyltransferases EHMT1 and EHMT2 and read by the heterochromatin protein 1 (HP1) chromobox (CBX) protein family, is dysregulated in many types of cancers. Approaches to inhibit regulators of this pathway are currently being evaluated for therapeutic purposes. Thus, knowledge of the complexes supporting the function of these writers and readers during the process of cell proliferation is critical for our understanding of their role in carcinogenesis. Here, we immunopurified each of these proteins and used mass spectrometry to define their associated non-histone proteins, individually and at two different phases of the cell cycle, namely G1/S and G2/M. Our findings identify novel binding proteins for these writers and readers, as well as corroborate known interactors, to show the formation of distinct protein complex networks in a cell cycle phase-specific manner. Furthermore, there is an organizational switch between cell cycle phases for interactions among specific writer-reader pairs. Through a multi-tiered bioinformatics-based approach, we reveal that many interacting proteins exhibit histone mimicry, based on an H3K9-like linear motif. Gene ontology analyses, pathway enrichment, and network reconstruction inferred that these comprehensive EHMT and CBX-associated interacting protein networks participate in various functions, including transcription, DNA repair, splicing, and membrane disassembly. Combined, our data reveals novel complexes that provide insight into key functions of cell cycle-associated epigenomic processes that are highly relevant for better understanding these chromatin-modifying proteins during cell cycle and carcinogenesis.

Mass spectrometry-based retina proteomics

A subfield of neuroproteomics, retina proteomics has experienced a transformative growth since its inception due to methodological advances in enabling chemical, biochemical, and molecular biology techniques. This review focuses on mass spectrometry's contributions to facilitate mammalian and avian retina proteomics to catalog and quantify retinal protein expressions, determine their posttranslational modifications, as well as its applications to study the proteome of the retina in the context of biology, health and diseases, and therapy developments.

Mass Spectrometry-Based Assessment of Prostate Cancer-Associated Crystalloids Reveals Enrichment for Growth & Differentiation Factor 15 (GDF15)

Intraluminal crystalloids are a common finding within malignant prostatic acini and are infrequently identified within benign glands. The proteomic composition of these crystalloids remains poorly understood and may provide insight regarding prostate cancer pathogenesis. Laser microdissection assisted liquid chromatography tandem mass spectrometry (LMD-LC-MS/MS) was performed to compare proteomic composition of corpora amylacea within benign acini (n=9), prostatic adenocarcinoma-associated crystalloids (n=8), benign (n=8), and malignant prostatic acini (n=6). The expression of candidate biomarkers was then measured in urine specimens from patients with (n=8) and without prostate cancer (n=10) using ELISA; and immunohistochemistry-based expression in adjacent prostate cancer and benign glands was assessed in 56 whole-slide sections from radical prostatectomy specimens. LMD-LC-MS/MS revealed enrichment for the C-terminal portion of growth and differentiation factor 15 (GDF15) in prostatic crystalloids. Although urinary GDF15 levels were higher in patients with prostatic adenocarcinoma compared to those without (median: 1561.2 vs 1101.3, arbitrary units), this did not meet statistical significance (p=0.07). Immunohistochemistry for GDF15 revealed occasional positivity in benign glands (median H-score: 30, n=56), and diffuse positivity in prostatic adenocarcinoma (median H-score: 200, n=56, p<0.0001). No significant difference was identified within different prognostic grade groups of prostatic adenocarcinoma, or within malignant glands with large cribriform morphology. Our results show that the C-terminal portion of GDF15 is enriched in prostate cancer-associated crystalloids, and higher GDF15 expression is seen in malignant rather than benign prostatic acini. Improved understanding of the proteomic composition of prostate cancer-associated crystalloids provides the rationale for evaluating GDF15 as a urine-based biomarker of prostate cancer.

Molecular signatures of inherited and acquired sporadic late onset nemaline myopathies

Acquired sporadic late onset nemaline myopathy (SLONM) and inherited nemaline myopathy (iNM) both feature accumulation of nemaline rods in muscle fibers. Unlike iNM, SLONM is amenable to therapy. The distinction between these disorders is therefore crucial when the diagnosis remains ambiguous after initial investigations. We sought to identify biomarkers facilitating this distinction and to investigate the pathophysiology of nemaline rod formation in these different disorders. Twenty-two muscle samples from patients affected by SLONM or iNM underwent quantitative histological analysis, laser capture microdissection for proteomic analysis of nemaline rod areas and rod-free areas, and transcriptomic analysis. In all iNM samples, nemaline rods were found in subsarcolemmal or central aggregates, whereas they were diffusely distributed within muscle fibers in most SLONM samples. In SLONM, muscle fibers harboring nemaline rods were smaller than those without rods. Necrotic fibers, increased endomysial connective tissue, and atrophic fibers filled with nemaline rods were more common in SLONM. Proteomic analysis detected differentially expressed proteins between nemaline rod areas and rod-free areas, as well as between SLONM and iNM. These differentially expressed proteins implicated immune, structural, metabolic, and cellular processes in disease pathophysiology. Notably, immunoglobulin overexpression with accumulation in nemaline rod areas was detected in SLONM. Transcriptomic analysis corroborated proteomic findings and further revealed substantial gene expression differences between SLONM and iNM. Overall, we identified unique pathological and molecular signatures associated with SLONM and iNM, suggesting distinct underlying pathophysiological mechanisms. These findings represent a step towards enhanced diagnostic tools and towards development of treatments for SLONM.

msmsEDA & msmsTests: Label-Free Differential Expression by Spectral Counts

msmsTests is an R/Bioconductor package providing functions for statistical tests in label-free LC-MS/MS data by spectral counts. These functions aim at discovering differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package. The three models admit blocking factors to control for nuisance variables. To assure a good level of reproducibility a post-test filter is available, where (1) a minimum effect size considered biologically relevant, and (2) a minimum expression of the most abundant condition, may be set. A companion package, msmsEDA, proposes functions to explore datasets based on msms spectral counts. The provided graphics help in identifying outliers, the presence of eventual batch factors, and check the effects of different normalizing strategies. This protocol illustrates the use of both packages on two examples: A purely spike-in experiment of 48 human proteins in a standard yeast cell lysate; and a cancer cell-line secretome dataset requiring a biological normalization.

Proteomic profiling of sporadic late-onset nemaline myopathy

Objective

To define the proteomic profile of sporadic late‐onset nemaline myopathy (SLONM) and explore its pathogenesis.

Methods

We performed mass spectrometry on laser‐dissected frozen muscle samples from five patients with SLONM, three of whom with an associated monoclonal protein (MP), and four controls, to determine the proteomic profile of SLONM. Furthermore, we assessed the role of the MP by evaluating the expression of the immunoglobulin light chain variable regions (IGVL).

Results

There were 294 differentially expressed proteins: 272 upregulated and 22 downregulated. Among the top 100 upregulated proteins, the most common categories were: nuclear or nucleic acid metabolism (24%), extracellular matrix and basal lamina (17%), immune response (13%), and actin dynamics (8%). Downregulated proteins consisted mostly of contractile proteins. Among upregulated proteins, there were 65 with a role related to the immune system, including eight proteins involved in major histocompatibility complex 1 (MHC1) and antigen processing, 15 in MHCII complex and phagocytosis, and 23 in B and/or T‐cell function. Among nine upregulated immunoglobulin proteins, there were two IGVL genes. However, these were also detected in SLONM cases without an MP, with no evidence of clonally dominant immunoglobulin deposition. In muscle sections from SLONM patients, nemaline rods tended to accumulate in atrophic fibers with marked rarefaction of the myofibrils. Increased MHC1 reactivity was present in fibers containing nemaline rods as well as adjacent nonatrophic fibers.

Conclusion

Our findings suggest that aberrant immune activation is present in SLONM, but do not support a direct causal relationship between the MP and SLONM.

Proteomic Profiling of the Substantia Nigra to Identify Determinants of Lewy Body Pathology and Dopaminergic Neuronal Loss

Proteinaceous aggregates containing α-synuclein protein called Lewy bodies in the substantia nigra is a hallmark of Parkinson's disease. The molecular mechanisms of Lewy body formation and associated neuronal loss remain largely unknown. To gain insights into proteins and pathways associated with Lewy body pathology, we performed quantitative profiling of the proteome. We analyzed substantia nigra tissue from 51 subjects arranged into three groups: cases with Lewy body pathology, Lewy body-negative controls with matching neuronal loss, and controls with no neuronal loss. Using a label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach, we characterized the proteome both in terms of protein abundances and peptide modifications. Statistical testing for differential abundance of the most abundant 2963 proteins, followed by pathway enrichment and Bayesian learning of the causal network structure, was performed to identify likely drivers of Lewy body formation and dopaminergic neuronal loss. The identified pathways include (1) Arp2/3 complex-mediated actin nucleation; (2) synaptic function; (3) poly(A) RNA binding; (4) basement membrane and endothelium; and (5) hydrogen peroxide metabolic process. According to the data, the endothelial/basement membrane pathway is tightly connected with both pathologies and likely to be one of the drivers of neuronal loss. The poly(A) RNA-binding proteins, including the ones relevant to other neurodegenerative disorders (e.g., TDP-43 and FUS), have a strong inverse correlation with Lewy bodies and may reflect an alternative mechanism of nigral neurodegeneration.

Bacterial DNA induces the formation of heat-resistant disease-associated proteins in human plasma

Our study demonstrated for the first time that bacterial extracellular DNA (eDNA) can change the thermal behavior of specific human plasma proteins, leading to an elevation of the heat-resistant protein fraction, as well as to de novo acquisition of heat-resistance. In fact, the majority of these proteins were not known to be heat-resistant nor do they possess any prion-like domain. Proteins found to become heat-resistant following DNA exposure were named "Tetz-proteins". Interestingly, plasma proteins that become heat-resistant following treatment with bacterial eDNA are known to be associated with cancer. In pancreatic cancer, the proportion of proteins exhibiting eDNA-induced changes in thermal behavior was found to be particularly elevated. Therefore, we analyzed the heat-resistant proteome in the plasma of healthy subjects and in patients with pancreatic cancer and found that exposure to bacterial eDNA made the proteome of healthy subjects more similar to that of cancer patients. These findings open a discussion on the possible novel role of eDNA in disease development following its interaction with specific proteins, including those involved in multifactorial diseases such as cancer.

A critical assessment of the feature selection methods used for biomarker discovery in current metaproteomics studies

Microbial community (MC) has great impact on mediating complex disease indications, biogeochemical cycling and agricultural productivities, which makes metaproteomics powerful technique for quantifying diverse and dynamic composition of proteins or peptides. The key role of biostatistical strategies in MC study is reported to be underestimated, especially the appropriate application of feature selection method (FSM) is largely ignored. Although extensive efforts have been devoted to assessing the performance of FSMs, previous studies focused only on their classification accuracy without considering their ability to correctly and comprehensively identify the spiked proteins. In this study, the performances of 14 FSMs were comprehensively assessed based on two key criteria (both sample classification and spiked protein discovery) using a variety of metaproteomics benchmarks. First, the classification accuracies of those 14 FSMs were evaluated. Then, their abilities in identifying the proteins of different spiked concentrations were assessed. Finally, seven FSMs (FC, LMEB, OPLS-DA, PLS-DA, SAM, SVM-RFE and T-Test) were identified as performing consistently superior or good under both criteria with the PLS-DA performing consistently superior. In summary, this study served as comprehensive analysis on the performances of current FSMs and could provide a valuable guideline for researchers in metaproteomics.

Reassessment of Exosome Composition

The heterogeneity of small extracellular vesicles and presence of non-vesicular extracellular matter have led to debate about contents and functional properties of exosomes. Here, we employ high-resolution density gradient fractionation and direct immunoaffinity capture to precisely characterize the RNA, DNA, and protein constituents of exosomes and other non-vesicle material. Extracellular RNA, RNA-binding proteins, and other cellular proteins are differentially expressed in exosomes and non-vesicle compartments. Argonaute 1-4, glycolytic enzymes, and cytoskeletal proteins were not detected in exosomes. We identify annexin A1 as a specific marker for microvesicles that are shed directly from the plasma membrane. We further show that small extracellular vesicles are not vehicles of active DNA release. Instead, we propose a new model for active secretion of extracellular DNA through an autophagy- and multivesicular-endosome-dependent but exosome-independent mechanism. This study demonstrates the need for a reassessment of exosome composition and offers a framework for a clearer understanding of extracellular vesicle heterogeneity.

Robust determination of differential abundance in shotgun proteomics using nonparametric statistics

Label-free shotgun mass spectrometry enables the detection of significant changes in protein abundance between different conditions. Due to often limited cohort sizes or replication, large ratios of potential protein markers to number of samples, as well as multiple null measurements pose important technical challenges to conventional parametric models. From a statistical perspective, a scenario similar to that of unlabeled proteomics is encountered in genomics when looking for differentially expressed genes. Still, the difficulty of detecting a large fraction of the true positives without a high false discovery rate is arguably greater in proteomics due to even smaller sample sizes and peptide-to-peptide variability in detectability. These constraints argue for nonparametric (or distribution-free) tests on normalized peptide values, thus minimizing the number of free parameters, as well as for measuring significance with permutation testing. We propose such a procedure with a class-based statistic, no parametric assumptions, and no parameters to select other than a nominal false discovery rate. Our method was tested on a new dataset which is available via ProteomeXchange with identifier PXD006447. The dataset was prepared using a standard proteolytic digest of a human protein mixture at 1.5-fold to 3-fold protein concentration changes and diluted into a constant background of yeast proteins. We demonstrate its superiority relative to other approaches in terms of the realized sensitivity and realized false discovery rates determined by ground truth, and recommend it for detecting differentially abundant proteins from MS data.

Plasma lipoproteome in Alzheimer's disease: a proof-of-concept study

Background

Although total plasma lipoproteome consists of proteins that have shown promises as biomarkers that can identify Alzheimer's disease (AD), effect sizes are modest. The objective of this study is to provide initial proof-of-concept that the plasma lipoproteome more likely differ between AD cases and controls when measured in individual plasma lipoprotein fractions than when measured as total in immunodepleted plasma.

Methods

We first developed a targeted proteomics method based on selected reaction monitoring (SRM) and liquid chromatography and tandem mass spectrometry for measurement of 120 tryptic peptides from 79 proteins that are commonly present in plasma lipoproteins. Then in a proof-of concept case-control study of 5 AD cases and 5 sex- and age-matched controls, we applied the targeted proteomic method and performed relatively quantification of 120 tryptic peptides in plasma lipoprotein fractions (fractionated by sequential gradient ultracentrifugation) and in immunodepleted plasma (of albumin and IgG). Unadjusted p values from two-sample t-tests and overall fold change was used to evaluate a peptide relative difference between AD cases and controls, with lower p values (< 0.05) or greater fold differences (> 1.05 or < 0.95) suggestive of greater peptide/protein differences.

Results

Within-day and between-days technical precisions (mean %CV [SD] of all SRM transitions) of the targeted proteomic method were 3.95% (2.65) and 9.31% (5.59), respectively. Between-days technical precisions (mean % CV [SD]) of the entire plasma lipoproteomic workflow including plasma lipoprotein fractionation was 27.90% (14.61). Ten tryptic peptides that belonged to 5 proteins in plasma lipoproteins had unadjusted p values < 0.05, compared to no peptides in immunodepleted plasma. Furthermore, 27, 32, 17, and 20 tryptic peptides in VLDL, IDL, LDL and HDL, demonstrated overall peptide fold differences > 1.05 or < 0.95, compared to only 6 tryptic peptides in immunodepleted plasma. The overall comparisons, therefore, suggested greater peptide/protein differences in plasma lipoproteome when measured in individual plasma lipoproteins than as total in immunodepleted plasma. Specifically, protein complement C3's peptide IHWESASLLR, had unadjusted p values of 0.00007, 0.00012, and 0.0006 and overall 1.25, 1.17, 1.14-fold changes in VLDL, IDL, and LDL, respectively. After positive False Discovery Rate (pFDR) adjustment, the complement C3 peptide IHWESASLLR in VLDL remained statistically different (adjusted p value < 0.05).

Discussion

The findings may warrant future studies to investigate plasma lipoproteome when measured in individual plasma lipoprotein fractions for AD diagnosis.

