Mitochondrial dysfunction leads to the accumulation of reactive oxygen species (ROS) which is associated with cellular dysfunction, disease etiology, and senescence. Here, we used the eukaryotic ...model Saccharomyces cerevisiae, commonly studied for cellular aging, to demonstrate how defective mitochondrial function affects yeast replicative lifespan (RLS). We show that RLS of respiratory-deficient cells decreases significantly, indicating that the maintenance of RLS requires active respiration. The shortening of RLS due to mitochondrial dysfunction was not related to the accumulation of extrachromosomal ribosomal DNA circles, a well-known cause of aging in yeast. Instead, intracellular ROS and oxidatively damaged proteins increased in respiratory-deficient mutants. We show that, while the protein kinase A activity is not elevated, ROS generation in respiratory-deficient cells depends on RAS signaling pathway. The ER-localized NADPH oxidase Yno1 also played a role in producing ROS. Our data suggest that a severe defect in mitochondrial respiration accelerates cellular aging by disturbing protein homeostasis in yeast.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Ugp1, UDP-glucose pyrophosphorylase, plays an important role in carbohydrate metabolism because it provides UDP-glucose that is a pivotal metabolite in several metabolic pathways in Saccharomyces ...cerevisiae. In this study, we show that a considerable reduction of glycogen and trehalose content in ugp1 knockdown cells is rescued by complementing the expression of Ugp1, indicating that Ugp1 is required for the production of storage carbohydrates. Because of the specific function of trehalose as a stress protectant, Ugp1 expression contributed to oxidative stress response and long-term cell survival during stationary phase. Furthermore, the modulation of Ugp1 level readjusted glycogen and trehalose accumulation in the protein kinase A (PKA)-related gene mutants. The PKA-dependent phenotypes of oxidative stress resistance and long-term cell survival were also alleviated via adjustment of Ugp1 level. Collectively, our data suggest that the regulation of UPG1 influences several PKA-dependent processes by adjusting the levels of various carbohydrates.
•Ugp1, a UDP-glucose pyrophosphorylase, plays a crucial role in carbohydrate metabolism in Saccharomyces cerevisiae.•We confirmed a new conditional ugp1 mutant (ugp1KD) cells show a defect in the production of glycogen and trehalose.•The modulation of Ugp1 level can alter oxidant sensitivity and long-term survival of wild-type cells.•The regulation of UGP1 expression plays an important role in the downstream effects of the PKA pathway.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The definition of protein-protein interactions (PPIs) in the natural cellular context is essential for properly understanding various biological processes. So far, however, most large-scale PPI ...analyses have not been performed in the natural cellular context. Here, we describe the construction of a Saccharomyces cerevisiae fusion library in which each endogenous gene is C-terminally tagged with the N-terminal fragment of Venus (VN) for a genome-wide bimolecular fluorescence complementation assay, a powerful technique for identifying PPIs in living cells. We illustrate the utility of the VN fusion library by systematically analyzing the interactome of the small ubiquitin-related modifier (SUMO) and provide previously unavailable information on the subcellular localization, types, and protease dependence of SUMO interactions. Our data set is highly complementary to the existing data sets and represents a useful resource for expanding the understanding of the physiological roles of SUMO. In addition, the VN fusion library provides a useful research tool that makes it feasible to systematically analyze PPIs in the natural cellular context.
•Ugp1 is essential for various cellular activities in Saccharomyces cerevisiae.•Msn2/4 bound to three STREs in the UGP1 promoter in a PKA-dependent manner.•The PHO pathway also controlled ...Msn2/4-dependent regulation of UGP1.•The PKA, PHO and stress response pathways regulate UGP1 expression via Msn2/4.
Ugp1, a UDP-glucose pyrophosphorylase, is essential for various cellular activities in Saccharomyces cerevisiae because its product, UDP-glucose, is a sole glucosyl donor in several metabolic pathways. Here, we report that Msn2/4 play a crucial role in the regulation of UGP1 expression. Msn2/4 bound to three stress response elements in the UGP1 promoter in a protein kinase A (PKA)-dependent manner. Several stresses induced UGP1 transcription, suggesting that the regulation of UGP1 mediated by Msn2/4 is involved in general stress response. Furthermore, the phosphate response (PHO) pathway also controlled Msn2/4-dependent regulation of UGP1, providing a novel link between the PKA and PHO pathways. Our data suggest that signals of the PKA, PHO and stress response pathways regulate UGP1 expression via Msn2/4 in S. cerevisiae.
