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Effect of sampling media and culture conditions on dendritic cell generation: ion depleted plasma negatively influences the survival of monocyte-derived dendritic cells

Abbreviations\n\nAutologous serum or plasma are often used as a supplementation in culture media for autoimmune disease studies. They contain many biologically and immunologically active molecules that might be involved in the development of these diseases. We examined the effect of different cultivating media supplemented with autologous serum and two types of plasma obtained from heparin and EDTA coated tubes on monocyte-derived dendritic cells viability. Our results show that medium with plasma from EDTA coated tubes is unsuitable for cultivation of myeloid cells due to the absence of bivalent ions and that the type of sampling tubes used for blood collection might be critical for successful experiment.

Cell Biology

Genetic correlations among brain-behavioral and immune-related phenotypes based on genome-wide association data.

Individuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies (GWASs) to determine if commonly varying single nucleotide polymorphisms (SNPs) are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (HESS) methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohns disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations amongst the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study.

Bioinformatics

The impact of the newly licensed dengue vaccine in endemic countries

BackgroundWith approximately 3 billion people at risk of acquiring the infection, dengue fever is now considered the most important mosquito-borne viral disease in the world, with 390 million dengue infections occurring every year, of which 96 million manifest symptoms with any level of disease severity. Treatment of uncomplicated dengue cases is only supportive and severe dengue cases require hospital intensive care. A vaccine now licensed in several countries and developed by Sanofi Pasteur (CYD-TDV, named Dengvaxia), is able to protect, in the first 25 months of the two Phase III, 66% of a subset of 9 - 16 year old participants. However, a significantly lower efficacy (including negative vaccine efficacy) was noted for children younger than 9 years of age.\n\nMethodology/Principal FindingsAnalysis of year 3 results of phase III trials of Dengvaxia suggest high rates of protection of vaccinated partial dengue immunes but high rates of hospitalizations during breakthrough dengue infections of persons who were vaccinated when seronegative, with vaccine appearing to induce enhancing antibodies (ADE). An age structured model was developed based on Sanofis recommendation to vaccinate persons age 945 years in dengue endemic countries. The model was used to explore the clinical burden of two vaccination strategies: 1) Vaccinate 4 or 20% of individuals, ages 9 - 45 years, seropositives and seronegatives, and 2) vaccinate 4 or 20% of individuals, ages 9 - 45 years, who are dengue immune only.\n\nConclusions/SignificanceOur results show that vaccinating dengue monotypic immune individuals prevents dengue hospitalizations, but at the same time dengue infections of vaccine-sensitized persons increases hospitalizations. When the vaccine is given only to partial immune individuals, after immuno-logical screening of the population, disease burden decreases considerably.\n\nAuthor SummaryCaused by four antigenically related but distinct serotypes a tetravalent vaccine is needed to protect against the huge burden of dengue disease. Dengvaxia is a vaccine candidate now licensed in several countries for individuals 9 - 45 years of age living in endemic countries with least 70% of seroprevalence. Modelers from Sanofi Pasteur have predicted that this vaccine has the potential to reduce by about 50% the disease burden within 5 years when 20% of an endemic country population is vaccinated, thus achieving a World Health Organization dengue prevention goal.\n\nIn this paper, mathematical modeling is used to investigate the impact of the newly licensed dengue vaccine using different scenarios. Our results show that to achieve significant reduction in disease bur-den, the vaccination program is most effective if it includes only individuals that have been already exposed to at least one dengue virus. Immunological screening of the population prior to vaccination is advised and vaccination strategies must be planned based on epidemiological disease dynamics for each specific endemic region.

Epidemiology

Detection and quantification of viral RNA in human tumors using open source pipeline: viGEN

An estimated 17% of cancers worldwide are associated with infectious causes. The extent and biological significance of viral presence/infection in actual tumor samples is generally unknown but could be measured using human transcriptome (RNA-seq) data from tumor samples.\n\nWe present an open source bioinformatics pipeline viGEN, which combines existing well-known and novel RNA-seq tools for not only the detection and quantification of viral RNA, but also variants in the viral transcripts.\n\nThe pipeline includes 4 major modules: The first module allows to align and filter out human RNA sequences; the second module maps and count (remaining un-aligned) reads against reference genomes of all known and sequenced human viruses; the third module quantifies read counts at the individual viral genes level thus allowing for downstream differential expression analysis of viral genes between experimental and controls groups. The fourth module calls variants in these viruses. To the best of our knowledge, there are no publicly available pipelines or packages that would provide this type of complete analysis in one open source package.\n\nIn this paper, we applied the viGEN pipeline to two case studies. We first demonstrate the working of our pipeline on a large public dataset, the TCGA cervical cancer cohort. We also performed additional in-depth analyses on a small focused study of TCGA liver cancer patients. In this cohort, we perform viral-gene quantification, viral-variant extraction and survival analysis. This allowed us to find differentially expressed viral-transcripts and viral-variants between the groups of patients, and connect them to clinical outcome.\n\nFrom our analyses, we show that we were able to successfully detect the human papilloma virus among the TCGA cervical cancer patients. We compared the viGEN pipeline with two metagenomics tools and demonstrate similar sensitivity/specificity. We were also able to quantify viral-transcripts and extract viral-variants using the liver cancer dataset. The results presented corresponded with published literature in terms of rate of detection, viral gene expression patterns and impact of several known variants of HBV genome. Results also show novel information about distinct patterns of expression and co-expression in Hepatitis B and the Human Endogenous Retrovirus (HERV) K113 viruses.\n\nThis pipeline is generalizable, and can be used to provide novel biological insights into the significance of viral and other microbial infections in complex diseases, tumorigeneses and cancer immunology. The source code, with example data and tutorial is available at: https://github.com/ICBI/viGEN/.

bioinformatics

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

Genetics can provide a systematic approach to discovering the tissues and cell types relevant for a complex disease or trait. Identifying these tissues and cell types is critical for following up on non-coding allelic function, developing ex-vivo models, and identifying therapeutic targets. Here, we analyze gene expression data from several sources, including the GTEx and PsychENCODE consortia, together with genome-wide association study (GWAS) summary statistics for 48 diseases and traits with an average sample size of 169,331, to identify disease-relevant tissues and cell types. We develop and apply an approach that uses stratified LD score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We detect tissue-specific enrichments at FDR < 5% for 34 diseases and traits across a broad range of tissues that recapitulate known biology. In our analysis of traits with observed central nervous system enrichment, we detect an enrichment of neurons over other brain cell types for several brain-related traits, enrichment of inhibitory over excitatory neurons for bipolar disorder but excitatory over inhibitory neurons for schizophrenia and body mass index, and enrichments in the cortex for schizophrenia and in the striatum for migraine. In our analysis of traits with observed immunological enrichment, we identify enrichments of T cells for asthma and eczema, B cells for primary biliary cirrhosis, and myeloid cells for Alzheimer's disease, which we validated with independent chromatin data. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signal.

genetics

Transcriptional response to West Nile virus infection in the zebra finch (Taeniopygia guttata), a songbird model for immune function

West Nile Virus (WNV) is the one of most widespread arboviruses worldwide. WNV exists in a bird-mosquito transmission cycle where passerine birds act as the primary reservoir host. As a public health concern, the mammalian immune response to WNV has been studied in detail. Little, however, is known about the avian immune response to WNV. Avian taxa show variable susceptibility to WNV and what drives this variation is unknown. Thus, to study the immune response to WNV in birds, we experimentally infected captive zebra finches (Taeniopygia guttata). Zebra finches provide a useful model, as like many natural avian hosts they are moderately susceptible to WNV and thus provide sufficient viremia to infect mosquitoes. We performed splenic RNAseq during peak viremia to provide an overview of the transcriptional response. In general, we find strong parallels with the mammalian immune response to WNV, including up-regulation of five genes in the Rig-I-like receptor signaling pathway, and offer insights into avian specific responses. Together with complementary immunological assays, we provide a model of the avian immune response to WNV and set the stage for future comparative studies among variably susceptible populations and species.

genomics

MAGIC: A diffusion-based imputation method reveals gene-gene interactions in single-cell RNA-sequencing data

