Quantitative variation in autocrine signaling and pathway crosstalk in the Caenorhabditis vulval network

Understanding developmental system drift

Developmental system drift (DSD) occurs when the genetic basis for homologous traits diverges over time despite conservation of the phenotype. In this Review, we examine the key ideas, evidence and open problems arising from studies of DSD. Recent work suggests that DSD may be pervasive, having been detected across a range of different organisms and developmental processes. Although developmental research remains heavily reliant on model organisms, extrapolation of findings to non-model organisms can be error-prone if the lineages have undergone DSD. We suggest how existing data and modelling approaches may be used to detect DSD and estimate its frequency. More direct study of DSD, we propose, can inform null hypotheses for how much genetic divergence to expect on the basis of phylogenetic distance, while also contributing to principles of gene regulatory evolution.

Evolutionary plasticity in the requirement for force exerted by ligand endocytosis to activate C. elegans Notch proteins

The conserved transmembrane receptor Notch has diverse and profound roles in controlling cell fate during animal development. In the absence of ligand, a negative regulatory region (NRR) in the Notch ectodomain adopts an autoinhibited confirmation, masking an ADAM protease cleavage site;1,2 ligand binding induces cleavage of the NRR, leading to Notch ectodomain shedding as the first step of signal transduction.3,4 In Drosophila and vertebrates, recruitment of transmembrane Delta/Serrate/LAG-2 (DSL) ligands by the endocytic adaptor Epsin, and their subsequent internalization by Clathrin-mediated endocytosis, exerts a "pulling force" on Notch that is essential to expose the cleavage site in the NRR.4-6 Here, we show that Epsin-mediated endocytosis of transmembrane ligands is not essential to activate the two C. elegans Notch proteins, LIN-12 and GLP-1. Using an in vivo force sensing assay in Drosophila,6 we present evidence (1) that the LIN-12 and GLP-1 NRRs are tuned to lower force thresholds than the NRR of Drosophila Notch, and (2) that this difference depends on the absence of a "leucine plug" that occludes the cleavage site in the Drosophila and vertebrate Notch NRRs.1,2 Our results thus establish an unexpected evolutionary plasticity in the force-dependent mechanism of Notch activation and implicate a specific structural element, the leucine plug, as a determinant.

Quantifying cell transitions in C. elegans with data-fitted landscape models

Increasing interest has emerged in new mathematical approaches that simplify the study of complex differentiation processes by formalizing Waddington's landscape metaphor. However, a rational method to build these landscape models remains an open problem. Here we study vulval development in C. elegans by developing a framework based on Catastrophe Theory (CT) and approximate Bayesian computation (ABC) to build data-fitted landscape models. We first identify the candidate qualitative landscapes, and then use CT to build the simplest model consistent with the data, which we quantitatively fit using ABC. The resulting model suggests that the underlying mechanism is a quantifiable two-step decision controlled by EGF and Notch-Delta signals, where a non-vulval/vulval decision is followed by a bistable transition to the two vulval states. This new model fits a broad set of data and makes several novel predictions.

Multiscale modeling of vertebrate limb development

We review the current state of mathematical modeling of cartilage pattern formation in vertebrate limbs. We place emphasis on several reaction-diffusion type models that have been proposed in the last few years. These models are grounded in more detailed knowledge of the relevant regulatory processes than previous ones but generally refer to different molecular aspects of these processes. Considering these models in light of comparative phylogenomics permits framing of hypotheses on the evolutionary order of appearance of the respective mechanisms and their roles in the fin-to-limb transition. This article is categorized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Mechanistic Models Developmental Biology > Developmental Processes in Health and Disease Analytical and Computational Methods > Analytical Methods.

An in silico analysis of robust but fragile gene regulation links enhancer length to robustness

Organisms must ensure that expression of genes is directed to the appropriate tissues at the correct times, while simultaneously ensuring that these gene regulatory systems are robust to perturbation. This idea is captured by a mathematical concept called r-robustness, which says that a system is robust to a perturbation in up to r - 1 randomly chosen parameters. r-robustness implies that the biological system has a small number of sensitive parameters and that this number can be used as a robustness measure. In this work we use this idea to investigate the robustness of gene regulation using a sequence level model of the Drosophila melanogaster gene even-skipped. We consider robustness with respect to mutations of the enhancer sequence and with respect to changes of the transcription factor concentrations. We find that gene regulation is r-robust with respect to mutations in the enhancer sequence and identify a number of sensitive nucleotides. In both natural and in silico predicted enhancers, the number of nucleotides that are sensitive to mutation correlates negatively with the length of the sequence, meaning that longer sequences are more robust. The exact degree of robustness obtained is dependent not only on DNA sequence, but also on the local concentration of regulatory factors. We find that gene regulation can be remarkably sensitive to changes in transcription factor concentrations at the boundaries of expression features, while it is robust to perturbation elsewhere.

The Signaling Network Controlling C. elegans Vulval Cell Fate Patterning

EGF, emitted by the Anchor Cell, patterns six equipotent C. elegans vulval precursor cells to assume a precise array of three cell fates with high fidelity. A group of core and modulatory signaling cascades forms a signaling network that demonstrates plasticity during the transition from naïve to terminally differentiated cells. In this review, we summarize the history of classical developmental manipulations and molecular genetics experiments that led to our understanding of the signals governing this process, and discuss principles of signal transduction and developmental biology that have emerged from these studies.

