Biology subjects

Carrara, F.

Publications and source records attributed to Carrara, F..

7 recordsLinked to original sources

bioRxiv2026

OptiCell3D: Precise inference of mechanical cell properties from microscopy imaging

We introduce OptiCell3D, an open-source image-based framework for inferring cellular mechanical properties directly from 3D microscopy data. By integrating short physical simulations with gradient-based optimization via backpropagation, our method substantially improves accuracy compared to existing approaches. Moreover, OptiCell3D enables mechanical inference in tissues that are too large to be fully imaged, extending its applicability to more complex biological systems. We demonstrate the power of our approach by applying OptiCell3D to five morphologically diverse mouse epithelial tissues. By combining inferred parameters with simulations and morphometric analysis, we find that the ratio of apical to lateral surface tension predicts cell aspect ratio across epithelial subtypes, linking a single mechanical parameter to the broad morphological diversity of epithelia. Finally, we apply our framework to stratified tissues, finding greater variability in pressure and surface tension between cells and tension gradients along the apico-basal axis.

biophysics↗

bioRxiv2026

Heritable diel energy reserves enhance diatom growth

Diatoms are important drivers of marine primary production and biogeochemistry1-4. Compared to other phytoplankton groups, diatoms divide more asynchronously (i.e., divisions occur in a manner that is less aligned with the diel cycle) under non-limiting conditions, resulting in divisions occurring during both day and night5-16. However, the mechanisms and rates of asynchronous division have remained elusive. Here, using microfluidics-based time-resolved cell tracking, we measure the growth dynamics of individual cells of the diatom Thalassiosira pseudonana and show that cells growing mostly during the dark phase achieve rapid generation times (8 hours), dividing as fast as cells growing fully in light. We found that this remarkable ability of rapid growth in the dark is a consequence of the light history of both the cell and its parent cell, as light history controls the amount of photosynthetic energy the cell has stored in the form of the polysaccharide chrysolaminarin when entering the night. Furthermore, a mathematical model of this mechanism yields an up to 14% increase in the daily asynchronous population growth rate compared to growth without diel energy reserves when nutrients are non-limiting. This results in an up to 17-fold predicted increase in cell abundance over a typical 10-day diatom bloom, the maximal growth advantage of heritable chrysolaminarin during exponential phases of growth. By directly demonstrating and quantifying the benefit of chrysolaminarin under different diel conditions, this work provides a mechanistic understanding of how heritable diel energy reserves contribute to the rapid growth of diatom populations in the ocean. Beyond the specific discovery of the role of heritable energy reserves, we anticipate that our experimental approach can be broadly utilized in phytoplankton research by providing a blueprint to study phytoplankton physiology and ecology at the single-cell level, revealing novel mechanisms normally obscured in bulk growth assays.

microbiology↗

bioRxiv2025

MicroSplit: Semantic Unmixing of Fluorescent Microscopy Data

Fluorescence microscopy, a key driver for progress in the life sciences, faces limitations due to the microscopes optics, fluorophore chemistry, and photon exposure limits, necessitating trade-offs in imaging speed, resolution, and depth. Here, we introduce Micro[S]plit, a computational multiplexing technique based on deep learning that allows multiple cellular structures to be imaged in a single fluorescent channel and then unmix them by computational means, allowing faster imaging and reduced photon exposure. We show that Micro[S]plit efficiently separates up to four superimposed noisy structures into distinct denoised fluorescent image channels. Furthermore, using Variational Splitting Encoder-Decoder (VSE) networks, our approach can sample diverse predictions from a trained posterior of solutions. The diversity of these samples scales with the uncertainty in a given input, allowing us to estimate the true prediction errors by computing the variability between posterior samples. We demonstrate the robustness of Micro[S]plit networks, which are trained for each splitting task at hand, across various datasets and noise levels and show its utility to image more, to image faster, and to improve downstream analysis. We provide Micro[S]plit along with all associated training and evaluation datasets as open resources, enabling life scientists to immediately benefit from the potential of computational multiplexing and thus help accelerate the rate of their scientific discovery process.

bioinformatics↗

bioRxiv2024

Pupillometry and Whole-Brain c-Fos Mapping Uncover Multimodal Mirror Mechanisms in Emotional Contagion Networks of Mice

