DOI QR코드

DOI QR Code

Bacterial Community Structure Shifted by Geosmin in Granular Activated Carbon System of Water Treatment Plants

  • Pham, Ngoc Dung (Department of Environmental Science and Engineering, Ewha Womans University) ;
  • Lee, Eun-Hee (Department of Environmental Science and Engineering, Ewha Womans University) ;
  • Chae, Seon-Ha (K-water Institute, Korea Water Resources Corporation) ;
  • Cho, Yongdeok (Korea Water Forum) ;
  • Shin, Hyejin (Bell Labs Seoul) ;
  • Son, Ahjeong (Department of Environmental Science and Engineering, Ewha Womans University)
  • 투고 : 2015.06.15
  • 심사 : 2015.10.05
  • 발행 : 2016.01.28

초록

We investigated the relation between the presence of geosmin in water and the bacterial community structure within the granular activated carbon (GAC) system of water treatment plants in South Korea. GAC samples were collected in May and August of 2014 at three water treatment plants (Sungnam, Koyang, and Yeoncho in Korea). Dissolved organic carbon and geosmin were analyzed before and after GAC treatment. Geosmin was found in raw water from Sungnam and Koyang water treatment plants but not in that from Yeoncho water treatment plant. Interestingly, but not surprisingly, the 16S rRNA clone library indicated that the bacterial communities from the Sungnam and Koyang GAC systems were closely related to geosmin-degrading bacteria. Based on the phylogenetic tree and multidimensional scaling plot, bacterial clones from GAC under the influence of geosmin were clustered with Variovorax paradoxus strain DB 9b and Comamonas sp. DB mg. In other words, the presence of geosmin in water might have inevitably contributed to the growth of geosmin degraders within the respective GAC system.

키워드

Introduction

Since antiquity, human civilizations and cities have been founded on geographical sites with ready access to water. In today’s mega cities, water often has to be transported from reservoirs and rivers many miles away and treated prior to distribution. In this regard, a water treatment plant is an extremely vital piece of infrastructure that has to be continually maintained and upgraded whenever possible. Water treatment consists of several key processes, including coagulation, sedimentation, filtration, and disinfection. In particular, an activated carbon filter stage is commonly used to remove both toxic compounds, such as benzenes and methylene chloride, as well as harmless but odorcausing compounds, such as trans-1,10-dimethyl-trans-9 decalol (geosmin) and 2-methylisoborneol (2-MIB), from the water.

Geosmin and 2-MIB are major taste and odor compounds that are known as biologically produced earthy-musty odorants [16]. Both compounds are tertiary alcohols that can be detected by human nose at concentrations as low as 4 pg/ml for geosmin and 9 pg/ml for 2-MIB in water, respectively [25]. Even though geosmin and 2-MIB were first identified in the early 1960s, they remain poorly understood regarding treatment, control, and prediction [17]. Geosmin has been shown to be recalcitrant to conventional water treatment processes consisting of coagulation, sedimentation, and filtration [2,13,14,25]. Therefore, adsorption using an activated carbon filter system is a well-known treatment technology for the effective removal of geosmin [8,12]. However, the presence of natural organic material adversely influences the activated carbon by decreasing the adsorptive capacity, and therefore it can lead to reduce the efficacy of geosmin removal from water [2,21].

It is also well known that the growth of bacteria on the surface of the activated carbon will eventually compromise its effectiveness in adsorbing the above-mentioned compounds. For example, an activated carbon surface coated with bacterial biofilm will not be able to effectively adsorb organic compounds in the water. As a maintenance procedure, the activated carbon stage is routinely backwashed. However, this procedure is only often undertaken when the bacterial biofilm becomes sufficiently thick to induce a detectable drop in filter pressure. By then, the activated carbon system would have already been coated with bacterial biofilm and rendered ineffective for the duration. Such challenge can be addressed by understanding the formation and growth of the bacterial community in the activated carbon system. In this way, we may be able to inhibit bacterial growth by withholding the presence of respective nutrients for the various bacteria.

