Highly multiplexed oligonucleotide probe-ligation testing enables efficient extraction-free SARS-CoV-2 detection and viral genotyping

Enhanced selective discrimination of point-mutated viral RNA through false amplification regulatory direct insertion in rolling circle amplification

Coronaviruses are single-stranded RNA viruses with high mutation rates. Although a diagnostic method for coronaviruses has been developed, variants appear rapidly. Low test accuracy owing to single-point mutations is one of the main factors in the failure to prevent the early spread of coronavirus infection. Although reverse transcription-quantitative polymerase chain reaction can detect coronavirus infection, it cannot exclude the possibility of false positives, and an additional multiplexing kit is needed to discriminate single nucleotide polymorphism (SNP) variants. Therefore, in this study, we introduced a new nucleic acid amplification method to determine whether an infected person has a SNP mutation using a lateral flow assay (LFA) as a point-of-care test. Unlike traditional DNA amplification methods, direct insertion into rolling circle amplification amplifies the target genes without false amplification. After SNP-selective nucleic acid amplification, nuclease enzymes are used to make double-stranded DNA fragments that the LFA can detect, where specific mismatched DNA is found and cleaved to show different signals when a SNP-type is present. Therefore, wild- and SNP-type variants can be selectively detected. In this study, the limit of detection was 400 aM for viral RNA, and we successfully identified a dominant SNP variant selectively. Clinical tests were also conducted.

Applying targeted gene hybridization capture to viruses with a focus to SARS-CoV-2

Although next-generation sequencing technologies are advancing rapidly, many research topics often require selective sequencing of genomic regions of interest. In addition, sequencing low-titre viruses is challenging, especially for coronaviruses, which are the largest RNA viruses. Prior to sequencing, enrichment of viral particles can help to significantly increase target sequence information as well as avoid large sequencing efforts and, consequently, can increase sensitivity and reduce sequencing costs. Targeting nucleic acids using capture by hybridization is another efficient method that can be performed by applying complementary probes (DNA or RNA baits) to directly enrich genetic information of interest while removing background non-target material. In studies where sequence capture by hybridization has been applied to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, most authors agree that this technique is useful to easily access sequence targets in complex samples. Furthermore, this approach allows for complete or near-complete sequencing of the viral genome, even in samples with low viral load or poor nucleic acid integrity. In addition, this strategy is highly efficient at discovering new variants by facilitating downstream investigations, such as phylogenetics, epidemiology, and evolution. Commercial kits, as well as in-house protocols, have been developed for enrichment of viral sequences. However, these kits have multiple variations in procedure, with differences in performance. This review compiles and describes studies in which hybridization capture has been applied to SARS-CoV-2 variant genomes.

Detection of viral RNAs at ambient temperature via reporter proteins produced through the target-splinted ligation of DNA probes

Nucleic acid assays are not typically deployable in point-of-care settings because they require costly and sophisticated equipment for the control of the reaction temperature and for the detection of the signal. Here we report an instrument-free assay for the accurate and multiplexed detection of nucleic acids at ambient temperature. The assay, which we named INSPECTR (for internal splint-pairing expression-cassette translation reaction), leverages the target-specific splinted ligation of DNA probes to generate expression cassettes that can be flexibly designed for the cell-free synthesis of reporter proteins, with enzymatic reporters allowing for a linear detection range spanning four orders of magnitude and peptide reporters (which can be mapped to unique targets) enabling highly multiplexed visual detection. We used INSPECTR to detect a panel of five respiratory viral targets in a single reaction via a lateral-flow readout and ~4,000 copies of viral RNA via additional ambient-temperature rolling circle amplification of the expression cassette. Leveraging synthetic biology to simplify workflows for nucleic acid diagnostics may facilitate their broader applicability at the point of care.

Metagenomic next-generation sequencing to characterize potential etiologies of non-malarial fever in a cohort living in a high malaria burden area of Uganda

Causes of non-malarial fevers in sub-Saharan Africa remain understudied. We hypothesized that metagenomic next-generation sequencing (mNGS), which allows for broad genomic-level detection of infectious agents in a biological sample, can systematically identify potential causes of non-malarial fevers. The 212 participants in this study were of all ages and were enrolled in a longitudinal malaria cohort in eastern Uganda. Between December 2020 and August 2021, respiratory swabs and plasma samples were collected at 313 study visits where participants presented with fever and were negative for malaria by microscopy. Samples were analyzed using CZ ID, a web-based platform for microbial detection in mNGS data. Overall, viral pathogens were detected at 123 of 313 visits (39%). SARS-CoV-2 was detected at 11 visits, from which full viral genomes were recovered from nine. Other prevalent viruses included Influenza A (14 visits), RSV (12 visits), and three of the four strains of seasonal coronaviruses (6 visits). Notably, 11 influenza cases occurred between May and July 2021, coinciding with when the Delta variant of SARS-CoV-2 was circulating in this population. The primary limitation of this study is that we were unable to estimate the contribution of bacterial microbes to non-malarial fevers, due to the difficulty of distinguishing bacterial microbes that were pathogenic from those that were commensal or contaminants. These results revealed the co-circulation of multiple viral pathogens likely associated with fever in the cohort during this time period. This study illustrates the utility of mNGS in elucidating the multiple potential causes of non-malarial febrile illness. A better understanding of the pathogen landscape in different settings and age groups could aid in informing diagnostics, case management, and public health surveillance systems.

A computational approach to biological pathogenicity

The current pandemic (COVID-19) has made evident the need to approach pathogenicity from a deeper and more systematic perspective that might lead to methodologies to quickly predict new strains of microbes that could be pathogenic to humans. Here we propose as a solution a general and principled definition of pathogenicity that can be practically implemented in operational ways in a framework for characterizing and assessing the (degree of) potential pathogenicity of a microbe to a given host (e.g., a human individual) just based on DNA biomarkers, and to the point of predicting its impact on a host a priori to a meaningful degree of accuracy. The definition is based on basic biochemistry, the Gibbs free Energy of duplex formation between oligonucleotides and some deep structural properties of DNA revealed by an approximation with certain properties. We propose two operational tests based on the nearest neighbor (NN) model of the Gibbs Energy and an approximating metric (the h-distance.) Quality assessments demonstrate that these tests predict pathogenicity with an accuracy of over 80%, and sensitivity and specificity over 90%. Other tests obtained by training machine learning models on deep features extracted from DNA sequences yield scores of 90% for accuracy, 100% for sensitivity and 80% for specificity. These results hint towards the possibility of an operational, objective, and general conceptual framework for prior identification of pathogens and their impact without the cost of death or sickness in a host (e.g., humans.) Consequently, a reasonable prediction of possible pathogens might pave the way to eventually transform the way we handle and prepare for future pandemic events and mitigate the adverse impact on human health, while reducing the number of clinical trials to obtain similar results.

State-of-the-Art Smart and Intelligent Nanobiosensors for SARS-CoV-2 Diagnosis

The novel coronavirus appeared to be a milder infection initially, but the unexpected outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), commonly called COVID-19, was transmitted all over the world in late 2019 and caused a pandemic. Human health has been disastrously affected by SARS-CoV-2, which is still evolving and causing more serious concerns, leading to the innumerable loss of lives. Thus, this review provides an outline of SARS-CoV-2, of the traditional tools to diagnose SARS-CoV-2, and of the role of emerging nanomaterials with unique properties for fabricating biosensor devices to diagnose SARS-CoV-2. Smart and intelligent nanomaterial-enabled biosensors (nanobiosensors) have already proven their utility for the diagnosis of several viral infections, as various detection strategies based on nanobiosensor devices are already present, and several other methods are also being investigated by researchers for the determination of SARS-CoV-2 disease; however, considerably more is undetermined and yet to be explored. Hence, this review highlights the utility of various nanobiosensor devices for SARS-CoV-2 determination. Further, it also emphasizes the future outlook of nanobiosensing technologies for SARS-CoV-2 diagnosis.

A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva

The COVID-19 pandemic has created an urgent need for rapid, effective, and low-cost SARS-CoV-2 diagnostic testing. Here, we describe COV-ID, an approach that combines RT-LAMP with deep sequencing to detect SARS-CoV-2 in unprocessed human saliva with a low limit of detection (5–10 virions). Based on a multi-dimensional barcoding strategy, COV-ID can be used to test thousands of samples overnight in a single sequencing run with limited labor and laboratory equipment. The sequencing-based readout allows COV-ID to detect multiple amplicons simultaneously, including key controls such as host transcripts and artificial spike-ins, as well as multiple pathogens. Here, we demonstrate this flexibility by simultaneous detection of 4 amplicons in contrived saliva samples: SARS-CoV-2, influenza A, human STATHERIN, and an artificial SARS calibration standard. The approach was validated on clinical saliva samples, where it showed excellent agreement with RT-qPCR. COV-ID can also be performed directly on saliva absorbed on filter paper, simplifying collection logistics and sample handling.

Recent Advances in Plasma-Engineered Polymers for Biomarker-Based Viral Detection and Highly Multiplexed Analysis

Infectious diseases remain a pervasive threat to global and public health, especially in many countries and rural urban areas. The main causes of such severe diseases are the lack of appropriate analytical methods and subsequent treatment strategies due to limited access to centralized and equipped medical centers for detection. Rapid and accurate diagnosis in biomedicine and healthcare is essential for the effective treatment of pathogenic viruses as well as early detection. Plasma-engineered polymers are used worldwide for viral infections in conjunction with molecular detection of biomarkers. Plasma-engineered polymers for biomarker-based viral detection are generally inexpensive and offer great potential. For biomarker-based virus detection, plasma-based polymers appear to be potential biological probes and have been used directly with physiological components to perform highly multiplexed analyses simultaneously. The simultaneous measurement of multiple clinical parameters from the same sample volume is possible using highly multiplexed analysis to detect human viral infections, thereby reducing the time and cost required to collect each data point. This article reviews recent studies on the efficacy of plasma-engineered polymers as a detection method against human pandemic viruses. In this review study, we examine polymer biomarkers, plasma-engineered polymers, highly multiplexed analyses for viral infections, and recent applications of polymer-based biomarkers for virus detection. Finally, we provide an outlook on recent advances in the field of plasma-engineered polymers for biomarker-based virus detection and highly multiplexed analysis.

Early sample tagging and pooling enables simultaneous SARS-CoV-2 detection and variant sequencing

Most severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic tests have relied on RNA extraction followed by reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays. Whereas automation improved logistics and different pooling strategies increased testing capacity, highly multiplexed next-generation sequencing (NGS) diagnostics remain a largely untapped resource. NGS tests have the potential to markedly increase throughput while providing crucial SARS-CoV-2 variant information. Current NGS-based detection and genotyping assays for SARS-CoV-2 are costly, mostly due to parallel sample processing through multiple steps. Here, we have established ApharSeq, in which samples are barcoded in the lysis buffer and pooled before reverse transcription. We validated this assay by applying ApharSeq to more than 500 clinical samples from the Clinical Virology Laboratory at Hadassah hospital in a robotic workflow. The assay was linear across five orders of magnitude, and the limit of detection was Ct 33 (~1000 copies/ml, 95% sensitivity) with >99.5% specificity. ApharSeq provided targeted high-confidence genotype information due to unique molecular identifiers incorporated into this method. Because of early pooling, we were able to estimate a 10- to 100-fold reduction in labor, automated liquid handling, and reagent requirements in high-throughput settings compared to current testing methods. The protocol can be tailored to assay other host or pathogen RNA targets simultaneously. These results suggest that ApharSeq can be a promising tool for current and future mass diagnostic challenges.

Emerging biosensing technologies for improved diagnostics of COVID-19 and future pandemics

Diagnostic tools play significant roles in the fight against COVID-19 and other pandemics. Existing tests, such as RT-qPCR, have limitations including long assay time, low throughput, inadequate sensitivity, and suboptimal portability. Emerging biosensing technologies hold the promise to develop tests that are rapid, highly sensitive, and suitable for point-of-care testing, which could significantly facilitate the testing of COVID-19. Despite that, practical applications of such biosensors in pandemics have yet to be achieved. In this review, we consolidate the newly developed diagnostic tools for COVID-19 using emerging biosensing technologies and discuss their application promise. In particular, we present nucleic acid tests and antibody tests of COVID-19 based on both conventional and emerging biosensing methods. We then provide perspectives on the existing challenges and potential solutions.