Title: Novel drivers of virulence in Clostridioides difficile identified via context-specific metabolic network analysis Running title: Metabolic determinants of C. difficile virulence Authors:

The pathogen Clostridioides difficile causes toxin-mediated diarrhea and is the leading cause of hospital-acquired infection in the US. Due to growing antibiotic resistance and recurrent infection, targeting C. difficile metabolism presents a new approach to combat this infection. Genome-scale metabolic network reconstructions (GENREs) have been used to identify therapeutic targets and uncover properties that determine cellular behaviors. Thus, we constructed C. difficile GENREs for a hyper-virulent isolate (str. R20291) and a historic strain (str. 630), validating both with in vitro and in vivo datasets. Growth simulations revealed significant correlations with measured carbon source usage (PPV ≥ 92.7%), and single-gene deletion analysis showed >89.0% accuracy. Next, we utilized each GENRE to identify metabolic drivers of both sporulation and biofilm formation. Through contextualization of each model using transcriptomes generated from in vitro and infection conditions, we discovered reliance on the Pentose Phosphate Pathway as well as increased usage of cytidine and N-acetylneuraminate when virulence expression is reduced, which was subsequently supported experimentally. Our results highlight the ability of GENREs to identify novel metabolite signals in bacterial pathogenesis. Importance Clostridioides difficile is a Gram-positive, sporulating anaerobe that has become the leading cause of hospital-acquired infections. Numerous studies have demonstrated the importance of specific metabolic pathways in aspects of C. difficile pathophysiology, from initial colonization to regulation of virulence factors. In the past, genome-scale metabolic network reconstruction (GENRE) analysis of bacteria has enabled systematic investigation of the genetic and metabolic properties that contribute to downstream virulence phenotypes. With this in mind, we generated and extensively curated C. difficile GENREs for both a well-studied laboratory strain (str. 630) as well as a more recently characterized hyper-virulent isolate (str. R20291). In silico validation of both GENREs revealed high degrees of agreement with experimental gene essentiality and carbon source utilization datasets. Subsequent exploration of context-specific metabolism during both in vitro growth and infection revealed consistent patterns of metabolism which corresponded with experimentally measured increases in virulence factor expression. Our results support that differential C. difficile virulence is associated with distinct metabolic programs related use of carbon sources and provides a platform for identification of novel therapeutic targets. Introduction Clostridioides difficile is a Gram-positive, sporulating anaerobic bacterium that remains a critical problem in healthcare facilities across the developed world (1, 2). Susceptibility to C. difficile infection (CDI) is most frequently preceded by exposure to antibiotic therapy (3). While these drugs are life-saving they also diminish the abundance of other bacteria in the microbiota, altering the metabolic environment of the gut, leaving it susceptible to colonization by C. difficile (4–6). Recently, we observed that C. difficile adapts transcription of distinct catabolic pathways to the unique conditions in susceptible gut environments following different antibiotic pretreatments (7, 8). These transcriptional shifts indicated that C. difficile must coordinate metabolic activity accordingly to compete within new hosts. In spite of these differences, there are known core elements of C. difficile metabolism across different environments including carbohydrate and amino acid fermentation (9). It is known that specific growth nutrients influence expression of virulence genes in C. difficile (9, 10). Given these findings, targeted therapeutic strategies that alter active metabolism and downregulate virulence may be possible without continued exposure to antibiotics. This form of treatment would be especially beneficial as there have been stark increases in the prevalence of antibiotic resistance and hyper-virulence among C. difficile clinical isolates (11, 12). Genome-scale metabolic network reconstructions (GENREs) are mathematical formalizations of metabolic reactions encoded in the genome of an organism. These models are subsequently constrained by known biological and physical parameters such as membrane transport and enzyme kinetics. GENREs can be utilized to interrogate the metabolic capability of a given organism, as well as providing a means to simulate growth and assess the impact of genotype on metabolism. GENREs have been implemented in directing genetic engineering efforts (13) and accurately predicting auxotrophies and interactions between species for growth substrates (14, 15). These platforms also create improved context for the interpretation of omics data (16), and have provided powerful utility