Proteomic Analysis of 17Î²-Estradiol Degradation ... - ACS Publications

Article pubs.acs.org/est

Proteomic Analysis of 17β-Estradiol Degradation by Stenotrophomonas maltophilia Zhongtian Li,† Renu Nandakumar,‡ Nandakumar Madayiputhiya,‡ and Xu Li†,* †

Department of Civil Engineering, ‡Proteomic and Metabolomic Core Facility, Redox Biology Center, Department of Biochemistry, University of Nebraska-Lincoln S Supporting Information *

ABSTRACT: Microbial degradation plays a critical role in determining the environmental fate of steroid hormones, such as 17β-estradiol (E2). The molecular mechanisms governing the microbial transformation of E2 and its primary degradation intermediate, estrone (E1), are largely unknown. The objective of this study was to identify metabolism pathways that might be involved in microbial estrogen degradation. To achieve the objective, Stenotrophomonas maltophilia strain ZL1 was used as a model estrogen degrading bacterium and its protein expression level during E2/E1 degradation was studied using quantitative proteomics. During an E2 degradation experiment, strain ZL1 first converted E2 to E1 stoichiometrically. At 16 h E1 reached its peak concentration, and microbial growth started. At the same time, enzymes involved in certain catabolic and anabolic pathways were most highly expressed compared to the other time points tested. Among those enzymes, the ones involved in protein and lipid biosyntheses were observed to be particularly active. Based on the metabolite information from a previous study and the proteomic data from this study, we hypothesized that S. maltophilia strain ZL1 was able to convert E1 to amino acid tyrosine through ring cleavage on a saturated ring of the E1 molecule and then utilize tyrosine in protein biosynthesis.

■

INTRODUCTION 17β-estradiol (E2) and its primary microbial degradation product, estrone (E1), have been detected in surface water, groundwater, livestock wastes, and municipal wastewater in North America, Europe, and Asia.1−9 E2, a strong estrogenic compound, can cause adverse impacts on the reproductive system of male fish at tens of ng/L.10,11 Due to the increasing concerns over their broad occurrence in source water and potential health impacts on human beings, U.S. Environmental Protection Agency recently added E2 and E1 to its Contaminant Candidate List 3.12 E2 degrading bacteria have been isolated from various environmental systems, such as wastewater, compost, and constructed wetlands.13−16 Identified E2 degrading bacteria are phylogenetically diverse, including species from Alpha-, Beta-, Gamma-proteobacteria, Actinobacteria, Bacilli, and Flavobacteria.14,17−19 The majority of the identified E2 degrading bacterial species can convert E2 to E1 but cannot further degrade E1, and thus E1 is often detected as the primary degradation metabolite of E2.14,19 A few E2 degrading bacterial strains, which belong to the genera of Sphingomonas, Nitrosomonas, and Rhodococcus, are able to degrade E1.14,17,19 It was speculated that these bacterial strains degrade E1 by utilizing it as a sole carbon and/or energy source. © 2012 American Chemical Society

A few enzymes have been proposed to be involved in the microbial degradation of natural and synthetic estrogens. Ammonia monooxygenase (AMO) in ammonia oxidizing bacteria (AOB) could cometabolically biotransform 17αethinylestradiol (EE2),20 likely by attacking the aromatic ring (the A ring) of EE2.21 In addition, dioxygenase was also thought to be involved in estrogen biodegradation because of its ability to mediate ring cleavage of polyaromatic compounds.22 Dioxygenase in heterotrophs can mineralize EE2 and EE2-derived metabolites generated by AOBs 20 or modify hydroxylated E1.23 To date, studies on the mechanisms of microbial degradation of estrogens primarily relied on the detection and identification of degradation intermediates. A complementary approach is to study the enzymatic systems in estrogen degrading bacteria and elucidate degradation mechanisms by identifying key enzymes involved in degradation. Proteomics directly addresses the level of gene products present in a given cell state.24 Quantitative proteomics typically includes liquid chromatography (LC) separation, tandem mass Received: Revised: Accepted: Published: 5947

January 20, 2012 May 15, 2012 May 15, 2012 May 15, 2012 dx.doi.org/10.1021/es300273k | Environ. Sci. Technol. 2012, 46, 5947−5955

