Metabolic Engineering 6 (2004) 212–219

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*Correspond

E-mail addr

1096-7176/$ - se

doi:10.1016/j.ym

Assaying gene function by growth competition experiment

Joshua Merritt and Jeremy S. Edwards*

Department of Chemical Engineering, University of Delaware, Newark, DE 19716, USA

Received 3 September 2003; accepted 23 October 2003

Abstract

High-throughput screening and analysis is one of the emerging paradigms in biotechnology. In particular, high-throughput

methods are essential in the field of functional genomics because of the vast amount of data generated in recent and ongoing genome

sequencing efforts. In this report we discuss integrated functional analysis methodologies which incorporate both a growth

competition component and a highly parallel assay used to quantify results of the growth competition. Several applications of the

two most widely used technologies in the field, i.e., transposon mutagenesis and deletion strain library growth competition, and

individual applications of several developing or less widely reported technologies are presented.

r 2004 Elsevier Inc. All rights reserved.

Keywords: Functional genomics; High-throughput screening; Growth competition

1. Introduction

Selection via growth competition is one of nature’smost pervasive and effectively used tools for theidentification of fitness in species (Darwin, 1859).Biotechnology has imitated nature by using growthcompetitions for numerous specific applications rangingfrom agricultural (Guingo et al., 1998) to wastetreatment (Fried et al., 2000). Recently, growth selectionin competitive environments has been used to character-ize gene function in complex cellular networks, an areaof research commonly referred to as functional geno-mics. The primary attribute that makes selection viagrowth competition attractive in the field of functionalgenomics is its ability to screen large numbers ofvariants concurrently and identify those most or leastsuited to survival under a given selection. Until recently,scientists have lacked the genetic, molecular biology andengineering tools needed to fully utilize growth competi-tions for this application.

Genome sequencing efforts have resulted in thecomplete genome sequences for many organisms (seehttp://www.ncbi.nih.gov/ and http://www.tigr.org/). De-spite the availability of sequence data, approximatelyonly 50% of the identified genes in most genomes have

ing author.

ess: edwards@che.udel.edu (J.S. Edwards).

e front matter r 2004 Elsevier Inc. All rights reserved.

ben.2003.10.009

been functionally characterized using low-throughputexperimental tools and bioinformatics. The need forhigher throughput experimental tools which can beused to characterize functionally undefined genes isessential. In this report we review several technologieswhich utilize growth competitions and high-throughputmonitoring technologies to further understand genefunction.

The technologies for studying microbial growthcompetitions fall into one of three categories: (1)insertional or transposon mutagenesis competition, (2)deletion strain pool competition and (3) a miscellaneouscategory which includes the many less establishedtechnologies which do not fall into the previous twocategories. Techniques used to quantify the results ofthese competitions vary widely and are generally specificto the competition experiment or technology to whichthey are applied. Below we will discuss the developmentsin each category.

2. Insertion mutagenesis competitions

Insertional or transposon mutagenesis arises from theability of a transposase enzyme to insert a specific DNAsequence termed a transposon into a site within genomicDNA (Judson and Mekalanos, 2000a, b). Simple trans-posons may consist of segments of DNA flanked by the

ARTICLE IN PRESSJ. Merritt, J.S. Edwards / Metabolic Engineering 6 (2004) 212–219 213

sequences (often inverted repeats) recognized by thetransposase enzyme. When a transposon is inserted intothe genomic DNA it will disrupt the gene positioned atthe insertion site. Therefore, transposon mutagenesis is apowerful and simple tool for disrupting/mutating genes.The fact that transposons are inserted in a pseudo-random manner (there are ‘hot spots’ for insertions)makes transposon mutagenesis very amenable to high-throughput studies.

The general strategy for using transposon mutagen-esis to generate a pool of mutants for growth competi-tions is described below. Initially chromosomal DNA,either the entire genome of the organism of interest or asmaller segment, is mutated with a transposon resultingin random insertions of the transposon into thechromosome and disruption of the genes into whichthey insert. Mutants carrying the transposon areselected, normally by using an antibiotic resistance geneengineered into the transposon, pooled and grownin competition. Methods for measuring the progressof the growth competition rely upon the natureof DNA sequences engineered into the transposon forthis purpose and are described below in selectedapplications.

