COVID-19 diagnostics in context

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest in developing COVID-19 serology tests to monitor population-level immunity. To address this critical need, we designed a paper-based multiplexed vertical flow assay (xVFA) using five structural proteins of SARS-CoV-2, detecting IgG and IgM antibodies to monitor changes in COVID-19 immunity levels. Our platform not only tracked longitudinal immunity levels but also categorized COVID-19 immunity into three groups: protected, unprotected, and infected, based on the levels of IgG and IgM antibodies. We operated two xVFAs in parallel to detect IgG and IgM antibodies using a total of 40 μL of human serum sample in <20 min per test. After the assay, images of the paper-based sensor panel were captured using a mobile phone-based custom-designed optical reader and then processed by a neural network-based serodiagnostic algorithm. The serodiagnostic algorithm was trained with 120 measurements/tests and 30 serum samples from 7 randomly selected individuals and was blindly tested with 31 serum samples from 8 different individuals, collected before vaccination as well as after vaccination or infection, achieving an accuracy of 89.5%. The competitive performance of the xVFA, along with its portability, cost-effectiveness, and rapid operation, makes it a promising computational point-of-care (POC) serology test for monitoring COVID-19 immunity, aiding in timely decisions on the administration of booster vaccines and general public health policies to protect vulnerable populations.

An Automated Versatile Diagnostic Workflow for Infectious Disease Detection in Low-Resource Settings

Laboratory automation effectively increases the throughput in sample analysis, reduces human errors in sample processing, as well as simplifies and accelerates the overall logistics. Automating diagnostic testing workflows in peripheral laboratories and also in near-patient settings -like hospitals, clinics and epidemic control checkpoints- is advantageous for the simultaneous processing of multiple samples to provide rapid results to patients, minimize the possibility of contamination or error during sample handling or transport, and increase efficiency. However, most automation platforms are expensive and are not easily adaptable to new protocols. Here, we address the need for a versatile, easy-to-use, rapid and reliable diagnostic testing workflow by combining open-source modular automation (Opentrons) and automation-compatible molecular biology protocols, easily adaptable to a workflow for infectious diseases diagnosis by detection on paper-based diagnostics. We demonstrated the feasibility of automation of the method with a low-cost Neisseria meningitidis diagnostic test that utilizes magnetic beads for pathogen DNA isolation, isothermal amplification, and detection on a paper-based microarray. In summary, we integrated open-source modular automation with adaptable molecular biology protocols, which was also faster and cheaper to perform in an automated than in a manual way. This enables a versatile diagnostic workflow for infectious diseases and we demonstrated this through a low-cost N. meningitidis test on paper-based microarrays.

A Fast and Sensitive One-Tube SARS-CoV-2 Detection Platform Based on RTX-PCR and Pyrococcus furiosus Argonaute

Since SARS-CoV-2 is a highly transmissible virus, alternative reliable, fast, and cost-effective methods are still needed to prevent virus spread that can be applied in the laboratory and for point-of-care testing. Reverse transcription real-time fluorescence quantitative PCR (RT-qPCR) is currently the gold criteria for detecting RNA viruses, which requires reverse transcriptase to reverse transcribe viral RNA into cDNA, and fluorescence quantitative PCR detection was subsequently performed. The frequently used reverse transcriptase is thermolabile; the detection process is composed of two steps: the reverse transcription reaction at a relatively low temperature, and the qPCR performed at a relatively high temperature, moreover, the RNA to be detected needs to pretreated if they had advanced structure. Here, we develop a fast and sensitive one-tube SARS-CoV-2 detection platform based on Ultra-fast RTX-PCR and Pyrococcus furiosus Argonaute-mediated Nucleic acid Detection (PAND) technology (URPAND). URPAND was achieved ultra-fast RTX-PCR process based on a thermostable RTX (exo-) with both reverse transcriptase and DNA polymerase activity. The URPAND can be completed RT-PCR and PAND to detect nucleic acid in one tube within 30 min. This method can specifically detect SARS-CoV-2 with a low detection limit of 100 copies/mL. The diagnostic results of clinical samples with one-tube URPAND displayed 100% consistence with RT-qPCR test. Moreover, URPAND was also applied to identify SARS-CoV-2 D614G mutant due to its single-nucleotide specificity. The URPAND platform is rapid, accurate, tube closed, one-tube, easy-to-operate and free of large instruments, which provides a new strategy to the detection of SARS-CoV-2 and other RNA viruses.

Are self-test kits still relevant post COVID-19 pandemic? Qualitative study on working adults' perceptions

BACKGROUND

Other than self-isolation measures, self-testing is likely to reduce the transmission of COVID-19 and may become a valuable approach in future outbreaks of infectious diseases. This study delves into the perceptions and experiences of working adults who utilised COVID-19 self-test kits in Singapore during the post-pandemic period.

METHODS

Employing a qualitative descriptive design, in-depth interviews were conducted with 40 working adults from diverse occupations, with a median age of 35 years. Thematic analysis of transcribed interviews was carried out by two independent qualitative research-trained researchers.

RESULTS

Facilitators included personal motivations like safeguarding vulnerable individuals and the convenience of user-friendly self-test kits. Proximal environmental factors encompassed situations involving close contacts and large gatherings, while distal factors involved workplace regulations, public health campaigns, mass media influence, and trust in authorised kits. Nonetheless, barriers include discomfort, cost, uncertainty about proper technique, and evolving testing requirements. Positive test results prompted participants to notify contacts and self-isolate, whereas negative results encouraged a return to normalcy. Participants recommend sustained testing for new variants and vulnerable groups, though some view it as unnecessary due to pandemic normalisation.

CONCLUSIONS

Self-testing emerged as a social phenomenon influenced by societal obligations and relationships across multiple levels. Effective communication strategies may play a role in fostering trust and ensuring that working adults sustain the practice of self-testing; therefore, further research is needed to explore their potential impact. Such efforts could be valuable for maintaining vigilance and achieving effective disease control in the post-COVID-19 pandemic landscape.

Socioeconomic and Demographic Effects on SARS-CoV-2 Testing: Evidence From the State of Uttar Pradesh, India

Background The rapid global spread of SARS-CoV-2 highlighted critical challenges in healthcare systems worldwide, with differences in testing access and utilization becoming particularly evident. This study investigates the socioeconomic and demographic factors influencing SARS-CoV-2 testing service access and utilization during the second wave of the pandemic in Uttar Pradesh (UP), India. Methods The study was conducted from July to October 2023 in two districts of Uttar Pradesh (UP). These districts were chosen because one had the highest and the other the lowest SARS-CoV-2 testing rates per million population as reported from March to June 2021. The study population included consenting adult individuals with self-reported symptoms indicative of SARS-CoV-2 infection during March-June 2021. The study excluded individuals under 18 years, those who did not consent, pregnant or lactating mothers, and those with communication-impairing medical conditions. Data were collected using a structured questionnaire based on Andersen's Behavioural Model of Health Services Use. We used chi-squared tests for all categorical variables to obtain p-values and Poisson regression to identify factors influencing testing rates. Results We screened 4,595 individuals and identified 675 eligible participants for this study. Adjusted prevalence ratios derived from multiple variate Poisson regression models showed that participants in Sitapur had a 0.47 (95% CI: 0.39-0.57) times the prevalence of being tested than those in Lucknow. Furthermore, individuals from other backward castes and scheduled castes had a 1.15 (95% CI: 0.99-1.34) and 1.22 (95% CI: 0.95-1.56) times prevalence of being tested for SARS-CoV-2, respectively, when compared to the general caste population. Scheduled Tribes showed a higher prevalence of being tested, contrasting with existing literature. Households with low, middle, and high income showed a 1.46 (95% CI: 1.12-1.89), 1.52 (95% CI: 1.14-2.02), and 1.73 (95% CI: 1.23-2.45) times the prevalence of SARS-CoV-2 testing compared to those below the poverty line, respectively. Behavioral factors such as media use showed an inverse relationship with testing prevalence; individuals who did not watch TV at all had a 0.83 (95% CI: 0.70-0.99) times prevalence of being tested compared to frequent viewers, and similarly, those not using the internet on mobiles had a 0.82 (95% CI: 0.67-0.99) times prevalence than daily users. Individuals using private healthcare facilities had a 0.87 (95% CI: 0.77-0.99) times prevalence of SARS-CoV-2 testing compared to those using government facilities. Conclusions These findings highlight the importance of public health strategies that address socio-economic and behavioral disparities to ensure equitable testing access across all community groups.

