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bioRxiv2021

Drosophila Evolution over Space and Time (DEST) - A New Population Genomics Resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last 20 years. A major challenge is the integration of these disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution and population structure of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 population samples from over 100 locations in >20 countries on four continents based on a combination of 121 unpublished and 150 previously published genomic datasets. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.

genomics↗

bioRxiv2021

Atorvastatin effectively inhibits late replicative cycle steps of SARS-CoV-2 in vitro

IntroductionSARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) has caused a pandemic of historic proportions and continues to spread worldwide. Currently, there is no effective therapy against this virus. This article evaluated the in vitro antiviral effect of Atorvastatin against SARS-CoV-2 and also identified the interaction affinity between Atorvastatin and three SARS-CoV-2 proteins, using in silico structure-based molecular docking approach. Materials and methodsThe antiviral activity of Atorvastatin against SARS-CoV-2 was evaluated by three different treatment strategies using a clinical isolate of SARS-CoV-2. The interaction of Atorvastatin with Spike, RNA-dependent RNA polymerase (RdRp) and 3C-like protease (3CLpro) was evaluated by molecular docking. ResultsAtorvastatin showed anti-SARS-CoV-2 activity of 79%, 54.8%, 22.6% and 25% at 31.2, 15.6, 7.9, and 3.9 {micro}M, respectively, by pre-post-treatment strategy. In addition, atorvastatin demonstrated an antiviral effect of 26.9% at 31.2 {micro}M by pre-infection treatment. This compound also inhibited SARS-CoV-2 in 66.9%, 75%, 27.9% and 29.2% at concentrations of 31.2, 15.6, 7.9, and 3.9 {micro}M, respectively, by post-infection treatment. The interaction of atorvastatin with SARS-CoV-2 Spike, RdRp and 3CL protease yielded a binding affinity of -8.5 Kcal/mol, -6.2 Kcal/mol, and -7.5 Kcal/mol, respectively. ConclusionOur study demonstrated the in vitro anti-SARS-CoV-2 activity of Atorvastatin, mainly against the late steps of the viral replicative cycle. A favorable binding affinity with viral proteins by bioinformatics methods was also shown. Due to its low cost, availability, well-established safety and tolerability, and the extensive clinical experience of atorvastatin, it could prove valuable in reducing morbidity and mortality from COVID-19. ImportanceThe COVID-19 pandemic constitutes the largest global public health crisis in a century, with enormous health and socioeconomic challenges. Therefore, it is necessary to search for specific antivirals against its causative agent (SARS-CoV-2). In this sense, the use of existing drugs may represent a useful treatment option in terms of safety, cost-effectiveness, and timeliness. Atorvastatin is widely used to prevent cardiovascular events. This compound modulates the synthesis of cholesterol, a molecule necessary in different stages of the viral replicative cycle. Our study demonstrated the antiviral potential of atorvastatin against SARS-CoV-2, using an in vitro model. Furthermore, the ability of Atorvastatin to directly interfere with three viral targets (Spike, RdRp and 3CL protease) was demonstrated by bioinformatic methods. This compound is a well-studied, low-cost, and generally well-tolerated drug, so it could be a promising antiviral for the treatment of COVID-19.

microbiology↗

bioRxiv2021

Discovery and validation of novel human genomic safe harbor sites for gene and cell therapies

Existing approaches for the integration and expression of genes of interest in a desired human cellular context are marred by the safety concerns related to either the random nature of viral-mediated integration or unpredictable pattern of gene expression in currently employed targeted genomic integration sites. Disadvantages of these methods lead to their limited use in clinical practice, thus encouraging future research in identifying novel human genomic sites that allow for predictable and safe expression of genes of interest. We conducted a bioinformatic search followed by experimental validation of novel genomic sites and identified two that demonstrated stable expression of integrated reporter and therapeutic genes without detrimental changes to cellular transcriptome. The cell-type agnostic criteria used in our bioinformatic search suggest wide-scale applicability of our sites for engineering of a diverse range of tissues for therapeutic as well as enhancement purposes, including modified T-cells for cancer therapy and engineered skin to ameliorate inherited diseases and aging. Additionally, the stable and robust levels of gene expression from identified sites allow for their use in industry-scale biomanufacturing of desired proteins in human cells.

genomics↗

bioRxiv2021

A multiepitope fusion protein-based p-ELISA method for diagnosing bovine and goat brucellosis

In recent years, the incidence of brucellosis has increased annually, which has caused tremendous economic losses in agriculture and husbandry in various countries. Therefore, developing rapid, sensitive and specific diagnostic techniques for brucellosis has become critical brucellosis research. Bioinformatics technology was used to predict the B cell epitopes of the main antigen proteins of Brucella, and the validity of each epitope was verified by indirect enzyme-linked immunosorbent assay (iELISA). The verified epitopes were connected in series to construct a multiepitope fusion protein, goat, bovine brucellosis sera, and rabbit sera were collected to verify the antigenicity and specificity of this protein. Then, the fusion protein was used as a diagnostic antigen to construct paper-based ELISA (p-ELISA) technology. A total of 22 effective epitopes were predicted, and a fusion protein was successfully constructed, which showed good antigenicity and specificity. The constructed p-ELISA method was used for the simultaneous detection of bovine and goat brucellosis. ROC curve analysis showed that the sensitivity and specificity of protein detection in goat serum were 98.85% and 98.51%, respectively. The positive and the negative predictive value was 99.29% and 98.15%, respectively. When assessing bovine serum, the sensitivity and specificity were 97.85% and 96.61%, respectively. The positive and the negative predictive value was 98.28% and 97.33%, respectively. This study combined bioinformatics, fusion protein development and p-ELISA technologies to establish a sensitive and specific rapid diagnosis technology for brucellosis that can be used to assess the serum of bovine, goats and other livestock. IMPORTANCEBrucellosis has caused tremendous economic losses in agriculture and husbandry in various countries. Therefore, developing rapid, sensitive and specific diagnostic techniques for brucellosis has become critical brucellosis research. In this study, we used immunoinformatic technology to predict the B cell epitopes in the major outer membrane proteins of Brucella, synthesized polypeptides and coupled them with KLH, screened these polypeptides by iELISA methods, selected effective polypeptides as diagnostic antigens, and established a p-ELISA for brucellosis diagnosis based on a multiepitope fusion protein that can be used to assess the serum of bovine, goats and other livestock.

microbiology↗

bioRxiv2021

Critical Assessment of Metaproteome Investigation (CAMPI): a Multi-Lab Comparison of Established Workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carried out the first community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluated the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observed that variability at the peptide level was predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappeared at the protein group level. While differences were observed for predicted community composition, similar functional profiles were obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

microbiology↗

bioRxiv2021

iTaxoTools 0.1: Kickstarting a specimen-based software toolkit for taxonomists

While powerful and user-friendly software suites exist for phylogenetics, and an impressive cybertaxomic infrastructure of online species databases has been set up in the past two decades, software specifically targeted at facilitating alpha-taxonomic work, i.e., delimiting and diagnosing species, is still in its infancy. Here we present a project to develop a bioinformatic toolkit for taxonomy, based on open-source Python code, including tools focusing on species delimitation and diagnosis and centered around specimen identifiers. At the core of iTaxoTools is user-friendliness, with numerous autocorrect options for data files and with intuitive graphical user interfaces. Assembled standalone executables for all tools or a suite of tools with a launcher window will be distributed for Windows, Linux, and Mac OS systems, and in the future also implemented on a web server. The alpha version (iTaxoTools 0.1) distributed with this paper contains GUI versions of six species delimitation programs (ABGD, ASAP, DELINEATE, GMYC, PTP, tr2) and a simple threshold-clustering delimitation tool. There are also new Python implementations of existing algorithms, including tools to compute pairwise DNA distances, ultrametric time trees based on non-parametric rate smoothing, species-diagnostic nucleotide positions, and standard morphometric analyses. Other utilities convert among different formats of molecular sequences, geographical coordinates, and units; merge, split and prune sequence files and tables; and perform simple statistical tests. As a future perspective, we envisage iTaxoTools to become part of a bioinformatic pipeline for next-generation taxonomy that accelerates the inventory of life while maintaining high-quality species hypotheses.

