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

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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 straightforward 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). The marked essential query gene deletion and pFE604T-ORF are transferred to recipient strains en masse by the Hfr conjugation gene transfer system. The DNA carrying the essential query gene deletion recombines with the recipient’s chromosome via homologous recombination. The oriT site present on pFE604T-ORF allows the transfer of the plasmid to the recipient cells. E represents essential gene and N represents nonessential gene.

Fig. 3. Doubling time of chromosomal knockout mutants as a function of IPTG concentration. Chromosomal knockout mutants have longer doubling times compared to the wild type in both IPTG concentrations. Error bars represent standard deviations in the measurements of the doubling times. Fig. 2. Diagram of pFE604T. The complementing plasmid, pFE604T, is used in both the construction of chromosomal knockout mutant of essential gene and in high throughput Development of a system for genetic interaction genetic interaction analysis. It is a single-copy mini-F deriva- analysis involving essential genes The rationale of tive that contains features for plasmid stability maintenance our high-throughput system for the determination of (green colors), selection markers (blue colors), expression of the genetic interaction is adopted from the previous studies essential gene (red colors), and conditional replication (orange color). A query gene can be cloned into the ORF region and its utilizing the Hfr conjugation gene transfer system: eSGA expression is under the regulation of the lacIq repressor system and GIANT-coli (Babu et al., 2011; Typas et al., 2008). (yellow colors) and a T5 promoter. Hfr donors were made by integrating a conjugative F 236 H. T. YONG et al. plasmid (CIP) into the chromosome of chromosomal plates, covering 3845 Keio deletions (Baba et al., 2006) knockout mutants (Fig. 3 of Typas et al. (2008)). The and 61 small RNA deletions marked with a kanamycin recipient strains were arrayed onto three 1536-density resistance cassette, for a total of 3906 nonessential gene

Fig. 4. Schematic of method for double mutant construction. E represents essential gene and N represents nonessential gene. Discovery of genetic interactions for essential genes 237 deletions (see Supplementary Information (Yamamoto et turbations, or have mutations that affect conjugation and al., 2009, Nomura et al, unpublished results). recombination efficiency. Unfortunately, reported nega- A schematic flowchart illustrating the procedure for tive interactions of genes located nearby the query gene high throughput generation of double mutants by conju- on the chromosome are not reliable since they could result gation is shown in Fig. 4. In step 1, an Hfr donor strain from linkage effects during recombination. When link- carrying pFE604T-ORF was mated with recipient strains age effects occur during recombination, the intact harboring a single nonessential gene deletion (marked sequence of the secondary deletion gene from the donor’s with kan) resulting in the transfer of the complementing chromosome replace the kanamycin resistance gene of the plasmid (marked with tet) to the recipients. This was nonessential gene deletion strain (Babu et al., 2011). accomplished in a high-throughput manner by transfer- This creates a strain that is incapable of growing in kana- ring the nonessential gene deletion library onto a bacte- mycin and creates the appearance of a genetic interaction rial lawn of the donor strain using replicator pins. In during the screens. Therefore, genes located within step 2, successful conjugants (single nonessential gene 35 kb of the query gene were not included in lists of sig- mutants harboring pFE604T-ORF) were selected by nificantly interacting genes even if their GI score quali- transferring colonies onto plates containing both kanamy- fies as significant, and they were excluded from further cin (Km) and tetracycline (Tc) using replicator pins and