Tracking SARS-CoV-2: Novel Trends and Diagnostic Strategies

Rapid and comprehensive detection of viral antibodies and nucleic acids via an acoustofluidic integrated molecular diagnostics chip: AIMDx

Precise and rapid disease detection is critical for controlling infectious diseases like COVID-19. Current technologies struggle to simultaneously identify viral RNAs and host immune antibodies due to limited integration of sample preparation and detection. Here, we present acoustofluidic integrated molecular diagnostics (AIMDx) on a chip, a platform enabling high-speed, sensitive detection of viral immunoglobulins [immunoglobulin A (IgA), IgG, and IgM] and nucleic acids. AIMDx uses acoustic vortexes and Gor'kov potential wells at a 1/10,000 subwavelength scale for concurrent isolation of viruses and antibodies while excluding cells, bacteria, and large (>200 nanometers) vesicles from saliva samples. The chip facilitates on-chip viral RNA enrichment, lysis in 2 minutes, and detection via transcription loop-mediated isothermal amplification, alongside electrochemical sensing of antibodies, including mucin-masked IgA. AIMDx achieved nearly 100% recovery of viruses and antibodies, a 32-fold RNA detection improvement, and an immunity marker sensitivity of 15.6 picograms per milliliter. This breakthrough provides a transformative tool for multiplex diagnostics, enhancing early infectious disease detection.

A deep transfer learning approach for COVID-19 detection and exploring a sense of belonging with Diabetes

COVID-19 is an epidemic disease that results in death and significantly affects the older adult and those afflicted with chronic medical conditions. Diabetes medication and high blood glucose levels are significant predictors of COVID-19-related death or disease severity. Diabetic individuals, particularly those with preexisting comorbidities or geriatric patients, are at a higher risk of COVID-19 infection, including hospitalization, ICU admission, and death, than those without Diabetes. Everyone's lives have been significantly changed due to the COVID-19 outbreak. Identifying patients infected with COVID-19 in a timely manner is critical to overcoming this challenge. The Real-Time Polymerase Chain Reaction (RT-PCR) diagnostic assay is currently the gold standard for COVID-19 detection. However, RT-PCR is a time-consuming and costly technique requiring a lab kit that is difficult to get in crises and epidemics. This work suggests the CIDICXR-Net50 model, a ResNet-50-based Transfer Learning (TL) method for COVID-19 detection via Chest X-ray (CXR) image classification. The presented model is developed by substituting the final ResNet-50 classifier layer with a new classification head. The model is trained on 3,923 chest X-ray images comprising a substantial dataset of 1,360 viral pneumonia, 1,363 normal, and 1,200 COVID-19 CXR images. The proposed model's performance is evaluated in contrast to the results of six other innovative pre-trained models. The proposed CIDICXR-Net50 model attained 99.11% accuracy on the provided dataset while maintaining 99.15% precision and recall. This study also explores potential relationships between COVID-19 and Diabetes.

Clinical Validation of GenBody COVID-19 Ag, Nasal and Nasopharyngeal Rapid Antigen Tests for Detection of SARS-CoV-2 in European Adult Population

Accurate and rapid identification of COVID-19 is critical for effective patient treatment and disease outcomes, as well as the prevention of SARS-CoV-2 transmission. Rapid antigen tests (RATs) for identifying SARS-CoV-2 are simpler, faster and less expensive than molecular assays. Any new product to be considered a medical device is subject to evaluation and data analysis to verify the in vitro diagnostic ability to achieve its intended purpose. Clinical validation of such a test is a prerequisite before clinical application. This study was a clinical validation on adult Europeans of GenBody COVID-19 Ag, nasal and nasopharyngeal RATs. A set of 103 positive and 301 negative from nose and nasopharynx samples confirmed by RT-qPCR were examined. The tests were safe to use and showed 100% specificity in both specimens, and high sensitivity of 94.17% (95%CI 87.75% to 97.83%) and 97.09% (95%CI 91.72% to 99.4%), respectively. The parameters were significantly better for samples with higher virus loads (the highest for CT ≤ 25). The GenBody COVID-19 Ag RATs are inexpensive (compared to RT-qPCR), reliable and rapid with high sensitivity and specificity, making them suitable for diagnosis and timely isolation and treatment of COVID-19 patients, contributing to the better control of virus spread.

Conventional and Novel Diagnostic Tools for the Diagnosis of Emerging SARS-CoV-2 Variants

Accurate identification at an early stage of infection is critical for effective care of any infectious disease. The "coronavirus disease 2019 (COVID-19)" outbreak, caused by the virus "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)", corresponds to the current and global pandemic, characterized by several developing variants, many of which are classified as variants of concern (VOCs) by the "World Health Organization (WHO, Geneva, Switzerland)". The primary diagnosis of infection is made using either the molecular technique of RT-PCR, which detects parts of the viral genome's RNA, or immunodiagnostic procedures, which identify viral proteins or antibodies generated by the host. As the demand for the RT-PCR test grew fast, several inexperienced producers joined the market with innovative kits, and an increasing number of laboratories joined the diagnostic field, rendering the test results increasingly prone to mistakes. It is difficult to determine how the outcomes of one unnoticed result could influence decisions about patient quarantine and social isolation, particularly when the patients themselves are health care providers. The development of point-of-care testing helps in the rapid in-field diagnosis of the disease, and such testing can also be used as a bedside monitor for mapping the progression of the disease in critical patients. In this review, we have provided the readers with available molecular diagnostic techniques and their pitfalls in detecting emerging VOCs of SARS-CoV-2, and lastly, we have discussed AI-ML- and nanotechnology-based smart diagnostic techniques for SARS-CoV-2 detection.

High—throughput and automated screening for COVID-19

The COVID-19 pandemic has become a global challenge for the healthcare systems of many countries with 6 million people having lost their lives and 530 million more having tested positive for the virus. Robust testing and a comprehensive track and trace process for positive patients are essential for effective pandemic control, leading to high demand for diagnostic testing. In order to comply with demand and increase testing capacity worldwide, automated workflows have come into prominence as they enable high-throughput screening, faster processing, exclusion of human error, repeatability, reproducibility and diagnostic precision. The gold standard for COVID-19 testing so far has been RT-qPCR, however, different SARS-CoV-2 testing methods have been developed to be combined with high throughput testing to improve diagnosis. Case studies in China, Spain and the United Kingdom have been reviewed and automation has been proven to be promising for mass testing. Free and Open Source scientific and medical Hardware (FOSH) plays a vital role in this matter but there are some challenges to be overcome before automation can be fully implemented. This review discusses the importance of automated high-throughput testing, the different equipment available, the bottlenecks of its implementation and key selected case studies that due to their high effectiveness are already in use in hospitals and research centres.

Microbiological and Clinical Findings of SARS-CoV-2 Infection after 2 Years of Pandemic: From Lung to Gut Microbiota

Early recognition and prompt management are crucial for improving survival in COVID-19 patients, and after 2 years of the pandemic, many efforts have been made to obtain an early diagnosis. A key factor is the use of fast microbiological techniques, considering also that COVID-19 patients may show no peculiar signs and symptoms that may differentiate COVID-19 from other infective or non-infective diseases. These techniques were developed to promptly identify SARS-CoV-2 infection and to prevent viral spread and transmission. However, recent data about clinical, radiological and laboratory features of COVID-19 at time of hospitalization could help physicians in early suspicion of SARS-CoV-2 infection and distinguishing it from other etiologies. The knowledge of clinical features and microbiological techniques will be crucial in the next years when the endemic circulation of SARS-CoV-2 will be probably associated with clusters of infection. In this review we provide a state of the art about new advances in microbiological and clinical findings of SARS-CoV-2 infection in hospitalized patients with a focus on pulmonary and extrapulmonary characteristics, including the role of gut microbiota.

