1
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Sano T, Losakul R, Schmidt H. Dual optofluidic distributed feedback dye lasers for multiplexed biosensing applications. Sci Rep 2023; 13:16824. [PMID: 37803034 PMCID: PMC10558432 DOI: 10.1038/s41598-023-42671-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 09/12/2023] [Indexed: 10/08/2023] Open
Abstract
Integrated optofluidic devices have become subjects of high interest for rapid biosensor devices due to their unique ability to combine the fluidic processing of small volumes of microfluidics with the analysis capabilities of photonic structures. By integrating dynamically reconfigurable optofluidic lasers on-chip, complex coupling can be eliminated while further increasing the capabilities of sensors to detect an increasing number of target biomarkers. Here, we report a polydimethylsiloxane-based device with two on-chip fluidic distributed feedback (DFB) laser cavities that are integrated with an orthogonal analyte channel for multiplexed fluorescence excitation. One DFB grating is filled with 4-(dicyanomethylene)-2-methyl-6-(4-dimethylaminostyryl)-4H-pyran dissolved in dimethyl sulfoxide. The second grating is filled with rhodamine 6G dissolved in a diluted ethylene glycol solution. We present characterization of both lasers through analysis of the lasing spectra for spectral narrowing along with a power series to observe threshold behavior. We then demonstrate simultaneous detection of two different fluorescent microbeads as a proof of concept for scalable, single biomarker analysis using on-chip optofluidic lasers.
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Affiliation(s)
- Tyler Sano
- Department of Electrical and Computer Engineering, University of California Santa Cruz (UCSC), 1156 High Street, Santa Cruz, CA, 95064, USA.
| | - Ravipa Losakul
- Department of Electrical and Computer Engineering, University of California Santa Cruz (UCSC), 1156 High Street, Santa Cruz, CA, 95064, USA
| | - Holger Schmidt
- Department of Electrical and Computer Engineering, University of California Santa Cruz (UCSC), 1156 High Street, Santa Cruz, CA, 95064, USA
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2
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Ganjalizadeh V, Hawkins AR, Schmidt H. Adaptive time modulation technique for multiplexed on-chip particle detection across scales. OPTICA 2023; 10:812-818. [PMID: 38818330 PMCID: PMC11138143 DOI: 10.1364/optica.489068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/15/2023] [Indexed: 06/01/2024]
Abstract
Integrated optofluidic biosensors have demonstrated ultrasensitivity down to single particle detection and attomolar target concentrations. However, a wide dynamic range is highly desirable in practice and can usually only be achieved by using multiple detection modalities or sacrificing linearity. Here, we demonstrate an analysis technique that uses temporal excitation at two different time scales to simultaneously enable digital and analog detection of fluorescent targets. We demonstrated the seamless detection of nanobeads across eight orders of magnitude from attomolar to nanomolar concentration. Furthermore, a combination of spectrally varying modulation frequencies and a closed-loop feedback system that provides rapid adjustment of excitation laser powers enables multiplex analysis in the presence of vastly different concentrations. We demonstrated this ability to detect across scales via an analysis of a mixture of fluorescent nanobeads at femtomolar and picomolar concentrations. This technique advances the performance and versatility of integrated biosensors, especially toward point-of-use applications.
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Affiliation(s)
- Vahid Ganjalizadeh
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California, 95064, USA
| | - Aaron R. Hawkins
- Electrical and Computer Engineering Department, Brigham Young University, Provo, Utah, 84602, USA
| | - Holger Schmidt
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California, 95064, USA
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3
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Hamblin M, Wright J, Schmidt H, Hawkins AR. Comparison of Illumination Methods for Flow-Through Optofluidic Biosensors. MICROMACHINES 2023; 14:723. [PMID: 37420956 DOI: 10.3390/mi14040723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/21/2023] [Accepted: 03/21/2023] [Indexed: 07/09/2023]
Abstract
Optofluidic biosensors have become an important medical diagnostic tool because they allow for rapid, high-sensitivity testing of small samples compared to standard lab testing. For these devices, the practicality of use in a medical setting depends heavily on both the sensitivity of the device and the ease of alignment of passive chips to a light source. This paper uses a model previously validated by comparison to physical devices to compare alignment, power loss, and signal quality for windowed, laser line, and laser spot methods of top-down illumination.
