IPD-IMGT/HLA Database

Blood group typing from whole-genome sequencing data

Many questions can be explored thanks to whole-genome data. The aim of this study was to overcome their main limits, software availability and database accuracy, and estimate the feasibility of red blood cell (RBC) antigen typing from whole-genome sequencing (WGS) data. We analyzed whole-genome data from 79 individuals for HLA-DRB1 and 9 RBC antigens. Whole-genome sequencing data was analyzed with software allowing phasing of variable positions to define alleles or haplotypes and validated for HLA typing from next-generation sequencing data. A dedicated database was set up with 1648 variable positions analyzed in KEL (KEL), ACKR1 (FY), SLC14A1 (JK), ACHE (YT), ART4 (DO), AQP1 (CO), CD44 (IN), SLC4A1 (DI) and ICAM4 (LW). Whole-genome sequencing typing was compared to that previously obtained by amplicon-based monoallelic sequencing and by SNaPshot analysis. Whole-genome sequencing data were also explored for other alleles. Our results showed 93% of concordance for blood group polymorphisms and 91% for HLA-DRB1. Incorrect typing and unresolved results confirm that WGS should be considered reliable with read depths strictly above 15x. Our results supported that RBC antigen typing from WGS is feasible but requires improvements in read depth for SNV polymorphisms typing accuracy. We also showed the potential for WGS in screening donors with rare blood antigens, such as weak JK alleles. The development of WGS analysis in immunogenetics laboratories would offer personalized care in the management of RBC disorders.

HLA-A29 and Birdshot Uveitis: Further Down the Rabbit Hole

HLA class I alleles constitute established risk factors for non-infectious uveitis and preemptive genotyping of HLA class I alleles is standard practice in the diagnostic work-up. The HLA-A29 serotype is indispensable to Birdshot Uveitis (BU) and renders this enigmatic eye condition a unique model to better understand how the antigen processing and presentation machinery contributes to non-infectious uveitis or chronic inflammatory conditions in general. This review will discuss salient points regarding the protein structure of HLA-A29 and how key amino acid positions impact the peptide binding preference and interaction with T cells. We discuss to what extent the risk genes ERAP1 and ERAP2 uniquely affect HLA-A29 and how the discovery of a HLA-A29-specific submotif may impact autoantigen discovery. We further provide a compelling argument to solve the long-standing question why BU only affects HLA-A29-positive individuals from Western-European ancestry by exploiting data from the 1000 Genomes Project. We combine novel insights from structural and immunopeptidomic studies and discuss the functional implications of genetic associations across the HLA class I antigen presentation pathway to refine the etiological basis of Birdshot Uveitis.

Generation of universal and hypoimmunogenic human pluripotent stem cells

There is a need to store very large numbers of conventional human pluripotent stem cell (hPSC) lines for their off‐the‐shelf usage in stem cell therapy. Therefore, it is valuable to generate “universal” or “hypoimmunogenic” hPSCs with gene‐editing technology by knocking out or in immune‐related genes. A few universal or hypoimmunogenic hPSC lines should be enough to store for their off‐the‐shelf usage. Here, we overview and discuss how to prepare universal or hypoimmunogenic hPSCs and their disadvantages. β2‐Microglobulin‐knockout hPSCs did not harbour human leukocyte antigen (HLA)‐expressing class I cells but rather activated natural killer (NK) cells. To avoid NK cell and macrophage activities, homozygous hPSCs expressing a single allele of an HLA class I molecule, such as HLA‐C, were developed. Major HLA class I molecules were knocked out, and PD‐L1, HLA‐G and CD47 were knocked in hPSCs using CRISPR/Cas9 gene editing. These cells escaped activation of not only T cells but also NK cells and macrophages, generating universal hPSCs.

A multiple peptides vaccine against COVID-19 designed from the nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the immunoinformatics approach

Due to the current Coronavirus (COVID-19) pandemic, the rapid discovery of a safe and effective vaccine is an essential issue. Consequently, this study aims to predict a potential COVID-19 peptide-based vaccine utilizing the Nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the Immunoinformatics approach. To achieve this goal, several Immune Epitope Database (IEDB) tools, molecular docking, and safety prediction servers were used. According to the results, The Spike peptide SQCVNLTTRTQLPPAYTNSFTRGVY is predicted to have the highest binding affinity to the B-Cells. The Spike peptide FTISVTTEI has the highest binding affinity to the Major Histocompatibility Complex class 1 (MHC I) Human Leukocyte Allele HLA-B*1503 (according to the MDockPeP and HPEPDOCK servers, docking scores were −153.9 and −229.356, respectively). The Nucleocapsid peptides KTFPPTEPK and RWYFYYLGTGPEAGL have the highest binding affinity to the MHC I HLA-A0202 allele and the three the Major Histocompatibility Complex class 2 (MHC II) Human Leukocyte Allele HLA-DPA1*01:03/DPB1*02:01, HLA-DQA1*01:02/DQB1-*06:02, HLA-DRB1, respectively. Docking scores of peptide KTFPPTEPK were −153.9 and −220.876. In contrast, docking scores of peptide RWYFYYLGTGPEAGL were ranged from 218 to 318. Furthermore, those peptides were predicted as non-toxic and non-allergen. Therefore, the combination of those peptides is predicted to stimulate better immunological responses with respectable safety.

Structural Modeling and Molecular Dynamics of the Immune Checkpoint Molecule HLA-G

HLA-G is considered to be an immune checkpoint molecule, a function that is closely linked to the structure and dynamics of the different HLA-G isoforms. Unfortunately, little is known about the structure and dynamics of these isoforms. For instance, there are only seven crystal structures of HLA-G molecules, being all related to a single isoform, and in some cases lacking important residues associated to the interaction with leukocyte receptors. In addition, they lack information on the dynamics of both membrane-bound HLA-G forms, and soluble forms. We took advantage of in silico strategies to disclose the dynamic behavior of selected HLA-G forms, including the membrane-bound HLA-G1 molecule, soluble HLA-G1 dimer, and HLA-G5 isoform. Both the membrane-bound HLA-G1 molecule and the soluble HLA-G1 dimer were quite stable. Residues involved in the interaction with ILT2 and ILT4 receptors (α3 domain) were very close to the lipid bilayer in the complete HLA-G1 molecule, which might limit accessibility. On the other hand, these residues can be completely exposed in the soluble HLA-G1 dimer, due to the free rotation of the disulfide bridge (Cys42/Cys42). In fact, we speculate that this free rotation of each protomer (i.e., the chains composing the dimer) could enable alternative binding modes for ILT2/ILT4 receptors, which in turn could be associated with greater affinity of the soluble HLA-G1 dimer. Structural analysis of the HLA-G5 isoform demonstrated higher stability for the complex containing the peptide and coupled β2-microglobulin, while structures lacking such domains were significantly unstable. This study reports for the first time structural conformations for the HLA-G5 isoform and the dynamic behavior of HLA-G1 molecules under simulated biological conditions. All modeled structures were made available through GitHub (https://github.com/KavrakiLab/), enabling their use as templates for modeling other alleles and isoforms, as well as for other computational analyses to investigate key molecular interactions.

