Chemogenomic profiling predicts antifungal synergies

13 Pages·2009·2.03 MB·English

by  Gregor Jansen

MolecularSystemsBiology5;Articlenumber338;doi:10.1038/msb.2009.95
Citation:MolecularSystemsBiology5:338
&2009EMBOandMacmillanPublishersLimited Allrightsreserved1744-4292/09
www.molecularsystemsbiology.com
Chemogenomic profiling predicts antifungal synergies
GregorJansen1,7,*,AnnaYLee2,3,7,EliasEpp4,5,Ame´lieFredette1,JamieSurprenant1,DoreenHarcus4,MichelleScott2,8,
ElaineTan1,TamikoNishimura1,MalcolmWhiteway4,5,MichaelHallett2,3,6andDavidYThomas1
1 DepartmentofBiochemistry,FacultyofMedicine,McGillUniversity,Montre´al,Que´bec,Canada,2 McGillCentreforBioinformatics,McGillUniversity,Montre´al,
Que´bec,Canada,3 SchoolofComputerScience,McGillUniversity,Montre´al,Que´bec,Canada,4 GeneticsGroup,BiotechnologyResearchInstitute,National
ResearchCouncilofCanada,Montre´al,Que´bec,Canada,5 DepartmentofBiology,McGillUniversity,Montre´al,Que´bec,Canadaand6 RosalindandMorrisGoodman
CancerCentre,McGillUniversity,Montre´al,Que´bec,Canada
7 Theseauthorscontributedequallytothiswork
8 Presentaddress:SchoolofLifeSciencesResearch,UniversityofDundee,ScotlandDD15EH,UK
* Correspondingauthor.DepartmentofBiochemistry,FacultyofMedicine,McGillUniversity,McIntyreMedicalSciencesBuilding,3655PromenadeSirWilliamOsler,
Montre´al,Que´bec,CanadaH3G1Y6.Tel.: þ15143981341;Fax: þ15143987384;E-mail:[email protected]
Received8.1.09;accepted28.10.09
Chemotherapies, HIV infections, and treatments to block organ transplant rejection are creating a
population of immunocompromised individuals at serious risk of systemic fungal infections. Since
single-agenttherapiesaresusceptibletofailureduetoeitherinherentoracquiredresistance,alternative
therapeuticapproachessuchasmulti-agenttherapiesareneeded.Wehavedevelopedabioinformatics-
driven approach that efficiently predicts compound synergy for such combinatorial therapies. The
approachuseschemogenomicprofilesinordertoidentifycompoundprofilesthathaveastatistically
significant degree of similarity to a fluconazole profile. The compounds identified were then
experimentallyverifiedtobesynergisticwithfluconazoleandwitheachother,inbothSaccharomyces
cerevisiae and the fungal pathogen Candida albicans. Our method is therefore capable of accurately
predictingcompoundsynergytoaidthedevelopmentofcombinatorialantifungaltherapies.
MolecularSystemsBiology5:338;publishedonline22December2009;doi:10.1038/msb.2009.95
SubjectCategories: functionalgenomics;computationalmethods
Keywords: antifungal;chemicalgenomics;drugprofiling;synergypredictor
Thisisanopen-accessarticledistributedunderthetermsoftheCreativeCommonsAttributionLicence,
whichpermitsdistributionandreproductioninanymedium,providedtheoriginalauthorandsourceare
credited.Thislicencedoesnotpermitcommercialexploitationorthecreationofderivativeworkswithout
specificpermission.
Introduction A sensitive, but low-throughput test for synergy is the dose-
matrix response assay; in its simplest form it tests serial
Drugs that act against individual molecular targets are often dilutionsoftwocompoundsinallpossiblepermutations.The
insufficient to combat fungal infections, multigenic diseases resultsfromthisassaycanbeanalysedwithrespecttodifferent
suchascancer,andmultiplecellortissuetypediseases,inclu- modelsforquantifyingsynergy.Eachmodeldefinesabaseline
ding immune and inflammatory disorders (White et al, 1998; efficacylevelforthecompounds,whenusedincombinationat
Sams-Dodd,2005;OnyewuandHeitman,2007;Zimmermann concentrations X and Y, describing the expected level if the
et al, 2007). Combinatorial therapies that impact multiple compounds are not synergistic. The Loewe additivity model
targets simultaneously are less prone to development of drug defines the baseline as the level that would be expected if a
resistance,andincreasetherapeuticefficacy(GrollandWalsh, compound were in fact combined with itself (Loewe, 1953).
2002; Zimmermannetal, 2007). One ofthe major benefitsof TheBlissboostingmodel,anextensionoftheBlissindepen-
combinatorialtherapiesisthe potentialforsynergisticeffects: dence model (Bliss, 1939), defines the baseline level as
thatis,theoveralltherapeuticbenefitofthedrugcombinationis I ¼I þI (cid:2)I I , where I and I are the efficacy levels of
Mult X Y XY X Y
greaterthanthesumoftheeffectsoftheindividualagents.In the compounds in isolation at concentrations X and Y,
particular, synergies between the constituent compounds can respectively(Leha´retal,2007).Alternatively,thepotentiation
providebroaderpharmacologicalwindowsandreducedtoxicity model defines the baseline level as I ¼max(I , I ) (Leha´r
Pot X Y
(Fitzgerald et al, 2006). These advantages have driven drug etal,2007).Theutilityofanyofthesemodelsdependsonthe
discoveryefforts towards the search for multi-agent therapies comprehensivenessofthedose-matrixresponsedata.
(Borisyetal,2003;Fitzgeraldetal,2006;OnyewuandHeitman, Large-scalesearcheshavedemonstratedthathigh-through-
2007;Zimmermannetal,2007). putscreensofthousandsofcompoundscanbestraightforward
Despite the obvious benefits, there are many challenges (Zhangetal,2007),butusuallythesescreenscanonlytesta
associated with the identification of multi-agent therapies. small fraction of the exponential number of chemical
&2009EMBOandMacmillanPublishersLimited MolecularSystemsBiology2009 1
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
combinations available. Moreover, simplified dose-matrix words,twocompoundsthatinducesensitivityinmanyofthe
assays are commonly used by these approaches, but the same gene deletion strains may target similar cellular path-
simplification may result in a failure to test the compound ways.Conversely,strainsthatbehavesimilarlyacrossapanel
concentrationsatwhichsynergiesoccur,andthereforeresult ofcompoundsmayindicatethatthecorrespondinggenesare
inreducedsynergydetection.Severallinesofresearchaddress functionally related (Haggarty et al, 2003; Lee et al, 2005;
theseproblems(Borisyetal,2003;Zhangetal,2007).Some Brown et al, 2006). The ability of chemogenomic profiles to
effortsreducethescaleissuebyscreeningonlycombinations predict similarities in cellular response, mode of action, and
that include a particular compound of interest (i.e. by fixing gene function poses the question as to whether they can be
onecomponent).Otherapproachestacklechallengeslaterin used to also predict synergy. This aspect has not been
thetherapydevelopmentpipelineusinginsilicoapproachesto investigatedtodateandwouldprovideasimpleapproachto
predict how two compounds act on pathways to achieve synergy prediction that does not require prior knowledge of
additiveorsynergisticeffects(Leha´retal,2007). thetargetsofcompoundsandextensivemodellingofprevious
Although improvements in the scale and sensitivity of approaches(Nelanderetal,2008).
