Diagnostic virology

Plate-Based High-Throughput Fluorescence Assay for Assessing Enveloped Virus Integrity

Viruses are a considerable threat to global health and place major burdens on economies worldwide. Manufactured viruses are also being widely used as delivery agents to treat (gene therapies) or prevent diseases (vaccines). Therefore, it is vital to study and fully understand the infectious state of viruses. Current techniques used to study viruses are often slow or nonexistent, making the development of new techniques of paramount importance. Here we present a high-throughput and robust, cell-free plate-based assay (FAIRY: Fluorescence Assay for vIRal IntegritY), capable of differentiating intact from nonintact enveloped viruses, i.e, infectious from noninfectious. Using a thiazole orange-terminated polymer, a 99% increase in fluorescence was observed between treated (heat or virucide) and nontreated. The FAIRY assay allowed for the rapid determination of the infectivity of a range of enveloped viruses, highlighting its potential as a valuable tool for the study of viruses and interventions against them.

Miniaturized MXene-based electrochemical biosensors for virus detection

The timely control of infectious diseases can prevent the spread of infections and mitigate the significant socio-economic damage witnessed during recent pandemics. Diagnostic methods play a significant role in detecting highly contagious agents, such as viruses, to prevent further transmission. The emergence of advanced point-of-care techniques offers several advantages over conventional approaches for detecting infectious agents. These techniques are highly sensitive, rapid, can be miniaturized, and are cost-effective. Recently, MXene-based 2D nanocomposites have proven beneficial for fabricating electrochemical biosensors due to their suitable electrical, optical, and mechanical properties. This article covers electrochemical biosensors based on MXene nanocomposite for the detection of viruses, along with the associated challenges and future possibilities. Additionally, we highlight various conventional techniques for the detection of infectious agents, discussing their pros and cons. We delve into the challenges faced during the fabrication of MXene-based biosensors and explore future endeavors. It is anticipated that the information presented in this work will pave the way for the development of Point-of-Care (POC) devices capable of sensitive and selective virus detection, enhancing preparedness for ongoing and future pandemics.

RNA virus diversity and prevalence in field and laboratory populations of melon fly throughout its distribution

Insects have a rich diversity of RNA viruses that can either cause acute infections or persist in host populations without visible symptoms. The melon fly, Zeugodacus cucurbitae (Tephritidae) causes substantial economic losses through infestation of diverse cucurbit and other crops. Of Indomalayan origin, it is now established in many tropical regions of the world. The virome diversity of Z. cucurbitae is largely unknown across large parts of its distribution, including the Indian subcontinent. We have analysed three transcriptomes each of one field-collected and one laboratory-reared Z. cucurbitae population from Bangalore (India) and discovered genomes of ten putative RNA viruses: two sigmaviruses, one chimbavirus, one cripavirus, one noda-like virus, one nora virus, one orbivirus, one partiti-like virus, one sobemovirus and one toti-like virus. Analysis of the only available host genome of a Hawaiian Z. cucurbitae population did not detect host genome integration of the detected viruses. While all ten viruses were found in the Bangalore field population only seven were detected in the laboratory population, indicating that these seven may cause persistent covert infections. Using virus-specific RNA-dependent RNA polymerase gene primers, we detected nine of the RNA viruses with an overall low variant diversity in some but not all individual flies from four out of five Indian regions. We then screened 39 transcriptomes of Z. cucurbitae laboratory populations from eastern Asia (Guangdong, Hainan, Taiwan) and the Pacific region (Hawaii), and detected seven of the ten virus genomes. We found additional genomes of a picorna-like virus and a negev-like virus. Hawaii as the only tested population from the fly's invasive range only had one virus. Our study provides evidence of new and high RNA virus diversity in Indian populations within the original range of Z. cucurbitae, as well as the presence of persistent covert infections in laboratory populations. It builds the basis for future research of tephritid-associated RNA viruses, including their host effects, epidemiology and application potential in biological control.

Monitoring the efficacy of antibiotic therapy in febrile pediatric oncology patients with bacteremia using infrared spectroscopy of white blood cells-based machine learning

Bacteremia refers to the presence of bacteria in the bloodstream, which can lead to a serious and potentially life-threatening condition. In oncology patients, individuals undergoing cancer treatment have a higher risk of developing bacteremia due to a weakened immune system resulting from the disease itself or the treatments they receive. Prompt and accurate detection of bacterial infections and monitoring the effectiveness of antibiotic therapy are essential for enhancing patient outcomes and preventing the development and dissemination of multidrug-resistant bacteria. Traditional methods of infection monitoring, such as blood cultures and clinical observations, are time-consuming, labor-intensive, and often subject to limitations. This manuscript presents an innovative application of infrared spectroscopy of leucocytes of pediatric oncology patients with bacteremia combined with machine learning to diagnose the etiology of infection as bacterial and simultaneously monitor the efficacy of the antibiotic therapy in febrile pediatric oncology patients with bacteremia infections. Through the implementation of effective monitoring, it becomes possible to promptly identify any indications of treatment failure. This, in turn, indirectly serves to limit the progression of antibiotic resistance. The logistic regression (LR) classifier was able to differentiate the samples as bacterial or control within an hour, after receiving the blood samples with a success rate of over 95 %. Additionally, initial findings indicate that employing infrared spectroscopy of white blood cells (WBCs) along with machine learning is viable for monitoring the success of antibiotic therapy. Our follow up results demonstrate an accuracy of 87.5 % in assessing the effectiveness of the antibiotic treatment.

Clinical diagnosis of viral hepatitis: Current status and future strategies

Viral hepatitis (VH) is a significant public health issue with tremendous potential to aggravate into chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma. Recent decade has witnessed remarkable uprising in the drug development and effective treatment of VH. An upsurge is seen in identification of antiviral therapies with low rates of viral resistance, the improvement of Hepatitis B Virus (HBV) vaccination and the development of direct-acting antivirals for Hepatitis C Virus (HCV). But unfortunately, the "2030 worldwide eradication" objective of World Health Organization (WHO) is still unmet. It can be largely attributed to the deficit faced by the healthcare system concerning screening and diagnosis. A timely, accurate and comprehensive screening; encompassing maximum population coverage is essential to combat this disease. However, advancements in VH diagnostics remain inadequate and with a marginal use in routine practice. This paper deliberates upon the lacunae in traditional and prevailing diagnostic methodology of viral hepatitis, especially their inadequacy in meeting the unique situations prevailing low- and middle-income countries (LMIC).

Shifting the paradigm in RNA virus detection: integrating nucleic acid testing and immunoassays through single-molecule digital ELISA

In this review article, we explore the characteristics of RNA viruses and their potential threats to humanity. We also provide a brief overview of the primary contemporary techniques used for the early detection of such viruses. After thoroughly analyzing the strengths and limitations of these methods, we highlight the importance of integrating nucleic acid testing with immunological assays in RNA virus detection. Although notable methodological differences between nucleic acid testing and immune assays pose challenges, the emerging single-molecule immunoassay-digital ELISA may be applied to technically integrate these techniques. We emphasize that the greatest value of digital ELISA is its extensive compatibility, which creates numerous opportunities for real-time, large-scale testing of RNA viruses. Furthermore, we describe the possible developmental trends of digital ELISA in various aspects, such as reaction carriers, identification elements, signal amplification, and data reading, thus revealing the remarkable potential of single-molecule digital ELISA in future RNA virus detection.

Duration of SARS-CoV-2 Culturable Virus Shedding in Children

This cohort study evaluates the duration of SARS-CoV-2 infectivity and its association with vaccination status in children after a positive COVID-19 test result.

Fucose Binding Cancels out Mechanical Differences between Distinct Human Noroviruses

The majority of nonbacterial gastroenteritis in humans and livestock is caused by noroviruses. Like most RNA viruses, frequent mutations result in various norovirus variants. The strain-dependent binding profiles of noroviruses to fucose are supposed to facilitate norovirus infection. It remains unclear, however, what the molecular mechanism behind strain-dependent functioning is. In this study, by applying atomic force microscopy (AFM) nanoindentation technology, we studied norovirus-like particles (noroVLPs) of three distinct human norovirus variants. We found differences in viral mechanical properties even between the norovirus variants from the same genogroup. The noroVLPs were then subjected to fucose treatment. Surprisingly, after fucose treatment, the previously found considerable differences in viral mechanical properties among these variants were diminished. We attribute a dynamic switch of the norovirus P domain upon fucose binding to the reduced differences in viral mechanical properties across the tested norovirus variants. These findings shed light on the mechanisms used by norovirus capsids to adapt to environmental changes and, possibly, increase cell infection. Hereby, a new step towards connecting viral mechanical properties to viral prevalence is taken.

Raman spectroscopy for viral diagnostics

Raman spectroscopy offers the potential for fingerprinting biological molecules at ultra-low concentration and therefore has potential for the detection of viruses. Here we review various Raman techniques employed for the investigation of viruses. Different Raman techniques are discussed including conventional Raman spectroscopy, surface-enhanced Raman spectroscopy, Raman tweezer, tip-enhanced Raman Spectroscopy, and coherent anti-Stokes Raman scattering. Surface-enhanced Raman scattering can play an essential role in viral detection by multiplexing nanotechnology, microfluidics, and machine learning for ensuring spectral reproducibility and efficient workflow in sample processing and detection. The application of these techniques to diagnose the SARS-CoV-2 virus is also reviewed.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-023-01059-4.

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.

Outcome of Newborns with Confirmed or Possible SARS-CoV-2 Vertical Infection-A Scoping Review

Severe acute respiratory syndrome virus 2 (SARS-CoV-2), the virus that causes 2019 coronavirus disease (COVID-19), has been isolated from various tissues and body fluids, including the placenta, amniotic fluid, and umbilical cord of newborns. In the last few years, much scientific effort has been directed toward studying SARS-CoV-2, focusing on the different features of the virus, such as its structure and mechanisms of action. Moreover, much focus has been on developing accurate diagnostic tools and various drugs or vaccines to treat COVID-19. However, the available evidence is still scarce and consistent criteria should be used for diagnosing vertical transmission. Applying the PRISMA ScR guidelines, we conducted a scoping review with the primary objective of identifying the types, and examining the range, of available evidence of vertical transmission of SARS-CoV-2 from mother to newborn. We also aimed to clarify the key concepts and criteria for diagnosis of SARS-CoV-2 vertical infection in neonates and summarize the existing evidence and advance the awareness of SARS-CoV-2 vertical infection in pregnancy. Most studies we identified were case reports or case series (about 30% of poor quality and inconsistent reporting of the findings). Summarizing the existing classification criteria, we propose an algorithm for consistent diagnosis. Registration: INPLASY2022120093.

Applications of Peptide Microarrays in Autoantibody, Infection, and Cancer Detection

The diversity of the antigen-specific humoral immune response reflects the interaction of the immune system with pathogens and autoantigens. Peptide microarray analysis opens up new perspectives for the use of antibodies as diagnostic biomarkers and provides unique access to a more differentiated view on humoral responses to disease. This review focuses on the latest applications of peptide microarrays for the serologic medical diagnosis of autoimmunity, infectious diseases (including COVID-19), and cancer.

Aptamer-based Emerging Tools for Viral Biomarker Detection: A Focus on SARS-CoV-2

Viral infections can cause fatal illnesses to humans as well as animals. Early detection of viruses is therefore crucial to provide effective treatment to patients. Recently, the Covid-19 pandemic has undoubtedly given an alarming call to develop rapid and sensitive detection platforms. The viral diagnostic tools need to be fast, affordable, and easy to operate with high sensitivity and specificity equivalent or superior to the currently used diagnostic methods. The present detection methods include direct detection of viral antigens or measuring the response of antibodies to viral infections. However, the sensitivity and quantification of the virus are still a significant challenge. Detection tools employing synthetic binding molecules like aptamers may provide several advantages over the conventional methods that use antibodies in the assay format. Aptamers are highly stable and tailorable molecules and are therefore ideal for detection and chemical sensing applications. This review article discusses various advances made in aptamer-based viral detection platforms, including electrochemical, optical, and colorimetric methods to detect viruses, specifically SARS-Cov-2. Considering the several advantages, aptamers could be game-changing in designing high-throughput biosensors for viruses and other biomedical applications in the future.

Understanding etiology of community-acquired central nervous system infections using metagenomic next-generation sequencing

Background

Community-acquired central nervous system infections (CA-CNS infections) have the characteristics of acute onset and rapid progression, and are associated with high levels of morbidity and mortality worldwide. However, there have been only limited studies on the etiology of this infections. Here, metagenomic next-generation sequencing (mNGS), a comprehensive diagnosis method, facilitated us to better understand the etiology of CA-CNS infections.

Methods

We conducted a single-center retrospective study between September 2018 and July 2021 in which 606 cerebrospinal fluid (CSF) samples were collected from suspected CNS infectious patients for mNGS testing, and all positive samples were included in this analysis

Results

After the exclusion criteria, a total of 131 mNGS-positive samples were finally enrolled. Bacterial, viral, fungal, parasitic, specific pathogen and mixed infections were accounted for 32.82% (43/131), 13.74% (18/131), 0.76% (1/131), 2.29% (3/131) and 6.87% (9/131), respectively. A total of 41 different pathogens were identified, including 16 bacteria, 12 viruses, 10 fungi, and 1 parasite and 3 specific pathogens. The most frequent infecting pathogens are Epstein-Barr virus (n = 14), Herpes simplex virus 1 (n = 14), Mycobacterium tuberculosis (n = 13), Streptococcus pneumoniae (n = 13), and Cryptococcus neoformans (n = 8). Some difficult-to-diagnose pathogen infections were also detected by mNGS, such as Streptococcus suis, Pseudorabies virus, Bunyavirus, Orientia tsutsugamushi and Toxoplasma gondii.

Conclusion

In this study, mNGS identified a wide variety of pathogens of CA-CNS infections and many of which could not be detected by conventional methods. Our data provide a better understanding of the etiology of CA-CNS infections and show that mNGS represents a comparative screening of CSF in an unbiased manner for a broad range of human pathogens.

Progress in COVID research and developments during pandemic

The pandemic respiratory disease COVID-19 has spread over the globe within a small span of time. Generally, there are two important points are being highlighted and considered towards the successful diagnosis and treatment process. The first point includes the reduction of the rate of infections and the next one is the decrease of the death rate. The major threat to public health globally progresses due to the absence of effective medication and widely accepted immunization for the COVID-19. Whereas, understanding of host susceptibility, clinical features, adaptation of COVID-19 to new environments, asymptomatic infection is difficult and challenging. Therefore, a rapid and an exact determination of pathogenic viruses play an important role in deciding treatments and preventing pandemic to save the people's lives. It is urgent to fix a standardized diagnostic approach for detecting the COVID-19. Here, this systematic review describes all the current approaches using for screening and diagnosing the COVID-19 infectious patient. The renaissance in pathogen due to host adaptability and new region, facing creates several obstacles in diagnosis, drug, and vaccine development process. The study shows that adaptation of accurate and affordable diagnostic tools based on candidate biomarkers using sensor and digital medicine technology can deliver effective diagnosis services at the mass level. Better prospects of public health management rely on diagnosis with high specificity and cost-effective manner along with multidisciplinary research, specific policy, and technology adaptation. The proposed healthcare model with defined road map represents effective prognosis system.

CRISPR Approaches for the Diagnosis of Human Diseases

CRISPR/Cas is a prokaryotic self-defense system, widely known for its use as a gene-editing tool. Because of their high specificity to detect DNA and RNA sequences, different CRISPR systems have been adapted for nucleic acid detection. CRISPR detection technologies differ highly among them, since they are based on four of the six major subtypes of CRISPR systems. In just 5 years, the CRISPR diagnostic field has rapidly expanded, growing from a set of specific molecular biology discoveries to multiple FDA-authorized COVID-19 tests and the establishment of several companies. CRISPR-based detection methods are coupled with pre-existing preamplification and readout technologies, achieving sensitivity and reproducibility comparable to the current gold standard nucleic acid detection methods. Moreover, they are very versatile, can be easily implemented to detect emerging pathogens and new clinically relevant mutations, and offer multiplexing capability. The advantages of the CRISPR-based diagnostic approaches are a short sample-to-answer time and no requirement of laboratory settings; they are also much more affordable than current nucleic acid detection procedures. In this review, we summarize the applications and development trends of the CRISPR/Cas13 system in the identification of particular pathogens and mutations and discuss the challenges and future prospects of CRISPR-based diagnostic platforms in biomedicine.

Aptamers-Diagnostic and Therapeutic Solution in SARS-CoV-2

The SARS-CoV-2 virus is currently the most serious challenge to global public health. Its emergence has severely disrupted the functioning of health services and the economic and social situation worldwide. Therefore, new diagnostic and therapeutic tools are urgently needed to allow for the early detection of the SARS-CoV-2 virus and appropriate treatment, which is crucial for the effective control of the COVID-19 disease. The ideal solution seems to be the use of aptamers—short fragments of nucleic acids, DNA or RNA—that can bind selected proteins with high specificity and affinity. They can be used in methods that base the reading of the test result on fluorescence phenomena, chemiluminescence, and electrochemical changes. Exploiting the properties of aptamers will enable the introduction of rapid, sensitive, specific, and low-cost tests for the routine diagnosis of SARS-CoV-2. Aptamers are excellent candidates for the development of point-of-care diagnostic devices and are potential therapeutic tools for the treatment of COVID-19. They can effectively block coronavirus activity in multiple fields by binding viral proteins and acting as carriers of therapeutic substances. In this review, we present recent developments in the design of various types of aptasensors to detect and treat the SARS-CoV-2 infection.

Two-dimensional material-based virus detection

Cost-effective, rapid, and accurate virus detection technologies play key roles in reducing viral transmission. Prompt and accurate virus detection enables timely treatment and effective quarantine of virus carrier, and therefore effectively reduces the possibility of large-scale spread. However, conventional virus detection techniques often suffer from slow response, high cost or sophisticated procedures. Recently, two-dimensional (2D) materials have been used as promising sensing platforms for the high-performance detection of a variety of chemical and biological substances. The unique properties of 2D materials, such as large specific area, active surface interaction with biomolecules and facile surface functionalization, provide advantages in developing novel virus detection technologies with fast response and high sensitivity. Furthermore, 2D materials possess versatile and tunable electronic, electrochemical and optical properties, making them ideal platforms to demonstrate conceptual sensing techniques and explore complex sensing mechanisms in next-generation biosensors. In this review, we first briefly summarize the virus detection techniques with an emphasis on the current efforts in fighting again COVID-19. Then, we introduce the preparation methods and properties of 2D materials utilized in biosensors, including graphene, transition metal dichalcogenides (TMDs) and other 2D materials. Furthermore, we discuss the working principles of various virus detection technologies based on emerging 2D materials, such as field-effect transistor-based virus detection, electrochemical virus detection, optical virus detection and other virus detection techniques. Then, we elaborate on the essential works in 2D material-based high-performance virus detection. Finally, our perspective on the challenges and future research direction in this field is discussed.

