Showing papers in "Journal of Proteome Research in 2015"

Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses

Abstract: Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological information is however very scarce in the literature and in metabolomics databases so far. Here we studied the influence of age, body mass index (BMI), and gender on metabolite concentrations in a large cohort of 183 adults by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). We implemented a comprehensive statistical workflow for univariate hypothesis testing and modeling by orthogonal partial least-squares (OPLS), which we made available to the metabolomics community within the online Workflow4Metabolomics.org resource. We found 108 urine metabolites displaying concentration variations with either age, BMI, or gender, by integrating the results from univariate p-values and multivariate variable importance in projection (VIP). Several metabolite clusters were further evidenced by correlation analysis, and they allowed stratification of the cohort. In conclusion, our study highlights the impact of gender and age on the urinary metabolome, and thus it indicates that these factors should be taken into account for the design of metabolomics studies.

The CPTAC Data Portal: A Resource for Cancer Proteomics Research.

Abstract: The Clinical Proteomic Tumor Analysis Consortium (CPTAC), under the auspices of the National Cancer Institute’s Office of Cancer Clinical Proteomics Research, is a comprehensive and coordinated effort to accelerate the understanding of the molecular basis of cancer through the application of proteomic technologies and workflows to clinical tumor samples with characterized genomic and transcript profiles. The consortium analyzes cancer biospecimens using mass spectrometry, identifying and quantifying the constituent proteins and characterizing each tumor sample’s proteome. Mass spectrometry enables highly specific identification of proteins and their isoforms, accurate relative quantitation of protein abundance in contrasting biospecimens, and localization of post-translational protein modifications, such as phosphorylation, on a protein’s sequence. The combination of proteomics, transcriptomics, and genomics data from the same clinical tumor samples provides an unprecedented opportunity for tumor proteoge...

Parallel Accumulation–Serial Fragmentation (PASEF): Multiplying Sequencing Speed and Sensitivity by Synchronized Scans in a Trapped Ion Mobility Device

Abstract: In liquid chromatography-mass spectrometry (LC-MS)-based proteomics, many precursors elute from the column simultaneously. In data-dependent analyses, these precursors are fragmented one at a time, whereas the others are discarded entirely. Here we employ trapped ion mobility spectrometry (TIMS) on an orthogonal quadrupole time-of-flight (QTOF) mass spectrometer to remove this limitation. In TIMS, all precursor ions are accumulated in parallel and released sequentially as a function of their ion mobility. Instead of selecting a single precursor mass with the quadrupole mass filter, we here implement synchronized scans in which the quadrupole is mass positioned with sub-millisecond switching times at the m/z values of appropriate precursors, such as those derived from a topN precursor list. We demonstrate serial selection and fragmentation of multiple precursors in single 50 ms TIMS scans. Parallel accumulation-serial fragmentation (PASEF) enables hundreds of MS/MS events per second at full sensitivity. Modeling the effect of such synchronized scans for shotgun proteomics, we estimate that about a 10-fold gain in sequencing speed should be achievable by PASEF without a decrease in sensitivity.

Review, Evaluation, and Discussion of the Challenges of Missing Value Imputation for Mass Spectrometry-Based Label-Free Global Proteomics

Abstract: In this review, we apply selected imputation strategies to label-free liquid chromatography–mass spectrometry (LC–MS) proteomics datasets to evaluate the accuracy with respect to metrics of variance and classification. We evaluate several commonly used imputation approaches for individual merits and discuss the caveats of each approach with respect to the example LC–MS proteomics data. In general, local similarity-based approaches, such as the regularized expectation maximization and least-squares adaptive algorithms, yield the best overall performances with respect to metrics of accuracy and robustness. However, no single algorithm consistently outperforms the remaining approaches, and in some cases, performing classification without imputation sometimes yielded the most accurate classification. Thus, because of the complex mechanisms of missing data in proteomics, which also vary from peptide to protein, no individual method is a single solution for imputation. On the basis of the observations in this r...

Mass-spectrometry-based molecular characterization of extracellular vesicles: lipidomics and proteomics.

Abstract: This review discusses extracellular vesicles (EVs), which are submicron-scale, anuclear, phospholipid bilayer membrane enclosed vesicles that contain lipids, metabolites, proteins, and RNA (micro and messenger). They are shed from many, if not all, cell types and are present in biological fluids and conditioned cell culture media. The term EV, as coined by the International Society of Extracellular Vesicles (ISEV), encompasses exosomes (30-100 nm in diameter), microparticles (100-1000 nm), apoptotic blebs, and other EV subsets. EVs have been implicated in cell-cell communication, coagulation, inflammation, immune response modulation, and disease progression. Multiple studies report that EV secretion from disease-affected cells contributes to disease progression, e.g., tumor niche formation and cancer metastasis. EVs are attractive sources of biomarkers due to their biological relevance and relatively noninvasive accessibility from a range of physiological fluids. This review is focused on the molecular profiling of the protein and lipid constituents of EVs, with emphasis on mass-spectrometry-based "omic" analytical techniques. The challenges in the purification and molecular characterization of EVs, including contamination of isolates and limitations in sample quantities, are discussed along with possible solutions. Finally, the review discusses the limited but growing investigation of post-translational modifications of EV proteins and potential strategies for future in-depth molecular characterization of EVs.

Human milk glycomics and gut microbial genomics in infant feces show a correlation between human milk oligosaccharides and gut microbiota: a proof-of-concept study.

Abstract: Human milk oligosaccharides (HMOs) play a key role in shaping and maintaining a healthy infant gut microbiota. This article demonstrates the potential of combining recent advances in glycomics and genomics to correlate abundances of fecal microbes and fecal HMOs. Serial fecal specimens from two healthy breast-fed infants were analyzed by bacterial DNA sequencing to characterize the microbiota and by mass spectrometry to determine abundances of specific HMOs that passed through the intestinal tract without being consumed by the luminal bacteria. In both infants, the fecal bacterial population shifted from non-HMO-consuming microbes to HMO-consuming bacteria during the first few weeks of life. An initial rise in fecal HMOs corresponded with bacterial populations composed primarily of non-HMO-consuming Enterobacteriaceae and Staphylococcaeae. This was followed by decreases in fecal HMOs as the proportion of HMO-consuming Bacteroidaceae and Bifidobacteriaceae increased. Analysis of HMO structures with isomer differentiation revealed that HMO consumption is highly structure-specific, with unique isomers being consumed and others passing through the gut unaltered. These results represent a proof-of-concept and are consistent with the highly selective, prebiotic effect of HMOs in shaping the gut microbiota in the first weeks of life. The analysis of selective fecal bacterial substrates as a measure of alterations in the gut microbiota may be a potential marker of dysbiosis.

Senescent human fibroblasts show increased glycolysis and redox homeostasis with extracellular metabolomes that overlap with those of irreparable DNA damage, aging, and disease.

Abstract: Cellular senescence can modulate various pathologies and is associated with irreparable DNA double-strand breaks (IrrDSBs). Extracellular senescence metabolomes (ESMs) were generated from fibroblasts rendered senescent by proliferative exhaustion (PEsen) or 20 Gy of γ rays (IrrDSBsen) and compared with those of young proliferating cells, confluent cells, quiescent cells, and cells exposed to repairable levels of DNA damage to identify novel noninvasive markers of senescent cells. ESMs of PEsen and IrrDSBsen overlapped and showed increased levels of citrate, molecules involved in oxidative stress, a sterol, monohydroxylipids, tryptophan metabolism, phospholipid, and nucleotide catabolism, as well as reduced levels of dipeptides containing branched chain amino acids. The ESM overlaps with the aging and disease body fluid metabolomes, supporting their utility in the noninvasive detection of human senescent cells in vivo and by implication the detection of a variety of human pathologies. Intracellular metabol...

Third-generation electrokinetically pumped sheath-flow nanospray interface with improved stability and sensitivity for automated capillary zone electrophoresis-mass spectrometry analysis of complex proteome digests.

Abstract: We have reported a set of electrokinetically pumped sheath flow nanoelectrospray interfaces to couple capillary zone electrophoresis with mass spectrometry. A separation capillary is threaded through a cross into a glass emitter. A side arm provides fluidic contact with a sheath buffer reservoir that is connected to a power supply. The potential applied to the sheath buffer drives electro-osmosis in the emitter to pump the sheath fluid at nanoliter per minute rates. Our first-generation interface placed a flat-tipped capillary in the emitter. Sensitivity was inversely related to orifice size and to the distance from the capillary tip to the emitter orifice. A second-generation interface used a capillary with an etched tip that allowed the capillary exit to approach within a few hundred micrometers of the emitter orifice, resulting in a significant increase in sensitivity. In both the first- and second-generation interfaces, the emitter diameter was typically 8 μm; these narrow orifices were susceptible to...

Kojak: efficient analysis of chemically cross-linked protein complexes.

Abstract: Protein chemical cross-linking and mass spectrometry enable the analysis of protein–protein interactions and protein topologies; however, complicated cross-linked peptide spectra require specialized algorithms to identify interacting sites. The Kojak cross-linking software application is a new, efficient approach to identify cross-linked peptides, enabling large-scale analysis of protein–protein interactions by chemical cross-linking techniques. The algorithm integrates spectral processing and scoring schemes adopted from traditional database search algorithms and can identify cross-linked peptides using many different chemical cross-linkers with or without heavy isotope labels. Kojak was used to analyze both novel and existing data sets and was compared to existing cross-linking algorithms. The algorithm provided increased cross-link identifications over existing algorithms and, equally importantly, the results in a fraction of computational time. The Kojak algorithm is open-source, cross-platform, and f...

The Use of Variable Q1 Isolation Windows Improves Selectivity in LC–SWATH–MS Acquisition

Abstract: As tryptic peptides and metabolites are not equally distributed along the mass range, the probability of cross fragment ion interference is higher in certain windows when fixed Q1 SWATH windows are applied. We evaluated the benefits of utilizing variable Q1 SWATH windows with regards to selectivity improvement. Variable windows based on equalizing the distribution of either the precursor ion population (PIP) or the total ion current (TIC) within each window were generated by an in-house software, swathTUNER. These two variable Q1 SWATH window strategies outperformed, with respect to quantification and identification, the basic approach using a fixed window width (FIX) for proteomic profiling of human monocyte-derived dendritic cells (MDDCs). Thus, 13.8 and 8.4% additional peptide precursors, which resulted in 13.1 and 10.0% more proteins, were confidently identified by SWATH using the strategy PIP and TIC, respectively, in the MDDC proteomic sample. On the basis of the spectral library purity score, some improvement warranted by variable Q1 windows was also observed, albeit to a lesser extent, in the metabolomic profiling of human urine. We show that the novel concept of "scheduled SWATH" proposed here, which incorporates (i) variable isolation windows and (ii) precursor retention time segmentation further improves both peptide and metabolite identifications.

The MetaProteomeAnalyzer: A Powerful Open-Source Software Suite for Metaproteomics Data Analysis and Interpretation

Abstract: The enormous challenges of mass spectrometry-based metaproteomics are primarily related to the analysis and interpretation of the acquired data. This includes reliable identification of mass spectra and the meaningful integration of taxonomic and functional meta-information from samples containing hundreds of unknown species. To ease these difficulties, we developed a dedicated software suite, the MetaProteomeAnalyzer, an intuitive open-source tool for metaproteomics data analysis and interpretation, which includes multiple search engines and the feature to decrease data redundancy by grouping protein hits to so-called meta-proteins. We also designed a graph database back-end for the MetaProteomeAnalyzer to allow seamless analysis of results. The functionality of the MetaProteomeAnalyzer is demonstrated using a sample of a microbial community taken from a biogas plant.

Discovery and validation of plasma biomarkers for major depressive disorder classification based on liquid chromatography-mass spectrometry.

Abstract: Major depressive disorder (MDD) is a debilitating mental disease with a pronounced impact on the quality of life of many people; however, it is still difficult to diagnose MDD accurately. In this study, a nontargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to find the differential metabolites in plasma samples from patients with MDD and healthy controls. Furthermore, a validation analysis focusing on the differential metabolites was performed in another batch of samples using a targeted approach based on the dynamic multiple reactions monitoring method. Levels of acyl carnitines, ether lipids, and tryptophan pronouncedly decreased, whereas LPCs, LPEs, and PEs markedly increased in MDD subjects as compared with the healthy controls. Disturbed pathways, mainly located in acyl carnitine metabolism, lipid metabolism, and tryptophan metabolism, were clearly brought to light in MDD subjects. The binary logistic regression result showed that carnitine C10:1, PE-O 36:5, LPE 18:1 sn-2, and tryptophan can be used as a combinational biomarker to distinguish not only moderate but also severe MDD from healthy control with good sensitivity and specificity. Our findings, on one hand, provide critical insight into the pathological mechanism of MDD and, on the other hand, supply a combinational biomarker to aid the diagnosis of MDD in clinical usage.

Metabolomics of Four Biofluids from Dairy Cows: Potential Biomarkers for Milk Production and Quality

Abstract: The fundamental understanding of the mechanisms regulating milk protein synthesis is limited. This study aimed to elucidate the metabolic mechanisms of milk production affected by forage quality through studying metabolites from four biofluids (rumen fluid, milk, serum, and urine) collected from 16 lactating cows fed alfalfa hay (AH, high-quality, n = 8) and corn stover (CS, low-quality, n = 8) using gas chromatography-time-of-flight/mass spectrometry. The cows fed AH exhibited higher milk yield (P 1 and P < 0.05) between the AH- and CS-fed animals. These metabolites were involved in glycine, serine, and threonine metabolism; tyrosine metabolism; and p...

Profiling of Serum Bile Acids in a Healthy Chinese Population Using UPLC–MS/MS

Abstract: Bile acids (BAs) are a group of important physiological agents for cholesterol metabolism, intestinal nutrient absorption, and biliary secretion of lipids, toxic metabolites, and xenobiotics. Extensive research in the last two decades has unveiled new functions of BAs as signaling molecules and metabolic regulators that modulate hepatic lipid, glucose, and energy homeostasis through the activation of nuclear receptors and G-protein-coupled receptor signaling in gut-liver metabolic axis involving host-gut microbial co-metabolism. Therefore, investigation of serum BA profiles, in healthy human male and female subjects with a wide range of age and body mass index (BMI), will provide important baseline information on the BA physiology as well as metabolic homeostasis among human subjects that are regulated by two sets of genome, host genome, and symbiotic microbiome. Previous reports on age- or gender-related changes on BA profiles in animals and human showed inconsistent results, and the information acquired from various studies was highly fragmentary. Here we profiled the serum BAs in a large population of healthy participants (n = 502) and examined the impact of age, gender, and BMI on serum BA concentrations and compositions using a targeted metabonomics approach with ultraperformance liquid chromatography triple-quadrupole mass spectrometry. We found that the BA profiles were dependent on gender, age, and BMI among study subjects. The total BAs were significantly higher in males than in females (p < 0.05) and higher in obese females than in lean females (p < 0.05). The difference in BA profiles between male and female subjects was decreased at age of 50-70 years, while the difference in BA profiles between lean and obese increased for subjects aged 50-70 years. The study provides a comprehensive understanding of the BA profiles in healthy subjects and highlights the need to take into account age, gender, and BMI differences when investigating pathophysiological changes of BAs resulting from gastrointestinal diseases.

