Artificial intelligence-assisted point-of-care testing system for ultrafast and quantitative detection of drug-resistant bacteria

Abstract

As one of the major causes of antimicrobial resistance, β-lactamase develops rapidly among bacteria. Detection of β-lactamase in an efficient and low-cost point-of-care testing (POCT) way is urgently needed. However, due to the volatile environmental factors, the quantitative measurement of current POCT is often inaccurate. Herein, we demonstrate an artificial intelligence (AI)-assisted mobile health system that consists of a paper-based β-lactamase fluorogenic probe analytical device and a smartphone-based AI cloud. An ultrafast broad-spectrum fluorogenic probe (B1) that could respond to β-lactamase within 20 s was first synthesized, and the detection limit was determined to be 0.13 nmol/L. Meanwhile, a three-dimensional microfluidic paper-based analytical device was fabricated for integration of B1. Also, a smartphone-based AI cloud was developed to correct errors automatically and output results intelligently. This smart system could calibrate the temperature and pH in the β-lactamase level detection in complex samples and mice infected with various bacteria, which shows the problem-solving ability in interdisciplinary research, and demonstrates potential clinical benefits.

Keywords

antimicrobial resistance / artificial intelligence / fluorogenic probe / microfluidic sensors / mobile health / point-of-care testing

References

[1] Blaser MJ. Antibiotic use and its consequences for the normal microbiome. Science. 2016;352(6285):544-545.

[2] Laxminarayan R, Sridhar D, Blaser M, Wang M, Woolhouse M. Achieving global targets for antimicrobial resistance. Science. 2016;353(6302):874-875.

[3] Sciarretta K, Røttingen JA, Opalska A, Van Hengel AJ, Larsen J. Economic incentives for antibacterial drug development: literature review and considerations from the transatlantic task force on antimicrobial resistance. Clin Infect Dis. 2016;63(11):1470-1474.

[4] Durand-Reville TF, Miller AA, O'Donnell JP, et al. Rational design of a new antibiotic class for drug-resistant infections. Nature. 2021;597(7878):698-702.

[5] Babic M, Hujer A, Bonomo R. What's new in antibiotic resistance? Focus on beta-lactamases. Drug Resist Updat. 2006;9(3):142-156.

[6] Gajdács M. The continuing threat of methicillin-resistant Staphylococcus aureus. Antibiotics. 2019;8(2):52.

[7] Zhang Y, Wang Q, Yin Y, et al. Epidemiology of carbapenem-resistant Enterobacteriaceae infections: report from the China CRE network. Antimicrob Agents Chemother. 2018;62(2):e01882-17.

[8] Hu FP, Guo Y, Zhu DM, et al. Resistance trends among clinical isolates in China reported from CHINET surveillance of bacterial resistance, 2005-2014. Clin Microbiol Infect. 2016;22(1):S9-S14.

[9] Xie H, Mire J, Kong Y, et al. Rapid point-of-care detection of the tuberculosis pathogen using a BlaC-specific fluorogenic probe. Nat Chem. 2012;4(10):802-809.

[10] Cheng Y, Xie J, Lee KH, et al. Rapid and specific labeling of single live Mycobacterium tuberculosis with a dual-targeting fluorogenic probe. Sci Transl Med. 2018;10(454):eaar4470.

[11] Mehta R, Rivera DD, Reilley DJ, et al. Visualizing the dynamic metalation state of New Delhi Metallo-β-lactamase-1 in bacteria using a reversible fluorescent probe. J Am Chem Soc. 2021;143(22):8314-8323.

[12] Ding Y, Li Z, Xu C, et al. Fluorogenic probes/inhibitors of β-lactamase and their applications in drug-resistant bacteria. Angew Chem Int Ed. 2021;60(1):24-40.

[13] Shatalin K, Nuthanakanti A, Kaushik A, et al. Inhibitors of bacterial H₂S biogenesis targeting antibiotic resistance and tolerance. Science. 2021;372(6547):1169-1175.

[14] Nordmann P, Gniadkowski M, Giske CG, Poirel L, Woodford N, Miriagou V. Identification and screening of carbapenemase-producing Enterobacteriaceae. Clin Microbiol Infect. 2012;18(5):432-438.

[15] Bernabeu S, Poirel L, Nordmann P. Spectrophotometry-based detection of carbapenemase producers among Enterobacteriaceae. Diagn Microbiol Infect Dis. 2012;74(1):88-90.

[16] Cohen Stuart J, Leverstein-Van Hall MA. Guideline for phenotypic screening and confirmation of carbapenemases in Enterobacteriaceae. Int J Antimicrob Agents. 2010;36(3):205-210.

[17] Savli H, Karadenizli A, Kolayli F, Gundes S, Ozbek U, Vahaboglu H. Expression stability of six housekeeping genes: a proposal for resistance gene quantification studies of Pseudomonas aeruginosa by real-time quantitative RT-PCR. J Med Microbiol. 2003;52(5):403-408.