Hemolymph protein profiles of subterranean termite Reticulitermes flavipes challenged with methicillin resistant Staphylococcus aureus or Pseudomonas aeruginosa

When the subterranean termite Reticulitermes flavipes is fed heat-killed methicillin resistant Staphylococcus aureus (MRSA) or Pseudomonas aeruginosa, the termite produces proteins with antibacterial activity against the inducer pathogen in its hemolymph. We used a proteomic approach to characterize the alterations in protein profiles caused by the inducer bacterium in the hemolymph of the termite. Nano-liquid chromatography-tandem mass spectrometry analysis identified a total of 221 proteins and approximately 70% of these proteins could be associated with biological processes and molecular functions. Challenges with these human pathogens induced a total of 57 proteins (35 in MRSA-challenged, 16 in P. aeruginosa-challenged, and 6 shared by both treatments) and suppressed 13 proteins by both pathogens. Quasi-Poisson likelihood modeling with false discovery rate adjustment identified a total of 18 and 40 proteins that were differentially expressed at least 2.5-fold in response to MRSA and P. aeruginosa-challenge, respectively. We selected 7 differentially expressed proteins and verified their gene expression levels via quantitative real-time RT-PCR. Our findings provide an initial insight into a putative termite immune response against MRSA and P. aeruginosa-challenge.

Exosomal proteomic analysis reveals changes in the urinary proteome of rats with unilateral ureteral obstruction

Congenital urinary tract obstruction (UTO) is a commonly noted disorder with the potential to cause permanent loss of renal function. Due to the possibility of spontaneous resolution, postnatal management strategies require lengthy and invasive surveillance methods to monitor the status of renal function and severity of obstruction. Here, a quantitative proteome analysis of urinary exosomes from weanling rats with surgically introduced UTO identifies a number of candidate biomarkers with the potential to improve diagnostic and prognostic methods for this disease. Using gel-assisted digestion coupled to liquid chromatography/tandem mass spectrometry (LC–MS/MS), 318 proteins were identified. Relative protein quantitation by spectral counting showed 190 proteins with significant changes in abundance due to either partial or complete obstruction. Numerous proteins identified here have been shown to be similarly altered in abundance in other renal diseases that cause tubule apoptosis and interstitial fibrosis. Extrapolating the role of the proteins showing quantifiable changes in abundance here from other forms of renal disease suggests they have potential for clinical applicability as biomarkers of congenital UTO. Included in the list of identified proteins are markers of apoptosis, oxidative stress, fibrosis, inflammation, and tubular cell damage, which are commonly associated with UTO. This study therefore provides a number of candidate biomarkers that, following validation in children experiencing UTO, have the potential to improve postnatal management of this disease.

Proteomic signatures differentiating Bacillus anthracis Sterne sporulation on soil relative to laboratory media

The process of sporulation is vital for the stability and infectious cycle of Bacillus anthracis. The spore is the infectious form of the organism and therefore relevant to biodefense. While the morphological and molecular events occurring during sporulation have been well studied, the influence of growth medium and temperature on the proteins expressed in sporulated cultures is not well understood. Understanding the features of B. anthracis sporulation specific to natural vs. laboratory production will address an important question in microbial forensics. In an effort to bridge this knowledge gap, a system for sporulation on two types of agar-immobilized soils was used for comparison to cultures sporulated on two common types of solid laboratory media, and one liquid sporulation medium. The total number of proteins identified as well as their identity differed between samples generated in each medium and growth temperature, demonstrating that sporulation environment significantly impacts the protein content of the spore. In addition, a subset of proteins common in all of the soil-cultivated samples was distinct from the expression profiles in laboratory medium (and vice versa). These differences included proteins involved in thiamine and phosphate metabolism in the sporulated cultures produced on soils with a notable increase in expression of ATP binding cassette (ABC) transporters annotated to be for phosphate and antimicrobial peptides. A distinct set of ABC transporters for amino acids, sugars and oligopeptides were found in cultures produced on laboratory media as well as increases in carbon and amino acid metabolism-related proteins. These protein expression changes indicate that the sporulation environment impacts the protein profiles in specific ways that are reflected in the metabolic and membrane transporter proteins present in sporulated cultures.

DnaJ Heat Shock Protein Family B Member 9 Is a Novel Biomarker for Fibrillary GN

Fibrillary GN (FGN) is a rare primary glomerular disease. Histologic and histochemical features of FGN overlap with those of other glomerular diseases, and no unique histologic biomarkers for diagnosing FGN have been identified. We analyzed the proteomic content of glomeruli in patient biopsy specimens and detected DnaJ heat shock protein family (Hsp40) member B9 (DNAJB9) as the fourth most abundant protein in FGN glomeruli. Compared with amyloidosis glomeruli, FGN glomeruli exhibited a >6-fold overexpression of DNAJB9 protein. Sanger sequencing and protein sequence coverage maps showed that the DNAJB9 protein deposited in FGN glomeruli did not have any major sequence or structural alterations. Notably, we detected DNAJB9 in all patients with FGN but not in healthy glomeruli or in 19 types of non-FGN glomerular diseases. We also observed the codeposition of DNAJB9 and Ig-γ Overall, these findings indicate that DNAJB9 is an FGN marker with 100% sensitivity and 100% specificity. The magnitude and specificity of DNAJB9 overabundance in FGN also suggests that this protein has a role in FGN pathogenesis. With this evidence, we propose that DNAJB9 is a strong biomarker for rapid diagnosis of FGN in renal biopsy specimens.

Unravelling the biology of chromatin in health and cancer using proteomic approaches

INTRODUCTION

Chromatin remodeling complexes play important roles in the control of genome regulation in both normal and diseased states, and are therefore critical components for the regulation of epigenetic states in cells. Given the role epigenetics plays in cancer, for example, chromatin remodeling complexes are routinely targeted for therapeutic intervention. Areas covered: Protein mass spectrometry and proteomics are powerful technologies used to study and understand chromatin remodeling. While impressive progress has been made in this area, there remain significant challenges in the application of proteomic technologies to the study of chromatin remodeling. As parts of large multi-subunit complexes that can be heavily modified with dynamic post-translational modifications, challenges in the study of chromatin remodeling complexes include defining the content, determining the regulation, and studying the dynamics of the complexes under different cellular states. Expert commentary: Impwortant considerations in the study of chromatin remodeling complexes include the complexity of sample preparation, the choice of proteomic methods for the analysis of samples, and data analysis challenges. Continued research in these three areas promise to yield even greater insights into the biology of chromatin remodeling and epigenetics and the dynamics of these systems in human health and cancer.

A comparative intracellular proteomic profiling of Pseudomonas aeruginosa strain ASP-53 grown on pyrene or glucose as sole source of carbon and identification of some key enzymes of pyrene biodegradation pathway

Pseudomonas aeruginosa strain ASP-53, isolated from a petroleum oil-contaminated soil sample, was found to be an efficient degrader of pyrene. PCR amplification of selected hydrocarbon catabolic genes (alkB gene, which encodes for monooxygenase, and the C12O, C23O, and PAH-RHDα genes encoding for the dioxygenase enzyme) from the genomic DNA of P. aeruginosa strain ASP-53 suggested its hydrocarbon degradation potential. The GC-MS analysis demonstrated 30.1% pyrene degradation by P. aeruginosa strain ASP-53 after 144h of incubation at pH6.5, 37°C. Expressions of 115 and 196 intracellular proteins were unambiguously identified and quantitated by shotgun proteomics analysis when the isolate was grown in medium containing pyrene and glucose, respectively. The pyrene-induced uniquely expressed and up-regulated proteins in P. aeruginosa strain ASP-53 in addition to substrate (pyrene) metabolism are also likely to be associated with different cellular functions for example-related to protein folding (molecular chaperone), stress response, metabolism of carbohydrate, proteins and amino acids, and fatty acids; transport of metabolites, energy generation such as ATP synthesis, electron transport and nitrate assimilation, and other oxidation-reduction reactions. Proteomic analyses identified some important enzymes involved in pyrene degradation by P. aeruginosa ASP-53 which shows that this bacterium follows the salicylate pathway of pyrene degradation.

