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Methanogenic population structure in a variety of anaerobic bioreactors

Sharon McHugh , Micheal Carton , Thérèse Mahony , Vincent O'Flaherty
DOI: http://dx.doi.org/10.1016/S0378-1097(03)00055-7 297-304 First published online: 1 February 2003

Abstract

The methanogenic community structures of six anaerobic sludges were examined using culture-independent techniques. The sludges were obtained from full-scale and laboratory-scale bioreactors, treating a variety of low- and high-strength, simple and complex wastewaters at psychrophilic (10–14°C), mesophilic (37°C) and thermophilic (55°C) temperatures. Amplified rDNA restriction analysis identified 18 methanogenic operational taxonomic units in the six samples. 16S rRNA gene sequencing and phylogenetic reconstruction demonstrated that five separate groups of methanogens were represented with Methanosaeta-like species dominant in all sludges, but particularly in samples from a psychrophilic bioreactor treating low-strength synthetic sewage (75% of all clones detected).

Keywords
  • Methanosaeta
  • Methanogenic
  • 16S rRNA
  • Amplified rDNA restriction analysis
  • Psychrophilic
  • Anaerobic digestion
  • Granular sludge

1 Introduction

The social and economic requirement for low-cost, low-technology wastewater treatment technologies has prompted study of more advanced levels of wastewater treatment, including the development of novel reactor designs and operating conditions. Anaerobic digestion is a biological treatment process that has many advantages over the more conventional aerobic processes including low levels of excess sludge production, low space requirements and the production of valuable biogas [1]. The currently most widely applied anaerobic bioreactors for industrial wastewater treatment are granular sludge-based systems such as the upflow anaerobic sludge blanket (UASB), the expanded granular sludge bed (EGSB) [1] and the anaerobic hybrid reactor [2]. Stable and efficient operation of these anaerobic bioreactors is primarily dependent on the growth and maintenance of sludge granules containing all the microbial trophic groups necessary for complete methanogenesis of the organic constituents of the wastewater [3,4].

Despite widespread application of granular sludge bioreactors such as the UASB, and fixed-film systems such as the anaerobic filter [5], knowledge of the structure, function and biological properties of the microbial communities involved is incomplete. The emergence in recent years of molecular microbiological techniques has revealed new levels of diversity within the microbial populations present in anaerobic reactors [68], soils [9] and sediments [10], which would not be possible using traditional culture-based techniques. However, much information remains to be elucidated, in particular on the nature of the microbial populations present in anaerobic bioreactors operating under new regimes of temperature and wastewater type. High-quality microbiological information will provide an invaluable tool in the design and process control of these new anaerobic digestion applications.

One of the most promising future areas of anaerobic digestion technology is the possibility of low- or ambient-temperature reactor operation [11,12]. This development, if established, will provide a major technological benefit, as the need to heat anaerobic bioreactors to mesophilic (30–40°C) or thermophilic (50–60°C) temperatures for treatment of the wide variety of industrial wastewaters discharged at low or ambient temperatures would be removed, thus greatly enhancing the economics of the process [11]. The principal factor allowing operation at low temperatures has been the development of granular bioreactor designs such as the EGSB, which compensate for the low biogas production rate by increased mixing through effluent recycle and elevated liquid upflow velocities [11]. Although results from the very few reactor trials carried out to date have been positive [12,13], as yet virtually nothing is known about the microbial community structure which will develop during low-temperature operation, or whether the growth and maintenance of granular sludge is feasible at these temperatures. In this regard, the dominance or otherwise of Methanosaeta sp. during low-temperature operation will be very important as these filamentous, acetate-utilising methanogens are widely accepted as having a crucial role in the formation and maintenance of stable anaerobic granules [3,4,14]. The comparison of the methanogenic communities of bioreactors operating at psychrophilic temperatures with mesophilic or thermophilic systems will thus provide a valuable indicator of the potential for the formation and maintenance of stable granular sludge.

