{"title":"Discovering Biological Conflict Systems Through Genome Analysis: Evolutionary Principles and Biochemical Novelty.","authors":"L. Aravind, L. Iyer, A. M. Burroughs","doi":"10.1146/annurev-biodatasci-122220-101119","DOIUrl":null,"url":null,"abstract":"Biological replicators, from genes within a genome to whole organisms, are locked in conflicts. Comparative genomics has revealed a staggering diversity of molecular armaments and mechanisms regulating their deployment, collectively termed biological conflict systems. These encompass toxins used in inter- and intraspecific interactions, self/nonself discrimination, antiviral immune mechanisms, and counter-host effectors deployed by viruses and intragenomic selfish elements. These systems possess shared syntactical features in their organizational logic and a set of effectors targeting genetic information flow through the Central Dogma, certain membranes, and key molecules like NAD+. These principles can be exploited to discover new conflict systems through sensitive computational analyses. This has led to significant advances in our understanding of the biology of these systems and furnished new biotechnological reagents for genome editing, sequencing, and beyond. We discuss these advances using specific examples of toxins, restriction-modification, apoptosis, CRISPR/second messenger-regulated systems, and other enigmatic nucleic acid-targeting systems. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":null,"pages":null},"PeriodicalIF":7.0000,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Biomedical Data Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1146/annurev-biodatasci-122220-101119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 8
Abstract
Biological replicators, from genes within a genome to whole organisms, are locked in conflicts. Comparative genomics has revealed a staggering diversity of molecular armaments and mechanisms regulating their deployment, collectively termed biological conflict systems. These encompass toxins used in inter- and intraspecific interactions, self/nonself discrimination, antiviral immune mechanisms, and counter-host effectors deployed by viruses and intragenomic selfish elements. These systems possess shared syntactical features in their organizational logic and a set of effectors targeting genetic information flow through the Central Dogma, certain membranes, and key molecules like NAD+. These principles can be exploited to discover new conflict systems through sensitive computational analyses. This has led to significant advances in our understanding of the biology of these systems and furnished new biotechnological reagents for genome editing, sequencing, and beyond. We discuss these advances using specific examples of toxins, restriction-modification, apoptosis, CRISPR/second messenger-regulated systems, and other enigmatic nucleic acid-targeting systems. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
期刊介绍:
The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.