External validation of models for KIR2DS1/KIR3DL1-informed selection of hematopoietic cell donors fails.

Several studies suggest that harnessing natural killer (NK) cell reactivity mediated through killer cell immunoglobulin-like receptors (KIRs) could reduce the risk of relapse after allogeneic hematopoietic cell transplantation. Based on one promising model, information on KIR2DS1 and KIR3DL1 and their cognate ligands can be used to classify donors as KIR-advantageous or KIR-disadvantageous. This study was aimed at externally validating this model in unrelated donor hematopoietic cell transplantation. The impact of the predictor on overall survival (OS) and relapse incidence was tested in a Cox regression model adjusted for patient age, a modified disease risk index, Karnofsky performance status, donor age, HLA match, sex match, cytomegalovirus match, conditioning intensity, type of T-cell depletion, and graft type. Data from 2222 patients with acute myeloid leukemia or myelodysplastic syndrome were analyzed. KIR genes were typed by using high-resolution amplicon-based next-generation sequencing. In univariable analyses and subgroup analyses, OS and the cumulative incidence of relapse of patients with a KIR-advantageous donor were comparable to patients with a KIR-disadvantageous donor. The adjusted hazard ratio from the multivariable Cox regression model was 0.99 (Wald test, P = .93) for OS and 1.04 (Wald test, P = .78) for relapse incidence. We also tested the impact of activating donor KIR2DS1 and inhibition by KIR3DL1 separately but found no significant impact on OS and the risk of relapse. Thus, our study shows that the proposed model does not universally predict NK-mediated disease control. Deeper knowledge of NK-mediated alloreactivity is necessary to predict its contribution to graft-versus-leukemia reactions and to eventually use KIR genotype information for donor selection.

High-throughput Interpretation of Killer-cell Immunoglobulin-like Receptor Short-read Sequencing Data with PING.

The killer-cell immunoglobulin-like receptor (KIR) complex on chromosome 19 encodes receptors that modulate the activity of natural killer cells, and variation in these genes has been linked to infectious and autoimmune disease, as well as having bearing on pregnancy and transplant outcomes. The medical relevance and high variability of KIR genes makes short-read sequencing an attractive technology for interrogating the region, providing a high-throughput, high-fidelity sequencing method that is cost-effective. However, because this gene complex is characterized by extensive nucleotide polymorphism, structural variation including gene fusions and deletions, and a high level of homology between genes, its interrogation at high resolution has been thwarted by bioinformatic challenges, with most studies limited to examining presence or absence of specific genes. Here, we present the PING (Pushing Immunogenetics to the Next Generation) pipeline, which incorporates empirical data, novel alignment strategies and a custom alignment processing workflow to enable high-throughput KIR sequence analysis from short-read data. PING provides KIR gene copy number classification functionality for all KIR genes through use of a comprehensive alignment reference. The gene copy number determined per individual enables an innovative genotype determination workflow using genotype-matched references. Together, these methods address the challenges imposed by the structural complexity and overall homology of the KIR complex. To determine copy number and genotype determination accuracy, we applied PING to European and African validation cohorts and a synthetic dataset. PING demonstrated exceptional copy number determination performance across all datasets and robust genotype determination performance. Finally, an investigation into discordant genotypes for the synthetic dataset provides insight into misaligned reads, advancing our understanding in interpretation of short-read sequencing data in complex genomic regions. PING promises to support a new era of studies of KIR polymorphism, delivering high-resolution KIR genotypes that are highly accurate, enabling high-quality, high-throughput KIR genotyping for disease and population studies.

Noninvasive Determination of CMV Serostatus From Dried Buccal Swab Samples: Assay Development, Validation, and Application to 1.2 Million Samples.

