Dynamic Metabolic and Transcriptional Profiling of Rhodococcus sp.Strain YYL during the Degradation of Tetrahydrofuran

Zhixing He,a Yanlai Yao,b Zhenmei Lu,a Yangfang Yec

College of Life Sciences, Zhejiang University, Hangzhou, Chinaa; Institute of Environment, Resource, Soil and Fertilizer, Zhejiang Academy of Agricultural Sciences,Hangzhou, Chinab; Key Laboratory of Applied Marine Biotechnology (Ningbo University), Ministry of Education, Ningbo, Chinac

Although tetrahydrofuran-degrading Rhodococcus sp. strain YYL possesses tetrahydrofuran (THF) degradation genes similar tothose of other tetrahydrofuran-degrading bacteria, a much higher degradation efficiency has been observed in strain YYL. In thisstudy, nuclear magnetic resonance (NMR)-based metabolomics analyses were performed to explore the metabolic profiling re-sponse of strain YYL to exposure to THF. Exposure to THF slightly influenced the metabolome of strain YYL when yeast extractwas present in the medium. The metabolic profile of strain YYL over time was also investigated using THF as the sole carbonsource to identify the metabolites associated with high-efficiency THF degradation. Lactate, alanine, glutarate, glutamate, glu-tamine, succinate, lysine, trehalose, trimethylamine-N-oxide (TMAO), NAD�, and CTP were significantly altered over time instrain YYL grown in 20 mM THF. Real-time quantitative PCR (RT-qPCR) revealed changes in the transcriptional expression lev-els of 15 genes involved in THF degradation, suggesting that strain YYL could accumulate several disturbances in osmoregula-tion (trehalose, glutamate, glutamine, etc.), with reduced glycolysis levels, an accelerated tricarboxylic acid cycle, and enhancedprotein synthesis. The findings obtained through 1H NMR metabolomics analyses and the transcriptional expression of the cor-responding genes are complementary for exploring the dynamic metabolic profile in organisms.

Microbial degradation is one of the main mechanisms respon-sible for the mineralization of pollutants in contaminated

environments (1). Many bacterial strains have been isolated fromcontaminated environments and used to degrade certain pollut-ants. Knowledge of the genes responsible for the catabolism ofpollutants will increase our understanding of the degradation ca-pacities of different strains. However, despite the presence of sim-ilar catabolic genes, the degradation of certain pollutants underthe optimum culturing conditions is highly variable between bac-terial strains. This difference might reflect the fact that pollutantdegradation induces basal metabolism changes in bacteria, andcertain metabolites might be more relevant for degradation ofspecific pollutants by the bacterial strain (2, 3). Therefore, func-tional analyses of the changes in basal metabolism in bacterialstrains during pollutant degradation are essential for understand-ing the mechanism of pollutant degradation.

Metabolomics is a top-down systems biology approach for themetabolic profiling of living organisms and is a tool for the compre-hensive and fully quantitative analysis of low-molecular-weight en-dogenous compounds (sugars, amino acids, fatty acids, etc.) withwhich metabolic responses to biological interventions or environ-mental factors are analyzed and modeled (4–6). Characterizing themetabolome via metabolic profiling provides insight into the state ofthe organism or substance at a particular moment (7). The evaluationof the metabolic profile can be accomplished using a variety of ana-lytical platforms, including gas chromatography-mass spectrometry,liquid chromatography-mass spectrometry, and nuclear magneticresonance (NMR) spectroscopy. Compared with the two chromato-graphic platforms, NMR-based analysis requires simple and easysample preparation, which is beneficial for minimizing changes in thechemical composition and reducing the loss of minor components(8, 9); simultaneously monitors various organic chemical species (10,11); and shows the potential for efficient high-throughput screening(12). Therefore, the application of an NMR-based platform inmetabolomics has been widely reported for studies with a variety of

microorganisms, including studies of metabolic flux changes in Esch-erichia coli during heat (13) and superoxide (14) stresses andthe role of genes in Saccharomyces cerevisiae (15, 16). High-throughput NMR-based metabolomics analysis facilitates thecharacterization of large numbers of individuals. Multivariate sta-tistical analyses, such as principal component analysis (PCA) andorthogonal projection to latent structures discriminant analysis(OPLS-DA), have proven efficient for reducing high-throughputNMR spectral data and visualizing the similarities between differ-ent groups (2, 17, 18).

The cyclic aliphatic ether tetrahydrofuran (THF) has beenwidely used as a common solvent in bulk chemical and pharma-ceutical industries and has received much attention due to its re-lease into environments and toxicity to organisms. The high watersolubility, vapor pressure, and high production volume pressureof THF make this pollutant easily detectable in groundwater (19).As an inhibitor of cytochrome P450-dependent enzymes, THFinduces central nervous system irritation, narcosis, edema, andcolonic muscle spasms in animals (20–22). Although THF is noteasily mineralized due to its cyclic structure, many microorgan-isms that utilize THF as their sole carbon and energy source underaerobic conditions have been isolated. These microorganisms pri-marily belong to Gram-positive actinomycetes of the genera Rho-

Received 13 December 2013 Accepted 3 February 2014

Published ahead of print 14 February 2014

Editor: H. Nojiri

Address correspondence to Zhenmei Lu, lzhenmei@zju.edu.cn, or Yangfang Ye,yeyangfang@nbu.edu.cn.

Supplemental material for this article may be found at http://dx.doi.org/10.1128/AEM.04131-13.

Copyright © 2014, American Society for Microbiology. All Rights Reserved.

doi:10.1128/AEM.04131-13

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dococcus (23–25) and Pseudonocardia (26, 27) and Gram-negativePseudomonas species (22, 28). Although the mechanism and path-way of THF oxidation have not been firmly established, THFmonooxygenase has been identified as a key enzyme for the initi-ation of THF degradation in these microorganisms. The THFmonooxygenase gene of Rhodococcus sp. strain YYL has beencloned and sequenced and has 96% similarity to that of Pseudono-cardia sp. strain K1 (29). Notably, Rhodococcus sp. strain YYL ex-hibits a high degradation rate, namely, 137.6 mg THF/(h · g [dryweight] strain YYL), which is more than approximately five timesgreater than the degradation rate of other THF-degrading strains(23). Therefore, it is important to characterize the mechanismsunderlying the high-efficiency THF degradation of strain YYL.The variations of the metabolome induced by THF in strain YYLshould be relevant to its THF degradation efficiency, and explor-ing the dynamic metabolic profile in response to THF might revealthe basic mechanism underlying its high degradation efficiency.

In this study, we used an NMR-based metabolomics methodcoupled with multivariate data analysis to systematically investi-gate the metabolic differences in strain YYL when utilizing THF oryeast extract, individually or simultaneously, as a carbon source.Moreover, real-time quantitative PCR (RT-qPCR) analysis wasfurther employed to measure the transcriptional expression of 15relevant genes when YYL cells utilized THF as the sole carbonsource. These findings will provide an overview of the physiolog-ical response and adaptation of Rhodococcus sp. YYL to THF ex-posure and degradation.

MATERIALS AND METHODSStrain and culture conditions. THF-degrading Rhodococcus sp. strainYYL was previously isolated from the activated sludge of a wastewatertreatment plant (23). Strain YYL was cultured in 100 ml liquid optimalbase mineral medium (BMM) (23). The medium was supplemented with1 g/liter yeast extract (CY), with 20 mM THF (CT), or with both THF andyeast extract (TY). During cultivation, the agitation ratio was maintainedat 140 rpm and the temperature was maintained at 30°C. One Erlenmeyerflask of culture was used for each sample, and eight replicates were pre-pared for every sampling time point in the three treatment groups.

Sample collection and metabolite extraction. The sampling time inthe experiment was decided according to the growth kinetics of Rhodo-coccus sp. strain YYL in the three treatment groups (see Fig. S1 in thesupplemental material). Three sampling time points were chosen in eachtreatment: 12 h (exponential-phase growth), 48 h (early stage of station-ary-phase growth), and 84 h (late stage of stationary-phase growth) in CY;12 h (exponential-phase growth), 48 h (exponential-phase growth), and84 h (stationary-phase growth) in TY; and 48 h (exponential-phasegrowth), 84 h (exponential-phase growth), and 132 h (stationary-phasegrowth) in CT. Metabolism was quenched after the flasks were chilled onice, followed by centrifugation at 6,000 rpm for 5 min at 4°C and thesubsequent decanting of the supernatant. The cell pellet was subsequentlywashed three times with 1 ml of ice-cold phosphate-buffered saline (6,000rpm, 5 min, 4°C) and homogenized in 600 �l of an ice-cold aqueousmethanol solution (methanol– double-distilled H2O [2:1]). Intracellularmetabolites were extracted ultrasonically (i.e., 3 s of sonication with a 3-sbreak) for 10 min. The supernatants were collected after 10 min of cen-trifugation at 12,000 rpm and 4°C, and the cell debris was further ex-tracted twice using the same procedure. After combining the three solu-tions obtained, the extracts were lyophilized after removing the methanolin vacuo. Each bacterial extract was separately reconstituted in 600 �lNa�/K� phosphate buffer (K2HPO4-NaH2PO4, 0.1 M, pH 7.4) contain-ing 100% D2O and 0.005% sodium 3-trimethylsilyl [2,2,3,3-d4] propi-onate (TSP). Following centrifugation, the supernatant (550 �l) of eachextract was transferred to a 5-mm NMR tube for NMR analysis.

NMR measurements. All NMR spectra of bacterial samples were re-corded using a Bruker Avance III 600-MHz spectrometer (Bruker Bio-Spin, Germany), operating at 600.13 MHz and 298 K during acquisition.A standard one-dimensional NMR spectrum was acquired with the firstincrement of the nuclear Overhauser enhancement spectroscopy pulsesequence (relaxation delay-90°-t1-90°-tm-90°-acquisition), with a relax-ation delay of 2 s, a mixing time (tm) of 100 ms, a delay time (t1) of 6.5 �s,and a 90° pulse length of 10 �s. Water suppression was achieved throughpresaturation at the water resonance frequency. Sixty-four free inductiondecays were collected into 32,000 data points for each spectrum, with aspectral width of 20 ppm centered at the water resonance. An exponentialwindow function with a line-broadening factor of 0.5 Hz was applied tofree induction decays prior to the Fourier transformation of the data. ForNMR signal assignment, a range of two-dimensional NMR spectra for theselected samples was acquired as previously described (2, 30), including1H-1H correlation spectroscopy (COSY), 1H-1H total correlation spec-troscopy (TOCSY), 1H-13C heteronuclear multiple-bond correlation(HMBC), and 1H-13C heteronuclear single quantum correlation (HSQC)spectra.

NMR data processing and multivariate data analysis. All 1H NMRspectra were manually phased, baseline corrected, and calibrated to TSP at� 0.00 using the TOPSPIN (v2.0) program (Bruker BioSpin, Germany).The data reduction was performed after dividing the region of � 9.7 to 0.7into bins with a width of 0.004 ppm (2.4 Hz) using the AMIX package(v3.8.3; Bruker BioSpin, Germany). The regions at � 3.4 to 3.3 and � 4.95to 4.7 were discarded to remove the effects of methanol and imperfectwater suppression resonance. Following the normalization of each spec-trum to the total spectral intensity, PCA was performed on the mean-centered NMR data using the SIMCA-P� software package (v11.0; Umet-rics, Sweden) to generate an overview of sample clustering, such asdistributions and possible outliers. OPLS-DA, a supervised multivariatedata analysis tool, was subsequently applied to analyze the 1H NMR spec-tral data scaled to unit variance as the x matrix and group information asthe y matrix. The OPLS-DA models were successively evaluated using an8-fold cross-validation (CV) method (31) and CV analysis of variance(ANOVA) (32). To facilitate the interpretation of the OPLS-DA results,the loading indicating altered metabolites in response to THF treatmentwas back-transformed (33) and plotted with a color-coded correlationcoefficient (r) using a Matlab script (Mathworks), with some modifica-tions. The coefficients describe the weighting of variables contributing tothe class separation of the model, with a hot color (i.e., red) being moresignificant than a cold color (i.e., blue). In this study, a cutoff value of 0.67(�r�, �0.67) for correlation coefficients was used for the statistical signif-icance analysis on the basis of the discrimination significance at the level ofP equal to �0.05. In addition, one-way ANOVA was used to test thevariances between CY and TY or over time in CT. The analysis was per-formed using SPSS (v16.0) statistical software.

RNA isolation, cDNA generation, and RT-qPCR. Total RNA of strainYYL grown in CT was separately extracted with the RNAiso Plus reagent(TaKaRa, Dalian, China) and reverse transcribed into cDNA using a Pri-meScript reverse transcriptase reagent kit (TaKaRa).

RT-qPCR reactions were performed in a 20-�l volume containing 10 �lSYBR Premix Ex Taq (TaKaRa), 0.4 �l of each forward and reverse gene-specific primer (10 �M), and 2.0 �l of cDNA (1:10 dilution). Gene-specificprimers were designed using Beacon Designer (v7) software (see Table S1 inthe supplemental material). The V3 region of 16S rRNA, used as an internalstandard, was amplified using the primers F338 (CCTACGGGAGGCAGCAG) and R518 (ATTACCGCGGCTCGTGG). All RT-qPCR experimentswere performed on a Mastercycler ep realplex system (Eppendorf, Hamburg,Germany) according to the user’s guide. Three independent cDNA sampleswere assayed, and the 2�CT method (where CT is the threshold cycle) (34)was used to calculate the gene expression levels for strain YYL. The expressionof 15 related genes at 48 h was normalized to 1. Analysis of variance wasperformed as described above.

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RESULTSMetabolites of strain YYL. Figure 1 shows some typical 1H NMRspectra of aqueous extracts of Rhodococcus sp. strain YYL grown inyeast extract (CY), THF (CT), and both yeast extract and THF(TY). The endogenous metabolite resonances were assigned ac-cording to their chemical shifts on the basis of data obtained fromthe literature (35, 36) and/or an online database (http://www.hmdb.ca/). We also confirmed peak assignments according to aseries of two-dimensional NMR experiments, including 1H-1HCOSY, 1H-1H TOCSY, 1H-13C HSQC, and 1H-13C HMBC (de-tailed information is provided in Table S2 in the supplementalmaterial). The spectra of strain YYL showed signals primarilyfrom sugars (trehalose and glucose), amino acids (isoleucine, leu-cine, valine, threonine, alanine, glutamine, glutamate, aspartate,D-hydroxylysine, lysine, and glycine), nucleoside and nucleotidemetabolites (adenosine, NAD�, adenosine 2=,3=-cyclic phosphate,CTP, and uridine), amines (trimethylamine, dimethylamine, andtrimethylamine-N-oxide [TMAO]), organic acids (glutarate, suc-cinate, fumarate, lactate, formate, acetate, and 3-D-hydroxybu-tyrate), ethanol, acetone, betaine, and choline. The visual inspec-tion of these spectra revealed that at 84 h strain YYL grown in TYhad a lower lactate level as well as a higher trehalose level than YYLgrown in CY (Fig. 1). Analysis of the NMR profiles for strain YYLgrown in CT showed significant changes of metabolites over time.For instance, an increased level of trehalose was observed at 84 hrelative to the level at 48 h, whereas at 132 h the trehalose level wasdecreased relative to that at 84 h (data not shown). To obtaindetailed information on THF-induced metabolic alterations, amultivariate data analysis of these NMR profiles was performed.

THF-related metabolomic changes. PCA of the normalizedNMR profiling of strain YYL was conducted (see Fig. S2 in thesupplemental material). The plot of the PCA scores obtained fromthe NMR data showed intercellular metabolomic differences(dashed line in Fig. S2 in the supplemental material) in strain YYL,dominated by the carbon resource intervention in the first twoprincipal components (PC1 and PC2), which cumulatively ex-plained 85.4% of the total variances. A clear difference between

the CY and CT groups was observed, reflecting differences in thecarbon resource; the TY group represented the transition of themetabolome in strain YYL using yeast extract and THF as cocar-bon sources. Moreover, the change trajectory illustrated relativelysimilar metabolic profiles between the CY and TY groups at 12 hand 48 h, but a clear difference in the metabolic profiles of the CYand TY groups was observed at 84 h. Notably, in the plot of PCAscores, the metabolic profile of strain YYL grown in TY at 84 hclustered with that of strain YYL grown in CT at 48 h.

Pairwise comparative OPLS-DA was further conducted withthe NMR data for strain YYL from the TY and CY groups obtainedat various time points and the NMR data obtained at differenttime points for the CT group. The quality of these OPLS-DA mod-els was validated through the Q2 (predicted classification) valuesand P values obtained from CV analysis of variance (ANOVA)(Table 1). The dominant metabolites for differentiation from se-lected models are shown in the OPLS-DA coefficient plots (Fig. 2).The values of the correlation coefficients for the metaboliteswhose levels were significantly altered are listed in Table 1. Com-pared with the levels for strain YYL in the CY group, a significantdecrease in the lactate level and a marked increase in the glutaminelevel in strain YYL in the TY group were observed at 12 and at 48 h,respectively. More significantly altered levels of metabolites, in-cluding a significant elevation of glutamate and trehalose levelsand a significant depletion of lactate, alanine, glutarate, lysine, andTMAO levels, were observed at 84 h for strain YYL grown in TYcompared with the values for strain YYL grown in CY. The THF-associated dynamic concentration variations for some metabolitesrepresenting different pathways were further determined usingone-way ANOVA (see Fig. S3 in the supplemental material). Ala-nine in strain YYL from both the CY and TY groups exhibitedsimilar trends of decreased levels over time, with a significant de-pletion in TY compared with the amount in CY at 84 h (P � 0.01).Glutarate and lysine in strain YYL in CY presented a trend ofdecreased levels, followed by a trend of increased levels, but main-tained a substantial depletion during the entire process whenstrain YYL was grown in TY. In contrast, glutamate and trehalose

FIG 1 Typical 600-MHz 1H NMR spectra of aqueous extracts of Rhodococcus sp. YYL grown in CY, TY, and CT. The spectral regions were vertically expanded2 and 8 times from � 0.7 to 3.3 and 32 times from � 5.7 to 9.5 compared with the spectra of the region from � 3.4 to 5.6. Key to the peaks: 1, isoleucine; 2, leucine;3, valine; 4, ethanol; 5, 3-D-hydroxybutyrate; 6, lactate; 7, threonine; 8, alanine; 9, acetate; 10, acetone; 11, glutarate; 12, glutamate; 13, glutamine; 14, succinate;15, aspartate; 16, dimethylamine; 17, trimethylamine; 18, D-hydroxylysine; 19, lysine; 20, choline; 21, betaine; 22, trimethylamine-N-oxide; 23, trehalose; 24,glycine; 25, -glucose; 26, �-glucose; 27, fumarate; 28, uridine; 29, adenosine 2=,3=-cyclic phosphate; 30, adenosine; 31, formate; 32, NAD�; 33, CTP; 34, residualmethanol.

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exhibited steady increases in levels in both of these groups, with amarked increase in TY compared with that in CY at 48 h (P �0.05) and 84 h (P � 0.01).

When strain YYL utilized THF as the sole carbon source, thecontent of metabolites varied with the bacterial growth stages andTHF degradation rates. As shown in the OPLS-DA coefficient plot(Fig. 2; see Fig. S3 in the supplemental material), strain YYL grownin CT for 84 h had a significantly higher level of trehalose (P �0.01) and remarkably lower levels of lactate, alanine, glutamate,glutamine, succinate, NAD�, and CTP compared with those at 48h (P � 0.01). At 132 h, strain YYL had dramatically higher levels oflactate, alanine, and TMAO and markedly lower levels of glu-tamine and trehalose compared with those at 84 h (P � 0.01).

RT-qPCR analysis of gene expression in strain YYL. The tran-scriptional levels of 15 related genes involved in THF degradation,sugar and amino acid synthesis, the central genetic processes, andoxidative stress in strain YYL grown in CT were assessed over time(48, 84, and 132 h) by RT-qPCR using paired primers (see TableS1 in the supplemental material). Our observations showed thatthe expression of thm, encoding THF-degrading monooxygenase,decreased with decreasing THF concentrations over time, with asignificant change in the level of thm expression at 84 h comparedwith the level at 48 h being observed when the strain was grown inCT (P � 0.01) (Fig. 3; see Fig. S1 in the supplemental material).

During glycolysis, phosphofructokinase (pfk) and glyceralde-hyde-3-phosphate dehydrogenase (gpd) regulate two significant

TABLE 1 Significantly altered metabolites in Rhodococcus sp. strain YYLin response to THF treatment

Metabolite

ra

TY vs CY CT

12 h 48 h 84 h 84 h vs 48 h 132 h vs 84 h

Lactate �0.85 — �0.92 �0.89 0.83Alanine — — �0.86 �0.95 0.77Glutarate — — �0.94 �0.72 —Glutamate — — 0.81 �0.88 —Glutamine — 0.94 — �0.89 �0.77Succinate — — — �0.84 —Lysine — — �0.93 — —TMAO — — �0.78 — 0.87Trehalose — — 0.98 0.69 �0.75NAD — — — �0.79 —CTP — — — �0.88 —a Positive and negative signs for the correlation coefficients indicate positive and negativecorrelations in the concentrations, respectively. P was equal to 0.05, 7 degrees of freedomwas used, and r equal to 0.67 was used as the corresponding cutoff value of the correlationcoefficient for the statistical significance on the basis of the discrimination significance. ForTY versus CY at 12, 48, and 84 h, R2X � 0.549, Q2 � 0.948, and P � 0.0062; R2X � 0.549,Q2 � 0.948, and P � 0.0072; and R2X � 0.549, Q2 � 0.948, and P � 4.86 10�7,respectively. For CT at 84 h versus 48 h and 132 h versus 84 h, R2X � 0.482, Q2 � 0.934,and P � 1.92 10�6 and R2X � 0.690, Q2 � 0.931, P � 1.38 10�5, respectively. —, |r|was less than the cutoff value. The R2X values describe the goodness of fit of the models withthe NMR data, and the Q2 values describe the predictive capacity of the model.

FIG 2 Cross-validated OPLS-DA scores (a to c) and corresponding coefficient plots (d to f) derived from the 1H NMR spectra of the extracts of Rhodococcus sp.YYL. (a, d) Comparison of results with growth in CY (black stars) and TY (red dots) at 84 h; (b, e) comparison of data at 48 h (black stars) and 84 h (red dots)with growth in CT; (c, f) comparison of data at 84 h (black stars) and 132 h (red dots) with growth in CT. In the scales on the right, red indicates importantdiscriminatory metabolites, whereas blue indicates no significance in discrimination. Metabolite keys are shown in Table 1. t[2]O, cross-validated score value;t[1]P, model score value.

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steps (from fructose-6-phosphate to fructose-1,6-bisphosphateand from glyceraldehyde-3-phosphate to 1,3-bisphosphoglycer-ate, respectively). The expression of pfk was upregulated 5-fold(P � 0.01) at 84 h compared with the level of regulation at 48 h and2-fold downregulated (P � 0.01) at 132 h compared with the levelof regulation at 84 h, while gpd expression was gradually down-regulated over time. Two genes involved in the citrate cycle, mdh,encoding malate dehydrogenase, and gltA, encoding citrate syn-thase, showed significant downregulation with decreasing THFconcentration (P � 0.01 between 48 and 84 h for mdh, P � 0.01over time for gltA). However, sdh, encoding succinate dehydroge-nase, exhibited the highest transcription level at 84 h, when strainYYL was in the initial stationary phase, and this was accompaniedby the highest THF degradation rate (1.92 mM THF/h · g [dryweight] strain YYL) (P � 0.01). Trehalose and glucose were theonly two sugars identified in the NMR analysis, and their relevantgenes were also analyzed. The gene otsA, encoding trehalose-6-phosphatase, responsible for converting UDP-glucose to treha-lose, showed a much higher level of expression during THF deg-radation when strain YYL was in the initial stationary phase (84 h)than when it was in the exponential phase (48 h) (P � 0.01), andexpression of the gene treS, encoding trehalose synthase for con-verting maltose to trehalose, showed no significant change in reg-ulation at 84 h compared with that at 48 h, but it was significantly

downregulated at 132 h compared with the level of regulation at 84h (Fig. 3).

The changes in the dynamic metabolic profile of strain YYL inresponse to THF may reflect not only the metabolite concentra-tion but also changes in other processes, such as DNA replication,RNA transcription, and the oxidative stress response system. Inthis study, DNA repair helicase (pcrA) and DNA gyrase (gyrB)were examined to determine changes in DNA replication, and itwas found that both of these genes were slightly upregulated at 84h compared with their levels of regulation at 48 and 132 h. Genesencoding RNA polymerase sigma factor (rpoB) and ATP-depen-dent RNA helicase (rhiB) were examined to explore the influenceof THF on RNA synthesis over time in CT. The expression of rpoBwas consistent with that of pcrA and gyrB, while rhiB expressiondecreased with increasing THF degradation (Fig. 3; see Fig. S1 inthe supplemental material). The differences between rpoB andrhiB might be due to the fact that the rpoB gene is responsible forRNA synthesis in converting DNA into RNA and the rhiB gene isresponsible for RNA synthesis in RNA self-replication. The serine/threonine protein kinase gene (pto), regulating protein phospho-kinase, showed a greater increase with decreasing THF concentra-tion over time in CT (Fig. 3; see Fig. S1 in the supplementalmaterial). Cytochrome P450 monooxygenase (cyp), which cata-lyzes the oxidation of a wide range of endogenous compounds inbiosynthetic and biodegradation pathways, as well as xenobiotics,such as drugs and environmental contaminants (37), showed anexpected increase in transcription level with decreasing THF con-centration, with a marked increase at 132 h compared with thetranscription level at 84 h (P � 0.01) (Fig. 3; see Fig. S1 in thesupplemental material). A higher concentration of THF had moreinhibitory effects on cytochrome P450-dependent monooxygen-ase in strain YYL, so when the THF concentration decreased overtime in CT, the transcription of cyp increased. Superoxide dismu-tase (sod), a significant antioxidative enzyme in strain YYL,showed decreased transcription with decreasing THF concentra-tion (P � 0.05) (Fig. 3; see Fig. S1 in the supplemental material).The THF concentration decreased due to strain YYL degradation,and the toxicity of THF to strain YYL was also alleviated. Hence, instrain YYL, expression of the activated antioxidant systems (sod)decreased due to weakened stress.

DISCUSSION

In the present study, we examined the metabolite changes in strainYYL in response to THF exposure and further analyzed thechanges in metabolites and gene transcription levels in strain YYLutilizing THF as the sole carbon source. Significant changes inmetabolites in strain YYL grown in TY compared with those instrain YYL grown in CY occurred only at 84 h, reflecting the ex-haustion of yeast extract and the utilization of THF as the primarycarbon source in mineral medium. These results demonstrate thatthe metabolome of strain YYL shows slight variations in responseto THF exposure when THF is utilized as a cocarbon source. Fur-thermore, remarkable alterations of gene expression, includinginhibition of cytochrome P450-dependent monooxygenase syn-thesis, transcription of degradation genes, and induction of acti-vated antioxidant systems to reduce toxicity, were found over timein strain YYL using THF as the sole carbon source. Changes werealso observed in a number of other genes and systemwide meta-bolic networks involved in glycolysis, the tricarboxylic acid (TCA)

FIG 3 Relative transcript levels (RTLs) of selected metabolism genes over timewith growth in CT. One-way ANOVA analysis was used to analyze variancesbetween 48 and 84 h with growth in CT and between 84 and 132 h with growthin CT. **, P � 0.01; *, P � 0.05. Genes in panel a: gyrB, DNA gyrase subunit Bgene; rpoB, RNA polymerase sigma gene; pcrA, ATP-dependent DNA helicasegene; rhiB, ATP-dependent RNA helicase gene; pto, serine/threonine proteinkinase gene; cyp, cytochrome P450 monooxygenase gene; sod, superoxide dis-mutase gene; thm, tetrahydrofuran monooxygenase gene. Genes in panel b:pfk, phosphofructokinase gene; gpd, glyceraldehyde-3-phosphate dehydroge-nase gene; treS, trehalose synthase gene; otsA, trehalose-6-phosphatase phos-phatase gene; mdh, malate dehydrogenase gene; sdh, succinate dehydrogenasegene; gltA, citrate synthase gene.

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cycle, osmoregulation, and amino acid and nucleotide metabo-lism (Fig. 4).