Pseudo-Luciferase Activity of the SARS-CoV-2 Spike Protein for Cypridina Luciferin

Enzymatic reactions that involve a luminescent substrate (luciferin) and enzyme (luciferase) from luminous organisms enable a luminescence detection of target proteins and cells with high specificity, albeit that conventional assay design requires a prelabeling of target molecules with luciferase. Here, we report a luciferase-independent luminescence assay in which the target protein directly catalyzes the oxidative luminescence reaction of luciferin. The SARS-CoV-2 antigen (spike) protein catalyzes the light emission of Cypridina luciferin, whereas no such catalytic function was observed for salivary proteins. This selective luminescence reaction is due to the enzymatic recognition of the 3-(1-guanidino)propyl group in luciferin at the interfaces between the units of the spike protein, allowing a specific detection of the spike protein in human saliva without sample pretreatment. This method offers a novel platform to detect virus antigens simply and rapidly without genetic manipulation or antibodies.

Assessment of the clinical and analytical performance of three Seegene Allplex SARS-CoV-2 assays within the VALCOR framework

The coronavirus disease 2019 (COVID-19) pandemic demonstrated the need for accurate diagnostic testing for the early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although the pandemic has ended, accurate assays are still needed to monitor viral spread at national levels and beyond through population and wastewater surveillance. To enhance early detection, SARS-CoV-2 assays should have high diagnostic accuracy and should be validated to assure accurate results. Three distinct SARS-CoV-2 assays were evaluated with clinical samples using the VALCOR (VALidation of SARS-CORona Virus-2 assays) framework, with the TaqPath COVID-19 assay (ThermoFisher Scientific, USA) as a comparator. We evaluated clinical sensitivity, specificity, limit of detection (LOD), and overall concordance between comparator and three index Allplex SARS-CoV-2 assays (Seegene, South Korea): Allplex-SC2, Allplex-SC2Fast (Fast PCR), and Allplex-SC2FabR (SARS-CoV-2/FluA/FluB/respiratory syncytial virus). Analytical performance and LOD of index assays were assessed using a dilution series of three synthetic SARS-CoV-2 sequence reference materials (RMs). Ninety SARS-CoV-2 positives and 90 SARS-CoV-2 negatives were tested. All Allplex assays had 100.0% sensitivity (95%CI = 95.9%-100.0%). Allplex-SC2 and Allplex-SC2Fast assays had 97.8% specificity (95%CI = 92.3%-99.7%) and 98.9% overall concordance [κ = 0.978 (95%CI = 0.947-1.000)]. Allplex-SC2FabR assay showed 100.0% specificity (95%CI = 95.9%-100.0%) and 100.0% overall concordance [κ = 1.000 (95%CI = 1.000-1.000)]. LOD assessment of index assays revealed detection down to 2.61 × 102 copies/mL in clinical samples, while the analytical LOD was 9.00 × 102 copies/mL. In conclusion, the evaluation of the three Seegene Allplex SARS-CoV-2 assays showed high sensitivity and specificity and an overall good assay concordance with the comparator. The assays showed low analytical LOD using RM and even a slightly lower LOD in clinical samples. Non-overlapping target gene sequences between SARS-CoV-2 assays and RMs emphasize the need for aligning targeted sequences of diagnostic assays and RMs.IMPORTANCEThe coronavirus disease 2019 pandemic has a significant impact on global public health, economies, and societies. As shown through the first phases of the pandemic, accurate and timely diagnosis is crucial for disease control, prevention, and monitoring. Though the pandemic phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has concluded, diagnostic assays remain in demand to monitor SARS-CoV-2 at the individual patient level, regionally, and nationally, as well as to remain an infectious disease preparedness instrument to monitor any new SARS-CoV-2 dissemination across borders using population and wastewater surveillance. The anticipation by WHO and central health care policy entities such as the Center for Disease Control, EMA, and multiple national health authorities is that SARS-CoV-2 will reside as an endemic respiratory disease for years to come. The key strategic consideration is hence shifting from combating a pandemic situation with a high number of patients to instead allowing precise diagnostics of suspected patients with the intention of correct management in a low-prevalence setting.

A comprehensive review on immunogen and immune-response proteins of SARS-CoV-2 and their applications in prevention, diagnosis, and treatment of COVID-19

Exposure to severe acute respiratory syndrome-corona virus-2 (SARS-CoV-2) prompts humoral immune responses in the human body. As the auxiliary diagnosis of a current infection, the existence of viral proteins can be checked from specific antibodies (Abs) induced by immunogenic viral proteins. For people with a weakened immune system, Ab treatment can help neutralize viral antigens to resist and treat the disease. On the other hand, highly immunogenic viral proteins can serve as effective markers for detecting prior infections. Additionally, the identification of viral particles or the presence of antibodies may help establish an immune defense against the virus. These immunogenic proteins rather than SARS-CoV-2 can be given to uninfected people as a vaccination to improve their coping ability against COVID-19 through the generation of memory plasma cells. In this work, we review immunogenic and immune-response proteins derived from SARS-CoV-2 with regard to their classification, origin, and diverse applications (e.g., prevention (vaccine development), diagnostic testing, and treatment (via neutralizing Abs)). Finally, advanced immunization strategies against COVID-19 are discussed along with the contemporary circumstances and future challenges.

UbiNAAT: a multiplexed point-of-care nucleic acid diagnostic platform for rapid at-home pathogen detection

The COVID-19 pandemic increased demands for respiratory disease testing to facilitate treatment and limit transmission, demonstrating in the process that most existing test options were too complex and expensive to perform in point-of-care or home scenarios. Lab-based molecular techniques can detect viral RNA in respiratory illnesses but are expensive and require trained personnel, while affordable antigen-based home tests lack sensitivity for early detection in newly infected or asymptomatic individuals. The few home RNA detection tests deployed were prohibitively expensive. Here, we demonstrate a point-of-care, paper-based rapid analysis device that simultaneously detects multiple viral RNAs; it is demonstrated on two common respiratory viruses (COVID-19 and influenza A) spiked onto a commercial nasal swab. The automated device requires no sample preparation by the user after insertion of the swab, minimizing user operation steps. We incorporated lyophilized amplification reagents immobilized in a porous matrix, a novel thermally actuated valve for multiplexed fluidic control, a printed circuit board that performs on-device lysis and amplification within a cell-phone-sized disposable device. Reverse transcription loop-mediated isothermal amplification (RT-LAMP) products are visualized via fluorescent dyes using a modified cell phone, resulting in detection of as few as 104 viral copies per swab across both pathogens within 30 minutes. This integrated platform could be commercialized in a form that would be inexpensive, portable, and sensitive; it can readily be multiplexed to detect as many as 8 different RNA or DNA sequences, and adapted to any desired RNA or DNA detection assays.

Computational design of scFv anti-receptor binding domain of SARS-CoV-2 spike protein based on antibody S230 anti-SARS-CoV-1

Developing therapeutics such as neutralizing antibodies targeting the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein is essential to halt the Covid-19 infection. However, antibody production is expensive and relatively inaccessible to many low-income countries. Therefore, a more efficient and smaller antibody fragment, such as a single-chain variable fragment (scFv), derived from a known neutralizing antibody structure, is of interest due to the lower cost of recombinant protein production and the ability to tailor scFvs against circulating viruses. In this study, we used computational design to create an scFv based on the structure of a known neutralizing antibody, S230, for SARS-CoV-1. By analyzing the interaction of S230 with the RBD of both SARS-CoV-1 and SARS-CoV-2, five mutations were introduced to improve the binding of the scFv to the RBD of SARS-CoV-2. These mutations were Ser32Thr, Trp99Val, Asn57Val, Lys65Glu, and Tyr106Ile. Molecular dynamics simulations were used to evaluate the stability and affinity of the designed scFv. Our results showed that the designed scFv improved binding to the RBD of SARS-CoV-2 compared to the original S230, as indicated by principal component analysis, distance analysis, and MM/GBSA interaction energy. Furthermore, a positive result in a spot test lateral flow assay of the expressed scFv against the RBD indicated that the mutations did not alter the protein's structure. The designed scFv showed a negative result when tested against human serum albumin as a negative control, indicating reasonable specificity. We hope that this study will be useful in designing a specific and low-cost therapeutic agent, particularly during early outbreaks when information on neutralizing antibodies is limited.Communicated by Ramaswamy H. Sarma.

