Parrini, M. C. | bioRxiv Science

bioRxiv2024

CausalXtract: a flexible pipeline to extract causal effects from live-cell time-lapse imaging data

Live-cell microscopy routinely provides massive amount of time-lapse images of complex cellular systems under various physiological or therapeutic conditions. However, this wealth of data remains difficult to interpret in terms of causal effects. Here, we describe CausalXtract, a flexible computational pipeline that discovers causal and possibly time-lagged effects from morphodynamic features and cell-cell interactions in live-cell imaging data. CausalXtract methodology combines network-based and information-based frameworks, which is shown to discover causal effects overlooked by classical Granger and Schreiber causality approaches. We showcase the use of CausalXtract to uncover novel causal effects in a tumor-on-chip cellular ecosystem under therapeutically relevant conditions. In particular, we find that cancer associated fibroblasts directly inhibit cancer cell apoptosis, independently from anti-cancer treatment. CausalXtract uncovers also multiple antagonistic effects at different time delays. Hence, CausalXtract provides a unique computational tool to interpret live-cell imaging data for a range of fundamental and translational research applications.

systems biology↗

bioRxiv2017

Gradients Of Rac1 Nanoclusters Support Spatial Patterns Of Rac1 Signaling

The dynamics of the cytoskeleton and cell shape relies on the coordinated activation of RhoGTPase molecular switches. Among them, Rac1 participates to the orchestration in space and time of actin branching and protrusion/retraction cycles of the lamellipodia at the cell front during mesenchymal migration. Biosensor imaging has revealed a graded concentration of active GTP-loaded Rac1 in protruding regions of the cell. Here, using single molecule imaging and super-resolution microscopy, we reveal an additional supramolecular organization of Rac1. We find that, similarly to H-Ras, Rac1 partitions and is immobilized into nanoclusters of 50-100 molecules each. These nanoclusters assemble due to the interaction of the polybasic tail of Rac1 with the phosphoinositide lipids PIP2 and PIP3. The additional interactions with GEFs, GAPs, downstream effectors, and possibly other partners are responsible for an enrichment of Rac1 nanoclusters in protruding regions of the cell. Using optogenetics and micropatterning tools, we find that activation of Rac1 leads to its immobilization in nanoclusters and that the local level of Rac1 activity matches the local density of nanoclusters. Altogether, our results show that subcellular patterns of Rac1 activity are supported by gradients of signaling nanodomains of heterogeneous molecular composition, which presumably act as discrete signaling platforms. This finding implies that graded distributions of nanoclusters might encode spatial information.\n\nSignificance statementThe plasma membrane of eukaryotic cells is a highly organized surface where hundreds of incoming signals are transduced to the intracellular space. How cells encode faithfully this myriad of signals is a fundamental question. Here we show that Rac1, a critical membrane-bound protein involved in the regulation of cytoskeletal dynamics, forms small aggregates together with other regulating proteins. These supramolecular assemblies, called nanoclusters, are the \"quantal\" units of signaling. By increasing the local concentration, nanoclusters set thresholds for downstream signaling and ensure the fidelity of information transduction. We found that Rac1 nanoclusters are distributed as spatial gradients matching the patterns of Rac1 activity. We propose that cells can encode positional information through distributed signaling quanta, hereby ensuring spatial fidelity.

biophysics↗