Reviews

Reviews: Arne Skjølsvold: Slettabøboplassen. Et bidrag til diskusjonen om forholdet mellem fangst- og bondesamfunnet i yngre steinalder og bronsealder. Stavanger 1977. (by Svend Nielsen). Klaus Ebbesen: Tragtbægerkultur i Nordjylland. Nordiske Fortidsminder. Ser. B, Vol. 5, 197 8. (by P. 0. Nielsen). Birgitta Hulthen: On Ceramic Technology during the Scanian Neolithic and Bronze Age. Stockholm 1977. (by Ulla Engberg). Renate Rolle: Totenkult der Skythen I. Das Steppengebiet. Vorgeschichtliche Forschungen 18,I, I and I,2. Berlin-N.Y. 1979. (by Ole Klindt-Jensen). Werner Haarnagel: Die Grabung Feddersen Wierde. Methode, Hausbau, Siedlungs- u. Wirtschaftsformen sowie Sozialstruktur. Wiesbaden 1979. (by Steen Hvass). U. Nasman and E. Wegraeus (eds.): Eketorp. Fortification and Settlement on Öland/Sweden. The Setting. Stockholm 1979. (by Ulla Lund Hansen). Ingrid Ulbricht: Die Geweihverarbeitung in Haithabu. Die Ausgrabungen in Haithabu, Vol. 7. Neumünster 1978 . Heid Gjöstein Resi: Die Specksteinfunde aus Haithabu. Berichte über die Ausgrabungen in Haithabu, Vol. 14. Neumünster 1979. (by Hans Jørgen Madsen)

Accelerating surveillance and research of antimicrobial resistance - an online repository for sharing of antimicrobial susceptibility data associated with whole-genome sequences

Antimicrobial resistance (AMR) is an emerging threat to modern medicine. Improved diagnostics and surveillance of resistant bacteria require the development of next-generation analysis tools and collabor

Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction

<p>Abstract</p> <p>Background</p> <p>Reliable predictions of Cytotoxic T lymphocyte (CTL) epitopes are essential for rational vaccine design. Most importantly, they can minimize the experimental effort needed to identify epitopes. NetCTL is a web-based tool designed for predicting human CTL epitopes in any given protein. It does so by integrating predictions of proteasomal cleavage, TAP transport efficiency, and MHC class I affinity. At least four other methods have been developed recently that likewise attempt to predict CTL epitopes: EpiJen, MAPPP, MHC-pathway, and WAPP. In order to compare the performance of prediction methods, objective benchmarks and standardized performance measures are needed. Here, we develop such large-scale benchmark and corresponding performance measures and report the performance of an updated version 1.2 of NetCTL in comparison with the four other methods.</p> <p>Results</p> <p>We define a number of performance measures that can handle the different types of output data from the five methods. We use two evaluation datasets consisting of known HIV CTL epitopes and their source proteins. The source proteins are split into all possible 9 mers and except for annotated epitopes; all other 9 mers are considered non-epitopes. In the RANK measure, we compare two methods at a time and count how often each of the methods rank the epitope highest. In another measure, we find the specificity of the methods at three predefined sensitivity values. Lastly, for each method, we calculate the percentage of known epitopes that rank within the 5% peptides with the highest predicted score.</p> <p>Conclusion</p> <p>NetCTL-1.2 is demonstrated to have a higher predictive performance than EpiJen, MAPPP, MHC-pathway, and WAPP on all performance measures. The higher performance of NetCTL-1.2 as compared to EpiJen and MHC-pathway is, however, not statistically significant on all measures. In the large-scale benchmark calculation consisting of 216 known HIV epitopes covering all 12 recognized HLA supertypes, the NetCTL-1.2 method was shown to have a sensitivity among the 5% top-scoring peptides above 0.72. On this dataset, the best of the other methods achieved a sensitivity of 0.64. The NetCTL-1.2 method is available at <url>http://www.cbs.dtu.dk/services/NetCTL</url>.</p> <p>All used datasets are available at <url>http://www.cbs.dtu.dk/suppl/immunology/CTL-1.2.php</url>.</p

