Transcriptome of the dead: characterisation of immune genes and marker development from necropsy samples in a free-ranging marine mammal

Background Transcriptomes are powerful resources, providing a window on the expressed portion of the genome that can be generated rapidly and at low cost for virtually any organism. However, because many genes have tissue-specific expression patterns, developing a complete transcriptome usually requires a 'discovery pool' of individuals to be sacrificed in order to harvest mRNA from as many different types of tissue as possible. This hinders transcriptome development in large, charismatic and endangered species, many of which stand the most to gain from such approaches. To circumvent this problem in a model pinniped species, we 454 sequenced cDNA from testis, heart, spleen, intestine, kidney and lung tissues obtained from nine adult male Antarctic fur seals (Arctocephalus gazella) that died of natural causes at Bird Island, South Georgia. Results After applying stringent quality control criteria based on length and annotation, we obtained 12,397 contigs which, in combination with 454 data previously obtained from skin, gave a total of 23,096 unique contigs. Homology was found to 77.0% of dog (Canis lupus familiaris) transcripts, suggesting that the combined assembly represents a substantial proportion of this species' transcriptome. Moreover, only 0.5% of transcripts revealed sequence similarity to bacteria, implying minimal contamination, and the percentage of transcripts involved in cell death was low at 2.6%. Transcripts with immune-related annotations were almost five-fold enriched relative to skin and represented 13.2% of all spleen-specific contigs. By reference to the dog, we also identified transcripts revealing homology to five class I, ten class II and three class III genes of the Major Histocompatibility Complex and derived the putative genomic distribution of 17,121 contigs, 2,119 in silico mined microsatellites and 9,382 single nucleotide polymorphisms. Conclusions Our findings suggest that transcriptome development based on samples collected post mortem may greatly facilitate genomic studies, not only of marine mammals but also more generally of species that are of conservation concern

DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells

BACKGROUND: The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs). RESULTS: Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DC-ATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules. CONCLUSIONS: The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies

Prediction of peptides binding to MHC class I and II alleles by temporal motif mining

Background: MHC (Major Histocompatibility Complex) is a key player in the immune response of most vertebrates. The computational prediction of whether a given antigenic peptide will bind to a specific MHC allele is important in the development of vaccines for emerging pathogens, the creation of possibilities for controlling immune response, and for the applications of immunotherapy. One of the problems that make this computational prediction difficult is the detection of the binding core region in peptides, coupled with the presence of bulges and loops causing variations in the total sequence length. Most machine learning methods require the sequences to be of the same length to successfully discover the binding motifs, ignoring the length variance in both motif mining and prediction steps. In order to overcome this limitation, we propose the use of time-based motif mining methods that work position-independently. Results: The prediction method was tested on a benchmark set of 28 different alleles for MHC class I and 27 different alleles for MHC class II. The obtained results are comparable to the state of the art methods for both MHC classes, surpassing the published results for some alleles. The average prediction AUC values are 0.897 for class I, and 0.858 for class II. Conclusions: Temporal motif mining using partial periodic patterns can capture information about the sequences well enough to predict the binding of the peptides and is comparable to state of the art methods in the literature. Unlike neural networks or matrix based predictors, our proposed method does not depend on peptide length and can work with both short and long fragments. This advantage allows better use of the available training data and the prediction of peptides of uncommon lengths

A study of the reduction of simulation modeling development time

This paper presents new ideas dealing with simulation model development that are derived from the principles of lean manufacturing, for example, the concept of treating the time that is spent in production activities as lead-time, and the feasibility of reducing the lead-time through different mechanisms, which are presented in a framework [44]. One of the main obstacles in developing simulation model is time. Simulation lead-time is composed of nine steps of simulation model development. These steps are: problem definition, establishing boundaries, establishing variables, data collection, model development, verification & validation, documentation, experimentation, and implementation. This paper presents the idea of treating the time spent in simulation modeling development as a lead-time. At the same time, it presents a new framework to reduce lead-time, which has never been addressed before. A new framework to reduce the simulation modeling development long lead-time similar to the Toyota production framework for reducing the production lead-time will be presented in this paperThe framework developed as a result of an actual simulation case study, which took place at a local company, and which took a very long lead-time. The framework was composed of different steps, techniques, and mechanisms that should reduce simulation modeling development lead-time every time a simulation project is conducted. One of the goals of this framework is to reduce one of the main obstacles of simulation model, which is the long lead-time. One of the new mechanisms that is presented in this framework is a geographical distributed communication tool, which is called NetMeeting. This tool is an application of the concept of distributed and Web-Based simulations

Emerging Vaccine Informatics

Vaccine informatics is an emerging research area that focuses on development and applications of bioinformatics methods that can be used to facilitate every aspect of the preclinical, clinical, and postlicensure vaccine enterprises. Many immunoinformatics algorithms and resources have been developed to predict T- and B-cell immune epitopes for epitope vaccine development and protective immunity analysis. Vaccine protein candidates are predictable in silico from genome sequences using reverse vaccinology. Systematic transcriptomics and proteomics gene expression analyses facilitate rational vaccine design and identification of gene responses that are correlates of protection in vivo. Mathematical simulations have been used to model host-pathogen interactions and improve vaccine production and vaccination protocols. Computational methods have also been used for development of immunization registries or immunization information systems, assessment of vaccine safety and efficacy, and immunization modeling. Computational literature mining and databases effectively process, mine, and store large amounts of vaccine literature and data. Vaccine Ontology (VO) has been initiated to integrate various vaccine data and support automated reasoning