Environmental Science & Technology

Article

15.4 μL water (Sigma-Aldrich, MO). The PCR condition included 2 min denaturing at 95 °C followed by 30 cycles of 2 min denaturing at 95 °C, 45 s of annealing at 58 °C, and 2 min extension at 72 °C, and a final extension for 10 min at 72 °C. PCR products were purified and sequenced bidirectionally at Eurofins MWG Operon (Huntsville, AL). Sequence alignment and phylogenetic tree construction were conducted according to a published protocol.34 The 16S rRNA gene sequences were deposited in NCBI under accession numbers JN085951JN085955. E2 Degradation Profile of S. maltophilia ZL1. To grow cells to a large quantity, bacteria were often cultured in rich media such as R2A and tryptic soy broth (TSB) before being transferred to NMS medium that contain no substrate but the contaminants.14,35 S. maltophilia ZL1 was grown in R2A medium at 30 °C for 24 h before being transferred to three sets of six flasks. Each flask contained 100 mL sterilized R2A medium and received 5-mL S. maltophilia ZL1 culture. After 10 h, cell cultures in the first two sets were centrifuged (8,000 × g for 10 min at 4 °C), washed with phosphate buffer saline (PBS, pH 7.2) twice, and transferred to 12 new flasks each containing 100 mL of E2-saturated NMS medium. Cells in the third set were autoclaved before they were processed in the same manner. The third set and a fourth set, which contained cellfree E2-saturated NMS medium, were used as negative controls. All four sets of flasks were incubated at 30 °C on a shaking table set at 120 rpm. At 0, 4, 16, 36, 68, and 104 h, 70 mL of solution from each flask was filtered (0.2 μm Teflon filter). The filtrate from each flask was collected in a 250 mL amber glass bottle and stored at −20 °C for estrogen measurements. At 0, 4, 16, 36, hours, cells from the first two sets of flasks were harvested by centrifuge, and cell pellets from the same time point were pooled for proteomic analysis. A flowchart describing the degradation experiment is provided in SI Figure S1. Sample Preparation for Proteomic Analysis. Harvested cells were resuspended in 1 mL of 50 mM ammonium bicarbonate containing 8 M urea and 1.5 mM phenylmethylsulfonyl fluoride (PMSF),36 and then lysed using beadbeating for 2.5 min. Cell lysates were centrifuged (16 000g for 10 min at 4 °C) and the bacterial proteins in the supernatant were precipitated with acetone. The proteins were resuspended in 100 mM ammonium bicarbonate containing 6 M urea. The protein concentrations in each sample were measured using a BCA Protein Assay Kit (Thermo Scientific) in the laboratory (SI Table S1), and then quantified again using 2-D Quant kit (GE Health Care) at the UNL Proteomic and Metabolomic Core Facility. Four hundred micrograms of protein from each sample were further reduced with 10 mM dithiothreitol, alkylated with 40 mM iodoacetamide, and digested with sequencing-grade trypsin (Roche) at 1:50 trypsin to protein ratio at 37 °C overnight. Tryptic peptides were desalted and concentrated using solid phase extraction (PepClean C-18 spin column, Pierce), vacuum-dried, and stored at −80 °C until analysis.36 2D Nano LC-MS/MS Analysis for Proteomics. Quantitative proteomics was performed on an Ultimate 3000 Dionex MDLC system (Dionex Corporation, CA) integrated with a nanospray source and LCQ Fleet Ion Trap mass spectrometer (Thermo Scientific). The detailed experimental procedure may be found in refs 36 and 37. In brief, the first dimensional separation was performed on an SCX column (Polysulfethyl, 1 mm i.d. × 15 cm, 5 μm, 300 Å, Dionex). Twenty μL sample

spectrometry (MS/MS) detection, and bioinformatics that identify proteins based on MS spectra.25,26 The resolution on protein expression levels offered by quantitative proteomics grants the technology great potential in studying microbial processes under environmental conditions. For example, proteomics could reveal the protein expression profiles of a polyphosphate accumulating population under aerobic and anaerobic conditions.27 Also, proteomics can detect the shift in oxidation/reduction potential (e.g., from iron reduction to sulfate reduction) at bioremediation sites by detecting changes in community proteome information from contributing bacterial populations.28 Finally, proteomics can also be used to study the importance of key enzymes during microbial degradation of contaminants under environmental conditions 29 and to verify the validity of biomarkers for contaminant remediation.30 Successful applications of quantitative proteomics in environmental studies suggest that it could be a powerful tool in elucidating enzymes involved in microbial degradation of natural estrogens. Identifying key enzymes in biodegradation could help discover microbial estrogen degradation pathways and suggest candidate biomarkers to monitor estrogen degradation by a microbial community. This study reports the global protein expression profile of Stenotrophomonas maltophilia strain ZL1 during E2 biodegradation. Two distinctive phases in microbial E2 degradation were identified and studied using differential protein expression profiles. An E2 degradation pathway was proposed based on protein identification and pathway annotation.

■

MATERIALS AND METHODS Isolating Estrogen Degrading Bacteria. Due to E2’s low solubility in water the E2 stock solution was prepared in acetone, and the acetone carried over to subsequent experiments was removed by heating and purging.14 Two batch reactors were established in 1-L amber glass bottles with 700 mL nitrate mineral salts (NMS) media saturated with E2 or E1 (i.e., ∼3 mg/L).31 Activated sludge from a local municipal wastewater treatment plant was used to seed the reactors. The operating conditions of the batch reactors were adapted from a published paper.14 In brief, the two reactors were aerated with 0.2-μm filtered air at a flow rate of 100 mL/min and operated at room temperature. 100 mL of well-mixed reactor content was replaced with fresh E2- or E1-saturated NMS medium every 7 days. After 78 days of enrichment, estrogen degrading bacteria were isolated using R2A plates amended with E2 or E1. Five isolates were screened for their capabilities of degrading estrogens (Supporting Information (SI)). The strain Stenotrophomonas maltophilia ZL1 was selected for further analyses due to its ability to degrade both E2 and E1. DNA Extraction, Sequencing and Phylogenetic Tree Construction. Total DNA was extracted from all five bacterial isolates using a phenol-chloroform method 32 and its quality was examined using 2% agarose gel electrophoresis. The 16S rRNA gene was amplified using PCR primers 27F (5′AGRGTTTGATCMTGGCTCAG-3′) and 1492R (5′GGTTACCTTGTTACGACTT-3′) on a Mastercycler ep realplex (Eppendorf International, Hamburg, Germany).33 TaKaRa Ex Taq kit was used for PCR amplification (TAKARA Bio Inc., Shiga, Japan). A 25-μL PCR reaction volume contained: 50 ng of DNA template, 1 pmol/μL of each primer, 0.1 μL high fidelity Ex-Taq polymerase (5 units/μL), 0.2 mM each dNTP, 2.5 μL 10 × MgCl2-free buffer, 2 mM MgCl2 and 5948

