Literature DB >> 29475721

A cross-taxa study using environmental DNA/RNA metabarcoding to measure biological impacts of offshore oil and gas drilling and production operations.

Olivier Laroche1, Susanna A Wood2, Louis A Tremblay3, Joanne I Ellis4, Gavin Lear5, Xavier Pochon6.   

Abstract

Standardized ecosystem-based monitoring surveys are critical for providing information on marine ecosystem health. Environmental DNA/RNA (eDNA/eRNA) metabarcoding may facilitate such surveys by quickly and effectively characterizing multi-trophic levels. In this study, we assessed the suitability of eDNA/eRNA metabarcoding to evaluate changes in benthic assemblages of bacteria, Foraminifera and other eukaryotes along transects at three offshore oil and gas (O&G) drilling and production sites, and compared these to morphologically characterized macro-faunal assemblages. Bacterial communities were the most responsive to O&G activities, followed by Foraminifera, and macro-fauna (the latter assessed by morphology). The molecular approach enabled detection of hydrocarbon degrading taxa such as the bacteria Alcanivorax and Microbulbifer at petroleum impacted stations. Most identified indicator taxa, notably among macro-fauna, were highly specific to site conditions. Based on our results we suggest that eDNA/eRNA metabarcoding can be used as a stand-alone method for biodiversity assessment or as a complement to morphology-based monitoring approaches.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bacteria 16S; Benthic ecology; Biomonitoring; Eukaryotes 18S; Foraminifera 18S; High-throughput sequencing

Mesh:

Substances:

Year:  2017        PMID: 29475721     DOI: 10.1016/j.marpolbul.2017.11.042

Source DB:  PubMed          Journal:  Mar Pollut Bull        ISSN: 0025-326X            Impact factor:   5.553


  12 in total

1.  Evaluating putative ecological drivers of microcystin spatiotemporal dynamics using metabarcoding and environmental data.

Authors:  A Banerji; M J Bagley; J A Shoemaker; D R Tettenhorst; C T Nietch; H J Allen; J W Santo Domingo
Journal:  Harmful Algae       Date:  2019-05-31       Impact factor: 4.273

2.  Developing Indicators of Nutrient Pollution in Streams Using 16S rRNA Gene Metabarcoding of Periphyton-Associated Bacteria.

Authors:  Erik M Pilgrim; Nathan J Smucker; Huiyun Wu; John Martinson; Christopher T Nietch; Marirosa Molina; John A Darling; Brent R Johnson
Journal:  Water (Basel)       Date:  2022-07-30       Impact factor: 3.530

3.  Metatranscriptomic Analysis of Oil-Exposed Seawater Bacterial Communities Archived by an Environmental Sample Processor (ESP).

Authors:  Kamila Knapik; Andrea Bagi; Adriana Krolicka; Thierry Baussant
Journal:  Microorganisms       Date:  2020-05-15

4.  Diatom diversity through HTS-metabarcoding in coastal European seas.

Authors:  Roberta Piredda; Jean-Michel Claverie; Johan Decelle; Colomban de Vargas; Micah Dunthorn; Bente Edvardsen; Wenche Eikrem; Dominik Forster; Wiebe H C F Kooistra; Ramiro Logares; Ramon Massana; Marina Montresor; Fabrice Not; Hiroyuki Ogata; Jan Pawlowski; Sarah Romac; Diana Sarno; Thorsten Stoeck; Adriana Zingone
Journal:  Sci Rep       Date:  2018-12-24       Impact factor: 4.379

Review 5.  Environmental DNA and RNA as Records of Human Exposome, Including Biotic/Abiotic Exposures and Its Implications in the Assessment of the Role of Environment in Chronic Diseases.

Authors:  Indu Shekhar Thakur; Deodutta Roy
Journal:  Int J Mol Sci       Date:  2020-07-10       Impact factor: 5.923

Review 6.  Omics-based ecosurveillance for the assessment of ecosystem function, health, and resilience.

Authors:  David J Beale; Oliver A H Jones; Utpal Bose; James A Broadbent; Thomas K Walsh; Jodie van de Kamp; Andrew Bissett
Journal:  Emerg Top Life Sci       Date:  2022-04-15

7.  Environmental DNA metabarcoding reveals comparable responses to agricultural stressors on different trophic levels of a freshwater community.

Authors:  Kevin K Beentjes; S Henrik Barmentlo; Ellen Cieraad; Menno Schilthuizen; Berry B van der Hoorn; Arjen G C L Speksnijder; Krijn B Trimbos
Journal:  Mol Ecol       Date:  2022-01-06       Impact factor: 6.622

8.  Dumpster diving for diatom plastid 16S rRNA genes.

Authors:  Krista L Bonfantine; Stacey M Trevathan-Tackett; Ty G Matthews; Ana Neckovic; Han Ming Gan
Journal:  PeerJ       Date:  2021-07-01       Impact factor: 2.984

9.  DNA metabarcoding of littoral hard-bottom communities: high diversity and database gaps revealed by two molecular markers.

Authors:  Owen S Wangensteen; Creu Palacín; Magdalena Guardiola; Xavier Turon
Journal:  PeerJ       Date:  2018-05-04       Impact factor: 2.984

10.  Sample size effects on the assessment of eukaryotic diversity and community structure in aquatic sediments using high-throughput sequencing.

Authors:  Francisco J A Nascimento; Delphine Lallias; Holly M Bik; Simon Creer
Journal:  Sci Rep       Date:  2018-08-06       Impact factor: 4.379

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