Horizontal transfer of exosomal microRNAs transduce apoptotic signals between pancreatic beta-cells.

BACKGROUND: Diabetes mellitus is a common metabolic disorder characterized by dysfunction of insulin-secreting pancreatic beta-cells. MicroRNAs are important regulators of beta-cell activities. These non-coding RNAs have recently been discovered to exert their effects not only inside the cell producing them but, upon exosome-mediated transfer, also in other recipient cells. This novel communication mode remains unexplored in pancreatic beta-cells. In the present study, the microRNA content of exosomes released by beta-cells in physiological and physiopathological conditions was analyzed and the biological impact of their transfer to recipient cells investigated. RESULTS: Exosomes were isolated from the culture media of MIN6B1 and INS-1 derived 832/13 beta-cell lines and from mice, rat or human islets. Global profiling revealed that the microRNAs released in MIN6B1 exosomes do not simply reflect the content of the cells of origin. Indeed, while a subset of microRNAs was preferentially released in exosomes others were selectively retained in the cells. Moreover, exposure of MIN6B1 cells to inflammatory cytokines changed the release of several microRNAs. The dynamics of microRNA secretion and their potential transfer to recipient cells were next investigated. As a proof-of-concept, we demonstrate that if cel-miR-238, a C. Elegans microRNA not present in mammalian cells, is expressed in MIN6B1 cells a fraction of it is released in exosomes and is transferred to recipient beta-cells. Furthermore, incubation of untreated MIN6B1 or mice islet cells in the presence of microRNA-containing exosomes isolated from the culture media of cytokine-treated MIN6B1 cells triggers apoptosis of recipient cells. In contrast, exosomes originating from cells not exposed to cytokines have no impact on cell survival. Apoptosis induced by exosomes produced by cytokine-treated cells was prevented by down-regulation of the microRNA-mediating silencing protein Ago2 in recipient cells, suggesting that the effect is mediated by the non-coding RNAs. CONCLUSIONS: Taken together, our results suggest that beta-cells secrete microRNAs that can be transferred to neighboring beta-cells. Exposure of donor cells to pathophysiological conditions commonly associated with diabetes modifies the release of microRNAs and affects survival of recipient beta-cells. Our results support the concept that exosomal microRNAs transfer constitutes a novel cell-to-cell communication mechanism regulating the activity of pancreatic beta-cells.

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

Hepatic circadian clock oscillators and nuclear receptors integrate microbiome-derived signals.

The liver is a key organ of metabolic homeostasis with functions that oscillate in response to food intake. Although liver and gut microbiome crosstalk has been reported, microbiome-mediated effects on peripheral circadian clocks and their output genes are less well known. Here, we report that germ-free (GF) mice display altered daily oscillation of clock gene expression with a concomitant change in the expression of clock output regulators. Mice exposed to microbes typically exhibit characterized activities of nuclear receptors, some of which (PPARα, LXRβ) regulate specific liver gene expression networks, but these activities are profoundly changed in GF mice. These alterations in microbiome-sensitive gene expression patterns are associated with daily alterations in lipid, glucose, and xenobiotic metabolism, protein turnover, and redox balance, as revealed by hepatic metabolome analyses. Moreover, at the systemic level, daily changes in the abundance of biomarkers such as HDL cholesterol, free fatty acids, FGF21, bilirubin, and lactate depend on the microbiome. Altogether, our results indicate that the microbiome is required for integration of liver clock oscillations that tune output activators and their effectors, thereby regulating metabolic gene expression for optimal liver function.

Hepatic circadian clock oscillators and nuclear receptors integrate microbiome-derived signals.

The liver is a key organ of metabolic homeostasis with functions that oscillate in response to food intake. Although liver and gut microbiome crosstalk has been reported, microbiome-mediated effects on peripheral circadian clocks and their output genes are less well known. Here, we report that germ-free (GF) mice display altered daily oscillation of clock gene expression with a concomitant change in the expression of clock output regulators. Mice exposed to microbes typically exhibit characterized activities of nuclear receptors, some of which (PPARα, LXRβ) regulate specific liver gene expression networks, but these activities are profoundly changed in GF mice. These alterations in microbiome-sensitive gene expression patterns are associated with daily alterations in lipid, glucose, and xenobiotic metabolism, protein turnover, and redox balance, as revealed by hepatic metabolome analyses. Moreover, at the systemic level, daily changes in the abundance of biomarkers such as HDL cholesterol, free fatty acids, FGF21, bilirubin, and lactate depend on the microbiome. Altogether, our results indicate that the microbiome is required for integration of liver clock oscillations that tune output activators and their effectors, thereby regulating metabolic gene expression for optimal liver function.