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Fecal communities transplanted into individuals can eliminate recurrent Clostridioides difficile infection (CDI) with high efficacy. However, this treatment is only used once CDI becomes resistant to antibiotics or has recurred multiple times. We sought to investigate whether a fecal community transplant (FCT) pre-treatment could be used to prevent CDI altogether. We treated male C57BL/6 mice with either clindamycin, cefoperazone, or streptomycin, and then inoculated them with the microbial community from untreated mice before challenging with C. difficile. We measured colonization and sequenced the V4 region of the 16S rRNA gene to understand the dynamics of the murine fecal community in response to the FCT and C. difficile challenge. Clindamycin-treated mice became colonized with C. difficile but cleared it naturally and did not benefit from the FCT. Cefoperazone-treated mice became colonized by C. difficile, but the FCT enabled clearance of C. difficile. In streptomycin-treated mice, the FCT was able to prevent C. difficile from colonizing. Then we diluted the FCT and repeated the experiments. Cefoperazone-treated mice no longer cleared C. difficile. However, streptomycin-treated mice colonized with 1:102 dilutions resisted C. difficile colonization. Streptomycin-treated mice that received a FCT diluted 1:103, C. difficile colonized but later was cleared. In streptomycin-treated mice, inhibition of C. difficile was associated with increased relative abundance of a group of bacteria related to Porphyromonadaceae and Lachnospiraceae. These data demonstrate that C. difficile colonization resistance can be restored to a susceptible community with a FCT as long as it complements the missing populations.ImportanceAntibiotic use, ubiquitous with the healthcare environment, is a major risk factor for Clostridioides difficile infection (CDI), the most common nosocomial infection. When C. difficile becomes resistant to antibiotics, a fecal microbiota transplant from a healthy individual can effectively restore the gut bacterial community and eliminate the infection. While this relationship between the gut bacteria and CDI is well established, there are no therapies to treat a perturbed gut community to prevent CDI. This study explored the potential of restoring colonization resistance to antibiotic-induced susceptible gut communities. We described the effect gut bacteria community variation has on the effectiveness of a fecal community transplant for inhibiting CDI. These data demonstrated that communities susceptible to CDI can be supplemented with fecal communities but the effectiveness depended on the structure of the community following the perturbation. Thus, a simplified bacterial community may be able to recover colonization resistance to patients treated with antibiotics.

SummaryInspired by well-established material and pedagogy provided by The Carpentries (Wilson 2016), we developed a two-day workshop curriculum that teaches introductory R programming for managing, analyzing, plotting and reporting data using packages from the tidyverse (Wickham et al. 2019), the Unix shell, version control with git, and GitHub. While the official Software Carpentry curriculum is comprehensive, we found that it contains too much content for a two-day workshop. We also felt that the independent nature of the lessons left learners confused about how to integrate the newly acquired programming skills in their own work. Thus, we developed a new curriculum that aims to teach novices how to implement reproducible research principles in their own data analysis. The curriculum integrates live coding lessons with individual-level and group-based practice exercises, and also serves as a succinct resource that learners can reference both during and after the workshop. Moreover, it lowers the entry barrier for new instructors as they do not have to develop their own teaching materials or sift through extensive content. We developed this curriculum during a two-day sprint, successfully used it to host a two-day virtual workshop with almost 40 participants, and updated the material based on instructor and learner feedback. We hope that our new curriculum will prove useful to future instructors interested in teaching workshops with similar learning objectives.

