Abstract

Brain function only makes sense in the context of the surrounding tissue. Unfortunately, the additional context adds several orders of magnitude more data. This issue is becoming addressable with tissue clearing, which allows 3D imaging of entire mouse bodies with cellular precision.

The big promise of tissue clearing is that it adds an unbiased, whole-organ, three-dimensional perspective to an anatomical analysis. It is especially well suited to study cell distributions (e.g. reactive microglia) or long, continuous structures (e.g. nerve bundles). However, until recently this meant a tradeoff in cell diversity that could be labelled in the same brain, typically a single round of max. two immunolabels.

The lab of our main speaker, Hei Ming Lai, has pioneered a way around this issue with their INSIHGT protocol. By using superchaotropes to precisely control antibody binding, INSIHGT allows multiplexed staining with up to 28 antibodies in the same tissue.

The next bottleneck is the amount of imaging data. Our next speaker and chairperson, Moritz Negwer, presents DELiVR, a computational analysis pipeline that uses VR to generate training data for a deep learning network.
However, viewing just the brain is missing most of the context - i.e. the rest of the body.

Our final speaker, Doris Kaltenecker, presents a detailed study tracing sensory axons throughout the (cleared) mouse body, and found a evidence of a body-wide diabetic neuropathy phenotype.

When combined, those innovations should enable a more context-aware view of brain function - either with much richer labeling (more cell types), and a larger spatial extent (whole-body nerve tracing). This should be relevant to an audience interested in systems neuroscience, neuroanatomy and cellular neuroscience.