Biology subjects

DiBenedetto, N.

Publications and source records attributed to DiBenedetto, N..

7 recordsLinked to original sources

bioRxiv2024

Unique growth and morphology properties of Clade 5 Clostridioides difficile strains revealed by single-cell time-lapse microscopy

Clostridioides difficile is a gastrointestinal pathogen of both humans and agricultural animals and thus a major One Health threat. The C. difficile species consists of five main clades, with Clade 5 currently undergoing speciation from Clades 1-4. Clade 5 strains are highly prevalent in agricultural animals and can cause zoonotic infections, suggesting that these strains have evolved phenotypes that distinguish them from Clade 1-4 strains. Here, we compare the growth properties of Clade 5 strains to those of Clade 1-4 strains using anaerobic time-lapse microscopy coupled with automated image analysis. Our analyses indicate that Clade 5 strains grow faster and are more likely to form long chains of cells than Clade 1-4 strains. Using comparative genomic and CRISPRi analyses, we show that the chaining phenotype of Clade 5 strains is driven by the orientation of the invertible cmr switch sequence, with chaining strains exhibiting a bias to the cmr-ON state. Interestingly, Clade 5 strains with a bias towards the cmr-ON state shifted to a largely cmr-OFF state during murine infection, suggesting that the cmr-OFF state is under positive selection during infection. Collectively, our data reveal that Clade 5 strains have distinct growth properties, which may allow them to inhabit diverse ecological niches. Author SummaryThe Clade 5 strains of the Clostridioides difficile species are so phylogenetically divergent that they almost meet the threshold of being a distinct species. Although these strains are ubiquitously isolated from agricultural and environmental settings and an important source of zoonotic and community-acquired infections, it is unclear whether they have distinct phenotypic properties that allow them to colonize diverse hosts or persist in the environment. By combining a novel anaerobic time-lapse microscopy method with automated image analysis, we discovered that Clade 5 strains grow faster than strains from other C. difficile clades and that they frequently form long chains. These chaining properties are driven by the environmentally responsive expression of a non-canonical signal transduction system, which our analyses suggest is selected against during murine infection. Collectively, our analyses reveal that Clade 5 strains have distinct growth properties that may promote their persistence in the environment.

microbiology↗

bioRxiv2022

Clostridium scindens colonization of gnotobiotic mice promotes a chronic unresolving infection with Clostridioides difficile

The commensal Clostridium scindens has been regarded as a promising bacteriotherapeutic against Clostridioides difficile infection due to its ability to consume host factors that can promote C. difficile growth, and its production of the antimicrobial compound 1-acetyl-{beta}-carboline. We investigated C. scindens protective effects against C. difficile using defined colonization studies in gnotobiotic mice. Mice infected with C. difficile develop lethal infection within 48 hours. In contrast, 88% of mice pre-colonized with C. scindens survived acute infection with delayed C. difficile colonization, lower biomass, and toxin B levels at 24 hours after infection. However, two weeks post-challenge, surviving mice showed comparable levels of cecal C. difficile vegetative and spore biomass and toxin B, as seen during acute infection. After two weeks, co-colonized mice exhibited mucosal colonic hyperplasia with focal pseudomembranes, modeling a chronic and recurrent infection state. Our findings illustrate how the commensal microbiota can modulate host and pathogen interactions leading to chonic C. difficile carriage and infection.

microbiology↗

bioRxiv2021

Intrinsic instability of the dysbiotic microbiome revealed through dynamical systems inference at scale

Dynamical systems models are a powerful tool for analyzing interactions, stability, resilience, and other key properties in biomedically important microbial ecosystems, such as the gut microbiome. Challenges to modeling and inference in this setting include the large number of species present, and data sparsity/noise characteristics. Here, we introduce a Bayesian statistical method, the Microbial Dynamical Systems Inference Engine 2 (MDSINE2), which infers compact and interpretable ecosystems-scale dynamical systems models from microbiome time-series data. We model microbial dynamics as stochastic processes driven by inferred interaction modules, or groups of microbes with similar interaction structure and responses to perturbations. Additionally, we model the noise characteristics of sequencing and qPCR measurements to provide uncertainty quantification for all outputs. To evaluate MDSINE2, and provide a benchmarking resource for the community, we generated the most densely sampled microbiome time-series to date, which consists of a cohort of mice that received fecal transplants from a human donor and were then subjected to dietary and antibiotic perturbations. Benchmarking on simulated and real data demonstrate that MDSINE2 significantly outperforms state-of-the-art methods, and moreover identifies interaction modules that shed new light on ecosystems-scale interactions in the gut microbiome. We provide MDSINE2 as an open-source Python package at: https://github.com/gerberlab/MDSINE2.

systems biology↗

bioRxiv2021

c-di-AMP signaling is required for bile salts resistance and long-term colonization by Clostridioides difficile

To cause disease, the important human enteropathogen Clostridioides difficile must colonize the gastro-intestinal tract but little is known on how this organism senses and responds to the harsh host environment to adapt and multiply. Nucleotide second messengers are signaling molecules used by bacteria to respond to changing environmental conditions. In this study, we showed for the first time that c-di-AMP is produced by C. difficile and controls the uptake of potassium, making it essential for growth. We found that c-di-AMP is involved in biofilm formation, cell wall homeostasis, osmotolerance as well as detergent and bile salt resistance in C. difficile. In a colonization mouse model, a strain lacking GdpP, a c-di-AMP degrading enzyme, failed to persist in the gut in contrast to the parental strain. We identified OpuR as a new regulator that binds c-di-AMP and represses the expression of the compatible solute transporter OpuC. Interestingly, an opuR mutant is highly resistant to a hyperosmotic or bile salt stress compared to the parental strain while an opuCA mutant is more susceptible A short exposure of C. difficile cells to bile salts resulted in a decrease of the c-di-AMP concentrations reinforcing the hypothesis that changes in membrane characteristics due to variations of the cellular turgor or membrane damages constitute a signal for the adjustment of the intracellular c-di-AMP concentration. Thus, c-di-AMP is a signaling molecule with pleiotropic effects that controls osmolyte uptake to confer osmotolerance and bile salt resistance in C. difficile and that is important for colonization of the host. One Sentence Summaryc-di-AMP is an essential regulatory molecule conferring resistance to osmotic and bile salt stresses by controlling osmolyte uptake and contributing to gut persistence in the human enteropathogen Clostridioides difficile.

microbiology↗

bioRxiv2021

Proanthocyanidin-enriched cranberry extract induces resilient bacterial community dynamics in a gnotobiotic mouse model

Cranberry consumption has numerous health benefits, with experimental reports showing its anti-inflammatory and anti-tumor properties. Importantly, microbiome research has demonstrated that the gastrointestinal bacterial community modulates host immunity, raising the question whether the cranberry-derived effect may be related to its ability to modulate the microbiome. Only a few studies have investigated the effect of cranberry products on the microbiome to date. Especially because cranberry is rich in dietary fibers, we do not know the extent of microbiome modulation that is caused solely by polyphenols, particularly proanthocyanidins (PACs). Since previous work has only focused on the long-term effects of cranberry extracts, in this study we investigated the effect of a water-soluble, polyphenol-rich cranberry juice extract (CJE) on the short-term dynamics of human-derived bacterial community in a gnotobiotic mouse model. CJE characterization revealed a high enrichment in PACs (57% PACs), the highest ever utilized in a microbiome study. In a 37-day experiment with a 10-day CJE intervention and 14-day recovery time, we profiled the microbiota via 16 rDNA sequencing and applied diverse time-series analytics methods to identify individual bacterial responses. We show that daily administration of CJE induces distinct dynamical patterns in bacterial abundances during and after treatment before recovering resiliently to pre-treatment levels. Specifically, we observed an increase of the immunomodulatory mucin degrading Akkermansia muciniphila after treatment, suggesting intestinal mucus accumulation due to CJE. Interestingly, this expansion coincided with an increase in the abundance of butyrate-producing Clostridia, a group of microbes known to promote numerous adaptive and innate anti-inflammatory phenotypes.

microbiology↗

bioRxiv2020

Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile

Though Clostridioides difficile is among the most studied anaerobes, the interplay of metabolism and regulation that underlies its ability to colonize the human gut is unknown. We have compiled public resources into three models and a portal to support comprehensive systems analysis of C. difficile. First, by leveraging 151 transcriptomes from 11 studies we generated a regulatory model (EGRIN) that organizes 90% of C. difficile genes into 297 high quality conditional co-regulation modules. EGRIN predictions, validated with independent datasets, recapitulated and extended regulons of key transcription factors, implicating new genes for sporulation, carbohydrate transport and metabolism. Second, by advancing a metabolic model, we discovered that 15 amino acids, diverse carbohydrates, and 10 metabolic genes are essential for C. difficile growth within an intestinal environment. Finally, by integrating EGRIN with the metabolic model, we developed a PRIME model that revealed unprecedented insights into combinatorial control of essential processes for in vivo colonization of C. difficile and its interactions with commensals. We have developed an interactive web portal (http://networks.systemsbiology.net/cdiff-portal/) to disseminate all data, algorithms, and models to support collaborative systems analyses of C. difficile.

systems biology↗

bioRxiv2020

The mechanisms of in vivo commensal control of Clostridioides difficile virulence

We define multiple mechanisms by which commensals protect against or worsen Clostridioides difficile infection. Leveraging new systems-level models we show how metabolically distinct species of Clostridia modulate the pathogens colonization, growth, and virulence to impact host survival. Gnotobiotic mice colonized with the amino acid fermenter Paraclostridium bifermentans survived infection while mice colonized with the butyrate- producer, Clostridium sardiniense, more rapidly succumbed. Systematic in vivo analyses revealed how each commensal altered the gut nutrient environment, modulating the pathogens metabolism, regulatory networks, and toxin production. Oral administration of P. bifermentans rescued conventional mice from lethal C. difficile infection via mechanisms identified in specifically colonized mice. Our findings lay the foundation for mechanistically informed therapies to counter C. difficile infections using systems biologic approaches to define host-commensal-pathogen interactions in vivo. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/894915v2_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@15a6940org.highwire.dtl.DTLVardef@b4290borg.highwire.dtl.DTLVardef@1f2af49org.highwire.dtl.DTLVardef@1d1e6b9_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

microbiology↗