analysis. allowing colonies to grow 24 hours. In step 3, the successful conjugants from step 2 were transferred to an Pilot study of five genes In our pilot study of the IPTG containing agar plate that was previously covered genetic interaction method using pFE604T, we studied with the chromosomal knockout mutant of Hfr donor. five essential query genes: dnaN, ftsW, trmD, yjgP, and The second conjugation ensued, and chromosomal DNA yrfF. dnaN is the beta subunit of DNA polymerase III, containing the essential gene deletion (marked with cat) ftsW is involved in cell division, trmD is required for was transferred to recipient strains, in which recombina- tRNA methylation, yjgP is a LPS transporter and yrfF tion created double mutants. Mating occurred over has unknown function. There were a large number of 12 hours. In step 4, colonies were transferred onto genes found genetically interacting with the five essential plates containing chloramphenicol (Cm), tetracycline and query genes in the pilot study (Supplementary Tables S2 IPTG for an intermediate selection that reduced further and S3). Each screen resulted in an average of 77 mating and avoided partial duplication artifacts. Colonies interactions. Thus, these essential genes are required grew for 24 hours. In step 5, colonies from intermediate for buffering many cellular processes. selection were pinned onto plates containing chloram- Functional enrichment analysis (Table 1) showed some phenicol, tetracycline, kanamycin and 0.1 mM IPTG. expected and unprecedented regulation mechanisms for functions of the query genes. dnaN , showed negative Computational processing After 24 hours, images of interactions with genes that are enriched in DNA-related the plates were obtained by scanning. An image- functions. yjgP, a gene that encodes a LPS transporter, processing program computed pixels for the density of col- shows negative interactions with genes enriched in onies on the plate. These raw data were normalized for lipopolysaccharide core region biosynthetic process. the plate edge effect (Baryshnikova et al., 2010) and for Other observations of functional enrichment are not read- plate-by-plate variation in average density. The genetic ily apparent from the primary function of the essential interaction scores (GI scores) we next calculated con- query gene. Some interactions may be due to secondary trolled for differences in density due to the nonessential effects caused by low levels of the essential protein. We gene deletion and the presence of the plasmid by normal- found that the recC and dnaT genes, which are important izing average double mutant (DKO) colony densities with for the repair of double strand breaks in DNA by recom- colony densities of the single nonessential gene deletion bination, show negative interaction with dnaN. This plus the query-specific plasmid (SKOp). Normal distri- result suggests that knock-down of dnaN expression bution parameters were estimated for modeling the dis- might result in double strand breaks, leading to induction tribution of non-interacting gene pairs. Values deviating of the SOS response. To investigate this hypothesis, a from this distribution, as determined by cut-offs of the plasmid expressing a GFP-sulA fusion protein (pTN175) genetic interaction score (using FDR = 0.1), were desig- was used for monitoring the SOS response (Nakayashiki nated as either negative interactions (low GI score) or et al., 2013). We found that the fluorescence signals of positive interactions (high GI score). Genes that have sulA-GFP in the dnaN chromosomal knockout mutant are negative interactions or positive interactions with three about 2020 ± 20 compared to 670 ± 15 in wild type, sug- or more query genes were filtered out of the lists of spe- gesting an approximately 3-fold increase of SOS response. cific genetic interactions (Supplementary Table S1). The The induction of SOS response was further evidenced by mutants of these common interacting genes are usually the observation of filamentous morphology under the either slow growers, which are sensitive to random per- microscope of the cells by microscopy. 238 H. T. YONG et al.