Pharmacological Undertreatment of Coronary Risk Factors in Patients with Psoriasis: Observational Study of the Danish Nationwide Registries

BACKGROUND: Patients with psoriasis have increased prevalence of coronary risk factors and limited recent results have suggested that these risk factors are undertreated in patients with psoriasis. This may contribute to the increased risk of cardiovascular diseases observed in patients with psoriasis. OBJECTIVE: To examine the pharmacological treatment of coronary risk factors in patients with severe psoriasis treated with biologic agents in a real-world setting. METHODS AND FINDINGS: Medical history of patients with severe psoriasis treated with biologic agents in the time period 2007-09 was retrieved from a Danish nationwide registry (DERMBIO). Individual-level linkage of nationwide administrative registries of hospitalizations, concomitant medications, and socioeconomic status was performed to gain insights into the use of pharmacological treatment. A total of 693 patients (mean age 46.1 ± 12.7 years, 65.7% male) with severe psoriasis treated with biologic agents were identified. Hypertension, hypercholesterolemia, and diabetes mellitus were identified in 16.6%, 9.2%, and 6.7% of cases, respectively. Patients with severe psoriasis were significantly less likely to receive cardiovascular pharmacotherapy compared to age, sex, and coronary risk factor matched controls. In psoriatic patients with hypertension 27.7% received no antihypertensive pharmacotherapy. Patients with dyslipidemia received cholesterol-lowering medications in 55.8% of cases and patients with diabetes mellitus received angiotensin converting enzyme inhibitors/angiotensin II receptor blockers and cholesterol-lowering medications in 42.1% and 23.7% of cases, respectively. Similar results were found for the subset of patients with >1 coronary risk factor and for high risk patients with established atherosclerotic disease. CONCLUSION: This nationwide study of patients with severe psoriasis demonstrated substantial undertreatment of coronary risk factors. Increased focus on identifying cardiovascular risk factors and initiation of preventive cardiovascular pharmacotherapy in patients with psoriasis is warranted

Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan

CD4 positive T helper cells control many aspects of specific immunity. These cells are specific for peptides derived from protein antigens and presented by molecules of the extremely polymorphic major histocompatibility complex (MHC) class II system. The identification of peptides that bind to MHC class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent. Validation of the method includes identification of endogenously derived HLA class II ligands, cross-validation, leave-one-molecule-out, and binding motif identification for hitherto uncharacterized HLA-DR molecules. The validation shows that the method can successfully predict binding for HLA-DR molecules-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC "space," enabling a highly efficient iterative process for improving MHC class II binding predictions

HLA Class I Binding 9mer Peptides from Influenza A Virus Induce CD4+ T Cell Responses

BACKGROUND: Identification of human leukocyte antigen class I (HLA-I) restricted cytotoxic T cell (CTL) epitopes from influenza virus is of importance for the development of new effective peptide-based vaccines. METHODOLOGY/PRINCIPAL FINDINGS: In the present work, bioinformatics was used to predict 9mer peptides derived from available influenza A viral proteins with binding affinity for at least one of the 12 HLA-I supertypes. The predicted peptides were then selected in a way that ensured maximal coverage of the available influenza A strains. One hundred and thirty one peptides were synthesized and their binding affinities for the HLA-I supertypes were measured in a biochemical assay. Influenza-specific T cell responses towards the peptides were quantified using IFNgamma ELISPOT assays with peripheral blood mononuclear cells (PBMC) from adult healthy HLA-I typed donors as responder cells. Of the 131 peptides, 21 were found to induce T cell responses in 19 donors. In the ELISPOT assay, five peptides induced responses that could be totally blocked by the pan-specific anti-HLA-I antibody W6/32, whereas 15 peptides induced responses that could be completely blocked in the presence of the pan-specific anti-HLA class II (HLA-II) antibody IVA12. Blocking of HLA-II subtype reactivity revealed that 8 and 6 peptide responses were blocked by anti-HLA-DR and -DP antibodies, respectively. Peptide reactivity of PBMC depleted of CD4(+) or CD8(+) T cells prior to the ELISPOT culture revealed that effectors are either CD4(+) (the majority of reactivities) or CD8(+) T cells, never a mixture of these subsets. Three of the peptides, recognized by CD4(+) T cells showed binding to recombinant DRA1*0101/DRB1*0401 or DRA1*0101/DRB5*0101 molecules in a recently developed biochemical assay. CONCLUSIONS/SIGNIFICANCE: HLA-I binding 9mer influenza virus-derived peptides induce in many cases CD4(+) T cell responses restricted by HLA-II molecules

