Cherchia, L. | bioRxiv Science

bioRxiv2025

Prolactin receptor localization and dynamics: Insights from quantitative imaging and mathematical modeling

Signal transduction through the prolactin receptor (PRLR) is crucial in pancreatic {beta}-cell pro-liferation, impacting pancreatic homeostasis. PRLR-induced JAK/STAT signaling is dynamic, involving changes in spatial organization of signaling molecules. Thus, the spatial organization of PRLR could have strong implications on signaling output. Internalization has been shown and modeled in other signaling pathways but has not been considered in a mathematical model of PRLR signaling. Here, we use live-cell fluorescence imaging, reconstitution approaches, and fluorescence correlation spectroscopy (FCS) to inform a mathematical model of PRLR signaling. Internal PRLR localization is observed in primary pancreatic tissue and in an engineered PRLR expression system. Our imaging data indicate the presence of intracellular and plasma membrane-bound receptor populations. We use FCS to resolve the membrane-bound PRLR population. Based on our data, we include internalization dynamics within an ordinary differential equation (ODE) model of PRLR signaling. We employ the model to explore how the spatial heterogeneity of PRLR affects downstream signaling. We show that the model is more sensitive to PRLR trafficking rates and ability to promote signaling than to its initial spatial distribution. Our data underscore the versatility of a modeling-imaging framework to quantitatively understand signal transduction in and beyond {beta}-cells. Significance StatementO_LIProlactin receptor (PRLR) signal transduction impacts the growth and survival of insulin-secreting cells, making this pathway a target for building our understanding of pancreatic homeostasis and exploring potential diabetes therapeutics. C_LIO_LILive fluorescence imaging techniques applied within an engineered PRLR expression platform indicate PRLR localization patterns consistent with primary pancreatic tissue and the presence of two spatially distinct PRLR populations. These observations inform a predictive mathematical model of PRLR signaling. C_LIO_LIIntegrating experimental data tailored to computational approaches shapes our understanding of complex, multiscale systems such as signal transduction. A generalizable modeling-imaging framework enables the study of molecular dynamics beyond {beta}-cells. C_LI

cell biology↗

bioRxiv2024

A Versatile Light Field Microscopy Platform for Multi-purpose Dynamic Volumetric Bio-imaging

Light field microscopy (LFM) has emerged in recent years as a unique solution for fast, scan-free volumetric imaging of dynamic biological samples. This is achieved by using a microlens array in the detection path to record both the lateral and angular information of the light fields coming from the sample, capturing a 3-dimensional (3D) volume in a single 2-dimensional (2D) snapshot. In post-acquisition, the 3D sample volume is computationally reconstructed from the recorded 2D images, thus enabling unprecedented 3D capture speed, not limited by the typical constraint of physically scanning the focal plane over the sample volume. Up to date, most published LFM imaging setups have been specialized single-purpose platforms, optimized for a narrow performance window in field of view and resolution, thus hampering widespread adoption of LFM for biomedical research. Here, we present a versatile LFM platform for fast 3D imaging across multiple scales, enabling applications from cell to system-level biology on the same imaging setup. Our multiscale LFM is built as an add-on module to a conventional commercially available wide field microscope, and the various imaging applications, with different ranges of field of view and resolution, are achieved by simply switching between the standard microscope objectives available on the wide field microscope. Importantly, we provide an open-source end-to-end software package for calculating the system performance parameters, processing the experimentally measured point spread function, and light field 3D image reconstruction. We demonstrate the performance of our multiscale LFM platform through imaging the whole-brain activity map of seizures in larval zebrafish, calcium dynamics in ex vivo mouse pancreatic islets, and subcellular protein dynamics in cultured cells.

bioengineering↗