Single-cell RNA-sequencing is fast becoming a major technology that is revolutionizing biological discovery in fields such as development, immunology and cancer. The ability to simultaneously measure thousands of genes at single cell resolution allows, among other prospects, for the possibility of learning gene regulatory networks at large scales. However, scRNA-seq technologies suffer from many sources of significant technical noise, the most prominent of which is dropout due to inefficient mRNA capture. This results in data that has a high degree of sparsity, with typically only ~10% non-zero values. To address this, we developed MAGIC (Markov Affinity-based Graph Imputation of Cells), a method for imputing missing values, and restoring the structure of the data. After MAGIC, we find that two- and three-dimensional gene interactions are restored and that MAGIC is able to impute complex and non-linear shapes of interactions. MAGIC also retains cluster structure, enhances cluster-specific gene interactions and restores trajectories, as demonstrated in mouse retinal bipolar cells, hematopoiesis, and our newly generated epithelial-to-mesenchymal transition dataset.

bioinformatics

Predicting Protein Binding Affinity With Word EmbeddingsAnd Recurrent Neural Networks

At the core of our immunological system lies a group of proteins named Major Histocompatibility Complex (MHC), to which epitopes (also proteins sometimes named antigenic determinants), bind to eliciting a response. These responses are extremely varied and of widely different nature. For instance, Killer and Helper T cells are responsible for, respectively, counteracting viral pathogens and tumorous cells. Many other types exist, but their underlying structure can be very similar due to the fact that they all are proteins and bind to the MHC receptor in a similar fashion. With this framework in mind, being able to predict with precision the structure of a protein that will elicit a specific response in the human body represents a novel computational approach to drug discovery. Although many machine learning approaches have been used, no attempt to solve this problem using Recurrent Neural Networks (RNNs) exist. We extend the current efforts in the field by applying a variety of network architectures based on RNNs and word embeddings (WE). The code is freely available and under current development at https://github.com/carlomazzaferro/mhcPreds

bioinformatics

Recent Advancement in Biosensors Technology for Animal and Livestock Health Management

The term biosensors encompasses devices that have the potential to quantify physiological, immunological and behavioural responses of livestock and multiple animal species. Novel biosensing methodologies offer highly specialised monitoring devices for the specific measurement of individual and multiple parameters covering an animals physiology as well as monitoring of an animals environment. These devices are not only highly specific and sensitive for the parameters being analysed, but they are also reliable and easy to use, and can accelerate the monitoring process. Novel biosensors in livestock management provide significant benefits and applications in disease detection and isolation, health monitoring and detection of reproductive cycles, as well as monitoring physiological wellbeing of the animal via analysis of the animals environment. With the development of integrated systems and the Internet of Things, the continuously monitoring devices are expected to become affordable. The data generated from integrated livestock monitoring is anticipated to assist farmers and the agricultural industry to improve animal productivity in the future. The data is expected to reduce the impact of the livestock industry on the environment, while at the same time driving the new wave towards the improvements of viable farming techniques. This review focusses on the emerging technological advancements in monitoring of livestock health for detailed, precise information on productivity, as well as physiology and well-being. Biosensors will contribute to the 4th revolution in agriculture by incorporating innovative technologies into cost-effective diagnostic methods that can mitigate the potentially catastrophic effects of infectious outbreaks in farmed animals

bioengineering

Impact Of Sequencing Depth And Read Length On Single Cell RNA Sequencing Data: Lessons From T Cells

Single cell RNA sequencing (scRNA-seq) has shown great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant sub-populations of T cells, and notably the identification of the full length T cell receptor (TCR{beta}), which defines the specificity against cognate antigens. Several factors, such as RNA library capture, cell quality, and sequencing output have been suggested to affect the quality of scRNA-seq data, but these factors have not been systematically examined.\n\nWe studied the effect of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCR{beta} reconstruction, utilising 1,305 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. TCR{beta} were detected in 1,027 cells (79%), with a success rate between 81% and 100% for datasets with at least 250,000 (PE) reads of length >50 bp.\n\nSufficient read length and sequencing depth can control technical noise to enable accurate identification of TCR{beta} and gene expression profiles from scRNA-seq data of T cells.

bioinformatics

An Amino Acid Motif In HLA-DRB1 Distinguishes Patients With Uveitis In Juvenile Idiopathic Arthritis

ObjectivesUveitis is a visually-debilitating disorder that affects up to 30% of children with the most common forms of juvenile idiopathic arthritis (JIA). The disease mechanisms predisposing only a subgroup of children to uveitis are unknown. To identify genetic susceptibility loci for uveitis in JIA, we conducted a genome-wide association study totalling 522 JIA cases.\n\nMethodsTwo cohorts of JIA patients with ophthalmological follow-up were separately genotyped and then imputed using a genome-wide imputation reference panel, and an HLA-specific reference panel used for imputing amino acids and HLA types in the major histocompatibility complex (MHC). After imputation, we performed genome-wide and MHC-specific analyses. We used a reverse immunology approach to model antigen presentation at 13 common HLA-DRB1 allotypes.\n\nResultsWe identified the amino acid serine at position 11 (serine-11) in HLA-DRB1 as associated to increased risk of uveitis (OR = 2.60, p = 5.43 x 10-10). We found the serine-11 signal to be specific to females (pfemales = 7.61 x 10-10, pmales = 0.18). Serine-11 resides in the YST-motif in the peptide binding groove of the HLA-DRB1 protein; all three amino acids are in perfect linkage disequilibrium and show identical association to disease. Quantitative prediction of binding affinity revealed that discernable peptide-binding preferences distinguish HLA-DRB1 allotypes with the YST-motif.\n\nConclusionOur findings highlight a genetically distinct, sexually-dimorphic feature of JIA-uveitis compared to JIA without uveitis in HLA-DRB1. The association indicates the potential involvement for antigen presentation by HLA-DRB1 in the development of uveitis in JIA.

genetics

APRIL and BAFF increase breast cancer cell stemness

Background: Recent advances in cancer immunology revealed immune-related properties of the cancer cell as a promising new therapeutic target. The two TNF superfamily members, APRIL and BAFF even though were primarily studied for their role in lymphocyte maturation, their presence in a number of normal and cancer solid tumors including breast cancer revealed an association with tumor growth and aggressiveness. Methods: In the present work, we have explored the role of APRIL and BAFF in breast tumor development, progression and metastasis as well as resistance to therapy. We studied their effect on the epithelial to mesenchymal transition and migration of breast cancer cells, and their action on the important sub-population of cancer stem cells identified by autofluorescence and ALDH activity. Their action on an number of pluripotency genes was examined and breast cancer stem cell ability to form mammospheres was also utilized. The receptor and the signaling pathway involved were also investigated as well as the role of steroid hormones in their action. Results: Our findings show that in breast cancer both APRIL and BAFF increase epithelial to mesenchymal transition and migratory capacity, as well as cancer stem cell numbers, by inducing pluripotency genes such as KLF4 and NANOG. These effects were mediated by their common receptor BCMA and the JNK signaling pathway. Interestingly, androgens enhance APRIL transcription and subsequently its pluripotency effect. Conclusions: All these data support the significant role of APRIL and BAFF in breast cancer disease progression and provide evidence for a new possible mechanism of therapy resistance, especially in aromatase inhibitors-treated patients, were local androgen is increased.

cancer biology

An improved experimental model of cystic hydatid disease in liver resembling natural infection route with stable growing dynamics and immune reaction

Cystic echinococcosis is an endemic parasitic infection in Xinjiang, China and is causing serious economic burdens and public health concerns. An experimental murine model in vivo for hepatic cystic echinococcosis was established in C57B/6 mice by injection with human protoscolices via the portal vein of three different concentrations. Mice were followed up 10 months by ultrasound, gross anatomy, pathological and immunological examinations. The protoscolice migration in portal vein, hydatid cyst growth, host immune reaction and hepatic histopathology were examed periodicly. The infection rate of the mice in the high, medium, and low concentration groups were 90%, 100%, and 63.6%, respectively. The protoscolices migrate in the portal vein with blood flow, settle in the liver and develop into orthotopic hepatic hydatid cysts, resembling the natural infection route and course. This study established an improved experimental model of low biohazard risk but stable growing dynamics and immune reaction. It is especially useful for new anti-parasite medication trials agains hydatid disease.\n\nSummary statementAn experimental murine model of cystic echinococcosis was set up. This orthotopic model resembles primary infection route and natural infectious course with low biohazard risk and high efficiency.

pathology

Single-Cell RNAseq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma

Glioblastoma is the most common primary brain cancer in adults and is notoriously difficult to treat due to its diffuse nature. We performed single-cell RNAseq on 3589 cells in a cohort of four patients. We obtained cells from the tumor core as well as surrounding peripheral tissue. Our analysis revealed cellular variation in the tumors genome and transcriptome, We were able to identify infiltrating neoplastic cells in regions peripheral to the core lesions. Despite the existence of significant heterogeneity among neoplastic cells, we found that infiltrating GBM cells share a consistent gene signature between patients, suggesting a common mechanism of infiltration. Additionally, in investigating the immunological response to the tumors, we found transcriptionally distinct myeloid cell populations residing in the tumor core and the surrounding peritumoral space. Our data provide a detailed dissection of GBM cell types, revealing an abundance of novel information about tumor formation and migration.

