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Quantitative proteomics cell bilayer (qPCB) method for studying cell-cell communication

ABSTRACT: Cellular communication is a fundamental process in biology. We developed an in vitro procedure for quantitatively analyzing proteome-wide changes triggered by interaction of different cell types. Using an adipocyte-macrophage bilayer co-culture model we detected thousands of proteins and deciphered regulatory pathways involved in low-grade inflammation leading to insulin resistance. The method can be applied for multiple cell-cell combinations to gain understanding in cellular interaction.

ORGANISM(S): Mus musculus

PROVIDER: GSE43426 | GEO | 2015/01/01

SECONDARY ACCESSION(S): PRJNA186076

REPOSITORIES: GEO

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Project description:MotivationIntercellular communication (i.e. cell-cell communication) plays an essential role in multicellular organisms coordinating various biological processes. Previous studies discovered that feedback loops between two cell types are a widespread and vital signaling motif regulating development, regeneration and cancer progression. While many computational methods have been developed to predict cell-cell communication based on gene expression datasets, these methods often predict one-directional ligand-receptor interactions from sender to receiver cells and are not suitable to identify feedback loops.ResultsHere, we describe ligand-receptor loop (LRLoop), a new method for analyzing cell-cell communication based on bi-directional ligand-receptor interactions, where two pairs of ligand-receptor interactions are identified that are responsive to each other and thereby form a closed feedback loop. We first assessed LRLoop using bulk datasets and found our method significantly reduces the false positive rate seen with existing methods. Furthermore, we developed a new strategy to assess the performance of these methods in single-cell datasets. We used the between-tissue interactions as an indicator of potential false-positive prediction and found that LRLoop produced a lower fraction of between-tissue interactions than traditional methods. Finally, we applied LRLoop to the single-cell datasets obtained from retinal development. We discovered many new bi-directional ligand-receptor interactions among individual cell types that potentially control proliferation, neurogenesis and/or cell fate specification.Availability and implementationAn R package is available at https://github.com/Pinlyu3/LRLoop. The source code can be found at figshare (https://doi.org/10.6084/m9.figshare.20126138.v1). The datasets can be found at figshare (https://doi.org/10.6084/m9.figshare.20126021.v1).Supplementary informationSupplementary data are available at Bioinformatics online.

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Quantitative proteomics cell bilayer (qPCB) method for studying cell-cell communication

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