evolutionary biology↗

bioRxiv2021

Histologic and Proteomic Remodeling of the Pulmonary Veins and Arteries in a Porcine Model of Chronic Pulmonary Venous Hypertension

AIMIn heart failure (HF), pulmonary venous hypertension (PVH) produces pulmonary hypertension (PH) with remodeling of pulmonary veins (PV) and arteries (PA). In a porcine PVH model, we performed proteomic-based bioinformatics to investigate unique pathophysiologic mechanisms mediating PA and PV remodeling. METHODSLarge PV were banded (PVH, n= 10) or not (Sham, n=9) in piglets. At sacrifice, PV and PA were perfusion labeled for vessel specific histology and proteomics. The PA and PV were separately sampled with laser-capture micro-dissection for mass spectrometry. RESULTSPulmonary vascular resistance (Wood Units; 8.6 versus 2.0) and PA (19.9 versus 10.3) and PV (14.2 versus 7.6) wall thickness/external diameter (%) were increased in PVH (p<0.01 for all). Similar numbers of proteins were identified in PA (2093) and PV (2085) with 94% overlap, but biological processes differed. There were more differentially expressed proteins (287 versus 161), altered canonical pathways (17 versus 3) and predicted up-stream regulators (PUSR; 22 versus 6) in PV than PA. In PA and PV, bioinformatics indicated activation of the integrated stress response and mTOR signaling with dysregulated growth. In PV, there was also activation of Rho/Rho kinase signaling with decreased actin cytoskeletal signaling and altered tight and adherens junctions, ephrin B, and caveolar mediated endocytosis signaling; all indicating disrupted endothelial barrier function. Indeed, protein biomarkers and the top PUSR in PV (TGF-{beta}) indicated endothelial mesenchymal transition (EndoMT) in PV. Findings were confirmed in human autopsy specimens. CONCLUSIONThese findings provide new therapeutic targets to oppose pulmonary vascular remodeling in HF-related PH. TRANSLATIONAL PERSPECTIVEIn heart failure (HF) related (Group 2) PH, despite remodeling of pulmonary veins (PV) and arteries (PA), therapies targeting PA biology altered in Group 1 PH have not shown consistent benefit. In a porcine Group 2 PH model, microdissection allowed vessel specific (PV and PA) proteomics/bioinformatics. In PA and PV, the integrated stress response and mTOR signaling were activated with evidence of dysregulated growth. In PV, many more pathways were altered with broad evidence of disrupted endothelial barrier function and endothelial mesenchymal transition. Findings were confirmed in human specimens and provide new therapeutic targets in Group 2 PH.

physiology↗

bioRxiv2021

A conserved Guided Entry of Tail-anchored pathway is involved in the trafficking of tail-anchored membrane proteins in Plasmodium falciparum.

Tail-anchored (TA) proteins are defined by the absence of N-terminus signal sequence and the presence of a single transmembrane domain (TMD) proximal to their extreme C-terminus. They play fundamental roles in cellular processes including vesicular trafficking, protein translocation and quality control. Accordingly, TA proteins are post-translationally integrated by the Guided Entry of TA (GET) pathway to the cellular membranes; with their N-terminus oriented towards the cytosol and C-terminus facing the organellar lumen. The TA repertoire and the GET machinery have been extensively characterized in the yeast and mammalian systems, however, they remain elusive in the human malaria parasite Plasmodium falciparum. In this study, we bioinformatically predicted a total of 63 TA proteins in the P. falciparum proteome and revealed the association of their subset with the P. falciparum homolog of Get3 (PfGet3). In addition, our proximity labelling studies either definitively identified or shortlisted the other eligible GET constituents, and our in vitro association studies validated associations between PfGet3 and the corresponding homologs of Get4 and Get2 in P. falciparum. Collectively, this study reveals the presence of proteins with hallmark TA signatures and the involvement of evolutionary conserved GET trafficking pathway for their targeted delivery within the parasite. SynopsisTail-anchored (TA) proteins, characterized by an absence of N-terminal signal sequence and the presence of a transmembrane domain near the C-terminus, are post-translationally inserted at organellar membranes by the conserved multi-component Guided Entry of TA (GET) pathway. Here, we identified the putative homologs of GET machinery in the human malaria parasite Plasmodium falciparum and revealed their association with a subset of bioinformatically predicted 63 putative TA proteins, thereby validating the functional existence of this trafficking pathway within the apicomplexan parasite. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=191 HEIGHT=200 SRC="FIGDIR/small/442402v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1c0239org.highwire.dtl.DTLVardef@d5ffbaorg.highwire.dtl.DTLVardef@1884a50org.highwire.dtl.DTLVardef@c6df7d_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2021

