Synthetic Genetic Interactions Research Articles

Abstract 2932: Computational discovery of paralog dependencies drives target identification in lung cancer

Abstract Lung cancer is the leading cause of cancer-related death in the United States, and worldwide, with the 5-year survival rate of non-small cell lung cancer at 24%. Treatment options are limited, and even in cancers that harbor druggable biomarkers, resistance is near-universal. Identifying novel treatment strategies is essential to improve the outcomes of patients with lung cancer and provide secondary strategies for those who acquire resistance to first-line therapeutics. Identifying targeted therapies based on the genotype or expression pattern of cancers is an ongoing endeavor. In lung cancer, treatment of patients that harbor activating mutations in EGFR with specific EGFR inhibitors has improved progression-free survival rates and extended the lifespan of patients diagnosed with this aggressive cancer, demonstrating the utility of targeted therapies based genetic-based vulnerabilities, or synthetic lethal interactions. A rich source of synthetic lethal genetic interactions are paralogous genes. Paralogs result from gene duplication events through evolutionary history, and many paralogs share both sequence homology and functional redundancy. Co-targeting of some paralogous genes induces a fitness defect that is synergistic compared to individual paralog loss alone. Nearly 70% of genes in the human genome are considered paralogs, and until recent efforts from the Berger lab and others, this buffering effect has caused them to be under-represented in lethality studies. Identifying frequently-inactivated paralog genes in lung cancer will provide a platform to identify new vulnerabilities in lung cancer and other cancer types that share mutational backgrounds. To identify patterns of mutation and expression of paralog genes in lung cancer, we have accessed publicly available data sets for both cell line and patient tumor samples. Using TCGA and CCLE data sources, and a set of 1030 paralog pairs identified previously by the Berger lab as potential drug targets, we have identified paralog genes that harbor high mutational frequencies in lung cancer. Using these candidates, we next asked whether genetic inactivation or transcriptional repression of one paralog influences the essentiality of its paired gene using CERES scores generated by the Cancer Dependency Map. Preliminary results identifies several paralog pairs with distinct dependency profiles in cell lines for which expression of one paralog is lost, including MAGOH/MAGOHB and TLK1/TLK2. Further work to characterize these dependencies in relevant cell line models is ongoing. Additionally, the druggability of these targets will be tested using targeted degradation using the dTAG system. This work will uncover a new set of paralog synthetic lethality targets, and further validate the utility of targeting known synthetic lethal paralogs for the treatment of highly lethal lung cancer. Citation Format: Siobhan O'Brien, Alice H. Berger. Computational discovery of paralog dependencies drives target identification in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2932.

ASTER: A Method to Predict Clinically Relevant Synthetic Lethal Genetic Interactions.

A Synthetic Lethal (SL) interaction is a functional relationship between two genes or functional entities where the loss of either entity is viable but the loss of both is lethal. Such pairs can be used to develop targeted anticancer therapies with fewer side effects and reduced overtreatment. However, finding clinically relevant SL interactions remains challenging. Leveraging unified gene expression data of both disease-free and cancerous samples, we design a new technique based on statistical hypothesis testing, called ASTER, to identify SL pairs. We empirically find that the patterns of mutually exclusivity ASTER finds using genomic and transcriptomic data provides a strong signal of synthetic lethality. For large-scale multiple hypothesis testing, we develop an extension called ASTER++ that can utilize additional input gene features within the hypothesis testing framework. Our computational and functional experiments demonstrate the efficacy of ASTER in identifying SL pairs with potential therapeutic benefits.

Abstract A176: Loss of SMAD4 unleashes mTOR and increases dependency on cap-dependent translation in esophageal tumorigenesis

Abstract Application of molecular targeted therapies for esophageal adenocarcinoma (EAC) has been limited by a lack of druggable oncogenic drivers. We propose that synthetic lethal interactions may provide new opportunities for targeted therapies in EAC. We have taken an integrated multi-omics approach incorporating Perturb-Seq (CRISPR editing combined with single cell RNA sequencing) and in vivo tumorigenesis assays to perform high-throughput characterisation of >70 high-confidence EAC driver genes, and genome-wide CRISPR-Cas9 knockout screens in isogenic models of EAC tumorigenesis to identify disease relevant synthetic lethal genetic interactions. MS-based proteomics, reverse phase protein arrays, polysome profiling and bulk RNA-sequencing of isogenic models were utilised to interrogate the biology of bona fide EAC drivers and associated driver specific gene dependencies. The overall goals were to (i) enhance our understanding of EAC tumorigenesis, (ii) identify potential opportunities for therapeutic interventions targeting EAC drivers via synthetic lethal-like approaches, and (iii) reduce the complexity of genetic heterogeneity by categorising EAC drivers with similar phenotypic outcomes. Through our approach we have identified complex crosstalk between the tumor suppressor SMAD4 and regulation of mTOR signaling, with specific downstream effects on translational reprogramming in EAC. Mutation or loss of SMAD4 occurs in up to 20% of EAC, but not pre-malignant tissue (Barrett’s esophagus), and is sufficient to promote transformation of pre-malignant cells in our in vivo tumorigenesis model. In this model, xenotransplanted SMAD4-deficient (via CRISPR-Cas9 knockout or shRNA knockdown) Barrett’s metaplasia cells formed invasive, metastatic tumors after a period of latency. SMAD4 deficient cells had downregulated expression of 4E-BP1, which inhibits EIF4E, the cap-dependent translation initiation factor. This was accompanied by increased mTOR activity, including phosphorylation and inactivation of 4EBP1. Moreover, we found that SMAD4-deficient cells preferentially upregulate cap-dependent translation and become addicted to translation of oncogenic mRNAs. Furthermore, perturbation of additional negative regulators of mTOR signaling in combination with SMAD4 knockout exacerbated these effects and accelerated tumorigenesis in vivo. We have extended these findings to a model of Barrett’s esophagus patient-derived organoids (PDOs) and observed increased proliferative potential of our genetically modified PDOs. Finally, analysing gene ontologies for differentially expressed genes from Perturb-seq revealed that driver-dependent transcriptional changes can be categorized into a smaller number of functional pathways allowing us to potentially consider groups of drivers as functional units. This work advances our understanding of EAC tumorigenesis, provides new mechanistic insights into SMAD4-driven transformation as well as novel potential therapeutic avenues for SMAD4-deficient EAC. Citation Format: Julia V Milne, Ebtihal Mustafa, Kenji Fujihara, Eric Kusnadi, Niko Thio, Maree Pechlivanis, Carlos Cabalag, Twishi Gulati, Kaylene Simpson, Cuong Duong, Luc Furic, Wayne Phillips, Nicholas J Clemons. Loss of SMAD4 unleashes mTOR and increases dependency on cap-dependent translation in esophageal tumorigenesis [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A176.

A global genetic interaction network by single-cell imaging and machine learning.

Cellular and organismal phenotypes are controlled by complex gene regulatory networks. However, reference maps of gene function are still scarce across different organisms. Here, we generated synthetic genetic interaction and cell morphology profiles of more than 6,800 genes in cultured Drosophila cells. The resulting map of genetic interactions was used for machine learning-based gene function discovery, assigning functions to genes in 47 modules. Furthermore, we devised Cytoclass as a method to dissect genetic interactions for discrete cell states at the single-cell resolution. This approach identified an interaction of Cdk2 and the Cop9 signalosome complex, triggering senescence-associated secretory phenotypes and immunogenic conversion in hemocytic cells. Together, our data constitute a genome-scale resource of functional gene profiles to uncover the mechanisms underlying genetic interactions and their plasticity at the single-cell level.

BAP1 Malignant Pleural Mesothelioma Mutations in Caenorhabditis elegans Reveal Synthetic Lethality between ubh-4/BAP1 and the Proteasome Subunit rpn-9/PSMD13.

