SNP-SVant: A Computational Workflow to Predict and Annotate Genomic Variants in Organisms Lacking Benchmarked Variants.

Whole-genome sequencing is widely used to investigate population genomic variation in organisms of interest. Assorted tools have been independently developed to call variants from short-read sequencing data aligned to a reference genome, including single nucleotide polymorphisms (SNPs) and structural variations (SVs). We developed SNP-SVant, an integrated, flexible, and computationally efficient bioinformatic workflow that predicts high-confidence SNPs and SVs in organisms without benchmarked variants, which are traditionally used for distinguishing sequencing errors from real variants. In the absence of these benchmarked datasets, we leverage multiple rounds of statistical recalibration to increase the precision of variant prediction. The SNP-SVant workflow is flexible, with user options to tradeoff accuracy for sensitivity. The workflow predicts SNPs and small insertions and deletions using the Genome Analysis ToolKit (GATK) and predicts SVs using the Genome Rearrangement IDentification Software Suite (GRIDSS), and it culminates in variant annotation using custom scripts. A key utility of SNP-SVant is its scalability. Variant calling is a computationally expensive procedure, and thus, SNP-SVant uses a workflow management system with intermediary checkpoint steps to ensure efficient use of resources by minimizing redundant computations and omitting steps where dependent files are available. SNP-SVant also provides metrics to assess the quality of called variants and converts between VCF and aligned FASTA format outputs to ensure compatibility with downstream tools to calculate selection statistics, which are commonplace in population genomics studies. By accounting for both small and large structural variants, users of this workflow can obtain a wide-ranging view of genomic alterations in an organism of interest. Overall, this workflow advances our capabilities in assessing the functional consequences of different types of genomic alterations, ultimately improving our ability to associate genotypes with phenotypes. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Predicting single nucleotide polymorphisms and structural variations Support Protocol 1: Downloading publicly available sequencing data Support Protocol 2: Visualizing variant loci using Integrated Genome Viewer Support Protocol 3: Converting between VCF and aligned FASTA formats.

Structure-Aware Mycobacterium tuberculosis Functional Annotation Uncloaks Resistance, Metabolic, and Virulence Genes.

Accurate and timely functional genome annotation is essential for translating basic pathogen research into clinically impactful advances. Here, through literature curation and structure-function inference, we systematically update the functional genome annotation of Mycobacterium tuberculosis virulent type strain H37Rv. First, we systematically curated annotations for 589 genes from 662 publications, including 282 gene products absent from leading databases. Second, we modeled 1,711 underannotated proteins and developed a semiautomated pipeline that captured shared function between 400 protein models and structural matches of known function on Protein Data Bank, including drug efflux proteins, metabolic enzymes, and virulence factors. In aggregate, these structure- and literature-derived annotations update 940/1,725 underannotated H37Rv genes and generate hundreds of functional hypotheses. Retrospectively applying the annotation to a recent whole-genome transposon mutant screen provided missing function for 48% (13/27) of underannotated genes altering antibiotic efficacy and 33% (23/69) required for persistence during mouse tuberculosis (TB) infection. Prospective application of the protein models enabled us to functionally interpret novel laboratory generated pyrazinamide (PZA)-resistant mutants of unknown function, which implicated the emerging coenzyme A depletion model of PZA action in the mutants' PZA resistance. Our findings demonstrate the functional insight gained by integrating structural modeling and systematic literature curation, even for widely studied microorganisms. Functional annotations and protein structure models are available at https://tuberculosis.sdsu.edu/H37Rv in human- and machine-readable formats. IMPORTANCE Mycobacterium tuberculosis, the primary causative agent of tuberculosis, kills more humans than any other infectious bacterium. Yet 40% of its genome is functionally uncharacterized, leaving much about the genetic basis of its resistance to antibiotics, capacity to withstand host immunity, and basic metabolism yet undiscovered. Irregular literature curation for functional annotation contributes to this gap. We systematically curated functions from literature and structural similarity for over half of poorly characterized genes, expanding the functionally annotated Mycobacterium tuberculosis proteome. Applying this updated annotation to recent in vivo functional screens added functional information to dozens of clinically pertinent proteins described as having unknown function. Integrating the annotations with a prospective functional screen identified new mutants resistant to a first-line TB drug, supporting an emerging hypothesis for its mode of action. These improvements in functional interpretation of clinically informative studies underscore the translational value of this functional knowledge. Structure-derived annotations identify hundreds of high-confidence candidates for mechanisms of antibiotic resistance, virulence factors, and basic metabolism and other functions key in clinical and basic tuberculosis research. More broadly, they provide a systematic framework for improving prokaryotic reference annotations.

Transcriptional regulation of the caspofungin-induced cell wall damage response in Candida albicans.

