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

Ashley L. Kiemen, Alicia M. Braxton, Mia P. Grahn, Kyu Sang Han, Jaanvi Mahesh Babu, Rebecca Reichel, Ann C. Jiang, Bridgette Kim, Jocelyn Hsu, Falone Amoa, Sashank Reddy, Seung Mo Hong, Toby C. Cornish, Elizabeth D. Thompson, Peng Huang, Laura D. Wood, Ralph H. Hruban, Denis Wirtz, Pei Hsun Wu

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)1490-1499
Number of pages10
JournalNature Methods
Volume19
Issue number11
DOIs
StatePublished - Nov 2022

ASJC Scopus subject areas

  • Molecular Biology
  • Biochemistry
  • Biotechnology
  • Cell Biology

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