Mostly Microbes and Infection - by David Ojcius

Abstract Pit mud (PM) microbiota play a vital role in Baijiu flavor formation, yet its ecological and functional succession during maturation remains incompletely elucidated. Here, physicochemical profiling, amplicon sequencing, and metagenomics were integrated to investigate 5-, 15-, and 30-year PM of Sichuan Tang Dynasty Laojiao cellars. Bacteria dominated the community (82.59%), followed by Archaea (16.99%), with Lactobacillus acetotolerans, Ruminococcaceae CPB6, and Methanobacterium paludis as major species. Discrepancies between sequencing methods were reflected in fungal taxa which had low-abundance. The 15-year PM exhibited distinct community and functional features, indicating a critical transitional stage. Functional analysis revealed that fermentation-relevant functions were mainly contributed by 7 key genera and 5 species. Physicochemical properties changed with pit age, characterized by increased moisture as well as decreased acidity and humic substance levels. Moisture,...

Highlights • Microbial pantothenic acid (PA) supply is reduced in individuals with MetS • panC enables B. fragilis to supply PA to the colonic microenvironment • B. fragilis PA biosynthesis preserves the gut barrier and alleviates MetS • Microbial PA sustains KLF4 via the PANK2/3-CoA axis to support differentiation

Highlight • Bacterial isolates showed positive or negative effects on barley growth. • GR effects were neutralized by GP and NA isolates in SynCom. • GP isolates suppressed GR via contact-dependent T6SS activity. • Cytokinin produced by GP/NA; Variovorax degraded IAA. • Root microbiome shaped by fertilization and season, not inoculation.

Highlights • Deficiency of MrMFS1 was confirmed to underlie to the accelerated growth. • No morphological or physiological alterations were observed upon deletion of MrMFS1 . • The deletion mutant exhibits enhanced stress tolerance and insecticidal activity. • MrMFS1 mediates the proton-coupled efflux of acetic acid.

Summary Antibiotics are among medicine’s greatest successes, but resistance evolution threatens their continued efficacy. Decades of research have deepened our understanding of the mechanisms and evolutionary dynamics of antimicrobial resistance. More recently, advances in machine learning (ML) and artificial intelligence (AI) show promise in predicting antimicrobial resistance in pathogens based on rapid whole-genome sequencing and other accessible data. In this perspective, we highlight advances in understanding the mechanisms and spread of antimicrobial resistance. We discuss how this knowledge, coupled with ML- and AI-based approaches, can inform the prediction of resistance and a precision-medicine strategy that targets pathogenic bacteria specifically, thereby limiting resistance evolution and collateral damage to the microbiome. These accurate predictions of bacterial vulnerabilities will enable the adaptation of classical antimicrobial treatments with adjuvants, as well as the ...

Highlights • Halococci differ from other haloarchaea by their thick cell wall structure. • Currently no viruses are known to infect Halococci. • Seven novel Halococcus strains were characterized and the genomes sequenced. • The novel Halococcus strains contain predicted anti-viral defence mechanisms. • Detected proviruses indicate that Halococci are infected by viruses in nature.