Development of a System for Discovery of Genetic Interactions for Essential Genes in Escherichia Coli K-12

Total Page:16

File Type:pdf, Size:1020Kb

Development of a System for Discovery of Genetic Interactions for Essential Genes in Escherichia Coli K-12 Genes Genet. Syst. (2013) 88, p. 233–240 Development of a system for discovery of genetic interactions for essential genes in Escherichia coli K-12 Han Tek Yong1§, Natsuko Yamamoto1‡§, Rikiya Takeuchi1, Yi-Ju Hsieh2#, Tom M. Conrad1, Kirill A. Datsenko2, Toru Nakayashiki1, Barry L. Wanner2† and Hirotada Mori1* 1Graduate School of Biological Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0101, Japan 2Department of Biological Sciences, Purdue University, 915 West State Street, West Lafayette, IN 47907-2054 USA (Received 16 May 2013, accepted 22 July 2013) Genetic interaction networks are especially useful for functional assignment of genes and gaining new insights into the systems-level organization of the cell. While studying interactions of nonessential genes can be relatively straight- forward via use of deletion mutants, different approaches must be used to reveal interactions of essential genes due to their indispensability. One method shown to be useful for revealing interactions of essential genes requires tagging the query protein. However, this approach can be complicated by mutational effects of potential hypomorphic alleles. Here, we describe a pilot study for a new scheme of systematically studying the interactions of essential genes. Our method uses a low-copy, F-based, complementing plasmid, pFE604T, from which the essential gene is conditionally expressed. The essential gene is expressed at lower levels, producing a moderate growth defect in a query host. Secondary mutations are introduced into the query host by conjugation and the resultant exconjugants are scored for growth by imaging them over time. We report results from studying five essential query genes: dnaN, ftsW, trmD, yrfF and yjgP, showing (on average) interactions with nearly 80 nonessential genes. This system should prove useful for genome-wide analyses of other essential genes in E. coli K-12. Key words: complementing F plasmid, epistasis, fitness, gene function processes, studying them can provide useful information INTRODUCTION for elucidation of gene function (Mani et al., 2008). Mod- Genetic interactions occur when two mutations els for genetic interaction networks have been constructed together result in an effect(s) different from either muta- in both eukaryotic and prokaryotic model systems (Byrne tion alone. Interactions are positive (additive) when two et al., 2007; Bakal et al., 2008; Butland et al., 2008; mutations show a synergistic effect that is more extreme Costanzo et al., 2010; Pan et al., 2007; Davierwala et al., than when alone, for example, synthetic lethality; inter- 2005; Roguev et al., 2008; Schuldiner et al., 2005; Tong et actions are negative (diminished) when the phenotype of al., 2001, 2004; Typas et al., 2008). These networks have the double mutant is less severe than either mutation revealed the global modular organization of gene products alone. Since genetic interactions often occur among and functional interaction of bioprocesses in several genes in compensatory pathways or interlinked biological model organisms (Dixon et al., 2009). Analyses of protein-protein interaction networks have Edited by Hisaji Maki revealed that proteins acting as hubs are more likely to * Corresponding author. E-mail: [email protected] be essential than less connected proteins (Jeong et al., † Corresponding author. E-mail: [email protected] 2001). Therefore, genetic interactions of essential genes ‡ Present address: Graduate School of Medicine, Osaka Univer- may unravel key new insights not revealed from studying sity. 2-2 Yamadaoka Suita, Osaka 565-0871, Japan genetic interactions of nonessential genes. Systematic # Present address: Department of Urology, Stanford University School of Medicine, Stanford, CA 94305-3900 efforts to map genetic interactions in E. coli K-12 have § These authors contributed equally. relied on the construction of double mutants by Hfr con- 234 H. T. YONG et al. jugation of donor and recipient cells with deletions and genes present on pFE604T (Ogura and Hiraga, 1983; different antibiotic resistance markers (Butland et al., Mori et al., 1986; Uga et al., 1999). Antibiotic resistance 2008; Typas et al., 2008). While these methods are use- markers (gentamycin and tetracycline) are incorporated ful for examining between nonessential genes, the same into pFE604T for selection. pFE604T has two origins of method cannot be used to study essential genes because replication: ori2 and oriRγ. ori2 is the default origin of such essential gene deletion mutants are non-viable. replication, resulting in a single copy of the plasmid dur- This experimental difficulty has been previously bypassed ing cell division, while oriRγ is a conditional origin of rep- by adding a C-terminal SPA (Sequential Peptide Affinity) lication that requires the trans-acting Π protein (encoded tag to the essential gene (Butland et al., 2008; Babu et al., on the chromosome by pir) for replication and results in 2011). An SPA