Detection of Cytopathic Effects Induced by Influenza, Parainfluenza, and Enterovirus Using Deep Convolution Neural Network

The isolation of a virus using cell culture to observe its cytopathic effects (CPEs) is the main method for identifying the viruses in clinical specimens. However, the observation of CPEs requires experienced inspectors and excessive time to inspect the cell morphology changes. In this study, we utilized artificial intelligence (AI) to improve the efficiency of virus identification. After some comparisons, we used ResNet-50 as a backbone with single and multi-task learning models to perform deep learning on the CPEs induced by influenza, enterovirus, and parainfluenza. The accuracies of the single and multi-task learning models were 97.78% and 98.25%, respectively. In addition, the multi-task learning model increased the accuracy of the single model from 95.79% to 97.13% when only a few data of the CPEs induced by parainfluenza were provided. We modified both models by inserting a multiplexer and de-multiplexer layer, respectively, to increase the correct rates for known cell lines. In conclusion, we provide a deep learning structure with ResNet-50 and the multi-task learning model and show an excellent performance in identifying virus-induced CPEs.

Clinical utility of novel biosensing platform: Diagnosis of coronavirus SARS-CoV-2 at point of care

Early detection is the first step in the fight against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, an efficient, rapid, selective, specific, and inexpensive SARS-CoV-2 diagnostic method is the need of the hour. The reverse transcription-polymerase chain reaction (RT-PCR) technology is massively utilized to detect infection with SARS-CoV-2. However, scientists continue to strive to create enhanced technology while continually developing nanomaterial-enabled biosensing methods that can provide new methodologies, potentially fulfilling the present demand for rapid and early identification of coronavirus disease 2019 (COVID-19) patients. Our review presents a summary of the recent diagnosis of SARS-CoV-2 of COVID-19 pandemic and nanomaterial-available biosensing methods. Although limited research on nanomaterials-based nanosensors has been published, allowing for biosensing approaches for diagnosing SARS-CoV-2, this study highlights nanomaterials that provide an enhanced biosensing strategy and potential processes that lead to COVID-19 diagnosis.

Pyrophosphate-Enhanced Oxidase Activity of Cerium Oxide Nanoparticles for Colorimetric Detection of Nucleic Acids

In recent years, cerium oxide (CeO₂) nanoparticles (NPs) have drawn significant attention owing to their intrinsic enzyme mimetic properties, which make them powerful tools for biomolecular detection. In this work, we evaluated the effect of pyrophosphate (PPi) on the oxidase activity of CeO₂ NPs. The presence of PPi was found to enhance the oxidase activity of CeO₂ NPs, with enhanced colorimetric signals. This particular effect was then used for the colorimetric detection of target nucleic acids. Overall, the PPi-enhanced colorimetric signals of CeO₂ NPs oxidase activity were suppressed by the presence of the target nucleic acids. Compared with previous studies using CeO₂ NPs only, our proposed system significantly improved the signal change (ca. 200%), leading to more sensitive and reproducible colorimetric analysis of target nucleic acids. As a proof-of-concept study, the proposed system was successfully applied to the highly selective and sensitive detection of polymerase chain reaction products derived from Klebsiella pneumoniae. Our findings will benefit the rapid detection of nucleic acid biomarkers (e.g., pathogenic bacterial DNA or RNA) in point-of-care settings.

Discrepancies in Infectivity of Flavivirus and SARS-CoV-2 Clinical Samples: An Improved Assay for Infectious Virus Shedding and Viremia Assessment

Infectivity and neutralizing antibody titers of flavivirus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are frequently measured using the conventional plaque assay. While the assay is useful in the determination of infectivity, conventional plaque assays generally possess lower sensitivity and are time-consuming compared to nucleic acid amplification tests. In this study, a microcrystalline cellulose (MCC), Avicel, was evaluated as an alternative to the conventional virus overlay medium, methylcellulose, for a plaque assay. The plaque assay was performed using dengue and COVID-19 clinical samples and laboratory-established flavivirus and SARS-CoV-2 strains. In virus titration of clinical samples, the plaques were significantly larger, and the virus titers were higher when Avicel MCC-containing overlay medium was used than with conventional methylcellulose overlay medium. In addition, for some clinical samples and laboratory virus strains, infectious particles were detected as plaques in the Avicel MCC-containing medium, but not in the conventional methylcellulose medium. The results suggest that the viremia titer determined using the new overlay medium containing Avicel MCC may better reflect the innate infectious and plaque-forming capabilities of clinical samples and better reflect virus infectivity.

Engineered nanomaterials as fighters against SARS-CoV-2: The way to control and treat pandemics

In this editorial trend, we aim to collect and present recently available data about the characteristics of SARS-CoV-2 virus, severity, infection, replication, diagnosis, and current medications. In addition, we propose the role of nanomaterials in controlling and treating COVID-19 through their antiviral and antibacterial potential with suggested action mechanisms indicating the capability of interaction between these nanomaterials and SARS-CoV-2. These nanomaterials might be among the possible and most effective cures against coronavirus.

CRISPR-based diagnostics

The accurate and timely diagnosis of disease is a prerequisite for efficient therapeutic intervention and epidemiological surveillance. Diagnostics based on the detection of nucleic acids are among the most sensitive and specific, yet most such assays require costly equipment and trained personnel. Recent developments in diagnostic technologies, in particular those leveraging clustered regularly interspaced short palindromic repeats (CRISPR), aim to enable accurate testing at home, at the point of care and in the field. In this Review, we provide a rundown of the rapidly expanding toolbox for CRISPR-based diagnostics, in particular the various assays, preamplification strategies and readouts, and highlight their main applications in the sensing of a wide range of molecular targets relevant to human health.

