Biology subjects

Weber, T.

Publications and source records attributed to Weber, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Consensus native-like hepatitis C virus E1E2 engages broadly neutralizing antibody precursors

A major goal for hepatitis C virus (HCV) vaccine development is to elicit broadly neutralizing antibodies (bNAbs) against the E1E2 glycoprotein complex located on the viral surface. Inducing HCV bNAbs requires engagement of their germline B cell precursors. HCV glycoproteins usually do not bind and activate inferred germline precursors of bNAbs (igl-bNAbs), possibly because most circulating strains contain non-conserved isolate-specific residues, even in bNAb epitopes. Here, we generated stabilized native-like soluble E1E2 (sE1E2) antigens based on a consensus sequence of HCV (HepCon) to limit the exposure of antigenically rare residues. The antigenicity and glycosylation profiles show that HepCon sE1E2 resembles a native-like E1E2 heterodimer. HepCon sE1E2 induced cross-reactive neutralizing antibody responses as a soluble protein immunogen and as membrane-anchored mRNA-delivered immunogen in animals. Importantly, HepCon sE1E2 engages multiple igl-bNAbs against two major epitopes: antigenic region 3 (AR3), which is targeted by igl-bNAbs derived from the widely expressed human VH1-69 B cell gene, and antigenic region 4 (AR4), which is only present on native-like E1E2. Nanoparticles with HepCon sE1E2 efficiently activated B cell lines expressing AR3 and AR4 igl-bNAb B cell receptors in vitro. Finally, using HepCon sE1E2 we elucidated the atomic contacts of an AR3 igl-bNAb by cryo-electron microscopy. Thus, HepCon sE1E2 is a promising candidate for germline-targeting vaccination strategies.

immunology↗

bioRxiv2026

A long-hidden prevalent PCR artifact and its application in DNA library screening

PCR artifacts can lead to aberrant DNA products and confound result interpretation, posing significant challenges in research and diagnostics. Traditionally, it has been blamed to misannealing of primers on unintended sites. However, by sequencing, we find that most PCR byproducts and artifacts actually have both primers bound correctly but lack a middle part of the target, a phenomenon we named as PCR leaping. The leaping occurs at random positions, is independent of sequence repeats and requires a single piece template, indicating an unprecedented mechanism. It is observed with various polymerases, template qualities, GC contents, and PCR programs, thus necessitating a reset of our PCR understanding and careful consideration in future studies, for example in CRISPR editing validations. On the other hand, it provides a simple way of DNA end pairing, based on which we develop a high throughput DNA library screening method for natural product discovery at substantially reduced cost.

molecular biology↗

bioRxiv2026

Toward understanding drivers of specialized metabolism in Actinomycetota: insights from 1432 transcriptomics datasets for 132 strains

Actinomycetota are major sources of specialized metabolites with applications in drug discovery and agriculture, yet much of their biosynthetic potential remains silent under standard laboratory conditions. Limited understanding of the mechanisms controlling biosynthetic gene cluster (BGC) activation constrains metabolite discovery and production. Here, we generated 1432 RNA-seq datasets from 132 Actinomycetota strains grown in eight media to identify patterns associated with BGC expression. On average, strains expressed 44% of their encoded BGCs across the tested conditions, with more expression observed among known BGCs (61%) compared to uncharacterized BGCs (35%). Co-expression analyses revealed frequent associations between BGCs and transporters, transcriptional regulators, and proteins containing DUF397 and DUF742 domains. Targeted overexpression of candidate genes selected from BGC-associated co-expression modules increased metabolite production, with DUF397- and DUF742-containing operons showing the broadest effects by boosting the levels of several different specialized metabolites. Other genes boosted levels in a metabolite-specific manner. Together, our results support a multilayered model of BGC regulation in Actinomycetota in which BGC expression is shaped by medium composition, BGC-specific regulators, and integration of BGCs into broader transcriptional network modules. By connecting BGC expression to specific media and co-expressed genes, this study also provides a resource for selecting growth conditions and engineering specialized metabolism.

microbiology↗

bioRxiv2026

RetroMol: Parsing a shared encoding from natural products and their biosynthetic gene clusters

