Background:Huntington's disease (HD) is a neurological disorder caused by mutations in the huntingtin (HTT) gene, the product of which leads to selective and progressive neuronal cell death in the striatum and cortex. Transcriptional dysregulation has emerged as a core pathologic feature in the CNS of human and animal models of HD. It is still unclear whether perturbations in gene expression are a consequence of the disease or importantly, contribute to the pathogenesis of HD. Objective: To examine if transcriptional dysregulation can be ameliorated with antisense oligonucleotides that reduce levels of mutant Htt and provide therapeutic benefit in the YAC128 mouse model of HD. Methods: Quantitative real-time PCR analysis was used to evaluate dysregulation of a subset of striatal genes in the YAC128 mouse model. Transcripts were then evaluated following ICV delivery of antisense oligonucleotides (ASO). Rota rod and Porsolt swim tests were used to evaluate phenotypic deficits in these mice following ASO treatment. Results: Transcriptional dysregulation was detected in the YAC128 mouse model and appears to progress with age. ICV delivery of ASOs directed against mutant Htt resulted in reduction in mutant Htt levels and amelioration in behavioral deficits in the YAC128 mouse model. These improvements were correlated with improvements in the levels of several dysregulated striatal transcripts. Conclusions:The role of transcriptional dysregulation in the pathogenesis of Huntington's disease is not well understood, however, a wealth of evidence now strongly suggests that changes in transcriptional signatures are a prominent feature in the brains of both HD patients and animal models of the disease. Our study is the first to show that a therapeutic agent capable of improving an HD disease phenotype is concomitantly correlated with normalization of a subset of dysregulated striatal transcripts. Our data suggests that correction of these disease-altered transcripts may underlie, at least in part, the therapeutic efficacy shown associated with ASO-mediated correction of HD phenotypes and may provide a novel set of early biomarkers for evaluating future therapeutic concepts for HD.

Under starvation conditions, a swarm of Myxococcus xanthus cells will undergo development, a multicellular process culminating in the formation of many aggregates called fruiting bodies, each of which contains up to 100,000 spores. The mechanics of symmetry breaking and the self-organization of cells into fruiting bodies is an active area of research. Here we use microcinematography and automated image processing to quantify several transient features of developmental dynamics. An analysis of experimental data indicates that aggregation reaches its steady state in a highly nonmonotonic fashion. The number of aggregates rapidly peaks at a value 2-to 3-fold higher than the final value and then decreases before reaching a steady state. The time dependence of aggregate size is also nonmonotonic, but to a lesser extent: average aggregate size increases from the onset of aggregation to between 10 and 15 h and then gradually decreases thereafter. During this process, the distribution of aggregates transitions from a nearly random state early in development to a more ordered state later in development. A comparison of experimental results to a mathematical model based on the traffic jam hypothesis indicates that the model fails to reproduce these dynamic features of aggregation, even though it accurately describes its final outcome. The dynamic features of M. xanthus aggregation uncovered in this study impose severe constraints on its underlying mechanisms.

When starved, a swarm of millions of Myxococcus xanthus cells coordinate their movement from outward swarming to inward coalescence. The cells then execute a synchronous program of multicellular development, arranging themselves into dome shaped aggregates. Over the course of development, about half of the initial aggregates disappear, while others persist and mature into fruiting bodies. This work seeks to develop a quantitative model for aggregation that accurately simulates which will disappear and which will persist. We analyzed time-lapse movies of M. xanthus development, modeled aggregation using the equations that describe Ostwald ripening of droplets in thin liquid films, and predicted the disappearance and persistence of aggregates with an average accuracy of 85%. We then experimentally validated a prediction that is fundamental to this model by tracking individual fluorescent cells as they moved between aggregates and demonstrating that cell movement towards and away from aggregates correlates with aggregate disappearance. Describing development through this model may limit the number and type of molecular genetic signals needed to complete M. xanthus development, and it provides numerous additional testable predictions.

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