Optimized chemical proteomics assay for kinase inhibitor profiling

Abstract: Solid supported probes have proven to be an efficient tool for chemical proteomics. The kinobeads technology features kinase inhibitors covalently attached to Sepharose for affinity enrichment of kinomes from cell or tissue lysates. This technology, combined with quantitative mass spectrometry, is of particular interest for the profiling of kinase inhibitors. It often leads to the identification of new targets for medicinal chemistry campaigns where it allows a two-in-one binding and selectivity assay. The assay can also uncover resistance mechanisms and molecular sources of toxicity. Here we report on the optimization of the kinobead assay resulting in the combination of five chemical probes and four cell lines to cover half the human kinome in a single assay (∼260 kinases). We show the utility and large-scale applicability of the new version of kinobeads by reprofiling the small molecule kinase inhibitors Alvocidib, Crizotinib, Dasatinib, Fasudil, Hydroxyfasudil, Nilotinib, Ibrutinib, Imatinib, and Suni...

LC-MS-based urinary metabolite signatures in idiopathic Parkinson's disease

Abstract: Increasing evidence has shown that abnormal metabolic phenotypes in body fluids reflect the pathogenesis and pathophysiology of Parkinson’s disease (PD). These body fluids include urine; however, the relationship between, specifically, urinary metabolic phenotypes and PD is not fully understood. In this study, urinary metabolites from a total of 401 clinical urine samples collected from 106 idiopathic PD patients and 104 normal control subjects were profiled by using high-performance liquid chromatography coupled to high-resolution mass spectrometry. Our study revealed significant correlation between clinical phenotype and urinary metabolite profile. Metabolic profiles of idiopathic PD patients differed significantly and consistently from normal controls, with related metabolic pathway variations observed in steroidogenesis, fatty acid beta-oxidation, histidine metabolism, phenylalanine metabolism, tryptophan metabolism, nucleotide metabolism, and tyrosine metabolism. In the fruit fly Drosophila melanogas...

Proteomics Unravels Extracellular Vesicles as Carriers of Classical Cytoplasmic Proteins in Candida albicans

Abstract: The commensal fungus Candida albicans secretes a considerable number of proteins and, as in different fungal pathogens, extracellular vesicles (EVs) have also been observed. Our report contains the first proteomic analysis of EVs in C. albicans and a comparative proteomic study of the soluble secreted proteins. With this purpose, cell-free culture supernatants from C. albicans were separated into EVs and EV-free supernatant and analyzed by LC–MS/MS. A total of 96 proteins were identified including 75 and 61 proteins in EVs and EV-free supernatant, respectively. Out of these, 40 proteins were found in secretome by proteomic analysis for the first time. The soluble proteins were enriched in cell wall and secreted pathogenesis related proteins. Interestingly, more than 90% of these EV-free supernatant proteins were classical secretory proteins with predicted N-terminal signal peptide, whereas all the leaderless proteins involved in metabolism, including some moonlighting proteins, or in the exocytosis and en...

Most highly expressed protein-coding genes have a single dominant isoform.

Abstract: Although eukaryotic cells express a wide range of alternatively spliced transcripts, it is not clear whether genes tend to express a range of transcripts simultaneously across cells, or produce dominant isoforms in a manner that is either tissue-specific or regardless of tissue. To date, large-scale investigations into the pattern of transcript expression across distinct tissues have produced contradictory results. Here, we attempt to determine whether genes express a dominant splice variant at the protein level. We interrogate peptides from eight large-scale human proteomics experiments and databases and find that there is a single dominant protein isoform, irrespective of tissue or cell type, for the vast majority of the protein-coding genes in these experiments, in partial agreement with the conclusions from the most recent large-scale RNAseq study. Remarkably, the dominant isoforms from the experimental proteomics analyses coincided overwhelmingly with the reference isoforms selected by two completely...

Metabolomic Pattern Analysis after Mediterranean Diet Intervention in a Nondiabetic Population: A 1- and 3-Year Follow-up in the PREDIMED Study

Abstract: The Mediterranean diet (MD) is considered a dietary pattern with beneficial effects on human health. The aim of this study was to assess the effect of an MD on urinary metabolome by comparing subjects at 1 and 3 years of follow-up, after an MD supplemented with either extra-virgin olive oil (MD + EVOO) or nuts (MD + Nuts), to those on advice to follow a control low-fat diet (LFD). Ninety-eight nondiabetic volunteers were evaluated, using metabolomic approaches, corresponding to MD + EVOO (n = 41), MD + Nuts (n = 27), or LFD (n = 30) groups. The 1H NMR urinary profiles were examined at baseline and after 1 and 3 years of follow-up. Multivariate data analysis (OSC-PLS-DA and HCA) methods were used to identify the potential biomarker discriminating groups, exhibiting a urinary metabolome separation between MD groups against baseline and LFD. Results revealed that the most prominent hallmarks concerning MD groups were related to the metabolism of carbohydrates (3-hydroxybutyrate, citrate, and cis-aconitate), ...

First Succinyl-Proteome Profiling of Extensively Drug-Resistant Mycobacterium tuberculosis Revealed Involvement of Succinylation in Cellular Physiology

Abstract: Protein lysine succinylation, an emerging protein post-translational modification widespread among eukaryotic and prokaryotic cells, represents an important regulator of cellular processes. However, the extent and function of lysine succinylation in Mycobacterium tuberculosis, especially extensively drug-resistant strain, remain elusive. Combining protein/peptide prefractionation, immunoaffinity enrichment, and LC–MS/MS analysis, a total of 686 succinylated proteins and 1739 succinylation sites of M. tuberculosis were identified, representing the first global profiling of M. tuberculosis lysine succinylation. The identified succinylated proteins are involved in a variety of cellular functions such as metabolic processes, transcription, translation, and stress responses and exhibit different subcellular localization via GO, protein interaction network, and other bioinformatic analysis. Notably, proteins involved in protein biosynthesis and carbon metabolism are preferred targets of lysine succinylation. Mo...

Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.

Abstract: The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ∼8%; DDA = ∼16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome...

Development of urinary pseudotargeted LC-MS-based metabolomics method and its application in hepatocellular carcinoma biomarker discovery.

Abstract: Hepatocellular carcinoma (HCC) is one of the pestilent malignancies leading to cancer-related death. Discovering effective biomarkers for HCC diagnosis is an urgent demand. To identify potential metabolite biomarkers, we developed a urinary pseudotargeted method based on liquid chromatography-hybrid triple quadrupole linear ion trap mass spectrometry (LC-QTRAP MS). Compared with nontargeted method, the pseudotargeted method can achieve better data quality, which benefits differential metabolites discovery. The established method was applied to cirrhosis (CIR) and HCC investigation. It was found that urinary nucleosides, bile acids, citric acid, and several amino acids were significantly changed in liver disease groups compared with the controls, featuring the dysregulation of purine metabolism, energy metabolism, and amino metabolism in liver diseases. Furthermore, some metabolites such as cyclic adenosine monophosphate, glutamine, and short- and medium-chain acylcarnitines were the differential metabolites of HCC and CIR. On the basis of binary logistic regression, butyrylcarnitine (carnitine C4:0) and hydantoin-5-propionic acid were defined as combinational markers to distinguish HCC from CIR. The area under curve was 0.786 and 0.773 for discovery stage and validation stage samples, respectively. These data show that the established pseudotargeted method is a complementary one of targeted and nontargeted methods for metabolomics study.

Quantitative Proteomics Analysis of Vitreous Humor from Diabetic Retinopathy Patients.

