Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA.
Plant Gene Expression Center, USDA-ARS, Albany, CA, USA.
Microbiome. 2021 Mar 24;9(1):69. doi: 10.1186/s40168-021-01014-z.
Host-microbiome interactions are recognized for their importance to host health. An improved understanding of the molecular underpinnings of host-microbiome relationships will advance our capacity to accurately predict host fitness and manipulate interaction outcomes. Within the plant microbiome research field, unlocking the functional relationships between plants and their microbial partners is the next step to effectively using the microbiome to improve plant fitness. We propose that strategies that pair host and microbial datasets-referred to here as holo-omics-provide a powerful approach for hypothesis development and advancement in this area. We discuss several experimental design considerations and present a case study to highlight the potential for holo-omics to generate a more holistic perspective of molecular networks within the plant microbiome system. In addition, we discuss the biggest challenges for conducting holo-omics studies; specifically, the lack of vetted analytical frameworks, publicly available tools, and required technical expertise to process and integrate heterogeneous data. Finally, we conclude with a perspective on appropriate use-cases for holo-omics studies, the need for downstream validation, and new experimental techniques that hold promise for the plant microbiome research field. We argue that utilizing a holo-omics approach to characterize host-microbiome interactions can provide important opportunities for broadening system-level understandings and significantly inform microbial approaches to improving host health and fitness. Video abstract.
宿主-微生物组的相互作用因其对宿主健康的重要性而受到重视。对宿主-微生物组关系的分子基础有了更深入的了解，将提高我们准确预测宿主适应性和操纵相互作用结果的能力。在植物微生物组研究领域，揭示植物与其微生物伙伴之间的功能关系是下一步有效利用微生物组来提高植物适应性的关键。我们提出，将宿主和微生物数据集配对的策略——这里称为全组学——为该领域的假说发展和推进提供了一种强大的方法。我们讨论了几个实验设计的考虑因素，并提出了一个案例研究，强调了全组学在生成植物微生物组系统内分子网络更全面视角方面的潜力。此外，我们还讨论了进行全组学研究的最大挑战；具体来说，缺乏经过验证的分析框架、公开可用的工具以及处理和整合异构数据所需的技术专长。最后，我们从全组学研究的适用案例、下游验证的必要性以及对植物微生物组研究领域有前途的新实验技术的角度进行了总结。我们认为，利用全组学方法来描述宿主-微生物组的相互作用，可以为拓宽系统水平的理解提供重要机会，并为改善宿主健康和适应性的微生物方法提供重要信息。视频摘要。
