Summary of Study ST002741
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 PR001706. The data can be accessed directly via it's Project DOI: 10.21228/M8642W 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 | ST002741 |
| Study Title | Integration of Meta-Multi-Omics Data Using Probabilistic Graphs and External Knowledge |
| Study Summary | Multi-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. |
| Institute | University of Nebraska-Lincoln |
| Last Name | Alvarez |
| First Name | Sophie |
| Address | 1901 Vine St |
| salvarez@unl.edu | |
| Phone | 4024724575 |
| Submit Date | 2023-06-19 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | abf, d |
| Analysis Type Detail | GC-MS |
| Release Date | 2023-08-10 |
| Release Version | 1 |
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Collection:
| Collection ID: | CO002911 |
| Collection Summary: | All samples were initially inoculated with a mixed culture of L. kefiri and L. kefiranofaciens inoculum blended from 3-day cultures. 20 mL MRS medium was inocu-lated with 0.5 mL of the combined inoculum and incubated for 3 days, one set of 10 at 30°C, and another set of 10 at 37°C. For controls, L. kefiri and L. kefiranofaciens were inoculated in triplicate for each temperature. The tubes were removed from the incubator after 3 days, and 0.1 mL of each sample was placed in a 96 well plate for OD (600 nm) analysis. Samples were then centrifuged (3000×g, 4°C, 10 min), and the supernatant was removed and frozen for further analysis. The pellet was washed in fresh MRS (pH 5.5), divided in three aliquots, re-pelleted in microcentrifuge tubes, and frozen at -80°C for subsequent transcriptomic, proteomic, and metabolomic analysis. |
| Sample Type: | Bacterial cells |
