Simon Snoeck, Oliver Johanndrees, Thorsten Nürnberger, Cyril Zipfel
{"title":"植物模式识别受体:从进化论到工程学","authors":"Simon Snoeck, Oliver Johanndrees, Thorsten Nürnberger, Cyril Zipfel","doi":"10.1038/s41576-024-00793-z","DOIUrl":null,"url":null,"abstract":"<p>The plant immune system relies on germline-encoded pattern recognition receptors (PRRs) that sense foreign and plant-derived molecular patterns, and signal health threats. Genomic and pangenomic data sets provide valuable insights into the evolution of PRRs and their molecular triggers, which is furthering our understanding of plant–pathogen co-evolution and convergent evolution. Moreover, in silico and in vivo methods of PRR identification have accelerated the characterization of receptor–ligand complexes, and advances in protein structure prediction algorithms are revealing novel PRR sensor functions. Harnessing these recent advances to engineer PRRs presents an opportunity to enhance plant disease resistance against a broad spectrum of pathogens, enabling more sustainable agricultural practices. This Review summarizes both established and innovative approaches to leverage genomic data and translate resulting evolutionary insights into engineering PRR recognition specificities.</p>","PeriodicalId":19067,"journal":{"name":"Nature Reviews Genetics","volume":"10 1","pages":""},"PeriodicalIF":39.1000,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Plant pattern recognition receptors: from evolutionary insight to engineering\",\"authors\":\"Simon Snoeck, Oliver Johanndrees, Thorsten Nürnberger, Cyril Zipfel\",\"doi\":\"10.1038/s41576-024-00793-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The plant immune system relies on germline-encoded pattern recognition receptors (PRRs) that sense foreign and plant-derived molecular patterns, and signal health threats. Genomic and pangenomic data sets provide valuable insights into the evolution of PRRs and their molecular triggers, which is furthering our understanding of plant–pathogen co-evolution and convergent evolution. Moreover, in silico and in vivo methods of PRR identification have accelerated the characterization of receptor–ligand complexes, and advances in protein structure prediction algorithms are revealing novel PRR sensor functions. Harnessing these recent advances to engineer PRRs presents an opportunity to enhance plant disease resistance against a broad spectrum of pathogens, enabling more sustainable agricultural practices. This Review summarizes both established and innovative approaches to leverage genomic data and translate resulting evolutionary insights into engineering PRR recognition specificities.</p>\",\"PeriodicalId\":19067,\"journal\":{\"name\":\"Nature Reviews Genetics\",\"volume\":\"10 1\",\"pages\":\"\"},\"PeriodicalIF\":39.1000,\"publicationDate\":\"2024-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Reviews Genetics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1038/s41576-024-00793-z\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Reviews Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1038/s41576-024-00793-z","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Plant pattern recognition receptors: from evolutionary insight to engineering
The plant immune system relies on germline-encoded pattern recognition receptors (PRRs) that sense foreign and plant-derived molecular patterns, and signal health threats. Genomic and pangenomic data sets provide valuable insights into the evolution of PRRs and their molecular triggers, which is furthering our understanding of plant–pathogen co-evolution and convergent evolution. Moreover, in silico and in vivo methods of PRR identification have accelerated the characterization of receptor–ligand complexes, and advances in protein structure prediction algorithms are revealing novel PRR sensor functions. Harnessing these recent advances to engineer PRRs presents an opportunity to enhance plant disease resistance against a broad spectrum of pathogens, enabling more sustainable agricultural practices. This Review summarizes both established and innovative approaches to leverage genomic data and translate resulting evolutionary insights into engineering PRR recognition specificities.
期刊介绍:
At Nature Reviews Genetics, our goal is to be the leading source of reviews and commentaries for the scientific communities we serve. We are dedicated to publishing authoritative articles that are easily accessible to our readers. We believe in enhancing our articles with clear and understandable figures, tables, and other display items. Our aim is to provide an unparalleled service to authors, referees, and readers, and we are committed to maximizing the usefulness and impact of each article we publish.
Within our journal, we publish a range of content including Research Highlights, Comments, Reviews, and Perspectives that are relevant to geneticists and genomicists. With our broad scope, we ensure that the articles we publish reach the widest possible audience.
As part of the Nature Reviews portfolio of journals, we strive to uphold the high standards and reputation associated with this esteemed collection of publications.