Although there has been an explosion in methods and applications of single-cell genomic profiling in mammalian systems, single-cell profiling approaches for measuring DNA or RNA in individual microbes remain in their infancy. 
Nevertheless, the field of microbiology recognizes single-cell approaches as a promising tool, for example, to characterize heterogeneity in functional responses to different conditions or challenges. The difficulty of microbial single-cell approaches is at least partly due to their physical and molecular properties. Our recent work (Elife 2023) was the first to tailor a nanolitre-droplet assay to profile individual transcriptomes of the fungal pathogen Candida albicans. We used this device to explore phenotypic heterogeneity in a laboratory strain of this fungus. Our study provided deeper insight into how genetically identical individuals have different responses to the same stresses that ultimately enable some individuals to survive and others to die. The heterogeneity observed in monocultures will likely be greatly magnified in complex microbial environments such as the gut microbiome.
Host-adapted microbial communities, commonly referred to as microbiomes, consist of diverse microorganisms including commensal, symbiotic, and pathogenic species occupying specific anatomical niches. Traditionally, community compositions are quantified as vectors of relative abundances at various taxonomic levels. Studies have found that host-adapted microbiomes are variable across individuals, yet certain configurations are observed more frequently across the global population than what we would expect by chance. Multiple factors, ranging from environmental pressures to intrinsic microbe-microbe interactions, could explain the existence of these preferred configurations.
In humans, significant efforts have been dedicated to defining dominant microbial configurations (MCs) within various microbiomes, including those of the vagina, skin, oral cavity, and gut. In the gut, MCs, also called enterotypes, have been associated with dietary, and various metabolic or immunological markers. Despite these advancements, the functional roles and the underlying mechanisms contributing to the stability and resilience of these MCs remain poorly understood.
Our research is developing novel computational approaches to identify and characterize specific MCs. We apply deep learning to analyze a large compendium of healthy adult gut microbiomes, capturing non-linear trends between features, such as taxa or pathway abundances. These efforts aim to refine the definition and understanding of both compositional and functional MCs. As we delve deeper into the intricacies of MCs, the opportunities to modulate them for varied applications in biomedicine, environment, and synthetic biology will expand.
Relevant recent papers:
Candida albicans exhibits heterogeneous and adaptive cytoprotective responses to anti-fungal compounds