title: Quantitative measurements and modeling of cargo-motor interactions during fast transport in the living axon.
abstract: The kinesins have long been known to drive microtubule-based transport of sub-cellular components, yet the mechanisms of their attachment to cargo remain a mystery. Several different cargo-receptors have been proposed based on their in vitro binding affinities to kinesin-1. Only two of these-phosphatidyl inositol, a negatively charged lipid, and the carboxyl terminus of the amyloid precursor protein (APP-C), a trans-membrane protein-have been reported to mediate motility in living systems. A major question is how these many different cargo, receptors and motors interact to produce the complex choreography of vesicular transport within living cells. Here we describe an experimental assay that identifies cargo-motor receptors by their ability to recruit active motors and drive transport of exogenous cargo towards the synapse in living axons. Cargo is engineered by derivatizing the surface of polystyrene fluorescent nanospheres (100 nm diameter) with charged residues or with synthetic peptides derived from candidate motor receptor proteins, all designed to display a terminal COOH group. After injection into the squid giant axon, particle movements are imaged by laser-scanning confocal time-lapse microscopy. In this report we compare the motility of negatively charged beads with APP-C beads in the presence of glycine-conjugated non-motile beads using new strategies to measure bead movements. The ensuing quantitative analysis of time-lapse digital sequences reveals detailed information about bead movements: instantaneous and maximum velocities, run lengths, pause frequencies and pause durations. These measurements provide parameters for a mathematical model that predicts the spatiotemporal evolution of distribution of the two different types of bead cargo in the axon. The results reveal that negatively charged beads differ from APP-C beads in velocity and dispersion, and predict that at long time points APP-C will achieve greater progress towards the presynaptic terminal. The significance of this data and accompanying model pertains to the role transport plays in neuronal function, connectivity, and survival, and has implications in the pathogenesis of neurological disorders, such as Alzheimer's, Huntington and Parkinson's diseases.
authors.affiliation: Department of Pathology, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA.
authors.forename: Pamela E
authors.initials: PE
authors.lastname: Seamster
authors.forename: Michael
authors.initials: M
authors.lastname: Loewenberg
authors.forename: Jennifer
authors.initials: J
authors.lastname: Pascal
authors.forename: Arnaud
authors.initials: A
authors.lastname: Chauviere
authors.forename: Aaron
authors.initials: A
authors.lastname: Gonzales
authors.forename: Vittorio
authors.initials: V
authors.lastname: Cristini
authors.forename: Elaine L
authors.initials: EL
authors.lastname: Bearer
mesh_terms: D016564:Amyloid beta-Protein Precursor / Q000378:metabolism; D000818:Animals; D001369:Axons / Q000378:metabolism*; D001692:Biological Transport; D001703:Biophysics / Q000379:methods; D049832:Decapodiformes / Q000166:cytology / Q000378:metabolism; D005998:Glycine / Q000737:chemistry / Q000378:metabolism; D016547:Kinesins / Q000378:metabolism; D008432:Mathematical Computing; D018613:Microscopy, Confocal / Q000379:methods; D008954:Models, Biological; D054118:Nanospheres; D010455:Peptides / Q000737:chemistry / Q000378:metabolism; D015203:Reproducibility of Results
chemical_list: D016564:Amyloid beta-Protein Precursor; D010455:Peptides; D016547:Kinesins; D005998:Glycine