Epitope prediction and identification- adaptive T cell responses in humans

Epitopes, in the context of T cell recognition, are short peptides typically derived by antigen processing, and presented on the cell surface bound to MHC molecules (HLA molecules in humans) for TCR scrutiny. The identification of epitopes is a context-dependent process, with consideration given to, for example, the source pathogen and protein, the host organism, and state of the immune reaction (e.g., following natural infection, vaccination, etc.). In the following review, we consider the various approaches used to define T cell epitopes, including both bioinformatic and experimental approaches, and discuss the concepts of immunodominance and immunoprevalence. We also discuss HLA polymorphism and epitope restriction, and the resulting impact on the identification of, and potential population coverage afforded by, epitopes or epitope-based vaccines. Finally, some examples of the practical application of T cell epitope identification are provided, showing how epitopes have been valuable for deriving novel immunological insights in the context of the immune response to various pathogens and allergens.

HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1 Allele and Haplotype Frequencies of 28,927 Saudi Stem Cell Donors Typed by Next-Generation Sequencing

Human leukocyte antigen (HLA) allele and haplotype frequency distribution varies widely between different ethnicities and geographical areas. Matching for HLA alleles is essential for successful related and unrelated stem cell transplantation. Among the Saudi population, data on HLA alleles and haplotypes are limited. A cross-sectional study was performed on 28,927 bone marrow donors. The most frequent HLA alleles were HLA-A*02:01:01G (20.2%), A*24:02:01G (7.5%); B*51:01:01G (19.0%), B*50:01:01G (12.3%); C*06:02:01G (16.7%), C*07:02:01G (12.2%); DRB1*07:01:01 (15.7%), DRB1*03:01:01G (13.3%); DQB1*02:01:01G (29.9%), DQB1*03:02:01G (13.2%); and DPB1*04:01:01G (35.2%), DPB1*02:01:02G (21.8%). The most frequent HLA-A~C~B~DRB1~DQB1 haplotypes were A*02:01:01G~C*06:02:01G~B*50:01:01G~DRB1*07:01:01G~DQB1*02:01:01G (1.9%) and A*02:05:01G~C*06:02:01G~B*50:01:01G~DRB1*07:01:01G~DQB1*02:01:01G (1.6%). The most frequent HLA-A~C~B~DRB1~DQB1~DPB1 haplotypes were A*02:01:01G~C*15:02:01G~B*51:01:01G~DRB1*04:02~DQB1*03:02:01G~DPB1*04:01:0G (1%) and A*02:01:01G~C*07:02:01G~B*07:02:01G~DRB1*15:01:01G~DQB1*06:02:01G~ DPB1*04:01:01G (0.9%). Based on these haplotype frequencies, we provide forecasts for the fraction of patients with full matching and single mismatched donors for 3 to 6 loci depending on the registry size. With one million donors, about 50% of the patients would find an 8/8 match and 90% a 7/8 match. These data are essential for registry planning, finding unrelated stem cell donors, population genetic studies, and HLA disease associations.

Self-Peptidome Variation Shapes Individual Immune Responses

The relationship between human genetic variation and disease has not been fully elucidated. According to the present view on infectious diseases pathogen resistance is linked to human leukocyte antigen (HLA) class I/II variants and their individual capacity to present pathogen-derived peptides. Yet, T cell education in the thymus occurs through negative and positive selection, and both processes are controlled by a combination of HLA class I/II variants and peptides from the self. Therefore, the capacity of given HLA class I/II variants to bind pathogen-derived peptides is only one part of the selective process to generate effective immune responses. We thus propose that peptidome variation contributes to shaping T cell receptor (TCR) repertoires and hence individual immune responses, and that this variation represents inherent modulator epitopes.

TCR repertoires emerge in the thymus in each individual as T cells undergo positive and negative selection.

T cell education is controlled by the combination of HLA class I/II molecules and their peptide pools (peptidome).

HLA class I/II molecules are highly plastic in human populations but the peptidome is also a source of variation. Hence combined diversity of HLA class I/II molecules and of self-peptides shapes individual immune responses.

Self-peptide variants that affect T cell repertoires represent inherent modulator epitopes.

Genomewide Association Study of Severe Covid-19 with Respiratory Failure

BACKGROUND

There is considerable variation in disease behavior among patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (Covid-19). Genomewide association analysis may allow for the identification of potential genetic factors involved in the development of Covid-19.

METHODS

We conducted a genomewide association study involving 1980 patients with Covid-19 and severe disease (defined as respiratory failure) at seven hospitals in the Italian and Spanish epicenters of the SARS-CoV-2 pandemic in Europe. After quality control and the exclusion of population outliers, 835 patients and 1255 control participants from Italy and 775 patients and 950 control participants from Spain were included in the final analysis. In total, we analyzed 8,582,968 single-nucleotide polymorphisms and conducted a meta-analysis of the two case-control panels.

RESULTS

We detected cross-replicating associations with rs11385942 at locus 3p21.31 and with rs657152 at locus 9q34.2, which were significant at the genomewide level (P<5×10-8) in the meta-analysis of the two case-control panels (odds ratio, 1.77; 95% confidence interval [CI], 1.48 to 2.11; P = 1.15×10-10; and odds ratio, 1.32; 95% CI, 1.20 to 1.47; P = 4.95×10-8, respectively). At locus 3p21.31, the association signal spanned the genes SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6 and XCR1. The association signal at locus 9q34.2 coincided with the ABO blood group locus; in this cohort, a blood-group-specific analysis showed a higher risk in blood group A than in other blood groups (odds ratio, 1.45; 95% CI, 1.20 to 1.75; P = 1.48×10-4) and a protective effect in blood group O as compared with other blood groups (odds ratio, 0.65; 95% CI, 0.53 to 0.79; P = 1.06×10-5).