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Affiliation(s)
- Matthew Hamblin
- Electrical and Computer Engineering, Brigham Young University, 450 Engineering Building, Provo, UT 84602, USA
| | - Joel Wright
- Electrical and Computer Engineering, Brigham Young University, 450 Engineering Building, Provo, UT 84602, USA
| | - Holger Schmidt
- Electrical and Computer Engineering, University of California, 1156 High Street, Santa Cruz, CA 95064, USA
| | - Aaron R Hawkins
- Electrical and Computer Engineering, Brigham Young University, 450 Engineering Building, Provo, UT 84602, USA
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4
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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] [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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5
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Guan T, Xu Z, Wang J, Liu Y, Shen X, Li X, Sun Y, Lei H. Multiplex optical bioassays for food safety analysis: Toward on-site detection. Compr Rev Food Sci Food Saf 2022; 21:1627-1656. [PMID: 35181985 DOI: 10.1111/1541-4337.12914] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 12/28/2021] [Accepted: 12/29/2021] [Indexed: 12/15/2022]
Abstract
Food safety analysis plays a significant role in controlling food contamination and supervision. In recent years, multiplex optical bioassays (MOBAs) have been widely applied to analyze multiple hazards due to their efficiency and low cost. However, due to the challenges such as multiplexing capacity, poor sensitivity, and bulky instrumentation, the further application of traditional MOBAs in food screening has been limited. In this review, effective strategies regarding food safety MOBAs are summarized, such as spatial-resolution modes performed in multi-T lines/dots strips or arrays of strip/microplate/microfluidic chip/SPR chip and signal-resolution modes employing distinguishable colorimetric/luminescence/fluorescence/surface plasma resonance/surface-enhanced Raman spectrum as signal tags. Following this, new trends on how to design engineered sensor architecture and exploit distinguishable signal reporters, how to improve both multiplexing capacity and sensitivity, and how to integrate these formats into smartphones so as to be mobile are summarized systematically. Typically, in the case of enhancing multiplexing capacity and detection throughput, microfluidic array chips with multichannel architecture would be a favorable approach to overcome the spatial and physical limitations of immunochromatographic assay (ICA) test strips. Moreover, noble metal nanoparticles and single-excitation, multiple-emission luminescence nanomaterials hold great potential in developing ultrasensitive MOBAs. Finally, the exploitation of innovative multiplexing strategy hybridized with powerful and widely available smartphones opens new perspectives to MOBAs. In future, the MOBAs should be more sensitive, have higher multiplexing capacity, and easier instrumentation.
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Affiliation(s)
- Tian Guan
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou, 510642, China
| | - Zhenlin Xu
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
| | - Jin Wang
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yingju Liu
- Department of Applied Chemistry, College of Materials and Energy, South China Agricultural University, Guangzhou, China
| | - Xing Shen
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou, 510642, China
| | - Xiangmei Li
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yuanming Sun
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou, 510642, China
| | - Hongtao Lei
- Guangdong Provincial Key Laboratory of Food Quality and Safety / Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou, 510642, China.,Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China
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Fernandez-Cuesta I, Llobera A, Ramos-Payán M. Optofluidic systems enabling detection in real samples: A review. Anal Chim Acta 2022; 1192:339307. [DOI: 10.1016/j.aca.2021.339307] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 11/16/2021] [Accepted: 11/17/2021] [Indexed: 12/20/2022]
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Rahman M, Sampad MJN, Hawkins A, Schmidt H. Recent advances in integrated solid-state nanopore sensors. LAB ON A CHIP 2021; 21:3030-3052. [PMID: 34137407 PMCID: PMC8372664 DOI: 10.1039/d1lc00294e] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
The advent of single-molecule probing techniques has revolutionized the biomedical and life science fields and has spurred the development of a new class of labs-on-chip based on powerful biosensors. Nanopores represent one of the most recent and most promising single molecule sensing paradigms that is seeing increased chip-scale integration for improved convenience and performance. Due to their physical structure, nanopores are highly sensitive, require low sample volume, and offer label-free, amplification-free, high-throughput real-time detection and identification of biomolecules. Over the last 25 years, nanopores have been extensively employed to detect a variety of biomolecules with a growing range of applicatons ranging from nucleic acid sequencing to ultrasensitive diagnostics to single-molecule biophysics. Nanopores, in particular those in solid-state membranes, also have the potential for integration with other technologies such as optics, plasmonics, microfluidics, and optofluidics to perform more complex tasks for an ever-expanding demand. A number of breakthrough results using integrated nanopore platforms have already been reported, and more can be expected as nanopores remain the focus of innovative research and are finding their way into commercial instruments. This review provides an overview of different aspects and challenges of nanopore technology with a focus on chip-scale integration of solid-state nanopores for biosensing and bioanalytical applications.
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Affiliation(s)
- Mahmudur Rahman
- School of Engineering, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA, 95064 USA. and Dhaka University of Engineering & Technology, Gazipur, Bangladesh
| | | | - Aaron 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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8
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Advances in Antimicrobial Resistance Monitoring Using Sensors and Biosensors: A Review. CHEMOSENSORS 2021. [DOI: 10.3390/chemosensors9080232] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The indiscriminate use and mismanagement of antibiotics over the last eight decades have led to one of the main challenges humanity will have to face in the next twenty years in terms of public health and economy, i.e., antimicrobial resistance. One of the key approaches to tackling antimicrobial resistance is clinical, livestock, and environmental surveillance applying methods capable of effectively identifying antimicrobial non-susceptibility as well as genes that promote resistance. Current clinical laboratory practices involve conventional culture-based antibiotic susceptibility testing (AST) methods, taking over 24 h to find out which medication should be prescribed to treat the infection. Although there are techniques that provide rapid resistance detection, it is necessary to have new tools that are easy to operate, are robust, sensitive, specific, and inexpensive. Chemical sensors and biosensors are devices that could have the necessary characteristics for the rapid diagnosis of resistant microorganisms and could provide crucial information on the choice of antibiotic (or other antimicrobial medicines) to be administered. This review provides an overview on novel biosensing strategies for the phenotypic and genotypic determination of antimicrobial resistance and a perspective on the use of these tools in modern health-care and environmental surveillance.
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Wright JG, Amin MN, Schmidt H, Hawkins AR. Performance Comparison of Flow-Through Optofluidic Biosensor Designs. BIOSENSORS 2021; 11:226. [PMID: 34356697 PMCID: PMC8301811 DOI: 10.3390/bios11070226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/01/2021] [Accepted: 07/03/2021] [Indexed: 12/04/2022]
Abstract
Optofluidic flow-through biosensors are being developed for single particle detection, particularly as a tool for pathogen diagnosis. The sensitivity of the biosensor chip depends on design parameters, illumination format (side vs. top), and flow configuration (parabolic, two- and three-dimensional hydrodynamic focused (2DHF and 3DHF)). We study the signal differences between various combinations of these design aspects. Our model is validated against a sample of physical devices. We find that side-illumination with 3DHF produces the strongest and consistent signal, but parabolic flow devices process a sample volume more quickly. Practical matters of optical alignment are also discussed, which may affect design choice.
