Project description:DNA, RNA and protein were extracted from the culture and subjected to massive parallel sequencing and nano-LC-MS-MS respectively Combination of these methods enabled the reconstruction of the complete genome sequence of M oxyfera from the metagenome and identification of the functionally relevant enzymes and genes
Project description:Metagenome sequencing All specimens were collected and immediately stored in a -80 freezer. All BALF samples were subjected to MS. DNA was extracted from BALF using the TIANamp Micro DNA kit (DP316, Tiangen Biotech). DNA libraries were constructed with the end-repair method and then sequenced on the BGI Sequencer platform (BGI Genomics, Shenzhen, China). Bioinformatic pipeline analysis Low-quality and short (<35 bp) reads were removed from raw data using fastp [10]. Remaining reads were mapped to the human reference genome (hg19) using the Burrows-Wheeler method to remove sequences of human origin. Filtered reads were classified with RefSeq, downloaded from NCBI (ftp://ftp.ncbi.nlm.nih.gov/genomes/).
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:This data set contains 1376 mass spectrometry reads from root, rhizosphere and leaf sample of Populus Trichocarpa, as well as associated controls. This metabolomics data set was collected as part of a larger campaign which complements the metabolomics data with metagenome sequencing, transcriptomics, and soil measurement data.
Project description:Sequencing the metatranscriptome can provide information about the response of organisms to varying environmental conditions. We present a methodology for obtaining random whole-community mRNA from a complex microbial assemblage using Pyrosequencing. The metatranscriptome had, with minimum contamination by ribosomal RNA, significant coverage of abundant transcripts, and included significantly more potentially novel proteins than in the metagenome. Keywords: metatranscriptome, mesocosm, ocean acidification
Project description:This study investigated microbial communities from two wastewater treatment plants (WWTPs) for their potential to degrade PET and investigated enzymes likely involved in its degradation. Activated sludge from urban and industrial WWTPs was analyzed using whole metagenome sequencing and metaproteomics to characterize biofilms and their expressed enzymes.
Project description:This data set contains 1376 mass spectrometry reads from root, rhizosphere and leaf sample of Populus Trichocarpa, as well as associated controls. This metabolomics data set was collected as part of a larger campaign which complements the metabolomics data with metagenome sequencing, transcriptomics, and soil measurement data.
Project description:Metagenome data from soil samples were collected at 0 to 10cm deep from 2 avocado orchards in Channybearup, Western Australia, in 2024. Amplicon sequence variant (ASV) tables were constructed based on the DADA2 pipeline with default parameters.
Project description:This dataset was utilized to assess the performance of a novel de novo metaproteomics pipeline, which performs sequence alignment of de novo sequences from complete metaproteomics experiments. Traditionally, metaproteomics data annotation relies on database searching that requires sample-specific databases derived from whole metagenome sequencing experiments. Creating these databases, however, is a complex, time-consuming, and error prone process, which can introduce biases affecting the outcomes and conclusions, highlighting the need for alternative methods. The evaluated approach offers rapid and orthogonal insights into metaproteomics data.