PLoS BIOLOGY Sorcerer II Global Ocean Sampling Expedition .

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PLoS BIOLOGYThe Sorcerer II Global Ocean SamplingExpedition: Northwest Atlantic throughEastern Tropical PacificDouglas B. Rusch1*, Aaron L. Halpern1, Granger Sutton1, Karla B. Heidelberg1,2, Shannon Williamson1, Shibu Yooseph1,Dongying Wu1,3, Jonathan A. Eisen1,3, Jeff M. Hoffman1, Karin Remington1,4, Karen Beeson1, Bao Tran1,Hamilton Smith1, Holly Baden-Tillson1, Clare Stewart1, Joyce Thorpe1, Jason Freeman1, Cynthia Andrews-Pfannkoch1,Joseph E. Venter1, Kelvin Li1, Saul Kravitz1, John F. Heidelberg1,2, Terry Utterback1, Yu-Hui Rogers1, Luisa I. Falcón5,Valeria Souza5, Germán Bonilla-Rosso5, Luis E. Eguiarte5, David M. Karl6, Shubha Sathyendranath7, Trevor Platt7,Eldredge Bermingham8, Victor Gallardo9, Giselle Tamayo-Castillo10, Michael R. Ferrari11, Robert L. Strausberg1,Kenneth Nealson1,12, Robert Friedman1, Marvin Frazier1, J. Craig Venter11 J. Craig Venter Institute, Rockville, Maryland, United States of America, 2 Department of Biological Sciences, University of Southern California, Avalon, California, UnitedStates of America, 3 Genome Center, University of California Davis, Davis, California, United States of America, 4 Your Genome, Your World, Rockville, Maryland, United Statesof America, 5 Departmento de Ecologı́a Evolutiva, Instituto de Ecologı́a, Universidad Nacional Autónoma de México, Mexico City, Mexico, 6 Department of Oceanography,University of Hawaii, Honolulu, Hawaii, United States of America, 7 Bedford Institute of Oceanography, Dartmouth, Nova Scotia, Canada, 8 Smithsonian Tropical ResearchInstitute, Balboa, Ancon, Republic of Panama, 9 Departamento de Oceanografı́a, Universidad de Concepción, Concepción, Chile, 10 Escuela de Quı́mica, Universidad de CostaRica, San Pedro, Costa Rica, 11 Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey, United States of America, 12 Department of EarthSciences, University of Southern California, Los Angles, California, United States of AmericaThe world’s oceans contain a complex mixture of micro-organisms that are for the most part, uncharacterized bothgenetically and biochemically. We report here a metagenomic study of the marine planktonic microbiota in whichsurface (mostly marine) water samples were analyzed as part of the Sorcerer II Global Ocean Sampling expedition.These samples, collected across a several-thousand km transect from the North Atlantic through the Panama Canal andending in the South Pacific yielded an extensive dataset consisting of 7.7 million sequencing reads (6.3 billion bp).Though a few major microbial clades dominate the planktonic marine niche, the dataset contains great diversity with85% of the assembled sequence and 57% of the unassembled data being unique at a 98% sequence identity cutoff.Using the metadata associated with each sample and sequencing library, we developed new comparative genomic andassembly methods. One comparative genomic method, termed ‘‘fragment recruitment,’’ addressed questions ofgenome structure, evolution, and taxonomic or phylogenetic diversity, as well as the biochemical diversity of genesand gene families. A second method, termed ‘‘extreme assembly,’’ made possible the assembly and reconstruction oflarge segments of abundant but clearly nonclonal organisms. Within all abundant populations analyzed, we foundextensive intra-ribotype diversity in several forms: (1) extensive sequence variation within orthologous regionsthroughout a given genome; despite coverage of individual ribotypes approaching 500-fold, most individualsequencing reads are unique; (2) numerous changes in gene content some with direct adaptive implications; and (3)hypervariable genomic islands that are too variable to assemble. The intra-ribotype diversity is organized intogenetically isolated populations that have overlapping but independent distributions, implying distinct environmentalpreference. We present novel methods for measuring the genomic similarity between metagenomic samples and showhow they may be grouped into several community types. Specific functional adaptations can be identified both withinindividual ribotypes and across the entire community, including proteorhodopsin spectral tuning and the presence orabsence of the phosphate-binding gene PstS.Citation: Rusch DB, Halpern AL, Sutton G, Heidelberg KB, Williamson S, et al. (2007) The Sorcerer II Global Ocean Sampling expedition: Northwest Atlantic through easterntropical Pacific. PLoS Biol 5(3): e77. doi:10.1371/journal.pbio.0050077Academic Editor: Nancy A. Moran, University of Arizona, United States of AmericaReceived July 14, 2006; Accepted January 16, 2007; Published March 13, 2007Copyright: Ó 2007 Rusch et al. This is an open-access article distributed under theterms of the Creative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided the original authorand source are credited.Abbreviations: CAMERA, Cyberinfrastructure for Advanced Marine MicrobialEcology Research and Analysis; GOS, Global Ocean Sampling; NCBI, NationalCenter for Biotechnology Information* To whom correspondence should be addressed. E-mail: DRusch@venterinstitute.orgThis article is part of Global Ocean Sampling collection in PLoS Biology. The fullcollection is available online at hp.PLoS Biology www.plosbiology.org0398March 2007 Volume 5 Issue 3 e77

