Differential regulation of the attachment of KSHV infected human B cells to ECM by KSHV encoded gB and cellular alpha-V integrins

Kaposi’s sarcoma-associated herpesvirus (KSHV) has two modes replication: latent and lytic replication. Reactivation from latency is dictated, in part, by the cell cycle. Herein, we have attempted to delineate the importance of cell cycle in KSHV pathogenesis by exploring the expression pattern of cell surface receptors during different phases of the cell cycle. αV integrin expression is augmented during S phase in fibroblasts, epithelial, and KSHV infected cells. Using a Matrigel system, we pioneer the concept that KSHV infected primary effusion lymphoma (PEL) cells can attach to extracellular matrix proteins. This attachment is mediated primarily via αV integrins or virally encoded gB, and occurs preferentially in cells from S phase or cells from S phase actively supporting a lytic infection, respectively. Such an ability of infected B cells to attach to endothelial cells may also aid in the dissemination of infection. The keystone of this work is that for the first time, we describe the ability of KSHV infected B cells to preferentially use cellular (αV) or viral (gB) receptors to specifically bind cells, depending upon the stage of the cell cycle and infection. Originally published Cellular Microbiology, Vol. 10, No. 7, July 200

miRGator v2.0 : an integrated system for functional investigation of microRNAs

miRGator is an integrated database of microRNA (miRNA)-associated gene expression, target prediction, disease association and genomic annotation, which aims to facilitate functional investigation of miRNAs. The recent version of miRGator v2.0 contains information about (i) human miRNA expression profiles under various experimental conditions, (ii) paired expression profiles of both mRNAs and miRNAs, (iii) gene expression profiles under miRNA-perturbation (e.g. miRNA knockout and overexpression), (iv) known/predicted miRNA targets and (v) miRNA-disease associations. In total, >8000 miRNA expression profiles, ∼300 miRNA-perturbed gene expression profiles and ∼2000 mRNA expression profiles are compiled with manually curated annotations on disease, tissue type and perturbation. By integrating these data sets, a series of novel associations (miRNA–miRNA, miRNA–disease and miRNA–target) is extracted via shared features. For example, differentially expressed genes (DEGs) after miRNA knockout were systematically compared against miRNA targets. Likewise, differentially expressed miRNAs (DEmiRs) were compared with disease-associated miRNAs. Additionally, miRNA expression and disease-phenotype profiles revealed miRNA pairs whose expression was regulated in parallel in various experimental and disease conditions. Complex associations are readily accessible using an interactive network visualization interface. The miRGator v2.0 serves as a reference database to investigate miRNA expression and function (http://miRGator.kobic.re.kr)

Multimodal imaging of pancreatic beta cells in vivo by targeting transmembrane protein 27 (TMEM27)

Aims/hypothesis: Non-invasive diagnostic tools specific for pancreatic beta cells will have a profound impact on our understanding of the pathophysiology of metabolic diseases such as diabetes. The objective of this study was to use molecular imaging probes specifically targeting beta cells on human samples and animal models using state-of-the-art imaging modalities (fluorescence and PET) with preclinical and clinical perspective. Methods: We generated a monoclonal antibody, 8/9-mAb, targeting transmembrane protein 27 (TMEM27; a surface N-glycoprotein that is highly expressed on beta cells), compared its expression in human and mouse pancreas, and demonstrated beta cell-specific binding in both. In vivo imaging was performed in mice with subcutaneous insulinomas overexpressing the human TMEM27 gene, or transgenic mice with beta cell-specific hTMEM27 expression under the control of rat insulin promoter (RIP-hTMEM27-tg), using fluorescence and radioactively labelled antibody, followed by tissue ex vivo analysis and fluorescence microscopy. Results: Fluorescently labelled 8/9-mAb showed beta cell-specific staining on human and mouse pancreatic sections. Real-time PCR on islet cDNA indicated about tenfold higher expression of hTMEM27 in RIP-hTMEM27-tg mice than in humans. In vivo fluorescence and PET imaging in nude mice with insulinoma xenografts expressing hTMEM27 showed high 8/9-mAb uptake in tumours after 72h. Antibody homing was also observed in beta cells of RIP-hTMEM27-tg mice by in vivo fluorescence imaging. Ex vivo analysis of intact pancreas and fluorescence microscopy in beta cells confirmed these findings. Conclusions/interpretation: hTMEM27 constitutes an attractive target for in vivo visualisation of pancreatic beta cells. Studies in mouse insulinoma models and mice expressing hTMEM27 demonstrate the feasibility of beta cell-targeted in vivo imaging, which is attractive for preclinical investigations and holds potential in clinical diagnostic