The deubiquitinase BAP1 (BRCA1-associated protein 1) is associated with BAP1 tumor predisposition syndrome (TPDS). BAP1 is a tumor suppressor gene whose alterations in cancer are commonly caused by gene mutations leading to protein loss of function. By CRISPR-Cas, we have generated mutations in ubh-4, the BAP1 ortholog in Caenorhabditis elegans, to model the functional impact of BAP1 mutations. We have found that a mimicked BAP1 cancer missense mutation (UBH-4 A87D; BAP1 A95D) resembles the phenotypes of ubh-4 deletion mutants. Despite ubh-4 being ubiquitously expressed, the gene is not essential for viability and its deletion causes only mild phenotypes without affecting 20S proteasome levels. Such viability facilitated an RNAi screen for ubh-4 genetic interactors that identified rpn-9, the ortholog of human PSMD13, a gene encoding subunit of the regulatory particle of the 26S proteasome. ubh-4[A87D], similarly to ubh-4 deletion, cause a synthetic genetic interaction with rpn-9 inactivation affecting body size, lifespan, and the development of germ cells. Finally, we show how ubh-4 inactivation sensitizes animals to the chemotherapeutic agent Bortezomib, which is a proteasome inhibitor. Thus, we have established a model to study BAP1 cancer-related mutations in C. elegans, and our data points toward vulnerabilities that should be studied to explore therapeutic opportunities within the complexity of BAP1 tumors.

Undecaprenyl phosphate translocases confer conditional microbial fitness

The microbial cell wall is essential for maintenance of cell shape and resistance to external stressors1. The primary structural component of the cell wall is peptidoglycan, a glycopolymer with peptide crosslinks located outside of the cell membrane1. Peptidoglycan biosynthesis and structure are responsive to shifting environmental conditions such as pH and salinity2–6, but the mechanisms underlying such adaptations are incompletely understood. Precursors of peptidoglycan and other cell surface glycopolymers are synthesized in the cytoplasm and then delivered across the cell membrane bound to the recyclable lipid carrier undecaprenyl phosphate7 (C55-P, also known as UndP). Here we identify the DUF368-containing and DedA transmembrane protein families as candidate C55-P translocases, filling a critical gap in knowledge of the proteins required for the biogenesis of microbial cell surface polymers. Gram-negative and Gram-positive bacteria lacking their cognate DUF368-containing protein exhibited alkaline-dependent cell wall and viability defects, along with increased cell surface C55-P levels. pH-dependent synthetic genetic interactions between DUF368-containing proteins and DedA family members suggest that C55-P transporter usage is dynamic and modulated by environmental inputs. C55-P transporter activity was required by the cholera pathogen for growth and cell shape maintenance in the intestine. We propose that conditional transporter reliance provides resilience in lipid carrier recycling, bolstering microbial fitness both inside and outside the host.

SCFFBXW7 regulates G2-M progression through control of CCNL1 ubiquitination.

FBXW7, which encodes a substrate-specific receptor of an SCF E3 ligase complex, is a frequently mutated human tumor suppressor gene known to regulate the post-translational stability of various proteins involved in cellular proliferation. Here, using genome-wide CRISPR screens, we report a novel synthetic lethal genetic interaction between FBXW7 and CCNL1 and describe CCNL1 as a new substrate of the SCF-FBXW7 E3 ligase. Further analysis showed that the CCNL1-CDK11 complex is critical at the G2-M phase of the cell cycle since defective CCNL1 accumulation, resulting from FBXW7 mutation, leads to shorter mitotic time. Cells harboring FBXW7 loss-of-function mutations are hypersensitive to treatment with a CDK11 inhibitor, highlighting a genetic vulnerability that could be leveraged for cancer treatment.

NHR-23 and SPE-44 regulate distinct sets of genes during Caenorhabditis elegans spermatogenesis.