Sorcerer II GOS ExpeditionAuthor Summarysame ribotype [11], otherwise referred to as species, operational taxonomic units, or phylotypes.Although rRNA-based analysis has revolutionized our viewof genetic diversity, and has allowed the analysis of a largepart of the uncultivated majority, it has been less useful inpredicting biochemical diversity. Furthermore, the relationship between genetic and biochemical diversity, even forcultivated microbes, is not always predictable or clear. Forinstance, organisms that have very similar ribotypes (97% orgreater homology) may have vast differences in physiology,biochemistry, and genome content. For example, the genecomplement of Escherichia coli O157:H7 was found to besubstantially different from the K12 strain of the same species[12].In this paper, we report the results of the first phase of theSorcerer II Global Ocean Sampling (GOS) expedition, ametagenomic study designed to address questions related togenetic and biochemical microbial diversity. This survey wasinspired by the British Challenger expedition that took placefrom 1872–1876, in which the diversity of macroscopicmarine life was documented from dredged bottom samplesapproximately every 200 miles on a circumnavigation [13–15].Through the substantial dataset described here, we identified60 highly abundant ribotypes associated with the open oceanand aquatic samples. Despite this relative lack of diversity inribotype content, we confirm and expand upon previousobservations that there is tremendous within-ribotype diversity in marine microbial populations [4,7,8,16,17]. Newtechniques and tools were developed to make use of thesampling and sequencing metadata. These tools include: (1)the fragment recruitment tool for performing and visualizingcomparative genomic analyses when a reference sequence isavailable; (2) new assembly techniques that use metadata toproduce assemblies for uncultivated abundant microbial taxa;and (3) a whole metagenome comparison tool to compareentire samples at arbitrary degrees of genetic divergence.Although there is tremendous diversity within cultivated anduncultivated microbes alike, this diversity is organized intophylogenetically distinct groups we refer to as subtypes.Subtypes can occupy similar environments yet remaingenetically isolated from each other, suggesting that they areadapted for different environmental conditions or roleswithin the community. The variation between and withinsubtypes consists primarily of nucleotide polymorphisms butincludes numerous small insertions, deletions, and hypervariable segments. Examination of the GOS data in theseterms sheds light on patterns of evolution and also suggestsapproaches towards improving the assembly of complexmetagenomic datasets. At least some of this variation can beassociated with functional characters that are a directresponse to the environment. More than 6.1 million proteins,including thousands of new protein families, have beenannotated from this dataset (described in the accompanyingpaper [18]). In combination, these papers bring us closer toreconciling the genetic and biochemical disconnect and tounderstanding the marine microbial community.We describe a metagenomic dataset generated from theSorcerer II expedition. The GOS dataset, which includes andextends our previously published Sargasso Sea dataset [19],now encompasses a total of 41 aquatic, largely marinelocations, constituting the largest metagenomic dataset yetproduced with a total of ;7.7 million sequencing reads. InMarine microbes remain elusive and mysterious, even though theyare the most abundant life form in the ocean, form the base of themarine food web, and drive energy and nutrient cycling. We knowso little about the vast majority of microbes because only a smallpercentage can be cultivated and studied in the lab. Here we reporton the Global Ocean Sampling expedition, an environmentalmetagenomics project that aims to shed light on the role of marinemicrobes by sequencing their DNA without first needing to isolateindividual organisms. A total of 41 different samples were takenfrom a wide variety of aquatic habitats collected over 8,000 