Computational characterization of the peptidome in transporter associated with antigen processing (TAP)-deficient cells

The transporter associated with antigen processing (TAP) is a key element of the major histocompatibility complex (MHC) class I antigen processing and presentation pathway. Nonfunctional TAP complexes impair the translocation of cytosol-derived proteolytic peptides to the endoplasmic reticulum lumen. This drastic reduction in the available peptide repertoire leads to a significant decrease in MHC class I cell surface expression. Using mass spectrometry, different studies have analyzed the cellular MHC class I ligandome from TAP-deficient cells, but the analysis of the parental proteins, the source of these ligands, still deserves an in-depth analysis. In the present report, several bioinformatics protocols were applied to investigate the nature of parental proteins for the previously identified TAP-independent MHC class I ligands. Antigen processing in TAP-deficient cells mainly focused on small, abundant or highly integral transmembrane proteins of the cellular proteome. This process involved abundant proteins of the central RNA metabolism. In addition, TAP-independent ligands were preferentially cleaved from the N- and C-terminal ends with respect to the central regions of the parental proteins. The abundance of glycine, proline and aromatic residues in the C-terminal sequences from TAP-independently processed proteins allows the accessibility and specificity required for the proteolytic activities that generates the TAP-independent ligandome. This limited proteolytic activity towards a set of preferred proteins in a TAP-negative environment would therefore suffice to promote the survival of TAP-deficient individuals.This work was supported by the Spanish Ministry of Economy (MINECO/FEDER) grant SAF2014-58052 and Acción Estratégica en Salud 2019 to DL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptS

Exploring and linking biomedical resources through multidimensional semantic spaces

Background The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). Results This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Conclusions Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for integration, exploration, and analysis tasks. Results over a real scenario demonstrate the viability and usefulness of the approach, as well as the quality of the generated multidimensional semantic spaces

Performance Analysis of Live-Virtual-Constructive and Distributed Virtual Simulations: Defining Requirements in Terms of Temporal Consistency

This research extends the knowledge of live-virtual-constructive (LVC) and distributed virtual simulations (DVS) through a detailed analysis and characterization of their underlying computing architecture. LVCs are characterized as a set of asynchronous simulation applications each serving as both producers and consumers of shared state data. In terms of data aging characteristics, LVCs are found to be first-order linear systems. System performance is quantified via two opposing factors; the consistency of the distributed state space, and the response time or interaction quality of the autonomous simulation applications. A framework is developed that defines temporal data consistency requirements such that the objectives of the simulation are satisfied. Additionally, to develop simulations that reliably execute in real-time and accurately model hierarchical systems, two real-time design patterns are developed: a tailored version of the model-view-controller architecture pattern along with a companion Component pattern. Together they provide a basis for hierarchical simulation models, graphical displays, and network I/O in a real-time environment. For both LVCs and DVSs the relationship between consistency and interactivity is established by mapping threads created by a simulation application to factors that control both interactivity and shared state consistency throughout a distributed environment

Human neutrophil clearance of bacterial pathogens triggers anti-microbial gamma delta T cell responses in early infection

Human blood Vc9/Vd2 T cells, monocytes and neutrophils share a responsiveness toward inflammatory chemokines and are rapidly recruited to sites of infection. Studying their interaction in vitro and relating these findings to in vivo observations in patients may therefore provide crucial insight into inflammatory events. Our present data demonstrate that Vc9/Vd2 T cells provide potent survival signals resulting in neutrophil activation and the release of the neutrophil chemoattractant CXCL8 (IL-8). In turn, Vc9/Vd2 T cells readily respond to neutrophils harboring phagocytosed bacteria, as evidenced by expression of CD69, interferon (IFN)-c and tumor necrosis factor (TNF)-a. This response is dependent on the ability of these bacteria to produce the microbial metabolite (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate (HMB-PP), requires cell-cell contact of Vc9/Vd2 T cells with accessory monocytes through lymphocyte function-associated antigen-1 (LFA-1), and results in a TNF-a dependent proliferation of Vc9/Vd2 T cells. The antibiotic fosmidomycin, which targets the HMB-PP biosynthesis pathway, not only has a direct antibacterial effect on most HMB-PP producing bacteria but also possesses rapid anti-inflammatory properties by inhibiting cd T cell responses in vitro. Patients with acute peritoneal-dialysis (PD)-associated bacterial peritonitis – characterized by an excessive influx of neutrophils and monocytes into the peritoneal cavity – show a selective activation of local Vc9/Vd2 T cells by HMB-PP producing but not by HMB-PP deficient bacterial pathogens. The cd T celldriven perpetuation of inflammatory responses during acute peritonitis is associated with elevated peritoneal levels of cd T cells and TNF-a and detrimental clinical outcomes in infections caused by HMB-PP positive microorganisms. Taken together, our findings indicate a direct link between invading pathogens, neutrophils, monocytes and microbe-responsive cd T cells in early infection and suggest novel diagnostic and therapeutic approaches.Martin S. Davey, Chan-Yu Lin, Gareth W. Roberts, Sinéad Heuston, Amanda C. Brown, James A. Chess, Mark A. Toleman, Cormac G.M. Gahan, Colin Hill, Tanya Parish, John D. Williams, Simon J. Davies, David W. Johnson, Nicholas Topley, Bernhard Moser and Matthias Eber