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bioRxiv2022

Discovery of a monomeric green fluorescent protein sensor for chloride by structure-guided bioinformatics

Chloride is an essential anion for all forms of life. Beyond electrolyte balance, an increasing body of evidence points to new roles for chloride in normal physiology and disease. Over the last two decades, this understanding has been advanced by chloride-sensitive fluorescent proteins for imaging applications in living cells. To our surprise, these sensors have been primarily engineered from the green fluorescent protein (GFP) found in the jellyfish Aequorea victoria. However, the GFP family has a rich sequence space that could already encode for new sensors with desired properties, thereby minimizing protein engineering efforts and accelerating biological applications. To efficiently sample this space, we present and validate a stepwise bioinformatics strategy focused first on the chloride binding pocket and second on a monomeric oligomerization state. Using this, we identified GFPxm163 from GFPxm found in the jellyfish Aequorea macrodactyla. In vitro characterization shows that the binding of chloride as well as bromide, iodide, and nitrate rapidly tunes the ground state chromophore equilibrium from the phenolate to the phenol state generating a pH-dependent, turn-off fluorescence response. Furthermore, live-cell fluorescence microscopy reveals that GFPxm163 provides a reversible, yet indirect readout of chloride transport via iodide exchange. With this demonstration, we anticipate that the paring of bioinformatics with protein engineering methods will provide an efficient methodology to discover and design new chloride-sensitive fluorescent proteins for cellular applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/499230v1_ufig1.gif" ALT="Figure 1"> View larger version (68K): org.highwire.dtl.DTLVardef@9c0daaorg.highwire.dtl.DTLVardef@14553cforg.highwire.dtl.DTLVardef@817107org.highwire.dtl.DTLVardef@23a6ba_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2022

Collaborative partnership model to transform bioinformatics core into a highly effective research partner and multiply the impact

Many bioinformatics cores face a multitude of challenges. We recognized that the primary source of these challenges was the service-centric approach. So, we initiated the transformation of our bioinformatics core, Computational Sciences (CS), at the Jackson Laboratory (Jax) to be a science-centric collaborative research partner for our faculty and project stakeholders. We call our model as collaborative partnership model. With the effective replacement of the service model with the collaborative partnership model, CS now acts as both an effective collaborator and a co-driver of scientific research and innovation at Jax. In this paper, we describe the principles and practices we adopted to realize this transformation and present the resulting growth in the impact of CS in the research enterprise at Jax.

scientific communication and education↗

bioRxiv2022

Multi-factorial examination of amplicon sequencing workflows from sample preparation to bioinformatic analysis

The development of sequencing technologies to evaluate bacterial microbiota composition has allowed new insights into the importance of microbial ecology. However, the variety of methodologies used among amplicon sequencing workflows leads to uncertainty about best practices as well as reproducibility and replicability among microbiome studies. Using a bacterial mock community composed of 37 soil isolates, we performed a comprehensive methodological evaluation of 540 workflows, each with a different combination of methodological factors spanning sample preparation to bioinformatic analysis to define sources of artifacts that affect sensitivity, specificity, and biases in the resulting compositional profiles. Of the 540 workflows examined, those using the V4-V4 primer set enabled the highest level of concordance between the original mock community and resulting microbiome sequence composition. Use of a high-fidelity polymerase, or a lower-fidelity polymerase with increased PCR elongation time limited chimera formation. Bioinformatic pipelines presented a trade-off between the fraction of distinct community members identified (sensitivity) and fraction of correct sequences (specificity). DADA2 and QIIME2 assembled V4-V4 reads amplified by Taq polymerase resulted in the highest specificity (100%), but only identified 52% of mock community members. Using mothur to assemble and denoise V4-V4 reads resulted in detection of 75% of mock community members among the resulting sequences, albeit with marginally lower specificity (99.5%). Optimization of microbiome workflows is critical for accuracy and to support reproducibility and replicability among microbiome studies. These aspects will help reveal the guiding principles of microbial ecology and impact the translation of microbiome research to human and environmental health.

microbiology↗

bioRxiv2023

Cell-type deconvolution of bulk RNA-Seq from kidney using opensource bioinformatic tools

