high throughput phenotyping of e. coli growth and...

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References

Conclusions Intracellularmetabolismhas adirect influenceonextracellularpH. Examining this relaDonshipmore closelymay yield important insight intometabolismand improve metabolicmodeling.TheseinsightsmayimproveourunderstandingofhumanassociatedmicrobesthataffecthealthviamanipulaDngextracellularpHsuchasthoseintheoralandskinmicrobiomes1,2.Despitethe importanceof this relaDonship, it has yet to be fully characterized in thewell studiedmodelorganismE.coliK12.WehypothesizedthathighthroughputphenotypingofE.coligrowthandextracellularpHwillrevealmoreaboutthisrelaDonship.UsingtheBiologPM196-wellplate,we characterized the growth and extracellular pH when E. coli was cultured aerobically on 96different carbon sources.Notablywewere able to group the results frommediawith similar chemical composiDons and thus idenDfy trends across andwithinmedia.WenoDced that aninverserelaDonshipexistsbetweengrowthrateandpHamongvarioussugarswetestedsuchas glucose, whereas growth on organic acids such as aceDc acid yielded a direct relaDonship.Previouslystudiedmetabolicmodelsyieldsimilarresults3,howeverthelackofhigh-throughput data leaves much leU to be characterized and analyzed. Future efforts will uDlize high throughput phenotyping to study a larger number of organisms under amore diverse set of condiDons such as anaerobic culDvaDon, and growth under different limiDng resources. In conjuncDonwith exisDngmetabolicmodels, this data will improve our understanding of theimportantrelaDonshipbetweenintracellularmetabolismandextracellularpH.

Abstract

Methods

Results

HighThroughputPhenotypingofE.coliGrowthandExtracellularpHGrahamKulig1,DavidBernstein2,AlanPacheco3,MeghanThommes2,DanielSegre2,3,4

1ElonUniversity;BostonUniversityBRITEBioinformaDcsREUProgram,Summer2016,2BostonUniversity,BiomedicalEngineeringDepartment,3BostonUniversity,BioinformaDcsProgram,4BostonUniversity,BiologyDepartment

IndicatorI.F.

I.F.+Indicator

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5.1. Combine inoculaDng fluid (IF) and pH indicator (amixture ofBromocresolPurpleandPhenolRed).2.Add100uLindicator+IFtoeverywell,letequilibrate.3.CultureafreshplateofE.colifromfrozenstock.4.Inoculatecellsintesttube,dilutetoOD600of0.3,add 20 uL to everywell.5. Insert plate into spectrophotometer,set toread for90hours, takingmeasurementsevery0.5hourat430,570,and800nm.• In order to obtain accurate pH measurements and not justesDmates,we removed theplate 3Dmesduring the experiment(and once at the beginning and end) tomeasure pH with a pHmeter.

Introduction Currently, there is not enough informaDon regarding the relaDonship between cellularmetabolism and extracellular pH. New informaDon can be used to beger understand theeffect of microbes on the human body by updaDng current metabolic models. Highthroughputphenotyping(HTP)isoneofthemostpowerfultoolscurrentlyaidinginmicrobecharacterizaDon and thereforemetabolicmodel construcDon4. In order to obtain HTP, theBiologPhenotypicMicroarrayplatewith96differentcarbonsourceswasused.Asoneofthemost well characterized bacterial models, and known for its relaDvely simple labreproducibility,Escherichia coli K12was chosenasa suitablemicrobe. Furthermore, E. colihastheabilitytorespirewithorwithoutoxygenandhasawidepHrangeforsurvival,makingthecharacterizaDonofE.coliaveryversaDletoolforcomparisonstomanyothermicrobes.StudyingthehydrogenionfluxasE.colimetabolizeshaspaintedaclearerpictureofhowanintracellularfuncDonaffectstheextracellularenvironmentofamicrobe.

