In a Nature Methods perspective, NOMIS researcher Ali Ertürk addresses the new era of 3D-omics by tissue clearing and AI, called deep 3D histology. He writes that “biomedical research needs to evolve beyond the analysis of structural and molecular biology in selected tissue sections, expanding its focus to entire organs and organisms.” Ertürk is leading the NOMIS Human Heart Atlas project.
Abstract
To comprehensively understand tissue and organism physiology and pathophysiology, it is essential to create complete three-dimensional (3D) cellular maps. These maps require structural data, such as the 3D configuration and positioning of tissues and cells, and molecular data on the constitution of each cell, spanning from the DNA sequence to protein expression. While single-cell transcriptomics is illuminating the cellular and molecular diversity across species and tissues, the 3D spatial context of these molecular data is often overlooked. Here, I discuss emerging 3D tissue histology techniques that add the missing third spatial dimension to biomedical research. Through innovations in tissue-clearing chemistry, labeling and volumetric imaging that enhance 3D reconstructions and their synergy with molecular techniques, these technologies will provide detailed blueprints of entire organs or organisms at the cellular level. Machine learning, especially deep learning, will be essential for extracting meaningful insights from the vast data. Further development of integrated structural, molecular and computational methods will unlock the full potential of next-generation 3D histology.
Read the Nature Methods publication: Deep 3D histology powered by tissue clearing, omics and AI
Feature image: Whole-body atlas of the nervous system of a mouse: The whole mouse was stained with an antibody specific for peripheral nerves and imaged after “tissue clearing” using light sheet fluorescence microscopy. The different colors represent different depths in the 3D image. (Photo © Helmholtz Munich)
