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Ganjalizadeh V, Meena GG, Stott MA, Hawkins AR, Schmidt H. Machine learning at the edge for AI-enabled multiplexed pathogen detection. Sci Rep 2023; 13:4744. [PMID: 36959357 PMCID: PMC10034896 DOI: 10.1038/s41598-023-31694-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 03/15/2023] [Indexed: 03/25/2023] Open
Abstract
Multiplexed detection of biomarkers in real-time is crucial for sensitive and accurate diagnosis at the point of use. This scenario poses tremendous challenges for detection and identification of signals of varying shape and quality at the edge of the signal-to-noise limit. Here, we demonstrate a robust target identification scheme that utilizes a Deep Neural Network (DNN) for multiplex detection of single particles and molecular biomarkers. The model combines fast wavelet particle detection with Short-Time Fourier Transform analysis, followed by DNN identification on an AI-specific edge device (Google Coral Dev board). The approach is validated using multi-spot optical excitation of Klebsiella Pneumoniae bacterial nucleic acids flowing through an optofluidic waveguide chip that produces fluorescence signals of varying amplitude, duration, and quality. Amplification-free 3× multiplexing in real-time is demonstrated with excellent specificity, sensitivity, and a classification accuracy of 99.8%. These results show that a minimalistic DNN design optimized for mobile devices provides a robust framework for accurate pathogen detection using compact, low-cost diagnostic devices.
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Affiliation(s)
- Vahid Ganjalizadeh
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, 95064, USA
| | - Gopikrishnan G Meena
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, 95064, USA
| | - Matthew A Stott
- Electrical and Computer Engineering Department, Brigham Young University, Provo, UT, 84602, USA
| | - Aaron R Hawkins
- Electrical and Computer Engineering Department, Brigham Young University, Provo, UT, 84602, USA
| | - Holger Schmidt
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, 95064, USA.
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Stambaugh A, Stott MA, Meena GG, Tamhankar M, Carrion R, Patterson JL, Hawkins AR, Schmidt H. Optofluidic Amplification-free Multiplex Detection of Viral Hemorrhagic Fevers. IEEE J Sel Top Quantum Electron 2021; 27:7200206. [PMID: 33390686 PMCID: PMC7774596 DOI: 10.1109/jstqe.2020.3024239] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Infectious disease outbreaks such as Ebola and other Viral Hemorrhagic Fevers (VHF) require low-complexity, specific, and differentiated diagnostics as illustrated by the recent outbreak in the Democratic Republic of Congo. Here, we describe amplification-free spectrally multiplex detection of four different VHF total RNA samples using multi-spot excitation on a multimode interference waveguide platform along with combinatorial fluorescence labeling of target nucleic acids. In these experiments, we observed an average of 8-fold greater fluorescence signal amplitudes for the Ebola total RNA sample compared to three other total RNA samples: Lake Victoria Marburg Virus, Ravn Marburg Virus, and Crimean-Congo Hemorrhagic Fever. We have attributed this amplitude amplification to an increased amount of RNA during synthesis of soluble glycoprotein in infection. This hypothesis is confirmed by single molecule detection of the total RNA sample after heat-activated release from the carrier microbeads. From these experiments, we observed at least a 5.3x higher RNA mass loading on the Ebola carrier microbeads compared to the Lake Victoria Marburg carrier microbeads, which is consistent with the known production of soluble glycoprotein during infection.
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Affiliation(s)
- Alexandra Stambaugh
- School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064 USA
| | - Matthew A Stott
- Department of Electrical and Computer Engineering, Brigham Young University, Provo UT 84602 USA
| | - Gopikrishnan G Meena
- School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064 USA
| | - Manasi Tamhankar
- Department of Virology and Immunology, Texas Biomedical Research Institute, San Antonio, TX 78227 USA
| | - Ricardo Carrion
- Department of Virology and Immunology, Texas Biomedical Research Institute, San Antonio, TX 78227 USA
| | - Jean L Patterson
- Department of Virology and Immunology, Texas Biomedical Research Institute, San Antonio, TX 78227 USA
| | - Aaron R Hawkins
- Department of Electrical and Computer Engineering, Brigham Young University, Provo UT 84602 USA
| | - Holger Schmidt
- School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064 USA
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Wright JG, Amin MN, Meena GG, Schmidt H, Hawkins AR. Optofluidic Flow-Through Biosensor Sensitivity - Model and Experiment. J Lightwave Technol 2021; 39:3330-3340. [PMID: 34177078 PMCID: PMC8224397 DOI: 10.1109/jlt.2021.3061872] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
We present a model and simulation for predicting the detected signal of a fluorescence-based optical biosensor built from optofluidic waveguides. Typical applications include flow experiments to determine pathogen concentrations in a biological sample after tagging relevant DNA or RNA sequences. An overview of the biosensor geometry and fabrication processes is presented. The basis for the predictive model is also outlined. The model is then compared to experimental results for three different biosensor designs. The model is shown to have similar signal statistics as physical tests, illustrating utility as a pre-fabrication design tool and as a predictor of detection sensitivity.
