Elucidating dynamic anaerobe metabolism with HRMAS 13C NMR and genome-scale modeling.

Anaerobic microbial metabolism drives critical functions within global ecosystems, host-microbiota interactions, and industrial applications, yet remains ill-defined. Here we advance a versatile approach to elaborate cellular metabolism in obligate anaerobes using the pathogen Clostridioides difficile, an amino acid and carbohydrate-fermenting Clostridia. High-resolution magic angle spinning nuclear magnetic resonance (NMR) spectroscopy of C. difficile, grown with fermentable 13C substrates, informed dynamic flux balance analysis (dFBA) of the pathogen's genome-scale metabolism. Analyses identified dynamic recruitment of oxidative and supporting reductive pathways, with integration of high-flux amino acid and glycolytic metabolism at alanine's biosynthesis to support efficient energy generation, nitrogen handling and biomass generation. Model predictions informed an approach leveraging the sensitivity of 13C NMR spectroscopy to simultaneously track cellular carbon and nitrogen flow from [U-13C]glucose and [15N]leucine, confirming the formation of [13C,15N]alanine. Findings identify metabolic strategies used by C. difficile to support its rapid colonization and expansion in gut ecosystems.

Reconsidering the in vivo functions of Clostridial Stickland amino acid fermentations.

Stickland amino acid fermentations occur primarily among species of Clostridia. An ancient form of metabolism, Stickland fermentations use amino acids as electron acceptors in the absence of stronger oxidizing agents and provide metabolic capabilities to support growth when other fermentable substrates, such as carbohydrates, are lacking. The reactions were originally described as paired fermentations of amino acid electron donors, such as the branched-chain amino acids, with recipients that include proline and glycine. We present a redox-focused view of Stickland metabolism following electron flow through metabolically diverse oxidative reactions and the defined-substrate reductase systems, including for proline and glycine, and the role of dual redox pathways for substrates such as leucine and ornithine. Genetic studies and Environment and Gene Regulatory Interaction Network (EGRIN) models for the pathogen Clostridioides difficile have improved our understanding of the regulation and metabolic recruitment of these systems, and their functions in modulating inter-species interactions within host-pathogen-commensal systems and uses in industrial and environmental applications.

HRMAS 13C NMR and genome-scale metabolic modeling identify threonine as a preferred dual redox substrate for Clostridioides difficile.

Stickland-fermenting Clostridia preferentially ferment amino acids to generate energy and anabolic substrates for growth. In gut ecosystems, these species prefer dual redox substrates, particularly mucin-abundant leucine. Here, we establish how theronine, a more prevalent, mucinabundant substrate, supports dual redox metabolism in the pathogen Clostridioides difficile. Realtime, High-Resolution Magic Angle Spinning NMR spectroscopy, with dynamic flux balance analyses, inferred dynamic recruitment of four distinct threonine fermentation pathways, including ones with intermediate accrual that supported changing cellular needs for energy, redox metabolism, nitrogen cycling, and growth. Model predictions with 13C isotopomer analyses of [U-13C]threonine metabolites inferred threonine's reduction to butyrate through the reductive leucine pathway, a finding confirmed by deletion of the hadA 2-hydroxyisocaproate CoA transferase. In vivo metabolomic and metatranscriptomic analyses illustrate how threonine metabolism in C. difficile and the protective commensal Paraclostridium bifermentans impacts pathogen colonization and growth, expanding the range of dual-redox substrates that modulate host risks for disease.

Central in vivo mechanisms by which C. difficile's proline reductase drives efficient metabolism, growth, and toxin production.

Clostridioides difficile (CD) is a sporulating and toxin-producing nosocomial pathogen that opportunistically infects the gut, particularly in patients with depleted microbiota after antibiotic exposure. Metabolically, CD rapidly generates energy and substrates for growth from Stickland fermentations of amino acids, with proline being a preferred reductive substrate. To investigate the in vivo effects of reductive proline metabolism on C. difficile's virulence in an enriched gut nutrient environment, we evaluated wild-type and isogenic ΔprdB strains of ATCC43255 on pathogen behaviors and host outcomes in highly susceptible gnotobiotic mice. Mice infected with the ΔprdB mutant demonstrated extended survival via delayed colonization, growth and toxin production but ultimately succumbed to disease. In vivo transcriptomic analyses demonstrated how the absence of proline reductase activity more broadly disrupted the pathogen's metabolism including failure to recruit oxidative Stickland pathways, ornithine transformations to alanine, and additional pathways generating growth-promoting substrates, contributing to delayed growth, sporulation, and toxin production. Our findings illustrate the central role for proline reductase metabolism to support early stages of C. difficile colonization and subsequent impact on the pathogen's ability to rapidly expand and cause disease.

Protocol for using negative pressure isolator systems to study BSL-2 organisms in gnotobiotic murine models.

Here, we present a protocol for the use of negative pressure isolator systems to maintain defined association and contain BSL-2 pathogens in germ-free and gnotobiotic mouse studies. We describe setup and operation of negative pressure isolators with integrated microbiologic procedures, using the BSL-2 pathogen Clostridioides difficile as a working example. This approach supports experimental systems with defined-association mice and enables high-resolution mechanistic studies of pathogen-commensal interactions and their impacts on host phenotypes. For complete details on the use and execution of this protocol, please refer to Girinathan et al. (2021).