CONCLUSIONS

We identified a 3p21.31 gene cluster as a genetic susceptibility locus in patients with Covid-19 with respiratory failure and confirmed a potential involvement of the ABO blood-group system. (Funded by Stein Erik Hagen and others.).

Role of CD4+ T Cells in Allergic Airway Diseases: Learning from Murine Models

The essential contribution of CD4⁺ T cells in allergic airway diseases has been demonstrated, especially by using various murine models of antigen-induced airway inflammation. In addition to antigen-immunized mouse models employing mast cell-deficient mice and CD4⁺ T cell-depleting procedure, antigen-specific CD4⁺ T cell transfer models have revealed the possible development of allergic inflammation solely dependent on CD4⁺ T cells. Regardless of the classical Th1/Th2 theory, various helper T cell subsets have the potential to induce different types of allergic inflammation. T cell receptor (TCR)-transgenic (Tg) mice have been used for investigating T cell-mediated immune responses. Besides, we have recently generated cloned mice from antigen-specific CD4⁺ T cells through somatic cell nuclear transfer. In contrast to TCR-Tg mice that express artificially introduced TCR, the cloned mice express endogenously regulated antigen-specific TCR. Upon antigen exposure, the mite antigen-reactive T cell-cloned mice displayed strong airway inflammation accompanied by bronchial hyperresponsiveness in a short time period. Antigen-specific CD4⁺ T cell-cloned mice are expected to be useful for investigating the detailed role of CD4⁺ T cells in various allergic diseases and for evaluating novel anti-allergic drugs.

[Individualized immunotherapy for malignant tumors using peptide vaccines-maybe it does work after all?]

Bereits der Arzt und Forscher Paul Ehrlich stellte die These auf, dass das Immunsystem nicht nur Infektionen bekämpft, sondern auch gegen Krebs vorgehen kann. Über die möglichen positiven Auswirkungen einer simultanen Infektion auf den Verlauf einer Krebserkrankung wurde bereits im alten Ägypten ca. 2600 v. Chr. berichtet. Jedoch wurde erst ab den 1960er-Jahren klar, dass das Immunsystem Krebszellen gezielt bekämpfen kann, und erst ab den 1990er-Jahren wurde langsam aufgeklärt, wie dies vor sich geht.

Vor diesem Hintergrund sollen deshalb die Bemühungen der letzten 30 Jahre hinsichtlich der Entwicklung therapeutischer Impfungen gegen Krebserkrankungen kurz zusammengefasst und deren bisherige Erfolglosigkeit beleuchtet werden. Außerdem werden in einem Ausblick zukünftige eventuell Erfolg versprechende Entwicklungen in diesem Kontext diskutiert. Dabei werden die verfügbare wissenschaftliche Literatur, aber auch eigene Ergebnisse berücksichtigt.

Es ergeben sich ganz zentrale Fragen, etwa: Wie unterscheiden sich Krebszellen von normalen Zellen? Wie kann das Immunsystem diese Unterschiede erkennen? Was sind tumorspezifische Antigene? Warum müssen tumorspezifische Antigene in individueller Weise ausgesucht und angewendet werden? Wie induziert man eine effiziente Immunantwort? Welche pharmazeutischen Formulierungen, Adjuvanzien und Impfrouten sind effektiv?

Letztlich stellen wir dar, warum es sich möglicherweise doch lohnt, die bisher völlig erfolglose Peptidimpfung (gemessen an bisher zugelassenen Therapeutika) weiterzuverfolgen.

Selective Stimulation of Duplicated Atlantic Salmon MHC Pathway Genes by Interferon-Gamma

Induction of cellular immune responses rely on Major histocompatibility complex (MHC) molecules presenting pathogenic peptides to T cells. Peptide processing, transport, loading and editing is a constitutive process in most cell types, but is accelerated upon infection. Recently, an unexpected complexity in the number of functional genes involved in MHC class I peptide cleavage, peptide transport, peptide loading and editing was found in teleosts, originating from the second and third whole genome duplication events. Salmonids have expanded upon this with functional duplicates also from a fourth unique salmonid whole genome duplication. However, little is known about how individual gene duplicates respond in the context of stimulation. Here we set out to investigate how interferon gamma (IFNg) regulates the transcription of immune genes in Atlantic salmon with particular focus on gene duplicates and MHC pathways. We identified a range of response patterns in Atlantic salmon gene duplicates, with upregulation of all duplicates for some genes, like interferon regulatory factor 1 (IRF1) and interferon induced protein 44-like (IFI44.L), but only induction of one or a few duplicates of other genes, such as TAPBP and ERAP2. A master regulator turned out to be the IRF1 and not the enhanceosome as seen in mammals. If IRF1 also collaborates with CIITA and possibly NLRC5 in regulating IFNg induction of MHCI and MHCII expression in Atlantic salmon, as in zebrafish, remains to be established. Altogether, our results show the importance of deciphering between gene duplicates, as they often respond very differently to stimulation and may have different biological functions.

Variation of HLA class I (-A and -C) genes in individuals infected with hepatitis B or hepatitis C virus in Cameroon

The Human Leucocyte Antigens (HLA) work in concert with other immune factors to modulate immunity to viral infections. Extensive variation has been reported in the genetic sequences and functions of classical HLA class I genes in many (mostly Western) populations, and several HLA associations with infectious disease outcomes have been reported. Little is known about their role in the susceptibility or resistance to hepatitis viruses in Central African populations. The aim of this study was to determine variants of two HLA class I genes (HLA-A and -C) in adults infected with hepatitis B (HBV)- or -C (HCV) virus in Cameroon. In this case-control study, a total of 169 unrelated adults comprising 68 HCV-infected, 38 HBV-infected and 63 uninfected (controls) individuals participated. Each consented participant was screened for HBV, HCV, and HIV infections and willingly donated a single blood sample for genomic DNA isolation and some clinical laboratory tests. HLA-A and HLA-C were genotyped using previously described sequence-based techniques (SBT). A total of 54 HLA alleles were identified in the study population (27 HLA-A and 27 HLA-C). HLA-A∗23:01 and HLA-C∗07:01 were the most common alleles with genotype frequencies of 31.4% and 29.3%, respectively. Hepatitis individuals were six times more likely to be HLA-A∗30:01 carriers than uninfected controls (OR = 6.30, p = 0.020 (HBV); OR = 6.21, p = 0.010 (HCV), respectively). Similarly, carriers of HLA-C∗17:01 were over-represented in the HBV-infected compared to the uninfected control group (21.9% vs. 6.4%, respectively) suggesting that this allele could play a role in the susceptibility to HBV infection. These findings demonstrate that carriers of HLA-A∗30:01 were over-represented in the hepatitis group compared to uninfected controls while HLA-C∗17:01 was completely absent in the HCV + group.

