Rat parietal cells express CCK2 receptor mRNA: gene expression analysis of single cells isolated by laser-assisted microdissection

2002 ◽  
Vol 297 (2) ◽  
pp. 335-340 ◽  
Author(s):  
Karin Tømmerås ◽  
Ingunn Bakke ◽  
Arne K Sandvik ◽  
Erik Larsson ◽  
Helge L Waldum
Author(s):  
Sadegh Fattahi ◽  
Galia Amirbozorgi ◽  
Maryam Lotfi ◽  
Batoul Amini Navaei ◽  
Saeid Kavoosian ◽  
...  

2019 ◽  
Vol 374 (1786) ◽  
pp. 20190098 ◽  
Author(s):  
Chuan Ku ◽  
Arnau Sebé-Pedrós

Understanding the diversity and evolution of eukaryotic microorganisms remains one of the major challenges of modern biology. In recent years, we have advanced in the discovery and phylogenetic placement of new eukaryotic species and lineages, which in turn completely transformed our view on the eukaryotic tree of life. But we remain ignorant of the life cycles, physiology and cellular states of most of these microbial eukaryotes, as well as of their interactions with other organisms. Here, we discuss how high-throughput genome-wide gene expression analysis of eukaryotic single cells can shed light on protist biology. First, we review different single-cell transcriptomics methodologies with particular focus on microbial eukaryote applications. Then, we discuss single-cell gene expression analysis of protists in culture and what can be learnt from these approaches. Finally, we envision the application of single-cell transcriptomics to protist communities to interrogate not only community components, but also the gene expression signatures of distinct cellular and physiological states, as well as the transcriptional dynamics of interspecific interactions. Overall, we argue that single-cell transcriptomics can significantly contribute to our understanding of the biology of microbial eukaryotes. This article is part of a discussion meeting issue ‘Single cell ecology’.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jennifer Ma ◽  
Gary Tran ◽  
Alwin M. D. Wan ◽  
Edmond W. K. Young ◽  
Eugenia Kumacheva ◽  
...  

AbstractGene expression analysis of individual cells enables characterization of heterogeneous and rare cell populations, yet widespread implementation of existing single-cell gene analysis techniques has been hindered due to limitations in scale, ease, and cost. Here, we present a novel microdroplet-based, one-step reverse-transcriptase polymerase chain reaction (RT-PCR) platform and demonstrate the detection of three targets simultaneously in over 100,000 single cells in a single experiment with a rapid read-out. Our customized reagent cocktail incorporates the bacteriophage T7 gene 2.5 protein to overcome cell lysate-mediated inhibition and allows for one-step RT-PCR of single cells encapsulated in nanoliter droplets. Fluorescent signals indicative of gene expressions are analyzed using a probabilistic deconvolution method to account for ambient RNA and cell doublets and produce single-cell gene signature profiles, as well as predict cell frequencies within heterogeneous samples. We also developed a simulation model to guide experimental design and optimize the accuracy and precision of the assay. Using mixtures of in vitro transcripts and murine cell lines, we demonstrated the detection of single RNA molecules and rare cell populations at a frequency of 0.1%. This low cost, sensitive, and adaptable technique will provide an accessible platform for high throughput single-cell analysis and enable a wide range of research and clinical applications.


2020 ◽  
Author(s):  
Yipeng Gao ◽  
Lei Li ◽  
Christopher I. Amos ◽  
Wei Li

AbstractAlternative polyadenylation (APA) is a major mechanism of post-transcriptional regulation in various cellular processes including cell proliferation and differentiation, but the APA heterogeneity among single cells remains largely unknown. Single-cell RNA sequencing (scRNA-seq) has been extensively used to define cell subpopulations at the transcription level. Yet, most scRNA-seq data have not been analyzed in an “APA-aware” manner. Here, we introduce scDaPars, a bioinformatics algorithm to accurately quantify APA events at both single-cell and single-gene resolution using standard scRNA-seq data. Validations in both real and simulated data indicate that scDaPars can robustly recover missing APA events caused by the low amounts of mRNA sequenced in single cells. When applied to cancer and human endoderm differentiation data, scDaPars not only revealed cell-type-specific APA regulation but also identified cell subpopulations that are otherwise invisible to conventional gene expression analysis. Thus, scDaPars will enable us to understand cellular heterogeneity at the post-transcriptional APA level.


2019 ◽  
Author(s):  
Aida Sarmiento-Castro ◽  
Eva Caamaño-Gutiérrez ◽  
Andrew H. Sims ◽  
Mark I. James ◽  
Angélica Santiago-Gómez ◽  
...  

SUMMARYEstrogen receptor-positive (ER+) breast tumours are often treated with anti-estrogen (AE) therapies but frequently develop resistance. Cancer Stem Cells (CSCs) with high aldehyde dehydrogenase (ALDH) activity (ALDH+ cells) are reported to be enriched following AE treatment. Here we perform in vitro and in vivo functional CSC assays and gene expression analysis to characterise the ALDH+ population in AE resistant metastatic patient samples and an ER+ cell line. We show that the IL1β signalling pathway is activated in ALDH+ cells and data from single cells reveals that AE treatment selects for IL1R1-expressing ALDH+ cells. Importantly, we demonstrate that increased expression of IL1R1 is observed in the tumours of patients treated with AE therapy and predicts for treatment failure. Single-cell gene expression analysis revealed that at least 2 sub-populations exist within the ALDH+ population, one proliferative and one quiescent. Following AE therapy, the quiescent ALDH+IL1R1+ population is expanded, which suggests CSC dormancy as an adaptive strategy that facilitates treatment resistance. Supporting this, analysis of AE resistant dormant tumours reveals significantly increased expression of ALDH1A1, ALDH1A3 and IL1R1 genes. Thus, we propose that targeting of ALDH+IL1R1+ cells will reverse AE resistance, including in patients with minimal residual disease.


2017 ◽  
Author(s):  
Rayna M. Harris ◽  
Adriane G. Otopalik ◽  
Colin J. Smith ◽  
Dirk Bucher ◽  
Jorge Golowasch ◽  
...  

ABSTRACTGene expression analysis from single cells has become increasingly prominent across biological disciplines; thus, it is important to train students in these approaches. Here, we present an experimental and analysis pipeline that we developed for the Neural Systems & Behavior (NS&B) course at Marine Biological Laboratory. Our approach used the Maxwell® 16 LEV simplyRNA Tissue Kit and GoTaq® 2-Step RT-qPCR System for gene expression analysis from single neurons of the crustacean stomatogastric ganglion, a model system to study the generation of rhythmic motor patterns. We used double-stranded RNA to knockdown expression of a putative neuromodulator-activated sodium channel. We then examined the electrophysiological responses to known neuromodulators and confirmed that the response was reduced. Finally, we measured how mRNA levels of several ion channel genes changed in response. Our results provide new insights into the neural mechanisms underlying the generation and modulation of rhythmic motor patterns.


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