Isolation of single cells from adherent cell lines using Smart Aliquotor CE v1 (protocols.io.bhjmj4k6)

protocols.io ◽  
2020 ◽  
Author(s):  
Lucy Kimbley ◽  
Rachel Parker ◽  
Maaike Sybil ◽  
John Holloway ◽  
Emily Swindle ◽  
...  
Keyword(s):  
Cell Lines ◽  
Single Cells ◽  
Adherent Cell

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 Multiplexed Profiling of Single-cell Extracellular Vesicles Secretion

2018 ◽  
Author(s):  
Yahui Ji ◽  
Dongyuan Qi ◽  
Linmei Li ◽  
Haoran Su ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Extracellular Vesicles ◽  
Single Cells ◽  
Cell Communication ◽  
Deep Understanding ◽  
Surface Markers ◽  
Cell Heterogeneity ◽  
Health And Disease ◽  
Cytokines Secretion

AbstractExtracellular vesicles (EVs) are important intercellular mediators regulating health and disease. Conventional EVs surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EVs secretion. Herein, by using spatially patterned antibodies barcode, we realized multiplexed profiling of single-cell EVs secretion from more than 1000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to deep understanding of previously undifferentiated single cell heterogeneity underlying EVs secretion. Notably, we observed the decrement of certain EV phenotypes (e.g. CD63+EVs) were associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EVs secretion and cytokines secretion simultaneously from the same single cells to investigate multidimensional spectrum of intercellular communications, from which we resolved three functional subgroups with distinct secretion profiles by visualized clustering. In particular, we found EVs secretion and cytokines secretion were generally dominated by different cell subgroups. The technology introduced here enables comprehensive evaluation of EVs secretion heterogeneity at single cell level, which may become an indispensable tool to complement current single cell analysis and EV research.SignificanceExtracellular vesicles (EVs) are cell derived nano-sized particles medicating cell-cell communication and transferring biology information molecules like nucleic acids to regulate human health and disease. Conventional methods for EV surface markers profiling can’t tell the differences in the quantity and phenotypes of EVs secretion between cells. To address this need, we developed a platform for profiling an array of surface markers on EVs from large numbers of single cells, enabling more comprehensive monitoring of cellular communications. Single cell EVs secretion assay led to previously unobserved cell heterogeneity underlying EVs secretion, which might open up new avenues for studying cell communication and cell microenvironment in both basic and clinical research.

scholarly journals Joint single cell DNA-seq and RNA-seq of gastric cancer cell lines reveals rules of in vitro evolution

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Noemi Andor ◽  
Billy T Lau ◽  
Claudia Catalanotti ◽  
Anuja Sathe ◽  
Matthew Kubit ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Single Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Gastric Cancer Cell ◽  
Phenotypic Diversity ◽  
Single Cells ◽  
Cancer Cell Lines ◽  
Gastric Cancer Cell Lines

Abstract Cancer cell lines are not homogeneous nor are they static in their genetic state and biological properties. Genetic, transcriptional and phenotypic diversity within cell lines contributes to the lack of experimental reproducibility frequently observed in tissue-culture-based studies. While cancer cell line heterogeneity has been generally recognized, there are no studies which quantify the number of clones that coexist within cell lines and their distinguishing characteristics. We used a single-cell DNA sequencing approach to characterize the cellular diversity within nine gastric cancer cell lines and integrated this information with single-cell RNA sequencing. Overall, we sequenced the genomes of 8824 cells, identifying between 2 and 12 clones per cell line. Using the transcriptomes of more than 28 000 single cells from the same cell lines, we independently corroborated 88% of the clonal structure determined from single cell DNA analysis. For one of these cell lines, we identified cell surface markers that distinguished two subpopulations and used flow cytometry to sort these two clones. We identified substantial proportions of replicating cells in each cell line, assigned these cells to subclones detected among the G0/G1 population and used the proportion of replicating cells per subclone as a surrogate of each subclone's growth rate.

scholarly journals Megakaryocytic cell line-specific hyperploidy by cytotoxic necrotizing factor bacterial toxins

