SARS-CoV-2 Delta and Omicron community transmission networks as added value to contact tracing.

OBJECTIVES: Calculations of SARS-CoV-2 transmission networks at a population level have been limited. Networks that estimate infections between individuals and whether this results in a mutation, can be a way to evaluate fitness of a mutational clone by how much it expands in number as well as determining the likelihood a transmission results in a new variant. METHODS: Australian Delta and Omicron SARS-CoV-2 sequences were downloaded from GISAID. Transmission networks of infection between individuals were estimated using a novel mathematical method. RESULTS: Many of the sequences were identical, with clone sizes following power law distributions driven by negative binomial probability distributions for both the number of infections per individual and the number of mutations per transmission (median 0.74 nucleotide changes for Delta and 0.71 for Omicron). Using these distributions, an agent-based model was able to replicate the observed clonal network structure, providing a basis for more detailed COVID-19 modelling. Possible recombination events, tracked by insertion/deletion (indel) patterns, were identified for each variant in these outbreaks. CONCLUSIONS: This modelling approach reveals key transmission characteristics of SARS-CoV-2 and may complement traditional contact tracing. This methodology can also be applied to other diseases as genetic sequencing of viruses becomes more commonplace.

Charting and tracking the evolution of the SARS CoV-2 coronavirus variants of concern with protein mass spectrometry.

The evolution of the SARS-CoV2 coronavirus spike S-protein is studied using a mass spectrometry based protein phylogenetic approach. A study of a large dataset comprising sets of peptide masses derived from over 3000 proteins of the SARS-CoV2 virus shows that the approach is capable of resolving and correctly displaying the evolution of the major variants of concern. Using these numerical datasets, through a pairwise comparison of sets of proteolytic peptide masses for each protein, the tree is built without the need for the sequence data itself or any sequence alignment. In the same analysis, single point mutations are calculated from peptide mass differences of different protein sets and these are displayed at the branch nodes on the tree. The tree topology is found to be consistent with that generated using conventional sequence-based phylogenetics by a manual visualisation and using a tree comparison algorithm. The mass tree resolves major variants of the virus and displays non-synonymous mutations, calculated based on the mass data alone, on the tree that enable protein evolution to be charted and tracked along interconnected branches. Tracking the evolution of the SARS-CoV2 coronavirus S-protein is of particular importance given its role in the attachment of the virus to host cells ahead of viral replication.

NGlyAlign: an automated library building tool to align highly divergent HIV envelope sequences.

BACKGROUND: The high variability in envelope regions of some viruses such as HIV allow the virus to establish infection and to escape subsequent immune surveillance. This variability, as well as increasing incorporation of N-linked glycosylation sites, is fundamental to this evasion. It also creates difficulties for multiple sequence alignment methods (MSA) that provide the first step in their analysis. Existing MSA tools often fail to properly align highly variable HIV envelope sequences requiring extensive manual editing that is impractical with even a moderate number of these variable sequences. RESULTS: We developed an automated library building tool NGlyAlign, that organizes similar N-linked glycosylation sites as block constraints and statistically conserved global sites as single site constraints to automatically enforce partial columns in consistency-based MSA methods such as Dialign. This combined method accurately aligns variable HIV-1 envelope sequences. We tested the method on two datasets: a set of 156 founder and chronic gp160 HIV-1 subtype B sequences as well as a set of reference sequences of gp120 in the highly variable region 1. On measures such as entropy scores, sum of pair scores, column score, and similarity heat maps, NGlyAlign+Dialign proved superior against methods such as T-Coffee, ClustalOmega, ClustalW, Praline, HIValign and Muscle. The method is scalable to large sequence sets producing accurate alignments without requiring manual editing. As well as this application to HIV, our method can be used for other highly variable glycoproteins such as hepatitis C virus envelope. CONCLUSIONS: NGlyAlign is an automated tool for mapping and building glycosylation motif libraries to accurately align highly variable regions in HIV sequences. It can provide the basis for many studies reliant on single robust alignments. NGlyAlign has been developed as an open-source tool and is freely available at https://github.com/UNSW-Mathematical-Biology/NGlyAlign_v1.0 .

Mutational networks of escape from transmitted HIV-1 infection.