Current status and future perspectives of HLA-edited induced pluripotent stem cells

In 2007, Human-induced pluripotent stem cells (iPSCs) were generated by transducing four genes (Oct3/4, Sox2, Klf4, c-Myc). Because iPSCs can differentiate into any types of cells in the body and have fewer ethical issues compared to embryonic stem (ES) cells, application of iPSCs for regenerative medicine has been actively examined. In fact, iPSCs have already been used for clinical applications, but at present, only autologous iPSC-derived grafts or HLA homozygous iPSC-derived grafts are being transplanted into patients following HLA matching. HLA is an important molecule that enables the immune system differentiates between self and non-self-components; thus, HLA mismatch is a major hurdle in the transplantation of iPSCs. To deliver inexpensive off-the-shelf iPSC-derived regenerative medicine products to more patients, it is necessary to generate universal iPSCs that can be transplanted regardless of the HLA haplotypes. The current strategy to generate universal iPSCs has two broad aims: deleting HLA expression and avoiding attacks from NK cells, which are caused by HLA deletion. Deletion of B2M and CIITA genes using the CRISPR/Cas9 system has been reported to suppress the expression of HLA class I and class II, respectively. Transduction of NK inhibitory ligands, such as HLA-E and CD47, has been used to avoid NK cell attacks. Most recently, the HLA-C retaining method has been used to generate semi-universal iPSCs. Twelve haplotypes of HLA-C retaining iPSCs can cover 95% of the global population. In future, studying which types of universal iPSCs are most effective for engraftment in various physiological conditions is necessary.

Variations in MHC class I antigen presentation and immunopeptidome selection pathways

Major histocompatibility class I (MHC-I) proteins mediate immunosurveillance against pathogens and cancers by presenting antigenic or mutated peptides to antigen receptors of CD8+ T cells and by engaging receptors of natural killer (NK) cells. In humans, MHC-I molecules are highly polymorphic. MHC-I variations permit the display of thousands of distinct peptides at the cell surface. Recent mass spectrometric studies have revealed unique and shared characteristics of the peptidomes of individual MHC-I variants. The cell surface expression of MHC-I–peptide complexes requires the functions of many intracellular assembly factors, including the transporter associated with antigen presentation (TAP), tapasin, calreticulin, ERp57, TAP-binding protein related (TAPBPR), endoplasmic reticulum aminopeptidases (ERAPs), and the proteasomes. Recent studies provide important insights into the structural features of these factors that govern MHC-I assembly as well as the mechanisms underlying peptide exchange. Conformational sensing of MHC-I molecules mediates the quality control of intracellular MHC-I assembly and contributes to immune recognition by CD8 at the cell surface. Recent studies also show that several MHC-I variants can follow unconventional assembly routes to the cell surface, conferring selective immune advantages that can be exploited for immunotherapy.

The shared frameshift mutation landscape of microsatellite-unstable cancers suggests immunoediting during tumor evolution

The immune system can recognize and attack cancer cells, especially those with a high load of mutation-induced neoantigens. Such neoantigens are abundant in DNA mismatch repair (MMR)-deficient, microsatellite-unstable (MSI) cancers. MMR deficiency leads to insertion/deletion (indel) mutations at coding microsatellites (cMS) and to neoantigen-inducing translational frameshifts. Here, we develop a tool to quantify frameshift mutations in MSI colorectal and endometrial cancer. Our results show that frameshift mutation frequency is negatively correlated to the predicted immunogenicity of the resulting peptides, suggesting counterselection of cell clones with highly immunogenic frameshift peptides. This correlation is absent in tumors with Beta-2-microglobulin mutations, and HLA-A*02:01 status is related to cMS mutation patterns. Importantly, certain outlier mutations are common in MSI cancers despite being related to frameshift peptides with functionally confirmed immunogenicity, suggesting a possible driver role during MSI tumor evolution. Neoantigens resulting from shared mutations represent promising vaccine candidates for prevention of MSI cancers.

Post-copulatory genetic matchmaking: HLA-dependent effects of cervical mucus on human sperm function

Several studies have demonstrated that women show pre-copulatory mating preferences for human leucocyte antigen (HLA)-dissimilar men. A fascinating, yet unexplored, possibility is that the ultimate mating bias towards HLA-dissimilar partners could occur after copulation, at the gamete level. Here, we explored this possibility by investigating whether the selection towards HLA-dissimilar partners occurs in the cervical mucus. After combining sperm and cervical mucus from multiple males and females (full factorial design), we found that sperm performance (swimming velocity, hyperactivation, and viability) was strongly influenced by the male–female combination. This indicates that sperm fertilization capability may be dependent on the compatibility between cervical mucus (female) and sperm (male). We also found that sperm viability was associated with partners' HLA dissimilarity, indicating that cervical mucus may selectively facilitate later gamete fusion between immunogenetically compatible partners. Together, these results provide novel insights into the female-mediated sperm selection (cryptic female choice) in humans and indicate that processes occurring after copulation may contribute to the mating bias towards HLA-dissimilar partners. Finally, by showing that sperm performance in cervical mucus is influenced by partners' genetic compatibility, the present findings may promote a deeper understanding of infertility.

The complex pattern of genetic associations of leprosy with HLA class I and class II alleles can be reduced to four amino acid positions

Leprosy is a chronic disease caused by Mycobacterium leprae. Worldwide, more than 200,000 new patients are affected by leprosy annually, making it the second most common mycobacterial disease after tuberculosis. The MHC/HLA region has been consistently identified as carrying major leprosy susceptibility variants in different populations at times with inconsistent results. To establish the unambiguous molecular identity of classical HLA class I and class II leprosy susceptibility factors, we applied next-generation sequencing to genotype with high-resolution 11 HLA class I and class II genes in 1,155 individuals from a Vietnamese leprosy case-control sample. HLA alleles belonging to an extended haplotype from HLA-A to HLA-DPB1 were associated with risk to leprosy. This susceptibility signal could be reduced to the HLA-DRB1*10:01~ HLA-DQA1*01:05 alleles which were in complete linkage disequilibrium (LD). In addition, haplotypes containing HLA-DRB3~ HLA-DRB1*12:02 and HLA-C*07:06~ HLA-B*44:03~ HLA-DRB1*07:01 alleles were found as two independent protective factors for leprosy. Moreover, we replicated the previously associated HLA-DRB1*15:01 as leprosy risk factor and HLA-DRB1*04:05~HLA-DQA1*03:03 as protective alleles. When we narrowed the analysis to the single amino acid level, we found that the associations of the HLA alleles were largely captured by four independent amino acids at HLA-DRβ1 positions 57 (D) and 13 (F), HLA-B position 63 (E) and HLA-A position 19 (K). Hence, analyses at the amino acid level circumvented the ambiguity caused by strong LD of leprosy susceptibility HLA alleles and identified four distinct leprosy susceptibility factors.

Despite global efforts to eliminate leprosy over the past 25 years, more than 200,000 new cases are reported annually, and leprosy still represents a major public health problem in endemic regions. Leprosy presents a strong link with the host genetic background. The most significant susceptibility factors are located in the MHC region and likely involve classical HLA genes. However, the molecular identity of the HLA class I/II-leprosy risk factor(s) has been a matter of longstanding scientific dispute. By conducting a comprehensive sequenced-based analysis of HLA class I and class II genes, we are able to provide a unifying view of the complex relationship of leprosy susceptibility and HLA alleles. In addition, we show that four amino acid polymorphisms in HLA-DRβ1, HLA-B and HLA-A are sufficient to explain the majority of leprosy-HLA associations which opens the way for select protein-HLA peptide binding studies.

Risk factors for cutaneous reactions to allopurinol in Kinh Vietnamese: results from a case-control study

OBJECTIVE

The aim of this study was to investigate risk factors for cutaneous adverse reactions (CARs) in Kinh Vietnamese.

METHODS

All patients were prospectively recruited in Ho Chi Minh City. Presence of the HLA-B*58:01 allele was determined by real-time PCR-sequence-specific amplification by using the PG5801 Detection Kit (Pharmigene, Taipei). Patients with severe (SCARs) and mild (MCARs) CARs and controls were compared for differences in features prospectively collected, and odds ratios (ORs) with 95% confidence intervals (CIs) were estimated.

RESULTS

On comparing 32 patients with SCARs and 395 tolerant controls, we identified eight strong risk factors: increased age (OR 15.1 [95% CI 5.8-40.1], P < 0.0001), female sex (OR 333 [40-43,453], P < 0.0001), allopurinol for asymptomatic hyperuricemia (OR 955 [120-125,847], P < 0.0001), allopurinol starting dose > 150 mg (OR 316 [101-122], P < 0.0001), diuretics intake (OR 304 [35-40,018], P < 0.0001), eGFR < 60 ml/min/1.73 m² (OR 100 [32-353], P < 0.0001), history of allopurinol-induced skin reaction (OR 78 [6-10,808], P = 0.004), and HLA-B*58:01 carriage (OR 147 [45-746], P < 0.0001). HLA-B*58:01 allele frequency in controls was 7.3%. For MCARs (n = 74), risk factors were eGFR < 60 ml/min/1.73 m² (OR 4.9 [1.61-14.6], P = 0.006), history of allopurinol-induced skin reaction (OR 27 [2-3777], P = 0.01), and asymptomatic hyperuricemia (OR 27 [2-3777], P = 0.01).

CONCLUSION

This study confirmed 8 risk factors, including HLA-B*58:01, for SCARs and identified 3 risk factors for MCARs in Kinh Vietnamese. HLA-B*58:01 genotyping could guide the indication for allopurinol in Kinh Vietnamese patients with gout.

Immunogenic SARS-CoV-2 Epitopes: In Silico Study Towards Better Understanding of COVID-19 Disease-Paving the Way for Vaccine Development

The emergence of the COVID-19 outbreak at the end of 2019, caused by the novel coronavirus SARS-CoV-2, has, to date, led to over 13.6 million infections and nearly 600,000 deaths. Consequently, there is an urgent need to better understand the molecular factors triggering immune defense against the virus and to develop countermeasures to hinder its spread. Using in silico analyses, we showed that human major histocompatibility complex (MHC) class I cell-surface molecules vary in their capacity for binding different SARS-CoV-2-derived epitopes, i.e., short sequences of 8-11 amino acids, and pinpointed five specific SARS-CoV-2 epitopes that are likely to be presented to cytotoxic T-cells and hence activate immune responses. The identified epitopes, each one of nine amino acids, have high sequence similarity to the equivalent epitopes of SARS-CoV virus, which are known to elicit an effective T cell response in vitro. Moreover, we give a structural explanation for the binding of SARS-CoV-2-epitopes to MHC molecules. Our data can help us to better understand the differences in outcomes of COVID-19 patients and may aid the development of vaccines against SARS-CoV-2 and possible future outbreaks of novel coronaviruses.

Large-Scale Structure-Based Prediction of Stable Peptide Binding to Class I HLAs Using Random Forests

Prediction of stable peptide binding to Class I HLAs is an important component for designing immunotherapies. While the best performing predictors are based on machine learning algorithms trained on peptide-HLA (pHLA) sequences, the use of structure for training predictors deserves further exploration. Given enough pHLA structures, a predictor based on the residue-residue interactions found in these structures has the potential to generalize for alleles with little or no experimental data. We have previously developed APE-Gen, a modeling approach able to produce pHLA structures in a scalable manner. In this work we use APE-Gen to model over 150,000 pHLA structures, the largest dataset of its kind, which were used to train a structure-based pan-allele model. We extract simple, homogenous features based on residue-residue distances between peptide and HLA, and build a random forest model for predicting stable pHLA binding. Our model achieves competitive AUROC values on leave-one-allele-out validation tests using significantly less data when compared to popular sequence-based methods. Additionally, our model offers an interpretation analysis that can reveal how the model composes the features to arrive at any given prediction. This interpretation analysis can be used to check if the model is in line with chemical intuition, and we showcase particular examples. Our work is a significant step toward using structure to achieve generalizable and more interpretable prediction for stable pHLA binding.

