4.6 Article

16S rRNA Monitoring Point-of-Care Magnetic Focus Lateral Flow Sensor

Journal

ACS OMEGA
Volume 6, Issue 16, Pages 11095-11102

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsomega.1c01307

Keywords

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Funding

  1. Jump Arches Seed grant of the Health Care Engineering Center
  2. Tumor Engineering and Phenotyping Facility of the Cancer Center at Illinois at the University of Illinois at UrbanaChampaign
  3. U.S. Department of Agriculture (USDA), Agricultural Research Service [59-8072-6001]

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The proposed highly sensitive colorimetric strategy allows for naked eye screening of 16S rRNA from pathogenic bacteria with significantly improved sensitivity compared to conventional methods. This method enables detection of target 16S rRNA in complex matrices within a short period of time.
The detection and profiling of pathogenic bacteria is critical for human health, environmental, and food safety monitoring. Herein, we propose a highly sensitive colorimetric strategy for naked eye screening of 16S ribosomal RNA (16S rRNA) from pathogenic agents relevant to infections, human health, and food safety monitoring with a magnetic focus lateral flow sensor (mLFS) platform. The method developed was demonstrated in model 16S rRNA sequences of the pathogen Escherichia coli O157:H7 to detect as low as 1 fM of targets, exhibiting a sensitivity improved by similar to 5 x 10(5) times compared to the conventional GNP-based colorimetric lateral flow assay used for oligonucleotide testing. Based on the grayscale values, semi-quantitation of up to 1 pM of target sequences was possible in similar to 45 min. The methodology could detect the target 16S rRNA from as low as 32 pg/mL of total RNA extracted from pathogens. Specificity was demonstrated with total RNA extracted from E. coli K-12 MG1655, Bacillus subtilis (B. subtilis), and Pseudomonas aeruginosa (P. aeruginosa). No signal was observed from as high as 320 pg/mL of total RNA from the nontarget bacteria. The recognition of target 16S rRNA from 32 pg/mL of total RNA in complex matrices was also demonstrated. The proposed mLFS method was then extended to monitoring B. subtilis and P. aeruginosa. Our approach highlights the possibility of extending this concept to screen specific nucleic acid sequences for the monitoring of infectious pathogens or microbiome implicated in a range of diseases including cancer.

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