tag integrated in the C terminal presum- multiple plasmid copies each division. Due to having ably alters the 3’-UTR and hence destabilizes certain these two origins of replication, pFE604T can replicate at transcripts (Babu et al., 2011). However, there are a single or medium plasmid copy number in non-pir or drawbacks to using SPA tags to affect a defect in an pir+ E. coli hosts, respectively. A non-pir host is used for essential gene for genetic interaction studies. The tag genetic interaction experiments, while a pir+ host is used often causes no measurable defect in the absence of sec- for producing additional plasmid. An oriT site is present ondary mutations. Furthermore, the mechanisms of on pFE604T, enabling the one-step transfer of pFE604T- defects are not clearly understood (Butland et al., 2008). ORF from an Hfr host to an array of nonessential gene In order to understand genetic interactions, one needs to deletion mutants en masse via conjugation. Transfer of understand the defect in the query genes. pFE604T-ORF to the nonessential gene mutant is critical Here we describe a pilot study for a new method for before or while transferring the second, essential gene high-throughput genetic interaction analysis in E. coli mutation to the nonessential gene mutant in order for between essential genes and nonessential genes. In this complementation of the essential gene to occur in the dou- method, a chromosomal knockout mutant of the essential ble mutant. gene is crossed with a high-density array of nonessential We began the construction of each chromosomal knock- deletions to construct by conjugation double mutants that out mutant of an essential query gene by transforming E. express knock-down levels of the essential query protein coli K-12 BW25113 with the pFE604T-ORF containing (Fig. 1). The major advantage of the system over the the essential gene. Next, the plasmid-borne essential SPA-tagging system is that the mutational defect of the query gene is expressed from pFE604T-ORF under the chromosomal knockout mutant of an essential gene is induction of IPTG, allowing disruption of the query gene known: the level of essential query gene protein is low- on the chromosome by one-step homologous recombina- ered, causing a moderate growth defect. tion (Datsenko and Wanner, 2000). The behavior of the doubling time of a chromosomal knockout mutant could in principle be modeled as a par- RESULTS abolic curve. Because bacteria tend to be programmed to Construction of low-copy, F-based complementing express proteins at optimal levels (Dekel and Alon, 2005), plasmid pFE604T pFE604T is a single-copy mini-F the minimum of that curve would correspond to an IPTG plasmid (Fig. 2) which was purposefully designed for sys- concentration resulting in expression of the essential gene tematic construction of chromosomal knockout mutants of at optimal, physiological levels. IPTG concentrations essential genes for their high-throughput genetic interac- less than “optimum” result in a subphysiological level of tion analyses. The essential gene is cloned into expression of the essential gene. Under this model, we pFE604T using SfiI restriction sites downstream of a T5 can prove a concentration of IPTG produces subphysiolog- promoter and lacI-O repressor-operator region, where is ical levels of expression of the essential gene by showing inducible by IPTG. Since E. coli genes in the ASKA that a higher concentration of IPTG results in a faster library are flanked by SfiI sites (Kitagawa et al., 2005), doubling time than the original concentration. In fact, any essential E. coli gene can readily be cloned into we observed that for five out of five pFE604T-ORF con- pFE604T. We refer to the pFE604T that can express an structs tested, doubling times were faster when using essential query gene as pFE604T-ORF. The viability of 1 mM IPTG than when using 0.1 mM IPTG (Fig. 3). We the chromosomal knockout mutant is sustained by conclude that a concentration of 0.1 mM IPTG produces expression of the essential query gene from the single- subphysiolical expression levels of the essential gene from copy pFE604T-ORF. Construction of pFE604T-ORF is pFE604T-ORF. Full complementation from pFE604T- shown in Supplementary Fig. S1 and described in detail ORF was not observed even at 1 mM IPTG, likely due to in the Supplementary Methods. the plasmid being present as only a single copy. Because Control of DNA replication, copy number, incompatibil- there are observable growth defects in the chromosomal ity, and partition from pKV713 (Kawasaki et al., 1990) are knockout mutants, they are amenable for genetic interac- stringently controlled by the ori2, incC, repE, and sopABC tion analysis. Discovery of genetic interactions for essential genes 235 Fig. 1. High-throughput method to find essential-nonessential gene interactions. Hfr donor strains are chromosomal knockout mutants with an essential query gene deletion marked with cat (chloramphenicol resistance cassette; blue box) but complemented by the IPTG inducible knock-down level of essential query protein from pFE604T-ORF (green triangle). Recipient strains are nonessential gene deletions marked with kan (kanamycin resistance cassette; pink box).
