Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

A novel phenotype for the dynein heavy chain mutation Loa: altered dendritic morphology, organelle density, and reduced numbers of trigeminal motoneurons.

Larisa M Wiggins | A Kuta | James C Stevens | Elizabeth M C Fisher | Christopher S von Bartheld
The Journal of comparative neurology | 2012

Dynein, the retrograde motor protein, is essential for the transport of cargo along axons and proximal dendrites in neurons. The dynein heavy chain mutation Loa has been reported to cause degeneration of spinal motor neurons, as well as defects of spinal sensory proprioceptive neurons, but cranial nerve nuclei have received little attention. Here, we examined the number and morphology of neurons in cranial nerve nuclei of young, adult, and aged heterozygous Loa mice, with a focus on the trigeminal, facial, and trochlear motor nuclei, as well as the proprioceptive mesencephalic trigeminal nucleus. By using stereological counting techniques, we report a slowly progressive and significant reduction, to 75% of wild-type controls, in the number of large trigeminal motoneurons, whereas normal numbers were found for sensory mesencephalic trigeminal, facial, and trochlear motoneurons. The morphology of many surviving large trigeminal motoneurons was substantially altered, in particular the size and length of perpendicularly extending primary dendrites, but not those of facial or trochlear motoneurons. At the ultrastructural level, proximal dendrites of large trigeminal motoneurons, but not other neurons, were significantly depleted in organelle content such as polyribosomes and showed abnormal (vesiculated) mitochondria. These data indicate primary defects in trigeminal α-motoneurons more than γ-motoneurons. Our findings expand the Loa heterozygote phenotype in two important ways: we reveal dendritic in addition to axonal defects or abnormalities, and we identify the Loa mutation as a mouse model for mixed motor-sensory loss when the entire neuraxis is considered, rather than a model primarily for sensory loss.

Pubmed ID: 22684941

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

  • Agency: NCRR NIH HHS, United States
    Id: P20 RR016464
  • Agency: NIGMS NIH HHS, United States
    Id: GM103554
  • Agency: NCRR NIH HHS, United States
    Id: RR016464
  • Agency: NCRR NIH HHS, United States
    Id: RR024210
  • Agency: NIGMS NIH HHS, United States
    Id: GM103440
  • Agency: NIGMS NIH HHS, United States
    Id: P20 GM103554
  • Agency: Medical Research Council, United Kingdom
    Id: G0500288
  • Agency: NCRR NIH HHS, United States
    Id: RR015581
  • Agency: NEI NIH HHS, United States
    Id: EY012841
  • Agency: NIGMS NIH HHS, United States
    Id: P20 GM103440
  • Agency: NCRR NIH HHS, United States
    Id: P20 RR015581
  • Agency: NEI NIH HHS, United States
    Id: R01 EY012841
  • Agency: NCRR NIH HHS, United States
    Id: P20 RR024210

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


NEURON (tool)

RRID:SCR_005393

NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything

View all literature mentions

SigmaStat (tool)

RRID:SCR_010285

Software tool for data graphing and analysis by Systat Software, Inc.

View all literature mentions