Epistasis-driven identification of SLC25A51 as a regulator of human mitochondrial NAD import

AbstractAbout a thousand genes in the human genome encode for membrane transporters. Among these, several solute carrier proteins (SLCs), representing the largest group of transporters, are still orphan and lack functional characterization. We reasoned that assessing genetic interactions among SLCs may be an efficient way to obtain functional information allowing their deorphanization. Here we describe a network of strong genetic interactions indicating a contribution to mitochondrial respiration and redox metabolism for SLC25A51/MCART1, an uncharacterized member of the SLC25 family of transporters. Through a combination of metabolomics, genomics and genetics approaches, we demonstrate a role for SLC25A51 as enabler of mitochondrial import of NAD, showcasing the potential of genetic interaction-driven functional gene deorphanization.

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A systematic genetic interaction map of human solute carriers assigns a role to SLC25A51/MCART1 in mitochondrial NAD uptake

10.1101/2020.08.31.275818 ◽

2020 ◽

Cited By ~ 1

Author(s):

Enrico Girardi ◽

Giuseppe Fiume ◽

Ulrich Goldmann ◽

Celine Sin ◽

Felix Müller ◽

...

Keyword(s):

Environmental Changes ◽

Genetic Interaction ◽

Genetic Interactions ◽

Functional Categories ◽

Functional Interaction ◽

Mitochondrial Import ◽

Systematic Mapping ◽

Solute Carriers ◽

Metabolic States ◽

Interaction Map

Solute Carriers (SLCs) represent the largest family of human transporter proteins, consisting of more than 400 members1,2. Despite the importance of these proteins in determining metabolic states and adaptation to environmental changes, a large proportion of them is still orphan and lacks associated substrates1,3,4. Here we describe a systematic mapping of genetic interactions among SLCs in human cells. Network-based identification of correlated genetic interaction profile neighborhoods resulted in initial functional assignments to dozens of previously uncharacterized SLCs. Focused validation identified SLC25A51/MCART1 as the SLC enabling mitochondrial import of NAD(H). This functional interaction map of the human transportome offers a route for systematic integration of transporter function with metabolism and provides a blueprint for elucidation of the dark genome by biochemical and functional categories.

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Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interaction networks

10.1101/111252 ◽

2017 ◽

Cited By ~ 3

Author(s):

Scott W. Simpkins ◽

Justin Nelson ◽

Raamesh Deshpande ◽

Sheena C. Li ◽

Jeff S. Piotrowski ◽

...

Keyword(s):

Biological Process ◽

Genetic Interaction ◽

Interaction Network ◽

Chemical Compounds ◽

Genetic Interactions ◽

Interaction Networks ◽

Biological Processes ◽

Functional Information ◽

Chemical Genetic ◽

Genetic Interaction Network

AbstractChemical-genetic interactions – observed when the treatment of mutant cells with chemical compounds reveals unexpected phenotypes – contain rich functional information linking compounds to their cellular modes of action. To systematically identify these interactions, an array of mutants is challenged with a compound and monitored for fitness defects, generating a chemical-genetic interaction profile that provides a quantitative, unbiased description of the cellular function(s) perturbed by the compound. Genetic interactions, obtained from genome-wide double-mutant screens, provide a key for interpreting the functional information contained in chemical-genetic interaction profiles. Despite the utility of this approach, integrative analyses of genetic and chemical-genetic interaction networks have not been systematically evaluated. We developed a method, called CG-TARGET (Chemical Genetic Translation via A Reference Genetic nETwork), that integrates large-scale chemical-genetic interaction screening data with a genetic interaction network to predict the biological processes perturbed by compounds. CG-TARGET compared favorably to a baseline enrichment approach across a variety of benchmarks, achieving similar accuracy while substantially improving the ability to control the false discovery rate of biological process predictions. We applied CG-TARGET to a recent screen of nearly 14,000 chemical compounds in Saccharomyces cerevisiae, integrating this dataset with the global S. cerevisiae genetic interaction network to prioritize over 1500 compounds with high-confidence biological process predictions for further study. Upon investigation of the compatibility of chemical-genetic and genetic interaction profiles, we observed that one-third of observed chemical-genetic interactions contributed to the highest-confidence biological process predictions and that negative chemical-genetic interactions overwhelmingly formed the basis of these predictions. We present here a detailed characterization of the CG-TARGET method along with experimental validation of predicted biological process targets, focusing on inhibitors of tubulin polymerization and cell cycle progression. Our approach successfully demonstrates the use of genetic interaction networks in the functional annotation of compounds to biological processes.

