Daum, A. | Search bioRxiv

bioRxiv2026

Large scale antibiotic-phage synergy studies reveal key combinations for urinary tract infection and urosepsis treatments

The growing problem of AMR infections in healthcare has prompted the search for alternative treatments, with increasing interest in bacteriophages. However, most bacteriophage-antibiotic interactions are incompletely understood, and the benefits of combining them remains context dependent. In this study, we screened thousands of phage-antibiotic combinations to assess interaction outcomes in clinical E. coli and K. pneumoniae isolates. By integrating bacteriophages into an existing, scalable clinical MIC determination platform, we identified shifts in antibiotic MIC and susceptibility, revealing patterns of additivity and antagonism. Overall, interactions showed a species-specific profile; additive interactions predominated, particularly for E. coli. Hierarchical clustering highlighted frequent positive interactions between {beta}-lactams and Tequatroviruses. Notably, closely related phages sometimes displayed divergent phenotypes, indicating that interaction outcomes cannot be inferred solely from taxonomic relatedness or genomic similarity. Taken together, these results establish a foundation for rational, evidence-based development of phage-antibiotic therapies to restore and broaden treatment options against multidrug-resistant infections.

microbiology↗

bioRxiv2025

Ion Channel Reaction Networks: Dielectric Screening and the Importance of Off-Pathway Flux

The transport of ions through channels involves multiple rare-event transitions through a web of interconnected intermediates. Extracting open channel mechanisms generally requires quantifying the relative flux through these intermediates in response to a range of electrochemical gradients. Although this is ideally suited to network-based representations like Markov state models (MSMs), the relative contributions from different pathways and the importance of network resolution remain open areas of research. Herein, we use a complementary approach called multiscale responsive kinetic modeling (MsRKM) to explore how the screening of ionic interactions and the competition between multiple mechanistic pathways contribute to channel mechanisms and current profiles of ion channels. We find that explicitly optimizing screened ionic interactions in the MsRKM framework vastly reduces the solution search space, enabling more efficient identification of physically robust solutions. Using a model of the Shaker Kv channel, we demonstrate that even when systems are well described by a single dominant flux pathway, the remaining contributing pathways and off-pathway flux play multiple essential roles, including shifting current profiles and mechanisms in response to different electrochemical gradients. We additionally discover that current continues to change above the experimentally predicted saturation point. Model systems explain how the degree of dielectric screening influences channel occupancy, the number of contributing pathways, and why current increases or decreases above its experimental saturation point. Our findings emphasize the importance of retaining a full network description to identify and understand ion channel mechanisms. Toc O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/637869v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1144eaaorg.highwire.dtl.DTLVardef@387f8eorg.highwire.dtl.DTLVardef@13e4e01org.highwire.dtl.DTLVardef@1732864_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