From "the Worm" to "the Worms" and Back Again: The Evolutionary Developmental Biology of Nematodes

Since the earliest days of research on nematodes, scientists have noted the developmental and morphological variation that exists within and between species. As various cellular and developmental processes were revealed through intense focus on Caenorhabditis elegans, these comparative studies have expanded. Within the genus Caenorhabditis, they include characterization of intraspecific polymorphisms and comparisons of distinct species, all generally amenable to the same laboratory culture methods and supported by robust genomic and experimental tools. The C. elegans paradigm has also motivated studies with more distantly related nematodes and animals. Combined with improved phylogenies, this work has led to important insights about the evolution of nematode development. First, while many aspects of C. elegans development are representative of Caenorhabditis, and of terrestrial nematodes more generally, others vary in ways both obvious and cryptic. Second, the system has revealed several clear examples of developmental flexibility in achieving a particular trait. This includes developmental system drift, in which the developmental control of homologous traits has diverged in different lineages, and cases of convergent evolution. Overall, the wealth of information and experimental techniques developed in C. elegans is being leveraged to make nematodes a powerful system for evolutionary cellular and developmental biology.

Physiological Starvation Promotes Caenorhabditis elegans Vulval Induction

Studying how molecular pathways respond to ecologically relevant environmental variation is fundamental to understand organismal development and its evolution. Here we characterize how starvation modulates Caenorhabditis elegans vulval cell fate patterning – an environmentally sensitive process, with a nevertheless robust output. Past research has shown many vulval mutants affecting EGF-Ras-MAPK, Delta-Notch and Wnt pathways to be suppressed by environmental factors, such as starvation. Here we aimed to resolve previous, seemingly contradictory, observations on how starvation modulates levels of vulval induction. Using the strong starvation suppression of the Vulvaless phenotype of lin-3/egf reduction-of-function mutations as an experimental paradigm, we first tested for a possible involvement of the sensory system in relaying starvation signals to affect vulval induction: mutation of various sensory inputs, DAF-2/Insulin or DAF-7/TGF-β signaling did not abolish lin-3(rf) starvation suppression. In contrast, nutrient deprivation induced by mutation of the intestinal peptide transporter gene pept-1 or the TOR pathway component rsks-1 (the ortholog of mammalian P70S6K) very strongly suppressed lin-3(rf) mutant phenotypes. Therefore, physiologically starved animals induced by these mutations tightly recapitulated the effects of external starvation on vulval induction. While both starvation and pept-1 RNAi were sufficient to increase Ras and Notch pathway activities in vulval cells, the highly penetrant Vulvaless phenotype of a tissue-specific null allele of lin-3 was not suppressed by either condition. This and additional results indicate that partial lin-3 expression is required for starvation to affect vulval induction. These results suggest a cross-talk between nutrient deprivation, TOR-S6K and EGF-Ras-MAPK signaling during C. elegans vulval induction.

Outstanding questions in developmental ERK signaling

The extracellular signal-regulated kinase (ERK) pathway leads to activation of the effector molecule ERK, which controls downstream responses by phosphorylating a variety of substrates, including transcription factors. Crucial insights into the regulation and function of this pathway came from studying embryos in which specific phenotypes arise from aberrant ERK activation. Despite decades of research, several important questions remain to be addressed for deeper understanding of this highly conserved signaling system and its function. Answering these questions will require quantifying the first steps of pathway activation, elucidating the mechanisms of transcriptional interpretation and measuring the quantitative limits of ERK signaling within which the system must operate to avoid developmental defects.

Signal Propagation in Sensing and Reciprocating Cellular Systems with Spatial and Structural Heterogeneity

Sensing and reciprocating cellular systems (SARs) are important for the operation of many biological systems. Production in interferon (IFN) SARs is achieved through activation of the Jak-Stat pathway, and downstream upregulation of IFN regulatory factor (IRF)-7 and IFN transcription, but the role that high- and low-affinity IFNs play in this process remains unclear. We present a comparative between a minimal spatio-temporal partial differential equation model and a novel spatio-structural-temporal (SST) model for the consideration of receptor, binding, and metabolic aspects of SAR behaviour. Using the SST framework, we simulate single- and multi-cluster paradigms of IFN communication. Simulations reveal a cyclic process between the binding of IFN to the receptor, and the consequent increase in metabolism, decreasing the propensity for binding due to the internal feedback mechanism. One observes the effect of heterogeneity between cellular clusters, allowing them to individualise and increase local production, and within clusters, where we observe 'subpopular quiescence'; a process whereby intra-cluster subpopulations reduce their binding and metabolism such that other such subpopulations may augment their production. Finally, we observe the ability for low-affinity IFN to communicate a long range signal, where high affinity cannot, and the breakdown of this relationship through the introduction of cell motility. Biological systems may utilise cell motility where environments are unrestrictive and may use fixed system, with low-affinity communication, where a localised response is desirable.

Gene-free methodology for cell fate dynamics during development

Models of cell function that assign a variable to each gene frequently lead to systems of equations with many parameters whose behavior is obscure. Geometric models reduce dynamics to intuitive pictorial elements that provide compact representations for sparse in vivo data and transparent descriptions of developmental transitions. To illustrate, a geometric model fit to vulval development in Caenorhabditis elegans, implies a phase diagram where cell-fate choices are displayed in a plane defined by EGF and Notch signaling levels. This diagram defines allowable and forbidden cell-fate transitions as EGF or Notch levels change, and explains surprising observations previously attributed to context-dependent action of these signals. The diagram also reveals the existence of special points at which minor changes in signal levels lead to strong epistatic interactions between EGF and Notch. Our model correctly predicts experiments near these points and suggests specific timed perturbations in signals that can lead to additional unexpected outcomes.

At first, embryos are made up of identical cells. Then, as the embryo develops, these cells specialize into different types, such as heart and brain cells. Chemical signals sent and received by the cells are key to forming the right type of cell at the right time and place. The cellular machinery that produces and interprets these signals is exceedingly complex and difficult to understand.

