Inhibition effect of isopropanol on acetyl-CoA synthetase expression level of acetoclastic methanogen, Methanosaeta concilii

Journal of Biotechnology 156 (2011) 95–99

Contents lists available at SciVerse ScienceDirect

Journal of Biotechnology journal homepage: www.elsevier.com/locate/jbiotec

Inhibition effect of isopropanol on acetyl-CoA synthetase expression level of acetoclastic methanogen, Methanosaeta concilii Bahar Ince a , Gozde Koksel a , Zeynep Cetecioglu b , Nilgun Ayman Oz c , Halil Coban a,∗ , Orhan Ince b a b c

Bogazici University, Institute of Environmental Sciences, Bebek, 34342 Istanbul, Turkey Istanbul Technical University, Department of Environmental Engineering, Maslak, 34469 Istanbul, Turkey Canakkale Onsekiz Mart University, Faculty of Engineering and Architecture, Department of Environmental Engineering, Canakkale, Turkey

a r t i c l e

i n f o

Article history: Received 24 February 2011 Received in revised form 10 June 2011 Accepted 12 August 2011 Available online 22 August 2011 Keywords: Isopropanol Acetyl-CoA synthetase mRNA Real-time PCR FISH Methanosaeta concilii

a b s t r a c t Isopropanol is a widely found solvent in industrial wastewaters, which have commonly been treated using anaerobic systems. In this study, inhibitory effect of isopropanol on the key microbial group in anaerobic bioreactors, acetoclastic methanogens, was investigated. Anaerobic sludges in serum bottles were repeatedly fed with acetate and isopropanol; and quantitative real-time PCR was used for determining effect of isopropanol on the expression level of a key enzyme in acetoclastic methane production, acetyl-CoA synthetase of Methanosaeta concilii. Active Methanosaeta spp. cells were also quantified using Fluorescent in situ hybridization (FISH). Transcript abundance of acetyl-CoA synthetase was 1.23 ± 0.62 × 106 mRNAs/mL in the uninhibited reactors with 222 mL cumulative methane production. First exposure to isopropanol resulted in 71.2%, 84.7%, 89.2% and 94.6% decrease in mRNA level and 35.0%, 65.0%, 91.5% and 100.0% reduction in methane production for isopropanol concentrations of 0.1 M, 0.5 M, 1.0 M and 2.0 M, respectively. Repeated exposures resulted in higher inhibitions; and at the end of test, fluorescent intensities of active Methanosaeta cells were significantly decreased due to isopropanol. The overall results indicated that isopropanol has an inhibitory effect on acetoclastic methanogenesis; and the inhibition can be detected by monitoring level of acetyl-CoA transcripts and rRNA level. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Anaerobic wastewater treatment, which is a cost-effective alternative to other treatment methods, has gained popularity for a wide range of industrial effluents containing organic solvents. The organic solvents are widely used to dissolve compounds required for certain industrial processes. However, there are still some concerns regarding the application of anaerobic treatment processes for solvent containing wastewaters. These processes are mostly limited by the extent of inhibitory effects of solvents found in waste streams, which influence in the microbial community structure that plays a role in anaerobic wastewater treatment. Although there some studies in the literature on anaerobic treatment of industrial wastewaters containing organic solvents, the number of studies on inhibition is limited. Also, literature on anaerobic digestion shows considerable variation in inhibition/toxicity levels reported for most substances. The major reason for these variations is the complexity of the anaerobic digestion process where mechanisms such as antagonism, synergism, acclimation, and complexing

∗ Corresponding author. Tel.: +90 212 359 4602. E-mail address: [email protected] (H. Coban). 0168-1656/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.jbiotec.2011.08.021

could significantly affect the phenomenon of inhibition (Chen et al., 2007). Methanogenesis is the most sensitive step in the anaerobic digestion process (Speece and Parkin, 1983). Acting as inhibitors, organic solvents in wastewater may affect the activity and composition of methanogens. About 70% of methane formed in a biogas reactor is derived from acetate (Gujer and Zehnder, 1983), therefore an inhibition in the activity of the acetate-utilizing methanogens severely affects the anaerobic degradation process. Only two genera are known to use acetate for methanogenesis: Methanosarcina and Methanosaeta. Compared to Methanosarcina, Methanosaeta is a superior acetate utilizer (Jetten et al., 1992; Zinder, 1993). This group can use acetate at concentration levels as low as 5–20 ␮M. Acetate must first be converted to acetyl coenzyme A (acetyl-CoA) before convertion to methane. Methanosaeta uses high-affinity adenosine monophosphate (AMP) – forming acetylCoA synthetase which is a key enzyme that activates acetate to acetyl-CoA (Jetten et al., 1992; Smith and Ingram-Smith, 2007). After that, acetyl-CoA can interact with carbon monoxide dehydrogenase (Eggen et al., 1991), and methyl group of acetate is transferred to the corronoid enzyme to yield CH3 -corronoid. These processes are followed by the CoM-mediated terminal step of methanogenesis (Wolfe, 1991; Ferry, 1992; Weiss and Thauer, 1993). In the last step of methane production, the methyl group

96

B. Ince et al. / Journal of Biotechnology 156 (2011) 95–99

is reduced to methane with electrons derived from oxidation of the carbonyl group of acetyl-CoA to CO2 . In this study, IPA (iso-propanol) was chosen as the organic solvent, as it is widely used in many different industrial branches such as rubber, cosmetics, textiles, and its production worldwide exceeds 1 million tonnes per annum. Until recently, inhibitory effect of this solvent on the anaerobic treatment has been known, however the mechanism of effect is unclear. The objective of this study is to investigate the effect of this solvent on the expression level of acetyl-CoA synthetase enzyme of Methanosaeta concilii, methane production and active microorganisms.

Table 1 Primers for acetyl Co-A synthetase gene of M. concilii.

2. Materials and methods

Superscript Vilo cDNA synthesis kit (Invitrogen, Carlsband, CA, USA) was used to synthesize cDNA from the extracted RNAs. Extracted RNAs were converted into cDNAs by the reverse transcription polymerase chain reaction (RT-PCR) using hexamer primers. cDNA synthesis for one cycle was run for 10 min at 25 ◦ C, 1 h at 42 ◦ C and 5 min at 85 ◦ C. The cDNA samples were stored at −20 ◦ C before Q-PCR (quantitative real-time PCR) analysis.

2.1. Characterization of seed sludge and set-up of serum bottle tests The inoculum sludge with TS (total solids) and TVS (total volatile solids) concentrations of 58 g/L and 48 g/L, respectively, was taken from a full scale UASB (upflow anaerobic sludge blanket) reactor with a 435 m3 active volume, treating alcohol (raki) distillery wastewater. The sludge has not been exposed to IPA before. Prior to use, presence of M. concilii in the seed sludge was confirmed via DGGE by running and comparing archaeal bands in the sludge with M. concilii clones (data not shown). Seed sludge was diluted to 2000 mg/L TVS with a mineral stock solution as described in a previous study (Valcke and Verstraete, 1983). Seed sludge and dilution solution were added to serum bottles (OECD protocol 311) and sealed with butyl rubber septa with liquid volume of 100 mL and headspace volume of 20 mL. pH was set to 7.0 by using HCl and KOH. Then, the bottles were stirred at 90 rpm in a water bath at 37 ◦ C during 7–10 days. Prior to inhibition tests, acetate concentrations in a range of 1000–5000 mg/L were tested in order to find maximum potential methane production rate. Among those, 2000 mg/L concentration was found to be optimum. The serum bottles were firstly fed with acetate at a concentration of 2000 mg/L. For inhibition tests, the bottles were exposed to IPA at concentrations of 0.1 M, 0.5 M, 1.0 M, 2.0 M. According to the results of GC analysis, acetate and IPA were added in every 10 days during 30 day-operation. Control reactors were also operated and fed with only acetate at a concentration of 2000 mg/L without isopropanol. 2.2. Analytical techniques After the anaerobic sludge in serum bottles was fed with acetate and solvents, the gas pressure in the bottles was measured with a manometer (Lutron, PM9107). Gas composition was measured using a gas chromatograph (HP Agilent 6850) with a thermal conductivity detector (HP Plot Q column 30 m × 530 ␮m). TS and TVS concentrations were determined according to standard methods (APHA, 2003). Methane production rates were calculated using ideal gas formula and reported as the volume in 1 atm pressure. 2.3. RNA isolation 1.5 mL samples was taken into sterile RNAse free tubes for RNA extraction. The tubes were kept in an ice bath and RNAs were immediately extracted. To extract the RNAs, Charge Switch RNA extraction kit (Invitrogen, Carlsband, CA, USA) with a magna rack (Invitrogen, Carlsband, CA, USA) was used and the recommended procedure by the supplier was followed. Concentration of total RNA in samples was measured using a Quant-It RiboGreen RNA Assay Kit (Invitrogen, Carlsband, CA, USA) and a fluorometer (Qubit, Invitrogen, Carlsband, CA, USA) after a traditional PCR check (data not

