Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products. Since 2011, the "antibiotics and secondary metabolite analysis shell-antiSMASH" (https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free-to-use web server and as a standalone tool under an OSI-approved open-source license. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi. Here, we present the updated version 6 of antiSMASH. antiSMASH 6 increases the number of supported cluster types from 58 to 71, displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, allows for the integration of results from other prediction tools, and more effectively detects tailoring enzymes in RiPP clusters.

/pdf/antismash-6-0-improving-cluster-detection-and-comparison-4zjmias6co.pdf

antiSMASH 6.0: improving cluster detection and comparison capabilities.

Summary Genes involved in biological pathways are often collocalised in gene clusters, the comparison of which can give valuable insights into their function and evolutionary history. However, comparison and visualisation of gene cluster similarity is a tedious process, particularly when many clusters are being compared. Here, we present clinker, a Python based tool, and clustermap.js, a companion JavaScript visualisation library, which used together can automatically generate accurate, interactive, publication-quality gene cluster comparison figures directly from sequence files. Availability and implementation Source code and documentation for clinker and clustermap.js is available on GitHub (github.com/gamcil/clinker and github.com/gamcil/clustermap.js, respectively) under the MIT license. clinker can be installed directly from the Python Package Index via pip. Supplementary information Supplementary data are available at Bioinformatics online.

clinker & clustermap.js: automatic generation of gene cluster comparison figures

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

/pdf/a-genomic-catalog-of-earth-s-microbiomes-4ftsmzx2fv.pdf

A genomic catalog of Earth’s microbiomes

An ever-increasing demand for novel antimicrobials to treat life-threatening infections caused by the global spread of multidrug-resistant bacterial pathogens stands in stark contrast to the current level of investment in their development, particularly in the fields of natural-product-derived and synthetic small molecules. New agents displaying innovative chemistry and modes of action are desperately needed worldwide to tackle the public health menace posed by antimicrobial resistance. Here, our consortium presents a strategic blueprint to substantially improve our ability to discover and develop new antibiotics. We propose both short-term and long-term solutions to overcome the most urgent limitations in the various sectors of research and funding, aiming to bridge the gap between academic, industrial and political stakeholders, and to unite interdisciplinary expertise in order to efficiently fuel the translational pipeline for the benefit of future generations.

/pdf/towards-the-sustainable-discovery-and-development-of-new-3ugkmuenu2.pdf

Towards the sustainable discovery and development of new antibiotics

Summary Genes involved in biological pathways are often collocalised in gene clusters, the comparison of which can give valuable insights into their function and evolutionary history. However, comparison and visualisation of gene cluster homology is a tedious process, particularly when many clusters are being compared. Here, we present clinker, a Python based tool, and clustermap.js, a companion JavaScript visualisation library, which used together can automatically generate accurate, interactive, publication-quality gene cluster comparison figures directly from sequence files. Availability and Implementation Source code and documentation for clinker and clustermap.js is available on GitHub (github.com/gamcil/clinker and github.com/gamcil/clustermap.js, respectively) under the MIT license. clinker can be installed directly from the Python Package Index via pip. Contact E-mail: cameron.gilchrist@research.uwa.edu.au, yitheng.chooi@uwa.edu.au

/pdf/clinker-clustermap-js-automatic-generation-of-gene-cluster-4ilrkk3rs5.pdf

clinker & clustermap.js: Automatic generation of gene cluster comparison figures

Fueled by the explosion of (meta)genomic data, genome mining of specialized metabolites has become a major technology for drug discovery and studying microbiome ecology. In these efforts, computational tools like antiSMASH have played a central role through the analysis of Biosynthetic Gene Clusters (BGCs). Thousands of candidate BGCs from microbial genomes have been identified and stored in public databases. Interpreting the function and novelty of these predicted BGCs requires comparison with a well-documented set of BGCs of known function. The MIBiG (Minimum Information about a Biosynthetic Gene Cluster) Data Standard and Repository was established in 2015 to enable curation and storage of known BGCs. Here, we present MIBiG 2.0, which encompasses major updates to the schema, the data, and the online repository itself. Over the past five years, 851 new BGCs have been added. Additionally, we performed extensive manual data curation of all entries to improve the annotation quality of our repository. We also redesigned the data schema to ensure the compliance of future annotations. Finally, we improved the user experience by adding new features such as query searches and a statistics page, and enabled direct link-outs to chemical structure databases. The repository is accessible online at https://mibig.secondarymetabolites.org/.

/pdf/mibig-2-0-a-repository-for-biosynthetic-gene-clusters-of-siyoqrs7gw.pdf

MIBiG 2.0: a repository for biosynthetic gene clusters of known function.

Land management practices can vastly influence belowground plant traits due to chemical, physical, and biological alteration of soil properties. Beneficial Pseudomonas spp. are agriculturally relevant bacteria with a plethora of plant growth promoting (PGP) qualities, including the potential to alter plant physiology by modulating plant produced ethylene via the action of the bacterial enzyme 1-aminocyclopropane-1-carboxylate (ACC) deaminase (acdS). This study evaluated the impact of land management legacy on the selection and function of wheat root associated culturable pseudomonad isolates. Three distinct previous land uses prior to wheat culture (grassland, arable, and bare fallow) were tested and culturable pseudomonad abundance, phylogeny (gyrB and acdS genes), function (ACC deaminase activity), and the co-selection of acdS with other PGP genes examined. The pseudomonad community could to some extent be discriminated based on previous land use. The isolates from rhizosphere and root compartments of wheat had a higher acdS gene frequency than the bulk soil, particularly in plants grown in soil from the bare fallow treatment which is known to have degraded soil properties such as low nutrient availability. Additionally, other genes of interest to agriculture encoding anti-fungal metabolites, siderophores, and genes involved in nitrogen metabolism were highly positively associated with the presence of the acdS gene in the long-term arable treatment in the genomes of these isolates. In contrast, genes involved in antibiotic resistance and type VI secretion systems along with nitrogen cycling genes were highly positively correlated with the acdS gene in bare fallow isolated pseudomonad. This highlights that the three land managements prior to wheat culture present different selection pressures that can shape culturable pseudomonad community structure and function either directly or indirectly via the influence of wheat roots.

/pdf/land-management-legacy-affects-abundance-and-function-of-the-4k6gttsflh.pdf

Land Management Legacy Affects Abundance and Function of the acdS Gene in Wheat Root Associated Pseudomonads.

Disease-suppressive soils protect plants against soilborne fungal pathogens that would otherwise cause root infections. Soil suppressiveness is, in most cases, mediated by the antagonistic activity of the microbial community associated with the plant roots. Considering the enormous taxonomic and functional diversity of the root-associated microbiome, identification of the microbial genera and mechanisms underlying this phenotype is challenging. One approach to unravel the underlying mechanisms is to identify metabolic pathways enriched in the disease-suppressive microbial community, in particular, pathways that harbor natural products with antifungal properties. An important class of these natural products includes peptides produced by nonribosomal peptide synthetases (NRPSs). Here, we applied functional amplicon sequencing of NRPS-associated adenylation domains (A domains) to a collection of eight soils that are suppressive or nonsuppressive (i.e., conducive) to Fusarium culmorum, a fungal root pathogen of wheat. To identify functional elements in the root-associated bacterial community, we developed an open-source pipeline, referred to as dom2BGC, for amplicon annotation and putative gene cluster reconstruction through analyzing A domain co-occurrence across samples. We applied this pipeline to rhizosphere communities from four disease-suppressive and four conducive soils and found significant similarities in NRPS repertoires between suppressive soils. Specifically, several siderophore biosynthetic gene clusters were consistently associated with suppressive soils, hinting at competition for iron as a potential mechanism of suppression. Finally, to validate dom2BGC and to allow more unbiased functional metagenomics, we performed 10× metagenomic sequencing of one suppressive soil, leading to the identification of multiple gene clusters potentially associated with the disease-suppressive phenotype. IMPORTANCE Soil-borne plant-pathogenic fungi continue to be a major threat to agriculture and horticulture. The genus Fusarium in particular is one of the most devastating groups of soilborne fungal pathogens for a wide range of crops. Our approach to develop novel sustainable strategies to control this fungal root pathogen is to explore and exploit an effective, yet poorly understood naturally occurring protection, i.e., disease-suppressive soils. After screening 28 agricultural soils, we recently identified four soils that were suppressive to root disease of wheat caused by Fusarium culmorum. We also confirmed, via sterilization and transplantation, that the microbiomes of these soils play a significant role in the suppressive phenotype. By adopting nonribosomal peptide synthetase (NRPS) functional amplicon screening of suppressive and conducive soils, we here show how computationally driven comparative analysis of combined functional amplicon and metagenomic data can unravel putative mechanisms underlying microbiome-associated plant phenotypes.

Dissecting Disease-Suppressive Rhizosphere Microbiomes by Functional Amplicon Sequencing and 10× Metagenomics.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

George Lund

Author Tools

Chat about Author

Papers

MIBiG 2.0: a repository for biosynthetic gene clusters of known function.

Land Management Legacy Affects Abundance and Function of the acdS Gene in Wheat Root Associated Pseudomonads.

Dissecting Disease-Suppressive Rhizosphere Microbiomes by Functional Amplicon Sequencing and 10× Metagenomics.