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  • 1
    Publication Date: 2022-10-26
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Coenen, A. R., Hu, S. K., Luo, E., Muratore, D., & Weitz, J. S. A primer for microbiome time-series analysis. Frontiers in Genetics, 11, (2020): 310, doi:10.3389/fgene.2020.00310.
    Description: Time-series can provide critical insights into the structure and function of microbial communities. The analysis of temporal data warrants statistical considerations, distinct from comparative microbiome studies, to address ecological questions. This primer identifies unique challenges and approaches for analyzing microbiome time-series. In doing so, we focus on (1) identifying compositionally similar samples, (2) inferring putative interactions among populations, and (3) detecting periodic signals. We connect theory, code and data via a series of hands-on modules with a motivating biological question centered on marine microbial ecology. The topics of the modules include characterizing shifts in community structure and activity, identifying expression levels with a diel periodic signal, and identifying putative interactions within a complex community. Modules are presented as self-contained, open-access, interactive tutorials in R and Matlab. Throughout, we highlight statistical considerations for dealing with autocorrelated and compositional data, with an eye to improving the robustness of inferences from microbiome time-series. In doing so, we hope that this primer helps to broaden the use of time-series analytic methods within the microbial ecology research community.
    Description: This work was supported by the Simons Foundation (SCOPE award ID 329108) and the National Science Foundation (NSF Bio Oc 1829636).
    Keywords: Microbial ecology ; Time-series analysis ; Marine microbiology ; Inference ; Clustering ; Periodicity ; Code:R ; Code:matlab
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-11-15
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ollison, G., Hu, S., Hopper, J., Stewart, B., Smith, J., Beatty, J., Rink, L., & Caron, D. Daily dynamics of contrasting spring algal blooms in Santa Monica Bay (central Southern California Bight). Environmental Microbiology. (2022), https://doi.org/10.1111/1462-2920.16137.
    Description: Protistan algae (phytoplankton) dominate coastal upwelling ecosystems where they form massive blooms that support the world's most important fisheries and constitute an important sink for atmospheric CO2. Bloom initiation is well understood, but the biotic and abiotic forces that shape short-term dynamics in community composition are still poorly characterized. Here, high-frequency (daily) changes in relative abundance dynamics of the metabolically active protistan community were followed via expressed 18S V4 rRNA genes (RNA) throughout two algal blooms during the spring of 2018 and 2019 in Santa Monica Bay (central Southern California Bight). A diatom bloom formed after wind-driven, nutrient upwelling events in both years, but different taxa dominated each year. Whereas diatoms bloomed following elevated nutrients and declined after depletion each year, a massive dinoflagellate bloom manifested under relatively low inorganic nitrogen conditions following diatom bloom senescence in 2019 but not 2018. Network analysis revealed associations between diatoms and cercozoan putative parasitic taxa and syndinean parasites during 2019 that may have influenced the demise of the diatoms, and the transition to a dinoflagellate-dominated bloom.
    Description: This work was supported by the National Science Foundation #1136818 (David A. Caron).