SIGNIFICANCE

This study is the first report on proteomic analysis of pyrene biodegradation pathway by Pseudomonas aeruginosa, isolated from a petroleum-oil contaminated soil sample. The pathway displays partial similarity with deduced pyrene degradation mechanisms of Mycobacterium vanbaalenii PYR-1. The GC-MS analysis as well as PCR amplification of hydrocarbon catabolic genes substantiated the potency of the bacterium under study to effectively degrade high molecular weight, toxic PAH such as pyrene for its filed scale bioremediation experiments. The proteomics approach (LC-MS/MS analysis) identified the differentially regulated intracellular proteins of the isolate P. aeruginosa ASP-53 when grown in pyrene medium. This study identified some important pyrene biodegradation enzymes in Pseudomonas aeruginosa ASP-53 and highlights that the bacterium follows salicylate pathway for pyrene degradation.

Probes for protein adduction in cholesterol biosynthesis disorders: Alkynyl lanosterol as a viable sterol precursor

The formation of lipid electrophile-protein adducts is associated with many disorders that involve perturbations of cellular redox status. The identities of adducted proteins and the effects of adduction on protein function are mostly unknown and an increased understanding of these factors may help to define the pathogenesis of various human disorders involving oxidative stress. 7-Dehydrocholesterol (7-DHC), the immediate biosynthetic precursor to cholesterol, is highly oxidizable and gives electrophilic oxysterols that adduct proteins readily, a sequence of events proposed to occur in Smith-Lemli-Opitz syndrome (SLOS), a human disorder resulting from an error in cholesterol biosynthesis. Alkynyl lanosterol (a-Lan) was synthesized and studied in Neuro2a cells, Dhcr7-deficient Neuro2a cells and human fibroblasts. When incubated in control Neuro2a cells and control human fibroblasts, a-Lan completed the sequence of steps involved in cholesterol biosynthesis and alkynyl-cholesterol (a-Chol) was the major product formed. In Dhcr7-deficient Neuro2a cells or fibroblasts from SLOS patients, the biosynthetic transformation was interrupted at the penultimate step and alkynyl-7-DHC (a-7-DHC) was the major product formed. When a-Lan was incubated in Dhcr7-deficient Neuro2a cells and the alkynyl tag was used to ligate a biotin group to alkyne-containing products, protein-sterol adducts were isolated and identified. In parallel experiments with a-Lan and a-7-DHC in Dhcr7-deficient Neuro2a cells, a-7-DHC was found to adduct to a larger set of proteins (799) than a-Lan (457) with most of the a-Lan protein adducts (423) being common to the larger a-7-DHC set. Of the 423 proteins found common to both experiments, those formed from a-7-DHC were more highly enriched compared to a DMSO control than were those derived from a-Lan. The 423 common proteins were ranked according to the enrichment determined for each protein in the a-Lan and a-7-DHC experiments and there was a very strong correlation of protein ranks for the adducts formed in the parallel experiments.

The airway epithelium undergoes metabolic reprogramming in individuals at high risk for lung cancer

The molecular determinants of lung cancer risk remain largely unknown. Airway epithelial cells are prone to assault by risk factors and are considered to be the primary cell type involved in the field of cancerization. To investigate risk-associated changes in the bronchial epithelium proteome that may offer new insights into the molecular pathogenesis of lung cancer, proteins were identified in the airway epithelial cells of bronchial brushing specimens from risk-stratified individuals by shotgun proteomics. Differential expression of selected proteins was validated by parallel reaction monitoring mass spectrometry in an independent set of individual bronchial brushings. We identified 2,869 proteins, of which 312 proteins demonstrated a trend in expression. Pathway analysis revealed enrichment of carbohydrate metabolic enzymes in high-risk individuals. Glucose consumption and lactate production were increased in human bronchial epithelial BEAS2B cells treated with cigarette smoke condensate for 7 months. Increased lipid biosynthetic capacity and net reductive carboxylation were revealed by metabolic flux analyses of [U-¹³C₅] glutamine in this in vitro model, suggesting profound metabolic reprogramming in the airway epithelium of high-risk individuals. These results provide a rationale for the development of potentially new chemopreventive strategies and selection of patients for surveillance programs.

Tag-Count Analysis of Large-Scale Proteomic Data

Label-free quantitative methods are advantageous in bottom-up (shotgun) proteomics because they are robust and can easily be applied to different workflows without additional cost. Both label-based and label-free approaches are routinely applied to discovery-based proteomics experiments and are widely accepted as semiquantitative. Label-free quantitation approaches are segregated into two distinct approaches: peak-abundance-based approaches and spectral counting (SpC). Peak abundance approaches like MaxLFQ, which is integrated into the MaxQuant environment, require precursor peak alignment that is computationally intensive and cannot be routinely applied to low-resolution data. Not limited by these constraints, SpC approaches simply use the number of peptide identifications corresponding to a given protein as a measurement of protein abundance. We show here that spectral counts from multidimensional proteomic data sets have a mean-dispersion relationship that can be modeled in edgeR. Furthermore, by simulating spectral counts, we show that this approach can routinely be applied to large-scale discovery proteomics data sets to determine differential protein expression.

Release of skeletal muscle peptide fragments identifies individual proteins degraded during insulin deprivation in type 1 diabetic humans and mice

Insulin regulates skeletal muscle protein degradation, but the types of proteins being degraded in vivo remain to be determined due to methodological limitations. We present a method to assess the types of skeletal muscle proteins that are degraded by extracting their degradation products as low-molecular weight (LMW) peptides from muscle samples. High-resolution mass spectrometry was used to identify the original intact proteins that generated the LMW peptides, which we validated in rodents and then applied to humans. We deprived insulin from insulin-treated streptozotocin (STZ) diabetic mice for 6 and 96 h and for 8 h in type 1 diabetic humans (T1D) for comparison with insulin-treated conditions. Protein degradation was measured using activation of autophagy and proteasome pathways, stable isotope tracers, and LMW approaches. In mice, insulin deprivation activated proteasome pathways and autophagy in muscle homogenates and isolated mitochondria. Reproducibility analysis of LMW extracts revealed that ∼80% of proteins were detected consistently. As expected, insulin deprivation increased whole body protein turnover in T1D. Individual protein degradation increased with insulin deprivation, including those involved in mitochondrial function, proteome homeostasis, nDNA support, and contractile/cytoskeleton. Individual mitochondrial proteins that generated more LMW fragment with insulin deprivation included ATP synthase subunit-γ (+0.5-fold, P = 0.007) and cytochrome c oxidase subunit 6 (+0.305-fold, P = 0.03). In conclusion, identifying LMW peptide fragments offers an approach to determine the degradation of individual proteins. Insulin deprivation increases degradation of select proteins and provides insight into the regulatory role of insulin in maintaining proteome homeostasis, especially of mitochondria.

Specificity of Protein Covalent Modification by the Electrophilic Proteasome Inhibitor Carfilzomib in Human Cells

Carfilzomib (CFZ) is a second-generation proteasome inhibitor that is Food and Drug Administration and European Commission approved for the treatment of relapsed or refractory multiple myeloma. CFZ is an epoxomicin derivative with an epoxyketone electrophilic warhead that irreversibly adducts the catalytic threonine residue of the β5 subunit of the proteasome. Although CFZ produces a highly potent, sustained inactivation of the proteasome, the electrophilic nature of the drug could potentially produce off-target protein adduction. To address this possibility, we synthesized an alkynyl analog of CFZ and investigated protein adduction by this analog in HepG2 cells. Using click chemistry coupled with streptavidin based IP and shotgun tandem mass spectrometry (MS/MS), we identified two off-target proteins, cytochrome P450 27A1 (CYP27A1) and glutathione S-transferase omega 1 (GSTO1), as targets of the alkynyl CFZ probe. We confirmed the adduction of CYP27A1 and GSTO1 by streptavidin capture and immunoblotting methodology and then site-specifically mapped the adducts with targeted MS/MS methods. Although CFZ adduction of CYP27A1 and GSTO1 in vitro decreased the activities of these enzymes, the small fraction of these proteins modified by CFZ in intact cells should limit the impact of these off-target modifications. The data support the high selectivity of CFZ for covalent modification of its therapeutic targets, despite the presence of a reactive electrophile. The approach we describe offers a generalizable method to evaluate the safety profile of covalent protein-modifying therapeutics.

