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.
Project description:To determine whether and how warming affects the functional capacities of the active microbial communities, GeoChip 5.0 microarray was used. Briefly, four fractions of each 13C-straw sample were selected and regarded as representative for the active bacterial community if 16S rRNA genes of the corresponding 12C-straw samples at the same density fraction were close to zero.
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:The characterization of microbial community structure via 16S rRNA gene profiling has been greatly advanced in recent years by the application of amplicon pyrosequencing. The possibility of barcode-tagged sequencing of templates gives the opportunity to massively screen multiple samples from environmental or clinical sources for community details. However, an on-going debate questions the reproducibility and semi-quantitative rigour of pyrotag sequencing and, as in the early days of genetic community fingerprinting, pros and cons are continuously provided. In this study we investigate the reproducibility of bacterial 454 pyrotag sequencing over biological and technical replicates of natural microbiota. Moreover, via quantitatively defined template spiking to the natural community, we explore the potential for recovering specific template ratios within complex microbial communities. For this reason, we pyrotag sequenced three biological replicates of three samples, each belonging from yearly sampling campaigns of sediment from a tar oil contaminated aquifer in Düsseldorf, Germany. Furthermore, we subjected one DNA extract to replicate technical analyses as well as to increasing ratios (0, 0.2, 2 and 20%) of 16S rRNA genes from a pure culture (Aliivibrio fisheri) originally not present in the sample. Unexpectedly, taxa abundances were highly reproducible in our hands, with max standard deviation of ~3% abundance across biological and ~2% for technical replicates. Furthermore, our workflow was also capable of recovering A. fisheri amendmend ratios in reliable amounts (0, 0.29, 3.9 and 23.8%). These results highlight that pyrotag sequencing, if done and evaluated with due caution, has the potential to robustly recapture taxa template abundances within environmental microbial communities. 9 Biological and 3 technical replicates were evaluated, as well as potential to recover qPCR-defined ratios of DNA, in 454 pyrotag sequencing
Project description:We aimed to investigate the microbial community composition in patients with intracerebral hemorrhage (ICH) and its effect on prognosis. The relationship between changes in bacterial flora and the prognosis of spontaneous cerebral hemorrhage was studied in two cohort studies. Fecal samples from healthy volunteers and patients with intracerebral hemorrhage were subjected to 16S rRNA sequencing at three time points: T1 (within 24 hours of admission), T2 (3 days post-surgery), and T3 (7 days post-surgery) using Illumina high-throughput sequencing technology.
Project description:Despite the global importance of forests, it is virtually unknown how their soil microbial communities adapt at the phylogenetic and functional level to long term metal pollution. Studying twelve sites located along two distinct gradients of metal pollution in Southern Poland revealed that both community composition (via MiSeq Illumina sequencing of 16S rRNA genes) and functional gene potential (using GeoChip 4.2) were highly similar across the gradients despite drastically diverging metal contamination levels. Metal pollution level significantly impacted microbial community structure (p = 0.037), but not bacterial taxon richness. Metal pollution altered the relative abundance of specific bacterial taxa, including Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Planctomycetes and Proteobacteria. Also, a group of metal resistance genes showed significant correlations with metal concentrations in soil, although no clear impact of metal pollution levels on overall functional diversity and structure of microbial communities was observed. While screens of phylogenetic marker genes, such as 16S rRNA, provided only limited insight into resilience mechanisms, analysis of specific functional genes, e.g. involved in metal resistance, appeared to be a more promising strategy. This study showed that the effect of metal pollution on soil microbial communities was not straightforward, but could be filtered out from natural variation and habitat factors by multivariate statistical analysis and spatial sampling involving separate pollution gradients.
Project description:Sequencing of 16S ribosomal RNA (rRNA) gene, which has improved the characterization of microbial community, has made it possible to detect a low level Helicobacter pylori (HP) sequences even in HP-negative subjects which were determined by a combination of conventional methods. This study was conducted to obtain a cutoff value for HP colonization in gastric mucosa biopsies and gastric juices by the pyrosequencing method. Corresponding author: Department of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam, Gyeonggi-do, Korea; Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea (Tel., +82-31-787-7008; e-mail, nayoungkim49@empas.com). Microbial DNA from gastric mucosal samples [gastric antrum (n=63, mucosal biopsy), follow-up sample on gastric antrum (n=16, mucosal biopsy), and gastric body (n=18, mucosal biopsy)] and gastric juices (n=4, not mucosal biopsy) was amplified by nested PCR using universal bacterial primers, and the 16S rRNA genes were pyrosequenced.
Project description:This study in rats was designed to investigate whether whole rhye (WR) can influence the metabolism of n-3 and n-6 long-chain fatty acids (LCFA) and gut microbiota composition. For 12 weeks, rats were fed a diet containing either 50% WR or 50% refined rye (RR). Total bacterial DNA was extracted from fecal and cecal samples (n=5 per group). 16S PCR amplification was performed to assess the microbial diversity at the family level using the HuGChip. Amplified DNA was purified and labelled with either Cy3 or Cy5 dye and hybridized on the microarray. A 15 chip study was realized, each corresponding to hybridization with 250ng of labelled 16S rRNA gene amplicons from either mice fecal and cecal samples. Each probe (4441) was synthetized in three replicates.
Project description:Investigation of microbial community composition in mouse models using an intestinal epithial-specific and inducible VilCreERT2-mediated conditional knockout of Jup under basal conditions and in acute dextran-sodium sulfate (DSS)-induced colitis We investigated the gut microbiome composition in a dextran sulfate sodium (DSS) colitis model using Jupfl/fl and iVilCreERT2Jupfl/fl mice. Fecal samples were collected after DSS treatment, and 16S rRNA sequencing was employed to analyze microbial communities. Our findings revealed no significant differences in microbial profiles between Jupfl/fl and iVilCreERT2Jupfl/fl under DSS treatment.
Project description:Humans and animals encounter a summation of exposures during their lifetime (the exposome). In recent years, the scope of the exposome has begun to include microplastics. Microplastics (MPs) have increasingly been found in locations where there could be an interaction with Salmonella enterica Typhimurium, one of the commonly isolated serovars from processed chicken. In this study, the microbiota response to a 24-hour co-exposure to Salmonella enterica Typhimurium and/or low-density polyethylene (PE) microplastics in an in vitro broiler cecal model was determined using 16S rRNA amplicon sequencing (Illumina) and untargeted metabolomics. Community sequencing results indicated that PE fiber with and without S. Typhimurium yielded a lower Firmicutes/Bacteroides ratio compared to other treatment groups, which is associated with poor gut health, and overall had greater changes to the cecal microbial community composition. However, changes in the total metabolome were primarily driven by the presence of S. Typhimurium. Additionally, the co-exposure to PE Fiber and S. Typhimurium caused greater cecal microbial community and metabolome changes than either exposure alone. Our results indicate that polymer shape is an important factor in effects resulting from exposure. It also demonstrates that microplastic-pathogen interactions cause metabolic alterations to the chicken cecal microbiome in an in vitro chicken cecal model.