Summary of Study ST001683
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 PR001074. The data can be accessed directly via it's Project DOI: 10.21228/M8W11P This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST001683 |
| Study Title | A gut microbe-focused metabolomics pipeline enables mechanistic interrogation of microbiome metabolism. |
| Study Summary | Gut microbes modulate host phenotypes and are associated with numerous health effects in humans, ranging from cancer immunotherapy response to metabolic disease and obesity. However, difficulty in accurate and high-throughput functional analysis of human gut microbes has hindered defining mechanistic connections between individual microbial strains and host phenotypes. One key way the gut microbiome influences host physiology is through the production of small molecules hindered by limited tools calibrated to detect products of anaerobic biochemistry in the gut. Here we construct a microbiome-focused, integrated mass-spectrometry pipeline to accelerate the identification of microbiota-dependent metabolites (MDMs) in diverse sample types. We report the metabolic profiles of 178 gut microbe strains using our library of 833 metabolites. Leveraging this metabolomics resource we establish deviations in the relationships between phylogeny and metabolism, use machine learning to discover novel metabolism in Bacteroides, and employ comparative genomics-based discovery of candidate biochemical pathways. MDMs can be detected in diverse body fluids in gnotobiotic and conventional mice and traced back to corresponding metabolomic profiles of cultured bacteria. Collectively, our microbiome-focused metabolomics pipeline and interactive metabolomics profile explorer are a powerful tool for characterizing microbe and microbe-host interactions. |
| Institute | Stanford University |
| Department | Microbiology & Immunology |
| Laboratory | Justin Sonnenburg |
| Last Name | Han |
| First Name | Shuo |
| Address | 299 Campus Drive, Stanford, CA, 94305-5124, USA |
| shuohan@stanford.edu | |
| Phone | - |
| Submit Date | 2021-02-06 |
| Publications | not published, status to be updated |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzML |
| Analysis Type Detail | LC-MS |
| Release Date | 2021-05-17 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN002747 | AN002748 | AN002749 |
|---|---|---|---|
| Analysis type | MS | MS | MS |
| Chromatography type | Reversed phase | Reversed phase | HILIC |
| Chromatography system | Agilent qTOF 6545 | Agilent qTOF 6545 | Agilent qTOF 6545 |
| Column | Waters Acquity BEH (100 x 2.1mm,1.7um) | Waters Acquity BEH (100 x 2.1mm,1.7um) | Waters Acquity BEH Amide (150 x 2.1mm,1.7um) |
| MS Type | ESI | ESI | ESI |
| MS instrument type | QTOF | QTOF | QTOF |
| MS instrument name | Agilent qTOF 6545 | Agilent qTOF 6545 | Agilent qTOF 6545 |
| Ion Mode | POSITIVE | NEGATIVE | POSITIVE |
| Units | Raw ion count (peak area) | Raw ion count (peak area) | Raw ion count (peak area) |
MS:
| MS ID: | MS002544 |
| Analysis ID: | AN002747 |
| Instrument Name: | Agilent qTOF 6545 |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The MS-DIAL software (v. 3.83) was used for analyzing all in vitro and in vivo data on a per-experimental run and per-analytical method basis. QC samples from each experimental run were used for peak alignment. Chemical assignment of molecular features in samples was performed by comparison of recorded RT and m/z information to our reference library constructed from authentic standards. Tolerance windows were set to 0.1 minute RT and 0.01 Da m/z for the C18 methods and 0.2 minute RT and 0.01 Da m/z for the HILIC method. The minimal peak count (height) filter was set to 3000 for all experiments except for select experiments in which the MS exhibited reduced sensitivity. For experiments where detection of internal standards goes beyond the 0.1 (C18 methods) or 0.2 (HILIC method) window, RT correction of the mz-RT reference library was conducted prior to feature annotation in MS-DIAL. The MS-DIAL analysis generated a list of m/z, RT, and ion counts (area under the curve) for high-confidence annotations (matched to the reference library) as well as unknown molecular features. Based on the list of annotations for each experiment, each set of aligned peaks was manually checked using the MS-DIAL graphical user interface. Select metabolite features were removed from this list when: 1) two adjacent but distinct peaks were concurrently assigned to a single molecular feature, 2) odd curvature/shape of the peak led to integration of several “peaks” from separate sections of the same peak, or 3) features were only detected in blank controls. Annotated peaks that passed this inspection were reported in the final output file. After MS-DIAL analysis, data were analyzed with a set of custom bioinformatics pipelines. In short, these pipelines implemented a set of filtration and normalization procedures with the goal of reducing technical variability and controlling for batch effects. |
