HoughFeature,a novel method for assessing drug effects in three-color cDNA microarray experiments

Background  

Three-color microarray experiments can be performed to assess drug effects on the genomic scale. The methodology may be useful in shortening the cycle, reducing the cost, and improving the efficiency in drug discovery and development compared with the commonly used dual-color technology. A visualization tool, the hexaMplot, is able to show the interrelations of gene expressions in normal-disease-drug samples in three-color microarray data. However, it is not enough to assess the complicated drug therapeutic effects based on the plot alone. It is important to explore more effective tools so that a deeper insight into gene expression patterns can be gained with three-color microarrays.     

抗白血病药物三尖杉酯碱对L1210细胞着丝粒蛋白含量及CenpB基因表达的影响

以小鼠白血病细胞系L1210为对象,探讨了抗白血病药物三尖杉酯碱(Harringtonine,HT或Har)对细胞内着丝粒蛋白含量及着丝粒蛋白CenP基因表达的影响。间接免疫荧光(IIF)检测结果显示,随HT作用时间延长,L1210细胞着丝粒荧光斑点减弱;免疫印迹(Western blot)检测结果显示,所用的抗着丝粒抗血清(ACA 血清)能够识别8种不同分子量的着丝粒蛋白：140、80、70、56、37、34、32和17kD。受HT作用,细胞中这些着丝粒蛋白的含量不同程度地降低。在L1210细胞中识别17、80 and l40kD蛋白质的ACA抗体也分别与分子量相当的已知为CenpA、CenpB和CenpC的3种蛋白发生交叉反应。Northern和Dot blot显示,HT的抑制作用使细胞中CenpB mRNA表达水平较之对照细胞下降。结果表明,HT可(通过抑制基因mRNA的表达)降低细胞中某些着丝粒蛋白的含量;HT对细胞的杀伤及诱导凋亡作用可能与CenpB等着丝粒蛋白基因的表达抑制有关。     

Gene expression profiles in human peripheral blood mononuclear cells as biomarkers for nutritional in vitro and in vivo investigations

Identification of chemopreventive substances may be achieved by measuring biological endpoints in human cells in vitro. Since generally only tumour cells are available for such investigations, our aim was to test the applicability of peripheral blood mononuclear cells (PBMC) as an in vitro primary cell model since they mimic the human in vivo situation and are relatively easily available. Cell culture conditions were refined, and the basal variation of gene expression related to drug metabolism and stress response was determined. Results were compared with profiles of an established human colon cell line (HT29) as standard. For biomarker development of nutritional effects, PBMC and HT29 cells were treated with potentially chemopreventive substances (chrysin and butyrate), and gene expression was determined. Key results were that relevant stress response genes, such as glutathione S-transferase T2 (GSTT2) and GSTM2, were modulated by butyrate in PBMC as in HT29 cells, but the blood cells were less sensitive and responded with high individual differences. We conclude that these cells may serve as a surrogate tissue in dietary investigations and the identified differentially expressed genes have the potential to become marker genes for population studies on biological effects.     

Establishment of combined analytical method to extract the genes of interest from transcriptome data

Techniques for analyzing genome-wide expression profiles, such as the microarray technique and next-generation sequencers, have been developed. While these techniques can provide a lot of information about gene expression, selection of genes of interest is complicated because of excessive gene expression data. Thus, many researchers use statistical methods or fold change as screening tools for finding gene sets whose expression is altered between groups, which may result in the loss of important information. In the present study, we aimed to establish a combined method for selecting genes of interest with a small magnitude of alteration in gene expression by coupling with proteome analysis. We used hypercholesterolemic rats to examine the effects of a crude herbal drug on gene expression and proteome profiles. We could not select genes of interest by using standard methods. However, by coupling with proteome analysis, we found several effects of the crude herbal drug on gene expression. Our results suggest that this method would be useful in selecting gene sets with expressions that do not show a large magnitude of alteration.     

High content screening in neurodegenerative diseases

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency. Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation. For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known. As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long. There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity. This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention. High-throughput screening (HTS) is an ideal methodology to address these issues. but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties. This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS). HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS. HCS has many advantages over HTS, but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility. Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism. Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets.     

