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Cotten, M.

Publications and source records attributed to Cotten, M..

10 recordsLinked to original sources

Fusion Peptide Insertion Configuration Determines the Mechanism of Membrane Curvature Induction in Human Parainfluenza Virus Type 3

Viral entry requires remodeling the host membrane with a short fusion peptide (FP) that anchors and deforms the target lipid bilayer. However, the contribution of the FP throughout the full fusion pathway remains unknown. Here, all-atom molecular dynamics simulations define the membrane- deformation mechanisms associated with two distinct insertion configurations of membrane-bound human parainfluenza virus type 3 (HPIV3) FP. Molecular simulations quantifying the linear response of curvature to the peptide are complemented with analyses of lipid organization and FP-lipid interactions to define the underlying membrane-deformation mechanisms. The surface-parallel FP configuration generates positive membrane curvature through deformation of the proximal leaflet, consistent with the classical hydrophobic insertion (wedging) mechanism. In contrast, the transmembrane FP configuration generates curvature through localized deformation of the distal leaflet, a distinct mechanism that would strongly influence later stages of fusion. Cryo-electron tomography shows that target membrane curvature at virus-host contact sites is consistent with the molecular dynamics prediction. In the absence of F-protein activation and FP insertion, the cryo-ET-determined curvature distribution shifts toward negative values, thereby isolating the role of the fusion protein in inducing early-stage curvature that enables the host and virus membranes to approach one another. Modeling key mutational changes isolates how aromatic and electrostatic interactions act together to promote curvature generation. Taken together, these findings establish FP insertion configuration as a determinant of productive membrane curvature across the full fusion pathway.

biophysics↗

SARS-CoV-2's evolutionary capacity is mostly driven by host antiviral molecules

The COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to human infection since its emergence in 2019. Here we use machine learning models to identify shared signatures, i.e., common underlying mutational processes, and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and not virus properties alone are associated with the rise and fall of regional SARS-CoV-2 reported infection numbers. This impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity, and the effectiveness of government stringency. In terms of underlying evolutionary change, we used non-negative matrix factorisation to observe three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 0, 1 and 3 were biased to C[->]T, T[->]C/A[->]G and G[->]T point mutations as would be expected of host antiviral molecules APOBEC, ADAR and ROS effects, respectively. We also observe a shift amidst the pandemic in relative mutational signature activity from predominantly APOBEC-like changes to an increasingly high proportion of changes consistent with ADAR editing. This could represent changes in how the virus and the host immune response interact, and indicates how SARS-CoV-2 may continue to accumulate mutations in the future. Linkage of the detected mutational signatures to the VOC defining amino acids substitutions indicates the majority of SARS-CoV-2s evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.

genomics↗

Evolution to increased positive charge on the viral spike protein may be part of the adaptation of SARS-CoV-2 to human transmission

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the coronavirus disease 2019 (COVID-19) pandemic, continues to evolve and infect individuals. The exterior surface of the SARS-CoV-2 virion is dominated by the spike protein and the current work examined spike protein biochemical features that have changed during the 2 years that SARS-CoV-2 has infected humans. These biochemical properties may influence virion survival and promote movement through the environment and within the human airway to reach target cells to bind, enter and establish the next round of infection. In addition to selective pressure to avoid immune recognition of viral proteins, we hypothesised that SARS-CoV-2 emerged from an animal reservoir capable of human infection and transmission but in a sub-optimum state and a second level of selective pressure is acting on these biochemical features. Our analysis identified a striking change in spike protein charge, from -8.3 in the original Lineage A and B viruses to -1.26 in the current Omicron viruses. In summary, we conclude that in addition to immune selection pressure, the evolution of SARS-CoV-2 has also altered viral spike protein biochemical properties. Future vaccine and therapeutic development should also exploit and target these biochemical properties.

