Generation and Characterization of a genetic zebrafish model of SMA carrying the human SMN2 gene

Background

Animal models of human diseases are essential as they allow analysis of the disease process at the cellular level and can advance therapeutics by serving as a tool for drug screening and target validation. Here we report the development of a complete genetic model of spinal muscular atrophy (SMA) in the vertebrate zebrafish to complement existing zebrafish, mouse, and invertebrate models and show its utility for testing compounds that alter SMN2 splicing.

Results

The human motoneuron disease SMA is caused by low levels, as opposed to a complete absence, of the survival motor neuron protein (SMN). To generate a true model of SMA in zebrafish, we have generated a transgenic zebrafish expressing the human SMN2 gene (hSMN2), which produces only a low amount of full-length SMN, and crossed this onto the smn ^-/- background. We show that human SMN2 is spliced in zebrafish as it is in humans and makes low levels of SMN protein. Moreover, we show that an antisense oligonucleotide that enhances correct hSMN2 splicing increases full-length hSMN RNA in this model. When we placed this transgene on the smn mutant background it rescued the neuromuscular presynaptic SV2 defect that occurs in smn mutants and increased their survival.

Conclusions

We have generated a transgenic fish carrying the human hSMN2 gene. This gene is spliced in fish as it is in humans and mice suggesting a conserved splicing mechanism in these vertebrates. Moreover, antisense targeting of an intronic splicing silencer site increased the amount of full length SMN generated from this transgene. Having this transgene on the smn mutant fish rescued the presynaptic defect and increased survival. This model of zebrafish SMA has all of the components of human SMA and can thus be used to understand motoneuron dysfunction in SMA, can be used as an vivo test for drugs or antisense approaches that increase full-length SMN, and can be developed for drug screening.     

Crystal structure of a new benzoic acid inhibitor of influenza neuraminidase bound with a new tilt induced by overpacking subsite C6

Background

The quaternary structure of eukaryotic NADH:ubiquinone oxidoreductase (complex I), the largest complex of the oxidative phosphorylation, is still mostly unresolved. Furthermore, it is unknown where transiently bound assembly factors interact with complex I. We therefore asked whether the evolution of complex I contains information about its 3D topology and the binding positions of its assembly factors. We approached these questions by correlating the evolutionary rates of eukaryotic complex I subunits using the mirror-tree method and mapping the results into a 3D representation by multidimensional scaling.

Results

More than 60% of the evolutionary correlation among the conserved seven subunits of the complex I matrix arm can be explained by the physical distance between the subunits. The three-dimensional evolutionary model of the eukaryotic conserved matrix arm has a striking similarity to the matrix arm quaternary structure in the bacterium Thermus thermophilus (rmsd=19 ?) and supports the previous finding that in eukaryotes the N-module is turned relative to the Q-module when compared to bacteria. By contrast, the evolutionary rates contained little information about the structure of the membrane arm. A large evolutionary model of 45 subunits and assembly factors allows to predict subunit positions and interactions (rmsd = 52.6 ?). The model supports an interaction of NDUFAF3, C8orf38 and C2orf56 during the assembly of the proximal matrix arm and the membrane arm. The model further suggests a tight relationship between the assembly factor NUBPL and NDUFA2, which both have been linked to iron-sulfur cluster assembly, as well as between NDUFA12 and its paralog, the assembly factor NDUFAF2.

Conclusions

The physical distance between subunits of complex I is a major correlate of the rate of protein evolution in the complex I matrix arm and is sufficient to infer parts of the complex??s structure with high accuracy. The resulting evolutionary model predicts the positions of a number of subunits and assembly factors.     

Prediction of peak pressure from clinical and radiological measurements in patients with diabetes

Background

Various structural and functional factors of foot function have been associated with high local plantar pressures. The therapist focuses on these features which are thought to be responsible for plantar ulceration in patients with diabetes. Risk assessment of the diabetic foot would be made easier if locally elevated plantar pressure could be indicated with a minimum set of clinical measures.

Methods

Ninety three patients were evaluated through vascular, orthopaedic, neurological and radiological assessment. A pressure platform was used to quantify the barefoot peak pressure for six forefoot regions: big toe (BT) and metatarsals one (MT-1) to five (MT-5). Stepwise regression modelling was performed to determine which set of the clinical and radiological measures explained most variability in local barefoot plantar peak pressure in each of the six forefoot regions. Comprehensive models were computed with independent variables from the clinical and radiological measurements. The difference between the actual plantar pressure and the predicted value was examined through Bland-Altman analysis.

Results

Forefoot pressures were significant higher in patients with neuropathy, compared to patients without neuropathy for the whole forefoot, the MT-1 region and the MT-5 region (respectively 138 kPa, 173 kPa and 88 kPa higher: mean difference). The clinical models explained up to 39 percent of the variance in local peak pressures. Callus formation and toe deformity were identified as relevant clinical predictors for all forefoot regions. Regression models with radiological variables explained about 26 percent of the variance in local peak pressures. For most regions the combination of clinical and radiological variables resulted in a higher explained variance. The Bland and Altman analysis showed a major discrepancy between the predicted and the actual peak pressure values.

Conclusion

At best, clinical and radiological measurements could only explain about 34 percent of the variance in local barefoot peak pressure in this population of diabetic patients. The prediction models constructed with linear regression are not useful in clinical practice because of considerable underestimation of high plantar pressure values. Identification of elevated plantar pressure without equipment for quantification of plantar pressure is inadequate. The use of quantitative plantar pressure measurement for diabetic foot screening is therefore advocated.