PUBLICATION
High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology
- Authors
- Lin, X., Duan, X., Jacobs, C., Ullmann, J., Chan, C.Y., Chen, S., Cheng, S.H., Zhao, W.N., Poduri, A., Wang, X., Haggarty, S.J., Shi, P.
- ID
- ZDB-PUB-181205-3
- Date
- 2018
- Source
- Nature communications 9: 5142 (Journal)
- Registered Authors
- Cheng, Shuk Han, Ullmann, Jeremy
- Keywords
- none
- MeSH Terms
-
- Animals
- Animals, Genetically Modified
- Brain/drug effects*
- Brain/pathology
- Brain/physiopathology
- Brain Mapping/methods*
- Convulsants/chemistry
- Convulsants/pharmacology
- Disease Models, Animal
- Drug Evaluation, Preclinical/methods
- Larva/drug effects
- Larva/physiology
- Machine Learning*
- Molecular Structure
- Neuropharmacology/methods*
- Pentylenetetrazole/chemistry
- Pentylenetetrazole/pharmacology
- Seizures/drug therapy
- Seizures/physiopathology
- Zebrafish
- PubMed
- 30510233 Full text @ Nat. Commun.
Citation
Lin, X., Duan, X., Jacobs, C., Ullmann, J., Chan, C.Y., Chen, S., Cheng, S.H., Zhao, W.N., Poduri, A., Wang, X., Haggarty, S.J., Shi, P. (2018) High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology. Nature communications. 9:5142.
Abstract
Technologies for mapping the spatial and temporal patterns of neural activity have advanced our understanding of brain function in both health and disease. An important application of these technologies is the discovery of next-generation neurotherapeutics for neurological and psychiatric disorders. Here, we describe an in vivo drug screening strategy that combines high-throughput technology to generate large-scale brain activity maps (BAMs) with machine learning for predictive analysis. This platform enables evaluation of compounds' mechanisms of action and potential therapeutic uses based on information-rich BAMs derived from drug-treated zebrafish larvae. From a screen of clinically used drugs, we found intrinsically coherent drug clusters that are associated with known therapeutic categories. Using BAM-based clusters as a functional classifier, we identify anti-seizure-like drug leads from non-clinical compounds and validate their therapeutic effects in the pentylenetetrazole zebrafish seizure model. Collectively, this study provides a framework to advance the field of systems neuropharmacology.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping