Scientists from the Eric Betzig lab at Howard Hughes Medical Institute’s Janelia Campus and the Ed Boyden Lab at Massachusetts Institute of Technology (MIT) collaborated to develop an imaging technique, ExLLSM, that combines expansion microscopy (ExM) with lattice light-sheet microscopy (LLSM) for nanoscale imaging of fly and mouse neuronal circuits at the molecular level. ExLLSM images neural structures with molecular contrast over millimeter-scale volumes, including (clockwise from top right) mouse pyramidal neurons and their processes; organelle morphologies in somata; dendritic spines and synaptic proteins across the cortex; stereotypy of projection neuron boutons in Drosophila; projection neurons traced to the central complex; and (center) dopaminergic neurons across the brain, including the ellipsoid body (circular inset). Courtesy of Gao et al./ Science 2019. Expansion microscopy, invented by the Boyden group, uses a chemical technique to make small specimens bigger so scientists can more easily see molecular details. To image vastly larger portions of brain tissue, however, the Boyden group needed a microscope that was both high-speed, high-resolution, and gentle on samples. In addition to being challenging to illuminate, expanding a sample just fourfold increases its volume 64-fold, so imaging speed becomes paramount, said Boyden team researcher Ruixuan Gao. “We needed something that was fast and didn’t have much photobleaching, and we knew there was a fantastic microscope at Janelia.” Janelia’s lattice light-sheet microscope (LLSM) sweeps an ultrathin sheet of light through a specimen, illuminating only the part in the microscope’s plane of focus. Out-of-focus areas stay dark, keeping the specimen’s fluorescence from being extinguished. After expanding the fruit fly brain to four times its usual size, scientists used lattice light-sheet microscopy to image all of the dopaminergic neurons (green). Courtesy of Gao et al./Science 2019. By combining ExM and LLSM, the researchers could rapidly image large portions of brain tissue at high resolution. Janelia researchers provided high-quality Drosophila brain specimens. MIT researchers collected some 50,000 cubes of data across each brain, which were computationally stitched together to form a 3D phantom specimen. Two hundred terabytes of data were combined to create movies to showcase the brain’s intricacies in detail. A forest of dendritic spines protrude from the branches of neurons in the mouse cortex. Courtesy of Gao et al./ Science 2019. The researchers investigated more than 1500 dendritic spines, imaged fatty sheaths that insulate mouse nerve cells, highlighted all of the dopaminergic neurons, and counted all the synapses across the entire fly brain. They were able to image in 3D with minimal photobleaching at speeds sufficient to image the entire Drosophila brain or across the width of the mouse cortex in just two to three days, with multiple markers at an effective resolution of about 60 by 60 by 90 nm for four times expansion. ExM and LLSM complement each other, said the researchers. “The result is that we get crystal-clear images at blazingly fast speeds over very large volumes compared to earlier microscopy techniques,” Boyden said. However, as with any kind of superresolution fluorescence microscopy, it can be challenging to make proteins fluorescent enough to be seen clearly at high resolution, said Betzig, who is now an HHMI investigator at the University of California, Berkeley. And since expansion microscopy requires many processing steps, there’s still the potential for artifacts to be introduced. Because of this, Betzig said, “We worked very hard to validate what we’ve done, and others would be well advised to do the same.” Now, Gao and the Janelia team are building a new lattice light-sheet microscope, which they plan to move to Boyden’s lab at MIT. “Our hope is to rapidly make maps of entire nervous systems,” Boyden said. Making detailed maps of the brain would require charting its activity and wiring — in humans, the thousands of connections made by each of more than 80 billion neurons. Such maps could help scientists spot where brain disease begins, build better artificial intelligence, or even explain behavior. The research was published in Science (http://dx.doi.org/10.1126/science.aau8302).