Sex-Biased Expression of MicroRNAs in Schistosoma mansoni

Schistosomiasis is an important neglected tropical disease caused by digenean helminth parasites of the genus Schistosoma. Schistosomes are unusual in that they are dioecious and the adult worms live in the blood system. MicroRNAs play crucial roles during gene regulation and are likely to be important in sex differentiation in dioecious species. Here we characterize 112 microRNAs from adult Schistosoma mansoni individuals, including 84 novel microRNA families, and investigate the expression pattern in different sexes. By deep sequencing, we measured the relative expression levels of conserved and newly identified microRNAs between male and female samples. We observed that 13 microRNAs exhibited sex-biased expression, 10 of which are more abundant in females than in males. Sex chromosomes showed a paucity of female-biased genes, as predicted by theoretical evolutionary models. We propose that the recent emergence of separate sexes in Schistosoma had an effect on the chromosomal distribution and evolution of microRNAs, and that microRNAs are likely to participate in the sex differentiation/maintenance process

At the Biological Modeling and Simulation Frontier

We provide a rationale for and describe examples of synthetic modeling and simulation (M&S) of biological systems. We explain how synthetic methods are distinct from familiar inductive methods. Synthetic M&S is a means to better understand the mechanisms that generate normal and disease-related phenomena observed in research, and how compounds of interest interact with them to alter phenomena. An objective is to build better, working hypotheses of plausible mechanisms. A synthetic model is an extant hypothesis: execution produces an observable mechanism and phenomena. Mobile objects representing compounds carry information enabling components to distinguish between them and react accordingly when different compounds are studied simultaneously. We argue that the familiar inductive approaches contribute to the general inefficiencies being experienced by pharmaceutical R&D, and that use of synthetic approaches accelerates and improves R&D decision-making and thus the drug development process. A reason is that synthetic models encourage and facilitate abductive scientific reasoning, a primary means of knowledge creation and creative cognition. When synthetic models are executed, we observe different aspects of knowledge in action from different perspectives. These models can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete while moving us closer to personalized medicine

Long non-coding RNAs and enhancer RNAs regulate the lipopolysaccharide-induced inflammatory response in human monocytes

Early reports indicate that long non-coding RNAs (lncRNAs) are novel regulators of biological responses. However, their role in the human innate immune response, which provides the initial defence against infection, is largely unexplored. To address this issue, here we characterize the long non-coding RNA transcriptome in primary human monocytes using RNA sequencing. We identify 76 enhancer RNAs (eRNAs), 40 canonical lncRNAs, 65 antisense lncRNAs and 35 regions of bidirectional transcription (RBT) that are differentially expressed in response to bacterial lipopolysaccharide (LPS). Crucially, we demonstrate that knockdown of nuclear-localized, NF-κB-regulated, eRNAs (IL1β-eRNA) and RBT (IL1β-RBT46) surrounding the IL1β locus, attenuates LPS-induced messenger RNA transcription and release of the proinflammatory mediators, IL1β and CXCL8. We predict that lncRNAs can be important regulators of the human innate immune response