Back to Search Start Over

Sample-to-answer sensing technologies for nucleic acid preparation and detection in the field.

Authors :
Liu CW
Tsutsui H
Source :
SLAS technology [SLAS Technol] 2023 Oct; Vol. 28 (5), pp. 302-323. Date of Electronic Publication: 2023 Jun 09.
Publication Year :
2023

Abstract

Efficient sample preparation and accurate disease diagnosis under field conditions are of great importance for the early intervention of diseases in humans, animals, and plants. However, in-field preparation of high-quality nucleic acids from various specimens for downstream analyses, such as amplification and sequencing, is challenging. Thus, developing and adapting sample lysis and nucleic acid extraction protocols suitable for portable formats have drawn significant attention. Similarly, various nucleic acid amplification techniques and detection methods have also been explored. Combining these functions in an integrated platform has resulted in emergent sample-to-answer sensing systems that allow effective disease detection and analyses outside a laboratory. Such devices have a vast potential to improve healthcare in resource-limited settings, low-cost and distributed surveillance of diseases in food and agriculture industries, environmental monitoring, and defense against biological warfare and terrorism. This paper reviews recent advances in portable sample preparation technologies and facile detection methods that have been / or could be adopted into novel sample-to-answer devices. In addition, recent developments and challenges of commercial kits and devices targeting on-site diagnosis of various plant diseases are discussed.<br />Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Hideaki Tsutsui reports financial support was provided by National Science Foundation. The corresponding author serves on the editorial board of SLAS Technology - H.T.<br /> (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
2472-6311
Volume :
28
Issue :
5
Database :
MEDLINE
Journal :
SLAS technology
Publication Type :
Academic Journal
Accession number :
37302751
Full Text :
https://doi.org/10.1016/j.slast.2023.06.002