synergy identification techniques promise a greater explora- We introduce herea combined experimental and bioinfor-
tion of combinatorial chemical space, it is unlikely that maticsapproachtoidentifyantifungalsynergies.Inparticular,
experimental techniques will be sufficient to completely for each compound of interest, we obtain a chemogenomic
surveythis vastspace in a cost-effective and timely manner. profile, which we define as a set of genes whose deletions
Consequently, there is a clear need for an approach that confer sensitivity to a given compound. The next step is to
winnowsthisspacetoamanageablylargesetofcombinations computationally measure the similarity between pairs of
that is enriched for synergistic combinations. The combina- profiles. We establish that compound pairs that have
tionsinthesetcouldthenberigorouslytestedexperimentally. correspondingly similar profiles are more likely to be
Asuggestedexperimentalapproachtofindingthissetentails synergistic when compared with randomly chosen com-
an iterative ‘maximal damage’ search (A´goston et al, 2005; pounds. This approach exploits the fact that chemogenomic
Leha´ret al, 2008a). In each iteration of the search, the most profiles make compounds instantly comparable in silico:
effectivecombinationfromthepreviousiterationistestedwith whereasexhaustivescreeningofonlypairwisecombinations
allothercompoundsseparatelytoidentifyacombinationthat alreadynecessitatesaquadraticnumberofdose-matrixassays,
is more effective. However, this directed strategy starts with the computational method requires only a linear number of
themosteffectivecompoundandwillthusmisspotentiating chemogenomic profiles and a small number of subsequent
synergies between compounds that incur minimal damage validation assays relative to the total number of possible
separately. In contrast, an accurate in silico approach would combinations. Our approach is thus a practical way to
alleviate this challenge of synergy identification by enabling comprehensivelysearchthevastchemicalspaceforsynergistic
comprehensiveandefficientexplorationofthecombinatorial compounds.
space. Such a strategy could employ data from single Wevalidatethismethodbyassessingtheantifungalactivity
compound treatments to effectively predict which combina- ofcompoundcombinationsinS.cerevisiaeandinthefungal
tions are most likely to behave synergistically. There are pathogenCandidaalbicans.InfectionsbyCandidaspeciesare
severalapproachesintheliterature,includingthatofNelander an increasing problem, especially in patients who are
etal(2008),thatattempttousedatafromperturbationscreens immunocompromised(GrollandWalsh,2002).Weshowthat
and prior knowledge regarding the targets of compounds to our approach successfully predicts antifungal synergies that
model the effects of these compounds when they are used occurinS.cerevisiaeandC.albicans.
aloneorincombination.Thisapproachiscurrentlylimitedto
compoundswithknowntargets,butsuchanapproachcould
potentiallybeextendedtopredictsynergisticcompoundpairs Results
(Nelanderetal,2008).
Ourgoalwastheidentificationofcompoundpairsthatexhibit
The use of chemogenomic profiles offers promise for
antifungalsynergy.Therearetwotypesofantifungalsynergy:
characterizing the global cellular response to an arbitrary
the constituent compounds act synergistically to kill fungal
compound,forpredictingthemodeofactionofacompound,
cells (cytotoxic synergy) or arrest growth only (fungistatic
and for inferring the function of genes. Here we focus
synergy).Althoughacombinationmaybefungistaticagainst
on chemogenomic profiles generated for Saccharomyces
one fungal species, it might exhibit more potent synergy
cerevisiae where each member of the yeast gene deletion
against others. Therefore, it may be useful to further
libraryisgrowninthepresenceofaparticularcompound,and
investigatewhethercombinationsthatarefungistaticagainst
theresultantgrowthfitnessisrecorded.Strainswithreduced
particular fungal species can be developed into antifungal
fitnessincomparisonwithuntreatedorwild-typecellssuggest
therapiesagainstotherfungalspecies.
that the loss of particular genes confers sensitivity to the
compound.Forexample,asetofgenesinvolvedinmulti-drug
resistance was identified by finding commonalities between
The collection and generation of chemogenomic
yeastchemogenomicprofilesofachemicallydiversepanelof
profiles
compounds (Parsonset al, 2004; Hillenmeyer et al, 2008). It
has also been established that similarity between chemoge- S. cerevisiae, with its accessible genetic resources, was used
nomicprofilesoftenimpliesasimilarityinthemodeofaction as the model for fungal pathogens. The first step in our
ofthecorrespondingcompounds(Parsonsetal,2006).Inother methodwastocollectfromtheliteraturetheresultsofB1300
2 MolecularSystemsBiology2009 &2009EMBOandMacmillanPublishersLimited
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
genome-wide,sensitivityandlethalityscreensgeneratedwith thehypomorphicstrainfortheessentialgeneERG11(Schuldi-
abroadrangeofcompounds (Supplementary TableSI).This ner et al, 2005; Breslow et al, 2008). Fluconazole directly
set forms our chemogenomic profile collection (Figure 1A). targets Erg11p and thus specifically inhibits its enzymatic
Although the screens were conducted differently (e.g. with activityinthebiosyntheticpathwayforergosterol,anessential
diploidsversushaploids;competitiveversusnon-competitive sterol in yeast (White et al, 1998). As expected, fluconazole
growth),theresultsofeachscreenpermittheidentificationof was lethal to the erg11 strain since inhibition of the already
asetofstrainsthatarehypersensitivetothecompound,which limitedcellularamountofErg11plikelydecreaseditsactivity
inturndefineasetofhypersensitivegenes.Wefocusonthis to fatal levels. Although previous studies have identified
hypersensitivegene setformatofachemogenomic profilein strainsthataresensitivetofluconazole(Parsonsetal,2004),
ouranalyses. were-screenedthedrugtofocusondeletionsthatarelethalin
Fluconazole,awidelyusedfungistaticdrugwithfavourable thepresenceoffluconazole.Theresultsdefineasetofgenes
pharmacokinetic and toxicological properties (Grant and that we call FCZ-Fungicidal (Supplementary Table SII). We
Clissold, 1990), would be an ideal constituent compound of next validated the profile by determining the minimum
a combinatorial antifungal therapy. We thus generated a inhibitory concentration (MIC) and minimum fungicidal
denovoprofileforfluconazoleusingtheyeasthaploiddeletion concentration (MFC) for each strain (Figure 1B and Supple-
straincollection(Winzeleretal,1999).Asacontrol,weused mentary Table SIII). These values represent dosages where
FCZ-Fungicidalstrainsareunabletorecoverafterexposureto
fluconazole,unlikewild-typecells.
A To exclude the possibility that any secondary mutations
Δ strains Hypersensitive set
present in the deletion strains were responsible for the FCZ-
Fungicidalphenotype,wecomplementedtheFCZ-Fungicidal
+ =
strains with plasmid-borne copies of their respective deleted
genes to demonstrate reversibility of the phenotype. The
presenceoftheoverexpressedgeneenabledthetransformants
+ =
to survive lethal concentrations of fluconazole above their
Chemogenomic profiling MFCs (data not shown) without conferring resistance to
fluconazolebeyondlevelsobservedforthewildtype.There-
fore, the complementation results confirm, for every FCZ-
Fungicidalstrain,thatthegenedeletionisresponsibleforthe
FCZ-Fungicidalphenotype.