Recommended publications
  • Essential Genes from Genome-Wide Screenings As a Resource for Neuropsychiatric Disorders Gene Discovery Wei Zhang1, Joao Quevedo 1,2,3,4 and Gabriel R
    Zhang et al. Translational Psychiatry (2021) 11:317 https://doi.org/10.1038/s41398-021-01447-y Translational Psychiatry ARTICLE Open Access Essential genes from genome-wide screenings as a resource for neuropsychiatric disorders gene discovery Wei Zhang1, Joao Quevedo 1,2,3,4 and Gabriel R. Fries 1,2,5 Abstract Genome-wide screenings of “essential genes”, i.e., genes required for an organism or cell survival, have been traditionally conducted in vitro in cancer cell lines, limiting the translation of results to other tissues and non-cancerous cells. Recently, an in vivo screening was conducted in adult mouse striatum tissue, providing the first genome-wide dataset of essential genes in neuronal cells. Here, we aim to investigate the role of essential genes in brain development and disease risk with a comprehensive set of bioinformatics tools, including integration with transcriptomic data from developing human brain, publicly available data from genome-wide association studies, de novo mutation datasets for different neuropsychiatric disorders, and case–control transcriptomic data from postmortem brain tissues. For the first time, we found that the expression of neuronal essential genes (NEGs) increases before birth during the early development of human brain and maintains a relatively high expression after birth. On the contrary, common essential genes from cancer cell line screenings (ACEGs) tend to be expressed at high levels during development but quickly drop after birth. Both gene sets were enriched in neurodevelopmental disorders, but only NEGs were robustly associated with neuropsychiatric disorders risk genes. Finally, NEGs were more likely to show differential expression in the brains of neuropsychiatric disorders patients than ACEGs.
    [Show full text]
  • Analyzing the Heterogeneous Structure of the Genes Interaction Network Through the Random Matrix Theory
    Analyzing the heterogeneous structure of the genes interaction network through the random matrix theory Nastaran Allahyari1, Ali Hosseiny1, Nima Abedpour2, and G. Reza Jafari1* 1Department of Physics, Shahid Beheshti University, G.C., Evin, Tehran 19839, Iran 2Department of Translational Genomics, University of Cologne, Weyertal 115b, 50931 Cologne, Germany * g [email protected] ABSTRACT There have been massive efforts devoted to understanding the collective behavior of genes. In this regard, a wide range of studies has focused on pairwise interactions. Understanding collective performance beyond pairwise interactions is a great goal in this field of research. In this work, we aim to analyze the structure of the genes interaction network through the random matrix theory. We focus on the Pearson Correlation Coefficient network of about 6000 genes of the yeast Saccharomyces cerevisiae. By comparing the spectrum of the eigenvalues of the interaction networks itself with the spectrum of the shuffled ones, we observe clear evidence that unveils the existence of the structure beyond pairwise interactions in the network of genes. In the global network, we identify 140 eigenvectors that have unnormal large eigenvalues.It is interesting to observe that when the essential genes as the influential and hubs of the network are excluded, still the special spectrum of the eigenvalues is preserved which is quite different from the random networks. In another analysis we derive the spectrum of genes based on the node participation ratio (NPR) index. We again observe noticeable deviation from a random structure. We indicate about 500 genes that have high values of NPR. Comparing with the records of the shuffled network, we present clear pieces of evidence that these high values of NPR are a consequence of the structures of the network.
