Department of Microbiology, The Ohio State University, Columbus, Ohio, USA.
Translational Data Analytics Institute, The Ohio State University, Columbus, Ohio, USA.
mBio. 2024 Jun 12;15(6):e0103924. doi: 10.1128/mbio.01039-24. Epub 2024 May 17.
Bacteria sense changes in their environment and transduce signals to adjust their cellular functions accordingly. For this purpose, bacteria employ various sensors feeding into multiple signal transduction pathways. Signal recognition by bacterial sensors is studied mainly in a few model organisms, but advances in genome sequencing and analysis offer new ways of exploring the sensory repertoire of many understudied organisms. The human gut is a natural target of this line of study: it is a nutrient-rich and dynamic environment and is home to thousands of bacterial species whose activities impact human health. Many gut commensals are also poorly studied compared to model organisms and are mainly known through their genome sequences. To begin exploring the signals human gut commensals sense and respond to, we have designed a framework that enables the identification of sensory domains, prediction of signals that they recognize, and experimental verification of these predictions. We validate this framework's functionality by systematically identifying amino acid sensors in selected bacterial genomes and metagenomes, characterizing their amino acid binding properties, and demonstrating their signal transduction potential.IMPORTANCESignal transduction is a central process governing how bacteria sense and respond to their environment. The human gut is a complex environment with many living organisms and fluctuating streams of nutrients. One gut inhabitant, , is a model organism for studying signal transduction. However, is not representative of most gut microbes, and signaling pathways in the thousands of other organisms comprising the human gut microbiota remain poorly understood. This work provides a foundation for how to explore signals recognized by these organisms.
细菌感知其环境的变化,并将信号转导以相应地调整其细胞功能。为此,细菌采用了各种传感器,并将其输入多个信号转导途径。细菌传感器的信号识别主要在少数几种模式生物中进行研究,但基因组测序和分析的进展为探索许多研究较少的生物体的感觉能力提供了新的方法。人类肠道是这一研究方向的天然目标:它是一个营养丰富且动态的环境,是数千种细菌的家园,这些细菌的活动影响着人类的健康。与模式生物相比,许多肠道共生菌的研究也较少,主要通过它们的基因组序列来了解。为了开始探索人类肠道共生菌感知和响应的信号,我们设计了一个框架,能够识别感觉域,预测它们识别的信号,并对这些预测进行实验验证。我们通过系统地在选定的细菌基因组和宏基因组中识别氨基酸传感器,描述它们的氨基酸结合特性,并证明它们的信号转导潜力,验证了该框架的功能。重要性信号转导是控制细菌感知和响应其环境的核心过程。人类肠道是一个复杂的环境,有许多生物体和不断变化的营养物质流。其中一种肠道寄居生物 是研究信号转导的模式生物。然而, 并不代表大多数肠道微生物,由构成人类肠道微生物组的数千种其他生物体组成的信号通路仍知之甚少。这项工作为探索这些生物体识别的信号提供了基础。