Development of automated microfluidic immunoassays for the detection of SARS-CoV-2 antibodies and antigen

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the coronavirus disease 2019 (COVID-19) global pandemic. Rapid and sensitive detection of the virus soon after infection is important for the treatment and prevention of transmission of COVID-19, and detection of antibodies is important for epidemiology, assessment of vaccine immunogenicity, and identification of the natural reservoir and intermediate host(s). Patient nasal or oropharyngeal swabs or saliva used in conjunction with polymerase chain reaction (PCR) detect SARS-CoV-2 RNA, whereas lateral flow immunoassays (LFI) detect SARS-CoV-2 proteins. Enzyme-linked immunosorbent assays (ELISA) detect anti-SARS-CoV-2 antibodies in blood. Although effective, these assays have poor sensitivity (e.g., LFI) or are labor intensive and time consuming (PCR and ELISA). Here we describe the development of rapid, automated ELISA-based immunoassays to detect SARS-CoV-2 antigens and antibodies against the virus. The Simple Plex™ platform uses rapid microfluidic reaction kinetics for sensitive analyte detection with small sample volumes. We developed three sensitive <90-min Simple Plex immunoassays that measure either the SARS-CoV-2 antigens or the immune response to SARS-CoV-2, including neutralizing antibodies, in serum from COVID-19 patients.

COVID-19 infection segmentation using hybrid deep learning and image processing techniques

The coronavirus disease 2019 (COVID-19) epidemic has become a worldwide problem that continues to affect people's lives daily, and the early diagnosis of COVID-19 has a critical importance on the treatment of infected patients for medical and healthcare organizations. To detect COVID-19 infections, medical imaging techniques, including computed tomography (CT) scan images and X-ray images, are considered some of the helpful medical tests that healthcare providers carry out. However, in addition to the difficulty of segmenting contaminated areas from CT scan images, these approaches also offer limited accuracy for identifying the virus. Accordingly, this paper addresses the effectiveness of using deep learning (DL) and image processing techniques, which serve to expand the dataset without the need for any augmentation strategies, and it also presents a novel approach for detecting COVID-19 virus infections in lung images, particularly the infection prediction issue. In our proposed method, to reveal the infection, the input images are first preprocessed using a threshold then resized to 128 × 128. After that, a density heat map tool is used for coloring the resized lung images. The three channels (red, green, and blue) are then separated from the colored image and are further preprocessed through image inverse and histogram equalization, and are subsequently fed, in independent directions, into three separate U-Nets with the same architecture for segmentation. Finally, the segmentation results are combined and run through a convolution layer one by one to get the detection. Several evaluation metrics using the CT scan dataset were used to measure the performance of the proposed approach in comparison with other state-of-the-art techniques in terms of accuracy, sensitivity, precision, and the dice coefficient. The experimental results of the proposed approach reached 99.71%, 0.83, 0.87, and 0.85, respectively. These results show that coloring the CT scan images dataset and then dividing each image into its RGB image channels can enhance the COVID-19 detection, and it also increases the U-Net power in the segmentation when merging the channel segmentation results. In comparison to other existing segmentation techniques employing bigger 512 × 512 images, this study is one of the few that can rapidly and correctly detect the COVID-19 virus with high accuracy on smaller 128 × 128 images using the metrics of accuracy, sensitivity, precision, and dice coefficient.

Biological biomarkers of oral cancer

The oral squamous cell carcinoma (OSCC) 5 year survival rate of 41% has marginally improved in the last few years, with less than a 1% improvement per year from 2005 to 2017, with higher survival rates when detected at early stages. Based on histopathological grading of oral dysplasia, it is estimated that severe dysplasia has a malignant transformation rate of 7%-50%. Despite these numbers, oral dysplasia grading does not reliably predict its clinical behavior. Thus, more accurate markers predicting oral dysplasia progression to cancer would enable better targeting of these lesions for closer follow-up, especially in the early stages of the disease. In this context, molecular biomarkers derived from genetics, proteins, and metabolites play key roles in clinical oncology. These molecular signatures can help predict the likelihood of OSCC development and/or progression and have the potential to detect the disease at an early stage and, support treatment decision-making and predict treatment responsiveness. Also, identifying reliable biomarkers for OSCC detection that can be obtained non-invasively would enhance management of OSCC. This review will discuss biomarkers for OSCC that have emerged from different biological areas, including genomics, transcriptomics, proteomics, metabolomics, immunomics, and microbiomics.

Clinical Characteristics, Diagnosis, and Therapeutics of COVID-19: A Review

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that suddenly emerged at the end of December 2019 and caused coronavirus disease 2019 (COVID-19) continues to afflict humanity, not only seriously affecting healthcare systems but also leading to global social and economic imbalances. As of August 2022, there were approximately 580 million confirmed cases of COVID-19 and approximately 6.4 million confirmed deaths due to this disease. The data are sufficient to highlight the seriousness of SARS-CoV-2 infection. Although most patients with COVID-19 present primarily with respiratory symptoms, an increasing number of extrapulmonary systemic symptoms and manifestations have been associated with COVID-19. Since the outbreak of COVID-19, much has been learned about the disease and its causative agent. Therefore, great effort has been aimed at developing treatments and drug interventions to treat and reduce the incidence of COVID-19. In this narrative review, we provide a brief overview of the epidemiology, mechanisms, clinical manifestations, diagnosis, and therapeutics of COVID-19.

Uncovering the morphological differences between SARS-CoV-2 and SARS-CoV based on transmission electron microscopy images

Comprehending the morphological disparities between SARS-CoV-2 and SARS-CoV viruses can shed light on the underlying mechanisms of infection and facilitate the development of effective diagnostic tools and treatments. Hence, this study aimed to conduct a comprehensive analysis and comparative assessment of the morphology of SARS-CoV-2 and SARS-CoV using transmission electron microscopy (TEM) images. The dataset encompassed 519 isolated SARS-CoV-2 images obtained from patients in Italy (INMI) and 248 isolated SARS-CoV images from patients in Germany (Frankfurt). In this paper, we employed TEM images to scrutinize morphological features, and the outcomes were contrasted with those of SARS-CoV viruses. The findings reveal disparities in the characteristics of SARS-CoV-2 and SARS-CoV, such as envelope protein (E) 98.6 and 102.2 nm, length of spike protein (S) 10.11 and 9.50 nm, roundness 0.86 and 0.88, circularity 0.78 and 0.76, and area sizes 25145.54 and 38591.35 pixels, respectively. In conclusion, these results will augment the identification of virus subtypes, aid in the study of antiviral medications, and enhance our understanding of disease progression and the virus life cycle. Moreover, these findings have the potential to assist in the development of more accurate epidemiological prediction models for COVID-19, leading to better outbreak management and saving lives.

Single virus fingerprinting by widefield interferometric defocus-enhanced mid-infrared photothermal microscopy

Clinical identification and fundamental study of viruses rely on the detection of viral proteins or viral nucleic acids. Yet, amplification-based and antigen-based methods are not able to provide precise compositional information of individual virions due to small particle size and low-abundance chemical contents (e.g., ~ 5000 proteins in a vesicular stomatitis virus). Here, we report a widefield interferometric defocus-enhanced mid-infrared photothermal (WIDE-MIP) microscope for high-throughput fingerprinting of single viruses. With the identification of feature absorption peaks, WIDE-MIP reveals the contents of viral proteins and nucleic acids in single DNA vaccinia viruses and RNA vesicular stomatitis viruses. Different nucleic acid signatures of thymine and uracil residue vibrations are obtained to differentiate DNA and RNA viruses. WIDE-MIP imaging further reveals an enriched β sheet components in DNA varicella-zoster virus proteins. Together, these advances open a new avenue for compositional analysis of viral vectors and elucidating protein function in an assembled virion.

