Signaling network responses can be highly heterogeneous across cells in a tissue because of many sources of genetic and non-genetic variance. The emergence of multiplexed single-cell technologies has ...made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of these technologies. We describe the computational tools for network characterization using single-cell data and discuss potential confounding factors that may affect single-cell analyses.
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Highlights
•Signaling networks can be highly heterogeneous across cells in a tissue.•Various technologies allow analyzing signaling networks at single-cell resolution.•The advantages and limitations of each single-cell approach are summarized.•Confounding factors in single-cell signaling network analysis are discussed.
Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.
Recent studies have shown that cell cycle and cell volume are confounding factors when studying biological phenomena in single cells. Here we present a combined experimental and computational method, ...CellCycleTRACER, to account for these factors in mass cytometry data. CellCycleTRACER is applied to mass cytometry data collected on three different cell types during a TNFα stimulation time-course. CellCycleTRACER reveals signaling relationships and cell heterogeneity that were otherwise masked.
Cells react to their microenvironment by integrating external stimuli into phenotypic decisions via an intracellular signaling network. To analyze the interplay of environment, local neighborhood, ...and internal cell state effects on phenotypic variability, we developed an experimental approach that enables multiplexed mass cytometric imaging analysis of up to 240 pooled spheroid microtissues. We quantified the contributions of environment, neighborhood, and intracellular state to marker variability in single cells of the spheroids. A linear model explained on average more than half of the variability of 34 markers across four cell lines and six growth conditions. The contributions of cell‐intrinsic and environmental factors to marker variability are hierarchically interdependent, a finding that we propose has general implications for systems‐level studies of single‐cell phenotypic variability. By the overexpression of 51 signaling protein constructs in subsets of cells, we also identified proteins that have cell‐intrinsic and cell‐extrinsic effects. Our study deconvolves factors influencing cellular phenotype in a 3D tissue and provides a scalable experimental system, analytical principles, and rich multiplexed imaging datasets for future studies.
SYNOPSIS
A barcoding‐based, high‐throughput approach enables multiplexed imaging of 3D spheroid microtissues. Quantitative single‐cell analyses show interdependence of global environment, local neighborhood, and internal cell state in determining cellular phenotype.
A novel barcoding‐based, high‐throughput approach enables multiplexed mass cytometric imaging of 3D microtissues.
A linear model quantifies environment, neighborhood, and internal cell state dependencies of marker expression.
A strong interdependence is identified between environmental and internal cell state predictors of cellular marker expression.
Systematic overexpression of signaling proteins within cells of 3D microtissues revealed non‐cell autonomous signaling.
A barcoding‐based, high‐throughput approach enables multiplexed imaging of 3D spheroid microtissues. Quantitative single‐cell analyses show interdependence of global environment, local neighborhood, and internal cell state in determining cellular phenotype.
To build comprehensive models of cellular states and interactions in normal and diseased tissue, genetic and proteomic information must be extracted with single-cell and spatial resolution. Here, we ...extended imaging mass cytometry to enable multiplexed detection of mRNA and proteins in tissues. Three mRNA target species were detected by RNAscope-based metal in situ hybridization with simultaneous antibody detection of 16 proteins. Analysis of 70 breast cancer samples showed that HER2 and CK19 mRNA and protein levels are moderately correlated on the single-cell level, but that only HER2, and not CK19, has strong mRNA-to-protein correlation on the cell population level. The chemoattractant CXCL10 was expressed in stromal cell clusters, and the frequency of CXCL10-expressing cells correlated with T cell presence. Our flexible and expandable method will allow an increase in the information content retrieved from patient samples for biomedical purposes, enable detailed studies of tumor biology, and serve as a tool to bridge comprehensive genomic and proteomic tissue analysis.
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•Imaging mass cytometry enables multiplexed RNA and protein detection in situ•mRNA measurement in IMC enables detection of as little as 6–14 mRNA copies per cell•Among patients, mRNA-to-protein ratios vary for CK19 but not for HER2•CXCL10-expressing cells form patches and are associated with T cell abundance
Here, we extend imaging mass cytometry to enable multiplexed detection of mRNA and protein in single cells in tissue sections. We show rigorous validation of the method and apply it to 70 samples from breast cancer patients. We investigate single-cell and population-based RNA-to-protein correlations in tissue and identify rare chemokine-expressing cells in the stroma that are associated with T cell abundance.
Kinase and phosphatase overexpression drives tumorigenesis and drug resistance. We previously developed a mass-cytometry-based single-cell proteomics approach that enables quantitative assessment of ...overexpression effects on cell signaling. Here, we applied this approach in a human kinome- and phosphatome-wide study to assess how 649 individually overexpressed proteins modulated cancer-related signaling in HEK293T cells in an abundance-dependent manner. Based on these data, we expanded the functional classification of human kinases and phosphatases and showed that the overexpression effects include non-catalytic roles. We detected 208 previously unreported signaling relationships. The signaling dynamics analysis indicated that the overexpression of ERK-specific phosphatases sustains proliferative signaling. This suggests a phosphatase-driven mechanism of cancer progression. Moreover, our analysis revealed a drug-resistant mechanism through which overexpression of tyrosine kinases, including SRC, FES, YES1, and BLK, induced MEK-independent ERK activation in melanoma A375 cells. These proteins could predict drug sensitivity to BRAF-MEK concurrent inhibition in cells carrying BRAF mutations.
