Evidence map›Paper›PMID 19789910›Full record

ArticleMicrobial ecology2010

Bacterial community structure of sediments of the bizerte lagoon (Tunisia), a southern Mediterranean coastal anthropized lagoon.

Olfa Ben Said, Marisol Goñi-Urriza, Monia El Bour, Patricia Aissa, Robert Duran

Abstract read
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In one paragraph

Article in Microbial ecology, 2010. 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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  5. Detection of Extended-SpectrumBioMed research international · 2020
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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

5 authors.

Olfa Ben SaidEquipe Environnement et Microbiologie-IPREM UMR 5254-IBEAS, Université de Pau et des Pays de l'Adour, Avenue de l'Université, BP 1155, 64013 Pau Cedex, France.
Marisol Goñi-Urriza
Monia El Bour
Patricia Aissa
Robert Duran

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to estimate how pollution affects the bacterial community structure and composition of sediments, chemical and molecular approaches were combined to investigate eight stations around the Bizerte lagoon. Terminal restriction fragment length polymorphism (T-RFLP) analysis of PCR-amplified 16S rRNA genes revealed that each station was characterized by a specific bacterial community structure. The combination of this data with those of chemical analysis showed a correlation between the bacterial fingerprint and the pollutant content, principally with hydrocarbon pollution. The composition of the bacterial community of two contrasted stations related to the pollution revealed sequences affiliated to alpha, beta, gamma, delta, epsilon subclass of the Proteobacteria, Actinobacteria, and Acidobacteria in both stations although in different extent. Gamma and delta subclass of the Proteobacteria were dominant and represent 70% of clones in the heavy-metal-contaminated station and 47% in the polyaromatic hydrocarbon (PAH)-contaminated. Nevertheless, most of the sequences found were unaffiliated to cultured bacteria. The adaptation of the bacterial community mainly to PAH compounds demonstrated here and the fact that these bacterial communities are mainly unknown suggest that the Bizerte lagoon is an interesting environment to understand the capacity of bacteria to cope with some pollutants.

Indexed as

BacteriaDNA FingerprintingGene LibraryGeologic SedimentsHydrocarbonsMediterranean RegionMetals, HeavyPhylogenyPolycyclic Aromatic HydrocarbonsPolymorphism, Restriction Fragment LengthRNA, BacterialRNA, Ribosomal, 16SSeawaterSequence Analysis, DNATunisiaWater Pollutants, ChemicalHydrocarbonsMetals, HeavyPolycyclic Aromatic HydrocarbonsRNA, BacterialRNA, Ribosomal, 16SWater Pollutants, Chemical

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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.