dx.doi.org/10.1021/es300273k | Environ. Sci. Technol. 2012, 46, 5947−5955


■

was loaded onto the first dimension SCX column and was eluted using a salt gradient of 0−600 mM. Selected fractions based on the UV absorbance of the eluted peptides were subjected to second dimension analysis. The second dimension separation incorporated an online sample preconcentration and desalting using a monolithic C18 trap column (Pep Map, 300 μm i.d. × 5 mm, 5 μm, 100 Å, Dionex). Desalted peptides were then eluted and separated on a C18 Pep Map column (75 μm i.d. × 15 cm, 3 μm, 100 Å) by applying an acetonitrile (ACN) gradient (ACN plus 0.1% formic acid, 90 min gradient) at a flow rate of 300 nL/min and were introduced into the mass spectrometer using the nanospray source. The LCQ Fleet mass spectrometer was operated in data dependent mode with four MS/MS spectra for every full scan, five microscans averaged for full scans and MS/MS scans, 3 m/z isolation width for MS/MS isolations and 35% collision energy for collision-induced dissociation.37 Protein Functional Category Classification and Pathway Mapping. Identified proteins were classified into functional groups according to annotation based on Clusters of Orthologous Groups (COG) using NCBI COGnitor.38,39 Functional category distribution of proteins was calculated by dividing the number of proteins that belong to a functional category by the total number of identified proteins in a sample. All identified protein sequences were also mapped into metabolic pathways using the Automatic Annotation Server on Kyoto Encyclopedia of Genes and Genomes (KEGG).40 Protein Identification. All MS/MS spectra were searched against the Stenotrophomonas maltophilia R551 genome using MASCOT (Version 2.2 Matrix Science, UK) with the following parameters: enzyme (trypsin); missed cleavages (2); mass (monoisotropic); fixed modification (carbamidomethyl (C)); peptide tolerance (1.5 Da); MS/MS fragment ion tolerance (1 Da). Probability assessment of peptide assignments and protein identifications were accomplished using Scaffold (Proteome Software Inc., Portland, OR). Only peptides with ≥90% probability were considered in this study. Criteria for protein identification included detection of at least two unique peptides in a protein and a protein probability score of ≥90%. Relative quantitation of the proteins was developed using a label-free method of spectral counting with normalized spectral counts.41 The number of identified proteins in each of the four samples ranged between 193 and 263. Gas Chromatography (GC)-Mass Spectrometry (MS) for Estrogen Quantification. E2 and its biodegradation intermediates, E1 and estriol (E3), were quantified using GCMS following solid phase extraction (SPE) and derivatization.42 Briefly, before being concentrated on SPE cartridges (C-18, Waters, USA), water samples were spiked with 20 μL of 10 mg/ L 17β-estradiol-16, 16, 17-d3 and 20 μL of 10 mg/L phenanthrene as the internal standard and surrogate, respectively. Adsorbed E2 and its biodegradation intermediates were eluted from cartridges using ethyl acetate. Eluted samples were blown dry, reconstituted, and derivatized using 50 μL dimethyl formamide and 50 μL BSTFA+1% TMCS at 75 °C for 30 min. Derivatized samples were transferred to GC vials with 250 μL insert and analyzed within 36 h. The overall recovery rates of E2 and E1 were 70−92% and 76−88%, respectively, and were used in calculating the estrogen concentrations in the original samples. The method detection limits (MDL) for E1, E2, E3 were determined to be 14.4 ng/L, 5.8 ng/L, and 11.4 ng/L, respectively, by following a standard procedure.43

Article

RESULTS Selection of Isolated E2 Degrading Bacterium for Proteomic Analyses. Five E2 degrading bacteria were isolated from the enrichment experiment. Taxonomic analyses based on the 16S rRNA gene revealed that the five isolates belonged to the genera Stenotrophomonas (strain ZL1), Alcaligenes (ZL2), Microbacterium (ZL3), and Rhodococcus (ZL4 and ZL5) (SI Figure S2). Criteria used to select a bacterial strain for proteomic analyses were (1) capability of estrogen degradation, (2) availability of genome information, and (3) availability of annotated metabolism pathways. Preliminary degradation experiments using end-point measurements were conducted to assess isolates′ abilities to degrade E2 and E1 (SI). Results showed that among the five isolates, Stenotrophomonas strain ZL1 and Rhodococcus strains ZL4 and ZL5 could degrade both E2 and E1. Strain ZL1 shared a >99% similarity in the 16S rRNA gene with Stenotrophomonas maltophilia R551, whose complete genome has been sequenced.44 In comparison, strains ZL4 and ZL5 did not have a closely related Rhodococcus strain whose genome information was available. In addition, the metabolism pathways of S. maltophilia R551 had been annotated using the KEGG Orthology system and publically available on KEGG. Therefore, S. maltophilia strain ZL1 was selected for further analyses in this study. E2 Degradation by S. maltophilia Strain ZL1. The E2 degradation experiment by strain ZL1 showed three distinctive phases (Figure 1). In phase 1 (0−16 h), E2 concentration

Figure 1. Concentration profiles of E2 and E1 (top) and optical density at 600 nm (OD600, bottom) in the degradation experiment of strain ZL1. Error bars represent the ranges of measurements from duplicate experimental sets. Control 1 was an E2-saturated NMS medium containing no cells, and Control 2 was an E2-saturated NMS medium containing autoclaved strain ZL1.

dropped from 3.3 mg/L to 0.02 mg/L, while E1 concentration increased to about 3.5 mg/L, suggesting that E2 was converted to E1. Optical density reading at 600 nm (OD600) indicated that there was no significant cell growth in phase 1. In phase 2 (16−36 h), E2 concentration remained low, while E1 concentration dropped to 1.7 mg/L. OD600 reading increased 5949



Article

Catabolic and Anabolic Pathways Affected by E2/E1 Degradation. Glycolysis, tricarboxylic acid (TCA) cycle, oxidative phosphorylation, amino acid metabolism, and lipid metabolism were selected for detailed analyses because of their importance in cell metabolisms (Table 1). The time course covered by the four time points (i.e., 0, 4, 16, and 36 h) was divided into two phases (i.e., phases 1 and 2, as marked in Figure 1). To determine if a protein was up- or down regulated, hour 0 and 16 were chosen as the reference time points for phase 1 and 2, respectively. A protein was considered upregulated when the expression level increased by ≥100%, and was considered down-regulated when the expression level decreased by ≥50%.45−47 The connections of these five pathways (i.e., glycolysis, TCA cycle, oxidative phosphorylation, protein biosynthesis, and lipid biosynthesis) are illustrated in Figure 3. Glycolysis. During phase 1 the expression level of pyruvate kinase (pyk) decreased considerably, suggesting decreased glycolysis activities (Table 1 and Figure 3). This trend was deemed reasonable given that at 0 h the strain ZL1 was transferred from a R2A medium, which contained glucose and soluble starch, to an NMS medium that contained spiked E2 as the sole energy and carbon source. During phase 2, pyruvate kinase and pyruvate dehydrogenase were up-regulated, although the increase in expression of the former enzyme was not significant (Table 1). The enzyme phosphoglycerate kinase decreased significantly in this phase. Oxidative Phosphorylation and TCA Cycle. ATP synthase, an integral membrane protein complex, derives energy from proton motive force and transfers the energy to adenosine diphosphate (ADP) molecules to form adenosine triphosphate (ATP) molecules. During phase 1, all three ATP synthase subunits were first down-regulated and then up-regulated. Between 4 and 16 h, the expressions of the alpha and beta subunits were up-regulated by 3.0 and 2.6 folds, respectively, and the epsilon subunit changed from nondetectable to detectable. Notably, the ATP synthase exhibited a similar expression pattern to that of the malate dehydrogenase in the TAC cycle (Table 1 and Figure 3). This is likely due to the fact that the NADPH molecules generated by malate dehydrogenase could be used to feed the electron transport chain and generate proton motive force to feed ATP synthase (Figure 3). During phase 2 (16−36 h), the expression levels of the three subunits of ATP synthase appeared to vary differently, however, the generally high levels of spectral counts matching ATP synthase suggest high energy demands of S. maltophilia ZL1 during E1 degradation and cell growth. Amino Acid Metabolism. Amino acid metabolism is important to cell vitality and growth. Aspartate-semialdehyde dehydrogenase, an enzyme catalyzing an initial step in synthesizing amino acids lysine, methionine, leucine and isoleucine from aspartate, was up-regulated by 6 fold at the end of the phase 1 and further increased 1.8 fold at the end of phase 2. In addition, aromatic-amino-acid transaminase, a protein capable of converting 4-hydroxyphenylpyruvate to tyrosine, was up-regulated throughout the two phases, although the increase in phase 2 was not significant. Given that biomass growth occurred in phase 2, it is not surprising that enzymes related to amino acid biosynthesis were up-regulated (Table 1 and Figure 3). Lipid Metabolism. 3-oxoacyl-[acyl-carrier protein] reductase (BKR) encoded by the gene fabG was down-regulated by 6 folds during phase 1 and was then up-regulated by 8 fold during

by approximately 0.2 unit, suggesting slow growth of S. maltophilia under the experimental condition tested. In phase 3 (36−104 h), both E2 and E1 concentrations remained stable, while the OD600 reading dropped about 0.1 unit toward the end of the phase. At the end of the experiment, E2 was nearly 100% degraded and about 50% of the E1 converted from E2 was further degraded by strain ZL1. The no-cell control (Control 1) and the control with autoclaved ZL1 (Control 2) showed no evident change in E2 concentration or any E1 accumulation. Based on the E2/E1 and OD600 profiles, biomass samples were collected at 0, 4, 16, and 36 h for proteomic analyses. Global Functional Distribution of S. maltophilia ZL1 proteome during E2 degradation. The proteins identified in the S. maltophilia ZL1 samples from the four time points were classified into 19 functional categories using COGnitor (Figure 2). Proteins in three functional categories were more

Figure 2. Functional category distribution of proteins expressed in strain ZL1 during E2 biodegradation. COG categories are labeled as follows: C: energy production and conversion; D: cell division and chromosome partitioning; E: amino acid transport and metabolism; F: nucleotide transport and metabolism; G: carbohydrate transport and metabolism; H: coenzyme metabolism; I: lipid metabolism; J: translation, ribosomal structure and biogenesis, K: transcription; L: DNA replication, recombination and repair; M: cell envelope biogenesis, outer membrane; N: cell motility and secretion; O: post translational modification, protein turnover, chaperones; P: inorganic ion transport and metabolism; Q: secondary metabolites biosynthesis, transport and catabolism; R: general function prediction only; S: function unknown; T: signal transduction mechanisms; and None: no related COGs.

abundant than those in other categories: energy production and conversion (C), translation, ribosomal structure and biogenesis (J), and post translational modification, protein turnover and chaperones (O). Although the number of proteins in category R was also high, they are defined as proteins with only predicted general functions. The functional distribution of the identified proteins did not show evident temporal changes during the course of E2 degradation. The number of proteins in the categories C and J showed a general trend of decrease during the time period tested. The proteins in the categories of carbohydrate transport and metabolism (G) and DNA replication, recombination and repair (L) became more abundant after strain ZL1 was exposed to E2. Notably, the number of proteins in the functional category of secondary metabolites biosynthesis, transport and catabolism (Q) decreased ∼85% between 16 and 36 h. 5950



Article

Table 1. Differential Expression of Proteins in Selected Metabolic Processesa

a

Proteins with normalized MS spectral counts 50% lower than the reference time are highlighted in light grey and proteins with normalized spectral counts 100% higher are highlighted in dark grey. Hour 0 and 16 are the reference time points for Phases 1 and 2, respectively.

■

DISCUSSION The E2 degradation pattern of S. maltophilia ZL1 was similar to that of an Aminobacter strain named KC7.14 Compared to KC7, ZL1 could convert E2 to E1 at a faster pace and show more pronounced biomass growth when estrogen was the sole carbon/energy source. In the E2-NMS medium, the growth of S. maltophilia ZL1 experienced an exponential growth phase between 16 and 36 h (Figure 1). During the same time period, aspartate-semialdehyde dehydrogenase (asd), which catalyzes one of initial steps in amino acid biosynthesis,52 was upregulated, and adenylosuccinate synthase (ADSS, encoded by purA) and adenylosuccinate lyase (ADSL, encoded by purB), which connect aspartate to the TCA cycle by incorporating

phase 2. Lipid biosynthesis typically involves four recurring steps, each of which adds two carbons to fatty acids per cycle. BKR is an enzyme involved in the fourth recurring step of lipid biosynthesis, and responsible for reducing (3R)-3-hydroxyacyl[acyl-carrier-protein] to (3R)-3-hydroxybutanoyl-[acyl-carrierprotein], two lipid derivatives with different numbers of carbon.48 In addition, glutathione peroxidase, an enzyme capable of reducing lipid hydroperoxides and free hydrogen peroxide (H2O2) to lipid alcohol and water,49,50 was gradually up-regulated during the biodegradation experiment. It is worth noting that the up-regulation of glutathione peroxidase often occurs simultaneously with elevated electron transport chain activities, a process that generates hydrogen peroxide.51 5951