Traditional bulk RNA-Seq pipelines do not assess cell-type composition within heterogeneous tissues. Therefore, it is difficult to determine whether conflicting findings among samples or datasets are the result of biological differences or technical differences due to variation in sample collections. This report provides a user-friendly, open source method to assess cell-type composition in bulk RNA-Seq datasets for heterogeneous tissues using published single cell (sc)RNA-Seq data as a reference. As an example, we apply the method to analysis of kidney cortex bulk RNA-Seq data from female (N=8) and male (N=9) baboons to assess whether observed transcriptome sex differences are biological or technical, i.e., variation due to ultrasound guided biopsy collections. We found cell-type composition was not statistically different in female versus male transcriptomes based on expression of 274 kidney cell-type specific transcripts, indicating differences in gene expression are not due to sampling differences. This method of cell-type composition analysis is recommended for providing rigor in analysis of bulk RNA-Seq datasets from complex tissues. It is clear that with reduced costs, more analyses will be done using scRNA-Seq; however, the approach described here is relevant for data mining and meta analyses of the thousands of bulk RNA-Seq data archived in the NCBI GEO public database. Author SummaryThis method, which provides a simple method for assessing sampling biases in bulk RNA-Seq datasets with evaluation of cell-type composition, will aid researchers in assessing whether bulk RNA-Seq from different studies of the same heterogeneous tissue are comparable. The additional layer of information can help determine if differential gene expression observed is biological or technical, i.e., cell composition variation among study samples. The described method uses publicly available bioinformatics resources and does not require coding expertise or high-capacity computational processing. Development of tools accessible to scientists without computing expertise will contribute to greater rigor and reproducibility for bioinformatic analyses of transcriptome data.

genomics↗

bioRxiv2023

Identification of watermelon genes involved in the ZYMV interaction through a miRNA bioinformatics analysis and characterization of ATRIP and RBOHB

Small RNA sequencing of healthy and ZYMV-infected watermelon (21 dpi) was performed and bioinformatics analysis identified 353 miRNAs from which 22 known and 331 new miRNAs. Important information about their precursors, their length, the loci of which they originated on watermelon genome are provided. The ZYMV genome could be a target for mir396a-3p, miR8706a, and miR1886i-5p from the miRbase, but none of them was identified in the watermelon miRNAome. Furthermore, watermelon miRNAome does not contain a miRNA targeting ZYMV genome with an expectation score [≤] 3.5. There were 34 resistance genes (CC-NBS-LRR, TIR-NBS-LRR, TIR-NBS) predicted as targets of 32 miRNAs in healthy watermelon. For nine differentially expressed miRNAs the respective target genes (10 in total) were bioinformatically predicted. For cla-new_miR307 (upregulated upon ZYMV infection) and cla-miR166h-3p (downregulated upon ZYMV infection) the targets were predicted to be ClaATRIP and ClaRBOHB, respectively, with ClaATRIP downregulated and ClaRBOHB upregulated upon ZYMV infection. ALSV-mediated VIGS of ClaATRIP rendered watermelon plants more resistant to ZYMV, whereas VIGS of ClaRBOHB resulted in higher levels of ZYMV titer in watermelon. These data suggest that ClaATRIP and ClaRBOHB are a susceptibility and resistant gene, respectively. Our results provide new insights in watermelon miRNAome and could propose new strategies for generating resistant watermelon to ZYMV. HighlightsO_LIBioinformatics analysis in healthy and ZYMV-infected watermelon plants gave 353 miRNAs, 22 known and 331 new. C_LIO_LIThe watermelon miRNAome identified in the present study does not appear to target the ZYMV genome (sense and reverse complement). C_LIO_LIThe differential expression of ten genes of watermelon in relation to ZYMV infection was validated. C_LIO_LIThe silencing of the two genes, ATRIP and RBOHB, through VIGS strongly suggested that ATRIP is a gene of susceptibility and RBOHB is a gene of resistance. C_LI

plant biology↗

bioRxiv2024

Bioinformatic analysis of sulfotransferases from an unexplored gut microbe, Sutterella wadsworthensis 3_1_45B: Possible roles towards detoxification via sulfation by the members of the human gut microbiome

