Pooled RNAi Screens - Technical and Biological Aspects

RNA interference (RNAi) screens have recently emerged as an exciting new tool for studying gene function in mammalian cells. In order to facilitate those studies, short hairpin RNA (shRNA) expression libraries covering the entire human transcriptome have become commercially available. To make use of the full potential of such large-scale shRNA libraries, microarray-based methods have been developed to analyze complex pooled RNAi screens. In terms of microarray analysis, different strategies have been pursued by different research groups, largely influenced by the employed shRNA library. In this review, we compare the three major shRNA expression libraries with a focus on their suitability for a microarray-based analysis of pooled screens. We analyze and compare approaches previously used to perform pooled RNAi screens and point out their advantages as well as limitations

Microarray study of gene expression in uterine leiomyoma

Uterine leiomyoma is a most common benign neoplasm in women of reproductive age. It arises from the myometrial compartment of the uterus and may transform in some cases to a malignant phenotype. Aim: To identify the genes involved in pathogenesis of uterine leiomyoma. Methods: We have studied differential gene expression in matched tissue samples of leiomyoma and normal myometrium from the very same people utilizing a cDNA microarray screening method. We also compared our results with previously published microarray data to identify the overlapping gene alterations. Results: Based on this comparison we can divide genes deregulated in our study into two groups. The first group comprises genes that to our knowledge have not been previously reported as deregulated in fibroids: CLDN1, FGF7 (KGF), HNRPM, ISOC1, MAGEC1 (CT7), MAPK12, RFC, TIE1, TNFRSF21 (DR6). The second group consists of genes identified also in previous studies: CCND1 (BCL1), CDKN1A (P21), CRABP2, FN1 and SOX4 (EVI16). In our study FN1 was the most up-regulated gene, occupying the place between the myometrium and fibroids ranging from 2.07 to 3.64, depending of the probe molecule used for detection. Conclusions: Newly identified genes may be regarded as potential diagnostic or prognostic markers of uterine leiomyoma and thus may be very useful as new therapeutic candidates.Лейомиома матки является одним из наиболее распространенных доброкачественных новообразований женской репродуктивной сферы. В некоторых случаях отмечают злокачественную трансформацию данного новообразования. Цель: идентификация генов, вовлеченных в патогенез лейомиомы. Методы: проведен анализ дифференциальной экспрессии генов в образцах лейомиомы и нормального миометрия одних и тех же пациентов методом ДНК-биочип-гибридизации и проведено сравнение полученных результатов с данными, опубликованными ранее. Результаты: выявлены различия в экспрессии ряда генов, которые можно разделить на две группы. Впервые выявлена повышенная экспрессия генов CLDN1, FGF7 (KGF), HNRPM, ISOC1, MAGEC1 (CT7), MAPK12, RFC, TIE1 и TNFRSF21 (DR6) в ткани лейомиомы по сравнению с нормальным миометрием. Ко второй группе можно отнести гены CCND1 (BCL1), CDKN1A (P21), CRABP2, FN1 и SOX4 (EVI16), уже упоминавшиеся в связи с патогенезом лейомиомы в ряде предыдущих исследований. Наибольшим изменением уровня экспрессии (в 2,07–3,64 раз в зависимости от зонда) характеризовался ген фибронектина FN1. Выводы: идентифицированные гены могут рассматриваться в качестве потенциальных диагностических и прогностических маркеров лейомиомы матки

Multiplex approaches in protein microarray technology

The success of genome sequencing projects has provided the basis for systematic analysis of protein function and has led to a shift from the description of single molecules to the characterization of complex samples. Such a task would not be possible without the provision of appropriate high-throughput technologies, such as protein microarray technology. In addition, the increasing number of samples necessitates the adaptation of such technologies to a multiplex format. This review will discuss protein microarray technology in the context of multiplex analysis and highlight its current prospects and limitations

Corrigendum to "Functional analysis of <i>Trypanosoma brucei</i> PUF1" [Mol. Biochem. Parasitol. 150 (2006) 340–349]

No abstract available

Glucose triggers different global responses in yeast, depending on the strength of the signal, and transiently stabilizes ribosomal protein mRNAs

Glucose exerts profound effects upon yeast physiology. In general, the effects of high glucose concentrations (0.1%. We also show that cytoplasmic ribosomal protein mRNAs are transiently stabilized by glucose, indicating that both transcriptional and post-transcriptional mechanisms combine to accelerate the accumulation of ribosomal protein mRNAs. Presumably, this facilitates rapid ribosome biogenesis after exposure to glucose. However, our data indicate that yeast activates ribosome biogenesis only when sufficient glucose is available to make this metabolic investment worthwhile. In contrast, the regulation of metabolic functions in response to very low glucose signals presumably ensures that yeast can exploit even minute amounts of this preferred nutrient

Monitoring the Switch from Housekeeping to Pathogen Defense Metabolism in Arabidopsis thaliana Using cDNA Arrays

Plants respond to pathogen attack by deploying several defense reactions. Some rely on the activation of preformed components, whereas others depend on changes in transcriptional activity. Using cDNA arrays comprising 13,000 unique expressed sequence tags, changes in the transcriptome of Arabidopsis thaliana were monitored after attempted infection with the bacterial plant pathogen Pseudomonas syringae pv. tomato carrying the avirulence gene avrRpt2. Sampling at four time points during the first 24 h after infiltration revealed significant changes in the steady state transcript levels of ~650 genes within 10 min and a massive shift in gene expression patterns by 7 h involving ~2,000 genes representing many cellular processes. This shift from housekeeping to defense metabolism results from changes in regulatory and signaling circuits and from an increased demand for energy and biosynthetic capacity in plants fighting off a pathogenic attack. Concentrating our detailed analysis on the genes encoding enzymes in glycolysis, the Krebs cycle, the pentose phosphate pathway, the biosynthesis of aromatic amino acids, phenylpropanoids, and ethylene, we observed interesting differential regulation patterns. Furthermore, our data showed potentially important changes in areas of metabolism, such as the glyoxylate metabolism, hitherto not suspected to be components of plant defense