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Juan Botas

During the past two decades many genes triggering neurological diseases have been identified. Some of these diseases are caused by gain of function mutations and/or impaired proteolysis of the respective proteins. Among these proteins are huntingtin (Huntington disease, HD), alpha-synuclein (Parkinson disease, PD) and the tau and amyloid precursor proteins (in Alzheimer's AD). On the other hand, diseases like Rett Syndrome are caused by loss of function mechanisms. In spite of many significant advances in our understanding of these diseases, we still have a poor understanding of what happens between the triggering of the disease by the faulty protein and the ultimate death of the neuron. What are the mechanisms of pathogenesis? What are the genetic pathways and specific genes and proteins involved during disease progression? Can we identify new therapeutic targets?

To address these questions, we have generated Drosophila models for several neurological and neuromuscular disorders that recapitulate key neuropathological phenotypes observed in patients. For example, Drosophila models the neurodegenerative diseases spinocerebellar ataxia type 1 (SCA1), Huntington’s and Alzheimer’s show late onset, formation of protein aggregates, accumulation of chaperones and ubiquitin-proteolytic pathway components in these aggregates, and progressive neuronal degeneration. These Drosophila models of disease allow us to carry out rapid, genome-wide genetic screens to identify genetic modifiers and therapeutic targets—genome-scale screens are possible in Drosophila but not feasible using mouse models. We have shown the validity of this approach using Drosophila models of SCA1, HD, AD, PD, Myotonic dystrophy type 1 (DM1) etc. (see list of publications). A second interest of our research program is to exploit these Drosophila models for comparative analysis of modifier genes and pathogenic mechanisms to identify therapeutic opportunities that may be applied to more than one disease. These genetic approaches are integrated with transcriptomic and metabolomics analysis of disease models and human tissues. A third goal of our lab is to perform chemical screens using behavioral readouts to assess CNS function/ dysfunction resulting form neurological disorders.

How Do We Make Sense Of -omic Datasets? A Strategy Integrating Gene Perturbation And Computational Analysis May Help

Neurological disorders remain one of the last frontiers of medicine. Available treatments are few; of those that exist, most only mitigate symptoms and do nothing to slow the progression of the disease. Both the inaccessibility and the complexity of the […]