Can molecular motors drive distance measurements in injured neurons?

Injury to nerve axons induces diverse responses in neuronal cell bodies, some of which are influenced by the distance from the site of injury. This suggests that neurons have the capacity to estimate the distance of the injury site from their cell body. Recent work has shown that the molecular motor dynein transports importin-mediated retrograde signaling complexes from axonal lesion sites to cell bodies, raising the question whether dynein-based mechanisms enable axonal distance estimations in injured neurons? We used computer simulations to examine mechanisms that may provide nerve cells with dynein-dependent distance assessment capabilities. A multiple-signals model was postulated based on the time delay between the arrival of two or more signals produced at the site of injury-a rapid signal carried by action potentials or similar mechanisms and slower signals carried by dynein. The time delay between the arrivals of these two types of signals should reflect the distance traversed, and simulations of this model show that it can indeed provide a basis for distance measurements in the context of nerve injuries. The analyses indicate that the suggested mechanism can allow nerve cells to discriminate between distances differing by 10% or more of their total axon length, and suggest that dynein-based retrograde signaling in neurons can be utilized for this purpose over different scales of nerves and organisms. Moreover, such a mechanism might also function in synapse to nucleus signaling in uninjured neurons. This could potentially allow a neuron to dynamically sense the relative lengths of its processes on an ongoing basis, enabling appropriate metabolic output from cell body to processes.

A scenario-based approach to modeling development: a prototype model of C. elegans vulval fate specification.

Studies of developmental biology are often facilitated by diagram "models" that summarize the current understanding of underlying mechanisms. The increasing complexity of our understanding of development necessitates computational models that can extend these representations to include their dynamic behavior. Here we present a prototype model of Caenorhabditis elegans vulval precursor cell fate specification that represents many processes crucial for this developmental event but that are hard to integrate using other modeling methodologies. We demonstrate the integrative capabilities of our methodology by comprehensively incorporating the contents of three seminal papers, showing that this methodology can lead to comprehensive models of developmental biology. The prototype computational model was built and is run using a language (Live Sequence Charts) and tool (the Play-Engine) that facilitate the same conceptual processes biologists use to construct and probe diagram-type models. We demonstrate that this modeling approach permits rigorous tests of mutual consistency between experimental data and mechanistic hypotheses and can identify specific conflicting results, providing a useful approach to probe developmental systems.

A motor-driven mechanism for cell-length sensing.

Size homeostasis is fundamental in cell biology, but it is not clear how large cells such as neurons can assess their own size or length. We examined a role for molecular motors in intracellular length sensing.Computational simulations suggest that spatial information can be encoded by the frequency of an oscillating retrograde signal arising from a composite negative feedback loop between bidirectional motor-dependent signals. The model predicts that decreasing either or both anterograde or retrograde signals should increase cell length, and this prediction was confirmed upon application of siRNAs for specific kinesin and/or dynein heavy chains in adult sensory neurons. Heterozygous dynein heavy chain 1 mutant sensory neurons also exhibited increased lengths both in vitro and during embryonic development.Moreover, similar length increases were observed in mouse embryonic fibroblasts upon partial downregulation of dynein heavy chain 1.Thus, molecular motors critically influence cell length sensing and growth control.

Monoclonal antibody to a DNA-binding domain of p53 mimics charge structure of DNA: anti-idiotypes to the anti-p53 antibody are anti-DNA.

Antibodies to DNA are important markers of various autoimmune diseases and can be pathogenic; however, their generation is not understood. We previously reported that anti-DNA antibodies could be induced in mice by idiotypic immunization to PAb-421, an antibody to a DNA-binding domain of p53. We now report that two monoclonal antibodies of moderate affinity (K(D) asymptotically equal to 10(-7)), raised from PAb-421-immunized mice, specifically recognized both PAb-421 and DNA. These antibodies feature multiple arginine residues in the antigen-binding site, a unique characteristic of disease-associated anti-DNA antibodies; nevertheless, these anti-DNA antibodies show specific complementarity to PAb-421 by competing with p53 for PAb-421 binding and recognize defined oligonucleotides with a specificity similar to that of p53. To study the structural basis for the cross-recognition of PAb-421 and DNA by the anti-DNA antibodies, we constructed computer models (fine-tuned by protein-protein docking) of PAb-421 and one of the monoclonal anti-DNA antibodies. The modeled structures manifested structural complementarity. Most notably, the modeled structure of PAb-421 resembled the structure of DNA by the positions of negatively charged groups and aromatic side chains. Thus, a protein molecule may mimic the structure of DNA and the elusive generation of anti-DNA antibodies could be explained by idiotypic immunity to a DNA-binding protein, like p53.