Epidemiological evidence from the current outbreak of Zika virus (ZIKV) and recent studies in animal models indicate a strong causal link between ZIKV and microcephaly. ZIKV infection induces cell-cycle arrest and apoptosis in proliferating neural progenitors. However, the mechanisms leading to these phenotypes are still largely obscure. In this report, we explored the possible similarities between transcriptional responses induced by ZIKV in human neural progenitors and those elicited by three different genetic mutations leading to severe forms of microcephaly in mice. We found that the strongest similarity between all these conditions is the activation of common P53 downstream genes. In agreement with these observations, we report that ZIKV infection increases total P53 levels and nuclear accumulation, as well as P53 Ser15 phosphorylation, correlated with genotoxic stress and apoptosis induction. Interestingly, increased P53 activation and apoptosis are induced not only in cells expressing high levels of viral antigens but also in cells showing low or undetectable levels of the same proteins. These results indicate that P53 activation is an early and specific event in ZIKV-infected cells, which could result from cell-autonomous and/or non-cell-autonomous mechanisms. Moreover, we highlight a small group of P53 effector proteins that could act as critical mediators, not only in ZIKV-induced microcephaly but also in many genetic microcephaly syndromes.

In phagocytes, GTPases of the Rac family control crucial antimicrobial functions. The RacGAP ArhGAP15 negatively modulates Rac activity in leukocytes, but its in vivo role in innate immunity remains largely unknown. Here we show that neutrophils and macrophages derived from mice lacking ArhGAP15 presented higher Rac activity but distinct phenotypes. In macrophages, the loss of ArhGAP15 induced increased cellular elongation and membrane protrusions but did not modify chemotactic responses. Conversely, the lack of ArhGAP15 in neutrophils affected critical Rac-dependent antimicrobial functions, specifically causing enhanced chemotactic responses, straighter directional migration, amplified reactive oxygen species production, increased phagocytosis, and improved bacterial killing. In vivo, in a model of severe abdominal sepsis, these effects contributed to increase neutrophil recruitment to the site of infection, thereby limiting bacterial growth, controlling infection spread, reducing systemic inflammation, and ultimately improving survival in ArhGAP15-null mice. Altogether, these results demonstrate the relevance of ArhGAP15 in the selective regulation of multiple neutrophil functions, suggesting that ArhGAP15 targeting might be beneficial in specific pathologic settings like severe sepsis.

Background: Post-transcriptional regulation is a complex mechanism that plays a central role in defining multiple cellular identities starting from a common genome. Modifications in the length of 3’UTRs have been found to play an important role in this context, since alternative 3’ UTRs could lead to differences for example in regulation by microRNAs and cellular localization of the transcripts thus altering their fate. Results: We propose a strategy to identify the genes undergoing regulation of 3’ UTR length using RNA sequencing data obtained from standard libraries, thus widely applicable to data originally obtained to perform classical differential expression analyses. We decided to exploit previously annotated APA sites from public databases, in contrast with other approaches recently proposed in which the location of the APA site is inferred from the data together with the relative abundance of the isoforms. We demonstrate the reliability of our method by comparing it to the results of other microarray based or specific RNA-seq libraries methods and show that using APA sites databases results in higher sensitivity compared to de novo site prediction approach. Conclusions: We implemented the algorithm in a Bioconductor package to facilitate its broad usage in the scientific community. The ability of this approach to detect shortening from libraries with a number of reads comparable to that needed for differential expression analyses makes it useful for investigating if alternative polyadenylation is relevant in a certain biological process without requiring specific experimental assays.

In patients with a negative prostate biopsy and persistent suspicion of prostate cancer, additional analyses such as the PCA3 score, PHI and multiparametric magnetic resonance imaging have been proposed to reduce the number of unnecessary repeat biopsies. In this study we evaluate the diagnostic accuracy of PCA3, PHI, multiparametric magnetic resonance imaging and various combinations of these tests in the repeat biopsy setting. A total of 170 patients with an initial negative prostate biopsy and persistent suspicion of prostate cancer were enrolled in this prospective study. The patients underwent measurements of the total prostate specific antigen and free prostate specific antigen rate, along with PHI, PCA3 tests and multiparametric magnetic resonance imaging before standard repeat biopsy that was performed by urologists blinded to the multiparametric magnetic resonance imaging results. Multivariate logistic regression models with various combinations of PCA3, PHI and multiparametric magnetic resonance imaging were used to identify the predictors of prostate cancer with repeat biopsy, and the performance of these models was compared using ROC curves, AUC analysis and decision curve analysis. In the ROC analysis the most significant contribution was provided by multiparametric magnetic resonance imaging (AUC 0.936), which was greater than the contribution of the PHI+PCA3 model (p <0.001). In the multivariate logistic regression analysis only multiparametric magnetic resonance imaging was a significant independent predictor of prostate cancer diagnosis with repeat biopsy (p <0.001). The results of the decision curve analysis confirmed that the most significant improvement in the net benefit was provided by multiparametric magnetic resonance imaging. Multiparametric magnetic resonance imaging provides high diagnostic accuracy in identifying patients with prostate cancer in the repeat biopsy setting compared with PCA3 and PHI.

In recent years long non coding RNAs (lncRNAs) have been the subject of increasing interest. Thanks to many recent functional studies, the existence of a large class of lncRNAs with potential regulatory functions is now widely accepted. Although an increasing number of lncRNAs is being characterized and shown to be involved in many biological processes, the functions of the vast majority lncRNA genes is still unknown. Therefore computational methods able to take advantage of the increasing amount of publicly available data to predict lncRNA functions could be very useful. Since coding genes are much better annotated than lncRNAs, we attempted to project known functional information regarding proteins onto non coding genes using the guilt by association principle: if a gene shows an expression profile that correlates with those of a set of coding genes involved in a given function, that gene is probably involved in the same function. We computed gene coexpression for 30 human tissues and 9 vertebrates and mined the resulting networks with a methodology inspired by the rank product algorithm used to identify differentially expressed genes. Using different types of reference data we can predict putative new annotations for thousands of lncRNAs and proteins, ranging from cellular localization to relevance for disease and cancer. New function of coding genes and lncRNA can be profitably predicted using tissue specific coexpression, as well as expression of orthologous genes in different species. The data are available for download and through a user-friendly web interface at www.funcpred.com .