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Francisco M. Cornejo-Castillo

Bio: Francisco M. Cornejo-Castillo is an academic researcher from Spanish National Research Council. The author has contributed to research in topics: Diazotroph & Prochlorococcus. The author has an hindex of 12, co-authored 24 publications receiving 2844 citations. Previous affiliations of Francisco M. Cornejo-Castillo include University of California, Berkeley & University of Paris.

Papers
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Journal ArticleDOI
22 May 2015-Science
TL;DR: This work identifies ocean microbial core functionality and reveals that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.
Abstract: Microbes are dominant drivers of biogeochemical processes, yet drawing a global picture of functional diversity, microbial community structure, and their ecological determinants remains a grand challenge. We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with >40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes. Using 139 prokaryote-enriched samples, containing >35,000 species, we show vertical stratification with epipelagic community composition mostly driven by temperature rather than other environmental factors or geography. We identify ocean microbial core functionality and reveal that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.

1,934 citations

Journal ArticleDOI
22 May 2015-Science
TL;DR: It is found that environmental factors are incomplete predictors of community structure and associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns.
Abstract: Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.

717 citations

Journal ArticleDOI
TL;DR: It is shown that by overcoming PCR biases related to amplification and primer mismatch, mi tags may provide more realistic estimates of community richness and evenness than amplicon 454 tags, and is now economically feasible given the dramatic reduction in high-throughput sequencing costs.
Abstract: Summary Sequencing of 16S rDNA polymerase chain reaction (PCR) amplicons is the most common approach for investigating environmental prokaryotic diversity, despite the known biases introduced during PCR. Here we show that 16S rDNA fragments derived from Illumina-sequenced environmental metagenomes (mitags) are a powerful alternative to 16S rDNA amplicons for investigating the taxonomic diversity and structure of prokaryotic communities. As part of the Tara Oceans global expedition, marine plankton was sampled in three locations, resulting in 29 subsamples for which metagenomes were produced by shotgun Illumina sequencing (ca. 700 Gb). For comparative analyses, a subset of samples was also selected for Roche-454 sequencing using both shotgun (m454tags; 13 metagenomes, ca. 2.4 Gb) and 16S rDNA amplicon (454tags; ca. 0.075 Gb) approaches. Our results indicate that by overcoming PCR biases related to amplification and primer mismatch, mitags may provide more realistic estimates of community richness and evenness than amplicon 454tags. In addition, mitags can capture expected beta diversity patterns. Using mitags is now economically feasible given the dramatic reduction in high-throughput sequencing costs, having the advantage of retrieving simultaneously both taxonomic (Bacteria, Archaea and Eukarya) and functional information from the same microbial community.

285 citations

Journal ArticleDOI
TL;DR: The first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene is reported, identifying the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered.
Abstract: The deep-sea is the largest biome of the biosphere, and contains more than half of the whole ocean's microbes. Uncovering their general patterns of diversity and community structure at a global scale remains a great challenge, as only fragmentary information of deep-sea microbial diversity exists based on regional-scale studies. Here we report the first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene. This work identifies the dominant prokaryotes in the pelagic deep ocean and reveals that 50% of the operational taxonomic units (OTUs) belong to previously unknown prokaryotic taxa, most of which are rare and appear in just a few samples. We show that whereas the local richness of communities is comparable to that observed in previous regional studies, the global pool of prokaryotic taxa detected is modest (~3600 OTUs), as a high proportion of OTUs are shared among samples. The water masses appear to act as clear drivers of the geographical distribution of both particle-attached and free-living prokaryotes. In addition, we show that the deep-oceanic basins in which the bathypelagic realm is divided contain different particle-attached (but not free-living) microbial communities. The combination of the aging of the water masses and a lack of complete dispersal are identified as the main drivers for this biogeographical pattern. All together, we identify the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered.