A proteomic analysis of Pakistan Daboia russelii russelii venom and assessment of potency of Indian polyvalent and monovalent antivenom

To address the dearth of knowledge on the biochemical composition of Pakistan Russell's Viper (Daboia russelii russelii) venom (RVV), the venom proteome has been analyzed and several biochemical and pharmacological properties of the venom were investigated. SDS-PAGE (reduced) analysis indicated that proteins/peptides in the molecular mass range of ~56.0-105.0kDa, 31.6-51.0kDa, 15.6-30.0kDa, 9.0-14.2kDa and 5.6-7.2kDa contribute approximately 9.8%, 12.1%, 13.4%, 34.1% and 30.5%, respectively of Pakistan RVV. Proteomics analysis of gel-filtration peaks of RVV resulted in identification of 75 proteins/peptides which belong to 14 distinct snake venom protein families. Phospholipases A2 (32.8%), Kunitz type serine protease inhibitors (28.4%), and snake venom metalloproteases (21.8%) comprised the majority of Pakistan RVV proteins, while 11 additional families accounted for 6.5-0.2%. Occurrence of aminotransferase, endo-β-glycosidase, and disintegrins is reported for the first time in RVV. Several of RVV proteins/peptides share significant sequence homology across Viperidae subfamilies. Pakistan RVV was well recognized by both the polyvalent (PAV) and monovalent (MAV) antivenom manufactured in India; nonetheless, immunological cross-reactivity determined by ELISA and neutralization of pro-coagulant/anticoagulant activity of RVV and its fractions by MAV surpassed that of PAV.

BIOLOGICAL SIGNIFICANCE

The study establishes the proteome profile of the Pakistan RVV, thereby indicating the presence of diverse proteins and peptides that play a significant role in the pathophysiology of RVV bite. Further, the proteomic findings will contribute to understand the variation in venom composition owing to different geographical location and identification of pharmacologically important proteins in Pakistan RVV.

Guaifenesin stone matrix proteomics: a protocol for identifying proteins critical to stone formation

Drug-related kidney stones are a diagnostic problem, since they contain a large matrix (protein) fraction and are frequently incorrectly identified as matrix stones. A urine proteomics study patient produced a guaifenesin stone during her participation, allowing us to both correctly diagnose her disease and identify proteins critical to this drug stone-forming process. The patient provided three random midday urine samples for proteomics studies; one of which contained stone-like sediment with two distinct fractions. These solids were characterized with optical microscopy and Fourier transform infrared spectroscopy. Immunoblotting and quantitative mass spectrometry were used to quantitatively identify the proteins in urine and stone matrix. Infrared spectroscopy showed that the sediment was 60 % protein and 40 % guaifenesin and its metabolite guaiacol. Of the 156 distinct proteins identified in the proteomic studies, 49 were identified in the two stone-components with approximately 50 % of those proteins also found in this patient's urine. Many proteins observed in this drug-related stone have also been reported in proteomic matrix studies of uric acid and calcium containing stones. More importantly, nine proteins were highly enriched and highly abundant in the stone matrix and 8 were reciprocally depleted in urine, suggesting a critical role for these proteins in guaifenesin stone formation. Accurate stone analysis is critical to proper diagnosis and treatment of kidney stones. Many matrix proteins were common to all stone types, but likely not related to disease mechanism. This protocol defined a small set of proteins that were likely critical to guaifenesin stone formation based on their high enrichment and high abundance in stone matrix, and it should be applied to all stone types.

Cortactin promotes exosome secretion by controlling branched actin dynamics

Sinha et al. show that the cytoskeletal and tumor-overexpressed protein cortactin promotes secretion of exosomes from cancer cells by stabilizing dynamic cortical actin docking sites for multivesicular endosomes, suggesting a potential mechanism by which cortactin may promote tumor aggressiveness.

Exosomes are extracellular vesicles that influence cellular behavior and enhance cancer aggressiveness by carrying bioactive molecules. The mechanisms that regulate exosome secretion are poorly understood. Here, we show that the actin cytoskeletal regulatory protein cortactin promotes exosome secretion. Knockdown or overexpression of cortactin in cancer cells leads to a respective decrease or increase in exosome secretion, without altering exosome cargo content. Live-cell imaging revealed that cortactin controls both trafficking and plasma membrane docking of multivesicular late endosomes (MVEs). Regulation of exosome secretion by cortactin requires binding to the branched actin nucleating Arp2/3 complex and to actin filaments. Furthermore, cortactin, Rab27a, and coronin 1b coordinately control stability of cortical actin MVE docking sites and exosome secretion. Functionally, the addition of purified exosomes to cortactin-knockdown cells rescued defects of those cells in serum-independent growth and invasion. These data suggest a model in which cortactin promotes exosome secretion by stabilizing cortical actin-rich MVE docking sites.

Efficient Microscale Basic Reverse Phase Peptide Fractionation for Global and Targeted Proteomics

Analysis of small biological samples would benefit from an efficient microscale fractionation strategy that minimizes sample handling, transfer steps, and accompanying losses. Here we describe a microscale basic reverse phase liquid chromatographic (bRPLC) fractionation method that offers high reproducibility and efficiency for peptide mixtures from small (5-20 μg) samples. We applied our platform to detect differentially expressed proteins from lung tumor cell lines that are sensitive (11-18) and resistant (11-18R) to the tyrosine kinase inhibitor erlotinib. Label-free analyses of 5-20 μg samples yielded identifications of approximately 3,200 to 4,000 proteins with coefficients of variation of 1.9-8.9% in replicate analyses. iTRAQ analyses produced similar protein inventories. Label-free and iTRAQ analyses displayed high concordance in identifications of proteins differentially expressed in 11-18 and 11-18R cells. Micro-bRPLC fractionation of cell proteomes increased sensitivity by an average of 4.5-fold in targeted quantitation using parallel reaction monitoring for three representative receptor tyrosine kinases (EGFR, PDGFRA, and BMX), which are present at low abundance in 11-18 and 11-18R cells. These data illustrate the broad utility of micro-bRPLC fractionation for global and targeted proteomic analyses. Data are available through Proteome eXchange Accession PXD003604.

A multi-model statistical approach for proteomic spectral count quantitation

The rapid development of mass spectrometry (MS) technologies has solidified shotgun proteomics as the most powerful analytical platform for large-scale proteome interrogation. The ability to map and determine differential expression profiles of the entire proteome is the ultimate goal of shotgun proteomics. Label-free quantitation has proven to be a valid approach for discovery shotgun proteomics, especially when sample is limited. Label-free spectral count quantitation is an approach analogous to RNA sequencing whereby count data is used to determine differential expression. Here we show that statistical approaches developed to evaluate differential expression in RNA sequencing experiments can be applied to detect differential protein expression in label-free discovery proteomics. This approach, termed MultiSpec, utilizes open-source statistical platforms; namely edgeR, DESeq and baySeq, to statistically select protein candidates for further investigation. Furthermore, to remove bias associated with a single statistical approach a single ranked list of differentially expressed proteins is assembled by comparing edgeR and DESeq q-values directly with the false discovery rate (FDR) calculated by baySeq. This statistical approach is then extended when applied to spectral count data derived from multiple proteomic pipelines. The individual statistical results from multiple proteomic pipelines are integrated and cross-validated by means of collapsing protein groups.

BIOLOGICAL SIGNIFICANCE

Spectral count data from shotgun proteomics experiments is semi-quantitative and semi-random, yet a robust way to estimate protein concentration. Tag-count approaches are routinely used to analyze RNA sequencing data sets. This approach, termed MultiSpec, utilizes multiple tag-count based statistical tests to determine differential protein expression from spectral counts. The statistical results from these tag-count approaches are combined in order to reach a final MultiSpec q-value to re-rank protein candidates. This re-ranking procedure is completed to remove bias associated with a single approach in order to better understand the true proteomic differences driving the biology in question. The MultiSpec approach can be extended to multiple proteomic pipelines. In such an instance, MultiSpec statistical results are integrated by collapsing protein groups across proteomic pipelines to provide a single ranked list of differentially expressed proteins. This integration mechanism is seamlessly integrated with the statistical analysis and provides the means to cross-validate protein inferences from multiple proteomic pipelines.