Components of the FCZ-Fungicidal set
Of the 4997 deletion strains screened, 21 were unable to
recoverafterexposuretofluconazole,inadditiontotheerg11
Measuring profile similarity
hypomorphic strain (Supplementary Table SII). Members of
the SAGA histone acetyltransferase complex and genes with
general RNA polymerase-II transcription factor activity (e.g.
members of the mediator complex) are significantly over-
representedintheFCZ-Fungicidalset(adjustedP¼3.7(cid:3)10(cid:2)6
and0.01,respectively;seeMaterialsandmethods).Members
ofthevacuolarmembraneHþ-ATPasecomplexandcytoske-
leton genes are also over-represented in the set (adjusted
P¼3.7(cid:3)10(cid:2)6 and 0.03, respectively; see Materials and
Testing compound pairs for synergy
methods).Takentogether,genesinvolvedwithtranscriptional
regulation, vacuole function, and cell structure are signifi-
B
wt cantlyassociatedwithsensitivitytofluconazole.
gcn5
Prediction of synergistic compounds
thr1 We assessed whether any given compound pair with a high
levelofsimilaritybetweenitschemogenomicprofilesislikely
vma10
to exhibitantifungal synergy. Agold standardset of positive
0 2 4 8 16 32 64 128 256 512 and negative examples of antifungal synergy was assembled
g/ml FCZ
for this purpose (Supplementary Table SIV). Specifically, the
Figure 1 A method for identifying synergistic compounds with antifungal positive and negative examples are synergistic compound
activity.(A)Aschematicillustratingthestepsofthemethod.(B)Validationofthe pairscuratedfromtheliteratureandpairsthatweshowedare
firststep:recoveryafterfluconazoletreatmentfordefiningthechemogenomic
not synergistic in S. cerevisiae using a dose-matrix response
profileofthedrug.Strainsweretreatedwithincreasingamountsoffluconazole
(0–128mg/ml)for24hbeforespottingaliquotsonYPDandincubatingat301C assay(seeMaterialsandmethods;SupplementaryTableSV),
for2days. respectively. Moreover, the gold standard set is limited to
&2009EMBOandMacmillanPublishersLimited MolecularSystemsBiology2009 3
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
compound pairs where each constituent compound is asso- using random permutations of our chemogenomic profile
ciated with at least one chemogenomic profile in our collection (see Materials and methods). The enrichment
collection.Althoughitwouldbeinterestingtoinvestigatethe estimates from the permutations establish a baseline enrich-
potential differences in the accuracy of a synergy predictor ment distribution. The significance of the true synergy
built exclusively from either diploid- or haploid-based enrichmentfromtheobserveddatawascomputedrelativeto
profiles, there are too few gold standard examples that are this baseline distribution. Significant enrichment would
associated with both types of profiles to enable such a suggestthattestingasetofcompoundpairsthatarepredicted
comparison(i.e.fourpositiveexamples).Similarly,thereare to be synergistic via profile similarity is expected to yield
toofewexamplestocomparetheaccuracyofpredictorsbuilt significantlymoretruesynergiesthantestinganequalnumber
exclusivelyfromeitherprofilesgeneratedfromcompetitiveor ofrandomlyselectedcompoundpairs.
non-competitive growth assays (the literature contains only The first measure of chemogenomic profile similarity that
one positive example). Therefore, the gold standard set, weassessedquantifiesthesignificanceoftheoverlapbetween
togetherwithourcompletechemogenomicprofilecollection, twohypersensitivegenesets(seetheexampleinFigure2A).In
was used to evaluate three different pairwise measures of particular,whenxgenesareobservedinbothhypersensitive
chemogenomic profile similarity for their ability to predict genesets,themeasureistheprobabilityofobtainingxormore
antifungalsynergy. genes in the overlap by chance (i.e. a P-value from a
Previousstudiessuggestthatthevastmajorityofcompound hypergeometric distribution). With this gene-based profile
pairs do not exhibit antifungal synergy. For example, Borisy similarity measure, a compound pair is predicted to be
etal(2003)tested560reference-listedcompounds(i.e.known synergistic if its P-value is less than or equal to a given
to have some bioactivity) in pairwise combination with
fluconazole using a dose-matrix proliferation assay using
fluconazole-resistant C. albicans. They described one syner-
gisticcombination,althoughtheyalsoconfirmed20combina- A B
tions as potentially synergistic because each of these
Caspofungin and
combinationsshowsaneffectthatisgreaterthanthebaseline FCZ-Fungicidal 12 M
x x x
lleavrgeelrdoeffitnheedebffyectthseprhoidghuecsetdsbinygtlhee-acgoennsttimtuoednetl,agthenattsisw,htehne 4967 genes mplemple mplene 1ne 2 ne N
oo oee e
CC CGG G
they are applied singly. Overall, their results suggest that
38 7 14
0.2–3.6% of the tested combinations exhibit antifungal Complex-based profile
synergy (and the limited number of antifungal synergies
reported in the literature in general suggests that synergy is Weights:
evenrarerinotherchemicallibraries).Thescarcityofsynergy
Significance of overlap
would suggest that the evaluation of a synergy predictor P = 3.26 x 10–10
should place great emphasis on the identification of true Weighted correlation
synergies.
C D
Itisstandardpracticetoevaluateapredictorbyestimating
its receiver-operating characteristic (ROC) curve. However,
applyingthistypeofevaluationtoasynergypredictorwould
equallyemphasizetheidentificationoftruesynergiesandfalse
positives. Furthermore, the estimated rarity of antifungal
synergyimpliesthataROCcurvewouldbeestimatedwitha
verysmallfractionofallnegativeexamplesofsynergyinthe
chemicalspacecoveredbyourchemogenomicprofilecollec-
tion.Thatis,only30outoftheestimatedB175000negative
examplesareknowninourstudy,wherethetotalnumberof
negative examples is based on the estimated frequency of
-
antifungal synergy, 3.6% (Borisy et al, 2003). A ROC curve
estimated with the small negative gold standard set would Figure 2 The measures of chemogenomic profile similarity and antifungal
synergypredictionsbasedonthesemeasures.(A)Anexampleofhowthegene-
likelyhidetheutilityofthesynergypredictorsimplybecause
basedmeasurequantifiesprofilesimilaritywiththehypergeometrictest.(B)The
oursampleofnegativeexamplesisnotsufficientlyrepresen- complex-based measure. This measure compares complex-based profiles
tative of the complete negative set. Therefore, instead of derived from hypersensitive gene sets. The similarity between the complex-
estimating ROC curves,weevaluated each synergypredictor basedprofilesismeasuredwithweightedPearsoncorrelation.Aproteincomplex
isweightedlessifithasmanysubunits,andallgenesthatarenotannotatedto
byestimating towhat degreeits predictions are enriched for
any complex (i.e. non-complex genes) are assigned maximal weight. (C) A
true synergies. That is, we computed a prediction score for
heatmapofthesimilarityvaluesofselectcompoundpairs,usingthegene-based
everypositiveandnegativeexampleinourgoldstandardset measure.Theintensityofpurpleforapaircorrespondstothedegreeofsimilarity.
and estimated to what degree the subset predicted to be All compounds in the heatmap are predicted as synergistic with fluconazole
synergistic is enriched with positive examples (with a (usingathresholdofPp10(cid:2)6.5),exceptforcamptothecin(includedforcontrast).
(D)AsinpanelC,exceptthatthesimilarityvalueswerecomputedusingthe
hypergeometric test). This type of evaluation places greater
complex-based measure. AlvC, alverine citrate; CASP, caspofungin; CsA,
valueontheidentificationoftruesynergiesasdesired.Wealso cyclosporine-A; FCZ, fluconazole; FEN, fenpropimorph; LatA, latrunculin-A;
estimated the true synergy enrichment of predictions made TUN,tunicamycin;WM,wortmannin.