Vir-Mir db: prediction of viral microRNA candidate hairpins

MicroRNAs have been found in various organisms and play essential roles in gene expression regulation of many critical cellular processes. Large-scale computational prediction of miRNAs has been conducted for many organisms using known genomic sequences; however, there has been no such effort for the thousands of known viral genomes. Some viruses utilize existing host cellular pathways for their own benefit. Furthermore, viruses are capable of encoding miRNAs and using them to repress host genes. Thus, identifying potential miRNAs in all viral genomes would be valuable to virologists who study virus–host interactions. Based on our previously reported hairpin secondary structure and feature selection filters, we have examined the 2266 available viral genome sequences for putative miRNA hairpins and identified 33 691 hairpin candidates in 1491 genomes. Evaluation of the system performance indicated that our discovery pipeline exhibited 84.4% sensitivity. We established an interface for users to query the predicted viral miRNA hairpins based on taxonomic classification, and a host target gene prediction service based on the RNAhybrid program and the 3′-UTR gene sequences of human, mouse, rat, zebrafish, rice and Arabidopsis. The viral miRNA prediction database (Vir-Mir) can be accessed via http://alk.ibms.sinica.edu.tw

The Impact of miRNA Target Sites in Coding Sequences and in 3′UTRs

Animal miRNAs are a large class of small regulatory RNAs that are known to directly and negatively regulate the expression of a large fraction of all protein encoding genes. The identification and characterization of miRNA targets is thus a fundamental problem in biology. miRNAs regulate target genes by binding to 3′ untranslated regions (3′UTRs) of target mRNAs, and multiple binding sites for the same miRNA in 3′UTRs can strongly enhance the degree of regulation. Recent experiments have demonstrated that a large fraction of miRNA binding sites reside in coding sequences. Overall, miRNA binding sites in coding regions were shown to mediate smaller regulation than 3′UTR binding. However, possible interactions between target sites in coding sequences and 3′UTRs have not been studied. Using transcriptomics and proteomics data of ten miRNA mis-expression experiments as well as transcriptome-wide experimentally identified miRNA target sites, we found that mRNA and protein expression of genes containing target sites both in coding regions and 3′UTRs were in general mildly but significantly more regulated than those containing target sites in 3′UTRs only. These effects were stronger for conserved target sites of length 7–8 nt in coding regions compared to non-conserved sites. Combined with our other finding that miRNA target sites in coding regions are under negative selection, our results shed light on the functional importance of miRNA targeting in coding regions

MicroRNAs in cardiac arrhythmia: DNA sequence variation of MiR-1 and MiR-133A in long QT syndrome.

Long QT syndrome (LQTS) is a genetic cardiac condition associated with prolonged ventricular repolarization, primarily a result of perturbations in cardiac ion channels, which predisposes individuals to life-threatening arrhythmias. Using DNA screening and sequencing methods, over 700 different LQTS-causing mutations have been identified in 13 genes worldwide. Despite this, the genetic cause of 30-50% of LQTS is presently unknown. MicroRNAs (miRNAs) are small (∼ 22 nucleotides) noncoding RNAs which post-transcriptionally regulate gene expression by binding complementary sequences within messenger RNAs (mRNAs). The human genome encodes over 1800 miRNAs, which target about 60% of human genes. Consequently, miRNAs are likely to regulate many complex processes in the body, indeed aberrant expression of various miRNA species has been implicated in numerous disease states, including cardiovascular diseases. MiR-1 and MiR-133A are the most abundant miRNAs in the heart and have both been reported to regulate cardiac ion channels. We hypothesized that, as a consequence of their role in regulating cardiac ion channels, genetic variation in the genes which encode MiR-1 and MiR-133A might explain some cases of LQTS. Four miRNA genes (miR-1-1, miR-1-2, miR-133a-1 and miR-133a-2), which encode MiR-1 and MiR-133A, were sequenced in 125 LQTS probands. No genetic variants were identified in miR-1-1 or miR-133a-1; but in miR-1-2 we identified a single substitution (n.100A> G) and in miR-133a-2 we identified two substitutions (n.-19G> A and n.98C> T). None of the variants affect the mature miRNA products. Our findings indicate that sequence variants of miR-1-1, miR-1-2, miR-133a-1 and miR-133a-2 are not a cause of LQTS in this cohort