Natural products such as polyketides and nonribosomal peptides (NRPs) are important sources of bioactive compounds, including many antibiotics. Many of them are assembled by modular enzyme complexes and further modified and diversified by tailoring reactions encoded by biosynthetic gene clusters (BGCs). Although natural products and their coding BGCs describe different data modalities of the same biochemical process, a unified language to jointly describe their biochemistry is lacking. Here we introduce a sequence-based representation of the core biosynthesis of modular natural products, which we call primary sequences, that bridges chemical structures and BGCs. We also present RetroMol, an algorithm that parses either natural product structures or their encoding BGCs into their primary sequences of natural product building blocks. RetroMol allows for similarity scoring between natural products and BGCs, enabling the retrieval of compounds, BGCs, and a combination of the two, based on their biosynthetic similarity. This can, for instance, be used to retrieve biosynthetically similar but structurally dissimilar compounds, or link natural products to candidate coding BGCs in large experimental datasets. We demonstrate the latter by rediscovering the nocardichelin B BGC as a proof of principle. We also exemplify the utility of biosynthetic similarity by showing various pairs of biosynthetically similar compounds with low structural similarity. Together, these results establish primary sequences as a shared biosynthetic encoding for natural product comparison and BGC prioritization.

bioinformatics↗

bioRxiv2026

Walking on the Moon: Hypogravity drives the emergence of a proprioception-dependent locomotor state

Animals must adapt locomotion to changing environmental conditions, but how the nervous system flexibly controls movement remains unclear. Gravity provides a powerful perturbation because it alters body loading, limb dynamics, and proprioceptive feedback. Apollo astronauts often skipped on the Moon, adopting an asymmetric gait rarely used on Earth, yet the sensorimotor basis of this behaviour is unknown. Here, by studying hypogravity locomotion in humans and mice, we show that reduced gravity reveals a conserved proprioception-dependent mechanism for locomotor state expression. In humans, skipping in simulated lunar gravity is generated through flexible temporal reconfiguration of existing motor modules rather than construction of a new motor architecture. In mice, simulated lunar gravity elicited a skipping-like locomotor state, and genetic elimination of muscle proprioceptors abolished this response. Thus, hypogravity reveals how proprioceptive feedback enables flexible expression of locomotor states.

neuroscience↗

bioRxiv2026

geneML: Gene annotation across diverse fungal species using deep learning

Accurate gene prediction remains a major bottleneck in fungal genomics, where lineage diversity and alternative splicing challenge existing ab initio methods. Here, we present geneML, a deep learning-based gene prediction tool tailored to fungal genomes. Across nine reference genomes spanning diverse fungal taxa, geneML improved gene-level F1 score from 64.9 to 67.1 compared to BRAKER3 with protein-based hints, driven by substantially higher recall (69.0 vs. 64.1) at equivalent precision. geneML also remains fast, averaging around 6 minutes per genome on a standard 8-core CPU. A key feature of geneML is its ability to predict alternative transcripts. Compared to Fusarium graminearum Iso-Seq control data, it achieves 41.1% transcript recall and 71.1% precision, outperforming AUGUSTUS (33.8% recall, 48.9% precision), one of the few tools that support isoform prediction. The predicted transcript diversity is consistent with experimentally observed fungal alternative splicing patterns. Reannotation of the curated training dataset further suggests improved biological completeness, with geneML recovering 15.3% more genes containing complete PFAM domains than the reference annotation. These results demonstrate that geneML enables faster, more sensitive, and more biologically informative fungal genome annotation. geneML is available as an open-source command-line tool at https://github.com/hexagonbio/geneML. Key Points- geneML improves gene prediction accuracy over both classical and recent deep learning-based methods, while substantially improving recall. - geneML predicts alternative transcripts with higher precision and recall than AUGUSTUS, expanding functional annotation. - Runtime was 32-fold decreased over BRAKER3, enabling efficient high-throughput genome annotation. - geneML identifies novel genes and recovers missing annotations, especially in under-annotated non-Ascomycete genomes.

bioinformatics↗

bioRxiv2026

Passive acoustic monitoring as a tool for early detection of invasive animal species: a systematic review and a case study

