Literature DB >> 29460220

Molecular identification of common Salmonella serovars using multiplex DNA sensor-based suspension array.

Muhsin Aydin1,2, Jacqueline Carter-Conger3, Ning Gao4, David F Gilmore5, Steven C Ricke6, Soohyoun Ahn7.   

Abstract

Salmonella is one of major foodborne pathogens and the leading cause of foodborne illness-related hospitalizations and deaths. It is critical to develop a sensitive and rapid detection assay that can identify Salmonella to ensure food safety. In this study, a DNA sensor-based suspension array system of high multiplexing ability was developed to identify eight Salmonella serovars commonly associated with foodborne outbreaks to the serotype level. Each DNA sensor was prepared by activating pre-encoded microspheres with oligonucleotide probes that are targeting virulence genes and serovar-specific regions. The mixture of 12 different types of DNA sensors were loaded into a 96-well microplate and used as a 12-plex DNA sensor array platform. DNA isolated from Salmonella was amplified by multiplex polymerase chain reaction (mPCR), and the presence of Salmonella was determined by reading fluorescent signals from hybridization between probes on DNA sensors and fluorescently labeled target DNA using the Bio-Plex® system. The developed multiplex array was able to detect synthetic DNA at the concentration as low as 100 fM and various Salmonella serovars as low as 100 CFU/mL within 1 h post-PCR. Sensitivity of this assay was further improved to 1 CFU/mL with 6-h enrichment. The array system also correctly and specifically identified serotype of tested Salmonella strains without any cross-reactivity with other common foodborne pathogens. Our results indicate the developed DNA sensor suspension array can be a rapid and reliable high-throughput method for simultaneous detection and molecular identification of common Salmonella serotypes.

Entities:  

Keywords:  Bead suspension array; Flow cytometry; Identification; Salmonella; Serotyping

Mesh:

Substances:

Year:  2018        PMID: 29460220     DOI: 10.1007/s00216-018-0938-5

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  6 in total

1.  Rapid identification of pathogens by using surface-enhanced Raman spectroscopy and multi-scale convolutional neural network.

Authors:  Jingyu Ding; Qingqing Lin; Jiameng Zhang; Glenn M Young; Chun Jiang; Yaoguang Zhong; Jianhua Zhang
Journal:  Anal Bioanal Chem       Date:  2021-05-07       Impact factor: 4.142

2.  MIR spectroscopy as alternative method for further confirmation of foodborne pathogens Salmonella spp. and Listeria monocytogenes.

Authors:  Catarina Moreirinha; Joana Trindade; Jorge A Saraiva; Adelaide Almeida; Ivonne Delgadillo
Journal:  J Food Sci Technol       Date:  2018-07-09       Impact factor: 2.701

3.  Simple, low-cost fabrication of acrylic based droplet microfluidics and its use to generate DNA-coated particles.

Authors:  Md Mamunul Islam; Amanda Loewen; Peter B Allen
Journal:  Sci Rep       Date:  2018-06-08       Impact factor: 4.379

4.  A high-throughput and ultrasensitive identification methodology for unauthorized GMP component based on suspension array and logical calculator.

Authors:  Pengyu Zhu; Wei Fu; Shuang Wei; Xiao Liu; Chenguang Wang; Yun Lu; Ying Shang; Xiyang Wu; Yuping Wu; Shuifang Zhu
Journal:  Sci Rep       Date:  2019-05-13       Impact factor: 4.379

5.  Multiplex ligation reaction based on probe melting curve analysis: a pragmatic approach for the identification of 30 common Salmonella serovars.

Authors:  Le Zuo; Min Jiang; Yixiang Jiang; Xiaolu Shi; Yinghui Li; Yiman Lin; Yaqun Qiu; Yinhua Deng; Minxu Li; Zeren Lin; Yiqun Liao; Jianbin Xie; Qingge Li; Qinghua Hu
Journal:  Ann Clin Microbiol Antimicrob       Date:  2019-12-05       Impact factor: 3.944

6.  Simultaneous Identification of Clinically Common Vibrio parahaemolyticus Serotypes Using Probe Melting Curve Analysis.

Authors:  Minxu Li; Yixiang Jiang; Xiaolu Shi; Yinghui Li; Min Jiang; Yiman Lin; Yaqun Qiu; Le Zuo; Yinhua Deng; Zeren Lin; Yiqun Liao; Qingge Li; Qinghua Hu
Journal:  Front Cell Infect Microbiol       Date:  2019-11-14       Impact factor: 5.293

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.