Tension and Robustness in Multitasking Cellular Networks

Cellular networks multitask by exhibiting distinct, context-dependent dynamics. However, network states (parameters) that generate a particular dynamic are often sub-optimal for others, defining a source of “tension” between them. Though multitasking is pervasive, it is not clear where tension arises, what consequences it has, and how it is resolved. We developed a generic computational framework to examine the source and consequences of tension between pairs of dynamics exhibited by the well-studied RB-E2F switch regulating cell cycle entry. We found that tension arose from task-dependent shifts in parameters associated with network modules. Although parameter sets common to distinct dynamics did exist, tension reduced both their accessibility and resilience to perturbation, indicating a trade-off between “one-size-fits-all” solutions and robustness. With high tension, robustness can be preserved by dynamic shifting of modules, enabling the network to toggle between tasks, and by increasing network complexity, in this case by gene duplication. We propose that tension is a general constraint on the architecture and operation of multitasking biological networks. To this end, our work provides a framework to quantify the extent of tension between any network dynamics and how it affects network robustness. Such analysis would suggest new ways to interfere with network elements to elucidate the design principles of cellular networks

Raman tweezers provide the fingerprint of cells supporting the late stages of KSHV reactivation

Kaposi's sarcoma-associated herpesvirus (KSHV) has both latent and lytic phases of replication. The molecular switch that triggers a reactivation is still unclear. Cells from S phase of cell cycle provide apt conditions for an active reactivation. In order to specifically delineate the Raman spectra of cells supporting KSHV reactivation, we followed a novel approach where cells were sorted based on the state of infection (latent Vs lytic) by a flow cytometer and then analyzed by the Raman tweezers. The Raman bands at 785, 813, 830, 1095, and 1128 cm-1 are specifically altered in cells supporting KSHV reactivation. These 5 peaks make up the Raman fingerprint of cells supporting KSHV reactivation. The physiological relevance of the changes in these peaks with respect to KSHV reactivation is discussed in the following report. Originally published Journal of Cellular and Molecular Medicine, Vol. 13, No. 8b, Aug 200

Experimental strategies for microRNA target identification

MicroRNAs (miRNAs) are important regulators of eukaryotic gene expression in most biological processes. They act by guiding the RNAi-induced silencing complex (RISC) to partially complementary sequences in target mRNAs to suppress gene expression by a combination of translation inhibition and mRNA decay. The commonly accepted mechanism of miRNA targeting in animals involves an interaction between the 5′-end of the miRNA called the ‘seed region’ and the 3′ untranslated region (3′-UTR) of the mRNA. Many target prediction algorithms are based around such a model, though increasing evidence demonstrates that targeting can also be mediated through sites other than the 3′-UTR and that seed region base pairing is not always required. The power and validity of such in silico data can be therefore hindered by the simplified rules used to represent targeting interactions. Experimentation is essential to identify genuine miRNA targets, however many experimental modalities exist and their limitations need to be understood. This review summarizes and critiques the existing experimental techniques for miRNA target identification

Synthetic lethality: a framework for the development of wiser cancer therapeutics

The challenge in medical oncology has always been to identify compounds that will kill, or at least tame, cancer cells while leaving normal cells unscathed. Most chemotherapeutic agents in use today were selected primarily for their ability to kill rapidly dividing cancer cells grown in cell culture and in mice, with their selectivity determined empirically during subsequent animal and human testing. Unfortunately, most of the drugs developed in this way have relatively low therapeutic indices (low toxic dose relative to the therapeutic dose). Recent advances in genomics are leading to a more complete picture of the range of mutations, both driver and passenger, present in human cancers. Synthetic lethality provides a conceptual framework for using this information to arrive at drugs that will preferentially kill cancer cells relative to normal cells. It also provides a possible way to tackle 'undruggable' targets. Two genes are synthetically lethal if mutation of either gene alone is compatible with viability but simultaneous mutation of both genes leads to death. If one is a cancer-relevant gene, the task is to discover its synthetic lethal interactors, because targeting these would theoretically kill cancer cells mutant in the cancer-relevant gene while sparing cells with a normal copy of that gene. All cancer drugs in use today, including conventional cytotoxic agents and newer 'targeted' agents, target molecules that are present in both normal cells and cancer cells. Their therapeutic indices almost certainly relate to synthetic lethal interactions, even if those interactions are often poorly understood. Recent technical advances enable unbiased screens for synthetic lethal interactors to be undertaken in human cancer cells. These approaches will hopefully facilitate the discovery of safer, more efficacious anticancer drugs that exploit vulnerabilities that are unique to cancer cells by virtue of the mutations they have accrued during tumor progression