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Affiliation(s)
- Joel G Wright
- Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, 84602, USA
| | - Md Nafiz Amin
- School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Gopikrishnan G Meena
- School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Holger Schmidt
- School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Aaron R Hawkins
- Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, 84602, USA
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Meena GG, Hanson RL, Wood RL, Brown OT, Stott MA, Robison RA, Pitt WG, Woolley AT, Hawkins AR, Schmidt H. 3× multiplexed detection of antibiotic resistant plasmids with single molecule sensitivity. Lab Chip 2020; 20:3763-3771. [PMID: 33048071 PMCID: PMC7574402 DOI: 10.1039/d0lc00640h] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Bacterial pathogens resistant to antibiotics have become a serious health threat. Those species which have developed resistance against multiple drugs such as the carbapenems, are more lethal as these are last line therapy antibiotics. Current diagnostic tests for these resistance traits are based on singleplex target amplification techniques which can be time consuming and prone to errors. Here, we demonstrate a chip based optofluidic system with single molecule sensitivity for amplification-free, multiplexed detection of plasmids with genes corresponding to antibiotic resistance, within one hour. Rotating disks and microfluidic chips with functionalized polymer monoliths provided the upstream sample preparation steps to selectively extract these plasmids from blood spiked with E. coli DH5α cells. Waveguide-based spatial multiplexing using a multi-mode interference waveguide on an optofluidic chip was used for parallel detection of three different carbapenem resistance genes. These results point the way towards rapid, amplification-free, multiplex analysis of antibiotic-resistant pathogens.
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Affiliation(s)
- G G Meena
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
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Meena GG, Jain A, Parks JW, Stambaugh A, Patterson JL, Hawkins AR, Schmidt H. Integration of sample preparation and analysis into an optofluidic chip for multi-target disease detection. Lab Chip 2018; 18:3678-3686. [PMID: 30376021 PMCID: PMC6264894 DOI: 10.1039/c8lc00966j] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Detection of molecular biomarkers with high specificity and sensitivity from biological samples requires both sophisticated sample preparation and subsequent analysis. These tasks are often carried out on separate platforms which increases required sample volumes and the risk of errors, sample loss, and contamination. Here, we present an optofluidic platform which combines an optical detection section with single nucleic acid strand sensitivity, and a sample processing unit capable of on-chip, specific extraction and labeling of nucleic acid and protein targets in complex biological matrices. First, on-chip labeling and detection of individual lambda DNA molecules down to concentrations of 8 fM is demonstrated. Subsequently, we demonstrate the simultaneous capture, fluorescence tagging and detection of both Zika specific nucleic acid and NS-1 protein targets in both buffer and human serum. We show that the dual DNA and protein assay allows for successful differentiation and diagnosis of Zika against cross-reacting species like dengue.
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Affiliation(s)
- Gopikrishnan G Meena
- School of Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
| | - Aadhar Jain
- School of Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
| | - Joshua W Parks
- School of Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
| | - Alexandra Stambaugh
- School of Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
| | - Jean L Patterson
- Department of Virology and Immunology, Texas Biomedical Research Institute, 7620 NW Loop 410, San Antonio, TX 78227, USA
| | - Aaron R Hawkins
- ECEn Department, Brigham Young University, 459 Clyde Building, Provo, UT 84602, USA
| | - Holger Schmidt
- School of Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
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Stambaugh A, Parks JW, Stott MA, Meena GG, Hawkins AR, Schmidt H. Optofluidic detection of Zika nucleic acid and protein biomarkers using multimode interference multiplexing. Biomed Opt Express 2018; 9:3725-3730. [PMID: 30338150 PMCID: PMC6191625 DOI: 10.1364/boe.9.003725] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 06/05/2018] [Accepted: 06/13/2018] [Indexed: 05/03/2023]
Abstract
The recent massive Zika virus (ZIKV) outbreak illustrates the need for rapid and specific diagnostic techniques. Detecting ZIKV in biological samples poses unique problems: antibody detection of ZIKV is insufficient due to cross-reactivity of Zika antibodies with other flaviviruses, and nucleic acid and protein biomarkers for ZIKV are detectable at different stages of infection. Here, we describe a new optofluidic approach for the parallel detection of different molecular biomarkers using multimode interference (MMI) waveguides. We report differentiated, multiplex detection of both ZIKV biomarker types using multi-spot excitation at two visible wavelengths with over 98% fidelity by combining several analysis techniques.
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Affiliation(s)
- Alexandra Stambaugh
- School of Engineering, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA
| | - Joshua W. Parks
- School of Engineering, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA
| | - Matthew A. Stott
- ECEn Department, Brigham Young University, 459 Clyde Building, Provo, UT 84602, USA
| | - Gopikrishnan G. Meena
- School of Engineering, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA
| | - Aaron R. Hawkins
- ECEn Department, Brigham Young University, 459 Clyde Building, Provo, UT 84602, USA
| | - Holger Schmidt
- School of Engineering, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA
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