Debarati Basu, Makaut (WB)
Human-induced pluripotent stem cells (hiPSC) obtained from neurons are mainly used by micro-electrode arrays (MEAs). Although they are becoming popular MEA recordings obtained from hiPSC derived neuronal networks are not utilized fully. They are not utilized fully in various aspects such as experimental design, execution, and data analysis. The study is carried on ten healthy persons with comparable phenotypic networks to standardize the healthiness of MEA-derived neuronal activity. For full utilization, recommendations are made on experimental design and analysis. As a result, MEAs can be utilized as a dependable platform for differentiating (disease-specific) phenotypic networks. The study further shows that MEAs are a supreme and robust tool to expose functional phenotypic networks from hiPSC-derived neuronal networks. They are also an important resource for advancing the hiPSC field regarding the utilization of MEAs for disease phenotyping and drug discovery.
Micro-electrode arrays (MEAs)
An important tool for studying complicated communication of healthy and diseased neuronal circuits is In vitro neuronal models. The prospect of measuring and manipulating the electrical activity by neuronal populations offers the idea of neuronal network development and organization. The cell cultures which are embedded into micro-electrodes and provide the non-invasive measurement of activities of the neuronal network are known as Micro-electrode arrays (MEAs). MEAs are utilized mainly for the measurement of activities from different ranges of neuronal culture systems. Some of the examples are that of primary cells, brain slices, or intact retinas that are mainly obtained from rodents.
The development in human induced pluripotent stem (hiPSC) technology made the differentiation of human neurons obtained from somatic cells possible. It further allows the phenotype of human neuronal networks. Human-induced pluripotent stem (hiPSC) -derived networks of neurons on MEA imitate the design of activities of neuronal networks of rodents. It includes a secure state of co-occurring network bursting which suggests the successful development of functional neuronal networks. Further improvements in the software of MEA analysis lead to simplification of extraction parameters which explain the pattern of neuronal activity. The popularity of MEA technology for studying neuronal network phenotypes is due to the developments in both human neuronal culturing systems and MEA analysis software.
Limitations of MEA technology
Although MEA technology is becoming popular it is not always used fully for investigating the hiPSC-derived neuronal network. The hiPSc.-derived neuronal networks are not standardized as the rodent neuronal cultures. It is not clear the factors that cause a change in cell culture conditions and influence batch-to-batch consistency. It is also not determined hiPSC-derived neuronal networks obtained from different lines can be compared or not.
All of this is caused due to absence of standardization. For determining a disease phenotype, it is advisable to utilize many hiPSC-derived neuronal lines or isogenic sets. It is mainly because there is a variation in genetic background between hipSc donors that influence the variance at the transcriptional level. There is only a little knowledge about the cell lines amount that is required for distinguishing phenotype on MEAs. It is also not known about the results of genetic background on hipSC-derived neuronal network function. Although extracting MEA parameters are simple, but analysis of data is difficult along with the experimental design. There is no proper explanation for complex network characteristics. So, there is a need for improving the standard quality.
Recommendations for improving MEA Technology
For improving the design, and analysis, and interpretation of MEA technology the following recommendations should be followed. The first point is a meta-analysis is performed on MEA recordings obtained from excitatory neuronal networks. The second point is that one should use hiPSc obtained from controls (ten healthy subjects) cultured for years by various researchers. It is shown that various control neuronal networks that are cultured on MEAs are greatly similar. They also provide strong parameters of MEA for describing neuronal activity and organization. Lastly one should use genetic aberrations that affected neuronal networks that cause Kleefstra syndrome (KS) or mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MEALS). Thus, we can say that MEA is an important platform tool for identifying genotypic-phenotypic correlations.
Results
Neurons are derived from healthy subjects. The study shows a similar phenotype on MEA. The control lines were obtained from biopsies of fibroblast skin which are obtained from ten healthy persons. The study includes ten healthy persons five of them are males and the remaining five are females. They have a mean age of 33.5yeas and a total of 17 parameters are taken into consideration for describing neuronal network activity and connectivity. A graph was plotted which showed the range in which all ten control lines MEA parameters behave. The mean was ±95%, and the values are calculated by first taking average per control line and then taking an average across all the control lines. The Coefficient of variation percentage explains the sturdiness of the MEA parameters respectively across all the ten control lines.
Conclusion
A meta-analysis was performed, and the largest dataset was obtained from hiPSC-derived from the Ngn2-induced network of neurons on MEA. It was mainly used for describing standardized control network signatures. It has been discovered that a network of neurons obtained from ten healthy individuals were collected together in PCA. The collection is done by various researchers for several years and not depending on age and sex at the biopsy of fibroblast.
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References:
- Mossink, B., Verboven, A. H. A., van Hugte, E. J. H., Klein Gunnewiek, T. M., Parodi, G., Linda, K., Schoenmaker, C., Kleefstra, T., Kozicz, T., van Bokhoven, H., Schubert, D., Nadif Kasri, N., & Frega, M. (2021). Human neuronal networks on micro-electrode arrays are a highly robust tool to study disease-specific genotype-phenotype correlations in vitro. Stem Cell Reports, S221367112100326X. https://doi.org/10.1016/j.stemcr.2021.07.001
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