The aim of this study was to examine the methanogenic community structure of a range of full-scale and laboratory bioreactors, including a laboratory-scale psychrophilic anaerobic hybrid reactor, originally seeded with mesophilic sludge. This was accomplished by amplified rDNA restriction analysis (ARDRA), 16S rDNA clone library construction, DNA sequence analysis and phylogenetic reconstruction of amplified euryarchaeotal gene sequences from the laboratory-scale psychrophilic reactor and five granular and non-granular anaerobic sludge samples obtained from mesophilic and thermophilic full-scale and laboratory-scale bioreactors treating a variety of wastewater types.

2 Materials and methods

2.1 Source of biomass

Six sludge samples from anaerobic reactors treating a variety of wastewaters were studied, including three full-scale samples: sludge A from an 8000-m3 fully packed reactor treating citric acid production wastewater (molasses-based wastewater, chemical oxygen demand (COD): 4 kg m−3; organic loading rate (OLR): 4 kg m−3 day−1; pH: 7–8) at 37°C (Archer Daniels and Midland, Ringaskiddy, Co. Cork, Ireland) [15]; sludge B from a downflow anaerobic filter treating milk processing wastewater (lactose, proteins and lipids (85:14:1 on a COD basis), COD: 5 kg m−3; OLR: 5 kg m−3 day−1; pH: 7.0) at 30°C (Kerry Ingredients, Listowel, Co. Kerry, Ireland) and sludge C from a granular sludge-based internal circulation reactor treating potato processing wastewater (starch-based wastewater, COD: 10 kg m−3; OLR: 40 kg m−3 day−1; pH: 7–7.3) at 37°C (Paques, The Netherlands).

Samples D–F were obtained from the granular sludge beds of laboratory-scale anaerobic hybrid reactors (AHR). The AHR were identical in size and were seeded with the same mixture of mesophilic granular sludges, obtained from a number of full-scale UASB digesters treating a variety of industrial wastewaters (Paques, The Netherlands). The seed sludge had been in long-term storage at 4°C prior to inoculation. The AHR were started up at the same time and operated for periods of 379–500 days. The sludge samples were removed from the reactors at the conclusion of the trials and immediately processed. AHR D treated a volatile fatty acid mixture (acetate, propionate, butyrate (1:1:1 on a COD basis); COD: 10 kg m−3; OLR 20 kg m−3 day−1; pH: 7.6–7.8) at 37°C [16]. AHR E treated a molasses wastewater (COD: 10 kg m−3; OLR: 48 kg m−3 day−1; pH: 7.0) at 55°C [17], and AHR F treated a synthetic sewage wastewater containing glucose and peptone as carbon sources [18] (COD: 0.45 kg m−3; OLR: 0.56 kg m−3 day−1; pH: 7–7.6) at 10–14°C [19]. Stable and efficient reactor performance was achieved in each, with COD removal efficiencies in excess of 90% observed at the applied loading rates [16,17,19].

2.2 DNA extraction

Reactor sludge was sampled in triplicate and DNA was extracted by using a modified version of the protocol developed by Zhou et al. [20]. Sludge samples were initially crushed using pestle and mortar grinding, and 500-µl aliquots of each were added to sterile microfuge tubes along with 1 ml of extraction buffer (100 mM Tris–HCl (pH 8.0), 100 mM sodium EDTA (pH 8.0), 100 mM sodium phosphate (pH 8.0), 1.5 M NaCl, 1% cetyltrimethyl-ammonium bromide) and 150 µl of 10% sodium dodecyl sulfate. The samples were incubated in a 70°C waterbath for 1.5 h with gentle end-over-end inversion every 15 min. After centrifugation at 10 000×g for 10 min, the supernatant was collected and added to equal volumes of 24:1 chloroform:isoamyl alcohol. After centrifugation at 10 000×g for 10 min the aqueous phase was removed and DNA was precipitated using 0.6 volumes of 100% isopropanol overnight at 20°C. The crudely extracted nucleic acids were pelleted by centrifugation at 10 000×g for 25 min, ethanol-washed and then resuspended in 100 µl of sterile deionised water. Extracted DNA was visualised after electrophoresis on a 1% TBE (2.16% w/v Tris, 1.1% w/v boric acid, 0.13% w/v EDTA) gel containing 1 µg ml−1 ethidium bromide.