Investigations of sequencing data and sample type on HLA class Ia typing with different computational tools

Human leukocyte antigen (HLA) can encode the human major histocompatibility complex (MHC) proteins and play a key role in adaptive and innate immunity. Emerging clinical evidences suggest that the presentation of tumor neoantigens and neoantigen-specific T cell response associated with MHC class I molecules are of key importance to activate the adaptive immune systemin cancer immunotherapy. Therefore, accurate HLA typing is very essential for the clinical application of immunotherapy. In this study, we conducted performance evaluations of 4 widely used HLA typing tools (OptiType, Phlat, Polysolver and seq2hla) for predicting HLA class Ia genes from WES and RNA-seq data of 28 cancer patients. HLA genotyping data using PCR-SBT method was firstly obtained as the golden standard and was subsequently compared with HLA typing data by using NGS techniques. For both WES data and RNA-seq data, OptiType showed the highest accuracy for HLA-Ia typing than the other 3 programs at 2-digit and 4-digit resolution. Additionally, HLA typing accuracy from WES data was higher than from RNA-seq data (99.11% for WES data versus 96.42% for RNA-seq data). The accuracy of HLA-Ia typing by OptiType can reach 100% with the average depth of HLA gene regions >20x. Besides, the accuracy of 2-digit and 4-digit HLA-Ia typing based on control samples was higher than tumor tissues. In conclusion, OptiType by using WES data from control samples with the high average depth (>20x) of HLA gene regions can present a probably superior performance for HLA-Ia typing, enabling its application in cancer immunotherapy.

Convergent Evolution of HLA-C Downmodulation in HIV-1 and HIV-2

HLA-C-mediated antigen presentation induces the killing of human immunodeficiency virus (HIV)-infected CD4+ T cells by cytotoxic T lymphocytes (CTLs). To evade killing, many HIV-1 group M strains decrease HLA-C surface levels using their accessory protein Vpu. However, some HIV-1 group M isolates lack this activity, possibly to prevent the activation of natural killer (NK) cells. Analyzing diverse primate lentiviruses, we found that Vpu-mediated HLA-C downregulation is not limited to pandemic group M but is also found in HIV-1 groups O and P as well as several simian immunodeficiency viruses (SIVs). We show that Vpu targets HLA-C primarily at the protein level, independently of its ability to suppress NF-κB-driven gene expression, and that in some viral lineages, HLA-C downregulation may come at the cost of efficient counteraction of the restriction factor tetherin. Remarkably, HIV-2, which does not carry a vpu gene, uses its accessory protein Vif to decrease HLA-C surface expression. This Vif activity requires intact binding sites for the Cullin5/Elongin ubiquitin ligase complex but is separable from its ability to counteract APOBEC3G. Similar to HIV-1 Vpu, the degree of HIV-2 Vif-mediated HLA-C downregulation varies considerably among different virus isolates. In agreement with opposing selection pressures in vivo, we show that the reduction of HLA-C surface levels by HIV-2 Vif is accompanied by increased NK cell-mediated killing. In summary, our results highlight the complex role of HLA-C in lentiviral infections and demonstrate that HIV-1 and HIV-2 have evolved at least two independent mechanisms to decrease HLA-C levels on infected cells.IMPORTANCE Genome-wide association studies suggest that HLA-C expression is a major determinant of viral load set points and CD4+ T cell counts in HIV-infected individuals. On the one hand, efficient HLA-C expression enables the killing of infected cells by cytotoxic T lymphocytes (CTLs). On the other hand, HLA-C sends inhibitory signals to natural killer (NK) cells and enhances the infectivity of newly produced HIV particles. HIV-1 group M viruses modulate HLA-C expression using the accessory protein Vpu, possibly to balance CTL- and NK cell-mediated immune responses. Here, we show that the second human immunodeficiency virus, HIV-2, can use its accessory protein Vif to evade HLA-C-mediated restriction. Furthermore, our mutational analyses provide insights into the underlying molecular mechanisms. In summary, our results reveal how the two human AIDS viruses modulate HLA-C, a key component of the antiviral immune response.

SOAPTyping: an open-source and cross-platform tool for sequence-based typing for HLA class I and II alleles

Background

The human leukocyte antigen (HLA) gene family plays a key role in the immune response and thus is crucial in many biomedical and clinical settings. Utilizing Sanger sequencing, the golden standard technology for HLA typing enables accurate identification of HLA alleles in high-resolution. However, only the commercial software, such as uTYPE, SBT-Assign, and SBTEngine, and very few open-source tools could be applied to perform HLA typing based on Sanger sequencing.

Results

We developed a user-friendly, cross-platform and open-source desktop application, known as SOAPTyping, for Sanger-based typing in HLA class I and II alleles. SOAPTyping can produce accurate results with a comprehensible protocol and featured functions. Moreover, SOAPTyping supports a more advanced group-specific sequencing primers (GSSP) module to solve the ambiguous typing results. We used SOAPTyping to analyze 36 samples with known HLA typing from the University of California Los Angeles (UCLA) International HLA DNA Exchange platform and 100 anonymous clinical samples, and the HLA typing results from SOAPTyping are identical to the golden results and 5.5 times faster than commercial software uTYPE, which shows the usability of SOAPTyping.

Conclusions

We introduce the SOAPTyping as the first open-source and cross-platform HLA typing software with the capability of producing high-resolution HLA typing predictions from Sanger sequence data.