CRISPR-Based Precision Molecular Diagnostics for Disease Detection and Surveillance

Sensitive, rapid, and portable molecular diagnostics is the future of disease surveillance, containment, and therapy. The recent SARS-CoV-2 pandemic has reminded us of the vulnerability of lives from ever-evolving pathogens. At the same time, it has provided opportunities to bridge the gap by translating basic molecular biology into therapeutic tools. One such molecular biology technique is CRISPR (clustered regularly interspaced short palindromic repeat) which has revolutionized the field of molecular diagnostics at the need of the hour. The use of CRISPR-Cas systems has been widespread in biology research due to the ease of performing genetic manipulations. In 2012, CRISPR-Cas systems were, for the first time, shown to be reprogrammable, i.e., capable of performing sequence-specific gene editing. This discovery catapulted the field of CRISPR-Cas research and opened many unexplored avenues in the field of gene editing, from basic research to therapeutics. One such field that benefitted greatly from this discovery was molecular diagnostics, as using CRISPR-Cas technologies enabled existing diagnostic methods to become more sensitive, accurate, and portable, a necessity in disease control. This Review aims to capture some of the trajectories and advances made in this arena and provides a comprehensive understanding of the methods and their potential use as point-of-care diagnostics.

Antibody- and aptamer-free SERS substrate for ultrasensitive and anti-interference detection of SARS-CoV-2 spike protein in untreated saliva

Sensitive and anti-interference detection of targeted signal(s) in body fluids is one of the paramount tasks in biosensing. Overcoming the complication and high cost of antibody/aptamer-modification, surface-enhanced Raman spectroscopy (SERS) based on antibody/aptamer-free (AAF) substrates has shown great promise, yet with rather limited detection sensitivity. Herein, we report ultrasensitive and anti-interference detection of SARS-CoV-2 spike protein in untreated saliva by an AAF SERS substrate, applying the evanescent field induced by the high-order waveguide modes of well-defined nanorods for SERS for the first time. A detection limit of 3.6 × 10-17 M and 1.6 × 10-16 M are obtained in phosphate buffered saline and untreated saliva, respectively; the detection limits are three orders of magnitude improved than the best records from AAF substrates. This work unlocks an exciting path to design AAF SERS substrates for ultrasensitive biosensing, not limited to detection of viral antigens.

Single-molecule RNA capture-assisted droplet digital loop-mediated isothermal amplification for ultrasensitive and rapid detection of infectious pathogens

To minimize and control the transmission of infectious diseases, a sensitive, accurate, rapid, and robust assay strategy for application on-site screening is critical. Here, we report single-molecule RNA capture-assisted digital RT-LAMP (SCADL) for point-of-care testing of infectious diseases. Target RNA was captured and enriched by specific capture probes and oligonucleotide probes conjugated to magnetic beads, replacing laborious RNA extraction. Droplet generation, amplification, and the recording of results are all integrated on a microfluidic chip. In assaying commercial standard samples, quantitative results precisely corresponded to the actual concentration of samples. This method provides a limit of detection of 10 copies mL-1 for the N gene within 1 h, greatly reducing the need for skilled personnel and precision instruments. The ultrasensitivity, specificity, portability, rapidity and user-friendliness make SCADL a competitive candidate for the on-site screening of infectious diseases.

Advances in the application of CRISPR-Cas technology in rapid detection of pathogen nucleic acid

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (Cas) are widely used as gene editing tools in biology, microbiology, and other fields. CRISPR is composed of highly conserved repetitive sequences and spacer sequences in tandem. The spacer sequence has homology with foreign nucleic acids such as viruses and plasmids; Cas effector proteins have endonucleases, and become a hotspot in the field of molecular diagnosis because they recognize and cut specific DNA or RNA sequences. Researchers have developed many diagnostic platforms with high sensitivity, high specificity, and low cost by using Cas proteins (Cas9, Cas12, Cas13, Cas14, etc.) in combination with signal amplification and transformation technologies (fluorescence method, lateral flow technology, etc.), providing a new way for rapid detection of pathogen nucleic acid. This paper introduces the biological mechanism and classification of CRISPR-Cas technology, summarizes the existing rapid detection technology for pathogen nucleic acid based on the trans cleavage activity of Cas, describes its characteristics, functions, and application scenarios, and prospects the future application of this technology.

Rapid, Point-of-Care Host-Based Gene Expression Diagnostics Using Giant Magnetoresistive Biosensors

Host-based gene expression analysis is a promising tool for a broad range of clinical applications, including rapid infectious disease diagnostics and real-time disease monitoring. However, the complex instrumentation requirements and slow turnaround-times associated with traditional gene expression analysis methods have hampered their widespread adoption at the point-of-care (POC). To overcome these challenges, we have developed an automated and portable platform that utilizes polymerase chain reaction (PCR) and giant magnetoresistive (GMR) biosensors to perform rapid multiplexed, targeted gene expression analysis at the POC. As proof-of-concept, we utilized our platform to amplify and measure the expression of four genes (HERC5, HERC6, IFI27, and IFIH1) that were previously shown to be upregulated in hosts infected with influenza viruses. The compact instrument conducted highly automated PCR amplification and GMR detection to measure the expression of the four genes in multiplex, then utilized Bluetooth communication to relay results to users on a smartphone application. To validate the platform, we tested 20 cDNA samples from symptomatic patients that had been previously diagnosed as either influenza-positive or influenza-negative using a RT-PCR virology panel. A non-parametric Mann-Whitney test revealed that day 0 (day of symptom onset) gene expression was significantly different between the two groups (p < 0.0001, n = 20). Hence, we preliminarily demonstrated that our platform could accurately discriminate between symptomatic influenza and non-influenza populations based on host gene expression in ∼30 min. This study not only establishes the potential clinical utility of our proposed assay and device for influenza diagnostics but it also paves the way for broadscale and decentralized implementation of host-based gene expression diagnostics at the POC.

Longitudinal analysis of anti-SARS-CoV-2 neutralizing antibody (NAb) titers in vaccinees using a novel giant magnetoresistive (GMR) assay

The COVID-19 pandemic has highlighted the need to monitor important correlates of immunity on a population-wide level. To this end, we have developed a competitive assay to assess neutralizing antibody (NAb) titer on the giant magnetoresistive (GMR) biosensor platform. We compared the clinical performance of our biosensor with established techniques such as Ortho's VITROS Anti-SARS-CoV-2 IgG Quantitative Antibody test. Results obtained between the VITROS test and the GMR assay showed correlation (r = -0.93). We then validated the assay with patient plasma samples that had been tested using focus reduction neutralization testing (FRNT). The results obtained from our GMR assay exhibit a previously identified trend of increased NAb titers 2 weeks post-vaccination. We further evaluated NAb titers 6 months post-vaccination and observed waning neutralizing antibody titers over that time in vaccinated patients. In addition, we calibrated our assay to an arbitrary unit (IU/mL) using World Health Organization (WHO) reference plasma provided by the National Institute of Biological Standards and Control (NIBSC). Our biosensor provides highly specific and sensitive results in serum and plasma with analytical, clinical, and point-of-care (POC) applications due to quick turnaround times on samples and the cost-effectiveness of the platform.

A Prototype Assay Multiplexing SARS-CoV-2 3CL-Protease and Angiotensin-Converting Enzyme 2 for Saliva-Based Diagnostics in COVID-19

With the current state of COVID-19 changing from a pandemic to being more endemic, the priorities of diagnostics will likely vary from rapid detection to stratification for the treatment of the most vulnerable patients. Such patient stratification can be facilitated using multiple markers, including SARS-CoV-2-specific viral enzymes, like the 3CL protease, and viral-life-cycle-associated host proteins, such as ACE2. To enable future explorations, we have developed a fluorescent and Raman spectroscopic SARS-CoV-2 3CL protease assay that can be run sequentially with a fluorescent ACE2 activity measurement within the same sample. Our prototype assay functions well in saliva, enabling non-invasive sampling. ACE2 and 3CL protease activity can be run with minimal sample volumes in 30 min. To test the prototype, a small initial cohort of eight clinical samples was used to check if the assay could differentiate COVID-19-positive and -negative samples. Though these small clinical cohort samples did not reach statistical significance, results trended as expected. The high sensitivity of the assay also allowed the detection of a low-activity 3CL protease mutant.

