Biology subjects

Hiscock, T. W.

Publications and source records attributed to Hiscock, T. W..

5 recordsLinked to original sources

bioRxiv2018

Heterogeneity of Sonic Hedgehog Response Dynamics and Fate Specification in Single Neural Progenitors

During neural tube patterning, a gradient of Sonic hedgehog (Shh) signaling specifies ventral progenitor fates. The cellular response to Shh is processed through a genetic regulatory network (GRN) to specify distinct fate decisions. This process integrates Shh response level, duration and other inputs and is affected by noise in signaling and cell position. How reliably Shh response profile predicts the fate choice of a single cell is unclear. Here we use live imaging to track neural progenitors in developing zebrafish and quantify both Shh and fate reporters in single cells over time. We found that there is significant heterogeneity between Shh response and fate choice in single cells. We quantitatively modeled reporter intensities to obtain single cell response levels over time and systematically evaluated their correlation with cell fate specification. Motor neuron progenitors (pMN) exhibit a high degree of variability in their Shh responses, which is particularly prominent in the posterior neural tube where the Shh response dynamics are similar to those of the more ventrally fated lateral floor plate cells (LFPs). Our results highlight the precision limit of morphogen-interpretation GRNs in small and dynamic target cell fields.

developmental biology↗

bioRxiv2018

Feedback control of neurogenesis by tissue packing

Balancing the rate of differentiation and proliferation in developing tissues is essential to produce organs of robust size and composition. Whilst many molecular regulators have been established, how these connect to physical and geometrical aspects of tissue architecture is poorly understood. Here, using high-resolution timelapse imaging, we find that dense tissue packing and complex cell geometries play a significant role in regulating differentiation rate in the zebrafish neural tube. Specifically, in regions of high cell density, progenitors are physically pushed away from the apical surface, which, in a Notch-dependent manner, leads to their differentiation. Using simulations we show that this naturally performs negative feedback control on cell number. Our results suggest a model whereby differentiation rate is carefully tuned to correct fluctuations in cell number, originating from variable cell cycle progression and inherently probabilistic differentiation programs.

developmental biology↗

bioRxiv2018

Observing the Cell in Its Native State: Imaging Subcellular Dynamics in Multicellular Organisms

True physiological imaging of subcellular dynamics requires studying cells within their parent organisms, where all the environmental cues that drive gene expression, and hence the phenotypes we actually observe, are present. A complete understanding also requires volumetric imaging of the cell and its surroundings at high spatiotemporal resolution without inducing undue stress on either. We combined lattice light sheet microscopy with two-channel adaptive optics to achieve, across large multicellular volumes, noninvasive aberration-free imaging of subcellular processes, including endocytosis, organelle remodeling during mitosis, and the migration of axons, immune cells, and metastatic cancer cells in vivo. The technology reveals the phenotypic diversity within cells across different organisms and developmental stages, and may offer insights into how cells harness their intrinsic variability to adapt to different physiological environments.\n\nOne Sentence SummaryCombining lattice light sheet microscopy with adaptive optics enables high speed, high resolution in vivo 3D imaging of dynamic processes inside cells under physiological conditions within their parent organisms.

cell biology↗

bioRxiv2017

Adapting machine-learning algorithms to design gene circuits

Biological systems rely on complex networks, such as transcriptional circuits and protein-protein interaction networks, to perform a variety of functions e.g. responding to stimuli, directing cell fate, or patterning an embryo. Mathematical models are often used to ask: given some network, what function does it perform? However, we often want precisely the opposite i.e. given some circuit - either observed in vivo, or desired for some engineering objective - what biological networks could execute this function? Here, we adapt optimization algorithms from machine learning to rapidly screen and design gene circuits capable of performing arbitrary functions. We demonstrate the power of this approach by designing circuits (1) that recapitulate important in vivo phenomena, such as oscillators, and (2) to perform complex tasks for synthetic biology, such as counting noisy biological events. Our method can be readily applied to biological networks of any type and size, and is provided as an open-source and easy-to-use python module, GeneNet.

systems biology↗

bioRxiv2017

Size-reduced embryos reveal a gradient scaling based mechanism for zebrafish somite formation

Little is known about how the sizes of animal tissues are controlled. A prominent example is somite size which varies widely both within an individual and across species. Despite intense study of the segmentation clock governing the timing of somite generation, how it relates to somite size is poorly understood. Here we examine somite scaling and find that somite size at specification scales with the length of the presomitic mesoderm (PSM) despite considerable variation in PSM length across developmental stages and in surgically size-reduced embryos. Measurement of clock period, axis elongation speed, and clock gene expression patterns demonstrate that existing models fail to explain scaling. We posit a \"clock and scaled gradient\" model, in which somite boundaries are set by a dynamically scaling signaling gradient across the PSM. Our model not only explains existing data, but also makes a unique prediction that we experimentally confirm--the formation of periodic \"echoes\" in somite size following perturbation of the size of one somite. Our findings demonstrate that gradient scaling plays a central role both in progression and size control of somitogenesis.\n\nSummary statementBy comparing patterning in zebrafish embryos of different size we show that a dynamically scaling gradient in the presomitic mesoderm regulates somite size control.

developmental biology↗