The community of microorganisms, or microbiota, in our intestines prevents pathogens like C. difficile from colonizing and causing infection. However, antibiotics can disturb the gut microbiota, which allows C. difficile to colonize. C. difficile infections (CDI) are primarily treated with antibiotics, which frequently leads to recurrent infections because the microbiota has not yet returned to a resistant state., The gut bacterial community prevents many pathogens from colonizing the intestine. Previous studies have associated specific bacteria with clearing Clostridioides difficile colonization across different community perturbations. However, those bacteria alone have been unable to clear C. difficile colonization. To elucidate the changes necessary to clear colonization, we compared differences in bacterial abundance between communities able and unable to clear C. difficile colonization. We treated mice with titrated doses of antibiotics prior to C. difficile challenge, resulting in no colonization, colonization and clearance, or persistent colonization. Previously, we observed that clindamycin-treated mice were susceptible to colonization but spontaneously cleared C. difficile. Therefore, we investigated whether other antibiotics would show the same result. We found that reduced doses of cefoperazone and streptomycin permitted colonization and clearance of C. difficile. Mice that cleared colonization had antibiotic-specific community changes and predicted interactions with C. difficile. Clindamycin treatment led to a bloom in populations related to Enterobacteriaceae. Clearance of C. difficile was concurrent with the reduction of those blooming populations and the restoration of community members related to the Porphyromonadaceae and Bacteroides. Cefoperazone created a susceptible community characterized by drastic reductions in the community diversity and interactions and a sustained increase in the abundance of many facultative anaerobes. Lastly, clearance in streptomycin-treated mice was associated with the recovery of multiple members of the Porphyromonadaceae, with little overlap in the specific Porphyromonadaceae observed in the clindamycin treatment. Further elucidation of how C. difficile colonization is cleared from different gut bacterial communities will improve C. difficile infection treatments. IMPORTANCE The community of microorganisms, or microbiota, in our intestines prevents pathogens like C. difficile from colonizing and causing infection. However, antibiotics can disturb the gut microbiota, which allows C. difficile to colonize. C. difficile infections (CDI) are primarily treated with antibiotics, which frequently leads to recurrent infections because the microbiota has not yet returned to a resistant state. The recurrent infection cycle often ends when the fecal microbiota from a presumed resistant person is transplanted into the susceptible person. Although this treatment is highly effective, we do not understand the mechanism. We hope to improve the treatment of CDI through elucidating how the bacterial community eliminates CDI. We found that C. difficile colonized susceptible mice but was spontaneously eliminated in an antibiotic treatment-specific manner. These data indicate that each community had different requirements for clearing colonization. Understanding how different communities clear colonization will reveal targets to improve CDI treatments.

Exploratory Science Center, Merck & Co , Inc , Cambridge, Massachusetts, United States of America Affiliation: Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, United States of America ORCID logo http://orcid org/0000-0003-3140-537X Patrick D Schloss * E-mail: pschloss@umich edu Affiliation: Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, United States of America ORCID logo http://orcid org/0000-0002-6935-4275 Introduction For most biologists, the ability to generate data has outpaced the ability to analyze those data In addition to building upon material from traditional coursework and staying current on the literature, Journal Clubs help strengthen skills in critical thinking, communication, and integrating the literature [11] Because most Journal Clubs occur on a regular schedule, they are effective by virtue of repeated practice With this model in mind, over the past four years we have experimented with creating a Code Club model with the goal of improving reproducible data analysis skills in a laboratory environment [ ]presenters were reluctant to offer to present again

The cobalamin or B12 cofactor supports sulfur and one-carbon metabolism and the catabolism of odd-chain fatty acids, branched-chain amino acids, and cholesterol. CblC is a B12-processing enzyme involved in an early cytoplasmic step in the cofactor-trafficking pathway. It catalyzes the glutathione (GSH)-dependent dealkylation of alkylcobalamins and the reductive decyanation of cyanocobalamin. CblC from Caenorhabditis elegans (ceCblC) also exhibits a robust thiol oxidase activity, converting reduced GSH to oxidized GSSG with concomitant scrubbing of ambient dissolved O2 The mechanism of thiol oxidation catalyzed by ceCblC is not known. In this study, we demonstrate that novel coordination chemistry accessible to ceCblC-bound cobalamin supports its thiol oxidase activity via a glutathionyl-cobalamin intermediate. Deglutathionylation of glutathionyl-cobalamin by a second molecule of GSH yields GSSG. The crystal structure of ceCblC provides insights into how architectural differences at the α- and β-faces of cobalamin promote the thiol oxidase activity of ceCblC but mute it in wild-type human CblC. The R161G and R161Q mutations in human CblC unmask its latent thiol oxidase activity and are correlated with increased cellular oxidative stress disease. In summary, we have uncovered key architectural features in the cobalamin-binding pocket that support unusual cob(II)alamin coordination chemistry and enable the thiol oxidase activity of ceCblC.

Diagnosing diseases using machine learning (ML) is rapidly being adopted in microbiome studies. However, the estimated performance associated with these models is likely overoptimistic. Moreover, there is a trend toward using black box models without a discussion of the difficulty of interpreting such models when trying to identify microbial biomarkers of disease. This work represents a step toward developing more-reproducible ML practices in applying ML to microbiome research. We implement a rigorous pipeline and emphasize the importance of selecting ML models that reflect the goal of the study. These concepts are not particular to the study of human health but can also be applied to environmental microbiology studies., Machine learning (ML) modeling of the human microbiome has the potential to identify microbial biomarkers and aid in the diagnosis of many diseases such as inflammatory bowel disease, diabetes, and colorectal cancer. Progress has been made toward developing ML models that predict health outcomes using bacterial abundances, but inconsistent adoption of training and evaluation methods call the validity of these models into question. Furthermore, there appears to be a preference by many researchers to favor increased model complexity over interpretability. To overcome these challenges, we trained seven models that used fecal 16S rRNA sequence data to predict the presence of colonic screen relevant neoplasias (SRNs) (n = 490 patients, 261 controls and 229 cases). We developed a reusable open-source pipeline to train, validate, and interpret ML models. To show the effect of model selection, we assessed the predictive performance, interpretability, and training time of L2-regularized logistic regression, L1- and L2-regularized support vector machines (SVM) with linear and radial basis function kernels, a decision tree, random forest, and gradient boosted trees (XGBoost). The random forest model performed best at detecting SRNs with an area under the receiver operating characteristic curve (AUROC) of 0.695 (interquartile range [IQR], 0.651 to 0.739) but was slow to train (83.2 h) and not inherently interpretable. Despite its simplicity, L2-regularized logistic regression followed random forest in predictive performance with an AUROC of 0.680 (IQR, 0.625 to 0.735), trained faster (12 min), and was inherently interpretable. Our analysis highlights the importance of choosing an ML approach based on the goal of the study, as the choice will inform expectations of performance and interpretability.

Antibiotics are the primary risk factor for Clostridioides difficile infections (CDIs), but other factors may also increase a person’s risk. In epidemiological studies, proton pump inhibitor (PPI) use has been associated with CDI incidence and recurrence. PPIs have also been associated with alterations in the human intestinal microbiota in observational and interventional studies. We evaluated the effects of the PPI omeprazole on the structure of the murine intestinal microbiota and its ability to disrupt colonization resistance to C. difficile. We found omeprazole treatment had minimal impact on the murine fecal microbiota and did not promote C. difficile colonization. Further studies are needed to determine whether other factors contribute to the association between PPIs and CDIs seen in humans or whether aspects of murine physiology may limit its utility to test these types of hypotheses., Proton pump inhibitor (PPI) use has been associated with microbiota alterations and susceptibility to Clostridioides difficile infections (CDIs) in humans. We assessed how PPI treatment alters the fecal microbiota and whether treatment promotes CDIs in a mouse model. Mice receiving a PPI treatment were gavaged with 40 mg of omeprazole per kg of body weight during a 7-day pretreatment phase, the day of C. difficile challenge, and the following 9 days. We found that mice treated with omeprazole were not colonized by C. difficile. When omeprazole treatment was combined with a single clindamycin treatment, one cage of mice remained resistant to C. difficile colonization, while the other cage was colonized. Treating mice with only clindamycin followed by challenge resulted in C. difficile colonization. 16S rRNA gene sequencing analysis revealed that omeprazole had minimal impact on the structure of the murine microbiota throughout the 16 days of omeprazole exposure. These results suggest that omeprazole treatment alone is not sufficient to disrupt microbiota resistance to C. difficile infection in mice that are normally resistant in the absence of antibiotic treatment. IMPORTANCE Antibiotics are the primary risk factor for Clostridioides difficile infections (CDIs), but other factors may also increase a person’s risk. In epidemiological studies, proton pump inhibitor (PPI) use has been associated with CDI incidence and recurrence. PPIs have also been associated with alterations in the human intestinal microbiota in observational and interventional studies. We evaluated the effects of the PPI omeprazole on the structure of the murine intestinal microbiota and its ability to disrupt colonization resistance to C. difficile. We found omeprazole treatment had minimal impact on the murine fecal microbiota and did not promote C. difficile colonization. Further studies are needed to determine whether other factors contribute to the association between PPIs and CDIs seen in humans or whether aspects of murine physiology may limit its utility to test these types of hypotheses.

Considering that colorectal cancer is the third leading cancer-related cause of death within the United States, it is important to detect colorectal tumors early and to prevent the formation of tumors. Short-chain fatty acids (SCFAs) are often used as a surrogate for measuring gut health and for being anticarcinogenic because of their anti-inflammatory properties. We evaluated the fecal SCFA concentrations of a cohort of individuals with different colonic tumor burdens who were previously analyzed to identify microbiome-based biomarkers of tumors. We were unable to find an association between SCFA concentration and tumor burden or use SCFAs to improve our microbiome-based models of classifying people based on their tumor status. Furthermore, we were unable to find an association between the fecal community structure and SCFA concentrations. Our results indicate that the association between fecal SCFAs, the gut microbiome, and tumor burden is weak., Colonic bacterial populations are thought to have a role in the development of colorectal cancer with some protecting against inflammation and others exacerbating inflammation. Short-chain fatty acids (SCFAs) have been shown to have anti-inflammatory properties and are produced in large quantities by colonic bacteria that produce SCFAs by fermenting fiber. We assessed whether there was an association between fecal SCFA concentrations and the presence of colonic adenomas or carcinomas in a cohort of individuals using 16S rRNA gene and metagenomic shotgun sequence data. We measured the fecal concentrations of acetate, propionate, and butyrate within the cohort and found that there were no significant associations between SCFA concentration and tumor status. When we incorporated these concentrations into random forest classification models trained to differentiate between people with healthy colons and those with adenomas or carcinomas, we found that they did not significantly improve the ability of 16S rRNA gene or metagenomic gene sequence-based models to classify individuals. Finally, we generated random forest regression models trained to predict the concentration of each SCFA based on 16S rRNA gene or metagenomic gene sequence data from the same samples. These models performed poorly and were able to explain at most 14% of the observed variation in the SCFA concentrations. These results support the broader epidemiological data that questions the value of fiber consumption for reducing the risks of colorectal cancer. Although other bacterial metabolites may serve as biomarkers to detect adenomas or carcinomas, fecal SCFA concentrations have limited predictive power.

Volume 4, issue 1, e00528-18, 2019, [https://doi.org/10.1128/mSphere.00528-18][1]. This article was published on 6 February 2019 with the first author’s name misspelled. The byline was updated in the current version, posted on 16 May 2019. [1]: /lookup/doi/10.1128/mSphere.00528-18

The gut microbial community has a profound influence on host physiology in both health and disease. In diabetic individuals, the gut microbiota can affect the course of disease, and some medications for diabetes, including metformin, seem to elicit some of their benefits via an interaction with the microbiota. Here, we report that acarbose, a glucoamylase inhibitor for type 2 diabetes, changes the murine gut bacterial community structure in a reversible and diet-dependent manner. In both high-starch and high-fiber diet backgrounds, acarbose treatment results in increased short-chain fatty acids, particularly butyrate, as measured in stool samples. As we learn more about how human disease is affected by the intestinal bacterial community, the interplay between medications such as acarbose and the diet will become increasingly important to evaluate., Acarbose is a safe and effective medication for type 2 diabetes that inhibits host glucoamylases to prevent starch digestion in the small intestines and thus decrease postprandial blood glucose levels. This results in an increase in dietary starch in the distal intestine, where it becomes food for the gut bacterial community. Here, we examined the effect of acarbose therapy on the gut community structure in mice fed either a high-starch (HS) or high-fiber diet rich in plant polysaccharides (PP). The fecal microbiota of animals consuming a low dose of acarbose (25 ppm) was not significantly different from that of control animals that did not receive acarbose. However, a high dose of acarbose (400 ppm) with the HS diet resulted in a substantial change to the microbiota structure. Most notably, the HS diet with a high dose of acarbose lead to an expansion of the Bacteroidaceae and Bifidobacteriaceae and a decrease in the Verrucomicrobiaceae (such as Akkermansia muciniphila) and the Bacteroidales S24-7. Once acarbose treatment ceased, the community composition quickly reverted to mirror that of the control group, suggesting that acarbose does not irreversibly alter the gut community. The high dose of acarbose in the PP diet resulted in a distinct community structure with increased representation of Bifidobacteriaceae and Lachnospiraceae. Short-chain fatty acids (SCFAs) measured from stool samples were increased, especially butyrate, as a result of acarbose treatment in both diets. These data demonstrate the potential of acarbose to change the gut community structure and increase beneficial SCFA output in a diet-dependent manner. IMPORTANCE The gut microbial community has a profound influence on host physiology in both health and disease. In diabetic individuals, the gut microbiota can affect the course of disease, and some medications for diabetes, including metformin, seem to elicit some of their benefits via an interaction with the microbiota. Here, we report that acarbose, a glucoamylase inhibitor for type 2 diabetes, changes the murine gut bacterial community structure in a reversible and diet-dependent manner. In both high-starch and high-fiber diet backgrounds, acarbose treatment results in increased short-chain fatty acids, particularly butyrate, as measured in stool samples. As we learn more about how human disease is affected by the intestinal bacterial community, the interplay between medications such as acarbose and the diet will become increasingly important to evaluate.