Abstract: Initial triggers for diabetic retinopathy (DR) are hyperglycemia-induced oxidative stress and advanced glycation end-products. The most pathological structural changes occur in retinal microvasculature, but the overall development of DR is multifactorial, with a complex interplay of microvascular, neurodegenerative, genetic/epigenetic, immunological, and secondary inflammation-related factors. Although several individual factors and pathways have been associated with retinopathy, a systems level understanding of the disease is lacking. To address this, we performed mass spectrometry based label-free quantitative proteomics analysis of 138 vitreous humor samples from patients with nonproliferative DR or the more severe proliferative form of the disease. Additionally, we analyzed samples from anti-VEGF (vascular endothelial growth factor) (bevacizumab)-treated patients from both groups. In our study, we identified 2482 and quantified the abundancy of 1351 vitreous proteins. Of these, the abundancy of 230 proteins was significantly higher in proliferative retinopathy compared with nonproliferative retinopathy. This specific subset of proteins was linked to inflammation, complement, and coagulation cascade proteins, protease inhibitors, apolipoproteins, immunoglobulins, and cellular adhesion molecules, reflecting the multifactorial nature of the disease. The identification of the key molecules of the disease is critical for the development of new therapeutic molecules and for the new use of existing drugs.

Fructose restores susceptibility of multidrug-resistant Edwardsiella tarda to kanamycin.

Abstract: Edwardsiella tarda, the causative agent of Edwardsiellosis, imposes medical challenges in both the clinic and aquaculture. The emergence of multidrug resistant strains makes antibiotic treatment impractical. The identification of molecules that facilitate or promote antibiotic efficacy is in high demand. In the present study, we aimed to identify small molecules whose abundance is correlated with kanamycin resistance in E. tarda by gas chromatography-mass spectrometry. We found that the abundance of fructose was greatly suppressed in kanamycin-resistant strains. The incubation of kanamycin-resistant bacteria with exogenous fructose sensitized the bacteria to kanamycin. Moreover, the fructose also functioned in bacteria persisters and biofilm. The synergistic effects of fructose and kanamycin were validated in a mouse model. Furthermore, the mechanism relies on fructose in activating TCA cycle to produce NADH, which generates proton motive force to increase the uptake of the antibiotics. Therefore, we present a novel approach in fighting against multidrug resistant bacteria through exploration of antibiotic-suppressed molecules.

Rapid and Reliable Identification of Phospholipids for Untargeted Metabolomics with LC-ESI-QTOF-MS/MS.

Abstract: Lipids are important components of biological systems, and their role can be currently investigated by the application of untargeted, holistic approaches such as metabolomics and lipidomics. Acquired data are analyzed to find significant signals responsible for the differentiation between the investigated conditions. Subsequently, identification has to be performed to bring biological meaning to the obtained results. Lipid identification seems to be relatively easy due to the known characteristic fragments; however, the large number of structural isomers and the formation of different adducts makes it challenging and at risk of misidentification. The inspection of data, acquired for plasma samples by a standard metabolic fingerprinting method, revealed multisignal formations for phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins by the formation of ions such as [M + H]+, [M + Na]+, and [M + K]+ in positive ionization mode and [M – H]−, [M + HCOO]−, and [M + Cl]− in negative mode. Moreover...

Comparative Proteomic Analysis of Human Liver Tissue and Isolated Hepatocytes with a Focus on Proteins Determining Drug Exposure

Abstract: Freshly isolated human hepatocytes are considered the gold standard for in vitro studies of liver functions, including drug transport, metabolism, and toxicity. For accurate predictions of the in vivo outcome, the isolated hepatocytes should reflect the phenotype of their in vivo counterpart, i.e., hepatocytes in human liver tissue. Here, we quantified and compared the membrane proteomes of freshly isolated hepatocytes and human liver tissue using a label-free shotgun proteomics approach. A total of 5144 unique proteins were identified, spanning over 6 orders of magnitude in abundance. There was a good global correlation in protein abundance. However, the expression of many plasma membrane proteins was lower in the isolated hepatocytes than in the liver tissue. This included transport proteins that determine hepatocyte exposure to many drugs and endogenous compounds. Pathway analysis of the differentially expressed proteins confirmed that hepatocytes are exposed to oxidative stress during isolation and su...

