Rapid functionalisation and detection of viruses via a novel Ca2+-mediated virus-DNA interaction

Single-molecule detection and super-resolution imaging with a portable and adaptable 3D-printed microscopy platform (Brick-MIC)

Over the past decades, single-molecule and super-resolution microscopy have advanced and represent essential tools for life science research. There is,however, a growing gap between the state-of-the-art and what is accessible to biologists, biochemists, medical researchers or labs with financial constraints. To bridge this gap, we introduce Brick-MIC, a versatile and affordable open-source 3D-printed micro-spectroscopy and imaging platform. Brick-MIC enables the integration of various fluorescence imaging techniques with single-molecule resolution within a single platform and exchange between different modalities within minutes. We here present variants of Brick-MIC that facilitate single-molecule fluorescence detection, fluorescence correlation spectroscopy and super-resolution imaging (STORM and PAINT). Detailed descriptions of the hardware and software components, as well as data analysis routines are provided, to allow non-optics specialist to operate their own Brick-MIC with minimal effort and investments. We foresee that our affordable, flexible, and opensource Brick-MIC platform will be a valuable tool for many laboratories worldwide.

Real-time detection of virus antibody interaction by label-free common-path interferometry

Viruses have a profound influence on all forms of life, motivating the development of rapid and minimally invasive methods for virus detection. In this study, we present a novel methodology that enables quantitative measurement of the interaction between individual biotic nanoparticles and antibodies in solution. Our approach employs a label-free, full-field common-path interferometric technique to detect and track biotic nanoparticles and their interactions with antibodies. It is based on the interferometric detection of light scattered by viruses in aqueous samples for the detection of individual viruses. We employ single-particle tracking analysis to characterize the size and properties of the detected nanoparticles, and to monitor the changes in their diffusive mobility resulting from interactions. To validate the sensitivity of our detection approach, we distinguish between particles having identical diffusion coefficients but different scattering signals, using DNA-loaded and DNA-devoid capsids of the Escherichia coli T5 virus phage. In addition, we have been able to monitor, in real time, the interaction between the bacteriophage T5 and purified antibodies targeting its major capsid protein pb8, as well as between the phage SPP1 and nonpurified anti-SPP1 antibodies present in rabbit serum. Interestingly, these virus-antibody interactions are observed within minutes. Finally, by estimating the number of viral particles interacting with antibodies at different concentrations, we successfully quantify the dissociation constant K d of the virus-antibody reaction using single-particle tracking analysis.

High-throughput super-resolution analysis of influenza virus pleomorphism reveals insights into viral spatial organization

Many viruses form highly pleomorphic particles. In influenza, virion structure is of interest not only in the context of virus assembly, but also because pleomorphic variations may correlate with infectivity and pathogenicity. We have used fluorescence super-resolution microscopy combined with a rapid automated analysis pipeline, a method well-suited to the study of large numbers of pleomorphic structures, to image many thousands of individual influenza virions; gaining information on their size, morphology and the distribution of membrane-embedded and internal proteins. We observed broad phenotypic variability in filament size, and Fourier transform analysis of super resolution images demonstrated no generalized common spatial frequency patterning of HA or NA on the virion surface, suggesting a model of virus particle assembly where the release of progeny filaments from cells occurs in a stochastic way. We also showed that viral RNP complexes are located preferentially within Archetti bodies when these were observed at filament ends, suggesting that these structures may play a role in virus transmission. Our approach therefore offers exciting new insights into influenza virus morphology and represents a powerful technique that is easily extendable to the study of pleomorphism in other pathogenic viruses.

Addressing the Silent Spread of Monkeypox Disease with Advanced Analytical Tools

Monkeypox disease is caused by a virus which belongs to the orthopoxvirus genus of the poxviridae family. This disease has recently spread out to several non-endemic countries. While some cases have been linked to travel from endemic regions, more recent infections are thought to have spread in the community without any travel links, raising the risks of a wider outbreak. This state of public health represents a highly unusual event which requires urgent surveillance. In this context, the opportunities and technological challenges of current bio/chemical sensors, nanomaterials, nanomaterial characterization instruments, and artificially intelligent biosystems collectively called "advanced analytical tools" are reviewed here, which will allow early detection, characterization, and inhibition of the monkeypox virus (MPXV) in the community and limit its expansion from endemic to pandemic. A summary of background information is also provided from biological and epidemiological perspective of monkeypox to support the scientific case for its holistic management using advanced analytical tools.

Differences in IgG autoantibody Fab glycosylation across autoimmune diseases

BACKGROUND

Increased prevalence of autoantibody Fab glycosylation has been demonstrated for several autoimmune diseases.