| Ion Mode: | POSITIVE |
| MS ID: | MS002545 |
| Analysis ID: | AN002748 |
| Instrument Name: | Agilent qTOF 6545 |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The MS-DIAL software (v. 3.83) was used for analyzing all in vitro and in vivo data on a per-experimental run and per-analytical method basis. QC samples from each experimental run were used for peak alignment. Chemical assignment of molecular features in samples was performed by comparison of recorded RT and m/z information to our reference library constructed from authentic standards. Tolerance windows were set to 0.1 minute RT and 0.01 Da m/z for the C18 methods and 0.2 minute RT and 0.01 Da m/z for the HILIC method. The minimal peak count (height) filter was set to 3000 for all experiments except for select experiments in which the MS exhibited reduced sensitivity. For experiments where detection of internal standards goes beyond the 0.1 (C18 methods) or 0.2 (HILIC method) window, RT correction of the mz-RT reference library was conducted prior to feature annotation in MS-DIAL. The MS-DIAL analysis generated a list of m/z, RT, and ion counts (area under the curve) for high-confidence annotations (matched to the reference library) as well as unknown molecular features. Based on the list of annotations for each experiment, each set of aligned peaks was manually checked using the MS-DIAL graphical user interface. Select metabolite features were removed from this list when: 1) two adjacent but distinct peaks were concurrently assigned to a single molecular feature, 2) odd curvature/shape of the peak led to integration of several “peaks” from separate sections of the same peak, or 3) features were only detected in blank controls. Annotated peaks that passed this inspection were reported in the final output file. After MS-DIAL analysis, data were analyzed with a set of custom bioinformatics pipelines. In short, these pipelines implemented a set of filtration and normalization procedures with the goal of reducing technical variability and controlling for batch effects. |
| Ion Mode: | NEGATIVE |
| MS ID: | MS002546 |
| Analysis ID: | AN002749 |
| Instrument Name: | Agilent qTOF 6545 |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The MS-DIAL software (v. 3.83) was used for analyzing all in vitro and in vivo data on a per-experimental run and per-analytical method basis. QC samples from each experimental run were used for peak alignment. Chemical assignment of molecular features in samples was performed by comparison of recorded RT and m/z information to our reference library constructed from authentic standards. Tolerance windows were set to 0.1 minute RT and 0.01 Da m/z for the C18 methods and 0.2 minute RT and 0.01 Da m/z for the HILIC method. The minimal peak count (height) filter was set to 3000 for all experiments except for select experiments in which the MS exhibited reduced sensitivity. For experiments where detection of internal standards goes beyond the 0.1 (C18 methods) or 0.2 (HILIC method) window, RT correction of the mz-RT reference library was conducted prior to feature annotation in MS-DIAL. The MS-DIAL analysis generated a list of m/z, RT, and ion counts (area under the curve) for high-confidence annotations (matched to the reference library) as well as unknown molecular features. Based on the list of annotations for each experiment, each set of aligned peaks was manually checked using the MS-DIAL graphical user interface. Select metabolite features were removed from this list when: 1) two adjacent but distinct peaks were concurrently assigned to a single molecular feature, 2) odd curvature/shape of the peak led to integration of several “peaks” from separate sections of the same peak, or 3) features were only detected in blank controls. Annotated peaks that passed this inspection were reported in the final output file. After MS-DIAL analysis, data were analyzed with a set of custom bioinformatics pipelines. In short, these pipelines implemented a set of filtration and normalization procedures with the goal of reducing technical variability and controlling for batch effects. |
| Ion Mode: | POSITIVE |
