Evidence map›Paper›PMID 37527243›Full record

ArticlePloS one2023

High throughput isolation of RNA from single-cells within an intact tissue for spatial and temporal sequencing a reality.

John Stanley, Akshar Lohith, Lucca Debiaso, Kevan Wang, Minh Ton, Wenwu Cui, Weiwei Gu, Aihua Fu, Nader Pourmand

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

9 authors.

John StanleyDepartment of Biomolecular Engineering, University of California, Santa Cruz, California, United States of America.ORCID 0000-0003-2355-8800
Akshar LohithDepartment of Biomolecular Engineering, University of California, Santa Cruz, California, United States of America.ORCID 0000-0001-7523-5259
Lucca DebiasoDepartment of Biomolecular Engineering, University of California, Santa Cruz, California, United States of America.ORCID 0000-0002-9747-5111
Kevan WangNVIGEN Inc, Campbell, California, United States of America.
Minh TonNVIGEN Inc, Campbell, California, United States of America.
Wenwu CuiNVIGEN Inc, Campbell, California, United States of America.
Weiwei GuNVIGEN Inc, Campbell, California, United States of America.
Aihua FuNVIGEN Inc, Campbell, California, United States of America.
Nader PourmandDepartment of Biomolecular Engineering, University of California, Santa Cruz, California, United States of America.ORCID 0000-0003-0251-9060

Funding

Topic 353: Highly Accurate Low Cost ctDNA Diagnostics with Magnetic Nanoparticle Enabled Automated Sample Prep - Moonshot75N91019C00035 · NCI · NVIGEN, INC. · PI FU, AIHUA · 2019 to 2019
$2.0M
SBIR TOPIC 403: HIGHLY ACCURATE SINGLE CELL SEQUENCING WITH SPATIAL RESOLUTION ENABLED BY NANOGENOMICS FORCANCER RESEARCH75N91020C00052 · NCI · NVIGEN, INC. · PI FU, AIHUA · 2020 to 2021
$455k
NCI NIH HHS 75N91019C00035NCI NIH HHS 75N91020C00052
6 · The paper itself

Abstract

Single-cell transcriptomics is essential for understanding biological variability among cells in a heterogenous population. Acquiring high-quality single-cell sequencing data from a tissue sample has multiple challenges including isolation of individual cells as well as amplification of the genetic material. Commercially available techniques require the isolation of individual cells from a tissue through extensive manual manipulation before single cell sequence data can be acquired. However, since cells within a tissue have different dissociation constants, enzymatic and mechanical manipulation do not guarantee the isolation of a homogenous population of cells. To overcome this drawback, in this research we have developed a revolutionary approach that utilizes a fully automated nanopipette technology in combination with magnetic nanoparticles to obtain high quality sequencing reads from individual cells within an intact tissue thereby eliminating the need for manual manipulation and single cell isolation. With the proposed technology, it is possible to sample an individual cell within the tissue multiple times to obtain longitudinal information. Single-cell RNAseq was achieved by aspirating only1-5% of sub-single-cell RNA content from individual cells within fresh frozen tissue samples. As a proof of concept, aspiration was carried out from 22 cells within a breast cancer tissue slice using quartz nanopipettes. The mRNA from the aspirate was then selectively captured using magnetic nanoparticles. The RNAseq data from aspiration of 22 individual cells provided high alignment rates (80%) with 2 control tissue samples. The technology is exceptionally simple, quick and efficient as the entire cell targeting and aspiration process is fully automated.

Indexed as

Gene Expression ProfilingRNACell SeparationHigh-Throughput Nucleotide SequencingRNA, MessengerSequence Analysis, RNASingle-Cell AnalysisRNARNA, Messenger

Identifiers

PMID37527243
PMCPMC10393160

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.