Grantee Research Project Results

2015 Progress Report: Development of a larval fish neurobehavior adverse outcome pathway to predict effects of contaminants at the ecosystem level and across multiple ecologically relevant taxa

EPA Grant Number: R835798
Title: Development of a larval fish neurobehavior adverse outcome pathway to predict effects of contaminants at the ecosystem level and across multiple ecologically relevant taxa
Investigators: Murphy, Cheryl A. , Carvan, Michael , Jones, Michael , Garcia-Reyero, Natàlia
Current Investigators: Murphy, Cheryl A. , Garcia-Reyero, Natàlia , Carvan, Michael , Jones, Michael
Institution: Michigan State University , Mississippi State University , University of Wisconsin - Milwaukee
Current Institution: Michigan State University , University of Wisconsin - Milwaukee , Mississippi State University
EPA Project Officer: Spatz, Kyle
Project Period: June 1, 2015 through May 31, 2018 (Extended to May 31, 2021)
Project Period Covered by this Report: June 1, 2015 through May 31,2016
Project Amount: $800,000
RFA: Systems-Based Research for Evaluating Ecological Impacts of Manufactured Chemicals (2014) RFA Text |  Recipients Lists
Research Category: Chemical Safety for Sustainability

Objective:

The overall objective of this project is to advance the adverse outcome pathway framework to predict effects of contaminants with different modes of action on the neurobehavior of larval fish from three different species and to determine what Adverse Outcome Pathways (AOPs) are common between species

Objective 1: Identify genes predictive of neurobehavior toxicity in response to exposure to two different chemicals with different molecular initiating events and modes of action in order to identify neurobehavior AOPs using a reverse engineering approach on zebrafish

Objective 2: Determine the effects of PCB126 and MeHg on gene expression and behavior of the larval stage of two species of ecological relevance (fathead minnow and yellow perch).

Objective 3: Incorporate behavioral effects and transcriptomics data from fathead minnow and yellow perch into an individual-based model (IBM) to predict changes in growth and survival to complete the neurobehavior AOP suitable for ecological risk assessment for MeHg and PCB126.

Objective 4: Define and compare neurobehavioral AOPs between species and contaminants to determine their similarities and to elucidate what kind of information is lost or gained by using a typical laboratory model to inform on environmentally relevant species at the population level.

Progress Summary:

The start of our project was delayed because of a delay in funding and it took a few months to search and hire post-doctoral research associates. However, we have made some significant progress.

Objective 1 and Objective 2

We developed a new microdissection technique to isolate larval fish brains for transcriptomic work. This technique will be quite valuable for the future because of the interest in using larval zebrafish in neurodevelopment work (for human and fish health evaluations). The microdissection technique successfully isolated the brain (Figure 1), and good quality RNA was extracted from 6-dpf zebrafish brains. Data from preliminary samples: 2.2 + 0.5 ng RNA per brain (mean+SD; n= 4 brains) with a RIN value of 8.35+0.6 (mean+SD).

Practice RNA samples also were isolated from 25-dpf perch brain: 510.9 + 264.3 ng RNA per brain (mean+SD; n= 5 brains) with a RIN value of 7.44+0.93 (mean+SD).

We also sequenced the yellow perch genome, and we plan to apply one additional technique to increase the number of reads. This is the first time the yellow perch transcriptome has been sequenced and it should add great value to many future studies that use yellow perch transcriptomics.

With a kmer size of 75, we have an assembly for perch with the following statistics, as reported by ABySS:

n                  n:500             L50         min       N80        N50       N20        E-size        max         sum          name

2328131      314204          59121     500       1417      3261      6773       4475         51683      684.4e6    75-unitigs.fa

1412396    251510         39265    500       2244     5737     12247    7902        83091     812.8e6   75-contigs.fa

1248929    165818         19448    500       3721     11164    25832   16351      150306   827.7e6 75-scaffolds.fa

The scaffold have an N50 of ~11k, with a sum that is close to the estimate produced by kmergenie.

Objective 3

We also designed a novel learning bioassay (Figure 3) that can be incorporated into an individual based model (Figure 3) . As a result, chemical impacts on learning can now be quantified and extrapolated to higher levels of biological organization such as population level impacts. We developed the learning assay algorithm for our individual based model using published data from lead exposed fathead minnow, but expect the data collected from these experiments will easily be incorporated into our algorithm.

Figure 2. The probability a juvenile fathead minnow will attack a larger daphnia before attacking a smaller daphnia over a 14 day period. Both the control and 0.5 ppm Pb fish adapted their preference to smaller daphnia by day 14 whereas the 1.0 ppm Pb fish do not change their preference.

Figure 3. Simulation from individual based model that incorporates learning impairment after exposure to chemical. The learning impaired cohort has a higher percentage of individuals that starve to death than the unexposed cohort of larval fish.

We developed a yellow perch individual based model that included realistic scenarios of community changes. We simulated two populations of larval yellow perch from two areas (Lake Michigan and Crystal Lake, MI) both have different trophic structures and temperature regimes. We then simulated how MeHg exposed fish would fare in both systems. This manuscript is in preparation and should be submitted to Canadian Journal of Fisheries and Aquatic Sciences in 2017.

Other Progress

We also initiated a collaborative agreement with Dr. Diane Nacci’s group at the EPA in Narragansett RI. They will conduct parallel experiments in killifish and we identified a PhD student at Stony Brook to assist with the experiments. We have also been collaborating with Dr. Roger Nisbet and his co-investigators of an EPA STAR grant funded under the same RFP as this grant, through a National Institute of Mathematical and Biological Synthesis (NIMBioS) working group to bridge our adverse outcome pathway work to dynamic energy budgets. This has potential to be quite transformative because it will mean we can screen thousands of chemical to predict impacts on thousands of species.

 

 

 

 

 

Future Activities:

The perch transcriptome will be completed in the very near future. We plan to continue to perform assays on yellow perch, zebrafish and fathead minnow. The transcriptome of the exposed zebrafish brain should be analyzed in the near future. We plan to develop the individual based model for the fathead minnow and we are going to begin addressing the topic of risk and error propagation.

Journal Articles:

No journal articles submitted with this report: View all 23 publications for this project

Supplemental Keywords:

transcriptomics, larval fish, fathead minnow, yellow perch, zebrafish, neurobehavior, MeHg, PCBs, adverse outcome pathways, individual-based models, ecological risk assessment, uncertainty.

Progress and Final Reports:

Original Abstract

2016 Progress Report

2017 Progress Report

2018 Progress Report

2019 Progress Report

Final Report