Proteomics and Metabolomics Analyses to Elucidate the Desulfurization Pathway of Chelatococcus sp

Desulfurization of dibenzothiophene (DBT) and alkylated DBT derivatives present in transport fuel through specific cleavage of carbon-sulfur (C-S) bonds by a newly isolated bacterium Chelatococcus sp. is reported for the first time. Gas chromatography-mass spectrometry (GC-MS) analysis of the products of DBT degradation by Chelatococcus sp. showed the transient formation of 2-hydroxybiphenyl (2-HBP) which was subsequently converted to 2-methoxybiphenyl (2-MBP) by methylation at the hydroxyl group of 2-HBP. The relative ratio of 2-HBP and 2-MBP formed after 96 h of bacterial growth was determined at 4:1 suggesting partial conversion of 2-HBP or rapid degradation of 2-MBP. Nevertheless, the enzyme involved in this conversion process remains to be identified. This production of 2-MBP rather than 2-HBP from DBT desulfurization has a significant metabolic advantage for enhancing the growth and sulfur utilization from DBT by Chelatococcus sp. and it also reduces the environmental pollution by 2-HBP. Furthermore, desulfurization of DBT derivatives such as 4-M-DBT and 4, 6-DM-DBT by Chelatococcus sp. resulted in formation of 2-hydroxy-3-methyl-biphenyl and 2-hydroxy -3, 3/- dimethyl-biphenyl, respectively as end product. The GC and X-ray fluorescence studies revealed that Chelatococcus sp. after 24 h of treatment at 37°C reduced the total sulfur content of diesel fuel by 12% by per gram resting cells, without compromising the quality of fuel. The LC-MS/MS analysis of tryptic digested intracellular proteins of Chelatococcus sp. when grown in DBT demonstrated the biosynthesis of 4S pathway desulfurizing enzymes viz. monoxygenases (DszC, DszA), desulfinase (DszB), and an NADH-dependent flavin reductase (DszD). Besides, several other intracellular proteins of Chelatococcus sp. having diverse biological functions were also identified by LC-MS/MS analysis. Many of these enzymes are directly involved with desulfurization process whereas the other enzymes/proteins support growth of bacteria at an expense of DBT. These combined results suggest that Chelatococcus sp. prefers sulfur-specific extended 4S pathway for deep-desulphurization which may have an advantage for its intended future application as a promising biodesulfurizing agent.

Thousand and one ways to quantify and compare protein abundances in label-free bottom-up proteomics

How to process and analyze MS data to quantify and statistically compare protein abundances in bottom-up proteomics has been an open debate for nearly fifteen years. Two main approaches are generally used: the first is based on spectral data generated during the process of identification (e.g. peptide counting, spectral counting), while the second makes use of extracted ion currents to quantify chromatographic peaks and infer protein abundances based on peptide quantification. These two approaches actually refer to multiple methods which have been developed during the last decade, but were submitted to deep evaluations only recently. In this paper, we compiled these different methods as exhaustively as possible. We also summarized the way they address the different problems raised by bottom-up protein quantification such as normalization, the presence of shared peptides, unequal peptide measurability and missing data. This article is part of a Special Issue entitled: Plant Proteomics--a bridge between fundamental processes and crop production, edited by Dr. Hans-Peter Mock.

Integrative subcellular proteomic analysis allows accurate prediction of human disease-causing genes

Proteomic profiling on subcellular fractions provides invaluable information regarding both protein abundance and subcellular localization. When integrated with other data sets, it can greatly enhance our ability to predict gene function genome-wide. In this study, we performed a comprehensive proteomic analysis on the light-sensing compartment of photoreceptors called the outer segment (OS). By comparing with the protein profile obtained from the retina tissue depleted of OS, an enrichment score for each protein is calculated to quantify protein subcellular localization, and 84% accuracy is achieved compared with experimental data. By integrating the protein OS enrichment score, the protein abundance, and the retina transcriptome, the probability of a gene playing an essential function in photoreceptor cells is derived with high specificity and sensitivity. As a result, a list of genes that will likely result in human retinal disease when mutated was identified and validated by previous literature and/or animal model studies. Therefore, this new methodology demonstrates the synergy of combining subcellular fractionation proteomics with other omics data sets and is generally applicable to other tissues and diseases.

Protein networks in induced sputum from smokers and COPD patients

RATIONALE

Subtypes of cigarette smoke-induced disease affect different lung structures and may have distinct pathophysiological mechanisms.

OBJECTIVE

To determine if proteomic classification of the cellular and vascular origins of sputum proteins can characterize these mechanisms and phenotypes.

SUBJECTS AND METHODS

Individual sputum specimens from lifelong nonsmokers (n=7) and smokers with normal lung function (n=13), mucous hypersecretion with normal lung function (n=11), obstructed airflow without emphysema (n=15), and obstruction plus emphysema (n=10) were assessed with mass spectrometry. Data reduction, logarithmic transformation of spectral counts, and Cytoscape network-interaction analysis were performed. The original 203 proteins were reduced to the most informative 50. Sources were secretory dimeric IgA, submucosal gland serous and mucous cells, goblet and other epithelial cells, and vascular permeability.

RESULTS

Epithelial proteins discriminated nonsmokers from smokers. Mucin 5AC was elevated in healthy smokers and chronic bronchitis, suggesting a continuum with the severity of hypersecretion determined by mechanisms of goblet-cell hyperplasia. Obstructed airflow was correlated with glandular proteins and lower levels of Ig joining chain compared to other groups. Emphysema subjects' sputum was unique, with high plasma proteins and components of neutrophil extracellular traps, such as histones and defensins. In contrast, defensins were correlated with epithelial proteins in all other groups. Protein-network interactions were unique to each group.

CONCLUSION

The proteomes were interpreted as complex "biosignatures" that suggest distinct pathophysiological mechanisms for mucin 5AC hypersecretion, airflow obstruction, and inflammatory emphysema phenotypes. Proteomic phenotyping may improve genotyping studies by selecting more homogeneous study groups. Each phenotype may require its own mechanistically based diagnostic, risk-assessment, drug- and other treatment algorithms.

Activation of the Endogenous Renin-Angiotensin-Aldosterone System or Aldosterone Administration Increases Urinary Exosomal Sodium Channel Excretion

Urinary exosomes secreted by multiple cell types in the kidney may participate in intercellular signaling and provide an enriched source of kidney-specific proteins for biomarker discovery. Factors that alter the exosomal protein content remain unknown. To determine whether endogenous and exogenous hormones modify urinary exosomal protein content, we analyzed samples from 14 mildly hypertensive patients in a crossover study during a high-sodium (HS, 160 mmol/d) diet and low-sodium (LS, 20 mmol/d) diet to activate the endogenous renin-angiotensin-aldosterone system. We further analyzed selected exosomal protein content in a separate cohort of healthy persons receiving intravenous aldosterone (0.7 μg/kg per hour for 10 hours) versus vehicle infusion. The LS diet increased plasma renin activity and aldosterone concentration, whereas aldosterone infusion increased only aldosterone concentration. Protein analysis of paired urine exosome samples by liquid chromatography-tandem mass spectrometry-based multidimensional protein identification technology detected 2775 unique proteins, of which 316 exhibited significantly altered abundance during LS diet. Sodium chloride cotransporter (NCC) and α- and γ-epithelial sodium channel (ENaC) subunits from the discovery set were verified using targeted multiple reaction monitoring mass spectrometry quantified with isotope-labeled peptide standards. Dietary sodium restriction or acute aldosterone infusion similarly increased urine exosomal γENaC[112-122] peptide concentrations nearly 20-fold, which correlated with plasma aldosterone concentration and urinary Na/K ratio. Urine exosomal NCC and αENaC concentrations were relatively unchanged during these interventions. We conclude that urinary exosome content is altered by renin-angiotensin-aldosterone system activation. Urinary measurement of exosomal γENaC[112-122] concentration may provide a useful biomarker of ENaC activation in future clinical studies.

