scholarly journals Development of a Serial Dilution Technique for Obtaining Monoclonal Cell Populations

2021 ◽  
Author(s):  
Maryam Ranjbar ◽  
Marjan Nourigorji ◽  
Farshid Amiri ◽  
Hossein Jafari Khamirani ◽  
Sina Zoghi ◽  
...  

Abstract Single cell-based techniques have drawn the attention of researchers, because they provide invaluable information of various domains ranging from genomics to epigenetics, transcriptomics, and proteomics. Single cell-derived clones provide a reliable and sustainable source of genetic information due to the homogeneity of the cell population. Aiming to obtain single-cell clones, several approaches were engineered, among which, the Limiting dilution approach stands out as a cost-effective and unsophisticated, and easy-to-apply method. Here, we demonstrate how to acquire single cell-derived clones through a simple 1:10 diluting from genetically modified heterogeneous cell populations.

2018 ◽  
Author(s):  
Jase Gehring ◽  
Jong Hwee Park ◽  
Sisi Chen ◽  
Matthew Thomson ◽  
Lior Pachter

AbstractWe describe a universal sample multiplexing method for single-cell RNA-seq in which cells are chemically labeled with identifying DNA oligonucleotides. Analysis of a 96-plex perturbation experiment revealed changes in cell population structure and transcriptional states that cannot be discerned from bulk measurements, establishing a cost effective means to survey cell populations from large experiments and clinical samples with the depth and resolution of single-cell RNA-seq.


Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 3503-3503
Author(s):  
Matthias Ritgen ◽  
Monika Brueggemann ◽  
Sebastian Boettcher ◽  
Thorsten Raff ◽  
Christiane Pott ◽  
...  

Abstract Allogeneic stem cell transplantation (SCT) is the only known curative treatment for high-risk CLL. We have recently shown that minimal residual disease (MRD) monitoring can identify patients with graft versus leukemia (GvL)-induced disease response to either reduction of immunosuppression (IS) or to administration of donor lymphocyte infusions (DLI), suggesting that those patients are potentially cured by an ongoing immunologic antileukemic effect induced by donor immune cells (Leukemia 22:1377). It is uncertain, however, which cell population maintains this process; although T as well as NK-cell mediated effects are discussed. The present study addressed the question whether disease response upon immunomodulation after SCT is associated with the occurrence of dominant T cell clones. Methods: 32 patients allografted for high-risk CLL who had MRD follow-up by clone-specific PCR or MRD-flow available were included in this investigation. We used the BIOMED T-cell receptor multiplex PCRs (TCR-PCR) to search for T cell clones which might be involved in the documented GVL effects. TCR rearrangements were sequenced and analyzed using the IMGT database. Results: 16 of 32 patients showed MRD response after IS reduction or DLI. GVL-induced MRD clearance was associated with onset of chronic GVHD in almost all instances. Twenty-four different dominant TCR rearrangements could be identified in 15/32 patients by BIMOD TCR-PCR. Most of the T cell populations show rearranged gamma/delta TCRs suggesting that regulatory gamma/delta T cells might be involved in this process. TCR sequences employed were TRGV9 (13), TRGV2 (2) and TRGV1, TRGV4, TRGV8, TRGV10, TRGV11, TRBV5, TRBV6, TRBV12, TRBV15. In 4 patients with a potential productive TCR rearrangement (TRGV4+TRDV1, TRBV6, TRGV2, TRGV11+TRGV9) we were able to design a TCR-specific real-time PCR for quantitative follow-up of this clonal T cell population. This data was compared to flow cytometric monitoring of T-cell subpopulations and MRD kinetics post SCT. In those 4 patients we could demonstrate an inverse correlation of the kinetics of MRD and the kinetics of clonal T cell expansions. T cell clones emerging during this phase remained on a stable level throughout the whole follow-up in patients showing durable MRD negativity. Conclusion: In CLL, MRD clearance after SCT is correlated to the emergence of dominant T cell clones, suggesting that GVL activity is based on allo- or CLL-specific T cell expansion. Further studies are needed to clarify the role of these T cell clones for GVL and GVHD development.


1982 ◽  
Vol 88 (2) ◽  
pp. 335-350 ◽  
Author(s):  
R. S. Tedder ◽  
J. L. Yao ◽  
M. J. Anderson

SummaryMice were immunized by three intraperitoneal and one intravenous injection of rubella haemagglutinin. Splenocytes from these mice were fused with the cells of a syngeneic myeloma cell line, and following culture for various periods of time, single-cell clones were derived by the technique of limiting dilution.A total of 139 clones were derived from 13 parent hybrid cultures. To date, four of these cloned cultures have been propagated as ascitic tumours in mice. The preparation of IgG from ascitic fluid and labelling of this antibody with 125I is described. Results indicate that the use of labelled monoclonal antibodies as indicator reagents in solid-phase IgM antibody capture assays for the detection of rubella-specific IgM results in enhanced performance of these tests.


2020 ◽  
Author(s):  
Johannes Smolander ◽  
Sini Junttila ◽  
Mikko S Venäläinen ◽  
Laura L Elo

AbstractSingle-cell RNA-seq allows researchers to identify cell populations based on unsupervised clustering of the transcriptome. However, subpopulations can have only subtle transcriptomic differences and the high dimensionality of the data makes their identification challenging. We introduce ILoReg (https://github.com/elolab/iloreg), an R package implementing a new cell population identification method that achieves high differentiation resolution through a probabilistic feature extraction step that is applied before clustering and visualization.


Author(s):  
Clint Piper ◽  
Emma Hainstock ◽  
Cheng Yin-Yuan ◽  
Yao Chen ◽  
Achia Khatun ◽  
...  

Gastrointestinal (GI) tract involvement is a major determinant for subsequent morbidity and mortality arising during graft versus host disease (GVHD). CD4+ T cells that produce GM-CSF have emerged as central mediators of inflammation in this tissue site as GM-CSF serves as a critical cytokine link between the adaptive and innate arms of the immune system. However, cellular heterogeneity within the CD4+ GM-CSF+ T cell population due to the concurrent production of other inflammatory cytokines has raised questions as to whether these cells have a common ontology or if there exists a unique CD4+ GM-CSF+ subset that differs from other defined T helper (TH) subtypes. Using single cell RNA sequencing analysis, we identified two CD4+ GM-CSF+ T cell populations that arose during GVHD and were distinguishable by the presence or absence of IFN-γ co-expression. CD4+ GM-CSF+ IFN-γ- T cells which emerged preferentially in the colon had a distinct transcriptional profile, employed unique gene regulatory networks, and possessed a non-overlapping TCR repertoire when compared to CD4+ GM-CSF+ IFN-γ+ T cells as well as all other transcriptionally defined CD4+ T cell populations in the colon. Functionally, this CD4+ GM-CSF+ T cell population contributed to pathological damage in the GI tract which was critically dependent upon signaling through the IL-7 receptor but was independent of type 1 interferon signaling. Thus, these studies help to unravel heterogeneity within CD4+ GM-CSF+ T cells that arise during GVHD and define a developmentally distinct colitogenic TH GM-CSF+ subset that mediates immunopathology.


Lab on a Chip ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 942-948
Author(s):  
Jinzhu Yu ◽  
Ki Oh ◽  
Sitapriya Moorthi ◽  
Ling Li ◽  
Helmut H. Strey ◽  
...  

We developed a simple, rapid and cost-effective enzymatic-based cytometry platform to measure intracellular signaling pathway activity. This platform may be broadly applied in single or dual parameter assays to study cell population heterogeneity.


2012 ◽  
Vol 90 (9) ◽  
pp. 1295-1301 ◽  
Author(s):  
Chris Stillwell ◽  
Fei Wang ◽  
Bo Xiang ◽  
Jixian Deng ◽  
Tarek Kashour ◽  
...  

