Comparative genomic hybridization analysis of craniopharyngiomas

Object. Craniopharyngioma is the most common childhood brain tumor and is thought to arise from embryonic remnants of the Rathke pouch. Some craniopharyngiomas are monoclonal in origin and hence presumably harbor somatic genetic alterations, although the precise molecular mechanisms involved in craniopharyngioma development are unknown. The goal of this study was to identify genetic alterations in craniopharyngiomas. Methods. To gain insight into the molecular mechanisms involved in development of these tumors, the authors analyzed nine adamantinomatous craniopharyngiomas by using comparative genomic hybridization. Six tumors (67%) displayed at least one genomic alteration, and three had six or more alterations. Only two tumors displayed a decrease in DNA copy number, and in all others an increase in DNA copy number was noted. Conclusions. The authors conclude that a subset of craniopharyngiomas consists of monoclonal tumors arising from activation of oncogenes located at specific chromosomal loci.

Optical fibre-based detection of DNA hybridization

A dual-peak LPFG (long-period fibre grating), inscribed in an optical fibre, has been employed to sense DNA hybridization in real time, over a 1 h period. One strand of the DNA was immobilized on the fibre, while the other was free in solution. After hybridization, the fibre was stripped and repeated detection of hybridization was achieved, so demonstrating reusability of the device. Neither strand of DNA was fluorescently or otherwise labelled. The present paper will provide an overview of our early-stage experimental data and methodology, examine the potential of fibre gratings for use as biosensors to monitor both nucleic acid and other biomolecular interactions and then give a summary of the theory and fabrication of fibre gratings from a biological standpoint. Finally, the potential of improving signal strength and possible future directions of fibre grating biosensors will be addressed.

Paediatric drug development:reformulation, in vitro, genomic and in vivo evaluation

Angiotensin converting enzyme (ACE) inhibitors lisinopril and ramipril were selected from EMA/480197/2010 and the potassium-sparing diuretic spironolactone was selected from the NHS specials list for November 2011 drug tariff with the view to produce oral liquid formulations providing dosage forms targeting paediatrics. Lisinopril, ramipril and spironolactone were chosen for their interaction with transporter proteins in the small intestine. Formulation limitations such as poor solubility or pH sensitivity needed consideration. Lisinopril was formulated without extensive development as drug and excipients were water soluble. Ramipril and spironolactone are both insoluble in water and strategies combating this were employed. Ramipril was successfully solubilised using low concentrations of acetic acid in a co-solvent system and also via complexation with hydroxypropyl-β-cyclodextrin. A ramipril suspension was produced to take formulation development in a third direction. Spironolactone dosages were too high for solubilisation techniques to be effective so suspensions were developed. A buffer controlled pH for the sensitive drug whilst a precisely balanced surfactant and suspending agent mix provided excellent physical stability. Characterisation, stability profiling and permeability assessment were performed following formulation development. The formulation process highlighted current shortcomings in techniques for taste assessment of pharmaceutical preparations resulting in early stage research into a novel in vitro cell based assay. The formulations developed in the initial phase of the research were used as model formulations investigating microarray application in an in vitro-in vivo correlation for carrier mediated drug absorption. Caco-2 cells were assessed following transport studies for changes in genetic expression of the ATP-binding cassette and solute carrier transporter superfamilies. Findings of which were compared to in vitro and in vivo permeability findings. It was not possible to ascertain a correlation between in vivo drug absorption and the expression of individual genes or even gene families, however there was a correlation (R2 = 0.9934) between the total number of genes with significantly changed expression levels and the predicted human absorption.

Exploring ant-based algorithms for gene expression data analysis

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.

Knowledge integration for analyzing ChIP-seq

To capture the genomic profiles for histone modification, chromatin immunoprecipitation (ChIP) is combined with next generation sequencing, which is called ChIP-seq. However, enriched regions generated from the ChIP-seq data are only evaluated on the limited knowledge acquired from manually examining the relevant biological literature. This paper proposes a novel framework, which integrates multiple knowledge sources such as biological literature, Gene Ontology, and microarray data. In order to precisely analyze ChIP-seq data for histone modification, knowledge integration is based on a unified probabilistic model. The model is employed to re-rank the enriched regions generated from peak finding algorithms. Through filtering the reranked enriched regions using some predefined threshold, more reliable and precise results could be generated. The combination of the multiple knowledge sources with the peaking finding algorithm produces a new paradigm for ChIP-seq data analysis. © (2012) Trans Tech Publications, Switzerland.