Primers MSaeta Aco-A f MSaeta Aco-A r

Annealing temperature (◦ C)

Sequence 



5 -taatccgccaaaagagttgg-3 5 -tcttctggactggctggtct-3

56 56

shown). The isolated RNA was stored at −80 ◦ C until synthesis of cDNA. 2.4. Reverse transcriptase PCR methodology

2.5. Gene specific primer design The primer set was designed by using publicly available acetylCoA synthetase gene sequence of M. concilii from European Bioinformatic Institute database (http://www.ebi.ac.uk). The gene sequence was aligned with acetyl-CoA synthetase genes of all known Methanogens, especially Methanosarcina spp. to discover inaccurate amplicons, if any, and suitable primer target sites. The primers were selected to amplify a 329-bp fragment using Primer3 (http://frodo.wi.mit.edu/primer3/) and they were confirmed by Amplify3X. The specificity of the primers was tested in silico (http://insilico.ehu.es/) (Table 1). 2.6. Standard curves Acetyl Co-A synthetase gene fragment of M. concilii was amplified from an anaerobic sludge containing a high M. concilii population. PCR products that are to be sequenced were purified by ethanol precipitation and then they were sequenced using the ABI prism Big Dye Terminator Cycle Sequencing Ready Reaction Kit on an ABI Prism 377 DNA sequencer (Applied Biosystems, USA) using primer MSaeta Aco-A f. After the primer specificity was confirmed by the sequence analysis, these amplicons were used as standards. Dilution series of the purified PCR product were used as calibration standards for real time PCR quantification after their DNA concentrations were determined by the fluorometer (Qubit, Invitrogen, Carlsband, CA, USA). Standard curves were constructed in each PCR run and the copy numbers of the genes in each sample were interpolated using these standard curves. 2.7. Real time PCR assays The procedure recommended by Roche was followed and a Light Cycler Master Kit (Roche, Applied Science, Switzerland) was used to set up the reaction (2.0 ␮L master mix, 1.6 ␮L MgCl2 1.0 ␮L Primer F and R, 13.4 ␮L H2 O, 2 ␮L sample). Absolute quantification analysis of the cDNA was carried out with a LightCycler 480 Instrument (Roche Applied Science, Switzerland). 2.8. Melting curve analysis For each PCR run with SYBR Green I detection, a melting curve analysis was performed to guarantee the specificity in each reaction tube by the absence of primer dimers and other nonspecific products. Reactions for all samples were shown to have only one

B. Ince et al. / Journal of Biotechnology 156 (2011) 95–99

97

Table 2 Oligonucleotide probes used in this study. Probe

Target group

Probe sequence (5 –3 )

Labelling (5 )