The Enterovirus Theory of Disease Etiology in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Critical Review

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multi-system disease whose etiological basis has not been established. Enteroviruses (EVs) as a cause of ME/CFS have sometimes been proposed, as they are known agents of acute respiratory and gastrointestinal infections that may persist in secondary infection sites, including the central nervous system, muscle, and heart. To date, the body of research that has investigated enterovirus infections in relation to ME/CFS supports an increased prevalence of chronic or persistent enteroviral infections in ME/CFS patient cohorts than in healthy individuals. Nevertheless, inconsistent results have fueled a decline in related studies over the past two decades. This review covers the aspects of ME/CFS pathophysiology that are consistent with a chronic enterovirus infection and critically reviews methodologies and approaches used in past EV-related ME/CFS studies. We describe the prior sample types that were interrogated, the methods used and the limitations to the approaches that were chosen. We conclude that there is considerable evidence that prior outbreaks of ME/CFS were caused by one or more enterovirus groups. Furthermore, we find that the methods used in prior studies were inadequate to rule out the presence of chronic enteroviral infections in individuals with ME/CFS. Given the possibility that such infections could be contributing to morbidity and preventing recovery, further studies of appropriate biological samples with the latest molecular methods are urgently needed.

Renal Involvement in Congenital Cytomegalovirus Infection: A Systematic Review

BACKGROUND

Congenital cytomegalovirus (cCMV) infection is the most frequent mother-to-child transmitted infection worldwide and a prevalent cause of neonatal disease and long-term morbidity. The kidney is a target organ for CMV, which replicates in renal tubules and is excreted in large quantities in urine for years in children with cCMV infection. Nonetheless, kidney disease has rarely been reported in cCMV-infected patients.

OBJECTIVE

We aimed to describe the available data on renal involvement in patients with cCMV infection at the pathologic, functional, anatomical, and/or clinical levels.

METHODS

A systematic search was performed in the MEDLINE/PubMed, SCOPUS, and Cochrane databases. Studies describing any renal involvement in fetuses or neonates aged ≤3 weeks at diagnosis of microbiologically confirmed cCMV infection were eligible.

RESULTS

Twenty-four articles were included, with a very low level of evidence. Pathologic findings in autopsy studies universally described CMV typical inclusion bodies in tubular cells. No functional studies were identified. cCMV infection was not associated with an increased risk of kidney malformations. Congenital nephrotic syndrome was the most common clinical condition associated with cCMV, but a causal relationship cannot be established.

CONCLUSIONS

Typical pathological features of cCMV infection are very common in renal tissue, but they do not seem to entail significant consequences at the anatomical or clinical levels.

Screening, Diagnostic and Prognostic Tests for COVID-19: A Comprehensive Review

While molecular testing with real-time polymerase chain reaction (RT-PCR) remains the gold-standard test for COVID-19 diagnosis and screening, more rapid or affordable molecular and antigen testing options have been developed. More affordable, point-of-care antigen testing, despite being less sensitive compared to molecular assays, might be preferable for wider screening initiatives. Simple laboratory, imaging and clinical parameters could facilitate prognostication and triage. This comprehensive review summarises current evidence on the diagnostic, screening and prognostic tests for COVID-19.

Screening, Diagnostic and Prognostic Tests for COVID-19: A Comprehensive Review

While molecular testing with real-time polymerase chain reaction (RT-PCR) remains the gold-standard test for COVID-19 diagnosis and screening, more rapid or affordable molecular and antigen testing options have been developed. More affordable, point-of-care antigen testing, despite being less sensitive compared to molecular assays, might be preferable for wider screening initiatives. Simple laboratory, imaging and clinical parameters could facilitate prognostication and triage. This comprehensive review summarises current evidence on the diagnostic, screening and prognostic tests for COVID-19.

Interrelationship between daily COVID-19 cases and average temperature as well as relative humidity in Germany

COVID-19 pandemic continues to obstruct social lives and the world economy other than questioning the healthcare capacity of many countries. Weather components recently came to notice as the northern hemisphere was hit by escalated incidence in winter. This study investigated the association between COVID-19 cases and two components, average temperature and relative humidity, in the 16 states of Germany. Three main approaches were carried out in this study, namely temporal correlation, spatial auto-correlation, and clustering-integrated panel regression. It is claimed that the daily COVID-19 cases correlate negatively with the average temperature and positively with the average relative humidity. To extract the spatial auto-correlation, both global Moran's [Formula: see text] and global Geary's [Formula: see text] were used whereby no significant difference in the results was observed. It is evident that randomness overwhelms the spatial pattern in all the states for most of the observations, except in recent observations where either local clusters or dispersion occurred. This is further supported by Moran's scatter plot, where states' dynamics to and fro cold and hot spots are identified, rendering a traveling-related early warning system. A random-effects model was used in the sense of case-weather regression including incidence clustering. Our task is to perceive which ranges of the incidence that are well predicted by the existing weather components rather than seeing which ranges of the weather components predicting the incidence. The proposed clustering-integrated model associated with optimal barriers articulates the data well whereby weather components outperform lag incidence cases in the prediction. Practical implications based on marginal effects follow posterior to model diagnostics.

Direct Detection of Conserved Viral Sequences and Other Nucleic Acid Motifs with Solid-State Nanopores

The rapid and reliable recognition of nucleic acid sequences is essential to a broad range of fields including genotyping, gene expression analysis, and pathogen screening. For viral detection in particular, the capability is critical for optimal therapeutic response and preventing disease transmission. Here, we report an approach for detecting identifying sequence motifs within genome-scale single-strand DNA and RNA based on solid-state nanopores. By designing DNA oligonucleotide probes with complementarity to target sequences within a target genome, we establish a protocol to yield affinity-tagged duplex molecules the same length as the probe only if the target is present. The product can subsequently be bound to a protein chaperone and analyzed quantitatively with a selective solid-state nanopore assay. We first use a model DNA genome (M13mp18) to validate the approach, showing the successful isolation and detection of multiple target sequences simultaneously. We then demonstrate the protocol for the detection of RNA viruses by identifying and targeting a highly conserved sequence within human immunodeficiency virus (HIV-1B).

