Bacteriophage therapy is re-emerging as a potential strategy to address antimicrobial resistance, but standardized patient education materials are limited. Large language models (LLMs) are increasingly used for patient-facing medical information. The quality of LLM-generated responses to 20 patient-relevant questions was evaluated by 12 clinicians and research experts in bacteriophage therapy independently rated each response for accuracy, completeness, clarity, and tone/empathy using 5-point Likert scales. Expert suggestions for improvement were recorded. A total of 960 ratings were analyzed. Adjusted mean scores ranged from 3.36 to 3.96 across domains, indicating generally favorable evaluations for all models. Significant differences among LLMs were observed for completeness and tone/empathy (Holm-adjusted p = 0.042 for both), but not for accuracy or clarity. Differences were small in magnitude (Cohen’s d = 0.12–0.29). Claude scored significantly lower than the other models for completeness and tone/empathy, while Perplexity achieved the highest completeness scores. Experts recommended improvements for 34–40% of responses; wrong information was given in 20%. The best responses were revised into an expert-informed patient guide provided as Supplementary Material, presenting a hybrid model in which LLMs generate draft patient information that is subsequently refined by clinical experts, particularly in rapidly evolving therapeutic domains lacking standardized educational resources.
N. Walter, D. Amanatullah, Laurent Debarbieux et al.· npj Viruses· 0 citations
ABSTRACT Monosodium glutamate (MSG; L-glutamate monosodium salt) is among the most widely used flavor enhancers, yet its molecular effects on gut microbial physiology remain poorly understood. Here, we examined the strain-specific transcriptomic and metabolic responses of Clostridium butyricum and Bacteroides thetaiotaomicron grown in pure anaerobic culture with 0.1% (wt/vol) MSG. Although MSG exposure was not associated with major changes in total bacterial biomass dynamics, both species showed a temporal functional reprogramming. In C. butyricum, MSG rapidly intensified metabolic activity to capitalize on exogenous glutamate by activating central carbon metabolism, redox-balancing pathways, and the GABA shunt, thereby collectively enhancing butyrate synthesis, a metabolite associated with gut barrier integrity, energy regulation, and anti-inflammatory signaling. On the other hand, B. thetaiotaomicron adopted a conservative, homeostatic response, suppressing glycan utilization and central carbon and energy metabolism, and maintaining stable SCFA production through controlled regulation that buffered against abrupt dietary perturbations. Overall, MSG functioned as a potent metabolic signal, triggering distinct adaptive strategies in two dominant gut bacteria. IMPORTANCE The impact of monosodium glutamate (MSG) as a highly consumed food additive on the gut microbiome is often overlooked, and community-level analyses reveal little change, masking distinct phenotypic responses of individual strains. By combining gene expression and metabolite profiling using two key human gut bacteria, we show that MSG is sensed as a metabolic signal. A butyrate-producing gut bacterium increases energy metabolism and butyrate production, and a fiber-degrading gut bacterium transiently moderates metabolism to maintain stable fermentation products. These differences suggest that MSG's physiological effects may depend on which bacterial groups dominate an individual’s microbiome. The impact of monosodium glutamate (MSG) as a highly consumed food additive on the gut microbiome is often overlooked, and community-level analyses reveal little change, masking distinct phenotypic responses of individual strains. By combining gene expression and metabolite profiling using two key human gut bacteria, we show that MSG is sensed as a metabolic signal. A butyrate-producing gut bacterium increases energy metabolism and butyrate production, and a fiber-degrading gut bacterium transiently moderates metabolism to maintain stable fermentation products. These differences suggest that MSG's physiological effects may depend on which bacterial groups dominate an individual’s microbiome.
Nazanin Nematzadeh Somehsaraei, Joshua Lemuel Hadi, M. Khan Mirzaei et al.· Msphere· 0 citations