Invasive animal species are spreading rapidly across the globe, creating an urgent need for efficient early-detection and monitoring tools. Passive acoustic monitoring has become an established method in biodiversity research, but its application to invasive species monitoring has been less systematically explored. Here, we combine a systematic literature review with a field-based case study to evaluate the potential of passive acoustic monitoring for invasive animal detection. We identified 26 studies on acoustic monitoring of invasive animals, mainly addressing amphibians (11 studies), birds and fish (five each) with most studies from the USA and Australia. The use of acoustic monitoring of invasive species has increased during the past decade, with recent studies applying automated detection, machine learning, and large-scale monitoring frameworks. As a case study, we further tested the feasibility of low-cost acoustic monitoring of the invasive American bullfrog (Lithobates catesbeianus) in southwestern Germany, combined with automated identification using BirdNET. We successfully confirmed bullfrog presence in eight of the eleven monitored lakes, including sites close to a protected nature reserve. Our results highlight the growing potential of passive acoustic monitoring of invasive species under field conditions. In combination with automated species detection, manual validation, and emerging real-time monitoring devices, passive acoustic monitoring becomes an increasingly powerful tool for early intervention and scalable management of biological invasions.

ecology↗

bioRxiv2026

Modeling Reliable Detection Range of Cetaceans Imaged with Infrared Cameras

Infrared (IR) imaging systems are used on vessels, platforms, and drones to detect cetaceans several kilometers away, helping to mitigate harm from maritime activities like vessel strikes and pile driving. To ensure operational effectiveness, the reliable detection range (RDR) --the distance at which 100% detection probability is achieved--is a critical metric. This study presents a radiometric model for calculating RDR across a wide range of environmental conditions and system parameters, which enables the evaluation of IR system performance without extensive at-sea data collection.

ecology↗

bioRxiv2026

Computational pipeline reveals nature's untapped reservoir of halogenating enzymes

Microbial halogenated natural products (hNPs) hold ecological, agricultural, and biomedical relevance. The hNP-producing potential of the organism can be assessed by the precise prediction of biosynthetic enzymes, yet the detailed annotations of halogenases are often missing from genomic and metagenomic data. We created a manually curated database (https://halogenases.secondarymetabolites.org/) containing information on the halide-specificity, role, and position of verified catalytic residues and results of the mutagenesis studies of more than 120 experimentally validated or in silico inferred halogenases. The collection of experimental data supports a computational pipeline that allows the family-, substrate-, and halide-scope-level annotation of halogenating enzymes by relying on catalytic residues, conserved motifs, and profile Hidden Markov Models (pHMMs). Our analysis with sequence similarity networks (SSNs) highlighted several underexplored clusters in the UniRef50 database. Such finding was a halogenase from Rhodopirellula baltica (RhobaVHPO) previously labelled as a hypothetical chloroperoxidase, which clustered apart from the known chloroperoxidases and bromoperoxidases, but accepted chloride and preferred bromide. Our database and workflow provide extensive and scalable solutions for the systematic and precise annotation of halogenating enzymes in genomic and metagenomic data. The in-depth categorization of halogenases will improve the chemical structure prediction of microbial hNPs, supporting ecological assessments and natural product discovery. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/700248v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@ebae51org.highwire.dtl.DTLVardef@10188f0org.highwire.dtl.DTLVardef@1c55684org.highwire.dtl.DTLVardef@b311bd_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

epsSMASH uncovers exopolysaccharide biosynthetic gene clusters in environmental and human microbiomes

Biofilms represent the default mode of bacterial life in natural and built environments, with extracellular polysaccharides (exoPS) serving as essential structural and functional components of the biofilm matrix. Despite their importance, exoPS production in these environments is largely unknown. Here we present epsSMASH, a bioinformatic tool and web service for predicting known and novel exoPS biosynthetic gene clusters (BGCs) in bacterial genomes. Benchmarking showed that comprehensive detection of exoPS gene clusters requires highly contiguous high-quality genome assemblies. We applied epsSMASH to high-quality bacterial genome catalogues representing four major ecosystems: Human gut, soil, ocean and activated sludge from wastewater treatment systems. In all catalogues, epsSMASH identified exoPS BGCs in most genomes (52.8-85.4%), with a median of 1-2 exoPS BGCs per genome. The number of exoPS BGC per genome was highly variable, with some taxa containing up to 19 distinct exoPS BGCs. Pel BGCs were abundant in human gut, ocean and activated sludge microbiomes, and were detected in 14 different phyla, making it the most phylogenetically widespread BGC in these environments. The vast majority (62-96%) of detected exoPS BGCs were uncharacterised. By constructing gene cluster families from uncharacterised systems, we identified novel and phylogenetically widespread exoPS BGCs. We investigated a novel exoPS gene cluster from the activated sludge microbiome and showed that it is conserved in most genera within the order Sphingomonadales. Our results highlight the remarkable number of uncharacterised exoPS gene clusters in environmental microbiomes and establish epsSMASH as an effective tool for identifying and classifying novel exoPS systems.

