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1.
Curr Protoc Chem Biol ; 12(3): e83, 2020 09.
Article in English | MEDLINE | ID: mdl-32805089

ABSTRACT

Metabolomic studies allow a deeper understanding of the processes of a given ecological community than nucleic acid-based surveys alone. In the case of the gut microbiota, a metabolic profile of, for example, a fecal sample provides details about the function and interactions within the distal region of the gastrointestinal tract, and such a profile can be generated in a number of different ways. This unit elaborates on the use of 1D 1 H NMR spectroscopy as a commonly used method to characterize small-molecule metabolites of the fecal metabonome (meta-metabolome). We describe a set of protocols for the preparation of fecal water extraction, storage, scanning, measurement of pH, and spectral processing and analysis. We also compare the effects of various sample storage conditions for processed and unprocessed samples to provide a framework for comprehensive analysis of small molecules from stool-derived samples. © 2020 Wiley Periodicals LLC Basic Protocol 1: Extracting fecal water from crude fecal samples Alternate Protocol 1: Extracting fecal water from small crude fecal samples Basic Protocol 2: Acquiring NMR spectra of metabolite samples Alternate Protocol 2: Acquiring NMR spectra of metabolite samples using Bruker spectrometer running TopSpin 3.x Alternate Protocol 3: Acquiring NMR spectra of metabolite samples by semiautomated process Basic Protocol 3: Measuring sample pH Support Protocol 1: Cleaning NMR tubes Basic Protocol 4: Processing raw spectra data Basic Protocol 5: Profiling spectra Support Protocol 2: Spectral profiling of sugars and other complex metabolites.


Subject(s)
Feces/chemistry , Metabolomics/methods , Proton Magnetic Resonance Spectroscopy , Humans , Hydrogen-Ion Concentration
2.
Sci Rep ; 9(1): 885, 2019 01 29.
Article in English | MEDLINE | ID: mdl-30696914

ABSTRACT

Many cases of Clostridioides difficile infection (CDI) are poorly responsive to standard antibiotic treatment strategies, and often patients suffer from recurrent infections characterized by severe diarrhea. Our group previously reported the successful cure of two patients with recurrent CDI using a standardized stool-derived microbial ecosystem therapeutic (MET-1). Using an in vitro model of the distal gut to support bacterial communities, we characterized the metabolite profiles of two defined microbial ecosystems derived from healthy donor stool (DEC58, and a subset community, MET-1), as well as an ecosystem representative of a dysbiotic state (ciprofloxacin-treated DEC58). The growth and virulence determinants of two C. difficile strains were then assessed in response to components derived from the ecosystems. CD186 (ribotype 027) and CD973 (ribotype 078) growth was decreased upon treatment with DEC58 metabolites compared to ciprofloxacin-treated DEC58 metabolites. Furthermore, CD186 TcdA and TcdB secretion was increased following treatment with ciprofloxacin-treated DEC58 spent medium compared to DEC58 spent medium alone. The net metabolic output of C. difficile was also modulated in response to spent media from defined microbial ecosystems, although several metabolite levels were divergent across the two strains examined. Further investigation of these antagonistic properties will guide the development of microbiota-based therapeutics for CDI.


Subject(s)
Clostridioides difficile/genetics , Feces/microbiology , Gastrointestinal Microbiome/genetics , Anti-Bacterial Agents/pharmacology , Bacterial Proteins/genetics , Bacterial Toxins/pharmacology , Ciprofloxacin/pharmacology , Clostridiales/genetics , Clostridiales/metabolism , Clostridioides difficile/metabolism , Clostridium Infections/microbiology , Diarrhea/microbiology , Dysbiosis/microbiology , Enterotoxins/pharmacology , Fecal Microbiota Transplantation/methods , Humans , Microbiota/genetics , Virulence/genetics , Virulence Factors/pharmacology
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