In silico prediction of drug targets in <Emphasis Type="Italic">Vibrio cholerae</Emphasis>

Identification of potential drug targets is the first step in the process of modern drug discovery, subjected to their validation and drug development. Whole genome sequences of a number of organisms allow prediction of potential drug targets using sequence comparison approaches. Here, we present a subtractive approach exploiting the knowledge of global gene expression along with sequence comparisons to predict the potential drug targets more efficiently. Based on the knowledge of 155 known virulence and their coexpressed genes mined from microarray database in the public domain, 357 coexpressed probable virulence genes for Vibrio cholerae were predicted. Based on screening of Database of Essential Genes using blastn, a total of 102 genes out of these 357 were enlisted as vitally essential genes, and hence good putative drug targets. As the effective drug target is a protein which is only present in the pathogen, similarity search of these 102 essential genes against human genome sequence led to subtraction of 66 genes, thus leaving behind a subset of 36 genes whose products have been called as potential drug targets. The gene ontology analysis using Blast2GO of these 36 genes revealed their roles in important metabolic pathways of V. cholerae or on the surface of the pathogen. Thus, we propose that the products of these genes be evaluated as target sites of drugs against V. cholerae in future investigations.     

Young intragenic miRNAs are less coexpressed with host genes than old ones: implications of miRNA-host gene coevolution

MicroRNAs (miRNAs) have emerged as key regulators of gene expression. Intragenic miRNAs account for ～50% of mammalian miRNAs. Classic studies reported that they are usually coexpressed with host genes. Here, using genome-wide miRNA and gene expression profiles from five sample sets, we show that evolutionarily conserved ('old') intragenic miRNAs tend to be coexpressed with host genes, but non-conserved ('young') ones rarely do so. This result is robust: in all sample sets, the coexpression rate of young miRNAs is significantly lower than that of conserved ones even after controlling for abundance. As a result, although young miRNAs dominate in human genome, the majority of intragenic miRNAs that show coexpression with host genes are phylogenetically old ones. For younger miRNAs, extrapolation of their expression profiles from those of their host genes should be treated with caution. We propose a model to explain this phenomenon in which the majority of young miRNAs are unlikely to be coexpressed with host genes; however, for some fraction of young miRNAs coexpression with their host genes, initially imbued by chromatin level effects, is advantageous and these are the ones likely to embed into the system and evolve ever higher levels of coexpression, possibly by evolving piggybacking mechanisms.     

Geography-Dependent Horizontal Gene Transfer from Vertebrate Predators to Their Prey

Horizontal transfer (HT) of genes between multicellular animals, once thought to be extremely rare, is being more commonly detected, but its global geographic trend and transfer mechanism have not been investigated. We discovered a unique HT pattern of Bovine-B (BovB) LINE retrotransposons in vertebrates, with a bizarre transfer direction from predators (snakes) to their prey (frogs). At least 54 instances of BovB HT were detected, which we estimate to have occurred across time between 85 and 1.3 Ma. Using comprehensive transcontinental sampling, our study demonstrates that BovB HT is highly prevalent in one geographical region, Madagascar, suggesting important regional differences in the occurrence of HTs. We discovered parasite vectors that may plausibly transmit BovB and found that the proportion of BovB-positive parasites is also high in Madagascar where BovB thus might be physically transported by parasites to diverse vertebrates, potentially including humans. Remarkably, in two frog lineages, BovB HT occurred after migration from a non-HT area (Africa) to the HT hotspot (Madagascar). These results provide a novel perspective on how the prevalence of parasites influences the occurrence of HT in a region, similar to pathogens and their vectors in some endemic diseases.     