As an initiation of in-depth understanding of the system, in this study we investigated the presence of geosmin in water intake and its potential role as an energy source to the selective growth of certain bacteria within the granular activated carbon (GAC) filter of water treatment plants. A 16S rRNA clone library was constructed for the GAC samples from several water treatment plants in Korea. Subsequent phylogenetic analyses were reported to identify the genetic affiliations of geosmin-utilizing bacteria in the GAC system. The effect of geosmin on the bacterial communities of GAC was reported for both temporal and spatial scales.

 

Materials and Methods

GAC Sampling Sites and Sample Collection

Three sampling sites were chosen on the basis of geographical location and significance. GAC samples were collected from GAC lines of three water treatment plants located at Sungnam and Koyang in Kyunggi-do and at Yeoncho in Kyungsangnam-do, South Korea (Fig. 1). Two GAC samples were collected in May and August of 2014 from the Sungnam water treatment plant to monitor temporal changes in microbial community structures. Another two samples collected in August 2014 from Koyang and Yeoncho plants were chosen to evaluate spatial changes. Sungnam and Koyang plants were selected owing to their importance in supplying portable water to more than four million people in Kyunggi-do, Korea. We also note that both Sungnam and Koyang plants receive their raw water from the same water source, which is Paldang Lake in Korea. The Yeoncho plant is a newly renovated water treatment plant located in the southern part of Korea and was reconstructed for the advanced water treatment in 2012. Owing to the relatively short-term operation for water treatment, no geosmin occurrence has been observed in Yeoncho plant thus far. Despite the geographical distance, Yeoncho was selected as a negative control as its GAC system has never been exposed to geosmin. Twenty grams of the GAC samples was transferred into sterilized 50 ml vials and stored at – 20℃ prior to the analysis.

Fig. 1.Map of the sampling sites for the granular activated carbon samples.

Analysis of Dissolved Organic Carbon and Geosmin Concentrations

Dissolved organic carbon (DOC) concentrations of influent and effluent at the water treatment plants were analyzed with a Shimadzu TOC-VCHP analyzer (Shimadzu Co., Kyoto, Japan) equipped at K-water Institute (Daejeon, Korea) according to the Standard Method 5310C [5]. Sampled water was filtrated with a 0.45-μm-pore membrane filter before analyzing DOC levels. Geosmin concentrations of influent and effluent at the plants were measured using a solid-phase micro-extraction method. Geosmin was extracted using polydimethyl-siloxane/divinyl-benzene (65 μm fiber coating) fiber by continuous stirring for 30 min, and then analyzed using gas chromatography equipped with a mass spectrometry detector (Perkin Elmer Clarus 600C, Shelton, USA). The detailed analysis conditions are described in the Standard Method 6040D [5]. All experiments were performed in duplicate and the detection limit of geosmin was 2 ng/l.

DNA Extraction

In order to analyze microbial community structures in the GAC system of water treatment plants based on DNA assays, genomic DNAs were extracted from the collected GAC samples using a probe ultrasonicator. The GAC samples were mixed via vortexing for 5 min to collect homogeneous samples. Four grams of the collected GAC sample was transferred into 50 ml vials, and then 4 ml of distilled water was added into the vials. The vials were subsequently placed in ice to prevent heat-induced DNA damage. The samples were ultrasonicated using an ultrasonic dismembrator with a P-1 microprobe (XL-2000; Qsonica, Newtown, USA) at 10 W for 1 min, which was the condition shown for optimum efficiency for DNA extraction (data not shown). After the ultrasonication, the samples were centrifuged at 3,500 rpm for 10 min. The genomic DNAs were extracted in triplicates and thenpooled for further experiments. DNA concentrations were measured using a NanoDrop ND1000 spectrophotometer (Thermo Scientific, Wilmington, USA). The extracted DNAs were immediately stored at -20℃ prior to use.

Polymerase Chain Reaction (PCR) Amplification

The evaluation of the microbial communities of the GAC samples was based on 16S ribosomal RNA (16S rRNA) sequence analysis. First, PCR was performed using a universal bacterial primer set of 27f and 1492r to amplify the 16S rRNA gene [19]. The primer set was commercially synthesized by Bioneer Corporation (Daejeon, Korea). The reaction mixture was prepared in a 25 μl volume containing 1 μmol/l of each primer, 1× Mg-free PCR buffer (Takara, Shiga, Japan), 20 mmol/l MgCl2, 400 nmol/l dNTPs, 0.1 U of Taq polymerase (Takara, Shiga, Japan), and 20 ng of DNA template. The PCR consisted of an initial denaturation for 5 min at 94℃; 35 cycles of 60 sec at 94℃, 60 sec at 55℃, and 120 sec at 72℃; and a f inal extension of 15 min at 72℃ (Applied Biosystems, Foster City, USA). PCR amplification was performed in triplicates and the products were combined prior to the further cloning experiment. The PCR amplicon was loaded onto a 1.0% agarose gel and the DNA band was visually inspected under UV illumination using a gel imaging system (Gel Logic 100; Molecular Imaging Systems, Carestream Health, Rochester, USA) after staining the gel with 10 mg/ml of ethidium bromide (Bio-Rad, Hercules, USA) in 0.5× TBE (Bioneer, Korea). The amplification product was purified u sing a DNA c lean & c oncentrator k it ( Zymo R esearch, Irvine, USA), according to the manufacturer’s recommendations. The purified PCR product was quantified using the ND1000 spectrophotometer.

16S rRNA Clone Library

Twenty nanograms of the purified PCR products was ligated into the pCR-2.1 TOPO vector and transformed into One Shot TOP10 chemically competent E. coli cells (Invitrogen TOPO TA Cloning kit; Life Technologies, Grand Island, USA), following the manufacturer’s instructions. The blue-white screening method was employed by culturing transformants on Luria-Bertani (LB) agar (BD Difco, NJ, USA) plates containing 64 μg/ml of 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside (X-gal, Bioneer), 0.16 mmoles/lof isopropyl β-D-1-thiogalactopyranoside (Bioneer), and 50 μg/ml of ampicillin (Biomax, Korea). White colonies were inoculated into LB broth containing 50 μg/ml of ampicillin and incubated at 37℃ with shaking at 180 rpm overnight. Subsequently, plasmids were extracted using a QIAprep Spin Miniprep kit (Qiagen, Valencia, USA). The DNA insert was excised with EcoRI (New England Biolabs, Ipswich, USA) and visually inspected on 1.0% agarose gel under UV illumination (Thermo Fisher Scientific, Pittsburgh, USA) using the Gel Logic 100 imaging system (Eastman Kodak Company, Stamford, USA). Twenty microliters of cloned PCR fragments was sequenced using the M13f 5’-GTAAAACGACGG CCAGT-3’ primer by Bioneer.

Phylogenetic Analysis

The analyzed sequences were compared with sequences from the GenBank database using the Basic Local Alignment Search Tool (BLAST) of the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/blast) [1] to determine the closest relatives. Our cloned DNA sequences were aligned with the sequences of closest relatives, including geosmin degraders (Table S1), using ClustalX 2.1 software [20]. Phylogenetic trees were constructed using the neighbor-joining algorithms with 1,000 bootstrap replicates in the MEGA 6.06 software package [26].

Multidimensional Scaling Analysis

Multidimensional scaling (MDS) was employed to represent the phylogenetic relation among clones, including the known geosmin degraders. MDS is a technique employed to construct a new configuration of objects using the information of distances (e.g., dissimilarity) between objects. MDS has been popularly used in the visualization for exploring similarities or dissimilarities in data in several fields, including biology [3,10,27]. The similarity table obtained from BLAST 2 analyses was subsequently converted to an MDS plot based on Kruskal's non-metric method [18]. This method chooses a configuration such that the points of larger dissimilarity would be farther away.

