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Protocol for the Differentiation of Human Induced Pluripotent Stem Cells into Mixed Cultures of Neurons and Glia for Neurotoxicity Testing
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Evaluation of 6-Hydroxydopamine and Rotenone In Vitro Neurotoxicity on Differentiated SH-SY5Y Cells Using Applied
Rui F Simões1,2, Paulo J Oliveira1, Teresa Cunha-Oliveira1
1CNC-Center for Neuroscience and Cell Biology, CIBB-Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004-504 Coimbra, Portugal.
Abstract:
With the increase in life expectancy and consequent aging of the world's population, the prevalence of many neurodegenerative diseases is increasing, without concomitant improvement in diagnostics and therapeutics. These diseases share neuropathological hallmarks, including mitochondrial dysfunction. In fact, as mitochondrial alterations appear prior to neuronal cell death at an early phase of a disease's onset, the study and modulation of mitochondrial alterations have emerged as promising strategies to predict and prevent neurotoxicity and neuronal cell death before the onset of cell viability alterations. In this work, differentiated SH-SY5Y cells were treated with the mitochondrial-targeted neurotoxicants 6-hydroxydopamine and rotenone. These compounds were used at different concentrations and for different time points to understand the similarities and differences in their mechanisms of action. To accomplish this, data on mitochondrial parameters were acquired and analyzed using unsupervised (hierarchical clustering) and supervised (decision tree) machine learning methods. Both biochemical and computational analyses resulted in an evident distinction between the neurotoxic effects of 6-hydroxydopamine and rotenone, specifically for the highest concentrations of both compounds.
Insights
Machine learning distinguished neurotoxic effects of 6-hydroxydopamine and rotenone on mitochondria. This approach aids in early prediction and prevention of neurotoxicity in aging populations.
Area of Science:
- Neuroscience
- Biochemistry
- Computational Biology
Background:
- Aging populations face rising neurodegenerative diseases with limited diagnostics and therapeutics.
- Mitochondrial dysfunction is a shared hallmark, appearing early and preceding neuronal death.
- Studying mitochondrial alterations offers potential for early neurotoxicity prediction and prevention.
Purpose of the Study:
- To investigate and differentiate the mechanisms of action of two mitochondrial neurotoxicants, 6-hydroxydopamine and rotenone.
- To explore the utility of machine learning in analyzing mitochondrial parameters for neurotoxicity assessment.
- To identify early markers of neurotoxicity in differentiated SH-SY5Y cells.
Main Methods:
- Differentiated SH-SY5Y cells were treated with 6-hydroxydopamine and rotenone at varying concentrations and time points.
- Mitochondrial parameters were measured and analyzed using biochemical assays.
- Unsupervised (hierarchical clustering) and supervised (decision tree) machine learning algorithms were applied to the data.
Main Results:
- Biochemical and computational analyses revealed distinct neurotoxic effects between 6-hydroxydopamine and rotenone.
- Machine learning methods successfully differentiated the impact of the two compounds, particularly at higher concentrations.
- Early-stage mitochondrial alterations were effectively characterized.
Conclusions:
- Machine learning provides a powerful tool for distinguishing the effects of different neurotoxicants on mitochondrial function.
- This approach can aid in the early detection and understanding of neurodegenerative disease mechanisms.
- Identifying distinct toxicological profiles is crucial for developing targeted therapeutic strategies.
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