BACKGROUND: Buccal swab sampling constitutes an attractive noninvasive alternative to blood drawings for antibody serostatus assays. Here we describe a method to determine the cytomegalovirus immunoglobulin G (CMV IgG) serostatus from dried buccal swab samples. METHODS: Upon solubilization, CMV IgG is determined by an ELISA assay specifically adapted to cope with low IgG concentrations. The derived CMV titer is normalized against the total protein concentration to adjust for incorrectly or less efficiently sampled buccal swabs. Assay parameters were optimized on a set of 713 samples. RESULTS: Validation with 1784 samples revealed distinct results for > 80% of samples with 98.6% specificity and 99.1% sensitivity. Based on the analysis of 1.2 million samples we derived age- and sex-stratified CMV prevalence statistics for Germany, Poland, United Kingdom, and Chile. To confirm accuracy of the assay in routine operation, the CMV status of 6518 donors was reassessed by independent laboratories based on conventional blood samples revealing 96.9% specificity and 97.4% sensitivity. CONCLUSIONS: The assay accurately delivers the CMV IgG serostatus from dried buccal swab samples for > 80% of the participants. Thereby it provides a noninvasive alternative to plasma-based CMV monitoring for nondiagnostic purposes such as hematopoietic stem cell transplantation donor screening or population studies.

DR2S: an integrated algorithm providing reference-grade haplotype sequences from heterozygous samples.

BACKGROUND: High resolution HLA genotyping of donors and recipients is a crucially important prerequisite for haematopoetic stem-cell transplantation and relies heavily on the quality and completeness of immunogenetic reference sequence databases of allelic variation. RESULTS: Here, we report on DR2S, an R package that leverages the strengths of two sequencing technologies-the accuracy of next-generation sequencing with the read length of third-generation sequencing technologies like PacBio's SMRT sequencing or ONT's nanopore sequencing-to reconstruct fully-phased high-quality full-length haplotype sequences. Although optimised for HLA and KIR genes, DR2S is applicable to all loci with known reference sequences provided that full-length sequencing data is available for analysis. In addition, DR2S integrates supporting tools for easy visualisation and quality control of the reconstructed haplotype to ensure suitability for submission to public allele databases. CONCLUSIONS: DR2S is a largely automated workflow designed to create high-quality fully-phased reference allele sequences for highly polymorphic gene regions such as HLA or KIR. It has been used by biologists to successfully characterise and submit more than 500 HLA alleles and more than 500 KIR alleles to the IPD-IMGT/HLA and IPD-KIR databases.

Multiple Knockout of Classical HLA Class II ß-Chains by CRISPR/Cas9 Genome Editing Driven by a Single Guide RNA.

Comprehensive knockout of HLA class II (HLA-II) ß-chain genes is complicated by their high polymorphism. In this study, we developed CRISPR/Cas9 genome editing to simultaneously target HLA-DRB, -DQB1, and -DPB1 through a single guide RNA recognizing a conserved region in exon 2. Abrogation of HLA-II surface expression was achieved in five different HLA-typed, human EBV-transformed B lymphoblastoid cell lines (BLCLs). Next-generation sequencing-based detection confirmed specific genomic insertion/deletion mutations with 99.5% penetrance in sorted cells for all three loci. No alterations were observed in HLA-I genes, the HLA-II peptide editor HLA-DMB, or its antagonist HLA-DOB, showing high on-target specificity. Transfection of full-length HLA-DPB1 mRNA into knockout BLCLs fully restored HLA-DP surface expression and recognition by alloreactive human CD4 T cells. The possibility to generate single HLA-II-expressing BLCLs by one-shot genome editing opens unprecedented opportunities for mechanistically dissecting the interaction of individual HLA variants with the immune system.

Estimating HLA haplotype frequencies from homozygous individuals - A Technical Report.

We estimated HLA haplotype frequencies based on individuals homozygous for 4, 5 or 6 loci. Validation of our approach using a sample of over 3.4 million German individuals was successful. Compared to an expectation-maximization algorithm, the errors were larger. However, our approach allows the unequivocal detection of rare haplotypes.

Immunogenetics in stem cell donor registry work: The DKMS example (Part 2).

DKMS is a leading stem cell donor registry with more than 9 million donors. Donor registry activities share many touch points with topics from immunogenetics or population genetics. In this two-part review article, we deal with these aspects of donor registry work by using the example of DKMS. In the second part of the review, we focus on donor typing of non-HLA genes, the impact of donor age, gender and CMV serostatus on donation probabilities, the identification of novel HLA, KIR and MIC alleles by high-throughput donor typing, the activities of the Collaborative Biobank and pharmacogenetics in the donor registry context.

Immunogenetics in stem cell donor registry work: The DKMS example (Part 1).

