Detection of SARS-CoV-2 in COVID-19 Patient Nasal Swab Samples Using Signal Processing

Alahmad, Mahmoud; Olule, Lillian J. A.; Meetani, Mohammed A.; Sheikh, Farrukh Amin; Blooshi, Rahima Al; Panicker, Neena G.; Mustafa, Farah; Rizvi, Tahir A.

doi:10.1109/jstsp.2021.3134073

Cited by 3 publications

(2 citation statements)

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“…Several other immunosensors have been introduced for the detection of N-proteins in swab samples, including works done by Eissa et al [51] on the development of electrochemical immunosensors, while other studies incorporating techniques, such as chemiluminescence [77] or opto-electrical sensing. [51,78] Among the electrochemical immunosensors used for N-protein detection, the sensor prepared by Eissa et al, in which the carbon electrodes were modified with goldnanoparticle functionalized with 11-mercaptoundecanoic acid (MUA), showed the lowest LoD of 400 fg mL −1 . Apart from the complexity of the fabrication of such sensors, the clinical performance of these sensors in a large clinical cohort, in comparison with RT-PCR and in detecting samples with low viral load has not been examined.…”

Section: Discussionmentioning

confidence: 99%

CoVSense: Ultrasensitive Nucleocapsid Antigen Immunosensor for Rapid Clinical Detection of Wildtype and Variant SARS‐CoV‐2

et al. 2023

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The widespread accessibility of commercial/clinically-viable electrochemical diagnostic systems for rapid quantification of viral proteins demands translational/preclinical investigations. Here, Covid-Sense (CoVSense) antigen testing platform; an all-in-one electrochemical nano-immunosensor for sample-to-result, self-validated, and accurate quantification of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N)-proteins in clinical examinations is developed. The platform's sensing strips benefit from a highly-sensitive, nanostructured surface, created through the incorporation of carboxyl-functionalized graphene nanosheets, and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) conductive polymers, enhancing the overall conductivity of the system. The nanoengineered surface chemistry allows for compatible direct assembly of bioreceptor molecules. CoVSense offers an inexpensive (<$2 kit) and fast/digital response (<10 min), measured using a customized hand-held reader (<$25), enabling data-driven outbreak management. The sensor shows 95% clinical sensitivity and 100% specificity (Ct<25), and overall sensitivity of 91% for combined symptomatic/asymptomatic cohort with wildtype SARS-CoV-2 or B.1.1.7 variant (N = 105, nasal/throat samples). The sensor correlates the N-protein levels to viral load, detecting high Ct values of ≈35, with no sample preparation steps, while outperforming the commercial rapid antigen tests. The current translational technology fills the gap in the workflow of rapid, point-of-care, and accurate diagnosis of COVID-19.

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Section: Discussionmentioning

confidence: 99%

CoVSense: Ultrasensitive Nucleocapsid Antigen Immunosensor for Rapid Clinical Detection of Wildtype and Variant SARS‐CoV‐2

et al. 2023

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“…These have proven accurate in detecting biomarkers for Huntington's disease, COVID-19, and more. [13][14][15][16][17][18][19][20][21][22] However, most of these studies used traditional spectrometers, which are typically bulky and expensive. More recently, a new class of miniaturized spectrometers has enabled the adaptation of this technology for inexpensive point-of-care diagnostics.…”