Sulfation, primarily facilitated by sulfotransferases, plays a crucial role in the detoxification pathways of both endogenous substances and xenobiotics, enhancing their water solubility and promoting metabolism and elimination. Traditionally, this bioconversion has been attributed to a family of human cytosolic sulfotransferases (hSULTs) known for their high sequence similarity and dependence on 3-phosphoadenosine 5-phosphosulfate (PAPS) as a sulfate donor. However, recent studies have revealed the presence of PAPS-dependent sulfotransferases within gut commensals, indicating that the gut microbiome may harbor a diverse array of sulfotransferase enzymes and may contribute to detoxification processes via sulfation. In this study, we investigated the prevalence of sulfotransferases in the members of the human gut microbiome. Interestingly, we stumbled upon a different class of sulfotransferases, known as aryl-sulfate sulfotransferases (ASSTs). ASSTs have been characterized from a few different prokaryotes including E. coli. ASSTs do not utilize PAPS which is the default sulfate donor for the human sulfotransferases. Our bioinformatics analyses revealed that the gut microbial genus Sutterella possesses a significant number of asst genes, possibly encoding multiple ASST enzymes. Fluctuations in the microbes of the genus Sutterella have been associated with various health conditions. For this reason, we characterized 17 different ASSTs from Sutterella wadsworthensis 3_1_45B with bioinformatics. Our findings reveal that SwASSTs share similarities with E. coli ASST but also exhibit significant structural variations and sequence diversity. These differences might drive potential functional diversification and likely reflect an evolutionary divergence from their PAPS-dependent counterparts.

biochemistry↗

bioRxiv2024

Bioinformatics analysis and validation of differentially expressed miRNA in the sperm of partners of patients with unexplained recurrent miscarriages

BackgroundRecurrent miscarriage is a common multifactorial disease, and even after systematic examination, the cause of the miscarriages cannot be determined in approximately 50% of patients. However, currently, few examinations are conducted for partners of patients with recurrent miscarriages. The contribution of spermatozoa to new individuals is not limited to half of the diploid genome. Recent studies have shown that spermatozoa add several components to oocytes, including a complex RNA population that plays an important role in paternal chromatin packaging, sperm maturation and empowerment, fertilisation, early embryogenesis, and developmental maintenance. In view of this, we constructed a sperm miRNA expression profile of partners of patients with unexplained recurrent miscarriages and explored the relationship between unexplained recurrent miscarriages and differential miRNA expression in sperm. MethodsSemen samples were obtained from the partners of patients with unexplained recurrent miscarriages treated at the affiliated hospital of Inner Mongolia Medical University, as well as healthy men who underwent physical examinations between July 2021 and February 2023. The miRNA expression profiles of the sperm in the two groups were detected using high-throughput sequencing. Bioinformatics analysis of differentially expressed miRNAs was performed to predict target genes and their action pathways and verify the expression levels of paternal miRNAs in known embryos in the study and control groups through RT-PCR technology. ResultA total of 83 differentially expressed miRNAs were detected between the two groups, of which 39 were significantly upregulated and 44 were significantly downregulated. The results showed that spermatic hsa-miR-34c-5p, hsa-miR-1285-3p, hsa-miR-486-3p, and hsa-miR-146b-3p may regulate the occurrence of unexplained recurrence through the Ras, PI3K-Akt, and MAPK signalling pathways in the bioinformatics analysis. The expression of hsa-miR-34c-5 in spouses of patients with unexplained miscarriage recurrence was downregulated (p < 0.001). Binary logistic regression analysis showed that low expression of hsa-miR-34c-5p was a high-risk factor for recurrent miscarriage (odds ratio [OR] = 4.344; 95% confidence interval [CI], 1.119-16.857; p < 0.05). ConclusionThe occurrence of unexplained recurrent miscarriages is associated with the differential expression of key miRNAs in the sperms of patients spouses.

molecular biology↗

bioRxiv2024

Data Hunters: bridging bioinformatics education and microbiome research

Vast sequencing data in public repositories offer researchers unprecedented opportunities for gaining insights through reanalysis and machine learning approaches, thereby advancing the microbiology field. However, the lack of standardized metadata poses a significant obstacle to big data reuse, necessitating advanced bioinformatics skills for curation and integration. To tackle this challenge, we organized the Data Hunters Workshop, enabling extensive human skin microbiome metadata curation through student community engagement. The Data Hunters Workshop constitutes a student-science initiative within the University of Milano-Bicocca, Italy. Integrating theoretical and hands-on phases, the workshops structure included a 6-hour lecture, covering metagenomics and metadata manipulation fundamentals, followed by an interactive practical phase designed as a learn-and-play activity. This phase was supported by in-house developed educational online and command-line resources, facilitating students acquisition of Python commands for managing microbiome metadata. Upon the workshops conclusion, its effectiveness was assessed through surveys and standardized evaluation scales. Twenty-nine students addressed the critical challenge of metagenomics metadata standardization. Workshops resources have equipped students with foundational knowledge in metagenomics and Python programming, empowering them to curate metadata from 379 amplicon-based and shotgun sequencing projects of the human skin microbiome. The collaborative endeavors of these students will ensure the construction of a curated metadata collection. The Data Hunters Workshop established a reusable model for similar educational aims, facilitating metagenomics and bioinformatics teaching and metadata curation. It bridged education and microbiome research by focusing on human skin microbiome metadata curation, ultimately striving to construct a specific collection promptly accessible to researchers.