Recent progress on rapid diagnosis of COVID-19 by point-of-care testing platforms

The outbreak of COVID-19 has drawn great attention around the world. SARS-CoV-2 is a highly infectious virus with occult transmission by many mutations and a long incubation period. In particular, the emergence of asymptomatic infections has made the epidemic even more severe. Therefore, early diagnosis and timely management of suspected cases are essential measures to control the spread of the virus. Developing simple, portable, and accurate diagnostic techniques for SARS-CoV-2 is the key to epidemic prevention. The advantages of point-of-care testing technology make it play an increasingly important role in viral detection and screening. This review summarizes the point-of-care testing platforms developed by nucleic acid detection, immunological detection, and nanomaterial-based biosensors detection. Furthermore, this paper provides a prospect for designing future highly accurate, cheap, and convenient SARS-CoV-2 diagnostic technology.

SERS Signature of SARS-CoV-2 in Saliva and Nasopharyngeal Swabs: Towards Perspective COVID-19 Point-of-Care Diagnostics

In this study, the intrinsic surface-enhanced Raman spectroscopy (SERS)-based approach coupled with chemometric analysis was adopted to establish the biochemical fingerprint of SARS-CoV-2 infected human fluids: saliva and nasopharyngeal swabs. The numerical methods, partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC), facilitated the spectroscopic identification of the viral-specific molecules, molecular changes, and distinct physiological signatures of pathetically altered fluids. Next, we developed the reliable classification model for fast identification and differentiation of negative CoV(-) and positive CoV(+) groups. The PLS-DA calibration model was described by a great statistical value-RMSEC and RMSECV below 0.3 and R²_cal at the level of ~0.7 for both type of body fluids. The calculated diagnostic parameters for SVMC and PLS-DA at the stage of preparation of calibration model and classification of external samples simulating real diagnostic conditions evinced high accuracy, sensitivity, and specificity for saliva specimens. Here, we outlined the significant role of neopterin as the biomarker in the prediction of COVID-19 infection from nasopharyngeal swab. We also observed the increased content of nucleic acids of DNA/RNA and proteins such as ferritin as well as specific immunoglobulins. The developed SERS for SARS-CoV-2 approach allows: (i) fast, simple and non-invasive collection of analyzed specimens; (ii) fast response with the time of analysis below 15 min, and (iii) sensitive and reliable SERS-based screening of COVID-19 disease.

Paper microfluidics with deep learning for portable intelligent nucleic acid amplification tests

During global outbreaks such as COVID-19, regular nucleic acid amplification tests (NAATs) have posed unprecedented burden on hospital resources. Data of traditional NAATs are manually analyzed post assay. Integration of artificial intelligence (AI) with on-chip assays give rise to novel analytical platforms via data-driven models. Here, we combined paper microfluidics, portable optoelectronic system with deep learning for SARS-CoV-2 detection. The system was quite streamlined with low power dissipation. Pixel by pixel signals reflecting amplification of synthesized SARS-CoV-2 templates (containing ORF1ab, N and E genes) can be real-time processed. Then, the data were synchronously fed to the neural networks for early prediction analysis. Instead of the quantification cycle (Cq) based analytics, reaction dynamics hidden at the early stage of amplification curve were utilized by neural networks for predicting subsequent data. Qualitative and quantitative analysis of the 40-cycle NAATs can be achieved at the end of 22nd cycle, reducing time cost by 45%. In particular, the attention mechanism based deep learning model trained by microfluidics-generated data can be seamlessly adapted to multiple clinical datasets including readouts of SARS-CoV-2 detection. Accuracy, sensitivity and specificity of the prediction can reach up to 98.1%, 97.6% and 98.6%, respectively. The approach can be compatible with the most advanced sensing technologies and AI algorithms to inspire ample innovations in fields of fundamental research and clinical settings.

Nucleocapsid protein binding DNA aptamers for detection of SARS-COV-2

The severe acute respiratory syndrome coronavirus (SARS-CoV-2) has infected millions of individuals and continues to be a major health concern worldwide. While reverse transcription-polymerase chain reaction remains a reliable method for detecting infections, limitations of this technology, particularly cost and the requirement of a dedicated laboratory, prevent rapid viral monitoring. Antigen tests filled this need to some extent but with limitations including sensitivity and specificity, particularly against emerging variants of concern. Here, we developed aptamers against the SARS-CoV-2 Nucleocapsid protein to complement or replace antibodies in antigen detection assays. As detection reagents in ELISA-like assays, our DNA aptamers were able to detect as low as 150 pg/mL of the protein and under 150 k copies of inactivated SARS-CoV-2 Wuhan Alpha strain in viral transport medium with little cross-reactivity to other human coronaviruses (HCoVs). Further, our aptamers were reselected against the SARS-CoV-2 Omicron variant of concern, and we found two sequences that had a more than two-fold increase in signal compared to our original aptamers when used as detection reagents against protein from the Omicron strain. These findings illustrate the use of aptamers as promising alternative detection reagents that may translate for use in current tests and our findings validate the method for the reselection of aptamers against emerging viral strains.

Reclassification of family A DNA polymerases reveals novel functional subfamilies and distinctive structural features

Family A DNA polymerases (PolAs) form an important and well-studied class of extant polymerases participating in DNA replication and repair. Nonetheless, despite the characterization of multiple subfamilies in independent, dedicated works, their comprehensive classification thus far is missing. We therefore re-examine all presently available PolA sequences, converting their pairwise similarities into positions in Euclidean space, separating them into 19 major clusters. While 11 of them correspond to known subfamilies, eight had not been characterized before. For every group, we compile their general characteristics, examine their phylogenetic relationships and perform conservation analysis in the essential sequence motifs. While most subfamilies are linked to a particular domain of life (including phages), one subfamily appears in Bacteria, Archaea and Eukaryota. We also show that two new bacterial subfamilies contain functional enzymes. We use AlphaFold2 to generate high-confidence prediction models for all clusters lacking an experimentally determined structure. We identify new, conserved features involving structural alterations, ordered insertions and an apparent structural incorporation of a uracil-DNA glycosylase (UDG) domain. Finally, genetic and structural analyses of a subset of T7-like phages indicate a splitting of the 3'-5' exo and pol domains into two separate genes, observed in PolAs for the first time.

A DNA biosensors-based microfluidic platform for attomolar real-time detection of unamplified SARS-CoV-2 virus

The emergence of the coronavirus 2019 (COVID-19) arose the need for rapid, accurate and massive virus detection methods to control the spread of infectious diseases. In this work, a device, deployable in non-medical environments, has been developed for the detection of non-amplified SARS-CoV-2 RNA. A SARS-CoV-2 specific probe was designed and covalently immobilized at the surface of glass slides to fabricate a DNA biosensor. The resulting system was integrated in a microfluidic platform, in which viral RNA was extracted from non-treated human saliva, before hybridizing at the surface of the sensor. The formed DNA/RNA duplex was detected in presence of SYBR Green I using an opto-electronic system, based on a high-power LED and a photo multiplier tube, which convert the emitted fluorescence into an electrical signal that can be processed in less than 10 min. The limit of detection of the resulting microfluidic platform reached six copies of viral RNA per microliter of sample (equal to 10 aM) and satisfied the safety margin. The absence of non-specific adsorption and the selectivity for SARS-CoV-2 RNA were established. In addition, the designed device could be applicable for the detection of a variety of viruses by simple modification of the immobilized probe.

Decreased breadth of the antibody response to the spike protein of SARS-CoV-2 after repeated vaccination

Introduction

The rapid development of vaccines to prevent COVID-19 has raised the need to compare the capacity of different vaccines in terms of developing a protective humoral response. Previous studies have shown inconsistent results in this area, highlighting the importance of further research to evaluate the efficacy of different vaccines.

Methods

This study utilized a highly sensitive and reliable flow cytometry method to measure the titers of IgG1 isotype antibodies in the blood of healthy volunteers after receiving one or two doses of various vaccines administered in Spain. The method was also used to simultaneously measure the reactivity of antibodies to the S protein of the original Wuhan strain and variants B.1.1.7 (Alpha), B.1.617.2 (Delta), and B.1.617.1 (Kappa).

Results

Significant differences were observed in the titer of anti-S antibodies produced after a first dose of the vaccines ChAdOx1 nCov-19/AstraZeneca, mRNA-1273/Moderna, BNT162b2/Pfizer-BioNTech, and Ad26.COV.S/Janssen. Furthermore, a relative reduction in the reactivity of the sera with the Alpha, Delta, and Kappa variants, compared to the Wuhan strain, was observed after the second boosting immunization.

