AOP-based ontologies for developmental toxicity Thomas B. Knudsen, - - PowerPoint PPT Presentation

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AOP-based ontologies for developmental toxicity Thomas B. Knudsen, - - PowerPoint PPT Presentation

Aug 17, 2022 173 likes •348 views

EUROTOX 2018, Brussels Symposium: Adverse Outcome Pathways and Development of Alternative Methods AOP-based ontologies for developmental toxicity Thomas B. Knudsen, PhD Developmental Systems Biologist US EPA, National Center for

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DISCLAIMER: The views expressed are those of the presenter and do not necessarily reflect Agency policy.

AOP-based ontologies for developmental toxicity

Thomas B. Knudsen, PhD Developmental Systems Biologist US EPA, National Center for Computational Toxicology

knudsen.thomas@epa.gov

ORCID 0000-0002-5036-596x EUROTOX 2018, Brussels Symposium: “Adverse Outcome Pathways and Development of Alternative Methods”

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  • Blood vessel development is essential to the embryo (cardiovascular is first

functioning organ system across Vertebrate species).

  • Vascular insufficiency is tied to many disease processes (stroke, diabetes, pre-

eclampsia, neonatal respiratory distress, osteoporosis, Alzheimer’s…).

  • Aop43: one of 28 AOPs included in the OECD work plan with status ‘open for

citation & comment’ [https://aopwiki.org/wiki/index.php/Aop:43].

Vascular Development

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AOP framework: developmental vascular toxicity (DVT)

Vasculogenesis Primary tubular network Angiogenesis Remodeling

SOURCE: Knudsen and Kleinstreuer (2011) Birth Defects Res 3

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1058 ToxCast chemicals ranked by pVDC ToxPi

(38 circled for validation)

24 ToxCast target assays

(pVDC ToxPi)

AOP-based ranking: predicted vascular disrupting chemicals (pVDCs)

SOURCE: Kate Saili, NCCT 4

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VEGFR2 inhibition (PTK787)

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SOURCE: Tal et al. (2014) Reprod Toxicol 5

malformation mortality

ISV length (72 hpf) Terata (120 hpf) Lifespan (10 dpf) 5

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How well does ToxCast do predicting endothelial disruption across the angiogenesis cycle?

  • 3D angiogenic sprouting [Belair et al. (2016) Acta Biomat]
  • nuCTNB and endothelial migration [in preparation]
  • HTS tubulogenesis [Li et al. (2018) SLAS Tech]
  • endothelial co-culture [in preparation]
  • engineered matrices [Nguyen et al. (2017) Nature Bioeng]
  • KDR-reporter zebrafish embryos [Tal et al. (2017) Reprod Toxicol]
  • rat whole embryo culture [Ellis-Hutchings et al. (2017) Reprod Toxicol]

Vasculogenesis Primary tubular network Angiogenesis Remodeling

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A pVDC ToxPi B HUVEC tubulogenesis (FICAM) C HUVEC tubulogenesis (NCATS) D tubulogenesis in synthetic matrices (HMAPS) E tubulogenesis in Matrigel (HMAPS) F nuCTNB biomarker (VALA) G endothelial cell migration (VALA) H iPSC endothelial sprouting (HMAPS) I ISV reporter zebrafish (NHEERL) J reporter zebrafish (UDUBLIN) K HUVEC tubulogenesis (VALA) L ANY (B to K)

38 chemical test set: qualification of pVDC ToxPi across 9 endothelial behaviors

ToxCast pVDC FICAM tubulogenesis NCATS tubulogenesis synthetic tubulohenesis Matrigel tubulogenesis nuCTNB EC Migration Sprouting UWisc ZF-TG embryo ZF hyaloid VALA tubulogenesis ANY

Decane 1,2,3-Trichloropropane Pymetrozine Methimazole Imazamox D-Mannitol Methylparaben Valproic acid Tris(2-ethylhexyl) phosphate PFOS TNP-470

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4-Nonylphenol, branched

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1,2,4-Trichlorobenzene

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Diethanolamine

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Reserpine

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Sodium dodecylbenzenesulfonate

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Oxytetracycline dihydrate

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Quercetin

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Tris(2-chloroethyl) phosphate

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2,4-Diaminotoluene

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Tris(1,3-dichloro-2-propyl)phosphate

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Celecoxib

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C.I. Solvent Yellow 14

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tert-Butylhydroquinone

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Triclosan

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Bisphenol AF

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Haloperidol

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Docusate sodium

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Cladribine

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Triclocarban

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Pyridaben

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1-Hydroxypyrene

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Disulfiram

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Bisphenol A

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Fluazinam

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Phenolphthalein

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Octyl gallate

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5HPP-33

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Sens 0.89, Spec 0.80 ACC 87% (PPV 93%, NPV 73%)

