350 research outputs found

    ImmuneDB, a Novel Tool for the Analysis, Storage, and Dissemination of Immune Repertoire Sequencing Data

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    ImmuneDB is a system for storing and analyzing high-throughput immune receptor sequencing data. Unlike most existing tools, which utilize flat-files, ImmuneDB stores data in a well-structured MySQL database, enabling efficient data queries. It can take raw sequencing data as input and annotate receptor gene usage, infer clonotypes, aggregate results, and run common downstream analyses such as calculating selection pressure and constructing clonal lineages. Alternatively, pre-annotated data can be imported and analyzed data can be exported in a variety of common Adaptive Immune Receptor Repertoire (AIRR) file formats. To validate ImmuneDB, we compare its results to those of another pipeline, MiXCR. We show that the biological conclusions drawn would be similar with either tool, while ImmuneDB provides the additional benefits of integrating other common tools and storing data in a database. ImmuneDB is freely available on GitHub at https://github.com/arosenfeld/immunedb, on PyPi at https://pypi.org/project/ImmuneDB, and a Docker container is provided at https://hub.docker.com/r/arosenfeld/immunedb. Full documentation is available at http://immunedb.com

    Computational Evaluation of B-Cell Clone Sizes in Bulk Populations

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    B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size—copy numbers, instances, and unique sequences—and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data

    Evidence That Mutation Is Universally Biased towards AT in Bacteria

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    Mutation is the engine that drives evolution and adaptation forward in that it generates the variation on which natural selection acts. Mutation is a random process that nevertheless occurs according to certain biases. Elucidating mutational biases and the way they vary across species and within genomes is crucial to understanding evolution and adaptation. Here we demonstrate that clonal pathogens that evolve under severely relaxed selection are uniquely suitable for studying mutational biases in bacteria. We estimate mutational patterns using sequence datasets from five such clonal pathogens belonging to four diverse bacterial clades that span most of the range of genomic nucleotide content. We demonstrate that across different types of sites and in all four clades mutation is consistently biased towards AT. This is true even in clades that have high genomic GC content. In all studied cases the mutational bias towards AT is primarily due to the high rate of C/G to T/A transitions. These results suggest that bacterial mutational biases are far less variable than previously thought. They further demonstrate that variation in nucleotide content cannot stem entirely from variation in mutational biases and that natural selection and/or a natural selection-like process such as biased gene conversion strongly affect nucleotide content

    An AT Mutational Bias in the Tiny GC-Rich Endosymbiont Genome of Hodgkinia

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    The fractional guanine + cytosine (GC) contents of sequenced bacterial genomes range from 13% to 75%. Despite several decades of research aimed at understanding this wide variation, the forces controlling GC content are not well understood. Recent work has suggested that a universal adenine + thymine (AT) mutational bias exists in all bacteria and that the elevated GC contents found in some bacterial genomes is due to genome-wide selection for increased GC content. These results are generally consistent with the low GC contents observed in most strict endosymbiotic bacterial genomes, where the loss of DNA repair mechanisms combined with the population genetic effects of small effective population sizes and decreased recombination should lower the efficacy of selection and shift the equilibrium GC content in the mutationally favored AT direction. Surprisingly, the two smallest bacterial genomes, Candidatus Hodgkinia cicadicola (144 kb) and Candidatus Tremblaya princeps (139 kb), have the unusual combination of highly reduced genomes and elevated GC contents, raising the possibility that these bacteria may be exceptions to the otherwise apparent universal bacterial AT mutational bias. Here, using population genomic data generated from the Hodgkinia genome project, we show that Hodgkinia has a clear AT mutational bias. These results provide further evidence that an AT mutational bias is universal in bacteria, even in strict endosymbionts with elevated genomic GC contents