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
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    Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu
    Publication Date: 2022-10-31
    Description: Dataset: Microbial eukaryotic focused metatranscriptome data
    Description: Seawater was collected via Niskin bottles mounted with a CTD from the San Pedro Ocean Time-series (SPOT) station off the coast of Southern California near the surface (5 m), 150 and 890 m, in late May 2015. Raw sequence data was generated as part of a metatranscriptome study targeting the protistan community. Raw sequences are available at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database (SRA Study ID: SRP110974, BioProject: PRJNA391503). Sequences for BioProject PRJNA608423 will be available at NCBI on Jan 1st, 2021. These data were published in Hu et al. (2018). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/745518
    Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1737409
    Keywords: Microbial ecology ; Microbial eukaryotes ; Metatranscriptomics ; Protistan trophic strategies ; Microbial eukaryotic metatranscriptomics
    Repository Name: Woods Hole Open Access Server
    Type: Dataset
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  • 4
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    Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu
    Publication Date: 2022-05-26
    Description: Dataset: Microbial eukaryotic diversity: Axial Seamount SRA
    Description: High throughput tag-sequencing accessions (18S rRNA gene region) and environmental metadata from Axial Seamount, 2013-2015. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/828345
    Description: NSF Division of Ocean Sciences (NSF OCE) OCE-0939564
    Repository Name: Woods Hole Open Access Server
    Type: Dataset
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  • 5
    Publication Date: 2022-05-26
    Description: Dataset: Microbial eukaryotic diversity: Gorda Ridge SRA
    Description: High throughput tag-sequencing data from Gorda Ridge Hydrothermal vent field, including 16S and 18S rRNA gene sequences, and environmental metadata from Gorda Ridge Seamount, May/June 2019. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/828392
    Description: NSF Division of Ocean Sciences (NSF OCE) OCE-0939564
    Repository Name: Woods Hole Open Access Server
    Type: Dataset
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  • 6
    Publication Date: 2022-10-26
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Coesel, S. N., Durham, B. P., Groussman, R. D., Hu, S. K., Caron, D. A., Morales, R. L., Ribalet, F., & Armbrust, E. V. Diel transcriptional oscillations of light-sensitive regulatory elements in open-ocean eukaryotic plankton communities. Proceedings of the National Academy of Sciences of the United States of America, 118(6), (2021): e2011038118, https://doi.org/10.1073./pnas.2011038118.
    Description: The 24-h cycle of light and darkness governs daily rhythms of complex behaviors across all domains of life. Intracellular photoreceptors sense specific wavelengths of light that can reset the internal circadian clock and/or elicit distinct phenotypic responses. In the surface ocean, microbial communities additionally modulate nonrhythmic changes in light quality and quantity as they are mixed to different depths. Here, we show that eukaryotic plankton in the North Pacific Subtropical Gyre transcribe genes encoding light-sensitive proteins that may serve as light-activated transcription factors, elicit light-driven electrical/chemical cascades, or initiate secondary messenger-signaling cascades. Overall, the protistan community relies on blue light-sensitive photoreceptors of the cryptochrome/photolyase family, and proteins containing the Light-Oxygen-Voltage (LOV) domain. The greatest diversification occurred within Haptophyta and photosynthetic stramenopiles where the LOV domain was combined with different DNA-binding domains and secondary signal-transduction motifs. Flagellated protists utilize green-light sensory rhodopsins and blue-light helmchromes, potentially underlying phototactic/photophobic and other behaviors toward specific wavelengths of light. Photoreceptors such as phytochromes appear to play minor roles in the North Pacific Subtropical Gyre. Transcript abundance of environmental light-sensitive protein-encoding genes that display diel patterns are found to primarily peak at dawn. The exceptions are the LOV-domain transcription factors with peaks in transcript abundances at different times and putative phototaxis photoreceptors transcribed throughout the day. Together, these data illustrate the diversity of light-sensitive proteins that may allow disparate groups of protists to respond to light and potentially synchronize patterns of growth, division, and mortality within the dynamic ocean environment.
    Description: This work was supported by a grant from the Simons Foundation (SCOPE Award 329108 [to E.V.A.]) and XSEDE Grant Allocation OCE160019 (to R.D.G.).
    Keywords: Photoreceptors ; Microbial eukaryotes ; Oligotrophic gyre ; Diel cycles ; Metatranscriptomics
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 7
    Publication Date: 2022-10-26
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cohen, N., Alexander, H., Krinos, A., Hu, S., & Lampe, R. Marine microeukaryotem metatranscriptomics: sample processing and bioinformatic workflow recommendations for ecological applications. Frontiers in Marine Science, 9, (2022): 867007, https://doi.org/10.3389/fmars.2022.867007.
    Description: Microeukaryotes (protists) serve fundamental roles in the marine environment as contributors to biogeochemical nutrient cycling and ecosystem function. Their activities can be inferred through metatranscriptomic investigations, which provide a detailed view into cellular processes, chemical-biological interactions in the environment, and ecological relationships among taxonomic groups. Established workflows have been individually put forth describing biomass collection at sea, laboratory RNA extraction protocols, and bioinformatic processing and computational approaches. Here, we present a compilation of current practices and lessons learned in carrying out metatranscriptomics of marine pelagic protistan communities, highlighting effective strategies and tools used by practitioners over the past decade. We anticipate that these guidelines will serve as a roadmap for new marine scientists beginning in the realms of molecular biology and/or bioinformatics, and will equip readers with foundational principles needed to delve into protistan metatranscriptomics.
    Description: We acknowledge funding support from the University of Georgia Skidaway Institute of Oceanography (to NRC), National Science Foundation (NSF) (OCE-1948025 to HA), and Department of Energy Computational Science Graduate Fellowship (DE-SC0020347 to AIK). SKH participation was supported through NSF OCE-1947776.
    Keywords: Metatranscriptomics ; Phytoplankton ; Biological oceanography ; Microbial ecology ; Bioinformatics
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 8
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    Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu
    Publication Date: 2022-05-26
    Description: Dataset: OTU table for 18S rRNA gene tag sequences from DNA and RNA
    Description: This dataset is a raw output operational taxonomic unit (OTU) table generated by processing and clustering raw 18S rRNA gene tag sequences from extracted DNA and RNA. Columns represent samples, including month sampled, material (either extracted RNA or DNA), and depth (in meters); thus values in each column represent the number of sequences in that sample that belong to a given OTU (OTUs by row). Each row represents a single OTU. The last column lists the taxonomic identifier assigned to each OTU. The raw sequence data can be found in the NCBI SRA database under accession number SRP070577 with the associated BioProject PRJNA311248. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/748064
    Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1737409
    Repository Name: Woods Hole Open Access Server
    Type: Dataset
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  • 9
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    Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu
    Publication Date: 2022-05-26
    Description: Dataset: 18S rRNA gene tag sequences from DNA and RNA
    Description: Raw DNA and RNA V4 tag sequences include spatially and temporally distinct samples from coastal California. Samples were collected in Niskin bottles with a CTD rosette at the San Pedro Ocean Time-series (SPOT) between April of 2013 and January of 2014. This dataset contains sequence data accession numbers and metadata for the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database (SRA Study ID: SRP070577, BioProject: PRJNA311248). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/745527
    Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1737409
    Repository Name: Woods Hole Open Access Server
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  • 10
    Publication Date: 2019-05-24
    Description: Sinking particles are a critical conduit for the export of organic material from surface waters to the deep ocean. Despite their importance in oceanic carbon cycling and export, little is known about the biotic composition, origins, and variability of sinking particles reaching abyssal depths. Here, we analyzed particle-associated nucleic acids captured and preserved in sediment traps at 4,000-m depth in the North Pacific Subtropical Gyre. Over the 9-month time-series, Bacteria dominated both the rRNA-gene and rRNA pools, followed by eukaryotes (protists and animals) and trace amounts of Archaea. Deep-sea piezophile-like Gammaproteobacteria, along with Epsilonproteobacteria, comprised 〉80% of the bacterial inventory. Protists (mostly Rhizaria, Syndinales, and ciliates) and metazoa (predominantly pelagic mollusks and cnidarians) were the most common sinking particle-associated eukaryotes. Some near-surface water-derived eukaryotes, especially Foraminifera, Radiolaria, and pteropods, varied greatly in their abundance patterns, presumably due to sporadic export events. The dominance of piezophile-like Gammaproteobacteria and Epsilonproteobacteria, along with the prevalence of their nitrogen cycling-associated gene transcripts, suggested a central role for these bacteria in the mineralization and biogeochemical transformation of sinking particulate organic matter in the deep ocean. Our data also reflected several different modes of particle export dynamics, including summer export, more stochastic inputs from the upper water column by protists and pteropods, and contributions from sinking mid- and deep-water organisms. In total, our observations revealed the variable and heterogeneous biological origins and microbial activities of sinking particles that connect their downward transport, transformation, and degradation to deep-sea biogeochemical processes.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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