Project description:Background: The soil environment is responsible for sustaining most terrestrial plant life on earth, yet we know surprisingly little about the important functions carried out by diverse microbial communities in soil. Soil microbes that inhabit the channels of decaying root systems, the detritusphere, are likely to be essential for plant growth and health, as these channels are the preferred locations of new root growth. Understanding the microbial metagenome of the detritusphere and how it responds to agricultural management such as crop rotations and soil tillage will be vital for improving global food production. Methods: The rhizosphere soils of wheat and chickpea growing under + and - decaying root were collected for metagenomics sequencing. A gene catalogue was established by de novo assembling metagenomic sequencing. Genes abundance was compared between bulk soil and rhizosphere soils under different treatments. Conclusions: The study describes the diversity and functional capacity of a high-quality soil microbial metagenome. The results demonstrate the contribution of the microbiome from decaying root in determining the metagenome of developing root systems, which is fundamental to plant growth, since roots preferentially inhabit previous root channels. Modifications in root microbial function through soil management, can ultimately govern plant health, productivity and food security.
Project description:Purpose: Deconstructing the soil microbiome into reduced-complexity functional modules represents a novel method of microbiome analysis. The goals of this study are to confirm differences in transcriptomic patterns among five functional module consortia. Methods: mRNA profiles of 3 replicates each of functional module enrichments of soil inoculum in M9 media with either 1) xylose, 2) n-acetylglucosamine, 3) glucose and gentamycin, 4) xylan, or 5) pectin were generated by sequencing using an Illumina platform (GENEWIZ performed sequencing). Sequence reads that passed quality filters were aligned to a soil metagenome using Burrows Wheeler Aligner. Resulting SAM files were converted to raw reads using HTSeq, and annotated using Uniref90 or EGGNOG databases. Results: To reduce the size of the RNA-Seq counts table and increase its computational tractability, transcripts containing a minimum of 75 total counts, but no more than 3 zero counts, across the 15 samples were removed. The subsequent dataset was normalized using DESeq2, resulting in a dataset consisting of 6947 unique transcripts across the 15 samples, and 185,920,068 reads. We identified gene categories that were enriched in a sample type relative to the overall dataset using Fisher’s exact test. Conclusions: our dataset confirms that the functional module consortia generated from targeted enrichments of a starting soil inoculum had distinct functional trends by enrichment type.
Project description:To understand 4-TU labelling kinetics in a novel zebrafish transgenic line (lf:UPRT), we exposed adult lf:UPRT zebrafish (whereby animals have hepatocyte-specific uracil phosphoribosyltransferase expression) with 4-TU for 1, 3, 6 and 9 hours. We then dissected adult livers for SLAM-ITseq to determine the optimal 4-TU labelling time in our SLAM-ITseq workflow to allow us to study hepatocyte-specific nascent transcriptional changes.
Project description:In high-throughput LC-MS/MS-based proteomics, information about the presence and stoichiometry of post-translational modifications is normally not readily available. To overcome this problem we developed multiFLEX-LF, a computational tool that builds upon FLEXIQuant and FLEXIQuant-LF, which detect modified peptides and quantify their modification extent by monitoring the differences between observed and expected intensities of the unmodified peptides. To this end, multiFLEX-LF relies on robust linear regression to calculate the modification extent of a given peptide relative to a within-study reference. multiFLEX-LF can analyze entire label-free discovery proteomics datasets. Furthermore, to analyze modification dynamics and co-regulated modifications, the peptides of all proteins are hierarchically clustered based on their computed relative modification scores. To demonstrate the versatility of multiFLEX-LF we applied it on a cell-cycle time series dataset acquired using data-independent acquisition. The clustering of the peptides highlighted several groups of peptides with different modification dynamics across the four analyzed time points providing evidence of the kinases involved in the cell-cycle. Overall, multiFLEX-LF enables fast identification of potentially differentially modified peptides and quantification of their differential modification extent in large datasets. Additionally, multiFLEX-LF can drive large-scale investigation of modification dynamics of peptides in time series and case-control studies. multiFLEX-LF is available at https://gitlab.com/SteenOmicsLab/multiflex-lf.
Project description:The experiment at three long-term agricultural experimental stations (namely the N, M and S sites) across northeast to southeast China was setup and operated by the Institute of Soil Science, Chinese Academy of Sciences. This experiment belongs to an integrated project (The Soil Reciprocal Transplant Experiment, SRTE) which serves as a platform for a number of studies evaluating climate and cropping effects on soil microbial diversity and its agro-ecosystem functioning. Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of soil type, soil transplant and landuse changes on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles.
Project description:Improvements in LC-MS/MS methods and technology have enabled the identification of thousands of modified peptides in a single experiment. However, protein regulation by post-translational modifications (PTMs) is not binary, making methods to quantify the modification extent crucial to fully understand the role of PTMs. Here, we introduce FLEXIQuant-LF, a software tool for large-scale identification of differentially modified peptides and quantification of their modification extent without prior knowledge of the type of modification. We developed FLEXIQuant-LF using label-free quantification of unmodified peptides and robust linear regression to quantify the modification extent of peptides. As proof of concept, we applied FLEXIQuant-LF to data-independent-acquisition (DIA) data of the anaphase promoting complex/cyclosome (APC/C) during mitosis. The unbiased approach of FLEXIQuant-LF to assess the modification extent in quantitative proteomics data provides a novel platform to better understand the function and regulation of PTMs in new experiments and reanalyzed data. The software is available at https://github.com/SteenOmicsLab/FLEXIQuantLF.