OBJECTIVES

To study whether elevated Fab glycosylation is a common feature of autoimmunity, this study investigated Fab glycosylation levels on serum IgG and its subclasses for autoantibodies associated with a range of different B cell-mediated autoimmune diseases, including rheumatoid arthritis, myasthenia gravis subtypes, pemphigus vulgaris, antineutrophil cytoplasmic antibody-associated vasculitis, systemic lupus erythematosus, anti-glomerular basement membrane glomerulonephritis, thrombotic thrombocytopenic purpura, and Guillain-Barré syndrome.

METHODS

The level of Fab glycosylated IgG antibodies was assessed by lectin affinity chromatography and autoantigen-specific immunoassays.

RESULTS

In 6 of 10 autoantibody responses, in 5 of 8 diseases, the investigators found increased levels of Fab glycosylation on IgG autoantibodies that varied from 86% in rheumatoid arthritis to 26% in systemic lupus erythematosus. Elevated autoantibody Fab glycosylation was not restricted to IgG₄, which is known to be prone to Fab glycosylation, but was also present in IgG₁. When autoimmune diseases with a chronic disease course were compared with more acute autoimmune illnesses, increased Fab glycosylation was restricted to the chronic diseases. As a proxy for chronic autoantigen exposure, the investigators determined Fab glycosylation levels on antibodies to common latent herpes viruses, as well as to glycoprotein 120 in individuals who are chronically HIV-1-infected. Immunity to these viral antigens was not associated with increased Fab glycosylation levels, indicating that chronic antigen-stimulation as such does not lead to increased Fab glycosylation levels.

CONCLUSIONS

These data indicate that in chronic but not acute B cell-mediated autoimmune diseases, disease-specific autoantibodies are enriched for Fab glycans.

Virus Detection and Identification in Minutes Using Single-Particle Imaging and Deep Learning

The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of fluorescently labeled intact particles of different viruses. Our assay achieves labeling, imaging, and virus identification in less than 5 min and does not require any lysis, purification, or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses. We were also able to differentiate closely related strains of influenza, as well as SARS-CoV-2 variants. Additional and novel pathogens can easily be incorporated into the test through software updates, offering the potential to rapidly utilize the technology in future infectious disease outbreaks or pandemics. Single-particle imaging combined with deep learning therefore offers a promising alternative to traditional viral diagnostic and genomic sequencing methods and has the potential for significant impact.

A review on colorimetric assays for DNA virus detection

Early detection is one of the ways to deal with DNA virus widespread prevalence, and it is necessary to know new diagnostic methods and techniques. Colorimetric assays are one of the most advantageous methods in detecting viruses. These methods are based on color change, which can be seen either with the naked eye or with special devices. The aim of this study is to introduce and evaluate effective colorimetric methods based on amplification, nanoparticle, CRISPR/Cas, and Lateral flow in the diagnosis of DNA viruses and to discuss the effectiveness of each of the updated methods. Compared to the other methods, colorimetric assays are preferred for faster detection, high efficiency, cheaper cost, and high sensitivity and specificity. It is expected that the spread of these viruses can be prevented by identifying and developing new methods.

Virus morphology: Insights from super-resolution fluorescence microscopy

As epitomised by the COVID-19 pandemic, diseases caused by viruses are one of the greatest health and economic burdens to human society. Viruses are ‘nanostructures’, and their small size (typically less than 200 nm in diameter) can make it challenging to obtain images of their morphology and structure. Recent advances in fluorescence microscopy have given rise to super-resolution techniques, which have enabled the structure of viruses to be visualised directly at a resolution in the order of 20 nm. This mini-review discusses how recent state-of-the-art super-resolution imaging technologies are providing new nanoscale insights into virus structure.

Healthcare Innovations to Address the Challenges of the COVID-19 Pandemic

We have been faced with an unprecedented challenge in combating the COVID-19/SARS-CoV2 outbreak that is threatening the fabric of our civilization, causing catastrophic human losses and a tremendous economic burden globally. During this difficult time, there has been an urgent need for biomedical engineers, clinicians, and healthcare industry leaders to work together to develop novel diagnostics and treatments to fight the pandemic including the development of portable, rapidly deployable, and affordable diagnostic testing kits, personal protective equipment, mechanical ventilators, vaccines, and data analysis and modeling tools. In this position paper, we address the urgent need to bring these inventions into clinical practices. This paper highlights and summarizes the discussions and new technologies in COVID-19 healthcare, screening, tracing, and treatment-related presentations made at the IEEE EMBS Public Forum on COVID-19. The paper also provides recent studies, statistics and data and new perspectives on ongoing and future challenges pertaining to the COVID-19 pandemic.