km. Theresulting 7.7 million sequencing reads provide an unprecedentedlook at the incredible diversity and heterogeneity in naturallyoccurring microbial populations. We have developed new bioinformatic methods to reconstitute large portions of both cultured anduncultured microbial genomes. Organism diversity is analyzed inrelation to sampling locations and environmental pressures. Takentogether, these data and analyses serve as a foundation for greatlyexpanding our understanding of individual microbial lineages andtheir evolution, the nature of marine microbial communities, andhow they are impacted by and impact our world.IntroductionThe concept of microbial diversity is not well defined. Itcan either refer to the genetic (taxonomic or phylogenetic)diversity as commonly measured by molecular geneticsmethods, or to the biochemical (physiological) diversitymeasured in the laboratory with pure or mixed cultures.However, we know surprisingly little about either the geneticor biochemical diversity of the microbial world [1], in partbecause so few microbes have been grown under laboratoryconditions [2,3], and also because it is likely that there areimmense numbers of low abundance ribotypes that have notbeen detected using molecular methods [4]. Our understanding of microbial physiological and biochemical diversityhas come from studying the less than 1% of organisms thatcan be maintained in enrichments or cultivated, while ourunderstanding of phylogenetic diversity has come from theapplication of molecular techniques that are limited in termsof identifying low-abundance members of the communities.Historically, there was little distinction between geneticand biochemical diversity because our understanding ofgenetic diversity was based on the study of cultivatedmicrobes. Biochemical diversity, along with a few morphological features, was used to establish genetic diversity via anapproach called numerical taxonomy [5,6]. In recent years thesituation has dramatically changed. The determination ofgenetic diversity has relied almost entirely on the use of geneamplification via PCR to conduct taxonomic environmentalgene surveys. This approach requires the presence of slowlyevolving, highly conserved genes that are found in otherwisevery diverse organisms. For example, the gene encoding thesmall ribosomal subunit RNA, known as 16S, based onsedimentation coefficient, is most often used for distinguishing bacterial and archaeal species [7–10]. The 16S rRNAsequences are highly conserved and can be used as aphylogenetic marker to classify organisms and place themin evolutionary context. Organisms whose 16S sequences areat least 97% identical are commonly considered to be thePLoS Biology www.plosbiology.org0399March 2007 Volume 5 Issue 3 e77

Sorcerer II GOS ExpeditionFigure 1. Sampling SitesMicrobial populations were sampled from locations in the order shown. Samples were collected at approximately 200 miles (320 km) intervals along theeastern North American coast through the Gulf of Mexico into the equatorial Pacific. Samples 00 and 01 identify sets of sites sampled as part of theSargasso Sea pilot study [19]. Samples 27 through 36 were sampled off the Galapagos Islands (see inset). Sites shown in gray were not analyzed as partof this environments as well as a few nonmarine aquatic samples forcontrast (Table 1).Several size fractions were isolated for every site (seeMaterials and Methods). Total DNA was extracted from oneor more fractions, mostly from the 0.1–0.8-lm size range.This fraction is dominated by bacteria, whose compactgenomes are particularly suitable for shotgun sequencing.Random-insert clone libraries were constructed. Dependingon the uniqueness of each sampling site and initial estimatesof the genetic diversity, between 44,000 and 420,000 clonesper sample were end-sequenced to generate mated sequencing reads. In all, the combined dataset includes 6.25 Gbp ofsequence data from 41 different locations. Many of the clonelibraries were constructed with a small insert size (,2 kbp) tomaximize cloning efficiency. As this often resulted in matedsequencing reads that overlapped one another, overlappingmated reads were combined, yielding a total of ;6.4 Mcontiguous sequences, totaling ;5.9 Gbp of nonredundantsequence. Taken together, this is the largest collection ofmetagenomic sequences to date, providing more than a 5-foldincrease over the dataset produced from the Sargasso Seapilot study [19] and more than a 90-fold increase over theother large marine metagenomic dataset [20].Sampling and the Metagenomic DatasetAssemblyMicrobial samples were collected as part of the Sorcerer IIexpedition between August 8, 2003, and May 22, 2004, by theS/V Sorcerer II, a 32-m sailing sloop modified for marineresearch. Most