bioinformatics↗

bioRxiv2025

A STAT5B-driven mouse model of hepatosplenic γδ T-cell lymphoma reveals therapeutic efficacy of JAK inhibition

Hepatosplenic T-cell lymphoma (HSTCL) is a rare and aggressive neoplasm associated with poor responses to standard chemotherapy regimens and low survival rates. No targeted therapies are available for HSTCL, and preclinical models to test new treatment options have not been established. The JAK-STAT signaling cascade is a key dysregulated pathway in HSTCL, and STAT5BN642His the most frequent somatic mutation in the disease. Here, we report on newly established clonal, murine {gamma}{delta} T-cell lymphoma cell lines initiated and driven by oncogenic STAT5BN642H, which recapitulate key immunophenotypic features, gene expression profiles and typically low cytolytic activity of patient-derived human HSTCL cells. CRISPR-Cas9 mediated knockout demonstrated growth dependence on STAT5BN642H. Murine C15 cells were allo-engrafted intravenously into both immunodeficient and immunocompetent mice to model an aggressive HSTCL-like disease at high penetrance, with recipient mice displaying hepatosplenomegaly and destructive {gamma}{delta} T cell organ infiltration, including bone marrow and blood involvement. We identified the potential of JAK inhibition as a targeted treatment strategy for HSTCL, and found the clinically approved JAK inhibitor upadacitinib to display selective anti-tumor efficacy against STAT5B-mutated HSTCL cell lines in vitro, in vivo, and in primary HSTCL patient samples. Overall, we describe the first robust STAT5B-driven preclinical model resembling features of HSTCL in an immune competent setting. This tool is expected to accelerate the study of HSTCL disease mechanisms and the testing of novel therapies. Our data further present the JAK inhibitor upadacitinib as a promising targeted treatment option for STAT5B-mutated HSTCL.

cancer biology↗

bioRxiv2025

Tying up loose ends: Recovering thousands of missing telomeres from Streptomyces and other Streptomycetaceae genomes

Members of the Gram-positive Streptomycetaceae family of bacteria have linear chromosomes and carry linear plasmids, which end in telomeres bound by proteins. In a large-scale analysis of 762 linear complete genomes, we discovered that the telomeres were truncated in most assemblies, as they are not captured by Oxford Nanopore sequencing. To address this issue, we present Telomore, a tool to reconstitute this missing telomeric sequence using ONT and Illumina data. In the studied dataset, Telomore increased detection of archetypal telomeres from 0% to 37%, which could be near the occurrence rate in nature. Combining these reconstituted telomeres with previously published telomeres and all complete Streptomycetaceae RefSeq genomes, we created a compendium of more than 2000 telomeres. Similarity-based clustering identified 137 telomere clusters. We find that 78% of Telomore-extended chromosomes encode both telomeres, while this is only the case for 15% of comparable RefSeq chromosomes. Therefore, most assignments of "complete" to Streptomycetaceae are erroneous. Finally, we mined the 762 genomes for known telomeric maintenance proteins and used those to identify a plasmid-specific archetypal telomere and to identify a previously unidentified protein family likely involved with the maintenance of Sg2247-class telomeres. Together, these results highlight a common issue assembling complete linear Streptomycetaceae genomes and provide a programmatic solution and identify a candidate for a new telomeric protein. VISUAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/682034v1_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@1adbb96org.highwire.dtl.DTLVardef@f68519org.highwire.dtl.DTLVardef@9c50b4org.highwire.dtl.DTLVardef@768c00_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

PhyloNaP: a user-friendly database of Phylogeny for Natural Product-producing enzymes