Spermatogenesis is the process through which mature male gametes are formed and is necessary for the transmission of genetic information. While much work has established how sperm fate is promoted and maintained, less is known about how the sperm morphogenesis program is executed. We previously identified a novel role for the nuclear hormone receptor transcription factor, NHR-23, in promoting Caenorhabditis elegans spermatogenesis. The depletion of NHR-23 along with SPE-44, another transcription factor that promotes spermatogenesis, caused additive phenotypes. Through RNA-seq, we determined that NHR-23 and SPE-44 regulate distinct sets of genes. The depletion of both NHR-23 and SPE-44 produced yet another set of differentially regulated genes. NHR-23-regulated genes are enriched in phosphatases, consistent with the switch from genome quiescence to post-translational regulation in spermatids. In the parasitic nematode Ascaris suum, MFP1 and MFP2 control the polymerization of Major Sperm Protein, the molecule that drives sperm motility and serves as a signal to promote ovulation. NHR-23 and SPE-44 regulate several MFP2 paralogs, and NHR-23 depletion from the male germline caused defective localization of MSD/MFP1 and NSPH-2/MFP2. Although NHR-23 and SPE-44 do not transcriptionally regulate the casein kinase gene spe-6, a key regulator of sperm development, SPE-6 protein is lost following NHR-23+SPE-44 depletion. Together, these experiments provide the first mechanistic insight into how NHR-23 promotes spermatogenesis and an entry point to understanding the synthetic genetic interaction between nhr-23 and spe-44.

Repression of essential cell cycle genes increases cellular fitness.

A network of transcription factors (TFs) coordinates transcription with cell cycle events in eukaryotes. Most TFs in the network are phosphorylated by cyclin-dependent kinase (CDK), which limits their activities during the cell cycle. Here, we investigate the physiological consequences of disrupting CDK regulation of the paralogous repressors Yhp1 and Yox1 in yeast. Blocking Yhp1/Yox1 phosphorylation increases their levels and decreases expression of essential cell cycle regulatory genes which, unexpectedly, increases cellular fitness in optimal growth conditions. Using synthetic genetic interaction screens, we find that Yhp1/Yox1 mutations improve the fitness of mutants with mitotic defects, including condensin mutants. Blocking Yhp1/Yox1 phosphorylation simultaneously accelerates the G1/S transition and delays mitotic exit, without decreasing proliferation rate. This mitotic delay partially reverses the chromosome segregation defect of condensin mutants, potentially explaining their increased fitness when combined with Yhp1/Yox1 phosphomutants. These findings reveal how altering expression of cell cycle genes leads to a redistribution of cell cycle timing and confers a fitness advantage to cells.

Synthetic Genetic Interactions Reveal a Dense and Cryptic Regulatory Network of Small Noncoding RNAs in Escherichia coli.

ABSTRACTOver the past 20 years, we have learned that bacterial small noncoding RNAs (sRNAs) can rapidly effect changes in gene expression in response to stress. However, the broader role and impact of sRNA-mediated regulation in promoting bacterial survival has remained elusive. Indeed, there are few examples where disruption of sRNA-mediated gene regulation results in a discernible change in bacterial growth or survival. The lack of phenotypes attributable to loss of sRNA function suggests that either sRNAs are wholly dispensable or functional redundancies mask the impact of deleting a single sRNA. We investigated synthetic genetic interactions among sRNA genes in Escherichia coli by constructing pairwise deletions in 54 genes, including 52 sRNAs. Some 1,373 double deletion strains were studied for growth defects under 32 different nutrient stress conditions and revealed 1,131 genetic interactions. In one example, we identified a profound synthetic lethal interaction between ArcZ and CsrC when E. coli was grown on pyruvate, lactate, oxaloacetate, or d-/l-alanine, and we provide evidence that the expression of ppsA is dysregulated in the double deletion background, causing the conditionally lethal phenotype. This work employs a unique platform for studying sRNA-mediated gene regulation and sheds new light on the genetic network of sRNAs that underpins bacterial growth.

Auxotrophic and prototrophic conditional genetic networks reveal the rewiring of transcription factors in Escherichia coli

Bacterial transcription factors (TFs) are widely studied in Escherichia coli. Yet it remains unclear how individual genes in the underlying pathways of TF machinery operate together during environmental challenge. Here, we address this by applying an unbiased, quantitative synthetic genetic interaction (GI) approach to measure pairwise GIs among all TF genes in E. coli under auxotrophic (rich medium) and prototrophic (minimal medium) static growth conditions. The resulting static and differential GI networks reveal condition-dependent GIs, widespread changes among TF genes in metabolism, and new roles for uncharacterized TFs (yjdC, yneJ, ydiP) as regulators of cell division, putrescine utilization pathway, and cold shock adaptation. Pan-bacterial conservation suggests TF genes with GIs are co-conserved in evolution. Together, our results illuminate the global organization of E. coli TFs, and remodeling of genetic backup systems for TFs under environmental change, which is essential for controlling the bacterial transcriptional regulatory circuits.

