scholarly journals Exposure to Glycolytic Carbon Sources Reveals a Novel Layer of Regulation for the MalT Regulon

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Sylvia A. Reimann ◽  
Alan J. Wolfe

Bacteria adapt to changing environments by means of tightly coordinated regulatory circuits. The use of synthetic lethality, a genetic phenomenon in which the combination of two nonlethal mutations causes cell death, facilitates identification and study of such circuitry. In this study, we show that theE.coli ompR malTcondouble mutant exhibits a synthetic lethal phenotype that is environmentally conditional. MalTcon, the constitutively active form of the maltose system regulator MalT, causes elevated expression of the outer membrane porin LamB, which leads to death in the absence of the osmoregulator OmpR. However, the presence and metabolism of glycolytic carbon sources, such as sorbitol, promotes viability and unveils a novel layer of regulation within the complex circuitry that controls maltose transport and metabolism.

1975 ◽  
Vol 28 (3) ◽  
pp. 301 ◽  
Author(s):  
MJ Hynes

Mutants of Apergillus nidulanswith lesions in a gene, areA (formerly called amdT), have been isolated by a variety of different selection methods. The areA mutants show a range of pleiotropic growth responses to a number of compounds as sole nitrogen sources, but are normal in utilization of carbon sources. The levels of two amidase enzymes as well as urease have been investigated in the mutants and have been shown to be affected by this gene. Most of the areA mutants have much lower amidase-specific activities when grown in ammonium-containing medium, compared with mycelium incubated in medium la9king a nitrogen source. Some of the areA. mutants do not show derepression of urease upon relief of ammonium repression. The dominance relationships of areA alleles have been investigated in� heterozygous diploids, and these studies lend support to the proposal that areA codes for a positively acting regulatory product. One of the new areA alleles is partially dominant to areA + and areA102. This may be a result of negative complementation or indicate that areA has an additional negative reiuIatory function. Investigation.of various amdR; areA double mutants has led to the conclusion that amdR and areA participate in independent regulatory circuits in the control of acetamide utilizatiol1. Studies on an amdRc; areA.double mutant indicate that areA is involved in derepression of acetamidase upon relief of ammo.nium repression.


2018 ◽  
Vol 62 (4) ◽  
Author(s):  
Suvitha Subramaniam ◽  
Christoph D. Schmid ◽  
Xue Li Guan ◽  
Pascal Mäser

ABSTRACT Combinatorial chemotherapy is necessary for the treatment of malaria. However, finding a suitable partner drug for a new candidate is challenging. Here we develop an algorithm that identifies all of the gene pairs of Plasmodium falciparum that possess orthologues in yeast that have a synthetic lethal interaction but are absent in humans. This suggests new options for drug combinations, particularly for inhibitors of targets such as P. falciparum calcineurin, cation ATPase 4, or phosphatidylinositol 4-kinase.


Genetics ◽  
1998 ◽  
Vol 149 (1) ◽  
pp. 101-116
Author(s):  
Vladimir P Efimov ◽  
N Ronald Morris

Abstract Cytoplasmic dynein is a ubiquitously expressed microtubule motor involved in vesicle transport, mitosis, nuclear migration, and spindle orientation. In the filamentous fungus Aspergillus nidulans, inactivation of cytoplasmic dynein, although not lethal, severely impairs nuclear migration. The role of dynein in mitosis and vesicle transport in this organism is unclear. To investigate the complete range of dynein function in A. nidulans, we searched for synthetic lethal mutations that significantly reduced growth in the absence of dynein but had little effect on their own. We isolated 19 sld (synthetic lethality without dynein) mutations in nine different genes. Mutations in two genes exacerbate the nuclear migration defect seen in the absence of dynein. Mutations in six other genes, including sldA and sldB, show a strong synthetic lethal interaction with a mutation in the mitotic kinesin bimC and, thus, are likely to play a role in mitosis. Mutations in sldA and sldB also confer hypersensitivity to the microtubule-destabilizing drug benomyl. sldA and sldB were cloned by complementation of their mutant phenotypes using an A. nidulans autonomously replicating vector. Sequencing revealed homology to the spindle assembly checkpoint genes BUB1 and BUB3 from Saccharomyces cerevisiae. Genetic interaction between dynein and spindle assembly checkpoint genes, as well as other mitotic genes, indicates that A. nidulans dynein plays a role in mitosis. We suggest a model for dynein motor action in A. nidulans that can explain dynein involvement in both mitosis and nuclear distribution.


eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Chue Vin Chin ◽  
Jisha Antony ◽  
Sarada Ketharnathan ◽  
Anastasia Labudina ◽  
Gregory Gimenez ◽  
...  

