Application of SWATH Mass Spectrometry and Machine Learning in the Diagnosis of Inflammatory Bowel Disease Based on the Stool Proteome.

Inflammatory bowel disease (IBD) flare-ups exhibit symptoms that are similar to other diseases and conditions, making diagnosis and treatment complicated. Currently, the gold standard for diagnosing and monitoring IBD is colonoscopy and biopsy, which are invasive and uncomfortable procedures, and the fecal calprotectin test, which is not sufficiently accurate. Therefore, it is necessary to develop an alternative method. In this study, our aim was to provide proof of concept for the application of Sequential Window Acquisition of All Theoretical Mass Spectra-Mass spectrometry (SWATH-MS) and machine learning to develop a non-invasive and accurate predictive model using the stool proteome to distinguish between active IBD patients and symptomatic non-IBD patients. Proteome profiles of 123 samples were obtained and data processing procedures were optimized to select an appropriate pipeline. The differentially abundant analysis identified 48 proteins. Utilizing correlation-based feature selection (Cfs), 7 proteins were selected for proceeding steps. To identify the most appropriate predictive machine learning model, five of the most popular methods, including support vector machines (SVMs), random forests, logistic regression, naive Bayes, and k-nearest neighbors (KNN), were assessed. The generated model was validated by implementing the algorithm on 45 prospective unseen datasets; the results showed a sensitivity of 96% and a specificity of 76%, indicating its performance. In conclusion, this study illustrates the effectiveness of utilizing the stool proteome obtained through SWATH-MS in accurately diagnosing active IBD via a machine learning model.

Galectin-8 modulates human osteoclast activity partly through isoform-specific interactions.

In overactive human osteoclasts, we previously identified an alternative splicing event in LGALS8, encoding galectin-8, resulting in decreased expression of the long isoform. Galectin-8, which modulates cell-matrix interactions and functions intracellularly as a danger recognition receptor, has never been associated with osteoclast biology. In human osteoclasts, inhibition of galectin-8 expression revealed its roles in bone resorption, osteoclast nuclearity, and mTORC1 signaling regulation. Galectin-8 isoform-specific inhibition asserted a predominant role for the short isoform in bone resorption. Moreover, a liquid chromatography with tandem mass spectrometry (LC-MS/MS) proteomic analysis of galectin-8 isoforms performed in HEK293T cells identified 22 proteins shared by both isoforms. Meanwhile, nine interacting partners were specific for the short isoform, and none were unique to the long isoform. Interactors specific for the galectin-8 short isoform included cell adhesion proteins and lysosomal proteins. We confirmed the interactions of galectin-8 with CLCN3, CLCN7, LAMP1, and LAMP2, all known to localize to secretory vesicles, in human osteoclasts. Altogether, our study reveals direct roles of galectin-8 in osteoclast activity, mostly attributable to the short isoform.

OpenProt 2.0 builds a path to the functional characterization of alternative proteins.

The OpenProt proteogenomic resource (https://www.openprot.org/) provides users with a complete and freely accessible set of non-canonical or alternative open reading frames (AltORFs) within the transcriptome of various species, as well as functional annotations of the corresponding protein sequences not found in standard databases. Enhancements in this update are largely the result of user feedback and include the prediction of structure, subcellular localization, and intrinsic disorder, using cutting-edge algorithms based on machine learning techniques. The mass spectrometry pipeline now integrates a machine learning-based peptide rescoring method to improve peptide identification. We continue to help users explore this cryptic proteome by providing OpenCustomDB, a tool that enables users to build their own customized protein databases, and OpenVar, a genomic annotator including genetic variants within AltORFs and protein sequences. A new interface improves the visualization of all functional annotations, including a spectral viewer and the prediction of multicoding genes. All data on OpenProt are freely available and downloadable. Overall, OpenProt continues to establish itself as an important resource for the exploration and study of new proteins.

OpenCustomDB: Integration of Unannotated Open Reading Frames and Genetic Variants to Generate More Comprehensive Customized Protein Databases.

