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Database mining of plant peptide homologues.

ABSTRACT: In plant-pathogen interactions, pathogens employ secreted molecules, known as effectors to overcome physical barriers, modulate plant immunity, and facilitate colonization. Among these diverse effectors, some are found to mimic the plant peptides, to target host's peptide receptors, and intervene in the peptide-regulated defense pathways and/or plant development. To better understand how pathogens have co-evolved with their plant hosts in order to improve disease management, we explored the presence of plant peptide mimics in microbes by bioinformatic analysis. In total, 36 novel peptide mimics belong to five plant peptide families were detected in bacterial and fungal kingdoms. Among them, phytosulfokine homologues were widely distributed in 22 phytopathogens and one bacterium, thereby constituted the largest proportion of the identified mimics. The putative functional peptide region is well conserved between plant and microbes, while the existence of a putative signal peptide varies between species. Our findings will increase understanding of plant-pathogen interactions, and provide new ideas for future studies of pathogenic mechanisms and disease management.

SUBMITTER: Yuan N

PROVIDER: S-EPMC8215471 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Database mining of plant peptide homologues.

Yuan Na N Furumizu Chihiro C Zhang Baolong B Sawa Shinichiro S

Plant biotechnology (Tokyo, Japan) 20210301 1

In plant-pathogen interactions, pathogens employ secreted molecules, known as effectors to overcome physical barriers, modulate plant immunity, and facilitate colonization. Among these diverse effectors, some are found to mimic the plant peptides, to target host's peptide receptors, and intervene in the peptide-regulated defense pathways and/or plant development. To better understand how pathogens have co-evolved with their plant hosts in order to improve disease management, we explored the pres ...[more]

PMID: 34177333

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Project description:BACKGROUND: Sireviruses are an ancient genus of the Copia superfamily of LTR retrotransposons, and the only one that has exclusively proliferated within plant genomes. Based on experimental data and phylogenetic analyses, Sireviruses have successfully infiltrated many branches of the plant kingdom, extensively colonizing the genomes of grass species. Notably, it was recently shown that they have been a major force in the make-up and evolution of the maize genome, where they currently occupy ~21% of the nuclear content and ~90% of the Copia population. It is highly likely, therefore, that their life dynamics have been fundamental in the genome composition and organization of a plethora of plant hosts. To assist studies into their impact on plant genome evolution and also facilitate accurate identification and annotation of transposable elements in sequencing projects, we developed MASiVEdb (Mapping and Analysis of SireVirus Elements Database), a collective and systematic resource of Sireviruses in plants. DESCRIPTION: Taking advantage of the increasing availability of plant genomic sequences, and using an updated version of MASiVE, an algorithm specifically designed to identify Sireviruses based on their highly conserved genome structure, we populated MASiVEdb (http://bat.infspire.org/databases/masivedb/) with data on 16,243 intact Sireviruses (total length >158Mb) discovered in 11 fully-sequenced plant genomes. MASiVEdb is unlike any other transposable element database, providing a multitude of highly curated and detailed information on a specific genus across its hosts, such as complete set of coordinates, insertion age, and an analytical breakdown of the structure and gene complement of each element. All data are readily available through basic and advanced query interfaces, batch retrieval, and downloadable files. A purpose-built system is also offered for detecting and visualizing similarity between user sequences and Sireviruses, as well as for coding domain discovery and phylogenetic analysis. CONCLUSION: MASiVEdb is currently the most comprehensive directory of Sireviruses, and as such complements other efforts in cataloguing plant transposable elements and elucidating their role in host genome evolution. Such insights will gradually deepen, as we plan to further improve MASiVEdb by phylogenetically mapping Sireviruses into families, by including data on fragments and solo LTRs, and by incorporating elements from newly-released genomes.

Project description:BackgroundBlood chemicals are routinely measured in clinical or preclinical research studies to diagnose diseases, assess risks in epidemiological research, or use metabolomic phenotyping in response to treatments. A vast volume of blood-related literature is available via the PubMed database for data mining.ObjectivesWe aimed to generate a comprehensive blood exposome database of endogenous and exogenous chemicals associated with the mammalian circulating system through text mining and database fusion.MethodsUsing NCBI resources, we retrieved PubMed abstracts, PubChem chemical synonyms, and PMC supplementary tables. We then employed text mining and PubChem crowdsourcing to associate phrases relating to blood with PubChem chemicals. False positives were removed by a phrase pattern and a compound exclusion list.ResultsA query to identify blood-related publications in the PubMed database yielded 1.1 million papers. Matching a total of 15 million synonyms from 6.5 million relevant PubChem chemicals against all blood-related publications yielded 37,514 chemicals and 851,999 publications records. Mapping PubChem compound identifiers to the PubMed database yielded 49,940 unique chemicals linked to 676,643 papers. Analysis of open-access metabolomics papers related to blood phrases in the PMC database yielded 4,039 unique compounds and 204 papers. Consolidating these three approaches summed up to a total of 41,474 achiral structures that were linked to 65,957 PubChem CIDs and to over 878,966 PubMed articles. We mapped these compounds to 50 databases such as those covering metabolites and pathways, governmental and toxicological databases, pharmacology resources, and bioassay repositories. In comparison, HMDB, the Human Metabolome Database, links 1,075 compounds to blood-related primary publications.ConclusionThis new Blood Exposome Database can be used for prioritizing chemicals for systematic reviews, developing target assays in exposome research, identifying compounds in untargeted mass spectrometry, and biological interpretation in metabolomics data. The database is available at http://bloodexposome.org. https://doi.org/10.1289/EHP4713.

Dataset Information

Database mining of plant peptide homologues.

Publications

Database mining of plant peptide homologues.

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