23 results on '"Nicholas A Lesniak"'
Search Results
2. Diluted Fecal Community Transplant Restores Clostridioides difficile Colonization Resistance to Antibiotic-Perturbed Murine Communities
- Author
-
Nicholas A. Lesniak, Sarah Tomkovich, Andrew Henry, Ana Taylor, Joanna Colovas, Lucas Bishop, Kathryn McBride, and Patrick D. Schloss
- Subjects
Clostridioides difficile ,colonization resistance ,microbial ecology ,microbiome ,fecal transplant ,mice ,Microbiology ,QR1-502 - Abstract
ABSTRACT 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) pretreatment 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 challenge 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. We then 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 an FCT diluted 1:103 became colonized with C. difficile but later cleared the infection. 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 an FCT as long as it complements the missing populations. IMPORTANCE Antibiotic use, ubiquitous with the health care 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 that gut bacterial 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 that the effectiveness depended on the structure of the community following the perturbation. Thus, a reduced bacterial community may be able to recover colonization resistance in patients treated with antibiotics.
- Published
- 2022
- Full Text
- View/download PDF
3. The Gut Bacterial Community Potentiates Clostridioides difficile Infection Severity
- Author
-
Nicholas A. Lesniak, Alyxandria M. Schubert, Kaitlin J. Flynn, Jhansi L. Leslie, Hamide Sinani, Ingrid L. Bergin, Vincent B. Young, and Patrick D. Schloss
- Subjects
CDI ,Clostridium difficile ,human microbiome ,humanized mice ,microbial ecology ,Microbiology ,QR1-502 - Abstract
ABSTRACT The severity of Clostridioides difficile infections (CDI) has increased over the last few decades. Patient age, white blood cell count, and creatinine levels as well as C. difficile ribotype and toxin genes have been associated with disease severity. However, it is unclear whether specific members of the gut microbiota are associated with variations in disease severity. The gut microbiota is known to interact with C. difficile during infection. Perturbations to the gut microbiota are necessary for C. difficile to colonize the gut. The gut microbiota can inhibit C. difficile colonization through bile acid metabolism, nutrient consumption, and bacteriocin production. Here, we sought to demonstrate that members of the gut bacterial communities can also contribute to disease severity. We derived diverse gut communities by colonizing germfree mice with different human fecal communities. The mice were then infected with a single C. difficile ribotype 027 clinical isolate, which resulted in moribundity and histopathologic differences. The variation in severity was associated with the human fecal community that the mice received. Generally, bacterial populations with pathogenic potential, such as Enterococcus, Helicobacter, and Klebsiella, were associated with more-severe outcomes. Bacterial groups associated with fiber degradation and bile acid metabolism, such as Anaerotignum, Blautia, Lactonifactor, and Monoglobus, were associated with less-severe outcomes. These data indicate that, in addition to the host and C. difficile subtype, populations of gut bacteria can influence CDI disease severity. IMPORTANCE Clostridioides difficile colonization can be asymptomatic or develop into an infection ranging in severity from mild diarrhea to toxic megacolon, sepsis, and death. Models that predict severity and guide treatment decisions are based on clinical factors and C. difficile characteristics. Although the gut microbiome plays a role in protecting against CDI, its effect on CDI disease severity is unclear and has not been incorporated into disease severity models. We demonstrated that variation in the microbiome of mice colonized with human feces yielded a range of disease outcomes. These results revealed groups of bacteria associated with both severe and mild C. difficile infection outcomes. Gut bacterial community data from patients with CDI could improve our ability to identify patients at risk of developing more severe disease and improve interventions that target C. difficile and the gut bacteria to reduce host damage.
