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Masucci, E. M.

Publications and source records attributed to Masucci, E. M..

2 recordsLinked to original sources

Kinesin-4 Motor Teams Effectively Navigate Dendritic Microtubule Arrays Through Track Switching and Regulation of Microtubule Dynamics

Microtubules establish the directionality of intracellular transport by kinesins and dynein through their polarized assembly, but it remains unclear how directed transport occurs along microtubules organized with mixed polarity. We investigated the ability of the plus-end directed kinesin-4 motor KIF21B to navigate mixed polarity microtubules in mammalian dendrites. Reconstitution assays with recombinant KIF21B and engineered microtubule bundles or extracted neuronal cytoskeletons indicate that nucleotide- independent microtubule binding regions of KIF21B modulate microtubule dynamics and promote directional switching on antiparallel microtubules. Optogenetic recruitment of KIF21B to organelles in live neurons resulted in unidirectional transport in axons but bi-directional transport with a net retrograde bias in dendrites; microtubule dynamics and the secondary microtubule binding regions are required for this net directional bias. We propose a model in which cargo-bound KIF21B motors coordinate nucleotide- sensitive and insensitive microtubule binding sites to achieve net retrograde movement along the dynamic mixed polarity microtubule arrays of dendrites.

cell biology

Cega: A Single Particle Segmentation Algorithm to Identify Moving Particles in a Noisy System

Improvements to particle tracking algorithms are required to effectively analyze the motility of biological molecules in complex or noisy systems. A typical single particle tracking (SPT) algorithm detects particle coordinates for trajectory assembly. However, particle detection filters fail for datasets with low signal-to-noise levels. When tracking molecular motors in complex systems, standard techniques often fail to separate the fluorescent signatures of moving particles from background noise. We developed an approach to analyze the motility of kinesin motor proteins moving along the microtubule cytoskeleton of extracted neurons using the Kullback-Leibler (KL) divergence to identify regions where there are significant differences between models of moving particles and background signal. We tested our software on both simulated and experimental data and found a noticeable improvement in SPT capability and a higher identification rate of motors as compared to current methods. This algorithm, called Cega, for find the object, produces data amenable to conventional blob detection techniques that can then be used to obtain coordinates for downstream SPT processing. We anticipate that this algorithm will be useful for those interested in tracking moving particles in complex in vitro or in vivo environments.

cell biology