We theoretically predict and experimentally show that the propagation direction of in vitro Min protein patterns can be controlled by a hydrodynamic flow of the bulk solution. We find downstream propagation of Min wave patterns relative to the bulk flow direction for low MinE:MinD concentration ratios, but upstream propagation for large MinE:MinD ratios, with multistability of both propagation directions in between. A theoretical model for the Min system reveals the mechanism underlying the upstream propagation and links it to the fast conformational switching of MinE in the bulk. For high MinE:MinD ratios, upstream propagation can be reproduced by a reduced model in which increased MinD bulk concentrations on the upstream side promote protein attachment and hence, propagation in that direction. For low MinE:D ratios, downstream propagation is described by the minimal model, as additionally confirmed by experiments with a non-switching MinE mutant. No advection takes place on the membrane surface where the protein patterns form, but advective bulk flow shifts the protein-concentration profiles in the bulk relative to the membrane-bound pattern. From a broader perspective, differential flows in a bulk volume relative to a surface are a relevant general feature in bulk-surface coupled systems. Our study shows how such a differential flow can control surface-pattern propagation and demonstrates how the global pattern's response may depend on specific molecular features of the reaction kinetics.
Membrane abscission, the final cut of the last connection between emerging daughter cells, is an indispensable event in the last stage of cell division, as well as in other cellular processes such as endocytosis, virus release, or bacterial sporulation. However, its mechanism remains poorly understood, which also impedes its application as a cell-division machinery for synthetic cells. Here, we use fluorescence microscopy and Fluorescence Recovery After Photobleaching (FRAP) to study the in vitro reconstitution of the bacterial protein Dynamin A (DynA) inside liposomes. Upon external reshaping of the liposomes into dumbbells, DynA self-assembles at the membrane neck, resulting in membrane hemi-scission and even full scission. DynA proteins constitute a simple one-component division machinery that is capable of splitting dumbbell-shaped liposomes, marking an important step towards building a synthetic cell.
The Min protein system is arguably the best-studied model system for biological pattern formation. It exhibits pole-to-pole oscillations in E. coli bacteria as well as a variety of surface wave patterns in in vitro reconstitutions. Such Min surface wave patterns pose particular challenges to quantification as they are typically only semi-periodic and non-stationary. Here, we present a methodology for quantitatively analysing such Min patterns, aiming for reproducibility, user-independence, and easy usage. After introducing pattern-feature definitions and image-processing concepts, we present an analysis pipeline where we use autocorrelation analysis to extract global parameters such as the average spatial wavelength and oscillation period. Subsequently, we describe a method that uses flow-field analysis to extract local properties such as the wave propagation velocity. We provide descriptions on how to practically implement these quantification tools and provide Python code that can directly be used to perform analysis of Min patterns.
The Min proteins constitute the best-studied model system for pattern formation in cell biology. We theoretically predict and experimentally show that the propagation direction of in vitro Min protein patterns can be controlled by a hydrodynamic flow of the bulk solution. We find downstream propagation of Min wave patterns for low MinE:MinD concentration ratios, upstream propagation for large ratios, but multistability of both propagation directions in between. Whereas downstream propagation can be described by a minimal model that disregards MinE conformational switching, upstream propagation can be reproduced by a reduced switch model, where increased MinD bulk concentrations on the upstream side promote protein attachment. Our study demonstrates that a differential flow, where bulk flow advects protein concentrations in the bulk, but not on the surface, can control surface-pattern propagation. This suggests that flow can be used to probe molecular features and to constrain mathematical models for pattern-forming systems.
The Min protein system is arguably the best-studied model systems for biological pattern formation. It exhibits pole-to-pole oscillations in E. coli bacteria as well as a variety of surface wave patterns in in vitro reconstitutions. Such Min surface wave patterns pose particular challenges to quantification as they are typically only semi-periodic and non-stationary. Here, we present a methodology for quantitatively analyzing such Min patterns, aiming for reproducibility, user-independence, and easy usage. After introducing pattern-feature definitions and image-processing concepts, we present an analysis pipeline where we use autocorrelation analysis to extract global parameters such as the average spatial wavelength and oscillation period. Subsequently, we describe a method that uses flow-field analysis to extract local properties such as the wave propagation velocity. We provide descriptions on how to practically implement these quantification tools and provide Python code that can directly be used to perform analysis of Min patterns.
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