Xenome--a tool for classifying reads from xenograft samples

Motivation Shotgun sequence read data derived from xenograft material contains a mixture of reads arising from the host and reads arising from the graft. Classifying the read mixture to separate the two allows for more precise analysis to be performed. Results We present a technique, with an associated tool Xenome, which performs fast, accurate and specific classification of xenograft-derived sequence read data. We have evaluated it on RNA-Seq data from human, mouse and human-in-mouse xenograft datasets.

Challenges in improving chronic disease survivorship outcomes using tele-health and self-managed online solutions

The advances in modern information and communication (ICT) technology continue to address the challenges and improve` health outcomes for the survivors of chronic disease such as prostate cancer. The management of survivorship is increasingly becoming an important need for the survivors to manage their chronic conditions. The technology interventions such as tele-health as well as self-managed technology applications have shown a potential to improve survivorship outcomes. However, the application of these tools should be supported by strong health economics evidence. This work discusses the challenges of technology led survivorship care models and presents an integrated approach to address these challenges.

Visual analytics for large-scale bioinformatic data sets

Rapid advances in sequencing technologies (Next Generation Sequencing or NGS) have led to a vast increase in the quantity of bioinformatics data available, with this increasing scale presenting enormous challenges to researchers seeking to identify complex interactions. This paper is concerned with the domain of transcriptional regulation, and the use of visualisation to identify relationships between specific regulatory proteins (the transcription factors or TFs) and their associated target genes (TGs). We present preliminary work from an ongoing study which aims to determine the effectiveness of different visual representations and large scale displays in supporting discovery. Following an iterative process of implementation and evaluation, representations were tested by potential users in the bioinformatics domain to determine their efficacy, and to understand better the range of ad hoc practices among bioinformatics literate users. Results from two rounds of small scale user studies are considered with initial findings suggesting that bioinformaticians require richly detailed views of TF data, features to compare TF layouts between organisms quickly, and ways to keep track of interesting data points.

Beyond blue gene: Intellectual property and bioinformatics

This article considers the challenges posed to intellectual property law by the emerging field of bioinformatics. It examines the intellectual property strategies of established biotechnology companies, such as Celera Genomics, and information technology firms entering into the marketplace, such as IBM. First this paper argues that copyright law is not irrelevant to biotechnology, as some commentators would suggest. It claims that the use of copyright law and contract law is fundamental to the protection of biomedical and genomic databases. Second this article questions whether biotechnology companies are exclusively interested in patenting genes and genetics sequences. Recent evidence suggests that biotechnology companies and IT firms are patenting bioinformatics software and Internet business methods, as well as underlying instrumentation such as microarrays and genechips. Finally, this paper evaluates what impact the privatisation of bioinformatics will have on public research and scientific communication. It raises important questions about integration, interoperability, and the risks of monopoly. It finally considers whether open source software such as the Ensembl Project and peer to peer technology like DSAS will be able to counter this trend of privatisation.

Estudo da cromatina nos sítios de fixação à matriz nuclear no domínio do gene TP53 e das modificações epigenéticas e no modelo de progressão tumoral mamária 21T