•  Weobservedthat,experimentallyandonamodelbasis,intracellularmetabolismand extracellular pH have an inverse relaDonship when E. coli is introduced tosugarssuchasglucose(Fig.2a).WeobservedtheoppositeeffectwhenE.coliwasgrownonacidicmediasuchasfumaricacid(Fig2b).Asgrowthrateincreased,sotoodidthepH,revealingadirectrelaDonship.Somemediadisplayedbothdirectand inverse relaDonships, such as Galactonic acid-g-Lactone (Fig. 2c). TheexponenDal growth phase for Galactonic acid-g-Lactonewas characterized by adropinpH(inverse)asitfedonLactone,andthenariseinpHasE.coliswitchedmetabolites toGalactonic acid, resulDng in an increasingpH (direct). SDll, othermediasuchasUridinegrewforall90hoursandchangedpHbyameasureofonly~0.2(Fig.2d).

•  InteresDnglyenoughE.coliprefersanopDmalpHof~7toproliferate5,yetwhengrownonavarietyofcarbonsources,E.coli altersitspHinamyriadofwaysasopposedtoremainingatastable,uniformpH.Goingforward,weplantofurtherinvesDgate themetabolic constraints that underlie this phenomenon. This datawill beused to conDnue to improvemetabolicmodels such that theywillmoreaccuratelypredict intracellularmetabolisminrelaDontoextracellularpH.FutureHTP will include the characterizaDon of other microbes that have an effect onhumanhealth.

Acknowledgements

1.  Lambers, H., Piessens, S., Bloem, A., Pronk, H. and Finkel, P. (2006), Natural skin surface pH is onaveragebelow5,whichisbeneficialforitsresidentflora.InternaDonalJournalofCosmeDcScience,28:359–370.doi:10.1111/j.1467-2494.2006.00344.x

2.  Loesche,W J. “Role of StreptococcusMutans in Human Dental Decay.”Microbiological Reviews 50.4(1986):353–380.Print.

3.  Adadi, Roi et al. “PredicDonofMicrobialGrowthRate versus Biomass Yield by aMetabolicNetworkwithKineDcParameters.”Ed.NathanD.Price.PLoSComputa>onalBiology8.7(2012):e1002575.PMC.Web.19July2016.

4.  ChristopherSHenry,MaghewDeJongh,AaronABest,PaulMFrybarger,BenLinsay,andRickLStevens.High-throughputGenera>on,Op>miza>onandAnalysisofGenome-scaleMetabolicModels.Rep.N.p.:NatureBiotechnology,n.d.Print.

5.  Zilberstein,Dan,etal."EscherichiacoliintracellularpH,membranepotenDal,andcellgrowth."Journalofbacteriology158.1(1984):246-252.

This work was funded by the Boston University BioinformaDcs BRITE REU program.Specifically, I’mverygracious forGaryBenson’s instrucDonover theBRITE2016summerprogram. A very special thank you is extended to David Bernstein, Alan Pacheco, andMeghanThommesfortheirinvaluableguidancethroughoutthisprocess.

Fig2:E.colipHandabsorbanceatOD800nmover90hours.A)GlucosegrowthcorrespondedwithadropinextracellularpHB)FumaricacidgrowthcorrespondedwithanincreaseinextracellularpHC)GalactonicAcid-g-LactoneexhibitedinteresDngpHdynamicswithaniniDaldecreasefollowedbyanincreaseD)UridinegrowthcorrespondedwithminimalpHchange

Spectrophotometer

Fig1:A)GraphofpHindicatorabsorpDonspectrum.•  The430and570nmreadingswereusedtomeasurepHusingthepHindicator(dye).ThisisbasedonthepHindicatordye:themediatransiDonsfromyellowtopurpleasthepHincreases.ThereforeasthepHincreases,thepurpleabsorbanceisdecreasingandtheyellowabsorbanceisincreasing.SotheraDoofyellowtopurpleabsorbancewillincreaseasthepHincreases.

•  800nmreadingwasusedtomeasurebacterialgrowthastheabsorbanceatthiswavelengthwasnotaffectedbypHchanges,andthusisdirectlyproporDonaltobiomass(growth)

B)Photographofplatefollowingexperiment•  Yellowwells resulted from carbon sources that droveE. coli to lower thepHwhile purplewellsresultedfromcarbonsourcesthatdidtheinverse.

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Fig3:ThepHesDmatebasedonthepHindicatordye(red)isplogedagainstactualpHmeasurements(lightblue).ThepHindicatordyewasarelaDvelyaccuratetoolforpredicDngpH.Aregressionline(black)showsthepredictedpHresponsebasedonesDmatedata.

EsFmate

Measurement

Regression