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. 2023 Mar 6;11(2):e0408622.
doi: 10.1128/spectrum.04086-22. Online ahead of print.

Nested PCR Approach for petB Gene Metabarcoding of Marine Synechococcus Populations

Affiliations

Nested PCR Approach for petB Gene Metabarcoding of Marine Synechococcus Populations

Denise Rui Ying Ong et al. Microbiol Spectr. .

Abstract

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.

Keywords: marine Synechococcus; marine picocyanobacteria; metabarcoding; nested PCR; petB.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

FIG 1
FIG 1
Synechococcus taxonomic composition at clade and subclade level from filtered samples obtained with the Mazard_2012 and Ong_2022 approaches. Samples were grouped by cycles and ordered across a spatial gradient, from subtropical (ST) to subantarctic (SA) cycles. Samples from all depths were combined.
FIG 2
FIG 2
Percentage of Synechococcus reads in each filtered sample for major subclades (A) and minor clades and subclades (B) and total number of ASVs (C) for each clade and subclade obtained by the Mazard_2012 and Ong_2022 methods. Clades and subclades are arranged in descending order according to the mean percentage of reads with the Ong_2022 method.
FIG 3
FIG 3
ASV nucleotide similarity within each clade and subclade obtained with the Mazard_2012 and Ong_2022 approaches and the reference sequence database.
FIG 4
FIG 4
Synechococcus taxonomic composition at clade and subclade level from flow cytometry-sorted populations. Samples were grouped by cycle and ordered across a spatial gradient, from subtropical (ST) to subantarctic (SA) cycles. The SUR and DCM depth samples were combined.

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