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Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples

Rapid detection of pathogenic bacteria within a few minutes is the key to control infectious disease. However, rapid detection of pathogenic bacteria in clinical samples is quite a challenging task due to the complex matrix, as well as the low abundance of bacteria in real samples. Herein, we employ...

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Detalles Bibliográficos
Autores principales: Chen, Shan, Su, Yu-Wen, Sun, Junjie, Chen, Tingting, Zheng, Yuhao, Sui, Lin-Jie, Yang, Shuangli, Liu, Chenbin, Wang, Pengcheng, Li, Tengfei, Chi, Qinghua, Sun, Hao, Chen, Jinghu, Xu, Bo-Qun, Huang, Zongxiong, Fang, Yimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546574/
https://www.ncbi.nlm.nih.gov/pubmed/36161913
http://dx.doi.org/10.1073/pnas.2206990119
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author Chen, Shan
Su, Yu-Wen
Sun, Junjie
Chen, Tingting
Zheng, Yuhao
Sui, Lin-Jie
Yang, Shuangli
Liu, Chenbin
Wang, Pengcheng
Li, Tengfei
Chi, Qinghua
Sun, Hao
Chen, Jinghu
Xu, Bo-Qun
Huang, Zongxiong
Fang, Yimin
author_facet Chen, Shan
Su, Yu-Wen
Sun, Junjie
Chen, Tingting
Zheng, Yuhao
Sui, Lin-Jie
Yang, Shuangli
Liu, Chenbin
Wang, Pengcheng
Li, Tengfei
Chi, Qinghua
Sun, Hao
Chen, Jinghu
Xu, Bo-Qun
Huang, Zongxiong
Fang, Yimin
author_sort Chen, Shan
collection PubMed
description Rapid detection of pathogenic bacteria within a few minutes is the key to control infectious disease. However, rapid detection of pathogenic bacteria in clinical samples is quite a challenging task due to the complex matrix, as well as the low abundance of bacteria in real samples. Herein, we employ a label-free single-particle imaging approach to address this challenge. By tracking the scattering intensity variation of single particles in free solution, the morphological heterogeneity can be well identified with particle size smaller than the diffraction limit, facilitating the morphological identification of single bacteria from a complex matrix in a label-free manner. Furthermore, the manipulation of convection in free solution enables the rapid screening of low-abundance bacteria in a small field of view, which significantly improves the sensitivity of single-particle detection. As a proof of concept demonstration, we are able to differentiate the group B streptococci (GBS)–positive samples within 10 min from vaginal swabs without using any biological reagents. This is the most rapid and low-cost method to the best of our knowledge. We believe that such a single-particle imaging approach will find wider applications in clinical diagnosis and disease control due to its high sensitivity, rapidity, simplicity, and low cost.
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spelling pubmed-95465742023-03-26 Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples Chen, Shan Su, Yu-Wen Sun, Junjie Chen, Tingting Zheng, Yuhao Sui, Lin-Jie Yang, Shuangli Liu, Chenbin Wang, Pengcheng Li, Tengfei Chi, Qinghua Sun, Hao Chen, Jinghu Xu, Bo-Qun Huang, Zongxiong Fang, Yimin Proc Natl Acad Sci U S A Biological Sciences Rapid detection of pathogenic bacteria within a few minutes is the key to control infectious disease. However, rapid detection of pathogenic bacteria in clinical samples is quite a challenging task due to the complex matrix, as well as the low abundance of bacteria in real samples. Herein, we employ a label-free single-particle imaging approach to address this challenge. By tracking the scattering intensity variation of single particles in free solution, the morphological heterogeneity can be well identified with particle size smaller than the diffraction limit, facilitating the morphological identification of single bacteria from a complex matrix in a label-free manner. Furthermore, the manipulation of convection in free solution enables the rapid screening of low-abundance bacteria in a small field of view, which significantly improves the sensitivity of single-particle detection. As a proof of concept demonstration, we are able to differentiate the group B streptococci (GBS)–positive samples within 10 min from vaginal swabs without using any biological reagents. This is the most rapid and low-cost method to the best of our knowledge. We believe that such a single-particle imaging approach will find wider applications in clinical diagnosis and disease control due to its high sensitivity, rapidity, simplicity, and low cost. National Academy of Sciences 2022-09-26 2022-10-04 /pmc/articles/PMC9546574/ /pubmed/36161913 http://dx.doi.org/10.1073/pnas.2206990119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Chen, Shan
Su, Yu-Wen
Sun, Junjie
Chen, Tingting
Zheng, Yuhao
Sui, Lin-Jie
Yang, Shuangli
Liu, Chenbin
Wang, Pengcheng
Li, Tengfei
Chi, Qinghua
Sun, Hao
Chen, Jinghu
Xu, Bo-Qun
Huang, Zongxiong
Fang, Yimin
Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples
title Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples
title_full Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples
title_fullStr Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples
title_full_unstemmed Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples
title_short Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples
title_sort label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546574/
https://www.ncbi.nlm.nih.gov/pubmed/36161913
http://dx.doi.org/10.1073/pnas.2206990119
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