cancer biology

PI3Kδ inhibition supports memory T cells with enhanced antitumor fitness

Phosphatidylinositol-3-kinase p110{delta} (PI3K{delta}) inhibition by Idelalisib (CAL-101) in hematological malignancies directly induces apoptosis in cancer cells and disrupts immunological tolerance by depleting regulatory T cells (Tregs). Yet, little is known about the direct impact of PI3K{delta} blockade on effector T cells from CAL-101 therapy. Herein, we demonstrate a direct effect of p110{delta} inactivation via CAL-101 on murine and human CD8+ T cells that promotes a strong undifferentiated memory phenotype (elevated CD62L/CCR7, CD127 and Tcf7). These CAL-101 T cells also persisted longer after transfer and exerted stronger antitumor immunity compared to traditionally expanded CD8+ T cells in two solid tumor models. Thus, this report describes a novel direct enhancement of CD8+ T cell memory by a p110{delta} inhibitor that leads to markedly improved tumor regression. This finding has significant implications to improve outcomes from next generation cancer immunotherapies.\n\nHighlightsO_LIIn vitro blockade of PI3K p110{delta} with CAL-101 endows antitumor T cells with a stronger memory phenotype than those treated with AKTi\nC_LIO_LIThe strong memory phenotype of CAL-101 treated cells translates into improved survival of mice bearing aggressive tumors after adoptive transfer of these T cells\nC_LIO_LIHuman CAR engineered T cells treated with CAL-101 possess an enhanced memory phenotype and robust antitumor efficacy\nC_LIO_LIThe antitumor efficacy of CAL-101 primed T cells is not mediated by high CD62L or CD127 expression, but is likely driven by their stem memory phenotype\nC_LI\n\neTOC BlurbBowers et al report a novel function of PI3K blockade using the p110{delta} subunit inhibitor CAL-101 to induce memory and antitumor potency in CD8+ T cells. Ex vivo treatment of T cells with CAL-101 leads to improved antitumor control and subject survival in both murine transgenic T cell and human CAR T cell models.

cancer biology

Metagenomic sequencing suggests arthropod antiviral RNA interference is highly derived, and identifies novel viral small RNAs in a mollusc and a brown alga

RNA interference (RNAi)-related pathways target viruses and transposable element (TE) transcripts in plants, fungi, and ecdysozoans (nematodes and arthropods), giving protection against infection and transmission. In each case, this produces abundant TE and virus-derived 20-30nt small RNAs, which provide a characteristic signature of RNAi-mediated defence. The broad phylogenetic distribution of the Argonaute and Dicer-family genes that mediate these pathways suggests that defensive RNAi is ancient and probably shared by most animal (metazoan) phyla. Indeed, while vertebrates had been thought an exception, it has recently been argued that mammals also possess an antiviral RNAi pathway, although its immunological relevance is currently uncertain and the viral small RNAs are not detectably under natural conditions. Here we use a metagenomic approach to test for the presence of virus-derived small RNAs in five divergent animal phyla (Porifera, Cnidaria, Echinodermata, Mollusca, and Annelida), and in a brown alga--which represents an independent origin of multicellularity from plants, fungi, and animals. We use metagenomic RNA sequencing to identify around 80 virus-like contigs in these lineages, and small RNA sequencing to identify small RNAs derived from those viruses. Contrary to our expectations, we were unable to identify canonical (i.e. Drosophila-, nematode- or plant-like) viral small RNAs in any of these organisms, despite the widespread presence of abundant micro-RNAs, and transposon-derived somatic Piwi-interacting piRNAs in the animals. Instead, we identified a distinctive group of virus-derived small RNAs in the mollusc, which have a piRNA-like length distribution but lack key signatures of piRNA biogenesis, and a group of 21U virus-derived small RNAs in the brown alga. We also identified primary piRNAs derived from putatively endogenous copies of DNA viruses in the cnidarian and the echinoderm, and an endogenous RNA virus in the mollusc. The absence of canonical virus-derived small RNAs from our samples may suggest that the majority of animal phyla lack an antiviral RNAi response. Alternatively, these phyla could possess an antiviral RNAi response resembling that reported for vertebrates, which is not detectable through simple metagenomic sequencing of wild-type individuals. In either case, our findings suggest that the current antiviral RNAi responses of arthropods and nematodes are highly diverged from the ancestral metazoan state, and that antiviral RNAi may even have evolved independently on multiple occasions.\n\nAuthor summaryThe presence of abundant virus-derived small RNAs in infected plants, fungi, nematodes, and arthropods suggests that Dicer-dependent antiviral RNAi is an ancient and conserved defence. Using metagenomic sequencing from wild-caught organisms we show that antiviral RNAi is highly variable across animals. We identify a distinctive group of virus-derived small RNAs in a mollusc, which have a piRNA-like length distribution but lack key signatures of piRNA biogenesis. We also report a group of 21U virus-derived small RNAs in a brown alga, which represents an origin of multicellularity separate from that of plants, fungi, and animals. The absence of virus-derived small RNAs from our samples may suggest that the majority of animal phyla lack an antiviral RNAi response or that these phyla could possess an antiviral RNAi response resembling that reported for vertebrates, which is not detectable through simple metagenomic sequencing of wild-type individuals. In addition, we report abundant somatic piRNAs across anciently divergent animals suggesting that this is the ancestral state in Bilateria. Our study challenges the widely-held assumption that most invertebrates possess an antiviral RNAi pathway likely similar to that seen in Drosophila, other arthropods, and nematodes.

