Back

DSF signalling integrates c-di-GMP and σ54 pathways with metabolic reprogramming to control Stenotrophomonas maltophilia pathogenicity and antibiotic resistance

Bravo, M.; Gomez, A.-C.; Conchillo-Sole, O.; Garcia-Navarro, A.; Pons, J. L.; Daura, X.; Gibert, I.; Yero, D.

2026-02-03 microbiology
10.64898/2026.02.02.703240 bioRxiv
Show abstract

Stenotrophomonas maltophilia is an opportunistic, multidrug-resistant pathogen whose pathogenicity is mainly driven by biofilm formation, extracellular enzyme production, surface adhesins and motility. In addition, a diffusible signal factor (DSF)-mediated quorum sensing (QS) system encoded by the rpf gene cluster coordinates collective behaviours and contributes to pathogenicity. While DSF signalling has been extensively studied in plant-pathogenic xanthomonads, its integration with transcriptional and metabolic regulation in human pathogens remains poorly defined. Here, we investigate how the DSF/Rpf system shapes virulence and adaptation in S. maltophilia by modulating downstream regulatory and metabolic pathways. Cell density-dependent activation of the RpfC-RpfG two-component system reduces intracellular c-di-GMP levels, promoting a growth phase-dependent switch between biofilm formation and motile lifestyle. This transition requires the global transcriptional regulator Clp, which functions as a transcriptional activator when unbound to c-di-GMP. Clp controls genes involved in motility, adhesion, and the alternative sigma factor {sigma} RpoN2, which inversely regulates flagellar motility and type IV pilus-mediated adhesion. Transcriptomic profiling uncovered additional DSF-dependent regulatory circuits linking quorum sensing to metabolism and antibiotic resistance. Notably, at the onset of stationary phase, the {sigma} paralog RpoN1 acts together with RpfF and RpfB to fine-tune DSF production through fatty acid and central carbon metabolism, coupling QS output to cellular metabolic state. This metabolic control constrains DSF output and impacts colistin susceptibility, highlighting clinically relevant consequences of DSF homeostasis. Together, these findings define a species-specific DSF regulatory architecture in S. maltophilia that integrates quorum sensing, second-messenger signalling, transcriptional regulation, and metabolic reprogramming to promote survival and pathogenicity. Author SummaryStenotrophomonas maltophilia is a bacterial pathogen that causes infections, particularly in hospitalized and immunocompromised patients. Its clinical impact is driven by intrinsic multidrug resistance and the ability to switch between a free-swimming state and a surface-attached biofilm state. Biofilms protect bacteria from antibiotics and the immune system, making infections persistent, while motility promotes spread and colonization. Understanding how S. maltophilia controls this balance is critical for combating infection. Like many bacteria, S. maltophilia uses chemical communication, known as quorum sensing, to sense population density and coordinate behaviours linked to virulence and survival. This system is based on the autoinducer DSF, allowing bacteria to decide when to move, attach, or alter metabolism. In this work, we show that DSF-based quorum sensing activates a regulatory cascade that modulates levels of the signalling molecule c-di-GMP, triggering a switch between biofilm formation and motility. This switch relies on global regulators that control genes involved in movement, adhesion, metabolism, and antibiotic resistance. We also uncover a metabolic feedback mechanism that fine-tunes DSF concentration, impacting bacteria state and antibiotic susceptibility. These findings reveal how bacterial communication, metabolism, and pathogenic behaviour are linked in S. maltophilia, highlighting opportunities for antimicrobial intervention.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.