Evidence map›Paper›PMID 32042039›Full record

ArticleScientific reports2020

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

Richa Hanamsagar, Timothy Reizis, Mathew Chamberlain, Robert Marcus, Frank O Nestle, Emanuele de Rinaldis, Virginia Savova

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In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Richa HanamsagarSanofi Immunology and Inflammation Research Therapeutic Area, 270 Albany St, Cambridge, MA, 02139, USA.
Timothy ReizisNew York University College of Arts and Sciences, 32 Waverly Pl, New York, NY, 10003, USA.
Mathew ChamberlainSanofi Immunology and Inflammation Research Therapeutic Area, 270 Albany St, Cambridge, MA, 02139, USA.
Robert MarcusSanofi Immunology and Inflammation Research Therapeutic Area, 270 Albany St, Cambridge, MA, 02139, USA.
Frank O NestleSanofi Immunology and Inflammation Research Therapeutic Area, 270 Albany St, Cambridge, MA, 02139, USA.
Emanuele de RinaldisSanofi Immunology and Inflammation Research Therapeutic Area, 270 Albany St, Cambridge, MA, 02139, USA.
Virginia SavovaSanofi Immunology and Inflammation Research Therapeutic Area, 270 Albany St, Cambridge, MA, 02139, USA. virginia.savova@sanofi.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

WorkflowCryopreservationGene Expression ProfilingHumansLeukocyte CountLeukocytes, MononuclearSingle-Cell AnalysisTranscriptome

Identifiers

PMID32042039
PMCPMC7010687

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.