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N-Terminomics/TAILS Profiling of Proteases and Their Substrates in Ulcerative Colitis.
Gordon, MH, Anowai, A, Young, D, Das, N, Campden, RI, Sekhon, H, Myers, Z, Mainoli, B, Chopra, S, Thuy-Boun, PS, et al
ACS chemical biology. 2019;(11):2471-2483
Abstract
Dysregulated protease activity is often implicated in the initiation of inflammation and immune cell recruitment in gastrointestinal inflammatory diseases. Using N-terminomics/TAILS (terminal amine isotopic labeling of substrates), we compared proteases, along with their substrates and inhibitors, between colonic mucosal biopsies of healthy patients and those with ulcerative colitis (UC). Among the 1642 N-termini enriched using TAILS, increased endogenous processing of proteins was identified in UC compared to healthy patients. Changes in the reactome pathways for proteins associated with metabolism, adherens junction proteins (E-cadherin, liver-intestinal cadherin, catenin alpha-1, and catenin delta-1), and neutrophil degranulation were identified between the two groups. Increased neutrophil infiltration and distinct proteases observed in ulcerative colitis may result in extensive break down, altered processing, or increased remodeling of adherens junctions and other cellular functions. Analysis of the preferred proteolytic cleavage sites indicated that the majority of proteolytic activity and processing comes from host proteases, but that key microbial proteases may also play a role in maintaining homeostasis. Thus, the identification of distinct proteases and processing of their substrates improves the understanding of dysregulated proteolysis in normal intestinal physiology and ulcerative colitis.
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2.
Small-protein Enrichment Assay Enables the Rapid, Unbiased Analysis of Over 100 Low Abundance Factors from Human Plasma.
Harney, DJ, Hutchison, AT, Su, Z, Hatchwell, L, Heilbronn, LK, Hocking, S, James, DE, Larance, M
Molecular & cellular proteomics : MCP. 2019;(9):1899-1915
Abstract
Unbiased and sensitive quantification of low abundance small proteins in human plasma (e.g. hormones, immune factors, metabolic regulators) remains an unmet need. These small protein factors are typically analyzed individually and using antibodies that can lack specificity. Mass spectrometry (MS)-based proteomics has the potential to address these problems, however the analysis of plasma by MS is plagued by the extremely large dynamic range of this body fluid, with protein abundances spanning at least 13 orders of magnitude. Here we describe an enrichment assay (SPEA), that greatly simplifies the plasma dynamic range problem by enriching small-proteins of 2-10 kDa, enabling the rapid, specific and sensitive quantification of >100 small-protein factors in a single untargeted LC-MS/MS acquisition. Applying this method to perform deep-proteome profiling of human plasma we identify C5ORF46 as a previously uncharacterized human plasma protein. We further demonstrate the reproducibility of our workflow for low abundance protein analysis using a stable-isotope labeled protein standard of insulin spiked into human plasma. SPEA provides the ability to study numerous important hormones in a single rapid assay, which we applied to study the intermittent fasting response and observed several unexpected changes including decreased plasma abundance of the iron homeostasis regulator hepcidin.
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3.
Quantitative proteomics analysis of vitreous body from type 2 diabetic patients with proliferative diabetic retinopathy.
Li, J, Lu, Q, Lu, P
BMC ophthalmology. 2018;(1):151
Abstract
BACKGROUND To compare the abundance of vitreous proteins between the patients with proliferative diabetic retinopathy (PDR) and idiopathic macular hole (IMH). METHODS In this study, we performed mass spectrometry-based label-free quantitative proteomics analysis of vitreous samples from type 2 diabetic patients with PDR (n = 9) and IMH subjects (n = 9) and identified the abundance of 610 proteins. RESULTS Out of 610 proteins, 64 proteins (Group A) were unique to PDR patients, while 212 proteins (Group B) could be identified in IMH vitreous only. Among the other 334 proteins that could be detected in both PDR and IMH eyes, 62 proteins differed significantly (p < 0.05, fold change > 2), which included 52 proteins (Group C) and 10 proteins (Group D) over- and under-expressed in PDR vitreous compared with the control. All proteins in these four groups were counted as significant proteins in our study. CONCLUSIONS We identified and quantified 610 proteins in total, which included 338 significant proteins in our study. Protein distribution analysis demonstrated a clear separation of protein expression in PDR and IMH. The protein function analysis illustrated that immunity and transport related proteins might be associated with PDR.