    General Rules for Optimal Codon Choice

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    Different synonymous codons are favored by natural selection for translation efficiency and accuracy in different organisms. The rules governing the identities of favored codons in different organisms remain obscure. In fact, it is not known whether such rules exist or whether favored codons are chosen randomly in evolution in a process akin to a series of frozen accidents. Here, we study this question by identifying for the first time the favored codons in 675 bacteria, 52 archea, and 10 fungi. We use a number of tests to show that the identified codons are indeed likely to be favored and find that across all studied organisms the identity of favored codons tracks the GC content of the genomes. Once the effect of the genomic GC content on selectively favored codon choice is taken into account, additional universal amino acid specific rules governing the identity of favored codons become apparent. Our results provide for the first time a clear set of rules governing the evolution of selectively favored codon usage. Based on these results, we describe a putative scenario for how evolutionary shifts in the identity of selectively favored codons can occur without even temporary weakening of natural selection for codon bias

    MIRU-VNTRplus: a web tool for polyphasic genotyping of Mycobacterium tuberculosis complex bacteria

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    Harmonized typing of bacteria and easy identification of locally or internationally circulating clones are essential for epidemiological surveillance and disease control. For Mycobacterium tuberculosis complex (MTBC) species, multi-locus variable number tandem repeat analysis (MLVA) targeting mycobacterial interspersed repetitive units (MIRU) has been internationally adopted as the new standard, portable, reproducible and discriminatory typing method. However, no specialized bioinformatics web tools are available for analysing MLVA data in combination with other, complementary typing data. Therefore, we have developed the web application MIRU-VNTRplus (http://www.miru-vntrplus.org). This freely accessible service allows users to analyse genotyping data of their strains alone or in comparison with a reference database of strains representing the major MTBC lineages. Analysis and comparisons of genotypes can be based on MLVA-, spoligotype-, large sequence polymorphism and single nucleotide polymorphism data, or on a weighted combination of these markers. Tools for data exploration include search for similar strains, creation of phylogenetic and minimum spanning trees and mapping of geographic information. To facilitate scientific communication, an expanding genotype nomenclature (MLVA MtbC15-9 type) that can be queried via a web- or a SOAP-interface has been implemented. An extensive documentation guides users through all application functions

    A phase 2, randomized, double-blind, placebo- controlled study of chemo-immunotherapy combination using motolimod with pegylated liposomal doxorubicin in recurrent or persistent ovarian cancer: a Gynecologic Oncology Group partners study.

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    A phase 2, randomized, placebo-controlled trial was conducted in women with recurrent epithelial ovarian carcinoma to evaluate the efficacy and safety of motolimod-a Toll-like receptor 8 (TLR8) agonist that stimulates robust innate immune responses-combined with pegylated liposomal doxorubicin (PLD), a chemotherapeutic that induces immunogenic cell death. Women with ovarian, fallopian tube, or primary peritoneal carcinoma were randomized 1 : 1 to receive PLD in combination with blinded motolimod or placebo. Randomization was stratified by platinum-free interval (≤6 versus >6-12 months) and Gynecologic Oncology Group (GOG) performance status (0 versus 1). Treatment cycles were repeated every 28 days until disease progression. The addition of motolimod to PLD did not significantly improve overall survival (OS; log rank one-sided P = 0.923, HR = 1.22) or progression-free survival (PFS; log rank one-sided P = 0.943, HR = 1.21). The combination was well tolerated, with no synergistic or unexpected serious toxicity. Most patients experienced adverse events of fatigue, anemia, nausea, decreased white blood cells, and constipation. In pre-specified subgroup analyses, motolimod-treated patients who experienced injection site reactions (ISR) had a lower risk of death compared with those who did not experience ISR. Additionally, pre-treatment in vitro responses of immune biomarkers to TLR8 stimulation predicted OS outcomes in patients receiving motolimod on study. Immune score (tumor infiltrating lymphocytes; TIL), TLR8 single-nucleotide polymorphisms, mutational status in BRCA and other DNA repair genes, and autoantibody biomarkers did not correlate with OS or PFS. The addition of motolimod to PLD did not improve clinical outcomes compared with placebo. However, subset analyses identified statistically significant differences in the OS of motolimod-treated patients on the basis of ISR and in vitro immune responses. Collectively, these data may provide important clues for identifying patients for treatment with immunomodulatory agents in novel combinations and/or delivery approaches. Clinicaltrials.gov, NCT 01666444
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