Autoantibody signature for the serologic detection of ovarian cancer

Abstract: Sera from patients with ovarian cancer contain autoantibodies (AAb) to tumor-derived proteins that are potential biomarkers for early detection. To detect AAb, we probed high-density programmable protein microarrays (NAPPA) expressing 5177 candidate tumor antigens with sera from patients with serous ovarian cancer (n = 34 cases/30 controls) and measured bound IgG. Of these, 741 antigens were selected and probed with an independent set of ovarian cancer sera (n = 60 cases/60 controls). Twelve potential autoantigens were identified with sensitivities ranging from 13 to 22% at >93% specificity. These were retested using a Luminex bead array using 60 cases and 60 controls, with sensitivities ranging from 0 to 31.7% at 95% specificity. Three AAb (p53, PTPRA, and PTGFR) had area under the curve (AUC) levels >60% (p < 0.01), with the partial AUC (SPAUC) over 5 times greater than for a nondiscriminating test (p < 0.01). Using a panel of the top three AAb (p53, PTPRA, and PTGFR), if at least two AAb were positive, then the sensitivity was 23.3% at 98.3% specificity. AAb to at least one of these top three antigens were also detected in 7/20 sera (35%) of patients with low CA 125 levels and 0/15 controls. AAb to p53, PTPRA, and PTGFR are potential biomarkers for the early detection of ovarian cancer.

Metrics for the Human Proteome Project 2015: Progress on the Human Proteome and Guidelines for High-Confidence Protein Identification

Abstract: Remarkable progress continues on the annotation of the proteins identified in the Human Proteome and on finding credible proteomic evidence for the expression of “missing proteins”. Missing proteins are those with no previous protein-level evidence or insufficient evidence to make a confident identification upon reanalysis in PeptideAtlas and curation in neXtProt. Enhanced with several major new data sets published in 2014, the human proteome presented as neXtProt, version 2014-09-19, has 16 491 unique confident proteins (PE level 1), up from 13 664 at 2012-12 and 15 646 at 2013-09. That leaves 2948 missing proteins from genes classified having protein existence level PE 2, 3, or 4, as well as 616 dubious proteins at PE 5. Here, we document the progress of the HPP and discuss the importance of assessing the quality of evidence, confirming automated findings and considering alternative protein matches for spectra and peptides. We provide guidelines for proteomics investigators to apply in reporting newly i...

Proteomic basis of stress responses in the gills of the pacific oyster Crassostrea gigas.

Abstract: The Pacific oyster Crassostrea gigas is one of the dominant sessile inhabitants of the estuarine intertidal zone, which is a physically harsh environment due to the presence of a number of stressors. Oysters have adapted to highly dynamic and stressful environments, but the molecular mechanisms underlying such stress adaptation are largely unknown. In the present study, we examined the proteomic responses in the gills of C. gigas exposed to three stressors (high temperature, low salinity, and aerial exposure) they often encounter in the field. We quantitatively compared the gill proteome profiles using iTRAQ-coupled 2-D LC–MS/MS. There were 3165 identified proteins among which 2379 proteins could be quantified. Heat shock, hyposalinity, and aerial exposure resulted in 50, 15, and 33 differentially expressed gill proteins, respectively. Venn diagram analysis revealed substantial different responses to the three stressors. Only xanthine dehydrogenase/oxidase showed a similar expression pattern across the th...

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology.

Abstract: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. The aims of this study were to characterize a metabolic signature of ASD and to evaluate multiplatform analytical methodologies in order to develop predictive tools for diagnosis and disease follow-up. Urine samples were analyzed using (1)H and (1)H-(13)C NMR-based approaches and LC-HRMS-based approaches (ESI+ and ESI- on HILIC and C18 chromatography columns). Data tables obtained from the six analytical modalities on a training set of 46 urine samples (22 autistic children and 24 controls) were processed by multivariate analysis (orthogonal partial least-squares discriminant analysis, OPLS-DA). The predictions from each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and receiver operating characteristic curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLS-DA model showed an enhanced performance (R(2)Y(cum) = 0.88, Q(2)(cum) = 0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC = 0.91, p-value = 0.006). Metabolites that are most significantly different between autistic and control children (p < 0.05) are indoxyl sulfate, N-α-acetyl-l-arginine, methyl guanidine, and phenylacetylglutamine. This multimodality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population.