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CellNeighborEX: deciphering neighbor‐dependent gene expression from spatial transcriptomics data

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...

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Autores principales: Kim, Hyobin, Kumar, Amit, Lövkvist, Cecilia, Palma, António M, Martin, Patrick, Kim, Junil, Bhoopathi, Praveen, Trevino, Jose, Fisher, Paul, Madan, Esha, Gogna, Rajan, Won, Kyoung Jae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10632736/
https://www.ncbi.nlm.nih.gov/pubmed/37815040
http://dx.doi.org/10.15252/msb.202311670
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author Kim, Hyobin
Kumar, Amit
Lövkvist, Cecilia
Palma, António M
Martin, Patrick
Kim, Junil
Bhoopathi, Praveen
Trevino, Jose
Fisher, Paul
Madan, Esha
Gogna, Rajan
Won, Kyoung Jae
author_facet Kim, Hyobin
Kumar, Amit
Lövkvist, Cecilia
Palma, António M
Martin, Patrick
Kim, Junil
Bhoopathi, Praveen
Trevino, Jose
Fisher, Paul
Madan, Esha
Gogna, Rajan
Won, Kyoung Jae
author_sort Kim, Hyobin
collection PubMed
description 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.
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spelling pubmed-106327362023-11-15 CellNeighborEX: deciphering neighbor‐dependent gene expression from spatial transcriptomics data Kim, Hyobin Kumar, Amit Lövkvist, Cecilia Palma, António M Martin, Patrick Kim, Junil Bhoopathi, Praveen Trevino, Jose Fisher, Paul Madan, Esha Gogna, Rajan Won, Kyoung Jae Mol Syst Biol Methods 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. John Wiley and Sons Inc. 2023-10-10 /pmc/articles/PMC10632736/ /pubmed/37815040 http://dx.doi.org/10.15252/msb.202311670 Text en © 2023 The Authors. Published under the terms of the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Kim, Hyobin
Kumar, Amit
Lövkvist, Cecilia
Palma, António M
Martin, Patrick
Kim, Junil
Bhoopathi, Praveen
Trevino, Jose
Fisher, Paul
Madan, Esha
Gogna, Rajan
Won, Kyoung Jae
CellNeighborEX: deciphering neighbor‐dependent gene expression from spatial transcriptomics data
title CellNeighborEX: deciphering neighbor‐dependent gene expression from spatial transcriptomics data
title_full CellNeighborEX: deciphering neighbor‐dependent gene expression from spatial transcriptomics data
title_fullStr CellNeighborEX: deciphering neighbor‐dependent gene expression from spatial transcriptomics data
title_full_unstemmed CellNeighborEX: deciphering neighbor‐dependent gene expression from spatial transcriptomics data
title_short CellNeighborEX: deciphering neighbor‐dependent gene expression from spatial transcriptomics data
title_sort cellneighborex: deciphering neighbor‐dependent gene expression from spatial transcriptomics data
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10632736/
https://www.ncbi.nlm.nih.gov/pubmed/37815040
http://dx.doi.org/10.15252/msb.202311670
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