HLA Evolutionary Divergence as a Prognostic Marker for AML Patients Undergoing Allogeneic Stem Cell Transplantation

The diversity of human leukocyte antigens (HLAs) enables the presentation of immense repertoires of peptides, including tumor-associated antigens (TAAs). As a surrogate for immunopeptidome diversity, the HLA evolutionary divergence (HED) between individual HLA alleles might directly define the ability to present TAAs, a prerequisite for graft-versus-leukemia effects. We therefore analyzed the impact of HED on survival within a cohort of 171 acute myeloid leukemia (AML) patients after matched donor allogeneic hematopoietic stem cell transplantation (HSCT). Low HED (<25th percentile) of HLA class I (HED^{class I}) or HLA-DR antigens (HED^DR) was a strong determinant for adverse overall survival after allogeneic HSCT (OS), with a hazard ratio for death of 1.9 (95% CI 1.2–3.2) and 2.1 (95% CI 1.3–3.4), respectively. Defining a cutoff value for the combined HED^total (HED^{class I} and HED^DR), the respective 5 year OS was 29.7% and 64.9% in patients with low and high HED^total (p < 0.001), respectively. Furthermore, the risk of relapse was significantly higher in patients with low HED^total (hazard ratio (HR) 2.2, 95% CI 1.3–3.6) and event-free survival (EFS) was significantly reduced (5 year EFS 25.7% versus 54.4%, p < 0.001). We here introduce HED, a fundamental metric of immunopeptidome diversity, as a novel prognostic factor for AML patients undergoing allogeneic HSCT.

Uncovering the Tumor Antigen Landscape: What to Know about the Discovery Process

According to the latest available data, cancer is the second leading cause of death, highlighting the need for novel cancer therapeutic approaches. In this context, immunotherapy is emerging as a reliable first-line treatment for many cancers, particularly metastatic melanoma. Indeed, cancer immunotherapy has attracted great interest following the recent clinical approval of antibodies targeting immune checkpoint molecules, such as PD-1, PD-L1, and CTLA-4, that release the brakes of the immune system, thus reviving a field otherwise poorly explored. Cancer immunotherapy mainly relies on the generation and stimulation of cytotoxic CD8 T lymphocytes (CTLs) within the tumor microenvironment (TME), priming T cells and establishing efficient and durable anti-tumor immunity. Therefore, there is a clear need to define and identify immunogenic T cell epitopes to use in therapeutic cancer vaccines. Naturally presented antigens in the human leucocyte antigen-1 (HLA-I) complex on the tumor surface are the main protagonists in evocating a specific anti-tumor CD8+ T cell response. However, the methodologies for their identification have been a major bottleneck for their reliable characterization. Consequently, the field of antigen discovery has yet to improve. The current review is intended to define what are today known as tumor antigens, with a main focus on CTL antigenic peptides. We also review the techniques developed and employed to date for antigen discovery, exploring both the direct elution of HLA-I peptides and the in silico prediction of epitopes. Finally, the last part of the review analyses the future challenges and direction of the antigen discovery field.

Binding affinities of 438 HLA proteins to complete proteomes of seven pandemic viruses and distributions of strongest and weakest HLA peptide binders in populations worldwide

We report detailed peptide‐binding affinities between 438 HLA Class I and Class II proteins and complete proteomes of seven pandemic human viruses, including coronaviruses, influenza viruses and HIV‐1. We contrast these affinities with HLA allele frequencies across hundreds of human populations worldwide. Statistical modelling shows that peptide‐binding affinities classified into four distinct categories depend on the HLA locus but that the type of virus is only a weak predictor, except in the case of HIV‐1. Among the strong HLA binders (IC₅₀ ≤ 50), we uncovered 16 alleles (the top ones being A*02:02, B*15:03 and DRB1*01:02) binding more than 1% of peptides derived from all viruses, 9 (top ones including HLA‐A*68:01, B*15:25, C*03:02 and DRB1*07:01) binding all viruses except HIV‐1, and 15 (top ones A*02:01 and C*14:02) only binding coronaviruses. The frequencies of strongest and weakest HLA peptide binders differ significantly among populations from different geographic regions. In particular, Indigenous peoples of America show both higher frequencies of strongest and lower frequencies of weakest HLA binders. As many HLA proteins are found to be strong binders of peptides derived from distinct viral families, and are hence promiscuous (or generalist), we discuss this result in relation to possible signatures of natural selection on HLA promiscuous alleles due to past pathogenic infections. Our findings are highly relevant for both evolutionary genetics and the development of vaccine therapies. However they should not lead to forget that individual resistance and vulnerability to diseases go beyond the sole HLA allelic affinity and depend on multiple, complex and often unknown biological, environmental and other variables.

HLA Class II Specificity Assessed by High-Density Peptide Microarray Interactions

The ability to predict and/or identify MHC binding peptides is an essential component of T cell epitope discovery, something that ultimately should benefit the development of vaccines and immunotherapies. In particular, MHC class I prediction tools have matured to a point where accurate selection of optimal peptide epitopes is possible for virtually all MHC class I allotypes; in comparison, current MHC class II (MHC-II) predictors are less mature. Because MHC-II restricted CD4⁺ T cells control and orchestrated most immune responses, this shortcoming severely hampers the development of effective immunotherapies. The ability to generate large panels of peptides and subsequently large bodies of peptide-MHC-II interaction data are key to the solution of this problem, a solution that also will support the improvement of bioinformatics predictors, which critically relies on the availability of large amounts of accurate, diverse, and representative data. In this study, we have used rHLA-DRB1*01:01 and HLA-DRB1*03:01 molecules to interrogate high-density peptide arrays, in casu containing 70,000 random peptides in triplicates. We demonstrate that the binding data acquired contains systematic and interpretable information reflecting the specificity of the HLA-DR molecules investigated, suitable of training predictors able to predict T cell epitopes and peptides eluted from human EBV-transformed B cells. Collectively, with a cost per peptide reduced to a few cents, combined with the flexibility of rHLA technology, this poses an attractive strategy to generate vast bodies of MHC-II binding data at an unprecedented speed and for the benefit of generating peptide-MHC-II binding data as well as improving MHC-II prediction tools.

Increasing accuracy of HLA imputation by a population-specific reference panel in a FinnGen biobank cohort

The HLA genes, the most polymorphic genes in the human genome, constitute the strongest single genetic susceptibility factor for autoimmune diseases, transplantation alloimmunity and infections. HLA imputation via statistical inference of alleles based on single-nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with alleles is a powerful first-step screening tool. Due to different LD structures between populations, the accuracy of HLA imputation may benefit from matching the imputation reference with the study population. To evaluate the potential advantage of using population-specific reference in HLA imputation, we constructed an HLA reference panel consisting of 1150 Finns with 5365 major histocompatibility complex region SNPs consistent between genome builds. We evaluated the accuracy of the panel against a European panel in an independent test set of 213 Finnish subjects. We show that the Finnish panel yields a lower imputation error rate (1.24% versus 1.79%). More than 30% of imputation errors occurred in haplotypes enriched in Finland. The frequencies of imputed HLA alleles were highly correlated with clinical-grade HLA allele frequencies and allowed accurate replication of established HLA–disease associations in ∼102 000 biobank participants. The results show that a population-specific reference increases imputation accuracy in a relatively isolated population within Europe and can be successfully applied to biobank-scale genome data collections.