Phylogenetic analysis is widely used to predict enzyme function, yet building annotated and reusable trees is labor-intensive and requires extensive knowledge about the specific enzymes. Existing resources rarely cover biosynthetic enzymes and lack the context needed for meaningful analysis. We present PhyloNaP, the first large-scale resource dedicated to phylogenies of biosynthetic enzymes. PhyloNaP provides [~]18,500 annotated and interactive trees enriched with chemical, functional, and taxonomic information. Users can classify their own sequences via phylogenetic placement, enabling functional inference in an evolutionary context. A contribution portal allows the community to submit curated trees. By combining scale, breadth of annotation, and interactive functionality, PhyloNaP fills a major gap in bioinformatics resources for enzyme discovery and annotation, with immediate applications to secondary metabolism and beyond. Availabilityhttps://phylonap.cs.uni-tuebingen.de

bioinformatics↗

bioRxiv2025

Genetic barcoding uncovers the clonal makeup of solid and liquid biopsies

Intra-tumoral heterogeneity (ITH) is fueling tumor progression in breast cancer, as specific clones present within a tumor may have a selective advantage to colonize distant organs and escape therapy. Accurate sampling of ITH is therefore a pressing challenge in clinical oncology, to adequately predict recurrence and inform rational and personalized therapies. Here we used cellular barcoding to track the spatio-temporal composition of human breast cancer clones in six preclinical models - across two cell lines and four patient derived xenografts (PDXs). This allowed direct side-by-side quantitative comparison not only of intra-tumor clonal composition, but also of how that composition was reflected in needle biopsies and cell-free DNA (cfDNA). These analyses highlighted several clinically relevant findings. First, the use of orthogonal genetic and optical barcoding revealed that clonal diversity in the center of non-necrotic primary tumors was significantly higher compared to their periphery. Second, cfDNA barcode analysis suggested that DNA shedding in the vasculature varied largely, not only depending on necrosis and tumor burden, but also between models. Third, combining information captured in both solid and liquid biopsies can provide a more robust assessment of tumor clonal composition. Taken together, these results showcases the utility of these barcoded models to optimize the use of solid and liquid biopsies as surrogate markers of ITH.

cancer biology↗

bioRxiv2025

Unlocking the biosynthetic potential of Paenibacilli through a genus-wide exploration of gene clusters for secondary metabolite production

The genus Paenibacillus is a prolific producer of secondary metabolites with diverse ecological and industrial applications. However, a comprehensive overview of the biosynthetic gene cluster (BGC) diversity and distribution throughout the genus has been limited. Here, we performed large-scale genome mining on 284 high-quality genomes and generated a non-redundant dataset of 126 representative genomes to explore the biosynthetic potential of this genus. A total of 3,273 BGCs were identified from the 284 genomes that clustered into 1,013 gene cluster families (GCFs), with 98.7% classified as unknown, indicating vast potential for novel secondary metabolite discovery in the Paenibacillus genus. Comparative analysis revealed significant phylogenetic and clade-specific distribution patterns of GCFs, with certain clades enriched in unique biosynthetic pathways while others exhibited low similarity to known BGCs, suggesting evolutionary adaptation to diverse ecological niches. This study uncovers the rich and largely untapped biosynthetic potential of the genus Paenibacillus, providing a foundation for future exploration of its natural products and their applications in biotechnology and medicine. IMPORTANCEBacterial secondary metabolites have been instrumental in the development of antibiotics, antifungals, and other bioactive compounds. The genus Paenibacillus is an underexplored source of such metabolites, with significant potential for novel discoveries. By integrating genome mining and phylogenetic analysis, this study systematically characterizes the diversity, distribution, and novelty of biosynthetic gene cluster across the genus. The identification of clade-specific biosynthetic patterns and numerous unknown gene cluster families highlights Paenibacillus as a promising target for uncovering novel compounds with ecological and therapeutic relevance. These findings not only expand our understanding of bacterial secondary metabolite biosynthesis but also offer new opportunities for the development of sustainable biotechnological applications.

microbiology↗

bioRxiv2024

StreptoCAD: An open-source software toolbox automating genome engineering workflows in streptomycetes