In the 1950s, Conrad Waddington presented an alternative way of thinking about how an unspecialized cell progresses to one of many different fates. He suggested visualizing the developing cell as a ball rolling along a hilly landscape. As the ball travels, obstacles in its way guide it along particular paths. Eventually the ball comes to rest in a valley, with each valley in the landscape representing a different cell fate. Although this “landscape model” is an appealing metaphor for how signaling events guide cell specialization, it was not clear whether it could be put to productive use.

The egg-laying organ in the worm species Caenorhabditis elegans is called the vulva, and is often studied by researchers who want to learn more about how organs develop. The vulva develops from a small number of identical cells that adopt one of three possible cell fates. Two chemical signals, called epidermal growth factor (EGF) and Notch, control this specialization process.

Corson and Siggia have now constructed a simple landscape model that can reproduce the normal arrangement of cell types in the vulva. When adjusted to describe the effect of genetic mutations that affect either EGF or Notch, the model could predict the outcome of mutations that affect both signals at once. The twists and turns of cell paths in the landscape could also account for several non-intuitive cell fate outcomes that had been assumed to result from subtle regulation of EGF and Notch signals.

Landscape models should be easy to apply to other developing tissues and organs. By providing an intuitive picture of how signals shape cellular decisions, the models could help researchers to learn how to control cell and tissue development. This could lead to new treatments to repair or replace failing organs, making regenerative medicine a reality.

Differing roles for sur-2/MED23 in C. elegans and C. briggsae vulval development

Normal vulval development in the nematode Caenorhabditis briggsae is identical to that in the related Caenorhabditis elegans. However, several experiments suggest that there are differences between the two species with respect to the contribution of EGF/Ras signaling. To investigate these differences genetically, we have characterized a C. briggsae mutant strain that phenocopies the effect observed when C. briggsae animals are treated with U0126, an inhibitor of the EGF pathway component MEK. We identify that the gene affected in the mutant strain is Cbr-sur-2, which encodes a MED23 mediator complex protein that acts downstream of EGF signaling in C. elegans and other organisms, such as mammals. When Cbr-sur-2 and Cel-sur-2 mutants are compared, we find that the production of additional vulval cells from P5.p and P7.p in C. elegans is dependent on proper development of P6.p, while C. briggsae does not have a similar requirement. Combined chemical and genetic interference with the EGF pathway completely eliminates vulval development in C. elegans but not in C. briggsae. Our results provide genetic evidence for the differing requirements for EGF signaling in the two species.

A computational model predicts genetic nodes that allow switching between species-specific responses in a conserved signaling network

Alterations to only specific parameters in a model including EGF, Wnt and Notch lead to cell behavior differences.

Evolution of New cis-Regulatory Motifs Required for Cell-Specific Gene Expression in Caenorhabditis

Patterning of C. elegans vulval cell fates relies on inductive signaling. In this induction event, a single cell, the gonadal anchor cell, secretes LIN-3/EGF and induces three out of six competent precursor cells to acquire a vulval fate. We previously showed that this developmental system is robust to a four-fold variation in lin-3/EGF genetic dose. Here using single-molecule FISH, we find that the mean level of expression of lin-3 in the anchor cell is remarkably conserved. No change in lin-3 expression level could be detected among C. elegans wild isolates and only a low level of change—less than 30%—in the Caenorhabditis genus and in Oscheius tipulae. In C. elegans, lin-3 expression in the anchor cell is known to require three transcription factor binding sites, specifically two E-boxes and a nuclear-hormone-receptor (NHR) binding site. Mutation of any of these three elements in C. elegans results in a dramatic decrease in lin-3 expression. Yet only a single E-box is found in the Drosophilae supergroup of Caenorhabditis species, including C. angaria, while the NHR-binding site likely only evolved at the base of the Elegans group. We find that a transgene from C. angaria bearing a single E-box is sufficient for normal expression in C. elegans. Even a short 58 bp cis-regulatory fragment from C. angaria with this single E-box is able to replace the three transcription factor binding sites at the endogenous C. elegans lin-3 locus, resulting in the wild-type expression level. Thus, regulatory evolution occurring in cis within a 58 bp lin-3 fragment, results in a strict requirement for the NHR binding site and a second E-box in C. elegans. This single-cell, single-molecule, quantitative and functional evo-devo study demonstrates that conserved expression levels can hide extensive change in cis-regulatory site requirements and highlights the evolution of new cis-regulatory elements required for cell-specific gene expression.

Diversification of mechanisms regulating gene expression of key developmental factors is a major force in the evolution of development. However, in the past, comparisons of gene expression across different species have often been qualitative (i.e. ‘expression is on versus off’ in a certain cell) without precise quantification. New experimental methods now allow us to quantitatively compare the expression of gene homologs across species, with single cell resolution. Moreover, the development of genome editing tools enables the dissection of regulatory DNA sequences that drive gene expression. We use here a well-established “textbook” example of animal organogenesis in the microscopic nematode, Caenorhabditis elegans, focusing on the expression of lin-3, coding for the main inducer of the vulva, in a single cell called the anchor cell. We find that the lin-3 expression level is remarkably conserved, with 20–25 messenger RNAs per anchor cell, in species that are molecularly as distant as fish and mammals. This conservation occurs despite substantial changes and compensation in the regulatory elements required for cell-specific gene expression.

