Identification and Characterization of Signals Recognized by Bacterial Extracellular Sensory Domains

Field: Immunology and Microbiology (Life Sciences)

Bacteria are ubiquitous and essential components of all ecosystems, not merely existing as solitary entities but rather within complex multispecies communities. The stability of these communities is maintained primarily through the complicated microbial interactions mediated by signal transduction systems. Comprehending these signaling mechanisms is crucial, as they play a role in various physiological processes such as motility, metabolism, biofilm formation, and antibiotic resistance. Although their conserved signaling core is well-characterized, signal recognition by bacterial sensors remains largely unknown. To bridge this gap, we aim to establish a systematic strategy to broadly explore the signals recognized by sensory receptors in different bacterial species, leveraging recent advances in experimental techniques, bioinformatics, and genomic analysis. In the first paper, we employed Pseudomonas aeruginosa PAO1 as a model organism to develop a screening strategy for identifying chemoreceptor specificities. Although Escherichia coli has the simplest and best-studied chemotaxis system, it lacks the diversity of sensory domains found in other organisms. In contrast, P. aeruginosa PAO1 harbors four different chemosensory pathways and diverse sensory domains that are crucial for detecting diverse stimuli. Given that accessing nutrients is the primary benefit of chemotaxis, this chemoreceptor-targeted strategy focused on metabolites with metabolic value. We first identified novel attractants of varying strength from these metabolites by performing capillary chemotaxis assays. Subsequently, a rational combination of various in vivo and in vitro methods enabled us to assign several new attractants to previously characterized chemoreceptors and to annotate a novel purine-specific receptor PctP. Overall, these findings suggested that our screening strategy can be applied to the systematic characterization of unknown chemoreceptors in a wide range of bacterial species. Recent advances in genome sequencing and analysis have revealed an extremely large repertoire of unknown sensory receptors, including not only chemoreceptors but also sensor histidine kinases and transcriptional regulators. This discovery provides a rich resource for extensively identifying sensory receptors in many understudied organisms. The human gut, in particular, is an ideal target for this field of research. Our second paper has developed a framework that enables the identification of sensory domains, prediction of the signals they recognize, and experimental verification of these predictions. This framework began with a bioinformatic approach for identifying sensory domains from both fully sequenced and metagenome-assembled genomes and further predicted their signals based on conserved binding motifs. Subsequently, we validated the accuracy of these predictions through various experimental approaches, as performed in our first study. This pipeline can be used in a variety of situations and is particularly suitable for complex research systems such as microbiota. Building upon our second paper, we successfully expanded our research scope from chemoreceptors in one organism to various sensory receptors in human gut microbiota and generated a curated list containing thousands of unknown sensory domains. In the third paper, we delved into approximately one hundred representative sensory domains selected from this curated list. Using high-throughput thermal shift assays, we characterized several novel bacterial sensory receptors that recognize physiologically relevant signaling molecules in the human gut, further elucidating their underlying molecular mechanisms. Our studies highlighted the differences in stimulus spectrum between two functional classes, with nutrient compounds primarily sensed by chemoreceptors but not by histidine kinases. Moreover, we defined two novel sensor subclasses that bind uracil and short-chain carboxylates, respectively. Ultimately, for the first time, we utilized several conserved binding motifs to predict the abundance of corresponding ligand-specific sensors at the human gut microbiome level. In conclusion, this thesis presents a genomics-guided and interdisciplinary strategy for identifying signals recognized by bacterial sensory receptors, applicable across a wide range of research areas from single bacteria to complex microbiota. These findings pave the way for a deeper understanding of bacterial chemotactic and metabolic preferences and provide novel insights into interspecies communication within the human gut.