Profiling Blood Serum Extracellular Vesicles in Plaque Psoriasis and Psoriatic Arthritis Patients Reveals Potential Disease Biomarkers

Psoriasis vulgaris (PsV) and psoriatic arthritis (PsA) are inflammatory diseases with unresolved pathophysiological aspects. Extracellular vesicles (EVs) play an important role in intercellular communication. We compared the miRNA contents and surface proteome of the EVs in the blood serum of PsV and PsA patients to healthy controls. Size-exclusion chromatography was used to isolate EVs from the blood serum of 12 PsV patients, 12 PsA patients and 12 healthy control subjects. EV samples were characterized and RNA sequencing was used to identify differentially enriched EV-bound miRNAs. We found 212 differentially enriched EV-bound miRNAs present in both PsV and PsA groups—a total of 13 miRNAs at FDR ≤ 0.05. The predicted target genes of these miRNAs were significantly related to lesser known but potentially disease-relevant pathways. The EV array revealed that PsV patient EV samples were significantly enriched with CD9 EV-marker compared to controls. Analysis of EV-bound miRNAs suggests that signaling via EVs in the blood serum could play a role in the pathophysiological processes of PsV and PsA. EVs may be able to fill the void in clinically applicable diagnostic and prognostic biomarkers for PsV and PsA.     

Cellular,Extracellular and Extracellular Vesicular miRNA Profiles of Pre-Ovulatory Follicles Indicate Signaling Disturbances in Polycystic Ovaries

Cell-free RNAs have the potential to act as a means of gene expression regulation between cells and are therefore used as diagnostic markers describing the state of tissue environment. The origin and functions of such RNAs in human ovarian follicle, the environment of oocyte maturation, are unclear. The current study investigates the difference in the microRNA profiles of fertile women and polycystic ovary syndrome (PCOS) patients in three compartments from the same preovulatory follicle: mural granulosa cells (MGC), cell-free follicular fluid (FF), and extracellular vesicles (EV) of the FF by small RNA sequencing. In silico analysis was used for the prediction and over-representation of targeted pathways for the detected microRNAs. PCOS follicles were distinguished from normal tissue by the differential expression of 30 microRNAs in MGC and 10 microRNAs in FF (FDR < 0.1) that commonly regulate cytokine signaling pathways. The concentration of EV-s was higher in the FF of PCOS patients (p = 0.04) containing eight differentially expressed microRNAs (p < 0.05). In addition, we present the microRNA profiles of MGC, FF, and EV in the fertile follicle and demonstrate that microRNAs loaded into EVs target mRNAs of distinct signaling pathways in comparison to microRNAs in FF. To conclude, the three follicular compartments play distinct roles in the signaling disturbances associated with PCOS.     

Framework for automated partitioning and execution of scientific workflows in the cloud

Scientific workflows have become a standardized way for scientists to represent a set of tasks to overcome/solve a certain scientific problem. Usually these workflows consist of numerous CPU and I/O-intensive jobs that are executed using workflow management systems (WfMS), on clouds, grids, supercomputers, etc. Previously, it was shown that using k-way partitioning to distribute a workflow’s tasks between multiple machines in the cloud reduces the overall data communication and therefore lowers the cost of the bandwidth usage. A framework was built to automate this process of partitioning and execution of any workflow submitted by a scientist that is meant to be run on Pegasus WfMS, in the cloud, with ease. The framework provisions the instances in the cloud using CloudML, configures and installs all the software needed for the execution, partitions and runs the provided scientific workflow, also showing the estimated makespan and cost.