Anchor cell signaling and vulval precursor cell positioning establish a reproducible spatial context during C. elegans vulval induction

How cells coordinate their spatial positioning through intercellular signaling events is poorly understood. Here we address this topic using Caenorhabditis elegans vulval patterning during which hypodermal vulval precursor cells (VPCs) adopt distinct cell fates determined by their relative positions to the gonadal anchor cell (AC). LIN-3/EGF signaling by the AC induces the central VPC, P6.p, to adopt a 1° vulval fate. Exact alignment of AC and VPCs is thus critical for correct fate patterning, yet, as we show here, the initial AC-VPC positioning is both highly variable and asymmetric among individuals, with AC and P6.p only becoming aligned at the early L3 stage. Cell ablations and mutant analysis indicate that VPCs, most prominently 1° cells, move towards the AC. We identify AC-released LIN-3/EGF as a major attractive signal, which therefore plays a dual role in vulval patterning (cell alignment and fate induction). Additionally, compromising Wnt pathway components also induces AC-VPC alignment errors, with loss of posterior Wnt signaling increasing stochastic vulval centering on P5.p. Our results illustrate how intercellular signaling reduces initial spatial variability in cell positioning to generate reproducible interactions across tissues.

The developmental genetics of biological robustness

BACKGROUND

Living organisms are continuously confronted with perturbations, such as environmental changes that include fluctuations in temperature and nutrient availability, or genetic changes such as mutations. While some developmental systems are affected by such challenges and display variation in phenotypic traits, others continue consistently to produce invariable phenotypes despite perturbation. This ability of a living system to maintain an invariable phenotype in the face of perturbations is termed developmental robustness. Biological robustness is a phenomenon observed across phyla, and studying its mechanisms is central to deciphering the genotype-phenotype relationship. Recent work in yeast, animals and plants has shown that robustness is genetically controlled and has started to reveal the underlying mechinisms behind it.

SCOPE AND CONCLUSIONS

Studying biological robustness involves focusing on an important property of developmental traits, which is the phenotypic distribution within a population. This is often neglected because the vast majority of developmental biology studies instead focus on population aggregates, such as trait averages. By drawing on findings in animals and yeast, this Viewpoint considers how studies on plant developmental robustness may benefit from strict definitions of what is the developmental system of choice and what is the relevant perturbation, and also from clear distinctions between gene effects on the trait mean and the trait variance. Recent advances in quantitative developmental biology and high-throughput phenotyping now allow the design of targeted genetic screens to identify genes that amplify or restrict developmental trait variance and to study how variation propagates across different phenotypic levels in biological systems. The molecular characterization of more quantitative trait loci affecting trait variance will provide further insights into the evolution of genes modulating developmental robustness. The study of robustness mechanisms in closely related species will address whether mechanisms of robustness are evolutionarily conserved.

Gap Gene Regulatory Dynamics Evolve along a Genotype Network

Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift.” System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organism Drosophila melanogaster and the nonmodel scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them with an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability).

The significance and scope of evolutionary developmental biology: a vision for the 21st century

Evolutionary developmental biology (evo-devo) has undergone dramatic transformations since its emergence as a distinct discipline. This paper aims to highlight the scope, power, and future promise of evo-devo to transform and unify diverse aspects of biology. We articulate key questions at the core of eleven biological disciplines-from Evolution, Development, Paleontology, and Neurobiology to Cellular and Molecular Biology, Quantitative Genetics, Human Diseases, Ecology, Agriculture and Science Education, and lastly, Evolutionary Developmental Biology itself-and discuss why evo-devo is uniquely situated to substantially improve our ability to find meaningful answers to these fundamental questions. We posit that the tools, concepts, and ways of thinking developed by evo-devo have profound potential to advance, integrate, and unify biological sciences as well as inform policy decisions and illuminate science education. We look to the next generation of evolutionary developmental biologists to help shape this process as we confront the scientific challenges of the 21st century.

An Atlas of Network Topologies Reveals Design Principles for Caenorhabditis elegans Vulval Precursor Cell Fate Patterning

The vulval precursor cell (VPC) fate patterning in Caenorhabditis elegans is a classic model experimental system for cell fate determination and patterning in development. Despite its apparent simplicity (six neighboring cells arranged in one dimension) and many experimental and computational efforts, the patterning strategy and mechanism remain controversial due to incomplete knowledge of the complex biology. Here, we carry out a comprehensive computational analysis and obtain a reservoir of all possible network topologies that are capable of VPC fate patterning under the simulation of various biological environments and regulatory rules. We identify three patterning strategies: sequential induction, morphogen gradient and lateral antagonism, depending on the features of the signal secreted from the anchor cell. The strategy of lateral antagonism, which has not been reported in previous studies of VPC patterning, employs a mutual inhibition of the 2° cell fate in neighboring cells. Robust topologies are built upon minimal topologies with basic patterning strategies and have more flexible and redundant implementations of modular functions. By simulated mutation, we find that all three strategies can reproduce experimental error patterns of mutants. We show that the topology derived by mapping currently known biochemical pathways to our model matches one of our identified functional topologies. Furthermore, our robustness analysis predicts a possible missing link related to the lateral antagonism strategy. Overall, we provide a theoretical atlas of all possible functional networks in varying environments, which may guide novel discoveries of the biological interactions in vulval development of Caenorhabditis elegans and related species.

Inferring regulatory networks from experimental morphological phenotypes: a computational method reverse-engineers planarian regeneration

Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method provides an automated, highly generalizable framework for identifying the underlying control mechanisms responsible for the dynamic regulation of growth and form.

