scholarly journals Identification of Intercellular Signaling Changes Across Conditions and Their Influence on Intracellular Signaling Response From Multiple Single-Cell Datasets

2021 ◽  
Vol 12 ◽  
Author(s):  
Mengqian Hao ◽  
Xiufen Zou ◽  
Suoqin Jin
Keyword(s):  
Single Cell ◽  
Intracellular Signaling ◽  
Target Gene ◽  
Cell Communication ◽  
Signaling Network ◽  
Intercellular Signaling ◽  
Signaling Mechanisms ◽  
Cord Injury ◽  
Intercellular Communications ◽  
Cell Cell

Identification of intercellular signaling changes across multiple single-cell RNA-sequencing (scRNA-seq) datasets as well as how intercellular communications affect intracellular transcription factors (TFs) to regulate target genes is crucial in understanding how distinct cell states respond to evolution, perturbations, and diseases. Here, we first generalized our previously developed tool CellChat, enabling flexible comparison analysis of cell–cell communication networks across any number of scRNA-seq datasets from interrelated biological conditions. This greatly facilitates the ready detection of signaling changes of cell–cell communication in response to any biological perturbations. We then investigated how intercellular communications affect intracellular signaling response by inferring a multiscale signaling network which bridges the intercellular communications at the population level and the cell state–specific intracellular signaling network at the molecular level. The latter is constructed by integrating receptor-TF interactions collected from public databases and TF-target gene regulations inferred from a network-regularized regression model. By applying our approaches to three scRNA-seq datasets from skin development, spinal cord injury, and COVID-19, we demonstrated the capability of our approaches in identifying the predominant signaling changes across conditions and the critical signaling mechanisms regulating target gene expression. Together, our work will facilitate the identification of both intercellular and intracellular dysregulated signaling mechanisms responsible for biological perturbations in diverse tissues.

scholarly journals Characterization of Cell-cell Communication in Autistic Brains with Single Cell Transcriptomes

2021 ◽  
Author(s):  
Maider Astorkia ◽  
Herbert Lachman ◽  
Deyou Zheng
Keyword(s):  
Single Cell ◽  
Signaling Pathways ◽  
Computational Study ◽  
Neurodevelopmental Disorder ◽  
Cell Communication ◽  
Autism Spectrum ◽  
Intercellular Signaling ◽  
Cell Type ◽  
Cell Data ◽  
Cell Cell

Autism spectrum disorder is a neurodevelopmental disorder, affecting 1-2% of children. Studies have revealed genetic and cellular abnormalities in the brains of affected individuals, leading to both regional and distal cell communication deficits. Recent application of single cell technologies, especially single cell transcriptomics, has significantly expanded our understanding of brain cell heterogeneity and further demonstrated that multiple cell types and brain layers or regions are perturbed in autism. The underlying high-dimensional single cell data provides opportunities for multi-level computational analysis that collectively can better deconvolute the molecular and cellular events altered in autism. Here, we apply advanced computation and pattern recognition approaches on single cell RNA-seq data to infer and compare inter-cell-type signaling communications in autism brains and controls. Our results indicate that at a global level there are cell-cell communication differences in autism in comparison to controls, largely involving neurons as both signaling senders and receivers, but glia also contribute to the communication disruption. Although the magnitude of change is moderate, we find that excitatory and inhibitor neurons are involved in multiple intercellular signaling that exhibit increased strengths in autism, such as NRXN and CNTN signaling. Not all genes in the intercellular signaling pathways are differentially expressed, but genes in the pathways are enriched for axon guidance, synapse organization, neuron migration, and other critical cellular functions. Furthermore, those genes are highly connected to and enriched for genes previously associated with autism risks. Overall, our proof-of-principle computational study using single cell data uncovers key intercellular signaling pathways that are potentially disrupted in the autism brains, suggesting that more studies examining cross-cell type affects can be valuable for understanding autism pathogenesis.

scholarly journals Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics

Cell Reports ◽  
2018 ◽  
Vol 25 (6) ◽  
pp. 1458-1468.e4 ◽  
Author(s):  
Manu P. Kumar ◽  
Jinyan Du ◽  
Georgia Lagoudas ◽  
Yang Jiao ◽  
Andrew Sawyer ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Communication ◽  
Tumor Characteristics ◽  
Rna Seq ◽  
Cell Cell

scholarly journals New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data

2020 ◽  
Vol 11 (12) ◽  
pp. 866-880 ◽  
Author(s):  
Xin Shao ◽  
Xiaoyan Lu ◽  
Jie Liao ◽  
Huajun Chen ◽  
Xiaohui Fan
Keyword(s):  
Single Cell ◽  
Communication Networks ◽  
Cell Communication ◽  
Receptor Interaction ◽  
Communication Studies ◽  
Transcriptomics Data ◽  
Phenotype Heterogeneity ◽  
Multicellular Organisms ◽  
Communication Study ◽  
Cell Cell

AbstractFor multicellular organisms, cell-cell communication is essential to numerous biological processes. Drawing upon the latest development of single-cell RNA-sequencing (scRNA-seq), high-resolution transcriptomic data have deepened our understanding of cellular phenotype heterogeneity and composition of complex tissues, which enables systematic cell-cell communication studies at a single-cell level. We first summarize a common workflow of cell-cell communication study using scRNA-seq data, which often includes data preparation, construction of communication networks, and result validation. Two common strategies taken to uncover cell-cell communications are reviewed, e.g., physically vicinal structure-based and ligand-receptor interaction-based one. To conclude, challenges and current applications of cell-cell communication studies at a single-cell resolution are discussed in details and future perspectives are proposed.

Single-Cell Analysis of Cell-Cell Communication of Exosome Components Derived from Melanoma Cells

2020 ◽  
Vol MA2020-02 (44) ◽  
pp. 2825-2825
Author(s):  
Miyu Fukaya ◽  
Tomohiro Hatakenaka ◽  
Nahoko Matsuki ◽  
Seiya Minagawa ◽  
Mikako Saito
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Cell Communication ◽  
Melanoma Cells ◽  
Cell Analysis ◽  
Cell Cell

scholarly journals Biomaterial-supported MSCs transplantation enhances cell-cell communication for spinal cord injury

2020 ◽  
Author(s):  
Bin Lv ◽  
Haosheng Wang ◽  
shengquan yang
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Nervous System ◽  
Cell Communication ◽  
Growth Potential ◽  
Peripheral Tissues ◽  
Positive Effects ◽  
Cord Injury ◽  
Biomaterial Scaffolds ◽  
Cell Cell

Abstract The spinal cord is part of the central nervous system (CNS) and serves to connect the brain to the peripheral nervous system and peripheral tissues. The cell types that primarily comprise the spinal cord are neurons and several categories of glia, including astrocytes, oligodendrocytes, and microglia. Ependymal cells and small populations of endogenous stem cells, such as oligodendrocyte progenitor cells, also reside in the spinal cord [1]. Neurons are interconnected in circuits; those that process cutaneous sensory input are mainly located in the dorsal spinal cord, while those involved in proprioception and motor control are predominately located in the ventral spinal cord [2]. Due to the importance of the spinal cord, neurodegenerative disorders and traumatic injuries affecting the spinal cord will lead to motor deficits and loss of sensory inputs. Spinal cord injury (SCI), resulting in paraplegia and tetraplegia as a result of deleterious interconnected mechanisms encompassed by the primary and secondary injury, represents a heterogeneously behavioral and cognitive deficit that remains incurable. Following SCI, various barriers containing the neuroinflammation, neural tissue defect (neurons, microglia, astrocytes, and oligodendrocytes), cavity formation, loss of neuronal circuitry and function must be overcame[3]. Notably, the pro -inflammatory and anti-inflammatory effect s of cell-cell communication networks play critical roles in homeostatic, driving the pathophysiologic and consequent cognitive outcomes. In the spinal cord, astrocytes, oligodendrocytes and microglia are involved in not only development but also pathology. Glial cells play dual roles (negative vs. positive effects) in these processes. After SCI, detrimental effects usually dominate and significantly retard functional recovery, and curbing these effects is critical for promoting neurological improvement. Indeed, residential innate immune cells (microglia and astrocytes) and infiltrating leukocytes (macrophages and neutrophils), activated by SCI, give rise to full-blown inflammatory cascades. These inflammatory cells release neurotoxins (proinflammatory cytokines and chemokines, free radicals, excitotoxic amino acids, nitric oxide (NO)), all of which partake in axonal and neuronal deficit[4]. Given the various multifaceted obstacles in SCI treatment, a combinatorial therapy of cell transplantation and biomaterial implantation may be addressed in detail here. For the sake of preserving damaged tissue integrity and providing physical support and trophic supply for axon regeneration, MSCs transplantation has come to the front stage in therapy for SCI with the constant progress of stem cell engineering [5]. MSCs transplantation promotes scaffold integration and regenerative growth potential. Integrating into the implanted scaffold, MSCs influences implant integration by improving the healing process[6]. Conversely, biomaterial scaffolds offer MSCs with a sheltered microenvironment from the surrounding pathological changes, in addition to bridging connection spinal cord stump and offering physical and directional support for axonal regeneration. Besides, Biomaterial scaffolds mimic the extracellular matrix to suppress immune responses. Here, we review the advances in combinatorial biomaterial scaffolds and MSCs transplantation approach that targets certain aspects of various intercellular communications in the pathologic process following SCI. Finally, the challenges of biomaterial-supported MSCs transplantation and its future direction for neuronal regeneration will be presented.