Biosensors as a future diagnostic approach for COVID-19

Biosensors are important devices in clinical diagnostics, food processing, and environmental monitoring for detecting various analytes, especially viruses. These biosensors provide rapid and effective instruments for qualitative and quantitative detection of infectious diseases in real-time. Here, we report the development of biosensors based on various techniques. Additionally, we will explain the mechanisms, advantages, and disadvantages of the most common biosensors that are currently used for viral detection, which could be optical (e.g., surface-enhanced Raman scattering (SERS), Surface plasmon resonance (SPR)) and electrochemical biosensors. Based on that, this review recommends methods for efficient, simple, low-cost, and rapid detection of SARS-CoV-2 (the causative agent of COVID-19) that employ the two types of biosensors depending on attaching hemoglobin β-chain and binding of specific antibodies with SARS-CoV-2 antigens, respectively.

Diagnostic Tests for COVID-19

The diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has ramifications on both an individual level and a public health level. The use of appropriate testing mechanisms is paramount to preventing transmission, along with offering treatment to those who are infected and show appropriate symptomatology. The choice of employing a specific test often relies on laboratory capabilities, including the abilities of the medical technologists, the cost of testing platforms, and the individual quirks of each test. This chapter intends to discuss the relevant issues relating to diagnostic testing for SARS-CoV-2, including specimen types and collection methods, viral detection methods, and serological testing.

Virus Detection: A Review of the Current and Emerging Molecular and Immunological Methods

Viruses are ubiquitous in the environment. While many impart no deleterious effects on their hosts, several are major pathogens. This risk of pathogenicity, alongside the fact that many viruses can rapidly mutate highlights the need for suitable, rapid diagnostic measures. This review provides a critical analysis of widely used methods and examines their advantages and limitations. Currently, nucleic-acid detection and immunoassay methods are among the most popular means for quickly identifying viral infection directly from source. Nucleic acid-based detection generally offers high sensitivity, but can be time-consuming, costly, and require trained staff. The use of isothermal-based amplification systems for detection could aid in the reduction of results turnaround and equipment-associated costs, making them appealing for point-of-use applications, or when high volume/fast turnaround testing is required. Alternatively, immunoassays offer robustness and reduced costs. Furthermore, some immunoassay formats, such as those using lateral-flow technology, can generate results very rapidly. However, immunoassays typically cannot achieve comparable sensitivity to nucleic acid-based detection methods. Alongside these methods, the application of next-generation sequencing can provide highly specific results. In addition, the ability to sequence large numbers of viral genomes would provide researchers with enhanced information and assist in tracing infections.

Viral Infectivity in Patients Undergoing Tracheotomy With COVID-19: A Preliminary Study

Objective

To establish the presence of live virus and its association with polymerase chain reaction (PCR) positivity and antibody status in patients with COVID-19 undergoing tracheotomy.

Study Design

Prospective observational study.

Setting

Single institution across 3 hospital sites during the first wave of the COVID-19 pandemic.

Methods

Patients who were intubated for respiratory wean tracheotomy underwent SARS-CoV-2 PCR nasal, throat, and endotracheal tube swabs at the time of the procedure. These were assessed via quantitative real-time reverse transcription PCR. The tracheal tissue excised during the tracheotomy was cultured for SARS-CoV-2 with Vero E6 and Caco2 cells. Serum was assessed for antibody titers against SARS-CoV-2 via neutralization assays.

Results

Thirty-seven patients were included in this study. The mean number of days intubated prior to undergoing surgical tracheotomy was 27.8. At the time of the surgical tracheotomy, PCR swab testing yielded 8 positive results, but none of the 35 individuals who underwent tissue culture were positive for SARS-CoV-2. All 18 patients who had serum sampling demonstrated neutralization antibodies, with a minimum titer of 1:80.

Conclusion

In our series, irrespective of positive PCR swab, the likelihood of infectivity during tracheotomy remains low given negative tracheal tissue cultures. While our results do not undermine national and international guidance on tracheotomy after day 10 of intubation, given the length of time to procedure in our data, infectivity at 10 days cannot be excluded. We do however suggest that a preoperative negative PCR swab not be a prerequisite and that antibody titer levels may serve as a useful adjunct for assessment of infectivity.

SARS-CoV-2: An Update on Genomics, Risk Assessment, Potential Therapeutics and Vaccine Development

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a great threat to public health, being a causative pathogen of a deadly coronavirus disease (COVID-19). It has spread to more than 200 countries and infected millions of individuals globally. Although SARS-CoV-2 has structural/genomic similarities with the previously reported SARS-CoV and MERS-CoV, the specific mutations in its genome make it a novel virus. Available therapeutic strategies failed to control this virus. Despite strict standard operating procedures (SOPs), SARS-CoV-2 has spread globally and it is mutating gradually as well. Diligent efforts, special care, and awareness are needed to reduce transmission among susceptible masses particularly elder people, children, and health care workers. In this review, we highlighted the basic genome organization and structure of SARS-CoV-2. Its transmission dynamics, symptoms, and associated risk factors are discussed. This review also presents the latest mutations identified in its genome, the potential therapeutic options being used, and a brief explanation of vaccine development efforts against COVID-19. The effort will not only help readers to understand the deadly SARS-CoV-2 virus but also provide updated information to researchers for their research work.

Diagnosis of inaccessible infections using infrared microscopy of white blood cells and machine learning algorithms

Physicians diagnose subjectively the etiology of inaccessible infections where sampling is not feasible (such as, pneumonia, sinusitis, cholecystitis, peritonitis), as bacterial or viral. The diagnosis is based on their experience with some medical markers like blood counts and medical symptoms since it is harder to obtain swabs and reliable laboratory results for most cases. In this study, infrared spectroscopy with machine learning algorithms was used for the rapid and objective diagnosis of the etiology of inaccessible infections and enables an assessment of the error for the subjective diagnosis of the etiology of these infections by physicians. Our approach allows for diagnoses of the etiology of both accessible and inaccessible infections as based on an analysis of the innate immune system response through infrared spectroscopy measurements of white blood cell (WBC) samples. In the present study, we examined 343 individuals involving 113 controls, 89 inaccessible bacterial infections, 54 accessible bacterial infections, 60 inaccessible viral infections, and 27 accessible viral infections. Using our approach, the results show that it is possible to differentiate between controls and infections (combined bacterial and viral) with 95% accuracy, and enabling the diagnosis of the etiology of accessible infections as bacterial or viral with >94% sensitivity and > 90% specificity within one hour after the collection of the blood sample with error rate <6%. Based on our approach, the error rate of the physicians' subjective diagnosis of the etiology of inaccessible infections was found to be >23%.