MHC Class I Regulation: The Origin Perspective

Viral-derived elements and non-coding RNAs that build up “junk DNA” allow for flexible and context-dependent gene expression. They are extremely dense in the MHC region, accounting for flexible expression of the MHC I, II, and III genes and adjusting the level of immune response to the environmental stimuli. This review brings forward the viral-mediated aspects of the origin and evolution of adaptive immunity and aims to link this perspective with the MHC class I regulation. The complex regulatory network behind MHC expression is largely controlled by virus-derived elements, both as binding sites for immune transcription factors and as sources of regulatory non-coding RNAs. These regulatory RNAs are imbalanced in cancer and associate with different tumor types, making them promising targets for diagnostic and therapeutic interventions.

Expected immune recognition of COVID-19 virus by memory from earlier infections with common coronaviruses in a large part of the world population

SARS-CoV-2 is the coronavirus agent of the COVID-19 pandemic causing high mortalities. In contrast, the widely spread human coronaviruses OC43, HKU1, 229E, and NL63 tend to cause only mild symptoms. The present study shows, by in silico analysis, that these common human viruses are expected to induce immune memory against SARS-CoV-2 by sharing protein fragments (antigen epitopes) for presentation to the immune system by MHC class I. A list of such epitopes is provided. The number of these epitopes and the prevalence of the common coronaviruses suggest that a large part of the world population has some degree of specific immunity against SARS-CoV-2 already, even without having been infected by that virus. For inducing protection, booster vaccinations enhancing existing immunity are less demanding than primary vaccinations against new antigens. Therefore, for the discussion on vaccination strategies against COVID-19, the available immune memory against related viruses should be part of the consideration.

Expected immune recognition of COVID-19 virus by memory from earlier infections with common coronaviruses in a large part of the world population

SARS-CoV-2 is the coronavirus agent of the COVID-19 pandemic causing high mortalities. In contrast, the widely spread human coronaviruses OC43, HKU1, 229E, and NL63 tend to cause only mild symptoms. The present study shows, by in silico analysis, that these common human viruses are expected to induce immune memory against SARS-CoV-2 by sharing protein fragments (antigen epitopes) for presentation to the immune system by MHC class I. A list of such epitopes is provided. The number of these epitopes and the prevalence of the common coronaviruses suggest that a large part of the world population has some degree of specific immunity against SARS-CoV-2 already, even without having been infected by that virus. For inducing protection, booster vaccinations enhancing existing immunity are less demanding than primary vaccinations against new antigens. Therefore, for the discussion on vaccination strategies against COVID-19, the available immune memory against related viruses should be part of the consideration.

Genome-wide Association Study Identifies HLA-DPB1 as a Significant Risk Factor for Severe Aplastic Anemia

Severe aplastic anemia (SAA) is a rare disorder characterized by hypoplastic bone marrow and progressive pancytopenia. The etiology of acquired SAA is not understood but is likely related to abnormal immune responses and environmental exposures. We conducted a genome-wide association study of individuals with SAA genetically matched to healthy controls in discovery (359 cases, 1,396 controls) and validation sets (175 cases, 1,059 controls). Combined analyses identified linked SNPs in distinct blocks within the major histocompatibility complex on 6p21. The top SNP encodes p.Met76Val in the P4 binding pocket of the HLA class II gene HLA-DPB1 (rs1042151A>G, odds ratio [OR] 1.75, 95% confidence interval [CI] 1.50-2.03, p = 1.94 × 10-13) and was associated with HLA-DP cell surface expression in healthy individuals (p = 2.04 × 10-6). Phylogenetic analyses indicate that Val76 is not monophyletic and likely occurs in conjunction with different HLA-DP binding groove conformations. Imputation of HLA-DPB1 alleles revealed increased risk of SAA associated with Val76-encoding alleles DPB1∗03:01, (OR 1.66, p = 1.52 × 10-7), DPB1∗10:01 (OR 2.12, p = 0.0003), and DPB1∗01:01 (OR 1.60, p = 0.0008). A second SNP near HLA-B, rs28367832G>A, reached genome-wide significance (OR 1.49, 95% CI 1.22-1.78, p = 7.27 × 10-9) in combined analyses; the association remained significant after excluding cases with clonal copy-neutral loss-of-heterozygosity affecting class I HLA genes (8.6% of cases and 0% of controls). SNPs in the HLA class II gene HLA-DPB1 and possibly class I (HLA-B) are associated with SAA. The replacement of Met76 to Val76 in certain HLA-DPB1 alleles might influence risk of SAA through mechanisms involving DP peptide binding specificity, expression, and/or other factors affecting DP function.

The 27th annual Nucleic Acids Research database issue and molecular biology database collection

The 2020 Nucleic Acids Research Database Issue contains 148 papers spanning molecular biology. They include 59 papers reporting on new databases and 79 covering recent changes to resources previously published in the issue. A further ten papers are updates on databases most recently published elsewhere. This issue contains three breakthrough articles: AntiBodies Chemically Defined (ABCD) curates antibody sequences and their cognate antigens; SCOP returns with a new schema and breaks away from a purely hierarchical structure; while the new Alliance of Genome Resources brings together a number of Model Organism databases to pool knowledge and tools. Major returning nucleic acid databases include miRDB and miRTarBase. Databases for protein sequence analysis include CDD, DisProt and ELM, alongside no fewer than four newcomers covering proteins involved in liquid-liquid phase separation. In metabolism and signaling, Pathway Commons, Reactome and Metabolights all contribute papers. PATRIC and MicroScope update in microbial genomes while human and model organism genomics resources include Ensembl, Ensembl genomes and UCSC Genome Browser. Immune-related proteins are covered by updates from IPD-IMGT/HLA and AFND, as well as newcomers VDJbase and OGRDB. Drug design is catered for by updates from the IUPHAR/BPS Guide to Pharmacology and the Therapeutic Target Database. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been revised, updating 305 entries, adding 65 new resources and eliminating 125 discontinued URLs; so bringing the current total to 1637 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.