Damage-induced cell–cell communication in different cochlear cell types via two distinct ATP-dependent Ca2+ waves

Interleukin-6 (IL-6) is a pleiotropic cytokine responsible for many different processes including the regulation of cell growth, apoptosis, differentiation, and survival in various cell types and organs, including the heart. Recent studies have indicated that IL-6 is a critical component in the cell-cell communication between myocytes and cardiac fibroblasts. In this study, we examined the effects of IL-6 deficiency on the cardiac cell populations, cardiac function, and interactions between the cells of the heart, specifically cardiac fibroblasts and myocytes. To examine the effects of IL-6 loss on cardiac function, we used the IL-6 −/− mouse. IL-6 deficiency caused severe cardiac dilatation, increased accumulation of interstitial collagen, and altered expression of the adhesion protein periostin. In addition, flow cytometric analyses demonstrated dramatic alterations in the cardiac cell populations of IL-6 −/− mice compared with wild-type littermates. We observed a marked increase in the cardiac fibroblast population in IL-6 −/− mice, whereas a concomitant decrease was observed in the other cardiac cell populations examined. Moreover, we observed increased cell proliferation and apoptosis in the developing IL-6 −/− heart. Additionally, we observed a significant decrease in the capillary density of IL-6 −/− hearts. To elucidate the role of IL-6 in the interactions between cardiac fibroblasts and myocytes, we performed in vitro studies and demonstrated that IL-6 deficiency attenuated the activation of the STAT3 pathway and VEGF production. Taken together, these data demonstrate that a loss of IL-6 causes cardiac dysfunction by shifting the cardiac cell populations, altering the extracellular matrix, and disrupting critical cell-cell interactions.

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FlyPhoneDB: An integrated web-based resource for cell-cell communication prediction in Drosophila

10.1101/2021.06.14.448430 ◽

2021 ◽

Author(s):

Yifang Liu ◽

Yanhui Hu ◽

Joshua Shing Shun Li ◽

Jonathan Rodiger ◽

Aram Comjean ◽

...

Keyword(s):

Cell Communication ◽

Cell Types ◽

Data Sets ◽

High Confidence ◽

Web Based ◽

Communication Events ◽

Single Cell Rna Sequencing ◽

Biological Interpretation ◽

Multicellular Organisms ◽

Cell Cell

Multicellular organisms rely on cell-cell communication to exchange information necessary for developmental processes and metabolic homeostasis. Cell-cell communication pathways can be inferred from transcriptomic datasets based on ligand-receptor (L-R) expression. Recently, data generated from single cell RNA sequencing (scRNA-seq) have enabled L-R interaction predictions at an unprecedented resolution. While computational methods are available to infer cell-cell communication in vertebrates such a tool does not yet exist for Drosophila. Here, we generated a high confidence list of L-R pairs for the major fly signaling pathways and developed FlyPhoneDB, a quantification algorithm that calculates interaction scores to predict L-R interactions between cells. At the FlyPhoneDB user interface, results are presented in a variety of tabular and graphical formats to facilitate biological interpretation. To demonstrate that FlyPhoneDB can effectively identify active ligands and receptors to uncover cell-cell communication events, we applied FlyPhoneDB to Drosophila scRNA-seq data sets from adult midgut, abdomen, and blood, and demonstrate that FlyPhoneDB can readily identify previously characterized cell-cell communication pathways. Altogether, FlyPhoneDB is an easy-to-use framework that can be used to predict cell-cell communication between cell types from scRNA-seq data in Drosophila.

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Microfluidic system-based time-course tracking of physical proximity between cells and its effect on gene expression for elucidating live single cancer-immune cell interactions

10.1101/2021.11.13.468447 ◽

2021 ◽

Author(s):

Bianca C.T Flores ◽

Smriti Chawla ◽

Ning Ma ◽

Chad Sanada ◽

Praveen Kumar Kujur ◽

...

Keyword(s):

Gene Expression ◽

Time Course ◽

Immune Cell ◽

Cell Communication ◽

Time Lapse ◽

Cell Types ◽

Temporal Variations ◽

Microfluidic System ◽

Cell Interactions ◽

Cell Cell

Cell-cell communication and physical interactions play a vital role in cancer initiation, homeostasis, progression, and immune response. Here, we report a system that combines live capture of different cell types, co-incubation, time-lapse imaging, and gene expression profiling of doublets using a microfluidic integrated fluidic circuit (IFC) that enables measurement of physical distances between cells and the associated transcriptional profiles due to cell-cell interactions. The temporal variations in natural killer (NK) - triple-negative breast cancer (TNBC) cell distances were tracked and compared with terminally profiled cellular transcriptomes. The results showed the time-bound activities of regulatory modules and alluded to the existence of transcriptional memory. Our experimental and bioinformatic approaches serve as a proof of concept for interrogating live cell interactions at doublet resolution, which can be applied across different cancers and cell types.

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Extracellular Vesicle-Mediated Cell–Cell Communication in the Nervous System: Focus on Neurological Diseases

International Journal of Molecular Sciences ◽

10.3390/ijms20020434 ◽

2019 ◽

Vol 20 (2) ◽

pp. 434 ◽

Cited By ~ 38

Author(s):

Celeste Caruso Bavisotto ◽

Federica Scalia ◽

Antonella Marino Gammazza ◽

Daniela Carlisi ◽

Fabio Bucchieri ◽

...

Keyword(s):

Nervous System ◽

Neurological Diseases ◽

Cell Communication ◽

Cell Types ◽

Extracellular Vesicle ◽

Response To Treatment ◽

Therapeutic Drugs ◽

The Central Nervous System ◽

Bioengineering Techniques ◽

Cell Cell

Extracellular vesicles (EVs), including exosomes, are membranous particles released by cells into the extracellular space. They are involved in cell differentiation, tissue homeostasis, and organ remodelling in virtually all tissues, including the central nervous system (CNS). They are secreted by a range of cell types and via blood reaching other cells whose functioning they can modify because they transport and deliver active molecules, such as proteins of various types and functions, lipids, DNA, and miRNAs. Since they are relatively easy to isolate, exosomes can be characterized, and their composition elucidated and manipulated by bioengineering techniques. Consequently, exosomes appear as promising theranostics elements, applicable to accurately diagnosing pathological conditions, and assessing prognosis and response to treatment in a variety of disorders. Likewise, the characteristics and manageability of exosomes make them potential candidates for delivering selected molecules, e.g., therapeutic drugs, to specific target tissues. All these possible applications are pertinent to research in neurophysiology, as well as to the study of neurological disorders, including CNS tumors, and autoimmune and neurodegenerative diseases. In this brief review, we discuss what is known about the role and potential future applications of exosomes in the nervous system and its diseases, focusing on cell–cell communication in physiology and pathology.

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FunRes: resolving tissue-specific functional cell states based on a cell–cell communication network model

Briefings in Bioinformatics ◽

10.1093/bib/bbaa283 ◽

2020 ◽

Author(s):

Sascha Jung ◽

Kartikeya Singh ◽

Antonio del Sol

Keyword(s):

Communication Network ◽

Communication Networks ◽

Cell Communication ◽

Cell Types ◽

Computational Method ◽

Tissue Specific ◽

Great Utility ◽

A Cell ◽

Cell Cell

Abstract The functional specialization of cell types arises during development and is shaped by cell–cell communication networks determining a distribution of functional cell states that are collectively important for tissue functioning. However, the identification of these tissue-specific functional cell states remains challenging. Although a plethora of computational approaches have been successful in detecting cell types and subtypes, they fail in resolving tissue-specific functional cell states. To address this issue, we present FunRes, a computational method designed for the identification of functional cell states. FunRes relies on scRNA-seq data of a tissue to initially reconstruct the functional cell–cell communication network, which is leveraged for partitioning each cell type into functional cell states. We applied FunRes to 177 cell types in 10 different tissues and demonstrated that the detected states correspond to known functional cell states of various cell types, which cannot be recapitulated by existing computational tools. Finally, we characterize emerging and vanishing functional cell states in aging and disease, and demonstrate their involvement in key tissue functions. Thus, we believe that FunRes will be of great utility in the characterization of the functional landscape of cell types and the identification of dysfunctional cell states in aging and disease.

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Micropatterned superhydrophobic structures for the simultaneous culture of multiple cell types and the study of cell–cell communication

Biomaterials ◽

10.1016/j.biomaterials.2012.11.034 ◽

2013 ◽

Vol 34 (7) ◽

pp. 1757-1763 ◽

Cited By ~ 69

Author(s):

Alexander N. Efremov ◽

Eliana Stanganello ◽

Alexander Welle ◽

Steffen Scholpp ◽

Pavel A. Levkin

Keyword(s):

Cell Communication ◽

Cell Types ◽

Multiple Cell ◽

Cell Cell

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Patient-Specific Cell Communication Networks Associate With Disease Progression in Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.667382 ◽

2021 ◽

Vol 12 ◽

Author(s):

David L. Gibbs ◽

Boris Aguilar ◽

Vésteinn Thorsson ◽

Alexander V. Ratushny ◽

Ilya Shmulevich

Keyword(s):

Communication Networks ◽

Probabilistic Method ◽

Cell Communication ◽

Cell Types ◽

Tumor Stage ◽

The Cancer Genome Atlas ◽

Patient Specific ◽

Specific Cell ◽

High Level ◽

Cell Cell

The maintenance and function of tissues in health and disease depends on cell–cell communication. This work shows how high-level features, representing cell–cell communication, can be defined and used to associate certain signaling “axes” with clinical outcomes. We generated a scaffold of cell–cell interactions and defined a probabilistic method for creating per-patient weighted graphs based on gene expression and cell deconvolution results. With this method, we generated over 9,000 graphs for The Cancer Genome Atlas (TCGA) patient samples, each representing likely channels of intercellular communication in the tumor microenvironment (TME). It was shown that cell–cell edges were strongly associated with disease severity and progression, in terms of survival time and tumor stage. Within individual tumor types, there are predominant cell types, and the collection of associated edges were found to be predictive of clinical phenotypes. Additionally, genes associated with differentially weighted edges were enriched in Gene Ontology terms associated with tissue structure and immune response. Code, data, and notebooks are provided to enable the application of this method to any expression dataset (https://github.com/IlyaLab/Pan-Cancer-Cell-Cell-Comm-Net).