Signature tagged mutagenesis, reported by Henselet al. (1995), is an insertion mutagenesis techniquedevised to identify virulence genes in human pathogenicbacteria (Fig. 1). A transposon library with a centrallylocated cassette containing unique 20 base pair tagsflanked by common PCR priming and restriction siteswas constructed and used in an in vivo whole genomemutagenesis of Salmonella typhimurium. Hensel et al.identified B1150 colonies surviving the mutagenesis andsubsequent antibiotic selection and transferred eachcolony to 96 well plates. The contents of each well werereplica blotted onto nylon filters. Contents of each 96well plate were pooled (12 separate pools weregenerated) and each pool was divided into two aliquots.The variable cassette region of the DNA from the firstaliquot was PCR amplified in the presence of radio-actively labeled primers. The labeled DNA was thenhybridized to one of the colony filter blots. The secondaliquot of mutant cells was injected into mice. Afterseveral days, bacteria were recovered from the mice andthe blotting procedure was repeated on a second filter.Strains whose signature tag was present on the pre-challenge blot but not on the post-challenge blot wereidentified as strains containing transposon insertion in avirulence related gene as disruption of these genesallowed host immunologic defenses to kill bacteriacarrying the mutations. Mutants of interest were thenidentified by sequencing the genomic region immediatelyadjacent to the transposon insert.

Using this method, 40 S. typhimurium mutants withdisruptions in apparent virulence genes were isolated.Subsequent sequencing identified a subset of at least

thirteen genes that had been previously characterized asvirulence related, thus providing some level of validationof the method. In a similar study (Edelstein et al., 1999),several known and putative virulence genes wereidentified in the pathogen Legionella pneumophila.

Unlike many other competition methods, signaturetagged mutagenesis seeks to identify genes associatedwith a complex phenotype—virulence—as opposed toonly identifying essential genes. To this end, the methodappears reasonably successful. However, there areseveral drawbacks which limit the general applicabilityand throughput of signature tagged mutagenesis. Mostnotable, the use of animal models and the limited size ofthe mutant pool that can be tested concurrently reducesthroughput. Further, the sequencing required to identifythe disrupted virulence genes and to determine thedegree of mutational saturation in the population is aheavy additional experimental burden.

A functional analysis method which couples insertionmutagenesis with genetic footprinting (Fig. 2A) inSaccharomyces cerevisiae was reported Smith et al.(1995). In vivo Ty1 transposon mutagenesis wasconducted on a large population of cells and themutagenized population was subject to selection viagrowth competition under various conditions. DNA wasisolated and PCR amplified with a gene specificfluorescently labeled primer for each gene of interestand a common primer, which targeted a region in theTy1 transposon. Results of each PCR reaction were thenquantified by polyacrylamide gel electrophoresis. Com-paring the selected and unselected populations from richand minimal media competitions, the authors were ableto identify disruptions in auxotrophic genes, essentialgenes and non-essential genes whose disruption resultedin a reduced growth rate in a set of 14 test genes. In anexpanded application of this technique (Smith et al.,1996), insertions in the 268 predicted genes on chromo-some V of S. cerevisiae were characterized under severalselections (i.e., rich and minimal media, carbon source,caffeine additive, high temperature, high salt andmating). This study successfully identified both knownand novel genes associated with each selection.

Inherent to the genetic footprinting method foranalyzing transposon mutagenesis competitions isbuilt-in confirmation that genes of interest are eithermutated or not mutated without further work (i.e.,sequencing) as insertion of the transposon is necessaryfor its detection in the unselected library. However, withthis strength comes the disadvantage that essentiallyonly one gene is detected at a time. While the techniqueis readily scalable by running multiple PCR reactionsand gels in parallel, larger scale analysis using thismethod would be resources and labor intensive. Inter-estingly, Smith et al. observed tolerated mutations inregions immediately 50 and 30 to the coding sequence ofmany genes and within the coding sequence of several

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Fig. 1. Signature tagged sequencing method.

