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Post-translational modification of proteins with ubiquitin-like SUMO modifiers is a tightly regulated and highly dynamic process. The SENP family of SUMO-specific isopeptidases comprises six cysteine proteases. They are instrumental in counterbalancing SUMO conjugation, but their regulation is not well understood. We demonstrate that in hypoxic cell extracts, the catalytic activity of SENP family members, in particular SENP1 and SENP3, is inhibited in a rapid and fully reversible process. Comparative mass spectrometry from normoxic and hypoxic cells defines a subset of hypoxia-induced SUMO1 targets, including SUMO ligases RanBP2 and PIAS2, glucose transporter 1, and transcriptional regulators. Among the most strongly induced targets, we identified the transcriptional co-repressor BHLHE40, which controls hypoxic gene expression programs. We provide evidence that SUMOylation of BHLHE40 is reversed by SENP1 and contributes to transcriptional repression of the metabolic master regulator gene PGC-1α. We propose a pathway that connects oxygen-controlled SENP activity to hypoxic reprogramming of metabolism.
Partial wave analysis of the reaction p(3.5 GeV) + p → pK +Λ to search for the "ppK−" bound state
(2015)
Employing the Bonn–Gatchina partial wave analysis framework (PWA), we have analyzed HADES data of the reaction p(3.5 GeV) + p → pK +Λ. This reaction might contain information about the kaonic cluster “ppK −” (with quantum numbers J P = 0− and total isospin I = 1/2) via its decay into pΛ. Due to interference effects in our coherent description of the data, a hypothetical KNN (or, specifically “ppK −”) cluster signal need not necessarily show up as a pronounced feature (e.g. a peak) in an invariant mass spectrum like pΛ. Our PWA analysis includes a variety of resonant and non-resonant intermediate states and delivers a good description of our data (various angular distributions and two-hadron invariant mass spectra) without a contribution of a KNN cluster. At a confidence level of CLs = 95% such a cluster cannot contribute more than 2–12% to the total cross section with a pK +Λ final state, which translates into a production cross-section between 0.7 μb and 4.2 μb, respectively. The range of the upper limit depends on the assumed cluster mass, width and production process.
Genetic generalised epilepsy (GGE) is the most common form of genetic epilepsy, accounting for 20% of all epilepsies. Genomic copy number variations (CNVs) constitute important genetic risk factors of common GGE syndromes. In our present genome-wide burden analysis, large (≥ 400 kb) and rare (< 1%) autosomal microdeletions with high calling confidence (≥ 200 markers) were assessed by the Affymetrix SNP 6.0 array in European case-control cohorts of 1,366 GGE patients and 5,234 ancestry-matched controls. We aimed to: 1) assess the microdeletion burden in common GGE syndromes, 2) estimate the relative contribution of recurrent microdeletions at genomic rearrangement hotspots and non-recurrent microdeletions, and 3) identify potential candidate genes for GGE. We found a significant excess of microdeletions in 7.3% of GGE patients compared to 4.0% in controls (P = 1.8 x 10-7; OR = 1.9). Recurrent microdeletions at seven known genomic hotspots accounted for 36.9% of all microdeletions identified in the GGE cohort and showed a 7.5-fold increased burden (P = 2.6 x 10-17) relative to controls. Microdeletions affecting either a gene previously implicated in neurodevelopmental disorders (P = 8.0 x 10-18, OR = 4.6) or an evolutionarily conserved brain-expressed gene related to autism spectrum disorder (P = 1.3 x 10-12, OR = 4.1) were significantly enriched in the GGE patients. Microdeletions found only in GGE patients harboured a high proportion of genes previously associated with epilepsy and neuropsychiatric disorders (NRXN1, RBFOX1, PCDH7, KCNA2, EPM2A, RORB, PLCB1). Our results demonstrate that the significantly increased burden of large and rare microdeletions in GGE patients is largely confined to recurrent hotspot microdeletions and microdeletions affecting neurodevelopmental genes, suggesting a strong impact of fundamental neurodevelopmental processes in the pathogenesis of common GGE syndromes.