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 interaction betweenEntamoeba histolyticaand enterobacteria shed light on an ancient antibacterial response

“…Further works in the Cell Biology of Parasitism unit and in collaborative groups put all of these findings into perspective. More insights on amoebic motility and the signalling pathways supporting displacements during infection have been published recently (Aguilar‐Rojas et al, ; Boquet‐Pujadas et al, ; Dufour, Olivo‐Marin, & Guillen, ; Manich et al, ; Hernandez‐Cuevas, Jhingan, Petropolis, Vargas, & Guillen, ). In agreement with the subject of this review, I will focus on the relationship between Enterobacteriaceae and E. histolytica .…”

Joint Motion Estimation and Source Identification using Convective Regularisation with an Application to the Analysis of Laser Nanoablations

“…Recently, optical flow methods have been used for the quantitative analysis of biological image sequences on cellular and subcellular level. See, for instance, [2,9,10,21,31,34,39,44,50]. While the concept is in practice well-suited for natural scenes, the use of the less restrictive continuity equation, which arises from mass conservation, can be more favourable in certain scenarios.…”

Optical flow analysis reveals that Kinesin-mediated advection impacts on the orientation of microtubules in theDrosophilaoocyte

“…OF methods outperform popular methods, such as particle image velocimetry (PIV), for motion analysis in certain settings and, in particular, in the presence of noise (Ruhnau et al, 2005; Vig et al ., 2016). While variational OF methods have been used predominantly to investigate the dynamics of entire cells (Amat et al ., 2013; Boric et al ., 2013; Guo, 2014), recent works focused also on intracellular motility (Delpiano et al ., 2012; Frerking et al ., 2014; Vig et al ., 2016; Boquet-Pujadas et al ., 2017; Huang et al ., 2017).…”

“…Importantly, OF methods have been shown to outperform popular methods, such as particle image velocimetry (PIV), for motion analysis, resulting in higher accuracy and efficiency in certain settings and, in particular, in the presence of noise 22,23 . While variational OF methods have been used predominantly to investigate the dynamics of entire cells 24–31 , recent works focused on their application to study intracellular motility as well 22,32–35 . The high noise level, poor contrast, and the relatively small size of the EB1 comets, constituted the main challenges in the analysis of our data.…”