Blood ◽  
1996 ◽  
Vol 88 (9) ◽  
pp. 3465-3473 ◽  
Author(s):  
KM Hudson ◽  
NC Denko ◽  
E Schwab ◽  
E Oswald ◽  
A Weiss ◽  
...  
Keyword(s):  
Cell Line ◽  
Cell Lines ◽  
Phorbol Ester ◽  
Dna Content ◽  
Nuclear Dna ◽  
Nuclear Dna Content ◽  
Adherent Cell ◽  
Target Cells ◽  
Suspension Cells ◽  
Cytotoxic Necrotizing Factor

Cytotoxic necrotizing factor (CNF) toxins, isolated from certain Escherichia coli strains known to cause intestinal and extra intestinal infections, induce reorganization of the actin cytoskeleton and generate hyperploidy in adherent cell lines. We have examined the effect of CNF toxin on one of the few cell types that naturally increase nuclear DNA content, megakaryocytes. Our studies show that only hematopoietic cells capable of differentiating along the megakaryocyte lineage responded to the CNF2 toxin by becoming polyploid and by reorganizing actin. The K562, HEL, and CHRF-288–11 cell lines can be induced with phorbol ester to differentiate along the megakaryocyte lineage, and these cells also respond to the toxin with increased DNA content and actin cytoskeletal rearrangements. Interestingly, treatment of the K562 and HEL cell lines with CNF2 does not result in an increase in production of the megakaryocytic marker glycoprotein IIIa, unlike phorbol ester treatment. Conversely, two T-cell leukemic cell lines, CEM and Molt4, and the promyelocytic HL-60 cell line, which do not differentiate along the megakaryocyte lineage in response to phorbol myristate acetate, do not respond to CNF2, by increased expression of gpIIIa, increased nuclear DNA content, or actin reorganization. A potential target of these toxins, RhoA, is expressed by both megakaryocytic and nonmegakaryocytic cell lines, as shown by reverse transcription-polymerase chain reaction and Western blot. Although it is clear that the CNF toxins can affect a wide variety of adherent nonhematopoietic cell lines, we propose that the response to CNF, in terms of reorganizing actin structure and increase in DNA content in hematologic suspension cells, correlates with the capability of these target cells to differentiate along the megakaryocytic lineage.

Enhancement of stress-induced apoptosis in B-lineage cells by caspase-9 inhibitor

Blood ◽  
2004 ◽  
Vol 104 (9) ◽  
pp. 2873-2878 ◽  
Author(s):  
Nisha Shah ◽  
Rebecca J. Asch ◽  
Alana S. Lysholm ◽  
Tucker W. LeBien
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Cell Lines ◽  
Lymphoblastic Leukemia ◽  
Leukemia Cell ◽  
Leukemic Cell ◽  
Adherent Cell ◽  
Cell Contact ◽  
Caspase 9 ◽  
B Lineage ◽  
B Lineage Cells

Abstract We have established human B-lineage (BLIN) acute lymphoblastic leukemia cell lines that retain a dependency on fibroblast monolayers for survival and proliferation. Eight hours following removal from adherent cell contact BLIN cells undergo a decrease in mitochondrial transmembrane potential and an increase in annexin V binding. Unexpectedly, the caspase-9 inhibitor (C9i) benzyloxycarbonyl-Leu-Glu-His-Asp-fluoromethylketone enhanced the appearance of apoptotic cells within 8 hours following removal of BLIN cells from fibroblast monolayers. C9i enhancement of apoptosis was dose dependent and did not occur with irreversible inhibitors of caspases-2, -3, -6, and -8. C9i also enhanced apoptosis in cord blood-derived CD19+ B-lineage cells (but not myeloid cells) removed from murine stromal cells. Longer exposure (> 18 hours) to C9i culminated in apoptosis in a panel of B-lineage acute lymphoblastic leukemia (ALL) cell lines in the presence or absence of fibroblast monolayers, as well as in 2 proliferating leukemic cell lines (RAMOS and CEM). BLIN-4L cells made deficient in caspase-9 by RNA interference exhibited no resistance to apoptotic signals and actually showed increased apoptotic sensitivity to staurosporine. These collective results suggest that a 4-amino acid caspase inhibitor of caspase-9 can promote apoptosis and that at least some types of apoptotic pathways in B-lineage ALL do not require caspase-9.

