Evidence map›Paper›PMID 31551441›Full record

ArticleScientific reports2019

Functional metagenomic analysis of dust-associated microbiomes above the Red Sea.

Nojood A Aalismail, David K Ngugi, Rubén Díaz-Rúa, Intikhab Alam, Michael Cusack, Carlos M Duarte

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 6% of its field
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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Microbial ecology of the atmosphere.FEMS microbiology reviews · 2022
    Review
  10. Article
  11. Article
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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

6 authors at 2 institutions in 2 countries.

Nojood A AalismailRed Sea Research Centre (RSRC) and Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Saudi Arabia. Nojood.aalismail@kaust.edu.sa.
David K NgugiDepartment of Microorganisms, Leibniz Institute DSMZ - German Collection of Microorganisms and Cell Culture, Inhoffenstrasse 7B, B38124, Braunschweig, Germany.
Rubén Díaz-RúaRed Sea Research Centre (RSRC) and Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Saudi Arabia.ORCID http://orcid.org/0000-0001-7046-3500
Intikhab AlamComputational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.ORCID http://orcid.org/0000-0001-5306-847X
Michael CusackRed Sea Research Centre (RSRC) and Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Saudi Arabia.
Carlos M DuarteRed Sea Research Centre (RSRC) and Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Saudi Arabia.ORCID http://orcid.org/0000-0002-1213-1361
King Abdullah University of Science and Technology · SALeibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atmospheric transport is a major vector for the long-range transport of microbial communities, maintaining connectivity among them and delivering functionally important microbes, such as pathogens. Though the taxonomic diversity of aeolian microorganisms is well characterized, the genomic functional traits underpinning their survival during atmospheric transport are poorly characterized. Here we use functional metagenomics of dust samples collected on the Global Dust Belt to initiate a Gene Catalogue of Aeolian Microbiome (GCAM) and explore microbial genetic traits enabling a successful aeolian lifestyle in Aeolian microbial communities. The GCAM reported here, derived from ten aeolian microbial metagenomes, includes a total of 2,370,956 non-redundant coding DNA sequences, corresponding to a yield of ~31 × 10

Indexed as

ArchaeaBacteriaBiodiversityDNA DamageDustEukaryotaIndian OceanMetagenomeMetagenomicsMicrobiotaVirusesDust

Identifiers

PMID31551441
PMCPMC6760216
OpenAlexW2975748584

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.