Nested PCR strategy for rpoB metabarcoding studies
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ABSTRACT:
PROVIDER: PRJEB81812 | ENA |
REPOSITORIES: ENA
Similar Datasets
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Project description:The molecular diversity of marine picocyanobacterial populations, an important component of phytoplankton communities, is better characterized using high-resolution marker genes than the 16S rRNA gene as they have greater sequence divergence to differentiate between closely related picocyanobacteria groups. Although specific ribosomal primers have been developed, another general disadvantage of bacterial ribosome-based diversity analyses is the variable number of rRNA gene copies. To overcome these issues, the single-copy petB gene, encoding the cytochrome b6 subunit of the cytochrome b6f complex, has been used as a high-resolution marker gene to characterize Synechococcus diversity. We have designed new primers targeting the petB gene and proposed a nested PCR method (termed Ong_2022) for metabarcoding of marine Synechococcus populations obtained by flow cytometry cell sorting. We evaluated the specificity and sensitivity of Ong_2022 against the standard amplification protocol (termed Mazard_2012) using filtered seawater samples. The Ong_2022 approach was also tested on flow cytometry-sorted Synechococcus populations. Samples (filtered and sorted) were obtained in the Southwest Pacific Ocean, from subtropical (ST) and subantarctic (SA) water masses. The two PCR approaches using filtered samples recovered the same dominant subclades, Ia, Ib, IVa, and IVb, with small differences in relative abundance across the distinct samples. For example, subclade IVa was dominant in ST samples with the Mazard_2012 approach, while the same samples processed with Ong_2022 showed similar contributions of subclades IVa and Ib to the total community. The Ong_2022 approach generally captured a higher genetic diversity of Synechococcus subcluster 5.1 than the Mazard_2012 approach while having a lower proportion of incorrectly assigned amplicon sequence variants (ASVs). All flow cytometry-sorted Synechococcus samples could be amplified only by our nested approach. The taxonomic diversity obtained with our primers on both sample types was in agreement with the clade distribution observed by previous studies that applied other marker genes or PCR-free metagenomic approaches under similar environmental conditions. IMPORTANCE The petB gene has been proposed as a high-resolution marker gene to access the diversity of marine Synechococcus populations. A systematic metabarcoding approach based on the petB gene would improve the characterization/assessment of the Synechococcus community structure in marine planktonic ecosystems. We have designed and tested specific primers to be applied in a nested PCR protocol (Ong_2022) for metabarcoding the petB gene. The Ong_2022 protocol can be applied to samples with low DNA content, such as those obtained by flow cytometry cell sorting, allowing the simultaneous assessment of the genetic diversity of Synechococcus populations and cellular properties and activities (e.g., nutrient cell ratios or carbon uptake rates). Our approach will allow future studies using flow cytometry to investigate the link between ecological traits and taxonomic diversity of marine Synechococcus.
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Project description:Understanding the structure and interplay of cellular signalling pathways is one of the great challenges in molecular biology. Boolean Networks can infer signalling networks from observations of protein activation. In situations where it is difficult to assess protein activation directly, Nested Effect Models are an alternative. They derive the network structure indirectly from downstream effects of pathway perturbations. To date, Nested Effect Models cannot resolve signalling details like the formation of signalling complexes or the activation of proteins by multiple alternative input signals. Here we introduce Boolean Nested Effect Models (B-NEM). B-NEMs combine the use of downstream effects with the higher resolution of signalling pathway structures in Boolean Networks. We show that B-NEMs accurately reconstruct signal flows in simulated data. Using B-NEM we then resolve BCR signalling via PI3K and TAK1 kinases in BL2 lymphoma cell lines.
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Project description:Understanding the structure and interplay of cellular signalling pathways is one of the great challenges in molecular biology. Boolean Networks can infer signalling networks from observations of protein activation. In situations where it is difficult to assess protein activation directly, Nested Effect Models are an alternative. They derive the network structure indirectly from downstream effects of pathway perturbations. To date, Nested Effect Models cannot resolve signalling details like the formation of signalling complexes or the activation of proteins by multiple alternative input signals. Here we introduce Boolean Nested Effect Models (B-NEM). B-NEMs combine the use of downstream effects with the higher resolution of signalling pathway structures in Boolean Networks. We show that B-NEMs accurately reconstruct signal flows in simulated data. Using B-NEM we then resolve BCR signalling via PI3K and TAK1 kinases in BL2 lymphoma cell lines. 84 BL2 cell-line samples were hybridized to HGU133+2 Affymetrix GeneChips.
2015-12-10 | E-GEOD-68761 | biostudies-arrayexpress
Project description:We carried out a parallel nested experiment performed simultaneously on RNA-Seq and microarrays that systematically split variation into four stages (treatment, biological variation, library preparation, and chip/lane noise), allowing a separation and comparison of the sources of variation in a well-controlled cellular system, Saccharomyces cerevisiae. Nested design. Two conditions (E for ethanol and G for glucose as sole carbon source), each grown on two biological replicates (1 and 2), prepared in two technical preparations (A and B), then hybridized to two chips (1 and 2) This submission represents microarray component of study.
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