Caron David A.

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David A.

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  • Article
    Development and application of a monoclonal-antibody technique for counting Aureococcus anophagefferens, an alga causing recurrent brown tides in the Mid-Atlantic United States
    (American Society for Microbiology, 2003-09) Caron, David A. ; Dennett, Mark R. ; Moran, Dawn M. ; Schaffner, Rebecca A. ; Lonsdale, Darcy J. ; Gobler, Christopher J. ; Nuzzi, Robert ; McLean, Tim I.
    A method was developed for the rapid detection and enumeration of Aureococcus anophagefferens, the cause of harmful algal blooms called "brown tides" in estuaries of the Mid-Atlantic United States. The method employs a monoclonal antibody (MAb) and a colorimetric, enzyme-linked immunosorbent assay format. The MAb obtained exhibits high reactivity with A. anophagefferens and very low cross-reactivities with a phylogenetically diverse array of other protists and bacteria. Standard curves are constructed for each 96-well microtiter plate by using known amounts of a preserved culture of A. anophagefferens. This approach allows estimation of the abundance of the alga in natural samples. The MAb method was compared to an existing method that employs polyclonal antibodies and epifluorescence microscopy and to direct microscopic counts of A. anophagefferens in samples with high abundances of the alga. The MAb method provided increased quantitative accuracy and greatly reduced sample processing time. A spatial survey of several Long Island estuaries in May 2000 using this new approach documented a range of abundances of A. anophagefferens in these bays spanning nearly 3 orders of magnitude.
  • 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.