Evidence map›Paper›PMID 31097816›Full record

ArticleNature biomedical engineering2019

Detection of unamplified target genes via CRISPR-Cas9 immobilized on a graphene field-effect transistor.

Reza Hajian, Sarah Balderston, Thanhtra Tran, Tara deBoer, Jessy Etienne, Mandeep Sandhu, Noreen A Wauford, Jing-Yi Chung, Jolie Nokes, Mitre Athaiya and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 218 papers.

0numbers the graph read from it
0cells of the map it votes in
218citing papers in PubMed
26.3field-weighted citation impact, top 1% of its field
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

218 citing papers in PubMed, 626 citations in OpenAlex.

  1. Review
  2. Article
  3. Engineering two-dimensional electronic biosensors.Nature reviews electrical engineering · 2026
    Article
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  5. Article
  6. Biophysical characterization ofSensors & diagnostics · 2026
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158 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 4 institutions in 2 countries.

Reza HajianKeck Graduate Institute, The Claremont Colleges, Claremont, CA, USA.
Sarah BalderstonKeck Graduate Institute, The Claremont Colleges, Claremont, CA, USA.
Thanhtra TranKeck Graduate Institute, The Claremont Colleges, Claremont, CA, USA.
Tara deBoerDepartment of Bioengineering, University of California, Berkeley, Berkeley, CA, USA.
Jessy EtienneDepartment of Bioengineering, University of California, Berkeley, Berkeley, CA, USA.
Mandeep SandhuKeck Graduate Institute, The Claremont Colleges, Claremont, CA, USA.
Noreen A WaufordDepartment of Bioengineering, University of California, Berkeley, Berkeley, CA, USA.
Jing-Yi ChungDepartment of Bioengineering, University of California, Berkeley, Berkeley, CA, USA.
Jolie NokesCardea Bio, San Diego, CA, USA.
Mitre AthaiyaKeck Graduate Institute, The Claremont Colleges, Claremont, CA, USA.
Jacobo ParedesTecnun, School of Engineering, University of Navarra, San Sebastián, Spain.
Regis PeytaviNanosens Innovations, San Diego, CA, USA.
Brett GoldsmithCardea Bio, San Diego, CA, USA.
Niren MurthyDepartment of Bioengineering, University of California, Berkeley, Berkeley, CA, USA.
Irina M ConboyDepartment of Bioengineering, University of California, Berkeley, Berkeley, CA, USA.
Kiana AranKeck Graduate Institute, The Claremont Colleges, Claremont, CA, USA. kiana_aran@kgi.edu.ORCID http://orcid.org/0000-0003-0268-6192
University of California, Berkeley · USClaremont Colleges · USCalifornia Medical Innovations Institute · USUniversidad de Navarra · ES

Funding

New Generation Blood Exchange Devices for Enhancing Tissue Regeneration and HealthR01HL139605 · NHLBI · UNIVERSITY OF CALIFORNIA BERKELEY · PI ARAN, KIANA, CONBOY, IRINA M · 2018 to 2021
$1.6M
Treatment of Duchenne Muscular Dystrophy with Cas9 Protein Complexed to Gold NanoparticlesR01EB023776 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI CONBOY, IRINA M, MURTHY, NIREN · 2017 to 2020
$1.4M
NHLBI NIH HHS R01 HL139605NIBIB NIH HHS R01 EB023776
6 · The paper itself

Abstract

Most methods for the detection of nucleic acids require many reagents and expensive and bulky instrumentation. Here, we report the development and testing of a graphene-based field-effect transistor that uses clustered regularly interspaced short palindromic repeats (CRISPR) technology to enable the digital detection of a target sequence within intact genomic material. Termed CRISPR-Chip, the biosensor uses the gene-targeting capacity of catalytically deactivated CRISPR-associated protein 9 (Cas9) complexed with a specific single-guide RNA and immobilized on the transistor to yield a label-free nucleic-acid-testing device whose output signal can be measured with a simple handheld reader. We used CRISPR-Chip to analyse DNA samples collected from HEK293T cell lines expressing blue fluorescent protein, and clinical samples of DNA with two distinct mutations at exons commonly deleted in individuals with Duchenne muscular dystrophy. In the presence of genomic DNA containing the target gene, CRISPR-Chip generates, within 15 min, with a sensitivity of 1.7 fM and without the need for amplification, a significant enhancement in output signal relative to samples lacking the target sequence. CRISPR-Chip expands the applications of CRISPR-Cas9 technology to the on-chip electrical detection of nucleic acids.

Indexed as

Nucleic Acid Amplification TechniquesTransistors, ElectronicCRISPR-Associated Protein 9CRISPR-Cas SystemsDNADystrophinExonsGenomeGraphiteHEK293 CellsHumansImmobilized ProteinsMaleMuscular Dystrophy, DuchenneMutationRNA, Guide, CRISPR-Cas SystemsCRISPR-Associated Protein 9DNADystrophinGraphiteImmobilized ProteinsRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID31097816
PMCPMC6556128
OpenAlexW2923727276

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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 OpenQuestion graph.