Population-level genome-wide STR typing in Plasmodium species reveals higher resolution population structure and genetic diversity relative to SNP typing

Short tandem repeats (STRs) are highly informative genetic markers that have been used extensively in population genetics analysis. They are an important source of genetic diversity and can also have functional impact. Despite the availability of bioinformatic methods that permit large-scale genome-wide genotyping of STRs from whole genome sequencing data, they have not previously been applied to sequencing data from large collections of malaria parasite field samples. Here, we have genotyped STRs using HipSTR in more than 3,000 Plasmodium falciparum and 174 Plasmodium vivax published whole-genome sequence data from samples collected across the globe. High levels of noise and variability in the resultant callset necessitated the development of a novel method for quality control of STR genotype calls. A set of high-quality STR loci (6,768 from P. falciparum and 3,496 from P. vivax) were used to study Plasmodium genetic diversity, population structures and genomic signatures of selection and these were compared to genome-wide single nucleotide polymorphism (SNP) genotyping data. In addition, the genome-wide information about genetic variation and other characteristics of STRs in P. falciparum and P. vivax have been made available in an interactive web-based R Shiny application PlasmoSTR (https://github.com/bahlolab/PlasmoSTR). Author summaryMalaria is a severe disease caused by a genus of parasites called Plasmodium and is transmitted to humans through infected Anopheles mosquitoes. P. falciparum and P. vivax are the predominant species responsible for more than 95% of all human malaria infections which continue to pose a significant challenge to human health. Antimalarial drug resistance is a serious threat hindering the elimination of malaria. As such, it is important to understand the role of genomic variation in the development of antimalarial drug resistance. STRs are an important source of genomic variation that, from a population genetics perspective, have several advantages over SNPs, including being highly polymorphic, having a higher mutation rate, and having been widely used to study the population structure and genetic diversity. However, STRs are not routinely genotyped with bioinformatic tools across the whole genome with short read sequencing data because they are difficult to identify and genotype accurately, as they vary in size and may align poorly to the reference genome, therefore requiring rigorous quality control (QC). In this study, we genotype STRs using HipSTR[1] in more than 3,000 P. falciparum and 174 P. vivax whole-genome sequence samples collected world-wide. We develop a multivariable logistic regression model for the measurement and prediction of the quality of STRs. In addition, we use a set of genome-wide high-quality STRs to study parasite population genetics and compare them to genome-wide SNP genotyping data, revealing both high consistency with SNP based signals, as well as identifying some signals unique to the STR marker data. These results demonstrate that the identification of highly informative STR markers from large numbers of population samples is a powerful approach to study the genetic diversity, population structures and genomic signatures of selection in P. falciparum and P. vivax. Furthermore, we built an interactive web-based R Shiny application PlasmoSTR (https://github.com/bahlolab/PlasmoSTR) that includes genome-wide information about genetic variation and other characteristics of the high quality STRs identified in P. falciparum and P. vivax, allowing researchers to explore and visualize the specific STRs.

genetics↗

bioRxiv2021

TnCentral: A Prokaryotic Transposable Element Database and Web Portal for Transposon Analysis

