Molecular mechanisms of zinc toxicity in the potworm Enchytraeus crypticus, analysed by high-throughput gene expression profiling

Susana I.L. Gomes, Tjalf E. de Boer, Cornelis A.M. van Gestel, Nico M. van Straalen, Amadeu M.V.M. Soares, Dick Roelofs, Mónica J.B. Amorim*

*Corresponding author for this work

    Research output: Contribution to JournalArticleAcademicpeer-review

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    Abstract

    Zinc (Zn) is known to be relatively toxic to some soil-living invertebrates including the ecologically important enchytraeid worms. To reveal the molecular mechanisms of zinc toxicity we assessed the gene expression profile of Enchytraeus crypticus (Enchytraeidae), exposed to the reproduction effect concentrations EC10 and EC50, over 4 consecutive days, using a high-throughput microarray (species customized). Three main mechanisms of toxicity to Zn were observed: 1) Zn trafficking (upregulation of zinc transporters, a defence response to regulate the cellular zinc level), 2) oxidative stress (variety of defence mechanisms, triggered by Reactive Oxygen Species (ROS)), and 3) effects on the nervous system (possibly the primary lesion explaining the avoidance behaviour and also why enchytraeids are relatively susceptible to Zn). The adverse outcome at the organism level (reproduction EC50) could be predicted based on gene expression (male gonad development, oocyte maturation), with Zn at the EC50 affecting processes related to higher stress levels. The gene expression response was time-dependent and reflected the cascade of events taking place over-time. The 1 to 4 days of exposure design was a good strategy as it captured the time for sequence of events towards zinc adverse outcomes in E. crypticus.

    Original languageEnglish
    Article number153975
    Pages (from-to)1-7
    Number of pages7
    JournalScience of the Total Environment
    Volume825
    Early online date17 Feb 2022
    DOIs
    Publication statusPublished - 15 Jun 2022

    Bibliographical note

    Funding Information:
    This study was supported by the European Commission Project H2020-NMBP-2017 BIORIMA (GA No. 760928 ), NanoInformaTIX (H2020-NMBP-14-2018, No. 814426 ) and NANORIGO (H2020-NMBP-13-2018, GA No. 814530 ). Further support was due to FCT / MCTES through national funds (PIDDAC), and the co-funding by the FEDER , within the PT2020 Partnership Agreement and Compete 2020 via “BEAUTY: Big gEnome wide Applications for an ecotoxicology soil model – a knowledge base to Unravel mechanisms (nanopesTY_cides)” ( PTDC/CTA-AMB/3970/2020 ) and via CESAM ( UIDP/50017/2020+UIDB/50017/2020+LA/P/0094/2020 ). S.I.L. Gomes is funded by national funds (OE), through FCT , I.P., in the scope of the framework contract foreseen in the numbers 4, 5 and 6 of the article 23, of the Decree-Law 57/2016, of August 29, changed by Law 57/2017, of July 19.

    Publisher Copyright:
    © 2022 Elsevier B.V.

    Funding

    This study was supported by the European Commission Project H2020-NMBP-2017 BIORIMA (GA No. 760928 ), NanoInformaTIX (H2020-NMBP-14-2018, No. 814426 ) and NANORIGO (H2020-NMBP-13-2018, GA No. 814530 ). Further support was due to FCT / MCTES through national funds (PIDDAC), and the co-funding by the FEDER , within the PT2020 Partnership Agreement and Compete 2020 via “BEAUTY: Big gEnome wide Applications for an ecotoxicology soil model – a knowledge base to Unravel mechanisms (nanopesTY_cides)” ( PTDC/CTA-AMB/3970/2020 ) and via CESAM ( UIDP/50017/2020+UIDB/50017/2020+LA/P/0094/2020 ). S.I.L. Gomes is funded by national funds (OE), through FCT , I.P., in the scope of the framework contract foreseen in the numbers 4, 5 and 6 of the article 23, of the Decree-Law 57/2016, of August 29, changed by Law 57/2017, of July 19.

    FundersFunder number
    Horizon 2020 Framework Programme
    European Commission760928, 814426, H2020-NMBP-13-2018, 814530, H2020-NMBP-14-2018
    Fundação para a Ciência e a Tecnologia
    Ministério da Ciência, Tecnologia e Ensino Superior
    European Regional Development FundLA/P/0094/2020, PTDC/CTA-AMB/3970/2020

      Keywords

      • AOP (adverse outcome pathway)
      • Microarrays
      • Soil
      • Time series

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