Longitudinal multiparameter assay of lymphocyte interactions from onset by microfluidic cell pairing and culture

Resolving how the early signaling events initiated by cell–cell interactions are transduced into diverse functional outcomes necessitates correlated measurements at various stages. Typical approaches that rely on bulk cocultures and population-wide correlations, however, only reveal these relationships broadly at the population level, not within each individual cell. Here, we present a microfluidics-based cell–cell interaction assay that enables longitudinal investigation of lymphocyte interactions at the single-cell level through microfluidic cell pairing, on-chip culture, and multiparameter assays, and allows recovery of desired cell pairs by micromanipulation for off-chip culture and analyses. Well-defined initiation of interactions enables probing cellular responses from the very onset, permitting single-cell correlation analyses between early signaling dynamics and later-stage functional outcomes within same cells. We demonstrate the utility of this microfluidic assay with natural killer cells interacting with tumor cells, and our findings suggest a possible role for the strength of early calcium signaling in selective coordination of subsequent cytotoxicity and IFN-gamma production. Collectively, our experiments demonstrate that this new approach is well-suited for resolving the relationships between complex immune responses within each individual cell.

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On-Chip Cell–Cell Interaction Monitoring at Single-Cell Level by Efficient Immobilization of Multiple Cells in Adjustable Quantities

Analytical Chemistry ◽

10.1021/acs.analchem.0c01148 ◽

2020 ◽

Vol 92 (17) ◽

pp. 11607-11616

Author(s):

Xiaoqing Tang ◽

Xiaoming Liu ◽

Pengyun Li ◽

Fengyu Liu ◽

Masaru Kojima ◽

...

Keyword(s):

Single Cell ◽

Cell Interaction ◽

Single Cell Level ◽

Cell Level ◽

On Chip ◽

Multiple Cells ◽

Cell Cell

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In silico analysis of DNA re-replication across a complete genome reveals cell-to-cell heterogeneity and genome plasticity

10.1101/2020.03.30.016576 ◽

2020 ◽

Author(s):

Maria Anna Rapsomaniki ◽

Stella Maxouri ◽

Manuel Ramirez Garrastacho ◽

Patroula Nathanailidou ◽

Nickolaos Nikiforos Giakoumakis ◽

...

Keyword(s):

Single Cell ◽

In Silico ◽

Complete Genome ◽

Population Level ◽

Yeast Genome ◽

Control Mechanisms ◽

Single Cell Level ◽

Genome Plasticity ◽

Cell Heterogeneity ◽

Cell Level

AbstractDNA replication is a complex and remarkably robust process: despite its inherent uncertainty, manifested through stochastic replication timing at a single-cell level, multiple control mechanisms ensure its accurate and timely completion across a population. Disruptions in these mechanisms lead to DNA re-replication, closely connected to genomic instability and oncogenesis. We present a stochastic hybrid model of DNA re-replication that accurately portrays the interplay between discrete dynamics, continuous dynamics, and uncertainty. Using experimental data on the fission yeast genome, model simulations show how different regions respond to re-replication, and permit insight into the key mechanisms affecting re-replication dynamics. Simulated and experimental population-level profiles exhibit good correlation along the genome, which is robust to model parameters, validating our approach. At a single-cell level, copy numbers of individual loci are affected by intrinsic properties of each locus, in cis effects from adjoining loci and in trans effects from distant loci. In silico analysis and single-cell imaging reveal that cell-to-cell heterogeneity is inherent in re-replication and can lead to a plethora of genotypic variations. Our thorough in silico analysis of DNA re-replication across a complete genome reveals that heterogeneity at the single cell level and robustness at the population level are emerging and co-existing principles of DNA re-replication. Our results indicate that re-replication can promote genome plasticity by generating many diverse genotypes within a population, potentially offering an evolutionary advantage in cells with aberrations in replication control mechanisms.

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Multiplexed fluorescence imaging of GPCR downstream signaling dynamics at the single-cell level

10.1101/2021.08.22.457285 ◽

2021 ◽

Author(s):

Ryosuke Tany ◽

Yuhei Goto ◽

Yohei Kondo ◽

Kazuhiro Aoki

Keyword(s):

Single Cell ◽

G Protein ◽

Fluorescence Imaging ◽

Imaging System ◽

Single Cell Level ◽

Cell Level ◽

Gpcr Signaling ◽

Downstream Signaling ◽

Signaling Dynamics ◽

Multiplexed Fluorescence Imaging

AbstractG-protein-coupled receptors (GPCRs) play an important role in sensing various extracellular stimuli, such as neurotransmitters, hormones, and tastants, and transducing the input information into the cell. While the human genome encodes more than 800 GPCR genes, only four Gα-proteins (Gαs, Gαi/o, Gαq/11, and Gα12/13) are known to couple with GPCRs. It remains unclear how such divergent GPCR information is translated into the downstream G-protein signaling dynamics. To answer this question, we report a multiplexed fluorescence imaging system for monitoring GPCR downstream signaling dynamics at the single-cell level. Genetically encoded biosensors for cAMP, Ca2+, RhoA, and ERK were selected as markers for GPCR downstream signaling, and were stably expressed in HeLa cells. GPCR was further transiently overexpressed in the cells. As a proof-of-concept, we visualized GPCR signaling dynamics of 5 dopamine receptors and 12 serotonin receptors, and found heterogeneity between GPCRs and between cells. Even when the same Gα proteins were known to be coupled, the patterns of dynamics in GPCR downstream signaling, including the signal strength and duration, were substantially distinct among GPCRs. These results suggest the importance of dynamical encoding in GPCR signaling.

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Recent Advances in Understandings Towards Pathogenesis and Treatment for Intrauterine Adhesion and Disruptive Insights from Single-Cell Analysis

Reproductive Sciences ◽

10.1007/s43032-020-00343-y ◽

2020 ◽

Cited By ~ 1

Author(s):

Ross Ka-Kit Leung ◽

Yixin Lin ◽

Yanhui Liu

Keyword(s):

Endothelial Cells ◽

Stem Cell ◽

Single Cell ◽

Expression Profile ◽

Cell Interaction ◽

Endometrial Tissue ◽

Cell Heterogeneity ◽

Mesenchymal Transition ◽

Intrauterine Adhesion ◽

Cell Cell

Abstract Intrauterine adhesion is a major cause of menstrual irregularities, infertility, and recurrent pregnancy losses and the progress towards its amelioration and therapy is slow and unsatisfactory. We aim to summarize and evaluate the current treatment progress and research methods for intrauterine adhesion. We conducted literature review in January 2020 by searching articles at PubMed on prevention and treatment, pathogenesis, the repair of other tissues/organs, cell plasticity, and the stem cell–related therapies for intrauterine adhesion. A total of 110 articles were selected for review. Uterine cell heterogeneity, expression profile, and cell-cell interaction were investigated based on scRNA-seq of uterus provided by Human Cell Landscape (HCL) project. Previous knowledge on intrauterine adhesion (IUA) pathogenesis was mostly derived from correlation studies by differentially expressed genes between endometrial tissue of intrauterine adhesion patients/animal models and normal endometrial tissue. Although the TGF-β1/SMAD pathway was suggested as the key driver for IUA pathogenesis, uterine cell heterogeneity and distinct expression profile among different cell types highlighted the importance of single-cell investigations. Cell-cell interaction in the uterus revealed the central hub of endothelial cells interacting with other cells, with endothelial cells in endothelial to mesenchymal transition and fibroblasts as the strongest interaction partners. The potential of stem cell–related therapies appeared promising, yet suffers from largely animal studies and nonstandard study design. The need to dissect the roles of endometrial cells, endothelial cells, and fibroblasts and their interaction is evident in order to elucidate the molecular and cellular mechanisms in both intrauterine adhesion pathogenesis and treatment.

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Signaling Dynamics at the Single Cell Level

Biophysical Journal ◽

10.1016/j.bpj.2009.12.4135 ◽

2010 ◽

Vol 98 (3) ◽

pp. 754a

Author(s):

Michael Elowitz

Keyword(s):

Single Cell ◽

Single Cell Level ◽

Cell Level ◽

Signaling Dynamics

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Improved SNV Discovery in Barcode-Stratified scRNA-seq Alignments

Genes ◽

10.3390/genes12101558 ◽

2021 ◽

Vol 12 (10) ◽

pp. 1558

Author(s):

Prashant N. M. ◽

Hongyu Liu ◽

Christian Dillard ◽

Helen Ibeawuchi ◽

Turkey Alsaeedy ◽

...

Keyword(s):

Single Cell ◽

Individual Cell ◽

Stop Codon ◽

Cellular Heterogeneity ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Cell Level ◽

Novel Variants ◽

Anticancer Treatment ◽

Mcf7 Cell Line

Currently, the detection of single nucleotide variants (SNVs) from 10 x Genomics single-cell RNA sequencing data (scRNA-seq) is typically performed on the pooled sequencing reads across all cells in a sample. Here, we assess the gaining of information regarding SNV assessments from individual cell scRNA-seq data, wherein the alignments are split by cellular barcode prior to the variant call. We also reanalyze publicly available data on the MCF7 cell line during anticancer treatment. We assessed SNV calls by three variant callers—GATK, Strelka2, and Mutect2, in combination with a method for the cell-level tabulation of the sequencing read counts bearing variant alleles–SCReadCounts (single-cell read counts). Our analysis shows that variant calls on individual cell alignments identify at least a two-fold higher number of SNVs as compared to the pooled scRNA-seq; these SNVs are enriched in novel variants and in stop-codon and missense substitutions. Our study indicates an immense potential of SNV calls from individual cell scRNA-seq data and emphasizes the need for cell-level variant detection approaches and tools, which can contribute to the understanding of the cellular heterogeneity and the relationships to phenotypes, and help elucidate somatic mutation evolution and functionality.

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