Analysis and Visualization of Quantitative Proteomics Data Using FragPipe-Analyst.

The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows, including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.

Mapping the IMiD-dependent cereblon interactome using BioID-proximity labelling.

Immunomodulatory imide drugs (IMiDs) are central components of therapy for multiple myeloma (MM). IMiDs bind cereblon (CRBN), an adaptor for the CUL4-DDB1-RBX1 E3 ligase to change its substrate specificity and induce degradation of 'neosubstrate' transcription factors that are essential to MM cells. Mechanistic studies to date have largely focussed on mediators of therapeutic activity and insight into clinical IMiD toxicities is less developed. We adopted BioID2-dependent proximity labelling (BioID2-CRBN) to characterise the CRBN interactome in the presence and absence of various IMiDs and the proteasome inhibitor, bortezomib. We aimed to leverage this technology to further map CRBN interactions beyond what has been achieved by conventional proteomic techniques. In support of this approach, analysis of cells expressing BioID2-CRBN following IMiD treatment displayed biotinylation of known CRBN interactors and neosubstrates. We observed that bortezomib alone significantly modifies the CRBN interactome. Proximity labelling also suggested that IMiDs augment the interaction between CRBN and proteins that are not degraded, thus designating 'neointeractors' distinct from previously disclosed 'neosubstrates'. Here we identify Non-Muscle Myosin Heavy Chain IIA (MYH9) as a putative CRBN neointeractor that may contribute to the haematological toxicity of IMiDs. These studies provide proof of concept for proximity labelling technologies in the mechanistic profiling of IMiDs and related E3-ligase-modulating drugs.

Loss of endogenous estrogen alters mitochondrial metabolism and muscle clock-related protein Rbm20 in female mdx mice.

Female carriers of a Duchenne muscular dystrophy (DMD) gene mutation manifest exercise intolerance and metabolic anomalies that may be exacerbated following menopause due to the loss of estrogen, a known regulator of skeletal muscle function and metabolism. Here, we studied the impact of estrogen depletion (via ovariectomy) on exercise tolerance and muscle mitochondrial metabolism in female mdx mice and the potential of estrogen replacement therapy (using estradiol) to protect against functional and metabolic perturbations. We also investigated the effect of estrogen depletion, and replacement, on the skeletal muscle proteome through an untargeted proteomic approach with TMT-labelling. Our study confirms that loss of estrogen in female mdx mice reduces exercise capacity, tricarboxylic acid cycle intermediates, and citrate synthase activity but that these deficits are offset through estrogen replacement therapy. Furthermore, ovariectomy downregulated protein expression of RNA-binding motif factor 20 (Rbm20), a critical regulator of sarcomeric and muscle homeostasis gene splicing, which impacted pathways involving ribosomal and mitochondrial translation. Estrogen replacement modulated Rbm20 protein expression and promoted metabolic processes and the upregulation of proteins involved in mitochondrial dynamics and metabolism. Our data suggest that estrogen mitigates dystrophinopathic features in female mdx mice and that estrogen replacement may be a potential therapy for post-menopausal DMD carriers.

A Semiautomated Proteomics and Phosphoproteomics Protocol for the Identification of Novel Therapeutic Targets and Predictive Biomarkers in In Vivo Xenograft Models of Pediatric Cancers.

Genomic profiling has identified therapeutic targets for precision treatment of certain cancers, but many patients lack actionable mutations. Additional omics approaches, like proteomics and phosphoproteomics, are essential for comprehensive mapping of cancer-associated molecular phenotypes. In vivo models, such as cell line and patient-derived xenografts (PDX), offer valuable insights into cancer biology and treatment strategies.This chapter presents a semiautomated high-throughput workflow for integrated proteomics and phosphoproteomics analysis on the Kingfish platform coupled with MagReSyn® Zr-IMAC HP. It enhances protein extraction from in vivo xenograft samples and provides better insights into cancers with poor prognosis. The approach successfully identified over 11,000 unique phosphosites and ~6000 proteins in SJSA-1 pediatric osteosarcoma xenografts, demonstrating its efficacy. This workflow is a valuable tool for studying tumor biology and developing precision oncology strategies.

Analysis and visualization of quantitative proteomics data using FragPipe-Analyst.

The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.

HtrA, fatty acids, and membrane protein interplay in Chlamydia trachomatis to impact stress response and trigger early cellular exit.

