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Author

Silvia G. Acinas

Bio: Silvia G. Acinas is an academic researcher from Spanish National Research Council. The author has contributed to research in topics: Metagenomics & Plankton. The author has an hindex of 45, co-authored 103 publications receiving 11663 citations. Previous affiliations of Silvia G. Acinas include Massachusetts Institute of Technology & Universidad Miguel Hernández de Elche.
Topics: Metagenomics, Plankton, Medicine, Biology, Population


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
Colomban de Vargas1, Colomban de Vargas2, Stéphane Audic2, Stéphane Audic1, Nicolas Henry2, Nicolas Henry1, Johan Decelle2, Johan Decelle1, Frédéric Mahé1, Frédéric Mahé2, Frédéric Mahé3, Ramiro Logares4, Enrique Lara, Cédric Berney2, Cédric Berney1, Noan Le Bescot1, Noan Le Bescot2, Ian Probert1, Ian Probert2, Margaux Carmichael5, Margaux Carmichael2, Margaux Carmichael1, Julie Poulain6, Sarah Romac1, Sarah Romac2, Sébastien Colin2, Sébastien Colin1, Sébastien Colin5, Jean-Marc Aury6, Lucie Bittner, Samuel Chaffron7, Samuel Chaffron8, Micah Dunthorn3, Stefan Engelen6, Olga Flegontova9, Olga Flegontova10, Lionel Guidi2, Lionel Guidi1, Aleš Horák9, Aleš Horák10, Olivier Jaillon11, Olivier Jaillon6, Olivier Jaillon2, Gipsi Lima-Mendez7, Gipsi Lima-Mendez8, Julius Lukeš12, Julius Lukeš9, Julius Lukeš10, Shruti Malviya5, Raphael Morard1, Raphael Morard13, Raphael Morard2, Matthieu Mulot, Eleonora Scalco14, Raffaele Siano15, Flora Vincent5, Flora Vincent8, Adriana Zingone14, Céline Dimier1, Céline Dimier5, Céline Dimier2, Marc Picheral2, Marc Picheral1, Sarah Searson1, Sarah Searson2, Stefanie Kandels-Lewis16, Tara Oceans Coordinators17, Silvia G. Acinas4, Peer Bork16, Peer Bork18, Chris Bowler5, Gabriel Gorsky2, Gabriel Gorsky1, Nigel Grimsley19, Nigel Grimsley2, Pascal Hingamp20, Daniele Iudicone14, Fabrice Not2, Fabrice Not1, Hiroyuki Ogata17, Stephane Pesant13, Jeroen Raes7, Jeroen Raes8, Michael E. Sieracki21, Michael E. Sieracki22, Sabrina Speich5, Sabrina Speich23, Lars Stemmann1, Lars Stemmann2, Shinichi Sunagawa16, Jean Weissenbach2, Jean Weissenbach6, Jean Weissenbach11, Patrick Wincker11, Patrick Wincker2, Patrick Wincker6, Eric Karsenti16, Eric Karsenti5 
22 May 2015-Science
TL;DR: Diversity emerged at all taxonomic levels, both within the groups comprising the ~11,200 cataloged morphospecies of eukaryotic plankton and among twice as many other deep-branching lineages of unappreciated importance in plankton ecology studies.
Abstract: Marine plankton support global biological and geochemical processes. Surveys of their biodiversity have hitherto been geographically restricted and have not accounted for the full range of plankton size. We assessed eukaryotic diversity from 334 size-fractionated photic-zone plankton communities collected across tropical and temperate oceans during the circumglobal Tara Oceans expedition. We analyzed 18S ribosomal DNA sequences across the intermediate plankton-size spectrum from the smallest unicellular eukaryotes (protists, >0.8 micrometers) to small animals of a few millimeters. Eukaryotic ribosomal diversity saturated at ~150,000 operational taxonomic units, about one-third of which could not be assigned to known eukaryotic groups. Diversity emerged at all taxonomic levels, both within the groups comprising the ~11,200 cataloged morphospecies of eukaryotic plankton and among twice as many other deep-branching lineages of unappreciated importance in plankton ecology studies. Most eukaryotic plankton biodiversity belonged to heterotrophic protistan groups, particularly those known to be parasites or symbiotic hosts.

