The design and analysis of microarray experiments: applications in parasitology

The core mouse response to infection by neospora caninum defined by gene set enrichment analyses

In this study, the BALB/c and Qs mouse responses to infection by the parasite Neospora caninum were investigated in order to identify host response mechanisms. Investigation was done using gene set (enrichment) analyses of microarray data. GSEA, MANOVA, Romer, subGSE and SAM-GS were used to study the contrasts Neospora strain type, Mouse type (BALB/c and Qs) and time post infection (6 hours post infection and 10 days post infection). The analyses show that the major signal in the core mouse response to infection is from time post infection and can be defined by gene ontology terms Protein Kinase Activity, Cell Proliferation and Transcription Initiation. Several terms linked to signaling, morphogenesis, response and fat metabolism were also identified. At 10 days post infection, genes associated with fatty acid metabolism were identified as up regulated in expression. The value of gene set (enrichment) analyses in the analysis of microarray data is discussed.

Transcriptome data analysis for cell culture processes

In the past decade, DNA microarrays have fundamentally changed the way we study complex biological systems. By measuring the expression levels of thousands of transcripts, the paradigm of studying organisms has shifted from focusing on the local phenomena of a few genes to surveying the whole genome. DNA microarrays are used in a variety of ways, from simple comparisons between two samples to more intricate time-series studies. With the large number of genes being studied, the dimensionality of the problem is inevitably high. The analysis of microarray data thus requires specific approaches. In the case of time-series microarray studies, data analysis is further complicated by the correlation between successive time points in a series.In this review, we survey the methodologies used in the analysis of static and time-series microarray data, covering data pre-processing, identification of differentially expressed genes, profile pattern recognition, pathway analysis, and network reconstruction. When available, examples of their use in mammalian cell cultures are presented.

Microarray analyses of mouse responses to infection by Neospora caninum identifies disease associated cellular pathways in the host response

Neospora caninum is a coccidian cyst-forming parasite found in a wide range of host species such as mice, dogs and cattle. The development of methods such as vaccines to prevent abortion and fetal loss due to neosporosis would be greatly assisted by further knowledge on immunity and host responses to infection. In this study we used microarray technology to investigate the protective host responses occurring at 6h post infection in the spleen of mice infected with a prototype live N. caninum vaccine. Naive non-pregnant mice were infected with the NC-Nowra isolate as such infections are known to induce protective host responses that will prevent transplacental transmission of a challenge given using pregnancy. The expression data was analysed by SAM (significance of microarrays), ANOVA and clustering methods. Gene lists were investigated for enrichment of gene ontology terms by functional annotation using hypergeometric tests. The results show that Qs and BALB/c mice infected with NC-Nowra differ in their transcriptional responses to infection and these affect a wide range of biological and molecular processes. Transcriptional changes in the Jak-STAT signaling pathway (as well as Irf and other IFN-γ regulated molecules such as GTPases) confirmed the influence of IFN-γ in the mouse response to N. caninum. Gene ontology analyses also assigned some of the molecules involved to well known disease pathways associated with cancer, Parkinson's and Alzheimer's diseases, which were linked to the cell cycle, mitochondrial electron transport chain and coupled proton transport pathways amongst others. Although infection of mice with NC-Nowra causes little or no signs of clinical disease, the molecular functions, processes and pathways identified through these studies clearly warrant further investigation for their role in the development of protective immunity as well as pathogenesis. These studies therefore provide new, exciting leads by which to study neosporosis.

Transcriptomics tool for the human Schistosoma blood flukes using microarray gene expression profiling

We report the design, fabrication, and validation of a microarray covering the majority of the Schistosoma japonicum and Schistosoma mansoni transcriptomes. The oligonucleotide microarray contains 12,166 S. mansoni and 7055 S. japonicum target sequences. A confidence threshold of <or=0.001 (P value) was used in all analyses. The cross hybridization potential of the microarray was representative of 10,362 probes detected in both channels, while 12,052 probes hybridised to S. japonicum and 11,254 probes hybridised to S. mansoni. Differential hybridisation consisted of 3422 probes to S. mansoni mRNA and 3103 probes to S. japonicum mRNA. Important biological functions, such as transport, metabolism, immune evasion and host-parasite immunological interplay, cell communication, and sexual maturation are represented on this microarray. This is the first microarray commercially manufactured for studying schistosomes, and the large size and verified quality of the resource demonstrate its power for characterising the schistosome transcriptome.

A comparison of match-only algorithms for the analysis of Plasmodium falciparum oligonucleotide arrays

This study is motivated by two data sets which employ a custom Plasmodium falciparum version of the Affymetrix GeneChip, containing only perfect match (PM) oligonucleotides. A PM-only chip cannot be analysed using the standard Affymetrix-supplied software. We compared the performance of three match-only algorithms on these data: the Match Only Integral Distribution (MOID) algorithm, Robust Multichip Analysis (RMA), and the Model Based Expression Index (MBEI). We validated the differential expression of several genes using quantitative reverse transcriptase-PCR. We also performed a comparison using two publicly available 'benchmarking' data sets: the Latin Square spike-in data set generated by Affymetrix, and the Gene Logic dilution series. Since we know what the true fold changes are in these special data sets, they are helpful for assessment of expression algorithms.

Transcriptional profiling using a novel cDNA array identifies differential gene expression during porcine embryo elongation

A novel porcine cDNA array, containing 1,015 PCR products selected for embryonic expression, was used for transcriptional profiling of conceptuses at four stages of peri-implantation development. Total conceptus RNA from small spherical, large spherical, tubular, and filamentous stages was amplified, converted to cDNA, and hybridized to membranes. Initially, normalized signal intensities obtained using cDNA from total RNA or from amplified RNA were compared. Uniform distribution of P-values associated with t-tests conducted for each gene indicated no evidence that amplification introduced bias. Analysis of data obtained by using amplified targets and the novel array identified genes differentially expressed across stages. Such genes were identified by testing for significant stage effects in gene-specific mixed models. A total of nine genes were declared differentially expressed. Six of the nine genes had P-values less than 0.001, and a false discovery rate of approximately 17% was associated with this significance threshold. Two out of six genes were significant when using the Bonferroni method to control the probability of one or more false positives. The other three genes had P-values between 0.001 and 0.01 and exhibited differences greater than twofold between stages. All four genes selected for confirmation (steroidogenic acute regulatory protein, interleukin 1 beta, transforming growth factor beta 3, and thymosin beta 10) were shown to be differentially expressed by using quantitative real time RT-PCR. Our study shows that RNA amplification is useful for transcriptional profiling with limiting porcine embryonic RNA, and that this novel targeted array can detect differential gene expression during trophoblastic elongation. Finally, our results contribute to an increased understanding of the temporal patterns of expression of known genes controlling conceptus development, as well as identify novel genes also differentially regulated during implantation.