Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data

Background: MicroRNAs (miRNAs) are short, non-coding RNA regulators of protein coding genes. miRNAs play a very important role in diverse biological processes and various diseases. Many algorithms are able to predict miRNA genes and their targets, but their transcription regulation is still under investigation. It is generally believed that intragenic miRNAs (located in introns or exons of protein coding genes) are co-transcribed with their host genes and most intergenic miRNAs transcribed from their own RNA polymerase II (Pol II) promoter. However, the length of the primary transcripts and promoter organization is currently unknown. Methodology: We performed Pol II chromatin immunoprecipitation (ChIP)-chip using a custom array surrounding regions of known miRNA genes. To identify the true core transcription start sites of the miRNA genes we developed a new tool (CPPP). We showed that miRNA genes can be transcribed from promoters located several kilobases away and that their promoters share the same general features as those of protein coding genes. Finally, we found evidence that as many as 26% of the intragenic miRNAs may be transcribed from their own unique promoters. Conclusion: miRNA promoters have similar features to those of protein coding genes, but miRNA transcript organization is more complex. © 2009 Corcoran et al

Peptide Substrates for Rho-Associated Kinase 2 (Rho-Kinase 2/ROCK2)

Peptide substrates sensitive for a certain protein kinase could be important for new-drug development and to understand the mechanism of diseases. Rho-associated kinase (Rho-kinase/ROCK) is a serine/threonine kinase, and plays an important part in cardiovascular disease, migration and invasion of tumor cells, and in neurological disorders. The purpose of this study was to find substrates with high affinity and sensitivity for ROCK2. We synthesized 136 peptide substrates from protein substrates for ROCK2 with different lengths and charged peptides. Incorporation of 32P [counts per minute (CPM)] for each peptide substrate was determined by the radiolabel assay using [γ-32P]ATP. When the top five peptide substrates showing high CPMs (R4, R22, R133, R134, and R135) were phosphorylated by other enzymes (PKA, PKCα, and ERK1), R22, R133, and R135 displayed the highest CPM level for ROCK2 compared with other enzymes, whereas R4 and R134 showed similar CPM levels for ROCK2 and PKCα. We hypothesize that R22, R133, and R135 can be useful peptide substrates for ROCK2

Computational Design of Auxotrophy-Dependent Microbial Biosensors for Combinatorial Metabolic Engineering Experiments

Combinatorial approaches in metabolic engineering work by generating genetic diversity in a microbial population followed by screening for strains with improved phenotypes. One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via http://www.cs.technion.ac.il/~tomersh/tools)

A qualitative investigation of lived experiences of long-term health condition management with people who are food insecure.

Background: As more people are living with one or more chronic health conditions, supporting patients to become activated, self-managers of their conditions has become a key health policy focus both in the UK and internationally. There is also growing evidence in the UK that those with long term health conditions have an increased risk of being food insecure. While international evidence indicates that food insecurity adversely affects individual's health condition management capability, little is known about how those so affected manage their condition(s) in this context. An investigation of lived experience of health condition management was undertaken with food insecure people living in north east Scotland. The study aimed to explore the challenges facing food insecure people in terms of, i. their self-care condition management practices, and ii. disclosing and discussing the experience of managing their condition with a health care professional, and iii. Notions of the support they might wish to receive from them. Methods: Twenty in-depth interviews were conducted with individuals attending a food bank and food pantry in north east Scotland. Interview audio recordings were fully transcribed and thematically analysed. Results: Individuals reporting multiple physical and mental health conditions, took part in the study. Four main themes were identified i.e.: 1. food practices, trade-offs and compromises, that relate to economic constraints and lack of choice; 2. illness experiences and food as they relate to physical and mental ill-health; 3. (in) visibility of participants' economic vulnerability within health care consultations; and 4. perceptions and expectations of the health care system. Conclusions: This study, the first of its kind in the UK, indicated that participants' health condition management aspirations were undermined by the experience of food insecurity, and that their health care consultations in were, on the whole, devoid of discussions of those challenges. As such, the study indicated practical and ethical implications for health care policy, practice and research associated with the risk of intervention-generated health inequalities that were suggested by this study. Better understanding is needed about the impact of household food insecurity on existing ill health, wellbeing and health care use across the UK

Sildenafil, a phosphodiesterase type 5 inhibitor, enhances the antidepressant activity of amitriptyline but not desipramine, in the forced swim test in mice