Article

contained a keto group on the D ring, one study proposed that the ring cleavage of E1 by sewage bacteria was initiated at that ring.53 Another study used an enriched AOB culture and suggested that the aromatic A ring on EE2 was more vulnerable because the electron density associated with the A ring was significantly higher than the other rings.21 A third study used a Sphingomonas culture and suggested that E2 be converted to intermediates 4-hydroxyestrone (4-OH-E1) and 4-hydroxyestradiol (4-OH-E2), or intermediates keto-estradiol (keto-E2) and keto-estrone (keto-E1), before ring cleavage happened.54 The same study also detected intermediates from ring cleavage, such as 3-(4-hydroxyphenyl)-2-hydroxyprop-2-enoic acid (compound VI) and 4-hydroxyphenylpyruvate (compound X). The former can be isomerized to the latter by phenylpyruvate tautomerase, an enzyme encoded in the S. maltophilia genome. Furthermore, 4-hydroxyphenylpyruvate can be converted to an amino acid, tyrosine, by aromatic-amino-acid transaminase, which was up-regulated throughout the degradation experiment in this study (Table 1). Taken together, we propose that E2 be converted to E1 by S. maltophilia ZL1, and E1 and its degradation intermediates be utilized in aromatic amino acid biosynthesis (Figure 4). This proposed pathway is partially supported by the results from a study using radiochromatograms, which showed radio-labeled carbon on the estradiol structure in EE2 was incorporated into the biomass.55 Although Kurisu and co-workers proposed that E2 could be directly converted to keto-E1,54 it is also possible that E2 could be converted to E1 first and then to keto-E1 (personal communication with Dr. Kurisu, University of Tokyo). Finally, it is worth mentioning that although the results of this study suggest that S. maltophilia initiated E2 cleavage on the D ring and that tyrosine pathway was involved in the E2/E1 degradation, it is possible that S. maltophilia may use other degradation mechanisms, including meta-cleavage at the A ring, under other experimental conditions. Although this is the first study to report that S. maltophilia degrades natural estrogens, the species has been reported to be capable of degrading aromatic hydrocarbons. S. maltophilia strain KB2 isolated from activated sludge could degrade monocyclic aromatic hydrocarbons, such as benzoate, catechol, 4-hydroxybenzoic acid, protocatechuic acid and vanillic acid.56 Other S. maltophilia strains can degrade polycyclic aromatic hydrocarbons (PAHs), such as benzo[a]pyrene, dibenz[a,h]anthracene, and coronene.57,58 Dioxygenases are believed to be involved in aromatic biodegradation by S. maltophilia, and different dioxygenases may be induced by different growth substrates. For example, catechol 1,2-dioxygenase was induced when benzoate and catechol were carbon sources, whereas protocatechuate 3,4-dioxygenase was induced after incubation with 4-hydroxybenoic acid, vanillic acid and protocatechuic acid.56 In this study, neither catechol 1,2-dioxygenase nor protocatechuate 3,4-dioxygenase were detected in the proteomic analyses. As previously mentioned, it is possible that S. maltophilia ZL1 initiated E2 cleavage primarily though the D ring. Hence, dioxygenases, which would initiate E2 cleavage on the aromatic A ring, were not expressed at substantial levels. The proteomic approach used in this study is not capable of detecting proteins at very low abundance,59,60 such as those that were not involved in a primary degradation pathway. It is anticipated that E2 degradation by S. maltophilia would be affected by the presence of other substrates and other microbial species under real environmental conditions. In this study, we did not detect dioxygenases in S. maltophilia

Figure 3. Connections among glycolysis, oxidative phosphorylation, fatty acid biosynthesis, protein biosynthesis, and TCA during 17βestradiol biodegradation, as well as proteins involved and their expression levels. Y-axies in the column plots are normalized spectral counts of selected protein. fbaB, fructose-bisphosphate aldolase; pgk, phosphoglycerate kinase; pph, ; pyk phosphoglycerate kinase; BKR, 3oxoacyl-[acyl-carrier-protein] reductase; atpD, F1F0 ATP synthase subunit beta; mdh, malate dehydrogenase; Cs, citrate synthase; aco, aconitase; Icdh, isocitrate dehydrogenase; akgd, alpha ketoglutarate dehydrogenase; sucoas, succinyl-CoA synthetase; sudh, succinyl-CoA dehydrogenase; fum, fumarase; ADSL, adenylosuccinate lyase; ADSS, adenylosuccinate synthase; AMPD, adenosine monophosphate deaminase; lysC, aspartate kinase; asd, aspartate-semialdehyde dehydrogenase. Solid arrows indicate reactions catalyzed by enzymes detected in the S. maltophilia proteomic, while dashed arrows indicate reactions catalyzed by enzymes coded in the genome but not detected in the proteome.

aspartate to adenylosuccinate, were down-regulated (Table 1 and Figure 3). The up-regulation of asd and down-regulation of ADSS and ADSL suggest that more aspartate was used for protein biosynthesis during cell exponential growth. Also, it is interesting to notice that with only a few exceptions, the majority of identified proteins were expressed throughout the degradation experiment (SI Figure S3). The overlapping of the majority of the proteins identified at the four time points tested suggests that few new proteins were induced after S. maltophilia ZL1 was exposed to E2 or when it degraded E2 and E1. Although microbial degradation of E1 has been documented, the biotransformation pathway of E1 is not well studied.13,14 Based on the detection of a putative intermediate that 5952



Article

Figure 4. Proposed biotransformation pathway of 17β-estradiol by S. maltophilia ZL1. The solid arrows represent reactions catalyzed by enzymes detected in the genome (gray) or proteome (black) of S. maltophilia. Compound numbers (II, VI, and X in square parentheses) and reactions connected with open arrows were adopted from Kurisu et al 2010.

