128-2 Response of Microbial Transcriptome, Proteome, and Activity to Rainfall Pulses in a Prairie Soil.

Poster Number 1214

See more from this Division: S03 Soil Biology & Biochemistry
See more from this Session: Soil Metagenomics
Monday, October 22, 2012
Duke Energy Convention Center, Exhibit Hall AB, Level 1
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Charles Rice1, Lydia Zeglin2, Peter Bottomley2, Nathaniel l. Tisdell2, Ari Jumpponen3, Maude M. David4, Emmanuel Prestat3, Janet K. Jansson5, Susannah G. Tringe6, Nathan VerBerkmoes7, Robert L. Hettich7, Andrew W. McGowan8, Priscilla Mfombep9, Miguel Arango1 and David Myrold2, (1)Agronomy, Kansas State University, Manhattan, KS
(2)Oregon State University, Corvallis, OR
(3)Division of Biology, Kansas State University, Manhattan, KS
(4)Departement of Ecology, Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA
(5)Department of Ecology, Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA
(6)DOE Joint Genome Institute, Walnut Creek, CA
(7)Oak Ridge National Laboratory, Oak Ridge, TN
(8)Department of Agronomy, Kansas State University, Manhattan, KS
(9)Kansas State University, Manhattan, KS
A significant amount of carbon (C) is processed and stored in prairie soils: grasslands cover 6.1-7.4% of the earth’s land surface and hold 7.3-11.4% of global soil C. Global change models predict that the future precipitation regime across the North American Great Plains will entail less frequent but larger rainfall events. The response of prairie soil microbial C processing and allocation to this scenario of higher hydrologic variability is not known, but will be a key determinant of the future capacity for prairie soil C sequestration. We are approaching this problem by assessing soil microbial function (respiration, C utilization efficiency, extracellular enzyme activity) and molecular indicators of dominant C allocation pathways (soil transcriptome and proteome) under ambient and experimentally modified precipitation regimes. The Rainfall Manipulation Plots (RaMPs) at the Konza Prairie Long-Term Ecological Research site in north-eastern Kansas, USA is a replicated field manipulation of the timing and magnitude of natural precipitation that was established in 1998. This experiment does not modify the total amount of growing season rainfall; it imposes extended dry periods with larger, less frequent rainfall events to simulate more “droughty” conditions. We collected soil before, during, and after rainfall events in both ambient and “droughty” treatments and measured microbial growth, respiration, and potential organic matter degradation responses. Notable results include: (1) Equivalent rainfall events caused equivalent microbial respiration responses in ambient and “droughty” treatments, but biomass increased after the rainfall in the “droughty” plots only. This implies a greater C use efficiency, or greater potential for belowground C retention, in “droughty” soils. (2) C:N ratio of biomass increased as soil water content decreased. This implies a physiological and/or population-level shift in the microbiota at lower soil water contents. (3) Extracellular enzyme activities shifted seasonally, but the greatest response was to the rainfall pulse in June, which resulted in increased activities of cellulolytic and proteolytic enzymes. This suggests a stimulation of degradation of readily available organic matter at this time. (4) Initial proteome data suggested shifts in proteins expressed in ambient vs. “droughty” soil. Collectively, these results lead to hypotheses regarding microbial physiological adaptation to drought stress in prairie soils. Additional molecular data (454 sequencing and QPCR of bacterial 16S rRNA and fungal ribosomal genes and transcripts, full transcriptomes, and proteomes) will be used to test these hypotheses: (H1) Microbial taxa that respond quickly to rainfall are more active in “droughty” soil with an altered precipitation regime history. (H2) Transcripts and proteins from COGs indicative of growth will be more abundant after rainfall in the “droughty” plots. (H3) In soils with low water contents, transcripts and proteins driving compatible solute production will be more abundant, whereas those associated with amino acid and sugar transport will respond to wetting. (H4) In soils with low water contents, fungi will be more abundant. Directly addressing these mechanistic hypotheses would not be possible without “omics” approaches.
See more from this Division: S03 Soil Biology & Biochemistry
See more from this Session: Soil Metagenomics