- Published
- 2022
- Full Text
- View/download PDF
4. An Osmotic Laxative Renders Mice Susceptible to Prolonged Clostridioides difficile Colonization and Hinders Clearance
- Author
-
Sarah Tomkovich, Ana Taylor, Jacob King, Joanna Colovas, Lucas Bishop, Kathryn McBride, Sonya Royzenblat, Nicholas A. Lesniak, Ingrid L. Bergin, and Patrick D. Schloss
- Subjects
Microbiology ,QR1-502 - Abstract
Diarrheal samples from patients taking laxatives are typically rejected for Clostridioides difficileC. difficile
- Published
- 2021
- Full Text
- View/download PDF
5. Clearance of Clostridioides difficile Colonization Is Associated with Antibiotic-Specific Bacterial Changes
- Author
-
Nicholas A. Lesniak, Alyxandria M. Schubert, Hamide Sinani, and Patrick D. Schloss
- Subjects
Microbiology ,QR1-502 - Abstract
The community of microorganisms, or microbiota, in our intestines prevents pathogens like C. difficileC. difficileC. difficile
- Published
- 2021
- Full Text
- View/download PDF
6. A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems
- Author
-
Begüm D. Topçuoğlu, Nicholas A. Lesniak, Mack T. Ruffin, Jenna Wiens, and Patrick D. Schloss
- Subjects
16S rRNA gene ,colon cancer ,machine learning ,microbial ecology ,microbiome ,Microbiology ,QR1-502 - Abstract
ABSTRACT 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. IMPORTANCE 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.
- Published
- 2020
- Full Text
- View/download PDF
7. The Proton Pump Inhibitor Omeprazole Does Not Promote Clostridioides difficile Colonization in a Murine Model
- Author
-
Sarah Tomkovich, Nicholas A. Lesniak, Yuan Li, Lucas Bishop, Madison J. Fitzgerald, and Patrick D. Schloss
- Subjects
16S rRNA gene ,Clostridioides difficile ,Clostridium difficile ,colonization resistance ,infection ,microbial ecology ,Microbiology ,QR1-502 - Abstract
ABSTRACT 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.
- Published
- 2019
- Full Text
- View/download PDF
8. Fecal Short-Chain Fatty Acids Are Not Predictive of Colonic Tumor Status and Cannot Be Predicted Based on Bacterial Community Structure
- Author
-
Marc A. Sze, Begüm D. Topçuoğlu, Nicholas A. Lesniak, Mack T. Ruffin, and Patrick D. Schloss
- Subjects
16S rRNA ,SCFA ,colon cancer ,machine learning ,metagenomics ,microbial ecology ,Microbiology ,QR1-502 - Abstract
ABSTRACT 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. IMPORTANCE 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.
- Published
- 2019
- Full Text
- View/download PDF
9. Erratum for Baxter et al., 'The Glucoamylase Inhibitor Acarbose Has a Diet-Dependent and Reversible Effect on the Murine Gut Microbiome'
- Author
-
Nielson T. Baxter, Nicholas A. Lesniak, Hamide Sinani, Patrick D. Schloss, and Nicole M. Koropatkin
- Subjects
Microbiology ,QR1-502 - Published
- 2019
- Full Text
- View/download PDF
10. The Glucoamylase Inhibitor Acarbose Has a Diet-Dependent and Reversible Effect on the Murine Gut Microbiome
- Author
-
Nielson T. Baxter, Nicholas A. Lesniak, Hamide Sinani, Patrick D. Schloss, and Nicole M. Koropatkin
- Subjects
acarbose ,gut microbiota ,starch ,Microbiology ,QR1-502 - Abstract
ABSTRACT 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.
- Published
- 2019
- Full Text
- View/download PDF
11. Simplified fecal community transplant restores Clostridioides difficile colonization resistance to antibiotic perturbed murine communities
- Author
-
Nicholas A. Lesniak, Sarah Tomkovich, Andrew Henry, Ana Taylor, Joanna Colovas, Lucas Bishop, Kathryn McBride, and Patrick D. Schloss
- Abstract
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.
- Published
- 2022
12. Developing and deploying an integrated workshop curriculum teaching computational skills for reproducible research
- Author
-
Kelly Sovacool, Courtney R. Armour, Zena Lapp, Sarah K. Lucas, Nicholas A. Lesniak, Sarah Tomkovich, Anderson Jm, Rucheng Diao, Tallant J, King D, Lapp Mm, Morgan Oneka, Barnier C, Krüger J, Matthew Flickinger, and Patrick D. Schloss
- Subjects
Unix ,Carpentry ,Resource (project management) ,Software ,business.industry ,Computer science ,ComputingMilieux_COMPUTERSANDEDUCATION ,Mathematics education ,Live coding ,business ,Host (network) ,Curriculum ,Barriers to entry - Abstract
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.