    [Show full text]
  • Genetic Network Complexity Shapes
    TIGS 1479 No. of Pages 9 Opinion Genetic Network Complexity Shapes Background-Dependent Phenotypic Expression 1, 1 1, 1, Jing Hou, * Jolanda van Leeuwen, Brenda J. Andrews, * and Charles Boone * The phenotypic consequences of a given mutation can vary across individuals. Highlights This so-called background effect is widely observed, from mutant fitness of The same mutation often does not lead loss-of-function variants in model organisms to variable disease penetrance to the same phenotype in different indi- and expressivity in humans; however, the underlying genetic basis often viduals due to other genetic variants that are specific to each individual remains unclear. Taking insights gained from recent large-scale surveys of genome. genetic interaction and suppression analyses in yeast, we propose that the Background modifiers can arise genetic network context for a given mutation may shape its propensity of through gain- or loss-of-function exhibiting background-dependent phenotypes. We argue that further efforts mutations in genes involved in related in systematically mapping the genetic interaction networks beyond yeast will cellular functions. provide not only key insights into the functional properties of genes, but also a Our ability to predict phenotypes relies better understanding of the background effects and the (un)predictability of on expanding our knowledge of the traits in a broader context. complex networks of genetic interac- tions underlying traits; however, the structure and complexity of the net- Genetic Background and the (Un)predictability of Traits work itself may be variable across A particular mutation in a given gene often leads to different phenotypes in different individuals.
    [Show full text]
  • Gene Essentiality Prediction with Graph Attention Networks
    1 EPGAT: Gene Essentiality Prediction With Graph Attention Networks Joo Schapke, Anderson Tavares, and Mariana Recamonde-Mendoza Abstract The identification of essential genes/proteins is a critical step towards a better understanding of human biology and pathology. Computational approaches helped to mitigate experimental constraints by exploring machine learning (ML) methods and the correlation of essentiality with biological infor- mation, especially protein-protein interaction (PPI) networks, to predict essential genes. Nonetheless, their performance is still limited, as network-based centralities are not exclusive proxies of essentiality, and traditional ML methods are unable to learn from non-Euclidean domains such as graphs. Given these limitations, we proposed EPGAT, an approach for essentiality prediction based on Graph Attention Networks (GATs), which are attention-based Graph Neural Networks (GNNs) that operate on graph- structured data. Our model directly learns patterns of gene essentiality from PPI networks, integrating additional evidence from multiomics data encoded as node attributes. We benchmarked EPGAT for four organisms, including humans, accurately predicting gene essentiality with AUC score ranging from 0.78 to 0.97. Our model significantly outperformed network-based and shallow ML-based methods and achieved a very competitive performance against the state-of-the-art node2vec embedding method. Notably, EPGAT was the most robust approach in scenarios with limited and imbalanced training data. Thus, the proposed approach offers a powerful and effective way to identify essential genes and proteins. Index Terms arXiv:2007.09671v1 [q-bio.MN] 19 Jul 2020 Bioinformatics, deep learning, essential genes, essential proteins, graph neural networks, multiomics data, prediction J. Schapke, A. Tavares, and M.
