Project description:The goal of this growth chamber experiment was to investigate the effects of diverse soil microbial communities on the transcriptional responses of plants to drought. Specifically, we sought to understand how soil microbiomes' past exposure to water-limited conditions (either long-term exposure to dry conditions in low-precipitation sites, or recent acute drought) impacted their interactions with plants. Six soils collected from remnant prairies crossing a steep precipitation gradient in Kansas, USA were used as the starting microbial communities. Thirty-two pots (or mesocosms) of each soil were divided among four treatments: droughted or well-watered, and with or without a host plant (Tripsacum dactyloides) in a factorial design. The soil mesocosms were "conditioned" in these treatments for five months. (Metagenome and metatranscriptome data from the baseline soils and the post-conditioning soils are available in a separate BioProject on NCBI SRA and GEO). Then, a microbial slurry extracted from each of the 192 conditioned soils was used to inoculate 4 plants in a subsequent experiment (the “Test Phase”): one pot per combination of watering treatment (droughted or control) and host species (Zea mays or Tripsacum dactyloides). After 4 weeks (for maize) or 5 weeks (for eastern gamagrass) we harvested one crown root per plant for 16S rRNA sequencing and another crown root for RNA-seq. The 16S and RNA-seq data for these plants (both species) are contained in this BioProject. Note that 16S rRNA sequencing data are available for all plants in this experiment, but we conducted RNA-seq only for a subset (all plants grown in microbiomes originating from the 2 driest and 2 wettest collection sites).
Project description:The goal of this growth chamber experiment was to investigate the effects of diverse soil microbial communities on the transcriptional responses of plants to drought. Specifically, we sought to understand how soil microbiomes' past exposure to water-limited conditions (either long-term exposure to dry conditions in low-precipitation sites, or recent acute drought) impacted their interactions with plants. Six soils collected from remnant prairies crossing a steep precipitation gradient in Kansas, USA were used as the starting microbial communities. Thirty-two pots (or mesocosms) of each soil were divided among four treatments: droughted or well-watered, and with or without a host plant (Tripsacum dactyloides) in a factorial design. The soil mesocosms were "conditioned" in these treatments for five months. (Metagenome and metatranscriptome data from the baseline soils and the post-conditioning soils are available in a separate BioProject on NCBI SRA and GEO). Then, a microbial slurry extracted from each of the 192 conditioned soils was used to inoculate 4 plants in a subsequent experiment (the “Test Phase”): one pot per combination of watering treatment (droughted or control) and host species (Zea mays or Tripsacum dactyloides). After 4 weeks (for maize) or 5 weeks (for eastern gamagrass) we harvested one crown root per plant for 16S rRNA sequencing and another crown root for RNA-seq. The 16S and RNA-seq data for these plants (both species) are contained in this BioProject. Note that 16S rRNA sequencing data are available for all plants in this experiment, but we conducted RNA-seq only for a subset (all plants grown in microbiomes originating from the 2 driest and 2 wettest collection sites).
Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities
Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities We used lignin degradation as a model process to demonstrate the use of an oligonucleotide microarray for directly detecting gene expression in soil communities using signal amplification instead of template amplification to avoid the introduction of PCR bias. In the current study, we analyzed mRNA isolated from two distinct soil microbial communities and demonstrate our ability to detect the expression of a small subset of lignin degrading genes following exposure to a lignitic substrate. We also included purified control amplicons and mixed target experiments with pure P. chrysosporium genomic cDNA to determine the level of interference from soil biomass on target hybridization.