Evolution of MHC class I genes in the endangered loggerhead sea turtle (Caretta caretta) revealed by 454 amplicon sequencing

Background: In evolutionary and conservation biology, parasitism is often highlighted as a major selective pressure. To fight against parasites and pathogens, genetic diversity of the immune genes of the major histocompatibility complex (MHC) are particularly important. However, the extensive degree of polymorphism observed in these genes makes it difficult to conduct thorough population screenings. Methods: We utilized a genotyping protocol that uses 454 amplicon sequencing to characterize the MHC class I in the endangered loggerhead sea turtle (Caretta caretta) and to investigate their evolution at multiple relevant levels of organization. Results: MHC class I genes revealed signatures of trans-species polymorphism across several reptile species. In the studied loggerhead turtle individuals, it results in the maintenance of two ancient allelic lineages. We also found that individuals carrying an intermediate number of MHC class I alleles are larger than those with either a low or high number of alleles. Conclusions: Multiple modes of evolution seem to maintain MHC diversity in the loggerhead turtles, with relatively high polymorphism for an endangered species

The effects of parameter choice on defining molecular operational taxonomic units and resulting ecological analyses of metabarcoding data

Copyright remains with the author(s) or their institution(s). Permission for reuse (free in most cases) can be obtained from RightsLink.This work was supported by a NSERC CREATE grant to M.E.C. and an Institutional Links grant 172726351 to E.L.C. under the Newton-Ungku Omar Fund, through the British Council in the UK and the Malaysian Industry-Government Group for High Technology in Malaysia. The Newton Fund is Overseas Development Assistance administered through the UK Department for Business Innovation and Skills (BIS). For further information, please visitwww.newtonfund.ac.uk

Adaptive Langevin Sampler for Separation of t-Distribution Modelled Astrophysical Maps

We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC) sampling scheme to unmix the astrophysical sources and describe the derivation details. In this scheme, we use the Langevin stochastic equation for transitions, which enables parallel drawing of random samples from the posterior, and reduces the computation time significantly (by two orders of magnitude). In addition, Student's t-distribution parameters are updated throughout the iterations. The results on astrophysical source separation are assessed with two performance criteria defined in the pixel and the frequency domains.Comment: 12 pages, 6 figure

Long-lived quantum coherence in photosynthetic complexes at physiological temperature

Photosynthetic antenna complexes capture and concentrate solar radiation by transferring the excitation to the reaction center which stores energy from the photon in chemical bonds. This process occurs with near-perfect quantum efficiency. Recent experiments at cryogenic temperatures have revealed that coherent energy transfer - a wavelike transfer mechanism - occurs in many photosynthetic pigment-protein complexes (1-4). Using the Fenna-Matthews-Olson antenna complex (FMO) as a model system, theoretical studies incorporating both incoherent and coherent transfer as well as thermal dephasing predict that environmentally assisted quantum transfer efficiency peaks near physiological temperature; these studies further show that this process is equivalent to a quantum random walk algorithm (5-8). This theory requires long-lived quantum coherence at room temperature, which never has been observed in FMO. Here we present the first evidence that quantum coherence survives in FMO at physiological temperature for at least 300 fs, long enough to perform a rudimentary quantum computational operation. This data proves that the wave-like energy transfer process discovered at 77 K is directly relevant to biological function. Microscopically, we attribute this long coherence lifetime to correlated motions within the protein matrix encapsulating the chromophores, and we find that the degree of protection afforded by the protein appears constant between 77 K and 277 K. The protein shapes the energy landscape and mediates an efficient energy transfer despite thermal fluctuations. The persistence of quantum coherence in a dynamic, disordered system under these conditions suggests a new biomimetic strategy for designing dedicated quantum computational devices that can operate at high temperature.Comment: PDF files, 15 pages, 3 figures (included in the PDF file

A Linear Epitope in the N-Terminal Domain of CCR5 and Its Interaction with Antibody.

The CCR5 receptor plays a role in several key physiological and pathological processes and is an important therapeutic target. Inhibition of the CCR5 axis by passive or active immunisation offers one very selective strategy for intervention. In this study we define a new linear epitope within the extracellular domain of CCR5 recognised by two independently produced monoclonal antibodies. A short peptide encoding the linear epitope can induce antibodies which recognise the intact receptor when administered colinear with a tetanus toxoid helper T cell epitope. The monoclonal antibody RoAb 13 is shown to bind to both cells and peptide with moderate to high affinity (6x10^8 and 1.2x107 M-1 respectively), and binding to the peptide is enhanced by sulfation of tyrosines at positions 10 and 14. RoAb13, which has previously been shown to block HIV infection, also blocks migration of monocytes in response to CCR5 binding chemokines and to inflammatory macrophage conditioned medium. A Fab fragment of RoAb13 has been crystallised and a structure of the antibody is reported to 2.1 angstrom resolution