We describe here the structure and organization of TnCentral (https://tncentral.proteininformationresource.org/). a web resource for prokaryotic transposable elements (TE). TnCentral currently contains ~400 carefully annotated TE, including transposons from the Tn3, Tn7, Tn402 and Tn554 families, compound transposons, integrons and associated insertion sequences (IS). These TE carry passenger genes, including genes conferring resistance to over 25 classes of antibiotics and nine types of heavy metal as well as genes responsible for pathogenesis in plants, toxin/antitoxin gene pairs, transcription factors and genes involved in metabolism. Each TE has its own entry page providing details about its transposition genes, passenger genes, and other sequence features required for transposition as well as a graphical map of all features. TnCentral content can be browsed and queried through text and sequence-based searches with a graphic output. We describe three use cases, which illustrate how the search interface, results tables, and entry pages can be used to explore and compare TEs. TnCentral also includes downloadable software to facilitate user-driven identification, with manual annotation, of certain types of TE in genomic sequences. Through the TnCentral homepage, users can also access TnPedia which provides comprehensive reviews of the major TE families including an extensive general section, and specialised sections with descriptions of insertion sequence and transposon families. TnCentral and TnPedia are intuitive resources that can be used by clinicians and scientists to assess TE diversity in clinical, veterinary and environmental samples. ImportanceThe ability of bacteria to undergo rapid evolution and adapt to changing environmental circumstances drives the public health crisis of multiple antibiotic resistance as well as outbreaks of disease in economically important agricultural crops and animal husbandry. Prokaryotic transposable elements (TE) play a critical role in this. Many carry "passenger genes" (not required for the transposition process) conferring resistance to antibiotics or heavy metals or causing disease in plants and animals. Passenger genes are spread by the normal TE transposition activities, by insertion into plasmids which then spread via conjugation within and across bacterial populations. Thus, an understanding of TE composition and transposition mechanisms is key to developing strategies to combat bacterial pathogenesis. Toward this end, we have developed TnCentral, a bioinformatics resource dedicated to describing and exploring the structural and functional features of prokaryotic TE and whose use is intuitive and accessible to users with or without bioinformatics expertise.

genomics↗

bioRxiv2021

Comparative phylogenomic analysis reveals evolutionary genomic changes and novel toxin families in endophytic Liberibacter pathogens

Liberibacter pathogens are the causative agents of several severe crop diseases worldwide, including citrus Huanglongbing and potato Zebra Chip. These bacteria are endophytic and non-culturable, which makes experimental approaches challenging and highlights the need for bioinformatic analysis in advancing our understanding about Liberibacter pathogenesis. Here, we performed an in-depth comparative phylogenomic analysis of the Liberibacter pathogens and their free-living, nonpathogenic, ancestral species, aiming to identify the major genomic changes and determinants associated with their evolutionary transitions in living habitats and pathogenicity. We found that prophage loci represent the most variable regions among Liberibacter genomes. Using gene neighborhood analysis and phylogenetic classification, we systematically recovered, annotated, and classified all prophage loci into four types, including one previously unrecognized group. We showed that these prophages originated through independent gene transfers at different evolutionary stages of Liberibacter and only the SC-type prophage was associated with the emergence of the pathogens. Using ortholog clustering, we vigorously identified two additional sets of genomic genes, which were either lost or gained in the ancestor of the pathogens. Consistent with the habitat change, the lost genes were enriched for biosynthesis of cellular building blocks. Importantly, among the gained genes, we uncovered several previously unrecognized toxins, including a novel class of polymorphic toxins, a YdjM phospholipase toxin, and a secreted EEP protein. Our results substantially extend the knowledge on the evolutionary events and potential determinants leading to the emergence of endophytic, pathogenic Liberibacter species and will facilitate the design of functional experiments and the development of new detection and blockage methods of these pathogens. ImportanceLiberibacter pathogens are associated with several severe crop diseases, including citrus Huanglongbing, the most destructive disease to the citrus industry. Currently, no effective cure or treatments are available, and no resistant citrus variety has been found. The fact that these obligate endophytic pathogens are not culturable has made it extremely challenging to experimentally uncover from the whole genome the genes/proteins important to Liberibacter pathogenesis. Further, earlier bioinformatics studies failed to identify the key genomic determinants, such as toxins and effector proteins, that underlie the pathogenicity of the bacteria. In this study, an in-depth comparative genomic analysis of Liberibacter pathogens together with their ancestral non-pathogenic species identified the prophage loci and several novel toxins that are evolutionarily associated with the emergence of the pathogens. These results shed new lights on the disease mechanism of Liberibacter pathogens and will facilitate the development of new detection and blockage methods targeting the toxins.

