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Biology subjects

Moreno, E. L.

Publications and source records attributed to Moreno, E. L..

2 recordsLinked to original sources

Coupling comprehensive pesticide-wide association study to iPSC dopaminergic screening identifies and classifies Parkinson-relevant pesticides

Parkinsons disease (PD) is a complex, multi-factorial neurodegenerative disease, known to involve genetic, aging-related components, but also to be highly sensitive to environmental factors. In particular, ample evidence links pesticides to PD etiology. Here, establishing a field-to-bench paradigm, we have combined record-based exposure assessment in a population-based epidemiologic study of PD with testing in dopaminergic neurons produced from iPSCs to further identify and classify PD-relevant pesticides. First, agricultural pesticide-application records in California enabled us to investigate exposure to nearly 300 specific pesticides and PD risk in a comprehensive, pesticide-wide association study (PWAS). We implicated long-term exposure to 53 pesticide active ingredients in PD risk and identified their relevant co-exposure profiles. Second, to identify which of these pesticides might contribute to PD through direct effects on dopaminergic neurons, we employed a live-cell imaging screening paradigm in which neurons, definitively identified with a tyrosine hydroxylase reporter, were exposed to 43 of the high-risk pesticides. Using detailed morphometric measures, we found 10 pesticides were directly toxic to these neurons. Further, we analyzed pesticides typically used in combinations in cotton farming. Among these "cotton cluster" pesticides, co-exposures resulted in markedly greater toxicity than any single pesticide. Trifluralin was a pivotal driver of toxicity to dopaminergic neurons and led to marked mitochondrial dysfunction. Our field-to-bench paradigm may prove useful to mechanistically dissect pesticide exposure implicated in PD risk, and guide agricultural policy in the future.

neuroscience↗

Mechanistic model-driven exometabolomic characterisation of human dopaminergic neuronal metabolism

Starting with a comprehensive generic reconstruction of human metabolism, we generated high-quality, constraint-based, genome-scale, cell-type and condition specific models of metabolism in human dopaminergic neurons, the cell type most vulnerable to degeneration in Parkinsons disease. They are a synthesis of extensive manual curation of the biochemical literature on neuronal metabolism, together with novel, quantitative, transcriptomic and targeted exometabolomic data from human stem cell-derived, midbrainspecific, dopaminergic neurons in vitro. Thermodynamic constraint-based modelling enabled qualitatively accurate and moderately quantitatively accurate prediction of dopaminergic neuronal metabolite exchange fluxes, including predicting the consequences of metabolic perturbations in a manner also consistent with literature on monogenic mitochondrial Parkinsons disease. These dopaminergic neurons models provide a foundation for a quantitative systems biochemistry approach to metabolic dysfunction in Parkinsons disease. Moreover, the plethora of novel mathematical and computational approaches required to develop them are generalisable to study any other disease associated with metabolic dysfunction.

systems biology↗