evolutionary biology↗

Unique protein features of SARS-CoV-2 relative to other Sarbecoviruses

Defining the unique properties of SARS-CoV-2 protein sequences, has potential to explain the range of Coronavirus Disease 2019 (COVID-19) severity. To achieve this we compared proteins encoded by all Sarbecoviruses using profile Hidden Markov Model similarities to identify protein features unique to SARS-CoV-2. Consistent with previous reports, a small set of bat and pangolin-derived Sarbecoviruses show the greatest similarity to SARS-CoV-2 but unlikely to be the direct source of SARS-CoV-2. Three proteins (nsp3, spike and orf9) showed differing regions between the bat Sarbecoviruses and SARS-CoV-2 and indicate virus protein features that might have evolved to support human infection and/or transmission. Spike analysis identified all regions of the protein that have tolerated change and revealed that the current SARS-CoV-2 variants of concern (VOCs) have sampled only a fraction (~31%) of the possible spike domain changes which have occurred historically in Sarbecovirus evolution. This result emphasises the evolvability of these coronaviruses and potential for further change in virus replication and transmission properties over the coming years.

evolutionary biology↗

Alternate primers for whole-genome SARS-CoV-2 sequencing

As the world is struggling to control the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there is an urgency to develop effective control measures. Essential information is encoded in the virus genome sequence with accurate and complete SARS-CoV-2 sequences essential for tracking the movement and evolution of the virus and for guiding efforts to develop vaccines and antiviral drugs. While there is unprecedented SARS-CoV-2 sequencing efforts globally, approximately 19 to 43% of the genomes generated monthly are gapped, reducing their information content. The current study documents the genome gap frequencies and their positions in the currently available data and provides an alternative primer set and a sequencing scheme to help improve the quality and coverage of the genomes.

genomics↗

Increased resolution of African Swine Fever Virus genome patterns based on profile HMM protein domains

African Swine Fever Virus (ASFV) was originally described in Africa almost 100 years ago and is now spreading uncontrolled across Europe and Asia and threatening to destroy the domestic pork industry. Neither effective antiviral drugs nor a protective vaccine are currently available. Efforts to understand the basis for viral pathogenicity and the development of attenuated potential vaccine strains are complicated by the large and complex ASFV genome. We report here a novel method of documenting viral diversity based on profile Hidden Markov Model domains on a genome scale. The method can be used to infer genomic relationships independent of genome alignments and also reveal ASFV genome sequence differences that alter the presence of functional protein domains in the virus. We show that the method can quickly identify differences and shared patterns between virulent and attenuated ASFV strains and will be a useful tool for developing much-needed vaccines and antiviral agents to help control this virus. The tool is rapid to run and easy to implement, readily available as a simple Docker image.

genomics↗

Lipopolysaccharide Simulations are Sensitive to Phosphate Charge and Ion Parameterization

The high proportion of lipopolysaccharide (LPS) molecules in the outer membrane of Gram-negative bacteria make it a highly effective barrier to small molecules, antibiotic drugs, and other antimicrobial agents. Given this vital role in protecting bacteria from potentially hostile environments, simulations of LPS bilayers and outer membrane systems represent a critical tool for understanding the mechanisms of bacterial resistance and the development of new antibiotic compounds that circumvent these defenses. The basis of these simulations are parameterizations of LPS, which have been developed for all major molecular dynamics force fields. However, these parameterizations differ in both the protonation state of LPS as well as how LPS membranes behave in the presence of various ion species. To address these discrepancies and understand the effects of phosphate charge on bilayer properties, simulations were performed for multiple distinct LPS chemotypes with different ion parameterizations in both protonated or deprotonated lipid A states. These simulations show that bilayer properties, such as the area per lipid and inter-lipid hydrogen bonding, are highly influenced by the choice of phosphate group charges, cation type, and ion parameterization, with protonated LPS and monovalent cations with modified nonbonded parameters providing the best match to experiments. Additionally, alchemical free energy simulations were performed to determine theoretical pKa values for LPS, and subsequently validated by 31P solid-state NMR experiments. Results from these complementary computational and experimental studies demonstrate that the protonated state dominates at physiological pH, contrary to the deprotonated form modeled by many LPS force fields. In all, these results highlight the sensitivity of LPS simulations to phosphate charge and ion parameters, while offering recommendations for how existing models should be updated for consistency between force fields as well as to best match experiments.

biophysics↗

The COMPARE Data Hubs

Data sharing enables research communities to exchange findings and build upon the knowledge that arises from their discoveries. Areas of public and animal health as well as food safety would benefit from rapid data sharing when it comes to emergencies. However, ethical, regulatory, and institutional challenges, as well as lack of suitable platforms which provide an infrastructure for data sharing in structured formats often lead to data not being shared, or at most shared in form of supplementary materials in journal publications. Here, we describe an informatics platform that includes workflows for structured data storage, managing and pre-publication sharing of pathogen sequencing data and its analysis interpretations with relevant stakeholders.

bioinformatics↗

Assessing the utility of minority variant composition in elucidating RSV transmission pathways

Reconstructing transmission pathways and defining the underlying determinants of virus diversity is critical for developing effective control measures. Whole genome consensus sequences represent the dominant virus subtype which does not provide sufficient information to resolve transmission events for rapidly spreading viruses with overlapping generations. We explored whether the within-host diversity of respiratory syncytial virus quantified from deep sequence data provides additional resolution to inform on who acquires infection from whom based on shared minor variants in samples that comprised epidemiological clusters and that shared similar genetic background. We report that RSV-A infections are characterized by low frequency diversity that occurs across the genome. Shared minor variant patterns alone, were insufficient to elucidate transmission chains within household members. However, they provided inference on potential transmission links where phylogenetic methods were uninformative of transmission when consensus sequences were identical. Interpretation of minor variant patterns was tractable only for small household outbreaks.

epidemiology↗

Whole genome analysis of local Kenyan and global sequences unravels the epidemiological and molecular evolutionary dynamics of RSV genotype ON1 strains

The respiratory syncytial virus (RSV) group A variant with the 72-nucleotide duplication in the G gene, genotype ON1, was first detected in Kilifi in 2012 and has almost completely replaced previously circulating genotype GA2 strains. This replacement suggests some fitness advantage of ON1 over the GA2 viruses, and might be accompanied by important genomic substitutions in ON1 viruses. Close observation of such a new virus introduction over time provides an opportunity to better understand the transmission and evolutionary dynamics of the pathogen. We have generated and analyzed 184 RSV-A whole genome sequences (WGS) from Kilifi (Kenya) collected between 2011 and 2016, the first ON1 genomes from Africa and the largest collection globally from a single location. Phylogenetic analysis indicates that RSV-A transmission into this coastal Kenya location is characterized by multiple introductions of viral lineages from diverse origins but with varied success in local transmission. We identify signature amino acid substitutions between ON1 and GA2 viruses within genes encoding the surface proteins (G, F), polymerase (L) and matrix M2-1 proteins, some of which were identified as positively selected, and thereby provide an enhanced picture of RSV-A diversity. Furthermore, five of the eleven RSV open reading frames (ORF) (i.e. G, F, L, N and P), analyzed separately, formed distinct phylogenetic clusters for the two genotypes. This might suggest that coding regions outside of the most frequently studied G ORF play a role in the adaptation of RSV to host populations with the alternative possibility that some of the substitutions are nothing more than genetic hitchhikers. Our analysis provides insight into the epidemiological processes that define RSV spread, highlights the genetic substitutions that characterize emerging strains, and demonstrates the utility of large-scale WGS in molecular epidemiological studies.\n\nAuthor summaryRespiratory syncytial virus (RSV) is the leading viral cause of severe pneumonia and bronchiolitis among infants and children globally. No vaccine exists to date. The high genetic variability of this RNA virus, characterized by group (A or B), genotype (within group) and variant (within genotype) replacement in populations, may pose a challenge to effective vaccine design by enabling immune response escape. To date most sequence data exists for the highly variable G gene encoding the RSV attachment protein, and there is little globally-sampled RSV genomic data to provide a fine resolution of the epidemiology and evolutionary dynamics of the pathogen. Here we use long-term RSV surveillance in coastal Kenya to track the introduction, spread and evolution of a new RSV genotype known as ON1 (having a 72-nucleotide duplication in the G gene). We present a set of 184 RSV-A whole genomes, including 176 of RSV ON1 (the first from Africa), describe patterns of local ON1 spread and show genome-wide changes between the two major RSV-A genotypes that may define the pathogens adaptation to the host. These findings have implications for vaccine design and improved understanding of RSV epidemiology and evolution.

epidemiology↗