Proteomic diversity in biological samples can be characterized by mass spectrometry (MS)-based proteomics using customized protein databases generated from sets of transcripts previously detected by RNA-seq. This diversity has only been increased by the recent discovery that many translated alternative open reading frames rest unannotated at unsuspected locations of mRNAs and ncRNAs. These novel protein products, termed alternative proteins, have been left out of all previous custom database generation tools. Consequently, genetic variations that impact alternative open reading frames and variant peptides from their translated proteins are not detectable with current computational workflows. To fill this gap, we present OpenCustomDB, a bioinformatics tool that uses sample-specific RNaseq data to identify genomic variants in canonical and alternative open reading frames, allowing for more than one coding region per transcript. In a test reanalysis of a cohort of 16 patients with acute myeloid leukemia, 5666 peptides from alternative proteins were detected, including 201 variant peptides. We also observed that a significant fraction of peptide-spectrum matches previously assigned to peptides from canonical proteins got better scores when reassigned to peptides from alternative proteins. Custom protein libraries that include sample-specific sequence variations of all possible open reading frames are promising contributions to the development of proteomics and precision medicine. The raw and processed proteomics data presented in this study can be found in PRIDE repository with accession number PXD029240.

Decoupling of mRNA and Protein Expression in Aging Brains Reveals the Age-Dependent Adaptation of Specific Gene Subsets.

During aging, changes in gene expression are associated with a decline in physical and cognitive abilities. Here, we investigate the connection between changes in mRNA and protein expression in the brain by comparing the transcriptome and proteome of the mouse cortex during aging. Our transcriptomic analysis revealed that aging mainly triggers gene activation in the cortex. We showed that an increase in mRNA expression correlates with protein expression, specifically in the anterior cingulate cortex, where we also observed an increase in cortical thickness during aging. Genes exhibiting an aging-dependent increase of mRNA and protein levels are involved in sensory perception and immune functions. Our proteomic analysis also identified changes in protein abundance in the aging cortex and highlighted a subset of proteins that were differentially enriched but exhibited stable mRNA levels during aging, implying the contribution of aging-related post- transcriptional and post-translational mechanisms. These specific genes were associated with general biological processes such as translation, ribosome assembly and protein degradation, and also important brain functions related to neuroplasticity. By decoupling mRNA and protein expression, we have thus characterized distinct subsets of genes that differentially adjust to cellular aging in the cerebral cortex.

Functional Characterization of a Phf8 Processed Pseudogene in the Mouse Genome.

Most pseudogenes are generated when an RNA transcript is reverse-transcribed and integrated into the genome at a new location. Pseudogenes are often considered as an imperfect and silent copy of a functional gene because of the accumulation of numerous mutations in their sequence. Here we report the presence of Pfh8-ps, a Phf8 retrotransposed pseudogene in the mouse genome, which has no disruptions in its coding sequence. We show that this pseudogene is mainly transcribed in testis and can produce a PHF8-PS protein in vivo. As the PHF8-PS protein has a well-conserved JmjC domain, we characterized its enzymatic activity and show that PHF8-PS does not have the intrinsic capability to demethylate H3K9me2 in vitro compared to the parental PHF8 protein. Surprisingly, PHF8-PS does not localize in the nucleus like PHF8, but rather is mostly located at the cytoplasm. Finally, our proteomic analysis of PHF8-PS-associated proteins revealed that PHF8-PS interacts not only with mitochondrial proteins, but also with prefoldin subunits (PFDN proteins) that deliver unfolded proteins to the cytosolic chaperonin complex implicated in the folding of cytosolic proteins. Together, our findings highlighted PHF8-PS as a new pseudogene-derived protein with distinct molecular functions from PHF8.

Proteomics Profiling of Stool Samples from Preterm Neonates with SWATH/DIA Mass Spectrometry for Predicting Necrotizing Enterocolitis.

Necrotizing enterocolitis (NEC) is a life-threatening condition for premature infants in neonatal intensive care units. Finding indicators that can predict NEC development before symptoms appear would provide more time to apply targeted interventions. In this study, stools from 132 very-low-birth-weight (VLBW) infants were collected daily in the context of a multi-center prospective study aimed at investigating the potential of fecal biomarkers for NEC prediction using proteomics technology. Eight of the VLBW infants received a stage-3 NEC diagnosis. Stools collected from the NEC infants up to 10 days before their diagnosis were available for seven of them. Their samples were matched with those from seven pairs of non-NEC controls. The samples were processed for liquid chromatography-tandem mass spectrometry analysis using SWATH/DIA acquisition and cross-compatible proteomic software to perform label-free quantification. ROC curve and principal component analyses were used to explore discriminating information and to evaluate candidate protein markers. A series of 36 proteins showed the most efficient capacity with a signature that predicted all seven NEC infants at least a week in advance. Overall, our study demonstrates that multiplexed proteomic signature detection constitutes a promising approach for the early detection of NEC development in premature infants.

Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities.

Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins, termed alternative proteins (altProts). This suggests that previously identified protein-protein interaction (PPI) networks are partially incomplete because altProts are not present in conventional protein databases. Here, we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset thereby revealing the presence of 261 altProts in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 altProts encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental gene. Finally, we experimentally validate several interactions involving altProts. These data improve the blueprints of the human PPI network and suggest functional roles for hundreds of altProts.

OpenVar: functional annotation of variants in non-canonical open reading frames.

BACKGROUND: Recent technological advances have revealed thousands of functional open reading frames (ORF) that have eluded reference genome annotations. These overlooked ORFs are found throughout the genome, in any reading frame of transcripts, mature or non-coding, and can overlap annotated ORFs in a different reading frame. The exploration of these novel ORFs in genomic datasets and of their role in genetic traits is hindered by a lack of software. RESULTS: Here, we present OpenVar, a genomic variant annotator that mends that gap and fosters meaningful discoveries. To illustrate the potential of OpenVar, we analysed all variants within SynMicDB, a database of cancer-associated synonymous mutations. By including non-canonical ORFs in the analysis, OpenVar yields a 33.6-fold, 13.8-fold and 8.3-fold increase in high impact variants over Annovar, SnpEff and VEP respectively. We highlighted an overlapping non-canonical ORF in the HEY2 gene where variants significantly clustered. CONCLUSIONS: OpenVar integrates non-canonical ORFs in the analysis of genomic variants, unveiling new research avenues to better understand the genotype-phenotype relationships.

Transcriptomic modulation in response to high-intensity interval training in monocytes of older women with type 2 diabetes.

PURPOSE: Type 2 diabetes is associated with a higher risk of cardiovascular diseases, lowering the quality of life and increasing mortality rates of affected individuals. Circulating monocytes are tightly involved in the atherosclerosis process leading to cardiovascular diseases (CVD), and their inflammatory profile can be modified by exercise. The objective was to exploratory identify genes associated with CVD that could be regulated by high-intensity interval training (HIIT) in monocytes of type 2 diabetes patients. METHODS: Next-generation RNA sequencing (RNA-seq) analyses were conducted on isolated circulating monocytes (CD14+) of six women aged 60 and over with type 2 diabetes who completed a 12-week supervised HIIT intervention on a treadmill. RESULTS: Following the intervention, a reduction of resting diastolic blood pressure was observed. Concomitant with this result, 56 genes were found to be downregulated following HIIT intervention in isolated monocytes. A large proportion of the regulated genes was involved in cellular adhesion, migration and differentiation into an "atherosclerosis-specific" macrophage phenotype. CONCLUSION: The downregulation of transcripts in monocytes globally suggests a favorable cardiovascular effect of the HIIT in older women with type 2 diabetes. In the context of precision medicine and personalized exercise prescription, shedding light on the fundamental mechanisms underlying HIIT effects on the gene profile of immune cells is essential to develop efficient nonpharmacological strategies to prevent CVD in high-risk population.

OpenProt 2021: deeper functional annotation of the coding potential of eukaryotic genomes.

OpenProt (www.openprot.org) is the first proteogenomic resource supporting a polycistronic annotation model for eukaryotic genomes. It provides a deeper annotation of open reading frames (ORFs) while mining experimental data for supporting evidence using cutting-edge algorithms. This update presents the major improvements since the initial release of OpenProt. All species support recent NCBI RefSeq and Ensembl annotations, with changes in annotations being reported in OpenProt. Using the 131 ribosome profiling datasets re-analysed by OpenProt to date, non-AUG initiation starts are reported alongside a confidence score of the initiating codon. From the 177 mass spectrometry datasets re-analysed by OpenProt to date, the unicity of the detected peptides is controlled at each implementation. Furthermore, to guide the users, detectability statistics and protein relationships (isoforms) are now reported for each protein. Finally, to foster access to deeper ORF annotation independently of one's bioinformatics skills or computational resources, OpenProt now offers a data analysis platform. Users can submit their dataset for analysis and receive the results from the analysis by OpenProt. All data on OpenProt are freely available and downloadable for each species, the release-based format ensuring a continuous access to the data. Thus, OpenProt enables a more comprehensive annotation of eukaryotic genomes and fosters functional proteomic discoveries.

