MICROBIOLOGY ECOLOGY. Characterization of microbial biofilms in a thermophilic biogas system by high-throughput metagenome sequencing.

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1 RESEARCH ARTICLE Characterization of microbial biofilms in a thermophilic biogas system by high-throughput metagenome sequencing Antje Rademacher 1,2, Martha Zakrzewski 3, Andreas Schlüter 3, Mandy Schönberg 1, Rafael Szczepanowski 3, Alexander Goesmann 3, Alfred Pühler 3 & Michael Klocke 1 1 Leibniz-Institut für Agrartechnik Potsdam-Bornim e.v. (ATB), Abteilung Bioverfahrenstechnik, Potsdam, Germany; 2 Institut für Technischen Umweltschutz, Technische Universität Berlin, Berlin, Germany; and 3 Centrum für Biotechnologie (CeBiTec), Universität Bielefeld, Bielefeld, Germany MICROBIOLOGY ECOLOGY Correspondence: Michael Klocke, Leibniz-Institut für Agrartechnik Potsdam- Bornim e.v. (ATB), Abteilung Bioverfahrenstechnik, Max-Eyth-Allee 100, Potsdam, Germany. Tel.: ; fax: ; mklocke@atb-potsdam.de Received 12 May 2011; revised 16 November 2011; accepted 16 November Final version published online 20 December DOI: /j x Editor: Christoph Tebbe Keywords anaerobic digestion; 454-pyrosequencing; methanogenesis; microbial community. Introduction Abstract Cultivation of energy crops for biogas production was rising continuously during the last years. In 2010, renewable biomass, predominantly maize, was cultivated on ha land in Germany (Agency for Renewable Resources, 2010), which formed among others the basic material for about 5800 full-scale biogas plants generating 2300 MW of electric power (Agency for Renewable Resources, 2011). Up to now, most of these full-scale biogas plants are continuously stirred tank reactors (CSTRs) operating at mesophilic temperatures. In contrast, experimental biogas systems operated under thermophilic conditions achieve higher methane rates than comparable mesophilic systems (Dugba & Zhang, 1999). Furthermore, biogas systems, which are separated in a hydrolytic/acidogenic and methanogenic phase, possess some principle DNAs of two biofilms of a thermophilic two-phase leach-bed biogas reactor fed with rye silage and winter barley straw were sequenced by 454-pyrosequencing technology to assess the biofilm-based microbial community and their genetic potential for anaerobic digestion. The studied biofilms matured on the surface of the substrates in the hydrolysis reactor (HR) and on the packing in the anaerobic filter reactor (AF). The classification of metagenome reads showed Clostridium as most prevalent bacteria in the HR, indicating a predominant role for plant material digestion. Notably, insights into the genetic potential of plant-degrading bacteria were determined as well as further bacterial groups, which may assist Clostridium in carbohydrate degradation. Methanosarcina and Methanothermobacter were determined as most prevalent methanogenic archaea. In consequence, the biofilm-based methanogenesis in this system might be driven by the hydrogenotrophic pathway but also by the aceticlastic methanogenesis depending on metabolite concentrations such as the acetic acid concentration. Moreover, bacteria, which are capable of acetate oxidation in syntrophic interaction with methanogens, were also predicted. Finally, the metagenome analysis unveiled a large number of reads with unidentified microbial origin, indicating that the anaerobic degradation process may also be conducted by up to now unknown species. advantages, especially under those thermophilic conditions. In so-called two-phase systems, it becomes possible to adjust optimal parameters for each microbial conversion step, hydrolysis/acidogenesis, or methanogenesis. Hence, these systems are able to achieve higher biogas yields than comparable one-phase systems (Demirer & Chen, 2005). Additionally, a hydrolysis carried out by a leach-bed process makes a biomethanation of biomass with high fiber content possible. Although such twophase leach-bed systems comprise several advantages, the participating bacterial and archaeal communities were rarely analyzed. Only few studies focused on the microbial community structure within such reactor types converting sugar beet, grass/clover, triticale and grass silage, but only under mesophilic conditions (Cirne et al., 2007; Klocke et al., 2008; Wang et al., 2010). Despite the obvious advantages of thermophilic fermentations, only

