Opto-magnetic capture of individual cells based on visual phenotypes
- Maisonneuve-Rosemont Hospital, Canada
Abstract
The ability to isolate rare live cells within a heterogeneous population based solely on visual criteria remains technically challenging, due largely to limitations imposed by existing sorting technologies. Here we present a new method that permits labeling cells of interest by attaching streptavidin-coated magnetic beads to their membranes using the lasers of a confocal microscope. A simple magnet allows highly-specific isolation of the labeled cells, which then remain viable and proliferate normally. As proof of principle, we tagged, isolated, and expanded individual cells based on three biologically-relevant visual characteristics: i) presence of multiple nuclei, ii) accumulation of lipid vesicles, and iii) ability to resolve ionizing radiation-induced DNA damage foci. Our method constitutes a rapid, efficient, and cost-effective approach for isolation and subsequent characterization of rare cells based on observable traits such as movement, shape, or location, which in turn can generate novel mechanistic insights into important biological processes.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files
Article and author information
Author details
Jean François Lemay
Santiago Costantino
Funding
Canadian Institutes of Health Research
- El Bachir Affar
- Elliot Drobetsky
- Hugo Wurtele
Natural Sciences and Engineering Research Council of Canada
- El Bachir Affar
- Elliot Drobetsky
- Hugo Wurtele
- Santiago Costantino
Genome Canada
- Santiago Costantino
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Binan et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Opto-magnetic capture of individual cells based on visual phenotypes
eLife 8:e45239.
https://doi.org/10.7554/eLife.45239
Further reading
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- Cancer Biology
- Immunology and Inflammation
In this study, we present a proof-of-concept classical vaccination experiment that validates the in silico identification of tumor neoantigens (TNAs) using a machine learning-based platform called NAP-CNB. Unlike other TNA predictors, NAP-CNB leverages RNA-seq data to consider the relative expression of neoantigens in tumors. Our experiments show the efficacy of NAP-CNB. Predicted TNAs elicited potent antitumor responses in mice following classical vaccination protocols. Notably, optimal antitumor activity was observed when targeting the antigen with higher expression in the tumor, which was not the most immunogenic. Additionally, the vaccination combining different neoantigens resulted in vastly improved responses compared to each one individually, showing the worth of multiantigen-based approaches. These findings validate NAP-CNB as an innovative TNA identification platform and make a substantial contribution to advancing the next generation of personalized immunotherapies.
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- Cancer Biology
Background:
Cervical adenocarcinoma (ADC) is more aggressive compared to other types of cervical cancer (CC), such as squamous cell carcinoma (SCC). The tumor immune microenvironment (TIME) and tumor heterogeneity are recognized as pivotal factors in cancer progression and therapy. However, the disparities in TIME and heterogeneity between ADC and SCC are poorly understood.
Methods:
We performed single-cell RNA sequencing on 11 samples of ADC tumor tissues, with other 4 SCC samples served as controls. The immunochemistry and multiplexed immunofluorescence were conducted to validate our findings.
Results:
Compared to SCC, ADC exhibited unique enrichments in several sub-clusters of epithelial cells with elevated stemness and hyper-malignant features, including the Epi_10_CYSTM1 cluster. ADC displayed a highly immunosuppressive environment characterized by the enrichment of regulatory T cells (Tregs) and tumor-promoting neutrophils. The Epi_10_CYSTM1 cluster recruits Tregs via ALCAM-CD6 signaling, while Tregs reciprocally induce stemness in the Epi_10_CYSTM1 cluster through TGFβ signaling. Importantly, our study revealed that the Epi_10_CYSTM1 cluster could serve as a valuable predictor of lymph node metastasis for CC patients.
Conclusions:
This study highlights the significance of ADC-specific cell clusters in establishing a highly immunosuppressive microenvironment, ultimately contributing to the heightened aggressiveness and poorer prognosis of ADC compared to SCC.
Funding:
Funded by the National Natural Science Foundation of China (82002753; 82072882; 81500475) and the Natural Science Foundation of Hunan Province (2021JJ40324; 2022JJ70103).