Developmental and regenerative biology experiments are producing a huge number of morphological phenotypes from functional perturbation experiments. However, existing pathway models do not generally explain the dynamic regulation of anatomical shape due to the difficulty of inferring and testing non-linear regulatory networks responsible for appropriate form, shape, and pattern. We present a method that automates the discovery and testing of regulatory networks explaining morphological outcomes directly from the resultant phenotypes, producing network models as testable hypotheses explaining regeneration data. Our system integrates a formalization of the published results in planarian regeneration, an in silico simulator in which the patterning properties of regulatory networks can be quantitatively tested in a regeneration assay, and a machine learning module that evolves networks whose behavior in this assay optimally matches the database of planarian results. We applied our method to explain the key experiments in planarian regeneration, and discovered the first comprehensive model of anterior-posterior patterning in planaria under surgical, pharmacological, and genetic manipulations. Beyond the planarian data, our approach is readily generalizable to facilitate the discovery of testable regulatory networks in developmental biology and biomedicine, and represents the first developmental model discovered de novo from morphological outcomes by an automated system.

Cells change their sensitivity to an EGF morphogen gradient to control EGF-induced gene expression

How cells in developing organisms interpret the quantitative information contained in morphogen gradients is an open question. Here we address this question using a novel integrative approach that combines quantitative measurements of morphogen-induced gene expression at single-mRNA resolution with mathematical modelling of the induction process. We focus on the induction of Notch ligands by the LIN-3/EGF morphogen gradient during vulva induction in Caenorhabditis elegans. We show that LIN-3/EGF-induced Notch ligand expression is highly dynamic, exhibiting an abrupt transition from low to high expression. Similar transitions in Notch ligand expression are observed in two highly divergent wild C. elegans isolates. Mathematical modelling and experiments show that this transition is driven by a dynamic increase in the sensitivity of the induced cells to external LIN-3/EGF. Furthermore, this increase in sensitivity is independent of the presence of LIN-3/EGF. Our integrative approach might be useful to study induction by morphogen gradients in other systems.

A model of the regulatory network involved in the control of the cell cycle and cell differentiation in the Caenorhabditis elegans vulva

BACKGROUND

There are recent experimental reports on the cross-regulation between molecules involved in the control of the cell cycle and the differentiation of the vulval precursor cells (VPCs) of Caenorhabditis elegans. Such discoveries provide novel clues on how the molecular mechanisms involved in the cell cycle and cell differentiation processes are coordinated during vulval development. Dynamic computational models are helpful to understand the integrated regulatory mechanisms affecting these cellular processes.

RESULTS

Here we propose a simplified model of the regulatory network that includes sufficient molecules involved in the control of both the cell cycle and cell differentiation in the C. elegans vulva to recover their dynamic behavior. We first infer both the topology and the update rules of the cell cycle module from an expected time series. Next, we use a symbolic algorithmic approach to find which interactions must be included in the regulatory network. Finally, we use a continuous-time version of the update rules for the cell cycle module to validate the cyclic behavior of the network, as well as to rule out the presence of potential artifacts due to the synchronous updating of the discrete model. We analyze the dynamical behavior of the model for the wild type and several mutants, finding that most of the results are consistent with published experimental results.

CONCLUSIONS

Our model shows that the regulation of Notch signaling by the cell cycle preserves the potential of the VPCs and the three vulval fates to differentiate and de-differentiate, allowing them to remain completely responsive to the concentration of LIN-3 and lateral signal in the extracellular microenvironment.

The Comet Cometh: Evolving Developmental Systems

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule’s prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach—which is based on reverse engineering, simulation, and mathematical analysis—the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

Quantitative system drift compensates for altered maternal inputs to the gap gene network of the scuttle fly Megaselia abdita

The segmentation gene network in insects can produce equivalent phenotypic outputs despite differences in upstream regulatory inputs between species. We investigate the mechanistic basis of this phenomenon through a systems-level analysis of the gap gene network in the scuttle fly Megaselia abdita (Phoridae). It combines quantification of gene expression at high spatio-temporal resolution with systematic knock-downs by RNA interference (RNAi). Initiation and dynamics of gap gene expression differ markedly between M. abdita and Drosophila melanogaster, while the output of the system converges to equivalent patterns at the end of the blastoderm stage. Although the qualitative structure of the gap gene network is conserved, there are differences in the strength of regulatory interactions between species. We term such network rewiring 'quantitative system drift'. It provides a mechanistic explanation for the developmental hourglass model in the dipteran lineage. Quantitative system drift is likely to be a widespread mechanism for developmental evolution.

Evolution of early development in dipterans: reverse-engineering the gap gene network in the moth midge Clogmia albipunctata (Psychodidae)

Understanding the developmental and evolutionary dynamics of regulatory networks is essential if we are to explain the non-random distribution of phenotypes among the diversity of organismic forms. Here, we present a comparative analysis of one of the best understood developmental gene regulatory networks today: the gap gene network involved in early patterning of insect embryos. We use gene circuit models, which are fitted to quantitative spatio-temporal gene expression data for the four trunk gap genes hunchback (hb), Krüppel (Kr), giant (gt), and knirps (kni)/knirps-like (knl) in the moth midge Clogmia albipunctata, and compare them to equivalent reverse-engineered circuits from our reference species, the vinegar fly Drosophila melanogaster. In contrast to the single network structure we find for D. melanogaster, our models predict four alternative networks for C. albipunctata. These networks share a core structure, which includes the central regulatory feedback between hb and knl. Other interactions are only partially determined, as they differ between our four network structures. Nevertheless, our models make testable predictions and enable us to gain specific insights into gap gene regulation in C. albipunctata. They suggest a less central role for Kr in C. albipunctata than in D. melanogaster, and show that the mechanisms causing an anterior shift of gap domains over time are largely conserved between the two species, although shift dynamics differ. The set of C. albipunctata gene circuit models presented here will be used as the starting point for data-constrained in silico evolutionary simulations to study patterning transitions in the early development of dipteran species.