scientific communication and education↗

bioRxiv2024

BEREN: A bioinformatic tool for recovering Giant viruses, Polinton-like Viruses, and Virophages in metagenomic data

Viruses in the kingdom Bamfordvirae, specifically giant viruses (NCLDVs) in the phylum Nucleocytoviricota and smaller members in the Preplasmiviricota phylum, are widespread and important groups of viruses that infect eukaryotes. While viruses in this kingdom such as giant viruses, polinton-like viruses, and virophages have gained large interest from researchers in recent years, there is still a lack of streamlined tools for the recovery of their genomes from metagenomic datasets. Here, we present BEREN, a comprehensive bioinformatic tool to unlock the diversity of these viruses in metagenomes through five modules for NCLDV genome, contig, and marker gene recovery, metabolic protein annotation, and Preplasmiviricota genome identification and annotation. BERENs performance was benchmarked against other mainstream virus recovery tools using a mock metagenome, demonstrating superior recovery rates of NCLDV contigs and Preplasmiviricota genomes. Applied to a real-world dataset from the Baltic Sea, BEREN identified diverse Bamfordvirae members, giving insight into viral interactions and metabolic functions in this region. Overall, BEREN offers a user-friendly, transparent bioinformatic solution for studying the ecological and functional roles of these eukaryotic viruses, facilitating broader access to their metagenomic analysis.

microbiology↗

bioRxiv2024

Bioinformatics of combined nuclear and mitochondrial phylogenomics to define key nodes for the classification of Coleoptera

Nuclear genome sequencing is resource-intensive and not practical for building densely sampled phylogenetic trees of the most species rich lineages of animals, while mitochondrial genomes can be sequenced and analysed with relative ease. Here, we develop a conceptual approach and bioinformatics workflow for combining nuclear single-copy orthologs with less informative but densely sampled mitochondrial genomes, for a detailed tree of Coleoptera (beetles). Basal relationships of Coleoptera were first inferred from >2,000 BUSCO loci mined from GenBanks Short Read Archive for 119 exemplars of all major lineages under various substitution models and levels of matrix completion, to reveal universally supported nodes. Second, the corresponding mitogenomes were extracted and combined with an additional 373 species selected for broad taxonomic and biogeographic coverage, roughly in proportion to the known global species diversity of Coleoptera. Bioinformatic processing of mitogenomes was conducted with a novel pipeline for rapid, accurate annotation of protein-coding genes. Finally, phylogenetic trees from all 492 mitogenomes were generated under a backbone constraint from the universal basal nodes, which produced a well-supported tree of the major lineages at family and superfamily level. Being genetically unlinked and showing unique character variation, mitogenomes provide a unique perspective of the phylogeny. Comparison with three recent nuclear phylogenomic studies resulted in the recognition of >80 nodes universally present across all analyses. These may now support the higher classification of Coleoptera and serve as backbone of further studies, as numerous full mitogenomes and mitochondrial DNA barcodes are added to an increasingly complete phylogenetic tree of this super-diverse insect order.

evolutionary biology↗

bioRxiv2025

Bioinformatic analysis reveals the molecular mechanisms of Trefoil factor 3 involved in asthma pathogenesis