- Published
- 2021
13. Clearance of Clostridioides difficile colonization is associated with antibiotic-specific bacterial changes
- Author
-
Alyxandria M. Schubert, Patrick D. Schloss, Hamide Sinani, and Nicholas A. Lesniak
- Subjects
medicine.drug_class ,Antibiotics ,Porphyromonadaceae ,Cefoperazone ,microbiome ,Colonisation resistance ,Gut flora ,Biology ,microbial ecology ,digestive system ,Microbiology ,Feces ,Mice ,03 medical and health sciences ,fluids and secretions ,colonization resistance ,microbiota ,medicine ,Animals ,Colonization ,Molecular Biology ,030304 developmental biology ,0303 health sciences ,Bacteria ,Clostridioides difficile ,030306 microbiology ,Clindamycin ,Clostridium difficile ,dynamics ,biology.organism_classification ,Enterobacteriaceae ,QR1-502 ,Anti-Bacterial Agents ,Gastrointestinal Microbiome ,stomatognathic diseases ,Clostridium Infections ,Streptomycin ,Disease Susceptibility ,16S rRNA gene ,Bacteroides ,Research Article ,medicine.drug - Abstract
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.
- Published
- 2020
14. Ten simple rules to increase computational skills among biologists with Code Clubs
- Author
-
William L. Close, Kathryn McBride, Matthew L. Jenior, Marc A. Sze, Begüm D. Topçuoğlu, Geoffrey D. Hannigan, Ada K. Hagan, Amanda G. Elmore, Kaitlin J. Flynn, Nicholas A. Lesniak, Sarah Tomkovich, Patrick D. Schloss, Lucas Bishop, Ariangela J. Kozik, Marcy J. Balunas, Kelly Sovacool, Matthew D. Doherty, Charlie C. Koumpouras, Samara Rifkin, and Joshua M. A. Stough
- Subjects
0301 basic medicine ,Science and Technology Workforce ,Molecular biology ,Social Sciences ,Biologists ,Careers in Research ,Respect ,0302 clinical medicine ,Learning and Memory ,Sequencing techniques ,Sociology ,Psychology ,Biology (General) ,Repeated practice ,Grammar ,Ecology ,Software Engineering ,RNA sequencing ,Research Assessment ,Reproducibility ,Schedule (workplace) ,Professions ,Computational Theory and Mathematics ,Modeling and Simulation ,Engineering and Technology ,Workshops ,Club ,Goals ,2019-20 coronavirus outbreak ,Computer and Information Sciences ,QH301-705.5 ,Science Policy ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Library science ,Logo ,Research and Analysis Methods ,Education ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Genetics ,Humans ,Learning ,Syntax ,Ecology, Evolution, Behavior and Systematics ,Data Science ,Cognitive Psychology ,Computational Biology ,Biology and Life Sciences ,Linguistics ,030104 developmental biology ,Molecular biology techniques ,Critical thinking ,Coursework ,People and Places ,Scientists ,Cognitive Science ,Population Groupings ,Programming Languages ,030217 neurology & neurosurgery ,Neuroscience - Abstract
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
- Published
- 2020
15. Coordination chemistry controls the thiol oxidase activity of the B12-trafficking protein CblC
- Author
-
Aranganathan Shanmuganathan, Zhu Li, Nicholas A. Lesniak, Markus Ruetz, Ruma Banerjee, Bernhard Kräutler, Kazuhiro Yamada, Thomas C. Brunold, and Markos Koutmos
- Subjects
0301 basic medicine ,chemistry.chemical_classification ,biology ,Catabolism ,Cell Biology ,Glutathione ,010402 general chemistry ,01 natural sciences ,Biochemistry ,Cobalamin ,Cofactor ,0104 chemical sciences ,03 medical and health sciences ,chemistry.chemical_compound ,030104 developmental biology ,chemistry ,Oxidoreductase ,polycyclic compounds ,Thiol ,biology.protein ,CBLC ,Thiol oxidase activity ,Molecular Biology - Abstract
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.
