Periodic Reporting for period 4 - LogNeuroDev (The molecular and cellular logic of vertebrate neural development)
Reporting period: 2022-07-01 to 2023-06-30
How are the right types of cells produced in the right place, at the right time and in the right amounts in an embryo? We study these questions in the central nervous system (CNS). Despite its complexity, the CNS is assembled in a remarkably precise and reliable manner. This precision is necessary for the wiring of nerves into the functional neural circuits that gives the CNS its function. Our research focuses on the spinal cord, which is the part of the CNS that contains the nerves that allow us to sense our environment and respond to it by moving muscles. Our goal is to identify the genes involved in spinal cord development and determine how they work to produce and organize the different types of nerve cells found in this part of the CNS. This will contribute to understanding the development of the spinal cord as well as shed light on diseased and damaged nervous systems.
We have previous developed mathematical models of the process of neural tube patterning. To test predictions of these models we have used genome engineering to introduce targeted alterations to a regulatory element controlling a key component of the neural tube regulatory network. These results revealed a major and surprising role for the regulatory network in determining the precision of tissue patterning. This is achieved, not by reducing noise in individual genes, but by the configuration of the network modulating the ability of stochastic fluctuations to initiate gene expression changes. A computational screen identified network properties that influence boundary precision, revealing two dynamical mechanisms by which small gene circuits attenuate the effect of noise in order to increase patterning precision. These results highlight design principles of gene regulatory networks that produce precise patterns of gene expression (Development DOI: 10.1242/dev.197566).
We have taken an unbiased approach to extend our knowledge of the gene regulatory programmes involved in neural tube development. Using single cell mRNA sequencing technology we have profiled the transcriptome of cells in the developing mouse neural tube between embryonic days 9.5-13.5. We confirmed that the data accurately recapitulates neural tube development and identified new components of the transcriptional network. In addition, the analysis highlighted a previously under-appreciated temporal component to the mechanisms that generate neuronal diversity. This is offering new insight into the mechanisms that are responsible for neuronal specification and a catalogue of gene expression for classifying spinal cord cell types that will support our future studies of neural tube development. This work is published (Development DOI: 10.1242/dev.173807).
We have also described a tissue scale model of cell behaviour in the neural tube (Development DOI: 10.1242/dev.176297). We used experimental measurements to develop a model based on cell mechanics of the apical surface of the neuroepithelium that incorporates inter-kinetic nuclear movement and spatially varying rates of neuronal differentiation. Simulations predicted that tissue growth and the shape of lineage-related clones of cells differ with the rate of differentiation. These predictions were consistent with experimental observations. .
We have continued to develop mathematical tools to help analyse the dynamics of gene regulatory networks, in particular extending some techniques from statistical physics and dynamical systems for use for the type of problems we study. By combining principled statistical methods with a framework based on catastrophe theory and approximate Bayesian computation we formulated a quantitative dynamical landscape that accurately predicts cell fate outcomes of pluripotent stem cells exposed to different combinations of signaling factors. Analysis of the landscape revealed two distinct ways in which cells make a binary choice between one of two fates. We suggest that these represent archetypal designs for developmental decisions. The approach is broadly applicable for the quantitative analysis of differentiation and for determining the logic of developmental decisions. (Cell Systems DOI: 10.1016/j.cels.2021.08.013)
Although many molecular mechanisms controlling developmental processes are evolutionarily conserved, the speed at which the embryo develops can vary substantially between species. Using in vitro directed differentiation of embryonic stem cells to motor neurons, we have found that the motor neuron differentiation program runs more than twice as fast in mouse as in human. This is not due to differences in signaling, nor the genomic sequence of genes or their regulatory elements. Instead, there is an approximately two-fold increase in protein stability and cell cycle duration in human cells compared with mouse cells. This can account for the slower pace of human development and suggests that differences in protein turnover play a role in interspecies differences in developmental tempo (Science DOI: 10.1126/science.aba7667)
Finally, we have discovered a global temporal patterning program that stratifies neurons based on the developmental time at which they are generated. This acts in parallel to spatial patterning, thereby increasing the diversity of neurons generated along the neuraxis. We found that this temporal program operates in stem cell-derived neurons and is under the control of the TGFβ signaling pathway. Targeted perturbation of components of the temporal program indicated their functional requirement for the generation of late-born neuronal subtypes. Together, these results provide evidence for the existence of a previously unappreciated global temporal transcriptional program of neuronal subtype identity and suggest that the integration of spatial and temporal patterning mechanisms diversifies and organizes neuronal subtypes in the vertebrate nervous system (PLoS Biology DOI: 10.1371/journal.pbio.3001450).