170 citations

Journal ArticleDOI
Adriana Alberti1, Julie Poulain, Stefan Engelen, Karine Labadie, Sarah Romac, Isabel Ferrera, Guillaume Albini, Jean-Marc Aury, Caroline Belser, Alexis Bertrand, Corinne Cruaud, Corinne Da Silva2, Carole Dossat, Frédérick Gavory, Shahinaz Gas, Guy Guy, Maud Haquelle, E'Krame Jacoby, Olivier Jaillon, Arnaud Lemainque, Eric Pelletier, Gaelle Samson, Mark Wessner, Pascal Bazire3, Odette Beluche3, Laurie Bertrand3, Marielle Besnard-Gonnet3, Isabelle Bordelais3, Magali Boutard, Maria Dubois4, Corinne Dumont5, Evelyne Ettedgui5, Patricia Fernandez6, Espérance Garcia7, Espérance Garcia8, Nathalie Aiach, Thomas Guerin, Chadia Hamon, Élodie Brun9, Sandrine Lebled10, Patricia Lenoble10, Claudine Louesse10, Eric Mahieu, Barbara Mairey, Nathalie Martins, Catherine Megret11, Claire Milani11, Jacqueline Muanga4, Jacqueline Muanga8, Céline Orvain12, Céline Orvain7, Emilie Payen, Peggy Perroud7, Peggy Perroud12, Emmanuel Petit, Dominique Robert, Murielle Ronsin, Benoit Vacherie, Silvia G. Acinas, Marta Royo-Llonch3, Francisco M. Cornejo-Castillo3, Ramiro Logares, Beatriz Fernández-Gómez3, Beatriz Fernández-Gómez13, Chris Bowler4, Guy Cochrane5, Clara Amid14, Petra ten Hoopen5, Colomban de Vargas, Nigel Grimsley, Élodie Desgranges7, Élodie Desgranges8, Stefanie Kandels-Lewis, Hiroyuki Ogata15, Nicole J. Poulton10, Michael E. Sieracki10, Ramunas Stepanauskas10, Matthew B. Sullivan11, Jennifer R. Brum, Melissa B. Duhaime16, Bonnie T. Poulos11, Bonnie L. Hurwitz11, Peer Bork, Emmanuel Boss, Michael J. Follows17, Gabriel Gorsky, Pascal Hingamp, Daniele Iudicone18, Lee Karp-Boss19, Eric Karsenti, Fabrice Not, Stephane Pesant, Jeroen Raes, Christian Sardet, Sabrina Speich, Lars Stemmann, Shinichi Sunagawa, Patrick Wincker20 
TL;DR: Detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, are provided and registries of genomics datasets available at the European Nucleotide Archive are described.
Abstract: A unique collection of oceanic samples was gathered by the Tara Oceans expeditions (2009-2013), targeting plankton organisms ranging from viruses to metazoans, and providing rich environmental context measurements. Thanks to recent advances in the field of genomics, extensive sequencing has been performed for a deep genomic analysis of this huge collection of samples. A strategy based on different approaches, such as metabarcoding, metagenomics, single-cell genomics and metatranscriptomics, has been chosen for analysis of size-fractionated plankton communities. Here, we provide detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, and we describe registries of genomics datasets available at the European Nucleotide Archive (ENA, www.ebi.ac.uk/ena). The association of these metadata to the experimental procedures applied for their generation will help the scientific community to access these data and facilitate their analysis. This paper complements other efforts to provide a full description of experiments and open science resources generated from the Tara Oceans project, further extending their value for the study of the world's planktonic ecosystems.

139 citations


Cited by
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01 Aug 2000
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

4,833 citations

Journal Article
TL;DR: FastTree as mentioned in this paper uses sequence profiles of internal nodes in the tree to implement neighbor-joining and uses heuristics to quickly identify candidate joins, then uses nearest-neighbor interchanges to reduce the length of the tree.
Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

2,436 citations

Journal ArticleDOI
TL;DR: The K EGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database, and the KO database for functional orthologs continues to be improved.
Abstract: KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which are perturbed molecular networks caused by human gene variants, viruses, other pathogens and environmental factors. The network variation maps are created as aligned sets of related networks showing, for example, how different viruses inhibit or activate specific cellular signaling pathways. The KEGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database. The KO database for functional orthologs continues to be improved and virus KOs are being expanded for better understanding of virus-cell interactions and for enabling prediction of viral perturbations.

2,087 citations

Journal ArticleDOI
TL;DR: It is shown that beyond in silico predictions, testing with mock communities and field samples is important in primer selection, and a single mismatch can strongly bias amplification, but even perfectly matched primers can exhibit preferential amplification.
Abstract: Summary Microbial community analysis via high-throughput sequencing of amplified 16S rRNA genes is an essential microbiology tool. We found the popular primer pair 515F (515F-C) and 806R greatly underestimated (e.g. SAR11) or overestimated (e.g. Gammaproteobacteria) common marine taxa. We evaluated marine samples and mock communities (containing 11 or 27 marine 16S clones), showing alternative primers 515F-Y (5′-GTGYCAGCMGCCGCGGTAA) and 926R (5′-CCGYCAATTYMTTTRAGTTT) yield more accurate estimates of mock community abundances, produce longer amplicons that can differentiate taxa unresolvable with 515F-C/806R, and amplify eukaryotic 18S rRNA. Mock communities amplified with 515F-Y/926R yielded closer observed community composition versus expected (r2 = 0.95) compared with 515F-Y/806R (r2 ∼ 0.5). Unexpectedly, biases with 515F-Y/806R against SAR11 in field samples (∼4–10-fold) were stronger than in mock communities (∼2-fold). Correcting a mismatch to Thaumarchaea in the 515F-C increased their apparent abundance in field samples, but not as much as using 926R rather than 806R. With plankton samples rich in eukaryotic DNA (> 1 μm size fraction), 18S sequences averaged ∼17% of all sequences. A single mismatch can strongly bias amplification, but even perfectly matched primers can exhibit preferential amplification. We show that beyond in silico predictions, testing with mock communities and field samples is important in primer selection.

2,077 citations

Journal ArticleDOI
22 May 2015-Science
TL;DR: This work identifies ocean microbial core functionality and reveals that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.
Abstract: Microbes are dominant drivers of biogeochemical processes, yet drawing a global picture of functional diversity, microbial community structure, and their ecological determinants remains a grand challenge. We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with >40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes. Using 139 prokaryote-enriched samples, containing >35,000 species, we show vertical stratification with epipelagic community composition mostly driven by temperature rather than other environmental factors or geography. We identify ocean microbial core functionality and reveal that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.

1,934 citations