■

ACKNOWLEDGMENTS This work was financially supported by the UNL startup fund to X.L. We thank the technical supports from Dan Snow and David Cassada at the UNL Water Sciences Laboratory on GCMS analyses.

proteome during E2/E1 degradation. However, it is possible that the presence of other substrates in the environment may trigger the expression of dioxygenases in S. maltophilia. In that case, a different degradation pathway may prevail. Such a phenomenon is common in environmental degradation. For example, the presence of tetrahydrofuran triggered the expression of monooxygenase which subsequently carried out 1,4-dioxane degradation.35 In addition, amino acids such as tyrosine are likely to be present in wastewater. The presence of environmental tyrosine could affect the E2/E1 biodegradation pathway that involves tyrosine formation, as feedback inhibition of enzyme activities may result from the presence of this downstream product.61 Finally, in a parallel study, we noticed that various nitrogen sources could affect the competition between S. maltophilia and other heterotrophs in a mixed microbial community.62

■

■

ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in the text. This material is available free of charge via the Internet at http://pubs.acs.org.

■

REFERENCES

(1) Benotti, M. J.; Trenholm, R. A.; Vanderford, B. J.; Holady, J. C.; Stanford, B. D.; Snyder, S. A. Pharmaceuticals and endocrine disrupting compounds in U.S. drinking water. Environ. Sci. Technol. 2009, 43 (3), 597−603. (2) Kim, S. D.; Cho, J.; Kim, I. S.; Vanderford, B. J.; Snyder, S. A. Occurrence and removal of pharmaceuticals and endocrine disruptors in South Korean surface, drinking, and waste waters. Water Res. 2007, 41 (5), 1013−1021. (3) Loos, R. Pan-European survey on the occurance of selected polar organic persistent pollutants in ground water. Water Res. 2010, 44, 4115. (4) Andersen, H.; Siegrist, H.; Halling-Sorensen, B.; Ternes, T. A. Fate of estrogens in a municipal sewage treatment plant. Environ. Sci. Technol. 2003, 37 (18), 4021−4026. (5) Baronti, C.; Curini, R.; D’Ascenzo, G.; Di Corcia, A.; Gentili, A.; Samperi, R. Monitoring natural and synthetic estrogens at activated sludge sewage treatment plants and in a receiving river water. Environ. Sci. Technol. 2000, 34 (24), 5059−5066. (6) Joss, A.; Andersen, H.; Ternes, T.; Richle, P. R.; Siegrist, H. Removal of estrogens in municipal wastewater treatment under aerobic and anaerobic conditions: Consequences for plant optimization. Environ. Sci. Technol. 2004, 38 (11), 3047−3055. (7) Khanal, S. K.; Xie, B.; Thompson, M. L.; Sung, S. W.; Ong, S. K.; Van Leeuwen, J. Fate, transport, and biodegradation of natural estrogens in the environment and engineered systems. Environ. Sci. Technol. 2006, 40 (21), 6537−6546.

AUTHOR INFORMATION

Corresponding Author

*Phone: +01-402-472-6042; fax: +1-402-472-8934; e-mail: [email protected]. Notes

The authors declare no competing financial interest. 5953



Article

(8) Raman, D. R.; Williams, E. L.; Layton, A. C.; Burns, R. T.; Easter, J. P.; Daugherty, A. S.; Mullen, M. D.; Sayler, G. S. Estrogen content of dairy and swine wastes. Environ. Sci. Technol. 2004, 38 (13), 3567− 3573. (9) Huang, C. H.; Sedlak, D. L. Analysis of estrogenic hormones in municipal wastewater effluent and surface water using enzyme-linked immunosorbent assay and gas chromatography/tandem mass spectrometry. Environ. Toxicol. Chem. 2001, 20 (1), 133−139. (10) Purdom, C. E. H., P.A.; Bye, V. J.; Eno, N. C.; Tyler, C. R.; Sumpter, J. P. Estrogenic effects of effluents from sewage treatment works. Chem Ecol 1994, 8, 275−285. (11) Imai, S.; Koyama, J.; Fujii, K. Effects of 17 beta-estradiol on the reproduction of Java-medaka (Oryzias javanicus), a new test fish species. Mar. Pollut. Bull. 2005, 51 (8−12), 708−714. (12) EPA, U. S. 2009. Drinking Water Contaminant Candidate List 3. http://www.epa.gov/fedrgstr/EPA-WATER/2009/October/Day08/w24287.htm. (13) Weber, S.; Leuschner, P.; Kampfer, P.; Dott, W.; Hollender, J. Degradation of estradiol and ethinyl estradiol by activated sludge and by a defined mixed culture. Appl. Microbiol. Biotechnol. 2005, 67 (1), 106−112. (14) Yu, C. P.; Roh, H.; Chu, K. H. 17 beta-estradiol-degrading bacteria isolated from activated sludge. Environ. Sci. Technol. 2007, 41 (2), 486−492. (15) Pauwels, B.; Wille, K.; Noppe, H.; De Brabander, H.; van de Wiele, T.; Verstraete, W.; Boon, N. 17 alpha-ethinylestradiol cometabolism by bacteria degrading estrone, 17 beta-estradiol and estriol. Biodegradation 2008, 19 (5), 683−693. (16) Iasur-Kruh, L.; Hadar, Y.; Minz, D. Isolation and bioaugmentation of an estradiol-degrading bacterium and its integration into a mature biofilm. Appl. Environ. Microbiol. 2011, 77 (11), 3734−3740. (17) Shi, J.; Fujisawa, S.; Nakai, S.; Hosomi, M. Biodegradation of natural and synthetic estrogens by nitrifying activated sludge and ammonia-oxidizing bacterium Nitrosomonas europaea. Water Res. 2004, 38 (9), 2323−2330. (18) Jiang, L. Y.; Yang, J.; Chen, J. M. Isolation and characteristics of 17 beta-estradiol-degrading Bacillus spp. strains from activated sludge. Biodegradation 2010, 21 (5), 729−736. (19) Iasur-Kruh, L.; Hadar, Y.; Minz, D. Estradiol-degrading bacterium--isolation, bioaugmentation and integration into mature biofilm. Appl. Environ. Microbiol. 2011, AEM.00691−11. (20) Khunjar, W. O.; Mackintosh, S. A.; Skotnicka-Pitak, J.; Baik, S.; Aga, D. S.; Love, N. G. Elucidating the relative roles of ammonia oxidizing and heterotrophic bacteria during the biotransformation of 17 alpha-ethinylestradiol and trimethoprim. Environ. Sci. Technol. 2011, 45 (8), 3605−3612. (21) Yi, T.; Harper, W. F. The link between nitrification and biotransformation of 17 alpha-ethinylestradiol. Environ. Sci. Technol. 2007, 41 (12), 4311−4316. (22) Schwarzenbach, R. G., P.; Imboden, D., Environmental Organic Chemistry, 2nd ed; John Wiley & Sons: Hoboken, NJ, 2003. (23) Coombe, R. G.; Tsong, Y. Y.; Hamilton, P. B.; Sih, C. J. Mechanisms of steroid oxidation by microorganisms .X. Oxidative cleavage of estrone. J. Biol. Chem. 1966, 241 (7), 1587−&. (24) Ong, S. E.; Mann, M. Mass spectrometry-based proteomics turns quantitative. Nat. Chem. Biol. 2005, 1 (5), 252−262. (25) Aebersold, R.; Mann, M. Mass spectrometry-based proteomics. Nature 2003, 422 (6928), 198−207. (26) Schneider, T.; Riedel, K. Environmental proteomics: Analysis of structure and function of microbial communities. Proteomics 2010, 10 (4), 785−798. (27) Wilmes, P.; Andersson, A. F.; Lefsrud, M. G.; Wexler, M.; Shah, M.; Zhang, B.; Hettich, R. L.; Bond, P. L.; VerBerkmoes, N. C.; Banfield, J. F. Community proteogenomics highlights microbial strainvariant protein expression within activated sludge performing enhanced biological phosphorus removal. ISME J. 2008, 2 (8), 853− 864. (28) Callister, S. J.; Wilkins, M. J.; Nicora, C. D.; Williams, K. H.; Banfield, J. F.; VerBerkmoes, N. C.; Hettich, R. L.; N’Guessan, L.;

Mouser, P. J.; Elifantz, H.; Smith, R. D.; Loyley, D. R.; Lipton, M. S.; Long, P. E. Analysis of biostimulated microbial communities from two field experiments reveals temporal and spatial differences in proteome profiles. Environ. Sci. Technol. 2010, 44 (23), 8897−8903. (29) Morris, R. M.; Fung, J. M.; Rahm, B. G.; Zhang, S.; Freedman, D. L.; Zinder, S. H.; Richardson, R. E. Comparative proteomics of Dehalococcoides spp. reveals strain-specific peptides associated with activity. Appl. Environ. Microbiol. 2007, 73 (1), 320−326. (30) Chuang, A. S.; Jin, Y. O.; Schmidt, L. S.; Li, Y. L.; Fogel, S.; Smoler, D.; Mattes, T. E. Proteomic analysis of ethene-enriched groundwater microcosms from a vinyl chloride-contaminated site. Environ. Sci. Technol. 2010, 44 (5), 1594−1601. (31) Chu, K. H.; Alvarez-Cohen, L. Trichloroethylene degradation by methane-oxidizing cultures grown with various nitrogen sources. Water Environ. Res 1996, 68 (1), 76−82. (32) Chomczynski, P.; Sacchi, N. Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction. Anal. Biochem. 1987, 162 (1), 156−159. (33) Xia, S. Q.; Duan, L. A.; Song, Y. H.; Li, J. X.; Piceno, Y. M.; Andersen, G. L.; Alvarez-Cohen, L.; Moreno-Andrade, I.; Huang, C. L.; Hermanowicz, S. W. Bacterial community structure in geographically distributed biological wastewater treatment reactors. Environ. Sci. Technol. 2010, 44 (19), 7391−7396. (34) Li, X.; Upadhyaya, G.; Yuen, W.; Brown, J.; Morgenroth, E.; Raskin, L. Changes in the structure and function of microbial communities in drinking water treatment bioreactors upon addition of phosphorus. Appl. Environ. Microbiol. 2010, 76 (22), 7473−7481. (35) Mahendra, S.; Alvarez-Cohen, L. Kinetics of 1,4-dioxane biodegradation by monooxygenase-expressing bacteria. Environ. Sci. Technol. 2006, 40 (17), 5435−5442. (36) Nandakumar, R.; Santo, C. E.; Madayiputhiya, N.; Grass, G. Quantitative proteomic profiling of the Escherichia coli response to metallic copper surfaces. Biometals 2011, 24 (3), 429−444. (37) Zhu, Y. F.; Nandakumar, R.; Sadykov, M. R.; Madayiputhiya, N.; Luong, T. T.; Gaupp, R.; Lee, C. Y.; Somerville, G. A. RpiR homologues may link Staphylococcus aureus RNAIII synthesis and pentose phosphate pathway regulation. J. Bacteriol. 2011, 193 (22), 6187−6196. (38) Tatusov, R. L.; Natale, D. A.; Garkavtsev, I. V.; Tatusova, T. A.; Shankavaram, U. T.; Rao, B. S.; Kiryutin, B.; Galperin, M. Y.; Fedorova, N. D.; Koonin, E. V. The COG database: New developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Res. 2001, 29 (1), 22−28. (39) Tatusov, R. L.; Galperin, M. Y.; Natale, D. A.; Koonin, E. V. The COG database: A tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000, 28 (1), 33−36. (40) Moriya, Y.; Itoh, M.; Okuda, S.; Yoshizawa, A. C.; Kanehisa, M. KAAS: An automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007, 35, W182−W185. (41) Liu, H. B.; Sadygov, R. G.; Yates, J. R. A model for random sampling and estimation of relative protein abundance in shotgun proteomics. Anal. Chem. 2004, 76 (14), 4193−4201. (42) Shareef, A.; Angove, M. J.; Wells, J. D. Optimization of silylation using N-methyl-N-(trimethylsilyl)-trifluoroacetamide, N,O-bis-(trimethyl.silyl)-trifluoroacetamide and N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide for the determination of the estrogens estrone and 17 alpha-ethinylestradiol by gas chromatography-mass spectrometry. J. Chromatogr., A 2006, 1108 (1), 121−128. (43) Definition and Procedure for the Determination of the Method Detection Limit, Revision 1.11, Code of Federal Regulations, 40 CFP Part 136; U.S. Environmental Protection Agency, 1984; p 554. (44) Johnson, M.; Zaretskaya, I.; Raytselis, Y.; Merezhuk, Y.; McGinnis, S.; Madden, T. L. NCBIBLAST: a better web interface. Nucleic Acids Res. 2008, 36, W5−W9. (45) Kashyap, M. K.; Harsha, H. C.; Renuse, S.; Pawar, H.; Sahasrabuddhe, N. A.; Kim, M. S.; Marimuthu, A.; Keerthikumar, S.; Muthusamy, B.; Kandasamy, K.; Subbannayya, Y.; Prasad, T. S. K.; Mahmood, R.; Chaerkady, R.; Meltzer, S. J.; Kumar, R. V.; Rustgi, A. K.; Pandey, A. SILAC-based quantitative proteomic approach to 5954



Article

identify potential biomarkers from the esophageal squamous cell carcinoma secretome. Cancer Biol. Ther. 2010, 10 (8), 796−810. (46) Zhang, B.; VerBerkmoes, N. C.; Langston, M. A.; Uberbacher, E.; Hettich, R. L.; Samatova, N. F. Detecting differential and correlated protein expression in label-free shotgun proteomics. J. Proteome Res. 2006, 5 (11), 2909−2918. (47) Karp, N. A.; Lilley, K. S. Design and analysis issues in quantitative proteomics studies. Proteomics 2007, 7 (Suppl 1), 42−50. (48) Magnuson, K.; Jackowski, S.; Rock, C. O.; Cronan, J. E., Jr Regulation of fatty acid biosynthesis in Escherichia coli. Microbiol. Mo.l Biol. Rev. 1993, 57 (3), 522−542. (49) Mills, G. C. Hemoglobin catabolism. J. Biol. Chem. 1957, 229 (1), 189−197. (50) Margis, R.; Dunand, C.; Teixeira, F. K.; Margis-Pinheiro, M. Glutathione peroxidase familyAn evolutionary overview. FEBS J. 2008, 275 (15), 3959−3970. (51) González-Flecha, B.; Demple, B. Metabolic sources of hydrogen peroxide in aerobically growing Escherichia coli. J. Biol. Chem. 1995, 270 (23), 13681−13687. (52) Cox, R. J.; Gibson, J. S.; Hadfield, A. T. Design, synthesis and analysis of inhibitors of bacterial aspartate semialdehyde dehydrogenase. Chembiochem 2005, 6 (12), 2255−2260. (53) Lee, H. B.; Liu, D. Degradation of 17 beta-estradiol and its metabolites by sewage bacteria. Water, Air, Soil Pollut. 2002, 134 (1− 4), 353−368. (54) Kurisu, F.; Ogura, M.; Saitoh, S.; Yamazoe, A.; Yagi, O. Degradation of natural estrogen and identification of the metabolites produced by soil isolates of Rhodococcus sp and Sphingomonas sp. J Biosci, Bioeng, 2010, 109 (6), 576−582. (55) Yi, T.; Mackintosh, S.; Aga, D. S.; Harper, W. F., Jr Exploring 17[alpha]-ethinylestradiol removal, mineralization, and bioincorporation in engineered bioreactors. Water Res. 2011, 45 (3), 1369−1377. (56) Urszula, G.; Izabela, G.; Danuta, W.; Sylwia, L. Isolation and characterization of a novel strain of stenotrophomonas maltophilia possessing various dioxygenases for monocyclic hydrocarbon degradation. Braz. J. Microbiol. 2009, 40 (2), 285−291. (57) Juhasz, A. L.; Stanley, G. A.; Britz, M. L. Microbial degradation and detoxification of high molecular weight polycyclic aromatic hydrocarbons by Stenotrophomonas maltophilia strain VUN 10,003. Lett. Appl. Microbiol. 2000, 30 (5), 396−401. (58) Boonchan, S.; Britz, M. L.; Stanley, G. A. Degradation and mineralization of high-molecular-weight polycyclic aromatic hydrocarbons by defined fungal-bacterial cocultures. Appl. Environ. Microbiol. 2000, 66 (3), 1007−1019. (59) Garbis, S.; Lubec, G.; Fountoulakis, M. Limitations of current proteomics technologies. J. Chromatogr., A 2005, 1077 (1), 1−18. (60) Ray, S.; Reddy, P. J.; Jain, R.; Gollapalli, K.; Moiyadi, A.; Srivastava, S. Proteomic technologies for the identification of disease biomarkers in serum: Advances and challenges ahead. Proteomics 2011, 11 (11), 2139−2161. (61) Nelson, D. L.; Cox, M. M. Lehninger Principles of Biochemistry, 3rd ed.; Worth Publishers: New York, NY, 2000. (62) Li, Z.; Li, X., Bacterial community dynamics in a biologically active carbon (BAC) reactor treating 17beta-estradiol contaminated drinking water. In preparation.

5955


Proteomic Analysis of 17Î²-Estradiol Degradation ... - ACS Publications

Recommend Documents