The quality of RNA is crucial in gene expression experiments. RNA degradation interferes in the measurement of gene expression, and in this context, microRNA quantification can lead to an incorrect estimation. In the present study, two different RNA isolation methods were used to perform microRNA microarray analysis on porcine brain tissue. One method is a phenol-guanidine isothiocyanate-based procedure that permits isolation of total RNA. The second method, miRVana™ microRNA isolation, is column based and recovers the small RNA fraction alone. We found that microarray analyses give different results that depend on the RNA fraction used, in particular because some microRNAs appear very sensitive to the RNA isolation method. We conclude that precautions need to be taken when comparing microarray studies based on RNA isolated with different methods.
Microarray technology changed the landscape of contemporary life sciences by providing vast amounts of expression data. Researchers are building up repositories of experiment results with various conditions and samples which serve the scientific community as a precious resource. Ensuring that the sample is of high quality is of utmost importance to this effort. The task is complicated by the fact that in many cases datasets lack information concerning pre-experimental quality assessment. Transcription profiling of tissue samples may be invalidated by an error caused by heterogeneity of the material. The risk of tissue cross contamination is especially high in oncological studies, where it is often difficult to extract the sample. Therefore, there is a need of developing a method detecting tissue contamination in a post-experimental phase. We propose Microarray Inspector: customizable, user-friendly software that enables easy detection of samples containing mixed tissue types. The advantage of the tool is that it uses raw expression data files and analyses each array independently. In addition, the system allows the user to adjust the criteria of the analysis to conform to individual needs and research requirements. The final output of the program contains comfortable to read reports about tissue contamination assessment with detailed information about the test parameters and results. Microarray Inspector provides a list of contaminant biomarkers needed in the analysis of adipose tissue contamination. Using real data (datasets from public repositories) and our tool, we confirmed high specificity of the software in detecting contamination. The results indicated the presence of adipose tissue admixture in a range from approximately 4% to 13% in several tested surgical samples.
Gene expression profiling is one of the most explored methods for studying cancers and microarray data repositories have become a rich and important resource. The most common human cancers develop in organs that are walled by smooth muscles. The only method of sample extraction free of unintentional contamination with surrounding tissue is microdissection. Nevertheless, such an approach is implemented infrequently. In the light of the above, there is a possibility of smooth muscle contamination in a large portion of publicly available data. In this study, 2292 publicly available microarrays were analysed to develop a simple screening method for detecting smooth muscle contamination. Microarray Inspector software was used to perform the tests since it has the unique ability to use many selected genes and probesets in a single group as a tissue definition. Furthermore, the test was dataset-independent. Two strategies of tissue definition were explored and compared. The first one depended on Tissue Specific Genes Database (TiSGeD) and BioGPS web resources, which themselves were based on meta-analysis of thousands of microarrays. The second method was based on a differential gene expression analysis of a few hundred preselected arrays. The comparison of the two methods proved the latter to be superior. Among the tested samples of undefined contamination, nearly half were identified to possibly contain significant smooth muscle traces. The obtained results equip researches with a simple method of examining microarray data for smooth muscle contamination. The presented work serves as an example of how to create definitions when searching for other possible contaminations.
Neuroblastoma is the most common extra-cranial solid tumor of childhood and it is characterized by the presence of a glycosphingolipid, GD2 ganglioside. Monoclonal antibodies targeting the antigen are currently tested in clinical trials. Additionally, several research groups reported results revealing that ganglioside-specific antibodies can affect cellular signaling and cause direct cytotoxicity against tumor cells. To shed more light on gene expression signatures of tumor cells, we used microarrays to analyze changes of transcriptome in IMR-32 human neuroblastoma cell cultures treated with doxorubicin (DOX) or a mouse monoclonal antibody binding to GD2 ganglioside 14G2a (mAb) for 24 h. The obtained results highlight that disparate cellular pathways are regulated by doxorubicin and 14G2a. Next, we used RT-PCR to verify mRNA levels of selected DOX-responsive genes such as RPS27L, PPM1D, SESN1, CDKN1A, TNFSF10B, and 14G2a-responsive genes such as SVIL, JUN, RASSF6, TLX2, ID1. Then, we applied western blot and analyzed levels of RPS27L, PPM1D, sestrin 1 proteins after DOX-treatment. Additionally, we aimed to measure effects of doxorubicin and topotecan (TPT) and 14G2a on expression of a novel human NDUFAF2 gene encoding for mimitin protein (MYC-induced mitochondrial protein) and correlate it with expression of the MYCN gene. We showed that expression of both genes was concomitantly decreased in the 14G2a-treated IMR-32 cells after 24 h and 48 h. Our results extend knowledge on gene expression profiles after application of DOX and 14G2a in our model and reveal promising candidates for further research aimed at finding novel anti-neuroblastoma targets.
