MIT scientists have developed a multi-scale imaging technique that allows them to examine brain tissue at close subcellular detail, as well as in terms of the long-range connectivity of neurons. The technique could improve the accuracy of efforts to map the connections within the human brain. The technique could also be used to aid in studies of other organs such as the heart, lungs, liver, and kidneys.
Called magnified analysis of proteome (MAP), the new technique (reversibly) expands tissue samples by flooding them with acrylamide – a colorless gel-like substance. Like a previous technique called CLARITY, which was also developed by senior author Kwanghun Chung, this process preserves the proteins inside the cells (collectively known as the proteome) while also making them transparent so that they can be labeled with fluorescent molecules.
Unlike CLARITY, however, the MAP method expands tissue samples to four or five times their original size. This allows the scientists to conduct more fine-grained imaging. They can reach resolutions as great as 60 nanometers, which is much better than the 200 to 250 nanometer resolution limit normally attainable by light microscopes – though it's not quite a match for an imaging tool developed last year by Boston and Harvard University scientists, which can see individual synaptic vesicles (tiny spheres less than 40 nm across that hold chemical signals called neurotransmitters).
MAP's 60 nm resolution is fine enough to identify neuronal structures such as axons and synapses, and because the treated sample retains its structural integrity the researchers can also use molecular markers like antibodies to visualize different neuron types as well as the connections between them.
The takeaway here is that with this new MAP technique scientists can image the same brain tissue sample at multiple scales, ranging from regional connectivity (neural networks and signaling pathways) to subcellular architecture (synapses, axons, dendrites) and molecular identity (proteins, neuron types).
That could be very helpful in ongoing efforts to map the connections of the human brain, though as before the greatest challenge is not in gathering the data but in analyzing and ultimately understanding it.
A paper describing the study was published in the journal Nature Biotechnology.
Source: MIT