Calling on Science: Making “Alternatives” the New Gold Standard

All of life’s great journeys start with a goal in mind! The 2007 NAS report, Toxicity Testing in the 21st Century – A Vision and A Strategy, has proposed a clear goal. This report envisions a not-so-distant future where all routine toxicity testing for environmental agents will be conducted in human cells in vitro evaluating perturbations of cellular responses in a suite of toxicity pathway assays. Dose response modeling would utilize computational systems biology models of the circuitry underlying each toxicity pathway; in vitro to in vivo extrapolations would use pharmacokinetic models, ideally physiologically based pharmacokinetic models, to predict human blood and tissue concentrations under specific exposure conditions. Results from these toxicity pathway assays and associated dose response modeling tools rather than those from high dose studies in animals would represent the new gold standard for chemical risk assessment. This talk focuses on some of the scientific challenges required to make this vision a reality, including characteristics of assay design, prospects for mapping and modeling toxicity pathways, assay validation, and biokinetic modeling. All of these tools necessary for this transformation of toxicity testing to an in vitro platform are either available or in advanced development. Science must lead the transformation. The scientific community, animal alternatives groups, regulatory agencies, and funding organizations will also have to muster the resolve to work together to make this vision a reality

Calling on Science: Making “Alternatives” the New Gold Standard

All of life’s great journeys start with a goal in mind! The 2007 NAS report, Toxicity Testing in the 21st Century – A Vision and A Strategy, has proposed a clear goal. This report envisions a not-so-distant future where all routine toxicity testing for environmental agents will be conducted in human cells in vitro evaluating perturbations of cellular responses in a suite of toxicity pathway assays. Dose response modeling would utilize computational systems biology models of the circuitry underlying each toxicity pathway; in vitro to in vivo extrapolations would use pharmacokinetic models, ideally physiologically based pharmacokinetic models, to predict human blood and tissue concentrations under specific exposure conditions. Results from these toxicity pathway assays and associated dose response modeling tools rather than those from high dose studies in animals would represent the new gold standard for chemical risk assessment. This talk focuses on some of the scientific challenges required to make this vision a reality, including characteristics of assay design, prospects for mapping and modeling toxicity pathways, assay validation, and biokinetic modeling. All of these tools necessary for this transformation of toxicity testing to an in vitro platform are either available or in advanced development. Science must lead the transformation. The scientific community, animal alternatives groups, regulatory agencies, and funding organizations will also have to muster the resolve to work together to make this vision a reality

Toxicity Pathways – from concepts to application in chemical safety assessment

Few would deny that the NRC report (NRC, 2007), "Toxicity Testing in the 21st Century: A Vision and Strategy”, represented a re-orientation of thinking surrounding the risk assessment of environmental chemicals. The key take-home message was that by understanding Toxicity Pathways (TP) we could profile the potential hazard and assess risks to humans and the environment using intelligent combinations of computational and in vitro methods. In theory at least, shifting to this new paradigm promises more efficient, comprehensive and cost effective testing strategies for every chemical in commerce while minimising the use of animals. For those of us who embrace the vision and the strategy proposed to achieve it, attention has increasingly focused on how we can actually practice what we preach. For a start, 21st century concepts described in the report have to be carefully interpreted and then translated into processes that essentially define and operationalize a TP framework for chemical risk assessment. In September 2011 the European Commission's Joint Research Centre (JRC) and the Hamner Institutes for Health Sciences co-organised a "Toxicity Pathways" workshop. It was hosted by the JRC and took place in Ispra, Italy. There were 23 invited participants with more or less equal representation from Europe and North America. The purpose of the meeting was to address three key questions surrounding a TP based approach to chemical risk assessment, namely – What constitutes a TP? How can we use TPs to develop in vitro assays and testing strategies? And, How can the results from TP testing be used in human health risk assessments? The meeting ran over two days and comprised a series of thought-starter presentations, breakout sessions and plenty of group discussions. The outcome was captured by rapporteurs and compiled as a workshop report which is available for download (without charge) from the JRC website. Here we expand on selected deliberations of the workshop to illustrate how TP thinking is still evolving and to indicate what pieces of the puzzle still need to fall into place before TP based risk assessment can become a reality.JRC.I.5-Systems Toxicolog

The Vision of Toxicity Testing in the 21st Century: Moving from Discussion to Action

Over the past year, a series on commentaries have appeared in the Toxicological Sciences Forum Series related to the 2007 National Research Council (NRC) publication, Toxicity Testing in the 21st Century: A Vision and A Strategy. The first article in the series provided an overview of the vision and was accompanied by an editorial by the three editors of Toxicological Sciences. During the past year, eight invited commentaries from the academic, industrial, and regulatory sectors have provided diverse perspectives on the vision, noted challenges to its implementation, and highlighted aspects of toxicity testing that were not addressed in the original NRC report. Here, we offer a summary of the main points raised by the commentators in tabular form, identify a number of common themes, and finish the series by providing our perspective on several key issues in charting the path forward to move from discussion to action

A deterministic map of Waddington's epigenetic landscape for cell fate specification