Dentre os diversos tipos de câncer agressivos, o câncer de mama é o mais comum em mulheres. Mutações hereditárias e adquiridas, assim como alterações epigenéticas atuam em sinergia na carcinogênese mamária e na progressão tumoral. A proteína P53 é uma supressora de tumor e possui uma atuação fundamental na integridade genômica. Apesar do vasto conhecimento sobre o controle da P53 a nível de proteína, ainda pouco se sabe sobre o controle transcricional do gene TP53. A série 21T, uma série de 4 linhagens celulares originadas da mama da mesma paciente, representando diferentes estágios de progressão tumoral mamária, é um eficiente modelo para investigação das alterações epigenéticas e suas influências na expressão gênica ao longo da progressão do câncer de mama. Nós analisamos a organização do domínio do gene TP53 através da técnica de arranjo de DNA, em diversas linhagens celulares de câncer de mama e linhagens controle, e realizamos uma tentativa de caracterizar estes elementos de DNA nas linhagens controle não-tumorais HB2 e MCF10A e nas tumorais MCF-7, MDA-MB-231, T47D, através dos marcadores epigenéticos de eucromatina, H4Ac, e heterocromatina, H3K9me3. Ainda analisamos a ligação de proteínas à região associada à matriz nuclear (MAR), denominada MAR 2, e a possível ligação da proteína ligante à matriz nuclear (MARBP), PARP-1, através de ensaios de gel shift (EMSA). Detectamos que na linhagem controle epitelial mamária, HB2, o gene TP53 está posicionado num domínio de DNA relativamente pequeno, aproximadamente 50 kb, delimitado por dois sítios de fixação à matriz nuclear. Interessantemente, esta estrutura de domínio se apresentou radicalmente diferente nas linhagens de câncer de mama estudadas, MCF7, T47D, MDA-MB-231 e BT474, nos quais o tamanho do domínio estudado estava aumentado e a transcrição do TP53 diminuída. Os enriquecimentos com os marcadores epigenéticos de cromatina H4Ac e H3K9me3 estão diferentemente distribuídos nas MARs nas linhagens celulares. Surpreendentemente, a MAR 2 apresentou uma ligação altamente específica, o que poderia representar a atuação de fatores transcricionais envolvidos na organização da cromatina. Através de programas de bioinformática, detectamos putativos sítios para interessantes fatores de transcrição, tais como o c/EBP-beta e c-myb, que poderiam atuar em cis regulando a expressão do gene TP53 e outros flanqueadores. Nós propusemos um modelo para a organização da cromatina na região de domínio do gene TP53 com os genes flanqueadores. Através da série 21T, detectamos uma hipometilação global genômica, nas células cancerosas 21NT e 21MT1. Uma importante diminuição da expressão global do marcador H4Ac nas células metastáticas 21MT1, foi detectada em relação às outras linhagens. Os níveis de RNAm das principais enzimas relacionadas as modificações epigenéticas são consistentes com as observadas hipometilação genômica e hipoacetilação. Através de microscopia confocal, verificamos que o marcador H4Ac está localizado, na maior parte na periferia e o marcador H3K9me3, pericêntrico nos núcleos tumorais. Por fim, verificamos que o promotor P1 do gene TP53 apresenta um estado de cromatina aberta, e a expressão do gene TP53 é similar em todas as células da série 21T.

Validation of Next Generation Sequencing Technologies in Comparison to Current Diagnostic Gold Standards for BRAF, EGFR and KRAS Mutational Analysis

Next Generation Sequencing (NGS) has the potential of becoming an important tool in clinical diagnosis and therapeutic decision-making in oncology owing to its enhanced sensitivity in DNA mutation detection, fast-turnaround of samples in comparison to current gold standard methods and the potential to sequence a large number of cancer-driving genes at the one time. We aim to test the diagnostic accuracy of current NGS technology in the analysis of mutations that represent current standard-of-care, and its reliability to generate concomitant information on other key genes in human oncogenesis. Thirteen clinical samples (8 lung adenocarcinomas, 3 colon carcinomas and 2 malignant melanomas) already genotyped for EGFR, KRAS and BRAF mutations by current standard-of-care methods (Sanger Sequencing and q-PCR), were analysed for detection of mutations in the same three genes using two NGS platforms and an additional 43 genes with one of these platforms. The results were analysed using closed platform-specific proprietary bioinformatics software as well as open third party applications. Our results indicate that the existing format of the NGS technology performed well in detecting the clinically relevant mutations stated above but may not be reliable for a broader unsupervised analysis of the wider genome in its current design. Our study represents a diagnostically lead validation of the major strengths and weaknesses of this technology before consideration for diagnostic use.

AnaBench: a Web/CORBA-based workbench for biomolecular sequence analysis

Affiliation: Département de biochimie, Faculté de médecine, Université de Montréal

Nonculture-based identification of bacteria in milk by protein fingerprinting

Traditional methods for bacterial identification include Gram staining, culturing, and biochemical assays for phenotypic characterization of the causative organism. These methods can be time-consuming because they require in vitro cultivation of the microorganisms. Recently, however, it has become possible to obtain chemical profiles for lipids, peptides, and proteins that are present in an intact organism, particularly now that new developments have been made for the efficient ionization of biomolecules. MS has therefore become the state-of-the-art technology for microorganism identification in microbiological clinical diagnosis. Here, we introduce an innovative sample preparation method for nonculture-based identification of bacteria in milk. The technique detects characteristic profiles of intact proteins (mostly ribosomal) with the recently introduced MALDI SepsityperTM Kit followed by MALDI-MS. In combination with a dedicated bioinformatics software tool for databank matching, the method allows for almost real-time and reliable genus and species identification. We demonstrate the sensitivity of this protocol by experimentally contaminating pasteurized and homogenized whole milk samples with bacterial loads of 10(3)-10(8) colony-forming units (cfu) of laboratory strains of Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus. For milk samples contaminated with a lower bacterial load (104 cfu mL-1), bacterial identification could be performed after initial incubation at 37 degrees C for 4 h. The sensitivity of the method may be influenced by the bacterial species and count, and therefore, it must be optimized for the specific application. The proposed use of protein markers for nonculture-based bacterial identification allows for high-throughput detection of pathogens present in milk samples. This method could therefore be useful in the veterinary practice and in the dairy industry, such as for the diagnosis of subclinical mastitis and for the sanitary monitoring of raw and processed milk products.

