Molecular mechanisms and regulatory networks governing Yersinia biofilm formation and host adaptation

ABSTRACT The genus Yersinia includes three human pathogens— Y . pestis , Y. pseudotuberculosis , and Y. enterocolitica —where biofilm formation plays distinct roles in transmission and environmental persistence. All three species share the core biofilm machinery—the hmsHFRS operon, encoding enzymes for poly-β-1,6-N-acetylglucosamine (PNAG) exopolysaccharide production, and the c-di-GMP signaling controlling this production—but their regulatory networks and biofilm outputs differ. Transcriptional control of hms involves an integrated network that includes the Rcs phosphorelay (reshaped by rcsA pseudogenization), PhoP/PhoQ, EnvZ/OmpR, BarA/UvrY, Fur/Zur, CRP-cAMP, RovM/RovA, and multiple sigma factors. Post-transcriptionally, the Hfq-sRNA and CsrA-CsrB/CsrC systems modulate gene expression; the latter is directly validated in Y. pestis and Y. pseudotuberculosis , whereas its role in Y. enterocolitica is inferred from genomic conservation. At the translational and enzymatic levels, polyamines sustain Hms protein production, while redox signals govern the HmsC-HmsD disulfide switch, controlling diguanylate cyclase activity. This multi-layer architecture ensures that biofilm output is tuned to species-specific ecological niches. In host adaptation, Y. pestis transitioned from a foodborne enteric pathogen to a flea-borne lifestyle through key genetic events—acquisition of ymt , pseudogenization of rcsA , inactivation of y2909 / y3389, and ureD —which are not shared with Y. pseudotuberculosis or Y. enterocolitica , thereby explaining their different biofilm-dependent transmission strategies. Studies in Caenorhabditis elegans have identified host O-glycosylation modifications as receptors for biofilm attachment. This review summarizes progress on the molecular mechanisms, regulatory networks, and host-adaptive functions of Yersinia biofilm formation and proposes future research directions to address knowledge gaps. Future priorities include the identification of c-di-GMP effectors, flea-specific signals, 3D biofilm imaging, and CRISPR-based detection.