A High-Throughput Assay for Circulating Antibodies Directed Against the S Protein of Severe Acute Respiratory Syndrome Coronavirus 2

More than 24 million infections with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were confirmed globally by September 2020. While polymerase chain reaction-based assays are used for diagnosis, there is a need for high-throughput, rapid serologic methods. A Luminex binding assay was developed and used to assess simultaneously the presence of coronavirus disease 2019 (COVID-19)-specific antibodies in human serum and plasma. Clear differentiation was achieved between specimens from infected and uninfected subjects, and a wide range of serum/plasma antibody levels was delineated in infected subjects. All 25 specimens from 18 patients with COVID-19 were positive in the assays with both the trimeric spike and the receptor-binding domain proteins. None of the 13 specimens from uninfected subjects displayed antibodies to either antigen. There was a highly statistically significant difference between the antibody levels of COVID-19-infected and -uninfected specimens (P < .0001). This high-throughput antibody assay is accurate, requires only 2.5 hours, and uses 5 ng of antigen per test.

Measurement of Antigen-Specific IgG Titers by Direct ELISA

Direct ELISA allows for the measurement of antibody levels to a particular antigen. Serum or plasma from the vaccinated subject are incubated on high-binding capacity microplates precoated with the antigen of interest and detected utilizing an enzyme-linked secondary antibody. Herein, using influenza hemagglutinin as model antigen, we describe the quantification of antigen-specific IgG titers in mouse serum to measure vaccine-induced humoral responses.

Biosensors: frontiers in rapid detection of COVID-19

The rapid community-spread of novel human coronavirus 2019 (nCOVID19 or SARS-Cov2) and morbidity statistics has put forth an unprecedented urge for rapid diagnostics for quick and sensitive detection followed by contact tracing and containment strategies, especially when no vaccine or therapeutics are known. Currently, quantitative real-time polymerase chain reaction (qRT-PCR) is being used widely to detect COVID-19 from various types of biological specimens, which is time-consuming, labor-intensive and may not be rapidly deployable in remote or resource-limited settings. This might lead to hindrance in acquiring realistic data of infectivity and community spread of SARS-CoV-2 in the population. This review summarizes the existing status of current diagnostic methods, their possible limitations, and the advantages of biosensor-based diagnostics over the conventional ones for the detection of SARS-Cov-2. Novel biosensors used to detect RNA-viruses include CRISPR-Cas9 based paper strip, nucleic-acid based, aptamer-based, antigen-Au/Ag nanoparticles-based electrochemical biosensor, optical biosensor, and Surface Plasmon Resonance. These could be effective tools for rapid, authentic, portable, and more promising diagnosis in the current pandemic that has affected the world economies and humanity. Present challenges and future perspectives of developing robust biosensors devices for rapid, scalable, and sensitive detection and management of COVID-19 are presented in light of the test-test-test theme of the World Health Organization (WHO).

Culture-Based Virus Isolation To Evaluate Potential Infectivity of Clinical Specimens Tested for COVID-19

Real-time reverse transcription-PCR (RT-PCR) is currently the most sensitive method to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, the correlation between detectable viral RNA and culturable virus in clinical specimens remains unclear. Here, we performed virus culture for 60 specimens that were confirmed to be positive for SARS-CoV-2 RNA by real-time RT-PCR. The virus could be successfully isolated from 12 throat and nine nasopharyngeal swabs and two sputum specimens.

Real-time reverse transcription-PCR (RT-PCR) is currently the most sensitive method to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, the correlation between detectable viral RNA and culturable virus in clinical specimens remains unclear. Here, we performed virus culture for 60 specimens that were confirmed to be positive for SARS-CoV-2 RNA by real-time RT-PCR. The virus could be successfully isolated from 12 throat and nine nasopharyngeal swabs and two sputum specimens. The lowest copy number required for virus isolation was determined to be 5.4, 6.0, and 5.7 log₁₀ genome copies/ml sample for detecting the nsp12, E, and N genes, respectively. We further examined the correlation of genome copy number and virus isolation in different regions of the viral genome, demonstrating that culturable specimens are characterized by high copy numbers with a linear correlation observed between copy numbers of amplicons targeting structural and nonstructural regions. Overall, these results indicate that in addition to the copy number, the integrity of the viral genome should be considered when evaluating the infectivity of clinical SARS-CoV-2 specimens.

Differentiation of Cytopathic Effects (CPE) induced by influenza virus infection using deep Convolutional Neural Networks (CNN)

Cell culture remains as the golden standard for primary isolation of viruses in clinical specimens. In the current practice, researchers have to recognize the cytopathic effects (CPE) induced by virus infection and subsequently use virus-specific monoclonal antibody to confirm the presence of virus. Considering the broad applications of neural network in various fields, we aimed to utilize convolutional neural networks (CNN) to shorten the timing required for CPE identification and to improve the assay sensitivity. Based on the characteristics of influenza-induced CPE, a CNN model with larger sizes of filters and max-pooling kernels was constructed in the absence of transfer learning. A total of 601 images from mock-infected and influenza-infected MDCK cells were used to train the model. The performance of the model was tested by using extra 400 images and the percentage of correct recognition was 99.75%. To further examine the limit of our model in evaluating the changes of CPE overtime, additional 1190 images from a new experiment were used and the recognition rates at 16 hour (hr), 28 hr, and 40 hr post virus infection were 71.80%, 98.25%, and 87.46%, respectively. The specificity of our model, examined by images of MDCK cells infected by six other non-influenza viruses, was 100%. Hence, a simple CNN model was established to enhance the identification of influenza virus in clinical practice.