microbiology↗

bioRxiv2021

Synthetic Natural Product-Inspired Peptides

Natural products (NPs) are a bountiful source of bioactive molecules. Unfortunately, discovery of novel bioactive NPs is challenging due to cryptic biosynthetic gene clusters (BGCs), low titers, and arduous purifications. Herein, we describe SNaPP (Synthetic Natural Product Inspired Peptides), a method for identifying NP-inspired bioactive molecules. SNaPP expedites bioactive molecule discovery by combining bioinformatics predictions of non-ribosomal peptide synthetases (NRPS) with chemical synthesis of the predicted NPs (pNPs). SNaPP utilizes a recently discovered cyclase, the penicillin binding protein (PBP)-like cyclase, as the lynchpin for the development of a library of cyclic peptide pNPs. Analysis of 500 BGCs allowed for identification of 131 novel pNPs. 51 diverse pNPs were synthesized using solid phase peptide synthesis and in-solution cyclization. Antibacterial testing revealed 14 pNPs with antibiotic activity, including activity against multidrug-resistant Gram-negative bacteria. Overall, SNaPP demonstrates the power of combining bioinformatics predictions with chemical synthesis to accelerate the discovery of bioactive molecules.

microbiology↗

bioRxiv2021

Train-the-Trainer as an Effective Approach to Building Global Networks of Experts in Genomic Surveillance of AMR

Advanced genomics and sequencing technologies are increasingly becoming critical for global health applications such as pathogen and antimicrobial resistance (AMR) surveillance. Limited resources challenge capacity development in low- and middle-income countries (LMICs), with few countries having genomics facilities and adequately trained staff. Training research and public health experts who are directly involved in the establishment of such facilities offers an effective, but limited, solution to a growing need. Instead, training them to impart their knowledge and skills to others provides a sustainable model for scaling up the much needed capacity and capability for genomic sequencing and analysis locally with global impact. We designed and developed a Train-the-Trainer course integrating pedagogical aspects with genomic and bioinformatics activities. The course was delivered to 18 participants from 12 countries in Africa, Asia, and Latin America. A combination of teaching strategies culminating in a group project created a foundation for continued development at home institutions. Upon follow-up after 6 months, at least 40% of trainees had initiated training programs and collaborations to build capacity at local, national, and regional level. This work provides a framework for implementing a training and capacity building program for the application of genomics tools and resources in AMR surveillance. 40-word summaryThis work provides a framework for implementing a training and capacity building program for the application of genomics tools and resources in AMR surveillance. We outline a Train-the-Trainer course integrating pedagogical aspects with genomic and bioinformatics activities.

scientific communication and education↗

bioRxiv2021

The SARS-CoV-2 host cell membrane fusion protein TMPRSS2 is a tumor suppressor and its downregulation correlates with increased antitumor immunity and immunotherapy response in lung adenocarcinoma

