Computational strategies for dissecting the high-dimensional complexity of adaptive immune repertoires

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity in order to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic and (iv) machine learning methods applied to dissect, quantify and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology towards coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.Comment: 27 pages, 2 figure

SETD6 mediates selective interaction and genomic occupancy of BRD4 and MITF in melanoma cells

Aberrant transcriptional programs mediate malignant transformation of melanoma, the most aggressive form of skin cancer. The lysine methyltransferase SETD6 has been implicated in regulating transcription, cell adhesion, migration, and other processes in various cancers; however its role in melanoma remains unexplored. We recently reported that SETD6 monomethylates the BRD4 at K99 to selectively regulate transcription of genes involved in mRNA (messenger RNA) translation. Here, we observed that BRD4 methylation at K99 by SETD6 occurs in melanoma cells. Knockout of SETD6 or a point mutation at BRD4-K99 disrupts BRD4 genomic occupancy. In addition, we show that SETD6 interacts with MITF, a master transcription factor in melanocytes and melanoma, and influences the genomic distribution of MITF. Mechanistically, we uncover a novel chromatin-localized interaction between BRD4 and MITF in melanoma. Our data suggest that BRD4 binds MITF in melanoma cells and that this interaction is dependent on both SETD6-mediated methylation of BRD4 and MITF acetylation. This chromatin complex plays a pivotal role in selective recruitment of BRD4 and MITF to different genomic loci in melanoma cells

Protein Activation in Periapical Reaction to Iodoform Containing Root Canal Sealer

Objectives: An association between root canal sealers and periapical lesions in primary dentition has been suggested, yet the chemical-protein interactions that may be involved in it have not been studied. The present study explored root sealer components' effect on periapical tissue proteins using bioinformatics tools. Study design: For each chemical component of Endoflas F.S. root sealing material we identified the known and predicted target proteins, using STITCH (search tool for interactions of chemicals http://stitch.embl.de/). Identified target proteins were grouped into functional categories using the annotation clustering tool from DAVID, the Database for Annotation, Visualization and Integrated Discovery (http://david.abcc.ncifcrf.gov/). STRING Protein-Protein Interaction network database identified associations between the proteins. Results: Sixteen proteins identified with STITCH served as input to DAVID annotation clustering tool. Only ZnO and Eugenol targeted proteins had statistically significant annotations. Gene Ontology terms of ZnO and Eugenol targeted proteins demonstrated that these proteins respond to mechanical stimulus and to oxidative stress. They highlight these proteins' role in the positive regulation of transcription, gene expression, cell proliferation and apoptosis, and their complementary role in the negative regulation of cell death. Conclusion: When stimulated by Zinc Oxide, Eugenol and Calcium hydroxide, chemical-protein and subsequent protein-protein interactions result in cell proliferation in the periapical area. Our findings indicate that certain root sealers components may cause enlargement of the permanent tooth follicle. Dentists should be aware of this phenomenon and radiographically monitor root canal treated teeth until shedding.</jats:p

Contribution of T Cell Receptor Alpha and Beta CDR3, MHC Typing, V and J Genes to Peptide Binding Prediction

IntroductionPredicting the binding specificity of T Cell Receptors (TCR) to MHC-peptide complexes (pMHCs) is essential for the development of repertoire-based biomarkers. This affinity may be affected by different components of the TCR, the peptide, and the MHC allele. Historically, the main element used in TCR-peptide binding prediction was the Complementarity Determining Region 3 (CDR3) of the beta chain. However, recently the contribution of other components, such as the alpha chain and the other V gene CDRs has been suggested. We use a highly accurate novel deep learning-based TCR-peptide binding predictor to assess the contribution of each component to the binding.MethodsWe have previously developed ERGO-I (pEptide tcR matchinG predictiOn), a sequence-based T-cell receptor (TCR)-peptide binding predictor that employs natural language processing (NLP) -based methods. We improved it to create ERGO-II by adding the CDR3 alpha segment, the MHC typing, V and J genes, and T cell type (CD4+ or CD8+) as to the predictor. We then estimate the contribution of each component to the prediction.Results and DiscussionERGO-II provides for the first time high accuracy prediction of TCR-peptide for previously unseen peptides. For most tested peptides and all measures of binding prediction accuracy, the main contribution was from the beta chain CDR3 sequence, followed by the beta chain V and J and the alpha chain, in that order. The MHC allele was the least contributing component. ERGO-II is accessible as a webserver at http://tcr2.cs.biu.ac.il/ and as a standalone code at https://github.com/IdoSpringer/ERGO-II.</jats:sec