Relation of glycolysis cycle to energy metabolism. An in-creased rate of metabolism of glucose in response to exposure tohazardous organic pollutants is observed in most bacterial strains(2, 38). The present study also revealed decreased glucose (�-glucose and -glucose combined) concentrations due to the in-creased metabolic rate in strain YYL in response to THF exposure;however, glucose accumulated over time during THF degradationwith growth in CT (see Fig. S3 in the supplemental material).Glycolysis is well-known to be the potential main pathway of glu-cose consumption. Two significant genes involved in glycolysis,those encoding phosphofructokinase (pfk) and glyceraldehyde-3-phosphate dehydrogenase (gpd), showed marked changes withgrowth in CT over time. The trend for a variation in the expressionof pfk differing from that of gpd may be due to anaerobic metab-olism in strain YYL, which resulted in the production of lactate orethanol in the glycolysis cycle (see Fig. S3 in the supplementalmaterial). Lactate was observed to be a metabolite significantlyaltered over time with growth in TY compared with growth in CYor CT (Table 1). THF exposure reduced lactate accumulation instrain YYL, and THF degradation also resulted in the depletion oflactate from 48 h to 84 h with growth in CT (see Fig. S3 in thesupplemental material). Thus, it can be inferred that THF is usedby strain YYL as an extra carbon resource and inhibits lactatefermentation in the cytoplasm.

Relation of TCA cycle to THF degradation pathway. THF canbe transformed into 4-hydroxybutyraldehyde through the oxida-tion or hydration pathway, and then 4-hydroxybutyraldehyde is

converted to succinate via succinate semialdehyde in Rhodococcusspecies (25). Therefore, succinate is the key intermediate linkingthe TCA cycle with the THF degradation pathway. THF exposureshowed almost no effect on the succinate concentration; however,over time the succinate concentration was significantly altered inresponse to THF when strain YYL was grown in CT. The reasonmight be that intracellular THF degradation enhances succinateaccumulation in strain YYL. This observation is in fair agreementwith the observations made in Pseudomonas sp. strain HF-1 dur-ing its degradation of nicotine (2). Succinate accumulation wouldinduce the transcription of succinate dehydrogenase (sdh), whichcatalyzes the conversion of succinate to fumarate, at a high level instrain YYL (Fig. 3), resulting in changes in the level of fumarate(P � 0.05; data not shown) with growth in CT over time. Twoother genes involving in the TCA cycle, the citrate synthase gene(gltA) and the malate dehydrogenase gene (mdh), showed highertranscription levels due to the higher THF concentration. Thedifferent trends in the changes in transcription levels between sdhand mdh might be because sdh expression mainly depends onsuccinate accumulation and mdh expression mainly depends onthe THF concentration. The results presented above reveal thatacceleration of the TCA cycle is beneficial for THF degradation.The TCA cycle is usually observed to be accelerated during theprocess of degradation of hazardous organic pollutants (39).

Osmoadaptation-associated metabolism. Trehalose is anonreducing disaccharide and is the main compatible solute pro-tecting cells against environmental stresses in bacteria (40, 41),Saccharomyces cerevisiae (42, 43), plants (44), and invertebrates(45). THF exposure caused a slight increase in trehalose levels in

FIG 4 Altered metabolic pathways in Rhodococcus sp. strain YYL over the time course of growth in CT. Descriptions of the genes, abbreviations, and symbols:gyrB, DNA gyrase subunit B gene; rpoB, RNA polymerase sigma gene; pcrA, ATP-dependent DNA helicase gene; rhiB, ATP-dependent RNA helicase gene; pto,serine/threonine protein kinase gene; mdh, malate dehydrogenase gene; sdh, succinate dehydrogenase gene; gltA, citrate synthase gene; thm, tetrahydrofuranmonooxygenase gene; cyp, cytochrome P450 monooxygenase gene; sod, superoxide dismutase gene; pfk, phosphofructokinase gene; gpd, glyceraldehyde-3-phosphate dehydrogenase gene; treS, trehalose synthase gene; otsA, trehalose-6-phosphatase phosphatase gene; F6P, fructose-6-phosphate; FBP, fructose-1,6-bisphosphate; DHAP, dihydroxyacetone phosphate; 1,3-BPG, 1,3-bisphosphoglycerate; acetyl-CoA, acetyl coenzyme A; blue, compounds detected from NMRdata; purple, gene names; dotted arrows, proposed metabolic pathways; red triangles, significant increase; inverted green triangles, significant decrease; blacksquares, no significant variations. The two symbols adjacent to genes or metabolites represent the variations over time with growth in CT, with the first symbolrepresenting the variation between 48 h and 84 h and the second one representing the variation between 84 h and 132 h. Glucose represents �-glucose and-glucose combined.

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strain YYL, and the obvious accumulation of trehalose was exhib-ited in strain YYL during THF degradation. It has been suggestedthat four pathways, including OtsA/B (from UDP-glucose to glu-cose-6-phosphate to form trehalose-6-phosphate and UDP),TreY/Z (from glycogen to trehalose), TreS (from maltose to treh-alose), and TreT (from ADP-glucose to trehalose) (46, 47), areinvolved in trehalose synthesis in bacteria. Among these, twopathways (OtsA/B and TreS) were detected in strain YYL on thebasis of whole-genome scanning (data not shown). The level ofotsA transcription was higher (P � 0.01) at 84 h than that at 48 h;however, the level of transcription of the treS gene showed a slightdifference between 84 and 48 h. Trehalose biosynthesis in bacteriadepends on bacterial physiological requirements under the givenenvironmental stresses (48). Interestingly, two patterns of treha-lose synthesis are flexibly used by strain YYL during THF degra-dation, and these may be beneficial to the balance between sugarmetabolism and glycolysis.

Amino acids also play a significant role in osmotic regulation inresponse to environmental stress in bacteria (13, 49). Amino acidsprotect cells in many ways, including acting as osmolytes, whichaffect cellular water retention, thereby increasing the thermosta-bility of proteins (50, 51). Glutamate and glutamine were shownto be compatible solutes in response to stress. For example, thelevels of glutamate and glutamine accumulation were consistentwith intermediate salinity (1.0 to 1.5 M NaCl) in the cell externalenvironment (49). In the present study, THF exposure inducedthe marked accumulation of glutamate in strain YYL grown in TY,whereas THF degradation resulted in the significant depletion ofboth glutamate and glutamine over time in strain YYL grown inCY. These observations indicate that these two amino acids func-tion as compatible solutes during THF exposure.

Moreover, it is particularly noteworthy that at 132 h a de-creased level of TMAO was observed in strain YYL grown in TYand an increased level of TMAO was observed in strain YYL grownin CY. TMAO is known to be a compatible osmolyte for proteins(52, 53). Such a protective role was shown as TMAO accumula-tion, which has been observed in marine cyanobacteria inhabitinghypersaline environments (54). However, opposite the previousobservations, in this study THF induced a significant decrease inTMAO together with marked THF depletion, which indicates thatTMAO may be not used by strain YYL as a primary osmolyte in thepresence of THF. However, TMAO was accumulated by strainYYL to resist resource exhaustion when this bacterium enteredinto decline phase. It is interesting to notice the different altera-tions of TMAO from trehalose as well, for which a reasonableexplanation could be that strain YYL has multiple compatible sol-ute systems in response to different stresses. The presence of dif-ferent osmoadaptation mechanisms was also found in the Halo-bacteriales (55). A bacterium could also asymmetrically respond todifferent stresses (56).

Amino acid metabolism and nucleotide metabolism. In thisstudy, slight variations in the levels of most amino acids wereinduced in strain YYL in response to THF exposure with growth inTY compared with the levels induced in response to THF exposurewith growth in CY, and significant variations only in the levels ofalanine, glutamate, and glutamine were observed during THFdegradation with growth in CT (Table 1). However, the totalamino acid concentration in strain YYL utilizing THF was lesswith growth in CT than that in CY or TY (data not shown). The

bacterium is usually found to decrease the amino acid concentra-tion under stringent growth conditions (39).

Nucleotides are considered of great interest, as these moleculesare involved in nucleic acid synthesis, energy production, proteinmodification, and antisense oligonucleotide synthesis (57, 58).The effect of THF exposure on the nucleotide concentration instrain YYL was slightly greater during growth in TY than duringgrowth in CY. A reduction in nucleotide biosynthesis is typicallyobserved in response to various stress conditions (59). The levelsof NAD� and CTP were both significantly reduced at 84 h (1.92mM THF/h · g [dry weight] strain YYL) compared with those at 48h (1.82 mM THF/h · g [dry weight] strain YYL) with growth in CT.RT-qPCR results showed that the levels of pcrA and rpoB tran-scription were slightly enhanced with increased THF degradationin CT (P � 0.05). According to the results obtained in the presentstudy, the reason for nucleotide variations might be bacterial cellgrowth and not THF exposure.

In summary, slight variations in the strain YYL metabolomebetween growth in CY and that in TY revealed that THF had littletoxicity to strain YYL. However, the metabolic profile exhibitedrelatively large fluctuations during THF degradation in CT. Inaddition, RT-qPCR was further used to explore the expression ofthe genes involved in the significantly changed metabolite profiles,as shown in the NMR data for strains grown in CT. These resultssuggest that the accumulation of trehalose, enhancement of theconversion of succinate to malate in the TCA, and acceleration ofprotein and nucleotide synthesis might be involved in THF deg-radation. Detailed information on the metabolomics and expres-sion of selected genes could be useful for understanding not onlyTHF degradation/catabolism mechanisms but also the effects ofTHF exposure on bacterial cells.

ACKNOWLEDGMENTS

This work was financially supported by the National Key TechnologiesResearch and Development Program of China during the 12th Five-YearPlan Period (no. 2012BAJ25B07) and the National Natural Science Foun-dation of China (no. 21107092 and 31100032).

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