Polymorphous granular cells in the lung of the primitive fish,the bichir Polypterus senegalus

This study describes the distribution and the coexpression of specific neurochemical markers in both neuroendocrine‐like cells (NEC‐like) and polymorphous granular cells (PGCs) that populate the mucociliated epithelium of the lung in the air‐breathing fish Polypterus senegalus, using confocal immunohistochemistry. Using confocal immunohistochemistry, we determined the coexpression of specific neurochemical markers. Colocalization studies showed that 5HT is coexpressed with calbindin and nNOS and choline acetyltransferase (ChAT) is coexpressed with nNOS in the PGCs. This study also shows for the first time the simultaneous occurrence of piscidin 1 and 5HT in the PGCs. The function of these cells being equivalent to ones found in fish gill subepithelial parenchyma is still not known. Due to the importance of piscidin 1 in local immune defence, more research is to be useful to understand a possible interaction of PGCs with immune response in the bichir lung. In fact, the capacity of PGCs to produce NO and other neuroactive substances found in immune cells of fish may represent a primitive form of immunoregulation of innate immunity and specifically antimicrobial function as NO induction and respiratory burst activity are correlated with immune response.     

Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies

MOTIVATION: In a typical gene expression profiling study, our prime objective is to identify the genes that are differentially expressed between the samples from two different tissue types. Commonly, standard analysis of variance (ANOVA)/regression is implemented to identify the relative effects of these genes over the two types of samples from their respective arrays of expression levels. But, this technique becomes fundamentally flawed when there are unaccounted sources of variability in these arrays (latent variables attributable to different biological, environmental or other factors relevant in the context). These factors distort the true picture of differential gene expression between the two tissue types and introduce spurious signals of expression heterogeneity. As a result, many genes which are actually differentially expressed are not detected, whereas many others are falsely identified as positives. Moreover, these distortions can be different for different genes. Thus, it is also not possible to get rid of these variations by simple array normalizations. This both-way error can lead to a serious loss in sensitivity and specificity, thereby causing a severe inefficiency in the underlying multiple testing problem. In this work, we attempt to identify the hidden effects of the underlying latent factors in a gene expression profiling study by partial least squares (PLS) and apply ANCOVA technique with the PLS-identified signatures of these hidden effects as covariates, in order to identify the genes that are truly differentially expressed between the two concerned tissue types. RESULTS: We compare the performance of our method SVA-PLS with standard ANOVA and a relatively recent technique of surrogate variable analysis (SVA), on a wide variety of simulation settings (incorporating different effects of the hidden variable, under situations with varying signal intensities and gene groupings). In all settings, our method yields the highest sensitivity while maintaining relatively reasonable values for the specificity, false discovery rate and false non-discovery rate. Application of our method to gene expression profiling for acute megakaryoblastic leukemia shows that our method detects an additional six genes, that are missed by both the standard ANOVA method as well as SVA, but may be relevant to this disease, as can be seen from mining the existing literature.     

Different estrogen receptor structural domains are required for estrogen- and tamoxifen-dependent anti-proliferative activity in human mammary epithelial cells expressing an exogenous estrogen receptor

Estrogen (E) inhibits the growth of both non-tumorigenic, immortal human mammary epithelial cells (HMEC) and breast cancer cells which stably express exogenous estrogen receptors (ER). The anti-estrogenic compounds 4-hydroxy-tamoxifen (HT) and ICI 164384 (ICI) have different effects on the growth of the ER-transfectants. HT is a potent growth inhibitor, while ICI has no effect by itself but is able to block the anti-proliferative effects of E and HT. In order to elucidate the mechanism by which E or HT-bound ER inhibit cell growth, we have evaluated the effects of these compounds on the growth of HMEC stably expressing ER with mutations or deletions in the N-terminal A/B domain, the DNA-binding domain (DBD), and the C-terminal ligand-binding domain. These studies revealed that E and HT require different structural domains of the ER for their anti-proliferative activities. The N-terminal A/B domain is required for HT-, but not E-dependent growth inhibition. The DNA-binding domain of the ER is not essential for HT-mediated anti-proliferative effects, but is important for E-dependent activity. The effect of ER mutations on the ligand-inducible expression of the endogenous progesterone receptor (PR) and pS2 genes was also evaluated. Neither gene was induced in the cells containing the ER mutated in the DBD, even though cell growth was inhibited. These results suggest that E and HT use different pathways to elicit their anti-proliferative effects and that this occurs via modulation of genes that are controlled by mechanisms different from those important for activation of the PR and pS2 genes.