Unknown

Dataset Information

0

Soil Metabolomics Predict Microbial Taxa as Biomarkers of Moisture Status in Soils from a Tidal Wetland.


ABSTRACT: We present observations from a laboratory-controlled study on the impacts of extreme wetting and drying on a wetland soil microbiome. Our approach was to experimentally challenge the soil microbiome to understand impacts on anaerobic carbon cycling processes as the system transitions from dryness to saturation and vice-versa. Specifically, we tested for impacts on stress responses related to shifts from wet to drought conditions. We used a combination of high-resolution data for small organic chemical compounds (metabolites) and biological (community structure based on 16S rRNA gene sequencing) features. Using a robust correlation-independent data approach, we further tested the predictive power of soil metabolites for the presence or absence of taxa. Here, we demonstrate that taking an untargeted, multidimensional data approach to the interpretation of metabolomics has the potential to indicate the causative pathways selecting for the observed bacterial community structure in soils.

SUBMITTER: RoyChowdhury T 

PROVIDER: S-EPMC9416152 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

Soil Metabolomics Predict Microbial Taxa as Biomarkers of Moisture Status in Soils from a Tidal Wetland.

RoyChowdhury Taniya T   Bramer Lisa M LM   Brown Joseph J   Kim Young-Mo YM   Zink Erika E   Metz Thomas O TO   McCue Lee Ann LA   Diefenderfer Heida L HL   Bailey Vanessa V  

Microorganisms 20220816 8


We present observations from a laboratory-controlled study on the impacts of extreme wetting and drying on a wetland soil microbiome. Our approach was to experimentally challenge the soil microbiome to understand impacts on anaerobic carbon cycling processes as the system transitions from dryness to saturation and vice-versa. Specifically, we tested for impacts on stress responses related to shifts from wet to drought conditions. We used a combination of high-resolution data for small organic ch  ...[more]

Similar Datasets

| S-EPMC4591843 | biostudies-literature
| S-EPMC6544822 | biostudies-literature
| S-EPMC6557889 | biostudies-literature
| S-EPMC6863828 | biostudies-literature
| S-EPMC9530717 | biostudies-literature
| S-EPMC6013439 | biostudies-literature
2014-09-12 | GSE61338 | GEO
| S-EPMC3114181 | biostudies-literature
2014-09-12 | E-GEOD-61338 | biostudies-arrayexpress
2014-12-10 | E-MTAB-2920 | biostudies-arrayexpress