The FUS gene is dual-coding with both proteins contributing to FUS-mediated toxicity.

Novel functional coding sequences (altORFs) are camouflaged within annotated ones (CDS) in a different reading frame. We show here that an altORF is nested in the FUS CDS, encoding a conserved 170 amino acid protein, altFUS. AltFUS is endogenously expressed in human tissues, notably in the motor cortex and motor neurons. Over-expression of wild-type FUS and/or amyotrophic lateral sclerosis-linked FUS mutants is known to trigger toxic mechanisms in different models. These include inhibition of autophagy, loss of mitochondrial potential and accumulation of cytoplasmic aggregates. We find that altFUS, not FUS, is responsible for the inhibition of autophagy, and pivotal in mitochondrial potential loss and accumulation of cytoplasmic aggregates. Suppression of altFUS expression in a Drosophila model of FUS-related toxicity protects against neurodegeneration. Some mutations found in ALS patients are overlooked because of their synonymous effect on the FUS protein. Yet, we show they exert a deleterious effect causing missense mutations in the overlapping altFUS protein. These findings demonstrate that FUS is a bicistronic gene and suggests that both proteins, FUS and altFUS, cooperate in toxic mechanisms.

Modelling of pathogen-host systems using deeper ORF annotations and transcriptomics to inform proteomics analyses.

The Zika virus is a flavivirus that can cause fulminant outbreaks and lead to Guillain-Barré syndrome, microcephaly and fetal demise. Like other flaviviruses, the Zika virus is transmitted by mosquitoes and provokes neurological disorders. Despite its risk to public health, no antiviral nor vaccine are currently available. In the recent years, several studies have set to identify human host proteins interacting with Zika viral proteins to better understand its pathogenicity. Yet these studies used standard human protein sequence databases. Such databases rely on genome annotations, which enforce a minimal open reading frame (ORF) length criterion. An ever-increasing number of studies have demonstrated the shortcomings of such annotation, which overlooks thousands of functional ORFs. Here we show that the use of a customized database including currently non-annotated proteins led to the identification of 4 alternative proteins as interactors of the viral capsid and NS4A proteins. Furthermore, 12 alternative proteins were identified in the proteome profiling of Zika infected monocytes, one of which was significantly up-regulated. This study presents a computational framework for the re-analysis of proteomics datasets to better investigate the viral-host protein interplays upon infection with the Zika virus.

How to Illuminate the Dark Proteome Using the Multi-omic OpenProt Resource.

Ten of thousands of open reading frames (ORFs) are hidden within genomes. These alternative ORFs, or small ORFs, have eluded annotations because they are either small or within unsuspected locations. They are found in untranslated regions or overlap a known coding sequence in messenger RNA and anywhere in a "non-coding" RNA. Serendipitous discoveries have highlighted these ORFs' importance in biological functions and pathways. With their discovery came the need for deeper ORF annotation and large-scale mining of public repositories to gather supporting experimental evidence. OpenProt, accessible at https://openprot.org/, is the first proteogenomic resource enforcing a polycistronic model of annotation across an exhaustive transcriptome for 10 species. Moreover, OpenProt reports experimental evidence cumulated across a re-analysis of 114 mass spectrometry and 87 ribosome profiling datasets. The multi-omics OpenProt resource also includes the identification of predicted functional domains and evaluation of conservation for all predicted ORFs. The OpenProt web server provides two query interfaces and one genome browser. The query interfaces allow for exploration of the coding potential of genes or transcripts of interest as well as custom downloads of all information contained in OpenProt. © 2020 The Authors. Basic Protocol 1: Using the Search interface Basic Protocol 2: Using the Downloads interface.

Reconsidering proteomic diversity with functional investigation of small ORFs and alternative ORFs.

