Integrative advances in bacterial sensory systems and AI-driven microbial biotechnology

Bacterial sensory systems represent a dynamic and rapidly evolving area at the intersection of molecular microbiology and biochemistry, where recent advances are reshaping our understanding of how microbes perceive, respond to, and interact with their environment. This research field is now a notable illustration of an integrated, multidisciplinary approach that results in engineering and cutting-edge technology.

The use of various Bacillus and Lactobacillus strains in the treatment of infections, metabolic disorders, obesity, cancer, and other genetic diseases already alludes to highly innovative technology and the future of health science. It becomes crucial to investigate and/or forecast how these various strains will come together and function as treatment, targeting the defective mutation or the toxicant, in order to prepare for a future in which there are no drugs and just natural medicine.

Recent breakthroughs have shed light on the diversity and sophistication of microbial sensory mechanisms—including chemoreceptors, photoreceptors, and complex regulatory cascades—that govern phenomena ranging from antagonistic inter-microbial interactions in animal organisms to the therapeutic benefits of commensal strains. Although “mechanistic” and functional research must be done within these symbiotic strains, completely autotrophic species like cyanobacteria that have existed in free-living environments for over 3000 years cannot be disregarded, particularly if we wish to study sensing and cell-cell interaction and apply the knowledge to prediction algorithms. If we also exclude bacteriophages and their close relationship with bacterial cells, then there can be no ideal model. Transduction (or horizontal transfer) is a process that depends on bacteriophages. In order to transfer a sensory ability or a biocatalytic repair enzyme from Bacillus to symbionts, bacteriophages must transfer genetic material from one bacteria to another. This is a crucial step in our future endeavors.

Notably, the exploration of cyanobacterial communication, spanning quorum sensing to phototaxis, and the dynamic roles of bacteriophages in bacterial population control, has broadened our understanding of microbial ecology, community resilience, and pathogenicity. Despite these advances, knowledge gaps remain significant; the molecular logic underlying bacterial “senses,” intercellular signaling, and environmental responsiveness has yet to be fully decoded, especially when it comes to potential medical applications. Each member of the family of bacilli, lactobacteria, cyanobacteria, and bacteriophages has a specificity that we must be able to integrate. In microbes and phages, many mechanisms that drive collective adaptation, affect resistance profiles, and enable functional specialization are not well understood, underscoring the field’s evolving nature and the pressing need for integrative methodologies.

When we talk about microorganisms, phages, and viruses that infect bacterial cells, we are referring to a portion of the universal but “infinitely small”, difficult-to-see, difficult-to-analyze, and difficult-to-interpret realm that, even after four centuries, is seamlessly transitioning into a new one of modern science (computers). Still, a major shift is occurring with the integration of artificial intelligence (AI) and computational biology, enabling researchers to analyze vast genomic datasets, uncover novel sensory pathways, and predict functional outcomes with unprecedented speed and accuracy. AI models now accelerate hypothesis generation while revealing genomic signatures underlying critical traits such as antibacterial resistance, sensory flexibility, and phage susceptibility. This multifaceted approach—as embodied by expertise in molecular microbiology, physiology, microbial biochemistry, genetics, proteomics, bacteriophage-bacteria interactions, and computational microbiomics—is essential for moving beyond descriptive “mechanistic” science to harness bacterial sensory systems and cell-cell interactions in practical applications. The Research Topic thus aims not only to elucidate genetic and molecular underpinnings but also to inspire engineering of innovative functionalities in microbial populations for use in medicine, environmental biosensing, and industrial bioprocesses. The optimum course of treatment, which will mostly include introducing new metabolic or sensory genes, can be determined by AI based on a patient’s or cell’s susceptibility to drugs and antibiotics.

We welcome submissions that bridge foundational scientific discovery with the development of novel technologies and practical applications. To gather further insights into how these bacterial systems can be better understood and utilized in AI, we welcome contributions spanning, but not limited to, the following themes:

o Genetic adaptation, evolutionary diversification, and functional genomics of microbial consortia

o Chemoreceptors, photoreceptors, mechanoreceptors, and bacterial sensory machinery

o Molecular and genetic basis of bacterial chemotaxis, olfaction, and photoresponse

o Cyanobacterial communication: from quorum sensing to phototaxis

o Bacteriophage-bacteria interactions and their therapeutic and ecological significance

o AI and computational approaches for modeling, analyzing, and redesigning bacterial sensory systems

o Applications of bio-inspired sensors and engineered microbes in biosensing, drug delivery, or environmental technology