Fuhrman Jed A.

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Jed A.

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  • Dataset
    A characterization of microbes at the San Pedro Ocean Time-series (SPOT) from 2005 to 2018, using SSU rRNA gene sequencing from two size fractions, with a universal primer set that amplifies from prokaryotes and eukaryotes
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2023-01-30) Yeh, Yi-Chun ; Fuhrman, Jed A.
    This study aims to characterize microbes at the San Pedro Ocean Time-series (SPOT) from 2005 to 2018, using small subunit (SSU) rRNA gene sequencing from two size fractions (0.2-1 and 1-80 μm), with a universal primer set that amplifies both prokaryotic 16S and eukaryotic 18S rRNA genes. This allows for direct comparisons of diversity patterns in a single set of analyses. This dataset includes National Center for Biotechnology Information (NCBI) accession numbers and related sample information. 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/885982
  • Preprint
    Global distribution and diversity of marine Verrucomicrobia
    ( 2011-12-08) Freitas, Sara ; Hatosy, Stephen ; Fuhrman, Jed A. ; Huse, Susan M. ; Mark Welch, David B. ; Sogin, Mitchell L. ; Martiny, Adam C.
    Verrucomicrobia is a bacterial phylum that is commonly detected in soil but little is known about the distribution and diversity of this phylum in the marine environment. To address this, we analyzed the marine microbial community composition in 506 samples from the International Census of Marine Microbes as well as eleven coastal samples taken from the California Current. These samples from both the water column and sediments covered a wide range of environmental conditions. Verrucomicrobia were present in 98% of the analyzed samples and thus appeared nearly ubiquitous in the ocean. Based on the occurrence of amplified 16S rRNA sequences, Verrucomicrobia constituted on average 2% of the water column and 1.4% of the sediment bacterial communities. The diversity of Verrucomicrobia displayed a biogeography at multiple taxonomic levels and thus, specific lineages appeared to have clear habitat preference. We found that Subdivision 1 and 4 generally dominated marine bacterial communities, whereas Subdivision 2 was confined to low salinity waters. Within the subdivisions, Verrucomicrobia community composition were significantly different in the water column compared to sediment as well as within the water column along gradients of salinity, temperature, nitrate, depth, and overall water column depth. Although we still know little about the ecophysiology of Verrucomicrobia lineages, the ubiquity of this phylum suggests that it may be important for the biogeochemical cycle of carbon in the ocean.
  • Article
    Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates
    (BioMed Central, 2011-12-14) Xia, Li C. ; Steele, Joshua A. ; Cram, Jacob A. ; Cardon, Zoe G. ; Simmons, Sheri L. ; Vallino, Joseph J. ; Fuhrman, Jed A. ; Sun, Fengzhu
    The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa
  • Article
    The ocean sampling day consortium
    (BioMed Central, 2015-06-19) Kopf, Anna ; Bicak, Mesude ; Kottmann, Renzo ; Schnetzer, Julia ; Kostadinov, Ivaylo ; Lehmann, Katja ; Fernandez-Guerra, Antonio ; Jeanthon, Christian ; Rahav, Eyal ; Ullrich, Matthias S. ; Wichels, Antje ; Gerdts, Gunnar ; Polymenakou, Paraskevi ; Kotoulas, Georgios ; Siam, Rania ; Abdallah, Rehab Z. ; Sonnenschein, Eva C. ; Cariou, Thierry ; O’Gara, Fergal ; Jackson, Stephen ; Orlic, Sandi ; Steinke, Michael ; Busch, Julia ; Duarte, Bernardo ; Caçador, Isabel ; Canning-Clode, Joao ; Bobrova, Oleksandra ; Marteinsson, Viggo ; Reynisson, Eyjolfur ; Loureiro, Clara Magalhaes ; Luna, Gian Marco ; Quero, Grazia Marina ; Loscher, Carolin R. ; Kremp, Anke ; DeLorenzo, Marie E. ; Øvreås, Lise ; Tolman, Jennifer ; LaRoche, Julie ; Penna, Antonella ; Frischer, Marc ; Davis, Timothy ; Katherine, Barker ; Meyer, Christopher P. ; Ramos, Sandra ; Magalhaes, Catarina ; Jude-Lemeilleur, Florence ; Aguirre-Macedo, Ma Leopoldina ; Wang, Shiao ; Poulton, Nicole ; Jones, Scott ; Collin, Rachel ; Fuhrman, Jed A. ; Conan, Pascal ; Alonso, Cecilia ; Stambler, Noga ; Goodwin, Kelly ; Yakimov, Michail M. ; Baltar, Federico ; Bodrossy, Levente ; Van De Kamp, Jodie ; Frampton, Dion M. F. ; Ostrowski, Martin ; Van Ruth, Paul ; Malthouse, Paul ; Claus, Simon ; Deneudt, Klaas ; Mortelmans, Jonas ; Pitois, Sophie ; Wallom, David ; Salter, Ian ; Costa, Rodrigo ; Schroeder, Declan C. ; Kandil, Mahrous M. ; Amaral, Valentina ; Biancalana, Florencia ; Santana, Rafael ; Pedrotti, Maria Luiza ; Yoshida, Takashi ; Ogata, Hiroyuki ; Ingleton, Timothy ; Munnik, Kate ; Rodriguez-Ezpeleta, Naiara ; Berteaux-Lecellier, Veronique ; Wecker, Patricia ; Cancio, Ibon ; Vaulot, Daniel ; Bienhold, Christina ; Ghazal, Hassan ; Chaouni, Bouchra ; Essayeh, Soumya ; Ettamimi, Sara ; Zaid, El Houcine ; Boukhatem, Noureddine ; Bouali, Abderrahim ; Chahboune, Rajaa ; Barrijal, Said ; Timinouni, Mohammed ; El Otmani, Fatima ; Bennani, Mohamed ; Mea, Marianna ; Todorova, Nadezhda ; Karamfilov, Ventzislav ; ten Hoopen, Petra ; Cochrane, Guy R. ; L’Haridon, Stephane ; Bizsel, Kemal Can ; Vezzi, Alessandro ; Lauro, Federico M. ; Martin, Patrick ; Jensen, Rachelle M. ; Hinks, Jamie ; Gebbels, Susan ; Rosselli, Riccardo ; De Pascale, Fabio ; Schiavon, Riccardo ; dos Santos, Antonina ; Villar, Emilie ; Pesant, Stephane ; Cataletto, Bruno ; Malfatti, Francesca ; Edirisinghe, Ranjith ; Herrera Silveira, Jorge A. ; Barbier, Michele ; Turk, Valentina ; Tinta, Tinkara ; Fuller, Wayne J. ; Salihoglu, Ilkay ; Serakinci, Nedime ; Ergoren, Mahmut Cerkez ; Bresnan, Eileen ; Iriberri, Juan ; Fronth Nyhus, Paul Anders ; Bente, Edvardsen ; Karlsen, Hans Erik ; Golyshin, Peter N. ; Gasol, Josep M. ; Moncheva, Snejana ; Dzhembekova, Nina ; Johnson, Zackary ; Sinigalliano, Christopher D. ; Gidley, Maribeth Louise ; Zingone, Adriana ; Danovaro, Roberto ; Tsiamis, Georgios ; Clark, Melody S. ; Costa, Ana Cristina ; El Bour, Monia ; Martins, Ana M. ; Collins, R. Eric ; Ducluzeau, Anne-Lise ; Martinez, Jonathan ; Costello, Mark J. ; Amaral-Zettler, Linda A. ; Gilbert, Jack A. ; Davies, Neil ; Field, Dawn ; Glockner, Frank Oliver
    Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world’s oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits.
  • Preprint
    Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications
    ( 2011-01-04) Yilmaz, Pelin ; Kottmann, Renzo ; Field, Dawn ; Knight, Rob ; Cole, James R. ; Amaral-Zettler, Linda A. ; Gilbert, Jack A. ; Karsch-Mizrachi, Ilene ; Johnston, Anjanette ; Cochrane, Guy R. ; Vaughan, Robert ; Hunter, Christopher ; Park, Joonhong ; Morrison, Norman ; Rocca-Serra, Philippe ; Sterk, Peter ; Arumugam, Manimozhiyan ; Bailey, Mark ; Baumgartner, Laura ; Birren, Bruce W. ; Blaser, Martin J. ; Bonazzi, Vivien ; Booth, Tim ; Bork, Peer ; Bushman, Frederic D. ; Buttigieg, Pier Luigi ; Chain, Patrick S. G. ; Charlson, Emily ; Costello, Elizabeth K. ; Huot-Creasy, Heather ; Dawyndt, Peter ; DeSantis, Todd ; Fierer, Noah ; Fuhrman, Jed A. ; Gallery, Rachel E. ; Gevers, Dirk ; Gibbs, Richard A. ; San Gil, Inigo ; Gonzalez, Antonio ; Gordon, Jeffrey I. ; Guralnick, Robert P. ; Hankeln, Wolfgang ; Highlander, Sarah ; Hugenholtz, Philip ; Jansson, Janet K. ; Kau, Andrew L. ; Kelley, Scott T. ; Kennedy, Jerry ; Knights, Dan ; Koren, Omry ; Kuczynski, Justin ; Kyrpides, Nikos C. ; Larsen, Robert ; Lauber, Christian L. ; Legg, Teresa ; Ley, Ruth E. ; Lozupone, Catherine A. ; Ludwig, Wolfgang ; Lyons, Donna ; Maguire, Eamonn ; Methe, Barbara A. ; Meyer, Folker ; Muegge, Brian ; Nakielny, Sara ; Nelson, Karen E. ; Nemergut, Diana ; Neufeld, Josh D. ; Newbold, Lindsay K. ; Oliver, Anna E. ; Pace, Norman R. ; Palanisamy, Giriprakash ; Peplies, Jorg ; Petrosino, Joseph ; Proctor, Lita ; Pruesse, Elmar ; Quast, Christian ; Raes, Jeroen ; Ratnasingham, Sujeevan ; Ravel, Jacques ; Relman, David A. ; Assunta-Sansone, Susanna ; Schloss, Patrick D. ; Schriml, Lynn M. ; Sinha, Rohini ; Smith, Michelle I. ; Sodergren, Erica ; Spor, Ayme ; Stombaugh, Jesse ; Tiedje, James M. ; Ward, Doyle V. ; Weinstock, George M. ; Wendel, Doug ; White, Owen ; Whiteley, Andrew ; Wilke, Andreas ; Wortman, Jennifer R. ; Yatsunenko, Tanya ; Glockner, Frank Oliver