Activating PIK3CA Mutations Induce an Epidermal Growth Factor Receptor (EGFR)/Extracellular Signal-regulated Kinase (ERK) Paracrine Signaling Axis in Basal-like Breast Cancer

Mutations in PIK3CA, the gene encoding the p110α catalytic subunit of phosphoinositide 3-kinase (PI3K) have been shown to transform human mammary epithelial cells (MECs). These mutations are present in all breast cancer subtypes, including basal-like breast cancer (BLBC). Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified 72 protein expression changes in human basal-like MECs with knock-in E545K or H1047R PIK3CA mutations versus isogenic MECs with wild-type PIK3CA. Several of these were secreted proteins, cell surface receptors or ECM interacting molecules and were required for growth of PIK3CA mutant cells as well as adjacent cells with wild-type PIK3CA. The proteins identified by MS were enriched among human BLBC cell lines and pointed to a PI3K-dependent amphiregulin/EGFR/ERK signaling axis that is activated in BLBC. Proteins induced by PIK3CA mutations correlated with EGFR signaling and reduced relapse-free survival in BLBC. Treatment with EGFR inhibitors reduced growth of PIK3CA mutant BLBC cell lines and murine mammary tumors driven by a PIK3CA mutant transgene, all together suggesting that PIK3CA mutations promote tumor growth in part by inducing protein changes that activate EGFR.

Comparative Proteomics of Human and Macaque Milk Reveals Species-Specific Nutrition during Postnatal Development

Milk has been well established as the optimal nutrition source for infants, yet there is still much to be understood about its molecular composition. Therefore, our objective was to develop and compare comprehensive milk proteomes for human and rhesus macaques to highlight differences in neonatal nutrition. We developed a milk proteomics technique that overcomes previous technical barriers including pervasive post-translational modifications and limited sample volume. We identified 1606 and 518 proteins in human and macaque milk, respectively. During analysis of detected protein orthologs, we identified 88 differentially abundant proteins. Of these, 93% exhibited increased abundance in human milk relative to macaque and include lactoferrin, polymeric immunoglobulin receptor, alpha-1 antichymotrypsin, vitamin D-binding protein, and haptocorrin. Furthermore, proteins more abundant in human milk compared with macaque are associated with development of the gastrointestinal tract, the immune system, and the brain. Overall, our novel proteomics method reveals the first comprehensive macaque milk proteome and 524 newly identified human milk proteins. The differentially abundant proteins observed are consistent with the perspective that human infants, compared with nonhuman primates, are born at a slightly earlier stage of somatic development and require additional support through higher quantities of specific proteins to nurture human infant maturation.

Proteomics of Colwellia psychrerythraea at subzero temperatures - a life with limited movement, flexible membranes and vital DNA repair

The mechanisms that allow psychrophilic bacteria to remain metabolically active at subzero temperatures result from form and function of their proteins. We present first proteomic evidence of physiological changes of the marine psychrophile Colwellia psychrerythraea 34H (Cp34H) after exposure to subzero temperatures (-1, and -10°C in ice) through 8 weeks. Protein abundance was compared between different treatments to understand the effects of temperature and time, independently and jointly, within cells transitioning to, and being maintained in ice. Parallel [3H]-leucine and [3H]-thymidine incubations indicated active protein and DNA synthesis to -10°C. Mass spectrometry-based proteomics identified 1763 proteins across four experimental treatments. Proteins involved in osmolyte regulation and polymer secretion were found constitutively present across all treatments, suggesting that they are required for metabolic success below 0°C. Differentially abundant protein groups indicated a reallocation of resources from DNA binding to DNA repair and from motility to chemo-taxis and sensing. Changes to iron and nitrogen metabolism, cellular membrane structures, and protein synthesis and folding were also revealed. By elucidating vital strategies during life in ice, this study provides novel insight into the extensive molecular adaptations that occur in cold-adapted marine organisms to sustain cellular function in their habitat.

Effects of bacterial inactivation methods on downstream proteomic analysis

Inactivation of pathogenic microbial samples is often necessary for the protection of researchers and to comply with local and federal regulations. By its nature, biological inactivation causes changes to microbial samples, potentially affecting observed experimental results. While inactivation-induced damage to materials such as DNA has been evaluated, the effect of various inactivation strategies on proteomic data, to our knowledge, has not been discussed. To this end, we inactivated samples of Yersinia pestis and Escherichia coli by autoclave, ethanol, or irradiation treatment to determine how inactivation changes liquid chromatography-tandem mass spectrometry data quality as well as apparent protein content of cells. Proteomic datasets obtained from aliquots of samples inactivated by different methods were highly similar, with Pearson correlation coefficients ranging from 0.822 to 0.985 and 0.816 to 0.985 for E. coli and Y. pestis, respectively, suggesting that inactivation had only slight impacts on the set of proteins identified. In addition, spectral quality metrics such as distributions of various database search algorithm scores remained constant across inactivation methods, indicating that inactivation does not appreciably degrade spectral quality. Though overall changes resulting from inactivation were small, there were detectable trends. For example, one-sided Fischer exact tests determined that periplasmic proteins decrease in observed abundance after sample inactivation by autoclaving (α=1.71×10(-2) for E. coli, α=4.97×10(-4) for Y. pestis) and irradiation (α=9.43×10(-7) for E. coli, α=1.21×10(-5) for Y. pestis) when compared to controls that were not inactivated. Based on our data, if sample inactivation is necessary, we recommend inactivation with ethanol treatment with secondary preference given to irradiation.

Biological network module-based model for the analysis of differential expression in shotgun proteomics

Protein differential expression analysis plays an important role in the understanding of molecular mechanisms as well as the pathogenesis of complex diseases. With the rapid development of mass spectrometry, shotgun proteomics using spectral counts has become a prevailing method for the quantitative analysis of complex protein mixtures. Existing methods in differential proteomics expression typically carry out analysis at the single-protein level. However, it is well-known that proteins interact with each other when they function in biological processes. In this study, focusing on biological network modules, we proposed a negative binomial generalized linear model for differential expression analysis of spectral count data in shotgun proteomics. In order to show the efficacy of the model in protein expression analysis at the level of protein modules, we conducted two simulation studies using synthetic data sets generated from theoretical distribution of count data and a real data set with shuffled counts. Then, we applied our method to a colorectal cancer data set and a nonsmall cell lung cancer data set. When compared with single-protein analysis methods, the results showed that module-based statistical model which takes account of the interactions among proteins led to more effective identification of subtle but coordinated changes at the systems level.

A two-stage spin cartridge for integrated protein precipitation, digestion and SDS removal in a comparative bottom-up proteomics workflow

Protein precipitation with organic solvent is an effective means of depleting contaminants such as sodium dodecyl sulfate (SDS), while maintaining high analyte recovery. Here, we report the use of a disposable two-stage spin cartridge to facilitate isolation of the precipitated protein, with subsequent enzyme digestion and peptide cleanup in the cartridge. An upper filtration cartridge retains over 95% of the protein (10 μg BSA), with 99.75% detergent depleted from a sample initially containing 2% SDS. Following precipitation, a plug attached to the base of the filtration cartridge retains the solution to enable tryptic digestion in the vial, while a solid phase extraction cartridge attached to the base of the filter facilitates peptide cleanup post-digestion. A GELFrEE fractionated Escherichia coli proteome extract processed with the spin cartridge yields similar protein identifications compared to controls (226 vs 216 for control), and with an increased number of unique peptides (1753 vs 1554 for control). The device is applied to proteome characterization of rat kidneys experiencing a surgically induced ureteral tract obstruction, revealing several statistically altered proteins, consistent with the morphology and expected pathophysiology of the disease.

BIOLOGICAL SIGNIFICANCE

Conventionally, protein precipitation involves extended centrifugation to pellet the sample, with careful pipetting to remove the supernatant without disturbing the pellet. The method is not only time consuming but is highly subject to the skill of the individual, particularly at lower protein concentrations where the pellet may not be visible. As such, protein precipitation is often overlooked in proteomics, favoring column-based approaches to concentrate or purify samples. Here, all aspects of sample manipulation are integrated into a simple disposable cartridge. The device enables SDS depletion, sample preconcentration, resolubilization, derivatization, digestion, and peptide cleanup in a highly repeatable and easily multiplexed format. The device is ideally suited for comparative proteome studies. Antenatal hydronephrosis is a congenital disorder affecting 1-5% of all pregnancies, and can require surgical intervention to avoid loss of renal function. Using our device, we investigated the impact of hydronephrosis on the kidneys in a surgically induced animal model of the disease. Proteome analysis points to decreased metabolic activity in the obstructed kidney, with upregulation of proteins involved in cytoskeletal organization. This article is part of a Special Issue entitled: Protein dynamics in health and disease. Guest Editors: Pierre Thibault and Anne-Claude Gingras.