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Identification and Functional Characterization of Zebrafish Solute Carrier Slc16a2 (Mct8) as a Thyroid Hormone Membrane Transporter

Endocrinology ◽

10.1210/en.2011-1166 ◽

2011 ◽

Vol 152 (12) ◽

pp. 5065-5073 ◽

Cited By ~ 49

Author(s):

Francisco J. Arjona ◽

Erik de Vrieze ◽

Theo J. Visser ◽

Gert Flik ◽

Peter H. M. Klaren

Keyword(s):

Thyroid Hormone ◽

Functional Characterization ◽

Proteolytic Processing ◽

The Body ◽

Membrane Transporters ◽

Monocarboxylate Transporter ◽

Independent Manner ◽

Organ Systems ◽

Solute Carrier ◽

Cloned Cdna

Most components of the thyroid system in bony fish have been described and characterized, with the notable exception of thyroid hormone membrane transporters. We have cloned, sequenced, and expressed the zebrafish solute carrier Slc16a2 (also named monocarboxylate transporter Mct8) cDNA and established its role as a thyroid hormone transport protein. The cloned cDNA shares 56–57% homology with its mammalian orthologs. The 526-amino-acid sequence contains 12 predicted transmembrane domains. An intracellular N-terminal PEST domain, thought to be involved in proteolytic processing of the protein, is present in the zebrafish sequence. Measured at initial rate and at the body/rearing temperature of zebrafish (26 C), T3 uptake by zebrafish Slc16a2 is a saturable process with a calculated Michaelis-Menten constant of 0.8 μM T3. The rate of T3 uptake is temperature dependent and Na+ independent. Interestingly, at 26 C, zebrafish Slc16a2 does not transport T4. This implies that at a normal body temperature in zebrafish, Slc16a2 protein is predominantly involved in T3 uptake. When measured at 37 C, zebrafish Slc16a2 transports T4 in a Na+-independent manner. In adult zebrafish, the Slc16a2 gene is highly expressed in brain, gills, pancreas, liver, pituitary, heart, kidney, and gut. Beginning from the midblastula stage, Slc16a2 is also expressed during zebrafish early development, the highest expression levels occurring 48 h after fertilization. This is the first direct evidence for thyroid hormone membrane transporters in fish. We suggest that Slc16a2 plays a key role in the local availability of T3 in adult tissues as well as during the completion of morphogenesis of primary organ systems.

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Expression of solute carrier proteins SLC35E1 and SLC35E2B in skin lesions of patients with Mycobacterium infection

Chinese Journal of Dermatology ◽

10.35541/cjd.20200429 ◽

2021 ◽

Keyword(s):

Skin Lesions ◽

Carrier Proteins ◽

Mycobacterium Infection ◽

Solute Carrier

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Genetic Interactions Effects of Cardiovascular Disorder Using Computational Models: A Review

Current Biotechnology ◽

10.2174/2211550109999201008125800 ◽

2020 ◽

Vol 9 (3) ◽

pp. 177-191

Author(s):

Sridharan Priya ◽

Radha K. Manavalan

Keyword(s):

Coronary Artery Disease ◽

Coronary Artery ◽

Cardiovascular Diseases ◽

Computational Models ◽

Genetic Interaction ◽

Association Studies ◽

Genetic Interactions ◽

Computational Techniques ◽

Genome Wide Association Studies ◽

Artery Disease

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.

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Stress Mediating Genes in Aging, Health, and Longevity Traits: Effects of Multiple Interactions

Innovation in Aging ◽

10.1093/geroni/igaa057.915 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 286-286

Author(s):

Anatoliy Yashin ◽

Dequing Wu ◽

Konstantin Arbeev ◽

Arseniy Yashkin ◽

Galina Gorbunova ◽

...

