Challenges and Opportunities for Clustered Regularly Interspaced Short Palindromic Repeats Based Molecular Biosensing.

CRISPR amplification-free sensing biosensing collateral cleavage detection specificity guide RNA microfluidics multiplexing capability noise nucleic acid testing (NAT)

Journal

ACS sensors
ISSN: 2379-3694
Titre abrégé: ACS Sens
Pays: United States
ID NLM: 101669031

Informations de publication

Date de publication:
23 07 2021
Historique:
pubmed: 19 6 2021
medline: 3 8 2021
entrez: 18 6 2021
Statut: ppublish

Résumé

Clustered regularly interspaced short palindromic repeats, CRISPR, has recently emerged as a powerful molecular biosensing tool for nucleic acids and other biomarkers due to its unique properties such as collateral cleavage nature, room temperature reaction conditions, and high target-recognition specificity. Numerous platforms have been developed to leverage the CRISPR assay for ultrasensitive biosensing applications. However, to be considered as a new gold standard, several key challenges for CRISPR molecular biosensing must be addressed. In this paper, we briefly review the history of biosensors, followed by the current status of nucleic acid-based detection methods. We then discuss the current challenges pertaining to CRISPR-based nucleic acid detection, followed by the recent breakthroughs addressing these challenges. We focus upon future advancements required to enable rapid, simple, sensitive, specific, multiplexed, amplification-free, and shelf-stable CRISPR-based molecular biosensors.

Identifiants

pubmed: 34143608
doi: 10.1021/acssensors.1c00530
doi:

Substances chimiques

Nucleic Acids 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2497-2522

Auteurs

Mengdi Bao (M)

Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.

Qun Chen (Q)

Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China.

Zhiheng Xu (Z)

Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.

Erik C Jensen (EC)

HJ Science & Technology Inc., San Leandro, California 94710, United States.

Changyue Liu (C)

Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China.

Jacob T Waitkus (JT)

Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.

Xi Yuan (X)

Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China.

Qian He (Q)

Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China.

Peiwu Qin (P)

Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China.

Ke Du (K)

Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.
Department of Microsystems Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States.
School of Chemistry and Materials Science, Rochester Institute of Technology, Rochester, New York 14623, United States.

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Classifications MeSH