ObjectiveInvestigate the expression, regulatory network and function of TFF3 in asthma from a multi-omics perspective through bioinformatics and cellular experiments to provide clues for understanding its molecular mechanisms in asthma. MethodsDownloaded two asthma-related datasets (GSE67472 and GSE147878) from GEO. Conducted differential expression analysis and WGCNA to find common genes related to asthma phenotype and TFF3 expression. Constructed a PPI network to identify key genes interacting with TFF3. Performed GO and pathway enrichment analysis using DAVID. Analyzed the relationship between TFF3 and immune cell infiltration with CIBERSORTx. Used molecular docking to validate interactions. In vitro, induced 16HBE cells with HDM to establish asthma model and detected inflammatory indicators and TFF3 by RT-qPCR and western blotting. ResultsTFF3 expression was significantly increased in asthma patients in both datasets. ROC analysis showed good diagnostic specificity and sensitivity. 57 co-expressed genes related to asthma and TFF3 were screened, with 11 genes directly interacting with TFF3 and upregulated. Functional enrichment analysis indicated involvement in asthma-related processes. Immune infiltration analysis showed increased M2 macrophages and mast cells, decreased M1 macrophages, and positive correlation with TFF3. Molecular docking confirmed stable binding. In vitro experiments showed increased inflammation index and TFF3 expression after HDM intervention. ConclusionThe study used bioinformatics and cellular experiments to show TFF3s key roles in asthma pathogenesis in aspects like gene expression, protein interaction, and immune microenvironment. TFF3 may regulate genes like AGR2 and AKT1, affect immune cells, and be involved in processes like cell migration and immune response. It provides clues for exploring molecular mechanisms and may offer new directions for asthma diagnosis and treatment.

genomics↗

bioRxiv2025

Endogenous antimicrobial peptides in human colostrum: a peptidomics study by liquid-chromatography high-resolution mass-spectrometry (LC-HRMS) and bioinformatics

Human colostrum is recognized as a source of bioactive compounds that impact on neonatal development, such as antimicrobial peptides. Antimicrobial peptides (AMPs) present some common characteristics, as they are relatively small (<10 kDa), most of them are positively charged and possess -helical regions. These molecules can protect the newborn against infectious agents such as bacteria, fungi, and viruses. Using an MS- based proteomic approach combined with the application of bioinformatic tools, 29 peptide sequences from human colostrum were annotated in human colostrum. These peptides are potentially antifungal and were enriched in glutamic acid (E), phenylalanine (F), lysine (K) and tryptophan (W) residues. Among the precursor proteins, two have a known 3D structure and their fragments are located in the protein core. In addition, in silico analyses revealed that AMPs containing regions of -helix and random structures, and high aliphatic index (mean of 85.29) tend to be thermostable. In this work with human colostrum, previously unreported peptides with potential antimicrobial activity were annotated and structurally characterized via bioinformatic tools.

biochemistry↗

bioRxiv2025

Correlating membrane-protein dynamics with function: Integrating bioinformatics, molecular dynamics, and single-molecule FRET

We present a strategy that deploys structural bioinformatics, molecular simulation, and single-molecule FRET microscopy for observing the ligand-dependent conformational dynamics of integral membrane proteins in situ. We focus on representative members of the small monotopic phosphoglycosyl transferase (SmPGT) superfamily, which catalyze transfer of a phosphosugar from a soluble nucleotide-sugar donor to a membrane-embedded polyprenol phosphate acceptor in the initiating step of glycoconjugate biosynthesis in prokaryotes. Substrate-specific structural features were identified across the superfamily and correlated with ligand-dependent conformational dynamics in all-atom simulations. To experimentally validate the role of this motion in ligand binding, we developed a platform to monitor intra-molecular protein dynamics in a native-like lipid environment. The presented approach incorporates selective cysteine protein labeling and non-canonical amino acid mutagenesis with bicyclononyne-tetrazine click chemistry to assemble dual-labeled variants of PglC, the initiating enzyme of the N-linked protein glycosylation pathway from Campylobacter jejuni. The modified proteins are then solubilized into styrene maleic acid liponanoparticles (SMALPs) to maintain an in situ membrane environment. The conformational changes of PglC upon inhibitor binding are diagnostic of inhibitor potency. The single-molecule FRET-SMALP strategy can be adapted to investigate protein dynamics across the superfamily of SmPGTs with different substrate selectivity where structure prediction and molecular dynamics support significant conformational changes upon ligand binding. Broader ImpactMembrane protein structure-function relationships are critical for understanding fundamental biological processes and for the development of small-molecule drug treatments. Bacterial glycoconjugate biosynthesis pathways are a promising target for strain-specific antibiotics and exemplify the challenges of characterizing biomolecular systems that depend on highly specific protein, lipid, and carbohydrate chemistries. We integrate molecular simulation, structural bioinformatics, and single-molecule FRET to elucidate details of small-molecule binding to the PGT superfamily.