Keyword(s):

Strong Interaction ◽

Genetic Interaction ◽

Interaction Effects ◽

Genetic Interactions ◽

Risk Scores ◽

Data Sets ◽

Interaction Patterns ◽

Polygenic Risk ◽

Drug Candidates ◽

Aging Health

Abstract Persistent stress of external or internal origin accelerates aging, increases risk of aging related health disorders, and shortens lifespan. Stressors activate stress response genes, and their products collectively influence traits. The variability of stressors and responses to them contribute to trait heterogeneity, which may cause the failure of clinical trials for drug candidates. The objectives of this paper are: to address the heterogeneity issue; to evaluate collective interaction effects of genetic factors on Alzheimer’s disease (AD) and longevity using HRS data; to identify differences and similarities in patterns of genetic interactions within two genders; and to compare AD related genetic interaction patterns in HRS and LOADFS data. To reach these objectives we: selected candidate genes from stress related pathways affecting AD/longevity; implemented logistic regression model with interaction term to evaluate effects of SNP-pairs on these traits for males and females; constructed the novel interaction polygenic risk scores for SNPs, which showed strong interaction potential, and evaluated effects of these scores on AD/longevity; and compared patterns of genetic interactions within the two genders and within two datasets. We found there were many genes involved in highly significant interactions that were the same and that were different within the two genders. The effects of interaction polygenic risk scores on AD were strong and highly statistically significant. These conclusions were confirmed in analyses of interaction effects on longevity trait using HRS data. Comparison of HRS to LOADFS data showed that many genes had strong interaction effects on AD in both data sets.

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Genome-wide mapping of unexplored essential regions in the Saccharomyces cerevisiae genome: evidence for hidden synthetic lethal combinations in a genetic interaction network

Nucleic Acids Research ◽

10.1093/nar/gku576 ◽

2014 ◽

Vol 42 (15) ◽

pp. 9838-9853 ◽

Cited By ~ 6

Author(s):

Saeed Kaboli ◽

Takuya Yamakawa ◽

Keisuke Sunada ◽

Tao Takagaki ◽

Yu Sasano ◽

...

Keyword(s):

Saccharomyces Cerevisiae ◽

Genetic Interaction ◽

Interaction Network ◽

Essential Genes ◽

Genetic Interactions ◽

Lethal Gene ◽

Synthetic Lethal ◽

Genome Wide ◽

A Genome ◽

Wide Scale

Abstract Despite systematic approaches to mapping networks of genetic interactions in Saccharomyces cerevisiae, exploration of genetic interactions on a genome-wide scale has been limited. The S. cerevisiae haploid genome has 110 regions that are longer than 10 kb but harbor only non-essential genes. Here, we attempted to delete these regions by PCR-mediated chromosomal deletion technology (PCD), which enables chromosomal segments to be deleted by a one-step transformation. Thirty-three of the 110 regions could be deleted, but the remaining 77 regions could not. To determine whether the 77 undeletable regions are essential, we successfully converted 67 of them to mini-chromosomes marked with URA3 using PCR-mediated chromosome splitting technology and conducted a mitotic loss assay of the mini-chromosomes. Fifty-six of the 67 regions were found to be essential for cell growth, and 49 of these carried co-lethal gene pair(s) that were not previously been detected by synthetic genetic array analysis. This result implies that regions harboring only non-essential genes contain unidentified synthetic lethal combinations at an unexpectedly high frequency, revealing a novel landscape of genetic interactions in the S. cerevisiae genome. Furthermore, this study indicates that segmental deletion might be exploited for not only revealing genome function but also breeding stress-tolerant strains.

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Sequence and Chromosomal Assignment of a Novel cDNA Identified by Immunoscreening of a Thyroid Expression Library: Similarity to a Family of Mitochondrial Solute Carrier Proteins

Molecular Endocrinology ◽

10.1210/mend-3-9-1498 ◽

1989 ◽

Vol 3 (9) ◽

pp. 1498-1508 ◽

Cited By ~ 39

Author(s):

Raffaele Zarrilli ◽

Edward L. Oates ◽

O. Wesley McBride ◽

Michael I. Lerman ◽

John Y. Chan ◽

...

Keyword(s):

Chromosomal Assignment ◽

Carrier Proteins ◽

Expression Library ◽

Solute Carrier

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Systematic characterization and genetic interaction analysis of adhesins in Candida albicans virulence

10.1101/2020.10.22.350991 ◽

2020 ◽

Author(s):

Sierra Rosiana ◽

Liyang Zhang ◽

Grace H. Kim ◽

Alexey V. Revtovich ◽

Arjun Sukumaran ◽

...

