Nelanuthala, A. V. S. | Search bioRxiv

bioRxiv2023

Deep learning reduces data requirements and allows real-time measurements in Imaging Fluorescence Correlation Spectroscopy

Imaging Fluorescence Correlation Spectroscopy (Imaging FCS) is a powerful tool to extract information on molecular mobilities, actions and interactions in live cells, tissues and organisms. Nevertheless, several limitations restrict its applicability. First, FCS is data hungry, requiring 50,000 frames at 1 ms time resolution to obtain accurate parameter estimates. Second, the data size makes evaluation slow. Thirdly, as FCS evaluation is model-dependent, data evaluation is significantly slowed unless analytic models are available. Here we introduce two convolutional neural networks (CNNs) - FCSNet and Im-FCSNet - for correlation and intensity trace analysis, respectively. FCSNet robustly predicts parameters in 2D and 3D live samples. ImFCSNet reduces the amount of data required for accurate parameter retrieval by at least one order of magnitude and makes correct estimates even in moderately defocused samples. Both CNNs are trained on simulated data, are model-agnostic, and allow autonomous, real-time evaluation of Imaging FCS measurements.

biophysics↗

bioRxiv2022

Long-ranged formation of the Bicoid gradient requires multiple dynamic modes that spatially vary across the embryo

Morphogen gradients provide essential positional information to gene networks through their spatially heterogeneous distribution. Yet, how morphogen gradients form is still hotly contested, with multiple models proposed for different systems. Here, we focus on the transcription factor Bicoid (Bcd), a morphogen that forms an exponential gradient across the anterior-posterior (AP) axis of the early Drosophila embryo. We utilise fluorescence correlation spectroscopy (FCS) and perturbations to Bcd, to dissect Bcd dynamics at multiple spatial and temporal locations. In both the cytoplasm and nucleus, we find two dynamic modes for Bicoid diffusion dynamics, consisting of fast and slow populations of Bcd. Surprisingly, there are spatial differences in Bcd diffusivity along the AP-axis, with Bcd diffusing more rapidly in the posterior. We establish that such spatially varying differences in the Bcd dynamics are sufficient to explain how Bcd can have a steep exponential gradient in the anterior half of the embryo and yet still have an observable fraction of Bcd near the posterior pole. We subsequently investigated which binding elements of Bcd are playing a role in its dynamics. In the nucleus, we demonstrate that the slower mode of Bcd transport is due to Bcd DNA binding. Addition of the Bcd homeodomain to eGFP::NLS can qualitatively replicate the observed Bcd concentration profile, suggesting this domain is the primary region regulating Bcd dynamics. This study provides a detailed analysis of morphogen dynamics at different spatial and temporal locations, revealing multiple modes of transport. These results explain how a long-ranged gradient can form while retaining a steep profile through much of its range.

developmental biology↗