Observation of cytopathic effects (CPE) induced by virus infection is a practical method to determine the prsence of viruses in the clinical specimens. However, CPE observation is labor-intensive and time-consuming because it requires medical examiner to inspect cell morphology changes for a period of time. Here, Convolutional Neural Networks (CNN) was applied to improve the disadvantage of CPE observation by using influenza virus as an example. To reduce the requirement for large image input of every clinical test, small amount of data was used to train our CNNs model without transfer learning and the trained model was examined with testing image data taken at 25hr post virus infection. The recognition of testing data shows that the model can identify CPE at 25hr and the high specificity of the model can differentiate the CPE induced by influenza viruses from those by other non-influenza viruses. The limit of our model was further examined by more experimental data of influenza-induced and mock-infected images, and the result shows our model can detect the slight changes at the initial stage of CPE development. Hence, our deep CNN model can significantly shorten the timing required to identify virus-induced cytopathic effects.

A High Through-put Assay for Circulating Antibodies Directed against the S Protein of Severe Acute Respiratory Syndrome Corona virus 2

Background.

More than one million infections with the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) have been confirmed. While PCR-based assays are used for diagnosis, high through-put serologic methods are needed to detect antibodies for seroserveillance and for identification of seroconversion, potential plasma donors, and the nature of the immune response to this pathogen.

Methods.

A Luminex binding assay was used to assess the presence of antibodies in human sera from COVID-19-infected and -uninfected individuals specific for two recombinant proteins of SARS-CoV-2.

Findings.

Fluorochrome-labeled beads were coated with a recombinant soluble stabilized trimeric SARS-CoV-2 S protein ectodomain or its central portion, the receptor binding domain (RBD). Coated beads were incubated with sera, followed by incubation with biotinylated anti-human total Ig antibodies and phycoerythrin (PE)-labeled streptavidin. Readout using a Luminex analyzer clearly differentiated between sera of the infected and uninfected subjects, delineating a wide range of serum antibody levels in infected subjects.

Interpretation.

Antibody assays of sera can identify individuals who are infected with SARS-CoV-2 and have seroconverted, as well as subjects who have been infected and recovered. The use of the Luminex binding Ab assay has the advantage that it can be run in approximately 2.5 hours, uses very little antigen, and permits a high through-put of samples/day.

Funding.

NIAID contracts and grants, Department of Veterans Affairs’ grants, the Microbiology Laboratory Clinical Services, Translational Science Hub, and Personalized Virology Initiative, and Department of Medicine of Mount Sinai Health System and Icahn School of Medicine at Mount Sinai.

Recent advances in lab-on-a-chip technologies for viral diagnosis

The global risk of viral disease outbreaks emphasizes the need for rapid, accurate, and sensitive detection techniques to speed up diagnostics allowing early intervention. An emerging field of microfluidics also known as the lab-on-a-chip (LOC) or micro total analysis system includes a wide range of diagnostic devices. This review briefly covers both conventional and microfluidics-based techniques for rapid viral detection. We first describe conventional detection methods such as cell culturing, immunofluorescence or enzyme-linked immunosorbent assay (ELISA), or reverse transcription polymerase chain reaction (RT-PCR). These methods often have limited speed, sensitivity, or specificity and are performed with typically bulky equipment. Here, we discuss some of the LOC technologies that can overcome these demerits, highlighting the latest advances in LOC devices for viral disease diagnosis. We also discuss the fabrication of LOC systems to produce devices for performing either individual steps or virus detection in samples with the sample to answer method. The complete system consists of sample preparation, and ELISA and RT-PCR for viral-antibody and nucleic acid detection, respectively. Finally, we formulate our opinions on these areas for the future development of LOC systems for viral diagnostics.

Rapid diagnosis of infection etiology in febrile pediatric oncology patients using infrared spectroscopy of leukocytes

Rapid diagnosis of the etiology of infection is highly important for an effective treatment of the infected patients. Bacterial and viral infections are serious diseases that can cause death in many cases. The human immune system deals with many viral and bacterial infections that cause no symptoms and pass quietly without treatment. However, oncology patients undergoing chemotherapy have a very weak immune system caused by leukopenia, and even minor pathogen infection threatens their lives. For this reason, physicians tend to prescribe immediately several types of antibiotics for febrile pediatric oncology patients (FPOPs). Uncontrolled use of antibiotics is one of the major contributors to the development of resistant bacteria. Therefore, for oncology patients, a rapid and objective diagnosis of the etiology of the infection is extremely critical. Current identification methods are time-consuming (>24 h). In this study, the potential of midinfrared spectroscopy in tandem with machine learning algorithms is evaluated for rapid and objective diagnosis of the etiology of infections in FPOPs using simple peripheral blood samples. Our results show that infrared spectroscopy enables the diagnosis of the etiology of infection as bacterial or viral within 70 minutes after the collection of the blood sample with 93% sensitivity and 88% specificity.

A nanoparticle pseudo pathogen for rapid detection and diagnosis of virus infection

We herein report a new rapid blood test for virus infection detection and diagnosis. A citrate gold nanoparticle is first coated with a virus lysate to form a gold nanoparticle pseudo pathogen. The gold nanoparticle pseudo virus is then mixed with a blood plasma or serum samples. If the blood sample is from a positive patient, the activated immune molecules in the blood such as antibodies, complement proteins and others will react with the nanoparticle pseudo virus, leading to nanoparticle aggregate formation. The nanoparticle aggregate formation is detected and measured using a particle sizing technique called dynamic light scattering. In this study, we applied this test for Zika virus infection detection. We tested blood plasma samples from 85 Zika positive patients, 40 Dengue positive patients, 10 Chikungunya positive patients, and 78 non-patient control samples collected from both endemic and non-endemic locations. The study shows that the new test has a higher sensitivity compared to some existing commercial tests in the market, while maintaining a similar specificity. Within 7 days from the symptom onset, the new test can detect 43% of the infected patients while a commercial anti-Zika IgM test detects only 26% of the infected patients. Within 14 days from the symptom onset, our new test detects 73% of the infected patients while the same commercial anti-Zika IgM test detects 53% of the infected patients. The test is extremely simple, easy to develop, with test results obtained within minutes. This new test platform may be potentially adapted for the detection and diagnosis of a wide range of viral infectious diseases, for example, the currently ongoing COVID-19.

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A rapid blood test for point-of-care virus infectious disease detection and diagnosis.

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The test uses a gold nanoparticle pseudo virus particle to detect active immune response from patient’s blood.

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The test is a single-step process with results obtained within 20 min.

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The test shows significantly better sensitivity than a commercially available serology test.

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The test platform may be adapted to develop diagnostic tests for different virus infections.