1,378 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: An upper bound of roughly threefold overestimation of bacterial diversity resulting from cloning and sequencing of 16S rRNA genes from the environment is suggested, however, the inclusion of genomes with a single rrn operon may lower this correction factor to approximately 2.5.
Abstract: The level of sequence heterogeneity among rrn operons within genomes determines the accuracy of diversity estimation by 16S rRNA-based methods. Furthermore, the occurrence of widespread horizontal gene transfer (HGT) between distantly related rrn operons casts doubt on reconstructions of phylogenetic relationships. For this study, patterns of distribution of rrn copy numbers, interoperonic divergence, and redundancy of 16S rRNA sequences were evaluated. Bacterial genomes display up to 15 operons and operon numbers up to 7 are commonly found, but 40% of the organisms analyzed have either one or two operons. Among the Archaea ,a single operon appears to dominate and the highest number of operons is five. About 40% of sequences among 380 operons in 76 bacterial genomes with multiple operons were identical to at least one other 16S rRNA sequence in the same genome, and in 38% of the genomes all 16S rRNAs were invariant. For Archaea, the number of identical operons was only 25%, but only five genomes with 21 operons are currently available. These considerations suggest an upper bound of roughly threefold overestimation of bacterial diversity resulting from cloning and sequencing of 16S rRNA genes from the environment; however, the inclusion of genomes with a single rrn operon may lower this correction factor to 2.5. Divergence among operons appears to be small overall for both Bacteria and Archaea, with the vast majority of 16S rRNA sequences showing <1% nucleotide differences. Only five genomes with operons with a higher level of nucleotide divergence were detected, and Thermoanaerobacter tengcongensis exhibited the highest level of divergence (11.6%) noted to date. Overall, four of the five extreme cases of operon differences occurred among thermophilic bacteria, suggesting a much higher incidence of HGT in these bacteria than in other groups. rRNA sequences play a central role in the study of microbial evolution and ecology. Particularly, the 16S rRNA genes have become the standard for the determination of phylogenetic relationships, the assessment of diversity in the environment, and the detection and quantification of specific populations (14, 16). Indeed, the rRNAs combine several properties which make them uniquely suited for such diverse applications. First, they are universally distributed, allowing the comparison of phylogenetic relationships among all extant organisms and thus the construction of a “tree of life.” Second, the rRNAs are generally thought to be part of a core of informational genes which are only weakly affected by horizontal gene transfer (HGT) (1, 8), so their relationships provide a solid framework for the assessment of evolutionary changes in lineages. Third, the rRNAs are functionally highly constrained mosaics of sequence stretches ranging from conserved to more variable. This enables the design of PCR primers and hybridization probes with various levels of taxonomic specificity and is exploited in microbial ecology when the number and distribution of different rRNA genes are taken as a measure of diversity (14). A testimony to the significance of these approaches is the vast and growing database of 16S rRNA genes, of which an increasing number are derived from the large majority of uncultured Bacteria and Archaea. Although many of these organisms appear to dominate in the environment, their distribution and relationships are only known from clone libraries derived from nucleic acids recovered from the en

605 citations

Journal ArticleDOI
TL;DR: Taq DNA polymerase errors were found to be the dominant sequence artifact but could be constrained by clustering the sequences into 99% sequence similarity groups, and no skew in sequence types was detected in the two libraries constructed from PCR products amplified for different numbers of cycles.
Abstract: The contribution of PCR artifacts to 16S rRNA gene sequence diversity from a complex bacterioplankton sample was estimated. Taq DNA polymerase errors were found to be the dominant sequence artifact but could be constrained by clustering the sequences into 99% sequence similarity groups. Other artifacts (chimeras and heteroduplex molecules) were significantly reduced by employing modified amplification protocols. Surprisingly, no skew in sequence types was detected in the two libraries constructed from PCR products amplified for different numbers of cycles. Recommendations for modification of amplification protocols and for reporting diversity estimates at 99% sequence similarity as a standard are given.

595 citations


Cited by
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Journal ArticleDOI
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

14,171 citations

Journal ArticleDOI
TL;DR: UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences, and in testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus.
Abstract: Motivation: Chimeric DNA sequences often form during polymerase chain reaction amplification, especially when sequencing single regions (e.g. 16S rRNA or fungal Internal Transcribed Spacer) to assess diversity or compare populations. Undetected chimeras may be misinterpreted as novel species, causing inflated estimates of diversity and spurious inferences of differences between populations. Detection and removal of chimeras is therefore of critical importance in such experiments. Results: We describe UCHIME, a new program that detects chimeric sequences with two or more segments. UCHIME either uses a database of chimera-free sequences or detects chimeras de novo by exploiting abundance data. UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences. In testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus. UCHIME is >100× faster than Perseus and >1000× faster than ChimeraSlayer. Contact: [email protected] Availability: Source, binaries and data: http://drive5.com/uchime. Supplementary information:Supplementary data are available at Bioinformatics online.

11,904 citations

01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

10,124 citations

Journal ArticleDOI
TL;DR: The results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.
Abstract: We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.

6,679 citations

Journal ArticleDOI
18 Oct 2016-PeerJ
TL;DR: VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with US EARCH for paired-ends read merging and dereplication.
Abstract: Background: VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods: When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results: VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion: VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.

5,850 citations