Secreting and sensing the same molecule allows cells to achieve versatile social behaviors

Cells that secrete and sense the same signaling molecule are ubiquitous. To uncover the functional capabilities of the core "secrete-and-sense" circuit motif shared by these cells, we engineered yeast to secrete and sense the mating pheromone. Perturbing each circuit element revealed parameters that control the degree to which the cell communicated with itself versus with its neighbors. This tunable interplay of self-communication and neighbor communication enables cells to span a diverse repertoire of cellular behaviors. These include a cell being asocial by responding only to itself and social through quorum sensing, and an isogenic population of cells splitting into social and asocial subpopulations. A mathematical model explained these behaviors. The versatility of the secrete-and-sense circuit motif may explain its recurrence across species.

Comparative RNAi screens in C. elegans and C. briggsae reveal the impact of developmental system drift on gene function

Although two related species may have extremely similar phenotypes, the genetic networks underpinning this conserved biology may have diverged substantially since they last shared a common ancestor. This is termed Developmental System Drift (DSD) and reflects the plasticity of genetic networks. One consequence of DSD is that some orthologous genes will have evolved different in vivo functions in two such phenotypically similar, related species and will therefore have different loss of function phenotypes. Here we report an RNAi screen in C. elegans and C. briggsae to identify such cases. We screened 1333 genes in both species and identified 91 orthologues that have different RNAi phenotypes. Intriguingly, we find that recently evolved genes of unknown function have the fastest evolving in vivo functions and, in several cases, we identify the molecular events driving these changes. We thus find that DSD has a major impact on the evolution of gene function and we anticipate that the C. briggsae RNAi library reported here will drive future studies on comparative functional genomics screens in these nematodes.

Evolutionarily dynamic roles of a PUF RNA-binding protein in the somatic development of Caenorhabditis briggsae

Gene duplication and divergence has emerged as an important aspect of developmental evolution. The genomes of Caenorhabditis nematodes encode an ancient family of PUF RNA-binding proteins. Most have been implicated in germline development, and are often redundant with paralogs of the same sub-family. An exception is Cbr-puf-2 (one of three Caenorhabditis briggsae PUF-2 sub-family paralogs), which is required for development past the second larval stage. Here, we provide a detailed functional characterization of Cbr-puf-2. The larval arrest of Cbr-puf-2 mutant animals is caused by inefficient breakdown of bacterial food, which leads to starvation. Cbr-puf-2 is required for the normal grinding cycle of the muscular terminal bulb during early larval stages, and is transiently expressed in this tissue. In addition, rescue of larval arrest reveals that Cbr-puf-2 also promotes normal vulval development. It is expressed in the anchor cell (which induces vulval fate) and vulval muscles, but not in the vulva precursor cells (VPCs) themselves. This contrasts with the VPC-autonomous repression of vulval development described for the Caenorhabditis elegans homologs fbf-1/2. These different roles for PUF proteins occur even as the vulva and pharynx maintain highly conserved anatomies across Caenorhabditis, indicating pervasive developmental system drift (DSD). Because Cbr-PUF-2 shares RNA-binding specificity with its paralogs and with C. elegans FBF, we suggest that functional novelty of RNA-binding proteins evolves through changes in the site of their expression, perhaps in concert with cis-regulatory evolution in target mRNAs.

A network model for the specification of vulval precursor cells and cell fusion control in Caenorhabditis elegans

The vulva of Caenorhabditis elegans has been long used as an experimental model of cell differentiation and organogenesis. While it is known that the signaling cascades of Wnt, Ras/MAPK, and NOTCH interact to form a molecular network, there is no consensus regarding its precise topology and dynamical properties. We inferred the molecular network, and developed a multivalued synchronous discrete dynamic model to study its behavior. The model reproduces the patterns of activation reported for the following types of cell: vulval precursor, first fate, second fate, second fate with reversed polarity, third fate, and fusion fate. We simulated the fusion of cells, the determination of the first, second, and third fates, as well as the transition from the second to the first fate. We also used the model to simulate all possible single loss- and gain-of-function mutants, as well as some relevant double and triple mutants. Importantly, we associated most of these simulated mutants to multivulva, vulvaless, egg-laying defective, or defective polarity phenotypes. The model shows that it is necessary for RAL-1 to activate NOTCH signaling, since the repression of LIN-45 by RAL-1 would not suffice for a proper second fate determination in an environment lacking DSL ligands. We also found that the model requires the complex formed by LAG-1, LIN-12, and SEL-8 to inhibit the transcription of eff-1 in second fate cells. Our model is the largest reconstruction to date of the molecular network controlling the specification of vulval precursor cells and cell fusion control in C. elegans. According to our model, the process of fate determination in the vulval precursor cells is reversible, at least until either the cells fuse with the ventral hypoderm or divide, and therefore the cell fates must be maintained by the presence of extracellular signals.

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions.

Evolutionary systems biology: what it is and why it matters

Evolutionary systems biology (ESB) is a rapidly growing integrative approach that has the core aim of generating mechanistic and evolutionary understanding of genotype-phenotype relationships at multiple levels. ESB's more specific objectives include extending knowledge gained from model organisms to non-model organisms, predicting the effects of mutations, and defining the core network structures and dynamics that have evolved to cause particular intracellular and intercellular responses. By combining mathematical, molecular, and cellular approaches to evolution, ESB adds new insights and methods to the modern evolutionary synthesis, and offers ways in which to enhance its explanatory and predictive capacities. This combination of prediction and explanation marks ESB out as a research manifesto that goes further than its two contributing fields. Here, we summarize ESB via an analysis of characteristic research examples and exploratory questions, while also making a case for why these integrative efforts are worth pursuing.

