Glutaminolysis and fumarate accumulation integrate immunometabolic and epigenetic programs in trained immunity

Induction of trained immunity (innate immune memory) is mediated by activation of immune and metabolic pathways that result in epigenetic rewiring of cellular functional programs. Through network-level integration of transcriptomics and metabolomics data, we identify glycolysis, glutaminolysis, and the cholesterol synthesis pathway as indispensable for the induction of trained immunity by ß-glucan in monocytes. Accumulation of fumarate, due to glutamine replenishment of the TCA cycle, integrates immune and metabolic circuits to induce monocyte epigenetic reprogramming by inhibiting KDM5 histone demethylases. Furthermore, fumarate itself induced an epigenetic program similar to ß-glucan-induced trained immunity. In line with this, inhibition of glutaminolysis and cholesterol synthesis in mice reduced the induction of trained immunity by ß-glucan. Identification of the metabolic pathways leading to induction of trained immunity contributes to our understanding of innate immune memory and opens new therapeutic avenues.Netherlands Organization for Scientific Research (NWO). B.N. is supported by an NHMRC (Australia) CJ Martin Early Career Fellowship. N.P.R. Netherlands Heart Foundation (2012T051). N.P.R. and M.G.N. received a H2020 grant (H2020-PHC-2015-667873-2) from the European Union (grant agreement 667837). Fundação para a Ciência e Tecnologia, FCT (IF/00735/2014 to A.C., IF/00021/2014 to R.S., RECI/BBB-BQB/0230/2012 to L.G.G., and SFRH/BPD/96176/2013 to C. Cunha). The NMR spectrometers are part of the National NMR Facility supported by FCT (RECI/BBB-BQB/0230/2012). The research leading to these results received funding from the Fundação para a Ciência e Tecnologia (FCT), cofunded by Programa Operacional Regional do Norte (ON.2—O Novo Norte); from the Quadro de Referência Estratégico Nacional (QREN) through the Fundo Europeu de Desenvolvimento Regional (FEDER) and from the Projeto Estratégico – LA 26 – 2013–2014 (PEst-C/SAU/LA0026/2013). NIH (DK43351 and DK097485) and Helmsley Trust. D.L.W. is supported, in part, by the NIH (GM53522, GM083016, GM119197, and C06RR0306551

Estimation for queues from queue length data

We consider the estimation of arrival and service rates for queues based on queue length data collected at successive, not necessarily equally spaced, time points. In particular, we consider the M/M/c queue, for c large, but application of the method to the repairman problem is almost identical, and the general approach presented should extend to other queue types. The estimation procedure makes use of an Ornstein-Uhlenbeck diffusion approximation to the Markov process description of the queue. We demonstrate the approach through simulation studies and discuss situations in which the approximation works best