    [Show full text]
  • The Non-Essentiality of Essential Genes in Yeast Provides Therapeutic Insights Into a Human Disease
    Downloaded from genome.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Jun 21, 2016 The non-essentiality of essential genes in yeast provides therapeutic insights into a human disease Piaopiao Chen1, Dandan Wang1, Han Chen1, Zhenzhen Zhou1, and Xionglei He1,2 1 Key Laboratory of Gene Engineering of Ministry of Education, Collaborative Innovation Center for Cancer Medicine, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China 2 State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China Correspondence to: Xionglei He School of Life Sciences Sun Yat-sen University 135 Xingang West Guangzhou 510275 China Email: [email protected] Running title: Non-essentiality of essential genes Keywords: Essential gene; Conditional essentiality; Rescuing interaction; ADSL 1 Downloaded from genome.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract Essential genes refer to those whose null mutation leads to lethality or sterility. Theoretical reasoning and empirical data both suggest that the fatal effect of inactivating an essential gene can be attributed to either the loss of indispensable core cellular function (Type I), or the gain of fatal side effects after losing dispensable periphery function (Type II). In principle, inactivation of Type I essential genes can be rescued only by re-gain of the core functions, whereas inactivation of Type II essential genes could be rescued by a further loss of function of another gene to eliminate the otherwise fatal side effects. Because such loss-of-function rescuing mutations may occur spontaneously, Type II essential genes may become non-essential in a few individuals of a large population.
    [Show full text]
  • A Deep Learning Framework for Predicting Human Essential Genes by Integrating Sequence and Functional Data
    bioRxiv preprint doi: https://doi.org/10.1101/2020.08.04.236646; this version posted August 5, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. A Deep Learning Framework for Predicting Human Essential Genes by Integrating Sequence and Functional data Wangxin Xiao1#, Xue Zhang2,3#*, Weijia Xiao4 1Faculty of Transportation Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu 223003, China 2Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu 223003, China 3School of Medicine, Tufts University, Boston, MA 02111, USA 4Boston Latin School, Boston, MA 02115, USA Abstract Motivation: Essential genes are necessary to the survival or reproduction of a living organism. The prediction and analysis of gene essentiality can advance our understanding to basic life and human diseases, and further boost the development of new drugs. Wet lab methods for identifying essential genes are often costly, time consuming, and laborious. As a complement, computational methods have been proposed to predict essential genes by integrating multiple biological data sources. Most of these methods are evaluated on model organisms. However, prediction methods for human essential genes are still limited and the relationship between human gene essentiality and different biological information still needs to be explored. In addition, exploring suitable deep learning techniques to overcome the limitations of traditional machine learning methods and improve the prediction accuracy is also important and interesting. Results: We propose a deep learning based method, DeepSF, to predict human essential genes.
    [Show full text]
  • New Insights on Human Essential Genes Based on Integrated Analysis
    bioRxiv preprint doi: https://doi.org/10.1101/260224; this version posted October 10, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. New insights on human essential genes based on integrated analysis Hebing Chen1,†, Zhuo Zhang1,†, Shuai Jiang 1,†, Ruijiang Li1,†, Wanying Li1, Chenghui Zhao1, Hao Hong1, Xin Huang1, Hao Li1,* and Xiaochen Bo1,* 1Beijing Institute of Radiation Medicine, Beijing 100850, China. *To whom correspondence should be addressed: Tel: +8601066932251; Email: [email protected] (H.L.); [email protected] (X.B). †These authors contributed equally to this work. Abstract Essential genes are those whose functions govern critical processes that sustain life in the organism. Recent gene-editing technologies have provided new opportunities to characterize essential genes. Here, we present an integrated analysis for comprehensively and systematically elucidating the genetic and regulatory characteristics of human essential genes. First, essential genes act as "hubs" in protein-protein interactions networks, in chromatin structure, and in epigenetic modifications, thus are essential for cell growth. Second, essential genes represent the conserved biological processes across species although gene essentiality changes itself. Third, essential genes are import for cell development due to its discriminate transcription activity in both embryo development and oncogenesis. In addition, we develop an interactive web server, the Human Essential Genes Interactive Analysis Platform (HEGIAP) (http://sysomics.com/HEGIAP/), which integrates abundant analytical tools to give a global, multidimensional interpretation of gene essentiality. Our study provides a new view for understanding human essential genes. bioRxiv preprint doi: https://doi.org/10.1101/260224; this version posted October 10, 2018.