 

Results and Discussion

Water Quality and Geosmin Concentration of Water Treatment Plants

Table 1 shows the water quality information of the water treatment plants where the GAC samples were taken. Sungnam plant is capable of treating 789,000 m3 of water per day. Koyang and Yeoncho treatment plants have capacities of 210,000 and 16,000 m3/day, respectively. All raw water at the water treatment plants had a neutral pH of 6.8–7.5. Influent DOC levels were in the range of 1.3–1.9 mg/l and it decreased to 0.9–1.2 mg/l after being passed through the GAC filter system. It is important to note that geosmin in the influent was detected only in August at Sungnam and Koyang water treatment plants, ranging from 35 to 48 ng/l of average influent geosmin concentrations. The highest levels of geosmin concentrations were 159 and 295 ng/l at Sungnam and Koyang water treatment plants, respectively. Sungnam and Koyang treatment plants received raw water from Paldang Lake, a reservoir that has a water storage capacity of 244 × 106 m3 and surface area of 20,085 km2 (Fig. 1). It was reported that geosmin outbreak occurs during the summer season of water supply in Korea [22,23]. Park et al. [23] reported that geosmin was detected in Paldang Lake and the concentration was increased to >4 ppb (ng/l) from mid-July to mid-August of 2012. Cyanobacterial blooms caused by Microcystis, Anabaena, and Oscillatoria have been considered to produce geosmin compounds [4], which are highly related to environmental variables such as water temperature [22]. August is the mid-summer season in Korea and maintains about 24–28℃ of average temperature. In August 2014, algae advisory was alerted in Paldang Lake that had exceeded 15 mg/m3 of chlorophyll-a or 500 algal cells/ml twice in a row. This probably induced the geosmin feed to the Sungnam and Koyang water treatment plants in August 2014 (Table 1).

Table 1.aDOC refers to dissolved organic carbon. bCi represents the concentration in influent of the water treatment plant. cCe represents the concentration in effluent of the water treatment plant. dAverage indicates the average concentration of geosmin in the influent. eHighest indicates the highest concentration of geosmin in the influent. fND, not detected.

Similarly, total trihalomethane (THM) levels were greater in August for Sungnam and Koyang samples than in May for Sungnam and in August for Yeoncho water treatment plants (Table 1). Several research projects have shown that THM levels are increased in the presence of precursors such as organic carbon [7,9,24]. Geosmin is classified as an organic compound, which possibly reacts with chlorine as a precursor to form THMs. Geosmin occurrence in this area probably induced a higher level of THMs in August from Sungnam and Koyang treatment plants.

Bacterial Community Structures of GAC Filter Systems

A 16S rRNA clone library was constructed to evaluate bacterial community structures of GAC adsorption systems in the three water treatment plants. As shown in Fig. 2, the Sungnam-May sample was dominated by three bacterial classes (Alphaproteobacteria, Betaproteobacteria, and Deltaproteobacteria). In comparison, bacterial clones in the Sungnam-August sample were grouped in four classes (Alphaproteobacteria, Betaproteobacteria, Deltaproteobacteria, and Gammaproteobacteria) (Fig. 3). Hence, a slight shift of bacterial class was observed in the temporal sample (May-August) of the Sungnam GAC system. Note that all the defined bacterial clones in the May and August Sungnam GAC samples belonged to the phylum Proteobacteria. Interestingly, in the August Sungnam GAC, the bacterial clones 2-15, 2-21, 2-29, and 2-45 were closely grouped with Variovorax paradoxus strain DB 9b (GQ365214) and Comamonas sp. DB mg (GQ365217), which are capable of growing with geosmin as a sole carbon and energy source (Fig. 3) [11]. Those bacterial clones show 90–93% and 89–91% of similarities with strain DB 9b and DB mg, respectively. This was also demonstrated by the MDS analysis shown in Fig. 4. With reference to Fig. 4, the clones 2-15, 2-21, 2-29, and 2-45 were gathered together with Variovorax paradoxus strain DB 9b and Comamonas sp. DB mg, indicating that those clones are closely related to geosmin degraders (Table S1). This result suggests that selective growth of geosmin degraders possibly occurred as compared with the bacterial community in the May Sungnam GAC sample. Note again that geosmin was only detected in August, which possibly leads to supply of geosmin as a carbon and energy source into the GAC system in August at Sungnam treatment plant (Table 1). On the other hand, as shown in Fig. 2, most of bacterial clones were not clustered with the bacteria capable of utilizing geosmin [6,11,14,15,28]. The bacterial clone 1-59 was only grouped with geosmin degraders of Variovorax paradoxus strain DB 9b and Comamonas sp. DB mg. However, the MDS analysis of Sungnam-May (Fig. S2) did not support this cluster, suggesting that this clone may not be close to geosmin degraders.

Fig. 2.Phylogenetic tree illustrating the genetic affiliation among the closest relatives in the RDP/GenBank database and the bacterial clones in the Sungnam-May sample.

Fig. 3.Phylogenetic tree of the Sungnam-August sample.

Fig. 4.Multidimensional scaling plot drawn from two sequences comparison by BLAST 2 analysis of the Sungnam-August sample.

This phenomenon was also observed in the bacterial community of the August GAC sample at Koyang plant. With reference to Fig. 5, the bacterial clones 7-22 and 7-40 were clustered with Oxalobacteraceae bacterium GSM-33 (HM989959) [28], Variovorax paradoxus strain DB 9b, and Comamonas sp. DB mg, which showed 84–86% and 85–88% of similarities, respectively. This confirmed that those clones were similar to Variovorax paradoxus strain DB 9b and Comamonas sp. DB mg, based on the analysis of MDS (Fig. 6). This possibly indicates that selective growth of similar species capable of biodegrading geosmin occurred in August at the Koyang GAC system, as that happened in August at the Sungnam GAC system. It should be noted that geosmin was detected in August samples only at Sungnam and Koyang treatment plants. This strongly implies that the occurrence of geosmin probably induced the level of selective growth of geomin degraders, which led to changes of the bacterial community structures at the GAC systems.

Fig. 5.Phylogenetic tree of the Koyang-August sample.

Fig. 6.Multidimensional scaling plot drawn for the Koyang-August sample.

The six bacterial classes (Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Deltaproteobacteria, Oscillatoriophycideae, and Sphingobacteriia) were detected in the August sample of Yeoncho GAC (Fig. 7). Since Yeoncho water plant receives source water from Yeoncho dam, where significant geosmin was not detected during the sample time, the possible effect from geosmin would be negligible. The Yeoncho sample was used as a negative control to evaluate the geosmin effect on the bacterial communities in the GAC system. Interestingly, the genus Phormidium (HM217043) and Terrimonas (NR_109427 and HQ113208) were only detected in the August Yeoncho sample as compared with that of other GAC samples (Figs. 2 –6). The class Oscillatoriophycideae comprised 35% of the bacterial community in the August sample of Yeoncho GAC system (Fig. S1). Although the bacterial clones 9-3, 9-9, 9-28, and 9-29 were grouped with geosmin-degrading bacteria Methylobacterium sp. GSM-19 (HM989961),Sphingopyxis sp. strains Geo24 (DQ137852) and Geo 48 (EU816422), and Novosphingobium sp. strain Geo25 (DQ137853), this was not statistically demonstrated by MDS analysis (Fig. S3). On the basis of the MDS plot, those clones were not clustered with geosmin degraders, which indicates that the bacterial community in the August sample at Yeoncho GAC system consisted of other bacterial genera such as Sphingomonas, Xanthobacter, and Phormidium.

Fig. 7.Phylogenetic tree of the Yeoncho-August sample.

The Shannon diversity indices showed similar levels of 3.84–4.12 in all bacterial communities (Table S2). The diversity index was slightly decreased in August at Sungnam as compared with that in May at Sungnam. This is probably due to the incremental Alphaproteobacteria composition in the bacterial community in August at the Sungnam GAC system. The class Alphaproteobacteria comprised 40% of the bacterial community in August, which was dramatically increased compared with that of 14% in May at the Sungnam GAC system (Fig. S1). It is considered that environmental variables such as temperature probably influenced the bacterial community structure. Note that the class Gammaproteobacteria was only detected in all GAC systems of August (Fig. S1) and this may be caused by seasonal changes.

