Comparison of Microarray Platforms for Measuring Differential MicroRNA Expression in Paired Normal/Cancer Colon Tissues

Background

Microarray technology applied to microRNA (miRNA) profiling is a promising tool in many research fields; nevertheless, independent studies characterizing the same pathology have often reported poorly overlapping results. miRNA analysis methods have only recently been systematically compared but only in few cases using clinical samples.

Methodology/Principal Findings

We investigated the inter-platform reproducibility of four miRNA microarray platforms (Agilent, Exiqon, Illumina, and Miltenyi), comparing nine paired tumor/normal colon tissues. The most concordant and selected discordant miRNAs were further studied by quantitative RT-PCR. Globally, a poor overlap among differentially expressed miRNAs identified by each platform was found. Nevertheless, for eight miRNAs high agreement in differential expression among the four platforms and comparability to qRT-PCR was observed. Furthermore, most of the miRNA sets identified by each platform are coherently enriched in data from the other platforms and the great majority of colon cancer associated miRNA sets derived from the literature were validated in our data, independently from the platform. Computational integration of miRNA and gene expression profiles suggested that anti-correlated predicted target genes of differentially expressed miRNAs are commonly enriched in cancer-related pathways and in genes involved in glycolysis and nutrient transport.

Conclusions

Technical and analytical challenges in measuring miRNAs still remain and further research is required in order to increase consistency between different microarray-based methodologies. However, a better inter-platform agreement was found by looking at miRNA sets instead of single miRNAs and through a miRNAs – gene expression integration approach.     

Some Filamentous Fungi on Grassland Vegetation from Kenya

Herbaceous plants endemic to native Kenyan grassland on the Marula Estate were assessed for their phylloplane fungal occurrence using leaf cultures on tap water agar. From 26 sampled plants, 261 fungal isolates representative of 58 genera and 92 taxa were identified. The principal filamentous fungi were of the genera: Alternaria, Bipolaris, Curvularia, Epicoccum, Fusarium, Nigrospora, Periconia, Phoma and Pithomyces. The fungal species that occurred most frequently were: Alternaria alternata aggreate (73%), Pithomyces chartarum (73%) Nigrospora sphaerica (42%), Torula herbarum (30%) and Microsphaeropsis olivacea (27%). Fungi of limited occurrence were: Didymosphaeria oblitescens, Doliomyces mysoriensis, Endophragmiella dimorphospora, Parapericonia angusii, Podospora minicaudata, Spegazzinia tessarthra, Sporormiella minima, Stagonospora vitensis, Stigmella effigurata and Truncatella conorum-piceae. It is postulated that the phylloplane of these endemic plants provides a niche for endemic fungi. This revised version was published online in June 2006 with corrections to the Cover Date.     

A novel experimental procedure based on pure shear testing of dermatome-cut samples applied to porcine skin

This paper communicates a novel and robust method for the mechanical testing of thin layers of soft biological tissues with particular application to porcine skin. The key features include the use of a surgical dermatome and the highly defined deformation kinematics achieved by pure shear testing. Thin specimens of accurate thickness were prepared using a dermatome and were subjected to different quasi-static and dynamic loading protocols. Although simple in its experimental realisation, pure shear testing provides a number of advantages over other classic uni- and biaxial testing procedures. The preparation of thin specimens of porcine dermis, the mechanical tests as well as first representative results are described and discussed in detail. The results indicate a pronounced anisotropy between the directions along and across the cleavage lines and a strain rate-dependent response.     

Group-wise ANOVA simultaneous component analysis for designed <Emphasis Type="Italic">omics</Emphasis> experiments

Introduction

Modern omics experiments pertain not only to the measurement of many variables but also follow complex experimental designs where many factors are manipulated at the same time. This data can be conveniently analyzed using multivariate tools like ANOVA-simultaneous component analysis (ASCA) which allows interpretation of the variation induced by the different factors in a principal component analysis fashion. However, while in general only a subset of the measured variables may be related to the problem studied, all variables contribute to the final model and this may hamper interpretation.

Objectives

We introduce here a sparse implementation of ASCA termed group-wise ANOVA-simultaneous component analysis (GASCA) with the aim of obtaining models that are easier to interpret.

Methods

GASCA is based on the concept of group-wise sparsity introduced in group-wise principal components analysis where structure to impose sparsity is defined in terms of groups of correlated variables found in the correlation matrices calculated from the effect matrices.

Results

The GASCA model, containing only selected subsets of the original variables, is easier to interpret and describes relevant biological processes.

Conclusions

GASCA is applicable to any kind of omics data obtained through designed experiments such as, but not limited to, metabolomic, proteomic and gene expression data.

     

Giardia cysts in wastewater treatment plants in Italy

Reductions in annual rainfall in some regions and increased human consumption have caused a shortage of water resources at the global level. The recycling of treated wastewaters has been suggested for certain domestic, industrial, and agricultural activities. The importance of microbiological and parasitological criteria for recycled water has been repeatedly emphasized. Among water-borne pathogens, protozoa of the genera Giardia and Cryptosporidium are known to be highly resistant to water treatment procedures and to cause outbreaks through contaminated raw or treated water. We conducted an investigation in four wastewater treatment plants in Italy by sampling wastewater at each stage of the treatment process over the course of 1 year. The presence of the parasites was assessed by immunofluorescence with monoclonal antibodies. While Cryptosporidium oocysts were rarely observed, Giardia cysts were detected in all samples throughout the year, with peaks observed in autumn and winter. The overall removal efficiency of cysts in the treatment plants ranged from 87.0 to 98.4%. The removal efficiency in the number of cysts was significantly higher when the secondary treatment consisted of active oxidation with O(2) and sedimentation instead of activated sludge and sedimentation (94.5% versus 72.1 to 88.0%; P = 0.05, analysis of variance). To characterize the cysts at the molecular level, the beta-giardin gene was PCR amplified, and the products were sequenced or analyzed by restriction. Cysts were typed as assemblage A or B, both of which are human pathogens, stressing the potential risk associated with the reuse of wastewater.