The cholinergic theory of depression highlights the involvement of muscarinic acetylcholine receptors in the neurobiology of mood disorders. The present study was designed to investigate the effect of sildenafil, a phosphodiesterase type 5 inhibitor which exhibits cholinomimetic properties, alone and in combination with scopolamine in the forced swim test in mice. Moreover, we assessed the ability of sildenafil to modify the antidepressant activity of two tricyclic antidepressants with distinct cholinolytic activity, amitriptyline and desipramine. Swim sessions were conducted by placing mice in glass cylinders filled with water for 6 min and the duration of behavioral immobility during the last 4 min of the test was evaluated. Locomotor activity was measured with photoresistor actimeters. To evaluate the potential pharmacokinetic interaction between amitriptyline and sildenafil, brain and serum concentrations of amitriptyline were determined by HPLC. Sildenafil (1.25–20 mg/kg) as well as scopolamine (0.5 mg/kg) and its combination with sildenafil (1.25 mg/kg) did not affect the total immobility time duration. However, joint administration of scopolamine with sildenafil at doses of 2.5 and 5 mg/kg significantly reduced immobility time as compared to control group. Moreover, co-administration of scopolamine with sildenafil at the highest dose (5 mg/kg) significantly decreased immobility time as compared to scopolamine-treated group. Sildenafil (1.25, 2.5 and 5 mg/kg) significantly enhanced the antidepressant activity of amitriptyline (5 mg/kg). No changes in anti-immobility action of desipramine (20 mg/kg) in combination with sildenafil (5, 10 and 20 mg/kg) were observed. Sildenafil did not affect amitriptyline level in both brain and serum. In conclusion, the present study suggests that sildenafil may enhance the activity of antidepressant drugs which exhibit cholinolytic activity

RNA-Seq Analyses Generate Comprehensive Transcriptomic Landscape and Reveal Complex Transcript Patterns in Hepatocellular Carcinoma

RNA-seq is a powerful tool for comprehensive characterization of whole transcriptome at both gene and exon levels and with a unique ability of identifying novel splicing variants. To date, RNA-seq analysis of HBV-related hepatocellular carcinoma (HCC) has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from HCC patients on Solexa/Illumina GAII platform. On average, about 21.6 million sequencing reads and 10.6 million aligned reads were obtained for samples sequenced on each lane, which was able to identify >50% of all the annotated genes for each sample. Furthermore, we identified 1,378 significantly differently expressed genes (DEGs) and 24, 338 differentially expressed exons (DEEs). Comprehensive function analyses indicated that cell growth-related, metabolism-related and immune-related pathways were most significantly enriched by DEGs, pointing to a complex mechanism for HCC carcinogenesis. Positional gene enrichment analysis showed that DEGs were most significantly enriched at chromosome 8q21.3–24.3. The most interesting findings were from the analysis at exon levels where we characterized three major patterns of expression changes between gene and exon levels, implying a much complex landscape of transcript-specific differential expressions in HCC. Finally, we identified a novel highly up-regulated exon-exon junction in ATAD2 gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of HBV-related HCC transcriptome including exon level expression changes and novel splicing variants, which illustrated the power of RNA-seq and provided important clues for understanding the molecular mechanisms of HCC pathogenesis at system-wide levels

Estimating the Global Clinical Burden of Plasmodium falciparum Malaria in 2007

Simon Hay and colleagues derive contemporary estimates of the global clinical burden of Plasmodium falciparum malaria (the deadliest form of malaria) using cartography-based techniques

The Impact of Multifunctional Genes on "Guilt by Association" Analysis

Many previous studies have shown that by using variants of “guilt-by-association”, gene function predictions can be made with very high statistical confidence. In these studies, it is assumed that the “associations” in the data (e.g., protein interaction partners) of a gene are necessary in establishing “guilt”. In this paper we show that multifunctionality, rather than association, is a primary driver of gene function prediction. We first show that knowledge of the degree of multifunctionality alone can produce astonishingly strong performance when used as a predictor of gene function. We then demonstrate how multifunctionality is encoded in gene interaction data (such as protein interactions and coexpression networks) and how this can feed forward into gene function prediction algorithms. We find that high-quality gene function predictions can be made using data that possesses no information on which gene interacts with which. By examining a wide range of networks from mouse, human and yeast, as well as multiple prediction methods and evaluation metrics, we provide evidence that this problem is pervasive and does not reflect the failings of any particular algorithm or data type. We propose computational controls that can be used to provide more meaningful control when estimating gene function prediction performance. We suggest that this source of bias due to multifunctionality is important to control for, with widespread implications for the interpretation of genomics studies