    [Show full text]
  • Cleave and Rescue, a Novel Selfish Genetic Element and General Strategy for Gene Drive
    Cleave and Rescue, a novel selfish genetic element and general strategy for gene drive Georg Oberhofera,1, Tobin Ivya,1, and Bruce A. Haya,2 aDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125 Edited by James J. Bull, The University of Texas at Austin, Austin, TX, and approved January 7, 2019 (received for review October 2, 2018) There is great interest in being able to spread beneficial traits high-fidelity HR. While important progress has been made, sustained throughout wild populations in ways that are self-sustaining. Here, alteration of a population [as opposed to suppression (20)] to we describe a chromosomal selfish genetic element, CleaveR [Cleave transgene-bearing genotype fixation with a synthetic HEG into ar- and Rescue (ClvR)], able to achieve this goal. ClvR comprises two tificial or naturally occurring sites remains to be achieved (21–30). linked chromosomal components. One, germline-expressed Cas9 and A number of other approaches to bringing about gene drive take guide RNAs (gRNAs)—the Cleaver—cleaves and thereby disrupts en- as their starting point naturally occurring, chromosomally located, dogenous copies of a gene whose product is essential. The other, a selfish genetic elements whose mechanism of spread does not in- recoded version of the essential gene resistant to cleavage and gene volve homing (4, 6, 31). Many of these elements can be represented conversion with cleaved copies—the Rescue—provides essential gene as consisting of a tightly linked pair of genes encoding a trans-acting function. ClvR enhances its transmission, and that of linked genes, by toxin and a cis-acting antidote that neutralizes toxin expression and/ creating conditions in which progeny lacking ClvR die because they or activity (TA systems) (4).
    [Show full text]
  • The Essential Gene Set of a Photosynthetic Organism PNAS PLUS
    The essential gene set of a photosynthetic organism PNAS PLUS Benjamin E. Rubina, Kelly M. Wetmoreb, Morgan N. Priceb, Spencer Diamonda, Ryan K. Shultzabergerc, Laura C. Lowea, Genevieve Curtina, Adam P. Arkinb,d, Adam Deutschbauerb, and Susan S. Goldena,1 aDivision of Biological Sciences, University of California, San Diego, La Jolla, CA 92093; bPhysical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720; cKavli Institute for Brain and Mind, University of California, San Diego, La Jolla, CA 92093; and dDepartment of Bioengineering, University of California, Berkeley, CA 94720 Contributed by Susan S. Golden, September 29, 2015 (sent for review July 16, 2015; reviewed by Caroline S. Harwood and William B. Whitman) Synechococcus elongatus PCC 7942 is a model organism used for Tn-seq–like system in Chlamydomonas reinhardtii; however, the studying photosynthesis and the circadian clock, and it is being mutant library currently lacks sufficient saturation to determine developed for the production of fuel, industrial chemicals, and gene essentiality (12). To date, the essential genes for photo- pharmaceuticals. To identify a comprehensive set of genes and autotrophs have only been estimated by indirect means, such as intergenic regions that impacts fitness in S. elongatus, we created by comparative genomics (13). The absence of experimentally a pooled library of ∼250,000 transposon mutants and used sequencing determined essential gene sets in photosynthetic organisms, de- to identify the insertion locations. By analyzing the distribution and spite their importance to the environment and industrial pro- survival of these mutants, we identified 718 of the organism’s 2,723 duction, is largely because of the difficulty and time required for genes as essential for survival under laboratory conditions.
    [Show full text]
  • Cross-Species Prediction of Essential Genes in Insects Through Machine
    bioRxiv preprint doi: https://doi.org/10.1101/2021.03.15.433440; this version posted March 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Cross-species prediction of essential genes in insects through machine 2 learning and sequence-based attributes 3 4 Authors: Giovanni Marques de Castro1*, Zandora Hastenreiter1, Thiago Augusto Silva Monteiro1, 5 Francisco Pereira Lobo1* 6 1 - Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil. 7 *Corresponding authors 8 Email addresses: 9 GMdC: [email protected] 10 FPL: [email protected], [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2021.03.15.433440; this version posted March 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 11 Abstract 12 Insects are organisms With a vast phenotypic diversity and key ecological roles. Several insect species 13 also have medical, agricultural and veterinary importance as parasites and vectors of diseases. 14 Therefore, strategies to identify potential essential genes in insects may reduce the resources needed 15 to find molecular players in central processes of insect biology. Furthermore, the detection of essential 16 genes that occur only in certain groups Within insects, such as lineages containing insect pests and 17 vectors, may provide a more rational approach to select essential genes for the development of 18 insecticides With feWer off-target effects.