Currently, stem cell donor registries include more than 35 million potential donors worldwide to provide HLA-matched stem cell products for patients in need of an unrelated donor transplant. DKMS is a leading stem cell donor registry with more than 9 million donors from Germany, Poland, the United States, the United Kingdom, India and Chile. DKMS donors have donated hematopoietic stem cells more than 80,000 times. Many aspects of donor registry work are closely related to topics from immunogenetics or population genetics. In this two-part review article, we describe, analyse and discuss these areas of donor registry work by using the example of DKMS. Part 1 of the review gives a general overview on DKMS and includes typical donor registry activities with special focus on the HLA system: high-throughput HLA typing of potential stem cell donors, HLA haplotype frequencies and resulting matching probabilities, and donor file optimization with regard to HLA diversity.

Etablierung der PCR-basierten SARS-CoV-2-Testung im Hochdurchsatz.

Timely identification and isolation of affected individuals is one of the most important factors to control spreading of the newly emerged SARS-CoV-2. Consequently, it is crucial to maintain sufficient sample capacities in diagnostic laboratories. Here, we present a high-through-put approach for PCR-based SARS-CoV-2 testing. The implementation of sample pooling reduces costs and workload, especially in times with low population prevalence.

Bioinformatics Strategies, Challenges, and Opportunities for Next Generation Sequencing-Based HLA Genotyping.

The advent of next generation sequencing (NGS) has altered the face of genotyping the human leukocyte antigen (HLA) system in clinical, stem cell donor registry, and research contexts. NGS has led to a dramatically increased sequencing throughput at high accuracy, while being more time and cost efficient than precursor technologies. This has led to a broader and deeper profiling of the key genes in the human immunogenetic make-up. The rapid evolution of sequencing technologies is evidenced by the development of varied short-read sequencing platforms with differing read lengths and sequencing capacities to long-read sequencing platforms capable of profiling full genes without fragmentation. Concomitantly, there has been development of a diverse set of computational analyses and software tools developed to deal with the various strengths and limitations of the sequencing data generated by the different sequencing platforms. This review surveys the different modalities involved in generating NGS HLA profiling sequence data. It systematically describes various computational approaches that have been developed to achieve HLA genotyping to different degrees of resolution. At each stage, this review enumerates the drawbacks and advantages of each of the platforms and analysis approaches, thus providing a comprehensive picture of the current state of HLA genotyping technologies.

2.7 million samples genotyped for HLA by next generation sequencing: lessons learned.

BACKGROUND: At the DKMS Life Science Lab, Next Generation Sequencing (NGS) has been used for ultra-high-volume high-resolution genotyping of HLA loci for the last three and a half years. Here, we report on our experiences in genotyping the HLA, CCR5, ABO, RHD and KIR genes using a direct amplicon sequencing approach on Illumina MiSeq and HiSeq 2500 instruments. RESULTS: Between January 2013 and June 2016, 2,714,110 samples largely from German, Polish and UK-based potential stem cell donors have been processed. 98.9% of all alleles for the targeted HLA loci (HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1) were typed at high resolution or better. Initially a simple three-step workflow based on nanofluidic chips in conjunction with 4-primer amplicon tagging was used. Over time, we found that this setup results in PCR artefacts such as primer dimers and PCR-mediated recombination, which may necessitate repeat typing. Split workflows for low- and high-DNA-concentration samples helped alleviate these problems and reduced average per-locus repeat rates from 3.1 to 1.3%. Further optimisations of the workflow included the use of phosphorothioate oligos to reduce primer degradation and primer dimer formation, and employing statistical models to predict read yield from initial template DNA concentration to avoid intermediate quantification of PCR products. Finally, despite the populations typed at DKMS Life Science Lab being relatively homogenous genetically, an analysis of 1.4 million donors processed between January 2015 and May 2016 led to the discovery of 1,919 distinct novel HLA alleles. CONCLUSIONS: Amplicon-based NGS HLA genotyping workflows have become the workhorse in high-volume tissue typing of registry donors. The optimisation of workflow practices over multiple years has led to insights and solutions that improve the efficiency and robustness of short amplicon based genotyping workflows.

ABO allele-level frequency estimation based on population-scale genotyping by next generation sequencing.