Comparison of genomic and proteomic data in recurrent airway obstruction affected horses using Ingenuity Pathway Analysis(R)

BACKGROUND: Recurrent airway obstruction (RAO) is a severe chronic respiratory disease affecting horses worldwide, though mostly in the Northern hemisphere. Environmental as well as genetic factors strongly influence the course and prognosis of the disease. Research has been focused on characterization of immunologic factors contributing to inflammatory responses, on genetic linkage analysis, and, more recently, on proteomic analysis of airway secretions from affected horses. The goal of this study was to investigate the interactions between eight candidate genes previously identified in a genetic linkage study and proteins expressed in bronchoalveolar lavage fluid (BALF) collected from healthy and RAO-affected horses. The analysis was carried out with Ingenuity Pathway Analysis(R) bioinformatics software. RESULTS: The gene with the greatest number of indirect interactions with the set of proteins identified is Interleukin 4 Receptor (IL-4R), whose protein has also been detected in BALF. Interleukin 21 receptor and chemokine (C-C motif) ligand 24 also showed a large number of interactions with the group of detected proteins. Protein products of other genes like that of SOCS5, revealed direct interactions with the IL-4R protein. The interacting proteins NOD2, RPS6KA5 and FOXP3 found in several pathways are reported regulators of the NFkappaB pathway. CONCLUSIONS: The pathways generated with IL-4R highlight possible important intracellular signaling cascades implicating, for instance, NFkappaB. Furthermore, the proposed interaction between SOCS5 and IL-4R could explain how different genes can lead to identical clinical RAO phenotypes, as observed in two Swiss Warmblood half sibling families because these proteins interact upstream of an important cascade where they may act as a functional unit.

Protein expression of Myt272-3 recombinant clone and in silico prediction of a possible vaccine candidate against Mycobacterium tuberculosis

Purpose: To investigate the expression of Myt272-3 recombinant protein and also to predict a possible protein vaccine candidate against Mycobacterium tuberculosis . Methods: Myt272-3 protein was expressed in pET30a+-Myt272-3 clone. The purity of the protein was determined using Dynabeads® His-Tag Isolation & Pulldown. Protein sequence was analysed in silico using bioinformatics software for the prediction of allergenicity, antigenicity, MHC-I and MHC-II binding, and B-cell epitope binding. Results: The candidate protein was a non-allergen with 15.19 % positive predictive value. It was also predicted to be antigenic, with binding affinity to MHC-I and MHC-II, as well as B-cell epitope binding. Conclusion: The predicted results obtained in this study provide a guide for practical design of a new tuberculosis vaccine.

Bioconductor: Open software development for computational biology and bioinformatics

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. We detail some of the design decisions, software paradigms and operational strategies that have allowed a small number of researchers to provide a wide variety of innovative, extensible, software solutions in a relatively short time. The use of an object oriented programming paradigm, the adoption and development of a software package system, designing by contract, distributed development and collaboration with other projects are elements of this project's success. Individually, each of these concepts are useful and important but when combined they have provided a strong basis for rapid development and deployment of innovative and flexible research software for scientific computation. A primary objective of this initiative is achievement of total remote reproducibility of novel algorithmic research results.

Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

NUVIEW:software for display and interactive manipulation of nucleic acid models

The NUVIEW software package allows skeletal models of any double helical nucleic acid molecule to be displayed out a graphics monitor and to apply various rotations, translations and scaling transformations interactively, through the keyboard. The skeletal model is generated by connecting any pair of representative points, one from each of the bases in the basepair. In addition to the above mentioned manipulations, the base residues can be identified by using a locator and the distance between any pair of residues can be obtained. A sequence based color coded display allows easy identification of sequence repeats, such as runs of Adenines. The real time interactive manipulation of such skeletal models for large DNA/RNA double helices, can be used to trace the path of the nucleic acid chain in three dimensions and hence get a better idea of its topology, location of linear or curved regions, distances between far off regions in the sequence etc. A physical picture of these features will assist in understanding the relationship between base sequence, structure and biological function in nucleic acids.