Emotional contagion (ECo) represents a fundamental form of empathy. In this study, we used pupillometry to quantify ECo by assessing pupil responses of a mouse watching another mouse receive a tail shock. Pupil dilation effectively measured both direct and vicarious emotional response thresholds at the individual level through psychometric curve analysis. The pupillary ECo response diminished when the observer could not see the demonstrator, suggesting a multisensory process involving vision. Viewing videos of tail-shocked mice was sufficient to elicit a pupil response in the observer. Whole-brain c-Fos mapping revealed a broad network of 88 brain regions activated during ECo, with all areas activated in the demonstrator also engaged in the observer. Additionally, in certain brain regions, correlated activation was detected between each observer-demonstrator pair, indicating that ECo promotes a shared neural state. These findings advance our understanding of the neural basis of empathy, with implications for analyzing neuropsychiatric disorder models.

neuroscience↗

bioRxiv2023

A Comprehensive Atlas of Perineuronal Net Distribution and Colocalization with Parvalbumin in the Adult Mouse Brain

Perineuronal nets (PNNs) surround specific neurons in the brain and are involved in various forms of plasticity and clinical conditions. However, our understanding of the PNN role in these phenomena is limited by the lack of highly quantitative maps of PNN distribution and association with specific cell types. Here, we present the first comprehensive atlas of PNN distribution (in Allen Brain Atlas coordinates) and colocalization with parvalbumin (PV) cells for over 600 regions of the adult mouse brain. Data analysis showed that PV expression is a good predictor of PNN aggregation. In the cortex, PNNs are dramatically enriched in layer 4 of all primary sensory areas in correlation with thalamocortical input density, and their distribution mirrors intracortical connectivity patterns. Gene expression analysis identified many PNN correlated genes. Strikingly, PNN anticorrelated transcripts were enriched in synaptic plasticity genes, generalizing PNN role as circuit stability factors. Overall, this atlas offers novel resources for understanding the organizational principles of the brain extracellular matrix.

neuroscience↗

bioRxiv2021

MEYE: Web-app for translational and real-time pupillometry

Pupil dynamics alterations have been found in patients affected by a variety of neuropsychiatric conditions, including autism. Studies in mouse models have used pupillometry for phenotypic assessment and as a proxy for arousal. Both in mice and humans, pupillometry is non-invasive and allows for longitudinal experiments supporting temporal specificity, however its measure requires dedicated setups. Here, we introduce a Convolutional Neural Network that performs on-line pupillometry in both mice and humans in a web app format. This solution dramatically simplifies the usage of the tool for non-specialist and non-technical operators. Because a modern web browser is the only software requirement, this choice is of great interest given its easy deployment and set-up time reduction. The tested model performances indicate that the tool is sensitive enough to detect both spontaneous and evoked pupillary changes, and its output is comparable with state-of-the-art commercial devices.

neuroscience↗

bioRxiv2020

Bistability in oxidative stress response determines the migration behavior of phytoplankton in turbulence

Turbulence is an important determinant of phytoplankton physiology, often leading to cell stress and damage. Turbulence affects phytoplankton migration, both by transporting cells and by triggering switches in migratory behavior, whereby vertically migrating cells can invert their direction of migration upon exposure to turbulent cues. However, a mechanistic link between single-cell physiology and vertical migration of phytoplankton in turbulence is currently missing. Here, by combining physiological and behavioral experiments with a mathematical model of stress accumulation and dissipation, we show that the mechanism responsible for the switch in the direction of migration in the marine raphidophyte Heterosigma akashiwo is the integration of reactive oxygen species (ROS) signaling generated by turbulent cues. Within timescales as short as tens of seconds, the emergent downward-migrating subpopulation exhibited a two-fold increase of ROS, an indicator of stress, 15% lower photosynthetic efficiency, and 35% lower growth rate over multiple generations compared to the upward-migrating subpopulation. The origin of the behavioral split in a bistable oxidative stress response is corroborated by the observation that exposure of cells to exogenous stressors (H2O2, UV-A radiation or high irradiance), in lieu of turbulence, caused comparable ROS accumulation and an equivalent split into the two subpopulations. By providing a mechanistic link between single-cell physiology, population-scale migration and fitness, these results contribute to our understanding of phytoplankton community composition in future ocean conditions. Significance StatementTurbulence has long been known to drive phytoplankton fitness and species succession: motile species dominate in calmer environments and non-motile species in turbulent conditions. Yet, a mechanistic understanding of the effect of turbulence on phytoplankton migratory behavior and physiology is lacking. By combining a method to generate turbulent cues, quantification of stress accumulation and physiology, and a mathematical model of stress dynamics, we show that motile phytoplankton use their mechanical stability to sense the intensity of turbulent cues and integrate these cues in time via stress signaling to trigger switches in migratory behavior. The stress-mediated warning strategy we discovered provides a paradigm for how phytoplankton cope with turbulence, thereby potentially governing which species will be successful in a changing ocean.

biophysics↗