The human fungal pathogen Candida albicans maintains pathogenic and commensal states primarily through cell wall functions. The echinocandin antifungal drug caspofungin inhibits cell wall synthesis and is widely used in treating disseminated candidiasis. Signaling pathways are critical in coordinating the adaptive response to cell wall damage (CWD). C. albicans executes a robust transcriptional program following caspofungin-induced CWD. A comprehensive analysis of signaling pathways at the transcriptional level facilitates the identification of prospective genes for functional characterization and propels the development of novel antifungal interventions. This review article focuses on the molecular functions and signaling crosstalk of the C. albicans transcription factors Sko1, Rlm1, and Cas5 in caspofungin-induced CWD signaling.

An expanded cell wall damage signaling network is comprised of the transcription factors Rlm1 and Sko1 in Candida albicans.

The human fungal pathogen Candida albicans is constantly exposed to environmental challenges impacting the cell wall. Signaling pathways coordinate stress adaptation and are essential for commensalism and virulence. The transcription factors Sko1, Cas5, and Rlm1 control the response to cell wall stress caused by the antifungal drug caspofungin. Here, we expand the Sko1 and Rlm1 transcriptional circuit and demonstrate that Rlm1 activates Sko1 cell wall stress signaling. Caspofungin-induced transcription of SKO1 and several Sko1-dependent cell wall integrity genes are attenuated in an rlm1Δ/Δ mutant strain when compared to the treated wild-type strain but not in a cas5Δ/Δ mutant strain. Genome-wide chromatin immunoprecipitation (ChIP-seq) results revealed numerous Sko1 and Rlm1 directly bound target genes in the presence of caspofungin that were undetected in previous gene expression studies. Notable targets include genes involved in cell wall integrity, osmolarity, and cellular aggregation, as well as several uncharacterized genes. Interestingly, we found that Rlm1 does not bind to the upstream intergenic region of SKO1 in the presence of caspofungin, indicating that Rlm1 indirectly controls caspofungin-induced SKO1 transcription. In addition, we discovered that caspofungin-induced SKO1 transcription occurs through self-activation. Based on our ChIP-seq data, we also discovered an Rlm1 consensus motif unique to C. albicans. For Sko1, we found a consensus motif similar to the known Sko1 motif for Saccharomyces cerevisiae. Growth assays showed that SKO1 overexpression suppressed caspofungin hypersensitivity in an rlm1Δ/Δ mutant strain. In addition, overexpression of the glycerol phosphatase, RHR2, suppressed caspofungin hypersensitivity specifically in a sko1Δ/Δ mutant strain. Our findings link the Sko1 and Rlm1 signaling pathways, identify new biological roles for Sko1 and Rlm1, and highlight the complex dynamics underlying cell wall signaling.

Cathepsin A inhibition attenuates myocardial infarction-induced heart failure on the functional and proteomic levels.

BACKGROUND: Myocardial infarction (MI) is a major cause of heart failure. The carboxypeptidase cathepsin A is a novel target in the treatment of cardiac failure. We aim to show that recently developed inhibitors of the protease cathepsin A attenuate post-MI heart failure. METHODS: Mice were subjected to permanent left anterior descending artery (LAD) ligation or sham operation. 24 h post-surgery, LAD-ligated animals were treated with daily doses of the cathepsin A inhibitor SAR1 or placebo. After 4 weeks, the three groups (sham, MI-placebo, MI-SAR1) were evaluated. RESULTS: Compared to sham-operated animals, placebo-treated mice showed significantly impaired cardiac function and increased plasma BNP levels. Cathepsin A inhibition prevented the increase of plasma BNP levels and displayed a trend towards improved cardiac functionality. Proteomic profiling was performed for the three groups (sham, MI-placebo, MI-SAR1). More than 100 proteins were significantly altered in placebo-treated LAD ligation compared to the sham operation, including known markers of cardiac failure as well as extracellular/matricellular proteins. This ensemble constitutes a proteome fingerprint of myocardial infarction induced by LAD ligation in mice. Cathepsin A inhibitor treatment normalized the marked increase of the muscle stress marker CA3 as well as of Igγ 2b and fatty acid synthase. For numerous further proteins, cathepsin A inhibition partially dampened the LAD ligation-induced proteome alterations. CONCLUSIONS: Our proteomic and functional data suggest that cathepsin A inhibition has cardioprotective properties and support a beneficial effect of cathepsin A inhibition in the treatment of heart failure after myocardial infarction.

Automated peptide mapping and protein-topographical annotation of proteomics data.

BACKGROUND: In quantitative proteomics, peptide mapping is a valuable approach to combine positional quantitative information with topographical and domain information of proteins. Quantitative proteomic analysis of cell surface shedding is an exemplary application area of this approach. RESULTS: We developed ImproViser ( http://www.improviser.uni-freiburg.de) for fully automated peptide mapping of quantitative proteomics data in the protXML data. The tool generates sortable and graphically annotated output, which can be easily shared with further users. As an exemplary application, we show its usage in the proteomic analysis of regulated intramembrane proteolysis. CONCLUSION: ImproViser is the first tool to enable automated peptide mapping of the widely-used protXML format.