16S rRNA gene amplicons
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA576645 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11307400_1.fastq.gz | Fastqsanger.gz | |||
| SRR11307400_2.fastq.gz | Fastqsanger.gz | |||
| SRR11307500_1.fastq.gz | Fastqsanger.gz | |||
| SRR11307500_2.fastq.gz | Fastqsanger.gz | |||
| SRR11307401_1.fastq.gz | Fastqsanger.gz |
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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:Human skin microbiome dysbiosis can have clinical consequences. Characterizing taxonomic composition of bacterial communities associated with skin disorders is important for dermatological advancement in both diagnosis and novel treatments. This study aims to analyze and improve the accuracy of taxonomic classification of skin bacteria with MinION™ nanopore sequencing using a defined skin mock community and a skin microbiome sample. We compared the Oxford Nanopore Technologies recommended procedures and concluded that their protocols highly bias the relative abundance of certain skin microbiome genera, most notably a large overrepresentation of Staphylococcus and underrepresentation of Cutibacterium and Corynebacterium. We demonstrated that changes in the amplification protocols improved the accuracy of the taxonomic classification for these three main skin bacterial genera. This study shows that MinION™ nanopore could be an efficient technology for full-length 16S rRNA sequencing; however, the analytical advantage is strongly influenced by the methodologies. The suggested alternatives in the sample processing improved characterization of a complex skin microbiome community using MinION™ nanopore sequencing.
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Project description:As new sequencing technologies become cheaper and older ones disappear, laboratories switch vendors and platforms. Validating the new setups is a crucial part of conducting rigorous scientific research. Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform. We designed a protocol using 50 barcode pairs to run samples in parallel and coded a pipeline to process the data. Sequencing the same sediment sample in 248 replicates as well as 70 samples from alkaline soda lakes, we evaluated the performance of the method with regards to estimates of alpha and beta diversity. Using different purification and DNA quantification procedures we always found up to 5-fold differences in the yield of sequences between individually barcodes samples. Using either a one-step or a two-step PCR preparation resulted in significantly different estimates in both alpha and beta diversity. Comparing with a previous method based on 454 pyrosequencing, we found that our Illumina protocol performed in a similar manner - with the exception for evenness estimates where correspondence between the methods was low. We further quantified the data loss at every processing step eventually accumulating to 50% of the raw reads. When evaluating different OTU clustering methods, we observed a stark contrast between the results of QIIME with default settings and the more recent UPARSE algorithm when it comes to the number of OTUs generated. Still, overall trends in alpha and beta diversity corresponded highly using both clustering methods. Our procedure performed well considering the precisions of alpha and beta diversity estimates, with insignificant effects of individual barcodes. Comparative analyses suggest that 454 and Illumina sequence data can be combined if the same PCR protocol and bioinformatic workflows are used for describing patterns in richness, beta-diversity and taxonomic composition.
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Project description:Bacterial community composition in a native forest catchment
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Project description:Profiling of 16S rRNA gene sequences is an important tool for testing hypotheses in complex microbial communities, and analysis methods must be updated and validated as sequencing technologies advance. In host-associated bacterial communities, the V1-V3 region of the 16S rRNA gene is a valuable region to profile because it provides a useful level of taxonomic resolution; however, use of Illumina MiSeq data for experiments targeting this region needs validation.Using a MiSeq machine and the version 3 (300 × 2) chemistry, we sequenced the V1-V3 region of the 16S rRNA gene within a mock community. Nineteen bacteria and one archaeon comprised the mock community, and 12 replicate amplifications of the community were performed and sequenced. Sequencing the large fragment (490 bp) that encompasses V1-V3 yielded a higher error rate (3.6 %) than has been reported when using smaller fragment sizes. This higher error rate was due to a large number of sequences that occurred only one or two times among all mock community samples. Removing sequences that occurred one time among all samples (singletons) reduced the error rate to 1.4 %. Diversity estimates of the mock community containing all sequences were inflated, whereas estimates following singleton removal more closely reflected the actual mock community membership. A higher percentage of the sequences could be taxonomically assigned after singleton and doubleton sequences were removed, and the assignments reflected the membership of the input DNA.Sequencing the V1-V3 region of the 16S rRNA gene on the MiSeq platform may require additional sequence curation in silico, and improved error rates and diversity estimates show that removing low-frequency sequences is reasonable. When datasets have a high number of singletons, these singletons can be removed from the analysis without losing statistical power while reducing error and improving microbiota assessment.