2.3 Determination of cell lysis efficiency

Bacteria in sludge samples were observed according to the method of Bitton and co-workers [21] with the exception that Sybr-Gold (Molecular Probes, USA) was used instead of acridine orange. A sample (0.1 g) of crushed sludge was suspended in 500 µl of filter-sterilised water. A 100-µl aliquot of this was added to 10 ml of filter sterilised water. An 8-ml volume of the diluted sample was filtered onto black Isopore® (Whatman) membrane filters and 200 µl of Sybr-Gold (10×stock solution in TE buffer, pH 8) was added to the remaining 2 ml of diluted sample and left for 5 min. The rest of the sample was then drawn onto the filter that was mounted onto a glass slide and a minimum of mineral oil was added under a coverslip. The samples were viewed using a Nikon Optiphot-2UV microscope fitted with a 100-W mercury bulb, a B-2A excitation filter for blue light, a 100× planar objective lens and 100× eyepieces.

2.4 Generation of 16S rDNA clone library

Euryarchaeota-specific 16S rDNA was amplified by performing polymerase chain reaction (PCR) in a thermocycler (Perkin-Elmer, Foster City, CA, USA) with forward primer 21F (5′-TTCCGGTTGATCCYGCCG-3′) and reverse primer Eury 498R (5′-CTTGCCCRGCCCTT-3′) [22,23]. Reaction mixtures (50 µl) contained 3 mM MgCl2, 1×NH4 buffer (16 mM (NH4)2SO4, 67 mM Tris–HCl (pH 8.8 at 25°C), 0.01% Tween-20), 200 µM dNTP (dATP, dCTP, dGTP, dTTP), 100 ng of each primer, 200 ng template DNA and 0.5 U Taq DNA polymerase. The PCR reactions were carried out under the following conditions: denaturation at 95°C for 1 min, annealing of primers at 45°C for 1 min and extension at 72°C for 1 min for a total of 30 cycles, followed by 10 min of extension at 72°C. For optimal amplification of sludges A and C touchdown PCR was required (53°C–46°C; 1 cycle at 1°C increments: 45°C; 22 cycles). Controls containing no DNA were also used to determine whether contaminants were being amplified. Each PCR product was visualised after electrophoresis on 1% agarose TBE gel containing 1 µg ml−1 ethidium bromide.

PCR products were ligated into the plasmid vector pCR 2.1-TOPO (Novagen) and the hybrid vectors were used to transform Escherichia coli TOP 10 competent cells by following the manufacturer's instructions. Transformants were screened using blue-white selection on Luria–Bertani agar plates containing 40 µg ml−1 X-Gal (5-bromo-4-chloro-3-indolyl-β-galactopyranoside) and 50 µg ml−1 kanamycin. Clone libraries were constructed by growing 100 randomly selected white colonies derived from each sludge sample overnight in 10 ml of LB broth medium containing 50 µg ml−1 kanamycin.

2.5 ARDRA

Sixty clones from each library (total 360) were screened, to determine whether they contained the insert of appropriate size, by carrying out PCR using 1 µl of the overnight broth cultures. M13 forward and reverse primers were used at a concentration of 100 ng, with the other PCR reagents as described previously. PCR was performed according to the following protocol: one cycle of 95°C for 10 min, 30 cycles of 95°C for 1 min, 55°C for 1 min, then 72°C for 1 min and a final cycle of 72°C for 10 min.

