The transcriptional function of the c-Myc oncoprotein and its regulation by the ubiquitin/proteasome pathway

The c-Myc proto-oncogene encodes a short lived-transcription factor that plays an important role in cellular proliferation, growth and apoptosis. c-myc is often rearranged in tumours resulting in deregulated expression. c-Myc both activates and represses transcription of a number of target genes. This thesis focuses firstly on the mechanism by which c-Myc represses differentiation-induced genes and secondly on the regulation of c-Myc by ubiquitin/proteasome mediated turnover and its consequences for c-Myc function in transcription. Our results show that differentiation-induced expression of the cyclin-dependent kinase inhibitor (CKI) p21Cip1 is repressed by Myc at the level of transcription. Myc was shown to repress the p21Cip1 core promoter by direct interaction with the initiator binding protein Miz-1. The rapid turnover of c-Myc is shown to be mediated by the ubiquitin/proteasome pathway and we have identified the phosphorylation site Thr58, which is frequently mutated in Burkitt’s lymphoma, as an important recognition site for this process. As a result of Thr58 mutation, c-Myc escapes this regulation which results in Myc protein accumulation. We further show that the E3 ubiquitin ligase SCFSkp2 interacts with Myc during G1-S phase transition of the cell cycle and promotes its ubiquitylation and proteasomal degradation. Surprisingly, Skp2 promotes c-Myc-induced S-phase transition and is required for transcriptional activation by Myc. Moreover our data suggest that Skp2 and components of the proteasome is recruited by c-Myc target gene promoters in conjunction with protein ubiquitylation. These results suggest that Skp2 is a transcriptional cofactor for c-Myc. The thesis suggests an important role for c-Myc at the G1/S transition by transcriptional repression of the CKI p21Cip1 and by stimulation of cell cycle genes via Skp2 coactivator function. The thesis also sheds light on the regulation of c-Myc turnover and suggests an important interdependence between transcription and ubiquitylation

Mesopore etching under supercritical conditions – A shortcut to hierarchically porous silica monoliths

Hierarchically porous silica monoliths are obtained in the two-step Nakanishi process, where formation of a macro microporous silica gel is followed by widening micropores to mesopores through surface etching. The latter step is carried out through hydrothermal treatment of the gel in alkaline solution and necessitates a lengthy solvent exchange of the aqueous pore fluid before the ripened gel can be dried and calcined into a mechanically stable macro mesoporous monolith. We show that using an ethanol water (95.6/4.4, v/v) azeotrope as supercritical fluid for mesopore etching eliminates the solvent exchange, ripening, and drying steps of the classic route and delivers silica monoliths that can withstand fast heating rates for calcination. The proposed shortcut decreases the overall preparation time from ca. one week to ca. one day. Porosity data show that the alkaline conditions for mesopore etching are crucial to obtain crack-free samples with a narrow mesopore size distribution. Physical reconstruction of selected samples by confocal laser scanning microscopy and subsequent morphological analysis confirms that monoliths prepared via the proposed shortcut possess the high homogeneity of silica skeleton and macropore space that is desirable in adsorbents for flow-through applications

Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)

With increasing data and model complexities, the time required to train neural networks has become prohibitively large. To address the exponential rise in training time, users are turning to data parallel neural networks (DPNN) and large-scale distributed resources on computer clusters. Current DPNN approaches implement the network parameter updates by synchronizing and averaging gradients across all processes with blocking communication operations after each forward-backward pass. This synchronization is the central algorithmic bottleneck. We introduce the Distributed Asynchronous and Selective Optimization (DASO) method, which leverages multi-GPU compute node architectures to accelerate network training while maintaining accuracy. DASO uses a hierarchical and asynchronous communication scheme comprised of node-local and global networks while adjusting the global synchronization rate during the learning process. We show that DASO yields a reduction in training time of up to 34% on classical and state-of-the-art networks, as compared to current optimized data parallel training methods

Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)

With increasing data and model complexities, the time required to train neural networks has become prohibitively large. To address the exponential rise in training time, users are turning to data parallel neural networks (DPNN) to utilize large-scale distributed resources on computer clusters. Current DPNN approaches implement the network parameter updates by synchronizing and averaging gradients across all processes with blocking communication operations. This synchronization is the central algorithmic bottleneck. To combat this, we introduce the Distributed Asynchronous and Selective Optimization (DASO) method which leverages multi-GPU compute node architectures to accelerate network training. DASO uses a hierarchical and asynchronous communication scheme comprised of node-local and global networks while adjusting the global synchronization rate during the learning process. We show that DASO yields a reduction in training time of up to 34% on classical and state-of-the-art networks, as compared to other existing data parallel training methods

Uptake and transport of novel amphiphilic polyelectrolyte-insulin nanocomplexes by caco-2 cells - towards oral insulin

