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 β 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.

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.

Comparison of ovarian cancer and normal precursors identifies key signaling pathways

Mitotic and cyclin-dependent kinases emerge as potential therapeutic targets

Previously identified hallmarks of homologous repair status and survival are confirmed

Replication stress appears to drive increased chromosomal instability

Abstract LB-006: Proteogenomic characterization of human colon cancer reveals new therapeutic opportunities

We prospectively collected matched tumor specimens, adjacent non-tumor tissues, and blood samples from 110 colon cancer patients and analyzed the samples using seven omics platforms, including whole-exome sequencing, copy number arrays, RNA-Seq, miRNA-Seq, label-free global proteomics, isobaric tandem mass tag (TMT) labeling-based global proteomics, and TMT-based phosphoproteomics. Comparative proteomic and phosphoproteomic analysis of paired tumor and adjacent normal samples produced the first comprehensive catalogue of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers and drug targets. These cancer-associated proteins and phosphosites had very little overlap with known cancer genes in the Cancer Gene Census, providing a novel information layer to our knowledge about colon cancer. One notable finding in differential proteome analysis is the identification of several cancer/testis antigens that were recurrently over-expressed in tumors compared to adjacent normal tissue, including IGF2BP3 (51%), SPAG1 (14%), and ATAD2 (8%). Through integrative analysis of the whole-exome sequencing, RNA-Seq, and proteomics data, we further predicted personalized neoantigens for 38% of the patients. In total, we found proteomics-supported neoantigens or cancer/testis antigens for 78% of the tumors in this cohort, demonstrating the potential of proteogenomics in identifying tumor antigens for cancer vaccine development. Proteomics data complemented somatic copy number analysis results and showed that multiple somatic copy number deletion events converge to repress the endocytosis pathway, suggesting its tumor suppressor role in colon cancer. In addition to reinforcing or complementing genomic findings, proteogenomic integration may also contradict genomics data-based inferences and lead to unexpected discoveries and therapeutic opportunities. Proteomics data identified SOX9 as an oncogene in colon cancer, whereas it was predicted to be a tumor suppressor based on somatic mutation data in the TCGA study. Phosphoproteomics data revealed a dual role of Rb phosphorylation in promoting proliferation and repressing apoptosis in colon cancer, clarifying the long-standing puzzle of colon cancer-specific amplification of this tumor suppressor and highlighting a unique opportunity for targeting Rb phosphorylation in colon cancer. Microsatellite instability status has been approved by the FDA as a biomarker for selecting patients for checkpoint inhibitor therapy in colorectal and other solid tumors. However, many MSI-high tumors fail to respond to checkpoint inhibition. Our proteogenomic analysis identified a subtype-specific association between increased glycolysis and decreased CD8 T cell infiltration in MSI-high colon tumors, suggesting glycolysis as a target for overcoming immune evasion in this MSI-H tumors. We make the primary and processed datasets available in publicly accessible data repositories and portals to allow broad use of these datasets for new biological discoveries and therapeutic hypothesis generation.

Citation Format: Bing Zhang, Suhas Vasaikar, Chen Huang, Xiaojing Wang, Vladislav A. Petyuk, Sara R. Savage, Bo Wen, Yongchao Dou, Yun Zhang, Zhiao Shi, Osama A. Arshad, Marina A. Gritsenko, Lisa J. Zimmerman, Jason E. McDermott, Therese R. Clauss, Ronald J. Moore, Rui Zhao, Matthew E. Monroe, Yi-Ting Wang, Matthew C. Chambers, Robbert J. Slebos, Ken S. Lau, Qianxing Mo, Li Ding, Matthew Ellis, Mathangi Thiagarajan, Christopher R. Kinsinger, Henry Rodriguez, Richard D. Smith, Karin D. Rodland, Daniel C. Liebler, Tao Liu, CPTAC Investigators. Proteogenomic characterization of human colon cancer reveals new therapeutic opportunities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-006.

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 β strands) as well as regions that were entirely unaffected (α helix).

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.

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.

Trauma-associated human neutrophil alterations revealed by comparative proteomics profiling

PURPOSE

Polymorphonuclear neutrophils (PMNs) play an important role in mediating the innate immune response after severe traumatic injury; however, the cellular proteome response to traumatic condition is still largely unknown.

EXPERIMENTAL DESIGN

We applied 2D-LC-MS/MS-based shotgun proteomics to perform comparative proteome profiling of human PMNs from severe trauma patients and healthy controls.

RESULTS

A total of 197 out of ~2500 proteins (being identified with at least two peptides) were observed with significant abundance changes following the injury. The proteomics data were further compared with transcriptomics data for the same genes obtained from an independent patient cohort. The comparison showed that the protein abundance changes for the majority of proteins were consistent with the mRNA abundance changes in terms of directions of changes. Moreover, increased protein secretion was suggested as one of the mechanisms contributing to the observed discrepancy between protein and mRNA abundance changes. Functional analyses of the altered proteins showed that many of these proteins were involved in immune response, protein biosynthesis, protein transport, NRF2-mediated oxidative stress response, the ubiquitin-proteasome system, and apoptosis pathways.