Five microlitres of PCR products obtained from the insert-containing clones (200 in total) from each sludge sample were digested with 1 U of the restriction endonuclease Hae III for 3 h at 37°C. The resulting DNA fragments were resolved by electrophoresis on 3.5% high-resolution agarose, containing 1 µg ml−1 ethidium bromide. Banding patterns were compared by visualisation and grouped into operational taxonomic units (OTUs) as described by Moyer et al. [24].

2.6 Partial rRNA gene sequencing and phylogenetic analysis

Inserts from clones representing 16 of the identified OTUs were sequenced. Template DNA was prepared from overnight cultures of positive transformants using an alkaline miniprep kit (Qiagen). Sequencing was performed on a Licor gel sequencer using vector-specific primers (MWG Biotech, Milton Keynes, UK). The resultant sequence data were compared to nucleotide databases using basic local alignment search tool (BLAST) as described previously [25]. The presence of chimaeric amplification products was screened for using the Ribosomal Database Project (RDP) Check-Chimera software package [26], none were present in the data generated from this study. Sequence data for 15 of the retrieved sequences were manually aligned to euryarchaeotal sequences obtained from the RDP [26]. The phylogenetic inference package Paup* 4.0b8 was used for all phylogenetic analysis [27]. The partial 16S rDNA gene sequences determined in this study were deposited in the GenBank database under accession numbers AY032982AY032996 and AF543691 with the generic name of ASDS (Anaerobic Sludge Diversity Study) 1–11, 13, 14, 16–18.

3 Results and discussion

Of the 200 clones from the six sludge samples analysed by ARDRA, 18 different OTUs were identified (Table 1). Sludges A and B contained eight distinct banding patterns, sludges C, E and F contained nine, while sludge D contained five OTUs. Two of the OTUs observed were identical to those identified and sequenced in a previous study (MUAHR 2 and 9 [17]) while the novel 16S rDNA inserts corresponding to the remaining OTUs were sequenced and classified in this study.

View this table:
1

Distribution of OTUs detected in the six anaerobic bioreactor sludge samples

Sludge sampleOTUTotal
123456789101112131415161718
A65116121133
B11875311137
C3315624126
D83513130
E981011211134
F912581121140
Total47393424218323522411211200

Although 18 OTUs had been identified by visualisation, sequence analysis revealed strong similarities between several of the OTUs, indicating that the ARDRA method is effective in detecting small differences in sequence between microbial species. Virtual analysis of the sequences, carried out by manually locating the enzyme restriction site and generating the resultant sequence fragments, revealed congruence between the OTUs defined on the basis of sequence and the particular ARDRA profile obtained. Although the size of the amplified PCR products used for ARDRA is relatively short (<500 bp), the number of OTUs obtained is comparable to those found in other studies [28,29], with all sludges (except sludge D) containing either eight or nine distinct OTUs. The use of a single restriction enzyme (Hae III) resulted in the generation of 18 OTUs, which correlates to the 21 archaeal OTUs obtained when two enzymes were used in a similar study detailing the microbial populations within an anaerobic bioreactor [30]. Indeed, the use of two enzymes might result in the generation of a large number of very specific and unique OTUs, greatly increasing the amount of sequencing and subsequent analysis required.

BLAST search results indicated that all the clones were assigned to the class Euryarchaeota, and all were close relatives of the methanogens. Phylogenetic reconstruction was carried out to determine the relationship of the OTUs to previously described 16S rDNA sequences (Fig. 1). Clones obtained in the study divided easily into five different clusters (I–V), with clones affiliated to Methanococcus (I), Methanobacteriales (II) Methanomicrobiales (III), Methanosarcina (IV) and Methanosaeta (V) found among the six sludge samples. Methanosaeta-like organisms were predominant in all six samples (Table 2). While over-extrapolation of trophic function from sequence data should be avoided, the presence of OTUs with a sequence divergence of less than 3% at the 16S rDNA level from cultivated organisms allows supposition of a role for the corresponding organisms [8]. ASDS 1 and 2 were the most frequently detected clones in all samples, comprising approximately 52% of clones in sludges B, E and F and 42.5% of all clones analysed. These were closely related to Methanosaeta concilii and were the only clones present in all six samples. ASDS 4, 15 and 17 were also affiliated with Methanosaeta and accounted for approximately 20% of the clones in each of the four samples from which they were retrieved. ASDS 15 was found to be identical to MUAHR 1 and 2 which were clones identified from a laboratory-scale molasses-fed AHR in a previous study [17]. In total, 111 Methanosaeta-like clones were found among the 200 analysed (56%).