Human immunodeficiency virus (HIV) is subject to immune selective pressure soon after it establishes infection at the founder stage. As an individual progresses from the founder to chronic stage of infection, immune pressure forces a history of mutations that are embedded in envelope sequences. Determining this pathway of coevolving mutations can assist in understanding what is different with the founder virus and the essential pathways it takes to maintain infection. We have combined operations research and bioinformatics methods to extract key networks of mutations that differentiate founder and chronic stages for 156 subtype B and 107 subtype C envelope (gp160) sequences. The chronic networks for both subtypes revealed strikingly different hub-and-spoke topologies compared to the less structured transmission networks. This suggests that the hub nodes are impacted by the immune response and the resulting loss of fitness is compensated by mutations at the spoke positions. The major hubs in the chronic C network occur at positions 12, 137 (within the N136 glycan), and 822, and at position 306 for subtype B. While both founder networks had a more heterogeneous connected network structure, interestingly founder B subnetworks around positions 640 and 837 preferentially contained CD4 and coreceptor binding domains. Finally, we observed a differential effect of glycosylation between founder and chronic subtype B where the latter had mutational pathways significantly driven by N-glycosylation. Our study provides insights into the mutational pathways HIV takes to evade the immune response, and presents features more likely to establish founder infection, valuable for effective vaccine design.

Mechanisms of antiviral resistance in influenza neuraminidase revealed by a mass spectrometry based phylonumerics approach.

A mass based phylonumerics approach is shown to be able to investigate the origins of the emergence of antiviral resistance mutations in influenza neuraminidase through a global view of mutational trends. Frequent ancestral and descendant mutations that precede and follow the manifestation of antiviral resistance mutations are identified in N2 neuraminidase. The majority occur in the head region around the active site and drive hydrophilicity changes, primarily through the incorporation or loss of hydroxyl groups. These increase or reduce the accessibility of the site to the bulk solvent. The most frequent ancestral mutations that occur on at least two occasions are I/L307M, G/A414S/T, I312T, I/L307S, P386S and S367N; the latter introducing a glycosylation site. The most frequent descendant mutation, after incorporation of an antiviral resistance mutation, is D/E401G/A. Together with others observed, this restore the protein's hydrophobicity about the active site region that limits entry of a sialic acid or inhibitor molecule and reduces viral fitness. The results of this global in silico phylonumerics study demonstrate that evolutionary mechanisms and functionally linked or compensatory mutations, remote in the sequence or structure, can be identified and interrogated at a molecular level.

Ancestral and Compensatory Mutations that Promote Antiviral Resistance in Influenza N1 Neuraminidase Revealed by a Phylonumerics Approach.

Implementation of a new phylonumerics approach to construct a mass tree representing over 6000 H1N1 human influenza strains has enabled ancestral and compensatory descendant mutations to be identified in N1 neuraminidase that promote antiviral resistance and restore viral fitness. Adjacent to the H275Y resistance mutation site, mutations S299A and S247N, respectively, lead the evolution of oseltamivir-resistant strains and restore viral fitness to those strains thereafter. Importantly the mass tree phylonumerics approach can identify such mutations globally, without any positional bias, so that functionally linked or compensatory mutations remote in the sequence or structure of the protein can be identified and interrogated. This is achieved using mass map datasets commonly employed for protein identification in proteomics applications, thus avoiding the need for either gene or protein sequences that are central to other phylogenetic methods.

Identification of epistatic mutations and insights into the evolution of the influenza virus using a mass-based protein phylogenetic approach.

A mass-based protein phylogenetic approach developed in this laboratory has been applied to study mutation trends and identify consecutive or near-consecutive mutations typically associated with positive epistasis. While epistasis is thought to occur commonly during the evolution of viruses, the extent of epistasis in influenza, and its role in the evolution of immune escape and drug resistant mutants, remains to be systematically investigated. Here putative epistatic mutations within H3 hemagglutinin in type A influenza are identified where leading parent mutations were found to predominate within reported antigenic sites of the protein. Frequent subsequent mutations resided exclusively in different antigenic regions, providing the virus with a possible immune escape mechanism, or at other remote sites that drive beneficial protein structural and functional change. The results also enable a "small steps" evolutionary model to be proposed where the more frequent consecutive, or near-consecutive, non-conservative mutations exhibited less structural, and thus functional, change. This favours the evolutionary survival of the virus over mutations associated with more substantive change that may cause or risk its own extinction.

Mutational analysis employing a phylogenetic mass tree approach in a study of the evolution of the influenza virus.

A mass based approach has been advanced to enable mutations associated with the evolution of proteins to be both charted and interrogated using phylogenetic trees built solely from the masses of peptides generated upon protein proteolysis. The modified MassTree algorithm identifies and displays all such mutations and calculates the frequency of a particular mutation across a tree. Its significance in terms of its position(s) on the tree is scored, where mutations that occur toward the basis of the tree are weighted more favourably. A comparison with data generated from a conventional sequence based tree demonstrates the reliability of mutational analysis employing this approach. Although illustrated for the study of the evolution of influenza hemagglutinin in this work, the approach has far broader applicability and can be applied to investigate the evolution of any organism. In the case of simple microorganisms this can be achieved even without the separation of component proteins. Given the central role that mass map or fingerprint data plays in protein identification in proteomics, this work demonstrates that such data can be successfully employed in a phylogenetics strategy to better understand and predict future evolutionary trends from the perspective of functional proteins expressed by the organism.