Back

The bacterial swarming factor SwrD forms hexameric rings reminiscent of DNA binding proteins.

Nair, D.; Zhang, K.; Li, C.; CRANE, B. R.

2026-05-29 biochemistry
10.64898/2026.05.26.727983 bioRxiv
Show abstract

Prokaryotic swarming is a collective surface-associated behavior that supports rapid colonization, biofilm formation, and host interactions. Swarming requires enhanced flagellar motor (FM) torque generation under high-load conditions. In many bacteria, this adaptation is achieved through increased stator unit recruitment and coordinated transcriptional regulation of motility genes. Genetic studies have implicated several relatively poorly characterized proteins in swarming, including SwrD, a component of the fla-che operon whose loss impairs torque generation in Bacillus subtilis. Intriguingly, SwrD is conserved in spirochetes that experience high viscous loads but do not exhibit canonical swarming, suggesting a broader functional role in FM regulation. Here, we structurally and biophysically characterize SwrD from B. subtilis and the spirochete Borrelia burgdorferi. In both cases, we show that SwrD assembles into a hexameric ring-like structure featuring a highly charged, disordered peripheral tail. Whereas SwrD displays structural similarities to DNA-binding proteins, key DNA interaction motifs are not conserved in SwrD. Deletion of swrD in B. subtilis results in pronounced swarming defects and altered expression of fla-che operon transcripts. In silico interaction analyses further identify the stator protein MotA as a high-confidence SwrD interactor, but this interaction could not be validated biochemically. Conserved SwrD residues mediate subunit interactions or locate to the hexamer periphery where they may mediate functionally important interactions.

Matching journals

The top 5 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.