1

Phylogenetic tree constructed with evolutionary distances calculated based on the Kimura-2 model and the neighbour-joining method of Saitou and Nei [31]. Three Crenarchaeotal sequences (Sulfolobus sp.) were defined as outgroups during phylogenetic reconstruction. Numbers at nodes represent bootstrap values (100 replicates).

View this table:
2

Relative abundance (%) of 16S rRNA gene sequence clones detected in the six anaerobic bioreactor sludge samples

Methanogenic clusterSludge sample
ABCDEF
(I) Methanococcus (OTU 5, 13, 14)3.040.743.32.5
(II) Methanobacteriales (OTU 3, 9, 10, 11, 12, 16)39.427.011.245.517.5
(III) Methanomicrobiales (OTU 8)5.0
(IV) Methanosarcina (OTU 6, 7, 18)6.121.63.02.5
(V) Methanosaeta (OTU 1, 2, 4, 15, 17)51.551.448.156.751.572.5
Total100100100100100100
  • <90% similarity.

The predominance of methanogens closely related to Methanosaeta soehngenii or M. concilii in mesophilic anaerobic reactors has been widely reported and these filamentous organisms are regarded as being important for the formation and maintenance of granular sludge [32,33]. Growth of these obligate acetate-utilising organisms is favoured over other acetoclastic methanogens such as Methanosarcina sp. by low levels of acetate, due to their low Ks value for this substrate [34]. The predominance of Methanosaeta-like clones in all six samples is consistent with the sludges being developed in stable reactors maintaining high removal efficiencies and thus low acetate concentrations.

With respect to the key area of psychrophilic methanogenesis, very few data are as yet available. In anoxic rice field soils methanogenesis was reported as being channeled predominantly through acetate, and specifically through Methanosaeta sp. at 15°C, while a predominance of Methanosarcina sp. was noted at 30°C [9]. This study found that 75% of the clones found in sludge F, the psychrophilic reactor sample, were assigned to the Methanosaeta group. Acetoclastic methanogenesis is known to be a key step in psychrophilic anaerobic digestion with previous studies showing acetate produced by homoacetogens from H2 as the main precursor of methane [35]. Lay et al. [36] found a substantially higher number of acetate-utilising methanogens in lake sediments under psychrophilic conditions than hydrogen utilisers.

With respect to the other methanogenic groups detected, clones ASDS 3, 9, 10, 11 and 16 (II) showed significant similarity to each other (>98.9%) and grouped together with members of the order Methanobacteriales. ASDS 3 was found in five of the six samples and comprised over one-third of the clones from both sludges A and E (Table 2), while ASDS 12 also grouped with Methanobacteriales and was very closely related to Methanobrevibacter formicicum. In total, this group accounted for 24% of clones analysed. Methanobacteriales is an order of mainly rod-shaped methanogens which grow by CO2 reduction and are frequently detected in anaerobic digesters [28]. It is likely that these clones represent the majority of hydrogenophilic methanogens in the five sludges where they were detected.

