Propofol is the most widely used i.v. general anesthetic to induce and maintain anesthesia. It is now recognized that this small molecule influences ligand-gated channels, including the GABA A receptor and others. Specific propofol binding sites have been mapped using photoaffinity ligands and mutagenesis; however, their precise target interaction profiles fail to provide complete mechanistic underpinnings for the anesthetic state. These results suggest that propofol and other common anesthetics, such as etomidate and ketamine, may target additional protein networks of the CNS to contribute to the desired and undesired anesthesia end points. Some evidence for anesthetic interactions with the cytoskeleton exists, but the molecular motors have received no attention as anesthetic targets. We have recently discovered that propofol inhibits conventional kinesin-1 KIF5B and kinesin-2 KIF3AB and KIF3AC, causing a significant reduction in the distances that these processive kinesins can travel. These microtubule-based motors are highly expressed in the CNS and the major anterograde transporters of cargos, such as mitochondria, synaptic vesicle precursors, neurotransmitter receptors, cell signaling and adhesion molecules, and ciliary intraflagellar transport particles. The single-molecule results presented show that the kinesin processive stepping distance decreases 40-60% with EC 50 values <100 nM propofol without an effect on velocity. The lack of a velocity effect suggests that propofol is not binding at the ATP site or allosteric sites that modulate microtubule-activated ATP turnover. Rather, we propose that a transient propofol allosteric site forms when the motor head binds to the microtubule during stepping.anesthesia | allosteric inhibitor | microtubule | etomidate | ketamine

Microtubules establish the directionality of intracellular transport by kinesins and dynein through 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 induces unidirectional transport in axons but bi-directional transport with a net retrograde bias in dendrites. Removal of the secondary microtubule binding regions of KIF21B or dampening of microtubule dynamics with low concentrations of nocodazole eliminates retrograde bias in live dendrites. Further exploration of the contribution of microtubule dynamics in dendrites to directionality revealed plus-end-out microtubules to be more dynamic than plus-end-in microtubules, with nocodazole preferentially stabilizing the plus-end-out population. We propose a model in which both nucleotide-sensitive and insensitive microtubule binding sites of KIF21B motors contribute to the search and selection of stable plus-end-in microtubules within the mixed polarity microtubule arrays characteristic of mammalian dendrites to achieve net retrograde movement of KIF21B-bound cargos. [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text]

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.

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 signal. 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. [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text]