CONCLUSIONS AND CLINICAL RELEVANCE

Our data suggest increased neutrophil activation and inhibited neutrophil apoptosis in response to trauma. The study not only reveals an overall picture of functional neutrophil response to trauma at the proteome level, but also provides a rich proteomics data resource of trauma-associated changes in the neutrophil that will be valuable for further studies of the functions of individual proteins in PMNs.

Quantitative phosphoproteomic analysis of soybean root hairs inoculated with Bradyrhizobium japonicum

Root hairs are single hair-forming cells on roots that function to increase root surface area, enhancing water and nutrient uptake. In leguminous plants, root hairs also play a critical role as the site of infection by symbiotic nitrogen fixing rhizobia, leading to the formation of a novel organ, the nodule. The initial steps in the rhizobia-root hair infection process are known to involve specific receptor kinases and subsequent kinase cascades. Here, we characterize the phosphoproteome of the root hairs and the corresponding stripped roots (i.e. roots from which root hairs were removed) during rhizobial colonization and infection to gain insight into the molecular mechanism of root hair cell biology. We chose soybean (Glycine max L.), one of the most important crop plants in the legume family, for this study because of its larger root size, which permits isolation of sufficient root hair material for phosphoproteomic analysis. Phosphopeptides derived from root hairs and stripped roots, mock inoculated or inoculated with the soybean-specific rhizobium Bradyrhizobium japonicum, were labeled with the isobaric tag eight-plex iTRAQ, enriched using Ni-NTA magnetic beads and subjected to nanoRPLC-MS/MS1 analysis using HCD and decision tree guided CID/ETD strategy. A total of 1625 unique phosphopeptides, spanning 1659 nonredundant phosphorylation sites, were detected from 1126 soybean phosphoproteins. Among them, 273 phosphopeptides corresponding to 240 phosphoproteins were found to be significantly regulated (>1.5-fold abundance change) in response to inoculation with B. japonicum. The data reveal unique features of the soybean root hair phosphoproteome, including root hair and stripped root-specific phosphorylation suggesting a complex network of kinase-substrate and phosphatase-substrate interactions in response to rhizobial inoculation.

Distinct cerebrospinal fluid proteomes differentiate post-treatment lyme disease from chronic fatigue syndrome

Background

Neurologic Post Treatment Lyme disease (nPTLS) and Chronic Fatigue (CFS) are syndromes of unknown etiology. They share features of fatigue and cognitive dysfunction, making it difficult to differentiate them. Unresolved is whether nPTLS is a subset of CFS.

Methods and Principal Findings

Pooled cerebrospinal fluid (CSF) samples from nPTLS patients, CFS patients, and healthy volunteers were comprehensively analyzed using high-resolution mass spectrometry (MS), coupled with immunoaffinity depletion methods to reduce protein-masking by abundant proteins. Individual patient and healthy control CSF samples were analyzed directly employing a MS-based label-free quantitative proteomics approach. We found that both groups, and individuals within the groups, could be distinguished from each other and normals based on their specific CSF proteins (p<0.01). CFS (n = 43) had 2,783 non-redundant proteins, nPTLS (n = 25) contained 2,768 proteins, and healthy normals had 2,630 proteins. Preliminary pathway analysis demonstrated that the data could be useful for hypothesis generation on the pathogenetic mechanisms underlying these two related syndromes.

Conclusions

nPTLS and CFS have distinguishing CSF protein complements. Each condition has a number of CSF proteins that can be useful in providing candidates for future validation studies and insights on the respective mechanisms of pathogenesis. Distinguishing nPTLS and CFS permits more focused study of each condition, and can lead to novel diagnostics and therapeutic interventions.

Transcriptional and translational regulatory responses to iron limitation in the globally distributed marine bacterium Candidatus pelagibacter ubique

Iron is recognized as an important micronutrient that limits microbial plankton productivity over vast regions of the oceans. We investigated the gene expression responses of Candidatus Pelagibacter ubique cultures to iron limitation in natural seawater media supplemented with a siderophore to chelate iron. Microarray data indicated transcription of the periplasmic iron binding protein sfuC increased by 16-fold, and iron transporter subunits, iron-sulfur center assembly genes, and the putative ferroxidase rubrerythrin transcripts increased to a lesser extent. Quantitative peptide mass spectrometry revealed that sfuC protein abundance increased 27-fold, despite an average decrease of 59% across the global proteome. Thus, we propose sfuC as a marker gene for indicating iron limitation in marine metatranscriptomic and metaproteomic ecological surveys. The marked proteome reduction was not directly correlated to changes in the transcriptome, implicating post-transcriptional regulatory mechanisms as modulators of protein expression. Two RNA-binding proteins, CspE and CspL, correlated well with iron availability, suggesting that they may contribute to the observed differences between the transcriptome and proteome. We propose a model in which the RNA-binding activity of CspE and CspL selectively enables protein synthesis of the iron acquisition protein SfuC during transient growth-limiting episodes of iron scarcity.