Dataset Information

An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples.

ABSTRACT: Establishing clinically relevant single-cell (SC) transcriptomic workflows from cryopreserved tissue is essential to move this emerging immune monitoring technology from the bench to the bedside. Improper sample preparation leads to detrimental cascades, resulting in loss of precious time, money and finally compromised data. There is an urgent need to establish protocols specifically designed to overcome the inevitable variations in sample quality resulting from uncontrollable factors in a clinical setting. Here, we explore sample preparation techniques relevant to a range of clinically relevant scenarios, where SC gene expression and repertoire analysis are applied to a cryopreserved sample derived from a small amount of blood, with unknown or partially known preservation history. We compare a total of ten cell-counting, viability-improvement, and lymphocyte-enrichment methods to highlight a number of unexpected findings. Trypan blue-based automated counters, typically recommended for single-cell sample quantitation, consistently overestimate viability. Advanced sample clean-up procedures significantly impact total cell yield, while only modestly increasing viability. Finally, while pre-enrichment of B cells from whole peripheral blood mononuclear cells (PBMCs) results in the most reliable BCR repertoire data, comparable T-cell enrichment strategies distort the ratio of CD4+ and CD8+ cells. Furthermore, we provide high-resolution analysis of gene expression and clonotype repertoire of different B cell subtypes. Together these observations provide both qualitative and quantitative sample preparation guidelines that increase the chances of obtaining high-quality single-cell transcriptomic and repertoire data from human PBMCs in a variety of clinical settings.

SUBMITTER: Hanamsagar R

PROVIDER: S-EPMC7010687 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples.

Hanamsagar Richa R Reizis Timothy T Chamberlain Mathew M Marcus Robert R Nestle Frank O FO de Rinaldis Emanuele E Savova Virginia V

Scientific reports 20200210 1

Establishing clinically relevant single-cell (SC) transcriptomic workflows from cryopreserved tissue is essential to move this emerging immune monitoring technology from the bench to the bedside. Improper sample preparation leads to detrimental cascades, resulting in loss of precious time, money and finally compromised data. There is an urgent need to establish protocols specifically designed to overcome the inevitable variations in sample quality resulting from uncontrollable factors in a clini ...[more]

PMID: 32042039

Similar Datasets

Project description:BackgroundMost diversity in the eukaryotic tree of life is represented by microbial eukaryotes, which is a polyphyletic group also referred to as protists. Among the protists, currently sequenced genomes and transcriptomes give a biased view of the actual diversity. This biased view is partly caused by the scientific community, which has prioritized certain microbes of biomedical and agricultural importance. Additionally, some protists remain difficult to maintain in cultures, which further influences what has been studied. It is now possible to bypass the time-consuming process of cultivation and directly analyze the gene content of single protist cells. Single-cell genomics was used in the first experiments where individual protists cells were genomically explored. Unfortunately, single-cell genomics for protists is often associated with low genome recovery and the assembly process can be complicated because of repetitive intergenic regions. Sequencing repetitive sequences can be avoided if single-cell transcriptomics is used, which only targets the part of the genome that is transcribed.ResultsIn this study we test different modifications of Smart-seq2, a single-cell RNA sequencing protocol originally developed for mammalian cells, to establish a robust and more cost-efficient workflow for protists. The diplomonad Giardia intestinalis was used in all experiments and the available genome for this species allowed us to benchmark our results. We could observe increased transcript recovery when freeze-thaw cycles were added as an extra step to the Smart-seq2 protocol. Further we reduced the reaction volume and purified the amplified cDNA with alternative beads to test different cost-reducing changes of Smart-seq2. Neither improved the procedure, and reducing the volumes by half led to significantly fewer genes detected. We also added a 5' biotin modification to our primers and reduced the concentration of oligo-dT, to potentially reduce generation of artifacts. Except adding freeze-thaw cycles and reducing the volume, no other modifications lead to a significant change in gene detection. Therefore, we suggest adding freeze-thaw cycles to Smart-seq2 when working with protists and further consider our other modification described to improve cost and time-efficiency.ConclusionsThe presented single-cell RNA sequencing workflow represents an efficient method to explore the diversity and cell biology of individual protist cells.

Dataset Information

An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples.

Publications

An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets