Mixing brain cells and nanodots

A team of Israeli researchers has grown self-organizing networks of rat brain cells by binding them to carbon nanotubes. And these neural networks are remarkably stable, surviving for almost three months in the lab. These hybrid networks could be used in future biological sensors by identify poisons for example.

It's not the first time that animal brain cells have been used in conjunction with nanoparticles. But now, a team of Israeli researchers has grown self-organizing networks of rat brain cells by binding them to carbon nanotubes. In a short article, New Scientist reports that these neural networks are remarkably stable, surviving for almost three months in the lab. These hybrid networks could be used in future biological sensors. For example, they could identify a poison by measuring its effect on such a network of brain cells. But read more...

Here is a short description of what did the team led by Yael Hanein of Tel Aviv University.

[[The team] used 100-micrometre-wide bundles of nanotubes to coax rat neurons into forming regular patterns on a sheet of quartz. The neurons cannot stick to the quartz surface but do bind to the nanotube dots, in clusters of about between 20 and 100. Once attached, these neuron bundles are just the right distance from one another to stretch out projections called axons and dendrites to make links with other clusters nearby.

As an example of such clustering, below are some pictures showing the dynamic evolution of "a network self-organization process on 100 µm patterned carbon nanotubes (CNT) islands, with 150 µm separation between the islands. The arrows indicate the process bundle interconnecting the two separating clusters. The sample was placed in the environmental chamber under the microscope immediately after plating. (A) 30 h after plating, (B) 40 h after plating, (C) 55 h after plating and (D) 69 h after plating. The final compact connectivity between the two isolated islands is depicted in (E)." (Credit for image and caption: Yael Hanein, Tel Aviv University).

Evolution of a self-organizing network

It is important to note that the longevity of these hybrid networks is quite exceptional.

Existing methods for growing networks of neurons cannot produce such neat patterns and clean links between cells. This is because neurons are normally deposited on surfaces that do not prevent them from growing out of ordered clusters onto projections, which makes for a messier network.
The process makes it possible to create more uniform neural networks, Hanein says. In experiments they last longer than other artificial networks, surviving for up to 11 weeks. This could be crucial for building biosensors using the cells, she claims.

If you want to learn more about this process, the research work has been published by the Journal of Neural Engineering under the title "Compact self-wiring in cultured neural networks" (Volume 3, Number 2, Pages 95-101, June 2006). Here are two links to the abstract and the full paper (PDF format, 7 pages, 778 KB). Below is the beginning of the conclusion of this paper from which the above illustration has been extracted.

The results presented here demonstrate a simple and reliable method to form engineered networks consisting of well-ordered interconnected neuronal clusters. The cluster-to-cluster connectivity is made of neuronal processes alone. The resulting patterning is very stable and can be maintained for many weeks. The method is consistent with the formation of networks made of large cell populations.

And for more information about other works from Yael Hanein, you can check her research activity and a list of her publications.

In particular, you should read a paper published by Physica A, "Engineered self-organization of neural networks using carbon nanotube clusters" (Volume 350, Issues 2-4, Pages 611-621, May 15, 2005). Here are the links to the abstract and to the full paper (PDF format, 11 pages, 473 KB)

So will we use in the future hybrid biosensors made of animal brain cells and carbon nanotubes? The answer is probably yes.

Sources: Tom Simonite, New Scientist, June 22, 2006; and various web sites

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