We have taken an unbiased approach to extend our knowledge of the gene regulatory programmes involved in neural tube development. Using single cell mRNA sequencing technology we have profiled the transcriptome of cells in the developing mouse neural tube between embryonic days 9.5-13.5. We confirmed that the data accurately recapitulates neural tube development and identified new components of the transcriptional network. In addition, the analysis highlighted a previously under-appreciated temporal component to the mechanisms that generate neuronal diversity. This is offering new insight into the mechanisms that are responsible for neuronal specification and a catalogue of gene expression for classifying spinal cord cell types that will support our future studies of neural tube development. This work is published (Development DOI: 10.1242/dev.173807).
We have also described a tissue scale model of cell behaviour in the neural tube (Development DOI: 10.1242/dev.176297). We used experimental measurements to develop a model based on cell mechanics of the apical surface of the neuroepithelium that incorporates inter-kinetic nuclear movement and spatially varying rates of neuronal differentiation. Simulations predicted that tissue growth and the shape of lineage-related clones of cells differ with the rate of differentiation. These predictions were consistent with experimental observations. .
We have continued to develop mathematical tools to help analyse the dynamics of gene regulatory networks, in particular extending some techniques from statistical physics and dynamical systems for use for the type of problems we study. By combining principled statistical methods with a framework based on catastrophe theory and approximate Bayesian computation we formulated a quantitative dynamical landscape that accurately predicts cell fate outcomes of pluripotent stem cells exposed to different combinations of signaling factors. Analysis of the landscape revealed two distinct ways in which cells make a binary choice between one of two fates. We suggest that these represent archetypal designs for developmental decisions. The approach is broadly applicable for the quantitative analysis of differentiation and for determining the logic of developmental decisions. (Cell Systems DOI: 10.1016/j.cels.2021.08.013)
Although many molecular mechanisms controlling developmental processes are evolutionarily conserved, the speed at which the embryo develops can vary substantially between species. Using in vitro directed differentiation of embryonic stem cells to motor neurons, we have found that the motor neuron differentiation program runs more than twice as fast in mouse as in human. This is not due to differences in signaling, nor the genomic sequence of genes or their regulatory elements. Instead, there is an approximately two-fold increase in protein stability and cell cycle duration in human cells compared with mouse cells. This can account for the slower pace of human development and suggests that differences in protein turnover play a role in interspecies differences in developmental tempo (Science DOI: 10.1126/science.aba7667)
Finally, we have discovered a global temporal patterning program that stratifies neurons based on the developmental time at which they are generated. This acts in parallel to spatial patterning, thereby increasing the diversity of neurons generated along the neuraxis. We found that this temporal program operates in stem cell-derived neurons and is under the control of the TGFβ signaling pathway. Targeted perturbation of components of the temporal program indicated their functional requirement for the generation of late-born neuronal subtypes. Together, these results provide evidence for the existence of a previously unappreciated global temporal transcriptional program of neuronal subtype identity and suggest that the integration of spatial and temporal patterning mechanisms diversifies and organizes neuronal subtypes in the vertebrate nervous system (PLoS Biology DOI: 10.1371/journal.pbio.3001450).
Our goals remain to understand how the gene regulatory network in the spinal cord controls neuronal subtype identity and how these mechanisms affect the dynamics and formation of reproducible pattern. We have developed in silico and in vitro models that accurately recapitulate in vivo development in order to facilitate tissue engineering of the muscloskeletal system. During this project we have developed our systematic and quantitative understanding of the genomic, molecular, and cellular mechanisms of neural tube development at multiple scales. This has led to the discovery of a perviously unappreciated temporal program of gene expression that increases the diversity of neuronal subtype generation. It has also revealed how the dynamics of the gene regulatory network modulate the effects of stochasticity in gene expression. We have developed further biomimetic in vitro generation of neural tissue, by applying principles derived from embryos to in vitro differentiation of mouse and human Embryonic Stem Cells (ESCs). This has been crucial for uncovering molecular mechanisms controlling the tempo of development and opened up new avenues of research. We have also deepened our established interdisciplinary collaborations with physicists and computer scientists allow us to develop novel data driven dynamical in silico methods that provide a new paradigm for the analysing cell fate decision making.