    Here we present a standard developed by the Genomic Standards Consortium (GSC) to describe marker gene sequences—the minimum information about a marker gene sequence (MIMARKS). We also introduce a system for describing the environment from which a biological sample originates. The “environmental packages” apply to any sequence whose origin is known and can therefore be used in combination with MIMARKS or other GSC checklists. Finally, to establish a unified standard for describing sequence data and to provide a single point of entry for the scientific community to access and learn about GSC checklists, we establish the minimum information about any (x) sequence (MIxS). Adoption of MIxS will enhance our ability to analyze natural genetic diversity across the Tree of Life as it is currently being documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.
  • Article
    Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys
    (American Society for Microbiology, 2015-12-22) Walters, William ; Hyde, Embriette R. ; Berg-Lyons, Donna ; Ackermann, Gail ; Humphrey, Greg ; Parada, Alma ; Gilbert, Jack A. ; Jansson, Janet K. ; Caporaso, J. Gregory ; Fuhrman, Jed A. ; Apprill, Amy ; Knight, Rob
    Designing primers for PCR-based taxonomic surveys that amplify a broad range of phylotypes in varied community samples is a difficult challenge, and the comparability of data sets amplified with varied primers requires attention. Here, we examined the performance of modified 16S rRNA gene and internal transcribed spacer (ITS) primers for archaea/bacteria and fungi, respectively, with nonaquatic samples. We moved primer bar codes to the 5′ end, allowing for a range of different 3′ primer pairings, such as the 515f/926r primer pair, which amplifies variable regions 4 and 5 of the 16S rRNA gene. We additionally demonstrated that modifications to the 515f/806r (variable region 4) 16S primer pair, which improves detection of Thaumarchaeota and clade SAR11 in marine samples, do not degrade performance on taxa already amplified effectively by the original primer set. Alterations to the fungal ITS primers did result in differential but overall improved performance compared to the original primers. In both cases, the improved primers should be widely adopted for amplicon studies.
  • Dataset
    Environmental data, nutrients, and leucine and thymidine bacterial production from samples collected by CTD during cruises in the San Pedro Channel on R/V Yellowfin from 2005 to 2018
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2023-01-30) Yeh, Yi-Chun ; Fuhrman, Jed A.
    This dataset includes temperature, oxygen, and fluorescence were recorded by a Seabird Scientific SBE25plus Sealogger CTD during San Pedro Ocean Time-series (SPOT) cruises from 2005 to 2018. Nutrient variables include nitrite, nitrate, and phosphate. Satellite sea surface temperature, chlorophyll-a concentration, and surface productivity estimates were downloaded from the NOAA Coastwatch browser website. Leucine and thymidine bacterial production data are also included. 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/885939
  • Dataset
    Nutrient concentrations and cell/virus-like particles counts
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2022-09-21) Fuhrman, Jed A. ; Sieradzki, Ella
    Nutrient concentrations and cell/virus-like particles counts. 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/866781