The cobalamin or B12 cofactor supports sulfur and one-carbon metabolism and the catabolism of odd-chain fatty acids, branched-chain amino acids, and cholesterol. CblC is a B12-processing enzyme involved in an early cytoplasmic step in the cofactor-trafficking pathway. It catalyzes the glutathione (GSH)-dependent dealkylation of alkylcobalamins and the reductive decyanation of cyanocobalamin. CblC from Caenorhabditis elegans (ceCblC) also exhibits a robust thiol oxidase activity, converting reduced GSH to oxidized GSSG with concomitant scrubbing of ambient dissolved O2. The mechanism of thiol oxidation catalyzed by ceCblC is not known. In this study, we demonstrate that novel coordination chemistry accessible to ceCblC-bound cobalamin supports its thiol oxidase activity via a glutathionyl-cobalamin intermediate. Deglutathionylation of glutathionyl-cobalamin by a second molecule of GSH yields GSSG. The crystal structure of ceCblC provides insights into how architectural differences at the α- and β-faces of cobalamin promote the thiol oxidase activity of ceCblC but mute it in wild-type human CblC. The R161G and R161Q mutations in human CblC unmask its latent thiol oxidase activity and are correlated with increased cellular oxidative stress disease. In summary, we have uncovered key architectural features in the cobalamin-binding pocket that support unusual cob(II)alamin coordination chemistry and enable the thiol oxidase activity of ceCblC.

CblC is involved in an early step in cytoplasmic cobalamin processing following entry of the cofactor into the cytoplasm. CblC converts the cobalamin cargo arriving from the lysosome to a common cob(II)alamin intermediate, which can be subsequently converted to the biologically active forms. Human CblC exhibits glutathione (GSH)-dependent alkyltransferase activity and flavin-dependent reductive decyanation activity with cyanocobalamin (CNCbl). In this study, we discovered two new GSH-dependent activities associated with the Caenorhabditis elegans CblC for generating cob(II)alamin: decyanation of CNCbl and reduction of aquocobalamin (OH2Cbl). We subsequently found that human CblC also catalyzes GSH-dependent decyanation of CNCbl and reduction of OH2Cbl, albeit efficiently only under anaerobic conditions. The air sensitivity of the human enzyme suggests interception by oxygen during the single-electron transfer step from GSH to CNCbl. These newly discovered GSH-dependent single-electron transfer reactions expand the repertoire of catalytic activities supported by CblC, a versatile B12-processing enzyme.

CblC, a B12 trafficking protein, exhibits glutathione transferase and reductive decyanase activities for processing alkylcobalamins and cyanocobalamin, respectively, to a common intermediate that is subsequently converted to the biologically active forms of the cofactor. We recently discovered that the Caenorhabditis elegans CblC catalyzes thiol-dependent decyanation of CNCbl and reduction of OH2Cbl and stabilizes the paramagnetic cob(II)alamin product under aerobic conditions. In this study, we report the striking ability of the worm CblC to stabilize the highly reactive cob(I)alamin product of the glutathione transferase reaction. The unprecedented stabilization of the supernucleophilic cob(I)alamin species under aerobic conditions by the intrinsic thiol oxidase activity of CblC, was exploited for the chemoenzymatic synthesis of organocobalamin derivatives under mild conditions.