Novel drivers of virulence inClostridioides difficileidentified via context-specific metabolic network analysis

Abstract

Clostridioides difficile is a Gram-positive, sporulating anaerobe that has become the leading cause of hospital-acquired infections. Over the previous decade, many studies have demonstrated the importance of metabolism in numerous aspects of C. difficile biology from initial colonization to regulation of virulence factors. Additionally, due to growing threats of antibiotic resistance and recurrent infection, targeting components of metabolism presents a novel possible approach to combat this infection. In the past, genome-scale metabolic network analysis of bacteria has enabled systematic investigation of the genetic and metabolic properties that potentially contribute to downstream phenotypes as well as prediction of outcome from perturbations to these pathways. These predictions ultimately create a platform for high-throughput identification and screening of metabolic targets prior to laboratory testing. To accomplish these goals in C. difficile, we constructed highly-curated genome-scale metabolic network reconstructions (GENREs) for a well-studied laboratory strain of the pathogen (str. 630) as well as a more recently characterized hyper-virulent isolate (str. R20291). These computational modeling platforms account for key components of C. difficile core metabolism and nutrient acquisition systems to recapitulate metabolic behaviors within the complex milieu of the gut. Simulating the impact of single-gene deletions resulted in accuracies of ~89.9% for both GENREs compared with transposon mutant libraries. Further analysis of both strains also revealed significant correlations between in silico and experimentally measured growth in carbon source utilization screens (p-values ≤ 0.002), with positive predictive values of ~95.0%. Subsequently, we generated context-specific models by integrating transcriptomic data from C. difficile grown in vitro or during in vivo infection. Simulations also predicted the consistent inverse patterns of carbohydrate and amino acid catabolism that corresponded with differential virulence factor expression measured experimentally. Collectively, our results indicate that GENRE-based analyses of C. difficile are an effective means for gaining novel insight into metabolism as it relates to pathogenesis and provides a platform for the identification of novel therapeutic targets.

Metabolic adaption to extracellular pyruvate triggers biofilm formation inClostridioides difficile

“…Furthermore, other signals, such as change in amino acids availability or increase SCFA production, could prevent C. difficile from entering a biofilm or persistence state and promote sporulation. These hypotheses are supported by recent in silico modeling of the metabolism in the context of sporulation and virulence where each context has distinct metabolic intake and efflux (Jenior et al, 2020).…”

Coordinated modulation of multiple processes through phase variation of a c-di-GMP phosphodiesterase in Clostridioides difficile

“…While we cannot exclude the possibility that phase variation occurred during experimentation, we ensured that the starting switch orientations in each strain did not explain the observed phenotypes. Future work will determine whether the motility, biofilm, and other conditions select for specific phase variants and identify the potential selective pressures in these environments (52).…”

Wolf in Sheep’s Clothing: Clostridioides difficile Biofilm as a Reservoir for Recurrent Infections

“…During an infection, metabolic adaptation is an important aspect that will shape the outcome of colonization and symptoms. The composition of the microbiota will greatly influence the concentration of available nutrients that can favor or prevent C. difficile colonization [ 271 ], and recent in silico modeling suggests that virulence and sporulation have specific metabolic intake and output [ 272 ]. Furthermore, computer-generated models of CDI support the idea that changes in specific nutrients such as amino acids and glucose, combined with a decrease in butyrate and an increase in acetate, drive disease progression and recurrence [ 273 , 274 ].…”