Chlamydia trachomatis is an intracellular bacterial pathogen that undergoes a biphasic developmental cycle, consisting of intracellular reticulate bodies and extracellular infectious elementary bodies. A conserved bacterial protease, HtrA, was shown previously to be essential for Chlamydia during the reticulate body phase, using a novel inhibitor (JO146). In this study, isolates selected for the survival of JO146 treatment were found to have polymorphisms in the acyl-acyl carrier protein synthetase gene (aasC). AasC encodes the enzyme responsible for activating fatty acids from the host cell or synthesis to be incorporated into lipid bilayers. The isolates had distinct lipidomes with varied fatty acid compositions. A reduction in the lipid compositions that HtrA prefers to bind to was detected, yet HtrA and MOMP (a key outer membrane protein) were present at higher levels in the variants. Reduced progeny production and an earlier cellular exit were observed. Transcriptome analysis identified that multiple genes were downregulated in the variants especially stress and DNA processing factors. Here, we have shown that the fatty acid composition of chlamydial lipids, HtrA, and membrane proteins interplay and, when disrupted, impact chlamydial stress response that could trigger early cellular exit. IMPORTANCE: Chlamydia trachomatis is an important obligate intracellular pathogen that has a unique biphasic developmental cycle. HtrA is an essential stress or virulence protease in many bacteria, with many different functions. Previously, we demonstrated that HtrA is critical for Chlamydia using a novel inhibitor. In the present study, we characterized genetic variants of Chlamydia trachomatis with reduced susceptibility to the HtrA inhibitor. The variants were changed in membrane fatty acid composition, outer membrane proteins, and transcription of stress genes. Earlier and more synchronous cellular exit was observed. Combined, this links stress response to fatty acids, membrane proteins, and HtrA interplay with the outcome of disrupted timing of chlamydial cellular exit.

Sex-Dependent Changes to the Intestinal and Hepatic Abundance of Drug Transporters and Metabolizing Enzymes in the SOD1G93A Mouse Model of Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is characterized by death and dysfunction of motor neurons that result in a rapidly progressing loss of motor function. While there are some data on alterations at the blood-brain barrier (BBB) in ALS and their potential impact on CNS trafficking of drugs, little is reported on the impact of this disease on the expression of drug-handling proteins in the small intestine and liver. This may impact the dosing of the many medicines that individuals with ALS are prescribed. In the present study, a proteomic evaluation was performed on small intestine and liver samples from postnatal day 120 SOD1G93A mice (a model of familial ALS that harbors a human mutant form of superoxide dismutase 1) and wild-type (WT) littermates (n = 7/genotype/sex). Untargeted, quantitative proteomics was undertaken using either label-based [tandem mass tag (TMT)] or label-free [data-independent acquisition (DIA)] acquisition strategies on high-resolution mass spectrometric instrumentation. Copper chaperone for superoxide dismutase (CCS) was significantly higher in SOD1G93A samples compared to the WT samples for both sexes and tissues, therefore representing a potential biomarker for ALS in this mouse model. Relative to WT mice, male SOD1G93A mice had significantly different proteins (Padj < 0.05, |fold-change|>1.2) in the small intestine (male 22, female 1) and liver (male 140, female 3). This included an up-regulation of intestinal transporters for dietary glucose [solute carrier (SLC) SLC5A1] and cholesterol (Niemann-Pick c1-like 1), as well as for several drugs (e.g., SLC15A1), in the male SOD1G93A mice. There was both an up-regulation (e.g., SLCO2A1) and down-regulation (ammonium transporter rh type b) of transporters in the male SOD1G93A liver. In addition, there was both an up-regulation (e.g., phosphoenolpyruvate carboxykinase) and down-regulation (e.g., carboxylesterase 1) of metabolizing enzymes in the male SOD1G93A liver. This proteomic data set identified male-specific changes to key small intestinal and hepatic transporters and metabolizing enzymes that may have important implications for the bioavailability of nutrients and drugs in individuals with ALS.

Sex differences in muscle protein expression and DNA methylation in response to exercise training.

BACKGROUND: Exercise training elicits changes in muscle physiology, epigenomics, transcriptomics, and proteomics, with males and females exhibiting differing physiological responses to exercise training. However, the molecular mechanisms contributing to the differing adaptations between the sexes are poorly understood. METHODS: We performed a meta-analysis for sex differences in skeletal muscle DNA methylation following an endurance training intervention (Gene SMART cohort and E-MTAB-11282 cohort). We investigated for sex differences in the skeletal muscle proteome following an endurance training intervention (Gene SMART cohort). Lastly, we investigated whether the methylome and proteome are associated with baseline cardiorespiratory fitness (maximal oxygen consumption; VO2max) in a sex-specific manner. RESULTS: Here, we investigated for the first time, DNA methylome and proteome sex differences in response to exercise training in human skeletal muscle (n = 78; 50 males, 28 females). We identified 92 DNA methylation sites (CpGs) associated with exercise training; however, no CpGs changed in a sex-dependent manner. In contrast, we identified 189 proteins that are differentially expressed between the sexes following training, with 82 proteins differentially expressed between the sexes at baseline. Proteins showing the most robust sex-specific response to exercise include SIRT3, MRPL41, and MBP. Irrespective of sex, cardiorespiratory fitness was associated with robust methylome changes (19,257 CpGs) and no proteomic changes. We did not observe sex differences in the association between cardiorespiratory fitness and the DNA methylome. Integrative multi-omic analysis identified sex-specific mitochondrial metabolism pathways associated with exercise responses. Lastly, exercise training and cardiorespiratory fitness shifted the DNA methylomes to be more similar between the sexes. CONCLUSIONS: We identified sex differences in protein expression changes, but not DNA methylation changes, following an endurance exercise training intervention; whereas we identified no sex differences in the DNA methylome or proteome response to lifelong training. Given the delicate interaction between sex and training as well as the limitations of the current study, more studies are required to elucidate whether there is a sex-specific training effect on the DNA methylome. We found that genes involved in mitochondrial metabolism pathways are differentially modulated between the sexes following endurance exercise training. These results shed light on sex differences in molecular adaptations to exercise training in skeletal muscle.

Phospho-Analyst: An Interactive, Easy-to-Use Web Platform To Analyze Quantitative Phosphoproteomics Data.

Phosphoproteomics is nowadays the method of choice to comprehensively identify and quantify thousands of phosphorylated peptides and their associated proteins with the goal of interrogating changes in signal transduction pathways and other cellular processes. One of the most popular software suites to analyze phosphoproteomic data sets is MaxQuant, which converts mass spectrometric raw data into quantitative information on phosphopeptides and proteins. However, despite the increased utilization of phosphoproteomics in biomedical research, simple and user-friendly tools supporting downstream statistical analysis and interpretation of these highly complex outputs are still lacking. We have therefore developed Phospho-Analyst, which─similar to its sibling LFQ-Analyst─is an easy-to-use, interactive web application specifically designed to reproducibly perform differential expression analyses with "one click" and to visualize phosphoproteomic results in a meaningful and practical manner. Furthermore, if quantitative total proteomic information is available for the same samples, Phospho-Analyst automatically normalizes all phosphoproteomic results to underlying protein abundance levels, thereby ensuring that only genuine changes in phosphorylation events are considered. As such, Phospho-Analyst can not only be used by experienced proteomic veterans but also by researchers without any prior knowledge in (phospho)proteomics, statistics, or bioinformatics. Phospho-Analyst, including a detailed manual, is freely available at https://analyst-suites.org/apps/phospho-analyst/.

SAPrIm, a semi-automated protocol for mid-throughput immunopeptidomics.

Human leukocyte antigen (HLA) molecules play a crucial role in directing adaptive immune responses based on the nature of their peptide ligands, collectively coined the immunopeptidome. As such, the study of HLA molecules has been of major interest in the development of cancer immunotherapies such as vaccines and T-cell therapies. Hence, a comprehensive understanding and profiling of the immunopeptidome is required to foster the growth of these personalised solutions. We herein describe SAPrIm, an Immunopeptidomics tool for the Mid-Throughput era. This is a semi-automated workflow involving the KingFisher platform to isolate immunopeptidomes using anti-HLA antibodies coupled to a hyper-porous magnetic protein A microbead, a variable window data independent acquisition (DIA) method and the ability to run up to 12 samples in parallel. Using this workflow, we were able to concordantly identify and quantify ~400 - 13000 unique peptides from 5e5 - 5e7 cells, respectively. Overall, we propose that the application of this workflow will be crucial for the future of immunopeptidome profiling, especially for mid-size cohorts and comparative immunopeptidomics studies.