specimens were collected from surface watermarine environments at approximately 320-km (200-mile)intervals. In all, 44 samples were obtained from 41 sites(Figure 1), covering a wide range of distinct surface marineAssembling genomic data into larger contigs and scaffolds,especially metagenomic data, can be extremely valuable, as itplaces individual sequencing reads into a greater genomiccontext. A largely contiguous sequence links genes intooperons, but also permits the investigation of largerbiochemical and/or physiological pathways, and also connectsotherwise-anonymous sequences with highly studied ‘‘taxo-the pilot Sargasso Sea study, 200 l surface seawater wasfiltered to isolate microorganisms for metagenomic analysis.DNA was isolated from the collected organisms, and genomeshotgun sequencing methods were used to identify more than1.2 million new genes, providing evidence for substantialmicrobial taxonomic diversity [19]. Several hundred new anddiverse examples of the proteorhodopsin family of lightharvesting genes were identified, documenting their extensive abundance and pointing to a possible important role inenergy metabolism under low-nutrient conditions. However,substantial sequence diversity resulted in only limitedgenome assembly. These results generated many additionalquestions: would the same organisms exist everywhere in theocean, leading to improved assembly as sequence coverageincreased; what was the global extent of gene and gene familydiversity, and can we begin to exhaust it with a large butachievable amount of sequencing; how do regions of theocean differ from one another; and how are differentenvironmental pressures reflected in organisms and communities? In this paper we attempt to address these issues.PLoS Biology www.plosbiology.org0400March 2007 Volume 5 Issue 3 e77

PLoS Biology www.plosbiology.org0401Sargasso Stations 13 and 11Sargasso Stations 13 and 11Sargasso Stations 3Sargasso Stations 13Hydrostation SHydrostation SHydrostation SGulf of MaineBrowns Bank, Gulf of MaineOutside Halifax, Nova ScotiaBedford Basin, Nova ScotiaBay of Fundy, Nova ScotiaNorthern Gulf of MaineNewport Harbor, RIBlock Island, NYCape May, NJDelaware Bay, NJChesapeake Bay, MDOff Nags Head, NCSouth of Charleston, SCOff Key West, FLGulf of MexicoYucatan ChannelRosario BankNortheast of ColónLake GatunGulf of Panama250 miles from Panama City30 miles from Cocos IslandDirty Rock, Cocos Island134 miles NE of GalapagosDevil’s Crown, FloreanaCoastal FloreanaNorth James Bay, SantigoWarm seep, Roca RedondaUpwelling, FernandinaMangrove, IsabellaPunta Cormorant Lagoon, FloreanaNorth SeamoreWolf IslandCabo Marshall, IsabellaEquatorial Pacific TAO Buoy201 miles from French PolynesiaRangirora 30GS31GS32GS33GS34GS35GS36GS37GS47GS51TotalBermuda (UK)Bermuda (UK)Bermuda (UK)Bermuda (UK)Bermuda maCosta RicaCosta ationalFrench PolynesiaBermuda (UK)Bermuda 3:3517:0616:4412:5216:3815:257:043183296 99 n; 63835942 99 w31810950 99 n; 64819927 99 w31832910 99 n; 63835970 99 w31810950n; 64819927 99 w32809930 99 n; 64800936 99 w3183296 99 n; 63835942 99 w32810900 99 n 64830900 99 w32810900 99 n; 64830900 99 w32810900 99 n; 64830900 99 w42830911 99 n; 67814924 99 w42851910 99 n; 6681392 99 w4488914 99 n; 63838940 99 w44841925 99 n; 63838914 99 w4586942 99 n; 64856948 99 w43837956 99 n; 66850950 99 w4182999 99 n; 7182194 99 w4185928 99 n; 7183698 99 w38856924 99 n; 7484196 99 w3982594 99 n; 75830915 99 w38856949 99 n; 7682592 99 w3680914 99 n; 75823941 99 w32830925 99 n; 79815950 99 w24829918 99 n; 8384912 99 w24810929 99 n; 84820940 99 w20831921 99 n; 85824949 99 w1882912 99 n; 8384795 99 w10842959 99 n; 80815916 99 w989952 99 n; 79850910 99 w887945 99 n; 79841928 99 w6829934 99 n; 82854914 99 w5838924 99 n; 86833955 99 w5833910 99 n; 8785916 99 w1815951 99 n; 90817942 99 w1812958 99 s; 90825922 99 w181391 99 s; 90819911 99 w081290 99 s; 9085097 99 w0816920 99 n; 9183890 99 w081894 99 s; 9183996 99 w0835938 99 s; 9184910 99 w1813942 99 s; 90825945 99 w0822959 99 s; 90816947 99 w1823921 99 n; 9184991 99 w081915 99 s; 91811952 99 w1858926 99 s; 9580953 99 w1087953 99 s; 135826958 99 w1588937 99 s; 14782696 99 wDate,Time Locationmm/dd/yyTemperature.Salinity.cMeasurements were acquired from nearby vessels and/or research pleLocationIDTable 1. Sampling Locations and Environmental 190.670.333571673,3342,40010.4,200.4,2

surface (mostly marine) water samples were analyzed as part of the Sorcerer II Global Ocean Sampling expedition. These samples, collected across a several-thousand km transect from the North Atlantic through the Panama Canal and ending in the South Pacific yielded an extensive dataset consisting of 7.7 million sequencing reads (6.3 billion bp).

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