Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Metabolic zonation and characterization of tissue slices with spatial transcriptomics

View through CrossRef
Abstract The exchanges of small molecules between cells and their environments are essential for the formation of functioning tissues. To study them at scale, we developed Harreman (Basque for “receive and give”), an algorithm for identifying metabolic crosstalk from spatially resolved transcriptomics of intact tissues. Unlike previous methods, which primarily focus on the secretion or reception of protein signals, Harreman reconstructs molecular metabolic crosstalk based on the co-localized expression of metabolite transporters. By utilizing a series of increasingly detailed models for testing spatial correlation, Harreman provides insight at multiple levels: a) coarse partition of the tissue into regions sharing metabolic characteristics; b) identification of metabolic exchanges within each region; and c) inference of the cell subsets involved in those exchanges. Harreman identified a sodium/calcium exchange at the tumor boundary in human lung metastases of human renal cancers, and associated it with nearby pro-inflammatory macrophages. In the mouse model of DSS-induced colitis, Harreman identified vitamin A and lysophosphatidylcholine transport at the interface of the epithelial monolayer as major signals associated with regeneration. Harreman is available at https://github.com/YosefLab/Harreman .
Title: Metabolic zonation and characterization of tissue slices with spatial transcriptomics
Description:
Abstract The exchanges of small molecules between cells and their environments are essential for the formation of functioning tissues.
To study them at scale, we developed Harreman (Basque for “receive and give”), an algorithm for identifying metabolic crosstalk from spatially resolved transcriptomics of intact tissues.
Unlike previous methods, which primarily focus on the secretion or reception of protein signals, Harreman reconstructs molecular metabolic crosstalk based on the co-localized expression of metabolite transporters.
By utilizing a series of increasingly detailed models for testing spatial correlation, Harreman provides insight at multiple levels: a) coarse partition of the tissue into regions sharing metabolic characteristics; b) identification of metabolic exchanges within each region; and c) inference of the cell subsets involved in those exchanges.
Harreman identified a sodium/calcium exchange at the tumor boundary in human lung metastases of human renal cancers, and associated it with nearby pro-inflammatory macrophages.
In the mouse model of DSS-induced colitis, Harreman identified vitamin A and lysophosphatidylcholine transport at the interface of the epithelial monolayer as major signals associated with regeneration.
Harreman is available at https://github.
com/YosefLab/Harreman .

Related Results

Baclofen and phaclofen modulate GABA release from slices of rat cerebral cortex and spinal cord but not from retina
Baclofen and phaclofen modulate GABA release from slices of rat cerebral cortex and spinal cord but not from retina
The effects of (−)‐baclofen, muscimol and phaclofen on endogeneous γ‐aminobutyric acid (GABA) release from rat cortical slices, spinal cord slices and entire retinas were studied.T...
Resource allocation and management techniques for network slicing in WiFi networks
Resource allocation and management techniques for network slicing in WiFi networks
Network slicing has recently been proposed as one of the main enablers for 5G networks; it is bound to cope with the increasing and heterogeneous performance requirements of these ...
SUMMARY
SUMMARY
SUMMARYThe purpose of the present monograph is to give an account of the distribution of fibrinolytic components in the organism, with special reference to the tissue activator of ...
SpaBatch: Deep Learning‐Based Cross‐Slice Integration and 3D Spatial Domain Identification in Spatial Transcriptomics
SpaBatch: Deep Learning‐Based Cross‐Slice Integration and 3D Spatial Domain Identification in Spatial Transcriptomics
AbstractWith the rapid accumulation of spatial transcriptomics (ST) data across diverse tissues, individuals, and technological platforms, there is an urgent need for a robust and ...
3D reconstruction of spatial transcriptomics with spatial pattern enhanced graph convolutional neural network
3D reconstruction of spatial transcriptomics with spatial pattern enhanced graph convolutional neural network
ABSTRACT Spatially resolved transcriptomics (SRT) is a promising new technology that enables simultaneous analysis of gene expression and spatial information for bi...
Spatial transcriptomics in autoimmune rheumatic disease: potential clinical applications and perspectives
Spatial transcriptomics in autoimmune rheumatic disease: potential clinical applications and perspectives
Abstract Spatial transcriptomics is a cutting-edge technology that analyzes gene expression at the cellular level within tissues while integrating spatial location inform...
Spatial sorting enables comprehensive characterization of liver zonation
Spatial sorting enables comprehensive characterization of liver zonation
Abstract The mammalian liver is composed of repeating hexagonal units termed lobules. Spatially-resolved single-cell transcriptomics revealed that about half of hep...

Back to Top