Discussion

The findings of this study provide a comparison of different vaccines in terms of anti-S antibody generation and cast doubts on the convenience of repeated immunization with the same S protein sequence. The multiplexed capacity of the flow cytometry method utilized in this study allowed for a comprehensive evaluation of the efficacy of various vaccines in generating a protective humoral response. Future research could focus on the implications of these findings for the development of effective COVID-19 vaccination strategies.

Challenges and future opportunities to unlock the critical supply chain of personal and protective equipment (PPE) encompassing decontamination and reuse under emergency use authorization (EUA) conditions during the COVID-19 pandemic: Through a reflective circularity and sustainability lens

Severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2), and the resulting coronavirus disease (COVID-19), was declared a public health emergency of global concern by the World Health Organization (WHO) in the early months of 2020. There was a marked lack of knowledge to inform national pandemic response plans encompassing appropriate disease mitigation and preparation strategies to constrain and manage COVID-19. For example, the top 16 "most cited" papers published at the start of the pandemic on core knowledge gaps collectively constitute a staggering 29,393 citations. Albeit complex, appropriate decontamination modalities have been reported and developed for safe reuse of personal and protective equipment (PPE) under emergency use authorization (EUA) where critical supply chain shortages occur for healthcare workers (HCWs) caused by the COVID-19 pandemic. Commensurately, these similar methods may provide solutions for the safe decontamination of enormous volumes of PPE waste promoting opportunities in the circular bioeconomy that will also protect our environment, habitats and natural capital. The co-circulation of the highly transmissive mix of COVID-19 variants of concern (VoC) will continue to challenge our embattled healthcare systems globally for many years to come with an emphasis placed on maintaining effective disease mitigation strategies. This viewpoint article addresses the rationale and key developments in this important area since the onset of the COVID-19 pandemic and provides an insight into a variety of potential opportunities to unlock the long-term sustainability of single-use medical devices, including waste management.

Label-Free Saliva Test for Rapid Detection of Coronavirus Using Nanosensor-Enabled SERS

The recent COVID-19 pandemic has highlighted the inadequacies of existing diagnostic techniques and the need for rapid and accurate diagnostic systems. Although molecular tests such as RT-PCR are the gold standard, they cannot be employed as point-of-care testing systems. Hence, a rapid, noninvasive diagnostic technique such as Surface-enhanced Raman scattering (SERS) is a promising analytical technique for rapid molecular or viral diagnosis. Here, we have designed a SERS- based test to rapidly diagnose SARS-CoV-2 from saliva. Physical methods synthesized the nanostructured sensor. It significantly increased the detection specificity and sensitivity by ~ten copies/mL of viral RNA (~femtomolar concentration of nucleic acids). Our technique combines the multiplexing capability of SERS with the sensitivity of novel nanostructures to detect whole virus particles and infection-associated antibodies. We have demonstrated the feasibility of the test with saliva samples from individuals who tested positive for SARS-CoV-2 with a specificity of 95%. The SERS-based test provides a promising breakthrough in detecting potential mutations that may come up with time while also preparing the world to deal with other pandemics in the future with rapid response and very accurate results.

A urine-based ELISA with recombinant non-glycosylated SARS-CoV-2 spike protein for detecting anti-SARS-CoV-2 spike antibodies

Serological assays have been widely used to detect anti-SARS-CoV-2 antibodies, which are generated from previous exposure to the virus or after vaccination. The presence of anti-SARS-CoV-2 Nucleocapsid antibodies was recently reported in patients´ urine using an in-house urine-based ELISA-platform, allowing a non-invasive way to collect clinical samples and assess immune conversion. In the current study, we evaluated and validated another in-house urine-based ELISA for the detection of anti-SARS-CoV-2 Spike antibodies. Three partial recombinant SARS-CoV-2 Spike proteins comprising the Receptor Binding Domain, expressed in eukaryotic or prokaryotic systems, were tested in an ELISA platform against a panel of over 140 urine and paired serum samples collected from 106 patients confirmed positive for SARS-CoV-2 by qRT-PCR. The key findings from our study were that anti-SARS-CoV-2 Spike antibodies could be detected in urine samples and that the prokaryotic expression of the rSARS-CoV-2 Spike protein was not a barrier to obtain relatively high serology efficiency for the urine-based assay. Thus, use of a urine-based ELISA assay with partial rSARS-CoV-2 Spike proteins, expressed in a prokaryotic system, could be considered as a convenient tool for screening for the presence of anti-SARS-CoV-2 Spike antibodies, and overcome the difficulties arising from sample collection and the need for recombinant proteins produced with eukaryotic expression systems.

Rate of True-Positive Findings of COVID-19 Typical Appearance at Chest CT per RSNA Consensus Guidelines in an Increasingly Vaccinated Population

Background RSNA consensus guidelines for COVID-19-related chest CT are widely used but, to the knowledge of the authors, their rate of true-positive findings for COVID-19 pneumonia in vaccinated patients has not been assessed. Purpose To assess the rate of true-positive findings of typical appearance for COVID-19 at chest CT by using RSNA guidelines in fully vaccinated patients with polymerase chain reaction (PCR)-confirmed COVID-19 infection compared with unvaccinated patients. Materials and Methods Included were patients with COVID-19 who had typical appearance on chest CT images and one PCR test for COVID-19 with a positive result or two tests with negative results within 7 days of undergoing chest CT between January 2021 and January 2022 at a quaternary academic medical center. True-positive findings were defined as chest CT images interpreted as COVID-19 typical appearance and PCR-confirmed COVID-19 infection within 7 days. Logistic regression models were constructed to quantify the association between PCR results and vaccination status, vaccination status and COVID-19 variants, and vaccination status and number of months. Results Included were 652 patients (median age, 59 years; IQR, 48-72 years; 371 men [57%]) with CT scans classified as typical appearance. Of those patients, 483 (74%) were unvaccinated and 169 (26%) were fully vaccinated. The overall rate of true-positive findings on CT images rated as typical appearance was lower in vaccinated versus unvaccinated patients (70 of 169 [41%; 95% CI: 34, 49] vs 352 of 483 [73%; 95% CI: 69, 77]; odds ratio [OR], 3.8 [95% CI: 2.6, 5.5]; P < .001). Unvaccinated patients were more likely to have true-positive findings on CT images compared with fully vaccinated patients during the peaks of COVID-19 variants Alpha (OR, 16; 95% CI: 6, 42; P < .001) and Delta (OR, 8; 95% CI: 4, 16; P < .001), but no statistical differences were found during the peak of the Omicron variant (OR, 1.7; 95% CI: 0.3, 11; P = .56). Conclusion Fully vaccinated patients with confirmed COVID-19 breakthrough infections had lower rates of true-positive findings of COVID-19 typical appearance at chest CT. © RSNA, 2022 Supplemental material is available for this article.

Applicability of a colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for SARS-CoV-2 detection in high exposure risk setting

OBJECTIVES

During the third wave, the growing number of COVID-19 case clusters reported countrywide in Thailand demonstrated the rapidly evolving characteristics of SARS-CoV-2, the causative agent of the COVID-19 pandemic. The rapid spread of COVID-19 infections had been extensively reported in public areas and construction camps, as well as in congested communities with poor sanitation. High demand for SARS-CoV-2 genome testing and quick reporting by an hour for case identification and isolation characterizes the COVID-19 crisis in Thailand. This situation leads to an urgent need for alternative molecular tests which are reliable, rapid, and cost-effective.

METHODS

In this study, we assessed colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP), using real-time reverse transcription-polymerase chain reaction (RT-PCR) as a reference standard, for active case finding in suspected (mostly asymptomatic) cases living in high-risk areas of Bangkok.

RESULTS

The diagnostic performance of the RT-LAMP compared with real-time RT-PCR in specimens from 549 Thais were computed in a real-world field study setting. Our study demonstrated that RT-LAMP achieved robust identification of SARS-CoV-2 infection, with a diagnostic sensitivity and specificity of 91.67% and 100%, respectively.

CONCLUSION

RT-LAMP is a reliable assay for SARS-CoV-2 detection and is scalable for use in the emergency response to a nationwide pandemic, despite resource limitations. The RT-LAMP real-world data derived from this field study validate its potential use in laboratory practice. RT-LAMP is a good choice as a laboratory-based SARS-CoV-2 molecular test when real-time RT-PCR is not available.