Functional Infectious Nanoparticle Detector: Finding Viruses by Detecting Their Host Entry Functions Using Organic Bioelectronic Devices

Emerging viruses will continue to be a threat to human health and wellbeing into the foreseeable future. The COVID-19 pandemic revealed the necessity for rapid viral sensing and inhibitor screening in mitigating viral spread and impact. Here, we present a platform that uses a label-free electronic readout as well as a dual capability of optical (fluorescence) readout to sense the ability of a virus to bind and fuse with a host cell membrane, thereby sensing viral entry. This approach introduces a hitherto unseen level of specificity by distinguishing fusion-competent viruses from fusion-incompetent viruses. The ability to discern between competent and incompetent viruses means that this device could also be used for applications beyond detection, such as screening antiviral compounds for their ability to block virus entry mechanisms. Using optical means, we first demonstrate the ability to recapitulate the entry processes of influenza virus using a biomembrane containing the viral receptor that has been functionalized on a transparent organic bioelectronic device. Next, we detect virus membrane fusion, using the same, label-free devices. Using both reconstituted and native cell membranes as materials to functionalize organic bioelectronic devices, configured as electrodes and transistors, we measure changes in membrane properties when virus fusion is triggered by a pH drop, inducing hemagglutinin to undergo a conformational change that leads to membrane fusion.

Viral detection and identification in 20 min by rapid single-particle fluorescence in-situ hybridization of viral RNA

The increasing risk from viral outbreaks such as the ongoing COVID-19 pandemic exacerbates the need for rapid, affordable and sensitive methods for virus detection, identification and quantification; however, existing methods for detecting virus particles in biological samples usually depend on multistep protocols that take considerable time to yield a result. Here, we introduce a rapid fluorescence in situ hybridization (FISH) protocol capable of detecting influenza virus, avian infectious bronchitis virus and SARS-CoV-2 specifically and quantitatively in approximately 20 min, in virus cultures, combined nasal and throat swabs with added virus and likely patient samples without previous purification. This fast and facile workflow can be adapted both as a lab technique and a future diagnostic tool in enveloped viruses with an accessible genome.

Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning

Deep-learning (DL)-based image processing has potential to revolutionize the use of smartphones in mobile health (mHealth) diagnostics of infectious diseases. However, the high variability in cellphone image data acquisition and the common need for large amounts of specialist-annotated images for traditional DL model training may preclude generalizability of smartphone-based diagnostics. Here, we employed adversarial neural networks with conditioning to develop an easily reconfigurable virus diagnostic platform that leverages a dataset of smartphone-taken microfluidic chip photos to rapidly generate image classifiers for different target pathogens on-demand. Adversarial learning was also used to augment this real image dataset by generating 16,000 realistic synthetic microchip images, through style generative adversarial networks (StyleGAN). We used this platform, termed smartphone-based pathogen detection resource multiplier using adversarial networks (SPyDERMAN), to accurately detect different intact viruses in clinical samples and to detect viral nucleic acids through integration with CRISPR diagnostics. We evaluated the performance of the system in detecting five different virus targets using 179 patient samples. The generalizability of the system was confirmed by rapid reconfiguration to detect SARS-CoV-2 antigens in nasal swab samples (n = 62) with 100% accuracy. Overall, the SPyDERMAN system may contribute to epidemic preparedness strategies by providing a platform for smartphone-based diagnostics that can be adapted to a given emerging viral agent within days of work.

Dietary supplements, vitamins and minerals as potential interventions against viruses: Perspectives for COVID-19

Abstract. The novel coronavirus (SARS-CoV-2) causing COVID-19 disease pandemic has infected millions of people and caused more than thousands of deaths in many countries across the world. The number of infected cases is increasing day by day. Unfortunately, we do not have a vaccine and specific treatment for it. Along with the protective measures, respiratory and/or circulatory supports and some antiviral and retroviral drugs have been used against SARS-CoV-2, but there are no more extensive studies proving their efficacy. In this study, the latest publications in the field have been reviewed, focusing on the modulatory effects on the immunity of some natural antiviral dietary supplements, vitamins and minerals. Findings suggest that several dietary supplements, including black seeds, garlic, ginger, cranberry, orange, omega-3 and -6 polyunsaturated fatty acids, vitamins (e.g., A, B vitamins, C, D, E), and minerals (e.g., Cu, Fe, Mg, Mn, Na, Se, Zn) have anti-viral effects. Many of them act against various species of respiratory viruses, including severe acute respiratory syndrome-related coronaviruses. Therefore, dietary supplements, including vitamins and minerals, probiotics as well as individual nutritional behaviour can be used as adjuvant therapy together with antiviral medicines in the management of COVID-19 disease.