Procedures to test for the serum-free cultivation of adherent cell lines on microcarriers

1983 ◽  
Vol 8 (4) ◽  
pp. 161-165 ◽  
Author(s):  
Berthold G. D. Bödeker ◽  
Guy J. Berg ◽  
Guy Hewlett ◽  
H. Dieter Schlumberger
Keyword(s):  
Cell Lines ◽  
Adherent Cell ◽  
Serum Free

scholarly journals Clonal analysis of the late stages of erythroleukemia induced by two distinct strains of Friend leukemia virus.

1981 ◽  
Vol 1 (8) ◽  
pp. 721-730 ◽  
Author(s):  
D Mager ◽  
M E MacDonald ◽  
I B Robson ◽  
T W Mak ◽  
A Bernstein
Keyword(s):  
Progenitor Cells ◽  
Cell Lines ◽  
Single Cells ◽  
Leukemia Virus ◽  
Significant Proportion ◽  
Erythroid Progenitor ◽  
Self Renewal ◽  
Friend Leukemia ◽  
P Colonies ◽  
Friend Leukemia Virus

We observed striking differences between the tumorigenic colony-forming cells present in the spleens of mice late after infection with the anemia-inducing strain of Friend leukemia virus (strain FV-A) and those present after infection with the polycythemia-inducing strain (strain FV-P). Cells within primary colonies derived from FV-A- and FV-P-transformed cells (CFU-FV-A and CFU-FV-P, respectively) contained hemoglobin and spectrin, indicating that the CFU-FV-A and CFU-FV-P were transformed erythroid progenitor cells. The proportion of cells containing hemoglobin was relatively high (> 25%) in newly isolated cell lines derived from CFU-FV-P colonies, whereas cell lines derived from CFU-FV-A colonies had only low levels (0 to 2%) of hemoglobin-containing cells. A high proportion of the cell lines derived from CFU-FV-A colonies responded to pure erythropoietin and accumulated spectrin and hemoglobin, whereas the cell lines derived from CFU-FV-P colonies did not. A cytogenetic analysis indicated that primary CFU-FV-P colony cells were diploid, whereas chromosomal aberrations were observed in the immediate progeny of CFU-FV-A. The presence of unique chromosomal markers in the majority of the cells within individual colonies derived from CFU-FV-A suggested that these colonies originated from single cells. Finally, leukemic progenitor cells transformed by strain FV-A appeared to have an extensive capacity to self-renew (i.e., form secondary colonies in methylcellulose), whereas a significant proportion of the corresponding cells transformed by strain FV-P did not. In addition, the self-renewal capacity of both CFU-FV-A and CFU-FV-P increased as the disease progressed. From these observations, we propose a model for the multistage nature of Friend disease; this model involves clonal evolution and expansion from a differentiating population with limited proliferative capacity to a population with a high capacity for self-renewal and proliferation.

Characterisation of four merkel cell carcinoma adherent cell lines

1995 ◽  
Vol 60 (1) ◽  
pp. 100-107 ◽  
Author(s):  
J. Helen Leonard ◽  
Peter Dash ◽  
Peter Holland ◽  
John H. Kearsley ◽  
John R. Bell
Keyword(s):  
Cell Carcinoma ◽  
Cell Lines ◽  
Merkel Cell Carcinoma ◽  
Adherent Cell ◽  
Merkel Cell

scholarly journals Scattome: A Single-Cell Analysis of Targeted Transcriptome Program to Predict Drug Sensitivity of Single Cells within Human Myeloma Tumors

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4249-4249
Author(s):  
Amit Kumar Mitra ◽  
Ujjal Mukherjee ◽  
Taylor Harding ◽  
Holly Stessman ◽  
Ying Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Lines ◽  
Research Funding ◽  
Drug Response ◽  
Drug Sensitivity ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Pcr Analysis ◽  
Cell Analysis