Genetic control of vulval development in Caenorhabditis briggsae

The nematode Caenorhabditis briggsae is an excellent model organism for the comparative analysis of gene function and developmental mechanisms. To study the evolutionary conservation and divergence of genetic pathways mediating vulva formation, we screened for mutations in C. briggsae that cause the egg-laying defective (Egl) phenotype. Here, we report the characterization of 13 genes, including three that are orthologs of Caenorhabditis elegans unc-84 (SUN domain), lin-39 (Dfd/Scr-related homeobox), and lin-11 (LIM homeobox). Based on the morphology and cell fate changes, the mutants were placed into four different categories. Class 1 animals have normal-looking vulva and vulva-uterine connections, indicating defects in other components of the egg-laying system. Class 2 animals frequently lack some or all of the vulval precursor cells (VPCs) due to defects in the migration of P-cell nuclei into the ventral hypodermal region. Class 3 animals show inappropriate fusion of VPCs to the hypodermal syncytium, leading to a reduced number of vulval progeny. Finally, class 4 animals exhibit abnormal vulval invagination and morphology. Interestingly, we did not find mutations that affect VPC induction and fates. Our work is the first study involving the characterization of genes in C. briggsae vulva formation, and it offers a basis for future investigations of these genes in C. elegans.

The inheritance of process: a dynamical systems approach

A central unresolved problem of evolutionary biology concerns the way in which evolution at the genotypic level relates to the evolution of phenotypes. This genotype-phenotype map involves developmental and physiological processes, which are complex and not well understood. These processes co-determine the rate and direction of adaptive change by shaping the distribution of phenotypic variability on which selection can act. In this study, we argue-expanding on earlier ideas by Goodwin, Oster, and Alberch-that an explicit treatment of this map in terms of dynamical systems theory can provide an integrated understanding of evolution and development. We describe a conceptual framework, which demonstrates how development determines the probability of possible phenotypic transitions-and hence the evolvability of a biological system. We use a simple conceptual model to illustrate how the regulatory dynamics of the genotype-phenotype map can be passed on from generation to generation, and how heredity itself can be treated as a dynamic process. Our model yields explanations for punctuated evolutionary dynamics, the difference between micro- and macroevolution, and for the role of the environment in major phenotypic transitions. We propose a quantitative research program in evolutionary developmental systems biology-combining experimental methods with mathematical modeling-which aims at elaborating our conceptual framework by applying it to a wide range of evolving developmental systems. This requires a large and sustained effort, which we believe is justified by the significant potential benefits of an extended evolutionary theory that uses dynamic molecular genetic data to reintegrate development and evolution.

A method for rapid and simultaneous mapping of genetic loci and introgression sizes in nematode species

Caenorhabditis briggsae is emerging as an attractive model organism not only in studying comparative biology against C. elegans, but also in developing novel experimentation avenues. In particular, recent identification of a new Caenorhabditis species, C. sp.9 with which it can mate and produce viable progeny provides an opportunity for studying the genetics of hybrid incompatibilities (HI) between the two. Mapping of a specific HI locus demands repeated backcrossing to get hold of the specific genomic region underlying an observed phenotype. To facilitate mapping of HI loci between C. briggsae and C. sp.9, an efficient mapping method and a genetic map ideally consisting of dominant markers are required for systematic introgression of genomic fragments between the two species. We developed a fast and cost-effective method for high throughput mapping of dominant loci with resolution up to 1 million bps in C. briggsae. The method takes advantage of the introgression between C. briggsae and C. sp.9 followed by PCR genotyping using C. briggsae specific primers. Importantly, the mapping results can not only serve as an effective way for estimating the chromosomal position of a genetic locus in C. briggsae, but also provides size information for the introgression fragment in an otherwise C. sp.9 background. In addition, it also helps generate introgression line as a side-product that is invaluable for the subsequent mapping of HI loci. The method will greatly facilitate the construction of a genetic map consisting of dominant markers and pave the way for systematic isolation of HI loci between C. briggsae and C. sp.9 which has so far not been attempted between nematode species. The method is designed for mapping of a dominant allele, but can be easily adapted for mapping of any other type of alleles in any other species if introgression between a sister species pair is feasible.

Evolution in developmental phenotype space

Developmental systems can produce a variety of patterns and morphologies when the molecular and cellular activities within them are varied. With the advent of quantitative modeling, the range of phenotypic output of a developmental system can be assessed by exploring model parameter space. Here I review recent examples where developmental evolution is studied using quantitative models, which increasingly rely on empirically determined molecular signaling pathways and their crosstalk. Quantitative pathway evolution may result in dramatic morphological changes. Alternatively, in many developmental systems, the phenotypic output is robust to a range of parameter variation, and cryptic developmental evolution may occur without morphological change. Formalization and measurements of the relationship between genetic variation and parameter variation in developmental models remain in their infancy.

Efficient reverse-engineering of a developmental gene regulatory network

Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to discover whether there are rules or regularities governing development and evolution of complex multi-cellular organisms.

