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Combining Machine Learning and Multiplexed, In Situ Profiling to Engineer Cell Type and Behavioral Specificity.

Michael J Leone1,2, Robert van de Weerd1,3, Ashley R Brown1,3

  • 1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, United States.

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Summary
This summary is machine-generated.

We developed ESCargoT, a platform using machine learning and multiplexed screening to discover enhancers for precise neural circuit control, successfully targeting pain and itch pathways in mice.

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Area of Science:

  • Neuroscience
  • Genetics
  • Bioengineering

Background:

  • Precise control of neural circuits is crucial for understanding and treating neurological disorders.
  • Discovering cell-specific enhancers for gene expression is challenging due to low in vivo success rates and species-specific activity.
  • Current methods lack spatial detail and struggle with multiplexing viral vectors like adeno-associated viruses (AAVs).

Purpose of the Study:

  • To accelerate the discovery of cell-targeting enhancers for the dorsal spinal cord, a key region for pain and itch processing.
  • To develop an integrated platform combining machine learning, modular AAV assembly, and in situ screening for enhancer discovery.
  • To enable spatially resolved, multiplexed in vivo screening of enhancers.

Main Methods:

  • Developed ESCargoT (Engineered Specificity of Cargo Transcription), an end-to-end platform for enhancer discovery.
  • Utilized cross-species chromatin accessibility data to train machine learning models for predicting enhancer activity in specific cell types.
  • Created a Spatial Parallel Reporter Assay (SPRA) integrating Golden-Gate assembly with multiplexed in situ screening for parallel profiling of an enhancer-AAV library.

Main Results:

  • Successfully identified and validated enhancers targeting excitatory dorsal horn neurons, leading to the reversal of mechanical allodynia.
  • Demonstrated the ability to screen a library of 27 enhancers simultaneously in vivo, targeting diverse cell types including oligodendrocytes and dorsal horn neuron subtypes.
  • Validated enhancers targeting Exc-LMO3 and Exc-SKOR2 neurons, with one shown to block chemical itch sensation.
  • Showcased cross-species applicability, with macaque-derived enhancers functional in mice.

Conclusions:

  • The ESCargoT platform significantly accelerates the discovery of cell-specific enhancers for neural circuit manipulation.
  • Spatially resolved, multiplexed in vivo screening is effective for identifying functional enhancers.
  • This approach facilitates the development of novel cell-targeting tools and gene therapies for pain and itch disorders.