McManus George

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McManus
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George
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  • Dataset
    Temperature and salinity measured at the UConn dock in Groton, CT, USA, associated with DNA collection
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2021-06-28) McManus, George ; Katz, Laura A. ; Santoferrara, Luciana
    This dataset includes temperature and salinity measurements collected from the UConn dock in Groton CT, USA (41˚ 18' 59" N, 72˚ 03'39" W), in association with DNA collection. Measurements were made weekly from January 2020 to April 2021. 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/854554
  • Article
    The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP) : illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing
    (Public Library of Science, 2014-06-24) Keeling, Patrick J. ; Burki, Fabien ; Wilcox, Heather M. ; Allam, Bassem ; Allen, Eric E. ; Amaral-Zettler, Linda A. ; Armbrust, E. Virginia ; Archibald, John M. ; Bharti, Arvind K. ; Bell, Callum J. ; Beszteri, Bank ; Bidle, Kay D. ; Cameron, Connor T. ; Campbell, Lisa ; Caron, David A. ; Cattolico, Rose Ann ; Collier, Jackie L. ; Coyne, Kathryn J. ; Davy, Simon K. ; Deschamps, Phillipe ; Dyhrman, Sonya T. ; Edvardsen, Bente ; Gates, Ruth D. ; Gobler, Christopher J. ; Greenwood, Spencer J. ; Guida, Stephanie M. ; Jacobi, Jennifer L. ; Jakobsen, Kjetill S. ; James, Erick R. ; Jenkins, Bethany D. ; John, Uwe ; Johnson, Matthew D. ; Juhl, Andrew R. ; Kamp, Anja ; Katz, Laura A. ; Kiene, Ronald P. ; Kudryavtsev, Alexander N. ; Leander, Brian S. ; Lin, Senjie ; Lovejoy, Connie ; Lynn, Denis ; Marchetti, Adrian ; McManus, George ; Nedelcu, Aurora M. ; Menden-Deuer, Susanne ; Miceli, Cristina ; Mock, Thomas ; Montresor, Marina ; Moran, Mary Ann ; Murray, Shauna A. ; Nadathur, Govind ; Nagai, Satoshi ; Ngam, Peter B. ; Palenik, Brian ; Pawlowski, Jan ; Petroni, Giulio ; Piganeau, Gwenael ; Posewitz, Matthew C. ; Rengefors, Karin ; Romano, Giovanna ; Rumpho, Mary E. ; Rynearson, Tatiana A. ; Schilling, Kelly B. ; Schroeder, Declan C. ; Simpson, Alastair G. B. ; Slamovits, Claudio H. ; Smith, David R. ; Smith, G. Jason ; Smith, Sarah R. ; Sosik, Heidi M. ; Stief, Peter ; Theriot, Edward ; Twary, Scott N. ; Umale, Pooja E. ; Vaulot, Daniel ; Wawrik, Boris ; Wheeler, Glen L. ; Wilson, William H. ; Xu, Yan ; Zingone, Adriana ; Worden, Alexandra Z.
    Microbial ecology is plagued by problems of an abstract nature. Cell sizes are so small and population sizes so large that both are virtually incomprehensible. Niches are so far from our everyday experience as to make their very definition elusive. Organisms that may be abundant and critical to our survival are little understood, seldom described and/or cultured, and sometimes yet to be even seen. One way to confront these problems is to use data of an even more abstract nature: molecular sequence data. Massive environmental nucleic acid sequencing, such as metagenomics or metatranscriptomics, promises functional analysis of microbial communities as a whole, without prior knowledge of which organisms are in the environment or exactly how they are interacting. But sequence-based ecological studies nearly always use a comparative approach, and that requires relevant reference sequences, which are an extremely limited resource when it comes to microbial eukaryotes. In practice, this means sequence databases need to be populated with enormous quantities of data for which we have some certainties about the source. Most important is the taxonomic identity of the organism from which a sequence is derived and as much functional identification of the encoded proteins as possible. In an ideal world, such information would be available as a large set of complete, well-curated, and annotated genomes for all the major organisms from the environment in question. Reality substantially diverges from this ideal, but at least for bacterial molecular ecology, there is a database consisting of thousands of complete genomes from a wide range of taxa, supplemented by a phylogeny-driven approach to diversifying genomics. For eukaryotes, the number of available genomes is far, far fewer, and we have relied much more heavily on random growth of sequence databases, raising the question as to whether this is fit for purpose.
  • Dataset
    CTD profiles collected with RV Connecticut on the Continental shelf and slope south of Montauk, NY on 14-15 June 2022.
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2022-09-16) McManus, George ; Santoferrara, Luciana ; Katz, Laura A.
    Seven stations on the shelf and slope south of Montauk, NY on 14-15 June 2022 were sampled. Basic hydrographic properties, including temperature, salinity, dissolved oxygen, and pH were measured and rosette samples were taken for chlorophyll, nutrients, and microplankton. Water was filtered for metagenomics and metatranscriptomics and picked individual microplankters for sequencing. Three to ten depths were sampled at each station. Our shallowest station was on the shelf at 38m and the deepest was at the slope edge at 2400m. Due to limitations of the CTD our deepest sampled depth was 1150m. At the two shallowest stations, we also deployed a Wetstar fluorometer for phytoplankton fluorescence. The CTD data were processed with SeaBird's Seasoft program and converted to spreadsheet format. 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/879380
  • Article
    Defining planktonic protist functional groups on mechanisms for energy and nutrient acquisition : incorporation of diverse mixotrophic strategies
    (Elsevier, 2016-01-03) Mitra, Aditee ; Flynn, Kevin J. ; Tillmann, Urban ; Raven, John A. ; Caron, David A. ; Stoecker, Diane K. ; Not, Fabrice ; Hansen, Per J. ; Hallegraeff, Gustaaf M. ; Sanders, Robert W. ; Wilken, Susanne ; McManus, George ; Johnson, Matthew D. ; Pitta, Paraskevi ; Våge, Selina ; Berge, Terje ; Calbet, Albert ; Thingstad, Frede ; Jeong, Hae Jin ; Burkholder, JoAnn M. ; Glibert, Patricia M. ; Graneli, Edna ; Lundgren, Veronica
    Arranging organisms into functional groups aids ecological research by grouping organisms (irrespective of phylogenetic origin) that interact with environmental factors in similar ways. Planktonic protists traditionally have been split between photoautotrophic “phytoplankton” and phagotrophic “microzooplankton”. However, there is a growing recognition of the importance of mixotrophy in euphotic aquatic systems, where many protists often combine photoautotrophic and phagotrophic modes of nutrition. Such organisms do not align with the traditional dichotomy of phytoplankton and microzooplankton. To reflect this understanding, we propose a new functional grouping of planktonic protists in an eco-physiological context: (i) phagoheterotrophs lacking phototrophic capacity, (ii) photoautotrophs lacking phagotrophic capacity, (iii) constitutive mixotrophs (CMs) as phagotrophs with an inherent capacity for phototrophy, and (iv) non-constitutive mixotrophs (NCMs) that acquire their phototrophic capacity by ingesting specific (SNCM) or general non-specific (GNCM) prey. For the first time, we incorporate these functional groups within a foodweb structure and show, using model outputs, that there is scope for significant changes in trophic dynamics depending on the protist functional type description. Accordingly, to better reflect the role of mixotrophy, we recommend that as important tools for explanatory and predictive research, aquatic food-web and biogeochemical models need to redefine the protist groups within their frameworks.