BACKGROUND: The characterization of the ABO blood group status is vital for blood transfusion and solid organ transplantation. Several methods for the molecular characterization of the ABO gene, which encodes the alleles that give rise to the different ABO blood groups, have been described. However, the application of those methods has so far been restricted to selected samples and not been applied to population-scale analysis. RESULTS: We describe a cost-effective method for high-throughput genotyping of the ABO system by next generation sequencing. Sample specific barcodes and sequencing adaptors are introduced during PCR, rendering the products suitable for direct sequencing on Illumina MiSeq or HiSeq instruments. Complete sequence coverage of exons 6 and 7 enables molecular discrimination of the ABO subgroups and many alleles. The workflow was applied to ABO genotype more than a million samples. We report the allele group frequencies calculated on a subset of more than 110,000 sampled individuals of German origin. Further we discuss the potential of the workflow for high resolution genotyping taking the observed allele group frequencies into account. Finally, sequence analysis revealed 287 distinct so far not described alleles of which the most abundant one was identified in 174 samples. CONCLUSIONS: The described workflow delivers high resolution ABO genotyping at low cost enabling population-scale molecular ABO characterization.

Proteome-wide cellular protein concentrations of the human pathogen Leptospira interrogans.

Mass-spectrometry-based methods for relative proteome quantification have broadly affected life science research. However, important research directions, particularly those involving mathematical modelling and simulation of biological processes, also critically depend on absolutely quantitative data--that is, knowledge of the concentration of the expressed proteins as a function of cellular state. Until now, absolute protein concentration measurements of a considerable fraction of the proteome (73%) have only been derived from genetically altered Saccharomyces cerevisiae cells, a technique that is not directly portable from yeast to other species. Here we present a mass-spectrometry-based strategy to determine the absolute quantity, that is, the average number of protein copies per cell in a cell population, for a large fraction of the proteome in genetically unperturbed cells. Applying the technology to the human pathogen Leptospira interrogans, a spirochete responsible for leptospirosis, we generated an absolute protein abundance scale for 83% of the mass-spectrometry-detectable proteome, from cells at different states. Taking advantage of the unique cellular dimensions of L. interrogans, we used cryo-electron tomography morphological measurements to verify, at the single-cell level, the average absolute abundance values of selected proteins determined by mass spectrometry on a population of cells. Because the strategy is relatively fast and applicable to any cell type, we expect that it will become a cornerstone of quantitative biology and systems biology.

Cost-efficient high-throughput HLA typing by MiSeq amplicon sequencing.

BACKGROUND: A close match of the HLA alleles between donor and recipient is an important prerequisite for successful unrelated hematopoietic stem cell transplantation. To increase the chances of finding an unrelated donor, registries recruit many hundred thousands of volunteers each year. Many registries with limited resources have had to find a trade-off between cost and resolution and extent of typing for newly recruited donors in the past. Therefore, we have taken advantage of recent improvements in NGS to develop a workflow for low-cost, high-resolution HLA typing. RESULTS: We have established a straightforward three-step workflow for high-throughput HLA typing: Exons 2 and 3 of HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 are amplified by PCR on Fluidigm Access Array microfluidic chips. Illumina sequencing adapters and sample specific tags are directly incorporated during PCR. Upon pooling and cleanup, 384 samples are sequenced in a single Illumina MiSeq run. We developed "neXtype" for streamlined data analysis and HLA allele assignment. The workflow was validated with 1140 samples typed at 6 loci. All neXtype results were concordant with the Sanger sequences, demonstrating error-free typing of more than 6000 HLA loci. Current capacity in routine operation is 12,000 samples per week. CONCLUSIONS: The workflow presented proved to be a cost-efficient alternative to Sanger sequencing for high-throughput HLA typing. Despite the focus on cost efficiency, resolution exceeds the current standards of Sanger typing for donor registration.

Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer.

