Evidence map›Paper›PMID 26353777›Full record

ArticleMicrobiome2015

Metagenomic and metatranscriptomic inventories of the lower Amazon River, May 2011.

Brandon M Satinsky, Caroline S Fortunato, Mary Doherty, Christa B Smith, Shalabh Sharma, Nicholas D Ward, Alex V Krusche, Patricia L Yager, Jeffrey E Richey, Mary Ann Moran and 1 more

Abstract read
In one paragraph

Article in Microbiome, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

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  13. Biotechnology reports (Amsterdam, Netherlands) · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Brandon M SatinskyDepartment of Microbiology, University of Georgia, Athens, GA, 30602, USA. bsatinsk@uga.edu.
Caroline S FortunatoHorn Point, Laboratory University of Maryland Center for Environmental Science, Cambridge, MD, 21612, USA. cfortunato@mbl.edu.
Mary DohertyHorn Point, Laboratory University of Maryland Center for Environmental Science, Cambridge, MD, 21612, USA. themaryd@gmail.com.
Christa B SmithDepartment of Marine Sciences, University of Georgia, Athens, GA, 30605-3636, USA. cbs649@uga.edu.
Shalabh SharmaDepartment of Marine Sciences, University of Georgia, Athens, GA, 30605-3636, USA. ssharmai@uga.edu.
Nicholas D WardSchool of Oceanography, University of Washington, Seattle, WA, 98112, USA. nickdward@gmail.com.
Alex V KruscheCENA-USP, Avenida Centenário 303, 13416-000, Piracicaba, São Paulo, Brazil. alex@cena.usp.br.
Patricia L YagerDepartment of Marine Sciences, University of Georgia, Athens, GA, 30605-3636, USA.
Jeffrey E RicheySchool of Oceanography, University of Washington, Seattle, WA, 98112, USA. jrichey@u.washington.edu.
Mary Ann MoranDepartment of Marine Sciences, University of Georgia, Athens, GA, 30605-3636, USA. mmoran@uga.edu.
Byron C CrumpCollege of Earth, Ocean, and Atmospheric Science, Oregon State University, CEOAS Admin Bldg, Corvallis, OR, 97331-5503, USA. bcrump@coas.oregonstate.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Amazon River runs nearly 6500 km across the South American continent before emptying into the western tropical North Atlantic Ocean. In terms of both volume and watershed area, it is the world's largest riverine system, affecting elemental cycling on a global scale.

resultsA quantitative inventory of genes and transcripts benchmarked with internal standards was obtained at five stations in the lower Amazon River during May 2011. At each station, metagenomes and metatranscriptomes were obtained in duplicate for two microbial size fractions (free-living, 0.2 to 2.0 μm; particle-associated, 2.0 to 297 μm) using 150 × 150 paired-end Illumina sequencing. Forty eight sample datasets were obtained, averaging 15 × 10(6) potential protein-encoding reads each (730 × 10(6) total). Prokaryotic metagenomes and metatranscriptomes were dominated by members of the phyla Actinobacteria, Planctomycetes, Betaproteobacteria, Verrucomicrobia, Nitrospirae, and Acidobacteria. The actinobacterium SCGC AAA027-L06 reference genome recruited the greatest number of reads overall, with this single bin contributing an average of 50 billion genes and 500 million transcripts per liter of river water. Several dominant taxa were unevenly distributed between the free-living and particle-associated size fractions, such as a particle-associated bias for reads binning to planctomycete Schlesneria paludicola and a free-living bias for actinobacterium SCGC AAA027-L06. Gene expression ratios (transcripts to gene copy ratio) increased downstream from Óbidos to Macapá and Belém, indicating higher per cell activity of Amazon River bacteria and archaea as river water approached the ocean.

conclusionThis inventory of riverine microbial genes and transcripts, benchmarked with internal standards for full quantitation, provides an unparalleled window into microbial taxa and functions in the globally important Amazon River ecosystem.

Indexed as

MetagenomeMetagenomicsSeasonsTranscriptomeMicrobiotaRivers

Identifiers

PMID26353777
PMCPMC4564970

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.