Concentration Sensing by the Moving Nucleus in Cell Fate Determination: A Computational Analysis

Nuclear crowding and nonlinear diffusion during interkinetic nuclear migration in the zebrafish retina

An important question in early neural development is the origin of stochastic nuclear movement between apical and basal surfaces of neuroepithelia during interkinetic nuclear migration. Tracking of nuclear subpopulations has shown evidence of diffusion - mean squared displacements growing linearly in time - and suggested crowding from cell division at the apical surface drives basalward motion. Yet, this hypothesis has not yet been tested, and the forces involved not quantified. We employ long-term, rapid light-sheet and two-photon imaging of early zebrafish retinogenesis to track entire populations of nuclei within the tissue. The time-varying concentration profiles show clear evidence of crowding as nuclei reach close-packing and are quantitatively described by a nonlinear diffusion model. Considerations of nuclear motion constrained inside the enveloping cell membrane show that concentration-dependent stochastic forces inside cells, compatible in magnitude to those found in cytoskeletal transport, can explain the observed magnitude of the diffusion constant.

Cell Kinetics in the Adult Neurogenic Niche and Impact of Diet-Induced Accelerated Aging

Neurogenesis in the adult brain, a powerful mechanism for neuronal plasticity and brain repair, is altered by aging and pathological conditions, including metabolic disorders. The search for mechanisms and therapeutic solutions to alter neurogenesis requires understanding of cell kinetics within neurogenic niches using a high-throughput quantitative approach. The challenge is in the dynamic nature of the process and multiple cell types involved, each having several potential modes of division or cell fate. Here we show that cell kinetics can be revealed through a combination of the BrdU/EdU pulse-chase, based on the circadian pattern of DNA replication, and a differential equations model that describes time-dependent cell densities. The model is validated through the analysis of cell kinetics in the cerebellar neurogenic niche of normal young adult male zebrafish, with cells quantified in 2D (sections), and with neuronal fate and reactivation of stem cells confirmed in 3D whole-brain images (CLARITY). We then reveal complex alterations in cell kinetics associated with accelerated aging due to chronic high caloric intake. Low activity of neuronal stem cells in this condition persists 2 months after reverting to normal diet, and is accompanied by overproduction of transient amplifying cells, their accelerated cell death, and slow migration of postmitotic progeny. This combined experimental and mathematical approach should allow for relatively high-throughput analysis of early signs of pathological and age-related changes in neurogenesis, evaluation of specific therapeutic targets, and drug efficacy.SIGNIFICANCE STATEMENT Understanding normal cell kinetics of adult neurogenesis and the type of cells affected by a pathological process is needed to develop effective prophylactic and therapeutic measures directed at specific cell targets. Complex time-dependent mechanisms involved in the kinetics of multiple cell types require a combination of experimental and mathematical modeling approaches. This study demonstrates such a combined approach by comparing normal neurogenesis with that altered by diet-induced accelerated aging in adult zebrafish.

Feedback between tissue packing and neurogenesis in the zebrafish neural tube

Balancing the rate of differentiation and proliferation in developing tissues is essential to produce organs of robust size and composition. Although 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 changes to cell geometry associated with dense tissue packing play a significant role in regulating differentiation rate in the zebrafish neural tube. Specifically, progenitors that are displaced away from the apical surface due to crowding, tend to differentiate in a Notch-dependent manner. Using simulations we show that interplay between progenitor density, cell shape and changes in differentiation rate could naturally result in negative-feedback control on progenitor cell number. Given these results, we suggest a model whereby differentiation rate is regulated by density dependent effects on cell geometry to: (1) correct variability in cell number; and (2) balance the rates of proliferation and differentiation over development to 'fill' the available space.

Matrix mechanics controls FHL2 movement to the nucleus to activate p21 expression

Substrate rigidity affects many physiological processes through mechanochemical signals from focal adhesion (FA) complexes that subsequently modulate gene expression. We find that shuttling of the LIM domain (domain discovered in the proteins, Lin11, Isl-1, and Mec-3) protein four-and-a-half LIM domains 2 (FHL2) between FAs and the nucleus depends on matrix mechanics. In particular, on soft surfaces or after the loss of force, FHL2 moves from FAs into the nucleus and concentrates at RNA polymerase (Pol) II sites, where it acts as a transcriptional cofactor, causing an increase in p21 gene expression that will inhibit growth on soft surfaces. At the molecular level, shuttling requires a specific tyrosine in FHL2, as well as phosphorylation by active FA kinase (FAK). Thus, we suggest that FHL2 phosphorylation by FAK is a critical, mechanically dependent step in signaling from soft matrices to the nucleus to inhibit cell proliferation by increasing p21 expression.

Stochasticity in the miR-9/Hes1 oscillatory network can account for clonal heterogeneity in the timing of differentiation

Recent studies suggest that cells make stochastic choices with respect to differentiation or division. However, the molecular mechanism underlying such stochasticity is unknown. We previously proposed that the timing of vertebrate neuronal differentiation is regulated by molecular oscillations of a transcriptional repressor, HES1, tuned by a post-transcriptional repressor, miR-9. Here, we computationally model the effects of intrinsic noise on the Hes1/miR-9 oscillator as a consequence of low molecular numbers of interacting species, determined experimentally. We report that increased stochasticity spreads the timing of differentiation in a population, such that initially equivalent cells differentiate over a period of time. Surprisingly, inherent stochasticity also increases the robustness of the progenitor state and lessens the impact of unequal, random distribution of molecules at cell division on the temporal spread of differentiation at the population level. This advantageous use of biological noise contrasts with the view that noise needs to be counteracted.