BackgroundTMPRSS2 is a host cell membrane fusion protein for SARS-CoV-2 invading human host cells. It also has an association with cancer, particularly prostate cancer. However, its association with lung cancer remains insufficiently explored. Thus, an in-depth investigation into the association between TMPRSS2 and lung cancer is significant, considering that lung cancer is the leading cause of cancer death and that the lungs are the primary organ SARS-CoV-2 attacks. MethodsUsing five lung adenocarcinoma (LUAD) genomics datasets, we explored associations between TMPRSS2 expression and immune signatures, cancer-associated pathways, tumor progression phenotypes, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we validated the findings from the bioinformatics analysis by performing in vitro experiments with the human LUAD cell line A549 and in vivo experiments with mouse tumor models. We also validated our findings in LUAD patients from Jiangsu Cancer Hospital, China. ResultsTMPRSS2 expression levels were negatively correlated with the enrichment levels of CD8+ T and NK cells and immune cytolytic activity in LUAD, which represent antitumor immune signatures. Meanwhile, TMPRSS2 expression levels were negatively correlated with the enrichment levels of CD4+ regulatory T cells and myeloid-derived suppressor cells and PD-L1 expression levels in LUAD, which represent antitumor immunosuppressive signatures. However, TMPRSS2 expression levels showed a significant positive correlation with the ratios of immune-stimulatory/immune-inhibitory signatures (CD8+ T cells/PD-L1) in LUAD. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory signatures than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with elevated activities of many oncogenic pathways in LUAD, including cell cycle, mismatch repair, p53, and extracellular matrix (ECM) signaling. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor advancement, and worse survival in LUAD. In vitro and in vivo experiments validated the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1. ConclusionsTMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a connection between lung cancer and pneumonia caused by SARS-CoV-2 infection.

immunology↗

bioRxiv2021

Combinations of Peptides Synergistically Activate the Regenerative Capacity of Skin Cells In Vitro

OBJECTIVETo explore synergistic effects related to skin regeneration, peptides with distinct biological mechanisms of action were evaluated in combination in different skin cell lines in the presence or absence of niacinamide (Nam). Furthermore, the synergistic responses of peptide combinations on global gene expression were compared to the changes that occur with fractional laser resurfacing treatment, a gold standard approach for skin rejuvenation, to further define optimal peptide combinations. METHODSMicroarray profiling was used to characterize the biological responses of peptide combinations (+/- Nam) relative to the individual components in epidermal keratinocyte and dermal fibroblast cell lines. Cellular functional assays were utilized to confirm the synergistic effects of peptide combinations. Bioinformatics approaches were used to link the synergistic effects of peptide combinations on gene expression to the transcriptomics of the skin rejuvenation response from fractional laser treatment. RESULTSMicroarray analysis of skin cells treated with peptide combinations revealed synergistic changes in gene expression compared to individual peptide controls. Bioinformatic analysis of synergy genes in keratinocytes revealed activation of NRF2-mediated oxidative stress responses by a combination of Ac-PPYL, Pal-KTTKS, and Nam. Additional analysis revealed direct downstream transcriptional targets of NRF2/ARE exhibiting synergistic regulation by this combination of materials, which was corroborated by a cellular reporter assay. NRF2-mediated oxidative stress response pathways were also found to be activated in the transcriptomics of the early skin rejuvenation response to fractional laser treatment, suggesting the importance of this biology in the early stages of tissue repair. Additionally, a second combination of peptides (pal-KT and Ac-PPYL) was found to synergistically restore cellular ATP levels that had been depleted due to the presence of ROS, indicating an additional mechanism whereby peptide synergies may accelerate skin repair. CONCLUSIONThrough combinatorial synergy studies, we have identified additional in vitro skin repair mechanisms beyond the previously described functions of individual peptides and correlated these to the transcriptomics of the skin rejuvenation response of fractional laser treatment. These findings suggest that specific peptides can act together, via complementary and synergistic mechanisms, to holistically enhance the regenerative capacity of in vitro skin cells.

molecular biology↗

bioRxiv2021

GAIT-GM integrative cross-omics analyses reveal cholinergic defects in a C. elegans model of Parkinson's disease

BackgroundParkinsons disease (PD) is a disabling neurodegenerative disorder in which multiple cell types, including dopaminergic and cholinergic neurons, are affected. The mechanisms of neurodegeneration in PD are unknown, limiting the development of therapies directed at disease-relevant molecular targets. C. elegans is a genetically tractable model system that can be used to disentangle disease mechanisms in complex diseases such as PD. Such mechanisms can be studied combining high-throughput molecular profiling technologies such as transcriptomics and metabolomics. However, the integrative analysis of multi-omics data in order to unravel disease mechanisms is a challenging task without advanced bioinformatics training. Galaxy, a widely-used resource for enabling bioinformatics analysis by the broad scientific community, has poor representation of multi-omics integration pipelines. ResultsWe present the integrative analysis of gene expression and metabolite levels of a C. elegans PD model using GAIT-GM, a new Galaxy tool for multi-omics data analysis. Using GAIT-GM, we discovered an association between branched-chain amino acid metabolism and cholinergic neurons in the C. elegans PD model. An independent follow-up experiment uncovered cholinergic neurodegeneration in the C. elegans model that is consistent with cholinergic cell loss observed in PD. ConclusionGAIT-GM is an easy to use Galaxy-based tool for generating novel testable hypotheses of disease mechanisms involving gene-metabolite relationships.