- Published
- 2017
16. A framework for effective application of machine learning to microbiome-based classification problems
- Author
-
Mack T. Ruffin, Jenna Wiens, Patrick D. Schloss, Nicholas A. Lesniak, and Begüm D. Topçuoğlu
- Subjects
Gastrointestinal Diseases ,Computer science ,Decision tree ,microbiome ,microbial ecology ,Machine learning ,computer.software_genre ,Logistic regression ,Microbiology ,Host-Microbe Biology ,Machine Learning ,Feces ,03 medical and health sciences ,0302 clinical medicine ,Predictive Value of Tests ,Virology ,Black box ,RNA, Ribosomal, 16S ,Diabetes mellitus ,medicine ,Humans ,Microbiome ,030304 developmental biology ,Interpretability ,0303 health sciences ,Receiver operating characteristic ,business.industry ,Microbiota ,Model selection ,medicine.disease ,QR1-502 ,Abstract machine ,Random forest ,Support vector machine ,Logistic Models ,colon cancer ,030220 oncology & carcinogenesis ,Colonic Neoplasms ,Linear Models ,16S rRNA gene ,Artificial intelligence ,business ,computer ,Research Article - Abstract
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.
- Published
- 2019
17. The proton pump inhibitor omeprazole does not promote Clostridioides difficile colonization in a murine model
- Author
-
Patrick D. Schloss, Nicholas A. Lesniak, Sarah Tomkovich, Lucas Bishop, Yuan Li, and Madison J. Fitzgerald
- Subjects
0301 basic medicine ,Antibiotics ,lcsh:QR1-502 ,microbiome ,Observation ,microbial ecology ,lcsh:Microbiology ,Feces ,Mice ,RNA, Ribosomal, 16S ,Cluster Analysis ,Colonization ,Phylogeny ,Omeprazole ,0303 health sciences ,Microbiota ,pathogenesis ,Clostridium difficile ,Fecal microbiota ,QR1-502 ,3. Good health ,Carrier State ,Disease Susceptibility ,medicine.drug ,DNA, Bacterial ,medicine.drug_class ,mouse model ,030106 microbiology ,Proton-pump inhibitor ,Colonisation resistance ,DNA, Ribosomal ,Microbiology ,Host-Microbe Biology ,03 medical and health sciences ,colonization resistance ,medicine ,Animals ,Microbiome ,Molecular Biology ,030304 developmental biology ,Clostridioides difficile ,030306 microbiology ,business.industry ,Clindamycin ,Proton Pump Inhibitors ,Sequence Analysis, DNA ,infection ,Disease Models, Animal ,030104 developmental biology ,13. Climate action ,Murine model ,Clostridium Infections ,16S rRNA gene ,business ,Clostridioides - Abstract
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.
- Published
- 2019
18. Fecal Short-Chain Fatty Acids Are Not Predictive of Colonic Tumor Status and Cannot Be Predicted Based on Bacterial Community Structure
- Author
-
Patrick D. Schloss, Nicholas A. Lesniak, Begüm D. Topçuoğlu, Marc A. Sze, and Mack T. Ruffin
- Subjects
Adenoma ,Colorectal cancer ,Physiology ,microbiome ,Observation ,Butyrate ,Biology ,microbial ecology ,Microbiology ,Host-Microbe Biology ,Feces ,03 medical and health sciences ,Tumor Status ,0302 clinical medicine ,scfa ,Clinical Decision Rules ,RNA, Ribosomal, 16S ,Virology ,medicine ,Humans ,Microbiome ,Gene ,030304 developmental biology ,0303 health sciences ,metagenomics ,Bacteria ,digestive, oral, and skin physiology ,Carcinoma ,Fatty Acids, Volatile ,medicine.disease ,United States ,QR1-502 ,Gastrointestinal Microbiome ,3. Good health ,machine learning ,colon cancer ,Metagenomics ,030220 oncology & carcinogenesis ,Colonic Neoplasms ,Cohort ,random forest ,16s rrna - Abstract
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.
- Published
- 2019
19. Erratum for Baxter et al., 'The Glucoamylase Inhibitor Acarbose Has a Diet-Dependent and Reversible Effect on the Murine Gut Microbiome'
- Author
-
Patrick D. Schloss, Hamide Sinani, Nicole M. Koropatkin, Nancy N. Baxter, and Nicholas A. Lesniak
- Subjects
business.industry ,Published Erratum ,lcsh:QR1-502 ,Medicine ,Pharmacology ,business ,Molecular Biology ,Microbiology ,Gut microbiome ,QR1-502 ,lcsh:Microbiology ,Acarbose ,medicine.drug - Abstract
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
- Published
- 2019
20. The Glucoamylase Inhibitor Acarbose Has a Diet-Dependent and Reversible Effect on the Murine Gut Microbiome
- Author
-
Nicole M. Koropatkin, Nancy N. Baxter, Patrick D. Schloss, Hamide Sinani, and Nicholas A. Lesniak
- Subjects
0301 basic medicine ,Dietary Fiber ,Male ,Bacteroidaceae ,030106 microbiology ,lcsh:QR1-502 ,Type 2 diabetes ,Biology ,Pharmacology ,Gut flora ,Microbiology ,lcsh:Microbiology ,Host-Microbe Biology ,03 medical and health sciences ,Feces ,Mice ,RNA, Ribosomal, 16S ,medicine ,Animals ,Glycoside Hydrolase Inhibitors ,Molecular Biology ,Acarbose ,Bacteria ,gut microbiota ,starch ,Lachnospiraceae ,biology.organism_classification ,medicine.disease ,Fatty Acids, Volatile ,QR1-502 ,3. Good health ,Metformin ,Diet ,Gastrointestinal Microbiome ,Bifidobacteriaceae ,Mice, Inbred C57BL ,Butyrates ,030104 developmental biology ,Postprandial ,Erratum ,acarbose ,Akkermansia muciniphila ,medicine.drug ,Research Article - Abstract
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.
- Published
- 2019
21. Coordination chemistry controls the thiol oxidase activity of the B
- Author
-
Zhu, Li, Aranganathan, Shanmuganathan, Markus, Ruetz, Kazuhiro, Yamada, Nicholas A, Lesniak, Bernhard, Kräutler, Thomas C, Brunold, Markos, Koutmos, and Ruma, Banerjee
- Subjects
Oxidative Stress ,polycyclic compounds ,Mutation, Missense ,Enzymology ,Animals ,Humans ,Oxidoreductases Acting on Sulfur Group Donors ,Cobamides ,Caenorhabditis elegans ,Caenorhabditis elegans Proteins ,Carrier Proteins ,Oxidoreductases - Abstract
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.
- Published
- 2017
22. Glutathione-dependent One-electron Transfer Reactions Catalyzed by a B12 Trafficking Protein
- Author
-
Nicholas A. Lesniak, Zhu Li, Ruma Banerjee, and Carmen Gherasim
- Subjects
Stereochemistry ,Polymerase Chain Reaction ,Biochemistry ,Cobalamin ,Redox ,Catalysis ,Cofactor ,Electron Transport ,chemistry.chemical_compound ,Lysosome ,medicine ,Sulfhydryl Compounds ,Molecular Biology ,DNA Primers ,chemistry.chemical_classification ,Base Sequence ,biology ,Cell Biology ,Glutathione ,Vitamin B 12 ,Enzyme ,medicine.anatomical_structure ,chemistry ,Enzymology ,biology.protein ,CBLC ,Alkyltransferase - Abstract
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.
- Published
- 2014
23. Unusual aerobic stabilization of Cob(I)alamin by a B12-trafficking protein allows chemoenzymatic synthesis of organocobalamins
- Author
-
Ruma Banerjee, Zhu Li, and Nicholas A. Lesniak
- Subjects
Stereochemistry ,Biochemistry ,Catalysis ,Cofactor ,Article ,Glutathione transferase ,chemistry.chemical_compound ,Colloid and Surface Chemistry ,polycyclic compounds ,Animals ,Humans ,Cyanocobalamin ,Thiol oxidase activity ,Caenorhabditis elegans ,Caenorhabditis elegans Proteins ,Glutathione Transferase ,biology ,Biological activity ,Biological Transport ,General Chemistry ,Glutathione ,biology.organism_classification ,Aerobiosis ,Vitamin B 12 ,chemistry ,biology.protein ,CBLC ,Oxidoreductases - Abstract
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.
- Published
- 2014
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.