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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.

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.

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.

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.

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.

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 opening of the large extracellular domain of CD81. Therefore, CD81 possesses a potential cholesterol sensing mechanism; however, the relevance of this 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 receptor activity whereas the closed mutant enhanced activity. These data are consistent with CD81 cholesterol sensing resulting in a switch 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.

The membrane proximal external region (MPER) of HIV-1 gp41 is targeted by broadly neutralizing antibodies (bnAbs) 4E10 and 10E8. In this proof-of-concept study, we evaluated a novel multi-immunogen vaccine strategy referred to as Incremental, Phased Antigenic Stimulation for Rapid Antibody Maturation (IPAS-RAM) to induce 4E10/10E8-like bnAbs. Rabbits were immunized sequentially, but in a phased manner, with three immunogens that are progressively more native (gp41-28×3, gp41-54CT, and rVV-gp160DH12). Although nAbs were not induced, epitope-mapping analyses indicated that IPAS-RAM vaccination was better able to target antibodies towards the 4E10/10E8 epitopes than homologous prime-boost immunization using gp41-28×3 alone. MPER-specific rabbit monoclonal antibodies were generated, including 9F6. Although it lacked neutralizing activity, the target epitope profile of 9F6 closely resembled those of 4E10 and 10E8 (671NWFDITNWLWYIK683). B-cell repertoire analyses suggested the importance of co-immunizations for maturation of 9F6, which warrants further evaluation of our IPAS-RAM vaccine strategy using an improved priming immunogen.

The immune rejection of allografts is mediated by T cells via two distinct pathways: the direct and the indirect pathways. Direct alloresponse to intact donor MHC molecules is ensured by T cells which are polyclonal and directed toward a variety of antigens. This response is highly sensitive to treatment by immunosuppressive drugs including Cyclosporin A. Indirect alloresponse is oligoclonal and involves a few dominant antigen peptides on donor MHC. In contrast to its direct counterpart, indirect allorecognition is thought to be poorly sensitive to blockade by cyclosporin A. It is likely that indirect and direct types of alloresponses play different roles in the physiology of the rejection process. T cell responses occurring via direct allorecognition play a critical role during the early phase of acute graft rejection by sensitizing the host to graft antigens. Alternatively, once such sensitization has taken place, indirect type of alloresponse may become predominant and presumably represent the driving force in the actual destruction of transplanted tissues. In addition, we and others have provided strong circumstantial evidence indicating that secondary T cell responses via indirect allorecognition spread to new determinants on donor MHC and tissue-specific antigens. This phenomenon is likely to play an important role in late and chronic rejection, a major obstacle to long-term graft acceptance in clinical transplantation. Finally, a series of studies have demonstrated that early, pre-transplant treatment with tolerogenic donor-derived MHC peptides can protect the graft from rejection in rodents. Although the mechanisms involved in MHC-peptide-induced tolerance are ill defined, this strategy represents a promising approach for ensuring long-lasting graft acceptance in the absence of widespread immunosuppression. It is now crucial to further explore the mechanims involved in immunogenicity and tolerogenicity of MHC peptides and to initiate clinical studies to evaluate the efficacy of blocking indirect alloresponses in transplanted patients.

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 ( 303 TRKSIHIGPGRAF 317 ) 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 ( 308 HIGPGRAFYTTGEI 323 ). Unexpectedly, the 315 RAFYTT 320 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.

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.

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.

Next-generation sequencing is making it possible to study the antibody repertoire of an organism in unprecedented detail, and, by so doing, to characterize its behavior in the response to infection and in pathological conditions such as autoimmunity and cancer. The polymorphic nature of the repertoire poses unique challenges that rule out the use of many commonly used NGS methods and require tradeoffs to be made when considering experimental design.We outline the main contexts in which antibody repertoire analysis has been used, and summarize the key tools that are available. The humoral immune response to vaccination has been a particular focus of repertoire analyses, and we review the key conclusions and methods used in these studies.

Understanding metabolic pathways is one of the most important fields in bioscience in the post-genomic era, but curating metabolic pathways requires considerable man-power. As such there is a lack of reliable, experimentally verified metabolic pathways in databases and databases are forced to predict all but the most immediately useful pathways.Text-mining has the potential to solve this problem, but while sophisticated text-mining methods have been developed to assist the curation of many types of biomedical networks, such as protein-protein interaction networks, the mining of metabolic pathways from the literature has been largely neglected by the text-mining community. In this chapter we describe a pipeline for the extraction of metabolic pathways built on freely available open-source components and a heuristic metabolic reaction extraction algorithm.

