An in vivo Rodent Model of Contraction-induced Injury and Non-invasive Monitoring of Recovery

Muscle strains are one of the most common complaints treated by physicians. A muscle injury is typically diagnosed from the patient history and physical exam alone, however the clinical presentation can vary greatly depending on the extent of injury, the patient''s pain tolerance, etc. In patients with muscle injury or muscle disease, assessment of muscle damage is typically limited to clinical signs, such as tenderness, strength, range of motion, and more recently, imaging studies. Biological markers, such as serum creatine kinase levels, are typically elevated with muscle injury, but their levels do not always correlate with the loss of force production. This is even true of histological findings from animals, which provide a "direct measure" of damage, but do not account for all the loss of function. Some have argued that the most comprehensive measure of the overall health of the muscle in contractile force. Because muscle injury is a random event that occurs under a variety of biomechanical conditions, it is difficult to study. Here, we describe an in vivo animal model to measure torque and to produce a reliable muscle injury. We also describe our model for measurement of force from an isolated muscle in situ. Furthermore, we describe our small animal MRI procedure.Download video file.^{(50M, mov)}     

The model–data fusion pitfall: assuming certainty in an uncertain world

Model–data fusion is a powerful framework by which to combine models with various data streams (including observations at different spatial or temporal scales), and account for associated uncertainties. The approach can be used to constrain estimates of model states, rate constants, and driver sensitivities. The number of applications of model–data fusion in environmental biology and ecology has been rising steadily, offering insights into both model and data strengths and limitations. For reliable model–data fusion-based results, however, the approach taken must fully account for both model and data uncertainties in a statistically rigorous and transparent manner. Here we review and outline the cornerstones of a rigorous model–data fusion approach, highlighting the importance of properly accounting for uncertainty. We conclude by suggesting a code of best practices, which should serve to guide future efforts.     

Constructing and validating initial Cα models from subnanometer resolution density maps with pathwalking

A significant number of macromolecular structures solved by electron cryo-microscopy and X-ray crystallography obtain resolutions of 3.5-6?, at which direct atomistic interpretation is difficult. To address this, we developed pathwalking, a semi-automated protocol to enumerate reasonable Cα models from near-atomic resolution density maps without a structural template or sequence-structure correspondence. Pathwalking uses an approach derived from the Traveling Salesman Problem to rapidly generate an ensemble of initial models for individual proteins, which can later be optimized to produce full atomic models. Pathwalking can also be used to validate and identify potential structural ambiguities in models generated from near-atomic resolution density maps. In this work, examples from the EMDB and PDB are used to assess the broad applicability and accuracy of our method. With the growing number of near-atomic resolution density maps from cryo-EM and X-ray crystallography, pathwalking can become an important tool in modeling protein structures.     

Novel function of cardiac protein kinase D1 as a dynamic regulator of Ca2+ sensitivity of contraction

Although the function of protein kinase D1 (PKD) in cardiac cells has remained enigmatic, recent work has shown that PKD phosphorylates the nuclear regulators HDAC5/7 (histone deacetylase 5/7) and CREB, implicating this kinase in the development of dysfunction seen in heart failure. Additional studies have shown that PKD also phosphorylates multiple sarcomeric substrates to regulate myofilament function. Initial studies examined PKD through adenoviral vector expression of wild type PKD, constitutively active PKD (caPKD), or dominant negative PKD in cultured adult rat ventricular myocytes. Confocal immunofluorescent images of these cells reveal a predominant distribution of all PKD forms in a non-nuclear, Z-line localized, striated reticular pattern, suggesting the importance of PKD in Ca(2+) signaling in heart. Consistent with an established role of PKD in targeting cardiac troponin I (cTnI), caPKD expression led to a marked decrease in contractile myofilament Ca(2+) sensitivity with an unexpected electrical stimulus dependence to this response. This desensitization was accompanied by stimulus-dependent increases in cTnI phosphorylation in control and caPKD cells with a more pronounced effect in the latter. Electrical stimulation also provoked phosphorylation of regulatory site Ser(916) on PKD. The functional importance of this phospho-Ser(916) event is demonstrated in experiments with a phosphorylation-defective mutant, caPKD-S916A, which is functionally inactive and blocks stimulus-dependent increases in cTnI phosphorylation. Dominant negative PKD expression resulted in sensitization of the myofilaments to Ca(2+) and blocked stimulus-dependent increases in cTnI phosphorylation. Taken together, these data reveal that localized PKD may play a role as a dynamic regulator of Ca(2+) sensitivity of contraction in cardiac myocytes.     

Gorgon and pathwalking: macromolecular modeling tools for subnanometer resolution density maps

The complex interplay of proteins and other molecules, often in the form of large transitory assemblies, are critical to cellular function. Today, X-ray crystallography and electron cryo-microscopy (cryo-EM) are routinely used to image these macromolecular complexes, though often at limited resolutions. Despite the rapidly growing number of macromolecular structures, few tools exist for modeling and annotating structures in the range of 3-10 ? resolution. To address this need, we have developed a number of utilities specifically targeting subnanometer resolution density maps. As part of the 2010 Cryo-EM Modeling Challenge, we demonstrated two of our latest de novo modeling tools, Pathwalking and Gorgon, as well as a tool for secondary structure identification (SSEHunter) and a new rigid-body/flexible fitting tool in Gorgon. In total, we submitted 30 structural models from ten different subnanometer resolution data sets in four of the six challenge categories. Each of our utlities produced accurate structural models and annotations across the various density maps. In the end, the utilities that we present here offer users a robust toolkit for analyzing and modeling protein structure in macromolecular assemblies at non-atomic resolutions.