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BFBNIB, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
BackgroundChimeric antigen receptor (CAR) -T cell therapies have proven to be effective against various liquid tumors. However, the development of CAR-T against solid tumors has been challenging due ...to insufficient efficacy and potential on-target off-tumor toxicities caused by low expression of tumor antigens on normal tissues. Testing various affinities of CARs has demonstrated that lower affinity CARs maintain its anti-tumor effect while minimizing safety concerns (1). In order to develop a CAR-T against solid tumors expressing Mucin1, we have screened for Mucin1 binding antibodies and tested their anti-tumor effect in vitro and in vivo. The potential of on-target off-tumor toxicity was also measured in vitro.MethodsAnti-Mucin1 human single chain variable fragments (scFv) were obtained via screening against a scFv display library. Anti-Mucin1 scFvs were incorporated into CARs and in vitro, in vivo functions against various tumor cells expressing Mucin1 were tested. For in vivo studies, tumor bearing NOG mice (HCC1954 cells) received anti-Mucin1 CAR-T cells. Therapeutic efficacy was evaluated by measuring tumor volumes. Potential on-target off-tumor toxicity against Mucin1 on normal cells was tested by investigating the killing effect of anti-Mucin1 CAR-T against cancer cell line (HCC70) and non-tumorigenic breast epithelial cell line (MCF-10A) in co-culture systemsResultsIn vitro activity of anti-Mucin1 CAR-T cells that displayed a range of affinities for Mucin1 (27nM to 320nM) showed similar cytokine secretion levels and cytotoxicity against Mucin-1 expressing tumor cell lines (HCC70 and T47D). Robust anti-tumor activity was also demonstrated in vivo against large tumors (400~500 mm3) with relatively small numbers of CAR-T cells (0.5 x 106 CAR-T cells per mouse). In vivo expansion of CAR-T cells were observed in all scFv-CAR-T cases and accompanied by close to complete regression of tumors within 25 days post CAR-T cell injection. Of the 4 scFv CAR-Ts, 2H08 (with a Kd of 94nM) was tested for activity against normal breast epithelial cells. When 2H08-CAR-T was cocultured with a mixture of HCC70 and MCF-10A cells, they preferentially killed only the Mucin1 overexpressing HCC70 cells leaving MCF-10 cells intact.ConclusionsOur study demonstrates anti-tumor activity of a novel scFv-derived CAR-T recognizing Mucin1 and its effectiveness in large pre-established tumors in vivo. We also demonstrate that 2H08-CAR-T can distinguish between target overexpressing cancer cells and normal epithelial cells, which suggests that by toning down the affinity of CAR against antigen one can improve the safety profile of solid tumor antigen targeting CAR-T cell therapies.ReferenceCastellarin M, Sands C, Da T, Scholler J, Graham K, Buza E, Fraietta J, Zhao Y, June C. A rational mouse model to detect on-target, off-tumor CAR T cell toxicity. JCI Insight 2020; 5:e136012Ethics ApprovalAll experiments were done under protocols approved by the Institutional Animal Care and Use Committee (IACUC) (Study#LGME21-011).ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.
We have developed a comprehensive TCAD framework that can predict the data retention time distribution of a dynamic random access memory (DRAM) chip using the information about the designed cell ...transistor by coupled physics-based device and statistical simulations. We estimate the cumulative distribution function of the retention time by calculating the leakage currents of a large number of DRAM cells generated by the Monte Carlo methods. The cells have different configurations in the number, locations, and energy levels of the traps that act as localized leakage sources by the extended Shockley-Read-Hall process that includes the trap-assisted tunneling and the stress-induced bandgap narrowing effects. The linear response in the leakage current of each cell to these leakage sources is obtained through the Green's function methods. As an application, we calculate the retention time distribution of a 128-Mb DRAM chip with the 0.18-/spl mu/m ground rule, and verify that the simulation results agree well with the experimental data. We also study the dependence of the retention time distribution on the temperature and negative wordline bias, and discuss the impact of the gate-induced drain leakage on the tail part of the distribution.
The authors have developed an efficient and accurate method to obtain the data retention time distribution of DRAM from the physics-based device simulation and the numerical integration of the ...probability space composed of three independent random variables, namely 1) the number, 2) the location, and 3) the energy level of traps, where each trap acts as a localized leakage source. Compared with the recently proposed Monte Carlo method, this method is much more efficient and free from the statistical error in the tail distribution. Furthermore, it can be easily applied to the problem involving a complex geometry and the nonuniform spatial distribution of traps. With this method, the retention time distribution of an 80-nm technology DRAM with the recess-channel-array transistor is studied
Reactive oxygen species (ROS)-mediated DNA adducts as well as DNA strand breaks are highly mutagenic leading to genomic instability and tumorigenesis. DNA damage repair pathways and oxidative stress ...response signaling have been proposed to be highly associated, but the underlying interaction remains unknown. In this study, we employed mutant strains lacking Rad51, the homolog of E. coli RecA recombinase, and Yap1 or Skn7, two major transcription factors responsive to ROS, to examine genetic interactions between double-strand break (DSB) repair proteins and cellular redox regulators in budding yeast Saccharomyces cerevisiae. Abnormal expression of YAP1 or SKN7 aggravated the mutation rate of rad51 mutants and their sensitivity to DSB- or ROS-generating reagents. Rad51 deficiency exacerbated genome instability in the presence of increased levels of ROS, and the accumulation of DSB lesions resulted in elevated intracellular ROS levels. Our findings suggest that evident crosstalk between DSB repair pathways and ROS signaling proteins contributes to cell survival and maintenance of genome integrity in response to genotoxic stress.
•Rad51 deficiency exacerbates genomic instability in response to increased ROS.•Overexpression of YAP1 or SKN7 adversely affects the growth of rad51 mutant cells.•Accumulation of DSB lesions increases intracellular ROS levels.•DSB repair pathways by HR and ROS responses have genetic crosstalk.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
A comprehensive Monte-Carlo method for the simulation of the data retention time distribution of DRAM cell has been developed using the current Green's function in the calculation of leakage current. ...The Monte-Carlo simulation results including the trap-assisted tunneling and the stress-induced bandgap narrowing models show that our model can explain the effects of the wide range of the bias, doping, and mechanical stress on the retention time distribution for both the main and tail parts of the cells.
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