Understanding metabolic pathways is one of the most important fields in bioscience in the post-genomic era, but curating metabolic pathways requires considerable man-power. As such there is a lack of reliable, experimentally verified metabolic pathways in databases and databases are forced to predict all but the most immediately useful pathways. Text-mining has the potential to solve this problem, but while sophisticated text-mining methods have been developed to assist the curation of many types of biomedical networks, such as protein–protein interaction networks, the mining of metabolic pathways from the literature has been largely neglected by the text-mining community. In this chapter we describe a pipeline for the extraction of metabolic pathways built on freely available open-source components and a heuristic metabolic reaction extraction algorithm.

‘Big Data’ and a surge in quantitative methodologies increasingly urge bioresearchers to train and improve their mathematical and computational skills. In response to this challenge the Biotechnology and Biological Sciences Research Council in the United Kingdom offered funds to develop web-based training in mathematics and computation for life scientists in all fields. The SysMIC consortium won the bid and implemented a new type of online course, which so far has been delivered to more than 1400 scientists, mostly in the UK. Researchers train self-paced or in cohorts in a media rich environment with materials based around intuitive biological examples. We describe the course, its trainee spectrum, and the modes of trainee engagement. We propose that tailored interactive online training is a scalable model for continuing professional development in the interdisciplinary life sciences in the 21st century.

The ultimate aim of the EU-funded ImmunoGrid project is to develop a natural-scale model of the human immune system—that is, one that reflects both the diversity and the relative proportions of the molecules and cells that comprise it—together with the grid infrastructure necessary to apply this model to specific applications in the field of immunology. These objectives present the ImmunoGrid Consortium with formidable challenges in terms of complexity of the immune system, our partial understanding about how the immune system works, the lack of reliable data and the scale of computational resources required. In this paper, we explain the key challenges and the approaches adopted to overcome them. We also consider wider implications for the present ambitious plans to develop natural-scale, integrated models of the human body that can make contributions to personalized health care, such as the European Virtual Physiological Human initiative. Finally, we ask a key question: How long will it take us to resolve these challenges and when can we expect to have fully functional models that will deliver health-care benefits in the form of personalized care solutions and improved disease prevention?

Highlights ► All the structural B-cell epitopes we examined are discontinuous. ► Only 18% of structural epitopes are spanned by a peptide fragment of 40 residues. ► Centralized and random distributions were considered for key functional residues. ► Fragments with only 7 residues will successfully span most key functional residues., Although it is widely acknowledged that most B-cell epitopes are discontinuous, the degree of discontinuity is poorly understood. For example, given that an antigen having a single epitope that has been chopped into peptides of a specific length, what is the likelihood that one of the peptides will span all the residues belonging to that epitope? Or, alternatively, what is the largest proportion of the epitope's residues that any peptide is likely to contain? These and similar questions are of direct relevance both to computational methods that aim to predict the location of epitopes from sequence (linear B-cell epitope prediction methods) and window-based experimental methods that aim to locate epitopes by assessing the strength of antibody binding to synthetic peptides on a chip. In this paper we present an analysis of the degree of B-cell epitope discontinuity, both in terms of the structural epitopes defined by a set of antigen–antibody complexes in the Protein Data Bank, and with respect to the distribution of key residues that form functional epitopes. We show that, taking a strict definition of discontinuity, all the epitopes in our data set are discontinuous. More significantly, we provide explicit guidance about the choice of peptide length when using window-based B-cell epitope prediction and mapping techniques based on a detailed analysis of the likely effectiveness of different lengths.

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.

We have developed a computational Grid that enables us to exploit through a single interface a range of local, national and international resources. It insulates the user as far as possible from issues concerning administrative boundaries, passwords and different operating system features. This work has been undertaken as part of the European Union ImmunoGrid project whose aim is to develop simulations of the immune system at the molecular, cellular and organ levels. The ImmunoGrid consortium has members with computational resources on both sides of the Atlantic. By making extensive use of existing Grid middleware, our Grid has enabled us to exploit consortium and publicly available computers in a unified way, notwithstanding the diverse local software and administrative environments. We took 40 000 polypeptide sequences from 4000 avian and mammalian influenza strains and used a neural network for class I T-cell epitope prediction tools for 120 class I alleles and haplotypes to generate over 14 million high-quality protein–peptide binding predictions that we are mapping onto the three-dimensional structures of the proteins. By contrast, the Grid is also being used for developing new methods for class T-cell epitope predictions, where we have running batches of 120 molecular dynamics free-energy calculations.