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Cell-cell signaling elicits local Ca2+ transients in melanocyte dendrites and dendritic spine-like structures

10.1101/390542 ◽

2018 ◽

Author(s):

Rachel L. Belote ◽

Sanford M. Simon

Keyword(s):

Dendritic Spines ◽

Cell Communication ◽

Human Keratinocytes ◽

Cell Types ◽

Primary Human Keratinocytes ◽

Human Melanocytes ◽

Neuronal Functions ◽

Dendritic Branches ◽

Cell Cell

AbstractCompartmentalized cytoplasmic fluctuations of Ca2+ within dendrites and dendritic spines regulate a variety of neuronal functions. Like some neurons and glia, melanocytes are neural crest derived and possess dendrites (Adameyko et al., 2009; Erickson et al., 1992; Fitzpatrick and Szabo, 1959). Here, we show that primary human melanocytes, when observed in situ have extensive dendritic branches with dendritic spines similar to neurons. When co-cultured with primary human keratinocytes, they have local Ca2+ transients within these spines and within the dendrites. These are elicited by secreted factors from adjacent keratinocytes. Thus other cell types with dendrites are capable of compartmentalized Ca2+ fluctuations in response to cell-cell communication. Furthermore, our observations within intact human skin suggest a more complex communication network between adjacent melanocytes and keratinocytes, and thus a more complex physiology to skin than previous appreciated.

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LR Hunting: A Random Forest Based Cell–Cell Interaction Discovery Method for Single-Cell Gene Expression Data

Frontiers in Genetics ◽

10.3389/fgene.2021.708835 ◽

2021 ◽

Vol 12 ◽

Author(s):

Min Lu ◽

Yifan Sha ◽

Tiago C. Silva ◽

Antonio Colaprico ◽

Xiaodian Sun ◽

...

Keyword(s):

Single Cell ◽

Cell Communication ◽

Cell Types ◽

Cell Interaction ◽

Data Imputation ◽

Novel Approach ◽

Cell Gene Expression ◽

Minimal Depth ◽

Discovery Method ◽

Cell Cell

Cell–cell interactions (CCIs) and cell–cell communication (CCC) are critical for maintaining complex biological systems. The availability of single-cell RNA sequencing (scRNA-seq) data opens new avenues for deciphering CCIs and CCCs through identifying ligand-receptor (LR) gene interactions between cells. However, most methods were developed to examine the LR interactions of individual pairs of genes. Here, we propose a novel approach named LR hunting which first uses random forests (RFs)-based data imputation technique to link the data between different cell types. To guarantee the robustness of the data imputation procedure, we repeat the computation procedures multiple times to generate aggregated imputed minimal depth index (IMDI). Next, we identify significant LR interactions among all combinations of LR pairs simultaneously using unsupervised RFs. We demonstrated LR hunting can recover biological meaningful CCIs using a mouse cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) dataset and a triple-negative breast cancer scRNA-seq dataset.

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CellPhoneDB v2.0: Inferring cell-cell communication from combined expression of multi-subunit receptor-ligand complexes

10.1101/680926 ◽

2019 ◽

Cited By ~ 25

Author(s):

Mirjana Efremova ◽

Miquel Vento-Tormo ◽

Sarah A. Teichmann ◽

Roser Vento-Tormo

Keyword(s):

Communication Networks ◽

Cell Communication ◽

Cell Types ◽

Published Data ◽

Data Sets ◽

Cellular Interactions ◽

Receptor Ligand ◽

Link Type ◽

Transcriptomics Data ◽

Cell Cell

AbstractCell-cell communication mediated by receptor-ligand complexes is crucial for coordinating diverse biological processes, such as development, differentiation and responses to infection. In order to understand how the context-dependent crosstalk of different cell types enables physiological processes to proceed, we developed CellPhoneDB, a novel repository of ligands, receptors and their interactions1. Our repository takes into account the subunit architecture of both ligands and receptors, representing heteromeric complexes accurately. We integrated our resource with a statistical framework that predicts enriched cellular interactions between two cell types from single-cell transcriptomics data. Here, we outline the structure and content of our repository, the procedures for inferring cell-cell communication networks from scRNA-seq data and present a practical step-by-step guide to help implement the protocol. CellPhoneDB v2.0 is a novel version of our resource that incorporates additional functionalities to allow users to introduce new interacting molecules and reduce the time and resources needed to interrogate large datasets. CellPhoneDB v2.0 is publicly available at https://github.com/Teichlab/cellphonedb and as a user-friendly web interface at http://www.cellphonedb.org/. In our protocol, we demonstrate how to reveal meaningful biological discoveries from CellPhoneDB v2.0 using published data sets.

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