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Efrat Muller edited this page Feb 15, 2024 · 26 revisions

Welcome to the curated gut microbiome-metabolome data resource wiki (v2.1.0)!

The resource was prepared by the Borenstein lab at Tel-Aviv University. Please contact us if you have any questions or would like to add your own dataset to the collection.

This dataset collection includes curated data from multiple studies where both metagenomic and metabolomic profiles were obtained from human fecal samples [1-14]. It was made publicly available for the benefit of the microbiome research community to facilitate integrative microbiome-metabolome meta-analysis and cross-study comparisons. Overall, the collection currently contains 14 datasets, including 2900 samples from 1849 subjects.

This wiki contains details about how the data is organized in the repository, the original studies that generated the data, how the data was processed, and a quick example of how the data could be used for cross-study comparisons. Use the Wiki's sidebar to navigate to the relevant sections. For transparency and reproducibility, scripts used for manipulating the originally-published data are available in the repository as well (and referred to within the relevant sections of this wiki).

We encourage users to review both the original publications and the processing notes provided in this wiki and in our supplementary tables before using and analyzing these data.

📌 Importantly, comparisons between studies and result interpretation should be made with caution, especially in regards to metabolomics data. Different metabolomic platforms differ in which chemical classes they are able to detect and at what sensitivity, meaning that a direct comparison of metabolite levels (or presence/absence) between studies is not possible. Please refer to the Key limitations section for an expanded discussion on this subject. In addition, there is substantial heterogeneity between studies that arises from differences in cohort characteristics (ages, geography, medical backgrounds, etc.) as well as study protocols and data generation methods (sample collection, storage protocols, sample processing, etc.). All of these factors are expected to introduce variation in both fecal microbiome and fecal metabolome profiles [15-20], and should therefore be considered in any cross-study analysis.

Wiki contents

Acknowledgements

We thank all the authors of the studies included in this collection, for making their data publicly available and for responding to inquires we had during the processing of this collection. We also thank Shira Limon for the illustration at the top of this page, and past and present Borenstein lab members for helpful inputs.

Citations

If you use the data provided here, please cite both the original publications who generated and published the data (see Data overview) as well as:

Muller, Efrat, Yadid M. Algavi, and Elhanan Borenstein. "The gut microbiome-metabolome dataset collection: a curated resource for integrative meta-analysis." npj Biofilms and Microbiomes 8.1 (2022): 1-7.

References

  1. Yachida, Shinichi, et al. "Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer." Nature medicine 25.6 (2019): 968-976.
  2. Franzosa, Eric A., et al. "Gut microbiome structure and metabolic activity in inflammatory bowel disease." Nature microbiology 4.2 (2019): 293-305.
  3. Sinha, Rashmi, et al. "Fecal microbiota, fecal metabolome, and colorectal cancer interrelations." PloS one 11.3 (2016): e0152126.
  4. He, Xuan, et al. "Fecal microbiome and metabolome of infants fed bovine MFGM supplemented formula or standard formula with breast-fed infants as reference: a randomized controlled trial." Scientific reports 9.1 (2019): 1-14.
  5. Lloyd-Price, Jason, et al. "Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases." Nature 569.7758 (2019): 655-662.
  6. Jacobs, Jonathan P., et al. "A disease-associated microbial and metabolomics state in relatives of pediatric inflammatory bowel disease patients." Cellular and molecular gastroenterology and hepatology 2.6 (2016): 750-766.
  7. Poyet, M., et al. "A library of human gut bacterial isolates paired with longitudinal multiomics data enables mechanistic microbiome research." Nature medicine 25.9 (2019): 1442-1452.
  8. Erawijantari et al. Influence of gastrectomy for gastric cancer treatment on faecal microbiome and metabolome profiles. Gut. 2020 Aug;69(8):1404-1415.
  9. Kim, Minsuk, et al. "Fecal metabolomic signatures in colorectal adenoma patients are associated with gut microbiota and early events of colorectal cancer pathogenesis." MBio 11.1 (2020): e03186-19.
  10. Mars, Ruben AT, et al. "Longitudinal multi-omics reveals subset-specific mechanisms underlying irritable bowel syndrome." Cell 182.6 (2020): 1460-1473.
  11. Kang, Dae-Wook, et al. "Differences in fecal microbial metabolites and microbiota of children with autism spectrum disorders." Anaerobe 49 (2018): 121-131.
  12. Kostic, Aleksandar D., et al. "The dynamics of the human infant gut microbiome in development and in progression toward type 1 diabetes." Cell host & microbe 17.2 (2015): 260-273.
  13. Wandro, Stephen, et al. "The microbiome and metabolome of preterm infant stool are personalized and not driven by health outcomes, including necrotizing enterocolitis and late-onset sepsis." Msphere 3.3 (2018): e00104-18.
  14. Wang, Xifan, et al. "Aberrant gut microbiota alters host metabolome and impacts renal failure in humans and rodents." Gut 69.12 (2020): 2131-2142.
  15. Smirnov, Kirill S., et al. "Challenges of metabolomics in human gut microbiota research." International Journal of Medical Microbiology 306.5 (2016): 266-279.
  16. Jovel, Juan, et al. "Characterization of the gut microbiome using 16S or shotgun metagenomics." Frontiers in microbiology 7 (2016): 459.
  17. Liang, Yali, et al. "Systematic analysis of impact of sampling regions and storage methods on fecal gut microbiome and metabolome profiles." Msphere 5.1 (2020): e00763-19.
  18. Debelius, Justine, et al. "Tiny microbes, enormous impacts: what matters in gut microbiome studies?." Genome biology 17.1 (2016): 1-12.
  19. Yatsunenko, Tanya, et al. "Human gut microbiome viewed across age and geography." nature 486.7402 (2012): 222-227.
  20. Falony, Gwen, et al. "Population-level analysis of gut microbiome variation." Science 352.6285 (2016): 560-564.

The curated gut microbiome-metabolome data resource


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