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

Reinfection with SARS-CoV-2 : discrete SIR (Susceptible, Infected, Recovered) modeling using empirical infection data

Background: The novel coronavirus SARS-CoV-2, which causes the COVID-19 disease, has resulted in a global pandemic. Since its emergence in December 2019, the virus has infected millions of people, caused the deaths of hundreds of thousands, and resulted in incalculable social and economic damage. Understanding the infectivity and transmission dynamics of the virus is essential to determine how best to reduce mortality while ensuring minimal social restrictions on the lives of the general population. Anecdotal evidence is available, but detailed studies have not yet revealed whether infection with the virus results in immunity. Objective: The objective of this study was to use mathematical modeling to investigate the reinfection frequency of COVID-19. Methods: We have used the SIR (Susceptible, Infected, Recovered) framework and random processing based on empirical SARS-CoV-2 infection and fatality data from different regions to calculate the number of reinfections that would be expected to occur if no immunity to the disease occurred. Results: Our model predicts that cases of reinfection should have been observed by now if primary SARS-CoV-2 infection did not protect individuals from subsequent exposure in the short term; however, no such cases have been documented. Conclusions: This work concludes that infection with SARS-CoV-2 provides short-term immunity to reinfection and therefore offers useful insight for serological testing strategies, lockdown easing, and vaccine development

Real-time analysis of single influenza virus replication complexes reveals large promoter-dependent differences in initiation dynamics

The viral RNA (vRNA) genome of influenza viruses is replicated by the RNA-dependent RNA polymerase (RNAP) via a complementary RNA (cRNA) intermediate. The vRNA promoter can adopt multiple conformations when bound by the RNAP. However, the dynamics, determinants, and biological role of these conformations are unknown; further, little is known about cRNA promoter conformations. To probe the RNA conformations adopted during initial replication, we monitored single, surface-immobilized vRNA and cRNA initiation complexes in real-time. Our results show that, while the 3′ terminus of the vRNA promoter exists in dynamic equilibrium between pre-initiation and initiation conformations, the cRNA promoter exhibited very limited dynamics. Two residues in the proximal 3′ region of the cRNA promoter (residues absent in the vRNA promoter) allowed the cRNA template strand to reach further into the active site, limiting promoter dynamics. Our results highlight promoter-dependent differences in influenza initiation mechanisms, and advance our understanding of virus replication

Single-molecule FRET for virology : 20 years of insight into protein structure and dynamics

Although viral protein structure and replication mechanisms have been explored extensively with X-ray crystallography, cryo-electron microscopy, and population imaging studies, these methods are often not able to distinguish dynamic conformational changes in real time. Single-molecule fluorescence resonance energy transfer (smFRET) offers unique insights into interactions and states that may be missed in ensemble studies, such as nucleic acid or protein structure, and conformational transitions during folding, receptor–ligand interactions, and fusion. We discuss the application of smFRET to the study of viral protein conformational dynamics, with a particular focus on viral glycoprotein dynamics, viral helicases, proteins involved in HIV reverse transcription, and the influenza RNA polymerase. smFRET experiments have played a crucial role in deciphering conformational changes in these processes, emphasising the importance of smFRET as a tool to help elucidate the life cycle of viral pathogens and identify key anti-viral targets

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

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

Current virus detection methods often take significant time or can be limited in sensitivity and specificity. The increasing frequency and magnitude of viral outbreaks in recent decades has resulted in an urgent need for diagnostic methods that are facile, sensitive, rapid and inexpensive. Here, we describe and characterise a novel, calcium-mediated interaction of the surface of enveloped viruses with DNA, that can be used for the functionalisation of intact virus particles via chemical groups attached to the DNA. Using DNA modified with fluorophores, we have demonstrated the rapid and sensitive labelling and detection of influenza and other viruses using single-particle tracking and particle-size determination. With this method, we have detected clinical isolates of influenza in just one minute, significantly faster than existing rapid diagnostic tests. This powerful technique is easily extendable to a wide range of other enveloped pathogenic viruses and holds significant promise as a future diagnostic tool

Identification of a novel splice variant form of the influenza a virus m2 ion channel with an antigenically distinct ectodomain

Segment 7 of influenza A virus produces up to four mRNAs. Unspliced transcripts encode M1, spliced mRNA2 encodes the M2 ion channel, while protein products from spliced mRNAs 3 and 4 have not previously been identified. The M2 protein plays important roles in virus entry and assembly, and is a target for antiviral drugs and vaccination. Surprisingly, M2 is not essential for virus replication in a laboratory setting, although its loss attenuates the virus. To better understand how IAV might replicate without M2, we studied the reversion mechanism of an M2-null virus. Serial passage of a virus lacking the mRNA2 splice donor site identified a single nucleotide pseudoreverting mutation, which restored growth in cell culture and virulence in mice by upregulating mRNA4 synthesis rather than by reinstating mRNA2 production. We show that mRNA4 encodes a novel M2-related protein (designated M42) with an antigenically distinct ectodomain that can functionally replace M2 despite showing clear differences in intracellular localisation, being largely retained in the Golgi compartment. We also show that the expression of two distinct ion channel proteins is not unique to laboratory-adapted viruses but, most notably, was also a feature of the 1983 North American outbreak of H5N2 highly pathogenic avian influenza virus. In identifying a 14th influenza A polypeptide, our data reinforce the unexpectedly high coding capacity of the viral genome and have implications for virus evolution, as well as for understanding the role of M2 in the virus life cycle

COMPASS identifies T-cell subsets correlated with clinical outcomes.

Advances in flow cytometry and other single-cell technologies have enabled high-dimensional, high-throughput measurements of individual cells as well as the interrogation of cell population heterogeneity. However, in many instances, computational tools to analyze the wealth of data generated by these technologies are lacking. Here, we present a computational framework for unbiased combinatorial polyfunctionality analysis of antigen-specific T-cell subsets (COMPASS). COMPASS uses a Bayesian hierarchical framework to model all observed cell subsets and select those most likely to have antigen-specific responses. Cell-subset responses are quantified by posterior probabilities, and human subject-level responses are quantified by two summary statistics that describe the quality of an individual's polyfunctional response and can be correlated directly with clinical outcome. Using three clinical data sets of cytokine production, we demonstrate how COMPASS improves characterization of antigen-specific T cells and reveals cellular 'correlates of protection/immunity' in the RV144 HIV vaccine efficacy trial that are missed by other methods. COMPASS is available as open-source software

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven\u27t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics