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APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Mar. 2011, p. 1816–1821 Vol. 77, No. 5 0099-2240/11/$12.00 doi:10.1128/AEM.02696-10 Copyright © 2011, American Society for Microbiology. All Rights Reserved. Subpopulation-Specific Metabolic Pathway Usage in Mixed Cultures as Revealed by Reporter Protein-Based 13 C Analysis Martin Ru ¨hl, 1,2 Wolf-Dietrich Hardt, 3 and Uwe Sauer 2 * Ph.D. Program in Molecular Life Sciences, Life Science Zurich Graduate School, 1 Institute of Molecular Systems Biology, 2 and Institute of Microbiology, 3 ETH Zurich, Zurich, Switzerland Received 17 November 2010/Accepted 22 December 2010 Most large-scale biological processes, like global element cycling or decomposition of organic matter, are mediated by microbial consortia. Commonly, the different species in such consortia exhibit mutual metabolic dependencies that include the exchange of nutrients. Despite the global importance, surpris- ingly little is known about the metabolic interplay between species in particular subpopulations. To gain insight into the intracellular fluxes of subpopulations and their interplay within such mixed cultures, we developed here a 13 C flux analysis approach based on affinity purification of the recombinant fusion glutathione S-transferase (GST) and green fluorescent protein (GFP) as a reporter protein. Instead of detecting the 13 C labeling patterns in the typically used amino acids from the total cellular protein, our method detects these 13 C patterns in amino acids from the reporter protein that has been expressed in only one species of the consortium. As a proof of principle, we validated our approach by mixed-culture experiments of an Escherichia coli wild type with two metabolic mutants. The reporter method quantita- tively resolved the expected mutant-specific metabolic phenotypes down to subpopulation fractions of about 1%. Consortia of microorganisms are responsible for diverse nat- ural processes that range from the decomposition of organic matter or biodegradation of anthropogenic xenobiotics in eco- systems (36) to beneficial effects of commensal microbiotas in the mammalian gut (31). Directly or indirectly, these processes involve interactions of metabolic activities between species, such as syntrophy in anaerobic global carbon cycles for decom- position (20, 33) or complex interactions in the competitive environment of the gut microbiome (6, 32). In sharp contrast to this environmental, nutritional, and disease relevance of microbial communities, our methodological repertoire is geared mainly to the analysis of single-species culture. To gain insights into the metabolic status and operation of single spe- cies or subpopulations within such consortia, currently used approaches include (i) differential gene expression (11, 18), (ii) proteome analyses of metabolic enzymes either as a shotgun technique or with fluorescence-assisted sorting prior to analy- sis (4, 45), (iii) metabolite investigations without species sep- aration (9, 19, 22, 44), and (iv) isotope probing combined with metagenomics (12, 37, 42), metabolite profiling (40), or imag- ing techniques (21, 41). Although these approaches provide valuable metabolic in- formation, they monitor only the inventory of the metabolic network and not its functional operation (25). This functional operation of the metabolic network is described by the intra- cellular fluxes (i.e., in vivo reaction rates) that integrate the response of all catalytic protein-metabolite and regulatory in- teractions at the genetic, posttranslational, allosteric, and ki- netic levels (26). Most important for the study of metabolic status and operation, the energy, redox factor, and precursor generating intracellular fluxes in central carbon metabolism are required. These intracellular carbon fluxes are per se not measurable and must be estimated by model-based interpre- tation of measured data, for which several approaches exist. Based on mass balances of measured substrate uptake rates with formation rates of biomass, by-products, and CO 2 within stoichiometric models, flux balance analysis typically provides a whole range of possible flux distributions, unless strong as- sumptions are made (5, 39). To avoid such assumptions, intra- cellular information that can be provided by 13 C isotope label- ing experiments is required. Here, the identification and quantification of specific metabolic pathways in vivo are based on unique 13 C labeling patterns in metabolites that result from the metabolic distribution and rearrangement of the intro- duced 13 C tracer (26, 35, 43, 46). The two complementary mathematical approaches, iterative isotopologue balancing and local flux ratio analysis, are used for such 13 C-based met- abolic flux analysis (47). Akin to flux balance analysis, iterative isotopologue balancing requires extracellular physiological rates and can thus be applied only to mixed populations when their individual rates are known. Flux ratio analysis, in con- trast, relies solely on the intracellular 13 C labeling patterns to calculate ratios of fluxes from converging pathways (14, 27, 34) and thus is potentially applicable to mixed populations for which extracellular rates are typically not available. Conventional 13 C flux ratio analysis is based on 13 C labeling patterns in protein-bound amino acids in cellular biomass (47) and hence is not readily applicable to mixed cultures. To spe- cifically resolve 13 C labeling patterns of a given population within a mixed culture, either the populations have to be sep- arated (13) or a unique protein representative for one popu- lation with selective purification is needed (28). For population * Corresponding author. Mailing address: Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli Str. 16, 8093 Zurich, Switzerland. Phone: 41-44-633 36 72. Fax: 41-44-633 10 51. E-mail: [email protected]. Published ahead of print on 7 January 2011. 1816 on July 25, 2019 by guest http://aem.asm.org/ Downloaded from

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APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Mar. 2011, p. 1816–1821 Vol. 77, No. 50099-2240/11/$12.00 doi:10.1128/AEM.02696-10Copyright © 2011, American Society for Microbiology. All Rights Reserved.

Subpopulation-Specific Metabolic Pathway Usage in Mixed Cultures asRevealed by Reporter Protein-Based 13C Analysis�

Martin Ruhl,1,2 Wolf-Dietrich Hardt,3 and Uwe Sauer2*Ph.D. Program in Molecular Life Sciences, Life Science Zurich Graduate School,1 Institute of Molecular Systems Biology,2 and

Institute of Microbiology,3 ETH Zurich, Zurich, Switzerland

Received 17 November 2010/Accepted 22 December 2010

Most large-scale biological processes, like global element cycling or decomposition of organic matter,are mediated by microbial consortia. Commonly, the different species in such consortia exhibit mutualmetabolic dependencies that include the exchange of nutrients. Despite the global importance, surpris-ingly little is known about the metabolic interplay between species in particular subpopulations. To gaininsight into the intracellular fluxes of subpopulations and their interplay within such mixed cultures, wedeveloped here a 13C flux analysis approach based on affinity purification of the recombinant fusionglutathione S-transferase (GST) and green fluorescent protein (GFP) as a reporter protein. Instead ofdetecting the 13C labeling patterns in the typically used amino acids from the total cellular protein, ourmethod detects these 13C patterns in amino acids from the reporter protein that has been expressed in onlyone species of the consortium. As a proof of principle, we validated our approach by mixed-cultureexperiments of an Escherichia coli wild type with two metabolic mutants. The reporter method quantita-tively resolved the expected mutant-specific metabolic phenotypes down to subpopulation fractions ofabout 1%.

Consortia of microorganisms are responsible for diverse nat-ural processes that range from the decomposition of organicmatter or biodegradation of anthropogenic xenobiotics in eco-systems (36) to beneficial effects of commensal microbiotas inthe mammalian gut (31). Directly or indirectly, these processesinvolve interactions of metabolic activities between species,such as syntrophy in anaerobic global carbon cycles for decom-position (20, 33) or complex interactions in the competitiveenvironment of the gut microbiome (6, 32). In sharp contrastto this environmental, nutritional, and disease relevance ofmicrobial communities, our methodological repertoire isgeared mainly to the analysis of single-species culture. To gaininsights into the metabolic status and operation of single spe-cies or subpopulations within such consortia, currently usedapproaches include (i) differential gene expression (11, 18), (ii)proteome analyses of metabolic enzymes either as a shotguntechnique or with fluorescence-assisted sorting prior to analy-sis (4, 45), (iii) metabolite investigations without species sep-aration (9, 19, 22, 44), and (iv) isotope probing combined withmetagenomics (12, 37, 42), metabolite profiling (40), or imag-ing techniques (21, 41).

Although these approaches provide valuable metabolic in-formation, they monitor only the inventory of the metabolicnetwork and not its functional operation (25). This functionaloperation of the metabolic network is described by the intra-cellular fluxes (i.e., in vivo reaction rates) that integrate theresponse of all catalytic protein-metabolite and regulatory in-teractions at the genetic, posttranslational, allosteric, and ki-

netic levels (26). Most important for the study of metabolicstatus and operation, the energy, redox factor, and precursorgenerating intracellular fluxes in central carbon metabolismare required. These intracellular carbon fluxes are per se notmeasurable and must be estimated by model-based interpre-tation of measured data, for which several approaches exist.

Based on mass balances of measured substrate uptake rateswith formation rates of biomass, by-products, and CO2 withinstoichiometric models, flux balance analysis typically provides awhole range of possible flux distributions, unless strong as-sumptions are made (5, 39). To avoid such assumptions, intra-cellular information that can be provided by 13C isotope label-ing experiments is required. Here, the identification andquantification of specific metabolic pathways in vivo are basedon unique 13C labeling patterns in metabolites that result fromthe metabolic distribution and rearrangement of the intro-duced 13C tracer (26, 35, 43, 46). The two complementarymathematical approaches, iterative isotopologue balancingand local flux ratio analysis, are used for such 13C-based met-abolic flux analysis (47). Akin to flux balance analysis, iterativeisotopologue balancing requires extracellular physiologicalrates and can thus be applied only to mixed populations whentheir individual rates are known. Flux ratio analysis, in con-trast, relies solely on the intracellular 13C labeling patterns tocalculate ratios of fluxes from converging pathways (14, 27, 34)and thus is potentially applicable to mixed populations forwhich extracellular rates are typically not available.

Conventional 13C flux ratio analysis is based on 13C labelingpatterns in protein-bound amino acids in cellular biomass (47)and hence is not readily applicable to mixed cultures. To spe-cifically resolve 13C labeling patterns of a given populationwithin a mixed culture, either the populations have to be sep-arated (13) or a unique protein representative for one popu-lation with selective purification is needed (28). For population

* Corresponding author. Mailing address: Institute of MolecularSystems Biology, ETH Zurich, Wolfgang-Pauli Str. 16, 8093 Zurich,Switzerland. Phone: 41-44-633 36 72. Fax: 41-44-633 10 51. E-mail:[email protected].

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separation, commonly either centrifugation or fluorescence-assisted cell sorting is used. The problem with the formerapproach is that centrifugation can separate species only withsufficient density differences and is not accurate enough forcomplex mixtures, while fluorescence-assisted sorting takes toolong for a reliable 13C labeling pattern analysis to be done.Here, we develop a method for 13C flux analysis of subpopu-lations within mixed cultures using a plasmid-based reporterprotein with glutathione S-transferase (GST) as the high-affin-ity purification tag and green fluorescent protein (GFP). For aproof of principle, we used cocultivation experiments of anEscherichia coli wild type and metabolic deletion mutants todefine the methodological requirements for quantitative 13Cflux analysis of subpopulations and to characterize the resolu-tion power of the method.

MATERIALS AND METHODS

Bacterial strains, growth conditions, and media. This study used E. coli K-12MG1655 (German Collection of Microorganisms and Cell Cultures, Braun-schweig, Germany) and its isogenic phosphoglucose isomerase (pgi protein) andmalate dehydrogenase (mdh protein) deletion mutants (2). For the reporterprotein plasmid, the published vector pGEX-KG, which carries already glutathi-one S-transferase (GST), was used, and green fluorescent protein (GFP) insertedafter the polylinker (16). For all experiments, frozen glycerol stocks were used toinoculate 5 ml of Luria-Bertani (LB) medium with ampicillin and/or kanamycinat final concentrations of 50 mg � liter�1 for metabolic mutants and strainscontaining a plasmid. After 5 h of incubation at 37°C and 300 rpm on a gyratoryshaker, 5-ml volumes of M9 minimal media were inoculated at 500- to 2,000-folddilutions as precultures. The mid-exponential-growth-phase M9 preculture at anoptical density at 600 nm (OD600) of 0.8 to 1.2 was then used to inoculate a 70-mlM9 batch monoculture in a 1-liter baffled shake flask to a maximal OD600 of 0.03.For mixed cultures of E. coli strains, the LB and M9 precultures were preparedas monocultures. For the M9 batch coculture of the wild type and mdh mutant,two 70-ml volumes were inoculated with both strains at an OD600 of 0.02. For theM9 batch coculture of the wild type and the pgi mutant, six 70-ml volumes wereinoculated with the wild type at an OD600 of 0.005 and with the pgi mutant at anOD600 of 0.08, due to the growth rate of the pgi mutant being four times lowerthan that of to the wild type.

The filter-sterilized M9 minimal medium consisted of the following per liter ofdeionized water: 7.5 g of Na2HPO4 � 2H2O, 3.0 g of KH2PO4, 1.5 g of(NH4)2SO4, and 0.5 g of NaCl. The following components were filter sterilizedseparately and then added (per liter of final medium): 1 ml of 1 M MgSO4, 1 mlof 0.1 M CaCl2, 0.6 ml of 0.1 M FeCl3, 20 ml of 25% (wt/vol) glucose, 2 ml of 1.5mM thiamine, and 10 ml of a trace element solution containing (per liter) 180 mgof ZnSO4 � 7H2O, 180 mg of CoCl2 � 6H2O, 120 mg of MnSO4 � H2O, and 120mg of CuCl2 � 2H2O. For plasmid-containing strains, ampicillin was added to theM9 medium at a final concentration of 50 mg � liter�1. For 13C flux analysis inbatch cultures, either a mixture of 20% (wt/wt) [U-13C]glucose and 80% (wt/wt)naturally labeled glucose or 100% [1-13C]glucose was used (both at �99%isotopic purity; Cambridge Isotope Laboratories, Andover, MA). For M9 pre-cultures of cocultivation experiments with E. coli strains, the same 13C-labeledglucose composition was used as for the M9 batch culture to avoid fractions withmore than 3% unlabeled biomass at the time of harvest that interfere with 13Cflux ratio analysis.

Determination of physiological parameters. Supernatant samples were pre-pared by centrifugation of 1 ml culture broth for 3 min at 4°C and 14,000 � g todetermine glucose and organic acids by the signals of a refractive index and diodearray detector on a high-pressure liquid chromatographer (HPLC) (Agilent1100), using a Aminex HPX-87H column at 60°C with 5 mM H2SO4 as an eluent.Cell growth was determined spectrophotometrically at 600 nm. The specificgrowth rate was calculated by linear regression versus time in monocultures.Growth curves of individual E. coli strains in mixed cultures were estimatedbased on start inocula and individually determined growth rates using the stan-dard exponential growth equation. The fluorescence signal from the GFP fusionreporter protein in the culture broth was measured (Tecan Infinite M200).

