The COVID-19 pandemic demonstrated the public health benefits of reliable and accessible point-of-care (POC) diagnostic tests for viral infections. Despite the rapid development of gold-standard reverse transcription polymerase chain reaction (RT-PCR) assays for SARS-CoV-2 only weeks into the pandemic, global demand created logistical challenges that delayed access to testing for months and helped fuel the spread of COVID-19. Additionally, the extreme sensitivity of RT-PCR had a costly downside as the tests could not differentiate between patients with active infection and those who were no longer infectious but still shedding viral genomes. To address these issues for the future, we propose a novel membrane-based sensor that only detects intact virions. The sensor combines affinity and size based detection on a membrane-based sensor and does not require external power to operate or read. Specifically, the presence of intact virions, but not viral debris, fouls the membrane and triggers a macroscopically visible hydraulic switch after injection of a 40 μL sample with a pipette. The device, which we call the μSiM-DX (microfluidic device featuring a silicon membrane for diagnostics), features a biotin-coated microslit membrane with pores ∼2–3× larger than the intact virus. Streptavidin-conjugated antibody recognizing viral surface proteins are incubated with the sample for ∼1 hour prior to injection into the device, and positive/negative results are obtained within ten seconds of sample injection. Proof-of-principle tests have been performed using preparations of vaccinia virus. After optimizing slit pore sizes and porous membrane area, the fouling-based sensor exhibits 100% specificity and 97% sensitivity for vaccinia virus ( n = 62). Moreover, the dynamic range of the sensor extends at least from 10 5.9 virions per mL to 10 10.4 virions per mL covering the range of mean viral loads in symptomatic COVID-19 patients (10 5.6 –10 7 RNA copies per mL). Forthcoming work will test the ability of our sensor to perform similarly in biological fluids and with SARS-CoV-2, to fully test the potential of a membrane fouling-based sensor to serve as a PCR-free alternative for POC containment efforts in the spread of infectious disease.
more »
« less
Direct detection of human adenovirus or SARS-CoV-2 with ability to inform infectivity using DNA aptamer-nanopore sensors
Viral infections are a major global health issue, but no current method allows rapid, direct, and ultrasensitive quantification of intact viruses with the ability to inform infectivity, causing misdiagnoses and spread of the viruses. Here, we report a method for direct detection and differentiation of infectious from noninfectious human adenovirus and SARS-CoV-2, as well as from other virus types, without any sample pretreatment. DNA aptamers are selected from a DNA library to bind intact infectious, but not noninfectious, virus and then incorporated into a solid-state nanopore, which allows strong confinement of the virus to enhance sensitivity down to 1 pfu/ml for human adenovirus and 1 × 10 4 copies/ml for SARS-CoV-2. Applications of the aptamer-nanopore sensors in different types of water samples, saliva, and serum are demonstrated for both enveloped and nonenveloped viruses, making the sensor generally applicable for detecting these and other emerging viruses of environmental and public health concern.
more »
« less
- Award ID(s):
- 2029215
- NSF-PAR ID:
- 10335872
- Date Published:
- Journal Name:
- Science Advances
- Volume:
- 7
- Issue:
- 39
- ISSN:
- 2375-2548
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
SARS-CoV-2 continues to upend human life by posing novel threats related to disease spread and mutations. Current models for the disease burden of SARS-CoV-2 consider the aggregate nature of the virus without differentiating between the potency of its multiple strains. Hence, there is a need to create a fundamental modeling framework for multi-strain viruses that considers the competing viral pathogenic pathways. Alongside the consideration that other viral pathogens may coexist, there is also a need for a generalizable modeling framework to account for multiple epidemics (i.e., multi-demics) scenarios, such as influenza and COVID-19 occurring simultaneously. We present a fundamental network thermodynamics approach for assessing, determining, and predicting viral outbreak severity, which extends well-known standard epidemiological models. In particular, we use historical data from New York City’s 2011–2019 influenza seasons and SARS-CoV-2 spread to identify the model parameters. In our model-based analysis, we employ a standard susceptible–infected–recovered (SIR) model with pertinent generalizations to account for multi-strain and multi-demics scenarios. We show that the reaction affinities underpinning the formation processes of our model can be used to categorize the severity of infectious or deceased populations. The spontaneity of occurrence captured by the change in Gibbs free energy of reaction (ΔG) in the system suggests the stability of forward occurring population transfers. The magnitude of ΔG is used to examine past influenza outbreaks and infer epidemiological factors, such as mortality and case burden. This method can be extrapolated for wide-ranging utility in computational epidemiology. The risk of overlapping multi-demics seasons between influenza and SARS-CoV-2 will persist as a significant threat in forthcoming years. Further, the possibility of mutating strains requires novel ways of analyzing the network of competing infection pathways. The approach outlined in this study allows for the identification of new stable strains and the potential increase in disease burden from a complex systems perspective, thereby allowing for a potential response to the significant question: are the effects of a multi-demic greater than the sum of its individual viral epidemics?more » « less
-
more » « less
Abstract The rapidly expanding severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and its variants demand a continuous monitoring method through portable and wearable devices. Utilizing the rich surface chemistry and high chemical‐to‐electrical signal conversion of 2D MXene‐graphene heterostructure thin films, a field‐effect‐transistor (FET) sensor, which has a flexible substrate to be assembled onto the mask and combines with a Bluetooth system for wireless transmission is developed, to detect the influenza and SARS‐CoV‐2 viruses in air and breath. At first, the developed sensors are examined in the laboratory through direct contact with sensing targets in solution form. The results show a low limit of detection (LOD) of 1 fg mL−1for recombinant SARS‐CoV‐2 spike protein and 125 copies mL−1for inactivated influenza A (H1N1) virus with high specificity in differing recombinant SARS‐CoV‐2 spike protein and inactivated H1N1 virus. Then the sensors are tested under various simulated human breathing modes through controlled exposure to atomizer‐generated aerosols in an enclosed chamber and mask coverage. The results show the high sensitivity of the developed sensors under varying distances to the source, viral load, flow rate, and enclosed conditions. At last, clinical tests are carried out to demonstrate the robustness and potential field applications of the sensors.