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Affiliation(s)
- Joel G. Wright
- Electrical and Computer Engineering, Brigham Young University, 450 Engineering Building, Provo, UT 84602, USA;
| | - Md Nafiz Amin
- Electrical and Computer Engineering, University of California, 1156 High Street, Santa Cruz, CA 95064, USA; (M.N.A.); (H.S.)
| | - Holger Schmidt
- Electrical and Computer Engineering, University of California, 1156 High Street, Santa Cruz, CA 95064, USA; (M.N.A.); (H.S.)
| | - Aaron R. Hawkins
- Electrical and Computer Engineering, Brigham Young University, 450 Engineering Building, Provo, UT 84602, USA;
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10
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Meena GG, Stambaugh AM, Ganjalizadeh V, Stott MA, Hawkins AR, Schmidt H. Ultrasensitive detection of SARS-CoV-2 RNA and antigen using single-molecule optofluidic chip. APL PHOTONICS 2021; 6:066101. [PMID: 35693725 PMCID: PMC9186413 DOI: 10.1063/5.0049735] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Nucleic acids and proteins are the two most important target types used in molecular diagnostics. In many instances, simultaneous sensitive and accurate detection of both biomarkers from the same sample would be desirable, but standard detection methods are highly optimized for one type and not cross-compatible. Here, we report the simultaneous multiplexed detection of SARS-CoV-2 RNAs and antigens with single molecule sensitivity. Both analytes are isolated and labeled using a single bead-based solid-phase extraction protocol, followed by fluorescence detection on a multi-channel optofluidic waveguide chip. Direct amplification-free detection of both biomarkers from nasopharyngeal swab samples is demonstrated with single molecule detection sensitivity, opening the door for ultrasensitive dual-target analysis in infectious disease diagnosis, oncology, and other applications.
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Affiliation(s)
- G. G. Meena
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, USA
| | - A. M. Stambaugh
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, USA
| | - V. Ganjalizadeh
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, USA
| | - M. A. Stott
- Electrical and Computer Engineering Department, Brigham Young University, Provo, Utah 84602, USA
| | - A. R. Hawkins
- Electrical and Computer Engineering Department, Brigham Young University, Provo, Utah 84602, USA
| | - H. Schmidt
- School of Engineering, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, USA
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Optofluidic multiplex detection of single SARS-CoV-2 and influenza A antigens using a novel bright fluorescent probe assay. Proc Natl Acad Sci U S A 2021; 118:2103480118. [PMID: 33947795 PMCID: PMC8158013 DOI: 10.1073/pnas.2103480118] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
This work introduces an ultrasensitive single protein capture and detection technique based on a bright fluorescent reporter probe that is sensed on a photonic chip with integrated microfluidics. We perform differentiated detection of single SARS-CoV-2 and influenza A antigens at clinically relevant concentrations from clinical nasal swab materials. This ultrasensitive capture and detection technique could one day be realized as a tool for molecular diagnostics at the point of care. The urgency for the development of a sensitive, specific, and rapid point-of-care diagnostic test has deepened during the ongoing COVID-19 pandemic. Here, we introduce an ultrasensitive chip-based antigen test with single protein biomarker sensitivity for the differentiated detection of both severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A antigens in nasopharyngeal swab samples at diagnostically relevant concentrations. The single-antigen assay is enabled by synthesizing a brightly fluorescent reporter probe, which is incorporated into a bead-based solid-phase extraction assay centered on an antibody sandwich protocol for the capture of target antigens. After optimization of the probe release for detection using ultraviolet light, the full assay is validated with both SARS-CoV-2 and influenza A antigens from clinical nasopharyngeal swab samples (PCR-negative spiked with target antigens). Spectrally multiplexed detection of both targets is implemented by multispot excitation on a multimode interference waveguide platform, and detection at 30 ng/mL with single-antigen sensitivity is reported.
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Wright JG, Amin MN, Meena GG, Schmidt H, Hawkins AR. Optofluidic Flow-Through Biosensor Sensitivity - Model and Experiment. JOURNAL OF LIGHTWAVE TECHNOLOGY : A JOINT IEEE/OSA PUBLICATION 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] [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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