A key barrier to the realization of personalized medicine for cancer is the identification of biomarkers. Here we describe a two-stage strategy for the discovery of serum biomarker signatures corresponding to specific cancer-causing mutations and its application to prostate cancer (PCa) in the context of the commonly occurring phosphatase and tensin homolog (PTEN) tumor-suppressor gene inactivation. In the first stage of our approach, we identified 775 N-linked glycoproteins from sera and prostate tissue of wild-type and Pten-null mice. Using label-free quantitative proteomics, we showed that Pten inactivation leads to measurable perturbations in the murine prostate and serum glycoproteome. Following bioinformatic prioritization, in a second stage we applied targeted proteomics to detect and quantify 39 human ortholog candidate biomarkers in the sera of PCa patients and control individuals. The resulting proteomic profiles were analyzed by machine learning to build predictive regression models for tissue PTEN status and diagnosis and grading of PCa. Our approach suggests a general path to rational cancer biomarker discovery and initial validation guided by cancer genetics and based on the integration of experimental mouse models, proteomics-based technologies, and computational modeling.

Submitting Novel Full-Length HLA, MIC, and KIR Alleles with TypeLoader2.

The Immuno Polymorphism Database (IPD) plays a pivotal role for immunogenetics. Due to technical limitations, genotyping often focuses on specific key regions like the antigen recognition domain (ARD) for HLA genotyping, and the databases are populated accordingly. More recently, though, modern next generation sequencing (NGS) assays allow using larger gene segments or even complete genes for genotyping. It is therefore essential that the databases are updated with complete genetic reference sequences to fully serve current and future applications. However, the process of manually annotating and submitting full-length allele sequences to IPD is time-consuming and error-prone, which may discourage HLA-genotyping laboratories or researchers from submitting full-length sequences of novel alleles.Here, we detail the process of preparing and submitting novel HLA, MIC, and KIR alleles to ENA and IPD using TypeLoader2, a convenient software tool developed to streamline this process by automating the sequence annotation, the creation of all necessary files, as well as parts of the submission process itself. The software is freely available from GitHub ( https://github.com/DKMS-LSL/typeloader ).

Full-Length Characterization of Novel HLA-DRB1 Alleles for Reference Database Submission.

The prerequisite for successful HLA genotyping is the integrity of the large allele reference database IPD-IMGT/HLA. Consequently, it is in the laboratories' best interest that the data quality of submitted novel sequences is high. However, due to its long and variable length, the gene HLA-DRB1 presents the biggest challenge and as of today only 16% of the HLA-DRB1 alleles in the database are characterized in full length. To improve this situation, we developed a protocol for long-range PCR amplification of targeted HLA-DRB1 alleles. By subsequently combining both long-read and short-read sequencing technologies, our protocol ensures phased and error-corrected sequences of reference grade quality. This dual redundant reference sequencing (DR2S) approach is of particular importance for correctly resolving the challenging repeat regions of DRB1 intron 1. Until today, we used this protocol to characterize and submit 384 full-length HLA-DRB1 sequences to IPD-IMGT/HLA.

Polygenic polymorphism is associated with NKG2A repertoire and influences lymphocyte phenotype and function.

CD94/NKG2A is a heterodimeric receptor commonly found on NK and T cells, and interaction with its ligand HLA-E on adjacent cells leads to inhibitory signaling and cell suppression. We have identified several KLRC1 (NKG2A) single nucleotide polymorphisms (SNPs) that are associated with NKG2A expression on NK cells, CD8+ T cells, and V9/V2+ T cells. Additionally, due to strong linkage disequilibrium, polymorphisms in KLRC2 (NKG2C) and KLRK1 (NKG2D) are also associated with NKG2A surface density and frequency. NKG2A surface expression correlates with single cell NK responsiveness, and NKG2A+ NK cell frequency is associated with total NK repertoire response and inhibitability, making identification of SNPs responsible for expression and frequency important for predicting innate immune response. As HLA-E expression is dependent on HLA class I signal peptide, we analyzed the relationship between peptide abundance and HLA-E expression levels. Our findings reveal a strong association between peptide availability and HLA-E expression. We identified the HLA-C KIR ligand epitope as a predictive marker for HLA-ABC expression, with the HLA-C1 epitope associated with high HLA-E expression, and the HLA-C2 epitope associated with low HLA-E expression. The relationship between HLA-C epitopes and HLA-E expression is independent of HLA-E allotypes and HLA-B leader peptide. While HLA-E expression shows no significant influence on NKG2A-mediated NK education, it does affect NK cell inhibition. In summary, these findings underscore the importance of NKG2A SNPs and HLA-C epitopes as predictive markers of NK cell phenotype and function and should be evaluated as prognostic markers for diseases expressing high levels of HLA-E.