Summary of Study ST002094

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001102. The data can be accessed directly via it's Project DOI: 10.21228/M8840R This work is supported by NIH grant, U2C- DK119886.

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Study ID	ST002094
Study Title	Commensal intestinal microbiota regulates host luminal proteolytic activity and intestinal barrier integrity through β-glucuronidase activity (Part 1)
Study Type	MS
Study Summary	Proteases constitute the largest enzyme gene family in vertebrates with intracellular and secreted proteases having critical roles in cellular and organ physiology. Intestinal tract contains diverse set of proteases mediating digestion, microbial responses, epithelial and immune signaling. Transit of chyme through the intestinal tract results in significant suppression of proteases. Although endogenous protease inhibitors have been identified, the broader mechanisms underlying protease regulation in the intestinal tract remains unclear. The objective of this study was to determine microbial regulation of proteolytic activity in intestinal tract using phenotype of post-infection irritable bowel syndrome, a condition characterized by high fecal proteolytic activity. Proteases of host pancreatic origin (chymotrypsin like pancreatic elastase 2A, 3B and trypsin 2) drove proteolytic activity. Of the 14 differentially abundant taxa, high proteolytic activity state was characterized by complete absence of the commensal Alistipes putredinis. Germ free mice had very high proteolytic activity (10-fold of specific-pathogen free mice) which dropped significantly upon humanization with microbiota from healthy volunteers. In contrast, high proteolytic activity microbiota failed to inhibit it, a defect that corrected with fecal microbiota transplant as well as addition of A. putredinis. These mice also had increased intestinal permeability similar to that seen in patients. Microbiota β-glucuronidases mediate bilirubin deconjugation and unconjugated bilirubin is an inhibitor of serine proteases. We found that high proteolytic activity patients had lower urobilinogen levels, a product of bilirubin deconjugation. Mice colonized with β-glucuronidase overexpressing E. coli demonstrated significant inhibition of proteolytic activity and treatment with β-glucuronidase inhibitors increased it. The findings establish that specific commensal microbiota mediates effective inhibition of host pancreatic proteases and maintains intestinal barrier function through the production of β-glucuronidases. This suggests an important homeostatic role for commensal intestinal microbiota.
Institute	Mayo Clinic
Department	Biomedical Statistics and Informatics
Last Name	Dasari
First Name	Surendra
Address	200 First Street SW, Rochester, MN, 55905, USA
Email	Dasari.Surendra@mayo.edu
Phone	507-284-0513
Submit Date	2022-02-17
Num Groups	2
Total Subjects	7
Raw Data Available	Yes
Raw Data File Type(s)	d
Analysis Type Detail	LC-MS
Release Date	2022-03-09
Release Version	1

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Sample Preparation:

Sampleprep ID:	SP002184
Sampleprep Summary:	Fecal samples were deproteinized with six times volume of cold acetonitrile:methanol (1:1 ratio), kept on ice with intermittent vortexing for 30 minutes at 4C, then centrifuged at 18000xg. 13C6-phenylalanine (3 µl at 250ng/µl) was added as internal standard to each sample prior to deproteinization. The supernatants were divided into 2 aliquots and dried down for analysis on a Quadrupole Time-of-Flight Mass Spectrometer (Agilent Technologies 6550 Q-TOF) coupled with an Ultra High Pressure Liquid Chromatograph (1290 Infinity UHPLC Agilent Technologies). Profiling data were acquired under both positive and negative electrospray ionization conditions over a mass range of 100 - 1200 m/z at a resolution of 10,000-35,000 (separate runs). Metabolite separation was achieved using two columns of differing polarity, a hydrophilic interaction column (HILIC, ethylene-bridged hybrid 2.1 x 150 mm, 1.7 mm; Waters) and a reversed-phase C18 column (high-strength silica 2.1 x 150 mm, 1.8 mm; Waters). For each column, the run time is 20 min using a flow rate of 400 ul/min. A total of four runs per sample will be performed to give maximum coverage of metabolites. Samples were injected in duplicate or triplicate, and a quality control sample, made up of a subset of samples from the study was injected several times during a run. All raw data files obtained were converted to compound exchange file format using Masshunter DA reprocessor software (Agilent). Mass Profiler Professional (Agilent) was used for data alignment and to convert each metabolite feature (m/z x intensity x time) into a matrix of detected peaks for compound identification.

Sampleprep ID:

SP002184

Sampleprep Summary:

Fecal samples were deproteinized with six times volume of cold acetonitrile:methanol (1:1 ratio), kept on ice with intermittent vortexing for 30 minutes at 4C, then centrifuged at 18000xg. 13C6-phenylalanine (3 µl at 250ng/µl) was added as internal standard to each sample prior to deproteinization. The supernatants were divided into 2 aliquots and dried down for analysis on a Quadrupole Time-of-Flight Mass Spectrometer (Agilent Technologies 6550 Q-TOF) coupled with an Ultra High Pressure Liquid Chromatograph (1290 Infinity UHPLC Agilent Technologies). Profiling data were acquired under both positive and negative electrospray ionization conditions over a mass range of 100 - 1200 m/z at a resolution of 10,000-35,000 (separate runs). Metabolite separation was achieved using two columns of differing polarity, a hydrophilic interaction column (HILIC, ethylene-bridged hybrid 2.1 x 150 mm, 1.7 mm; Waters) and a reversed-phase C18 column (high-strength silica 2.1 x 150 mm, 1.8 mm; Waters). For each column, the run time is 20 min using a flow rate of 400 ul/min. A total of four runs per sample will be performed to give maximum coverage of metabolites. Samples were injected in duplicate or triplicate, and a quality control sample, made up of a subset of samples from the study was injected several times during a run. All raw data files obtained were converted to compound exchange file format using Masshunter DA reprocessor software (Agilent). Mass Profiler Professional (Agilent) was used for data alignment and to convert each metabolite feature (m/z x intensity x time) into a matrix of detected peaks for compound identification.