Reference

MX825 ARC915 EUB338 UNIV1392 NON338

Methanosaeta spp. Archaea Bacteria Virtually all known organisms Non sense probe

TCGCACCGTGGCCCACACCTAGC GTGCTCCCCCGCCAATTCCT GCTGCCTCCCGTAGGAGT ACGGGCGGTGTGTAC ACTCCTACGGCAGGCAGC

CY3 CY3 CY3 CY3 CY3

Raskin et al. (1994) Stahl and Amann (1991) Amann et al. (1990) Olsen et al. (1986) Wallner et al. (1993)

melting peak, which indicated a specific amplification and an accurate quantification. 2.9. Fluorescent in situ hybridization (FISH) At the end of 30 days, 5 mL samples was taken from each of the serum bottles and mixed with ethanol (1:1 (v/v)). The samples were kept at −20 ◦ C and standard PFA fixation was carried out within 3 days. For PFA fixation, 1000 ␮L of sludge-ethanol mix (1:1 (v/v)) was washed once with 0.5 mL 3× phosphate-buffered saline (PBS) [130 mM NaCl, 10 mM sodium phosphate, pH 7.2] and resuspended in 0.5 mL PBS. 0.75 mL of freshly prepared 4% PFA in PBS (pH 7.2) was added to the suspension and incubated for at least 3 h, or overnight, at 4 ◦ C. After fixation, cells were washed once with PBS, resuspended in 0.5 mL of PBS–absolute ethanol (1:1 (v/v)) and stored at −20 ◦ C. For the hybridization part, 16S rRNAtargeted oligonucleotide probes were used in this study and their target microbial groups nucleotide sequences are listed in Table 2. All probes were obtained commercially (Qiagen Corp.). In situ hybridization was conducted according to protocols previously described (Nielsen et al., 1999; Sekiguchi et al., 1999). 200 ␮L of the fixed samples was washed twice with PBS and once with MilliQ water. Then the fixed samples were dehydrated at room temperature in increasing concentrations of ethanol (50%, 80%, and 100%). 3 ␮L of probe (50 ng/␮L) and 17 ␮L hybridization buffer (4.5 M NaCl, 2 mg/mL Ficoll, 2 mg/mL bovine serum albumen, 2 mg/mL polyvinyl pyrolidone, 5 mM EDTA, Tris–HCl, pH 7.2, 25 mM NaH2 PO4 , pH 7.0, 0.1% SDS) were added and incubated at the optimal hybridization temperature for the used probe for at least 4 h or overnight. Following hybridization, the cells were washed twice in a wash buffer containing 20 mM Tris–HCl (pH 7.2), 0.01% SDS, 4.5 M NaCl before a final wash in MilliQ water. The cells were resuspended in MilliQ water, and then were dried. Cells were stained with DAPI also, in order to quantify all organisms independent of they were metabolically active or not. 10 ␮L of DABCO (1,4-diazabicyclo[2.2.2]octane) [Sigma D-2522]: 0.233 g DABCO 800 ␮L ddH2 O 200 ␮L Tris–HCl (pH 7.2) was added to the cells, and a coverslip was applied and sealed with nail polish before epifluorescence microscopy. Slides were examined under Olympus BX 50 epifluorescence microscope equipped with a 100 W high-pressure mercury lamp, U-MWIB and U-MWG filter cubes. Images were captured using a Spot RT charged coupled device (CCD) camera having special software supplied by the camera manufacturer (Diagnostic Instruments Ltd., UK). The images were processed and analyzed using Image-Pro Plus version 6.3 software (Media Cybernetics, USA).

compare the means for each exposure (applied to non-zero results). Pearson’s correlation was used to identify relationships between variables. 3. Results and discussion 3.1. Serum bottle test 74.0 ± 4.4 mL methane was produced every 10 day in control bottles. Utilization of 1.0 mmol of acetate in microbial metabolism was reported to produce around 0.97 mmol of methane. According to this, 82.3 mL methane should have been generated. About 10% loss in the methane generated could be occurred because of experimental error during serum bottle operation where gas losses are usual during pressure measurements. Methane production was negatively affected with isopropanol concentration (r = −0.698, p < 0.05). At the end of first exposure, on day 10, 35.0%, 65.0%, 91.5% and 100% inhibitions in methane production were obtained for concentrations of 0.1 M, 0.5 M, 1 M and 2 M, respectively (Fig. 1). IC50 of IPA in methane generation was calculated as 270 mM in first run. Second exposures to IPA resulted in increased inhibitions of 56.8%, 74.3%, 95.7% and 100% for IPA concentrations of 0.1 M, 0.5 M, 1 M and 2 M, respectively. After 3rd exposures, 2.57 mL and 0.30 mL methane productions were observed in 0.1 M and 0.5 M IPA concentrations whereas they were below detectable limit for concentrations higher than 0.5 M. Methane productions were given in Fig. 2. 3.2. Acetyl-CoA mRNA level This study for the first time, investigated the expression levels of acetyl-CoA synthetase genes of M. concilii, which codes for the protein that encodes conversion of acetate to acetyl-CoA. This conversion is a key step in acetoclastic methanogenesis in anaerobic processes. The mRNA copy numbers for control reactor were 1.23 ± 0.62 × 106 during feeding with acetate and were decreasing with IPA concentrations (r = −0.527, p < 0.05). For 0.1 M IPA added reactor, the gene copy numbers were 2.56 × 105 and 4.41 × 105 at the 1st and 2nd exposures, and no mRNA copy could be detected after the 3rd exposure. The reason of this increase in the copy