Keyword(s):

Candida Albicans ◽

Genetic Interaction ◽

Interaction Analysis ◽

Genetic Interactions ◽

Fungal Virulence ◽

C Elegans ◽

Adhesin Proteins ◽

Insight Into

AbstractCandida albicans is a microbial fungus that exists as a commensal member of the human microbiome and an opportunistic pathogen. Cell surface-associated adhesin proteins play a crucial role in C. albicans’ ability to undergo cellular morphogenesis, develop robust biofilms, colonize, and cause infection in a host. However, a comprehensive analysis of the role and relationships between these adhesins has not been explored. We previously established a CRISPR-based platform for efficient generation of single- and double-gene deletions in C. albicans, which was used to construct a library of 144 mutants, comprising 12 unique adhesin genes deleted singly, or in every possible combination of double deletions. Here, we exploit this adhesin mutant library to explore the role of adhesin proteins in C. albicans virulence. We perform a comprehensive, high-throughput screen of this library, using Caenorhabditis elegans as a simplified model host system, which identified mutants critical for virulence and significant genetic interactions. We perform follow-up analysis to assess the ability of high- and low-virulence strains to undergo cellular morphogenesis and form biofilms in vitro, as well as to colonize the C. elegans host. We further perform genetic interaction analysis to identify novel significant negative genetic interactions between adhesin mutants, whereby combinatorial perturbation of these genes significantly impairs virulence, more than expected based on virulence of the single mutant constituent strains. Together, this yields important new insight into the role of adhesins, singly and in combinations, in mediating diverse facets of virulence of this critical fungal pathogen.SummaryCandida albicans is a human fungal pathogen and cause of life-threatening systemic infections. Cell surface-associated adhesins play a central role in this pathogen’s ability to establish infection. Here, we provide a comprehensive analysis of adhesin factors, and their role in fungal virulence. Exploiting a high-throughput workflow, we screened an adhesin mutant library using C. elegans as a simple model host, and identified mutants and genetic interactions involved in virulence. We found that adhesin mutants are impaired in in vitro pathogenicity, irrespective of their virulence. Together, this work provides new insight into the role of adhesin factors in mediating fungal virulence.

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Interrogation of kinase genetic interactions provides a global view of PAK1-mediated signal transduction pathways

Journal of Biological Chemistry ◽

10.1074/jbc.ra120.014831 ◽

2020 ◽

Vol 295 (50) ◽

pp. 16906-16919

Author(s):

Jae-Hong Kim ◽

Yeojin Seo ◽

Myungjin Jo ◽

Hyejin Jeon ◽

Young-Seop Kim ◽

...

Keyword(s):

Signal Transduction ◽

Cell Migration ◽

Intracellular Signaling ◽

Mammalian Cells ◽

Drug Targets ◽

Large Scale ◽

Genetic Interaction ◽

Genetic Interactions ◽

Signal Transduction Pathways ◽

Global View

Kinases are critical components of intracellular signaling pathways and have been extensively investigated with regard to their roles in cancer. p21-activated kinase-1 (PAK1) is a serine/threonine kinase that has been previously implicated in numerous biological processes, such as cell migration, cell cycle progression, cell motility, invasion, and angiogenesis, in glioma and other cancers. However, the signaling network linked to PAK1 is not fully defined. We previously reported a large-scale yeast genetic interaction screen using toxicity as a readout to identify candidate PAK1 genetic interactions. En masse transformation of the PAK1 gene into 4,653 homozygous diploid Saccharomyces cerevisiae yeast deletion mutants identified ∼400 candidates that suppressed yeast toxicity. Here we selected 19 candidate PAK1 genetic interactions that had human orthologs and were expressed in glioma for further examination in mammalian cells, brain slice cultures, and orthotopic glioma models. RNAi and pharmacological inhibition of potential PAK1 interactors confirmed that DPP4, KIF11, mTOR, PKM2, SGPP1, TTK, and YWHAE regulate PAK1-induced cell migration and revealed the importance of genes related to the mitotic spindle, proteolysis, autophagy, and metabolism in PAK1-mediated glioma cell migration, drug resistance, and proliferation. AKT1 was further identified as a downstream mediator of the PAK1-TTK genetic interaction. Taken together, these data provide a global view of PAK1-mediated signal transduction pathways and point to potential new drug targets for glioma therapy.

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