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others. Presence of tolerated insertions within the codingsequences allowed for some sub-whole gene analysis(e.g., the identification of non-essential regions of aprotein), however, such results also have the potential tomisclassify genes which are essential if totally inacti-vated.

Sharma et al. (2001) present an alternative to geneticfootprinting which they refer to as quantitative targetdisplay using DNA fingerprints. To demonstrate proof-of-concept, pools of S. cerevisiae (10–20 mutants each)were made from individual mutant stocks previouslyisolated from a transposon mutagenized library. Fol-lowing growth competition, genomic DNA was isolatedfrom the pool, digested with a restriction enzyme andthen common ends were ligated to the genomic DNAdigest. The ligated product was used as template DNAfor a PCR using common primers which target aninverted repeat inside the transposon and the ligatedends. This PCR results in the amplification of DNA

between the transposon and the closest restriction siteon each side of the transposon. The two products foreach inserted transposon constitute a DNA fingerprintfor the system when imaged on an acrylamide gel.

While the fingerprinting method appears to workreasonably well in this small, defined system, the authorsrightly observe that it would not be possible to apply itto a larger, undefined system without modification. In afull-genome mutagenesis, it would be expected that (1)the size of the PCR products from many different geneswould approximately overlap making them impossibleto distinguish and (2) heterogeneity of the insertionswithin a single gene would result in a complex andunpredictable fingerprint. The authors conclude bysuggesting that these problems might be overcome byhybridizing the PCR products to a colony blot or aDNA microarray.

Badarinarayana et al. (2001) used a similar strategy toanalyze nearly 700 genes in parallel in Escherichia coli

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In vivomutagenesis

In vitromutagenesis

P1

P1

P2

P1

Time = 0 Time > 0

Gene X

~10 kb

P3

P4

P2

P2

P4

P4

P4

P4

P4

P4(A) (B)

Fig. 2. Genetic footprinting (A) in vivo mutagenesis. Step 1—plasmid carrying transposon (r) is transformed into target bacteria. Step 2—the

transposon randomly inserts into chromosome. Step 3—for each gene, PCR with gene-specific (P1) and transposon-specific (P2) primers is

performed. Step 4—a gel is run to determine the location of the transposon insertion. (B) In vitro mutagenesis. Step 1–10 kb chromosomal segment

amplified via PCR Step 2—transform the 10 kb region into cells, and insertion into chromosome occurs via homologous recombination. Step 3—

select for recombinants with growth and PCRDNA pool with chromosome-specific (P3) and transposon-specific (P4) primers to identify insertions in

essential regions of target segment. Step 4—gel electrophoresis is used to determine the location of insertion.

J. Merritt, J.S. Edwards / Metabolic Engineering 6 (2004) 212–219 215

using subgenic-resolution microarrays (Fig. 3). In thiswork, an E. coli transposon mutant library was madeusing Tn10 transposase. DNA was isolated, digestedand common ends were ligated as described aboveexcept that the common ends contained a ‘Y-shapedlinker’ which enabled specific amplification of transpo-son-containing fragments in a subsequent PCR. ThisPCR product, each DNA molecule containing thegenomic DNA sequence adjacent to one of thetransposon inserts, was then transcribed in vitro. Theresulting RNA was reverse transcribed in the presence offluorescently labeled deoxynucleotide triphosphates andthe fluorescently labeled cDNA was hybridized tospecially designed microarrays spotted with approxi-mately 350 base pair segments of 680 different E. coli

genes. The fate of each mutant in the growth competi-tion (complex vs. minimal media) was evaluated bymeasuring the fluorescence signal of the microarray spotassociated with the given gene. Briefly, the authors wereable to identify conditionally essential (required forgrowth in minimal media) genes, genes whose deletion isknown to cause growth defect in both rich and minimal

media and several uncharacterized genes which result ingrowth defect.

Akerley et al. (1998) report a variation of transposonmutagenesis followed by genetic footprinting which theycall in vitro mariner mutagenesis (Fig. 2B). Transposonmutagenesis is conducted in vitro using Himar1 trans-posase with an approximately 10 kb segment of genomicDNA isolated via PCR from the target organism.Following the mutagenesis, an in vitro gap repair isconducted. Mutated DNA is then transformed into thetarget cells where it inserts into the chromosome viahomologous recombination. Recombinants are selectedbased upon an antibiotic resistance carried on thetransposon, are pooled and are grown competitively.Genomic DNA is isolated from the competitive growthexperiment and used as template in a PCR whichincludes primers that target the transposon and one endof the 10 kb segment inserted via homologous recombi-nation. The resulting set of bands, imaged on an agarosegel, represents all transposon inserts into the targetDNA region that are still present in the population at agiven point during the competition. Assuming sufficient

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IS10R IS10R

MCS

T7KanR

R6K ori

AmpRtnp* (Ptac)

laclq

Isolate genomic DNA

transposon

Restriction digest

Ligation of Y-linker

PCR Enrichment of DNA adjacent to insert

T7In vitrotranscription

RNA LabeledcDNA

cDNA synthesisfor microarray hybridization

(A)

(B)

Fig. 3. Experimental design for microarray based readout of growth

competitions. (A) Transposable element and the suicide vector. Based

on the figure provided in Badarinarayana et al. (2001). (B) The

protocol for the amplification and labeling of genomic DNA fragments

adjacent to the transposon.

J. Merritt, J.S. Edwards / Metabolic Engineering 6 (2004) 212–219216

insertion saturation, blank regions in the gel show thelocation of genes whose disruption resulted in growthdefect (competition eliminated or reduced the number ofcells containing the insertion below a detectable level) orloss of viability of the host (essential genes).

This method was initially used to analyze approxi-mately 50 kb of Haemophilus influenzae DNA and 10 kbof Streptococcus pneumoniae DNA. Experiments con-firmed the essential nature of nine of nine knownessential genes and identified four additional hypothe-tical genes, which putatively encode essential functions.In a subsequent work (Akerley et al., 2002), in vitromariner mutagenesis was used to characterize the entireH. influenzae genome using 366 overlapping segments ofthe chromosome and nearly 1500 footprinting reactions.

Modifications to this technique have been primarilyaimed at expanding its application. For example, Wongand Mekalanos (2000) developed a method they termed‘SCE jumping’ which facilitates allelic exchange inorganisms not able to take up naked DNA forchromosomal integration. They subsequently demon-strated the utility of SCE jumping in Pseudomonas

aeruginosa. Similarly, Guo and Mekalanos (2001)modified the in vitro mariner mutagenesis method sothat it could be applied to the human pathogenHelicobacter pylori. In both cases the primary modifica-tions to the method centered on DNA delivery forrecombination rather than the footprinting analysis.

In a final example of gene characterization usingtransposon based mutagenesis, Judson and Mekalanos(2000a, b) present a system based upon positive selectionrather than gene disruption. In this system, theTnAraOut transposon, which contains both the KanR

gene and an outward facing arabinose-inducible pro-moter (PBAD), was used to mutagenize Vibrio cholerae.Following mutagenesis, cells were selected on mediacontaining both the antibiotic and arabinose. Arabinosedependent cells were then identified by replica platingonto arabinose deficient media. It was reasoned that thecollection of KanR arabinose dependent cells repre-sented some portion of the population in which thetransposon disrupted the promoter upstream of anessential gene. Using this system, the authors identified16 essential or conditionally essential genes. Subsequentsequencing identified insertions upstream of four knownessential genes while the remainder were localizedupstream of known and hypothetical genes not pre-viously identified as essential.

