An ontology for developmental processes and toxicities of neural tube closure
Introduction
The development and implementation of animal-free approaches to chemical and pharmaceutical hazard and risk assessment has reached a critical crossroad. The realization grows that the approach of implementing individual animal-free alternative methods is limited by the complexity of toxicities at the level of the intact organism [1,2]. A novel paradigm emerges that takes a fundamentally different starting point in contrast to the approach that replaces individual animal studies with reductionistic in vitro assays [3]. Alternatively, an approach from the perspective of human biology, physiology and toxicology takes an open view towards what knowledge is needed to sufficiently cover all aspects necessary for an inclusive human hazard and risk assessment [4,5]. Briefly, the general idea is that a map of human biology will allow one to identify comprehensive networks of quantitative Adverse Outcome Pathways (qAOP) in the future. The human biology map, when captured in an in silico model, has been referred to as the virtual human [6]. The molecular network underlying human biology responding to toxic insults has been named the toxicological ontology [7,8]. The quantitative aspect of this ontology will allow the selection of a limited number of steps in the network that need to be monitored to reliably calculate the response of the network as a whole and hence to predict the adverse outcome. Based on these selected steps, which are comparable to key events in an AOP, dedicated animal-free, preferably human-based, assays can be selected with which quantitative concentration-responses to chemical exposures can be measured. The integration of individual quantitative key event responses requires an intelligent computational tool that calculates dose-dependent compound-induced changes in the ontology leading to the adverse outcome prediction [9]. For application in integrated risk assessments, this dynamic model calculating quantitative concentration-dependent adverse outcomes needs to be appended with kinetic models and exposure estimates [4].
This open view approach allows a fresh perspective on what toxicities and diseases need to be considered, which can be significantly broader than currently required under existing legislation. Given that the integral human biology is the starting point, this approach includes all possible adverse outcomes, and therefore is in principle more inclusive than current practice which is limited by the spectrum of end points addressed in current regulatory guideline animal studies.
The current paradigm is considered to be adequately health protective, but it does not scale to the problem of testing 80 K chemicals in the human exposure landscape. The computational models can provide a tier 1 screen to inform targeted testing for, in this case, developmental toxicity. Virtual embryo simulations such as those developed in US EPA’s ‘Virtual Embryo’ program can work to translate data-driven machine learning models into mechanistic simulations for critical developmental transitions. These models can feed into Integrated Approaches to Testing and Assessment (IATA) in which the dynamics of those key events that represent tipping points in the qAOP network are combined with exposure and dosimetry to predict adversity and to achieve an integrated risk assessment.
The human biology map, when captured in an in silico model, has been referred to as the virtual human [10]. This concept provides an integral model of human physiology, which increasingly finds applications in clinical medicine as well as toxicological approaches [11]. In toxicology, it facilitates the integration of a wide variety of data types relevant for toxicity assessment, including kinetics and dynamics of chemicals in biological systems such as the wealth in vitro assays compiled in the Tox Cast library [12,13]. Thus, the virtual human concept aims at data integration towards computational modelling of the causation of adverse health effects, and consequently of chemical hazard and risk assessment [14]. Although it should be acknowledged that building the virtual human and the toxicological ontology require significant effort and time, its principal point of departure, together with the slow progress of implementing animal-free alternatives in current human safety assessment, merit strong investments in this innovative approach. Ongoing efforts in the realm of computational models for human physiology and disease, diagnostics and therapy, coupled with big data analysis through artificial intelligence and machine learning, indicate that in other areas of human health these virtual approaches are rapidly becoming mainstream [[15], [16], [17], [18], [19]]. Toxicological risk assessment need such innovations to move away from the scientifically and ethically challenged animal experimentation.
