Single-molecule tracking (SMT) offers rich information on the dynamics of underlying biological processes, but multicolor SMT has been challenging due to spectral cross talk and a need for multiple laser excitations. Here, we describe a single-molecule spectral imaging approach for live-cell tracking of multiple fluorescent species at once using a single-laser excitation. Fluorescence signals from all the molecules in the field of view are collected using a single objective and split between positional and spectral channels. Images of the same molecule in the two channels are then combined to determine both the location and the identity of the molecule. The single-objective configuration of our approach allows for flexible sample geometry and the use of a live-cell incubation chamber required for live-cell SMT. Despite a lower photon yield, we achieve excellent spatial (20-40 nm) and spectral (10-15 nm) resolutions comparable to those obtained with dual-objective, spectrally resolved Stochastic Optical Reconstruction Microscopy. Furthermore, motions of the fluorescent molecules did not cause loss of spectral resolution owing to the dual-channel spectral calibration. We demonstrate SMT in three (and potentially more) colors using spectrally proximal fluorophores and single-laser excitation, and show that trajectories of each species can be reliably extracted with minimal cross talk.
Several organelles in eukaryotic cells, including mitochondria and the endoplasmic reticulum, form interconnected tubule networks extending throughout the cell. These tubular networks host many biochemical pathways that rely on proteins diffusively searching through the network to encounter binding partners or localized target regions. Predicting the behavior of such pathways requires a quantitative understanding of how confinement to a reticulated structure modulates reaction kinetics. In this work, we develop both exact analytical methods to compute mean first passage times and efficient kinetic Monte Carlo algorithms to simulate trajectories of particles diffusing in a tubular network. Our approach leverages exact propagator functions for the distribution of transition times between network nodes and allows large simulation time steps determined by the network structure. The methodology is applied to both synthetic planar networks and organelle network structures, demonstrating key general features such as the heterogeneity of search times in different network regions and the functional advantage of broadly distributing target sites throughout the network. The proposed algorithms pave the way for future exploration of the interrelationship between tubular network structure and biomolecular reaction kinetics.
Graphic Abstract
Transport of intracellular components relies on a variety of active and passive mechanisms, ranging from the diffusive spreading of small molecules over short distances to motor-driven motion across long distances. The cell-scale behavior of these mechanisms is fundamentally dependent on the morphology of the underlying cellular structures. Diffusion-limited reaction times can be qualitatively altered by the presence of occluding barriers or by confinement in complex architectures, such as those of reticulated organelles. Motor-driven transport is modulated by the architecture of cytoskeletal filaments that serve as transport highways. In this review, we discuss the impact of geometry on intracellular transport processes that fulfill a broad range of functional objectives, including delivery, distribution, and sorting of cellular components. By unraveling the interplay between morphology and transport efficiency, we aim to elucidate key structure–function relationships that govern the architecture of transport systems at the cellular scale. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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