Evolutionary remodelling of N-terminal domain loops fine-tunes SARS-CoV-2 spike.

The emergence of SARS-CoV-2 variants has exacerbated the COVID-19 global health crisis. Thus far, all variants carry mutations in the spike glycoprotein, which is a critical determinant of viral transmission being responsible for attachment, receptor engagement and membrane fusion, and an important target of immunity. Variants frequently bear truncations of flexible loops in the N-terminal domain (NTD) of spike; the functional importance of these modifications has remained poorly characterised. We demonstrate that NTD deletions are important for efficient entry by the Alpha and Omicron variants and that this correlates with spike stability. Phylogenetic analysis reveals extensive NTD loop length polymorphisms across the sarbecoviruses, setting an evolutionary precedent for loop remodelling. Guided by these analyses, we demonstrate that variations in NTD loop length, alone, are sufficient to modulate virus entry. We propose that variations in NTD loop length act to fine-tune spike; this may provide a mechanism for SARS-CoV-2 to navigate a complex selection landscape encompassing optimisation of essential functionality, immune-driven antigenic variation and ongoing adaptation to a new host.

Mechanistic diversity in MHC class I antigen recognition.

Throughout its evolution, the human immune system has developed a plethora of strategies to diversify the antigenic peptide sequences that can be targeted by the CD8+ T cell response against pathogens and aberrations of self. Here we provide a general overview of the mechanisms that lead to the diversity of antigens presented by MHC class I complexes and their recognition by CD8+ T cells, together with a more detailed analysis of recent progress in two important areas that are highly controversial: the prevalence and immunological relevance of unconventional antigen peptides; and cross-recognition of antigenic peptides by the T cell receptors of CD8+ T cells.

VDJbase: an adaptive immune receptor genotype and haplotype database.

VDJbase is a publicly available database that offers easy searching of data describing the complete sets of gene sequences (genotypes and haplotypes) inferred from adaptive immune receptor repertoire sequencing datasets. VDJbase is designed to act as a resource that will allow the scientific community to explore the genetic variability of the immunoglobulin (Ig) and T cell receptor (TR) gene loci. It can also assist in the investigation of Ig- and TR-related genetic predispositions to diseases. Our database includes web-based query and online tools to assist in visualization and analysis of the genotype and haplotype data. It enables users to detect those alleles and genes that are significantly over-represented in a particular population, in terms of genotype, haplotype and gene expression. The database website can be freely accessed at https://www.vdjbase.org/, and no login is required. The data and code use creative common licenses and are freely downloadable from https://bitbucket.org/account/user/yaarilab/projects/GPHP.

OGRDB: a reference database of inferred immune receptor genes.

High-throughput sequencing of the adaptive immune receptor repertoire (AIRR-seq) is providing unprecedented insights into the immune response to disease and into the development of immune disorders. The accurate interpretation of AIRR-seq data depends on the existence of comprehensive germline gene reference sets. Current sets are known to be incomplete and unrepresentative of the degree of polymorphism and diversity in human and animal populations. A key issue is the complexity of the genomic regions in which they lie, which, because of the presence of multiple repeats, insertions and deletions, have not proved tractable with short-read whole genome sequencing. Recently, tools and methods for inferring such gene sequences from AIRR-seq datasets have become available, and a community approach has been developed for the expert review and publication of such inferences. Here, we present OGRDB, the Open Germline Receptor Database (https://ogrdb.airr-community.org), a public resource for the submission, review and publication of previously unknown receptor germline sequences together with supporting evidence.

Cholesterol sensing by CD81 is important for hepatitis C virus entry.

CD81 plays a central role in a variety of physiological and pathological processes. Recent structural analysis of CD81 indicates that it contains an intramembrane cholesterol-binding pocket and that interaction with cholesterol may regulate a conformational switch in the large extracellular domain of CD81. Therefore, CD81 possesses a potential cholesterol-sensing mechanism; however, its relevance for protein function is thus far unknown. In this study we investigate CD81 cholesterol sensing in the context of its activity as a receptor for hepatitis C virus (HCV). Structure-led mutagenesis of the cholesterol-binding pocket reduced CD81-cholesterol association but had disparate effects on HCV entry, both reducing and enhancing CD81 receptor activity. We reasoned that this could be explained by alterations in the consequences of cholesterol binding. To investigate this further we performed molecular dynamic simulations of CD81 with and without cholesterol; this identified a potential allosteric mechanism by which cholesterol binding regulates the conformation of CD81. To test this, we designed further mutations to force CD81 into either the open (cholesterol-unbound) or closed (cholesterol-bound) conformation. The open mutant of CD81 exhibited reduced HCV receptor activity, whereas the closed mutant enhanced activity. These data are consistent with cholesterol sensing switching CD81 between a receptor active and inactive state. CD81 interactome analysis also suggests that conformational switching may modulate the assembly of CD81-partner protein networks. This work furthers our understanding of the molecular mechanism of CD81 cholesterol sensing, how this relates to HCV entry, and CD81's function as a molecular scaffold; these insights are relevant to CD81's varied roles in both health and disease.