3. Deletion strain pool competitions

The recent completion of a genome-wide single genedeletion library in S. cerevisiae now provides analternative to insertion mutagenesis for high-throughputfunctional analysis of genes. This library, which containsstrains carrying start-to-stop codon deletions of nearlyevery known and hypothesized open reading frame inthe S. cerevisiae genome, was constructed one gene at atime using homologous recombination as described byWinzeler et al. (1999). Knockout cassettes for each genewere made which include the KanMX4 cassette flankedby gene specific ‘barcode’ sequences which are in turnflanked by common priming sites for PCR. Thisspecialized makeup facilitates high-throughput analysisof growth competitions using the following procedure.Mutant pools are initially subject to growth competitionunder the selection of interest. Genomic DNA is isolatedfrom the competition culture(s) at various time pointsand PCR with common primers (fluorescently labeled) isused to isolate the entire library of deletion cassettes

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Fragmentgenomic DNA

Gel purify,ligate into expressionvector

Transform into

cells, growth of

population with

selection

Purify plasmids,

fragment,fluorescently

label fragments

Hybridizelabeled inserts

to microarray

Fig. 4. Genome-wide screening method for identifying genes whose

overexpression results in a discernable phenotypic advantage.

J. Merritt, J.S. Edwards / Metabolic Engineering 6 (2004) 212–219 217

represented in the culture. The pool of labeled deletioncassettes is then hybridized to a microarray containingspots of DNA complementary to the gene specificbarcode sequence included in the deletion cassette foreach gene. Finally, the quantity of each mutant in theculture is determined by the intensity of the spot on themicroarray corresponding to the gene deletion it carries.Several interesting applications of this technology aredescribed below.

In the initial report using the S. cerevisiae deletionpool, Winzeler et al. analyzed the growth, on rich andminimal media, of a 558 strain subset of the currentpool. The authors report that their microarray arrayresults compare well with previous work using alternateanalysis methods (i.e., genetic footprinting).

Birrell et al. (2001) screened the entire pool of non-essential gene deletion strains (4627 strains) for genesrelated to UV radiation sensitivity. Briefly, the pool wassubject to mild UVB and UVC in separate experiments.Following irradiation, cells were allowed to recover for18 h in rich medium. DNA was then isolated from thepools and hybridized to microarrays as described above.Using this method, the authors identified most knownUV sensitive gene deletions in the pool and several genesnot previously reported to result in UV sensitivity. Theauthors note that known UV sensitive genes notidentified by their screen were within the top 2% ofthe pool with respect to UV sensitivity but did not meetthe statistical criteria they used to define UV sensitivity.

Steinmetz et al. (2002) used growth competitions ofthe S. cerevisiae gene deletion pool in media containingvarious fermentable and non-fermentable carbonsources to identify 466 genes whose deletions resultedin impaired mitochondrial respiration. Of these genes265 were new. They further extended their analysis,identifying 29 human orthologs of these genes which areknown or suspected to be associated with humanmitochondrial disease suggesting that this method mightserve as a way to identify human genes not previouslyknown to be disease related.

In a final example, Deutschbauer et al. (2002) used theS. cerevisiae gene deletion pool to identify genesassociated with yeast sporulation and postgerminationgrowth. As a result of this study, the number of genesfunctionally implicated in sporulation was doubled from200 to nearly 400 genes.

The use of a deletion pool and high-density micro-arrays in growth competitions is an effective method forhigh-throughput functional analysis of genes. Unfortu-nately, the general applicability of the method suffersfrom the high cost and effort required to constructsuch a pool. At this time, the S. cerevisiae pool is theonly whole-genome deletion library that has beenconstructed. However, Baba et al. (2002) recentlyreported their initial efforts in constructing an E. coli

gene deletion library. As deletion libraries for more

organisms are constructed and become publicly avail-able the utility of this method will continue to increase.

4. Other technologies

Several additional technologies which have not yetbeen widely applied exist for the high-throughputanalysis gene function. Three selected technologies arediscussed in this section.

Gill et al. (2002) recently reported a genome-widescreening method for identifying genes whose over-expression results in a discernable phenotypic advantageunder a given growth selection (Fig. 4). Gill and co-workers constructed a library of expression vectorscontaining all E. coli genes by randomly shearinggenomic DNA and then ligating it into the TOPO-TApBAD plasmid. This library was transformed intobacteria and the bacterial pool was competitively grownin the presence of a mild selection (low-level antibiotic).At various time points during the competition, extra-chromosomal DNA was isolated, fluorescently labeledand hybridized to DNA microarrays containing 1160 E.

coli gene probes. Enrichment or depletion of a givenstrain, corresponding to genes conferring antibioticresistance or sensitivity, was evaluated by measuring

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* *

*

**

Plasmid library expressingmutants of protein X whichcompliment function in agene X deletion strain

Growth competitionenriches more activemutants. Plasmids purified.Genes isolated via PCR.