4 MolecularSystemsBiology2009 &2009EMBOandMacmillanPublishersLimited
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
S1A).Takentogether,theseresultssuggestthatthecomplex-
based profile similarity measure can predict synergy more
effectivelythanthesimplergene-basedmeasure.
Lastly,weassessedaprofilesimilaritymeasurethatexploits
the detailed quantitative data available for a subset of our
chemogenomic profile collection. Namely, for some profiles
eachgeneisassociatedwithalog ratiothatreflectsthegrowth
2
of untreated versus chemically treated cells of the relevant
deletion strain (Parsons et al, 2006; Hillenmeyer et al, 2008;
Figure 3 Statistical evaluation of the gene-based chemogenomic profile
Hoonetal,2008).Wethusconsideredthecorrelationacross
similaritymeasureasapredictorofantifungalsynergy.Theevaluationisbased
ontheenrichmentofthepredictionswithtruepositives/synergies,andhigher these log2ratios as a measure of profile similarity. Again, a
values in this figure indicate greater enrichment. Baseline enrichment values compoundpairispredictedtobesynergisticifthesimilarityof
wereestimatedusingrandompermutationsofthedata(n¼5000permutations, the corresponding profiles is greater than or equal to an
seeMaterialsandmethods).Thesignificanceoftheenrichmentestimatedfrom
optimalthreshold.Unlikemeasuresofprofilesimilaritybased
the observed data is computed relative to the baseline enrichment values.
(A) The true synergy enrichment estimated from observed and randomly on hypersensitive gene sets, enrichment of the predictions
permuteddata,atdifferentsimilaritythresholds. Thex-axisshowsthe(cid:2)log with true synergies is not significant for the log ratio-based
10 2
transformation of the threshold values. The triangles indicate the enrichment measure,relativetotheexpectedbaselinelevel(P¼0.3109;see
values estimated from the observed data, at different thresholds. For each
SupplementaryFigureS1A).Therefore,wefocusonthegene-
threshold,themedian(o)andinterquartilerange(whiskers)oftheenrichment
based profile similarity measure as a predictor of synergy
values computed from the different permutations are also shown.
(B) The significance of the true synergy enrichment associated with the (using the threshold Pp10(cid:2)6.5) due to its simplicity and
predictorusedwithathresholdof10(cid:2)6.5,relativetothepermutationdistribution significant enrichment of its predictions with true synergies
ofthebaselineenrichment.Theredlineindicatestheenrichmentestimatedfrom (Figure1A).
theobserveddataanditsP-valueofsignificanceisalsoshown.Thethresholdof
10(cid:2)6.5resultsinthemostsignificantenrichmentandisthereforeconsideredthe Consistentwiththeevidencethatantifungalsynergyisrare,
optimalprofilesimilaritythresholdfordefiningthesynergypredictions. themajorityofcompoundpairsinthechemicalspacecovered
byourchemogenomicprofilecollectionarenotpredictedtobe
synergistic (see the x-axis of Supplementary Figure S2A). In
addition, theestimated accuracyofthepredictor(¼0.745) is
significantlyabovetheexpectedbaselinelevel(P¼0.018;see
threshold. We evaluated this profile similarity measure as a SupplementaryFigureS2B),despitethefactthattheestimate
synergy predictor at different thresholds (Figure 3A). The islikelybasedonasmallfractionofallnegativeexamples.If
predictions defined by the threshold Pp10(cid:2)6.5 exhibit a true insteadweover-estimateandassumethatallcompoundpairs
synergyenrichmentthatrepresentsasignificantimprovement in our chemical space are negative examples (i.e. B182000
over the expected baseline level (P¼0.0236; see Figure 3B). insteadoftheestimatedB175000examples,wherethetotal
Furthermore, this threshold produces the most significant number of negative examples is based on the estimated
improvement and is thus optimal for defining synergy frequency of antifungal synergy, 3.6%; Borisy et al, 2003),
predictions.Takentogether,theseresultssuggestthatchemo- our estimates would be based on a more representative
genomicprofilesimilaritypredictsantifungalsynergy. set of negative examples (see Supplementary Figure S2A for
We also assessed a chemogenomic profile similarity theROCcurve).Attheselectedthreshold,theestimatedtrue
measure that accounts for additional commonality that is positiverateis B67% and, using the overlarge negative set,
observable by viewing the profiles at the level of protein the estimated false positive rate and accuracy are B5 and
complexes (Figure 2B). That is, although one subunit of a B95%, respectively. Furthermore, the level at which the
protein complex may be associated with sensitivity to one predictionsareenrichedwithtruesynergieswouldincreaseif
compound and a different subunit associated with a second the number of negative examples in the gold standard set
compound,itisnonethelessinterestingthatthesamecomplex were to increase and if all new examples were predicted
isassociatedwithsensitivitytoeithercompound.Eachprofile as true negatives (Supplementary Figure S2C). Taken
wasconvertedintoacomplex-basedprofiledefinedbyalistof together, we have shown statistically that the predictor is
0s and 1s indicating absence or presence (respectively) of surprisingly accurate and the estimate of its accuracy will
each complex, and also each non-complex gene, in the increase as the community develops a more representative
hypersensitive gene set. The similarity between two such gold standard set. Therefore, we have shown that our
profiles was measured via weighted Pearson correlation. A predictor is useful for efficient identification of antifungal
proteincomplexwithmanysubunitsisweightedlessbecause synergies.
itislessrareforthatcomplex,viaanyoneofitssubunits,tobe The nextstep in thesynergyidentification method forour
included in any given hypersensitive gene set. As with the fluconazole example requires measuring the similarity be-
gene-based profile similarity measure, a compound pair is tween the FCZ-Fungicidal profile and each member of the
predictedtobesynergisticifthesimilarityofthecorresponding chemogenomic profilecollection. The FCZ-Fungicidal profile
profilesisgreaterthanorequaltoanoptimalthreshold.The is significantly similar to 10 profiles (Pp10(cid:2)6.5) and these
enrichment of the predictions with true synergies is more other profiles are associated with eight different compounds
significantforthecomplex-basedmeasurethanforthegene- (Supplementary Table SVI). Consequently, eight compounds
based measure, relative to the expected baseline levels are predicted to be synergistic with fluconazole through the
(P¼0.0092and0.0378,respectively;seeSupplementaryFigure FCZ-Fungicidalprofile.
&2009EMBOandMacmillanPublishersLimited MolecularSystemsBiology2009 5
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
Validation of predicted synergies in S. cerevisiae A Cyclosporin A B Cyclosporin A
0 62.5 125 250 500 0 1.63.16.312.525 50100
Of the eight compounds predicted to be synergistic with
0 0
fluconazole through the FCZ-Fungicidal profile, seven were
1.5625
tested for fungistatic and cytotoxic synergy with fluconazole in 62.5 3.125
iSn.ec-eAre,vFiKsi5a0e6:,laatlrvuenricnuelicnit-rAa,tec,aasnpdofwunogrtimn,atnunniinca.mFeyncpinro,pciymcloorspphoirs- FK506 125 FK506 612.2.55
predicted to be synergistic with fluconazole through a different 250 25
fluconazoleprofile(P¼9.20(cid:3)10(cid:2)45).Therefore,wealsoincluded 500 50
100
fenpropimorph in our synergy tests. In total, eight predicted
fluconazolecombinationswereexperimentallytestedforsynergy.
