Dataset Information

Novel approach in whole genome mining and transcriptome analysis reveal conserved RiPPs in Trichoderma spp.

ABSTRACT: BACKGROUND:Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a highly diverse group of secondary metabolites (SM) of bacterial and fungal origin. While RiPPs have been intensively studied in bacteria, little is known about fungal RiPPs. In Fungi only six classes of RiPPs are described. Current strategies for genome mining are based on these six known classes. However, the genes involved in the biosynthesis of theses RiPPs are normally organized in biosynthetic gene clusters (BGC) in fungi. RESULTS:Here we describe a comprehensive strategy to mine fungal genomes for RiPPs by combining and adapting existing tools (e.g. antiSMASH and RiPPMiner) followed by extensive manual curation based on conserved domain identification, (comparative) phylogenetic analysis, and RNASeq data. Deploying this strategy, we could successfully rediscover already known fungal RiPPs. Further, we analysed four fungal genomes from the Trichoderma genus. We were able to find novel potential RiPP BGCs in Trichoderma using our unconventional mining approach. CONCLUSION:We demonstrate that the unusual mining approach using tools developed for bacteria can be used in fungi, when carefully curated. Our study is the first report of the potential of Trichoderma to produce RiPPs, the detected clusters encode novel uncharacterized RiPPs. The method described in our study will lead to further mining efforts in all subdivisions of the fungal kingdom.

SUBMITTER: Vignolle GA

PROVIDER: S-EPMC7099791 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Novel approach in whole genome mining and transcriptome analysis reveal conserved RiPPs in Trichoderma spp.

Vignolle Gabriel A GA Mach Robert L RL Mach-Aigner Astrid R AR Derntl Christian C

BMC genomics 20200327 1

<h4>Background</h4>Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a highly diverse group of secondary metabolites (SM) of bacterial and fungal origin. While RiPPs have been intensively studied in bacteria, little is known about fungal RiPPs. In Fungi only six classes of RiPPs are described. Current strategies for genome mining are based on these six known classes. However, the genes involved in the biosynthesis of theses RiPPs are normally organized in biosyntheti ...[more]

PMID: 32216757

Similar Datasets

Project description:BackgroundProteins within aphid saliva play a crucial role as the molecular interface between aphids and their host plants. These salivary effectors modulate plant responses to favour aphid feeding and facilitate infestation. The identification of effectors from economically important pest species is central in understanding the molecular events during the aphid-plant interaction. The Russian wheat aphid (Diuraphis noxia, Kurdjumov) is one such pest that causes devastating losses to wheat and barley yields worldwide. Despite the severe threat to food security posed by D. noxia, the non-model nature of this pest and its host has hindered progress towards understanding this interaction. In this study, in the absence of a salivary gland transcriptome, whole-body transcriptomics data was mined to generate a candidate effector catalogue for D. noxia.ResultsMining the transcriptome identified 725 transcripts encoding putatively secreted proteins amongst which were transcripts specific to D. noxia. Six of the seven examined D. noxia putative effectors, termed DnE's (Diuraphis noxia effectors) exhibited salivary gland-specific expression. A comparative analysis between whole-body D. noxia transcriptome data versus the head and body transcriptomes from three other aphid species allowed us to define a catalogue of transcripts putatively upregulated in D. noxia head tissue. Five of these were selected for RT-qPCR confirmation, and were found to corroborate the differential expression predictions, with a further three confirmed to be highly expressed in D. noxia salivary gland tissue.ConclusionsDetermining a putative effector catalogue for D. noxia from whole-transcriptome data, particularly the identification of salivary-specific sequences potentially unique to D. noxia, provide the basis for future functional characterisation studies to gain further insight into this aphid-plant interaction. Furthermore, due to a lack of publicly available aphid salivary gland transcriptome data, the capacity to use comparative transcriptomics to compile a list of putative effector candidates from whole-body transcriptomics data will further the study of effectors in various aphid species.

Project description:Background:Cross-species whole-genome sequence alignment is a critical first step for genome comparative analyses, ranging from the detection of sequence variants to studies of chromosome evolution. Animal genomes are large and complex, and whole-genome alignment is a computationally intense process, requiring expensive high-performance computing systems due to the need to explore extensive local alignments. With hundreds of sequenced animal genomes available from multiple projects, there is an increasing demand for genome comparative analyses. Results:Here, we introduce G-Anchor, a new, fast, and efficient pipeline that uses a strictly limited but highly effective set of local sequence alignments to anchor (or map) an animal genome to another species' reference genome. G-Anchor makes novel use of a databank of highly conserved DNA sequence elements. We demonstrate how these elements may be aligned to a pair of genomes, creating anchors. These anchors enable the rapid mapping of scaffolds from a de novo assembled genome to chromosome assemblies of a reference species. Our results demonstrate that G-Anchor can successfully anchor a vertebrate genome onto a phylogenetically related reference species genome using a desktop or laptop computer within a few hours and with comparable accuracy to that achieved by a highly accurate whole-genome alignment tool such as LASTZ. G-Anchor thus makes whole-genome comparisons accessible to researchers with limited computational resources. Conclusions:G-Anchor is a ready-to-use tool for anchoring a pair of vertebrate genomes. It may be used with large genomes that contain a significant fraction of evolutionally conserved DNA sequences and that are not highly repetitive, polypoid, or excessively fragmented. G-Anchor is not a substitute for whole-genome aligning software but can be used for fast and accurate initial genome comparisons. G-Anchor is freely available and a ready-to-use tool for the pairwise comparison of two genomes.

Project description:UnlabelledGenome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways.ImportanceMicrobial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including streptothricins, borrelidin, two novel lipopeptides, and one unknown antibiotic from Streptomyces rochei Sal35. The transfer, expression, and screening of the library were all performed in a high-throughput way, so that this approach is scalable and adaptable to industrial automation for next-generation antibiotic discovery.

Dataset Information

Novel approach in whole genome mining and transcriptome analysis reveal conserved RiPPs in Trichoderma spp.

Publications

Novel approach in whole genome mining and transcriptome analysis reveal conserved RiPPs in Trichoderma spp.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets