Evidence map›Paper›PMID 34341931›Full record

ArticleEnvironmental science and pollution research international2022

Screening of metallic pollution in complex environmental samples through a transcriptomic fingerprint method.

Mickael Cregut, Anna Hua, Sulivan Jouanneau, Ali Assaf, Christophe B Y Cordella, Gérald Thouand, Marie-José Durand

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Mickael Cregut *University of Nantes, Oniris, CNRS, GEPEA, UMR 6144, F-85000, La Roche sur Yon, France. mickael.cregut@univ-nantes.fr.ORCID http://orcid.org/0000-0002-2779-4475
Anna Hua *University of Nantes, Oniris, CNRS, GEPEA, UMR 6144, F-85000, La Roche sur Yon, France.
Sulivan JouanneauUniversity of Nantes, Oniris, CNRS, GEPEA, UMR 6144, F-85000, La Roche sur Yon, France.
Ali AssafUniversity of Nantes, Oniris, CNRS, GEPEA, UMR 6144, F-85000, La Roche sur Yon, France.
Christophe B Y CordellaUniversity of Paris-Saclay, UMR AgroParisTech/INRA 914 Physiologie de la Nutrition et du Comportement Alimentaire, Rue Claude Bernard, 75, ,005, Paris, France.
Gérald ThouandUniversity of Nantes, Oniris, CNRS, GEPEA, UMR 6144, F-85000, La Roche sur Yon, France.
Marie-José DurandUniversity of Nantes, Oniris, CNRS, GEPEA, UMR 6144, F-85000, La Roche sur Yon, France.

Funding

Conseil Régional des Pays de la Loire MATIERES Research program
6 · The paper itself

Abstract

Characterizing waste ecotoxicity is laborious because of both the undefined nature of environmental samples and the diversity of contaminants that can be present. With regard to these limitations, traditional approaches do not provide information about the nature of the pollution encountered. To improve such assessments, a fluorescent library of 1870 transcriptomic reporters from Escherichia coli K12 MG1655 was used to report the ecotoxic status of environmental samples. The reliability of the approach was evaluated with 6 metallic pollutants (As, Cu, Cd, Hg, Pb, Zn) used alone and in mixture in pure and complex matrices. A total of 18 synthetic samples were used to characterize the specificity of the resulting metallic contamination fingerprints. Metallic contamination impacted 4.5 to 10.2% of the whole transcriptomic fingerprint of E. coli. The analysis revealed that a subset of 175 transcriptomic reporters is sufficient to characterize metallic contamination, regardless of the nature of the sample. A statistical model distinguished patterns due to metallic contamination and provided information about the level of toxicity with 93 to 98% confidence. The use of the transcriptomic assessment was validated for 17 complex matrices with various toxicities and metal contaminants, such as activated sludge, wastewater effluent, soil, wood and river water. The presence of metals and their associated toxicity, which seems linked to their bioavailabilities, were thereby determined. This method constitutes a possible tool to screen unknown complex samples for their metallic status and identify those for which a deeper characterization must be achieved by the use of traditional biosensors and analytical methods.

Indexed as

Metals, HeavySoil PollutantsWater Pollutants, ChemicalChinaEnvironmental MonitoringEscherichia coliReproducibility of ResultsRisk AssessmentTranscriptomeWastewaterMetals, HeavySoil PollutantsWastewaterWater Pollutants, ChemicalBioassaysBioreporterBiosensorEcotoxicity assessmentEnvironmental pollutantsMetalsTranscriptome profiling

Identifiers

What OpenQuestion holds

Textmetadata
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.