A B C D E F G H I J K L

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SOURCE: Ellis-Hutchings et al. (2017) Reprod Toxicol

5HPP-33

  • synthetic thalidomide analog
  • microtubule disruptor
  • ↓ endothelial networks
  • critical effect - embryo viability
  • AC50 = 21.2 µM
  • TI threshold from hESC = 9.5 µM

TNP-470

  • synthetic fumagillin analog
  • MetAP II inhibitor
  • non-canonical WNT signaling
  • critical effect - dysmorphogenesis
  • AC50 = 0.038 µM
  • TI threshold from hESC = 0.01 µM

Embryotoxicity: 5HPP-33 vs TNP-470

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RNAseq: 5HPP-33 vs TNP-470 whole embryo culture

SOURCE: K Saili, J Franzosa (collaboration with DOW Chemical) 2831 DEGs overlap SOM (464 genes in ROI box) ROI clusters

  • FXR and LXR pathways

common to 5HPP-33 and TNP-470 response.

  • FXR (+) and LXR (-) pathways

may be key events via RXR heterodimerization.

  • splicesome and RNA metabolism
  • protesosome and ubiquitination

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VEGF165 MMPs VEGF121 sFlit1 TIE2 CXCL10 CCL2

SOFTWARE: www.CompuCell3D.org BioComplexity Institute, Indiana U

Computer simulation: cell agent-based models

Kleinstreuer et al. (2013) PLoS Comp Biol Nicole Kleinstreuer

VEGF corridors

Li and Carmeliet (2018) Science

Network assembly

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control Imazamox PFOS Disulfiram Pyridaben Fluazinam Bisphenol A Octyl gallate 5HPP-33

 VEGF

       

Simulated (in silico) profiling

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SOURCE: Zurlinden et al. (2018), NCCT

Tata et al. (2015) Mechanism Devel

VEGF-A gradient: NPCs in subventricular zone endothelial tip cell endothelial stalk cell microglial cell Microglial-Endothelial network

Neural tube vascularization

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Simulated dose-response: brain angiogenesis from in vitro HTS data (ToxCast)

13 https://www.epa.gov/chemical-research/toxcast-dashboard

0.03 µM 0.3 µM 2.0 µM 6.0 µM CompTox Chemicals Dashboard

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W Murphy, W Daly, G Kaushick – U Wisconsin (HMAPS)

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Biomimetic reconstruction (hNVU)

Todd Zurlinden, Kate Saili - NCCT

Computational prediction (cNVU) Critical concentration:

  • predicted in silico ~0.5 µM
  • observed in vitro ~0.3 µM
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Summary: decoding the toxicological blueprint of vascular development

  • HTS profiles can assess in vitro bioactivity of large numbers of chemicals but translation

remains a challenge for complex processes such as DevTox.

  • Mapping HTS features to AOPs brings into context the weight of evidence for critical

determinants potential invoking the altered phenotype in a self-organizing system.

  • AOP-based ontologies provide the necessary structure for quantitative prediction of

cellular and tissue responses to molecular perturbation.

  • The ‘angiogenic cycle’ is responsive to genetic and physiological signals in the embryonic

microenvironment, and can be useful for predictive toxicology.

  • For DevTox, this can be demonstrated by an AOP network for embryonic vascular

disruption represented in the OECD AOP-KB (Aop43).

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  • Nicole Kleinstreuer - NCCT (now NTP/NICEATM)
  • Richard Spencer – EMVL
  • Nancy Baker – Leidos / NCCT
  • Jill Franzosa – NCCT (now CSS/NHEERL)
  • Ed Carney† – Dow Chemical Company
  • Rob Ellis-Hutchings – Dow Chemical Company
  • Raj Settivari – Dow Chemical Company
  • Tuula Heinonen – U Tampere / FICAM
  • Tarja Tomela – U Tampere / FICAM
  • Maria Bondesson – U Houston (TIVS) (now Indiana U)
  • James Glazier – Indiana U (TIVS)
  • Kate Saili – NCCT
  • Todd Zurlinden – NCCT
  • BeiBei Cai – Vala Sciences
  • Jill Franzosa – NCCT (now CSS)
  • Eric Nguyen – U Wisconsin (HMAPS)
  • Guarav Kaushick – U Wisconsin (HMAPS)
  • William Murphy – U Wisconsin (HMAPS)
  • William Daly – U Wisconsin (HMAPS)
  • Tamara Tal – NHEERL/ISTD
  • David Belair – NHEERL/TAD (now CellGene)
  • Florent Ginhoux – A*STAR/SIgN
  • Aymeric Silvin – A*STAR/SIgN

Acknowledgements

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