SARS-CoV-2 molecular diagnostic point-of-care testing based on loop-mediated isothermal amplification: A prospective, single-center validation study

Objectives

Rapid and accurate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic tests are crucial for controlling the spread of infections in emergency settings. This study evaluated the diagnostic accuracy of a point-of-care (POC) test based on loop-mediated isothermal amplification (LAMP) that produces rapid results within 30 min.

Methods

We prospectively included adult patients (age >19 years) who were diagnosed with SARS-CoV-2 infection within the last 3 days and symptomatic patients who had visited the emergency room. Posterior nasopharyngeal (PNP) swabs and throat swabs collected by physicians were used to test the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and Cohen's Kappa coefficient (k) of the POC index and reference reverse transcription quantitative polymerase chain reaction (RT-qPCR) test devices.

Results

Of the 352 participants, 102 (29.0%) tested positive via the RT-PCR-based reference test device; the RT-LAMP-based POC test had a sensitivity of 70.6% and specificity of 98.0%, with 93.5% PPV, 89.1% NPV, 35.5% PLR, and 3.4% NLR. Cohen's k correlation of results from the two devices was 0.74. The cycle threshold value between the positive and negative POC test results differed (17.6 vs. 24.6, p < 0.001).

Conclusions

The RT-LAMP POC test in the emergency medical setting has a fair predictive value in high viral load cases in terms of infectivity.

COVID-19 Detection Using a 3D-Printed Micropipette Tip and a Smartphone

The COVID-19 pandemic has caused over 7 million deaths worldwide and over 1 million deaths in the US as of October 15, 2022. Virus testing lags behind the level or availability necessary for pandemic events like COVID-19, especially in resource-limited settings. Here, we report a low cost, mix-and-read COVID-19 assay using a synthetic SARS-CoV-2 sensor, imaged and processed using a smartphone. The assay was optimized for saliva and employs 3D-printed micropipette tips with a layer of monoclonal anti-SARS-CoV-2 inside the tip. A polymeric sensor for SARS-CoV-2 spike (S) protein (COVRs) synthesized as a thin film on silica nanoparticles provides 3,3',5-5'-tetramethylbenzidine responsive color detection using streptavidin-poly-horseradish peroxidase (ST-poly-HRP) with 400 HRP labels per molecule. COVRs were engineered with an NHS-PEG4-biotin coating to reduce nonspecific binding and provide affinity for ST-poly-HRP labels. COVRs binds to S-proteins with binding strengths and capacities much larger than salivary proteins in 10% artificial saliva-0.01%-Triton X-100 (as virus deactivator). A limit of detection (LOD) of 200 TCID50/mL (TCID50 = tissue culture infectious dose 50%) in artificial saliva was obtained using the Color Grab smartphone app and verified using ImageJ. Viral load values obtained in 10% pooled human saliva spiked with inactivated SARS-COV-2 virus gave excellent correlation with viral loads obtained from qPCR (p = 0.0003, r = 0.99).

Capabilities of Double-Resonance LPG and SPR Methods for Hypersensitive Detection of SARS-CoV-2 Structural Proteins: A Comparative Study

The danger of the emergence of new viral diseases and their rapid spread demands apparatuses for continuous rapid monitoring in real time. This requires the creation of new bioanalytical methods that overcome the shortcomings of existing ones and are applicable for point-of-care diagnostics. For this purpose, a variety of biosensors have been developed and tested in proof-of-concept studies, but none of them have been introduced for commercial use so far. Given the importance of the problem, in this study, long-period grating (LPG) and surface plasmon resonance (SPR) biosensors, based on antibody detection, were examined, and their capabilities for SARS-CoV-2 structural proteins detection were established. Supersensitive detections of structural proteins in the order of several femtomoles were achieved by the LPG method, while the SPR method demonstrated a sensitivity of about one hundred femtomoles. The studied biosensors are compatible in sensitivity with ELISA and rapid antigen tests but, in contrast, they are quantitative, which makes them applicable for acute SARS-CoV-2 infection detection, especially during the early stages of viral replication.

Assessment of the clinical and analytical performance of the Aptima SARS-CoV-2 assay using the VALCOR protocol

BACKGROUND

The COVID-19 pandemic highlighted the importance of diagnostic testing against curbing the spread of SARS-CoV-2. The urgent need and scale for diagnostic tools resulted in manufacturers of SARS-CoV-2 assays receiving emergency authorization that lacked robust analytical or clinical evaluation. As it is highly likely that testing for SARS-CoV-2 will continue to play a central role in public health, the performance characteristics of assays should be evaluated to ensure reliable diagnostic outcomes are achieved.

METHODS

VALCOR or "VALidation of SARS-CORona Virus-2 assays" is a study protocol designed to set up a framework for test validation of SARS-CoV-2 virus assays. Using clinical samples collated from VALCOR, the performance of Aptima SARS-CoV-2 assay was assessed against a standard comparator assay. Diagnostic test parameters such as sensitivity, specificity and overall per cent agreement were calculated for the clinical performance of Aptima SARS-CoV-2 assay.

RESULTS

A total of 180 clinical samples were tested with an addition of 40 diluted clinical specimens to determine the limit of detection. When compared to the standard comparator assay Aptima had a sensitivity of 100.0% [95% CI 95.9-100.0] and specificity of 96.7% [95% CI 90.8-99.3]. The overall percent agreement was 98.3% with an excellent Cohen's coefficient of κ = 0.967 [95% CI 0.929-1.000]. For the limit of detection, Aptima was able to detect all of the diluted clinical samples.

CONCLUSION

In conclusion. validation of Aptima SARS-CoV-2 assay using clinical samples collated through the VALCOR protocol showed excellent test performance. Additionally, Aptima demonstrated high analytical sensitivity by detecting all diluted clinical samples corresponding to a low limit of detection.

Inexpensive High-Throughput Multiplexed Biomarker Detection Using Enzymatic Metallization with Cellphone-Based Computer Vision

Multiplexed biomarker detection can play a critical role in reliable and comprehensive disease diagnosis and prediction of outcome. Enzyme-linked immunosorbent assay (ELISA) is the gold standard method for immunobinding-based biomarker detection. However, this is currently expensive, limited to centralized laboratories, and usually limited to the detection of a single biomarker at a time. We present a low-cost, smartphone-based portable biosensing platform for high-throughput, multiplexed, sensitive, and quantitative detection of biomarkers from single, low-volume drops (<1 μL) of clinical samples. Biomarker binding to spotted capture antigens is converted, via enzymatic metallization, to the localized surface deposition of amplified, dry-stable, silver metal spots whose darkness is proportional to biomarker concentration. A custom smartphone application is developed, which uses real-time computer vision to enable easy optical detection of the deposited metal spots and sensitive and reproducible quantification of the biomarkers. We demonstrate the use of this platform for high-throughput, multiplexed detection of multiple viral antigen-specific antibodies from convalescent COVID-19 patient serum as well as vaccine-elicited antibody responses from uninfected vaccine-recipient serum and show that distinct multiplexed antibody fingerprints are observed among them.

Review of HIV Self Testing Technologies and Promising Approaches for the Next Generation

The ability to self-test for HIV is vital to preventing transmission, particularly when used in concert with HIV biomedical prevention modalities, such as pre-exposure prophylaxis (PrEP). In this paper, we review recent developments in HIV self-testing and self-sampling methods, and the potential future impact of novel materials and methods that emerged through efforts to develop more effective point-of-care (POC) SARS-CoV-2 diagnostics. We address the gaps in existing HIV self-testing technologies, where improvements in test sensitivity, sample-to-answer time, simplicity, and cost are needed to enhance diagnostic accuracy and widespread accessibility. We discuss potential paths toward the next generation of HIV self-testing through sample collection materials, biosensing assay techniques, and miniaturized instrumentation. We discuss the implications for other applications, such as self-monitoring of HIV viral load and other infectious diseases.