Adipose tissue stromal fraction (ASF) contains multipotent cells capable of differentiation towards several lineages and may be used for the treatment of various degenerative diseases. However, the multipotent cells within ASF have not been fully characterized. In this study we have attempted to characterize stem cells in the ASF obtained through serial dilution. Five single-cell clones were studied. It was found that the single-cell clones exhibited slight but significant differences in proliferative capacity and differentiation potential. We conclude that ASF houses different subtypes of stem cells.


2018 ◽  
Author(s):  
Qi Liu ◽  
Charles A. Herring ◽  
Quanhu Sheng ◽  
Jie Ping ◽  
Alan J. Simmons ◽  
...  

AbstractSingle-cell RNA-sequencing (scRNA-seq) has become a powerful tool for the systematic investigation of cellular diversity. As a number of computational tools have been developed to identify and visualize cell populations within a single scRNA-seq dataset, there is a need for methods to quantitatively and statistically define proportional shifts in cell population structures across datasets, such expansion or shrinkage, or emergence or disappearance of cell populations. Here we present sc-UniFrac, a framework to statistically quantify compositional diversity in cell populations between single-cell transcriptome landscapes. sc-UniFrac enables sensitive and robust quantification in simulated and experimental datasets in terms of both population identity and quantity. We have demonstrated the utility of sc-UniFrac in multiple applications, including assessment of biological and technical replicates, classification of tissue phenotypes, identification and definition of altered cell populations, and benchmarking batch correction tools. sc-UniFrac provides a framework for quantifying diversity or alterations in cell populations across conditions, and has broad utility for gaining insight on how cell populations respond to perturbations.


2021 ◽  
Author(s):  
Massimo Andreatta ◽  
Ariel J. Berenstein ◽  
Santiago J Carmona

A common bioinformatics task in single-cell data analysis is to purify a cell type or cell population of interest from heterogeneous datasets. Here we present scGate, an algorithm that automatizes marker-based purification of specific cell populations, without requiring training data or reference gene expression profiles. scGate purifies a cell population of interest using a set of markers organized in a hierarchical structure, akin to gating strategies employed in flow cytometry. In our benchmark for blood-derived and tumor-infiltrating immune cells, scGate outperforms SingleR, a state-of-the-art classifier for single-cell data. scGate is implemented as an R package and integrated with the Seurat framework, providing an intuitive tool to isolate cell populations of interest from complex scRNA-seq datasets. Availability: R package source code and reproducible tutorials are available at https://github.com/carmonalab/scGate


Author(s):  
Johannes Smolander ◽  
Sini Junttila ◽  
Mikko S Venäläinen ◽  
Laura L Elo

Abstract Motivation Single-cell RNA-seq allows researchers to identify cell populations based on unsupervised clustering of the transcriptome. However, subpopulations can have only subtle transcriptomic differences and the high dimensionality of the data makes their identification challenging. Results We introduce ILoReg, an R package implementing a new cell population identification method that improves identification of cell populations with subtle differences through a probabilistic feature extraction step that is applied before clustering and visualization. The feature extraction is performed using a novel machine learning algorithm, called iterative clustering projection (ICP), that uses logistic regression and clustering similarity comparison to iteratively cluster data. Remarkably, ICP also manages to integrate feature selection with the clustering through L1-regularization, enabling the identification of genes that are differentially expressed between cell populations. By combining solutions of multiple ICP runs into a single consensus solution, ILoReg creates a representation that enables investigating cell populations with a high resolution. In particular, we show that the visualization of ILoReg allows segregation of immune and pancreatic cell populations in a more pronounced manner compared with current state-of-the-art methods. Availability and implementation ILoReg is available as an R package at https://bioconductor.org/packages/ILoReg. Supplementary information Supplementary data are available at Bioinformatics online.


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