Shotgun proteomics: identification of unique protein profiles of apoptotic bodies from biliary epithelial cells

Shotgun proteomics is a powerful analytic method to characterize complex protein mixtures in combination with multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). We used this platform for proteomic characterization of apoptotic bodies in an effort to define the complex protein mixtures found in primary cultures of human intrahepatic biliary epithelial cells (HiBEC), human renal proximal tubular epithelial cells, human bronchial epithelial cells, isolated intrahepatic biliary epithelial cells from explanted primary biliary cirrhosis (PBC), and control liver using a total of 24 individual samples. Further, as additional controls and for purposes of comparison, proteomic signatures were also obtained from intact cells and apoptotic bodies. The data obtained from LC-MS/MS, combined with database searches and protein assembly algorithms, allowed us to address significant differences in protein spectral counts and identify unique pathways that may be a component of the induction of the signature inflammatory cytokine response against BECs, including the Notch signaling pathway, interleukin (IL)8, IL6, CXCR2, and integrin signaling. Indeed, there are 11 proteins that localize specifically to apoptotic bodies of HiBEC and eight proteins that were specifically absent in HiBEC apoptotic bodies.

CONCLUSION

Proteomic analysis of BECs from PBC liver compared to normal liver are significantly different, suggesting that an immunological attack affects the repertoire of proteins expressed and that such cells should be thought of as living in an environment undergoing continuous selection secondary to an innate and adaptive immune response, reflecting an almost "Darwinian" bias.

A metabonomic study of cardioprotection of ginsenosides, schizandrin, and ophiopogonin D against acute myocardial infarction in rats

Background

Metabonomics is a useful tool for studying mechanisms of drug treatment using systematic metabolite profiles. Ginsenosides Rg1 and Rb1, ophiopogonin D, and schizandrin are the main bioactive components of a traditional Chinese formula (Sheng-Mai San) widely used for the treatment of coronary heart disease. It remains unknown the effect of individual bioactive component and how the multi-components in combination affect the treating acute myocardial infarction (AMI).

Methods

Rats were divided into 7 groups and dosed consecutively for 7 days with mono and combined-therapy administrations. Serum samples were analyzed by proton nuclear magnetic resonance (¹H NMR) spectroscopy. Partial least squares discriminate analysis (PLS-DA) was employed to distinguish the metabolic profile of rats in different groups and identify potential biomarkers.

Results

Score plots of PLS-DA exhibited that combined-therapy groups were significantly different from AMI group, whereas no differences were observed for mono-therapy groups. We found that AMI caused comprehensive metabolic changes involving stimulation of glycolysis, suppression of fatty acid oxidation, together with disturbed metabolism of arachidonic acid, linoleate, leukotriene, glycerophospholipid, phosphatidylinositol phosphate, and some amino acids. β-hydroxybutyrate, cholines and glucose were regulated by mono-therapy of schizandrin and ginsenosides respectively. Besides these metabolites, combined-therapy ameliorated more of the AMI-induced metabolic changes including glycerol, and O-acetyl glycoprotein. A remarkable reduction of lactate suggested the therapeutic effect of combined-therapy through improving myocardial energy metabolism.

Conclusions

This study provided novel metabonomic insights on the mechanism of synergistic cardioprotection of combined-therapy with ginsenosides, schizandrin, and ophiopogonin D, and demonstrated the potential of discovering new drugs by combining bioactive components from traditional Chinese formula.

Electronic supplementary material

The online version of this article (doi:10.1186/1472-6882-14-350) contains supplementary material, which is available to authorized users.

Proteogenomic characterization of human colon and rectal cancer

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Enhancing the Biological Relevance of Secretome-Based Proteomics by Linking Tumor Cell Proliferation and Protein Secretion

Secretome profiling has become a methodology of choice for the identification of tumor biomarkers. We hypothesized that due to the dynamic nature of secretomes cellular perturbations could affect their composition but also change the global amount of protein secreted per cell. We confirmed our hypothesis by measuring the levels of secreted proteins taking into account the amount of proteome produced per cell. Then, we established a correlation between cell proliferation and protein secretion that explained the observed changes in global protein secretion. Next, we implemented a normalization correcting the statistical results of secretome studies by the global protein secretion of cells into a generalized linear model (GLM). The application of the normalization to two biological perturbations on tumor cells resulted in drastic changes in the list of statistically significant proteins. Furthermore, we found that known epithelial-to-mesenchymal transition (EMT) effectors were only statistically significant when the normalization was applied. Therefore, the normalization proposed here increases the sensitivity of statistical tests by increasing the number of true-positives. From an oncology perspective, the correlation between protein secretion and cellular proliferation suggests that slow-growing tumors could have high-protein secretion rates and consequently contribute strongly to tumor paracrine signaling.

Quantitative proteomics in cardiovascular research: global and targeted strategies

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here, we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation.

Analysis of surface-exposed outer membrane proteins in Helicobacter pylori

More than 50 Helicobacter pylori genes are predicted to encode outer membrane proteins (OMPs), but there has been relatively little experimental investigation of the H. pylori cell surface proteome. In this study, we used selective biotinylation to label proteins localized to the surface of H. pylori, along with differential detergent extraction procedures to isolate proteins localized to the outer membrane. Proteins that met multiple criteria for surface-exposed outer membrane localization included known adhesins, as well as Cag proteins required for activity of the cag type IV secretion system, putative lipoproteins, and other proteins not previously recognized as cell surface components. We identified sites of nontryptic cleavage consistent with signal sequence cleavage, as well as C-terminal motifs that may be important for protein localization. A subset of surface-exposed proteins were highly susceptible to proteolysis when intact bacteria were treated with proteinase K. Most Hop and Hom OMPs were susceptible to proteolysis, whereas Hor and Hof proteins were relatively resistant. Most of the protease-susceptible OMPs contain a large protease-susceptible extracellular domain exported beyond the outer membrane and a protease-resistant domain at the C terminus with a predicted β-barrel structure. These features suggest that, similar to the secretion of the VacA passenger domain, the N-terminal domains of protease-susceptible OMPs are exported through an autotransporter pathway. Collectively, these results provide new insights into the repertoire of surface-exposed H. pylori proteins that may mediate bacterium-host interactions, as well as the cell surface topology of these proteins.

Towards an animal model of ovarian cancer: cataloging chicken blood proteins using combinatorial peptide ligand libraries coupled with shotgun proteomic analysis for translational research

Epithelial ovarian cancer is the most deadly gynecological cancer around the world, with high morbidity in industrialized countries. Early diagnosis is key in reducing its morbidity rate. Yet, robust biomarkers, diagnostics, and animal models are still limited for ovarian cancer. This calls for broader omics and systems science oriented diagnostics strategies. In this vein, the domestic chicken has been used as an ovarian cancer animal model, owing to its high rate of developing spontaneous epithelial ovarian tumors. Chicken blood has thus been considered a surrogate reservoir from which cancer biomarkers can be identified. However, the presence of highly abundant proteins in chicken blood has compromised the applicability of proteomics tools to study chicken blood owing to a lack of immunodepletion methods. Here, we demonstrate that a combinatorial peptide ligand library (CPLL) can efficiently remove highly abundant proteins from chicken blood samples, consequently doubling the number of identified proteins. Using an integrated CPLL-1DGE-LC-MSMS workflow, we identified a catalog of 264 unique proteins. Functional analyses further suggested that most proteins were coagulation and complement factors, blood transport and binding proteins, immune- and defense-related proteins, proteases, protease inhibitors, cellular enzymes, or cell structure and adhesion proteins. Semiquantitative spectral counting analysis identified 10 potential biomarkers from the present chicken ovarian cancer model. Additionally, many human homologs of chicken blood proteins we have identified have been independently suggested as diagnostic biomarkers for ovarian cancer, further triangulating our novel observations reported here. In conclusion, the CPLL-assisted proteomic workflow using the chicken ovarian cancer model provides a feasible platform for translational research to identify ovarian cancer biomarkers and understand ovarian cancer biology. To the best of our knowledge, we report here the most comprehensive survey of the chicken blood proteome to date.