2017 Progress Report: Dynamical Systems Models Based on Energy Budgets for Ecotoxicological Impact Assessment

EPA Grant Number: R835797
Title: Dynamical Systems Models Based on Energy Budgets for Ecotoxicological Impact Assessment
Investigators: Nisbet, Roger M. , Muller, Erik B , Whitehead, Andrew
Institution: University of California - Santa Barbara , University of California - Davis
EPA Project Officer: Lasat, Mitch
Project Period: June 1, 2015 through May 31, 2018 (Extended to May 31, 2019)
Project Period Covered by this Report: June 1, 2017 through May 31,2018
Project Amount: $799,723
RFA: Systems-Based Research for Evaluating Ecological Impacts of Manufactured Chemicals (2014) RFA Text |  Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Ecosystems , Safer Chemicals

Objective:

The overarching questions motivating the research are:

a. How do changes in suborganismal-level endpoints (e.g., molecular, cellular, and tissue level responses) relate qualitatively and quantitatively to changes in apical endpoints such as survival, growth, and reproduction?

b. How can we characterize the qualitative and quantitative relationships between changes in apical endpoints and those at higher levels of biological organization (population, community, landscape)?

The specific objectives are:

Objective 1: Formulate and test new theory relating organismal dynamics to suborganismal responses to toxicant exposure

- 1a) Develop new DEB models with mechanistic connections to suborganismal processes including those currently used in Adverse Outcome Pathway (AOP) studies

- 1b) Use data from literature and new experiments to determine for two model organisms the extent to which transcriptomic data relate to DEB model parameters and organismal dynamics

- 1c) Use the new DEB models for qualitative prediction of “tipping points” caused by failure of feedback processes within an organism.

Objective 2: Use individual-based population models to predict possible population level responses to exposure to toxicants

- 2a) Formulate and test individual-based population models to project effects on interacting phytoplankton and zooplankton populations

- 2b) Use models from objective 2a to investigate the likelihood of “tipping points” representing abrupt extinctions

- 2c) Develop models of adaptation to stress that take account of sub-organismal regulatory processes and thereby provide tools for evaluating the likelihood of evolutionary rescue in chronically polluted environments.

Objective 3: Investigate applicability of new concepts to non-model organisms

- 3a) Determine the additional information required for generalizing findings from

objectives 1 and 2.

Progress Summary:

Objective 1a. In years 1 and 2, in collaboration with Dr. Cheryl Murphy and others, we developed a new, general, conceptual framework for relating information from Adverse Outcome Pathways (AOP) to processes in DEB models. The key idea in that work is to relate “key events” in an AOP with abstract “damage” variables in dynamic energy budget (DEB) theory. In year 3, we completed a publication that emphasizes practical application of the new framework [4]. We developed and published new DEB theory on the dynamics of variables describing “damage” to organisms exposed to environmental stress [3]. We also continued work on the variant (demandDEB) of the “standard” DEB model, reported in year 2 and intended for application to fish with an annual reproductive cycle. A manuscript on that work, with application to rainbow trout, was submitted for publication and is currently in revision following reviews.

Objective 1b. The greatest effort in year 3 focused on applying and testing the new methodology, described in 1a, on the Atlantic killifish Fundulus heteroclitus. This work is being performed in collaboration with Dr. Diane Nacci’s group (EPA Atlantic Ecology Division). We are testing our models using dioxin-like chemicals (DLCs), which are of particular interest in this species due to the well-documented large intraspecific variability in sensitivity of F. heteroclitus to DLCs. The accepted AOP for DLC exposure is through activation of the Aryl hydrocarbon receptor (AhR) pathway, however the precise toxic mechanism of DLCs is poorly understood. Many previous studies involving DLCs have survival as an endpoint, but sublethal effects of DLCs are less studied. Preliminary data indicate that sublethal exposure to PCB126 during embryonic development reduces growth rate in larval killifish (Nacci Lab, unpublished data). We connected AOP Key Events (KEs) to DEB processes through a TK/TD representation of “damage” dynamics, driven by the internal toxicant concentration. In our model, damage-inducing compounds are produced at a rate proportional to the body burden of toxicant; in turn these damage-inducing compounds inflict damage. We used suborganismal information, specifically CYP1A induction rates (an enzyme that is a hallmark of AhR pathway activation) to parametrize the process of damage production. The model predicts regulated but increasing concentrations of damage in response to increasing toxicant exposure and also “tipping points” of internal toxicant concentration above which damage outpaces regulatory feedbacks, leading to mortality. A feedback mechanism whereby damage impacts DEB parameters that in turn impact organismal endpoints was hypothesized from transcriptomic information, using DAVID analysis to identify a handful of significantly enriched gene clusters from data on hundreds of genes, giving a broad outline of impacted pathways. The model fits data on effects on sublethal growth of larval fish and relates the tipping point in damage dynamics to the onset of lethal effects. As an independent model test, we are testing the model’s ability to use low-level data to predict the response of fish from a population previous shown to be resistant to DLCs. In previous years, working in collaboration with 5 members of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) working group we designed a sampling regime for following changes in gene expression and vital processes in experiments on individual Daphnia exposed to fly ash. The experiments on growth, reproduction, and survival, were completed during the current reporting period. RNA samples were extracted, and RNAseq analysis is in progress.

Objective 1c. The theoretical work on tipping points was completed and in described in year 1 report. This theory is now being applied. Specifically, the dynamic mechanism responsible for the occurrence of the tipping point in the theory is part of the killifish model (objective 1b).

Objective 2a. In year 2, we reported progress in parameterizing and testing a DEB model that underpins an individual based population model of the response of interacting phytoplankton and Daphnia populations to waterborne silver nanoparticles. The primary finding was that feedbacks mediated by indirect effects on phytoplankton may to some extent mitigate the impacts of exposure. A paper on this work is in preparation, but completion has been delayed because of prioritizing the killifish work under objective 1b. The paper will be completed during the no-cost extension.

Objective 2b. There was no work on this during the reporting period.

Objective 2c. We have started work on a DEB-based approach using a phytoplankton model.

Objective 3a. As a first step towards generalizing our new theory and mathematical models to non-model organisms, we are developing models of inter-specific variation in no-effect concentration (NEC). Our model was motivated by a publication in 2015 by J. Baas and S.A.L.M. Kooijman, who found that for several compounds, NEC co-varies negatively with mass-specific metabolic rate. We hypothesize that an organism’s response to increasing stress involves a cascade of failures of metabolic regulatory processes, represented mathematically by tipping points in damage dynamics, as described above. NEC is now identified with the tipping point as it represents the point at which some very low-level regulation fails. We have derived a formula that predicts the variation of NEC with organism size, but requires knowledge of the bioconcentration factor for non-model organisms. One immediate area of application will be to help interpret species sensitivity distributions (SSDs); we are pursuing this possibility using published SSDs for several engineered nanoparticles.

Leveraged activities

Leveraged activities enhanced by this award included an application of the representation of “damage” dynamics used in the killifish modeling to an important disease [1], a DEB model of coral bleaching[2], and applications of DEB theory and related dynamic models in projects performed in collaboration with investigators in the University of California Center for Environmental Implications of Nanotechnology (UC CEIN). UC CEIN related work included DEB-inspired models of mortality in amphipods exposed to CuCl2 and to several copper nanoparticles, and remediation of cadmium toxicity in phytoplankton by sulfidized nano-iron [5]. The latter study inspired a new project, in collaboration with Dr. P. Antczac (University of Liverpool, UK), in which we conducted an experiment exposing Chlamydomonas reinhardtii, a naturally abundant and widely studied freshwater green algae, to copper (CuCl2) and collected samples for whole organismal effects (biomass measured by chlorophyll), metabolomic response, nutrient availability (PO4), and copper concentration at multiple time points. The metabolomic data will allow us to connect the dynamic response of algae to its suborganismal signal, identifying specific metabolites that we hypothesize could explain copper-induced changes in energy use as predicted by DEB models. This connection between suborganismal (metabolomic) and organismal-level information may enhance our ability to utilize existing data on molecular responses of algae to toxicants to predict effects on whole cells and on populations of algae.

Future Activities:

Top priority during the remaining (no-cost extension) year of the award is to complete work on the primary case studies (objective 1b) with two papers submitted. We also anticipate that the delayed paper relating population dynamics to individual organismal responses of Daphnia exposed to silver nanoparticles will be submitted (objective 2a). We aim to advance objective 2c (adaptation to stressed environments) using literature data on freshwater phytoplankton. We will continue the study of NECs in non-model organisms as described above (objective 3a).


Journal Articles on this Report : 5 Displayed | Download in RIS Format

Other project views: All 38 publications 14 publications in selected types All 13 journal articles
Type Citation Project Document Sources
Journal Article Civitello DJ, Fatima H, Johnson LR, Nisbet RM, Rohr JR. Bioenergetic theory predicts infection dynamics of human schistosomes in intermediate host snails across ecological gradients. Ecology Letters 2018;21(5):692-701. R835797 (2017)
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  • Journal Article Cunning R, Muller EB, Gates RD, Nisbet RM. A dynamic bioenergetic model for coral-Symbiodinium symbioses and coral bleaching as an alternate stable state. Journal of Theoretical Biology 2017;431:49-62. R835797 (2017)
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  • Journal Article Murphy CA, Nisbet RM, Antczak P, Garcia-Reyero N, Gergs A, Lika K, Mathews T, Muller EB, Nacci D, Peace A, Remien CH, Schultz IR, Stevenson LM, Watanabe KH. Incorporating suborganismal processes into dynamic energy budget models for ecological risk assessment. Integrated Environmental Assessment and Management 2018;14(5):615-624. R835797 (2017)
    R835798 (2017)
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  • Journal Article Stevenson LM, Krattenmaker KE, Johnson E, Bowers AJ, Adeleye AS, McCauley E, Nisbet RM. Standardized toxicity testing may underestimate ecotoxicity:environmentally relevant food rations increase the toxicity of silver nanoparticles to Daphnia. Environmental Toxicology and Chemistry 2017;36(11):3008-2018. R835797 (2016)
    R835797 (2017)
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  • Journal Article Stevenson LM, Adeleye AS, Su Y, Zhang Y, Keller AA, Nisbet RM. Remediation of cadmium toxicity by sulfidized nano-iron: the importance of organic material. ACS Nano 2017;11(10):10558-10567. R835797 (2017)
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  • Supplemental Keywords:

    Individual-based model; dynamic energy budget, DEB, DEBtox; adverse outcome pathways; metabolism; ecology; ecosystem; scaling; toxics.

    Progress and Final Reports:

    Original Abstract
  • 2015 Progress Report
  • 2016 Progress Report