Genetic background and mistranslation frequency determine the impact of mistranslating tRNASerUGG.

Transfer RNA variants increase the frequency of mistranslation, the misincorporation of an amino acid not specified by the “standard” genetic code, to frequencies approaching 10% in yeast and bacteria. Cells cope with these variants by having multiple copies of each tRNA isodecoder and through pathways that deal with proteotoxic stress. In this study, we define the genetic interactions of the gene encoding tRNASerUGG,G26A, which mistranslates serine at proline codons. Using a collection of yeast temperature-sensitive alleles, we identify negative synthetic genetic interactions between the mistranslating tRNA and 109 alleles representing 91 genes, with nearly half of the genes having roles in RNA processing or protein folding and turnover. By regulating tRNA expression, we then compare the strength of the negative genetic interaction for a subset of identified alleles under differing amounts of mistranslation. The frequency of mistranslation correlated with the impact on cell growth for all strains analyzed; however, there were notable differences in the extent of the synthetic interaction at different frequencies of mistranslation depending on the genetic background. For many of the strains, the extent of the negative interaction with tRNASerUGG,G26A was proportional to the frequency of mistranslation or only observed at intermediate or high frequencies. For others, the synthetic interaction was approximately equivalent at all frequencies of mistranslation. As humans contain similar mistranslating tRNAs, these results are important when analyzing the impact of tRNA variants on disease, where both the individual’s genetic background and the expression of the mistranslating tRNA variant need to be considered.

Abstract MS1-1: CRISPR screens to identify novel DNA repair defects synthetic lethal therapies

Abstract The orchestration of DNA repair is of fundamental importance to the maintenance of genomic integrity and tumor suppression. DNA damage must be detected in the context of the varied chromatin landscape, its presence must be communicated throughout the cell to alter many ongoing processes, and the machinery that will mend the lesion must be recruited to the damage site. In my presentation, I will discuss our recent efforts in mapping genome maintenance pathways using genome-scale CRISPR/Cas9 screens in human cells. I will highlight how these screens can also identify potentially actionable synthetic lethal genetic interactions that could form the basis of new oncology drug discovery efforts. I will focus particularly on our efforts to uncover and characterize the synthetic lethal interaction network surrounding BRCA1 and BRCA2 deficiency, as well as our work that led to the discovery that inhibition of the PKMYT1 kinase is lethal in cells with amplification in the cyclin E-coding gene, CCNE1. Citation Format: D Durocher. CRISPR screens to identify novel DNA repair defects synthetic lethal therapies [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr MS1-1.

Using Synthetic Genetic Interactions in Candida glabrata as a Novel Method to Detect Genes with Roles in Antifungal Drug Resistance.

Synthetic genetic interaction analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the interactions between genes, categorize into biological pathways, and characterize genes of unknown function. It has been extensively employed in model organisms for fundamental, systems-level assessment of the interactions between genes. However, more recently, genetic interaction mapping has been applied to fungal pathogens and has been instrumental for the study of clinically important infectious organisms. This protocol herein explains in the detail the methodology and analysis that can be employed to develop interaction maps in microbial pathogens. Such techniques can aid in bridging our understanding of complex genetic networks, with applications to diverse microbial pathogens to further our understanding of virulence, the use of antimicrobial therapies, and host-pathogen interactions.

Conducting genetic interaction analysis with CRISPR-Cas9-based strategies in Candida albicans

Candida albicans is an opportunistic fungal pathogen found in the oral mucosa, the gut, the vaginal mucosa, and humans' skin. While C. albicans can cause superficial infections, severe invasive infections can occur in immunocompromised individuals. Understanding the survival mechanisms and pathogenesis of C. albicans is critical for novel antifungal drug discovery. Determining the relationships between different genes can create a genetic interaction map, which can identify complementary gene sets, central to C. albicans survival, as potential drug targets in combination therapy. A genetic approach using the CRISPR-Cas9-based genome editing platform will focus on genetic interaction analysis of C. albicans stress response genes. The ultimate goal is to create a stress response gene deletion library to study its pathogen survival role. This library of single and double stress response gene mutants will be screened under diverse growth conditions to assess their relative fitness. Genetic interaction analysis will help map out epistatic interactions between fungal genes involved in growth, survival, and pathogenesis and uncover putative targets for combination antifungal therapy based on negative or synthetic lethal genetic interactions.