evolutionary biology

The antibody repertoire of colorectal cancer

3Immunotherapy is becoming increasingly important in the fight against cancers, utilizing and manipulating the bodys immune response to treat tumors. Understanding the immune repertoire - the collection of immunological proteins - of treated and untreated cells is possible at the genomic, but technically difficult at the protein level. Standard protein databases do not include the highly divergent sequences of somatic rearranged immunoglobulin genes, and may lead to missed identifications in a mass spectrometry search. We introduce a novel proteogenomic approach, AbScan, to identify these highly variable antibody peptides, by developing a customized antibody database construction method using RNA-seq reads aligned to immunoglobulin (Ig) genes.\n\nAbScan starts by filtering transcript (RNA-seq) reads that match the template for Ig genes. The retained reads are used to construct a repertoire graph using the split de Bruijn graph: a graph structure that improves upon the standard de Bruijn graph to capture the high diversity of Ig genes in a compact manner. AbScan corrects for sequencing errors, and converts the graph to a format suitable for searching with MS/MS search tools. We used AbScan to create an antibody database from 90 RNA-seq colorectal tumor samples. Next, we used proteogenomics analysis to search MS/MS spectra of matched colorectal samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) against the AbScan generated database. AbScan identified 1, 940 distinct antibody peptides. Correlating with previously identified Single Amino-Acid Variants (SAAVs) in the tumor samples, we identified 163 pairs (antibody peptide, SAAV) with significant co-occurrence pattern in the 90 samples. The presence of co-expressed antibody and mutated peptides was correlated with survival time of the individuals. Our results suggest that AbScan(https://github.com/csw407/AbScan.git) is an effective tool for a proteomic exploration of the immune response in cancers.\n\n\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@62001corg.highwire.dtl.DTLVardef@1f542faorg.highwire.dtl.DTLVardef@10048d0org.highwire.dtl.DTLVardef@1ac5a75org.highwire.dtl.DTLVardef@66db0f_HPS_FORMAT_FIGEXP M_TBL C_TBL

bioinformatics

Accurate typing of class I human leukocyte antigen by Oxford nanopore sequencing

Oxford Nanopore Technologies MinION has expanded the current DNA sequencing toolkit by delivering long read lengths and extreme portability. The MinION has the potential to enable expedited point-of-care human leukocyte antigen (HLA) typing, an assay routinely used to assess the immunological compatibility between organ donors and recipients, but the platforms high error rate makes it challenging to type alleles with clinical-grade accuracy. Here, we developed and validated Athlon, an algorithm that iteratively scores nanopore reads mapped to a hierarchical database of HLA alleles to arrive at a consensus diploid genotype; Athlon achieved a 100% accuracy in class I HLA typing at high resolution.

bioinformatics