In summary, we have evaluated the occurrence of geosmin in water intake and its associated bacterial community changes in GAC systems of Korean water treatment plants. Substantial levels of geosmin were detected in August 2014 samples at Sungnam and Koyang plants. It was concluded that the existence of geosmin in the source water probably induced the selective growth of geosmin-utilizing bacteria in the GAC systems. The bacterial communities in August at Sungnam and Koyang plants were closely related to the strains Variovorax paradoxus strain DB 9b and Comamonas sp. DB mg, which are known geosmin-degrading bacteria. The class Gammaproteobacteria was only detected in the bacterial communities of all GAC systems in August. Seasonal changes such as temperature increase presumably influenced the bacterial community structures. A follow-up study is needed to identify the biological degradation possibility of geosmin in the GAC systems. Further research is necessary in order to acquire a better understanding of the relations and mechanism between water quality and the dynamics of bacterial communities.

참고문헌

  1. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. 1990. Basic local alignment search tool. J. Mol. Biol. 215: 403-410. https://doi.org/10.1016/S0022-2836(05)80360-2
  2. Cook D, Newcombe G, Sztajnbok P. 2001. The application of powdered activated carbon for MIB and geosmin removal: predicting PAC doses in four raw waters. Water Res. 35: 1325-1333. https://doi.org/10.1016/S0043-1354(00)00363-8
  3. Cox TF, Cox MAA. 2000. Multidimensional Scaling, pp. 1-30. 2nd Ed. Chapman & Hall, London.
  4. De Figueiredo DR, Azeiteiro UM, Esteves SM, Goncalves FJM, Pereira MJ. 2004. Microcystin-producing blooms - a serious global public health issue. Ecotoxicol. Environ. Saf. 59: 151-163. https://doi.org/10.1016/j.ecoenv.2004.04.006
  5. Eaton AD, Franson MAH, Association APH, Association AWW, Federation WE. 2005. Standard Methods for the Examination of Water & Wastewater. 21st Ed. American Public Health Association, Washington, DC.
  6. Eaton RW, Sandusky P. 2009. Biotransformations of 2-methylisoborneol by camphor-degrading bacteria. Appl. Environ. Microbiol. 75: 583-588. https://doi.org/10.1128/AEM.02126-08
  7. Garcia-Villanova RJ, Garcia C, Gomez JA, Garcia MP, Ardanuy R. 1997. Formation, evolution and modeling of trihalomethanes in the drinking water of a town: I. At the municipal treatment utilities. Water Res. 31: 1299-1308. https://doi.org/10.1016/S0043-1354(96)00335-1
  8. Glaze WH, Schep R, Chauncey W, Ruth EC, Zarnoch JJ, Aieta EM, et al. 1990. Evaluating oxidants for the removal of model taste and odor compounds from a municipal water supply. J. Am. Water Works Assoc. 82: 79-84. https://doi.org/10.1002/j.1551-8833.1990.tb06967.x
  9. Golfinopoulos SK, Xilourgidis NK, Kostopoulou MN, Lekkas TD. 1998. Use of a multiple regression model for predicting trihalomethane formation. Water Res. 32: 2821-2829. https://doi.org/10.1016/S0043-1354(98)00022-0
  10. Gower JC. 1966. Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53: 325-338. https://doi.org/10.1093/biomet/53.3-4.325
  11. Guttman L, van Rijn J. 2012. Isolation of bacteria capable of growth with 2-methylisoborneol and geosmin as the sole carbon and energy sources. Appl. Environ. Microbiol. 78: 363-370. https://doi.org/10.1128/AEM.06333-11
  12. Ho L, Croue JP, Newcombe G. 2004. The effect of water quality and NOM character on the ozonation of MIB and geosmin. Water Sci. Technol. 49: 249-255.
  13. Ho L, Newcombe G, Croue JP. 2002. Influence of the character of NOM on the ozonation of MIB and geosmin. Water Res. 36: 511-518. https://doi.org/10.1016/S0043-1354(01)00253-6