Geometry, epistasis, and developmental patterning

Developmental signaling networks are composed of dozens of components whose interactions are very difficult to quantify in an embryo. Geometric reasoning enumerates a discrete hierarchy of phenotypic models with a few composite variables whose parameters may be defined by in vivo data. Vulval development in the nematode Caenorhabditis elegans is a classic model for the integration of two signaling pathways; induction by EGF and lateral signaling through Notch. Existing data for the relative probabilities of the three possible terminal cell types in diverse genetic backgrounds as well as timed ablation of the inductive signal favor one geometric model and suffice to fit most of its parameters. The model is fully dynamic and encompasses both signaling and commitment. It then predicts the correlated cell fate probabilities for a cross between any two backgrounds/conditions. The two signaling pathways are combined additively, without interactions, and epistasis only arises from the nonlinear dynamical flow in the landscape defined by the geometric model. In this way, the model quantitatively fits genetic experiments purporting to show mutual pathway repression. The model quantifies the contributions of extrinsic vs. intrinsic sources of noise in the penetrance of mutant phenotypes in signaling hypomorphs and explains available experiments with no additional parameters. Data for anchor cell ablation fix the parameters needed to define Notch autocrine signaling.

Different cell fates from cell-cell interactions: core architectures of two-cell bistable networks

The acquisition of different fates by cells that are initially in the same state is central to development. Here, we investigate the possible structures of bistable genetic networks that can allow two identical cells to acquire different fates through cell-cell interactions. Cell-autonomous bistable networks have been previously sampled using an evolutionary algorithm. We extend this evolutionary procedure to take into account interactions between cells. We obtain a variety of simple bistable networks that we classify into major subtypes. Some have long been proposed in the context of lateral inhibition through the Notch-Delta pathway, some have been more recently considered and others appear to be new and based on mechanisms not previously considered. The results highlight the role of posttranscriptional interactions and particularly of protein complexation and sequestration, which can replace cooperativity in transcriptional interactions. Some bistable networks are entirely based on posttranscriptional interactions and the simplest of these is found to lead, upon a single parameter change, to oscillations in the two cells with opposite phases. We provide qualitative explanations as well as mathematical analyses of the dynamical behaviors of various created networks. The results should help to identify and understand genetic structures implicated in cell-cell interactions and differentiation.

Role of pleiotropy in the evolution of a cryptic developmental variation in Caenorhabditis elegans

Using vulval phenotypes in Caenorhabditis elegans, the authors show that cryptic genetic variation can evolve through selection for pleiotropic effects that alter fitness, and identify a cryptic variant that has conferred enhanced fitness on domesticated worms under laboratory conditions.

Robust biological systems are expected to accumulate cryptic genetic variation that does not affect the system output in standard conditions yet may play an evolutionary role once phenotypically expressed under a strong perturbation. Genetic variation that is cryptic relative to a robust trait may accumulate neutrally as it does not change the phenotype, yet it could also evolve under selection if it affects traits related to fitness in addition to its cryptic effect. Cryptic variation affecting the vulval intercellular signaling network was previously uncovered among wild isolates of Caenorhabditis elegans. Using a quantitative genetic approach, we identify a non-synonymous polymorphism of the previously uncharacterized nath-10 gene that affects the vulval phenotype when the system is sensitized with different mutations, but not in wild-type strains. nath-10 is an essential protein acetyltransferase gene and the homolog of human NAT10. The nath-10 polymorphism also presents non-cryptic effects on life history traits. The nath-10 allele carried by the N2 reference strain leads to a subtle increase in the egg laying rate and in the total number of sperm, a trait affecting the trade-off between fertility and minimal generation time in hermaphrodite individuals. We show that this allele appeared during early laboratory culture of N2, which allowed us to test whether it may have evolved under selection in this novel environment. The derived allele indeed strongly outcompetes the ancestral allele in laboratory conditions. In conclusion, we identified the molecular nature of a cryptic genetic variation and characterized its evolutionary history. These results show that cryptic genetic variation does not necessarily accumulate neutrally at the whole-organism level, but may evolve through selection for pleiotropic effects that alter fitness. In addition, cultivation in the laboratory has led to adaptive evolution of the reference strain N2 to the laboratory environment, which may modify other phenotypes of interest.

Robustness is a property of biological systems that ensures the production of reproducible phenotypes in spite of underlying environmental, stochastic, and genetic variability. A consequence of robustness is that potentially functional genetic variation is free to accumulate in natural populations because it is buffered at the phenotypic level. Even if this so-called “cryptic” genetic variation has no obvious effects under standard conditions, it may become phenotypically expressed upon major genetic or environmental perturbations. Here we used the model organism Caenorhabditis elegans to identify genetic variations involved in the cryptic evolution of vulval cell fate induction between wild strains. We found that a mutation in the essential nath-10 gene not only contributes to cryptic genetic variation in the vulval system, but also affects key life history traits that are expected to be under a strong selective pressure (brood size, age at sexual maturity, sperm number and rate of progeny production). Indeed, an allele of nath-10 that emerged during the laboratory domestication of C. elegans about 50 years ago confers a strong competitive advantage over the ancestral allele under laboratory conditions. A genetic variation that is cryptic for a robust trait can therefore affect more sensitive phenotypes and thus evolve under selection.

Life's attractors : understanding developmental systems through reverse engineering and in silico evolution

We propose an approach to evolutionary systems biology which is based on reverse engineering of gene regulatory networks and in silico evolutionary simulations. We infer regulatory parameters for gene networks by fitting computational models to quantitative expression data. This allows us to characterize the regulatory structure and dynamical repertoire of evolving gene regulatory networks with a reasonable amount of experimental and computational effort. We use the resulting network models to identify those regulatory interactions that are conserved, and those that have diverged between different species. Moreover, we use the models obtained by data fitting as starting points for simulations of evolutionary transitions between species. These simulations enable us to investigate whether such transitions are random, or whether they show stereotypical series of regulatory changes which depend on the structure and dynamical repertoire of an evolving network. Finally, we present a case study-the gap gene network in dipterans (flies, midges, and mosquitoes)-to illustrate the practical application of the proposed methodology, and to highlight the kind of biological insights that can be gained by this approach.