Project description:Healthy plants are vital for successful, long-duration missions in space, as they provide the crew with life support, food production, and psychological benefits. The microorganisms that associate with plant tissues play a critical role in improving plant growth, health, and production. To that end, it is necessary to develop methodologies that investigate the metabolic activities of the plant’s microbiome in orbit to enable rapid responses regarding the care of plants in space. In this study, we developed a protocol to characterize the endophytic and epiphytic microbial metatranscriptome of red romaine lettuce, a key salad crop that was grown under International Space Station (ISS)-like conditions. Microbial transcripts enriched from host-microbe total RNA were sequenced using the Oxford Nanopore MinION sequencing platform. Results showed that this enrichment approach was highly reproducible and effective for rapid on-site detection of microbial transcriptional activity. Taxonomic analysis based on 16S and 18S rRNA transcripts identified that the top five most abundant phyla in the lettuce microbiome were Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, and Ascomycota. The metatranscriptomic analysis identified the expression of genes involved in many metabolic pathways, including carbohydrate metabolism, energy metabolism, and signal transduction. Network analyses of the expression data show that, within the signal transduction pathway of the fungal community, the Mitogen-Activated Protein Kinase signaling pathway was tightly regulated across all samples and could be a potential driver for fungal proliferation. Our results demonstrated the feasibility of using MinION-based metatranscriptomics of enriched microbial RNA as a method for rapid, on-site monitoring of the transcriptional activity of crop microbiomes, thereby helping to facilitate and maintain plant health for on-orbit space food production.
Project description:We report the use of high-throughput sequencing technology to detect the microbial composition and abundance of mice grastic contents before and after Helicobacter pylori infection or Lactobacillus paracasei ZFM54 pretreatment/treatment. The genomic DNA was obtained by the QIAamp PowerFecal DNA Kit. Then, the DNA samples were sent to BGI Genomics Co., Ltd. (Shenzhen, China) for V3-V4 region of the 16S rRNA gene high-throughput sequencing with an Illumina MiSeq platform. DNA samples were sequenced using primers 338F (forward primer sequence ACTCCTACGGGAGGCAGCAG)-806R (reverse primer sequence GGACTACHVGGGTWTCTAAT). The sequencing analyses were carried out using silva138/16s database as a reference for the assignation of Amplicon Sequence Variant (ASV) at 100% similarity.
Project description:Sensitive models of climate change impacts would require a better integration of multi-omics approaches that connect the abundance and activity of microbial populations. Here, we show that climate is a fundamental driver of the protein abundance of microbial populations (metaproteomics), yet not their genomic abundance (16S rRNA gene amplicon sequencing), supporting the hypothesis that metabolic activity may be more closely linked to climate than community composition.
Project description:16S rRNA gene metabarcoding reveals a potential metabolic role for intracellular bacteria in a major marine planktonic calcifier (Foraminifera).
Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.
2017-05-12 | PXD006118 | Pride
Project description:Comparative analysis of MinION and MiSeq using 16S rRNA Gene Amplicon sequencing in human gut microbiome
| PRJNA1058165 | ENA
Project description:16S rRNA gene-based bacterial identification using ONT MinION sequencing