biochemistry↗

bioRxiv2025

Integration of Bioinformatics and Machine Learning to Characterize Fusobacterium nucleatum's Pathogenicity

Fusobacterium nucleatum has been found to be associated with cancer lesions in both oral and colon cancers. Although important studies have dissected the clinical aspects of its remarkable pathogenicity, there is a lack of molecular studies. This study aimed to computationally predict potential pathogenicity islands in F. nucleatum ATCC 25586, with candidate functional relation-ships among PAI-encoded proteins, and generate testable hypotheses regarding iron-dependent virulence mechanisms. We employed an integrative bioinformatics pipeline combining genomic is-land prediction (IslandViewer), promoter analysis (PePPER), codon adaptation index calculation, protein interaction prediction (STRING), co-expression network inference (bnlearn), structural modeling (AlphaFold-Multimer), and genome-scale metabolic modeling (CarveMe/COBRApy). Computational predication was integrated with published literature to formulate mechanistic hy-potheses. Our analysis identified three candidate genomic islands, with Region 2 (PAI2; 1,496,613 to 1,523,855 bp) exhibiting the characteristics most consistent with a functional pathogenicity island, including predicted mobile genetic elements, putative toxin-antitoxin systems, and strong promoter motifs. We propose a mechanistic hypothesis linking hemolysin-mediated iron acquisi-tion to cancer promotion through oxidative stress and Hippo pathway modulation. Our work has two immediate and important benefits: the improved understanding of the biological processes that shape the pathogenicity and evolution of Fusobacterium nucleatum at the molecular level and the improved ability to integrate and automate the state-of-the-art bioinformatics tools and machine learning approaches in the inference of the mechanistic interpretability of a pathogenic phenotype.

microbiology↗

bioRxiv2025

Bioinformatics-based stereochemical elucidation of MM 46115: an unusual antiviral spirotetronate that inhibits clathrin-mediated endocytosis

The influenza virus is a leading cause of respiratory tract infection in humans, with the emergence of antiviral drug resistance posing an ongoing challenge to the treatment of influenza. This underscores the urgent need for effective new antiviral treatments. Spirotetronates are a family of bacterial natural products with a range of potent bioactivities. Some members of this family have antiviral activity. Here, we report the bioinformatics-based stereochemical assignment, antiviral properties, and mechanism of action of the unusual type II spirotetronate MM 46115 (renamed pellemicin). We show that pellemicin is active against both influenza A and B viruses at non-toxic concentrations, and inhibits clathrin-mediated endocytosis, which is required for virus internalisation. Given the need for new treatments for viral infections, the results of our work suggest that pellemicin and related spirotetronates could provide a basis for developing promising alternatives to existing antivirals to combat drug-resistant influenza. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/677008v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@177aacforg.highwire.dtl.DTLVardef@16f0b26org.highwire.dtl.DTLVardef@144f9dcorg.highwire.dtl.DTLVardef@16fe673_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMM 46115 (here renamed pellemicin) produced by a mycetoma pathogen is a promising antiviral C_LIO_LIThe pellemicin biosynthetic gene cluster was identified in Actinomadura pelletieri DSM 43383 C_LIO_LISequence analysis of biosynthetic enzymes enabled full stereochemical assignment C_LIO_LIPellemicin inhibits clathrin-mediated endocytosis, an early stage of the viral life cycle C_LI SignificanceThe influenza virus is a respiratory pathogen with epidemic and pandemic potential, resulting in tens of thousands of deaths each year and causing significant health, social and economic impact. The rise of resistant influenza strains against existing antiviral drugs creates a pressing need for alternative treatments. Natural products - specialised metabolites of bacteria, fungi, and plants that often have antimicrobial activity - are a promising source of therapeutics to treat human disease. Here, we identify a cryptic polyketide biosynthetic gene cluster in the genome sequence of Actinomadura pelletieri DSM 43383, an Actinomycete that causes mycetoma in humans. This is proposed to direct production of the previously reported spirotetronate MM 46115 (here renamed pellemicin), which has activity against the influenza virus. Sequence analyses of a polyketide synthase and Diels-Alderase involved in pellemicin biosynthesis, combined with comparative analysis of NMR data for other spirotetronates, enabled us to fully resolve longstanding stereochemical ambiguities in the structure of pellemicin. This underscores the emerging power of bioinformatics-based approaches, and their complementarity to traditional spectroscopic methods, for natural product structure elucidation. We also report extensive insights into the antiviral properties and mechanism of pellemicin, demonstrating that it exhibits antiviral activity at non-toxic doses for up to eight hours after administration and inhibits clathrin-mediated endocytosis, a process that many viruses exploit to enter cells. Only one other bacterial natural product, ikarugamycin, is known to inhibit clathrin-mediated endocytosis. Ikarugamycin contains a tetramate group, which bears a close structural relationship to the tetronate moiety of pellemicin, suggesting that inhibition of clathrin-mediated endocytosis may be a general mechanism of action for antiviral spirotetronates. Our findings therefore indicate that pellemicin, and related spirotetronate natural products, could form a basis for development of new drugs to combat antiviral resistance, and serve as useful tools to study the process of endocytosis.