Flexibility and intrinsic disorder are conserved features of hepatitis C virus E2 glycoprotein.

The glycoproteins of hepatitis C virus, E1E2, are unlike any other viral fusion machinery yet described, and are the current focus of immunogen design in HCV vaccine development; thus, making E1E2 both scientifically and medically important. We used pre-existing, but fragmentary, structures to model a complete ectodomain of the major glycoprotein E2 from three strains of HCV. We then performed molecular dynamic simulations to explore the conformational landscape of E2, revealing a number of important features. Despite high sequence divergence, and subtle differences in the models, E2 from different strains behave similarly, possessing a stable core flanked by highly flexible regions, some of which perform essential functions such as receptor binding. Comparison with sequence data suggest that this consistent behaviour is conferred by a network of conserved residues that act as hinge and anchor points throughout E2. The variable regions (HVR-1, HVR-2 and VR-3) exhibit particularly high flexibility, and bioinformatic analysis suggests that HVR-1 is a putative intrinsically disordered protein region. Dynamic cross-correlation analyses demonstrate intramolecular communication and suggest that specific regions, such as HVR-1, can exert influence throughout E2. To support our computational approach we performed small-angle X-ray scattering with purified E2 ectodomain; this data was consistent with our MD experiments, suggesting a compact globular core with peripheral flexible regions. This work captures the dynamic behaviour of E2 and has direct relevance to the interaction of HCV with cell-surface receptors and neutralising antibodies.

Increased Epitope Complexity Correlated with Antibody Affinity Maturation and a Novel Binding Mode Revealed by Structures of Rabbit Antibodies against the Third Variable Loop (V3) of HIV-1 gp120.

The third variable (V3) loop of HIV-1 gp120 is an immunodominant region targeted by neutralizing antibodies (nAbs). Despite limited breadth, better characterization of the structural details of the interactions between these nAbs and their target epitopes would enhance our understanding of the mechanism of neutralization and facilitate designing better immunogens to induce nAbs with greater breadth. Recently, we isolated two anti-V3 neutralizing monoclonal antibodies (MAbs), 10A3 and 10A37, from a rabbit immunized with gp120 of the M group consensus sequence. In this study, crystal structures of these MAbs bound to target epitopes were determined. 10A3 binds to the V3 crown (303TRKSIHIGPGRAF317) using the cradle binding mode, similar to human V3 MAbs encoded by IGHV5-51 germ line genes, and its epitope structure resembles that bound to the human antibodies. In contrast, 10A37, which exhibits greater breadth and potency than 10A3, binds the V3 crown and the succeeding stem region (308HIGPGRAFYTTGEI323). Unexpectedly, the 315RAFYTT320 portion of the epitope existed as helical turns, a V3 structure that has not been observed previously. Its main chain-dominated antigen-antibody interactions not only explain the broad neutralization of 10A37 but also show that its epitope is a potential vaccine target to be further evaluated. In conclusion, our study provides novel insights about neutralization-susceptible epitope structures of the V3 loop of HIV-1 gp120 and demonstrates that, despite low amino acid sequence similarity to human antibody germ line genes, rabbits can serve as a useful animal model to evaluate human vaccine candidates.IMPORTANCE The apex crown of V3 of HIV-1 gp120 is the most immunogenic region of the surface glycoprotein, and many MAbs targeting this region have been developed. Structural understanding of V3 crown MAbs not only can help understand how antibody responses target this unique region but also contribute to immunogen design for vaccine development. We present here crystal structures of two neutralizing V3 MAbs, 10A3 and 10A37, developed from a rabbit immunized with gp120. Our analysis of 10A3 in complex with V3 provided a detailed example of how epitope complexity can evolve with affinity maturation, while that of 10A37 revealed a novel V3 binding mode targeting the C-terminal side of the V3 crown and showed that this region can form a helical structure. Our study provides novel insights about neutralization-susceptible V3 epitope structures and demonstrates that rabbits can serve as a useful animal model to evaluate human vaccine candidates.

Factor VIII cross-matches to the human proteome reduce the predicted inhibitor risk in missense mutation hemophilia A.

