Quantitative spatial connectomics of liver reveals a partially exposed sympathetic network that integrates multiple cell types across the portal tract
Year: 2026
Type: preprint
Abstract: Summary Peripheral tissues are innervated by sparse axonal networks that regulate homeostasis, regeneration and disease, yet their three-dimensional architecture and cellular targets remain largely unknown. Here, we present an EM workflow for quantitative 3D spatial connectomics to define these networks. We identify the mouse liver connectome as a meshwork, rather than a tree-like structure, of mainly sympathetic axons, in which partial Schwann cell coverage is associated with exposed varicosities along the length of individual axons with large regions of the network devoid of glial coverage. Axon tracing identified axonal terminals throughout the network, but the vast majority of cellular contacts involved exposed “en passant” varicosities. While both terminals and varicosities innervated the vasculature, most synaptic-like contacts involved hepatocytes, fibroblasts, macrophages, and the stem-cell niche, with all individual axons contacting different cell types along their length, highlighting the network nature of liver innervation, the potential for co-ordinating tissue function and demonstrating the power of this approach for decoding connectivity in peripheral tissues.
Authors: Luke A. Noon, Giulia Casal, Mario Soriano-Navarro, Anne-Laure Cattin, Rafael Camacho, Carlos Acosta Umanzor, Carmen Rojo Sanz, Arantxa Leal Tassias, Julia Fernandez-Rodriguez, Elisabeth Verboven, Jose Antonio Gomez Sanchez, Marousa Darsinou, Alex Power, Antonella Riccio, Emma R. Andersson, Jemima J. Burden, Alison C. Lloyd
Institutions: Centro de Investigacion Principe Felipe, MRC Laboratory for Molecular Cell Biology, University College London, University of Gothenburg, Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas, Karolinska Institutet, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL)
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7224829495
