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Title: Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity

Abstract

The integration of rapid assays, large data sets, informatics and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality, were established at realistic exposure levels and used to develop a predictive model of nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both core composition and outermost surface chemistry of nanomaterials. The resulting clusters guided the development of a predictive model of gold nanoparticle toxicity to embryonic zebrafish. In addition, our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. These findings reveal the need to expeditiously increase the availability of quantitative measures of nanomaterial hazard and broaden the sharing of that data and knowledge to support predictive modeling. In addition, research should continue to focus on methodologies for developing predictive models of nanomaterial hazard based on sub-lethal responses to low dose exposures.

Authors:
 [1];  [2];  [2];  [2];  [3];  [2];  [4];  [1]
  1. Oregon State Univ., Corvallis, OR (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Intelligent Automation, Inc., Rockville, MD (United States)
  4. Oswaldo Cruz Foundation, Recife (Brazil)
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1224504
Report Number(s):
PNNL-SA-101181
Journal ID: ISSN 1388-0764; TRN: US1500797
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Nanoparticle Research
Additional Journal Information:
Journal Volume: 17; Journal Issue: 6; Journal ID: ISSN 1388-0764
Publisher:
Tsinghua University Press
Country of Publication:
United States
Language:
English
Subject:
77 NANOSCIENCE AND NANOTECHNOLOGY; nanoparticle; zebrafish; toxicity; surface chemistry; nanotechnology; toxicology; informatics

Citation Formats

Harper, Bryan, Thomas, Dennis G., Chikkagoudar, Satish, Baker, Nathan A., Tang, Kaizhi, Heredia-Langner, Alejandro, Lins, Roberto D., and Harper, Stacey. Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity. United States: N. p., 2015. Web. doi:10.1007/s11051-015-3051-0.
Harper, Bryan, Thomas, Dennis G., Chikkagoudar, Satish, Baker, Nathan A., Tang, Kaizhi, Heredia-Langner, Alejandro, Lins, Roberto D., & Harper, Stacey. Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity. United States. https://doi.org/10.1007/s11051-015-3051-0
Harper, Bryan, Thomas, Dennis G., Chikkagoudar, Satish, Baker, Nathan A., Tang, Kaizhi, Heredia-Langner, Alejandro, Lins, Roberto D., and Harper, Stacey. Thu . "Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity". United States. https://doi.org/10.1007/s11051-015-3051-0. https://www.osti.gov/servlets/purl/1224504.
@article{osti_1224504,
title = {Comparative hazard analysis and toxicological modeling of diverse nanomaterials using the embryonic zebrafish (EZ) metric of toxicity},
author = {Harper, Bryan and Thomas, Dennis G. and Chikkagoudar, Satish and Baker, Nathan A. and Tang, Kaizhi and Heredia-Langner, Alejandro and Lins, Roberto D. and Harper, Stacey},
abstractNote = {The integration of rapid assays, large data sets, informatics and modeling can overcome current barriers in understanding nanomaterial structure-toxicity relationships by providing a weight-of-the-evidence mechanism to generate hazard rankings for nanomaterials. Here we present the use of a rapid, low-cost assay to perform screening-level toxicity evaluations of nanomaterials in vivo. Calculated EZ Metric scores, a combined measure of morbidity and mortality, were established at realistic exposure levels and used to develop a predictive model of nanomaterial toxicity. Hazard ranking and clustering analysis of 68 diverse nanomaterials revealed distinct patterns of toxicity related to both core composition and outermost surface chemistry of nanomaterials. The resulting clusters guided the development of a predictive model of gold nanoparticle toxicity to embryonic zebrafish. In addition, our findings suggest that risk assessments based on the size and core composition of nanomaterials alone may be wholly inappropriate, especially when considering complex engineered nanomaterials. These findings reveal the need to expeditiously increase the availability of quantitative measures of nanomaterial hazard and broaden the sharing of that data and knowledge to support predictive modeling. In addition, research should continue to focus on methodologies for developing predictive models of nanomaterial hazard based on sub-lethal responses to low dose exposures.},
doi = {10.1007/s11051-015-3051-0},
journal = {Journal of Nanoparticle Research},
number = 6,
volume = 17,
place = {United States},
year = {Thu Jun 04 00:00:00 EDT 2015},
month = {Thu Jun 04 00:00:00 EDT 2015}
}

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Cited by: 28 works
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In vivo biodistribution and toxicity depends on nanomaterial composition, size, surface functionalisation and route of exposure
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Fullerene C60 exposure elicits an oxidative stress response in embryonic zebrafish
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Lab-on-a-Chip-Based High-Throughput Screening of the Genotoxicity of Engineered Nanomaterials
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Advancing risk assessment of engineered nanomaterials: Application of computational approaches
journal, December 2012

  • Gajewicz, Agnieszka; Rasulev, Bakhtiyor; Dinadayalane, Tandabany C.
  • Advanced Drug Delivery Reviews, Vol. 64, Issue 15
  • DOI: 10.1016/j.addr.2012.05.014

In vivo evaluation of carbon fullerene toxicity using embryonic zebrafish
journal, August 2007


Silver exposure in developing zebrafish (Danio rerio): Persistent effects on larval behavior and survival
journal, May 2010

  • Powers, Christina M.; Yen, Jerry; Linney, Elwood A.
  • Neurotoxicology and Teratology, Vol. 32, Issue 3
  • DOI: 10.1016/j.ntt.2010.01.009

Developmental toxicity of low generation PAMAM dendrimers in zebrafish
journal, November 2007

  • King Heiden, Tisha C.; Dengler, Emelyne; Kao, Weiyuan John
  • Toxicology and Applied Pharmacology, Vol. 225, Issue 1
  • DOI: 10.1016/j.taap.2007.07.009

Fullerene C60 exposure elicits an oxidative stress response in embryonic zebrafish
journal, May 2008

  • Usenko, Crystal Y.; Harper, Stacey L.; Tanguay, Robert L.
  • Toxicology and Applied Pharmacology, Vol. 229, Issue 1
  • DOI: 10.1016/j.taap.2007.12.030

Nanomaterial Toxicity Testing in the 21st Century: Use of a Predictive Toxicological Approach and High-Throughput Screening
journal, June 2012

  • Nel, Andre; Xia, Tian; Meng, Huan
  • Accounts of Chemical Research, Vol. 46, Issue 3
  • DOI: 10.1021/ar300022h

In Silico Analysis of Nanomaterials Hazard and Risk
journal, July 2012

  • Cohen, Yoram; Rallo, Robert; Liu, Rong
  • Accounts of Chemical Research, Vol. 46, Issue 3
  • DOI: 10.1021/ar300049e

Systematic Evaluation of Nanomaterial Toxicity: Utility of Standardized Materials and Rapid Assays
journal, May 2011

  • Harper, Stacey L.; Carriere, Jason Lee; Miller, John M.
  • ACS Nano, Vol. 5, Issue 6
  • DOI: 10.1021/nn200546k

Concept of Assessing Nanoparticle Hazards Considering Nanoparticle Dosemetric and Chemical/Biological Response Metrics
journal, February 2010

  • Rushton, Erik K.; Jiang, Jingkun; Leonard, Stephen S.
  • Journal of Toxicology and Environmental Health, Part A, Vol. 73, Issue 5-6
  • DOI: 10.1080/15287390903489422

In vivo biodistribution and toxicity depends on nanomaterial composition, size, surface functionalisation and route of exposure
journal, September 2008

  • Harper, S.; Usenko, C.; Hutchison, J. E.
  • Journal of Experimental Nanoscience, Vol. 3, Issue 3
  • DOI: 10.1080/17458080802378953

Silver nanoparticle toxicity in the embryonic zebrafish is governed by particle dispersion and ionic environment
journal, February 2013


Comparison of Molecular and Histological Changes in Zebrafish Gills Exposed to Metallic Nanoparticles
journal, December 2008

  • Griffitt, Robert J.; Hyndman, Kelly; Denslow, Nancy D.
  • Toxicological Sciences, Vol. 107, Issue 2
  • DOI: 10.1093/toxsci/kfn256

The New Toxicology of Sophisticated Materials: Nanotoxicology and Beyond
journal, December 2010

  • Maynard, A. D.; Warheit, D. B.; Philbert, M. A.
  • Toxicological Sciences, Vol. 120, Issue Supplement 1
  • DOI: 10.1093/toxsci/kfq372

Multidimensional In Vivo Hazard Assessment Using Zebrafish
journal, October 2013

  • Truong, Lisa; Reif, David M.; St Mary, Lindsey
  • Toxicological Sciences, Vol. 137, Issue 1
  • DOI: 10.1093/toxsci/kft235

Automated Zebrafish Chorion Removal and Single Embryo Placement: Optimizing Throughput of Zebrafish Developmental Toxicity Screens
journal, February 2012

  • Mandrell, David; Truong, Lisa; Jephson, Caleb
  • Journal of Laboratory Automation, Vol. 17, Issue 1
  • DOI: 10.1177/2211068211432197

The Relationships among Structure, Activity, and Toxicity of Engineered Nanoparticles
journal, January 2014


Quantitative Nanostructure−Activity Relationship Modeling
text, January 2010

  • Alexander, Tropsha,; Y., Shaw, Stanley; Ralph, Weissleder,
  • The University of North Carolina at Chapel Hill University Libraries
  • DOI: 10.17615/wj1d-x926

Predictive modeling of nanomaterial exposure effects in biological systems
journal, September 2013


Concern-driven integrated approaches to nanomaterial testing and assessment – report of the NanoSafety Cluster Working Group 10
journal, March 2013


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Practices and Trends of Machine Learning Application in Nanotoxicology
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Practices and Trends of Machine Learning Application in Nanotoxicology
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