<p>Abstract</p> <p>Background</p> <p>The image of the "epigenetic landscape", with a series of branching valleys and ridges depicting stable cellular states and the barriers between those states, has been a popular visual metaphor for cell lineage specification - especially in light of the recent discovery that terminally differentiated adult cells can be reprogrammed into pluripotent stem cells or into alternative cell lineages. However the question of whether the epigenetic landscape can be mapped out quantitatively to provide a predictive model of cellular differentiation remains largely unanswered.</p> <p>Results</p> <p>Here we derive a simple deterministic path-integral quasi-potential, based on the kinetic parameters of a gene network regulating cell fate, and show that this quantity is minimized along a temporal trajectory in the state space of the gene network, thus providing a marker of directionality for cell differentiation processes. We then use the derived quasi-potential as a measure of "elevation" to quantitatively map the epigenetic landscape, on which trajectories flow "downhill" from any location. Stochastic simulations confirm that the elevation of this computed landscape correlates to the likelihood of occurrence of particular cell fates, with well-populated low-lying "valleys" representing stable cellular states and higher "ridges" acting as barriers to transitions between the stable states.</p> <p>Conclusions</p> <p>This quantitative map of the epigenetic landscape underlying cell fate choice provides mechanistic insights into the "forces" that direct cellular differentiation in the context of physiological development, as well as during artificially induced cell lineage reprogramming. Our generalized approach to mapping the landscape is applicable to non-gradient gene regulatory systems for which an analytical potential function cannot be derived, and also to high-dimensional gene networks. Rigorous quantification of the gene regulatory circuits that govern cell lineage choice and subsequent mapping of the epigenetic landscape can potentially help identify optimal routes of cell fate reprogramming.</p

Dose Response Relationship in Anti-Stress Gene Regulatory Networks

To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O(2), is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on the level of local gains, presence of gain-changing events, and degree of feedforward gene activation, this region can appear as superlinear, sublinear, or even J-shaped. The general dose response transition proposed here was further examined in a complex anti-electrophilic stress pathway, which involves multiple genes, enzymes, and metabolic reactions. This work would help biologists and especially toxicologists to better assess and predict the cellular impact brought about by biological stressors

Binary gene induction and protein expression in individual cells

BACKGROUND: Eukaryotic gene transcription is believed to occur in either a binary or a graded fashion. With binary induction, a transcription activator (TA) regulates the probability with which a gene template is switched from the inactive to the active state without affecting the rate at which RNA molecules are produced from the template. With graded, also called rheostat-like, induction the gene template has continuously varying levels of transcriptional activity, and the TA regulates the rate of RNA production. Support for each of these two mechanisms arises primarily from experimental studies measuring reporter proteins in individual cells, rather than from direct measurement of induction events at the gene template. METHODS AND RESULTS: In this paper, using a computational model of stochastic gene expression, we have studied the biological and experimental conditions under which a binary induction mode operating at the gene template can give rise to differentially expressed "phenotypes" (i.e., binary, hybrid or graded) at the protein level. We have also investigated whether the choice of reporter genes plays a significant role in determining the observed protein expression patterns in individual cells, given the diverse properties of commonly-used reporter genes. Our simulation confirmed early findings that the lifetimes of active/inactive promoters and half-lives of downstream mRNA/protein products are important determinants of various protein expression patterns, but showed that the induction time and the sensitivity with which the expressed genes are detected are also important experimental variables. Using parameter conditions representative of reporter genes including green fluorescence protein (GFP) and β-galactosidase, we also demonstrated that graded gene expression is more likely to be observed with GFP, a longer-lived protein with low detection sensitivity. CONCLUSION: The choice of reporter genes may determine whether protein expression is binary, graded or hybrid, even though gene induction itself operates in an all-or-none fashion

Dose-Incidence Relationships Derived from Superposition of Distributions of Individual Susceptibility on Mechanism-Based Dose Responses for Biological Effects

Dose-response relationships for incidence are based on quantal response measures. A defined effect is either present or not present in an individual. The dose-incidence curve therefore reflects differences in individual susceptibility (the "tolerance distribution”). At low dose, only the more susceptible individuals manifest the effect, while higher doses are required for more resistant individuals to be recruited into the affected fraction of the group. Here, we analyze how such dose-incidence relationships are related to mechanism-based dose-response relationships for biological effects described on a continuous scale. As an example, we use the quantal effect "cell division” triggered by occupancy of growth factor receptors (R) by a hormone or mitogenic ligand (L). The biologically effective dose (BED) is receptor occupancy (RL). The dose-BED relationship is described by the hyperbolic Michaelis-Menten function, RL/Rtot = L / (L + KD). For the conversion of the dose-BED relationship to a dose-cell division relationship, the dose-BED curve has to be combined with a function that describes the distribution of susceptibilities among the cells to be triggered into mitosis. We assumed a symmetrical sigmoid curve for this function, approximated by a truncated normal distribution. Because of the supralinear dose-BED relationship due to the asymptotic saturation of the Michaelis-Menten function, the composite curve that describes cell division (incidence) as a function of dose becomes skewed to the right. Logarithmic transformation of the dose axis reverses this skewing and provides a nearly perfect fit to a normal distribution in the central 95% incidence range. This observation may explain why dose-incidence relationships can often be described by a cumulative normal curve using the logarithm of the administered dose. The dominant role of the tolerance distribution for dose-incidence relationships is also illustrated with the example of a linear dose-BED relationship, using adducts to protein or DNA as the BED. Superimposed by a sigmoid distribution of individual susceptibilities, a sigmoid dose-incidence curve results. Linearity is no longer observed. We conclude that differences in susceptibility should always be considered for toxicological risk assessment and extrapolation to low dos