Reporter protein production and purification. Reporter protein productionwas induced with a 10 mM IPTG (isopropyl-�-D-thiogalactoside) stock solutionat an OD600 of 0.1 to 0.2 during exponential growth (29) at a final concentrationof 0.05 mM. Batch-grown cultures were harvested during the mid-exponential

growth phase at an OD600 of about 2 by centrifugation for 1 min at roomtemperature and 15,500 � g. The biomass pellets were directly frozen in liquidnitrogen and kept at �80°C until reporter protein purification. For reporterprotein purification, biomass pellets resulting from 70 ml culture broth wereresuspended in 4 ml lysis buffer (50 mM Tris [pH 7.6], 100 mM NaCl, 1 mMMgCl2, 2 mM dithiothreitol, and 4 mM phenylmethylsulfonyl fluoride) anddisrupted by two passages through a French press cell at 4°C. Cell-free lysateswere obtained by centrifugation at 23,000 � g for 10 min at 4°C and directlyapplied to 1 ml equilibrated glutathione Sepharose beads according to the man-ufacturer manual (GE Healthcare Europe, Switzerland). After incubation for 1 hon ice under gentle shaking, the beads were recovered by centrifugation at 800 �g at 4°C for 5 min and washed seven times with 5 ml lysis buffer withoutphenylmethylsulfonyl fluoride. To elute the reporter protein, the beads wereincubated four times with 1 ml 15 mM fresh glutathione solution (reduced form)in 100 mM Tris [pH 7.6] at room temperature for 30 min.

To remove residual Tris buffer and glutathione, which can interfere with thederivatization for GC-MS analysis, 16 ml �20°C acetone was added to thepooled eluates for protein precipitation. After at least 1 h of incubation at�20°C, the solution was centrifuged at 15,000 � g for 10 min at �10°C, and theprecipitated reporter protein resuspended in 400 �l deionized water and precip-itated with 1.6 ml �20°C cold acetone. After three wash steps, the precipitatedreporter was stored at �20°C or directly hydrolyzed in 1.5 ml 6 M HCl for 24 hat 105°C in sealed microtubes for gas chromatography mass spectrometry (GC-MS) analysis described below.

13C labeling pattern analysis of protein-bound amino acids by GC-MS and13C-constrained metabolic flux ratio analysis. Samples of protein-bound aminoacids from whole-cell protein for GC-MS were prepared as described previously(47). Briefly, cell pellets were obtained by centrifugation of 1 ml culture broth for3 min at 4°C and 14,000 � g, washed once with 1 ml 0.9% NaCl, and hydrolyzedin 1.5 ml 6 M HCl for 24 h at 105°C in sealed microtubes. After drying at 95°C,the samples were derivatized in 30 �l dimethylformamide (Fluka, Switzerland)and 30 �l N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide (Sigma, Swit-zerland) at 85°C for 1 h. For analysis of derivatized amino acids by GC-MS, anAgilent 5973 mass spectrometer coupled to an Agilent 6890 gas chromatographand an Rtx-5Sil MS fused-silica column (10 m by 0.18 mm inside diameter,0.18-�m film thickness, Restek U.S., Bellefonte, PA) was used. The oven gradi-ent raised from 160°C with 20°C/min to a final temperature of 280°C.

The 13C labeling patterns were obtained by the software FiatFlux (48), withimplemented peak integration, removal of faulty 13C labeling patterns, andcorrection for naturally occurring isotopes (47). Metabolic flux ratio analysis wasbased on previously established methods implemented in the used softwareFiatFlux (14, 47, 48). Briefly, corrected mass distributions of amino acids weremapped to the precursor metabolites in central carbon metabolism by a least-squares fit and locally interpreted by algebraic equations to calculate ratios offluxes in convergent pathways. Standard deviations for flux ratios were deter-mined from redundant mass distributions.

RESULTS

The reporter protein provides equivalent 13C labeling infor-mation to whole-cell protein. To resolve 13C labeling patternsin subpopulations, we used a plasmid-based reporter protein,consisting of GST for highly selective purification by affinitychromatography (16) and GFP for monitoring of expression.For initial method validation, a tac promoter induced by thelactose analogue IPTG (1) was used to induce the reporterprotein. First, we determined the optimal IPTG concentra-tion that allows for sufficient reporter protein expressionand unperturbed exponential growth to avoid physiologicaleffects (29). For reporter induction in exponentially growingE. coli wild-type cultures, 0.05 mM IPTG was optimal forstrong induction without significant growth perturbation(Fig. 1A and B).

Next, we determined whether the applied purification pro-cedure yielded exclusively the reporter protein. For this pur-pose, we induced the reporter protein in 70-ml batch culturesof the E. coli wild type and compared aliquots from differentprotein purification steps by SDS gel electrophoresis (Fig. 1C).

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During purification, the affinity matrix turned green andyielded a green eluate that consisted of a single protein band inthe SDS-PAGE gel with the expected reporter protein size of51 kDa. Thus, we concluded that a pure reporter protein wasobtained with a yield of about 1 mg dry reporter protein from70 ml E. coli batch culture harvested at an OD600 of 2, whichcorresponds to a total biomass dry weight of about 50 mg.

Having now a potentially suitable reporter protein system,we next verified that the 13C label information of the reporterprotein was equivalent to the label information of the whole-cell protein. Hence, we purified the reporter protein from two70-ml batch cultures of the E. coli wild type grown on either20% (wt/wt) [U-13C]glucose and 80% naturally labeled glucoseor 100% [1-13C]glucose. After purification, the GC-MS-de-rived 13C labeling patterns of hydrolyzed reporter protein from70-ml batch cultures were compared to those of the whole-cellprotein hydrolyzate from a 1-ml culture aliquot of the samecultures. For a comprehensive comparison of 13C labeling pat-terns, we determined intracellular ratios of converging fluxesto yield information about key pathways in central carbonmetabolism (14, 47) (Fig. 2). The obtained flux ratios werehighly similar for both 13C labeling pattern sources andmatched previously published results for E. coli wild-type batchcultures with glycolysis as the main route for glucose break-down (cf. serine derived through glycolysis), absent gluconeo-genesis (cf. phosphoenolpyruvate [PEP] originating from oxa-loacetate), and almost equal contributions of tricarboxylic acid(TCA) cycle and anaplerosis to oxaloacetate (cf. oxaloacetateoriginating from PEP) (14, 24). Hence, we concluded that thereporter protein is a reliable source of 13C labeling patternsand equivalent to whole-cell protein for determination of met-abolic pathway activity as was shown previously (28).

The reporter protein allows for identification of metabolicmutant-specific 13C patterns in cocultivation experiments. Toexamine the general applicability of the reporter protein tomixed cultures, we cocultivated the E. coli wild type with thepgi or mdh deletion mutant containing the reporter plasmid.To verify the mutant-specific metabolism, we determined fluxratios in separate batch cultures on a mixture of 20% (wt/wt)[U-13C]glucose and 80% naturally labeled glucose (Fig. 3A). Incontrast to the primary glucose catabolism via glycolysis in thewild type, the pgi mutant showed the expected reroutingthrough the pentose phosphate (PP) pathway (14). Also for themdh mutant with an impaired TCA cycle, the local flux rerout-ing with an increased relative anaplerotic flux compared to thewild type was confirmed (Fig. 3A). Since the mdh deletion canbe partially replaced by the isoenzyme malate:quinone-oxi-doreductase (38), an anaplerotic flux significantly lower thanthe theoretically expected value of 100% was observed.

Next, we tested whether these mutant-specific flux ratioscould be resolved by a reporter-based 13C flux analysis incocultivation experiments. Each mutant containing the re-porter plasmid was grown in a mixed batch culture with thewild type on a mixture of 20% (wt/wt) [U-13C]glucose and 80%naturally labeled glucose (Fig. 3B and C). The determinedoverall growth curves could be well described as a superposi-tion of two independently, exponentially growing populationscalculated from their inoculum and previously determinedgrowth rates in monocultures (i.e., pgi mutant, 0.21 h�1; mdhmutant, 0.50 h�1; and wild type, 0.71 h�1). Thus, a pseudo-steady state could be assumed for both cocultures, and the 13Clabeling patterns were derived from the individual purifiedreporter proteins in the two mutants. Since the thereby-derivedflux ratios matched favorably with the ones obtained from

FIG. 1. Batch growth of E. coli wild type containing the GST-GFP reporter plasmid upon increasing IPTG supplementation at an OD600 of 0.1(dashed line) (A) and the fluorescence signal resulting from the GFP-fusion reporter protein (B). (C) SDS-PAGE of the different proteinpurification steps. M, marker; 1 and 2, different sample volumes of cell extract; 3 and 4, different amounts of cell debris after disruption; 5, cellextract after loading of the affinity matrix; 6 to 12, wash steps; 13 to 15, glutathione elution steps; 16, empty.

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separate mutant cultures (Fig. 3A and D), we concluded thatthe reporter protein can be used to investigate the metabolicpathway usage of a specific population in cocultivated, mixedcultures.

Subpopulation resolvability with the reporter protein de-pends mainly on the purified protein amount. To elucidate theresolvability of metabolic pathway activity in mixed cultureswith various subpopulation fractions, we prepared fractions of0%, 1%, 5%, 10%, and 100% of induced E. coli pgi mutantbatch cultures containing the reporter plasmid together withthe E. coli wild type in a total volume of 70 ml. Both cultures

were grown separately to the same OD600 value and mixed inthe various proportions before cell disintegration. To focus onone key pathway, we investigated the relative PP pathway fluxby using a 100% [1-13C]glucose experiment, and 13C labelingpatterns were derived from the purified, hydrolyzed reporterprotein and whole-cell protein, representing the culture aver-age (Fig. 4).

As expected, the culture average displayed an increase in therelative PP pathway activity in proportion to the fraction of thepgi mutant population in the overall culture. The reporterprotein clearly resolved the increased relative PP pathway ac-tivity in the pgi mutant down to a population fraction of 1%,which corresponds to a volume as small as 0.7 ml for the pgimutant in 70 ml total culture volume. Presumably, even smallerpgi mutant fractions could be clearly distinguished from theculture average based on the hyperbolic curve for the reporterprotein-derived flux ratios. With this hyperbolic curve, the in-creased relative PP pathway activity should be traceable intheory to a population fraction of 0.25% for the pgi mutant, forwhich a PP pathway ratio of about 38% could be clearly dis-tinguished from the culture average.

Nevertheless, the hyperbolic curve also indicated an under-estimation of the relative PP pathway activity in the pgi mutant,which should be at a value of 100% for the PP pathway ratio(Fig. 4). Such an underestimation was not observed in the caseof the cocultivation experiment of the E. coli wild type and pgimutant, in which a 17% pgi mutant culture fraction was unam-biguously identified with the same PP pathway ratio as that ofthe pgi mutant monoculture (Fig. 3A and D). The major dif-ference between the subpopulation resolvability experimentand the cocultivation experiment were the used culture vol-umes. While in the subpopulation resolvability experiment, 0.7ml pgi mutant culture broth was used in a 70-ml total culturevolume, the cocultivation experiment used larger volumes, witha ca. 70-ml pgi mutant culture volume in a 410-ml total culturevolume, corresponding to a 17% pgi mutant culture fraction.Based on these results, we concluded that the underestimatedPP pathway ratio values in the subpopulation resolvability ex-periment were caused by unspecific binding of wild-type pro-teins to the affinity matrix and can be significantly reduced bygreater reporter protein amounts for purification. Thus, forquantitative 13C flux analysis, 1 mg of purified reporter proteinobtained from a 70-ml subpopulation volume, correspondingto a ca. 50-mg subpopulation biomass dry weight, is optimalwith the used purification protocol.

DISCUSSION

We present here a reporter protein-based 13C method toquantitatively resolve subpopulation-specific intracellularfluxes. For a proof of principle, we unambiguously identifiedthe E. coli pgi and mdh mutant-specific metabolic phenotypesin cocultivations with the wild type. The ability to resolvepopulations down to fractions of 1% renders the method ap-plicable to microbial consortia with few species, such as (i)certain natural phototropic consortia (23), (ii) enriched micro-bial communities for degradation/removal of anthropogenicsubstances (7, 17, 30, 45), or (iii) mixed starter cultures in foodbiotechnology (8, 10). Provided that 13C-labeled substrates aredirectly taken up by the species of interest, this method allows

FIG. 2. (A) 13C-determined ratios of converging fluxes calculatedfrom 13C labeling patterns in amino acids of whole-cell protein orpurified reporter protein of E. coli wild-type batch grown on either20% [U-13C]glucose and 80% (wt/wt) naturally labeled glucose or100% [1-13C]glucose (indicated by the asterisk). Standard deviationswere calculated by linearized error propagation (14, 48). (B) Thedirectly calculated flux ratio values (black underlined numbers) at theresolved nodes and their inferred complementary values (gray num-bers). Abbreviations: PP pathway, pentose phosphate pathway; EDpathway, Entner-Doudoroff pathway; TCA cycle, tricarboxylic acidcycle; ub, upper bound; lb, lower bound.

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us to quantify species-specific intracellular flux patterns withinthe consortium.

The current limit for this type of quantitative 13C flux ratioanalysis is the requirement of about 50 mg of subpopulationdry weight to obtain about 1 mg of purified reporter protein.Should that be difficult to achieve for particular applications, afurther reduction of subpopulation biomass would be possibleby (i) reducing the affinity matrix volume to decrease unspecificbinding, (ii) including a size exclusion chromatography stepafter affinity purification to obtain only the fluorescent fractionfor subsequent GC-MS analysis, and (iii) optimizing GC-MSanalysis with large-volume injection techniques (3) to obtainreliable 13C labeling patterns with only 0.1 mg of reporterprotein. The size exclusion chromatography step would notonly significantly reduce unspecific binding to the affinity ma-trix but also reduce glutathione binding proteins from otherpopulations based on the size difference of the reporter proteinand its GFP fluorescence signal that can be used for a simpleassay.

While the resolution of intracellular fluxes would be desir-able, one key metabolic question in microbial consortia is typ-ically much more trivial (15): which nutrients does a particularspecies or subpopulation actually consume? This question ishard to address directly because mixed cultures thrive in orgenerate themselves often complex nutritional conditions withseveral possible carbon substrates. Without ab initio knowledgeof the consumed substrates, 13C flux analysis cannot resolveintracellular fluxes in subpopulations. Here, our reporter pro-tein method can be used as a discovery tool to identify theconsumed or exchanged carbon substrate for subpopulationgrowth. This could be achieved, for example, by adding occur-ring substrates as the 13C-labeled tracers and detecting 13C-labeled enrichment in the amino acids of the reporter protein.The IPTG induction used here could potentially cause physi-ological changes in consortia, e.g., changes in the populationdistribution. Hence, the experimenter should choose an appro-priately inducible promoter or use instead a constitutive, spe-cies-specific promoter for the reporter protein. By choosing a

FIG. 3. (A) 13C-determined ratios of converging fluxes calculated from 13C labeling patterns in amino acids of the purified reporterprotein obtained from separate E. coli wild-type and pgi and mdh deletion mutant batch cultures grown on a mixture of 20% [U-13C]glucoseand 80% naturally labeled glucose. The affected enzymatic reactions of the pgi and mdh deletion mutants in the metabolic network of E. coliare highlighted by black boxes. Cocultivation experiments of E. coli wild type with the pgi deletion mutant (B) or mdh deletion mutant(C) containing the reporter plasmid and grown on a mixture of 20% [U-13C]glucose and 80% naturally labeled glucose. Reporter proteinproduction was induced upon addition of 0.05 mM IPTG at an OD600 of 0.1. Dashed lines represent growth curves of each strain estimatedfrom inocula and individual growth rates from monocultures. The black lines are the sums of those estimated growth curves. Black circlesmark the time of harvest of the complete culture with final population fractions of 17% for the pgi mutant and 49% for the mdh mutant.(D) 13C-determined ratios of converging fluxes calculated from 13C labeling patterns in amino acids of the purified reporter protein fromthe cocultivation experiments described for panels B and C. Abbreviations: G6P, glucose 6-phosphate; GAP, glyceraldehyde 3-phosphate;E4P, erythrose-4-phosphate; F6P, fructose 6-phosphate; FBP, fructose 1,6-bisphosphate; PGA, phosphoglycerate; R5P, ribose 5-phosphate;Ru5P, ribulose 5-phosphate; S7P, sedoheptulose 7-phosphate; X5P, xylose 5-phosphate.