C
Weexperimentallyexaminedeachcompoundcombination Alverine citrate
0 31.2562.5125250500
usingadose-matrixresponseassaythatmeasuresthegrowth
0
oftreatedcells.Theresultswereusedtoquantifygrowtharrest
2
sByanrcehrgieysiuestinagl,th19e98L)oe(wseee aMdadtietirviaitlys amnoddemle(thLoodews;eS,u1p9p5l3e-; nazole 4
mentaryTableSV).Thedose-matrixresponsedatawerealso uco 8
Fl 16
fitted to Bliss boosting and potentiation models of synergy
32
(Leha´retal,2007)(seeMaterialsandmethods;Supplementary
Table SVII). There is partial agreement between the results
D Tunicamycin
from the Loewe additivity model and the other models. 0 0.5 1 2 4 8
However,wechosetoidentifysynergiesrelativetotheadditive 0
compound-with-itselfbaselinesinceitisthemostconservative
3.125
ofthetestedmodels.Eachdosematrixoftreatedcellswasalso n A
spottedonYPDtoexaminerecoveryofthecellsposttreatment ori 6.25
p
(thFeigturreeat4m).eAnbtsheanscseoomfevicsyibtoletocxoilconefifeescatsf.teSry2n4erhgsyuigngteesrtmstshoaft Cyclos 122.55
thiscytotoxicphenotypewasalsoquantifiedwiththeLoewe
50
additivitymodel(seeMaterialsandmethods).Thecytotoxicity
of compound combinations at particular concentrations was E Fluconazole
confirmed by a large reduction in the number of colony- 0 0.5 1 2 4 8
forming units of treated versus untreated cells (data not 0
shown).Compoundcombinationsthatexhibitgrowtharrestbut 0.003125
not cytotoxic synergy are referred to as exhibiting fungistatic ph0.00625
or
synergy. Figure 4C and D show examples of fungistatic and m 0.0125
pi
cytotoxicsynergy(respectively)inS.cerevisiae. pro 0.025
n
Five compounds were validated as synergistic with flucona- Fe 0.05
zole,includingfenpropimorph(SupplementaryFigureS3Aand 0.1
TableSV).Furthermore,wenoticedthatmanyofthecompounds 0.2
predictedtobesynergisticwithfluconazolearealsopredictedto
besynergisticwitheachother(Figure2C).Thesameobservation F Tunicamycin
0 0.39 0.781.56253.125
canbemadebasedonpredictionswiththecomplex-basedprofile
0
similaritymeasure(Figure2D).Wethusextendedourvalidation
efforts to include 10 pairings of the predicted fluconazole 60.05
0
partners. These pairings include two that are not predicted to K5 0.1
F
be synergistic: cyclosporine-Aþfenpropimorph and fenpropi- 0.2
morphþwortmannin.Ofthe18experimentallytestedcombina-
0.39
tionsintotal,11showedasynergisticrelationshipwithsixand
fivedemonstratedfungistaticandcytotoxiceffects,respectively
(Table I andSupplementary Figure S3and Table SV). The two
synergies involving fenpropimorph listed above are false
Figure4 Dose-matrixresponsestocompoundpairsthatexhibitantifungalsynergy.
negatives,althoughtheyareconsistentwiththeobservationthat
(C–F)Growthinhibitionlevelsofcellsgrowninthepresenceofthecompoundsare
compounds that are synergistic with fluconazole tend to be
shownontheleft.Therecoveryofcellsposttreatmentisshownontheright.(A,B)
synergisticwitheachother.Takentogether,theresultsindicatea RecoveryofcellstreatedwithacompoundpairthatisnotsynergisticinS.cerevisiae
validationsuccessrateof56%inS.cerevisiae. andC.albicans,respectively.(C,D)Compoundpairsthatexhibitfungistaticand
fungicidalsynergyinS.cerevisiae,respectively.(E,F)Compoundpairsthatexhibit
fungistaticandfungicidalsynergyinC.albicans,respectively.
Validation of predicted synergies in C. albicans
in the model S. cerevisiae. Four compound pairs that we
We sought to identify synergies in C. albicans that establish identifiedassynergisticinS.cerevisiaearealreadydescribedin
potentialmulti-agenttherapies,aftervalidatingourapproach theliteratureassynergisticinCandidaspecies,suggestingthat
6 MolecularSystemsBiology2009 &2009EMBOandMacmillanPublishersLimited
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
our approach may successfully identify synergies in (SupplementaryTableSVIII),althoughwealsofittedthedose-
C. albicans (Table I). Using the dose-matrix response assay, matrixresponsedatatoothersynergymodels(Supplementary
the 18 combinations tested in S. cerevisiae were tested in Table SIX). Table I lists the complete set of synergistic
C. albicans resulting in the identification of 10 synergistic compound pairs that we identified. We showed that eight
combinations in the fungal pathogen, nine of which are synergistic combinations identified in S. cerevisiae are also
cytotoxic (see Figure 4E and F for examples of fungistatic synergistic in C. albicans, and we identified two additional
and cytotoxic synergy, respectively, and see Supplementary synergiesinthefungalpathogen thatcouldnotbeidentified
FigureS4forallsynergiesidentifiedinC.albicans).Asbefore, in S. cerevisiae (caspofunginþfluconazole and fluconazo-
we used the Loewe additivity model to quantify synergy leþlatrunculin-A).Takentogether,thevalidationsuccessrate
for the predictor of antifungal synergy is 69%. This implies
thatourmethodidentifiestruesynergiesataratethatisB20-
TableI Compoundpairsthatexhibitantifungalsynergy
fold better than the estimated rate for testing randomly
Compoundpair S.cerevisiae C.albicans selectedcompoundpairs.
Finally,wetestedoneofthenovelsynergisticcombinations
AlvC+FCZ Fungistatic Cytotoxic influconazole-resistantclinicalisolatesofC.albicans.These
CASP+FCZ — Cytotoxic
CsA+FENa Fungistatic Cytotoxic strains acquired fluconazole resistance by mutations that
CsA+FCZa Cytotoxic Cytotoxic eitherleadtoupregulationofthetargetoffluconazole(ERG11,
CsA+TUN Cytotoxic Cytotoxic strainS2;Dunkeletal,2008),orincreasedtheexpressionofa
FEN+FK506a Fungistatic —
multi-drugeffluxpump(MDR1,strainG5;Morschhauseretal,
FEN+FCZ Fungistatic Fungistatic
FEN+WM Cytotoxic — 2007). We chose to test fluconazole (FDA-approved) in
FK506+FCZa Fungistatic Cytotoxic combination with wortmannin, analogues of which are in
FK506+TUN Cytotoxic Cytotoxic phase-Iclinicaltrials(Nobleetal,2004).Evenwhenappliedat
FK506+WM Cytotoxic —
FCZ+LatA — Cytotoxic concentrationsB1000-foldhigherthantheMICincorrespond-
FCZ+WM Cytotoxic Cytotoxic ing wild-type strains, fluconazole has no readily detectable
effect on cell growth in the clinical isolates. However, the
AlvC,alverinecitrate;CASP,caspofungin;CsA,cyclosporine-A;FCZ,flucona- combinationoffluconazoleandwortmanninexhibitsastrong
zole; FEN, fenpropimorph; LatA, latrunculin-A; TUN, tunicamycin; WM,
cytotoxic effect (Figure 5), suggesting potential clinical
wortmannin.
aPreviouslyshowntobesynergistic. relevance.
A DMSO Fluconazole
0 16 32 64 128 256 5121024
0
3.125
6.25
n
ni
O n 12.5
S a
M m
D ort 25
W
50
100
200
B DMSO Fluconazole
0 16 32 64 1282565121024
0
3.125
6.25
n
O nni 12.5
S a
M m
D ort 25
W
50
100
200
Figure5 Thedose-matrixrecoveryfromtreatmentwithfluconazoleandwortmannin,acompoundpairexhibitingantifungalsynergyin(A)themultidrug-resistant
clinicalC.albicansisolateG5and(B)thefluconazole-resistantclinicalC.albicansisolateS2.Solventcontrolsareshownontheleft.
&2009EMBOandMacmillanPublishersLimited MolecularSystemsBiology2009 7
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
Acomparisonofpredictorsdependentonhaploid- forthepredictionofsynergy.Ourcollectionincludesprofiles
and/or diploid-based profiles basedoncompetitiveornon-competitivegrowthofdiploidsor
haploids.Despitetheheterogeneityofourcollection,weused
Afteraddingournovelsynergisticcompoundpairstothegold
it in its entirety for better coverage of chemical space when
standardsetofantifungalsynergies,werevisitedthequestion
predicting antifungal synergies.Forexample, had we limited
of whether the type of chemogenomic profiles used by the
thechemogenomicprofilecollectiontohaploid-basedprofiles,
synergypredictorinfluencestheenrichmentofitspredictions
thecytotoxicsynergyinvolvinglatrunculin-Awouldnothave
withtruesynergies.Wethereforemeasuredthesignificanceof
been predicted because a haploid-based profile was not
the enrichment associated with predictors dependent on
generatedforthiscompound.Despitetheexpecteddifferences
haploid-based profiles only, diploid-based profiles only, and
intheprofilessimplyduetothedifferentwaysinwhichthey
both haploid- and diploid-based profiles. However, this
were generated, our approach was able to identify synergies
comparisoncouldonlybemadeusingprofilesgeneratedfrom
based on the similarity between profiles generated with
acompetitivegrowthassay(i.e.theassaycanusehaploidsor
different methods (e.g. the FCZ-Fungicidal profile derived
diploids)sincethereisaninsufficientnumberofgoldstandard
fromnon-competitivegrowthofhaploidsandthelatrunculin-
examples to also make the comparison in the context of
A profile derived from competitive growth of diploids).
profiles generated from a non-competitive growth assay.
Therefore, different types of profiles may lead to false
Although augmenting the gold standard set with validated
negatives; however, our approach generates predictions that
synergiesfromthisstudymaybiastheenrichmentvalues,all
areenrichedwithtrueantifungalsynergiesmoresignificantly
three predictors were subjected to the same bias since they
thanwhatisexpectedbychance.
wereallevaluatedwiththesamegoldstandardset,andhere
A chemogenomic profile encodes the genes involved in
weareonlyinterestedincomparingthepredictorsrelativeto
resistancetoaparticularcompound(Leeetal,2005;Parsons
each other. As before, optimal prediction thresholds were
etal,2006).Iftheprofilesoftwocompoundsaresimilar,there
selectedforeachofthethreevariantsofthesynergypredictor
islikelysomeunderlyingdrug-resistancemachinerytowhich
in the comparison. Our results suggest that the variant that
both apply stress. Cells treated with both compounds
exclusively uses haploid-based profiles produces predictions
concurrentlymaynotbeabletomountaneffectiveresponse
thatareenrichedwithtruesynergiesmostsignificantlyrelative
to the challenge, and the compounds thus exhibit antifungal
to the expected baseline enrichment level, followed by the
synergy. Previous studies have identified drug-resistance
variantthatusesbothhaploid-anddiploid-basedprofilesand
machinery (Parsons et al, 2004). Interestingly, the FCZ-
the variant that exclusively uses diploid-based profiles
Fungicidal set (Supplementary Table SII) includes the pleio-
(P¼0.0372,0.0572,and0.0794,respectively;seeSupplemen-
tropicdrugpumpPDR5,genesthatregulatethetranscription
tary Figure S1B). However, our collection of haploid-based
ofthispumpasmembersoftheSAGAandmediatorcomplexes
profilescontainsdataforonly20compounds.Therefore,itis
(Gao et al, 2004), and genes with vacuolar functionality. In
currentlybesttousealltypesofchemogenomicprofileswith
short, the FCZ-Fungicidal set includes genes that have
ourapproachforbettercoverageofchemicalspace,andthus,
previouslybeenassociatedwithdrugresistance.Ourmethod,
for enabling potential identification of more synergistic
therefore,exploitsthedrug-responsemachineryidentifiedby
combinations.
chemogenomicprofilingtopredictsynergy.
Our results show that chemogenomic profile similarity
TheFCZ-Fungicidalsetalsoincludesgenesassociatedwith
predicts antifungal synergy. The similarity values for all
thecytoskeletonorcellwall,twoofwhich(BEM2,SLT2)are
pairings of the chemogenomic profiles in our collection are
synthetically lethal with the target of fluconazole, ERG11
containedinSupplementaryTableSX.Thesedatacanbeused
(Parsons et al, 2004). It is possible that these genes become
immediately to identify compound pairs that are likely to
vital for maintaining the structural integrity of the cell to
exhibit antifungal synergy, and thus should stimulate the
compensate for the instability that may result from reduced
searchforeffectivecombinatorialtherapies.
ergosterol production. This is a possible explanation for
whythesegenesareassociatedwithresistancetofluconazole
(i.e. if the genes are deleted, cells are hypersensitive to the
Discussion
drug).Bysimilarreasoning,wewouldexpectthesegenestobe
We have developed a bioinformatics-driven approach using associatedwithresistancetolatrunculin-A,acompoundthat
chemogenomicprofilestopredictcompoundpairsthatexhibit disruptstheactincytoskeleton(Ayscoughetal,1997).Indeed,
antifungal synergy. First, we collected sensitivity-based the hypersensitive gene set of latrunculin-A overlaps signifi-
chemogenomic profiles from the literature and generated a cantly with the FCZ-Fungicidal set, and the overlap includes
profile in S. cerevisiae for the widely used fungistatic drug genes associated with the cell wall or cytoskeleton (Supple-
fluconazole. We then showed statistical evidence supporting mentary Table SVI). Latrunculin-A was thus predicted as
the use of our gene-based measure of profile similarity for synergistic with fluconazole and this synergy was subse-
predicting synergistic compound pairs. Our predictions of quently shown in C. albicans. Therefore, the FCZ-Fungicidal
synergisticcompoundpairsvalidatedwithahighsuccessrate. genesprovidemechanismstogeneratesynergy.
Overall, the results confirm that chemogenomic profile Previous work suggests that compounds with similar
similaritycanpredictantifungalsynergies. chemogenomicprofileshavesimilarmodesofaction(Parsons
Chemogenomic profiles can be generated in several ways. etal,2004).However,inbothS.cerevisiaeandC.albicanswe
Asmoreprofilesofdifferenttypebecomeavailable,itwouldbe identified synergy between fluconazole and cyclosporine-A,
interestingtofurtherinvestigatetherelativeutilityofeachtype which target ergosterol biosynthesis (White et al, 1998) and
8 MolecularSystemsBiology2009 &2009EMBOandMacmillanPublishersLimited
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
calcineurin (Wang and Heitman, 2005), respectively. While Inaddition,ourmethodisefficientbecauseitiscapableof
fluconazole and cyclosporine-A profiles have distinguishing reducingahugesetofallpossiblecompoundpairsdowntoa
features (as expected due to the distinct targets of the set of manageable size for thorough synergy testing in fungi
compounds), our method uses a statistic that recognizesthe and indeed may be applied to other organisms. Our results
profile similarities as significant, given what is possible by show that compounds that are synergistic with fluconazole
chance.Thatis,fivegenesintheoverlapofthehypersensitive tend to be synergistic with each other, suggesting that our
gene sets is in fact highly significant given that there are method is also able to identify compound synergy clusters.
B5000 possible genes for each set (with B20 genes). As a Overall,thenetgainfromourmethodisgreatercomparedwith
predictor,ourgene-basedmeasureofprofilesimilarityisthus that from traditional screens since costs are reduced and
usefulforidentifyingsynergiesthatmightbeunexpectedgiven sensitivityisincreased.
whatisalreadyknownabouttheparticipatingcompounds. Importantly,ourmethodidentifiednoveldrugrelationships,
Theresultsestablishthatourmethodpredictssynergywell including cytotoxic synergy between fluconazole and wort-
inS.cerevisiae.ItcanalsopredictsynergyinC.albicansbased mannininS.cerevisiae,C.albicansanddrug-resistantclinical
onchemogenomicprofilesinS.cerevisiae.Despitedifferences isolatesofC.albicans.FluconazoleisanFDA-approveddrug
in regulatory circuitry that have been observed between the andwortmanninanaloguesareinphase-Iclinicaltrials(Noble
fungal species (Martchenko et al, 2007; Hogues et al, 2008; etal,2004).Themethodhasthusuncoveredanewsynergistic
Tuch et al, 2008), the majority of the synergies identified in combinationthatcanbepursuedasaviabletherapy.
C. albicans were transferred directly from S. cerevisiae. This Combinatorialtherapieshavebeenwidelyusedindifferent
suggests that the predicted synergies could be tested in medicalscenarios(Keithetal,2005;Zimmermannetal,2007).
C. albicans immediately, without first testing the predicted However,todiscovernewcombinationsusingthevastnumber
combinationsinS.cerevisiaetofilteroutunlikelycandidates. ofcompoundsavailable(410millioncompoundsavailable—
We have, therefore, shown that our method effectively uses http//www.emolecules.com), screening strategies must be
S. cerevisiae resources to identify antifungal synergies in adapted to address the scale of the discovery task. We have
C. albicans. Furthermore, our method predicts synergies developed a powerful tool for rapid synergy discovery that
previouslyshowninotherfungalpathogens(seeSupplemen- representsapromisingsteptowardsrealizingthepotentialof
taryTableSIVforreferences)anditwouldthusbeinteresting combinatorialtherapies.Wehavevalidatedthisapproachwith
tofurtherinvestigatewhetherourmethodcanpredictbroad- antifungal combinations and pointed out a potential path to
spectrumantifungalcombinationsthatexhibitsynergy. attack the persisting problem of drug-resistant C. albicans
Wealsostatisticallyevaluatedanalternativeprofilesimilarity strainsintheclinic.Itwouldthusbeinterestingtoinvestigate
measure,basedonthecorrelationoflog ratiosthatquantifythe whether our approach can be used to streamline the
2
growth of untreated versus treated cells, as a predictor of combinatorial therapy development process in other thera-
antifungalsynergy.Wefoundthatthismeasurepredictssynergy peuticsituations.
markedly worse than the validated gene-based measure
(Supplementary Figure S1A). Interestingly, the gene-based
Materials and methods
measure compares log ratio profiles by first converting them
2
intohypersensitivegenesets.Thissuggeststhatthequantitative
Strains and media
profiledatathatareusefulforpredictingsynergyareeffectively
summarizedbyahypersensitivegeneset. TheS.cerevisiaehaploidstrainBY4741(MATahis3D1leu2D0met15D0
ura3D0)andthecompleteyeastdeletionarraycollectionintheBY4741
Our method for predicting antifungal synergy clearly
backgroundwereobtainedfromtheAmericanTypeCultureCollection.
requires chemogenomic profiles for compounds. Although S. cerevisiae was cultured in rich media (YPD), synthetic complete
constructionofachemogenomicprofileforacompoundisa media(SC),orsyntheticdrop-outmedia(SD-ura);forsolidmedia2%
significanttask,theprofilewouldbeabeneficialresourcein agarwasadded.TheC.albicanswild-typestrainSC5314,aswellasthe
general because it is a multi-valued description of the fluconazole-andmulti-drug-resistantstrainsS2(Dunkeletal,2008)
and G5 (Morschhauser et al, 2007), respectively, were cultured in
bioactivity of a compound and can be used in all future
YPDUmedia(YPDsupplementedwith50mg/lofuridine);forsolid
studies. In fact, the number of published chemogenomic media 2% agar was added. Amiodarone, benomyl, camptothecin,
profilesisincreasing(Leha´retal,2008b)andasaresult,the carboplatin,fenpropimorph,FK506,fluconazole,mycophenolicacid,
scopeofoursynergypredictionmethodisexpanding. myriocin, tunicamycin, and wortmannin were dissolved in DMSO;
chlorpromazine,desipramine,doxycycline,MMS,andnystatinwere
Moreover, an alternative profile similarity measure was
dissolved in water; and cyclosporine-A was dissolved in ethanol.
defined to enable analysis at the protein complex level.
Fluconazole was a gift from Pfizer Limited (Sandwich, Kent, UK),
Statistical evaluation of this measure as a predictor of caspofunginwasagiftfromMerckFrosstLimited(Kirkland,Que´bec,
antifungalsynergy(usingthegoldstandardset)suggeststhat Canada)andallothercompoundswerepurchasedfromSigma.
themeasureactuallypredictssynergybetterthanthevalidated
gene-based approach (Supplementary Figure S1A), although
Library screen to generate the lethality-based
thismaybeanartefactofthesmallsizeofthegoldstandard
chemogenomic profile for fluconazole
set. Nevertheless, in combination with a variant of the
complex-basedmeasure,itmaythereforebefeasibletopredict Ninety-six-wellplatescontainingtheAmericanTypeCultureCollec-
synergyusingchemogenomicprofilesbuiltsolelyfromstrains tion S. cerevisiae deletion strains were replicated with a 96-pin
replicator (Boekel) to single-well Omnitray plates (Nalgene Nunc)
pertaining to key members of protein complexes, thereby
containingYPDagarandgeneticin(200mg/ml),and,simultaneously,
reducingthescaleofthescreeningtask.Thiswouldrepresent toplatescontainingYPDagarandfluconazole(85mg/ml).Theplates
anotherimportantadvanceinourmethodology. wereincubatedat301Cfor48h.Followingincubation,cellsontheYPD
&2009EMBOandMacmillanPublishersLimited MolecularSystemsBiology2009 9
Chemogenomicprofilingpredictsantifungalsynergies
GJansenetal
control and fluconazole plates were replicated to fresh YPD plates for growth. The complementation test was performed under both
(without fluconazole) and incubated at 301C for 48h. Plates were inducing (SC: 4% galactose) and non-inducing (SC: 2% glucose)
scoredfordeletionstrainsthatwereunabletogrowafterexposureto conditions.
fluconazole.Strainsthatfitthiscriterionweresubsequentlyretestedin
MICandrecoveryassays(seebelow).Thedeletionstrainsthatwere
unabletorecoverfromfluconazoleatconcentrationsthatincontrast The chemogenomic profile collection
did not affect wild-type cells, were assigned a score of 1 in the
chemogenomicprofileandallotherstrainswereassigned0.Moreover, Wecollectedtheresultsofcompoundsensitivityscreensdescribedin
genes associated with the deletion strains with score 1 define our theliterature.Differentscreensuseddifferentschemestoscoreeach
hypersensitivegenesetforfluconazole(i.e.theFCZ-Fungicidalset). deletion strain based on its observed level of sensitivity to a given
compound (and the complete set of strain scores defines the
chemogenomic profile of the compound). For each chemogenomic
MIC assays, recovery assays, and compound profile,weidentifiedstrainsthatwerescoredasmoderatelytohighly
sensitive to the compound by noting the strains with scores that
synergy tests in S. cerevisiae and C. albicans
surpassthethresholdspecifiedinSupplementaryTableSI.Thegenes
Antifungalsensitivitytestingwasperformedwithamodifiedversion associatedwiththesestrainsdefinethehypersensitivegenesetofthe
oftheCLSI(formerlyNCCLS)procedure(NCCLS.ReferenceMethod compound.
for Broth Antifungal Susceptibility Testing of Yeasts: Approved
Standard-Second Edition. NCCLS document M27-A2). Briefly, over-
night cultures of the wild-type and deletion strains were diluted to Annotations of the FCZ-Fungicidal genes
anOD of0.0005forS.cerevisiaeandOD 0.001forC.albicans.