The discovery of functional yet non-annotated open reading frames (ORFs) throughout the genome of several species presents an unprecedented challenge in current genome annotation. These novel ORFs are shorter than annotated ones and many can be found on the same RNA, in opposition to current assumptions in annotation methodologies. Whilst the literature lacks consensus, these novel ORFs are commonly referred to as small ORFs (sORFs) or alternative ORFs (alt-ORFs). Unannotated ORFs represent an overlooked layer of complexity in the coding potential of genomes and are transforming our current vision of the nature of coding genes. In this review, we outline what constitutes a sORF or an alt-ORF and emphasize differences between both nomenclatures. We then describe complementary large-scale methods to accurately discover novel ORFs as well as yield functional insights on the novel proteins they encode. While serendipitous discoveries highlighted the functional importance of some novel ORFs, omics methods facilitate and improve their characterization to better understand physiological and pathological pathways. Functional annotation of sORFs, alt-ORFs and their corresponding microproteins will likely help fundamental and clinical research.

UBB pseudogene 4 encodes functional ubiquitin variants.

Pseudogenes are mutated copies of protein-coding genes that cannot be translated into proteins, but a small subset of pseudogenes has been detected at the protein level. Although ubiquitin pseudogenes represent one of the most abundant pseudogene families in many organisms, little is known about their expression and signaling potential. By re-analyzing public RNA-sequencing and proteomics datasets, we here provide evidence for the expression of several ubiquitin pseudogenes including UBB pseudogene 4 (UBBP4), which encodes UbKEKS (Q2K, K33E, Q49K, N60S). The functional consequences of UbKEKS conjugation appear to differ from canonical ubiquitylation. Quantitative proteomics shows that UbKEKS modifies specific proteins including lamins. Knockout of UBBP4 results in slower cell division, and accumulation of lamin A within the nucleolus. Our work suggests that a subset of proteins reported as ubiquitin targets may instead be modified by ubiquitin variants that are the products of wrongly annotated pseudogenes and induce different functional effects.

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames.

Genome annotation is central to today's proteomic research as it draws the outlines of the proteomic landscape. Traditional models of open reading frame (ORF) annotation impose two arbitrary criteria: a minimum length of 100 codons and a single ORF per transcript. However, a growing number of studies report expression of proteins from allegedly non-coding regions, challenging the accuracy of current genome annotations. These novel proteins were found encoded either within non-coding RNAs, 5' or 3' untranslated regions (UTRs) of mRNAs, or overlapping a known coding sequence (CDS) in an alternative ORF. OpenProt is the first database that enforces a polycistronic model for eukaryotic genomes, allowing annotation of multiple ORFs per transcript. OpenProt is freely accessible and offers custom downloads of protein sequences across 10 species. Using OpenProt database for proteomic experiments enables novel proteins discovery and highlights the polycistronic nature of eukaryotic genes. The size of OpenProt database (all predicted proteins) is substantial and need be taken in account for the analysis. However, with appropriate false discovery rate (FDR) settings or the use of a restricted OpenProt database, users will gain a more realistic view of the proteomic landscape. Overall, OpenProt is a freely available tool that will foster proteomic discoveries.

Conservation of physiological dysregulation signatures of aging across primates.

Two major goals in the current biology of aging are to identify general mechanisms underlying the aging process and to explain species differences in aging. Recent research in humans suggests that one important driver of aging is dysregulation, the progressive loss of homeostasis in complex biological networks. Yet, there is a lack of comparative data for this hypothesis, and we do not know whether dysregulation is widely associated with aging or how well signals of homeostasis are conserved. To address this knowledge gap, we use unusually detailed longitudinal biomarker data from 10 species of nonhuman primates housed in research centers and data from two human populations to test the hypotheses that (a) greater dysregulation is associated with aging across primates and (b) physiological states characterizing homeostasis are conserved across primates to degrees associated with phylogenetic proximity. To evaluate dysregulation, we employed a multivariate distance measure, calculated from sets of biomarkers, that is associated with aging and mortality in human populations. Dysregulation scores positively correlated with age and risk of mortality in most nonhuman primates studied, and signals of homeostatic state were significantly conserved across species, declining with phylogenetic distance. Our study provides the first broad demonstration of physiological dysregulation associated with aging and mortality risk in multiple nonhuman primates. Our results also imply that emergent signals of homeostasis are evolutionarily conserved, although with notable variation among species, and suggest promising directions for future comparative studies on dysregulation and the aging process.