Surprisingly, clones showing strong similarity to the group Methanosarcina, and in particular to Methanomethylovorans (ASDS 6, 7 and 18; IV), were only detected in three of the sludges (5.5% of total clones; Table 2). OTU 8 (III) was unique to the psychrophilically grown sludge F and was affiliated with the group Methanomicrobiales, with the most closely related organisms being a previously described archaeon clone TAO2 also isolated from an anaerobic reactor [38] and the uncultured archaeon WCHD3-07 retrieved from a contaminated aquifer [39]. ASDS 5, 13 and 14 were affiliated to the group Methanococcus, and ASDS 5 was identical to clone MUAHR 9, previously isolated from a molasses-fed methanogenic upflow AHR reactor [17]. These clones form a distinct grouping (I), only distantly related to the closest Methanococcus species (<90% sequence similarity or distance values of over 0.24), and may be a distinct, but as yet uncharacterised, genus (Fig. 1). This will require further investigation by whole gene sequencing and, if possible, isolation and culture. Cluster I clones represented 15% of total clones studied, with ASDS 5 representing 43.3% of sludge D and the only non-Methanosaeta-like clone present in the sample. This suggests that ASDS 5 comprises the hydrogenotrophic population present in sludge D and is responsible for methane formation from H2 within the sludge.

It is apparent that many of the sequences obtained in this study were related closely only to uncultured clones for which physiological and other properties remain unknown. This illustrates the incomplete nature of the microbial database and also the need for further basic research in this area. A number of studies have been carried out to determine whether methanogenic populations present in anaerobic sludges are governed by the intrinsic characteristics of the ecosystems themselves or simply arise from the operation of the bioreactors. It was hypothesised that the populations resulted from selective forces, such as temperature and/or operating conditions, acting on the microbes in the original inoculum over a period of time [40]. This would lead to the development of very different microbial populations within different bioreactors.

The results of the present study support this view as the distribution of clones recovered within each of the samples varied. Although all three lab-scale AHR were inoculated with the same seed sludge, the methanogenic populations present in samples D, E and F differed considerably, presumably due to a combination of differences in temperature, OLR and hydraulic retention time as well as feed composition. Sludge D treated a simple volatile fatty acid mix wastewater consisting of acetate, propionate and butyrate [16] and had the lowest number of methanogenic OTUs (5), all of which corresponded to either one acetoclastic methanogen — cluster V (Methanosaeta-like) — or one hydrogenophilic methanogen — cluster I. This is compared to the other five sludges, all of which had treated more complex wastewaters and had more than two groups of methanogens present (Table 2). Previous studies reported that sludge from thermophilic bioreactors contain less methanogenic diversity than those obtained from mesophilic reactors and that Methanosaeta sp. were not as prevalent as in mesophilic systems [40], and indeed were gradually lost from the system during thermophilic operation [32], an observation that was not supported by the results (using sludge E) of this study. However, further variations in wastewater content, including the presence of sulfate in the influent, may influence the community structure in a fashion not observed here [2,41,42]. The psychrophilic anaerobic bioreactor sludge F, although obtained after over 300 days of psychrophilic reactor operation, did not display any less apparent methanogenic diversity. Two acetoclastic methanogenic groups (IV, V) and three hydrogenotrophic groups (I, II, III) were represented, with a unique group (III) present.

The sludge samples from the full-scale fixed-film reactors, sludges A and B, were very similar to the full-scale granular sludge sample C, and to all laboratory-scale reactors in terms of methanogenic community structure. In fact, the only distinguishing feature between the methanogenic community structure present in the three full-scale reactors was the absence of sequences related to the Methanococcus group in sludge B and the Methanosarcina group in sludge C. High levels of cluster IV (Methanosarcina-like) sequences and cluster I (Methanococcus-like) were present in sludges B and C, respectively.

Although the two lab-scale samples (E and F) had the greatest number of distinguishable OTUs (nine), sequence analysis revealed the majority of these to correspond to either Methanosaeta or Methanobacteriales (accounting together for 93.9% and 90% of sludge E and sludge F clones, respectively). This suggests that measuring diversity by the number of OTUs detected, sequences recovered and methanogenic groups present, rather than merely on percentage values, is important if we are to take into account the inevitable biases of the techniques employed.