-
Background: Among the most consequential unknowns of the devastating COVID-19 pandemic are the durability of immunity and time to likely reinfection. There are limited direct data on SARS-CoV-2 long-term immune responses and reinfection. The aim of this study is to use data on the durability of immunity among evolutionarily close coronavirus relatives of SARS-CoV-2 to estimate times to reinfection by a comparative evolutionary analysis of related viruses SARS-CoV, MERS-CoV, human coronavirus (HCoV)-229E, HCoV-OC43, and HCoV-NL63. Methods: We conducted phylogenetic analyses of the S, M, and ORF1b genes to reconstruct a maximum-likelihood molecular phylogeny of human-infecting coronaviruses. This phylogeny enabled comparative analyses of peak-normalised nucleocapsid protein, spike protein, and whole-virus lysate IgG antibody optical density levels, in conjunction with reinfection data on endemic human-infecting coronaviruses. We performed ancestral and descendent states analyses to estimate the expected declines in antibody levels over time, the probabilities of reinfection based on antibody level, and the anticipated times to reinfection after recovery under conditions of endemic transmission for SARS-CoV-2, as well as the other human-infecting coronaviruses. Findings: We obtained antibody optical density data for six human-infecting coronaviruses, extending from 128 days to 28 years after infection between 1984 and 2020. These data provided a means to estimate profiles of the typical antibody decline and probabilities of reinfection over time under endemic conditions. Reinfection by SARS-CoV-2 under endemic conditions would likely occur between 3 months and 5·1 years after peak antibody response, with a median of 16 months. This protection is less than half the duration revealed for the endemic coronaviruses circulating among humans (5-95% quantiles 15 months to 10 years for HCoV-OC43, 31 months to 12 years for HCoV-NL63, and 16 months to 12 years for HCoV-229E). For SARS-CoV, the 5-95% quantiles were 4 months to 6 years, whereas the 95% quantiles for MERS-CoV were inconsistent by dataset. Interpretation: The timeframe for reinfection is fundamental to numerous aspects of public health decision making. As the COVID-19 pandemic continues, reinfection is likely to become increasingly common. Maintaining public health measures that curb transmission-including among individuals who were previously infected with SARS-CoV-2-coupled with persistent efforts to accelerate vaccination worldwide is critical to the prevention of COVID-19 morbidity and mortality. Funding: US National Science Foundation.more » « less
-
Abstract Rapid, inexpensive, and easy-to-use coronavirus disease 2019 (COVID-19) home tests are key tools in addition to vaccines in the world wide fight to eliminate national and local shutdowns. However, currently available tests for SARS-CoV-2, the virus that causes COVID-19, are too expensive, painful, and irritating, or not sufficiently sensitive for routine, accurate home testing. Herein, we employ custom-formulated graphene inks and aerosol jet printing to create a rapid electrochemical immunosensor for direct detection of SARS-CoV-2 spike receptor-binding domain (RBD) in saliva samples acquired noninvasively. This sensor demonstrated limits of detection that are considerably lower than most commercial SARS-CoV-2 antigen tests (22.91 ± 4.72 pg ml −1 for spike RBD and 110.38 ± 9.00 pg ml −1 for spike S1) as well as fast response time (∼30 min), which was facilitated by the functionalization of printed graphene electrodes in a single-step with SARS-CoV-2 polyclonal antibody through the carbodiimide reaction without the need for nanoparticle functionalization or secondary antibody or metallic nanoparticle labels. This immunosensor presents a wide linear sensing range from 1 to 1000 ng ml −1 and does not react with other coexisting influenza viruses such as H1N1 hemagglutinin. By combining high-yield graphene ink synthesis, automated printing, high antigen selectivity, and rapid testing capability, this work offers a promising alternative to current SARS-CoV-2 antigen tests.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1126/sciadv.abh2848