neuroscience↗

bioRxiv2021

COPILOT: a Containerised wOrkflow for Processing ILlumina genOtyping daTa

BackgroundThe Illumina genotyping microarrays generate data in image format, which is processed by the platform-specific software GenomeStudio, followed by an array of complex bioinformatics analyses. This process can be time-consuming, lead to reproducibility errors, and be a daunting task for novice bioinformaticians. ResultsHere we introduce the COPILOT (Containerised wOrkflow for Processing ILlumina genOtyping daTa) protocol, which provides an in-depth and clear guide to process raw Illumina genotype data in GenomeStudio, followed by a containerised workflow to automate an array of complex bioinformatics analyses involved in a GWAS quality control (QC). The COPILOT protocol was applied to two independent cohorts consisting of 2791 and 479 samples genotyped on the Infinium Global Screening (GSA) array with Multi-disease (MD) drop-in (~750,000 markers) and the Infinium H3Africa consortium array (~2,200,000 markers) respectively. Following the COPILOT protocol, an average sample quality improvement of 1.24% was observed across sample call rates, with notable improvement for low-quality samples. For example, from the 3270 samples processed, 141 samples had an initial sample call rate below 98%, averaging 96.6% (95% CI 95.6-97.7%), which is considered below the acceptable sample call rate threshold for a typical GWAS analysis. However, following the COPILOT protocol, all 141 samples had a call rate above 98% after QC and averaged 99.6% (95% CI 99.5-99.7%). In addition, the COPILOT pipeline automatically identified potential data issues, including gender discrepancies, heterozygosity outliers, related individuals, and population outliers through ancestry estimation. ConclusionsThe COPILOT protocol makes processing Illumina genotyping data transparent, effortless and reproducible. The container is deployable on multiple platforms, improves data quality, and the end product is analysis-ready PLINK formatted data, with a comprehensive and interactive summary report to guide the user for further data analyses.

genomics↗

bioRxiv2021

In-depth analysis of Bacillus anthracis 16S rRNA genes and transcripts reveals intra- and intergenomic diversity and facilitates anthrax detection

Analysis of 16S ribosomal RNA (rRNA) genes provides a central means of taxonomic classification of bacterial species. Based on presumed sequence identity among species of the Bacillus cereus sensu lato group, the 16S rRNA genes of B. anthracis have been considered unsuitable for diagnosis of the anthrax pathogen. With the recent identification of a single nucleotide polymorphism in some 16S rRNA gene copies, specific identification of B. anthracis becomes feasible. Here, we designed and evaluated a set of in situ-, in vitro- and in silico-assays to assess the yet unknown 16S-state of B. anthracis from different perspectives. Using a combination of digital PCR, fluorescence in situ hybridization, long-read genome sequencing and bioinformatics we were able to detect and quantify a unique 16S rRNA gene allele of B. anthracis (16S-BA-allele). This allele was found in all available B.anthracis genomes and may facilitate differentiation of the pathogen from any close relative. Bioinformatics analysis of 959 B. anthracis genome data-sets inferred that abundances and genomic arrangements of the 16S-BA-allele and the entire rRNA operon copy-numbers differ considerably between strains. Expression ratios of 16S-BA-alleles were proportional to the respective genomic allele copy-numbers. The findings and experimental tools presented here provide detailed insights into the intra- and intergenomic diversity of 16S rRNA genes and may pave the way for improved identification of B. anthracis and other pathogens with diverse rRNA operons.

microbiology↗