Rapid identification of a subset of foodborne bacteria in live-cell assays
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APPLIED GENETICS AND MOLECULAR BIOTECHNOLOGY
Rapid identification of a subset of foodborne bacteria in live-cell assays Qingsu Cheng 1,2 & Bahram Parvin 1,2 Received: 20 February 2020 / Revised: 6 September 2020 / Accepted: 21 October 2020 / Published online: 13 November 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The detection and identification of microbial pathogens in meat and fresh produce play an essential role in food safety for reducing foodborne illnesses every year. A new approach based on targeting a specific sequence of the 16S rRNA region for each bacterium is proposed and validated. The probe complex consists of a C60, a conjugated RNA detector which targets a specific 16S rRNA sequence, and a complementary fluorescent reporter. The RNA detectors were designed by integrating NIH nucleotide and Vienna RNA Webservice databases, and their specificities were validated by the RDP database. Probe complexes were synthesized for identifying E. coli K12, E. coli O157: H7, S. enterica, Y. enterocolitica, C. perfringens, and L. monocytogenes. First, under controlled conditions of known bacterial mixtures, the efficiency and crosstalk for identifying the foodborne bacteria were quantified to be above 94% and below 5%, respectively. Second, experiments were designed by inoculating meat products by known numbers of bacteria and measuring the limit of detection. In one experiment, 225 g of autoclaved ground chicken was inoculated with 9 E. coli O157:H7, where 6.8 ± 1.2 bacteria with 95% confidence interval were recovered. Third, by positionally printing probe complexes in microwells, specific microorganisms were identified with only one fluorophore. The proposed protocol is a cell-based system, can identify live bacteria in 15 min, requires no amplification, and has the potential to open new surveillance opportunities. Key points • The identification of foodborne bacteria is enabled in live-cell assays. • The limit of detection for 100 g of fresh chicken breast inoculated with 4 bacteria is 2.7 ± 1.4 with 95% confidence interval. • The identification of five bacteria in a coded microwell chip is enabled with only one fluorophore. Keywords Foodborne bacteria . C60 . 16S rRNA . Live-cell assays . Fluorescent microscopy
Introduction The detection and identification of microbial pathogens are crucial for public health and food safety (Law et al. 2014). Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s00253-02010970-9. * Bahram Parvin [email protected] 1
Department of Electrical and Biomedical Engineering, University of Nevada, Reno, 1664 N. Virginia St., NV 89557 Reno, USA
2
Department of Cell and Molecular Biology, University of Nevada, Reno, 1664 N. Virginia St., Reno, NV 89557, USA
The CDC reported that there were about 48 million cases of foodborne illness each year. Roughly, one in six Americans will become sick from contaminated food, resulting in an estimated 128,000 hospitalizations and 3000 deaths annually (CDC 2
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