Exploring Carbon Nanomaterial Diversity for Nucleation of Protein Crystals

Controlling crystal nucleation is a crucial step in obtaining high quality protein crystals for structure determination by X-ray crystallography. Carbon nanomaterials (CNMs) including carbon nanotubes, graphene oxide, and carbon black provide a range of surface topographies, porosities and length scales; functionalisation with two different approaches, gas phase radical grafting and liquid phase reductive grafting, provide routes to a range of oligomer functionalised products. These grafted materials, combined with a range of controls, were used in a large-scale assessment of the effectiveness for protein crystal nucleation of 20 different carbon nanomaterials on five proteins. This study has allowed a direct comparison of the key characteristics of carbon-based nucleants: appropriate surface chemistry, porosity and/or roughness are required. The most effective solid system tested in this study, carbon black nanoparticles functionalised with poly(ethylene glycol) methyl ether of mean molecular weight 5000, provides a novel highly effective nucleant, that was able to induce crystal nucleation of four out of the five proteins tested at metastable conditions

Specificity, Privacy, and Degeneracy in the CD4 T Cell Receptor Repertoire Following Immunization.

T cells recognize antigen using a large and diverse set of antigen-specific receptors created by a complex process of imprecise somatic cell gene rearrangements. In response to antigen-/receptor-binding-specific T cells then divide to form memory and effector populations. We apply high-throughput sequencing to investigate the global changes in T cell receptor sequences following immunization with ovalbumin (OVA) and adjuvant, to understand how adaptive immunity achieves specificity. Each immunized mouse contained a predominantly private but related set of expanded CDR3β sequences. We used machine learning to identify common patterns which distinguished repertoires from mice immunized with adjuvant with and without OVA. The CDR3β sequences were deconstructed into sets of overlapping contiguous amino acid triplets. The frequencies of these motifs were used to train the linear programming boosting (LPBoost) algorithm LPBoost to classify between TCR repertoires. LPBoost could distinguish between the two classes of repertoire with accuracies above 80%, using a small subset of triplet sequences present at defined positions along the CDR3. The results suggest a model in which such motifs confer degenerate antigen specificity in the context of a highly diverse and largely private set of T cell receptors

Error, reproducibility and sensitivity : a pipeline for data processing of Agilent oligonucleotide expression arrays

Background Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2% of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log2 units ( 6% of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators. Conclusions This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells

Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence.

The clonal theory of adaptive immunity proposes that immunological responses are encoded by increases in the frequency of lymphocytes carrying antigen-specific receptors. In this study, we measure the frequency of different T-cell receptors (TcR) in CD4 + T cell populations of mice immunized with a complex antigen, killed Mycobacterium tuberculosis, using high throughput parallel sequencing of the TcRβ chain. Our initial hypothesis that immunization would induce repertoire convergence proved to be incorrect, and therefore an alternative approach was developed that allows accurate stratification of TcR repertoires and provides novel insights into the nature of CD4 + T-cell receptor recognition

Feature selection using a one dimensional naïve Bayes' classifier increases the accuracy of support vector machine classification of CDR3 repertoires.

MOTIVATION: Somatic DNA recombination, the hallmark of vertebrate adaptive immunity, has the potential to generate a vast diversity of antigen receptor sequences. How this diversity captures antigen specificity remains incompletely understood. In this study we use high throughput sequencing to compare the global changes in T cell receptor β chain complementarity determining region 3 (CDR3β) sequences following immunization with ovalbumin administered with complete Freund's adjuvant (CFA) or CFA alone. RESULTS: The CDR3β sequences were deconstructed into short stretches of overlapping contiguous amino acids. The motifs were ranked according to a one-dimensional Bayesian classifier score comparing their frequency in the repertoires of the two immunization classes. The top ranking motifs were selected and used to create feature vectors which were used to train a support vector machine. The support vector machine achieved high classification scores in a leave-one-out validation test reaching  : >90% in some cases. SUMMARY: The study describes a novel two-stage classification strategy combining a one-dimensional Bayesian classifier with a support vector machine. Using this approach we demonstrate that the frequency of a small number of linear motifs three amino acids in length can accurately identify a CD4 T cell response to ovalbumin against a background response to the complex mixture of antigens which characterize Complete Freund's Adjuvant. AVAILABILITY AND IMPLEMENTATION: The sequence data is available at www.ncbi.nlm.nih.gov/sra/?term¼SRP075893 The Decombinator package is available at github.com/innate2adaptive/Decombinator The R package e1071 is available at the CRAN repository https://cran.r-project.org/web/packages/e1071/index.html CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online