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Schum, D.

Publications and source records attributed to Schum, D..

2 recordsLinked to original sources

The glucocorticoid dexamethasone influences motility of the sulfate-reducing bacterium Desulfovibrio desulfuricans by targeting the filament cap protein FliD

Glucocorticoids such as dexamethasone (DXE) are first-line treatments for inflammatory bowel disease (IBD). Beyond their effects on the host immune system, accumulating evidence suggests that glucocorticoids can also influence the gut microbiota. Notably, IBD patients exhibit an increased intestinal colonization by sulfate-reducing Desulfovibrio spp. Here, we show that DXE modulates bacterial motility in the gut commensal Desulfovibrio desulfuricans through a metabolism-independent mechanism. To identify bacterial targets, we developed a DXE-derived chemical probe and performed affinity-based protein profiling, which revealed the flagellar cap protein FliD (Ddes_0530) as a principal binding partner. Structural modeling using AlphaFold3 and Boltz2 predicted DXE binding within a conserved groove of the FliD C-terminal domain. Furthermore, the tip of the flagellum of Desulfovibrio, but not that of Escherichia coli, could be fluorescently labeled with TAMRA-DXE, but not with the structurally related steroid probe TAMRA-norethiosterone, indicating that flagellar labeling is specific to DXE rather than the steroid scaffold itself. As a consequence of this interaction, transmission electron microscopy showed that DXE treatment prevented flagellation in a subpopulation and reduced flagellar length in D. desulfuricans strains ATCC 27774 and CCUG 72978, respectively. Quantitative motility tracking revealed a non-monotonic, dose-dependent modulation of swimming velocity, with peak stimulation at 10 {micro}M DXE, accompanied by straighter trajectories and enhanced net displacement. Together, these findings uncover a previously unrecognized mode of action for DXE which directly perturbs flagellar biogenesis and motility of an important gut microbiome member of IBD patients. SignificanceGlucocorticoids are widely prescribed for inflammatory conditions, yet their direct effects on gut bacteria remain largely unexplored. We demonstrate that dexamethasone, a synthetic glucocorticoid, binds to the flagellar cap protein FliD of the gut commensal Desulfovibrio desulfuricans, affecting flagellar assembly and altering motility behavior. Unlike previously characterized steroid-metabolizing bacteria such as Clostridium steroidoreducens, Desulfovibrio does not degrade dexamethasone, indicating that the observed effects result from direct drug-protein interaction. These findings establish a new paradigm for metabolism-independent drug-microbiome interactions and suggest that glucocorticoid effects on gut bacteria extend beyond enzymatic degradation pathways.

microbiology↗

Decoding antibiotic modes of action from multimodal cellular responses

Antibiotic resistance continues to rise, yet most new drug candidates act through long-established targets. Faster mode of action (MoA) assessment would enable more effective prioritization of screening hits and help identify compounds with novel mechanisms. In this study, we aimed to develop a scalable framework for MoA inference from antibiotic-induced cellular response profiles in Escherichia coli. We generated a multimodal dataset spanning more than 50 antibiotics, including proteome profiles, chemical structure descriptors, inhibitory concentrations and growth dynamics, and used it to build MAPPER (Mode of Action Prediction via Proteomics-Enhanced Representation), a framework comprising a fixed multimodal predictor and an uncertainty module. MAPPER accurately classified antibiotics across nine mechanistic classes, flagged compounds with likely novel mechanisms and retained predictive power in proteomics-only transfer experiments across mass spectrometry platforms and external data. Together, these results establish MAPPER as an innovative tool for MoA prediction and novelty detection, enabling prioritization of antibacterial candidates with distinct mechanisms.

bioinformatics↗