Evidence map›Paper›PMID 35178038›Full record

ArticleFrontiers in microbiology2021

Definition of the Metagenomic Profile of Ocean Water Samples From the Gulf of Mexico Based on Comparison With Reference Samples From Sites Worldwide.

Antonio Loza, Fernando García-Guevara, Lorenzo Segovia, Alejandra Escobar-Zepeda, Maria Del Carmen Sanchez-Olmos, Enrique Merino, Alejandro Sanchez-Flores, Liliana Pardo-Lopez, Katy Juarez, Rosa-Maria Gutierrez-Rios

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

3 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

10 authors at 1 institution in 1 country.

Antonio LozaInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Fernando García-GuevaraInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Lorenzo SegoviaInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Alejandra Escobar-ZepedaInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Maria Del Carmen Sanchez-OlmosInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Enrique MerinoInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Alejandro Sanchez-FloresInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Liliana Pardo-LopezInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Katy JuarezInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Rosa-Maria Gutierrez-RiosInstituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
Universidad Nacional Autónoma de México · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computational and statistical analysis of shotgun metagenomes can predict gene abundance and is helpful for elucidating the functional and taxonomic compositions of environmental samples. Gene products are compared against physicochemical conditions or perturbations to shed light on the functions performed by the microbial community of an environmental sample; however, this information is not always available. The present study proposes a method for inferring the metabolic potential of metagenome samples by constructing a reference based on determining the probability distribution of the counts of each enzyme annotated. To test the methodology, we used marine water samples distributed worldwide as references. Then, the references were utilized to compare the annotated enzymes of two different water samples extracted from the Gulf of Mexico (GoM) to distinguish those enzymes with atypical behavior. The enzymes whose annotation counts presented frequencies significantly different from those of the reference were used to perform metabolic reconstruction, which naturally identified pathways. We found that several of the enzymes were involved in the biodegradation of petroleum, which is consistent with the impact of human hydrocarbon extraction activity and its ubiquitous presence in the GoM. The examination of other reconstructed pathways revealed significant enzymes indicating the presence of microbial communities characterizing each ocean depth and ocean cycle, providing a fingerprint of each sampled site.

Indexed as

Gulf of Mexicohydrocarbon degradationkey enzymesmetabolic networkmetabolic potentialreference metagenomes

Identifiers

PMID35178038
PMCPMC8846951
OpenAlexW4210789001

What OpenQuestion holds

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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.