  14. Hoefel D, Ho L, Aunkofer W, Monis PT, Keegan A, Newcombe G, Saint CP. 2006. Cooperative biodegradation of geosmin by a consortium comprising three gram-negative bacteria isolated from the biofilm of a sand filter column. Lett. Appl. Microbiol. 43: 417-423. https://doi.org/10.1111/j.1472-765X.2006.01974.x
  15. Hoefel D, Ho L, Monis PT, Newcombe G, Saint CP. 2009. Biodegradation of geosmin by a novel gram-negative bacterium; isolation, phylogenetic characterisation and degradation rate determination. Water Res. 43: 2927-2935. https://doi.org/10.1016/j.watres.2009.04.005
  16. Izaguirre G, Taylor WD. 2004. A guide to geosmin- and MIB-producing cyanobacteria in the United States. Water Sci. Technol. 49: 19-24.
  17. Juttner F, Watson SB. 2007. Biochemical and ecological control of geosmin and 2-methylisoborneol in source waters. Appl. Environ. Microbiol. 73: 4395-4406. https://doi.org/10.1128/AEM.02250-06
  18. Kruskal JB. 1964. Nonmetric multidimensional scaling: a numerical method. Psykometrika 29: 115-129. https://doi.org/10.1007/BF02289694
  19. Lane DJ. 1991. 16S/23S rRNA sequencing, pp. 115-175. In Goodfellow M, Stackebrandt E (eds.). Nucleic Acid Techniques in Bacterial Systematics, 1st Ed. John Wiley & Sons, Chichester.
  20. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al. 2007. Clustal W and Clustal X version 2.0. Bioinformatics 23: 2947-2948. https://doi.org/10.1093/bioinformatics/btm404
  21. Newcombe G, Drikas M, Hayes R. 1997. Influence of characterized natural organic material on activated carbon adsorption: II. Effect on pore volume distribution and adsorption of 2-methylisoborneol. Water Res. 31: 1065-1073. https://doi.org/10.1016/S0043-1354(96)00325-9
  22. Oh HM, Ahn CY, Lee JW, Chon TS, Choi KH, Park YS. 2007. Community patterning and identification of predominant factors in algal bloom in Daechung Reservoir (Korea) using artificial neural networks. Ecol. Model. 203: 109-118. https://doi.org/10.1016/j.ecolmodel.2006.04.030
  23. Park TJ, Yu MN, Kim HS, Cho HS, Hwang MY, Yang HJ, et al. 2014. Characteristics of actinomycetes producing geosmin in Paldang Lake, Korea. Desalin. Water Treat.
  24. Rodriguez MJ, Serodes JB. 2001. Spatial and temporal evolution of trihalomethanes in three water distribution systems. Water Res. 35: 1572-1586. https://doi.org/10.1016/S0043-1354(00)00403-6
  25. Suffet IH, Ho J, Chou D, Khiari D, Mallevialle J. 1995. Tasteand-odor problems observed during drinking water treatment, pp. 1-22. In Suffet IH, Mallevialle J, Kawczynski E (eds.). Advances in Taste and Odor Treatment and Control. American Water Works Association Research Foundation, Denver.
  26. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. 2013. MEGA6: molecular evolutionary genetics analysis version 6.0. Mol. Biol. Evol. 30: 2725-2729. https://doi.org/10.1093/molbev/mst197
  27. Torgerson WS. 1952. Multidimensional scaling I: theory and method. Psycometrika 17: 401-419. https://doi.org/10.1007/BF02288916
  28. Xue Q, Shimizu K, Sakharkar MK, Utsumi M, Cao G, Li M, et al. 2012. Geosmin degradation by seasonal biofilm from a biological treatment facility. Environ. Sci. Pollut. Res. Int. 19: 700-707. https://doi.org/10.1007/s11356-011-0613-2

피인용 문헌

  1. Plant Growth Promoting and Biocontrol Activity of Streptomyces spp. as Endophytes vol.19, pp.4, 2016, https://doi.org/10.3390/ijms19040952
  2. Characteristics of Bacterial Communities in Biological Filters of Full-Scale Drinking Water Treatment Plants vol.29, pp.1, 2016, https://doi.org/10.4014/jmb.1808.07068