microbiology↗

bioRxiv2019

Analysis of Vibrio cholerae genomes using a novel bioinformatic tool identifies new, active Type VI Secretion System gene clusters

BackgroundLike many bacteria, Vibrio cholerae, which causes fatal cholera, deploys a harpoon-like Type VI Secretion System (T6SS) to compete against other microbes in environmental and host settings. The T6SS punctures adjacent cells and delivers toxic effector proteins that are harmless to bacteria carrying cognate immunity factors. Only four effector/immunity pairs encoded on one large and three auxiliary gene clusters have been characterized from largely clonal, patient-derived strains of V. cholerae. ResultsWe sequenced two dozen V. cholerae strain genomes from diverse sources and developed a novel and adaptable bioinformatic tool based on Hidden Markov Models. We identified two new T6SS auxiliary gene clusters; one, Aux 5, is described here. Four Aux 5 loci are present in the host strain, each with an atypical effector/immunity gene organization. Structural prediction of the putative effector indicated it is a lipase, which we name TleV1 (Type VI lipase effector Vibrio, TleV1). Ectopic TleV1 expression induced toxicity in E. coli, which was rescued by co-expression of the TleV1 immunity factor. A clinical V. cholerae reference strain expressing the Aux 5 cluster used TleV1 to lyse its parental strain upon contact via its T6SS but was unable to kill parental cells expressing TleV1s immunity factor. ConclusionWe developed a novel bioinformatic method and identified new T6SS gene clusters in V. cholerae. We also showed the TleV1 toxin is delivered in a T6SS-manner by V. cholerae and can lyse other bacterial cells. Our web-based tool may be modified to identify additional novel T6SS genomic loci in diverse bacterial species.

microbiology↗

bioRxiv2019

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

BackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a one-stop test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.\n\nMethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ( participants) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.\n\nResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.\n\nConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

microbiology↗

bioRxiv2025

Virome of Culex nigripalpus at an Alabama aquaculture site reveals diverse insect-specific viruses and the impact of dual bioinformatic pipelines

Mosquitoes are important cosmopolitan insect vectors that threaten humans and host a variety of diseases. Catfish production from Alabama fisheries supports the development of favorable habitats that benefit fish, birds, and insects. Our study found that Culex nigripalpus was a major vector associated with catfish ponds. As Culex nigripalpus harbors medically important viruses like St. Louis encephalitis, studies often focus on these without exploring the full virus diversity. To address this, we performed an RNA-Seq analysis on Culex nigripalpus and compared bioinformatic methodologies, testing two approaches. In the first method (reference-based assembly), the characterized genome of Culex quinquefasciatus was used with a mapping cutoff, and assembled contigs were annotated with megablast against the NCBI nucleotide database. In a second method, reads were assembled de novo, and the contigs were annotated with a BLAST against the NCBI viral genomic database. In addition, the cross-validation of the contigs generated by the two methods was conducted to identify the common and unique viral contigs, adding support for identification. RNA-Seq analysis identified fifteen different viruses. Both methods identified three common viruses, Merida virus isolate Cx. nigripalpus1 (PQ963471), Hubei mosquito virus 5 isolate Cx. nigripalpus2 (PQ963472), and Zhejiang mosquito virus isolate Cx. nigripalpus3 (PQ963484). The first method also identified ten unique viruses, and the second method generated two unique viruses. Selected viruses were independently validated by RT-PCR amplification of viral genomic regions. Overall, our data suggest that different approaches to bioinformatic analysis complement each other and improve viral genome recovery from metatranscriptomic datasets.

microbiology↗