DNA extraction may introduce several biases, and this is particularly true for the archaeal DNA extraction, as the Archaea have tough and unusual cell wall structures. The extraction method employed in this study, although effective, is milder than mechanical methods and was used to minimise shearing and thus the chance of chimeric DNA amplification [43]. The initial crushing of the sludge was used to recover a more representative DNA sample, and the diversity of sequences retrieved from the clone libraries (five distinct clusters) indicates that this was achieved. Potential PCR bias must also be taken into consideration during environmental microbiology studies [44]. The number of cycles used in this study (30) is greater than that recommended by Suzuki and Giovanni [45]. The number is, however, similar to those of other studies dealing with archaeal communities [29,46]. In addition it has been reported that in an environmental sample containing highly diverse template, the PCR-induced bias will be small [45]. The results obtained in this study also correlate with those found in similar studies, in particular in the prevalence of Methanosaeta sp. and Methanomicrobiales sp. as the main acetoclastic and hydrogenophilic methanogens. Although some researchers have reported a bias towards Methanosaeta-like species using cloning-based techniques [47], a similar scale of diversity has been obtained by immunotechnology [29,40] and oligonucleotide probe hybridisation [32,48]. Methanosaeta sp. were reported to comprise >90% of the archaeal population within an anaerobic bioreactor, with Methanosarcina accounting for less than 1%, using fluorescent in situ hybridisation [32]. The same technique was also used to show the predominance of Methanosaeta sp. in both mesophilic and thermophilic granules [48].

Until very recently, psychrophilic anaerobic digestion was not thought to be feasible because of microbiological constraints [11]. However, this opinion may have resulted from a lack of fundamental understanding of the microbiology of anaerobic digestion and although currently very little is known about the bacterial populations involved in anaerobic digestion at psychrophilic temperatures, initial reactor trials [11,13] supported by the findings of this study provide grounds for optimism. More basic research is required to develop this concept which would be an attractive treatment process for the many industrial wastewaters discharged at low temperatures, including those from the bottling, malting, brewery and soft drinks industries. To this end, molecular techniques are now an invaluable tool in elucidating members of complex microbial communities, and when used in conjunction with process engineering and physiological measurements they will allow a more extensive knowledge and understanding of the physiology and biochemistry of the microbial populations involved in anaerobic digestion. This information is necessary in order to fully understand the complex microbial interactions and dynamics that occur during the process so that increased efficiency and exploitation of anaerobic technology can be achieved. Regardless of the reason for the prevalence of Methanosaeta sp. in the psychrophilic AHR F in this study, their presence is significant as, along with the fact that the sludge F biomass presented as a well-settling granular sludge even after 300 days of reactor operation [17], it suggests that the maintenance of granular sludge, even at low-temperature operation during treatment of challenging low-strength wastewaters, such as domestic sewage, is feasible during long-term reactor operation. Moreover, if filamentous microbial forms prevail under low substrate concentrations as reported [37], the anaerobic granulation process may even be enhanced. These findings, along with promising reactor trials carried out at laboratory scale [1113], suggest that the application of low-temperature treatment to a variety of wastewaters may be feasible.

4 Conclusions

Due to the complex microbiological nature of the anaerobic digestion process, variations in reactor design, operating conditions and feed composition will result in changes within the microbial populations present in the system. Further insight into these changes is not only beneficial from a microbiological point of view but also in the development of novel reactor designs and modes of operation.

The predominance of Methanosaeta sp. in all sludges tested, irrespective of wastewater type or operating temperature, indicates the importance of this organism in the stable and efficient operation of an anaerobic bioreactor. The high number of Methanosaeta-like clones present in the psychrophilic sludge sample suggests that the maintenance of granular sludge is feasible at low temperatures, which is essential if the anaerobic treatment of wastewater at low temperatures is to be considered as a viable treatment option. However, much work remains to be done on the microbial populations present, including the eubacterial trophic groups in granular sludge, and the effect of low-temperature operation on these groups should be the next phase of research.

Acknowledgements

This work was supported by the Higher Education Authority of Ireland through the Biofilm Research Group, National Centre for Biomedical Engineering Science, National University of Ireland, Galway.

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View Abstract