Implications of the three-dimensional chromatin organization for genome evolution in a fungal plant pathogen.

The spatial organization of eukaryotic genomes is linked to their biological functions, although it is not clear how this impacts the overall evolution of a genome. Here, we uncover the three-dimensional (3D) genome organization of the phytopathogen Verticillium dahliae, known to possess distinct genomic regions, designated adaptive genomic regions (AGRs), enriched in transposable elements and genes that mediate host infection. Short-range DNA interactions form clear topologically associating domains (TADs) with gene-rich boundaries that show reduced levels of gene expression and reduced genomic variation. Intriguingly, TADs are less clearly insulated in AGRs than in the core genome. At a global scale, the genome contains bipartite long-range interactions, particularly enriched for AGRs and more generally containing segmental duplications. Notably, the patterns observed for V. dahliae are also present in other Verticillium species. Thus, our analysis links 3D genome organization to evolutionary features conserved throughout the Verticillium genus.

Exploring the Interspecific Interactions and the Metabolome of the Soil Isolate Hylemonella gracilis.

Microbial community analysis of aquatic environments showed that an important component of its microbial diversity consists of bacteria with cell sizes of ~0.1 µm. Such small bacteria can show genomic reductions and metabolic dependencies with other bacteria. However, so far, no study has investigated if such bacteria exist in terrestrial environments like soil. Here, we isolated soil bacteria that passed through a 0.1-µm filter. The complete genome of one of the isolates was sequenced and the bacterium was identified as Hylemonella gracilis. A set of coculture assays with phylogenetically distant soil bacteria with different cell and genome sizes was performed. The coculture assays revealed that H. gracilis grows better when interacting with other soil bacteria like Paenibacillus sp. AD87 and Serratia plymuthica. Transcriptomics and metabolomics showed that H. gracilis was able to change gene expression, behavior, and biochemistry of the interacting bacteria without direct cell-cell contact. Our study indicates that in soil there are bacteria that can pass through a 0.1-µm filter. These bacteria may have been overlooked in previous research on soil microbial communities. Such small bacteria, exemplified here by H. gracilis, can induce transcriptional and metabolomic changes in other bacteria upon their interactions in soil. In vitro, the studied interspecific interactions allowed utilization of growth substrates that could not be utilized by monocultures, suggesting that biochemical interactions between substantially different sized soil bacteria may contribute to the symbiosis of soil bacterial communities. IMPORTANCE Analysis of aquatic microbial communities revealed that parts of its diversity consist of bacteria with cell sizes of ~0.1 µm. Such bacteria can show genomic reductions and metabolic dependencies with other bacteria. So far, no study investigated if such bacteria exist in terrestrial environments such as soil. Here, we show that such bacteria also exist in soil. The isolated bacteria were identified as Hylemonella gracilis. Coculture assays with phylogenetically different soil bacteria revealed that H. gracilis grows better when cocultured with other soil bacteria. Transcriptomics and metabolomics showed that H. gracilis was able to change gene expression, behavior, and biochemistry of the interacting bacteria without direct contact. Our study revealed that bacteria are present in soil that can pass through 0.1-µm filters. Such bacteria may have been overlooked in previous research on soil microbial communities and may contribute to the symbiosis of soil bacterial communities.

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

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.

Microbial and volatile profiling of soils suppressive to Fusarium culmorum of wheat.

In disease-suppressive soils, microbiota protect plants from root infections. Bacterial members of this microbiota have been shown to produce specific molecules that mediate this phenotype. To date, however, studies have focused on individual suppressive soils and the degree of natural variability of soil suppressiveness remains unclear. Here, we screened a large collection of field soils for suppressiveness to Fusarium culmorum using wheat (Triticum aestivum) as a model host plant. A high variation of disease suppressiveness was observed, with 14% showing a clear suppressive phenotype. The microbiological basis of suppressiveness to F. culmorum was confirmed by gamma sterilization and soil transplantation. Amplicon sequencing revealed diverse bacterial taxonomic compositions and no specific taxa were found exclusively enriched in all suppressive soils. Nonetheless, co-occurrence network analysis revealed that two suppressive soils shared an overrepresented bacterial guild dominated by various Acidobacteria. In addition, our study revealed that volatile emission may contribute to suppression, but not for all suppressive soils. Our study raises new questions regarding the possible mechanistic variability of disease-suppressive phenotypes across physico-chemically different soils. Accordingly, we anticipate that larger-scale soil profiling, along with functional studies, will enable a deeper understanding of disease-suppressive microbiomes.

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

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/.

Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome.

Microorganisms living inside plants can promote plant growth and health, but their genomic and functional diversity remain largely elusive. Here, metagenomics and network inference show that fungal infection of plant roots enriched for Chitinophagaceae and Flavobacteriaceae in the root endosphere and for chitinase genes and various unknown biosynthetic gene clusters encoding the production of nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs). After strain-level genome reconstruction, a consortium of Chitinophaga and Flavobacterium was designed that consistently suppressed fungal root disease. Site-directed mutagenesis then revealed that a previously unidentified NRPS-PKS gene cluster from Flavobacterium was essential for disease suppression by the endophytic consortium. Our results highlight that endophytic root microbiomes harbor a wealth of as yet unknown functional traits that, in concert, can protect the plant inside out.

BiosyntheticSPAdes: reconstructing biosynthetic gene clusters from assembly graphs.

Predicting biosynthetic gene clusters (BGCs) is critically important for discovery of antibiotics and other natural products. While BGC prediction from complete genomes is a well-studied problem, predicting BGCs in fragmented genomic assemblies remains challenging. The existing BGC prediction tools often assume that each BGC is encoded within a single contig in the genome assembly, a condition that is violated for most sequenced microbial genomes where BGCs are often scattered through several contigs, making it difficult to reconstruct them. The situation is even more severe in shotgun metagenomics, where the contigs are often short, and the existing tools fail to predict a large fraction of long BGCs. While it is difficult to assemble BGCs in a single contig, the structure of the genome assembly graph often provides clues on how to combine multiple contigs into segments encoding long BGCs. We describe biosyntheticSPAdes, a tool for predicting BGCs in assembly graphs and demonstrate that it greatly improves the reconstruction of BGCs from genomic and metagenomics data sets.

Mining prokaryotes for antimicrobial compounds: from diversity to function.

The bacterial kingdom provides a major source of antimicrobials that can either be directly applied or used as scaffolds to further improve their functionality in the host. The rapidly increasing amount of bacterial genomic, metabolomic and transcriptomic data offers unique opportunities to apply a variety of approaches to mine for existing and novel antimicrobials. Here, we discuss several powerful mining approaches to identify novel molecules with antimicrobial activity across structurally diverse natural products, including ribosomally synthesized and posttranslationally modified peptides, nonribosomal peptides and polyketides. We not only discuss the direct mining of genomes based on identification of biosynthetic gene clusters, but also describe more advanced and integrative approaches in ecology-based mining, functionality-based mining and mode-of-action-based mining. These efforts are likely to accelerate the discovery and development of novel antimicrobial drugs.