Single missense mutations in the F8 gene encoding the coagulation protein factor VIII give rise predominantly to non-severe hemophilia A. Despite only a single amino acid sequence difference between the replacement, therapeutic factor VIII and the patient's endogenous factor VIII, therapeutic factor VIII may still be perceived as foreign by the recipient's immune system and trigger an immune response (inhibitor). Inhibitor formation is a life-long risk for patients with non-severe hemophilia A treated with therapeutic factor VIII, but remains difficult to predict. The aim of this study was to understand whether fortuitous, primary sequence cross-matches between therapeutic factor VIII and proteins in the human proteome are the reason why certain F8 mutations are not associated with inhibitor formation. We predicted which therapeutic factor VIII differences are potentially perceived as foreign by helper T cells - a necessary precursor to inhibitor development - and then scanned potentially immunogenic peptides against more than 100,000 proteins in the proteome. As there are hundreds of disease-causing F8 missense mutations and the human leukocyte antigen gene complex governing peptide presentation to helper T cells is highly polymorphic, these calculations pose a huge combinatorial challenge that we addressed computationally. We found that cross-matches between therapeutic factor VIII and the human proteome are commonplace and have a profound impact on the predicted risk of inhibitor development. Our results emphasize the importance of knowing both the F8 missense mutation and the human leukocyte antigen alleles of a patient with missense mutation hemophilia A if his underlying risk of inhibitor development is to be estimated.

N-linked glycans on influenza A H3N2 hemagglutinin constrain binding of host antibodies, but shielding is limited.

The extent of the role of N-linked glycans (N-glycans) in shielding influenza A hemagglutinin (HA) against host antibodies has proved controversial, with different authors making widely different assumptions. One common assumption is that N-glycans physically shield surface residues that are near to glycosylation sites, thereby preventing antibodies from binding to them. However, it is unclear, from existing experimental evidence, whether antibodies that bind close to N-glycans are a rare or commonplace feature of human herd immune responses to influenza AHA. The aim of this paper is to present a computational analysis of mutations in the vicinity of N-glycans that will facilitate a better understanding of their protective role. We identify, from an analysis of over 6000 influenza A H3N2 sequences, a set of residues adjacent to N-glycosylation sites that are highly likely to be involved in antigenic escape from host antibodies. Fifteen of these residues occur within 10 Å of an N-glycosylation site. Hence, we conclude that it is relatively common for antibodies to bind in close proximity to N-glycans on the surface ofHA, with any shielding effect largely attributable to the inability of host antibodies to bind across an N-glycan attachment site, rather than to the physical masking of neighboring residues.

A large-scale computational study of inhibitor risk in non-severe haemophilia A.

Over 500 missense F8 mutations have been reported to cause non-severe haemophilia A. Some F8 genotypes appear to confer a higher risk of inhibitor formation than others and individuals with the same F8 genotype may have differing risks of inhibitor formation. We present an in silico strategy demonstrating the heterogeneity of factor VIII (FVIII)-derived antigen presentation whilst identifying patterns of human leucocyte antigen (HLA) peptide binding that might predict future inhibitor risk. A well-validated computational tool, NetMHCII, enabled large-scale comparison of predicted antigen presentation between endogenous, mutated FVIII-derived peptides and wild-type, therapeutic FVIII-derived peptides spanning all F8 missense mutation positions reported to The Haemophilia A Mutation, Structure and Resource Site (HADB). We identify 40 F8 genotypes to be 'low risk' at a 50% inhibitory concentration (IC50 )-binding threshold of 300 nmol/l (P = 0·00005), defined as absence of novel peptide-major histocompatibility complex (MHC) surfaces for all 14 common HLA-DR alleles assessed. Analysing each of the possible 7280 F8 genotype/HLA-DR permutations individually at an IC50 threshold of 300 nmol/l, 65% are predicted to not generate a novel peptide-MHC surface that would be necessary to engage T cell help for subsequent anti-FVIII antibody generation. This study demonstrates the future importance of interpreting F8 genotype in the context of an individual's HLA profile to personalize inhibitor risk prediction.

Evolution in the influenza A H3 stalk - a challenge for broad-spectrum vaccines?

Recently, a number of broad-spectrum human antibodies binding to the stalk region of influenza A haemagglutinin (HA) have been isolated. As this region tends to develop substitutions at a slower rate than other regions of HA, a vaccine eliciting such antibodies could have a longer effective life. But this begs a question: is the stalk resistant to change even in the face of evolutionary pressure? In this paper, we analysed the known epitopes in the H3 stalk and, utilizing a collection of 3440 sequences, present a novel approach for detecting putative B-cell epitopes in regions such as this, in which mutations occur infrequently. We concluded that there have been periods of activity in the stalk that are consistent with the evolution of antigenic escape. This work casts light on the presence of stalk-binding antibodies in the population as a whole and, through the analysis of antigenically active regions in the stalk, may contribute to the identification of epitopes that are refractive to change and hence useful for vaccine development.

