TY - JOUR
T1 - Simpler Procedure and Improved Performance for Pathogenic Bacteria Analysis with a Paper-Based Ratiometric Fluorescent Sensor Array
AU - Laliwala, Aayushi
AU - Svechkarev, Denis
AU - Sadykov, Marat R.
AU - Endres, Jennifer
AU - Bayles, Kenneth W.
AU - Mohs, Aaron M.
N1 - Funding Information:
This work was funded in part by the Nebraska Research Initiative to A.M. and research grants from the National Institutes of Health: R01 EB027662 to A.M.; P30 CA036727 (Fred & Pamela Buffett Cancer Center), 1S10RR17846, 1S10RR027940, P20 GM103480 (Nebraska Center for Nanomedicine), P01 AI83211 to K.W.B., and R01 AI125589 to K.W.B. This work was also funded by Bukey Memorial Funds to A.L. The authors would like to thank Dr. Barbara Cabrera for providing bacterial species used in this study ( Gemella. spp., E. gallinarum, S. mitis, P. vulgaris, S. marcescens, E. cloacae, and M. morganii) and Nicholas Conoan of the Electron Microscopy Core Facility (EMCF) at the University of Nebraska Medical Center for technical assistance. The EMCF is supported by state funds from the Nebraska Research Initiative (NRI) and the University of Nebraska Foundation and institutionally by the Office of the Vice-Chancellor for Research.
Publisher Copyright:
© 2022 American Chemical Society
PY - 2022/2/8
Y1 - 2022/2/8
N2 - Bacterial infections are the leading cause of morbidity and mortality in the world, particularly due to a delay in treatment and misidentification of the bacterial species causing the infection. Therefore, rapid and accurate identification of these pathogens has been of prime importance. The conventional diagnostic techniques include microbiological, biochemical, and genetic analyses, which are time-consuming, require large sample volumes, expensive equipment, reagents, and trained personnel. In response, we have now developed a paper-based ratiometric fluorescent sensor array. Environment-sensitive fluorescent dyes (3-hydroxyflavone derivatives) pre-adsorbed on paper microzone plates fabricated using photolithography, upon interaction with bacterial cell envelopes, generate unique fluorescence response patterns. The stability and reproducibility of the sensor array response were thoroughly investigated, and the analysis procedure was refined for optimal performance. Using neural networks for response pattern analysis, the sensor was able to identify 16 bacterial species and recognize their Gram status with an accuracy rate greater than 90%. The paper-based sensor was stable for up to 6 months after fabrication and required 30 times lower dye and sample volumes as compared to the analogous solution-based sensor. Therefore, this approach opens avenues to a state-of-the-art diagnostic tool that can be potentially translated into clinical applications in low-resource environments.
AB - Bacterial infections are the leading cause of morbidity and mortality in the world, particularly due to a delay in treatment and misidentification of the bacterial species causing the infection. Therefore, rapid and accurate identification of these pathogens has been of prime importance. The conventional diagnostic techniques include microbiological, biochemical, and genetic analyses, which are time-consuming, require large sample volumes, expensive equipment, reagents, and trained personnel. In response, we have now developed a paper-based ratiometric fluorescent sensor array. Environment-sensitive fluorescent dyes (3-hydroxyflavone derivatives) pre-adsorbed on paper microzone plates fabricated using photolithography, upon interaction with bacterial cell envelopes, generate unique fluorescence response patterns. The stability and reproducibility of the sensor array response were thoroughly investigated, and the analysis procedure was refined for optimal performance. Using neural networks for response pattern analysis, the sensor was able to identify 16 bacterial species and recognize their Gram status with an accuracy rate greater than 90%. The paper-based sensor was stable for up to 6 months after fabrication and required 30 times lower dye and sample volumes as compared to the analogous solution-based sensor. Therefore, this approach opens avenues to a state-of-the-art diagnostic tool that can be potentially translated into clinical applications in low-resource environments.
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U2 - 10.1021/acs.analchem.1c05021
DO - 10.1021/acs.analchem.1c05021
M3 - Article
C2 - 35073053
AN - SCOPUS:85124160601
SN - 0003-2700
VL - 94
SP - 2615
EP - 2624
JO - Analytical Chemistry
JF - Analytical Chemistry
IS - 5
ER -