scholarly journals Cell-specific localization of alkaloids in Catharanthus roseus stem tissue measured with Imaging MS and Single-cell MS

2016 ◽  
Vol 113 (14) ◽  
pp. 3891-3896 ◽  
Author(s):  
Kotaro Yamamoto ◽  
Katsutoshi Takahashi ◽  
Hajime Mizuno ◽  
Aya Anegawa ◽  
Kimitsune Ishizaki ◽  
...  
Keyword(s):  
Single Cell ◽  
Catharanthus Roseus ◽  
Metabolic Pathway ◽  
Imaging Mass Spectrometry ◽  
Parenchyma Cell ◽  
Principal Component ◽  
Longitudinal Section ◽  
Tissue Imaging ◽  
Stem Tissue ◽  
Imaging Ms

Catharanthus roseus (L.) G. Don is a medicinal plant well known for producing antitumor drugs such as vinblastine and vincristine, which are classified as terpenoid indole alkaloids (TIAs). The TIA metabolic pathway in C. roseus has been extensively studied. However, the localization of TIA intermediates at the cellular level has not been demonstrated directly. In the present study, the metabolic pathway of TIA in C. roseus was studied with two forefront metabolomic techniques, that is, Imaging mass spectrometry (MS) and live Single-cell MS, to elucidate cell-specific TIA localization in the stem tissue. Imaging MS indicated that most TIAs localize in the idioblast and laticifer cells, which emit blue fluorescence under UV excitation. Single-cell MS was applied to four different kinds of cells [idioblast (specialized parenchyma cell), laticifer, parenchyma, and epidermal cells] in the stem longitudinal section. Principal component analysis of Imaging MS and Single-cell MS spectra of these cells showed that similar alkaloids accumulate in both idioblast cell and laticifer cell. From MS/MS analysis of Single-cell MS spectra, catharanthine, ajmalicine, and strictosidine were found in both cell types in C. roseus stem tissue, where serpentine was also accumulated. Based on these data, we discuss the significance of TIA synthesis and accumulation in the idioblast and laticifer cells of C. roseus stem tissue.

scholarly journals TAMI-45. PHENOGENOMIC CHARACTERIZATION OF IMMUNOMODULATORY PURINERGIC SIGNALING IN GLIOBLASTOMA

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii222-ii223
Author(s):  
Shannon Coy ◽  
Rumana Rashid ◽  
Sylwia Stopka ◽  
Jia-Ren Lin ◽  
Philipp Euskirchen ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Single Cell ◽  
Purinergic Signaling ◽  
Progression Free Survival ◽  
Tissue Imaging ◽  
Phenotypic Properties ◽  
Spatially Resolved ◽  
Therapeutic Benefits ◽  
Adenosine Concentration ◽  
Cd73 Expression

Abstract INTRODUCTION Purinergic signaling plays critical roles in the regulation of tumor growth and anti-tumor immunity via autocrine/paracrine binding of metabolites to receptors on neoplastic and non-neoplastic populations. Extracellular purine concentrations are mediated by the ectonucleotidase enzymes CD39 and CD73, which catabolize ATP to adenosine. Within tumors such as glioblastoma, neoplastic, immune, and stromal cells expressing these enzymes may co-localize to generate immunosuppressive adenosine-rich environments. However, the composition, architecture, and phenotypic properties of these tumor ecosystems and their relationship to tumor genotype are poorly characterized. METHODS We quantified CD73 expression by immunohistochemistry in a cohort of CNS tumors [meningiomas(n=222), gliomas(n=244), ependymomas(n=44), medulloblastomas(n=24), and craniopharyngiomas(n=38)]. We used publicly-available single-cell RNA-seq data and 36-marker multiplexed tissue imaging (t-CyCIF) of 139 clinically and genomically annotated glioblastoma resections to characterize CD39 and CD73-expressing populations, define the immune architecture and tumor cell-states at single cell resolution, and identify markers of clinical outcome. We used mass spectrometry imaging (MALDI-MSI) to generate spatially-resolved quantification of purine metabolite levels in glioblastoma resections (n=10). RESULTS CD73 exhibited strong expression in a subset of gliomas and meningiomas but was typically not expressed in ependymomas or medulloblastomas. CD73 expression correlated with poor progression-free-survival in IDH-wildtype glioblastoma (p=0.04). scRNA-seq and t-CyCIF in glioblastoma showed CD73 expression in tumor cells, and CD39 expression in macrophages and endothelial cells. MALDI-MSI showed significantly greater adenosine concentrations (3.5-fold;p=0.04) in glioblastomas with high CD73 expression. scRNA-seq showed direct correlations between stem-like mRNA expression, proliferation, and CD73 expression in DIPG. CD73 expression significantly correlated with EGFR amplification, interferon signaling, and PD-L1 expression in glioblastoma. CONCLUSIONS Phenogenomic analysis of purinergic immunomodulatory signaling revealed significant interplay between CD73 activity and genotype, adenosine concentration, differentiation-state, clinical outcome, and possible interaction between CD39-positive macrophages and CD73-positive neoplastic cells. Anti-CD73 therapy may provide therapeutic benefits in glioblastoma by blunting immunosuppressive and oncogenic adenosine signaling.

