16S rRNA gene amplicon time-series in BBMO
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB38773 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR4234280_1.fastq.gz | Fastqsanger.gz | |||
| ERR4234280_2.fastq.gz | Fastqsanger.gz | |||
| ERR4234290_1.fastq.gz | Fastqsanger.gz | |||
| ERR4234290_2.fastq.gz | Fastqsanger.gz | |||
| ERR4234300_1.fastq.gz | Fastqsanger.gz |
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Project description:Microbial amplicon sequencing studies are an important tool in biological and biomedical research. Widespread 16S rRNA gene microbial surveys have shed light on the structure of many ecosystems inhabited by bacteria, including the human body. However, specialized software and algorithms are needed to convert raw sequencing data into biologically meaningful information (i.e. tables of bacterial counts). While different bioinformatic pipelines are available in a rapidly changing and improving field, users are often unaware of limitations and biases associated with individual pipelines and there is a lack of agreement regarding best practices. Here, we compared six bioinformatic pipelines for the analysis of amplicon sequence data: three OTU-level flows (QIIME-uclust, MOTHUR, and USEARCH-UPARSE) and three ASV-level (DADA2, Qiime2-Deblur, and USEARCH-UNOISE3). We tested workflows with different quality control options, clustering algorithms, and cutoff parameters on a mock community as well as on a large (N = 2170) recently published fecal sample dataset from the multi-ethnic HELIUS study. We assessed the sensitivity, specificity, and degree of consensus of the different outputs. DADA2 offered the best sensitivity, at the expense of decreased specificity compared to USEARCH-UNOISE3 and Qiime2-Deblur. USEARCH-UNOISE3 showed the best balance between resolution and specificity. OTU-level USEARCH-UPARSE and MOTHUR performed well, but with lower specificity than ASV-level pipelines. QIIME-uclust produced large number of spurious OTUs as well as inflated alpha-diversity measures and should be avoided in future studies. This study provides guidance for researchers using amplicon sequencing to gain biological insights.
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Project description:Primers targeting the 16S small subunit ribosomal RNA marker gene, used to characterize bacterial and archaeal communities, have recently been re-evaluated for marine planktonic habitats. To investigate whether primer selection affects the ecological interpretation of bacterioplankton populations and community dynamics, amplicon sequencing with four primer sets targeting several hypervariable regions of the 16S rRNA gene was conducted on both mock communities constructed from cloned 16S rRNA genes and a time-series of DNA samples from the temperate coastal Santa Barbara Channel. Ecological interpretations of community structure (delineation of depth and seasonality, correlations with environmental factors) were similar across primer sets, while population dynamics varied. We observed substantial differences in relative abundances of taxa known to be poorly resolved by some primer sets, such as Thaumarchaeota and SAR11, and unexpected taxa including Roseobacter clades. Though the magnitude of relative abundances of common OTUs differed between primer sets, the relative abundances of the OTUs were nonetheless strongly correlated. We do not endorse one primer set but rather enumerate strengths and weaknesses to facilitate selection appropriate to a system or experimental goal. While 16S rRNA gene primer bias suggests caution in assessing quantitative population dynamics, community dynamics appear robust across studies using different primers.
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Project description:Background16S rRNA amplicon sequencing is an accurate method of detecting microbial infection without culture. It is unclear if sequencing has additional benefits over routine diagnostic methods for Helicobacter pylori testing.MethodsWe enrolled Mongolian volunteers with dyspepsia. Using routine diagnostic methods, positive H. pylori was defined as positive results on histology/immunohistochemistry, culture, rapid urease test, or serology; negative H. pylori was defined by negative results from all these tests. We performed 16S rRNA sequencing on gastric biopsy specimens and calculated cutoffs for operational taxonomic units (OTUs) and relative abundance (RA) to define positive results using ROC curves.ResultsWe examined 161 individuals with a mean age of 43.6 years, and 64.6% were women. Using routine diagnostic methods, 122 (75.8%) participants were H. pylori positive, the sensitivity and specificity for 16S rRNA sequencing were 94.3% and 82.1% or 93.4% and 82.1% when cutoff values were set to 1113 (OTU number) or 4.4% RA, respectively (both p < .001). When combining the validated values, the concordance rate was high (91.1%); however, 16S rRNA sequencing had additional positive yield in 9 cases (5.6%) compared with routine diagnostic methods, and much greater additional positive yield compared to histopathology/IHC, culture, RUT, serology separately with 12 (7.4%), 37 (23.0%) and 43 (26.7%).Conclusion16S rRNA amplicon sequencing detects potentially important proportion of H. pylori-positive cases that test negative with routine diagnostic methods. The quantitative number of H. pylori can help to understand how it can be changing by diseases and RA give opportunity to understand how H. pylori communicate with other microbiota.
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