This manuscript follows the concept of the virtual human, focusing on one specific area in developmental toxicology that is highly relevant to human risk [20,21]. It describes the biology of neural tube closure from a molecular and cellular perspective. Neural tube defects are among the most prevalent human congenital malformations, which warrants specific attention in chemical safety assessment [22]. We took advantage of the highly conserved nature of the molecular mechanisms underlying neural tube closure throughout vertebrate biology, which leads to the pharyngula stage embryo that all vertebrates pass through during development before species-specific developmental differences become morphologically apparent [23]. It allowed us to mine the extensive literature of the molecular regulation of vertebrate neural tube closure, considering the relevance for humans where possible, starting from the literature available for the mouse. This approach has of course been performed with a critical eye towards species specificity. This description of the molecular and cellular developmental biology underlying neural tube closure follows up on our earlier studies focused on the morphogenetic role of mesoderm-derived all-trans-retinoic acid (ATRA) in neural tube development [24,25].
ATRA provides a small but well-known and important fraction of the essential molecular regulators of neural tube formation. The current manuscript explores in more detail the developmental biology of neural tube closure, focusing on ATRA-related molecular pathways linked to the various cell types in which they occur, and their role in driving intercellular interaction and its morphogenetic consequences, ultimately leading to closure of the neural tube. ATRA gradients play critical roles in early embryonic cell differentiation, and are regulated in time and space throughout embryo development. Retinoic acid response has also emerged from an extensive ToxCast library multi-assay response analysis as the most prominent developmental toxicant response [26]. It is the local balance between ATRA-producing retinol dehydrogenase families and ATRA-metabolizing cytochrome P450 family 26 (CYP26) enzyme families that determines local ATRA concentrations. In the neural tube ATRA as a differentiation inducer counteracts the activity of fibroblast growth factor (FGF) which stimulates cell proliferation. Opposite gradients of ATRA and FGF direct development along the rostro-caudal axis of the vertebrate embryo. In the ventro-dorsal direction a host of different factors such as chorda-derived sonic hedgehog (SHH) and neuroectoderm-derived WNT3 co-determine specific morphogenetic differentiation avenues. The resulting molecular neural tube closure map was collected in CellDesigner® software [27]. In follow-up research, based on existing data on the perturbation of gene expression by chemicals in cellular assays, from this map a qAOP network representing a toxicological ontology can be derived and represented in an in silico model. This ontology can inform the assays that need to be applied and combined to build the in silico model to calculate the adverse outcome at the level of the intact embryo.
The present manuscript compiles and integrates existing information on the molecular, cellular and spatial regulation of mammalian (mouse and/or human) neural tube closure in a systems biology network, representing the first step towards the generation of an in silico model for spinal/caudal neural tube closure. The construction of the biological regulation map underlying the in silico model is dependent on existing knowledge of the molecular regulation on embryogenesis. Although our systems model is presented as a two-dimensional map, morphogenesis is critically three-dimensional. This allows anterior-posterior, and dorsoventral gradients to interact in driving morphogenesis and generate left-right symmetry. While mammalian development at the early stages of embryogenesis up to the pharyngula stage is highly conserved [28], it should be kept in mind that building a virtual human embryo based on animal (mouse) data comes with unknown limitations.
Section snippets
Methods
The morphology of neural tube closure was used to define cell compartments playing a role in neural tube closure. Data were collected on changes in these cell compartments required for normal neural tube closure. Underlying genetic processes and interactions, and establishment of gradients of key molecular factors were identified based on literature search using the Abstract Sifter tool [29]. Publications from the PubMed database (until 2016) were selected if they were annotated with the
Results
To develop a systems biology network that is ready for integration in a computer model, we focused on five tissue compartments or cell populations for their roles in autonomous signalling in the developing neural tube. These are the (non-neural or surface) ectoderm, the (future) neural crest cells (ectodermal of origin), the neuroectoderm, the paraxial mesoderm and the notochord. Within the neuroectoderm, two populations of cells were operationally discriminated based on their behavior at the
Conclusion/ discussion
The molecular network underlying neural tube closure presented here is a work in progress and does not visualize all genes and intermediate steps that may play a role in this process. Specifically, those genes that have an intermediate role are not always included for reasons of simplification. Relations between genes are suggested to be direct in the network, but may actually be missing intermediate steps. Whether these steps serve a functional “gate-keeper” role remains to be elucidated.