Decision support based on genomics:integration of data-and knowledge-driven reasoning

The breadth and depth of available clinico-genomic information, present an enormous opportunity for improving our ability to study disease mechanisms and meet the individualised medicine needs. A difficulty occurs when the results are to be transferred 'from bench to bedside'. Diversity of methods is one of the causes, but the most critical one relates to our inability to share and jointly exploit data and tools. This paper presents a perspective on current state-of-the-art in the analysis of clinico-genomic data and its relevance to medical decision support. It is an attempt to investigate the issues related to data and knowledge integration. Copyright © 2010 Inderscience Enterprises Ltd.

Exploring the biological basis for Salmonella persistence in food manufacturing environments

The persistence of Salmonella spp. in low moisture foods is a challenge for the food industry as despite control strategies already in place, notable outbreaks still occur. The aim of this study was to characterise isolates of Salmonella, known to be persistent in the food manufacturing environment, by comparing their microbiological characteristics with a panel of matched clinical and veterinary isolates. The gross morphology of the challenge panel was phenotypically characterised in terms of cellular size, shape and motility. In all the parameters measured, the factory isolates were indistinguishable from the human, clinical and veterinary strains. Further detailed metabolic profiling was undertaken using the biolog Microbial ID system. Multivariate analysis of the metabolic microarray revealed differences in metabolism of the factory isolate of S.Montevideo, based on its upregulated ability to utilise glucose and the sugar alcohol groups. The remainder of the serotype-matched isolates were metabolically indistinguishable. Temperature and humidity are known to influence bacterial survival and through environmental monitoring experimental parameters were defined. The results revealed Salmonella survival on stainless steel was affected by environmental temperatures that may be experienced in a food processing environment; with higher survival rates (D25=35.4) at temperatures at 25°C and lower humidity levels of 15% RH, however a rapid decline in cell count (D10=3.4) with lower temperatures of 10°C and higher humidity of 70% RH. Several resident factories strains survived in higher numbers on stainless steel (D25=29.69) compared to serotype matched clinical and veterinary isolates (D25=22.98). Factory isolates of Salmonella did not show an enhanced growth rate in comparison to serotype matched solates grown in Luria broth, Nutrient broth and M9 minimal media indicating that as an independent factor, growth was unlikely to be a major factor driving Salmonella persistence. Using a live / dead stain coupled with fluorescence microscopy revealed that when no longer culturable, isolates of S.Schwarzengrund entered into a viable nonculturable state. The biofilm forming capacity of the panel was characterised and revealed that all were able to form biofilms. None of the factory isolates showed an enhanced capability to form biofilms in comparison to serotype-matched isolates. In disinfection studies, planktonic cells were more susceptible to disinfectants than cells in biofilm and all the disinfectants tested were successful in reducing bacterial load. Contact time was one of the most important factors for reducing bacterial populations in a biofilm. The genomes of eight strains were sequenced. At the nucleotide and amino acid level the food factory isolates were similar to those of isolates from other environments; no major genomic rearrangements were observed, supporting the conclusions of the phenotypic and metabolic analysis. In conclusion, having investigated a variety of morphological, biochemical and genomic factors, it is unlikely that the persistence of Salmonella in the food manufacturing environment is attributable to a single phenotypic, metabolic or genomic factor. Whilst a combination of microbiological factors may be involved it is also possible that strain persistence in the factory environment is a consequence of failure to apply established hygiene management principles.

Label-free oligonucleotide biosensor based on dual-peak long period fiber grating

We report the simplification and development of biofunctionalization methodology based on one-step 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC)-mediated reaction. The dual-peak long period grating (dLPG) has been demonstrated its inherent ultrahigh sensitivity to refractive index (RI), achieving 50-fold improvement in RI sensitivity over a standard LPG sensor used in low RI range. With the simple and efficient immobilization of unmodified oligonucleotides on sensor surface, dLPG-based biosensor has been used to monitor the hybridization of complementary oligonucleotides showing a detectable oligonucleotide concentration of 4 nM with the advantages of label-free, real-time, and ultrahigh sensitivity.