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Cell fixation and preservation for droplet-based single-cell transcriptomics

Overview of attention for article published in BMC Biology, May 2017
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Title
Cell fixation and preservation for droplet-based single-cell transcriptomics
Published in
BMC Biology, May 2017
DOI 10.1186/s12915-017-0383-5
Pubmed ID
Authors

Jonathan Alles, Nikos Karaiskos, Samantha D. Praktiknjo, Stefanie Grosswendt, Philipp Wahle, Pierre-Louis Ruffault, Salah Ayoub, Luisa Schreyer, Anastasiya Boltengagen, Carmen Birchmeier, Robert Zinzen, Christine Kocks, Nikolaus Rajewsky

Abstract

Recent developments in droplet-based microfluidics allow the transcriptional profiling of thousands of individual cells in a quantitative, highly parallel and cost-effective way. A critical, often limiting step is the preparation of cells in an unperturbed state, not altered by stress or ageing. Other challenges are rare cells that need to be collected over several days or samples prepared at different times or locations. Here, we used chemical fixation to address these problems. Methanol fixation allowed us to stabilise and preserve dissociated cells for weeks without compromising single-cell RNA sequencing data. By using mixtures of fixed, cultured human and mouse cells, we first showed that individual transcriptomes could be confidently assigned to one of the two species. Single-cell gene expression from live and fixed samples correlated well with bulk mRNA-seq data. We then applied methanol fixation to transcriptionally profile primary cells from dissociated, complex tissues. Low RNA content cells from Drosophila embryos, as well as mouse hindbrain and cerebellum cells prepared by fluorescence-activated cell sorting, were successfully analysed after fixation, storage and single-cell droplet RNA-seq. We were able to identify diverse cell populations, including neuronal subtypes. As an additional resource, we provide 'dropbead', an R package for exploratory data analysis, visualization and filtering of Drop-seq data. We expect that the availability of a simple cell fixation method will open up many new opportunities in diverse biological contexts to analyse transcriptional dynamics at single-cell resolution.

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Geographical breakdown

Country Count As %
United States 3 <1%
Israel 1 <1%
Sweden 1 <1%
Unknown 673 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 150 22%
Researcher 145 21%
Student > Bachelor 55 8%
Student > Master 51 8%
Student > Doctoral Student 32 5%
Other 102 15%
Unknown 143 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 202 30%
Agricultural and Biological Sciences 134 20%
Medicine and Dentistry 40 6%
Neuroscience 39 6%
Immunology and Microbiology 36 5%
Other 64 9%
Unknown 163 24%