Table 1. Functional enrichment analysis of gene interactions with down regulated of essential query gene will be a Query Type of valuable experimental resource for the E. coli community. Functional enrichment of interacting genes genes interaction Genetic interaction analysis of three out of our five dnaN Peptidoglycan based cell wall Positive query genes have been studied previously using SPA- tagging (Babu et al., 2011). Surprisingly, there is no Organelle envelope overlap between the genetic interaction lists of these dnaN Homologous recombination Negative studies. An explanation for the lack of consistency might Pyrimidine metabolism be that the perturbation of the essential gene used in this DNA replication study is vastly different than the previously used pertur- ftsW Oxidative phosphorylation Negative bation of SPA-tagging. Furthermore, the laboratory Organelle envelope environment external to experiment might affect the out- come of the genetic interaction analysis (Michaut and Quinone Bader, 2012). Although the two methods do not produce TCA cycle reproducible lists of interactions, the lists may be thought trmD Oxidative phosphorylation Positive of as complementary and providing insight into different Organelle envelope dimensions of genetic interaction. Purine nucleotide biosynthetic process We observed that genes of disparate function interact yjgP Iron sulfur protein Positive with the same essential gene. Such interactions might not be uncommon, as they were also evident in yeast ATP-biosynthesis (Davierwala et al., 2005). In fact, essential genes tend to yjgP Lipopolysaccharide core region process Negative have more functional links than nonessential genes (Babu yrfF Organelle inner membrane Positive et al., 2011; Davierwala et al., 2005), and the tendency of Cell membrane having proximate functional relationship between inter- yrfF Organelle envelope Negative acting genes is not as strong as it is for nonessential genes RNA degradation (Davierwala et al., 2005). The average genetic interactions per query gene for essential genes in this study are approximately 77, as compared to 20 in the nonessential genes (Babu et al., 2011). Thus, essential genes might be DISCUSSION much more functionally involved in the cellular processes Genetic interaction analysis of essential genes is vital than what we have thought. for the systems-level understanding of E. coli. The genetic interactions of essential genes in E. coli have not MATERIALS AND METHODS been satisfactorily examined, owing, at least in part, to the difficulty of the essential gene perturbation. While Strains and growth conditions The library of 3906 the reported genetic interactions involving essential strains carrying a single nonlethal mutation consisted of genes in E. coli determined using SPA-tagged mutants mutants from the Keio collection (Baba et al., 2006) and has been an important step in this direction (Babu et al., a small RNA deletion mutant library (Nomura et al., 2011), previously mentioned shortcomings in the method unpublished data). Non- pir BW25113 was used as the of SPA-tagging may limit the applicability of results background to construct the chromosomal knockout obtained from these studies. Here we described a system mutants (referred to as “wild type” in the text). The pir+ for the systematic determination of nonessential-essential strain BW25141 (Datsenko and Wanner, 2000) was used gene pairs in E. coli. The interpretation of the interac- to increase plasmid copy number. All the strains used tions is more straightforward as compared to studies were routinely grown in LB medium containing 1% Bacto relied on SPA-tagging, because the knock-down effect is Tryptone (Difco), 0.5% yeast extract (Difco), and 1% NaCl obvious: the shortage of the essential query protein. (Wako, Osaka, Japan) with or without antibiotics at Our system was demonstrated in five essential query 50 μg/ml for ampicillin, 30 μg/ml for kanamycin, 5 μg/ml genes encoding proteins involved in different cellular for gentamycin, 12.5 μg/ml for tetracycline, 25 μg/ml for functions. We found that these essential genes interact chloramphenicol, 15 μg/ml for streptomycin at 30°C or with high number of nonessential genes with similar or 37°C. All antibiotics and IPTG were from Wako (Osaka, dissimilar functions. In the future, it is readily possible Japan). Chromosomal knockout mutants of essential to obtain lists of genetic interactions for all 328 essential genes were grown in LB medium containing tetracycline, genes of E. coli using the pFE604T plasmid. These lists chloramphenicol and 0.1 mM IPTG at 37°C. Hfr donor can serve as an interaction catalogue for biologists to look strains were grown in media that included streptomycin. for potential candidates to study further. Also, the construction of a library of chromosomal knockout mutants Plasmids pAH143 (Haldimann and Wanner, 2001), Discovery of genetic interactions for essential genes 239 pLZ2210-CAS8 (Zhou and Wanner, unpublished data), tionally, we filtered out interactions with genes located pKD46 and pKD3 (Datsenko and Wanner, 2000), pTN175 within 35 kb of the query, since such “interactions” are (Nakayashiki et al., 2013), and ASKA ORF clones (Kitagawa often due to overwriting of the nonessential gene deletion et al., 2005) have been described. Development of CIP and antibiotic resistance gene during recombination with plasmids (Typas et al., 2008, Takeuchi et al., unpublished DNA carrying the deletion of the query gene (Babu et al., results) will be described elsewhere. 