Mutations in genes encoding subunits of the cohesin complex are common in several cancers, but may also expose druggable vulnerabilities. We generated isogenic MCF10A cell lines with deletion mutations of genes encoding cohesin subunits SMC3, RAD21, and STAG2 and screened for synthetic lethality with 3009 FDA-approved compounds. The screen identified several compounds that interfere with transcription, DNA damage repair and the cell cycle. Unexpectedly, one of the top ‘hits’ was a GSK3 inhibitor, an agonist of Wnt signaling. We show that sensitivity to GSK3 inhibition is likely due to stabilization of β-catenin in cohesin-mutant cells, and that Wnt-responsive gene expression is highly sensitized in STAG2-mutant CMK leukemia cells. Moreover, Wnt activity is enhanced in zebrafish mutant for cohesin subunits stag2b and rad21. Our results suggest that cohesin mutations could progress oncogenesis by enhancing Wnt signaling, and that targeting the Wnt pathway may represent a novel therapeutic strategy for cohesin-mutant cancers.


2021 ◽  
Author(s):  
Iñigo Apaolaza ◽  
Edurne San José-Enériz ◽  
Luis Valcarcel ◽  
Xabier Agirre ◽  
Felipe Prosper ◽  
...  

Synthetic Lethality (SL) is a promising concept in cancer research. A number of computational methods have been developed to predict SL in cancer metabolism, among which our network-based computational approach, based on genetic Minimal Cut Sets (gMCSs), can be found. A major challenge of these approaches to SL is to systematically consider tumor environment, which is particularly relevant in cancer metabolism. Here, we propose a novel definition of SL for cancer metabolism that integrates genetic interactions and nutrient availability in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase inhibition in different environments. Finally, our novel approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.


Author(s):  
Chue Vin Chin ◽  
Jisha Antony ◽  
Sarada Ketharnathan ◽  
Gregory Gimenez ◽  
Kate M. Parsons ◽  
...  

AbstractMutations in genes encoding subunits of the cohesin complex are common in several cancers, but may also expose druggable vulnerabilities. We generated isogenic MCF10A cell lines with deletion mutations of genes encoding cohesin subunits SMC3, RAD21 and STAG2 and screened for synthetic lethality with 3,009 FDA-approved compounds. The screen identified several compounds that interfere with transcription, DNA damage repair and the cell cycle. Unexpectedly, one of the top ‘hits’ was a GSK3 inhibitor, an agonist of Wnt signaling. We show that sensitivity to GSK3 inhibition is likely due to stabilization of β-catenin in cohesin mutant cells, and that Wnt-responsive gene expression is highly sensitized in STAG2-mutant CMK leukemia cells. Moreover, Wnt activity is enhanced in zebrafish mutant for cohesin subunit rad21. Our results suggest that cohesin mutations could progress oncogenesis by enhancing Wnt signaling, and that targeting the Wnt pathway may represent a novel therapeutic strategy for cohesin mutant cancers.


2018 ◽  
Vol 18 (4) ◽  
pp. 337-346 ◽  
Author(s):  
Anuradha Gupta ◽  
Anas Ahmad ◽  
Aqib Iqbal Dar ◽  
Rehan Khan

Cancer is an evolutionary disease with multiple genetic alterations, accumulated due to chromosomal instability and/or aneuploidy and it sometimes acquires drug-resistant phenotype also. Whole genome sequencing and mutational analysis helped in understanding the differences among persons for predisposition of a disease and its treatment non-responsiveness. Thus, molecular targeted therapies came into existence. Among them, the concept of synthetic lethality have enthralled great attention as it is a pragmatic approach towards exploiting cancer cell specific mutations to specifically kill cancer cells without affecting normal cells and thus enhancing anti-cancer drug therapeutic index. Thus, this approach helped in discovering new therapeutic molecules for development of precision medicine. Nanotechnology helped in delivering these molecules to the target site in an effective concentration thus reducing off target effects of drugs, dose and dosage frequency drugs. Researchers have tried to deliver siRNA targeting synthetic lethal partner for target cancer cell killing by incorporating it in nanoparticles and it has shown efficacy by preventing tumor progression. This review summarizes the brief introduction of synthetic lethality, and synthetic lethal gene interactions, with a major focus on its therapeutic anticancer potential with the application of nanotechnology for development of personalized medicine.