Genetic landscape of T cells identifies synthetic lethality for T-ALL

To capture the global gene network regulating the differentiation of immature T cells in an unbiased manner, large-scale forward genetic screens in zebrafish were conducted and combined with genetic interaction analysis. After ENU mutagenesis, genetic lesions associated with failure of T cell development were identified by meiotic recombination mapping, positional cloning, and whole genome sequencing. Recessive genetic variants in 33 genes were identified and confirmed as causative by additional experiments. The mutations affected T cell development but did not perturb the development of an unrelated cell type, growth hormone-expressing somatotrophs, providing an important measure of cell-type specificity of the genetic variants. The structure of the genetic network encompassing the identified components was established by a subsequent genetic interaction analysis, which identified many instances of positive (alleviating) and negative (synthetic) genetic interactions. Several examples of synthetic lethality were subsequently phenocopied using combinations of small molecule inhibitors. These drugs not only interfered with normal T cell development, but also elicited remission in a model of T cell acute lymphoblastic leukaemia. Our findings illustrate how genetic interaction data obtained in the context of entire organisms can be exploited for targeted interference with specific cell types and their malignant derivatives.

SLC5A3-Dependent Myo-inositol Auxotrophy in Acute Myeloid Leukemia.

An enhanced requirement for nutrients is a hallmark property of cancer cells. Here, we optimized an in vivo genetic screening strategy in acute myeloid leukemia (AML), which led to the identification of the myo-inositol transporter SLC5A3 as a dependency in this disease. We demonstrate that SLC5A3 is essential to support a myo-inositol auxotrophy in AML. The commonality among SLC5A3-dependent AML lines is the transcriptional silencing of ISYNA1, which encodes the rate-limiting enzyme for myo-inositol biosynthesis, inositol-3-phosphate synthase 1. We use gain- and loss-of-function experiments to reveal a synthetic lethal genetic interaction between ISYNA1 and SLC5A3 in AML, which function redundantly to sustain intracellular myo-inositol. Transcriptional silencing and DNA hypermethylation of ISYNA1 occur in a recurrent manner in human AML patient samples, in association with IDH1/IDH2 and CEBPA mutations. Our findings reveal myo-inositol as a nutrient dependency in AML caused by the aberrant silencing of a biosynthetic enzyme. SIGNIFICANCE: We show how epigenetic silencing can provoke a nutrient dependency in AML by exploiting a synthetic lethality relationship between biosynthesis and transport of myo-inositol. Blocking the function of this solute carrier may have therapeutic potential in an epigenetically defined subset of AML.This article is highlighted in the In This Issue feature, p. 275.

The amino acid substitution affects cellular response to mistranslation.

Mistranslation, the misincorporation of an amino acid not specified by the “standard” genetic code, occurs in all organisms. tRNA variants that increase mistranslation arise spontaneously and engineered tRNAs can achieve mistranslation frequencies approaching 10% in yeast and bacteria. Interestingly, human genomes contain tRNA variants with the potential to mistranslate. Cells cope with increased mistranslation through multiple mechanisms, though high levels cause proteotoxic stress. The goal of this study was to compare the genetic interactions and the impact on transcriptome and cellular growth of two tRNA variants that mistranslate at a similar frequency but create different amino acid substitutions in Saccharomyces cerevisiae. One tRNA variant inserts alanine at proline codons whereas the other inserts serine for arginine. Both tRNAs decreased growth rate, with the effect being greater for arginine to serine than for proline to alanine. The tRNA that substituted serine for arginine resulted in a heat shock response. In contrast, heat shock response was minimal for proline to alanine substitution. Further demonstrating the significance of the amino acid substitution, transcriptome analysis identified unique up- and down-regulated genes in response to each mistranslating tRNA. Number and extent of negative synthetic genetic interactions also differed depending upon type of mistranslation. Based on the unique responses observed for these mistranslating tRNAs, we predict that the potential of mistranslation to exacerbate diseases caused by proteotoxic stress depends on the tRNA variant. Furthermore, based on their unique transcriptomes and genetic interactions, different naturally occurring mistranslating tRNAs have the potential to negatively influence specific diseases.

Genetic and Chemical-Genetic Interactions Map Biogenesis and Permeability Determinants of the Outer Membrane of Escherichia coli.

Gram-negative bacteria are intrinsically resistant to many antibiotics due to their outer membrane barrier. Although the outer membrane has been studied for decades, there is much to uncover about the biology and permeability of this complex structure. Investigating synthetic genetic interactions can reveal a great deal of information about genetic function and pathway interconnectivity. Here, we performed synthetic genetic arrays (SGAs) in Escherichia coli by crossing a subset of gene deletion strains implicated in outer membrane permeability with nonessential gene and small RNA (sRNA) deletion collections. Some 155,400 double-deletion strains were grown on rich microbiological medium with and without subinhibitory concentrations of two antibiotics excluded by the outer membrane, vancomycin and rifampin, to probe both genetic interactions and permeability. The genetic interactions of interest were synthetic sick or lethal (SSL) gene deletions that were detrimental to the cell in combination but had a negligible impact on viability individually. On average, there were ∼30, ∼36, and ∼40 SSL interactions per gene under no-drug, rifampin, and vancomycin conditions, respectively; however, many of these involved frequent interactors. Our data sets have been compiled into an interactive database called the Outer Membrane Interaction (OMI) Explorer, where genetic interactions can be searched, visualized across the genome, compared between conditions, and enriched for gene ontology (GO) terms. A set of SSL interactions revealed connectivity and permeability links between enterobacterial common antigen (ECA) and lipopolysaccharide (LPS) of the outer membrane. This data set provides a novel platform to generate hypotheses about outer membrane biology and permeability.IMPORTANCE Gram-negative bacteria are a major concern for public health, particularly due to the rise of antibiotic resistance. It is important to understand the biology and permeability of the outer membrane of these bacteria in order to increase the efficacy of antibiotics that have difficulty penetrating this structure. Here, we studied the genetic interactions of a subset of outer membrane-related gene deletions in the model Gram-negative bacterium E. coli We systematically combined these mutants with 3,985 nonessential gene and small RNA deletion mutations in the genome. We examined the viability of these double-deletion strains and probed their permeability characteristics using two antibiotics that have difficulty crossing the outer membrane barrier. An understanding of the genetic basis for outer membrane integrity can assist in the development of new antibiotics with favorable permeability properties and the discovery of compounds capable of increasing outer membrane permeability to enhance the activity of existing antibiotics.

FMN reduces Amyloid-\u03b2 toxicity in yeast by regulating redox status and cellular metabolism

Alzheimer’s disease (AD) is defined by progressive neurodegeneration, with oligomerization and aggregation of amyloid-β peptides (Aβ) playing a pivotal role in its pathogenesis. In recent years, the yeast Saccharomyces cerevisiae has been successfully used to clarify the roles of different human proteins involved in neurodegeneration. Here, we report a genome-wide synthetic genetic interaction array to identify toxicity modifiers of Aβ42, using yeast as the model organism. We find that FMN1, the gene encoding riboflavin kinase, and its metabolic product flavin mononucleotide (FMN) reduce Aβ42 toxicity. Classic experimental analyses combined with RNAseq show the effects of FMN supplementation to include reducing misfolded protein load, altering cellular metabolism, increasing NADH/(NADH + NAD+) and NADPH/(NADPH + NADP+) ratios and increasing resistance to oxidative stress. Additionally, FMN supplementation modifies Htt103QP toxicity and α-synuclein toxicity in the humanized yeast. Our findings offer insights for reducing cytotoxicity of Aβ42, and potentially other misfolded proteins, via FMN-dependent cellular pathways.