Disclaimer
The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
Declaration of Competing Interest
The authors reported no declarations of interest.
Acknowledgements
We gratefully acknowledge the financial support from CEFIC-LRI under project codes AIMT-5 and AIMT5.2. The authors would like to thank Eric Gremmer for valuable contribution to the artwork.
References (88)
- et al.
Workshop on acceleration of the validation and regulatory acceptance of alternative methods and implementation of testing strategies
Toxicol. Vitr.
(2018) - et al.
Workshop on the validation and regulatory acceptance of innovative 3R approaches in regulatory toxicology – evolution versus revolution
Toxicol. Vitr.
(2019) - et al.
The virtual human in chemical safety assessment
Curr. Opin. Toxicol.
(2019) - et al.
A mode-of-action ontology model for safety evaluation of chemicals: outcome of a series of workshops on repeated dose toxicity
Toxicol. Vitr.
(2019) - et al.
The virtual human in chemical safety assessment
Curr. Opin. Toxicol.
(2019) - et al.
Modelling towards a more holistic medicine: the Virtual Physiological Human (VPH)
Morphologie
(2019) - et al.
Systems modeling of developmental vascular toxicity
Curr. Opin. Toxicol.
(2019) - et al.
Digital monitoring and care: virtual medicine
Trends Cardiovasc. Med.
(2016) - et al.
Computational modeling and simulation of genital tubercle development
Reprod. Toxicol.
(2016) - et al.
An adverse outcome pathway framework for neural tube and axial defects mediated by modulation of retinoic acid homeostasis
Reprod. Toxicol.
(2015)
Retinoic acid in developmental toxicology: teratogen, morphogen and biomarker
Reprod. Toxicol.
An adverse outcome pathway framework for neural tube and axial defects mediated by modulation of retinoic acid homeostasis
Reprod. Toxicol.
The role of Zic genes in neural development
Mol. Cell. Neurosci.
Temporally coordinated signals progressively pattern the anteroposterior and dorsoventral body axes
Semin. Cell Dev. Biol.
Dynamics and precision in retinoic acid morphogen gradients
Curr. Opin. Genet. Dev.
Active signals, gradient formation and regional specificity in neural induction
Exp. Cell Res.
Pax3 and Zic1 trigger the early neural crest gene regulatory network by the direct activation of multiple key neural crest specifiers
Dev. Biol.
The BMP antagonist Noggin promotes cranial and spinal neurulation by distinct mechanisms
Dev. Biol.
Dynamic analysis of actin cable function during Drosophila dorsal closure
Curr. Biol.
Grainyhead-like 2 regulates neural tube closure and adhesion molecule expression during neural fold fusion
Dev. Biol.
The early steps of neural crest development
Mech. Dev.
Folic acid remodels chromatin on Hes1 and Neurog2 promoters during caudal neural tube development
J. Biol. Chem.
Gene-regulatory interactions in neural crest evolution and development
Dev. Cell
Design and validation of an ontology-driven animal-free testing strategy for developmental neurotoxicity testing
Toxicol. Appl. Pharmacol.
Computational modeling and simulation of genital tubercle development
Reprod. Toxicol.
Correlation of chemical structure with reproductive and developmental toxicity as it relates to the use of the threshold of toxicological concern
Regul. Toxicol. Pharmacol.
A critical appraisal of the process of regulatory implementation of novel in vivo and in vitro methods for chemical hazard and risk assessment
Crit. Rev. Toxicol.
Advanced toxicological risk assessment by implementation of ontologies operationalized in computational models
Appl. In Vitro Toxicol.
Rethinking developmental toxicity testing: Evolution or revolution?
Birth Defects Res.