Cholesteatoma is described as cystic lesion consisting of keratinizing squamous cell epithelium, filed with keratin debris, surrounded by inflammatory fibrous tissue, gradually expanding in the middle ear and causing destruction of neighboring bones. This paper presents brief review of existing hypotheses explaining its etiology in the light of the researches using high throughput, “omics”, technologies of molecular biology. Classic theories of pathogenesis of acquired cholesteatoma as: immigration, squamous metaplasia, basal cell hyperplasia or invagination theory have not been able to explain fully all pathological processes observed in cholesteatoma tissue. This also concerns the newer concepts that cholesteatoma is a result of mucosal traction generated by interaction of migrating opposing surfaces, a natural attempt by the body to cure the underlying inflammation in the cavity or chronic wound healing process triggered by micro defects in the basement membrane of the epithelium in the retraction pocket. Introduction of high-throughput, “omics”, technologies of molecular biology to the studies under cholesteatoma pathogenesis allowed identification of cholesteatoma-related gene expression signatures using full-genome microarrays as well as proteomic analysis of cholesteatoma. Those studies confirmed known pathological processes observed in cholesteatoma tissue such as: high proliferative activity, decreased signal transduction, active immunological response, alterations in the extracellular matrix, increased expression of proinflammatory cytokines, neovascularization and may others. This technique allows precise and complete insight into molecular mechanisms in those processes. However, it is still unknown what is the cause that trigger epithelial hyperplasia, inhibited migration and inflammatory response in the preexisting retraction pocket.
Lipid multilayer microarrays are a promising approach to miniaturize laboratory procedures by taking advantage of the microscopic compartmentalization capabilities of lipids. Here, we demonstrate a new method to pattern lipid multilayers on surfaces based on solvent evaporation along the edge where a stencil contacts a surface called evaporative edge lithography (EEL). As an example of an application of this process, we use EEL to make microarrays suitable for a cell-based migration assay. Currently existing cell migration assays require a separate compartment for each drug which is dissolved at a single concentration in solution. An advantage of the lipid multilayer microarray assay is that multiple compounds can be tested on the same surface. We demonstrate this by testing the effect of two different lipophilic drugs, Taxol and Brefeldin A, on collective cell migration into an unpopulated area. This particular assay should be scalable to test of 2000 different lipophilic compounds or dosages on a standard microtiter plate area, or if adapted for individual cell migration, it would allow for high-throughput screening of more than 50,000 compounds per plate.
Two-color DNA microarrays are commonly used for the analysis of global gene expression. They provide information on relative abundance of thousands of mRNAs. However, the generated data need to be normalized to minimize systematic variations so that biologically significant differences can be more easily identified. A large number of normalization procedures have been proposed and many softwares for microarray data analysis are available. Here, we have applied two normalization methods (median and loess) from two packages of microarray data analysis softwares. They were examined using a sample data set. We found that the number of genes identified as differentially expressed varied significantly depending on the method applied. The obtained results, i.e. lists of differentially expressed genes, were consistent only when we used median normalization methods. Loess normalization implemented in the two software packages provided less coherent and for some probes even contradictory results. In general, our results provide an additional piece of evidence that the normalization method can profoundly influence final results of DNA microarray-based analysis. The impact of the normalization method depends greatly on the algorithm employed. Consequently, the normalization procedure must be carefully considered and optimized for each individual data set.
The systemic inflammatory reaction (acute phase response) is induced by many noxious stimuli but in all cases the inflammatory cytokines, such as interleukin-1-beta (IL-1β) and interleukin-6 (IL-6), are involved. Liver cell response to inflammation manifested by a characteristic change in the profile of synthesized plasma proteins (acute phase proteins) has been extensively studied. Here we describe a model system of cultured human hepatoma HepG2 cells stimulated with IL-1β to evaluate the transcriptome induced by this cytokine during 24 h of treatment. By using differential display analysis we found IL-1β-induced upregulation of several genes coding for cellular trafficking/motor proteins, proteins participating in the translation machinery or involved in posttranscription/posttranslation modifications, proteases, proteins involved in cellular metabolism, activity modulators, proteins of the cell cycle machinery and also some new proteins so far functionally not classified.
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