BioFlow: a non-invasive, image-based method to measure speed, pressure and forces inside living cells

Abstract : Cell motility is governed by a complex molecular machinery that converts physico-chemical cues into whole-cell movement. Understanding the underlying biophysical mechanisms requires the ability to measure physical quantities inside the cell in a simple, reproducible and preferably non-invasive manner. To this end, we developed BioFlow, a computational mechano-imaging method and associated software able to extract intracellular measurements including pressure, forces and velocity everywhere inside freely moving cells in two and three dimensions with high spatial resolution in a non-invasive manner. This is achieved by extracting the motion of intracellular material observed using fluorescence microscopy, while simultaneously inferring the parameters of a given theoretical model of the cell interior. We illustrate the power of BioFlow in the context of amoeboid cell migration, by modelling the intracellular actin bulk flow of the parasite Entamoeba histolytica using fluid dynamics, and report unique experimental measures that complement and extend both theoretical estimations and invasive experimental measures. Thanks to its flexibility, BioFlow is easily adaptable to other theoretical models of the cell, and alleviates the need for complex or invasive experimental conditions, thus constituting a powerful tool-kit for mechano-biology studies. BioFlow is open-source and freely available via the Icy software. The ability of cells to define and alter their shape, maintain cell-cell contact, initiate and regulate movement is central to numerous fundamental biological processes including development, microbial infection, immune response, and cancer metastasis 1. The mechanisms underlying cell shape and motility involve complex molecular machinery that senses and translates both internal and external signals (mechanical and chemical) into physical quantities. At the mechanical level, deciphering how cells deform and migrate requires a better understanding of the biophysical quantities driving intracellular dynamics, including intracellular pressure, stiffness, viscosity and forces 2. Unfortunately, many of these quantities cannot be measured directly with current methodologies, and are typically estimated using various indirect or invasive experimental approaches 3. Many such methods operate at the extracellular level, and typically involve interacting with the cell surface. This can be done either actively, e.g. using micro-pipette aspiration 4 , Atomic Force Microscopy 5 and micro-particle insertion 6 , or passively , e.g. using Traction Force Microscopy, where the cells freely interact with engineered substrates formed either of micro-pillars of known properties 7 or filled with fluorescent beads 8, 9. At the intracellular level however , biophysical measurements remain scarce and limited by experimental constraints. Foreign particles can be inserted inside the cell and tracked through video-microscopy in order to characterise intracellular dynamics (Particle Tracking Velocimetry 10, 11). This technique generally requires controlled manipulation of the particles, which is usually achieved via magnetic 12 or optical 13 tweezers. Unfortunately, these methods are highly localised
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Scientific Reports, Nature Publishing Group, 2017, 7 (1), pp.9178. 〈https://www.nature.com/articles/s41598-017-09240-y#Abs1〉. 〈10.1038/s41598-017-09240-y〉
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Aleix Boquet-Pujadas, Timothée Lecomte, Maria Manich, Roman Thibeaux, Elisabeth Labruyère, et al.. BioFlow: a non-invasive, image-based method to measure speed, pressure and forces inside living cells. Scientific Reports, Nature Publishing Group, 2017, 7 (1), pp.9178. 〈https://www.nature.com/articles/s41598-017-09240-y#Abs1〉. 〈10.1038/s41598-017-09240-y〉. 〈pasteur-01581995〉

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