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Hummel, M.

Publications and source records attributed to Hummel, M..

4 recordsLinked to original sources

TNF-α induces reactivation of human cytomegalovirus independently of myeloid cell differentiation following post-transcriptional establishment of latency

We used the Kasumi-3 model to study HCMV latency and reactivation in myeloid progenitor cells. Kasumi-3 cells were infected with HCMV strain TB40/Ewt-GFP, flow sorted for GFP+ cells, and cultured for various times to monitor establishment of latency, as judged by repression of viral gene expression (RNA/DNA ratio) and loss of virus production. We found that, in the vast majority of cells, latency was established post-transcriptionally in the GFP+ infected cells: transcription was initially turned on, and then turned off. We also found that some of the GFP-cells were infected, suggesting that latency might be established in these cells at the outset of infection. We were not able to test this hypothesis because some GFP-cells expressed lytic genes, and thus, it was not possible to separate them from GFP-quiescent cells. In addition, we found that the pattern of expression of lytic genes that have been associated with latency, including UL138, US28, and RNA2.7, was the same as that of other lytic genes, indicating that there was no preferential expression of these genes once latency is established. We confirmed previous studies showing that TNF- induced reactivation of infectious virus, and by analyzing expression of the progenitor cell marker CD34 as well as myeloid cell differentiation markers in IE+ cells after treatment with TNF-, we showed that TNF- induced transcriptional reactivation of IE gene expression independently of differentiation. TNF--mediated reactivation in Kasumi-3 cells was correlated with activation of NF-{kappa}B, KAP-1 and ATM.\n\nIMPORTANCEHCMV is an important human pathogen that establishes lifelong latent infection in myeloid progenitor cells, and reactivates frequently to cause significant disease in immunocompromised people. Our observation that viral gene expression is first turned on, and then turned off to establish latency suggests that there is a host defense, which may be myeloid-specific, responsible for transcriptional silencing of viral gene expression. Our observation that TNF- induces reactivation independently of differentiation provides insight into molecular mechanisms that control reactivation.

microbiology

MDM4 is an essential disease driver targeted by 1q gain in Burkitt lymphoma

Oncogenic MYC activation promotes cellular proliferation in Burkitt lymphoma (BL), but also induces cell cycle arrest and apoptosis mediated by TP53, a tumor suppressor gene that is mutated in 40% of BL cases. To identify therapeutic targets in BL, we investigated molecular dependencies in BL cell lines using RNAi-based, loss-of-function screening. By integrating genotypic and RNAi data, we identified a number of genotype-specific dependencies including the dependence of TCF3/ID3 mutant cell lines on TCF3 and of MYD88 mutant cell lines on TLR signaling. TP53 wild-type (TP53wt) BL were dependent on MDM4, a negative regulator of TP53. In BL cell lines, MDM4 knockdown induced cell cycle arrest and decreased tumor growth in a xenograft model in a p53-dependent manner, while small molecule inhibition of the MDM4-p53 interaction restored p53 activity resulting in cell cycle arrest. Consistent with the pathogenic effect of MDM4 upregulation in BL, we found that TP53wt BL samples were enriched for gain of chromosome 1q which includes the MDM4 locus. 1q gain was also enriched across non-BL cancer cell lines (n=789) without TP53 mutation (23% in TP53wt and 12% in TP53mut, p<0.001). In a set of 216 cell lines representing 19 cancer entities from the Achilles project, MDM4 was the strongest genetic dependency in TP53wt cell lines (p<0.001).\n\nOur findings show that in TP53wt BL, MDM4-mediated inhibition of p53 is a mechanism to evade cell cycle arrest. The data highlight the critical role of p53 as a tumor suppressor in BL, and identifies MDM4 as a key functional target of 1q gain in a wide range of cancers, which is therapeutically targetable.

cancer biology

A stress recovery signaling network for enhanced flooding tolerance in Arabidopsis thaliana

Abiotic stresses in plants are often transient and the recovery phase following stress removal is critical. Flooding, a major abiotic stress that negatively impacts plant biodiversity and agriculture, is a sequential stress where tolerance is strongly dependent on viability underwater and during the postflooding period. Here we show that in Arabidopsis thaliana accessions (Bay-0 and Lp2-6), different rates of submergence recovery correlate with submergence tolerance and fecundity. A genome-wide assessment of ribosome-associated transcripts in Bay-0 and Lp2-6 revealed a signaling network regulating recovery processes. Differential recovery between the accessions was related to the activity of three genes: RESPIRATORY BURST OXIDASE HOMOLOG (RBOHD), SENESCENCE-ASSOCIATED GENE113 (SAG113) and ORESARA1 (ORE1/NAC6) which function in a regulatory network involving a reactive oxygen species (ROS) burst upon de-submergence and the hormones abscisic acid and ethylene. This regulatory module controls ROS homeostasis, stomatal aperture and chlorophyll degradation during submergence recovery. This work uncovers a signaling network that regulates recovery processes following flooding to hasten the return to pre-stress homeostasis.\n\nSignificance statementFlooding due to extreme weather events can be highly detrimental to plant development and yield. Speedy recovery following stress removal is an important determinant of tolerance, yet mechanisms regulating this remain largely uncharacterized. We identified a regulatory network in Arabidopsis thaliana that controls water loss and senescence to influence recovery from prolonged submergence. Targeted control of the molecular mechanisms facilitating stress recovery identified here can potentially improve performance of crops in flood-prone areas.

plant biology

ACEseq - allele specific copy number estimation from whole genome sequencing

ACEseq is a computational tool for allele-specific copy number estimation in tumor genomes based on whole genome sequencing. In contrast to other tools it features GC-bias correction, unique replication timing-bias correction and integration of structural variant (SV) breakpoints for improved genome segmentation. ACEseq clearly outperforms widely used state-of-the art methods, provides a fully automated estimation of tumor cell content and ploidy, and additionally computes homologous recombination deficiency scores.

bioinformatics