Redox oscillation frequency reshapes antibiotic resistance-gene expression through metabolic and ecological selection in a freshwater community

Authors

Manna, B., Keenum, I., Liu, Q., Singhal, N.

Abstract

Aquatic environments can maintain and express antibiotic resistance genes even without antibiotic pressure, but the conditions that govern their activity remain poorly understood. Redox oscillations are pervasive in natural and engineered waters and strongly alter microbial metabolism, yet whether their frequency shapes resistance expression is unknown. We reanalyzed paired metagenomes and metatranscriptomes from a published chemostat experiment in which a sulfidic stream community was cycled between oxic and anoxic conditions at high, medium and low frequency (HF, MF, LF), with strain-resolved population genomics of the dominant Pseudomonas lineage. Resistance genes were broadly distributed across treatments, whereas transcription concentrated under fast cycling, reaching a median 168 TPM under HF against 38 under LF although no antibiotic was present, so genetic potential and expression diverged. Fast cycling induced ROS-generating flavoproteins, antioxidant defenses and transcription-coupled DNA repair, and Pseudomonas supplied 99% of resistance-gene transcripts under HF, chiefly through its intrinsic efflux systems. Within the dominant Pseudomonas genome, however, the four resistance genes carried no sequence variants under HF, where coverage was deepest, and no fixed difference from the reference in any sample. Genome-wide selection remained purifying throughout (pooled pN/pS 0.72 under HF against 0.12 under LF, both below 1), and the relaxation trended toward redox and central metabolism. Redox frequency therefore raises resistance expression by selecting a metabolically versatile, high-efflux lineage, while the resistance sequences themselves stay conserved. Resistance activity in aquatic systems responds to an abiotic driver, which argues for weighing expression alongside gene presence in environmental surveillance.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 02 Oct 2026.

Stats

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.