[18] Huang Y, Chen W, Chung J, Yin J, Yoon J. Recent progress in fluorescent probes for bacteria. Chem Soc Rev. 2021;50(13):7725-7744.

[19] Gao W, Xing B, Tsien RY, Rao J. Novel fluorogenic substrates for imaging β-lactamase gene expression. J Am Chem Soc. 2003;125(37):11146-11147.

[20] Yao H, So M, Rao J. A bioluminogenic substrate for in vivo imaging of β-lactamase activity. Angew Chem Int Ed. 2007;46(37):7031-7034.

[21] Chen Y, Xianyu Y, Wu J, Zheng W, Rao J, Jiang X. Point-of-care detection of β-lactamase in milk with a universal fluorogenic probe. Anal Chem. 2016;88(11):5605-5609.

[22] Mao W, Xia L, Wang Y, Xie H. A self-immobilizing and fluorogenic probe for β-lactamase detection. Chem Asian J. 2016;11(24):3493-3497.

[23] Li L, Li Z, Shi W, Li X, Ma H. Sensitive and selective near-infrared fluorescent off-on probe and its application to imaging different levels of β-lactamase in Staphylococcus aureus. Anal Chem. 2014;86(12):6115-6120.

[24] Luo Z, Lv T, Zhu K, et al. Paper-based ratiometric fluorescence analytical devices towards point-of-care testing of human serum albumin. Angew Chem Int Ed. 2020;59(8):3131-3136.

[25] Chu S, Wang H, Ling X, Yu S, Yang L, Jiang C. A portable smartphone platform using a ratiometric fluorescent paper strip for visual quantitative sensing. ACS Appl Mater Interfaces. 2020;12(11):12962-12971.

[26] Boehle KE, Gilliand J, Wheeldon CR, et al. Utilizing paper-based devices for antimicrobial-resistant bacteria detection. Angew Chem Int Ed. 2017;56(24):6886-6890.

[27] Arumugam S, Colburn DAM, Sia SK. Biosensors for personal mobile health: a system architecture perspective. Adv Mater Technol. 2020;5(3):1900720.

[28] Tu J, Torrente-Rodríguez RM, Wang M, Gao W. The era of digital health: a review of portable and wearable affinity biosensors. Adv Funct Mater. 2020;30(29):1906713.

[29] Liu J, Geng Z, Fan Z, Liu J, Chen H. Point-of-care testing based on smartphone: the current state-of-the-art (2017-2018). Biosens Bioelectron. 2019;132:17-37.

[30] Li W, Wang M, Mille LS, et al. A smartphone-enabled portable digital light processing 3D printer. Adv Mater. 2021;33(35):2102153.

[31] Fang H, Zhang H, Li L, et al. Rational design of a two-photon fluorogenic probe for visualizing monoamine oxidase A activity in human glioma tissues. Angew Chem Int Ed. 2020;59(19):7536-7541.

[32] Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455-461.

[33] Wu M, Suo F, Zhou J, et al. Paper-based fluorogenic device for detection of copper ions in a biological system. ACS Appl Bio Mater. 2018;1(5):1523-1529.

[34] Wiegand I, Hilpert K, Hancock REW. Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nat Protoc. 2008;3(2):163-175.

[35] Xie J, Zhou M, Qian Y, et al. Addressing MRSA infection and antibacterial resistance with peptoid polymers. Nat Commun. 2021;12(1):5898.

[36] Stjerndahl M, Lundberg D, Chauhan V, Bordes R, Holmberg K. Cleavable surfactants: a comparison between ester, amide, and carbonate as the weak bond. J Surfactants Deterg. 2019;22(5):1139-1145.

[37] Xue Y, Bai H, Peng B, et al. Stimulus-cleavable chemistry in the field of controlled drug delivery. Chem Soc Rev. 2021;50(8):4872-4931.

[38] Roose BW, Zemerov SD, Wang Y, Kasimova MA, Carnevale V, Dmochowski IJ. A structural basis for ¹²⁹Xe hyper-CEST signal in TEM-1 β-lactamase. Chemphyschem. 2019;20(2):260-267.

[39] Doughty MJ. pH dependent spectral properties of sodium fluorescein ophthalmic solutions revisited. Ophthalmic Physiol Opt. 2010;30(2):167-174.

[40] Church D, Elsayed S, Reid O, Winston B, Lindsay R. Burn wound infections. Clin Microbiol Rev. 2006;19(2):403-434.

[41] Zhang J, Jia Q, Yue Z, et al. An electroluminodynamic flexible device for highly efficient eradication of drug-resistant bacteria. Adv Mater. 2022;34(17):2200334.

RIGHTS & PERMISSIONS

2023 The Authors. SmartMat published by Tianjin University and John Wiley & Sons Australia, Ltd.