2.10. Statistical analysis Statistical analyses were conducted in SPSS 11.5 (SPSS Inc., USA). Analysis of variation was investigated using a one way ANOVA. Multiple comparisons were performed using a post hoc Tukey test (Tukey, 1953). The test was used to examine the differences in gene expression between control and IPA added reactors. In addition, to find out whether the difference in gene expression between parallel serum bottles was significant, we used student’s t-test to

Fig. 1. Methane inhibition percentages in solvent added serum bottles.

98

B. Ince et al. / Journal of Biotechnology 156 (2011) 95–99

Fig. 2. Methane productions during the test.

Fig. 3. Number of mRNA transcripts detected in real-time PCR.

numbers after second exposure than first exposure for 0.1 M IPA could be the degradation of IPA to acetone and formation of acetate as an intermediary in acetone degradation (Platen and Schink, 1987). For 0.5 M, 1.0 M and 2.0 M IPA added reactors, the copy numbers were 1.36 × 105 , 9.61 × 104 and 4.82 × 104 for the 1st exposure. No acetyl-CoA synthetase expression could be detected after 2nd and 3rd exposures for higher molarities. The elevated decrease in expression level of acetyl-CoA synthetase of M. concilii in the third exposure could be explained by both the inhibitory effect of IPA and higher affinity of Methanosarcina spp. to acetate for higher acetate concentrations as non-converted acetate was accumulated (Jetten et al., 1992; Min & Zinder, 1989). Acetyl-CoA synthetase gene expression levels were given in Fig. 3. The PCR amplification efficiencies were not lower than 95%. In the literature, most of the variability in Q-PCR assays has been described based on CT values and gene copy numbers (Dionisi et al., 2003; Smith et al., 2006; Saikaly et al., 2007). Based on gene copy numbers, CVs were calculated for the intra-assay of three replicates (within an experiment) and interassay reproducibility was evaluated by running same reaction in two separate plates (between experiments) to evaluate the reproducibility of the Q-PCR assay. Low CVs for both the inter- (0.25–12.5%) and intra-assay variability (0.46–5.42%) indicate good reproducibility of the Q-PCR reaction.

Fig. 4. Mean fluorescent intensities of cells at the end of test.

added reactors were quantified relatively by FISH. In control reactors, 77% of the total cells were metabolically active. 56% of the active cells belonged to domain Bacteria while 44% of them were Archaea. Methanosaeta spp. were detected as 45% of the active archaeal cells. Table 3 shows active cell percentages in reactors. In isopropanol added serum bottles, no significant change in active cell percentages was obtained. This is consistent with a previous study that diversity of Archaea remained unaltered during the different phases of an experiment assessing the effect of another solvent, toluene, concentrations between 20 mM and 100 mM on

3.3. Microbiological activity At the end of test, active total bacterial and archaeal cells as well as Methanosaeta spp. in control, 0.1 M and 1.0 M isopropanol Table 3 Active cell percentages at the end of 30 days digestion. Control Active cells Active bacterial cells Active archaeal cells Active Methanosaeta spp.a a

77.2 43.2 33.5 45.1

± ± ± ±

0.1 M isopropanol added reactors 4.0% 2.0% 1.2% 0.9%

76.0 42.1 34.0 45.0

± ± ± ±

1 M isopropanol added reactors

1.1% 0.8% 1.3% 0.2%

76.3 42.1 34.2 43.8

± ± ± ±

1.1% 0.8% 1.3% 0.2%

Relative percentage in active archaeal cells.

Table 4 Correlations between isopropanol molarity, methane production and microbiological data. Isopropanol molarity Isopropanol molarity Methane production Acetyl-CoA transcripts Bacterial rRNA Archaeal rRNA Methanosaeta spp. rRNA a b

p < 0.05. p < 0.01.

−0.698a −0.527a N.S. −0.936a −0.954a

Methane production

Acetyl-CoA transcripts

Bacterial rRNA

Archaeal rRNA

Methanosaeta spp. rRNA

−0.698a

−0.527a 0.839a

N.S. N.S. N.S.

−0.936a 0.722a 0.702a N.S.

−0.954a 0.747a 0.726a N.S. 0.940b

0.839a N.S. 0.722a 0.747a

N.S. 0.702a 0.726a

N.S. N.S.

0.940b

B. Ince et al. / Journal of Biotechnology 156 (2011) 95–99

a horizontal-flow anaerobic immobilized biomass (HAIB) reactor (Cattony et al., 2005). In addition to number of active cells, fluorescent intensities were also recorded. Fluorescent intensity can be a better indicator of cell activity. While the intensity of bacterial probe binded cells did not significantly affected by isopropanol, fluorescent intensities of total Archaea and Methanosaeta spp. were decreased by 12% and 51% for IPA concentrations 0.1 M and 1.0 M, respectively (Fig. 4). There was a nearly perfect correlation between rRNA level of Methanosaeta cells and total archaeal cells. Fluorescence intensity of Methanosaeta cells, which were highly correlated with acetylCoA synthetase mRNA level, were found decreasing with increasing IPA concentrations (Table 4). 4. Conclusions Results indicated that there is a negative impact of increasing isopropanol concentrations on methane production and acetylCoA expression level. Acetyl-CoA synthetase which plays a key role in methane production could not be detected in iso-propanol added reactors after the second and third exposures for isopropanol concentrations over 0.1 M. Even though no significant effect was observed on the numbers of active Methanosaeta spp., fluorescent intensities were decreased. These results indicated that IPA has an inhibitory effect on the acetoclastic methane production pathway. In future, more detailed examination such as expression level of specific enzymes which have a role on the previous steps of acetoclastic methanogenesis would be done to clarify the adverse effect of IPA. Acknowledgements This work was supported by grants from the Foundation of the Scientific and Technological Research Council of Turkey (Project No. 106Y241), and Research Fund of Bogazici University (Project No. 01M102). References American Public Health Association (APHA), 2003. Standard methods for the examination of water and wastewater, 20th ed. American Public Health Association, Washington, DC. Amann, R.I., Binder, B.J., Olson, R.J., Chisholm, S.W., Devereux, R., Stahl, D.A., 1990. Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl. Environ. Microbiol. 56, 1919–1925. Cattony, E.B.M., Chinalia, F.A., Ribeiro, R., Zailat, M., Foresti, E., Varesche, M.B.A., 2005. Biotechnol. Bioeng. 91, 244–253. Chen, Y., Cheng, J.J., Creamer, K.S., 2007. Inhibition of anaerobic digestion process: a review. Bioresour. Technol. 99, 4044–4064.