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

<p>Abstract</p> <p>Background</p> <p>Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles.</p> <p>Results</p> <p>The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR), we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors.</p> <p>Conclusion</p> <p>The SMM-align method was shown to outperform other state of the art MHC class II prediction methods. The method predicts quantitative peptide:MHC binding affinity values, making it ideally suited for rational epitope discovery. The method has been trained and evaluated on the, to our knowledge, largest benchmark data set publicly available and covers the nine HLA-DR supertypes suggested as well as three mouse H2-IA allele. Both the peptide benchmark data set, and SMM-align prediction method (<it>NetMHCII</it>) are made publicly available.</p

Amino Acid Similarity Accounts for T Cell Cross-Reactivity and for “Holes” in the T Cell Repertoire

Background: Cytotoxic T cell (CTL) cross-reactivity is believed to play a pivotal role in generating immune responses but the extent and mechanisms of CTL cross-reactivity remain largely unknown. Several studies suggest that CTL clones can recognize highly diverse peptides, some sharing no obvious sequence identity. The emerging realization in the field is that T cell receptors (TcR) recognize multiple distinct ligands. Principal Findings: First, we analyzed peptide scans of the HIV epitope SLFNTVATL (SFL9) and found that TCR specificity is position dependent and that biochemically similar amino acid substitutions do not drastically affect recognition. Inspired by this, we developed a general model of TCR peptide recognition using amino acid similarity matrices and found that such a model was able to predict the cross-reactivity of a diverse set of CTL epitopes. With this model, we were able to demonstrate that seemingly distinct T cell epitopes, i.e., ones with low sequence identity, are in fact more biochemically similar than expected. Additionally, an analysis of HIV immunogenicity data with our model showed that CTLs have the tendency to respond mostly to peptides that do not resemble self-antigens. Conclusions: T cell cross-reactivity can thus, to an extent greater than earlier appreciated, be explained by amino acid similarity. The results presented in this paper will help resolving some of the long-lasting discussions in the field of T cel

Identification of CD8+ T Cell Epitopes in the West Nile Virus Polyprotein by Reverse-Immunology Using NetCTL

West Nile virus (WNV) is a growing threat to public health and a greater understanding of the immune response raised against WNV is important for the development of prophylactic and therapeutic strategies.In a reverse-immunology approach, we used bioinformatics methods to predict WNV-specific CD8(+) T cell epitopes and selected a set of peptides that constitutes maximum coverage of 20 fully-sequenced WNV strains. We then tested these putative epitopes for cellular reactivity in a cohort of WNV-infected patients. We identified 26 new CD8(+) T cell epitopes, which we propose are restricted by 11 different HLA class I alleles. Aiming for optimal coverage of human populations, we suggest that 11 of these new WNV epitopes would be sufficient to cover from 48% to 93% of ethnic populations in various areas of the World.The 26 identified CD8(+) T cell epitopes contribute to our knowledge of the immune response against WNV infection and greatly extend the list of known WNV CD8(+) T cell epitopes. A polytope incorporating these and other epitopes could possibly serve as the basis for a WNV vaccine