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4.
HLA class I binding prediction via convolutional neural networks.
Vang, YS, Xie, X
Bioinformatics (Oxford, England). 2017;(17):2658-2665
Abstract
MOTIVATION Many biological processes are governed by protein-ligand interactions. One such example is the recognition of self and non-self cells by the immune system. This immune response process is regulated by the major histocompatibility complex (MHC) protein which is encoded by the human leukocyte antigen (HLA) complex. Understanding the binding potential between MHC and peptides can lead to the design of more potent, peptide-based vaccines and immunotherapies for infectious autoimmune diseases. RESULTS We apply machine learning techniques from the natural language processing (NLP) domain to address the task of MHC-peptide binding prediction. More specifically, we introduce a new distributed representation of amino acids, name HLA-Vec, that can be used for a variety of downstream proteomic machine learning tasks. We then propose a deep convolutional neural network architecture, name HLA-CNN, for the task of HLA class I-peptide binding prediction. Experimental results show combining the new distributed representation with our HLA-CNN architecture achieves state-of-the-art results in the majority of the latest two Immune Epitope Database (IEDB) weekly automated benchmark datasets. We further apply our model to predict binding on the human genome and identify 15 genes with potential for self binding. AVAILABILITY AND IMPLEMENTATION Codes to generate the HLA-Vec and HLA-CNN are publicly available at: https://github.com/uci-cbcl/HLA-bind . CONTACT xhx@ics.uci.edu. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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5.
Proteomics: a tool to develop novel diagnostic methods and unravel molecular mechanisms of pediatric diseases.
Torres-Arroyo, A, Ruiz-Lara, A, Castillo-Villanueva, A, Méndez-Cruz, ST, Espinosa-Padilla, SE, Espinosa-Rosales, FJ, Zarate-Mondragón, F, Cervantes-Bustamante, R, Bosch-Canto, V, Vizzuett-López, I, et al
Boletin medico del Hospital Infantil de Mexico. 2017;(3):233-240
Abstract
Proteomics is the study of the expression of changes and post-translational modifications (PTM) of proteins along a metabolic condition either normal or pathological. In the field of health, proteomics allows obtaining valuable data for treatment, diagnosis or pathophysiological mechanisms of different illnesses. To illustrate the aforementioned, we describe two projects currently being performed at the Instituto Nacional de Pediatría: The immuno-proteomic study of cow milk allergy and the Proteomic study of childhood cataract. Cow's milk proteins (CMP) are the first antigens to which infants are exposed and generate allergy in some of them. In Mexico, the incidence of CMP allergy has been estimated at 5-7%. Clinical manifestations include both gastrointestinal and extra-gastrointestinal symptoms, making its diagnosis extremely difficult. An inappropriate diagnosis affects the development and growth of children. The goals of the study are to identify the main immune-reactive CMP in Mexican pediatric population and to design more accurate diagnostic tools for this disease. Childhood cataract is a major ocular disease representing one of the main causes of blindness in infants; in developing countries, this disease promotes up to 27% of cases related to visual loss. From this group, it has been estimated that close to 60% of children do not survive beyond two years after vision lost. PTM have been pointed out as the main cause of protein precipitation at the crystalline and, consequently, clouding of this tissue. The study of childhood cataract represents an outstanding opportunity to identify the PTM associated to the cataract-genesis process.