single-molecule-tracking-microscopy-tool-for-determining-diffusive

Single-Molecule Tracking Microscopy - A Tool for Determining the Diffusive States of Cytosolic Molecules

Single-molecule localization microscopy probes the position and motions of individual molecules in living cells with tens of nanometer spatial and ...

In bacterial type 3 secretion, substrate proteins are actively transported from the bacterial cytoplasm into the host cell cytoplasm by a large membrane-embedded machinery called the injectisome. Injectisomes transport secretion substrates in response to specific environmental signals, but the molecular details by which the cytosolic secretion substrates are selected and transported through the type 3 secretion pathway remain unclear. Secretion activity and substrate selectivity are thought to be controlled by a sorting platform consisting of the proteins SctK, SctQ, SctL, and SctN, which together localize to the cytoplasmic side of membrane-embedded injectisomes. However, recent work revealed that sorting platform proteins additionally exhibit substantial cytosolic populations and that SctQ reversibly binds to and dissociates from the cytoplasmic side of membrane-embedded injectisomes. Based on these observations, we hypothesized that dynamic molecular turnover at the injectisome and cytosolic assembly among sorting platform proteins is a critical regulatory component of type 3 secretion. To determine whether sorting platform complexes exist in the cytosol, we measured the diffusive properties of the two central sorting platform proteins, SctQ and SctL, using live cell high-throughput 3D single-molecule tracking microscopy. Single-molecule trajectories, measured in wild-type and mutant Yersinia enterocolitica cells, reveal that both SctQ and SctL exist in several distinct diffusive states in the cytosol, indicating that these proteins form stable homo- and hetero-oligomeric complexes in their native environment. Our findings provide the first diffusive state-resolved insights into the dynamic regulatory network that interfaces stationary membrane-embedded injectisomes with the soluble cytosolic components of the type 3 secretion system.

Single-molecule tracking in live Yersinia enterocolitica reveals distinct cytosolic complexes of injectisome subunits.

The trajectory of a single protein in the cytosol of a living cell contains information about its molecular interactions in its native environment. However, it has remained challenging to accurately resolve and characterize the diffusive states that can manifest in the cytosol using analytical approaches based on simplifying assumptions. Here, we show that multiple intracellular diffusive states can be successfully resolved if sufficient single-molecule trajectory information is available to generate well-sampled distributions of experimental measurements and if experimental biases are taken into account during data analysis. To address the inherent experimental biases in camera-based and MINFLUX-based single-molecule tracking, we use an empirical data analysis framework based on Monte Carlo simulations of confined Brownian motion. This framework is general and adaptable to arbitrary cell geometries and data acquisition parameters employed in two-dimensional or three-dimensional single-molecule tracking. We show that, in addition to determining the diffusion coefficients and populations of prevalent diffusive states, the timescales of diffusive state switching can be determined by stepwise increasing the time window of averaging over subsequent single-molecule displacements. Time-averaged diffusion analysis of single-molecule tracking data may thus provide quantitative insights into binding and unbinding reactions among rapidly diffusing molecules that are integral for cellular functions.

Article	Year
Single-molecule tracking in live Yersinia enterocolitica reveals distinct cytosolic complexes of injectisome subunits. Integrative biology : quantitative biosciences from nano to macro\| PubMed ID: 30101242	2018
Resolving Cytosolic Diffusive States in Bacteria by Single-Molecule Tracking. Biophysical journal\| PubMed ID: 31030884	2019

Andreas Gahlmann

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