2011). Functional enrichment was tested for sets of negative interactions and sets of positive interactions using Construction of double mutant involving a chromo- the Database for Annotation, Visualization, and Inte- somal knockout mutant of essential gene using grated Discovery (DAVID) v6.7 (Huang et al., 2009a, b). automated strain arraying We arrayed colonies using a replica-pinning ROTOR HDA bench-top robot Growth curve analysis of chromosomal knockout (Singer instrument) to automate the process of construc- mutants of essential query genes Overnight cultures tion of double mutants. An outline of the technique is of chromosomal knockout mutants were inoculated into shown in Fig. 4. 96-well microtitre plates containing 200 μl of liquid medium supplemented with 1 mM or 0.1 mM of IPTG, Data analysis Images of each plate were scanned incubated at 37°C for 24 hours with optical density using an EPSON GT-X970 scanner. Raw colony densi- (600 nm) measured every 30 min using an automated ties were quantified from plate images using an in-house SpectraMax® GEMINI EM (Molecular Devices Inc). Dou- developed image analysis program (Takeuchi et al, bling time of each strain cultivated in different IPTG con- unpublished results), producing a 32 × 48 matrix of pixel centrations was calculated using an online calculator: values. Data from plates was categorized as either a sin- http://www.doubling-time.com/compute.php. gle deletion plus plasmid (SKOp) or as a double mutant (DKO). Because colony sizes tend to be larger in outer Flow cytometry analysis The dnaN chromosomal layers due to a position effect (Baryshnikova et al., 2010), knockout mutant harboring a sulA-GFP plasmid, pTN175, we normalized entries the outermost three columns/rows was grown overnight to stationary phase and diluted of the matrix by multiplying the colony density by the 1000× with 1× phosphate-buffered saline. Data were col- median colony across all plates in the category (SKOp or lected using AccuriTM C6 flow cytometer (Becton Dickinson) DKO) divided by the mean colony central density within with a 488-nm argon laser and a 515- to 545-nm emission only the particular layer the data point is located in, aver- filter (FL1) at high flow rate. aged across all plates in the category. We next normalized all colony sizes within each data matrix by dividing Author’s contributions HTY designed and carried out by the mean value of the values in the matrix. the experiment and wrote a draft of the manuscript. NY A single genetic interaction score was calculated for and TN participated in the design of the study. KAD each DKO combination by dividing the mean normalized and YH participated in plasmid design, especially work colony density of the DKO by the mean normalized colony carried out by HTY, NY, and RK at Purdue University. central density of the corresponding SKOp. We assume RT developed the colony quantification program. TC the genetic interaction scores of non-interacting gene participated in computational analysis. TN provided pairs will form a normal distribution. We estimate the direct supervision, helpful comments, and discussion parameters of this distribution using a least-squares fit of throughout this study. BLW and HM jointly oversaw all the graph of a normal probability distribution function aspects of this research and rewrote the draft manuscript with the density plot of the genetic interaction scores of for publication. each query gene. Density plots are obtained using the default function in R (http://www.r-project.org/). Fitting This study was supported in part by a Grant-in-Aid for Scien- only considers the central 50% density of the genetic tific Research (A), (C) and a Grant-in-Aid for Scientific Research interaction scores, with the density plot scaled so that the (Kakenhi) on Priority Areas System Genomics from the Ministry of Education, Culture, Sports, Science, and Technology of Japan area under curve is the same for density plot and the fit- to the Nara Institute of Science and Technology to HM, NIH ted curve. We then separately consider for negative and GM077905 from U. S. Public Health Service and Award 106394 positive interactions the false discovery rates calculated from the US National Science Foundation to BLW. by this model when using various cutoffs for significance. We chose cut-offs for positive and negative interactions REFERENCES that result in a predicted 10% false discovery rate. 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