Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity.

Type 1 diabetes (T1D) results from autoimmune destruction of ß cells. Insufficient availability of biomarkers represents a significant gap in understanding the disease cause and progression. We conduct blinded, two-phase case-control plasma proteomics on the TEDDY study to identify biomarkers predictive of T1D development. Untargeted proteomics of 2,252 samples from 184 individuals identify 376 regulated proteins, showing alteration of complement, inflammatory signaling, and metabolic proteins even prior to autoimmunity onset. Extracellular matrix and antigen presentation proteins are differentially regulated in individuals who progress to T1D vs. those that remain in autoimmunity. Targeted proteomics measurements of 167 proteins in 6,426 samples from 990 individuals validate 83 biomarkers. A machine learning analysis predicts if individuals would remain in autoimmunity or develop T1D 6 months before autoantibody appearance, with areas under receiver operating characteristic curves of 0.871 and 0.918, respectively. Our study identifies and validates biomarkers, highlighting pathways affected during T1D development.

New Insights Into Lignification via Network and Multi-Omics Analyses of Arogenate Dehydratase Knock-Out Mutants in Arabidopsis thaliana.

Multiple Arabidopsis arogenate dehydratase (ADT) knock-out (KO) mutants, with phenotypes having variable lignin levels (up to circa 70% reduction), were studied to investigate how differential reductions in ADTs perturb its overall plant systems biology. Integrated "omics" analyses (metabolome, transcriptome, and proteome) of wild type (WT), single and multiple ADT KO lines were conducted. Transcriptome and proteome data were collapsed into gene ortholog (GO) data, with this allowing for enzymatic reaction and metabolome cross-comparisons to uncover dominant or likely metabolic biosynthesis reactions affected. Network analysis of enzymes-highly correlated to stem lignin levels-deduced the involvement of novel putative lignin related proteins or processes. These included those associated with ribosomes, the spliceosome, mRNA transport, aminoacyl tRNA biosynthesis, and phosphorylation. While prior work helped explain lignin biosynthesis regulation at the transcriptional level, our data here provide support for a new hypothesis that there are additional post-transcriptional and translational level processes that need to be considered. These findings are anticipated to lead to development of more accurate depictions of lignin/phenylpropanoid biosynthesis models in situ, with new protein targets identified for further biochemical analysis and/or plant bioengineering. Additionally, using KEGG defined functional categorization of proteomics and transcriptomics analyses, we detected significant changes to glucosinolate, α-linolenic acid, nitrogen, carotenoid, aromatic amino acid, phenylpropanoid, and photosynthesis-related metabolic pathways in ADT KO mutants. Metabolomics results also revealed that putative carotenoid and galactolipid levels were generally increased in amount, whereas many glucosinolates and phenylpropanoids (including flavonoids and lignans) were decreased in the KO mutants.

Correction: Proteogenomic Characterization of Ovarian HGSC Implicates Mitotic Kinases, Replication Stress in Observed Chromosomal Instability.

[This corrects the article PMC7289043.].

Proteogenomic Characterization of Ovarian HGSC Implicates Mitotic Kinases, Replication Stress in Observed Chromosomal Instability.

In the absence of a dominant driving mutation other than uniformly present TP53 mutations, deeper understanding of the biology driving ovarian high-grade serous cancer (HGSC) requires analysis at a functional level, including post-translational modifications. Comprehensive proteogenomic and phosphoproteomic characterization of 83 prospectively collected ovarian HGSC and appropriate normal precursor tissue samples (fallopian tube) under strict control of ischemia time reveals pathways that significantly differentiate between HGSC and relevant normal tissues in the context of homologous repair deficiency (HRD) status. In addition to confirming key features of HGSC from previous studies, including a potential survival-associated signature and histone acetylation as a marker of HRD, deep phosphoproteomics provides insights regarding the potential role of proliferation-induced replication stress in promoting the characteristic chromosomal instability of HGSC and suggests potential therapeutic targets for use in precision medicine trials.

Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities.

We performed the first proteogenomic study on a prospectively collected colon cancer cohort. Comparative proteomic and phosphoproteomic analysis of paired tumor and normal adjacent tissues produced a catalog of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers, drug targets, and cancer/testis antigens. Proteogenomic integration not only prioritized genomically inferred targets, such as copy-number drivers and mutation-derived neoantigens, but also yielded novel findings. Phosphoproteomics data associated Rb phosphorylation with increased proliferation and decreased apoptosis in colon cancer, which explains why this classical tumor suppressor is amplified in colon tumors and suggests a rationale for targeting Rb phosphorylation in colon cancer. Proteomics identified an association between decreased CD8 T cell infiltration and increased glycolysis in microsatellite instability-high (MSI-H) tumors, suggesting glycolysis as a potential target to overcome the resistance of MSI-H tumors to immune checkpoint blockade. Proteogenomics presents new avenues for biological discoveries and therapeutic development.

Mineral Surfaces as Agents of Environmental Proteolysis: Mechanisms and Controls.

We investigated the extent to which contact with mineral surfaces affected the molecular integrity of a model protein, with an emphasis on identifying the mechanisms (hydrolysis, oxidation) and conditions leading to protein alteration. To this end, we studied the ability of four mineral surface archetypes (negatively charged, positively charged, neutral, redox-active) to abiotically fragment a well-characterized protein (GB1) as a function of pH and contact time. GB1 was exposed to the soil minerals montmorillonite, goethite, kaolinite, and birnessite at pH 5 and pH 7 for 1, 8, 24, and 168 h and the supernatant was screened for peptide fragments using Tandem Mass Spectrometry. To distinguish between products of oxidative and hydrolytic cleavage, we combined results from the SEQUEST algorithm, which identifies protein fragments that were cleaved hydrolytically, with the output of a deconvolution algorithm (DECON-Routine) designed to identify oxidation fragments. All four minerals were able to induce protein cleavage. Manganese oxide was effective at both hydrolytic and oxidative cleavage. The fact that phyllosilicates-which are not redox active-induced oxidative cleavage indicates that surfaces acted as catalysts and not as reactants. Our results extend previous observations of proteolytic capabilities in soil minerals to the groups of phyllosilicates and Fe-oxides. We identified structural regions of the protein with particularly high susceptibility to cleavage (loops and ß strands) as well as regions that were entirely unaffected (α helix).

Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry.

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 µg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data.

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those because of collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality because of the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality because of both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.

High-Fat Diets Alter the Modulatory Effects of Xenobiotics on Cytochrome P450 Activities.

Cytochrome P450 monooxygenase (P450) enzymes metabolize critical endogenous chemicals and oxidize nearly all xenobiotics. Dysregulated P450 activities lead to altered capacity for drug metabolism and cellular stress. The effects of mixed exposures on P450 expression and activity are variable and elusive. A high-fat diet (HFD) is a common exposure that results in obesity and associated pathologies including hepatotoxicity. Herein, we report the effects of cigarette smoke on P450 activities of normal weight and HFD induced obese mice. Activity-based protein profiling results indicate that HFD mice had significantly decreased P450 activity, likely instigated by proinflammatory chemicals, and that P450 enzymes involved in detoxification, xenobiotic metabolism, and bile acid synthesis were effected by HFD and smoke interaction. Smoking increased activity of all lung P450 and coexposure to diet effected P450 2s1. We need to expand our understanding of common exposures coupled to altered P450 metabolism to enhance the safety and efficacy of therapeutic drug dosing.

Effects of delayed NSAID administration after experimental eccentric contraction injury - A cellular and proteomics study.

BACKGROUND: Acute muscle injuries are exceedingly common and non-steroidal anti-inflammatory drugs (NSAIDs) are widely consumed to reduce the associated inflammation, swelling and pain that peak 1-2 days post-injury. While prophylactic use or early administration of NSAIDs has been shown to delay muscle regeneration and contribute to loss of muscle strength after healing, little is known about the effects of delayed NSAID use. Further, NSAID use following non-penetrating injury has been associated with increased risk and severity of infection, including that due to group A streptococcus, though the mechanisms remain to be elucidated. The present study investigated the effects of delayed NSAID administration on muscle repair and sought mechanisms supporting an injury/NSAID/infection axis. METHODS: A murine model of eccentric contraction (EC)-induced injury of the tibialis anterior muscle was used to profile the cellular and molecular changes induced by ketorolac tromethamine administered 47 hr post injury. RESULTS: NSAID administration inhibited several important muscle regeneration processes and down-regulated multiple cytoprotective proteins known to inhibit the intrinsic pathway of programmed cell death. These activities were associated with increased caspase activity in injured muscles but were independent of any NSAID effect on macrophage influx or phenotype switching. CONCLUSIONS: These findings provide new molecular evidence supporting the notion that NSAIDs have a direct negative influence on muscle repair after acute strain injury in mice and thus add to renewed concern about the safety and benefits of NSAIDS in both children and adults, in those with progressive loss of muscle mass such as the elderly or patients with cancer or AIDS, and those at risk of secondary infection after trauma or surgery.

Elucidation of roles for vitamin B12 in regulation of folate, ubiquinone, and methionine metabolism.

Only a small fraction of vitamin B12-requiring organisms are able to synthesize B12 de novo, making it a common commodity in microbial communities. Initially recognized as an enzyme cofactor of a few enzymes, recent studies have revealed additional B12-binding enzymes and regulatory roles for B12 Here we report the development and use of a B12-based chemical probe to identify B12-binding proteins in a nonphototrophic B12-producing bacterium. Two unexpected discoveries resulted from this study. First, we identified a light-sensing B12-binding transcriptional regulator and demonstrated that it controls folate and ubiquinone biosynthesis. Second, our probe captured proteins involved in folate, methionine, and ubiquinone metabolism, suggesting that it may play a role as an allosteric effector of these processes. These metabolic processes produce precursors for synthesis of DNA, RNA, and protein. Thereby, B12 likely modulates growth, and by limiting its availability to auxotrophs, B12-producing organisms may facilitate coordination of community metabolism.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry.

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches.

Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer.

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.

Preserved DNA Damage Checkpoint Pathway Protects against Complications in Long-Standing Type 1 Diabetes.

The mechanisms underlying the development of complications in type 1 diabetes (T1D) are poorly understood. Disease modeling of induced pluripotent stem cells (iPSCs) from patients with longstanding T1D (disease duration ≥ 50 years) with severe (Medalist +C) or absent to mild complications (Medalist -C) revealed impaired growth, reprogramming, and differentiation in Medalist +C. Genomics and proteomics analyses suggested differential regulation of DNA damage checkpoint proteins favoring protection from cellular apoptosis in Medalist -C. In silico analyses showed altered expression patterns of DNA damage checkpoint factors among the Medalist groups to be targets of miR200, whose expression was significantly elevated in Medalist +C serum. Notably, neurons differentiated from Medalist +C iPSCs exhibited enhanced susceptibility to genotoxic stress that worsened upon miR200 overexpression. Furthermore, knockdown of miR200 in Medalist +C fibroblasts and iPSCs rescued checkpoint protein expression and reduced DNA damage. We propose miR200-regulated DNA damage checkpoint pathway as a potential therapeutic target for treating complications of diabetes.

Compensatory Islet Response to Insulin Resistance Revealed by Quantitative Proteomics.

Compensatory islet response is a distinct feature of the prediabetic insulin-resistant state in humans and rodents. To identify alterations in the islet proteome that characterize the adaptive response, we analyzed islets from 5 month old male control, high-fat diet fed (HFD), or obese ob/ob mice by LC-MS/MS and quantified ~1100 islet proteins (at least two peptides) with a false discovery rate < 1%. Significant alterations in abundance were observed for ~350 proteins among groups. The majority of alterations were common to both models, and the changes of a subset of ~40 proteins and 12 proteins were verified by targeted quantification using selected reaction monitoring and western blots, respectively. The insulin-resistant islets in both groups exhibited reduced expression of proteins controlling energy metabolism, oxidative phosphorylation, hormone processing, and secretory pathways. Conversely, an increased expression of molecules involved in protein synthesis and folding suggested effects in endoplasmic reticulum stress response, cell survival, and proliferation in both insulin-resistant models. In summary, we report a unique comparison of the islet proteome that is focused on the compensatory response in two insulin-resistant rodent models that are not overtly diabetic. These data provide a valuable resource of candidate proteins to the scientific community to undertake further studies aimed at enhancing ß-cell mass in patients with diabetes. The data are available via the MassIVE repository, under accession no. MSV000079093.

Microscale depletion of high abundance proteins in human biofluids using IgY14 immunoaffinity resin: analysis of human plasma and cerebrospinal fluid.

Removal of highly abundant proteins in plasma is often carried out using immunoaffinity depletion to extend the dynamic range of measurements to lower abundance species. While commercial depletion columns are available for this purpose, they generally are not applicable to limited sample quantities (<20 µL) due to low yields stemming from losses caused by nonspecific binding to the column matrix and concentration of large eluent volumes. Additionally, the cost of the depletion media can be prohibitive for larger-scale studies. Modern LC-MS instrumentation provides the sensitivity necessary to scale-down depletion methods with minimal sacrifice to proteome coverage, which makes smaller volume depletion columns desirable for maximizing sample recovery when samples are limited, as well as for reducing the expense of large-scale studies. We characterized the performance of a 346 µL column volume microscale depletion system, using four different flow rates to determine the most effective depletion conditions for ∼6-µL injections of human plasma proteins and then evaluated depletion reproducibility at the optimum flow rate condition. Depletion of plasma using a commercial 10-mL depletion column served as the control. Results showed depletion efficiency of the microscale column increased as flow rate decreased, and that our microdepletion was reproducible. In an initial application, a 600-µL sample of human cerebrospinal fluid (CSF) pooled from multiple sclerosis patients was depleted and then analyzed using reversed phase liquid chromatography-mass spectrometry to demonstrate the utility of the system for this important biofluid where sample quantities are more commonly limited.

Proteomics informed by transcriptomics identifies novel secreted proteins in Dermacentor andersoni saliva.

Dermacentor andersoni, known as the Rocky Mountain wood tick, is found in the western United States and transmits pathogens that cause diseases of veterinary and public health importance including Rocky Mountain spotted fever, tularemia, Colorado tick fever and bovine anaplasmosis. Tick saliva is known to modulate both innate and acquired immune responses, enabling ticks to feed for several days without detection. During feeding ticks subvert host defences such as hemostasis and inflammation, which would otherwise result in coagulation, wound repair and rejection of the tick. Molecular characterization of the proteins and pharmacological molecules secreted in tick saliva offers an opportunity to develop tick vaccines as an alternative to the use of acaricides, as well as new anti-inflammatory drugs. We performed proteomics informed by transcriptomics to identify D. andersoni saliva proteins that are secreted during feeding. The transcript data generated a database of 21,797 consensus sequences, which we used to identify 677 proteins secreted in the saliva of D. andersoni ticks fed for 2 and 5days, following proteomic investigations of whole saliva using mass spectrometry. Salivary gland transcript levels of unfed ticks were compared with 2 and 5day fed ticks to identify genes upregulated early during tick feeding. We cross-referenced the proteomic data with the transcriptomic data to identify 157 proteins of interest for immunomodulation and blood feeding. Proteins of unknown function as well as known immunomodulators were identified.

The proteome and phosphoproteome of Neurospora crassa in response to cellulose, sucrose and carbon starvation.

Improving cellulolytic enzyme production by plant biomass degrading fungi holds great potential in reducing costs associated with production of next-generation biofuels generated from lignocellulose. How fungi sense cellulosic materials and respond by secreting enzymes has mainly been examined by assessing function of transcriptional regulators and via transcriptional profiling. Here, we obtained global proteomic and phosphoproteomic profiles of the plant biomass degrading filamentous fungus Neurospora crassa grown on different carbon sources, i.e. sucrose, no carbon, and cellulose, by performing isobaric tags for relative and absolute quantification (iTRAQ)-based LC-MS/MS analyses. A comparison between proteomes and transcriptomes under identical carbon conditions suggests that extensive post-transcriptional regulation occurs in N. crassa in response to exposure to cellulosic material. Several hundred amino acid residues with differential phosphorylation levels on crystalline cellulose (Avicel) or carbon-free medium vs sucrose medium were identified, including phosphorylation sites in a major transcriptional activator for cellulase genes, CLR1, as well as a cellobionic acid transporter, CBT1. Mutation of phosphorylation sites on CLR1 did not have a major effect on transactivation of cellulase production, while mutation of phosphorylation sites in CBT1 increased its transporting capacity. Our data provides rich information at both the protein and phosphorylation levels of the early cellular responses to carbon starvation and cellulosic induction and aids in a greater understanding of the underlying post-transcriptional regulatory mechanisms in filamentous fungi.

Automated data extraction from in situ protein-stable isotope probing studies.

Protein-stable isotope probing (protein-SIP) has strong potential for revealing key metabolizing taxa in complex microbial communities. While most protein-SIP work to date has been performed under controlled laboratory conditions to allow extensive isotope labeling of the target organism(s), a key application will be in situ studies of microbial communities for short periods of time under natural conditions that result in small degrees of partial labeling. One hurdle restricting large-scale in situ protein-SIP studies is the lack of algorithms and software for automated data processing of the massive data sets resulting from such studies. In response, we developed Stable Isotope Probing Protein Extraction Resources software (SIPPER) and applied it for large-scale extraction and visualization of data from short-term (3 h) protein-SIP experiments performed in situ on phototrophic bacterial mats isolated from Yellowstone National Park. Several metrics incorporated into the software allow it to support exhaustive analysis of the complex composite isotopic envelope observed as a result of low amounts of partial label incorporation. SIPPER also enables the detection of labeled molecular species without the need for any prior identification.

A comprehensive collection of systems biology data characterizing the host response to viral infection.

The Systems Biology for Infectious Diseases Research program was established by the U.S. National Institute of Allergy and Infectious Diseases to investigate host-pathogen interactions at a systems level. This program generated 47 transcriptomic and proteomic datasets from 30 studies that investigate in vivo and in vitro host responses to viral infections. Human pathogens in the Orthomyxoviridae and Coronaviridae families, especially pandemic H1N1 and avian H5N1 influenza A viruses and severe acute respiratory syndrome coronavirus (SARS-CoV), were investigated. Study validation was demonstrated via experimental quality control measures and meta-analysis of independent experiments performed under similar conditions. Primary assay results are archived at the GEO and PeptideAtlas public repositories, while processed statistical results together with standardized metadata are publically available at the Influenza Research Database (www.fludb.org) and the Virus Pathogen Resource (www.viprbrc.org). By comparing data from mutant versus wild-type virus and host strains, RNA versus protein differential expression, and infection with genetically similar strains, these data can be used to further investigate genetic and physiological determinants of host responses to viral infection.