Microbead-based extracorporeal immuno-affinity virus capture: a feasibility study to address the SARS-CoV-2 pandemic

In this paper, we report on the utilization of micro-technology based tools to fight viral infections. Inspired by various hemoperfusion and immune-affinity capture systems, a blood virus depletion device has been developed that offers highly efficient capture and removal of the targeted virus from the circulation, thus decreasing virus load. Single-domain antibodies against the Wuhan (VHH-72) virus strain produced by recombinant DNA technology were immobilized on the surface of glass micro-beads, which were then utilized as stationary phase. For feasibility testing, the virus suspension was flown through the prototype immune-affinity device that captured the viruses and the filtered media left the column. The feasibility test of the proposed technology was performed in a Biosafety Level 4 classified laboratory using the Wuhan SARS-CoV-2 strain. The laboratory scale device actually captured 120,000 virus particles from the culture media circulation proving the feasibility of the suggested technology. This performance has an estimated capture ability of 15 million virus particles by using the therapeutic size column design, representing three times over-engineering with the assumption of 5 million genomic virus copies in an average viremic patient. Our results suggested that this new therapeutic virus capture device could significantly lower virus load thus preventing the development of more severe COVID-19 cases and consequently reducing mortality rate.

Rapid point-of-care detection of SARS-CoV-2 RNA with smartphone-based upconversion luminescence diagnostics

Accurate COVID-19 screening via molecular technologies is still hampered by bulky instrumentation, complicated procedure, high cost, lengthy testing time, and the need for specialized personnel. Herein, we develop point-of-care upconversion luminescence diagnostics (PULD), and a streamlined smartphone-based portable platform facilitated by a ready-to-use assay for rapid SARS-CoV-2 nucleocapsid (N) gene testing. With the complementary oligo-modified upconversion nanoprobes and gold nanoprobes specifically hybridized with the target N gene, the luminescence resonance energy transfer effect leads to a quenching of fluorescence intensity that can be detected by the easy-to-use diagnostic system. A remarkable detection limit of 11.46 fM is achieved in this diagnostic platform without the need of target amplification, demonstrating high sensitivity and signal-to-noise ratio of the assay. The capability of the developed PULD is further assessed by probing 9 RT-qPCR-validated SARS-CoV-2 variant clinical samples (B.1.1.529/Omicron) within 20 min, producing reliable diagnostic results consistent with those obtained from a standard fluorescence spectrometer. Importantly, PULD is capable of identifying the positive COVID-19 samples with superior sensitivity and specificity, making it a promising front-line tool for rapid, high-throughput screening and infection control of COVID-19 or other infectious diseases.

Digital Droplet PCR to Track SARS-CoV-2 Outbreak in a Hospital Transitional Care Unit

We describe an outbreak of SARS-CoV-2 on a transition unit composed of elderly patients awaiting placement. Environmental and patient sample analyses using digital droplet PCR (ddPCR) suggested possible fomite transmission and a high viral burden source from a few individual patients. This outbreak illustrates challenges inherent to this specific patient population.

CRISPR Cas12a-Powered Silicon Surface-Enhanced Raman Spectroscopy Ratiometric Chip for Sensitive and Reliable Quantification

Sensitive and reliable clustered regularly interspaced short palindromic repeats (CRISPR) quantification without preamplification of the sample remains a challenge. Herein, we report a CRISPR Cas12a-powered silicon surface-enhanced Raman spectroscopy (SERS) ratiometric chip for sensitive and reliable quantification. As a proof-of-concept application, we select the platelet-derived growth factor-BB (PDGF-BB) as the target. We first develop a microfluidic synthetic strategy to prepare homogeneous silicon SERS substrates, in which uniform silver nanoparticles (AgNPs) are in situ grown on a silicon wafer (AgNPs@Si) by microfluidic galvanic deposition reactions. Next, one 5'-SH-3'-ROX-labeled single-stranded DNA (ssDNA) is modified on AgNPs via Ag-S bonds. In our design, such ssDNA has two fragments: one fragment hybridizes to its complementary DNA (5'-Cy3-labeled ssDNA) to form double-stranded DNA (dsDNA) and the other fragment labeled with 6'-carboxy-X-rhodmine (ROX) extends out as a substrate for Cas12a. The cleavage of the ROX-tagged fragment by Cas12a is controlled by the presence or not of PDGF-BB. Meanwhile, Cy3 molecules serving as internal standard molecules still stay at the end of the rigid dsDNA, and their signals remain constant. Thereby, the ratio of ROX signal intensity to Cy3 intensity can be employed for the reliable quantification of PDGF-BB concentration. The developed chip features an ultrahigh sensitivity (e.g., the limit of detection is as low as 3.2 pM, approximately 50 times more sensitive than the fluorescence counterpart) and good reproducibility (e.g., the relative standard deviation is less than 5%) in the detection of PDGF-BB.

Antibiotic discovery in the artificial intelligence era

As the global burden of antibiotic resistance continues to grow, creative approaches to antibiotic discovery are needed to accelerate the development of novel medicines. A rapidly progressing computational revolution-artificial intelligence-offers an optimistic path forward due to its ability to alleviate bottlenecks in the antibiotic discovery pipeline. In this review, we discuss how advancements in artificial intelligence are reinvigorating the adoption of past antibiotic discovery models-namely natural product exploration and small molecule screening. We then explore the application of contemporary machine learning approaches to emerging areas of antibiotic discovery, including antibacterial systems biology, drug combination development, antimicrobial peptide discovery, and mechanism of action prediction. Lastly, we propose a call to action for open access of high-quality screening datasets and interdisciplinary collaboration to accelerate the rate at which machine learning models can be trained and new antibiotic drugs can be developed.

A statistical model for early estimation of the prevalence and severity of an epidemic or pandemic from simple tests for infection confirmation

Epidemics and pandemics require an early estimate of the cumulative infection prevalence, sometimes referred to as the infection "Iceberg," whose tip are the known cases. Accurate early estimates support better disease monitoring, more accurate estimation of infection fatality rate, and an assessment of the risks from asymptomatic individuals. We find the Pivot group, the population sub-group with the highest probability of being detected and confirmed as positively infected. We differentiate infection susceptibility, assumed to be almost uniform across all population sub-groups at this early stage, from the probability of being confirmed positive. The latter is often related to the likelihood of developing symptoms and complications, which differs between sub-groups (e.g., by age, in the case of the COVID-19 pandemic). A key assumption in our method is the almost-random subgroup infection assumption: The risk of initial infection is either almost uniform across all population sub-groups or not higher in the Pivot sub-group. We then present an algorithm that, using the lift value of the pivot sub-group, finds a lower bound for the cumulative infection prevalence in the population, that is, gives a lower bound on the size of the entire infection "Iceberg." We demonstrate our method by applying it to the case of the COVID-19 pandemic. We use UK and Spain serological surveys of COVID-19 in its first year to demonstrate that the data are consistent with our key assumption, at least for the chosen pivot sub-group. Overall, we applied our methods to nine countries or large regions whose data, mainly during the early COVID-19 pandemic phase, were available: Spain, the UK at two different time points, New York State, New York City, Italy, Norway, Sweden, Belgium, and Israel. We established an estimate of the lower bound of the cumulative infection prevalence for each of them. We have also computed the corresponding upper bounds on the infection fatality rates in each country or region. Using our methodology, we have demonstrated that estimating a lower bound for an epidemic's infection prevalence at its early phase is feasible and that the assumptions underlying that estimate are valid. Our methodology is especially helpful when serological data are not yet available to gain an initial assessment on the prevalence scale, and more so for pandemics with an asymptomatic transmission, as is the case with Covid-19.

Amplification Free Detection of SARS-CoV-2 Using Multi-Valent Binding

We present the development of electrochemical impedance spectroscopy (EIS)-based biosensors for sensitive detection of SARS-CoV-2 RNA using multi-valent binding. By increasing the number of probe-target binding events per target molecule, multi-valent binding is a viable strategy for improving the biosensor performance. As EIS can provide sensitive and label-free measurements of nucleic acid targets during probe-target hybridization, we used multi-valent binding to build EIS biosensors for targeting SARS-CoV-2 RNA. For developing the biosensor, we explored two different approaches including probe combinations that individually bind in a single-valent fashion and the probes that bind in a multi-valent manner on their own. While we found excellent biosensor performance using probe combinations, we also discovered unexpected signal suppression. We explained the signal suppression theoretically using inter- and intra-probe hybridizations which confirmed our experimental findings. With our best probe combination, we achieved a LOD of 182 copies/μL (303 aM) of SARS-CoV-2 RNA and used these for successful evaluation of patient samples for COVID-19 diagnostics. We were also able to show the concept of multi-valent binding with shorter probes in the second approach. Here, a 13-nt-long probe has shown the best performance during SARS-CoV-2 RNA binding. Therefore, multi-valent binding approaches using EIS have high utility for direct detection of nucleic acid targets and for point-of-care diagnostics.