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CODA: quantitative 3D reconstruction of large tissues at cellular resolution

Authors :
Kiemen, Ashley L.
Braxton, Alicia M.
Grahn, Mia P.
Han, Kyu Sang
Babu, Jaanvi Mahesh
Reichel, Rebecca
Jiang, Ann C.
Kim, Bridgette
Hsu, Jocelyn
Amoa, Falone
Reddy, Sashank
Hong, Seung-Mo
Cornish, Toby C.
Thompson, Elizabeth D.
Huang, Peng
Wood, Laura D.
Hruban, Ralph H.
Wirtz, Denis
Wu, Pei-Hsun
Source :
Nature Methods; November 2022, Vol. 19 Issue: 11 p1490-1499, 10p
Publication Year :
2022

Abstract

A central challenge in biology is obtaining high-content, high-resolution information while analyzing tissue samples at volumes relevant to disease progression. We address this here with CODA, a method to reconstruct exceptionally large (up to multicentimeter cubed) tissues at subcellular resolution using serially sectioned hematoxylin and eosin-stained tissue sections. Here we demonstrate CODA’s ability to reconstruct three-dimensional (3D) distinct microanatomical structures in pancreas, skin, lung and liver tissues. CODA allows creation of readily quantifiable tissue volumes amenable to biological research. As a testbed, we assess the microanatomy of the human pancreas during tumorigenesis within the branching pancreatic ductal system, labeling ten distinct structures to examine heterogeneity and structural transformation during neoplastic progression. We show that pancreatic precancerous lesions develop into distinct 3D morphological phenotypes and that pancreatic cancer tends to spread far from the bulk tumor along collagen fibers that are highly aligned to the 3D curves of ductal, lobular, vascular and neural structures. Thus, CODA establishes a means to transform broadly the structural study of human diseases through exploration of exhaustively labeled 3D microarchitecture.

Details

Language :
English
ISSN :
15487091 and 15487105
Volume :
19
Issue :
11
Database :
Supplemental Index
Journal :
Nature Methods
Publication Type :
Periodical
Accession number :
ejs61047882
Full Text :
https://doi.org/10.1038/s41592-022-01650-9