Building a developmental toxicity ontology
Birth Defects Res.
The next generation blueprint of computational toxicology at the U.S. Environmental Protection Agency
Toxicol. Sci.
Virtual tissues in toxicology
J. Toxicol. Environ. Health B Crit. Rev.
Computational toxicology as implemented by the U.S. EPA: providing high throughput decision support tools for screening and assessing chemical exposure, hazard and risk
J. Toxicol. Environ. Health B Crit. Rev.
The virtual physiological human: ten years after
Annu. Rev. Biomed. Eng.
Machine learning-based virtual screening and its applications to alzheimer’s drug discovery: a review
Curr. Pharm. Des.
The virtual heart as a platform for screening drug cardiotoxicity
Br. J. Pharmacol.
The virtual intestine: in silico modeling of small intestinal electrophysiology and motility and the applications
WIREs Syst. Biol. Med.
Computational model of secondary palate fusion and disruption
Chem. Res. Toxicol.
Describing the prevalence of neural tube defects worldwide: a systematic literature review
PLoS One
The developmental hourglass model: a predictor of the basic body plan?
Development
Predictive models of prenatal developmental toxicity from ToxCast high-throughput screening data
Toxicol. Sci.
Modeling and simulation using CellDesigner
The developmental hourglass model: a predictor of the basic body plan?
Development
Abstract Sifter: a comprehensive front-end system to PubMed
F1000Research
Cited by (14)
Innovating human chemical hazard and risk assessment through an holistic approach
2023, Current Opinion in ToxicologyApplication of AOPs to assist regulatory assessment of chemical risks – Case studies, needs and recommendations
2023, Environmental ResearchCitation Excerpt :However, DNT-related AOPs submitted to the AOP-Wiki remain limited. To fill in this gap, new (quantitative) AOPs are being developed (such as the AOP 434) and derived from physiological maps of the developing brain such as the neural tube closure physiological map (Heusinkveld et al., 2021) in the framework of the ongoing European H2020 project ONTOX. The objective is the integration of the qAOP network into an AI-based NAM that includes the DNT IVB and predicts systemic repeated dose toxicity for the purpose of NGRA of chemicals (Vinken et al., 2021).
Dynamic regulation of gene expression and morphogenesis in the zebrafish embryo test after exposure to all-trans retinoic acid
2023, Reproductive ToxicologyCitation Excerpt :This gradient regulates other major developmental pathways such as wnt, bmp, fgf8, shh [32–37]. Together they act in the regulation of complex morphogenetic processes such as axial patterning [28, 31, 38], craniofacial morphogenesis, limb development [39,40] and neural tube closure [25, 41, 42]. The concentration of ATRA is strictly maintained locally by a balance between synthesizing enzymes such as the raldh family and metabolizing enzymes of the cyp26 family[43].
Application of the adverse outcome pathway to identify molecular changes in prenatal brain programming induced by IUGR: Discoveries after EGCG exposure
2022, Food and Chemical ToxicologyCitation Excerpt :This discovery was possible thanks to the previous existence of a putative AOP: “Binding to the extracellular matrix protein laminin leading to decreased cognitive function” (Klose et al., 2022), which was submitted to the OECD in 2019. Creating AOP-structured collections of molecular/cellular/organ/organism-event networks underlying human biology responding to toxic insults (named as toxicological ontology (Baker et al., 2018; Desprez et al., 2019; Heusinkveld et al., 2021)) is an extremely powerful strategy because it allows to cross information from different fields, in this case developmental neurotoxicity, developmental biology, and developmental physiopathology, to identify the molecular events behind specific cellular effects and finally design experiments which are directly aimed to evaluate the relevant KE or AO while saving animals, time and resources because the search is more directed. Our results support and expand the previously submitted AOP, and after combining them with the literature results, we can say that compared to the previous one, the new version of the AOP: 1) is more chemically agnostic, 2) includes a new branch of key events, and 3) is more specific at the organ and organism level.