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Project description:BackgroundThe miniaturised and portable DNA sequencer MinION™ has been released to the scientific community within the framework of an early access programme to evaluate its application for a wide variety of genetic approaches. This technology has demonstrated great potential, especially in genome-wide analyses. In this study, we tested the ability of the MinION™ system to perform amplicon sequencing in order to design new approaches to study microbial diversity using nearly full-length 16S rDNA sequences.ResultsUsing R7.3 chemistry, we generated more than 3.8 million events (nt) during a single sequencing run. These data were sufficient to reconstruct more than 90 % of the 16S rRNA gene sequences for 20 different species present in a mock reference community. After read mapping and 16S rRNA gene assembly, consensus sequences and 2d reads were recovered to assign taxonomic classification down to the species level. Additionally, we were able to measure the relative abundance of all the species present in a mock community and detected a biased species distribution originating from the PCR reaction using 'universal' primers.ConclusionsAlthough nanopore-based sequencing produces reads with lower per-base accuracy compared with other platforms, the MinION™ DNA sequencer is valuable for both high taxonomic resolution and microbial diversity analysis. Improvements in nanopore chemistry, such as minimising base-calling errors and the nucleotide bias reported here for 16S amplicon sequencing, will further deliver more reliable information that is useful for the specific detection of microbial species and strains in complex ecosystems.
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Project description:The importance of 16S rRNA gene amplicon profiles for understanding the influence of microbes in a variety of environments coupled with the steep reduction in sequencing costs led to a surge of microbial sequencing projects. The expanding crowd of scientists and clinicians wanting to make use of sequencing datasets can choose among a range of multipurpose software platforms, the use of which can be intimidating for non-expert users. Among available pipeline options for high-throughput 16S rRNA gene analysis, the R programming language and software environment for statistical computing stands out for its power and increased flexibility, and the possibility to adhere to most recent best practices and to adjust to individual project needs. Here we present the Rhea pipeline, a set of R scripts that encode a series of well-documented choices for the downstream analysis of Operational Taxonomic Units (OTUs) tables, including normalization steps, alpha- and beta-diversity analysis, taxonomic composition, statistical comparisons, and calculation of correlations. Rhea is primarily a straightforward starting point for beginners, but can also be a framework for advanced users who can modify and expand the tool. As the community standards evolve, Rhea will adapt to always represent the current state-of-the-art in microbial profiles analysis in the clear and comprehensive way allowed by the R language. Rhea scripts and documentation are freely available at https://lagkouvardos.github.io/Rhea.
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Project description:Anthropogenic impacts on microbial communities of boreal forest soils
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Project description:The applicability of next generation DNA sequencing (NGS) methods for water quality assessment has so far not been broadly investigated. This study set out to evaluate the potential of an NGS-based approach in a complex catchment with importance for drinking water abstraction. In this multi-compartment investigation, total bacterial communities in water, faeces, soil, and sediment samples were investigated by 454 pyrosequencing of bacterial 16S rRNA gene amplicons to assess the capabilities of this NGS method for (i) the development and evaluation of environmental molecular diagnostics, (ii) direct screening of the bulk bacterial communities, and (iii) the detection of faecal pollution in water. Results indicate that NGS methods can highlight potential target populations for diagnostics and will prove useful for the evaluation of existing and the development of novel DNA-based detection methods in the field of water microbiology. The used approach allowed unveiling of dominant bacterial populations but failed to detect populations with low abundances such as faecal indicators in surface waters. In combination with metadata, NGS data will also allow the identification of drivers of bacterial community composition during water treatment and distribution, highlighting the power of this approach for monitoring of bacterial regrowth and contamination in technical systems.
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Project description:The analysis of 16S-rDNA sequences to assess the bacterial community composition of a sample is a widely used technique that has increased with the advent of high throughput sequencing. Although considerable effort has been devoted to identifying the most informative region of the 16S gene and the optimal informatics procedures to process the data, little attention has been paid to the PCR step, in particular annealing temperature and primer length. To address this, amplicons derived from 16S-rDNA were generated from chicken caecal content DNA using different annealing temperatures, primers and different DNA extraction procedures. The amplicons were pyrosequenced to determine the optimal protocols for capture of maximum bacterial diversity from a chicken caecal sample. Even at very low annealing temperatures there was little effect on the community structure, although the abundance of some OTUs such as Bifidobacterium increased. Using shorter primers did not reveal any novel OTUs but did change the community profile obtained. Mechanical disruption of the sample by bead beating had a significant effect on the results obtained, as did repeated freezing and thawing. In conclusion, existing primers and standard annealing temperatures captured as much diversity as lower annealing temperatures and shorter primers.
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