Systematic MicroRNA Analysis Identifies ATP6V0C as an Essential Host Factor for Human Cytomegalovirus Replication

Recent advances in microRNA target identification have greatly increased the number of putative targets of viral microRNAs. However, it is still unclear whether all targets identified are biologically relevant. Here, we use a combined approach of RISC immunoprecipitation and focused siRNA screening to identify targets of HCMV encoded human cytomegalovirus that play an important role in the biology of the virus. Using both a laboratory and clinical strain of human cytomegalovirus, we identify over 200 putative targets of human cytomegalovirus microRNAs following infection of fibroblast cells. By comparing RISC-IP profiles of miRNA knockout viruses, we have resolved specific interactions between human cytomegalovirus miRNAs and the top candidate target transcripts and validated regulation by western blot analysis and luciferase assay. Crucially we demonstrate that miRNA target genes play important roles in the biology of human cytomegalovirus as siRNA knockdown results in marked effects on virus replication. The most striking phenotype followed knockdown of the top target ATP6V0C, which is required for endosomal acidification. siRNA knockdown of ATP6V0C resulted in almost complete loss of infectious virus production, suggesting that an HCMV microRNA targets a crucial cellular factor required for virus replication. This study greatly increases the number of identified targets of human cytomegalovirus microRNAs and demonstrates the effective use of combined miRNA target identification and focused siRNA screening for identifying novel host virus interactions

Sequence Relationships among C. elegans, D. melanogaster and Human microRNAs Highlight the Extensive Conservation of microRNAs in Biology

microRNAs act in a prevalent and conserved post-transcriptional gene regulatory mechanism that impacts development, homeostasis and disease, yet biological functions for the vast majority of miRNAs remain unknown. Given the power of invertebrate genetics to promote rapid evaluation of miRNA function, recently expanded miRNA identifications (miRBase 10.1), and the importance of assessing potential functional redundancies within and between species, we evaluated miRNA sequence relationships by 5′ end match and overall homology criteria to compile a snapshot overview of miRNA families within the C. elegans and D. melanogaster genomes that includes their identified human counterparts. This compilation expands literature documentation of both the number of families and the number of family members, within and between nematode and fly models, and highlights sequences conserved between species pairs or among nematodes, flies and humans. Themes that emerge include the substantial potential for functional redundancy of miRNA sequences within species (84/139 C. elegans miRNAs and 70/152 D. melanogaster miRNAs share significant homology with other miRNAs encoded by their respective genomes), and the striking extent to which miRNAs are conserved across species—over half (73/139) C. elegans miRNAs share sequence homology with miRNAs encoded also in both fly and human genomes. This summary analysis of mature miRNA sequence relationships provides a quickly accessible resource that should facilitate functional and evolutionary analyses of miRNAs and miRNA families

A Bounding Technique for Probabilistic PERT

Part 3: Collaborative Networks and Project ManagementInternational audienceBounding time distributions has been an effective way of improvements of the original PERT method. Analytical enhancement of PERT is often an effective time bounding approach. However, one thing that is missing today is a combination of time distributions which parameters can be effectively obtained empirically and the effective bounding technique for them. We aim at addressing this gap and suggest Cornish-Fisher expansion (CFE) to compute time bounds in formal models like the classical PERT.We argue that CFE allows us to evaluate analytically approximate time bounds easily without resort to simulations. This bounding approach is useful in case of complex distribution functions of task durations, because analytical derivation of project completion time distribution is tedious. Our example shows CFE usage for uniform time distributions and comparison with time bounds of classical PERT