Scientists Grow Functional 3D Human Neural Network from Stem Cells

  • New 3D model of human brain tissue can accurately mimic brain’s functional and structural features. 
  • It allows scientists to measure cellular properties, and visualize behavior and growth of individual cells in the brain. 

With billions of neurons connected by trillions of synapses, human brain is one of the most complex things in nature. The interconnections of neurons release chemical messengers called neurotransmitters (that transfer, amplify and modulate signals between neurons and other cells) in response to nerve impulses.

Although scientists around the world are constantly trying to map brain’s function and capabilities, they haven’t been able to obtain the single-cell level of resolution, even by using multiple techniques (like fMRI and EEG) together. A few of their recent works involving the use of CRISPR, for instance, have received both praise and criticism.

Now, researchers from Tufts University have developed a working three dimensional model of human brain tissue. It can mimic brain’s functional as well as structural features and show neural activities sustained over a longer period of time (in months). This model will enable researchers to explore intersections between cells and analyze diseases, including Parkinson’s and Alzheimer’s disease, and their response to treatment.

Using Induced Pluripotent Stem Cells

The new 3D brain tissue model uses human iPSCs (short for Induced pluripotent stem cells) which are mostly obtained from the patient skin. In the past, neurological tissues were hardly extracted from healthy patients, limiting the availability of human neuronal cell sources. That’s not the case anymore.

The recent advancements in reprogramming somatic cells into iPSCs have reduced the problem of human source neurons. These pluripotent cells can now be significantly expanded, and under suitable conditions, they can be directed to distinguish into certain types of cells, including neurons and astrocytes that support the expanding neural networks.

Researchers discovered that silk-collagen scaffolds offer the perfect environment to create cells with similar electrical signaling and genetic signatures found in native neural tissues.

Reference: ACS Publications | doi:10.1021/acsbiomaterials.8b00622 | Tufts University 

Advantages Over Other Models

The 3D matrix outputs a more comprehensive mix of cells than 2D clustering cells. It provides more accurate expression and morphology of neurotransmitters and receptors.

Although other methods also use iPSCs to generate 3D miniaturized versions of brain tissues for understanding functions and growth of the brain, they cannot effectively map the process of each cell in real-time.

3D Human Neural Network3D brain tissue with neurons (green) collagen and astrocytes (red)

It’s very difficult to provide enough nutrients or oxygen in the central cells of these miniaturized versions, which limits their ability to operate in a native state. However, the permeable structure of the new 3D brain tissue model provides enough nutrients and oxygenation. The center of each three-dimensional matrix has a clear window that allows scientists to measure cellular properties, and visualize behavior and growth of individual cells.

It doesn’t matter whether the cells were extracted from healthy people or patients with Parkinson’s or Alzheimer’s diseases, the 3D tissue model showed a consistent and sustainable growth in both cases. This gives researchers a reliable system to analyze several disease conditions and observe how cells change over a long period of time.

Read: The First Brain-to-Brain Interface Lets 3 People Share Thoughts Directly To Each Other’s Head

The authors plan to build a more comprehensive brain model that can map complex interactions involved in plasticity, learning, and degeneration. To do this, they will exploit the 3D tissue model with modern imaging technologies, and the addition of different types of cells like endothelial and microglial cells.

Written by
Varun Kumar

Varun Kumar is a professional science and technology journalist and a big fan of AI, machines, and space exploration. He received a Master's degree in computer science from Indraprastha University. To find out about his latest projects, feel free to directly email him at [email protected] 

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