scholarly journals Multiplexed profiling of single-cell extracellular vesicles secretion

2019 ◽  
Vol 116 (13) ◽  
pp. 5979-5984 ◽  
Author(s):  
Yahui Ji ◽  
Dongyuan Qi ◽  
Linmei Li ◽  
Haoran Su ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Extracellular Vesicles ◽  
Single Cell Analysis ◽  
Comprehensive Evaluation ◽  
Single Cells ◽  
Deep Understanding ◽  
Principal Component ◽  
Cell Heterogeneity ◽  
Indispensable Tool

Extracellular vesicles (EVs) are important intercellular mediators regulating health and diseases. Conventional methods for EV surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EV secretion. Herein, by using spatially patterned antibody barcodes, we realized multiplexed profiling of single-cell EV secretion from more than 1,000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to a deep understanding of previously undifferentiated single-cell heterogeneity underlying EV secretion. Notably, we observed that the decrement of certain EV phenotypes (e.g.,CD63+EV) was associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EV secretion and cytokines secretion simultaneously from the same single cells to investigate the multidimensional spectrum of cellular communications, from which we resolved tiered functional subgroups with distinct secretion profiles by visualized clustering and principal component analysis. In particular, we found that different cell subgroups dominated EV secretion and cytokine secretion. The technology introduced here enables a comprehensive evaluation of EV secretion heterogeneity at single-cell level, which may become an indispensable tool to complement current single-cell analysis and EV research.

scholarly journals M6a Regulator-Associated Methylation Modification Patterns Shape Tumor Microenvironment Characteristics in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Bobin Ning ◽  
Yonggan Xue ◽  
Hongyi Liu ◽  
Hongyu Sun ◽  
Baoqing Jia
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Signaling Pathways ◽  
Principal Component ◽  
Unsupervised Clustering ◽  
Survival Prediction ◽  
Multiple Perspectives ◽  
Single Cell Sequencing ◽  
Survival Expectations

Abstract Although substantial achievements in the tumor microenvironment (TME) of hepatocellular carcinoma (HCC) have led to fundamental improvements both in the basic research and clinical management, the potential mechanisms and regulatory relationships between m6A regulators and the TME are still unknown. We first conducted unsupervised clustering on the samples according to the core m6A expression, and then compared the signaling pathways, differential genes (DEGs), and TME between the m6A phenotypes, and re-validated the relationship between m6A regulators and TME by single cell sequencing. Then, the geneCluster was obtained by another unsupervised clustering of the DEGs, and the clinical as well as TME traits were evaluated among the geneClusters. Finally, the m6A scores of individual patients were calculated by principal component analysis (PCA) to verify the correlation from multiple perspectives, including survivals, clinical characters, mutations, TME, immunotherapy, and chemotherapy. Through a comprehensive analysis of 729 samples, we classified HCC patients into three m6A clusters and three geneClusters. Each group exhibited remarkable variations in terms of signaling pathways, clinical traits, and survival expectations. Notably, the m6A phenotypes corresponded to three different types of TME, namely immune-inflamed, immune-excluded, and immune-desert, respectively. In addition, the m6A regulator can accurately reflect the individualized microenvironment in HCC, and present supreme expression levels in the stromal microenvironment. However, the m6A score system is able to make accurate predictions not only in terms of clinical traits, survival prediction, and TME mentioned above, but also in the sensitivity of HCC patients to immunotherapy and chemotherapy. This study revealed the uniqueness and pluripotency of m6A regulators in the TME of HCC by combining single-cell sequencing and bulk sequencing. The quantified m6A modification indices were able to accurately predict patient survival expectations, clinical traits, TME, and sensitivity to immunotherapy and chemotherapy.