600 600
Volumesof50mlofculturewereinoculatedinto96-wellflat-bottom DescriptionsoftheFCZ-Fungicidalgenesweredownloadedfromthe
platescontaining50mlofSCmediaforS.cerevisiaeandYPDmedia Saccharomyces Genome Database (SGD; ftp://ftp.yeastgenome.org/
for C. albicans with increasing concentrations of compound (in yeast/).GeneOntology(GO)-basedgeneannotations(Ashburneretal,
twofoldserialdilutions).Theculturesweregrownwithoutshakingat 2000) were used to test whether particular biological processes,
301Cfor24handOD measurementsweretakenwithaTecanSafire molecularfunctions,andcellularcomponentsaresignificantlyover-
600
microplatemonochromatorreader(Tecan,Austria,GmbH).TheMIC represented in the FCZ-Fungicidal gene set. For each GO gene set,
wasdeterminedbythefirstwellwithagrowthreductionofatleast aP-valuewasobtainedfromahypogeometrictestperformedwithin
95%inthepresenceofacompoundascomparedwithuntreatedcells. thescopeofthesetofgenesassociatedwithstrainsthatwereusedin
Cellswerethenspotted(2ml)ontoYPDplatesandincubatedat301C the FCZ-Fungicidal screen. The P-values were adjusted for multiple
for48htoassesstheextenttowhichcellsrecoverfromthetreatments. comparisonsusingtheBenjaminiandHochbergmethod(Benjamini
TheMFCofagivenstrainwasdeterminedfromtheserecoveryassays andHochberg,1995).
(SupplementaryTablesSVandSVII).
Compoundsynergyinteractionswereassessedbygrowthinadose-
matrix titration assay. Volumes of 50ml of each compound were The gold standard set
twofoldseriallydilutedinSCmediaforS.cerevisiaeandYPDmedia
forC.albicans,anddispensedinto96-wellflat-bottomplates,either Agoldstandardsetofpositiveandnegativeexamplesofantifungal
acrosscolumnsoftheplates(compound-A)ordownrowsoftheplates synergy was assembled to evaluate the synergy predictors (Supple-
(compound-B). Wells were then inoculated with 50ml of wild-type mentary Table SIV). Specifically, the 21 positive examples are
yeast prepared as in the MIC assay. Plates were incubated at 301C synergistic compound pairs curated from the literature. The 30
withoutshakingandOD measurementsweretakenafter24h.MICs negative examples are pairs that we showed are not synergistic in
weredeterminedforthe6c0o0mpoundsaloneandincombinationbythe S. cerevisiae using a dose-matrix response assay (Supplementary
firstwell,withX95%decreaseinabsorbancerelativetothecontrol. TableSV).
The growth arrest synergy of a compound pair was quantified
with respect to the Loewe additivity model (Loewe, 1953) through
the fractional inhibitory concentration index (FICI )¼ The measures of chemogenomic profile similarity
growthArrest
(MIC /MIC )þ(MIC /MIC ).Acompoundpair
Aincombo Aalone Bincombo Balone ConsiderprofilesAandBandtheirassociatedhypersensitivegenesets
isclassifiedassynergisticifitsFICIisp0.5,thestandardthreshold
G andG ,respectively.LetU andU representthesetsofallgenes
(Loewe,1953;Barchiesietal,1998).Cellswerealsospotted(2ml)onto A B A B
associatedwithstrainsthatwerescreenedtogenerateprofilesAandB,
freshYPDplatesandincubatedat301Cfor24htotestforcytotoxic
respectively.U andU maydifferif,forexample,onescreeninvolved
synergy.Theminimumcytotoxicconcentration(MCC)wasdefinedfor A B
essentialgenes(throughheterozygousstrains)andtheotherdidnot.
acompoundaloneandincombinationasthelowestconcentrationthat
did not result in visible colonies on the plate. Cytotoxicity was WedefineU¼UA-UBasthescopeofthestatisticaltestthatmeasures
the similarity between profiles A and B, and therefore compute
confirmedbymeasuringcolony-formingunits(CFUs)aftercompound
treatment.CellsweretreatedwithbothcompoundsattheirMCCs,then GA0¼GA-UandGB0¼GB-U.
Thegene-basedprofilesimilaritymeasurecomparesthehypersen-
plated on YPD plates and CFUs were counted after 48h incubation
sitivegenesetsassociatedwiththeprofiles.Themeasureisdefinedas
at 301C. The cytotoxic synergy of a compound pair was quantified as
the P-value obtained froma hypergeometrictest that quantifies the
FICI ¼(MCC /MCC )þ(MCC /MCC ).
AcocmytoptooxuicndpairAwiansccolmabsosifiedaAsaeloxnheibitingfuBnginistcaomtibcosynergByailfonwee significanceof|GA0-GB0|(i.e.theprobabilityofobtaininganequalor
largernumberbychance),given|G 0|,|G 0|and|U|.
identified the pair as synergistic with respect to the growth arrest A B
Thecomplex-basedprofilesimilaritymeasurecompareshypersen-
phenotypeonly.
sitive gene sets that have been transformed into complex-based
profiles (Figure 2B). Mappings of genes to GO-defined protein
complexes were downloaded from SGD. Let C represent the set of
Complementation assay i
genesassociatedwithcomplexi.TheGOhierarchysubdividessome
To demonstrate that fluconazole sensitivity was dependent on complexesintoitsconstituentdomains.Inthesecases,wetreateach
particular gene deletion and not on acquired secondary mutations, domain as a separate complex, and the genes associated with the
the deletion strains were transformed with plasmids carrying their domainsareremovedfromthegenesetoftheparentcomplex(toavoid
respectivedeletedgenesexpressedfromthegalactose-inducibleGAL1 redundancy). For protein complex i, we compute Ci0¼Ci-U. If
promoter(Gelperinetal,2005;Jansenetal,2005).Thetransformants G0-Ci0a+,wesaythatcomplexiispresentinG0,elseitisabsent.
were incubated in two sequential overnight cultures. Cells were Wegenerateacomplex-basedprofilex ,definedasavectorof0sand
A
diluted and treated with fluconazole as described above and then 1sindicatingabsenceorpresence(respectively)ofeachcomplex,and
incubated at 301C for 24h. After incubation, 2ml of cultures were alsoeachnon-complexgene,inG 0.Similarly,x wasgeneratedwith
A B
spottedontofreshYPDplates,incubatedat301Cfor2days,andscored G 0. The similarity between x and x is measured via weighted
B A B
10 MolecularSystemsBiology2009 &2009EMBOandMacmillanPublishersLimited