for identification of novel drug and gene targets accelerating downstream laboratory testing (17). This concept is especially critical when delineating a complex array of signals from communities of organisms like the gut microbiome (18). Leveraging these tools, several recent studies have identified nodes of metabolism that promise to provide novel therapeutic targets in clinically-relevant pathogens including Klebsiella pneumoniae, Staphylococcus aureus, and Streptococcus mutans (17, 19, 20). However, there has been limited progress to date applying GENREs to obtain mechanistic understanding for metabolism during infection as they relate to colonization and virulence. Taken together, these principles make GENREs strong platforms for deciphering novel metabolic drivers of virulence-associated phenotypes in C. difficile. We began by generating new GENREs for two strains of C. difficile including a highly-characterized laboratory strain C. difficile str. 630 (21), as well as a more recently isolated hyper-virulent strain R20291 (22). De novo reconstruction for both models was followed by extensive literature-driven manual curation of catabolic pathways and related metabolite transport, with specific emphasis on Stickland fermentation for ATP generation and C. difficile-specific redox maintenance (23). Additionally, both GENREs contain a tailored biomass objective function (an in silico proxy for bacterial growth, requiring synthesis of major macromolecular components) which accounts for codon biases and amino acid balance, and cell wall structure. Growth simulations from both GENREs were compared against in vitro gene essentiality and carbon utilization screens, which indicated significant levels of agreement across all validation datasets. To assess potential mechanisms of metabolic control of virulence, we then created context-specific models of C. difficile metabolism by integrating transcriptomic data collected from both laboratory culture and infection conditions where differential expression of C. difficile virulence factors was observed. Overall, during increased virulence expression both strains of C. difficile were predicted to favor increased fermentation of amino acids and decreased reliance carbohydrate usage. Specifically in the hyper-virulent strain R20291 during states of phase variation, we found efflux of the biofilm component N-acetylglucosamine in variants known to produce significantly more biofilm experimentally. Additionally, this state was predicted to have increased reliance on glucose to fuel nucleotide synthesis, instead of ATP generation. When tested in vitro, we indeed found that the colony morphology associated with this phase variant was dependent on environmental glucose availability. Alternatively in infection-specific models of strain 630, we identified consistent patterns of proline and ornithine fermentation in states of both high and low sporulation, which agreed with metabolomic analysis of each condition. However, in instances of lower spore burden our model predicted significantly greater usage of the host-derived glycan N-Acetylneuraminate and the nucleotide precursor cytidine as primary sources of carbon. In subsequent laboratory testing we were able to show that not only can C. difficile use the substrates for growth, but both also lead to lower quantities of spores, which are essential for transmission of the pathogen (24, 25). This work is the first time that contextualized GENREs of a pathogen have been utilized to identify new metabolite signals of virulence regulation. As such, the high-quality GENREs described here can greatly augment the discovery of novel metabolism-directed therapeutics to treat CDI. Moreover, our results demonstrate that GENREs provide an advantage for delineating complex patterns in transcriptomic and metabolomic datasets into tractable experimental targets. Results C. difficile metabolic network generation, gap-filling, and curation The emergence of hypervirulent strains of C. difficile that have unique metabolism and virulence factors highlights the importance for the in-depth study of metabolic pathways to understand and identify targets within these isolates. Core metabolic processes also present an attractive target for novel antimicrobial measures as they may be less likely to allow for acquired antibiotic resistance (26). With these concepts in mind, we focused on the most well-characterized hypervirulent isolate, str. R20291. However, to maximize the utility of the bulk of published C. difficile metabolic research, we elected to generate a reconstruction for the lab-adapted str. 630 in parallel. This focus afforded the ability to continuously cross-reference curations between the models and to more readily identify emergent differences that are specifically due to genomic content. We began the reconstruction process by accessing the re-annotated genome of str. 630 (27) and the published str. R20291 genome (22), both available on the Pathosystems Resource Integration Center database (PATRIC) (28). Following an established proto