Insulin and TOR pathways regulate cellular and organismal growth through the myc oncogene in Drosophila

A large body of literature documents in both mice and Drosophila the involvement of Insulin pathway in growth regulation, probably due to its role in glucose and lipid import, nutrient storage, and translation of RNAs implicated in ribosome biogenesis (Vanhaesebroeck et al. 2001). Moreover several lines of evidence implicate this pathway as a causal factor in cancer (Sale, 2008; Zeng and Yee 2007; Hursting et al., 2007; Chan et al., 2008). With regards to Myc, studies in cell culture have implied this family of transcription factors as regulators of the cell cycle that are rapidly induced in response to growth factors. Myc is a potent oncogene, rearranged and overexpressed in a wide range of human tumors and necessary during development. Its conditional knock-out in mice results in reduction of body weight due to defect in cell proliferation (Trumpp et al. 2001). Evidence from in vivo studies in Drosophila and mammals suggests a critical function for myc in cell growth regulation (Iritani and Eisenman 1999; Johnston et al. 1999; Kim et al. 2000; de Alboran et al. 2001; Douglas et al. 2001). This role is supported by our analysis of Myc target genes in Drosophila, which include genes involved in RNA binding, processing, ribosome biogenesis and nucleolar function (Orain et al 2003, Bellosta et al., 2005, Hulf et al, 2005). The fact that Insulin signaling and Myc have both been associated with growth control suggests that they may interact with each other. However, genetic evidence suggesting that Insulin signaling regulates Myc in vivo is lacking. In this work we were able to show, for the first time, a direct modulation of dMyc in response to Insulin stimulation/silencing both in vitro and in vivo. Our results suggest that dMyc up-regulation in response to DILPs signaling occurs both at the mRNA and potein level. We believe dMyc protein accumulation after Insulin signaling activation is conditioned to AKT-dependent GSK3β/sgg inactivation. In fact, we were able to demonstate that dMyc protein stabilization through phosphorylation is a conserved feature between Drosophila and vertebrates and requires multiple events. The final phosphorylation step, that results in a non-stable form of dMyc protein, ready to be degraded by the proteasome, is performed by GSK3β/sgg kinase (Sears, 2004). At the same time we demonstrated that CKI family of protein kinase are required to prime dMyc phosphorylation. DILPs and TOR/Nutrient signalings are known to communicate at several levels (Neufeld, 2003). For this reason we further investigated TOR contribution to dMyc-dependent growth regulation. dMyc protein accumulates in S2 cells after aminoacid stimulation, while its mRNA does not seem to be affected upon TORC1 inhibition, suggesting that the Nutrient pathway regulates dMyc mostly post-transcriptionally. In support to this hypothesis, we observed a TORC1-dependent GSK3β/sgg inactivation, further confirming a synergic effect of DILPs and Nutrients on dMyc protein stability. On the other hand, our data show that Rheb but not S6K, both downstream of the TOR kinase, contributes to the dMyc-induced growth of the eye tissue, suggesting that Rheb controls growth independently of S6K.. Moreover, Rheb seems to be able to regulate organ size during development inducing cell death, a mechanism no longer occurring in absence of dmyc. These observations suggest that Rheb might control growth through a new pathway independent of TOR/S6K but still dependent on dMyc. In order to dissect the mechanism of dMyc regulation in response to these events, we analyzed the relative contribution of Rheb, TOR and S6K to dMyc expression, biochemically in S2 cells and in vivo in morphogenetic clones and we further confirmed an interplay between Rheb and Myc that seems to be indipendent from TOR. In this work we clarified the mechanisms that stabilize dMyc protein in vitro and in vivo and we observed for the first time dMyc responsiveness to DILPs and TOR. At the same time, we discovered a new branch of the Nutrient pathway that appears to drive growth through dMyc but indipendently from TOR. We believe our work shed light on the mechanisms cells use to grow or restrain growth in presence/absence of growth promoting cues and for this reason it contributes to understand the physiology of growth control.

Interactions of G-quadruplex binders and Topoisomerase I inhibitors in cancer cells

Top1-DNA cleavage complexes (Top1ccs) trigger an accumulation of antisense RNAPII transcripts specifically at active divergent CpG-island promoters in a replication independent and Top1 dependent manner, leading to transcription-dependent genome instability and altered transcription regulation. Using different cancer cell lines of colon and osteo origins, we show that they display different sensitivity to CPT and G4 binder that is independent from Top1 level. To look at the interactions between Top1 and G4, we show that co-treatment with G4 binders potentiate the cell cytotoxicity of CPT regardless of the treatment sequences. Potentiation is indicated by a reduced inhibition concentration (IC50) with a more profound cytotoxicity in CPT-resistant cell lines, HCT15 and U2OS, hence, indicating an interaction between Top1inhibitor and G4 binders. Moreover, computational analysis confirmed the present of G4 motifs in genes with CPT-induced antisense transcription. G4 motifs are present mostly 5000 bp upstream from transcription start site and notably lower in genes. Comparisons between genes with no antisense transcription and genes with antisense transcription show that G4 motifs in this region are notably lower in the genes with antisense transcripts. Since CPT increases negative supercoils at promoters of intermediate activity, the formation of G4 is also increased in CPT-treated cells. Suprisingly, formation of G4 is regulated in parallel to the transient stabilization of R-loops, indicating a role in response to CPT-induced stress. G4 formation is highly elevated in Pyridostatin treated cells, which previous study shows increased formation of γH2Ax foci. This effect is also seen in the CPT-resistant cell lines, HCT15, indicating that the formation is a general event in response to CPT. We also show that R-loop formation is greatly increased in Pyridostatin treated cells. In order to study the role of R-loops and G4 structures in Top1cc-dependant repair pathway, we inhibited tyrosyl-phosphodiestrase 1 (TDP-1) using a TDP-1 inhibitor.

Type 2 diabetes is associated with reduced ATP-binding cassette transporter A1 gene expression, protein and function

Objective Increasing plasma glucose levels are associated with increasing risk of vascular disease. We tested the hypothesis that there is a glycaemia-mediated impairment of reverse cholesterol transport (RCT). We studied the influence of plasma glucose on expression and function of a key mediator in RCT, the ATP binding cassette transporter-A1 (ABCA1) and expression of its regulators, liver X receptor-α (LXRα) and peroxisome proliferator-activated receptor–γ (PPARγ). Methods and Results Leukocyte ABCA1, LXRα and PPARγ expression was measured by polymerase chain reaction in 63 men with varying degrees of glucose homeostasis. ABCA1 protein concentrations were measured in leukocytes. In a sub-group of 25 men, ABCA1 function was quantified as apolipoprotein-A1-mediated cholesterol efflux from 2–3 week cultured skin fibroblasts. Leukocyte ABCA1 expression correlated negatively with circulating HbA1c and glucose (rho = −0.41, p<0.001; rho = −0.34, p = 0.006 respectively) and was reduced in Type 2 diabetes (T2DM) (p = 0.03). Leukocyte ABCA1 protein was lower in T2DM (p = 0.03) and positively associated with plasma HDL cholesterol (HDL-C) (rho = 0.34, p = 0.02). Apolipoprotein-A1-mediated cholesterol efflux correlated negatively with fasting glucose (rho = −0.50, p = 0.01) and positively with HDL-C (rho = 0.41, p = 0.02). It was reduced in T2DM compared with controls (p = 0.04). These relationships were independent of LXRα and PPARγ expression. Conclusions ABCA1 expression and protein concentrations in leukocytes, as well as function in cultured skin fibroblasts, are reduced in T2DM. ABCA1 protein concentration and function are associated with HDL-C levels. These findings indicate a glycaemia- related, persistent disruption of a key component of RCT.

Learned irrelevance and associative learning is attenuated in individuals at risk for psychosis but not in asymptomatic first-degree relatives of schizophrenia patients: translational state markers of psychosis?

Learned irrelevance (LIrr) refers to a form of selective learning that develops as a result of prior noncorrelated exposures of the predicted and predictor stimuli. In learning situations that depend on the associative link between the predicted and predictor stimuli, LIrr is expressed as a retardation of learning. It represents a form of modulation of learning by selective attention. Given the relevance of selective attention impairment to both positive and cognitive schizophrenia symptoms, the question remains whether LIrr impairment represents a state (relating to symptom manifestation) or trait (relating to schizophrenia endophenotypes) marker of human psychosis. We examined this by evaluating the expression of LIrr in an associative learning paradigm in (1) asymptomatic first-degree relatives of schizophrenia patients (SZ-relatives) and in (2) individuals exhibiting prodromal signs of psychosis ("ultrahigh risk" [UHR] patients) in each case relative to demographically matched healthy control subjects. There was no evidence for aberrant LIrr in SZ-relatives, but LIrr as well as associative learning were attenuated in UHR patients. It is concluded that LIrr deficiency in conjunction with a learning impairment might be a useful state marker predictive of psychotic state but a relatively weak link to a potential schizophrenia endophenotype.

From the chiral magnetic wave to the charge dependence of elliptic flow

The quark-gluon plasma formed in heavy ion collisions contains charged chiral fermions evolving in an external magnetic field. At finite density of electric charge or baryon number (resulting either from nuclear stopping or from fluctuations), the triangle anomaly induces in the plasma the Chiral Magnetic Wave (CMW). The CMW first induces a separation of the right and left chiral charges along the magnetic field; the resulting dipolar axial charge density in turn induces the oppositely directed vector charge currents leading to an electric quadrupole moment of the quark-gluon plasma. Boosted by the strong collective flow, the electric quadrupole moment translates into the charge dependence of the elliptic flow coefficients, so that $v_2(\pi^+) < v_2(\pi^-)$ (at positive net charge). Using the latest quantitative simulations of the produced magnetic field and solving the CMW equation, we make further quantitative estimates of the produced $v_2$ splitting and its centrality dependence. We compare the results with the available experimental data.

A Cox Model for Biostatistics of the Future

Professor Sir David R. Cox (DRC) is widely acknowledged as among the most important scientists of the second half of the twentieth century. He inherited the mantle of statistical science from Pearson and Fisher, advanced their ideas, and translated statistical theory into practice so as to forever change the application of statistics in many fields, but especially biology and medicine. The logistic and proportional hazards models he substantially developed, are arguably among the most influential biostatistical methods in current practice. This paper looks forward over the period from DRC's 80th to 90th birthdays, to speculate about the future of biostatistics, drawing lessons from DRC's contributions along the way. We consider "Cox's model" of biostatistics, an approach to statistical science that: formulates scientific questions or quantities in terms of parameters gamma in probability models f(y; gamma) that represent in a parsimonious fashion, the underlying scientific mechanisms (Cox, 1997); partition the parameters gamma = theta, eta into a subset of interest theta and other "nuisance parameters" eta necessary to complete the probability distribution (Cox and Hinkley, 1974); develops methods of inference about the scientific quantities that depend as little as possible upon the nuisance parameters (Barndorff-Nielsen and Cox, 1989); and thinks critically about the appropriate conditional distribution on which to base infrences. We briefly review exciting biomedical and public health challenges that are capable of driving statistical developments in the next decade. We discuss the statistical models and model-based inferences central to the CM approach, contrasting them with computationally-intensive strategies for prediction and inference advocated by Breiman and others (e.g. Breiman, 2001) and to more traditional design-based methods of inference (Fisher, 1935). We discuss the hierarchical (multi-level) model as an example of the future challanges and opportunities for model-based inference. We then consider the role of conditional inference, a second key element of the CM. Recent examples from genetics are used to illustrate these ideas. Finally, the paper examines causal inference and statistical computing, two other topics we believe will be central to biostatistics research and practice in the coming decade. Throughout the paper, we attempt to indicate how DRC's work and the "Cox Model" have set a standard of excellence to which all can aspire in the future.

Power and Robustness of Linkage Tests for Quantitative Traits in General Pedigrees

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, would allow the incorporation of environmental covariates, and would be appropriate in the presence of selective sampling. We recently described a general framework for quantitative trait linkage analysis, based on generalized estimating equations, for which many current methods are special cases. This procedure is appropriate for general pedigrees and easily accommodates environmental covariates. In this paper, we use computer simulations to investigate the power robustness of a variety of linkage test statistics built upon our general framework. We also propose two novel test statistics that take account of higher moments of the phenotype distribution, in order to accommodate non-normality. These new linkage tests are shown to have high power and to be robust to non-normality. While we have not yet examined the performance of our procedures in the context of selective sampling via computer simulations, the proposed tests satisfy all of the other qualities of an ideal quantitative trait linkage analysis method.

Bioconductor: Open software development for computational biology and bioinformatics

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. We detail some of the design decisions, software paradigms and operational strategies that have allowed a small number of researchers to provide a wide variety of innovative, extensible, software solutions in a relatively short time. The use of an object oriented programming paradigm, the adoption and development of a software package system, designing by contract, distributed development and collaboration with other projects are elements of this project's success. Individually, each of these concepts are useful and important but when combined they have provided a strong basis for rapid development and deployment of innovative and flexible research software for scientific computation. A primary objective of this initiative is achievement of total remote reproducibility of novel algorithmic research results.