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naturally induced, species-specific promoter, one can directlystudy the metabolic response that activates this promoter, e.g.,different nutrients or stress conditions.

ACKNOWLEDGMENTS

This work was supported by European Union BaSysBio ProgramGrant LSHG-CT-2006-037469.

We thank B. Stecher for generously providing the reporter plasmid.

REFERENCES

1. Amann, E., J. Brosius, and M. Ptashne. 1983. Vectors bearing a hybridtrp-lac promoter useful for regulated expression of cloned genes in Esche-richia coli. Gene 25:167–178.

2. Baba, T., et al. 2006. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol. Syst. Biol. 2:2006.0008.

3. Bailey, R. 2005. Injectors for capillary gas chromatography and their appli-cation to environmental analysis. J. Environ. Monit. 7:1054–1058.

4. Becker, D., et al. 2006. Robust Salmonella metabolism limits possibilities fornew antimicrobials. Nature 440:303–307.

5. Bonarius, H. P. J., G. Schmid, and J. Tramper. 1997. Flux analysis ofunderdetermined metabolic networks: the quest for the missing constraints.Trends Biotechnol. 15:308–314.

6. Brown, S. A., K. L. Palmer, and M. Whiteley. 2008. Revisiting the host as agrowth medium. Nat. Rev. Microbiol. 6:657–666.

7. Carvalho, M. F., C. C. Alves, M. I. Ferreira, P. De Marco, and P. M. Castro.2002. Isolation and initial characterization of a bacterial consortium able tomineralize fluorobenzene. Appl. Environ. Microbiol. 68:102–105.

8. Ciani, M., F. Comitini, I. Mannazzu, and P. Domizio. 2010. Controlledmixed culture fermentation: a new perspective on the use of non-Saccharo-myces yeasts in winemaking. FEMS Yeast Res. 10:123–133.

9. Claus, S. P., et al. 2008. Systemic multicompartmental effects of the gutmicrobiome on mouse metabolic phenotypes. Mol. Syst. Biol. 4:219.

10. Cogan, T. M., et al. 2007. Invited review: advances in starter cultures andcultured foods. J. Dairy Sci. 90:4005–4021.

11. DeLong, E. F. 2009. The microbial ocean from genomes to biomes. Nature459:200–206.

12. Dumont, M. G., and J. C. Murrell. 2005. Stable isotope probing—linkingmicrobial identity to function. Nat. Rev. Microbiol. 3:499–504.

13. Eylert, E., et al. 2008. Carbon metabolism of Listeria monocytogenes growinginside macrophages. Mol. Microbiol. 69:1008–1017.

14. Fischer, E., and U. Sauer. 2003. Metabolic flux profiling of Escherichia colimutants in central carbon metabolism using GC-MS. Eur. J. Biochem. 270:880–891.

15. Glaeser, J., and J. Overmann. 2003. The significance of organic carboncompounds for in situ metabolism and chemotaxis of phototrophic consortia.Environ. Microbiol. 5:1053–1063.

16. Guan, K. L., and J. E. Dixon. 1991. Eukaryotic proteins expressed in Esch-erichia coli: an improved thrombin cleavage and purification procedure offusion proteins with glutathione S-transferase. Anal. Biochem. 192:262–267.

17. Kim, H. J., J. Q. Boedicker, J. W. Choi, and R. F. Ismagilov. 2008. Definedspatial structure stabilizes a synthetic multispecies bacterial community.Proc. Natl. Acad. Sci. U. S. A. 105:18188–18193.

18. Leroy, Q., and D. Raoult. 2010. Review of microarray studies for host-intracellular pathogen interactions. J. Microbiol. Methods 81:81–95.

19. Li, M., et al. 2008. Symbiotic gut microbes modulate human metabolicphenotypes. Proc. Natl. Acad. Sci. U. S. A. 105:2117–2122.

20. McInerney, M. J., J. R. Sieber, and R. P. Gunsalus. 2009. Syntrophy inanaerobic global carbon cycles. Curr. Opin. Biotechnol. 20:623–632.

21. Musat, N., et al. 2008. A single-cell view on the ecophysiology of anaerobicphototrophic bacteria. Proc. Natl. Acad. Sci. U. S. A. 105:17861–17866.

22. Olszewski, K. L., et al. 2009. Host-parasite interactions revealed by Plasmo-dium falciparum metabolomics. Cell Host Microbe 5:191–199.

23. Overmann, J. 2010. The phototrophic consortium “Chlorochromatium aggre-gatum”—a model for bacterial heterologous multicellularity. Adv. Exp. Med.Biol. 675:15–29.

24. Perrenoud, A., and U. Sauer. 2005. Impact of global transcriptional regula-tion by ArcA, ArcB, Cra, Crp, Cya, Fnr, and Mlc on glucose catabolism inEscherichia coli. J. Bacteriol. 187:3171–3179.

