Adenovirus small E1A directs activation of Alu transcription at YAP/TEAD- and AP-1-bound enhancers through interactions with the EP400 chromatin remodeler.

Alu retrotransposons, which form the largest family of mobile DNA elements in the human genome, have recently come to attention as a potential source of regulatory novelties, most notably by participating in enhancer function. Even though Alu transcription by RNA polymerase III is subjected to tight epigenetic silencing, their expression has long been known to increase in response to various types of stress, including viral infection. Here we show that, in primary human fibroblasts, adenovirus small e1a triggered derepression of hundreds of individual Alus by promoting TFIIIB recruitment by Alu-bound TFIIIC. Epigenome profiling revealed an e1a-induced decrease of H3K27 acetylation and increase of H3K4 monomethylation at derepressed Alus, making them resemble poised enhancers. The enhancer nature of e1a-targeted Alus was confirmed by the enrichment, in their upstream regions, of the EP300/CBP acetyltransferase, EP400 chromatin remodeler and YAP1 and FOS transcription factors. The physical interaction of e1a with EP400 was critical for Alu derepression, which was abrogated upon EP400 ablation. Our data suggest that e1a targets a subset of enhancer Alus whose transcriptional activation, which requires EP400 and is mediated by the e1a-EP400 interaction, may participate in the manipulation of enhancer activity by adenoviruses.

Time-course transcriptome analysis of a double challenge bleomycin-induced lung fibrosis rat model uncovers ECM homoeostasis-related translationally relevant genes.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is an irreversible disorder with a poor prognosis. The incomplete understanding of IPF pathogenesis and the lack of accurate animal models is limiting the development of effective treatments. Thus, the selection of clinically relevant animal models endowed with similarities with the human disease in terms of lung anatomy, cell biology, pathways involved and genetics is essential. The bleomycin (BLM) intratracheal murine model is the most commonly used preclinical assay to evaluate new potential therapies for IPF. Here, we present the findings derived from an integrated histomorphometric and transcriptomic analysis to investigate the development of lung fibrosis in a time-course study in a BLM rat model and to evaluate its translational value in relation to IPF. METHODS: Rats were intratracheally injected with a double dose of BLM (days 0-4) and sacrificed at days 7, 14, 21, 28 and 56. Histomorphometric analysis of lung fibrosis was performed on left lung sections. Transcriptome profiling by RNAseq was performed on the right lung lobes and results were compared with nine independent human gene-expression IPF studies. RESULTS: The histomorphometric and transcriptomic analyses provided a detailed overview in terms of temporal gene-expression regulation during the establishment and repair of the fibrotic lesions. Moreover, the transcriptomic analysis identified three clusters of differentially coregulated genes whose expression was modulated in a time-dependent manner in response to BLM. One of these clusters, centred on extracellular matrix (ECM)-related process, was significantly correlated with histological parameters and gene sets derived from human IPF studies. CONCLUSIONS: The model of lung fibrosis presented in this study lends itself as a valuable tool for preclinical efficacy evaluation of new potential drug candidates. The main finding was the identification of a group of persistently dysregulated genes, mostly related to ECM homoeostasis, which are shared with human IPF.

Time-resolved transcriptomic profiling of the developing rabbit's lungs: impact of premature birth and implications for modelling bronchopulmonary dysplasia.

BACKGROUND: Premature birth, perinatal inflammation, and life-saving therapies such as postnatal oxygen and mechanical ventilation are strongly associated with the development of bronchopulmonary dysplasia (BPD); these risk factors, alone or combined, cause lung inflammation and alter programmed molecular patterns of normal lung development. The current knowledge on the molecular regulation of lung development mainly derives from mechanistic studies conducted in newborn rodents exposed to postnatal hyperoxia, which have been proven useful but have some limitations. METHODS: Here, we used the rabbit model of BPD as a cost-effective alternative model that mirrors human lung development and, in addition, enables investigating the impact of premature birth per se on the pathophysiology of BPD without further perinatal insults (e.g., hyperoxia, LPS-induced inflammation). First, we characterized the rabbit's normal lung development along the distinct stages (i.e., pseudoglandular, canalicular, saccular, and alveolar phases) using histological, transcriptomic and proteomic analyses. Then, the impact of premature birth was investigated, comparing the sequential transcriptomic profiles of preterm rabbits obtained at different time intervals during their first week of postnatal life with those from age-matched term pups. RESULTS: Histological findings showed stage-specific morphological features of the developing rabbit's lung and validated the selected time intervals for the transcriptomic profiling. Cell cycle and embryo development, oxidative phosphorylation, and WNT signaling, among others, showed high gene expression in the pseudoglandular phase. Autophagy, epithelial morphogenesis, response to transforming growth factor ß, angiogenesis, epithelium/endothelial cells development, and epithelium/endothelial cells migration pathways appeared upregulated from the 28th day of gestation (early saccular phase), which represents the starting point of the premature rabbit model. Premature birth caused a significant dysregulation of the inflammatory response. TNF-responsive, NF-κB regulated genes were significantly upregulated at premature delivery and triggered downstream inflammatory pathways such as leukocyte activation and cytokine signaling, which persisted upregulated during the first week of life. Preterm birth also dysregulated relevant pathways for normal lung development, such as blood vessel morphogenesis and epithelial-mesenchymal transition. CONCLUSION: These findings establish the 28-day gestation premature rabbit as a suitable model for mechanistic and pharmacological studies in the context of BPD.

