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Diversity of Synechococcus at the Martha's Vineyard Coastal Observatory: Insights from Culture Isolations, Clone Libraries, and Flow Cytometry.

ABSTRACT: The cyanobacterium Synechococcus is a ubiquitous, important phytoplankter across the world's oceans. A high degree of genetic diversity exists within the marine group, which likely contributes to its global success. Over 20 clades with different distribution patterns have been identified. However, we do not fully understand the environmental factors that control clade distributions. These factors are likely to change seasonally, especially in dynamic coastal systems. To investigate how coastal Synechococcus assemblages change temporally, we assessed the diversity of Synechococcus at the Martha's Vineyard Coastal Observatory (MVCO) over three annual cycles with culture-dependent and independent approaches. We further investigated the abundance of both phycoerythrin (PE)-containing and phycocyanin (PC)-only Synechococcus with a flow cytometric setup that distinguishes PC-only Synechococcus from picoeukaryotes. We found that the Synechococcus assemblage at MVCO is diverse (13 different clades identified), but dominated by clade I representatives. Many clades were only isolated during late summer and fall, suggesting more favorable conditions for isolation at this time. PC-only strains from four different clades were isolated, but these cells were only detected by flow cytometry in a few samples over the time series, suggesting they are rare at this site. Within clade I, we identified four distinct subclades. The relative abundances of each subclade varied over the seasonal cycle, and the high Synechococcus cell concentration at MVCO may be maintained by the diversity found within this clade. This study highlights the need to understand how temporal aspects of the environment affect Synechococcus community structure and cell abundance.

SUBMITTER: Hunter-Cevera KR

PROVIDER: S-EPMC4728178 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Diversity of Synechococcus at the Martha's Vineyard Coastal Observatory: Insights from Culture Isolations, Clone Libraries, and Flow Cytometry.

Hunter-Cevera Kristen R KR Post Anton F AF Peacock Emily E EE Sosik Heidi M HM

Microbial ecology 20150802 2

The cyanobacterium Synechococcus is a ubiquitous, important phytoplankter across the world's oceans. A high degree of genetic diversity exists within the marine group, which likely contributes to its global success. Over 20 clades with different distribution patterns have been identified. However, we do not fully understand the environmental factors that control clade distributions. These factors are likely to change seasonally, especially in dynamic coastal systems. To investigate how coastal S ...[more]

PMID: 26233669

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Project description:Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

Dataset Information

Diversity of Synechococcus at the Martha's Vineyard Coastal Observatory: Insights from Culture Isolations, Clone Libraries, and Flow Cytometry.

Publications

Diversity of Synechococcus at the Martha's Vineyard Coastal Observatory: Insights from Culture Isolations, Clone Libraries, and Flow Cytometry.

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