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

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

doi:10.1186/s12915-017-0383-5

Cited by 206 publications

(202 citation statements)

References 27 publications

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“…1a). Cells were directly sorted into methanol for fixation 18 , and further processed to profile their transcriptomes by a high-throughput droplet-based approach (Drop-Seq) 19 . In total, 26 single-cell RNA libraries were generated from 12 control and 14 double-mutant (tumor-bearing) salivary glands of either female or male mice from an early and a late tumor stage at postnatal days 40 (P40) and 90 (P90), respectively ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Monodisperse droplets of about 1 nl in size were generated using microfluidic PDMS devices (Drop-SEQ chips, FlowJEM, Toronto, Canada; pre-coated with Aquapel). Barcoded microparticles (Barcoded Beads SeqB; ChemGenes Corp., Wilmington, MA, USA) were prepared and flowed in using a self-built Drop-seq set up 19 (Online-Dropseq-Protocol-v.3.1: http://mccarrolllab.com/dropseq/) as previously described 18 . Cell preparations and reagents were kept on ice and handled in the cold.…”

Section: Methodsmentioning

confidence: 99%

“…Cell preparations and reagents were kept on ice and handled in the cold. Methanolfixed cells 18 were centrifuged at 3000-5000 × g for 5 min, rehydrated in 1 ml PBS + 0.01% BSA supplemented with RNAse inhibitors (1 unit/μl RiboLock, Thermo-Fisher), pelleted and resuspended again in 0.5 ml PBS + 0.01% BSA in the presence of RNAse inhibitors. Cells were manually counted by means of a hemocytometer and diluted to a suspension of typically~50-100 cells/μl in PBS + 0.01% BSA.…”

Section: Methodsmentioning

confidence: 99%

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Tracing tumorigenesis in a solid tumor model at single-cell resolution

et al. 2020

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Characterizing the complex composition of solid tumors is fundamental for understanding tumor initiation, progression and metastasis. While patient-derived samples provide valuable insight, they are heterogeneous on multiple molecular levels, and often originate from advanced tumor stages. Here, we use single-cell transcriptome and epitope profiling together with pathway and lineage analyses to study tumorigenesis from a developmental perspective in a mouse model of salivary gland squamous cell carcinoma. We provide a comprehensive cell atlas and characterize tumor-specific cells. We find that these cells are connected along a reproducible developmental trajectory: initiated in basal cells exhibiting an epithelial-tomesenchymal transition signature, tumorigenesis proceeds through Wnt-differential cancer stem cell-like subpopulations before differentiating into luminal-like cells. Our work provides unbiased insights into tumor-specific cellular identities in a whole tissue environment, and emphasizes the power of using defined genetic model systems.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Tracing tumorigenesis in a solid tumor model at single-cell resolution

et al. 2020

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“…Another very recent advance is the ability to methanol fix and freeze dissociated cells, followed by rehydration and DropSeq analysis. 54 Methanol fixation is compatible both with library preparation and next generation RNA-sequencing. 55 This approach will greatly simplify the workflow for analyzing kidney biopsies and even enable the creation of biobanks of fixed kidney samples (the tissue must be dissociated before fixation however) that can be processed for scRNA-seq at a later date, for example after the pathologic diagnosis is known.…”

Section: Challenges To Overcome and Future Technological Developmentmentioning

confidence: 99%

The promise of single-cell RNA sequencing for kidney disease investigation

Humphreys

2017

Kidney International

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New techniques for single cell RNA sequencing (scRNA-seq) at high throughput are leading to profound new discoveries in biology. The ability to generate vast amounts of transcriptomic data at cellular resolution represents a transformative advance allowing the identification of novel cell types, states and dynamics. In this review, we summarize the development of scRNA-seq methodologies and highlight their advantages and drawbacks. We discuss available software tools for analyzing scRNA-Seq data and summarize current computational challenges. Finally, we outline ways in which this powerful technology might be applied to discovery research in kidney development and disease.

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“…Fortunately, many platforms are compatible with cell fixation and storage protocols. Transcriptomic programs obtained from these cells seem similar to those of freshly processed cells [53,54] (Figure 2).…”

Section: Limitations Of Single-cell Technologies In Human Cancermentioning

confidence: 62%

Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies

2020

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Effective cancer treatment has been precluded by the presence of various forms of intratumoral complexity that drive treatment resistance and metastasis. Recent single-cell sequencing technologies are significantly facilitating the characterization of tumor internal architecture during disease progression. New applications and advances occurring at a fast pace predict an imminent broad application of these technologies in many research areas. As occurred with next-generation sequencing (NGS) technologies, once applied to clinical samples across tumor types, single-cell sequencing technologies could trigger an exponential increase in knowledge of the molecular pathways involved in cancer progression and contribute to the improvement of cancer treatment. Multifaceted Heterogeneity and Its Impact on Cancer ProgressionTumors comprise various cell populations in constant evolution. Some of this complex heterogeneity derives from genetic diversification and Darwinian selection of tumor cells as they adapt to variable environments. Next-generation sequencing (NGS; see Glossary) used for the past decade had enough sensitivity to detect mutations present in minor cell populations and, combined with multisampling of human tumors (multisampling sequencing), fostered many studies that characterized intratumor heterogeneity in various cancers [1]. The level of intratumor heterogeneity is considered a main driver of therapy resistance and metastasis and is associated with poor prognosis [2].In addition, human cancers frequently have tumor cell populations with different transcriptional programs. This functional diversity is likely associated with the genetic heterogeneity described above but is also the result of many other factors. First, the presence of a hierarchical structure, where a group of quiescent stem-like cells fosters the growth of a tumor comprising cells in different differentiation states, was demonstrated in various tumor types [3]. Additionally, different transcriptional programs can be activated in tumor cells as a response to stochastic factors or to a variable tumor microenvironment. This functional diversity provides tumors with a plasticity that grants a high capacity for adaptation [4].Finally, human tumors comprise not only malignant/transformed cells but also a plethora of different cell types recruited from the surrounding tissue and the immune system. The tumor microenvironment shows also genetic and transcriptional diversity and plays important roles in tumor progression, metastasis, and treatment resistance [1,5].Fine characterization of these levels of tumor heterogeneity is essential to the successful treatment of cancer patients. The recent development of technologies based on sequencing individual cells (single-cell sequencing technologies) opens new ways for the characterization of tumor heterogeneity. At the genetic level, single-cell DNA-seq technologies offer higher sensitivity in the detection of minority clones, the reconstruction of clone structure, and the identification of concurrent ...

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

Cited by 206 publications

References 27 publications

Tracing tumorigenesis in a solid tumor model at single-cell resolution

Tracing tumorigenesis in a solid tumor model at single-cell resolution

The promise of single-cell RNA sequencing for kidney disease investigation

Tumor Functional Heterogeneity Unraveled by scRNA-seq Technologies

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