Summary of Study ST002741

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench,, where it has been assigned Project ID PR001706. The data can be accessed directly via it's Project DOI: 10.21228/M8642W This work is supported by NIH grant, U2C- DK119886.


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.

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Study IDST002741
Study TitleIntegration of Meta-Multi-Omics Data Using Probabilistic Graphs and External Knowledge
Study SummaryMulti-omics has the promise to provide a detailed molecular picture for biological systems. Although obtaining multi-omics data is relatively easy, methods that analyze such data have been lagging. In this paper, we present an algorithm that uses probabilistic graph representations and external knowledge to perform optimum structure learning and deduce a multifarious interaction network for multi-omics data from a bacterial community. Kefir grain, a microbial community that ferments milk and creates kefir, represents a self-renewing, stable, natural microbial community. Kefir has been shown to associate with a wide range of health benefits. We obtained a controlled bacterial community using the two most abundant and well-studied species in kefir grains: Lentilactobacillus kefiri and Lactobacillus kefiranofaciens. We applied growth temperatures of 30°C and 37°C, and obtained transcriptomic, metabolomic, and proteomic data for the same 20 samples (10 samples per temperature). We obtained a multi-omics interaction network, which generated insights that would not have been possible with single-omics analysis. We identified interactions among transcripts, proteins, and metabolites suggesting active toxin/antitoxin systems. We also observed multifarious interactions that involved the shikimate pathway. These observations helped explain bacterial adaptation to different stress conditions, co-aggregation, and increased activation of L. kefiranofaciens at 37°C.
University of Nebraska-Lincoln
Last NameAlvarez
First NameSophie
Address1901 Vine St
Submit Date2023-06-19
Raw Data AvailableYes
Raw Data File Type(s)abf, d
Analysis Type DetailGC-MS
Release Date2023-08-10
Release Version1
Sophie Alvarez Sophie Alvarez application/zip

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Combined analysis:

Analysis ID AN004571
Analysis type MS
Chromatography type GC
Chromatography system Agilent 7890B
Column Agilent HP5-MS (30m x 0.25mm, 0.25 um)
MS Type EI
MS instrument type Single quadrupole
MS instrument name Agilent 5977A
Units normalized intensity