Virulence typing of Escherichia coli using microarrays

We describe a microarray based broad-range screening technique for Escherichia coli virulence typing. Gene probes were amplified by PCR from a plasmid bank of characterised E. coli virulence genes and were spotted onto a glass slide to form an array of capture probes. Genomic DNA from E. coli strains which were to be tested for the presence of these virulence gene sequences was labelled with fluorescent cyanine dyes by random amplification and then hybridised against the array of probes. The hybridisation, washing and data analysis conditions were optimised for glass slides, and the applicability of the method for identifying the presence of the virulence genes was determined using reference strains and clinical isolates. It was found to be a sensitive screening method for detecting virulence genes, and a powerful tool for determining the pathotype of E. coli. It will be possible to expand and automate this microarray technique to make it suitable for rapid and reliable diagnostic screening of bacterial isolates.

Comparison of amplification methods for transcriptomic analyses of low abundance prokaryotic RNA sources

Microarrays have established as instrumental for bacterial detection, identification, and genotyping as well as for transcriptomic studies. For gene expression analyses using limited numbers of bacteria (derived from in vivo or ex vivo origin, for example), RNA amplification is often required prior to labeling and hybridization onto microarrays. Evaluation of the fidelity of the amplification methods is crucial for the robustness and reproducibility of microarray results. We report here the first utilization of random primers and the highly processive Phi29 phage polymerase to amplify material for transcription profiling analyses. We compared two commercial amplification methods (GenomiPhi and MessageAmp kits) with direct reverse-transcription as the reference method, focusing on the robustness of mRNA quantification using either microarrays or quantitative RT-PCR. Both amplification methods using either poly-A tailing followed by in vitro transcription, or direct strand displacement polymerase, showed appreciable linearity. Strand displacement technique was particularly affordable compared to in vitro transcription-based (IVT) amplification methods and consisted in a single tube reaction leading to high amplification yields. Real-time measurements using low-, medium-, and highly expressed genes revealed that this simple method provided linear amplification with equivalent results in terms of relative messenger abundance as those obtained by conventional direct reverse-transcription.

A novel universal DNA labeling and amplification system for rapid microarray-based detection of 117 antibiotic resistance genes in Gram-positive bacteria.

A rapid and simple DNA labeling system has been developed for disposable microarrays and has been validated for the detection of 117 antibiotic resistance genes abundant in Gram-positive bacteria. The DNA was fragmented and amplified using phi-29 polymerase and random primers with linkers. Labeling and further amplification were then performed by classic PCR amplification using biotinylated primers specific for the linkers. The microarray developed by Perreten et al. (Perreten, V., Vorlet-Fawer, L., Slickers, P., Ehricht, R., Kuhnert, P., Frey, J., 2005. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J.Clin.Microbiol. 43, 2291-2302.) was improved by additional oligonucleotides. A total of 244 oligonucleotides (26 to 37 nucleotide length and with similar melting temperatures) were spotted on the microarray, including genes conferring resistance to clinically important antibiotic classes like β-lactams, macrolides, aminoglycosides, glycopeptides and tetracyclines. Each antibiotic resistance gene is represented by at least 2 oligonucleotides designed from consensus sequences of gene families. The specificity of the oligonucleotides and the quality of the amplification and labeling were verified by analysis of a collection of 65 strains belonging to 24 species. Association between genotype and phenotype was verified for 6 antibiotics using 77 Staphylococcus strains belonging to different species and revealed 95% test specificity and a 93% predictive value of a positive test. The DNA labeling and amplification is independent of the species and of the target genes and could be used for different types of microarrays. This system has also the advantage to detect several genes within one bacterium at once, like in Staphylococcus aureus strain BM3318, in which up to 15 genes were detected. This new microarray-based detection system offers a large potential for applications in clinical diagnostic, basic research, food safety and surveillance programs for antimicrobial resistance.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Her2 amplification is significantly more frequent in lymph node metastases from urothelial bladder cancer than in the primary tumours

Her2, an alias for the protein of v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian), might be an attractive therapeutic target in metastasising bladder cancer. Genotype and phenotype of primary tumours and their metastases may differ.

Dimethyloxalylglycine stabilizes HIF-1α in cultured human endothelial cells and increases random-pattern skin flap survival in vivo

The goal of this study was to evaluate in vitro and in vivo the effects of up-regulation of the proangiogenic hypoxia inducible factor (HIF)-1α induced by dimethyloxalylglycine on endothelial cell cultures and on skin flap survival.