Evidence map›Paper›PMID 34109003›Full record

ArticleCellular and molecular bioengineering2021

Optimization of a Clinically Relevant Chemical-Mechanical Tissue Dissociation Workflow for Single-Cell Analysis.

E Celeste Welch, Harry Yu, Anubhav Tripathi

Abstract read
In one paragraph

Article in Cellular and molecular bioengineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

E Celeste WelchSchool of Engineering, Center for Biomedical Engineering, Brown University, Providence, RI 02916 USA.
Harry YuSchool of Engineering, Center for Biomedical Engineering, Brown University, Providence, RI 02916 USA.
Anubhav TripathiSchool of Engineering, Center for Biomedical Engineering, Brown University, Providence, RI 02916 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWhile single-cell analysis technology has flourished, obtaining single cells from complex tissues continues to be a challenge. Current methods require multiple steps and several hours of processing. This study investigates chemical and mechanical methods for clinically relevant preparation of single-cell suspension from frozen biopsy cores of complex tissues. The developed protocol can be completed in 15 min.

methodsFrozen bovine liver biopsy cores were normalized by weight, dimension, and calculated cellular composition. Various chemical reagents were tested for their capability to dissociate the tissue via confocal microscopy, hemocytometry and quantitative flow cytometry. Images were processed using ImageJ. Quantitative flow cytometry with gating analysis was also used for the analysis of dissociation. Physical modeling simulations were conducted in COMSOL Multiphysics.

resultsA rapid method for tissue dissociation was developed for single-cell analysis techniques. The results of this study show that a combination of 1% type-1 collagenase and pronase or hyaluronidase in 100 U/µL HBSS solution is the most effective at dissociating 2.5 mm thawed bovine liver biopsy cores in 15 min, with dissociation efficiency of 37-42% and viability >90% as verified using live MDA-MB-231 cancer cells. Cellular dissociation is significantly improved by adding a controlled mechanical force during the chemical process, to dissociate 93

conclusionsUnderstanding cellular dissociation in SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s12195-021-00667-y) contains supplementary material, which is available to authorized users.

Indexed as

CancerDiagnosticsFlow cytometryScreeningSingle-cell sequencing

Identifiers

PMID34109003
PMCPMC8175683

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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.