Activated CD8+ T cells choose between terminal effector cell (TEC) or memory precursor cell (MPC) fates. We show that Notch controls this choice. Notch promoted differentiation of immediately protective TECs and was correspondingly required for clearance of an acute influenza virus infection. Notch activated a major portion of the TEC-specific gene expression program and suppressed the MPC-specific program. Expression of Notch receptors was induced on naïve CD8+ T cells by inflammatory mediators and interleukin 2 (IL-2) via mTOR and T-bet dependent pathways. These pathways were subsequently amplified downstream of Notch, creating a positive feedback loop. Notch thus functions as a central hub where information from different sources converges to match effector T cell differentiation to the demands of the infection.

microRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at a posttranscriptional level and play a crucial role in the development of cells of the immune system. Macrophages are essential for generating inflammatory reactions upon tissue damage and encountering of invading pathogens, yet modulation of their immune responses is critical for maintaining tissue homeostasis. Macrophages can present different phenotypes, depending on the cytokine environment they encounter in the affected tissues. In this study, we have identified expression signatures of miRNAs that are differentially regulated during maturation of monocytes and polarization of macrophages by cytokines. We present a comprehensive characterization of miRNA expression in human monocytes and M1, M2a, and M2c polarized macrophages, using next-generation sequencing. Furthermore, we show that miRNA expression signatures are closely related to the various immune functions of polarized macrophages and therefore are involved in shaping the diverse phenotypes of these cells. The miRNAs identified here serve as markers for identification of inflammatory macrophages involved in the development of immune responses. Our findings contribute to understanding the role of miRNAs in determining the macrophage function in healthy and diseased tissues.

. (2015). MetDFBA: incorporating time-resolved metabolomics measurements into dynamic flux balance analysis. Molecular BioSystems, 11(1), 137-145. DOI: 10.1039/c4mb00510d General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Understanding cellular adaptation to environmental changes is one of the major challenges in systems biology. To understand how cellular systems react towards perturbations of their steady state, the metabolic dynamics have to be described. Dynamic properties can be studied with kinetic models but development of such models is hampered by limited in vivo information, especially kinetic parameters.Therefore, there is a need for mathematical frameworks that use a minimal amount of kinetic information. One of these frameworks is dynamic flux balance analysis (DFBA), a method based on the assumption that cellular metabolism has evolved towards optimal changes to perturbations. However, DFBA has some limitations. It is less suitable for larger systems because of the high number of parameters to estimate and the computational complexity. In this paper, we propose MetDFBA, a modification of DFBA, that incorporates measured time series of both intracellular and extracellular metabolite concentrations, in order to reduce both the number of parameters to estimate and the computational complexity. MetDFBA can be used to estimate dynamic flux profiles and, in addition, test hypotheses about metabolic regulation. In a first case study, we demonstrate the validity of our method by comparing our results to flux estimations based on dynamic 13 C MFA measurements, which we considered as experimental reference. For these estimations time-resolved metabolomics data from a feast-famine experiment with Penicillium chrysogenum was used. In a second case study, we used time-resolved metabolomics data from glucose pulse experiments during aerobic growth of Saccharomyces cerevisiae to test various metabolic objectives.

BackgroundCardiovascular and neural malformations are common sequels of diabetic pregnancies, but the underlying molecular mechanisms remain unknown. We hypothesized that maternal hyperglycemia would affect the embryos most shortly after the glucose-sensitive time window at embryonic day (ED) 7.5 in mice.MethodsMice were made diabetic with streptozotocin, treated with slow-release insulin implants and mated. Pregnancy aggravated hyperglycemia. Gene expression profiles were determined in ED8.5 and ED9.5 embryos from diabetic and control mice using Serial Analysis of Gene Expression and deep sequencing.ResultsMaternal hyperglycemia induced differential regulation of 1,024 and 2,148 unique functional genes on ED8.5 and ED9.5, respectively, mostly in downward direction. Pathway analysis showed that ED8.5 embryos suffered mainly from impaired cell proliferation, and ED9.5 embryos from impaired cytoskeletal remodeling and oxidative phosphorylation (all P ≤ E-5). A query of the Mouse Genome Database showed that 20–25% of the differentially expressed genes were caused by cardiovascular and/or neural malformations, if deficient. Despite high glucose levels in embryos with maternal hyperglycemia and a ~150-fold higher rate of ATP production from glycolysis than from oxidative phosphorylation on ED9.5, ATP production from both glycolysis and oxidative phosphorylation was reduced to ~70% of controls, implying a shortage of energy production in hyperglycemic embryos.ConclusionMaternal hyperglycemia suppressed cell proliferation during gastrulation and cytoskeletal remodeling during early organogenesis. 20–25% of the genes that were differentially regulated by hyperglycemia were associated with relevant congenital malformations. Unexpectedly, maternal hyperglycemia also endangered the energy supply of the embryo by suppressing its glycolytic capacity.