Identifying Modules of Coexpressed Transcript Units and Their Organization of Saccharopolyspora erythraea from Time Series Gene Expression Profiles

BACKGROUND: The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization. METHODOLOGY/PRINCIPAL FINDINGS: In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs) across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A), and secondary metabolism is induced when the growth is slowed down (phase B). Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery) gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected. CONCLUSIONS: This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies on other prokaryotic microorganisms

Self-Assembled Polymeric Micellar Nanoparticles as Nanocarriers for Poorly Soluble Anticancer Drug Ethaselen

A series of monomethoxy poly(ethylene glycol)-poly(lactide) (mPEG-PLA) diblock copolymers were synthesized, and mPEG-PLA micelle was fabricated and used as a nanocarrier for solubilization and delivery of a promising anticancer drug ethaselen. Ethaselen was efficiently encapsulated into the micelles by the dialysis method, and the solubility of ethaselen in water was remarkably increased up to 82 μg/mL before freeze-drying. The mean diameter of ethaselen-loaded micelles ranged from 51 to 98 nm with a narrow size distribution and depended on the length of PLA block. In vitro hemolysis study indicated that mPEG-PLA copolymers and ethaselen-loaded polymeric micelles had no hemolytic effect on the erythrocyte. The enhanced antitumor efficacy and reduced toxic effect of ethaselen-loaded polymeric micelle when compared with ethaselen-HP-β-CD inclusion were observed at the same dose in H22human liver cancer cell bearing mouse models. These suggested that mPEG-PLA polymeric micelle nanoparticles had great potential as nanocarriers for effective solubilization of poorly soluble ethaselen and further reducing side effects and toxicities of the drug

Event Timing in Associative Learning: From Biochemical Reaction Dynamics to Behavioural Observations

Associative learning relies on event timing. Fruit flies for example, once trained with an odour that precedes electric shock, subsequently avoid this odour (punishment learning); if, on the other hand the odour follows the shock during training, it is approached later on (relief learning). During training, an odour-induced Ca++ signal and a shock-induced dopaminergic signal converge in the Kenyon cells, synergistically activating a Ca++-calmodulin-sensitive adenylate cyclase, which likely leads to the synaptic plasticity underlying the conditioned avoidance of the odour. In Aplysia, the effect of serotonin on the corresponding adenylate cyclase is bi-directionally modulated by Ca++, depending on the relative timing of the two inputs. Using a computational approach, we quantitatively explore this biochemical property of the adenylate cyclase and show that it can generate the effect of event timing on associative learning. We overcome the shortage of behavioural data in Aplysia and biochemical data in Drosophila by combining findings from both systems

Profiles of Small Non-Coding RNAs in Schistosoma japonicum during Development

Schistosomiasis, a debilitating disease, caused by agents of the genus Schistosoma afflicts more than 200 million people worldwide. Schistosomes could serve as an interesting model to explore gene regulation due to its evolutional position, complex life cycle and sexual dimorphism. We previously indicated that sncRNA profile in the parasite S. japonicum was developmentally regulated in hepatic and adult stages. In this study, we systematically investigated mircoRNA (miRNA) and endogenous siRNA (endo-siRNA) profile in this parasite in more detailed developmental stages (cercariae, lung-stage schistosomula, separated adult worms, and liver tissue-trapped eggs) using high-throughput RNA sequencing technology. We observed that the ratio of miRNAs to endo-siRNAs was dynamically changed throughout different developmental stages of the parasite. MiRNAs were expressed dominantly in cercariae, while endo-siRNAs accumulated in adult female worms and hepatic eggs. We demonstrated that miRNAs were mostly derived from intergenic regions whereas siRNAs were mostly derived from transposable elements. We also annotated miRNAs and siRNAs with stage- and gender- biased expression. Our findings would facilitate to understand the gene regulation mechanism of this parasite and discover novel targets for anti-parasite drugs

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe