Pharmaceuticals are very useful in treating human diseases but they are excreted to the environment sometimes in their original form or as byproducts of human metabolism. Pharmaceuticals and their metabolites have been proven by studies to be harmful to non-target ecological species and may be persistent in different water matrices. In this regard, there is an emergent need to eliminate these compounds to prevent their adverse effects on aquatic species. Biodegradation using white-rot fungi is a promising technology for the removal of recalcitrant compounds; however, products of fungal biodegradation can also be detrimental. In this novel study, we evaluated the ability of Phanerochaete chrysosporium to degrade amlodipine, an anti-hypertensive drug which was recently found in water systems. Analysis of amlodipine metabolites was done using quadrupole time-of-flight liquid chromatography mass spectrometry after the degradation set-up of 120 hours. Pharmaceutical degradation was seen using triple quadrupole liquid chromatography tandem mass spectrometry. Ninety-two significant metabolites (P-value ≤ 0.05) were significantly expressed after false discovery rate adjustment at a significance threshold of q = 0.05. Pyridine derivatives which were identified from samples became the basis of the proposed degradation pathway of amlodipine in this study.

INTRODUCTION

Pharmaceutical and personal care products (PPCPs) represent a wide group of chemicals used for human and veterinary medicine. These types of compounds are considered to be emerging pollutants due to their recalcitrant nature which may last for months to years (Ternes & Joss 2006; Kosjek et al. 2007). Pharmaceuticals (such as antibiotics and antipyretic drugs) are generally absorbed by humans or animals after intake and are then attacked by metabolic degradation processes. However, significant fractions of the original substances often are excreted in unmetabolized form or as active metabolites via urine or feces to be emitted into raw sewage, which may or may not be treated (Halling-Sørensen et al. 1998; Daughton & Ternes 1999). These pharmaceuticals are designed either to be highly active and interact with receptors in humans and animals or to be toxic for many infectious organisms, including bacteria, fungi, and parasites (Khetan & Collins 2007). Moreover, they can have adverse effects on non-target ecological species when released to the environment. Continuous releases and chronic exposure can result in subtle effects on aquatic species and could pose a risk to human health associated with consuming contaminated drinking water over a lifetime (Dorne et al. 2007). In this regard, effective elimination of these pharmaceuticals in the environment is essential. Currently, methods such as physical separation, a combination of biological, photochemical, and physical processes (Sedlak & Pinkston 2011), and advanced oxidation processes (Huber et al. 2005; Ternes et al. 2007) are being used in drinking water treatment plants in the United States, Switzerland, Germany, and other countries (Monteiro & Boxall 2010). Meanwhile, sorption onto sediments, biodegradation, abiotic or photo degradation, and dissipation in water sediment systems are the usual fate of pharmaceuticals in the environment (Lam et al. 2004; Löffler et al. 2005; Andreozzi et al. 2006; Jim et al. 2006). These days, biodegradation has been used to remove PPCPs from water systems and it has gained popularity because of its efficiency and cost effectiveness. Bioremediation utilizes the metabolic potential of microorganisms to clean up the environment (Watanabe 2001). Recently, the capability of white rot fungi (WRF) for biodegradation of xenobiotic and recalcitrant pollutants has generated a considerable research interest in the area of environmental microbiology (Asgher et al. 2008). In this study, we have carried out pioneering research on the degradation of an antihypertensive drug amlodipine using WRF, Phanerochaete chrysosporium. Amlodipine is a dihydropyridine calcium channel blocker used in treatment for hypertension and ischemic heart disease (Suchanova et al. 2008). This drug was used due to its detection in sewage treatment plants and surface water (Huerta-Fontela et al. 2011; Al-Odaini et al. 2013) and no studies have delved into its biodegradation to date according to the authors' knowledge. This study aims to view biodegradation of an anthropogenic compound in a different perspective through metabolomic analysis.

MATERIAL AND METHODS

Organisms and chemicals

Phanerochaete chrysosporium (KCTC 6147) was purchased from the Korean Collection for Type Cultures, Daejeon, Korea. The WRF was grown by inoculating 10 mm mycelial plugs to potato dextrose agar with 0.5% yeast extract plates and incubated at 30 °C for 7 days. Plates with mycelial growth were stored at 4 °C and used within 7 days for the degradation experiment. Commercially available 5 mg amlodipine orotate tablets (Dong-A Pharma, Hanoi, Vietnam) were pulverized and stored according to manufacturer's instructions.

Degradation set-up

Mycelial plugs (10 mm) of P. chrysosporium from agar plates were inoculated in 100 mL potato dextrose broth with 0.5% yeast extract and incubated at 30 °C with constant shaking (150 rpm) for 7 days. Mycelial pellets were harvested and washed five times with the degradation medium containing phosphate buffer supplemented with 2 g/100 mL glucose (energy source) to remove excess growth medium from the mycelia. The degradation experiment was carried out in baffled erlenmeyer flasks (250 mL) with 100 mL of the degradation medium, 10 mg/L amlodipine orotate, and washed mycelial pellets. The flask were incubated using the same conditions for growth of the fungi.

Five mL were taken from each flasks at 0, 24, 48, 72, and 120 hours, filtered using 0.45 μm syringe filters, and kept at −20 °C until analysis. The samples were analyzed within 3 days to prevent further degradation of metabolites.

Analysis of degradation products

The samples for quantitative degradation were filtered and injected into a triple quadrupole liquid chromatography tandem mass spectrometer (LC-MS/MS, Agilent Technologies, Santa Clara, CA, USA) and analyzed using a multiple reaction monitoring (MRM) technique specific for amlodipine. A C18 column (TARGA C18 5 μm 100 × 2.1 mm, Higgins Analyticals, Mountain View, CA, USA) was used with two mobile phases (0.1% formic acid in acetonitrile and the same quantity in water). For the qualitative analysis of metabolites, samples were pre-treated with acetonitrile (2:1) (Soltow et al. 2013) and then centrifuged at 16,000 × g for 10 minutes to remove proteins which may interfere with the sample analysis. Minimal extraction was done to avoid perturbation of the relative metabolite abundance (Park et al. 2012). Extracts were placed in a refrigerated auto sampler and 100 μL volumes were analyzed in duplicate with LC-MS platforms using the aforementioned C18 column. Data were collected by Q-TOF mass spectrometer (Agilent Technologies, Santa Clara, CA, USA) with m/z values ranging from 50 to 1,000 over 30 minutes with each sample analyzed in triplicate. Peak extraction and quantification of ion intensities were performed with the R package, adaptive processing of high-resolution LC/MS, which provides tables containing m/z values, retention time, and integrated ion intensity for each m/z feature (Yu et al. 2009).

Data analysis

The mass spectrometry generated thousands of m/z features from the samples which need to be processed to determine only the ones with significance. To do this, data were processed by multivariate statistical analysis and were log-transformed, median centered, and quantile normalized prior to statistical and bioinformatics analyses for better distribution. Linear model for microarray data (LIMMA) in Bioconductor was used to identify differentially expressed features at a significance threshold of q = 0.05 after false discovery rate (FDR) adjustment which is visualized in the Manhattan plot. The FDR adjustment was carried out to eliminate false positives which increases accuracy of the array of data. Two-way hierarchical clustering analysis (HCA) was performed to identify clusters of individuals associated with discriminating clusters of metabolites using the heatmap.2 function in the R package gplots (Bolker et al. 2010). Hierarchical clustering was performed using the built-in hclust() function in R that uses the complete-linkage method for clustering. The significant features were identified using the Metlin database (metlin.scripps.edu/index.php), an online metabolites database. Two positive adducts were considered, M + H and M + Na at 10 ppm level of confidence.

RESULTS AND DISCUSSION

Degradation of amlodipine

Currently, there is no recorded degradation of amlodipine by a biological agent. In this study, Phanerochaete chrysosporium was used for the degradation of amlodipine and was found to be a potential agent to efficiently degrade this compound. Triple quadrupole LC-MS/MS was used to verify whether degradation took place during the incubation period. Figure 1 shows the peak of amlodipine at 6.04 retention time from samples taken after 24 hours of pharmaceutical-organism interaction. On the third day of incubation, there were no peaks seen at the same retention time (Figure 1). The MRM technique is very specific for the masses of the parent and daughter ions at a certain fragmentation voltage. The absence of a peak using this method clearly suggests that the test compound was not found from the sample analyzed and that it has undergone degradation.

Figure 1

Triple quadrupole LC-MS/MS chromatogram of amlodipine from 24-hour (top) and 72-hour (bottom) samples.

Figure 1

Triple quadrupole LC-MS/MS chromatogram of amlodipine from 24-hour (top) and 72-hour (bottom) samples.

Qualitative analysis of metabolites using Q-TOF LC-MS

To prove the results from quantitative analysis of degradation, samples were analyzed using mass spectrometry which identifies masses of every compound from the range of 50–1,000 mass-to-charge ratios (m/z). After FDR adjustment of P-values of m/z data from Q-TOF, significant m/z values of each control and time-dependent pairs (e.g., 0 and 24, 0 and 48, etc.) were considered for a comprehensive analysis of metabolites in the samples. The total number of significant extracellular metabolites produced by Phanerochaete chrysosporium is expected to increase from 0 hours to the last day of incubation (120 hours) due to an increase in enzymatic activity of the organism. The ability to use amlodipine as a substrate for carbon and energy source leading to an increase in cellular processes might have taken place during the incubation period. Figure 2 shows the number of significant metabolites found after the 120-hour study duration. From an initial count of 128 significant metabolites for 0 and 24-hour baseline, it increased to 240 for the 0 and 120-hour point. This means that the organism is actively producing metabolites and possibly degrading amlodipine. Pair-matching of significant m/z values was also carried out to determine which metabolites can be found until the last day of the set-up as well as those found to be unique from their respective pairs. Forty-nine of the 128 metabolites were found to be present until the 120th hour. It can be said that the metabolites which were found during the initial point were metabolized further by the organism. Conversely, there were also metabolites seen to be different from those observed on the baseline. Of the 240 metabolites seen on the last day of the degradation set up, 191 metabolites were distinct. Lastly, an increasing pattern of distinct metabolites observed is directly proportional with increasing metabolite production as the day of incubation progresses.

Figure 2

Total number of significant metabolites of Phanerochaete chrysosporium in the presence of amlodipine in time-dependent analysis of the control (0 and 24) and of time-dependent points.

Figure 2

Total number of significant metabolites of Phanerochaete chrysosporium in the presence of amlodipine in time-dependent analysis of the control (0 and 24) and of time-dependent points.

Manhattan plot and HCA of significant metabolites

A statistical analysis of all m/z values using LIMMA package in R showed 92 significantly expressed metabolites. These metabolites are illustrated in a Manhattan plot of the negative log of the P-values seen as green dots above the FDR q value of 0.05 in Figure 3 (the full color version of this figure is available online at http://www.iwaponline.com/wst/toc.htm). The farther the green dots are from the blue-dotted line, the more significantly expressed they are compared to other metabolites in this representation. The rest of the metabolites with P-values > 0.05 were grouped based on their m/z and can be seen below the blue-dotted line. Conversely, an HCA of these significant features showed that the time-dependent points were clustered together and separated from the control (Figure 4). The colors in the HCA represent the z-score values of each metabolite signal. A positive z-score value (flesh) is a set of data above the mean while a negative z-score (blue) is below the mean. Since the concentration of some metabolites increase with day of incubation, it is expected that the colors will change from blue to a lighter color signifying an increase of concentration (or z-score).

Figure 3

Manhattan plot of the negative log of P-values of the 92 significant m/z features after FDR adjustment at significance threshold of q = 0.05. The full color version of this figure is available online at http://www.iwaponline.com/wst/toc.htm.

Figure 3

Manhattan plot of the negative log of P-values of the 92 significant m/z features after FDR adjustment at significance threshold of q = 0.05. The full color version of this figure is available online at http://www.iwaponline.com/wst/toc.htm.

Figure 4

HCA of the 92 significant m/z features of the control (red) and time-dependent samples (green). The full color version of this figure is available online at http://www.iwaponline.com/wst/toc.htm.

Figure 4

HCA of the 92 significant m/z features of the control (red) and time-dependent samples (green). The full color version of this figure is available online at http://www.iwaponline.com/wst/toc.htm.

Metabolites of amlodipine

The significantly expressed metabolite per time point was identified using Metlin and filtered at 10 ppm level of confidence for more accurate results. Among the many detected metabolites, a group of pyridine-containing compounds became the basis of our proposed pathway for amlodipine degradation by WRF (Figure 5). Pyridine is a basic heterocyclic organic compound with the chemical formula C5H5N. It is harmful if inhaled, swallowed or absorbed through the skin. Pyridine might also have minor neurotoxic, genotoxic, and clastogenic effects. Despite these harmful effects, pyridine is readily degraded by bacteria to ammonia and carbon dioxide (Sims et al. 1989). The compound amlodipine or 3-ethyl-5-methyl-2(2-aminoethoxymethyl)-4-(2-chlorophenyl)-6-methyl-1,4-dihydropyridine-3,5-dicarboxylate was metabolized to 3,5-pyridinedicarboxylic acid, 1,4-dihydro-2,6-dimethyl-4-(3-nitrophenyl)-carboxymethyl methyl ester. This degradation product was found from the sample collected after 24 hours of incubation of Phanerochaete chrysosporium with amlodipine. In addition, this metabolite was not found in any other time points (e.g., 48, 72, and 120 hours) which supports the results of the quantitative analysis where the parent compound was not already detected on the third day (Figure 1). According to the Metlin database, this degradation product of amlodipine can also be used for the treatment of angina and hypertension which is hypothetically the same with that of the parent compound. Subsequently, it is hypothesized that this metabolite is further degraded to 3,6-dihydropyridine which is apparently found during all data points from 24–120 hours.

Figure 5

Proposed degradation pathway of amlodipine based on pyridine derivatives.

Figure 5

Proposed degradation pathway of amlodipine based on pyridine derivatives.

Dihydropyridine, a molecule based upon pyridine, is known in pharmacology as an L-type calcium channel blocker which is used in the treatment of hypertension.

Lastly, our data show the presence of hydroxy-pyridines. These metabolites are believed to have been formed through enzyme degradation of pyridines by monooxygenases. Phanerochaete chrysosporium has been shown to possess an extensive P450 enzyme system, with approximately 150 P450 monooxygenase genes in its genome (Martinez et al. 2004; Doddapaneni et al. 2005). Pyridine metabolites might have undergone this degradation pathway by the P450 mono-oxygenase system of the organism used in this study. Although this proposed pathway has not been verified yet, these results were based on the metabolites identified by the database. Further studies are encouraged to validate this proposed degradation pathway.

CONCLUSIONS

In this study, we have shown the ability of Phanerochaete chrysosporium to degrade the drug amlodipine orotate. This was based on both quantitative and qualitative analyses of the samples from the experiment. As expected, production of metabolites increase as the duration of the study progresses which is probably due to an increase in enzymatic activity of the organism. The formation of pyridine derivatives suggests an effective breaking down of the parent structure to a more readily biodegradable product. Although pyridines can have detrimental effects on the environment as well as on humans, it can readily be degraded by bacteria to ammonia and carbon dioxide.

ACKNOWLEDGEMENTS

This research was financially supported by the Korea Institute of Science and Technology Institutional Program (2E25312) and by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number HI14C2686).

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