    [Show full text]
  • Protein Interaction Potential Landscapes for Yeast Replicative Aging Hao‑Bo Guo1,2,5*, Mehran Ghafari1, Weiwei Dang4 & Hong Qin1,2,3*
    www.nature.com/scientificreports OPEN Protein interaction potential landscapes for yeast replicative aging Hao‑Bo Guo1,2,5*, Mehran Ghafari1, Weiwei Dang4 & Hong Qin1,2,3* We proposed a novel interaction potential landscape approach to map the systems‑level profle changes of gene networks during replicative aging in Saccharomyces cerevisiae. This approach enabled us to apply quasi‑potentials, the negative logarithm of the probabilities, to calibrate the elevation of the interaction landscapes with young cells as a reference state. Our approach detected opposite landscape changes based on protein abundances from transcript levels, especially for intra‑essential gene interactions. We showed that essential proteins play diferent roles from hub proteins on the age‑dependent interaction potential landscapes. We verifed that hub proteins tend to avoid other hub proteins, but essential proteins prefer to interact with other essential proteins. Overall, we showed that the interaction potential landscape is promising for inferring network profle change during aging and that the essential hub proteins may play an important role in the uncoupling between protein and transcript levels during replicative aging. Studies of replicative lifespan (RLS) in budding yeast, Saccharomyces cerevisiae, provided mechanistic insights on cellular aging 1, and contributed to the understanding of aging in other organisms including humans 2–5. Dele- tions of single genes, such as FOB16, and suppression or overexpression of genes, such as SIR27,8, could change the yeast RLS. Other factors that afect lifespan, such as caloric restriction (CR), were also found dependent on the genotypes9. A recent report found overexpression of both SIR2 and HAP4 genes leads to a cell state with considerably long RLS 10.
    [Show full text]
  • Experimental Determination and System Level Analysis of Essential Genes in Escherichia Coli MG1655 S
    JOURNAL OF BACTERIOLOGY, Oct. 2003, p. 5673–5684 Vol. 185, No. 19 0021-9193/03/$08.00ϩ0 DOI: 10.1128/JB.185.19.5673–5684.2003 Copyright © 2003, American Society for Microbiology. All Rights Reserved. Experimental Determination and System Level Analysis of Essential Genes in Escherichia coli MG1655 S. Y. Gerdes,1 M. D. Scholle,1 J. W. Campbell,1 G. Bala´zsi,2 E. Ravasz,3 M. D. Daugherty,1 A. L. Somera,2 N. C. Kyrpides,1 I. Anderson,1 M. S. Gelfand,1 A. Bhattacharya,1 V. Kapatral,1 M. D’Souza,1 M. V. Baev,1 Y. Grechkin,1 F. Mseeh,1 M. Y. Fonstein,1 R. Overbeek,1 A.-L. Baraba´si,3 Z. N. Oltvai,2* and A. L. Osterman1* Integrated Genomics, Inc., Chicago, Illinois 606121; Department of Pathology, Northwestern University, Chicago, Illinois 606112; and Department of Physics, University of Notre Dame, Notre Dame, Indiana 465563 Received 26 March 2003/Accepted 14 July 2003 Defining the gene products that play an essential role in an organism’s functional repertoire is vital to understanding the system level organization of living cells. We used a genetic footprinting technique for a genome-wide assessment of genes required for robust aerobic growth of Escherichia coli in rich media. We identified 620 genes as essential and 3,126 genes as dispensable for growth under these conditions. Functional context analysis of these data allows individual functional assignments to be refined. Evolutionary context analysis demonstrates a significant tendency of essential E. coli genes to be preserved throughout the bacterial kingdom. Projection of these data over metabolic subsystems reveals topologic modules with essential and evolutionarily preserved enzymes with reduced capacity for error tolerance.
    [Show full text]