Streptomycetes hold immense potential for discovering novel bioactive molecules for applications in medicine or sustainable agriculture. However, high-throughput exploration is hampered by the current Streptomyces genetic engineering methods that involve the manual design of complex experimental molecular biological engineering strategies for each targeted gene. Here, we introduce StreptoCAD, an open-source software toolbox that automates and streamlines the design of genome engineering strategies in Streptomyces, supporting various CRISPR-based and gene overexpression methods. Once initiated, StreptoCAD designs all necessary DNA primers and CRISPR guide sequences, simulates plasmid assemblies (cloning) and the resulting modification of the genomic target(s), and further summarizes the information needed for laboratory implementation and documentation. StreptoCAD currently offers six design workflows, including the construction of overexpression libraries, base-editing, including multiplexed CRISPR-BEST plasmid generation, and genome engineering using CRISPR-Cas9, CRISPR-Cas3, and CRISPRi systems. In addition to automating the design process, StreptoCAD further secures compliance with the FAIR principles, ensuring reproducibility and ease of data management via standardized output files. To experimentally demonstrate the design process and output of StreptoCAD, we designed and constructed a series of gene overexpression strains in Streptomyces Go40/10, underscoring the tools efficiency and user-friendliness. This tool simplifies complex genetic engineering tasks and promotes collaboration through standardized workflows and design parameters. StreptoCAD is set to transform genome engineering in Streptomyces, making sophisticated genetic manipulations accessible for all and accelerating natural product discovery. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/629370v1_ufig1.gif" ALT="Figure 1000"> View larger version (56K): org.highwire.dtl.DTLVardef@42a7deorg.highwire.dtl.DTLVardef@1aef57org.highwire.dtl.DTLVardef@574e59org.highwire.dtl.DTLVardef@1d8dd3d_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

ActinoMation: a literate programming approach for medium-throughput robotic conjugation of Streptomyces spp.

The genus Streptomyces are valuable producers of antibiotics and other pharmaceutically important bioactive compounds. Advances in molecular engineering tools, such as CRISPR, has provided some access to the metabolic potential of Streptomyces, but efficient genetic engineering of strains is hindered by laborious and slow manual transformation protocols. In this paper, we present a semi-automated medium-throughput workflow for the introduction of recombinant DNA into Streptomyces spp. using the affordable and open-sourced Opentrons (OT-2) robotics platform. To increase the accessibility of the workflow we provide an open-source protocol-creator, ActinoMation. ActinoMation is a literate programming environment using Python in Jupyter Notebook. We validated the method by transforming Streptomyces coelicolor (M1152 and M1146), S. albidoflavus (J1047), and S. venezuelae (DSM40230) with the plasmids pSETGUS and pIJ12551. We demonstrate conjugation efficiencies of 3.33*10-3 for M1152 with pSETGUS and pIJ12551; 2.96*10-3 for M1146 with pSETGUS and pIJ12551; 1.21*10-5 for J1047 with pSETGUS and 4.70*10-4 with pIJ12551, and 4.97*10-2 for DSM40230 with pSETGUS and 6.13*10-2 with pIJ12551 with a false positive rate between 8.33% and 54.54%. Automation of the conjugation workflow improves consistency when handling large sample sizes that facilitates easy reproducibility on a larger scale.

bioengineering↗

bioRxiv2024

BGC Atlas: A Web Resource for Exploring the Global Chemical Diversity Encoded in Bacterial Genomes

Secondary metabolites are compounds not essential for an organisms development, but provide significant ecological and physiological benefits. These compounds have applications in medicine, biotechnology, and agriculture. Their production is encoded in biosynthetic gene clusters (BGCs), groups of genes collectively directing their biosynthesis. The advent of metagenomics has allowed researchers to study BGCs directly from environmental samples, identifying numerous previously unknown BGCs encoding unprecedented chemistry. Here, we present the BGC Atlas (https://bgc-atlas.cs.uni-tuebingen.de), a web resource that facilitates the exploration and analysis of BGC diversity in metagenomes. The BGC Atlas identifies and clusters BGCs from publicly available datasets, offering a centralized database and a web interface for metadata-aware exploration of BGCs and gene cluster families (GCFs). We analyzed over 35,000 datasets from MGnify, identifying nearly 1.8 million BGCs, which were clustered into GCFs. The analysis showed that ribosomally synthesized and post-translationally modified peptides (RiPPs) are the most abundant compound class, with most GCFs exhibiting high environmental specificity. We believe that our tool will enable researchers to easily explore and analyze the BGC diversity in environmental samples, significantly enhancing our understanding of bacterial secondary metabolites, and promote the identification of ecological and evolutionary factors shaping the biosynthetic potential of microbial communities.

bioinformatics↗