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Advancements in prokaryotic systematics and the role of Bergey's International Society for Microbial Systematicsin addressing challenges in the meta-data era.

Jian-Yu JiaoRashidin AbdugheniDao-Feng ZhangIftikhar AhmedMukhtiar AliMaria ChuvochinaSvetlana N DedyshXiuzhu DongMarkus GökerBrian P HedlundPhilip HugenholtzKamlesh JangidShuang-Jiang LiuEdward R B MooreManik Prabhu Narsing RaoAharon OrenRamon Rossello-MoraBhagwan Narayan RekadwadNimaichand SalamWensheng ShuIain C SutcliffeWee Fei Aaron TeoMartha E TrujilloStephanus N VenterWilliam B WhitmanGuoping ZhaoWen-Jun Li
Published in: National science review (2024)
Prokaryotes are ubiquitous in the biosphere, important for human health and drive diverse biological and environmental processes. Systematics of prokaryotes, whose origins can be traced to the discovery of microorganisms in the 17th century, has transitioned from a phenotype-based classification to a more comprehensive polyphasic taxonomy and eventually to the current genome-based taxonomic approach. This transition aligns with a foundational shift from studies focused on phenotypic traits that have limited comparative value to those using genome sequences. In this context, Bergey's Manual of Systematics of Archaea and Bacteria (BMSAB) and Bergey's International Society for Microbial Systematics (BISMiS) play a pivotal role in guiding prokaryotic systematics. This review focuses on the historical development of prokaryotic systematics with a focus on the roles of BMSAB and BISMiS. We also explore significant contributions and achievements by microbiologists, highlight the latest progress in the field and anticipate challenges and opportunities within prokaryotic systematics. Additionally, we outline five focal points of BISMiS that are aimed at addressing these challenges. In conclusion, our collaborative effort seeks to enhance ongoing advancements in prokaryotic systematics, ensuring its continued relevance and innovative characters in the contemporary landscape of genomics and bioinformatics.
Keyphrases
  • human health
  • risk assessment
  • genome wide
  • microbial community
  • single cell
  • climate change
  • deep learning
  • machine learning
  • dna methylation
  • gene expression
  • quality improvement
  • artificial intelligence