Abstract Multiple myeloma (MM) is characterized by significant genetic diversity at subclonal levels that likely plays a defining role in the heterogeneity of tumor progression, clinical aggressiveness and drug sensitivity. Such heterogeneity is a driving factor in the evolution of MM, from founder clones through outgrowth of subclonal fractions. DNA Sequencing studies on MM samples have indeed demonstrated such heterogeneity in subclonal architecture at diagnosis based on recurrent mutations in pathologically relevant genes that may ultimately to lead to relapse. However, no study so far has reported a predictive gene expression signature that can identify, distinguish and quantify drug sensitive and drug-resistant subpopulations within a bulk population of myeloma cells. In recent years, our laboratory has successfully developed a gene expression profile (GEP)-based signature that could not only distinguish drug response of MM cell lines, but also was effective in stratifying patient outcomes when applied to GEP profiles from MM clinical trials using proteasome inhibitors (PI) as chemotherapeutic agents. Further, we noted myeloma cell lines that responded to the drug often contained residual sub-population of cells that did not respond, and likely were selectively propagated during drug treatment in vitro, and in patients. In this study, we performed targeted qRT-PCR analysis of single cells using a gene panel that included PI sensitivity genes and gene signatures that could discriminate between low and high-risk myeloma followed by intensive bioinformatics and statistical analysis for the classification and prediction of PI response in individual cells within bulk multiple myeloma tumors. Fluidigm's C1 Single-Cell Auto Prep System was used to perform automated single-cell capture, processing and cDNA synthesis on 576 pre-treatment cells from 12 cell lines representing a wide range of PI-sensitivity and 370 cells from 7 patient samples undergoing PI treatment followed by targeted gene expression profiling of single cells using automated, high-throughput on-chip qRT-PCR analysis using 96.96 Dynamic Array IFCs on the BioMark HD System. Probability of resistance for each individual cell was predicted using a pipeline that employed the machine learning methods Random Forest, Support Vector Machine (radial and sigmoidal), LASSO and kNN (k Nearest Neighbor) for making single-cell GEP data-driven predictions/ decisions. The weighted probabilities from each of the algorithms were used to quantify resistance of each individual cell and plotted using Ensemble forecasting algorithm. Using our drug response GEP signature at the single cell level, we could successfully identify distinct subpopulations of tumor cells that were predicted to be sensitive or resistant to PIs. Subsequently, we developed a R Statistical analysis package (http://cran.r-project.org), SCATTome (Single Cell Analysis of Targeted Transcriptome), that can restructure data obtained from Fluidigm qPCR analysis run, filter missing data, perform scaling of filtered data, build classification models and successfully predict drug response of individual cells and classify each cell's probability of response based on the targeted transcriptome. We will present the program output as graphical displays of single cell response probabilities. This package provides a novel classification method that has the potential to predict subclonal response to a variety of therapeutic agents. Disclosures Kumar: Skyline: Consultancy, Honoraria; BMS: Consultancy; Onyx: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

scholarly journals Human Plasma-Derived 3D Cultures Model Breast Cancer Treatment Responses and Predict Clinically Effective Drug Treatment Concentrations

Cancers ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1722 ◽  
Author(s):  
Kristin Calar ◽  
Simona Plesselova ◽  
Somshuvra Bhattacharya ◽  
Megan Jorgensen ◽  
Pilar de la Puente
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Human Plasma ◽  
Cell Lines ◽  
Single Cells ◽  
3D Culture ◽  
3D Models ◽  
Preclinical Models ◽  
Culture Model ◽  
3D Culture Model

Lack of efficacy and a low overall success rate of phase I-II clinical trials are the most common failures when it comes to advancing cancer treatment. Current drug sensitivity screenings present several challenges including differences in cell growth rates, the inconsistent use of drug metrics, and the lack of translatability. Here, we present a patient-derived 3D culture model to overcome these limitations in breast cancer (BCa). The human plasma-derived 3D culture model (HuP3D) utilizes patient plasma as the matrix, where BCa cell lines and primary BCa biopsies were grown and screened for drug treatments. Several drug metrics were evaluated from relative cell count and growth rate curves. Correlations between HuP3D metrics, established preclinical models, and clinical effective concentrations in patients were determined. HuP3D efficiently supported the growth and expansion of BCa cell lines and primary breast cancer tumors as both organoids and single cells. Significant and strong correlations between clinical effective concentrations in patients were found for eight out of ten metrics for HuP3D, while a very poor positive correlation and a moderate correlation was found for 2D models and other 3D models, respectively. HuP3D is a feasible and efficacious platform for supporting the growth and expansion of BCa, allowing high-throughput drug screening and predicting clinically effective therapies better than current preclinical models.

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