An automatic sequence search and analysis protocol (DomainFinder) based on PSI-BLAST and IMPALA, and using conservative thresholds, has been developed for reliably integrating gene sequences from GenBank into their respective structural families within the CATH domain database (http://www.biochem.ucl.ac.uk/bsm/cath_new). DomainFinder assigns a new gene sequence to a CATH homologous superfamily provided that PSI-BLAST identifies a clear relationship to at least one other Protein Data Bank sequence within that superfamily. This has resulted in an expansion of the CATH protein family database (CATH-PFDB v1.6) from 19,563 domain structures to 176,597 domain sequences. A further 50,000 putative homologous relationships can be identified using less stringent cut-offs and these relationships are maintained within neighbour tables in the CATH Oracle database, pending further evidence of their suggested evolutionary relationship. Analysis of the CATH-PFDB has shown that only 15% of the sequence families are close enough to a known structure for reliable homology modeling. IMPALA/PSI-BLAST profiles have been generated for each of the sequence families in the expanded CATH-PFDB and a web server has been provided so that new sequences may be scanned against the profile library and be assigned to a structure and homologous superfamily.

The Forkhead box transcription factor FoxP3 is pivotal to the development and function of regulatory T cells (Tregs), which make a major contribution to peripheral tolerance. FoxP3 is believed to perform a regulatory role in all the vertebrate species in which it has been detected. The prevailing view is that FoxP3 is absent in birds and that avian Tregs rely on alternative developmental and suppressive pathways. Prompted by the automated annotation of foxp3 in the ground tit (Parus humilis) genome, we have questioned this assumption. Our analysis of all available avian genomes has revealed that the foxp3 locus is missing, incomplete or of poor quality in the relevant genomic assemblies for nearly all avian species. Nevertheless, in two species, the peregrine falcon (Falco peregrinus) and the saker falcon (F. cherrug), there is compelling evidence for the existence of exons showing synteny with foxp3 in the ground tit. A broader phylogenomic analysis has shown that FoxP3 sequences from these three species are similar to crocodilian sequences, the closest living relatives of birds. In both birds and crocodilians, we have also identified a highly proline-enriched region at the N terminus of FoxP3, a region previously identified only in mammals.

Although secondary structure prediction methods have recently improved, progress from secondary to tertiary structure prediction has been limited. A promising but largely unexplored route to this goal is to predict structure motifs from secondary structure knowledge. Here we present a novel method for the recognition of β hairpins that combines secondary structure predictions and threading methods by using a database search and a neural network approach. The method successfully predicts 48 and 77%, respectively, of all of hairpin and nonhairpin β-coil-β motifs in a protein database. We find that the main contributors to motif recognition are predicted accessibility and turn propensities.

We present a novel web-based resource,Gene3D, of precalculated structural assignments to gene sequences and whole genomes. This resource assigns structural domains from the CATH database to whole genes and links these to their curated functional and structural annotations within the CATH domain structure database, the functional Dictionary of Homologous Superfamilies (DHS) and PDBsum. CurrentlyGene3D provides annotation for 36 complete genomes (two eukaryotes, six archaea, and 28 bacteria). On average, between 30% and 40% of the genes of a given genome can be structurally annotated. Matches to structural domains are found using the profile-based method (PSI-BLAST). and a novel protocol, DRange, is used to resolve conflicts in matches involving different homologous superfamilies.

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 A 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.

The study of biological networks is playing an increasingly important role in the life sciences. Many different kinds of biological system can be modelled as networks; perhaps the most important examples are protein-protein interaction (PPI) networks, metabolic pathways, gene regulatory networks, and signalling networks. Although much useful information is easily accessible in publicly databases, a lot of extra relevant data lies scattered in numerous published papers. Hence there is a pressing need for automated text-mining methods capable of extracting such information from full-text articles. Here we present practical guidelines for constructing a text-mining pipeline from existing code and software components capable of extracting PPI networks from full-text articles. This approach can be adapted to tackle other types of biological network.

The study of biological networks is playing an increasingly important role in the life sciences. Many different kinds of biological system can be modelled as networks; perhaps the most important examples are protein-protein interaction (PPI) networks, metabolic pathways, gene regulatory networks, and signalling networks. Although much useful information is easily accessible in publicly databases, a lot of extra relevant data lies scattered in numerous published papers. Hence there is a pressing need for automated text-mining methods capable of extracting such information from full-text articles. Here we present practical guidelines for constructing a text-mining pipeline from existing code and software components capable of extracting PPI networks from full-text articles. This approach can be adapted to tackle other types of biological network.