A text-mining system for extracting metabolic reactions from full-text articles.

BACKGROUND: Increasingly biological text mining research is focusing on the extraction of complex relationships relevant to the construction and curation of biological networks and pathways. However, one important category of pathway - metabolic pathways - has been largely neglected.Here we present a relatively simple method for extracting metabolic reaction information from free text that scores different permutations of assigned entities (enzymes and metabolites) within a given sentence based on the presence and location of stemmed keywords. This method extends an approach that has proved effective in the context of the extraction of protein-protein interactions. RESULTS: When evaluated on a set of manually-curated metabolic pathways using standard performance criteria, our method performs surprisingly well. Precision and recall rates are comparable to those previously achieved for the well-known protein-protein interaction extraction task. CONCLUSIONS: We conclude that automated metabolic pathway construction is more tractable than has often been assumed, and that (as in the case of protein-protein interaction extraction) relatively simple text-mining approaches can prove surprisingly effective. It is hoped that these results will provide an impetus to further research and act as a useful benchmark for judging the performance of more sophisticated methods that are yet to be developed.

Analysis of antigenically important residues in human influenza A virus in terms of B-cell epitopes.

In this paper we undertake an analysis of the antigenicity of influenza A virus hemagglutinin. We developed a novel computational approach to the identification of antigenically active regions and showed that the amino acid substitutions between successive predominant seasonal strains form clusters that are consistent, in terms of both their location and their size, with the properties of B-cell epitopes in general and with those epitopes that have been identified experimentally in influenza A virus hemagglutinin to date. Such an interpretation provides a biologically plausible framework for an understanding of the location of antigenically important substitutions that is more specific than the canonical "antigenic site" model and provides an effective basis for deriving models that predict antigenic escape in the H3N2 subtype. Our results support recent indications that antibodies binding to the "stalk" region of hemagglutinin are found in the human population and exert evolutionary pressure on the virus. Our computational approach provides a possible method for identifying antigenic escape through evolution in this region, which in some cases will not be identified by the hemagglutinin inhibition assay.

An entropic safety catch controls hepatitis C virus entry and antibody resistance.

E1 and E2 (E1E2), the fusion proteins of Hepatitis C Virus (HCV), are unlike that of any other virus yet described, and the detailed molecular mechanisms of HCV entry/fusion remain unknown. Hypervariable region-1 (HVR-1) of E2 is a putative intrinsically disordered protein tail. Here, we demonstrate that HVR-1 has an autoinhibitory function that suppresses the activity of E1E2 on free virions; this is dependent on its conformational entropy. Thus, HVR-1 is akin to a safety catch that prevents premature triggering of E1E2 activity. Crucially, this mechanism is turned off by host receptor interactions at the cell surface to allow entry. Mutations that reduce conformational entropy in HVR-1, or genetic deletion of HVR-1, turn off the safety catch to generate hyper-reactive HCV that exhibits enhanced virus entry but is thermally unstable and acutely sensitive to neutralising antibodies. Therefore, the HVR-1 safety catch controls the efficiency of virus entry and maintains resistance to neutralising antibodies. This discovery provides an explanation for the ability of HCV to persist in the face of continual immune assault and represents a novel regulatory mechanism that is likely to be found in other viral fusion machinery.

ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization.

Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccines. ImmunoGrid modules share common conceptual models and ontologies. The ImmunoGrid portal offers access to educational simulators where previously defined cases can be displayed, and to research simulators that allow the development of new, or tuning of existing, computational models. The portal is accessible at .

A computational analysis of the antigenic properties of haemagglutinin in influenza A H3N2.

MOTIVATION: Modelling antigenic shift in influenza A H3N2 can help to predict the efficiency of vaccines. The virus is known to exhibit sudden jumps in antigenic distance, and prediction of such novel strains from amino acid sequence differences remains a challenge. RESULTS: From analysis of 6624 amino acid sequences of wild-type H3, we propose updates to the frequently referenced list of 131 amino acids located at or near the five identified antibody binding regions in haemagglutinin (HA). We introduce a class of predictive models based on the analysis of amino acid changes in these binding regions, and extend the principle to changes in HA1 as a whole by dividing the molecule into regional bands. Our results show that a range of simple models based on banded changes give better predictive performance than models based on the established five canonical regions and can identify a higher proportion of vaccine escape candidates among novel strains than a current state-of-the-art model.

Characterization of the MurT/GatD complex in Mycobacterium tuberculosis towards validating a novel anti-tubercular drug target.

OBJECTIVES: Identification and validation of novel therapeutic targets is imperative to tackle the rise of drug resistance in tuberculosis. An essential Mur ligase-like gene (Rv3712), expected to be involved in cell-wall peptidoglycan (PG) biogenesis and conserved across mycobacteria, including the genetically depleted Mycobacterium leprae, was the primary focus of this study. METHODS: Biochemical analysis of Rv3712 was performed using inorganic phosphate release assays. The operon structure was identified using reverse-transcriptase PCR and a transcription/translation fusion vector. In vivo mycobacterial protein fragment complementation assays helped generate the interactome. RESULTS: Rv3712 was found to be an ATPase. Characterization of its operon revealed a mycobacteria-specific promoter driving the co-transcription of Rv3712 and Rv3713. The two gene products were found to interact with each other in vivo. Sequence-based functional assignments reveal that Rv3712 and Rv3713 are likely to be the mycobacterial PG precursor-modifying enzymes MurT and GatD, respectively. An in vivo network involving Mtb-MurT, regulatory proteins and cell division proteins was also identified. CONCLUSIONS: Understanding the role of the enzyme complex in the context of PG metabolism and cell division, and the implications for antimicrobial resistance and host immune responses will facilitate the design of therapeutics that are targeted specifically to M. tuberculosis.

An intuitionistic approach to scoring DNA sequences against transcription factor binding site motifs.

BACKGROUND: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs is a crucial problem in computational biology and includes the subtask of predicting the location of known TFBS motifs in a given DNA sequence. It has previously been shown that, when scoring matches to known TFBS motifs, interdependencies between positions within a motif should be taken into account. However, this remains a challenging task owing to the fact that sequences similar to those of known TFBSs can occur by chance with a relatively high frequency. Here we present a new method for matching sequences to TFBS motifs based on intuitionistic fuzzy sets (IFS) theory, an approach that has been shown to be particularly appropriate for tackling problems that embody a high degree of uncertainty. RESULTS: We propose SCintuit, a new scoring method for measuring sequence-motif affinity based on IFS theory. Unlike existing methods that consider dependencies between positions, SCintuit is designed to prevent overestimation of less conserved positions of TFBSs. For a given pair of bases, SCintuit is computed not only as a function of their combined probability of occurrence, but also taking into account the individual importance of each single base at its corresponding position. We used SCintuit to identify known TFBSs in DNA sequences. Our method provides excellent results when dealing with both synthetic and real data, outperforming the sensitivity and the specificity of two existing methods in all the experiments we performed. CONCLUSIONS: The results show that SCintuit improves the prediction quality for TFs of the existing approaches without compromising sensitivity. In addition, we show how SCintuit can be successfully applied to real research problems. In this study the reliability of the IFS theory for motif discovery tasks is proven.

Germline immunoglobulin genes: disease susceptibility genes hidden in plain sight?

Immunoglobulin genes are rarely considered as disease susceptibility genes despite their obvious and central contributions to immune function. This appears to be a consequence of historical views on antibody repertoire formation that no longer stand, and of difficulties that until recently surrounded the documentation of the suite of antibody genes in any individual. If these important genes are to be accessible to GWAS studies, allelic variation within the human population needs to be better documented, and a curated set of genomic variations associated with antibody genes needs to be formulated. Repertoire studies arising from the COVID-19 pandemic provide an opportunity to meet these needs, and may provide insights into the profound variability that is seen in outcomes to this infection.

A realistic assessment of methods for extracting gene/protein interactions from free text.

BACKGROUND: The automated extraction of gene and/or protein interactions from the literature is one of the most important targets of biomedical text mining research. In this paper we present a realistic evaluation of gene/protein interaction mining relevant to potential non-specialist users. Hence we have specifically avoided methods that are complex to install or require reimplementation, and we coupled our chosen extraction methods with a state-of-the-art biomedical named entity tagger. RESULTS: Our results show: that performance across different evaluation corpora is extremely variable; that the use of tagged (as opposed to gold standard) gene and protein names has a significant impact on performance, with a drop in F-score of over 20 percentage points being commonplace; and that a simple keyword-based benchmark algorithm when coupled with a named entity tagger outperforms two of the tools most widely used to extract gene/protein interactions. CONCLUSION: In terms of availability, ease of use and performance, the potential non-specialist user community interested in automatically extracting gene and/or protein interactions from free text is poorly served by current tools and systems. The public release of extraction tools that are easy to install and use, and that achieve state-of-art levels of performance should be treated as a high priority by the biomedical text mining community.