TY - JOUR

T1 - CellNeighborEX

T2 - deciphering neighbor-dependent gene expression from spatial transcriptomics data

AU - Kim, Hyobin

AU - Kumar, Amit

AU - Lövkvist, Cecilia

AU - Palma, António M.

AU - Martin, Patrick

AU - Kim, Junil

AU - Bhoopathi, Praveen

AU - Trevino, Jose

AU - Fisher, Paul

AU - Madan, Esha

AU - Gogna, Rajan

AU - Won, Kyoung Jae

N1 - Publisher Copyright: © 2023 The Authors. Published under the terms of the CC BY 4.0 license.

PY - 2023

Y1 - 2023

N2 - Cells have evolved their communication methods to sense their microenvironments and send biological signals. In addition to communication using ligands and receptors, cells use diverse channels including gap junctions to communicate with their immediate neighbors. Current approaches, however, cannot effectively capture the influence of various microenvironments. Here, we propose a novel approach to investigate cell neighbor-dependent gene expression (CellNeighborEX) in spatial transcriptomics (ST) data. To categorize cells based on their microenvironment, CellNeighborEX uses direct cell location or the mixture of transcriptome from multiple cells depending on ST technologies. For each cell type, CellNeighborEX identifies diverse gene sets associated with partnering cell types, providing further insight. We found that cells express different genes depending on their neighboring cell types in various tissues including mouse embryos, brain, and liver cancer. Those genes are associated with critical biological processes such as development or metastases. We further validated that gene expression is induced by neighboring partners via spatial visualization. The neighbor-dependent gene expression suggests new potential genes involved in cell–cell interactions beyond what ligand-receptor co-expression can discover.

AB - Cells have evolved their communication methods to sense their microenvironments and send biological signals. In addition to communication using ligands and receptors, cells use diverse channels including gap junctions to communicate with their immediate neighbors. Current approaches, however, cannot effectively capture the influence of various microenvironments. Here, we propose a novel approach to investigate cell neighbor-dependent gene expression (CellNeighborEX) in spatial transcriptomics (ST) data. To categorize cells based on their microenvironment, CellNeighborEX uses direct cell location or the mixture of transcriptome from multiple cells depending on ST technologies. For each cell type, CellNeighborEX identifies diverse gene sets associated with partnering cell types, providing further insight. We found that cells express different genes depending on their neighboring cell types in various tissues including mouse embryos, brain, and liver cancer. Those genes are associated with critical biological processes such as development or metastases. We further validated that gene expression is induced by neighboring partners via spatial visualization. The neighbor-dependent gene expression suggests new potential genes involved in cell–cell interactions beyond what ligand-receptor co-expression can discover.

KW - cellular communication

KW - cell–cell interactions

KW - neighbor-dependent genes

KW - spatial transcriptomics

U2 - 10.15252/msb.202311670

DO - 10.15252/msb.202311670

M3 - Journal article

C2 - 37815040

AN - SCOPUS:85173779356

VL - 19

JO - Molecular Systems Biology

JF - Molecular Systems Biology

SN - 1744-4292

IS - 11

M1 - e11670

ER -