Summary of Study ST004389

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 PR002782. The data can be accessed directly via it's Project DOI: 10.21228/M82C1P This work is supported by NIH grant, U2C- DK119886.

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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 IDST004389
Study TitleLongitudinal Multi-omics Profiling Reveals Different Adaptation to Heat Stress in Genomically Divergent Lactating Sows
Study SummaryHeat stress (HS) poses a growing threat to health and productivity across mammals, a problem exacerbated by climate change. Simultaneously, the gut microbiome plays a crucial role in host adaptation to environmental stressors, yet the molecular mechanisms underlying microbiome-mediated heat tolerance remain poorly understood. Although multi-omics profiling has recently emerged as a powerful tool to explore host–microbiome interactions, no prior study, to our knowledge, has simultaneously integrated metagenomics, metatranscriptomics, and metabolomics in genetically characterized lactating mammals under HS conditions. Here, we present a time-resolved, multi-omics analysis of genomically divergent sows (heat-tolerant, TOL, and heat-sensitive, SEN) exposed to controlled HS, with the aim of identifying microbial and metabolic signatures of resilience. Metagenomic analyses revealed enrichment of specific taxa in TOL sows, including Treponema, F23-B02, and Bifidobacterium, with both enduring and time-specific effects. Metatranscriptomic profiling uncovered functional reprogramming in carbohydrate metabolism, membrane remodeling, and oxidative stress responses in TOL animals. These findings were further supported by metabolomic signatures indicating alterations in lipid turnover, amino acid metabolism, and redox homeostasis. Finally, integration of multi-omics data highlighted coordinated, time-specific microbial responses in TOL sows, reflecting robust host–microbiome adaptations to HS. By identifying candidate microbial biomarkers and conserved functional pathways, this study provides new insights into mammalian HS resilience and establishes a framework for cross-species investigations into heat resilience, stress physiology, and microbiome-targeted interventions.
Institute
North Carolina State University
Last NameVan Vliet
First NameStephan
AddressCenter for Human Nutrition Studies, Department of Nutrition, Dietetics, and Food Sciences, Utah State University, Logan, UT
Emailstephan.vanvliet@usu.edu
Phone1217785001
Submit Date2025-11-19
Raw Data AvailableYes
Raw Data File Type(s)mzML
Analysis Type DetailLC-MS
Release Date2025-11-28
Release Version1
Stephan Van Vliet Stephan Van Vliet
https://dx.doi.org/10.21228/M82C1P
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR002782
Project DOI:doi: 10.21228/M82C1P
Project Title:Longitudinal Multi-omics Profiling Reveals Different Adaptation to Heat Stress in Genomically Divergent Lactating Sows
Project Summary:Heat stress (HS) poses a growing threat to health and productivity across mammals, a problem exacerbated by climate change. Simultaneously, the gut microbiome plays a crucial role in host adaptation to environmental stressors, yet the molecular mechanisms underlying microbiome-mediated heat tolerance remain poorly understood. Although multi-omics profiling has recently emerged as a powerful tool to explore host–microbiome interactions, no prior study, to our knowledge, has simultaneously integrated metagenomics, metatranscriptomics, and metabolomics in genetically characterized lactating mammals under HS conditions. Here, we present a time-resolved, multi-omics analysis of genomically divergent sows (heat-tolerant, TOL, and heat-sensitive, SEN) exposed to controlled HS, with the aim of identifying microbial and metabolic signatures of resilience. Metagenomic analyses revealed enrichment of specific taxa in TOL sows, including Treponema, F23-B02, and Bifidobacterium, with both enduring and time-specific effects. Metatranscriptomic profiling uncovered functional reprogramming in carbohydrate metabolism, membrane remodeling, and oxidative stress responses in TOL animals. These findings were further supported by metabolomic signatures indicating alterations in lipid turnover, amino acid metabolism, and redox homeostasis. Finally, integration of multi-omics data highlighted coordinated, time-specific microbial responses in TOL sows, reflecting robust host–microbiome adaptations to HS. By identifying candidate microbial biomarkers and conserved functional pathways, this study provides new insights into mammalian HS resilience and establishes a framework for cross-species investigations into heat resilience, stress physiology, and microbiome-targeted interventions.
Institute:North Carolina State University
Last Name:Van Vliet
First Name:Stephan
Address:Center for Human Nutrition Studies, Department of Nutrition, Dietetics, and Food Sciences, Utah State University, Logan, UT
Email:stephan.vanvliet@usu.edu
Phone:1217785001

Subject:

Subject ID:SU004548
Subject Type:Mammal
Subject Species:Sus scrofa domesticus
Taxonomy ID:9825
Gender:Female

Factors:

Subject type: Mammal; Subject species: Sus scrofa domesticus (Factor headings shown in green)

mb_sample_id local_sample_id Sample source Factor
SA521015QC09QC QC
SA521016QC08QC QC
SA521017QC07QC QC
SA521018QC06QC QC
SA521019QC05QC QC
SA521020QC04QC QC
SA521021QC03QC QC
SA521022QC02QC QC
SA521023QC01QC QC
SA521024P88698T2HTSwine feces Non Heat
SA521025P88890T3HTSwine feces Non Heat
SA521026P88890T2HTSwine feces Non Heat
SA521027P76969T1NHTSwine feces Non Heat
SA521028P88890T0HTSwine feces Non Heat
SA521029P88698T3HTSwine feces Non Heat
SA521030P88422T0HTSwine feces Non Heat
SA521031P88698T1HTSwine feces Non Heat
SA521032P88698T0HTSwine feces Non Heat
SA521033P88422T3HTSwine feces Non Heat
SA521034P88422T2HTSwine feces Non Heat
SA521035P88422T1HTSwine feces Non Heat
SA521036P89021T1HTSwine feces Non Heat
SA521037P88020T3HTSwine feces Non Heat
SA521038P89021T0HTSwine feces Non Heat
SA521039P89153T3NHTSwine feces Non Heat
SA521040P89021T2HTSwine feces Non Heat
SA521041P89021T3HTSwine feces Non Heat
SA521042P89153T0NHTSwine feces Non Heat
SA521043P89153T2NHTSwine feces Non Heat
SA521044P87798T3HTSwine feces Non Heat
SA521045P89346T0NHTSwine feces Non Heat
SA521046P89346T1NHTSwine feces Non Heat
SA521047P89346T2NHTSwine feces Non Heat
SA521048P89346T3NHTSwine feces Non Heat
SA521049PO-4T0NHTSwine feces Non Heat
SA521050PO-4T1NHTSwine feces Non Heat
SA521051PO-4T2NHTSwine feces Non Heat
SA521052PO-4T3NHTSwine feces Non Heat
SA521053PO-5T1HTSwine feces Non Heat
SA521054PO-5T2HTSwine feces Non Heat
SA521055P88020T0HTSwine feces Non Heat
SA521056P76969T0NHTSwine feces Non Heat
SA521057P87798T2HTSwine feces Non Heat
SA521058P87798T0HTSwine feces Non Heat
SA521059P83109T2HTSwine feces Non Heat
SA521060P83109T0HTSwine feces Non Heat
SA521061P82972T3NHTSwine feces Non Heat
SA521062P82972T2NHTSwine feces Non Heat
SA521063P82972T0NHTSwine feces Non Heat
SA521064P81239T3NHTSwine feces Non Heat
SA521065P81239T2NHTSwine feces Non Heat
SA521066P81239T1NHTSwine feces Non Heat
SA521067P79697T3NHTSwine feces Non Heat
SA521068P83165T0HTSwine feces Non Heat
SA521069P79697T2NHTSwine feces Non Heat
SA521070P79697T1NHTSwine feces Non Heat
SA521071P79697T0NHTSwine feces Non Heat
SA521072P79416T2NHTSwine feces Non Heat
SA521073P79416T1NHTSwine feces Non Heat
SA521074P79416T0NHTSwine feces Non Heat
SA521075P76969T3NHTSwine feces Non Heat
SA521076P76969T2NHTSwine feces Non Heat
SA521077P83143T0HTSwine feces Non Heat
SA521078P88890T1HTSwine feces Non Heat
SA521079P83165T1HTSwine feces Non Heat
SA521080P84637T2NHTSwine feces Non Heat
SA521081P83165T2HTSwine feces Non Heat
SA521082P84660T1NHTSwine feces Non Heat
SA521083P84660T2NHTSwine feces Non Heat
SA521084P84660T3NHTSwine feces Non Heat
SA521085P84769T0HTSwine feces Non Heat
SA521086P87155T0HTSwine feces Non Heat
SA521087P87155T1HTSwine feces Non Heat
SA521088P87155T2HTSwine feces Non Heat
SA521089P87155T3HTSwine feces Non Heat
SA521090P87611T0NHTSwine feces Non Heat
SA521091P84637T0NHTSwine feces Non Heat
SA521092P84253T2NHTSwine feces Non Heat
SA521093P84253T0NHTSwine feces Non Heat
SA521094P83306T3HTSwine feces Non Heat
SA521095P83306T2HTSwine feces Non Heat
SA521096P83306T1HTSwine feces Non Heat
SA521097P83306T0HTSwine feces Non Heat
SA521098P83165T3HTSwine feces Non Heat
SA521099M88422T1HTSwine milk Heat
SA521100MO-5T3HTSwine milk Heat
SA521101M89021T3HTSwine milk Heat
SA521102M88890T1HTSwine milk Heat
SA521103M88698T1HTSwine milk Heat
SA521104M84769T1HTSwine milk Heat
SA521105M88020T1HTSwine milk Heat
SA521106M87798T1HTSwine milk Heat
SA521107M83109T2HTSwine milk Heat
SA521108M83143T2HTSwine milk Heat
SA521109M83165T3HTSwine milk Heat
SA521110M83306T3HTSwine milk Heat
SA521111M84253T1HTSwine milk Heat
SA521112M87155T3HTSwine milk Heat
SA521113MO-4T3NHTSwine milk Non Heat
SA521114M84637T2NHTSwine milk Non Heat
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Collection:

Collection ID:CO004541
Collection Summary:All samples were fecal, collected via fecal loop at 12:00 pm on sampling days, placed in individual sterile centrifuge tubes, and stored at −80 ◦C until further analyses. Sow milk was collected manually and immediately aliquot 1-2 mL into cryovials and stored at -80°C to maintain metabolite stability.
Sample Type:Feces, Milk
Storage Conditions:-80℃

Treatment:

Treatment ID:TR004557
Treatment Summary:During the trial, sows and their litters were exposed to controlled cyclical heat conditions until weaning (mean: 21.3 ± 1.1 days of age). Environmental parameters included nocturnal temperatures of 28.90 ± 2.6 ◦C and 49.29 ± 12.10% relative humidity (RH), and diurnal temperatures of 30.23 ± 1.31 ◦C with 48.75 ± 11.28% RH [6]. All sows were provided ad libitum access to water and a lactation diet based primarily on corn and soybean meal. Metagenomic samples were collected on days 4, 8, and 14 of lactation, while metatranscriptomic sampling was performed on days 1 and 18.

Sample Preparation:

Sampleprep ID:SP004554
Sampleprep Summary:Fecal samples were thawed, homogenized, and extracted with methanol:water (7:3, v/v) containing internal stan- dards. Samples underwent shaking, incubation, centrifugation, protein freeze-out, and LC-MS analysis. 50 μL of milk sample and 300 μL of the extraction solution (ACN : Methanol = 1:4, V/V) containing internal standards were mixed in a 2 mL microcentrifuge tube. The sample was vortexed for 3 min and then centrifuged at 12000 rpm for 10 min (4 °C). 200 μL of the supernatant was collected and placed in -20 °C for 30 min followed by centrifugation at 12000 rpm for 3 min (4 °C). A 180 μL aliquot of the supernatant was used for LC-MS analysis.

Chromatography:

Chromatography ID:CH005564
Instrument Name:ExionLC AD
Column Name:Waters ACQUITY UPLC HSS T3 (100 x 2.1mm,1.8um)
Column Temperature:40 °C
Flow Gradient:Over the time course, component A decreases from 95% at 0.0 minutes to 80% at 2.0 minutes, then to 40% at 5.0 minutes and reaches a minimum of 1% at 6.0 and 7.5 minutes, before rising back to 95% at 7.6 minutes and remaining at 95% at 10.0 minutes. Component B shows the opposite trend, increasing from 5% at 0.0 minutes to 20% at 2.0 minutes, then to 60% at 5.0 minutes, peaking at 99% at 6.0 and 7.5 minutes, before dropping back to 5% at 7.6 and 10.0 minutes
Flow Rate:0.40 mL/min
Solvent A:100% water; 0.1 % formic acid
Solvent B:100% acetonitrile; 0.1 % formic acid
Chromatography Type:Reversed phase
  
Chromatography ID:CH005565
Instrument Name:ExionLC AD
Column Name:Waters XBridge BEH Amide (100 x 2.1mm,2.5um)
Column Temperature:40 °C
Flow Gradient:Across the time course, component A starts high at 95% at 0.0 minutes, decreases to 80% at 2.0 minutes, drops further to 40% at 5.0 minutes, and reaches a minimum of 1% at both 6.0 and 7.5 minutes. It then rapidly returns to 95% at 7.6 minutes and stays at 95% at 10.0 minutes. In contrast, component B begins at 5%, rises to 20% at 2.0 minutes, increases to 60% at 5.0 minutes, then peaks at 99% at both 6.0 and 7.5 minutes, before dropping sharply back to 5% at 7.6 and remaining at 5% at 10.0 minutes.
Flow Rate:0.40 mL/min
Solvent A:60% acetonitrile/30 % water/10% methanol; 20 mM ammonium formate, pH 10.6
Solvent B:40% acetonitrile/60% water; 20 mM ammonium formate, pH 10.6
Chromatography Type:HILIC

Analysis:

Analysis ID:AN007332
Laboratory Name:Metware Biotechnology Inc.
Analysis Type:MS
Chromatography ID:CH005564
Num Factors:4
Num Metabolites:2918
Units:AU
  
Analysis ID:AN007333
Laboratory Name:Metware Biotechnology Inc.
Analysis Type:MS
Chromatography ID:CH005564
Num Factors:4
Num Metabolites:6413
Units:AU
  
Analysis ID:AN007334
Laboratory Name:Metware Biotechnology Inc.
Analysis Type:MS
Chromatography ID:CH005565
Num Factors:4
Num Metabolites:1188
Units:AU
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