**

*

Polyacrylamide gel − immobilized PCR. Eachspot (polony) arises from asingle template molecule.

ATAGTCCTAGGGATC

Cy3-A

ATAGTCCTAGGGATC

Cy3-A

Single-base primerextension with labelednucleotides to identifymutant polonies

Fig. 5. Polymerase colony based approach for identifying the

functional implication of single base changes.

J. Merritt, J.S. Edwards / Metabolic Engineering 6 (2004) 212–219218

changes in the fluorescent signal of the microarray spotidentifying the gene of interest. Nineteen genes confer-ring antibiotic resistance and 27 genes whose over-expression resulted in antibiotic sensitivity wereidentified using this procedure. This technique, whilenot well suited to identifying essential or conditionallyessential genes, may, as the authors observe, find wideapplication in the field of metabolic engineering. Forexample, this method might be used to improve growthor product yield of industrial strains on a particularcarbon source or in particular environmental condi-tions. Further, application to systems other than E. coli

should be relatively straightforward. The primary draw-back to application in other organisms is the require-ment that organism-specific microarrays be constructed.Alternatively, screening the E. coli gene library in otherorganisms using E. coli microarrays should be possibleby simply switching to an appropriate expressionplasmid.

Antisense RNA technology has also been applied tofunctional analysis of genes. For example, Ji et al. (2001)generated a plasmid library carrying small (200–800 bp)fragments of the Staphylococcus aureus genome whichcould be expressed under the control of an induciblepromoter. Strains carrying plasmids capable of inacti-vating essential genes were identified by replica platingonto media containing the inducer. Finally the identityof the gene being inactivated was determined bysequencing. This technique has the advantage that thelibrary can be maintained because selection, even ofessential genes, does not occur until expression isinduced. However, the sequencing requirement is athroughput bottleneck and the method would certainlybenefit from the application of a higher throughputstrain identification method (e.g., genomic microarrayhybridization).

Merritt et al. (2003) recently reported a method forsubgenic (i.e., single nucleotide) functional characteriza-tion of mutant proteins which couples functionalcomplementation in S. cerevisiae with immobilizedpolymerase colony (polony) technology (Mitra andChurch, 1999). Single base mutants of the yeast PGK1protein were cloned into a low copy plasmid and theplasmids carrying the mutant genes were transformedinto a pgk1 deficient strain. The mutant strains werethen pooled and grown competitively in minimal glucosemedium. Plasmid DNA was isolated at several timepoints and identified using polony technology (Fig. 5).Briefly, polonies are made by including all PCRcomponents in a thin polyacrylamide gel atop amodified glass slide. Slides are thermalcycled andindividual PCR colonies arise from single DNAtemplate molecules. Single base mutants are thenidentified by annealing a sequencing primer immediatelyupstream of the site of mutation and performing aprimer extension with Klenow polymerase and the

fluorescently labeled dNTP of interest. Using thismethod, the authors were able to quantify the fitness(growth rate) of several single base mutants in parallel.This method is limited at the current time to the analysisof defined mutant pools. However, with the develop-ment of high-fidelity polony sequencing technology(Mitra et al., 2003) it should be possible to expandapplication of this method to randomly generated singlebase or multibase mutant libraries.

5. Conclusions

In this report we have discussed the integratedfunctional analysis methodologies which incorporateboth a growth competition component and a highlyparallel assay used to quantify results of the growthcompetition. The primary attribute that makes selectionvia growth competition attractive in the field offunctional genomics is its ability to screen large numbersof variants concurrently and identify those most or leastsuited to survival under a given selection. Growthcompetition thus holds extraordinary promise in func-tional genomics for uncovering the function of unknowngenes.

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