Rapid SARS-CoV-2 Detection Using the Lucira™ Check It COVID-19 Test Kit

The need for the early identification of SARS-CoV-2 has let to a quest for reliable tests that meet the standards of polymerase chain reaction (PCR) tests, on the one hand, and are low-cost, easy-to-use, and fast, on the other hand. One such test is the Lucira™ Check It COVID-19 Test kit (“Lucira”) (Lucira Health, Inc., Emeryville, CA, USA), which utilizes real-time loop-mediated isothermal amplification technology, developed for at-home use. This study evaluated the clinical sensitivity and specificity of Lucira in identifying the virus in 190 nasopharyngeal samples collected between January and October 2021. Each sample was also subjected to RT-PCR. All negative RT-PCR results were paralleled by a negative Lucira result. Out of 90 participants who had a positive RT-PCR result, 82 (91.1%) tested positive by Lucira. Among the 72 symptomatic participants, 67 (93%) tested positive by Lucira. All samples with a positive RT-PCR result with a threshold cycle (Ct) > 36, yielded a negative Lucira result. In addition, a significant positive correlation was found between Ct and time-to-positivity with Lucira (R = 0.8612, p < 0.0001). The implementation of such a portable and affordable assay may aid in breaking the COVID-19 transmission chain.

Rational Design of CRISPR/Cas12a-RPA Based One-Pot COVID-19 Detection with Design of Experiments

Simple and effective molecular diagnostic methods have gained importance due to the devastating effects of the COVID-19 pandemic. Various isothermal one-pot COVID-19 detection methods have been proposed as favorable alternatives to standard RT-qPCR methods as they do not require sophisticated and/or expensive devices. However, as one-pot reactions are highly complex with a large number of variables, determining the optimum conditions to maximize sensitivity while minimizing diagnostic cost can be cumbersome. Here, statistical design of experiments (DoE) was employed to accelerate the development and optimization of a CRISPR/Cas12a-RPA-based one-pot detection method for the first time. Using a definitive screening design, factors with a significant effect on performance were elucidated and optimized, facilitating the detection of two copies/μL of full-length SARS-CoV-2 (COVID-19) genome using simple instrumentation. The screening revealed that the addition of a reverse transcription buffer and an RNase inhibitor, components generally omitted in one-pot reactions, improved performance significantly, and optimization of reverse transcription had a critical impact on the method’s sensitivity. This strategic method was also applied in a second approach involving a DNA sequence of the N gene from the COVID-19 genome. The slight differences in optimal conditions for the methods using RNA and DNA templates highlight the importance of reaction-specific optimization in ensuring robust and efficient diagnostic performance. The proposed detection method is automation-compatible, rendering it suitable for high-throughput testing. This study demonstrated the benefits of DoE for the optimization of complex one-pot molecular diagnostics methods to increase detection sensitivity.

In Silico Prediction and Selection of Target Sequences in the SARS-CoV-2 RNA Genome for an Antiviral Attack

The SARS-CoV-2 pandemic has urged the development of protective vaccines and the search for specific antiviral drugs. The modern molecular biology tools provides alternative methods, such as CRISPR-Cas and RNA interference, that can be adapted as antiviral approaches, and contribute to this search. The unique CRISPR-Cas13d system, with the small crRNA guide molecule, mediates a sequence-specific attack on RNA, and can be developed as an anti-coronavirus strategy. We analyzed the SARS-CoV-2 genome to localize the hypothetically best crRNA-annealing sites of 23 nucleotides based on our extensive expertise with sequence-specific antiviral strategies. We considered target sites of which the sequence is well-conserved among SARS-CoV-2 isolates. As we should prepare for a potential future outbreak of related viruses, we screened for targets that are conserved between SARS-CoV-2 and SARS-CoV. To further broaden the search, we screened for targets that are conserved between SARS-CoV-2 and the more distantly related MERS-CoV, as well as the four other human coronaviruses (OC43, 229E, NL63, HKU1). Finally, we performed a search for pan-corona target sequences that are conserved among all these coronaviruses, including the new Omicron variant, that are able to replicate in humans. This survey may contribute to the design of effective, safe, and escape-proof antiviral strategies to prepare for future pandemics.