99

Dionisi, H.M., Harms, G., Layton, A.C., Gregory, I.R., Parker, J., Hawkins, S.A., 2003. Power analysis for real-time PCR quantification of genes in activated sludge and analysis of the variability introduced by DNA extraction. Appl. Environ. Microbiol. 69, 6597–6604. Eggen, R.I.L., Gerrling, A.C.M., Jetten, M.S.M., de Vos, W.M., 1991. Cloning, expression, and sequence analysis of the genes for carbon monoxide dehydrogenase of Methanothrix soehngenii. J. Biol. Chem. 266, 6883–6887. Ferry, J.G., 1992. Biochemistry of methanogenesis. Crit. Rev. Biochem. Mol. Biol. 27, 473–503. Gujer, W., Zehnder, A.J.B., 1983. Conversion processes in anaerobic digestion. Water Sci. Technol. 15, 127–167. Jetten, M.S.M., Stams, A.J.M., Zehnder, A.J.B., 1992. Methanogenesis from acetate: a comparison of the acetate metabolism in Methanothrix soehngenii and Methanosarcina spp. FEMS Microbiol. Rev. 88, 181–198. Min, H., Zinder, S.H., 1989. Kinetics of acetate utilization by two thermophilic acetotrophic methanogens: Methanosarcina sp. strain CALS-1 and Methanotrix sp. strain CALS-1. Appl. Environ. Microbiol. 55, 488–491. Nielsen, P.H., Andreasen, K., Lee, N., Wagner, M., 1999. Use of microautoradiography and fluorescent in situ hybridisation for characterization of microbial activity in activated sludge. Water Sci. Technol. 39, 1–9. OECD Organization for Economic Co-operation and Development, 2006. OECD Guidelines for the Testing of Chemicals: Anaerobic Biodegradability of Organic Compounds in Digested Sludge by Measurement of Gas Production. Olsen, G.J., Lane, D.J., Giovannoni, S.J., Pace, N., Stahl, D.A., 1986. Microbial ecology and evolution: a ribosomal RNA approach. Annu. Rev. Microbiol. 40, 337–365. Platen, H., Schink, B., 1987. Methanogenic degradation of acetone by an enrichment culture. Arch. Microbiol. 149, 136–141. Raskin, L., Stromley, J.M., Rittmann, B.E., Stahl, D.A., 1994. Group-specific 16S rRNA hybridization probes to describe natural communities of methanogens. Appl. Env. Microbiol. 60, 1232–1240. Saikaly, P.E., Barlaz, M.A., de los Reyes III, F.L., 2007. Development of quantitative real-time PCR assays for detection and quantification of surrogate biological warfare agents in building debris and leachate. Appl. Environ. Microbiol. 73, 6557–6565. Sekiguchi, Y., Kamagata, Y., Nakamura, K., Ohashi, A., Harada, H., 1999. Fluorescence in situ hybridization using 16S rRNA-targeted oligonucleotides reveals localization of methanogens and selected uncultured bacteria in mesophilic and thermophilic sludge granules. Appl. Environ. Microbiol. 65, 1280–1288. Smith, C.J., Nedwell, D.B., Dong, L.F., Osborn, A.M., 2006. Evaluation of quantitative polymerase reaction-based approaches for determining genecopy and gene transcript numbers in environmental samples. Environ. Microbiol. 8, 804–815. Smith, K.S., Ingram-Smith, C., 2007. Methanosaeta, the forgotten methanogen? Trends Microbiol. 15, 150–155. Speece, R.E., Parkin, G.F., 1983. The response of methane bacteria to toxicity. In: Proceedings of the 3rd International Symposium on Anaerobic Digestion, Boston, MA. Stahl, D.A., Amann, R., 1991. Development and application of nucleic acid probes. In: Stackebrant, E., Goodfellow, M. (Eds.), Nucleic acid techniques in bacterial systematics. John Wiley and Sons Ltd, Chichester, England, pp. 205–248. Tukey, J.W.,1953. The problem of multiple comparisons. In: The Collected Works of John W. Tukey, vol. VIII, Multiple Comparisons: 1948–1983. Chapman and Hall, New York, p. 300. Valcke, D., Verstraete, W., 1983. A practical method to estimate the actoclastic methanogenic biomass in anaerobic reactors. J. Water Pollut. Control Fed. 55, 1191–1195. Wallner, G., Amann, R., Beisker, W., 1993. Optimizing fluorescent in situ hybridization with rRNA-targeted oligonucleotide probes for flow cytometric identification of microorganisms. Cytometry 14, 136–143. Weiss, D.S., Thauer, R.K., 1993. Methanogenesis and the unity of biochemistry. Cell 72, 819–822. Wolfe, R.S., 1991. My kind of biology. Annu. Rev. Microbiol. 45, 1–35. Zinder, S., 1993. Physiological ecology of methanogens. In: Ferry, J.G. (Ed.), Methanogenesis. Chapman and Hall, New York, NY, pp. 128–206.