Dataset Information

Inflammatory Stimuli Responsive Non-Faradaic, Ultrasensitive Combinatorial Electrochemical Urine Biosensor.

ABSTRACT: In this work, we propose a novel diagnostic biosensor that can enable stratification of disease states based on severity and hence allow for clear and actionable diagnoses. The scheme can potentially boost current Point-Of-Care (POC) biosensors for diseases that require time-critical stratification. Here, two key inflammatory biomarkers-Interleukin-8 and Interleukin-6-have been explored as proof of concept, and a four-class stratification of inflammatory disease severity is discussed. Our method is superior to traditional lab techniques as it is faster (<4 minutes turn-around time) and can work with any combination of disease biomarkers to categorize diseases by subtypes and severity. At its core, the biosensor relies on electrochemical impedance spectroscopy to transduce subtle inflammatory stimuli at the input for IL-8 and IL-6 for a limit of detection (LOD) of 1 pg/mL each. The biosensing scheme utilizes a two-stage random forest machine learning model for 4-state output disease classification with a 98.437% accuracy. This scheme can potentially boost the diagnostic power of current electrochemical biosensors for better precision therapy and improved patient outcomes.

SUBMITTER: Ganguly A

PROVIDER: S-EPMC9611881 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Inflammatory Stimuli Responsive Non-Faradaic, Ultrasensitive Combinatorial Electrochemical Urine Biosensor.

Ganguly Antra A Gunda Varun V Thai Kevin K Prasad Shalini S

Sensors (Basel, Switzerland) 20221013 20

In this work, we propose a novel diagnostic biosensor that can enable stratification of disease states based on severity and hence allow for clear and actionable diagnoses. The scheme can potentially boost current Point-Of-Care (POC) biosensors for diseases that require time-critical stratification. Here, two key inflammatory biomarkers—Interleukin-8 and Interleukin-6—have been explored as proof of concept, and a four-class stratification of inflammatory disease severity is discussed. Our method ...[more]

PMID: 36298107

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Project description:A large-scale diagnosis of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is essential to downregulate its spread within as well as across communities and mitigate the current outbreak of the pandemic novel coronavirus disease 2019 (COVID-19). Herein, we report the development of a rapid (less than 5 min), low-cost, easy-to-implement, and quantitative paper-based electrochemical sensor chip to enable the digital detection of SARS-CoV-2 genetic material. The biosensor uses gold nanoparticles (AuNPs), capped with highly specific antisense oligonucleotides (ssDNA) targeting viral nucleocapsid phosphoprotein (N-gene). The sensing probes are immobilized on a paper-based electrochemical platform to yield a nucleic-acid-testing device with a readout that can be recorded with a simple hand-held reader. The biosensor chip has been tested using samples collected from Vero cells infected with SARS-CoV-2 virus and clinical samples. The sensor provides a significant improvement in output signal only in the presence of its target-SARS-CoV-2 RNA-within less than 5 min of incubation time, with a sensitivity of 231 (copies ?L-1)-1 and limit of detection of 6.9 copies/?L without the need for any further amplification. The sensor chip performance has been tested using clinical samples from 22 COVID-19 positive patients and 26 healthy asymptomatic subjects confirmed using the FDA-approved RT-PCR COVID-19 diagnostic kit. The sensor successfully distinguishes the positive COVID-19 samples from the negative ones with almost 100% accuracy, sensitivity, and specificity and exhibits an insignificant change in output signal for the samples lacking a SARS-CoV-2 viral target segment (e.g., SARS-CoV, MERS-CoV, or negative COVID-19 samples collected from healthy subjects). The feasibility of the sensor even during the genomic mutation of the virus is also ensured from the design of the ssDNA-conjugated AuNPs that simultaneously target two separate regions of the same SARS-CoV-2 N-gene.

Dataset Information

Inflammatory Stimuli Responsive Non-Faradaic, Ultrasensitive Combinatorial Electrochemical Urine Biosensor.

Publications

Inflammatory Stimuli Responsive Non-Faradaic, Ultrasensitive Combinatorial Electrochemical Urine Biosensor.

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