“The original publication is available at www.springerlink.com”. Copyright SpringerPurpose: The influence of polymer architecture on cellular uptake and transport across Caco-2 cells of novel amphiphilic polyelectrolyte-insulin nanocomplexes was investigated. Method: Polyallylamine (PAA) (15 kDa) was grafted with palmitoyl chains (Pa) and subsequently modified with quaternary ammonium moieties (QPa). These two amphiphilic polyelectrolytes (APs) were tagged with rhodamine and their uptake by Caco-2 cells or their polyelectrolyte complexes (PECs) with fluorescein isothiocyanate-insulin (FITC-insulin) uptake were investigated using fluorescence microscopy. The integrity of the monolayer was determined by measurement of transepithelial electrical resistance (TEER). Insulin transport through Caco-2 monolayers was determined during TEER experiments. Result: Pa and insulin were co-localised in the cell membranes while QPa complexes were found within the cytoplasm. QPa complex uptake was not affected by calcium, cytochalasin D or nocodazole. Uptake was reduced by co-incubation with sodium azide, an active transport inhibitor. Both polymers opened tight junctions reversibly where the TEER values fell by up to 35 % within 30 minutes incubation with Caco-2 cells. Insulin transport through monolayers increased when QPa was used (0.27 ngmL-1 of insulin in basal compartment) compared to Pa (0.14 ngmL-1 of insulin in basal compartment) after 2 hours. Conclusion: These APs have been shown to be taken up by Caco-2 cells and reversibly open tight cell junctions. Further work is required to optimise these formulations with a view to maximising their potential to facilitate oral delivery of insulin.Peer reviewe

RNA contact prediction by data efficient deep learning

On the path to full understanding of the structure-function relationship or even design of RNA, structure prediction would offer an intriguing complement to experimental efforts. Any deep learning on RNA structure, however, is hampered by the sparsity of labeled training data. Utilizing the limited data available, we here focus on predicting spatial adjacencies ("contact maps") as a proxy for 3D structure. Our model, BARNACLE, combines the utilization of unlabeled data through self-supervised pre-training and efficient use of the sparse labeled data through an XGBoost classifier. BARNACLE shows a considerable improvement over both the established classical baseline and a deep neural network. In order to demonstrate that our approach can be applied to tasks with similar data constraints, we show that our findings generalize to the related setting of accessible surface area prediction

COMMD1 promotes the ubiquitination of NF‐κB subunits through a cullin‐containing ubiquitin ligase

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102213/1/emboj7601489.pd

Characterization of ARF-BP1/HUWE1 Interactions with CTCF, MYC, ARF and p53 in MYC-Driven B Cell Neoplasms

Transcriptional activation of MYC is a hallmark of many B cell lineage neoplasms. MYC provides a constitutive proliferative signal but can also initiate ARF-dependent activation of p53 and apoptosis. The E3 ubiquitin ligase, ARF-BP1, encoded by HUWE1, modulates the activity of both the MYC and the ARF-p53 signaling pathways, prompting us to determine if it is involved in the pathogenesis of MYC-driven B cell lymphomas. ARF-BP1 was expressed at high levels in cell lines from lymphomas with either wild type or mutated p53 but not in ARF-deficient cells. Downregulation of ARF-BP1 resulted in elevated steady state levels of p53, growth arrest and apoptosis. Co-immunoprecipitation studies identified a multiprotein complex comprised of ARF-BP1, ARF, p53, MYC and the multifunctional DNA-binding factor, CTCF, which is involved in the transcriptional regulation of MYC, p53 and ARF. ARF-BP1 bound and ubiquitylated CTCF leading to its proteasomal degradation. ARF-BP1 and CTCF thus appear to be key cofactors linking the MYC proliferative and p53-ARF apoptotic pathways. In addition, ARF-BP1 could be a therapeutic target for MYC-driven B lineage neoplasms, even if p53 is inactive, with inhibition reducing the transcriptional activity of MYC for its target genes and stabilizing the apoptosis-promoting activities of p53

Mechanisms of c-Myc Degradation by Nickel Compounds and Hypoxia

Nickel (Ni) compounds have been found to cause cancer in humans and animal models and to transform cells in culture. At least part of this effect is mediated by stabilization of hypoxia inducible factor (HIF1a) and activating its downstream signaling. Recent studies reported that hypoxia signaling might either antagonize or enhance c-myc activity depending on cell context. We investigated the effect of nickel on c-myc levels, and demonstrated that nickel, hypoxia, and other hypoxia mimetics degraded c-myc protein in a number of cancer cells (A549, MCF-7, MDA-453, and BT-474). The degradation of the c-Myc protein was mediated by the 26S proteosome. Interestingly, knockdown of both HIF-1α and HIF-2α attenuated c-Myc degradation induced by Nickel and hypoxia, suggesting the functional HIF-1α and HIF-2α was required for c-myc degradation. Further studies revealed two potential pathways mediated nickel and hypoxia induced c-myc degradation. Phosphorylation of c-myc at T58 was significantly increased in cells exposed to nickel or hypoxia, leading to increased ubiquitination through Fbw7 ubiquitin ligase. In addition, nickel and hypoxia exposure decreased USP28, a c-myc de-ubiquitinating enzyme, contributing to a higher steady state level of c-myc ubiquitination and promoting c-myc degradation. Furthermore, the reduction of USP28 protein by hypoxia signaling is due to both protein degradation and transcriptional repression. Nickel and hypoxia exposure significantly increased the levels of dimethylated H3 lysine 9 at the USP28 promoter and repressed its expression. Our study demonstrated that Nickel and hypoxia exposure increased c-myc T58 phosphorylation and decreased USP28 protein levels in cancer cells, which both lead to enhanced c-myc ubiquitination and proteasomal degradation