Section: Introductionmentioning

confidence: 99%

Reagent-free Hyperspectral Diagnosis of SARS-CoV-2 Infection in saliva samples

Saint-John,

Wolf-Yadlin,

Jacobsen

et al. 2024

Preprint

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BackgroundRapid, reagent-free pathogen-agnostic diagnostics that can be performed at the point of need are vital for preparedness against future outbreaks. Yet, many current strategies (polymerase chain reaction, lateral flow immunoassays) are pathogen-specific and require reagents; whereas others such as sequencing-based methods; while agnostic, are not (as yet) conducive for use at the point of need. Herein, we present hyperspectral sensing as an opportunity to overcome these barriers, realizing truly agnostic reagent-free diagnostics. This approach can identify both pathogen and host signatures, without complex logistical considerations, in complex clinical samples. The spectral signature of biomolecules across multiple wavelength regimes provides rich biochemical information, which, coupled with machine learning, can facilitate expedited diagnosis of disease states, the feasibility of which is demonstrated here.InnovationFirst, we present ProSpectral™ V1, a novel, miniaturized (∼8 lbs) hyperspectral platform with ultra-high (2-5 nm full-width, half-max, i.e., FWHM) spectral resolution that incorporates two mini-spectrometers (visual and near-infrared). This engineering innovation has enabled reagent-free biosensing for the first time. To enable expedient outcomes, we developed state-of-the-art machine learning algorithms for near real-time analysis of multi-wavelength spectral signatures in complex samples. Taken together, these innovations enable near-field ready, reagent-free, expedient agnostic diagnostics in complex clinical samples. Herein, we demonstrate the feasibility of this synergy of ProSpectral™ V1 with machine learning to accurately identifySARS-CoV-2 infection status in double-blinded saliva samples in real-time (3 seconds/measurement). The infection status of the samples was validated with the CDC-approved polymerase-chain reaction (PCR). We report accuracies comparable to first-in-class PCR tests. Further, we provide preliminary support that this signal is specific to SARS-CoV-2, and not associated with other respiratory conditions.InterpretationPreparedness against unanticipated pathogens and democratization of diagnostics requires moving away from technologies that demand specific reagents; and relying on intrinsic biochemical properties that can, theoretically, inform onallpathologies. Integration of hyperspectral sensors and in-line machine learning analytics, as reported here, shows the feasibility of such diagnostics. If realized to full potential, the ProSpectral™ V1 platform can enable agnostic diagnostics, thereby improving situational awareness and decision-making at the point of need; especially in resource-limited settings – enabling the distribution of newly developed tests for emerging pathogens with only a simple software update.FundingThe U.S. Department of Energy, the Defense Threat Reduction Agency, Lawrence Berkeley National Laboratory, Los Alamos National Laboratory, and Pattern Computer Inc.Research in contextEvidence before this studyOur inability to quickly and effectively deploy and use reliable diagnostics at the point of need is a major limitation in our arsenal against infectious diseases. We searched PubMed and Google Scholar for articles published before May 2024 in English applying hyperspectral sensing technologies of pathogen detection with terms, “hyperspectral,” “pathogens”, and “COVID-19”. Various factors such as speed, sensitivity, availability of reagents, deployability, requirements (expertise, resources), and others determine our choice of diagnostic. Today, diagnosis of infection remains largely pathogen-specific, requiring ligands specific to the target of interest.Indeed, Polymerase Chain Reaction (PCR)-based methods, the gold-standard technology to diagnose COVID-19, are pathogen-specific and have to be re-evaluated with the emergence of new variants. Lateral flow immunoassays, while readily deployable, are associated with lower sensitivity and specificity, and require the development of ligands, which can be time-consuming when addressing unanticipated or new threats. Select pathogen-agnostic methods such as sequencing are evolving and becoming more feasible, but still require sample processing, reagents, cold-chain, and expert handlers - and hence are not (as yet) available for routine point-of-care use. In contrast, the characterization of biochemical signatures across multiple spectral regimes (hyperspectral) can facilitate reagent-free agnostic diagnostics. Yet, many spectroscopic methods are either limited to narrow wavelength ranges; or are too large for use in the point-of-care setting; and may require complex and time-consuming analytics.Added value of this studyThis manuscript presents a paradigm-shifting miniaturized hyperspectral sensor with embedded machine learning-enabled analytics that can overcome the above limitations, making reagent-free agnostic diagnostics achievable. To our knowledge, this establishes the fastest hyperspectral diagnostic platform (3 seconds/measurement), with no preprocessing and in a small form factor, and executable with liquid (clinical) samples, without ligands or reagents. Our data demonstrates that the sensitivity of this assay is comparable to gold-standard PCR-based assays; and that the signatures are specific to COVID-19 and not associated with influenza and other respiratory pathogens – establishing the truly agnostic nature of the platform. The sensor consists of two embedded spectrometers, covering spectral bandwidth 400-1700 nm, which covers spectral patterns associated with relevant biological moieties. With appropriate data processing, we demonstrate balanced accuracies between 0·97 and 1·0 under a 10-fold cross-validation (depending on the ML/AI algorithm used for prediction).Implications of all the available evidenceWith the optimization of algorithms and analytical methods and the development of appropriate spectral databases, the ProSpectral™ hyperspectral diagnostics platform can be a flexible tool for rapid, reagent-free pathogen-agnostic detection/diagnosis of disease at the point of need, which can be a disruptive force in our preparedness to counter emerging diseases and threats.

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