25. Roling, W. F. M., M. Ferrer, and P. N. Golyshin. 2010. Systems approachesto microbial communities and their functioning. Curr. Opin. Biotechnol.21:532–538.

26. Sauer, U. 2006. Metabolic networks in motion: 13C-based flux analysis. Mol.Syst. Biol. 2:62.

27. Sauer, U., et al. 1999. Metabolic flux ratio analysis of genetic and environ-mental modulations of Escherichia coli central carbon metabolism. J. Bac-teriol. 181:6679–6688.

28. Shaikh, A. S., Y. J. Tang, A. Mukhopadhyay, and J. D. Keasling. 2008.Isotopomer distributions in amino acids from a highly expressed protein asa proxy for those from total protein. Anal. Chem. 80:886–890.

29. Shitu, J. O., J. M. Woodley, R. Wnek, M. Chartrain, and C. J. Hewitt. 2009.Induction studies with Escherichia coli expressing recombinant interleu-kin-13 using multi-parameter flow cytometry. Biotechnol. Lett. 31:577–584.

30. Snellinx, Z., S. Taghavi, J. Vangronsveld, and D. van der Lelie. 2003. Mi-crobial consortia that degrade 2,4-DNT by interspecies metabolism: isolationand characterisation. Biodegradation 14:19–29.

31. Stecher, B., and W. D. Hardt. 2008. The role of microbiota in infectiousdisease. Trends Microbiol. 16:107–114.

32. Stecher, B., et al. 2007. Salmonella enterica serovar Typhimurium exploits in-flammation to compete with the intestinal microbiota. PLoS Biol. 5:2177–2189.

33. Stolyar, S., et al. 2007. Metabolic modeling of a mutualistic microbial com-munity. Mol. Syst. Biol. 3:92.

34. Szyperski, T., et al. 1999. Bioreaction network topology and metabolic fluxratio analysis by biosynthetic fractional 13C labeling and two-dimensionalNMR spectroscopy. Metab. Eng. 1:189–197.

35. Tang, Y. J., et al. 2009. Advances in analysis of microbial metabolic fluxes via13C isotopic labeling. Mass Spectrom. Rev. 28:362–375.

36. Trigo, A., A. Valencia, and I. Cases. 2009. Systemic approaches to biodeg-radation. FEMS Microbiol. Rev. 33:98–108.

37. Uhlík, O., K. Jecna, M. B. Leigh, M. Mackova, and T. Macek. 2009. DNA-based stable isotope probing: a link between community structure and func-tion. Sci. Total Environ. 407:3611–3619.

38. van der Rest, M. E., C. Frank, and D. Molenaar. 2000. Functions of themembrane-associated and cytoplasmic malate dehydrogenases in the citricacid cycle of Escherichia coli. J. Bacteriol. 182:6892–6899.

39. Varma, A., and B. O. Palsson. 1994. Metabolic flux balancing: basic concepts,scientific and practical use. Nat. Biotechnol. 12:994–998.

40. Villas-Boas, S. G., and P. Bruheim. 2007. The potential of metabolomicstools in bioremediation studies. OMICS 11:305–313.

41. Wagner, M., P. H. Nielsen, A. Loy, J. L. Nielsen, and H. Daims. 2006.Linking microbial community structure with function: fluorescence in situhybridization-microautoradiography and isotope arrays. Curr. Opin. Bio-technol. 17:83–91.

42. Whiteley, A. S., M. Manefield, and T. Lueders. 2006. Unlocking the “micro-bial black box” using RNA-based stable isotope probing technologies. Curr.Opin. Biotechnol. 17:67–71.

43. Wiechert, W. 2001. 13C metabolic flux analysis. Metab. Eng. 3:195–206.44. Wikoff, W. R., et al. 2009. Metabolomics analysis reveals large effects of gut

microflora on mammalian blood metabolites. Proc. Natl. Acad. Sci. U. S. A.106:3698–3703.

45. Wilmes, P., et al. 2008. Community proteogenomics highlights microbialstrain-variant protein expression within activated sludge performing en-hanced biological phosphorus removal. ISME J. 2:853–864.

46. Wittmann, C., and E. Heinzle. 1999. Mass spectrometry for metabolic fluxanalysis. Biotechnol. Bioeng. 62:739–750.

47. Zamboni, N., S. M. Fendt, M. Ruhl, and U. Sauer. 2009. 13C-based metabolicflux analysis. Nat. Protoc. 4:878–892.

48. Zamboni, N., E. Fischer, and U. Sauer. 2005. FiatFlux: a software for metabolicflux analysis from 13C-glucose experiments. BMC Bioinformatics 6:209.

FIG. 4. Dependency of the 13C-determined split ratio between gly-colysis and PP pathway on the relative proportion of the E. coli pgideletion mutant and wild type in artificially mixed cultures determinedfrom 13C labeling patterns in amino acids of the purified reporterprotein (black line) or whole-cell protein (gray line) as the cultureaverage. Separate batch cultures were grown on 100% [1-13C]glucoseand mixed to the indicated biomass fractions in a total volume of 70 ml.We used, as controls for the relative PP pathway activity, purifiedreporter proteins from 70-ml monocultures of the E. coli wild type andpgi deletion mutant. Errors for flux ratios were within 2% based onlinearized error propagation (14, 48).

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