2020 ◽  
Vol 40 (22) ◽  
Author(s):  
Liam Baird ◽  
Takafumi Suzuki ◽  
Yushi Takahashi ◽  
Eiji Hishinuma ◽  
Daisuke Saigusa ◽  
...  

ABSTRACT Activating mutations in KEAP1-NRF2 are frequently found in tumors of the lung, esophagus, and liver, where they are associated with aggressive growth, resistance to cancer therapies, and low overall survival. Despite the fact that NRF2 is a validated driver of tumorigenesis and chemotherapeutic resistance, there are currently no approved drugs which can inhibit its activity. Therefore, there is an urgent clinical need to identify NRF2-selective cancer therapies. To this end, we developed a novel synthetic lethal assay, based on fluorescently labeled isogenic wild-type and Keap1 knockout cell lines, in order to screen for compounds which selectively kill cells in an NRF2-dependent manner. Through this approach, we identified three compounds based on the geldanamycin scaffold which display synthetic lethality with NRF2. Mechanistically, we show that products of NRF2 target genes metabolize the quinone-containing geldanamycin compounds into more potent HSP90 inhibitors, which enhances their cytotoxicity while simultaneously restricting the synthetic lethal effect to cells with aberrant NRF2 activity. As all three of the geldanamycin-derived compounds have been used in clinical trials, they represent ideal candidates for drug repositioning to target the currently untreatable NRF2 activity in cancer.


Cancers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1682 ◽  
Author(s):  
Xiang Deng ◽  
Shaoli Das ◽  
Kristin Valdez ◽  
Kevin Camphausen ◽  
Uma Shankavaram

Synthetic lethality exploits the phenomenon that a mutation in a cancer gene is often associated with new vulnerability which can be uniquely targeted therapeutically, leading to a significant increase in favorable outcome. DNA damage and survival pathways are among the most commonly mutated networks in human cancers. Recent data suggest that synthetic lethal interactions between a tumor defect and a DNA repair pathway can be used to preferentially kill tumor cells. We recently published a method, DiscoverSL, using multi-omic cancer data, that can predict synthetic lethal interactions of potential clinical relevance. Here, we apply the generality of our models in a comprehensive web tool called Synthetic Lethality Bio Discovery Portal (SL-BioDP) and extend the cancer types to 18 cancer genome atlas cohorts. SL-BioDP enables a data-driven computational approach to predict synthetic lethal interactions from hallmark cancer pathways by mining cancer’s genomic and chemical interactions. Our tool provides queries and visualizations for exploring potentially targetable synthetic lethal interactions, shows Kaplan–Meier plots of clinical relevance, and provides in silico validation using short hairpin RNA (shRNA) and drug efficacy data. Our method would thus shed light on mechanisms of synthetic lethal interactions and lead to the discovery of novel anticancer drugs.


2019 ◽  
Vol 20 (S19) ◽  
Author(s):  
Jiang Huang ◽  
Min Wu ◽  
Fan Lu ◽  
Le Ou-Yang ◽  
Zexuan Zhu

Abstract Background Synthetic lethality has attracted a lot of attentions in cancer therapeutics due to its utility in identifying new anticancer drug targets. Identifying synthetic lethal (SL) interactions is the key step towards the exploration of synthetic lethality in cancer treatment. However, biological experiments are faced with many challenges when identifying synthetic lethal interactions. Thus, it is necessary to develop computational methods which could serve as useful complements to biological experiments. Results In this paper, we propose a novel graph regularized self-representative matrix factorization (GRSMF) algorithm for synthetic lethal interaction prediction. GRSMF first learns the self-representations from the known SL interactions and further integrates the functional similarities among genes derived from Gene Ontology (GO). It can then effectively predict potential SL interactions by leveraging the information provided by known SL interactions and functional annotations of genes. Extensive experiments on the synthetic lethal interaction data downloaded from SynLethDB database demonstrate the superiority of our GRSMF in predicting potential synthetic lethal interactions, compared with other competing methods. Moreover, case studies of novel interactions are conducted in this paper for further evaluating the effectiveness of GRSMF in synthetic lethal interaction prediction. Conclusions In this paper, we demonstrate that by adaptively exploiting the self-representation of original SL interaction data, and utilizing functional similarities among genes to enhance the learning of self-representation matrix, our GRSMF could predict potential SL interactions more accurately than other state-of-the-art SL interaction prediction methods.


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