a Laboratory of Microbiology , Wageningen University & Research , Wageningen , The Netherlands.
b Department of Microbial Ecology, Groningen Institute for Evolutionary Life Sciences (GELIFES) , Rijksuniversiteit Groningen , Groningen , The Netherlands.
Crit Rev Microbiol. 2018 Mar;44(2):212-229. doi: 10.1080/1040841X.2017.1332003. Epub 2017 May 31.
The numbers and diversity of microbes in ecosystems within and around us is unmatched, yet most of these microorganisms remain recalcitrant to in vitro cultivation. Various high-throughput molecular techniques, collectively termed multi-omics, provide insights into the genomic structure and metabolic potential as well as activity of complex microbial communities. Nonetheless, pure or defined cultures are needed to (1) decipher microbial physiology and thus test multi-omics-based ecological hypotheses, (2) curate and improve database annotations and (3) realize novel applications in biotechnology. Cultivation thus provides context. In turn, we here argue that multi-omics information awaits integration into the development of novel cultivation strategies. This can build the foundation for a new era of omics information-guided microbial cultivation technology and reduce the inherent trial-and-error search space. This review discusses how information that can be extracted from multi-omics data can be applied for the cultivation of hitherto uncultured microorganisms. Furthermore, we summarize groundbreaking studies that successfully translated information derived from multi-omics into specific media formulations, screening techniques and selective enrichments in order to obtain novel targeted microbial isolates. By integrating these examples, we conclude with a proposed workflow to facilitate future omics-aided cultivation strategies that are inspired by the microbial complexity of the environment.
生态系统内和周围的微生物数量和多样性是无与伦比的，但这些微生物大多数仍然难以在体外培养。各种高通量分子技术，统称为多组学，提供了对基因组结构和代谢潜力以及复杂微生物群落活性的深入了解。尽管如此，仍需要纯培养或定义培养来：(1) 破译微生物生理学，从而检验基于多组学的生态假设；(2) 整理和改进数据库注释；(3) 在生物技术中实现新的应用。因此，培养提供了背景。反过来，我们在这里认为，多组学信息有待于整合到新的培养策略的开发中。这可以为基于组学信息的新型微生物培养技术的新时代奠定基础，并减少固有试错的搜索空间。本文讨论了如何从多组学数据中提取的信息可用于培养迄今为止未培养的微生物。此外，我们总结了一些开创性的研究，这些研究成功地将多组学数据中提取的信息转化为特定的培养基配方、筛选技术和选择性富集，以获得新的目标微生物分离物。通过整合这些例子，我们得出了一个建议的工作流程，以促进未来受环境中微生物复杂性启发的基于组学的培养策略。
