Designing an In Silico Strategy to Select Tissue-Leakage Biomarkers Using the Galaxy Framework

A Galaxy of informatics resources for MS-based proteomics

INTRODUCTION

Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting the analysis requirements of increasingly complex MS-based proteomic data and associated multi-omic data are critically needed. These requirements included availability of software that would span diverse types of analyses, scalability for large-scale, compute-intensive applications, and mechanisms to ease adoption of the software.

AREAS COVERED

The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses.

EXPERT OPINION

The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.

Comparison of extracellular matrix enrichment protocols for the improved characterization of the skin matrisome by mass spectrometry

A striking feature of skin organization is that the extracellular matrix (ECM) occupies a larger volume than the cells. Skin ECM also directly contributes to aging and most cutaneous diseases. In recent years, specific ECM enrichment protocols combined with in silico approaches allowed the proteomic description of the matrisome of various organs and tumor samples. Nevertheless, the skin matrisome remains under-studied and protocols allowing the efficient recovery of the diverse ECM found in skin are still to be described. Here, we compared four protocols allowing the enrichment of ECM proteins from adult mouse back skin and found that all protocols led to a significant enrichment (up to 65%) of matrisome proteins when compared to total skin lysates. The protocols based on decellularization and solubility profiling gave the best results in terms of numbers of proteins identified and confirmed that skin matrisome proteins exhibit very diverse solubility and abundance profiles. We also report the first description of the skin matrisome of healthy adult mice that includes 236 proteins comprising 95 core matrisome proteins and 141 associated matrisome proteins. These results provide a reliable basis for future characterizations of skin ECM proteins and their dysregulations in disease-specific contexts. SIGNIFICANCE: Extracellular matrix proteins are key players in skin physiopathology and have been involved in several diseases such as genetic disorders, wound healing defects, scleroderma and skin carcinoma. However, skin ECM proteins are numerous, diverse and challenging to analyze by mass spectrometry due to the multiplicity of their post-translational modifications and to the heterogeneity of their solubility profiles. Here, we performed the thorough evaluation of four ECM enrichment protocols compatible with the proteomic analysis of mouse back skin and provide the first description of the adult mouse skin matrisome in homeostasis conditions. Our work will greatly facilitate the future characterization of skin ECM alterations in preclinical mouse models and will inspire new optimizations to analyze the skin matrisome of other species and of human clinical samples.

Proteomic Identification of an Endogenous Synaptic SUMOylome in the Developing Rat Brain

Synapses are highly specialized structures that interconnect neurons to form functional networks dedicated to neuronal communication. During brain development, synapses undergo activity-dependent rearrangements leading to both structural and functional changes. Many molecular processes are involved in this regulation, including post-translational modifications by the Small Ubiquitin-like MOdifier SUMO. To get a wider view of the panel of endogenous synaptic SUMO-modified proteins in the mammalian brain, we combined subcellular fractionation of rat brains at the post-natal day 14 with denaturing immunoprecipitation using SUMO2/3 antibodies and tandem mass spectrometry analysis. Our screening identified 803 candidate SUMO2/3 targets, which represents about 18% of the synaptic proteome. Our dataset includes neurotransmitter receptors, transporters, adhesion molecules, scaffolding proteins as well as vesicular trafficking and cytoskeleton-associated proteins, defining SUMO2/3 as a central regulator of the synaptic organization and function.

Advances and Utility of the Human Plasma Proteome

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

Mass Spectrometry-Based Proteomics Reveal Alcohol Dehydrogenase 1B as a Blood Biomarker Candidate to Monitor Acetaminophen-Induced Liver Injury

Acute liver injury (ALI) is a severe disorder resulting from excessive hepatocyte cell death, and frequently caused by acetaminophen intoxication. Clinical management of ALI progression is hampered by the dearth of blood biomarkers available. In this study, a bioinformatics workflow was developed to screen omics databases and identify potential biomarkers for hepatocyte cell death. Then, discovery proteomics was harnessed to select from among these candidates those that were specifically detected in the blood of acetaminophen-induced ALI patients. Among these candidates, the isoenzyme alcohol dehydrogenase 1B (ADH1B) was massively leaked into the blood. To evaluate ADH1B, we developed a targeted proteomics assay and quantified ADH1B in serum samples collected at different times from 17 patients admitted for acetaminophen-induced ALI. Serum ADH1B concentrations increased markedly during the acute phase of the disease, and dropped to undetectable levels during recovery. In contrast to alanine aminotransferase activity, the rapid drop in circulating ADH1B concentrations was followed by an improvement in the international normalized ratio (INR) within 10–48 h, and was associated with favorable outcomes. In conclusion, the combination of omics data exploration and proteomics revealed ADH1B as a new blood biomarker candidate that could be useful for the monitoring of acetaminophen-induced ALI.

GO Enrichment Analysis for Differential Proteomics Using ProteoRE

With the increased simplicity of producing proteomics data, the bottleneck has now shifted to the functional analysis of large lists of proteins to translate this primary level of information into meaningful biological knowledge. Tools implementing such approach are a powerful way to gain biological insights related to their samples, provided that biologists/clinicians have access to computational solutions even when they have little programming experience or bioinformatics support. To achieve this goal, we designed ProteoRE (Proteomics Research Environment), a unified online research service that provides end-users with a set of tools to interpret their proteomics data in a collaborative and reproducible manner. ProteoRE is built upon the Galaxy framework, a workflow system allowing for data and analysis persistence, and providing user interfaces to facilitate the interaction with tools dedicated to the functional and the visual analysis of proteomics datasets. A set of tools relying on computational methods selected for their complementarity in terms of functional analysis was developed and made accessible via the ProteoRE web portal. In this chapter, a step-by-step protocol linking these tools is designed to perform a functional annotation and GO-based enrichment analyses applied to a set of differentially expressed proteins as a use case. Analytical practices, guidelines as well as tips related to this strategy are also provided. Tools, datasets, and results are freely available at http://www.proteore.org , allowing researchers to reuse them.

The Functionally Unannotated Proteome of Human Male Tissues: A Shared Resource to Uncover New Protein Functions Associated with Reproductive Biology

In the context of the Human Proteome Project, we built an inventory of 412 functionally unannotated human proteins for which experimental evidence at the protein level exists (uPE1) and which are highly expressed in tissues involved in human male reproduction. We implemented a strategy combining literature mining, bioinformatics tools to collate annotation and experimental information from specific molecular public resources, and efficient visualization tools to put these unknown proteins into their biological context (protein complexes, tissue and subcellular location, expression pattern). The gathered knowledge allowed pinpointing five uPE1 for which a function has recently been proposed and which should be updated in protein knowledge bases. Furthermore, this bioinformatics strategy allowed to build new functional hypotheses for five other uPE1s in link with phenotypic traits that are specific to male reproductive function such as ciliogenesis/flagellum formation in germ cells (CCDC112 and TEX9), chromatin remodeling (C3orf62) and spermatozoon maturation (CCDC183). We also discussed the enigmatic case of MAGEB proteins, a poorly documented cancer/testis antigen subtype. Tools used and computational outputs produced during this study are freely accessible via ProteoRE (http://www.proteore.org), a Galaxy-based instance, for reuse purposes. We propose these five uPE1s should be investigated in priority by expert laboratories and hope that this inventory and shared resources will stimulate the interest of the community of reproductive biology.