Alu RNA Modulates the Expression of Cell Cycle Genes in Human Fibroblasts.

Alu retroelements, whose retrotransposition requires prior transcription by RNA polymerase III to generate Alu RNAs, represent the most numerous non-coding RNA (ncRNA) gene family in the human genome. Alu transcription is generally kept to extremely low levels by tight epigenetic silencing, but it has been reported to increase under different types of cell perturbation, such as viral infection and cancer. Alu RNAs, being able to act as gene expression modulators, may be directly involved in the mechanisms determining cellular behavior in such perturbed states. To directly address the regulatory potential of Alu RNAs, we generated IMR90 fibroblasts and HeLa cell lines stably overexpressing two slightly different Alu RNAs, and analyzed genome-wide the expression changes of protein-coding genes through RNA-sequencing. Among the genes that were upregulated or downregulated in response to Alu overexpression in IMR90, but not in HeLa cells, we found a highly significant enrichment of pathways involved in cell cycle progression and mitotic entry. Accordingly, Alu overexpression was found to promote transition from G1 to S phase, as revealed by flow cytometry. Therefore, increased Alu RNA may contribute to sustained cell proliferation, which is an important factor of cancer development and progression.

Referral Decision Making of General Practitioners: A Signal Detection Study.

BACKGROUND: Signal detection theory (SDT) describes how respondents categorize ambiguous stimuli over repeated trials. It measures separately "discrimination" (ability to recognize a signal amid noise) and "criterion" (inclination to respond "signal" v. "noise"). This is important because respondents may produce the same accuracy rate for different reasons. We employed SDT to measure the referral decision making of general practitioners (GPs) in cases of possible lung cancer. METHODS: We constructed 44 vignettes of patients for whom lung cancer could be considered and estimated their 1-year risk. Under UK risk-based guidelines, half of the vignettes required urgent referral. We recruited 216 GPs from practices across England. Practices differed in the positive predictive value (PPV) of their urgent referrals (chance of referrals identifying cancer) and the sensitivity (chance of cancer patients being picked up via urgent referral from their practice). Participants saw the vignettes online and indicated whether they would refer each patient urgently or not. We calculated each GP's discrimination ( d ') and criterion ( c) and regressed these on practice PPV and sensitivity, as well as on GP experience and gender. RESULTS: Criterion was associated with practice PPV: as PPV increased, GPs' c also increased, indicating lower inclination to refer ( b = 0.06 [0.02-0.09]; P = 0.001). Female GPs were more inclined to refer than male GPs ( b = -0.20 [-0.40 to -0.001]; P = 0.049). Average discrimination was modest ( d' = 0.77), highly variable (range, -0.28 to 1.91), and not associated with practice referral performance. CONCLUSIONS: High referral PPV at the organizational level indicates GPs' inclination to avoid false positives, not better discrimination. Rather than bluntly mandating increases in practice PPV via more referrals, it is necessary to increase discrimination by improving the evidence base for cancer referral decisions.

Interpreting and integrating big data in non-coding RNA research.

In the last two decades, we have witnessed an impressive crescendo of non-coding RNA studies, due to both the development of high-throughput RNA-sequencing strategies and an ever-increasing awareness of the involvement of newly discovered ncRNA classes in complex regulatory networks. Together with excitement for the possibility to explore previously unknown layers of gene regulation, these advancements led to the realization of the need for shared criteria of data collection and analysis and for novel integrative perspectives and tools aimed at making biological sense of very large bodies of molecular information. In the last few years, efforts to respond to this need have been devoted mainly to the regulatory interactions involving ncRNAs as direct or indirect regulators of protein-coding mRNAs. Such efforts resulted in the development of new computational tools, allowing the exploitation of the information spread in numerous different ncRNA data sets to interpret transcriptome changes under physiological and pathological cell responses. While experimental validation remains essential to identify key RNA regulatory interactions, the integration of ncRNA big data, in combination with systematic literature mining, is proving to be invaluable in identifying potential new players, biomarkers and therapeutic targets in cancer and other diseases.