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•Human kinome- and phosphatome-wide screen of overexpression-altered signaling network•Classification of the kinome and phosphatome based on abundance-dependent effects•Phosphatase overexpression sustains MAPK-ERK signaling by halting negative feedback•SRC, FES, YES1, and BLK lead to drug resistance in BRAF-MEK combined inhibition
Lun et al. perform mass-cytometry-based single-cell analysis to study how the expression levels of 649 kinases and phosphatases affect the intracellular signaling network. They expand the functional classification of the kinome and phosphatome based on abundance-dependent effects and identify novel signaling mechanisms underlying overexpression-driven diseases and drug resistance.
Inferring cell-signaling networks from high-throughput data is a challenging problem in systems biology. Recent advances in cytometric technology enable us to measure the abundance of a large number ...of proteins at the single-cell level across time. Traditional network reconstruction approaches usually consider each time point separately, resulting thus in inferred networks that strongly vary across time. To account for the possibly time-invariant physical couplings within the signaling network, we extend the traditional graphical lasso with an additional regularizer that penalizes network variations over time. ROC evaluation of the method on in silico data showed higher reconstruction accuracy than standard graphical lasso. We also tested our approach on single-cell mass cytometry data of IFNγ-stimulated THP1 cells with 26 phospho-proteins simultaneously measured. Our approach recapitulated known signaling relationships, such as connection within the JAK/STAT pathway, and was further validated in characterizing perturbed signaling network with PI3K, MEK1/2 and AMPK inhibitors.
Intracellular signaling pathways are at the core of cellular information processing. The states of these pathways and their inputs determine signaling dynamics and drive cell function. Within a ...cancerous tumor, many combinations of cell states and microenvironments can lead to dramatic variations in responses to treatment. Network rewiring has been thought to underlie these context-dependent differences in signaling; however, from a biochemical standpoint, rewiring of signaling networks should not be a prerequisite for heterogeneity in responses to stimuli. Here we address this conundrum by analyzing an
model of the epithelial mesenchymal transition (EMT), a biological program implicated in increased tumor invasiveness, heterogeneity, and drug resistance. We used mass cytometry to measure EGF signaling dynamics in the ERK and AKT signaling pathways before and after induction of EMT in Py2T murine breast cancer cells. Analysis of the data with standard network inference methods suggested EMT-dependent network rewiring. In contrast, use of a modeling approach that adequately accounts for single-cell variation demonstrated that a single reaction-based pathway model with constant structure and near-constant parameters is sufficient to represent differences in EGF signaling across EMT. This result indicates that rewiring of the signaling network is not necessary for heterogeneous responses to a signal and that unifying reaction-based models should be employed for characterization of signaling in heterogeneous environments, such as cancer.
Signaling networks are key regulators of cellular function. Although the concentrations of signaling proteins are perturbed in disease states, such as cancer, and are modulated by drug therapies, our ...understanding of how such changes shape the properties of signaling networks is limited. Here we couple mass-cytometry-based single-cell analysis with overexpression of tagged signaling proteins to study the dependence of signaling relationships and dynamics on protein node abundance. Focusing on the epidermal growth factor receptor (EGFR) signaling network in HEK293T cells, we analyze 20 signaling proteins during a 1-h EGF stimulation time course using a panel of 35 antibodies. Data analysis with BP-R
, a measure that quantifies complex signaling relationships, reveals abundance-dependent network states and identifies novel signaling relationships. Further, we show that upstream signaling proteins have abundance-dependent effects on downstream signaling dynamics. Our approach elucidates the influence of node abundance on signal transduction networks and will further our understanding of signaling in health and disease.
Aberrant microRNA expression is common in colorectal cancer and DNA methylation is believed to be responsible for this alteration. In this study, we performed evaluation in vivo and in vitro to ...determine the role of miR-181b as a potential diagnostic and prognostic biomarker in colorectal cancer. Ninty-seven pairs of colorectal cancer tissues and adjacent normal tissues were collected. The expression level and methylation status of miR-181b was determined in tissue samples and multiple colorectal cancer cell lines. RASSF1A, a predicted target gene of miR-181b, was investigated in vitro. Further mechanistic explorations were conducted. It was found that miR-181b expression was frequently downregulated in cancer samples. This lower expression level resulted from higher hypermethylation in cancer tissue and was closely related to TNM stage. Following artificial synthesis of miR-181b stimulation, colorectal cancer cell proliferation was greatly inhibited in CRC cells while apoptosis percentage markedly increased. miR-181b achieved the tumor suppressive effects via direct targeting of the RASSF1A gene. This study indicated the clinical significance of miR-181b and the influence of miR-181b promoter region in epigenetic silencing of tumorigenicity in colorectal cancer, and implied the possible usage of miR-181b as a diagnostic and prognostic biomarker in colorectal cancer.
Abstract
Mamestra brassicae L. is an important, regionally migratory pest of vegetable crops in Europe and Asia. Its migratory activity contributes significantly to population outbreaks, causing ...severe crop yield losses. Because an in-depth understanding of flight performance is key to revealing migratory patterns, here we used a computer-linked flight mill and stroboscope to study the flight ability and wingbeat frequency (WBF) of M. brassicae in relation to sex, age, temperature, and relative humidity (RH). The results showed that age significantly affected the flight ability and WBF of M. brassicae, and 3-d-old individuals performed the strongest performance (total flight distance: 45.6 ± 2.5 km; total flight duration: 9.3 ± 0.3 h; WBF: 44.0 ± 0.5 Hz at 24°C and 75% RH). The age for optimal flight was considered to be 2–3 d old. Temperature and RH also significantly affected flight ability and WBF; flight was optimal from 23°C to 25°C and 64–75% RH. Because M. brassicae thus has great potential to undertake long-distance migration, better knowledge of its flight behavior and migration will help establish a pest forecasting and early-warning system.
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