scholarly journals More than efficacy revealed by single-cell analysis of antiviral therapeutics

2019 ◽  
Author(s):  
Wu Liu ◽  
Mehmet U. Caglar ◽  
Zhangming Mao ◽  
Andrew Woodman ◽  
Jamie J. Arnold ◽  
...  
Keyword(s):  
Single Cell ◽  
Drug Targets ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Principal Component ◽  
Viral Population ◽  
Cell Analysis ◽  
Toxic Dose ◽  
Time Required

SUMMARYDevelopment of antiviral therapeutics emphasizes minimization of the effective dose and maximization of the toxic dose, first in cell culture and later in animal models. Long-term success of an antiviral therapeutic is determined not only by its efficacy but also by the duration of time required for drug-resistance to evolve. We have developed a microfluidic device comprised of ~6000 wells, with each well containing a microstructure to capture single cells. We have used this device to characterize enterovirus inhibitors with distinct mechanisms of action. In contrast to population methods, single-cell analysis reveals that each class of inhibitor interferes with the viral infection cycle in a manner that can be distinguished by principal component analysis. Single-cell analysis of antiviral candidates reveals not only efficacy but also properties of the members of the viral population most sensitive to the drug, the stage of the lifecycle most affected by the drug, and perhaps even if the drug targets an interaction of the virus with its host.

scholarly journals More than efficacy revealed by single-cell analysis of antiviral therapeutics

2019 ◽  
Vol 5 (10) ◽  
pp. eaax4761 ◽  
Author(s):  
Wu Liu ◽  
Mehmet U. Caglar ◽  
Zhangming Mao ◽  
Andrew Woodman ◽  
Jamie J. Arnold ◽  
...  
Keyword(s):  
Viral Infection ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Principal Component ◽  
Cell Analysis ◽  
Infection Cycle ◽  
Reporter Protein ◽  
Fluorescent Reporter ◽  
Infection Dynamics ◽  
Infected Cells

Because many aspects of viral infection dynamics and inhibition are governed by stochastic processes, single-cell analysis should provide more information than approaches using population averaging. We have developed a microfluidic device composed of ~6000 wells, with each well containing a microstructure to capture single, infected cells replicating an enterovirus expressing a fluorescent reporter protein. We have used this system to characterize enterovirus inhibitors with distinct mechanisms of action. Single-cell analysis reveals that each class of inhibitor interferes with the viral infection cycle in a manner that can be distinguished by principal component analysis. Single-cell analysis of antiviral candidates not only reveals efficacy but also facilitates clustering of drugs with the same mechanism of action and provides some indication of the ease with which resistance will develop.

scholarly journals Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
F. William Townes ◽  
Stephanie C. Hicks ◽  
Martin J. Aryee ◽  
Rafael A. Irizarry
Keyword(s):  
Feature Selection ◽  
Dimension Reduction ◽  
Single Cell ◽  
Current Practice ◽  
Principal Component ◽  
Ground Truth ◽  
Rna Seq ◽  
Normal Distributions ◽  
Multinomial Sampling ◽  
Negative Controls

AbstractSingle-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative controls, we show UMI counts follow multinomial sampling with no zero inflation. Current normalization procedures such as log of counts per million and feature selection by highly variable genes produce false variability in dimension reduction. We propose simple multinomial methods, including generalized principal component analysis (GLM-PCA) for non-normal distributions, and feature selection using deviance. These methods outperform the current practice in a downstream clustering assessment using ground truth datasets.

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