scholarly journals A Critical-like Collective State Leads to Long-range Cell Communication in Dictyostelium discoideum Aggregation

2016 ◽  
Author(s):  
Giovanna De Palo ◽  
Darvin Yi ◽  
Robert G. Endres
Keyword(s):  
Single Cell ◽  
Dictyostelium Discoideum ◽  
Long Range ◽  
Early Development ◽  
Cell Communication ◽  
Multiscale Model ◽  
Wild Type ◽  
Social Amoeba ◽  
Range Cell ◽  
Cell Cell

AbstractThe transition from single-cell to multicellular behavior is important in early development but rarely studied. The starvation-induced aggregation of the social amoeba Dictyostelium discoideum into a multicellular slug is known to result from single-cell chemotaxis towards emitted pulses of cyclic adenosine monophosphate (cAMP). However, how exactly do transient short-range chemical gradients lead to coherent collective movement at a macroscopic scale? Here, we developed a multiscale model verified by quantitative microscopy to describe wide-ranging behaviors from chemotaxis and excitability of individual cells to aggregation of thousands of cells. To better understand the mechanism of long-range cell-cell communication and hence aggregation, we analyzed cell-cell correlations, showing evidence of self-organization at the onset of aggregation (as opposed to following a leader cell). Surprisingly, cell collectives, despite their finite size, show features of criticality known from phase transitions in physical systems. By comparing wild-type and mutant cells with impaired aggregation, we found the longest cellcell communication distance in wild-type cells, suggesting that criticality provides an adaptive advantage and optimally sized aggregates for the dispersal of spores.Author SummaryCells are often coupled to each other in cell collectives, such as aggregates during early development, tissues in the developed organism, and tumors in disease. How do cells communicate over macroscopic distances much larger than the typical cell-cell distance to decide how they should behave? Here, we developed a multiscale model of social amoeba, spanning behavior from individuals to thousands of cells. We show that local cell-cell coupling via secreted chemicals may be tuned to a critical value, resulting in emergent long-range communication and heightened sensitivity. Hence, these aggregates are remarkably similar to bacterial biofilms and neuronal networks, all communicating in a pulse-like fashion. Similar organizing principles may also aid our understanding of the remarkable robustness in cancer development.

scholarly journals A new improved and extended version of the multicell bacterial simulator gro

2016 ◽  
Author(s):  
Martín Gutiérrez ◽  
Paula Gregorio-Godoy ◽  
Guillermo Pérez del Pulgar ◽  
Luis Muñoz ◽  
Sandra Sáez ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Timed Automata ◽  
Cell Communication ◽  
Colony Growth ◽  
Communication Process ◽  
Intercellular Signaling ◽  
Dividing Cells ◽  
A Cell ◽  
Local Cell ◽  
Cell Cell

Abstractgro is a cell programming language developed in Klavins Lab for simulating colony growth and cell-cell communication. It is used as a synthetic biology prototyping tool for simulating multicellular biocircuits. In this work, we present several extensions made to gro that improve the performance of the simulator, make it easier to use and provide new functionalities. The new version of gro is between one and two orders of magnitude faster than the original version. It is able to grow microbial colonies with up to 105 cells in less than 20 minutes. A new library, CellEngine, accelerates the resolution of spatial physical interactions between growing and dividing cells by implementing a new shoving algorithm. A genetic library, CellPro, based on Probabilistic Timed Automata, simulates gene expression dynamics using simplified and easy to compute digital proteins. We also propose a more convenient language specification layer, ProSpec, based on the idea that proteins drive cell behavior. CellNutrient, another library, implements Monod-based growth and nutrient uptake functionalities. The intercellular signaling management was improved and extended in a library called CellSignals. Finally, bacterial conjugation, another local cell-cell communication process, was added to the simulator. To show the versatility and potential outreach of this version of gro, we provide studies and novel examples ranging from synthetic biology to evolutionary microbiology. We believe that the upgrades implemented for gro have made it into a powerful and fast prototyping tool capable of simulating a large variety of systems and synthetic biology designs.

scholarly journals Inference and analysis of cell-cell communication using CellChat

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Suoqin Jin ◽  
Christian F. Guerrero-Juarez ◽  
Lihua Zhang ◽  
Ivan Chang ◽  
Raul Ramos ◽  
...  
Keyword(s):  
Communication Networks ◽  
Cell Communication ◽  
Molecular Complexes ◽  
Web Based ◽  
Single Cell Rna Sequencing ◽  
Context Specific ◽  
Global Communications ◽  
Complex Signaling ◽  
Intercellular Communications ◽  
Cell Cell

AbstractUnderstanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer (http://www.cellchat.org/) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues.

scholarly journals Cellinker: a platform of ligand–receptor interactions for intercellular communication analysis

2021 ◽  
Author(s):  
Yang Zhang ◽  
Tianyuan Liu ◽  
Jing Wang ◽  
Bohao Zou ◽  
Le Li ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Intercellular Communication ◽  
Rapid Development ◽  
Cell Communication ◽  
Supplementary Information ◽  
Protein Protein Interactions ◽  
Communication Analysis ◽  
Mediate Cell ◽  
Intercellular Communications ◽  
Cell Cell

Abstract Motivation Ligand–receptor (L–R) interactions mediate cell adhesion, recognition and communication and play essential roles in physiological and pathological signaling. With the rapid development of single-cell RNA sequencing (scRNA-seq) technologies, systematically decoding the intercellular communication network involving L–R interactions has become a focus of research. Therefore, construction of a comprehensive, high-confidence and well-organized resource to retrieve L–R interactions in order to study the functional effects of cell–cell communications would be of great value. Results In this study, we developed Cellinker, a platform of literature-supported L–R interactions that play roles in cell–cell communication. We aimed to provide a useful platform for studies on cell–cell communication mediated by L–R interactions. The current version of Cellinker documents over 3700 human and 3200 mouse L–R protein–protein interactions (PPIs) and embeds a practical and convenient webserver with which researchers can decode intercellular communications based on scRNA-seq data. And over 400 endogenous small molecule (sMOL) related L–R interactions were collected as well. Moreover, to help with research on coronavirus (CoV) infection, Cellinker collects information on 16L–R PPIs involved in CoV–human interactions (including 12L–R PPIs involved in SARS-CoV-2 infection). In summary, Cellinker provides a user-friendly interface for querying, browsing and visualizing L–R interactions as well as a practical and convenient web tool for inferring intercellular communications based on scRNA-seq data. We believe this platform could promote intercellular communication research and accelerate the development of related algorithms for scRNA-seq studies. Availability and implementation Cellinker is available at http://www.rna-society.org/cellinker/ Supplementary information Supplementary data are available at Bioinformatics online.

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