2 786 A. Rademacher et al. technological studies of thermophilic two-phase leach-bed systems converting energy crops (Lv et al., 2010; Zielonka et al., 2010; Schönberg & Linke, 2011), which did not consider the inherent microbial communities, have been conducted. Furthermore, phase-separated systems converting renewable biomass favor the formation of microbial biofilms in contrast to mixed-phase processes such as CSTR (Bauer et al., 2008; Krakat et al., 2010). Within the system regarded in this study, the formation of a hydrolytic/ cellulolytic biofilm on the surface of the introduced crop material (silage) in the hydrolysis reactor (HR) as well as a more acidotrophic/methanogenic biofilm on the surface of the packing of the methanogenesis fermenter here constructed as anaerobic filter reactor (AF) can be assumed. The evolved biofilms, for instance, on the surface of the supplied crops are of major importance. Carbohydrate-degrading bacteria specifically adhere to hemicellulose and cellulose fibers, allowing their cellulosome complex to degrade such fibers (Bayer et al., 2004). Notably, members of the genus Clostridium are known for carbohydrate-degrading cellulosomes (Felix & Ljungdahl, 1993). In general, members of the taxon Bacteria possess the capability to accomplish the whole anaerobic degradation process starting with the plant biomass breakdown (hydrolysis), followed by the production of volatile fatty acids (VFA) (acidogenesis) and the formation of acetic acid and CO 2 /H 2 (acetogenesis). The latter products serve as precursors for methane production (methanogenesis) conducted by aceticlastic and hydrogenotrophic archaea, respectively (Deppenmeier et al., 1996). However, acetate can also be oxidized to CO 2 /H 2 by syntrophic acetate-oxidizing bacteria, which compete with aceticlastic methanogens for acetate (Ahring, 1995). In this study, we analyzed a two-phase thermophilic leach-bed biogas system focusing on the microbial communities fixed in biofilms in contrast to the vast majority of microbiological studies owing to their obvious merits on digestion and methanogenesis efficiency. For community analysis, a culture-independent 454-pyrosequencing approach was applied using a Genome Sequencer (GS) FLX Titanium System, which bears some principle advantages over other frequently applied methods, such as the cloning and sequencing of the 16S rrna gene (McHugh et al., 2004; Klocke et al., 2007; Kröber et al., 2009; Liu et al., 2009; Krakat et al., 2010; Nettmann et al., 2010). Although the construction of 16S rrna clone libraries is a valuable culture-independent method, it bears some drawbacks, such as the PCR bias and the relatively low number of clones that can be analyzed. Furthermore, the high-throughput method, namely 454-pyrosequencing, was recently used for a successful analysis of a production-scale biogas plant operating under mesophilic conditions (Krause et al., 2008a; Schlüter et al., 2008; Jaenicke et al., 2011). The aim of our approach was (1) to assess the bacterial and archaeal community and their interaction in this system, (2) to receive a first insight into the spatial distribution of the microbial community, and (3) to get a glimpse of the genetic potential for anaerobic biomass degradation and methanogenesis within the involved microorganisms. Therefore, we focused on the attached microbial community residing on the surface of the crop material within the HR and on the packing within the downstream AF representing the methanogenesis phase. Materials and methods Reactor setup and sampling Samples were taken from an experimental two-phase leach-bed biogas reactor system, which was operated since The two-phase system consisted of a gastight HR (net volume 100 L), an effluent storage reactor (net volume 60 L), and a downstream AF (net volume 30 L) with 390 packings (Bioflow 40; Rauschert, Judenbach-Heinersdorf, Germany) (Fig. 1). The HR was supplied discontinuously with 10 kg of rye silage and 1 kg of winter barley straw with a retention time of 21 days. Two internal circulations of leachate (Fig. 1) were applied to distribute nutrients and microorganisms and to maintain moisture and temperature level. Every day, an automatic gas analy- Fig. 1. Scheme of the two-phase thermophilic leach-bed system; HR, hydrolysis reactor (net volume 100 L); HS, effluent storage reactor (net volume 60 L); AF, anaerobic filter reactor (net volume 30 L); GB, gas bag (modified after Schönberg & Linke, 2011).

3 Microbial biofilms in thermophilic biogas systems 787 sis was conducted by a gas meter (Ritter, Bochum, Germany) and a biogas analyzer (Pronova, Berlin, Germany). All reactors were heated by a water jacket and operated at a mean temperature of 55 C. Altogether, the studied biogas fermentation process achieved a biogas yield of L kg 1 volatile solid (VS) (normalized to 0 C and 1013 hpa) with a methane content of 51%. In detail, the HR reactor achieved L kg 1 VS (CH 4 : L kg 1 VS) and the AF reactor L kg 1 VS (CH 4 : L kg 1 VS). During the first 5 days of fermentation, ph, chemical oxygen demand (COD) and VFA of the reactor effluent were measured once a day. Afterwards, the measured intervals were enlarged to 2 or 3 days. The ph ranged between 6.64 and 8.18 during the whole fermentation. The leachate of the HR reactor achieved a maximum of g L 1 COD and 7.06 g L 1 VFA during the start and 9.38 g L 1 COD and 0.06 g L 1 VFA at the end of the fermentation process. VFA were calculated as acetic acid equivalents (HAc eq.). Total ammonia (NH þ 4 -N + NH 3-N) concentration was determined four times during the fermentation process of 21 days (Table 1). The concentration of free ammonia was calculated with the following formula according to Anthonisen et al. (1976) and Nettmann et al. (2010): NH 3 -N = (total ammonia (NH þ 4 -N + NH 3- N) 9 10 ph )/(K b /K w + 10 ph ), where the total ammonia concentration is measured in g L 1 and K b /K w is e (6344/ (273 + t)) with t equal to the temperature in C. After a fermentation period of 21 days, two different samples were taken to investigate the microbial community residing in the reactor system. One mixed sample (approximately 50 g) was taken from the digestate of the HR containing the cellulolytic biofilm. Another sample was taken from the packing taken from the upper half of the AF reactor representing the methanogenic biofilm. Accordingly, the biofilm of this packing was detached using a sterile scalpel. To remove the leachate, which adheres to the analyzed packing, the packing was rinsed with sterile 19 phosphate-buffered saline before biofilm detachment. All samples were stored at 20 C until further processing. DNA extraction and purification The genomic DNA was extracted according to slightly modified protocols as published by Rheims & Stackebrandt (1999) and Klocke et al. (2008). Briefly, 10 subsamples of each 0.2 g of the methanogenic biofilm (AF) were washed twice with 1 ml sodium phosphate buffer (0.1 M, ph 7.0). Then, the samples were centrifuged at 3500 g for 15 min. The obtained cell pellets were resuspended in 1 ml of saline EDTA (0.1 M EDTA and 0.15 M NaCl). Afterwards, 10 subsamples of each 0.3 g of the digestate (HR), comprising the cellulolytic biofilm, were resuspended in 1 ml of saline EDTA without an additional washing step. In addition to the chemical and enzymatic cell lysis, a mechanical lysis step was also applied. Therefore, sterile glass beads (1 9 4 mm and mm in diameter) were added to the samples, which were homogenized by maximum speed on a test tube shaker (Heidolph, Schwabach, Germany) for 5 min. Afterwards, mg of polyvinylpolypyrrolidone and 30 ll of lysozyme (10 mg ml 1 ) were added, and the samples were incubated at 37 C for 60 min. Briefly, 30 ll of proteinase K (10 mg ml 1 ), 120 ll of SDS (10% w/v) and 120 ll of CaCl 2 (10 mm) were added for lysing the cells. After incubation at 65 C for 45 min, the samples were centrifuged at 6000 g for 10 min and the supernatants were adjusted to 0.7 M NaCl and 5% (w/v) CTAB (hexadecyltrimethylammonium bromide). Then, the samples were incubated at 65 C for 30 min on a heating block (Eppendorf, Hamburg, Germany). Subsequently, the DNA was extracted twice with an equal volume of Table 1. Operating conditions of the two-phase leach-bed biogas reactor system indicating important fermentation days Day of retention ph (HR; AF) Temperature (HR) ( C) NH 3 -N + NH þ 4 -N (AF) (g L 1 ) NH 3 -N (g L 1 ) NH þ 4 -N (g L 1 ) Acetic acid (HR) (mm) VFA (HR) (g HAc eq. L 1 ) COD (HR) (g L 1 ) ; ; NA NA NA ; NA NA NA ; ; ; Mean ± SD 7.55 ± 0.50; 7.88 ± ± ± ± ± ± ± ± 3.26 Free ammonia was calculated with the formula NH 3 -N = (total ammonia (NH þ 4 -N + NH 3-N) 9 10 ph )/(K b /K w ) + 10 ph ). Calculation of mean from all analytical samples. NA, not analyzed; SD, standard deviation.

4 788 A. Rademacher et al. chloroform isoamylalcohol (24 : 1 v/v) and precipitated from the obtained water phase by adding 0.1 volumes of 3 M sodium acetate (ph 5.2) and an equal volume of isopropanol. The precipitated DNA was received by centrifugation at g for 20 min at 4 C. The achieved pellets were washed twice with ethanol (70% v/v), dried, and resuspended in 50 ll of HPLC-H 2 O. The DNA was stored at 4 C until further processing. All chemicals were provided by AppliChem (Darmstadt, Germany). The genomic DNA from subsamples of the respective biofilm samples were pooled and then purified with NucleoBond CB 20 kit (Macherey-Nagel, Düren, Germany) according to manufacturer s instructions. Purity and concentration of the genomic DNA were verified using NanoPhotometer (Implen, München, Germany) and NanoDrop 3300 (Thermo Fisher Scientific, Wilmington, DE). The DNA, extracted from the cellulolytic and the methanogenic biofilm, had a concentration of and lg ll 1, respectively, and was highly pure with an absorption of A 260 /A 280 = 1.8. To confirm that the extracted DNA showed a high microbial diversity, terminal restriction fragment length polymorphism (TRFLP) analysis was applied revealing a wide-ranged, highly diverse fingerprint (data not shown). Sequencing of metagenomic DNA on the GS FLX Titanium platform For sequencing of metagenomic DNAs, isolated from biofilms of an experimental thermophilic leach-bed biogas reactor, on the GS FLX platform (Roche Applied Science), libraries were constructed applying the GS Rapid Library Prep kit (Roche Applied Science) according to the protocol provided by the manufacturer. Two libraries representing different biofilm communities were each sequenced in a quarter of a PicoTiterPlate on the GS FLX system using the Titanium sequencing chemistry (Roche Applied Science). Raw data were processed by means of the analysis pipeline for whole-genome shotgun sequence reads applying the GS FLX System Software (version 2.3.). The subsequent phylogenetic and functional analyses were conducted using SAMS (Bekel et al., 2009) for metagenomic data. Phylogenetic classification by RDP, CARMA, and the lowest common ancestor (LCA) analysis For the identification of 16S rrna fragments, a BLAST (Altschul et al., 1990) search vs. the database of the ribosomal database project (RDP) (Release 10.19) was conducted. The sequence complexity filter was disabled (option -F F ) to allow the analysis of reads with low complexity. Reads with an E-value cutoff of were extracted and classified using the RDP classifier (Wang et al., 2007) and a confidence value of at least 80%. The accuracy of RDP classification ranges from 99.5% to 99.8% at phylum level and 83.2% to 88.7% at genus rank for nucleotide segments analyzing type strain sequences and further rrna sequences (Wang et al., 2007). To provide a classification based on environmental gene tags (EGTs) identified on sequencing reads matching Pfam family members, the CARMA (Krause et al., 2008b) tool was applied using the default settings. Here, a specificity of the classification with 97% at superkingdom and 68% at genus rank can be achieved for short EGTs of a synthetic data set produced from 77 complete genomes (Krause et al., 2008b). In a further approach (LCA analysis), a BLAST search vs. the NCBI NR database with an E-value cutoff of was conducted. For each read having hits to more than one organism, the LCA was calculated and assigned to it. Functional characterization using clusters of orthologous groups of proteins (COG), Pfam, and gene ontology (GO) databases To get insights into the biological processes within the underlying community, the sequencing reads were classified according to the COG (Muller et al., 2010). The metagenome reads were compared against the COG database using BLASTX (option -F F and an E-value cutoff of ) and annotated with the COG accession according to their best hit. Moreover, Pfam (Finn et al., 2008) and GO (Harris et al., 2004) profiles obtained from CARMA were used for functional characterization. In a further step, the functional information based on the Pfam accessions was combined with the results of the phylogenetic classification obtained by CARMA. Therefore, enzymes relevant for the methanogenesis process were identified with the help of KEGG (Ogata et al., 1999) and categorized according to Pfam protein families. For each sequence read, classified to the selected Pfam accessions, the assignment to taxonomic groups was retrieved. Finally, a taxonomic profile for the Pfam accessions of interest was constructed. Results The microbial metagenome of biogas biofilms A metagenome approach analyzing the cellulolytic and the methanogenic biofilm of an experimental thermophilic leach-bed biogas reactor was applied. Total community DNA was isolated from both biofilms and

5 Microbial biofilms in thermophilic biogas systems 789 Table 2. Obtained reads by means of 454-pyrosequencing and the distribution of identified reads using RDP, CARMA, and the LCA analysis Cellulolytic biofilm Methanogenic biofilm Both samples Reads Distribution (%) Reads Distribution (%) Reads Distribution (%) Obtained 454-reads Identified reads using RDP Identified EGTs using CARMA Identified reads using LCA SD, standard deviation. sequenced by means of the 454-pyrosequencing technology, resulting in reads with bases sequence information for the sample representing the biofilm community from the digested rye silage (cellulolytic biofilm) and reads with sequenced bases for the second library representing the community of the second, methanogenic stage of the biogas reactor (methanogenic biofilm) (Table 2). The average read length was, respectively, 397 and 394 bp for the two metagenome sequence data sets. Microbial community structure based on 16S rrna gene sequences The taxonomic composition of the community based on reads encoding 16S rrna was analyzed with the RDP classifier (Wang et al., 2007). A number of 673 (cellulolytic biofilm) and 469 reads (methanogenic biofilm) were identified encoding parts of the 16S rrna gene. These 1142 reads were assigned to the domains Bacteria and Archaea representing together 0.21% of all metagenomic reads (Table 2). However, Bacteria contributed with 98% of assigned 16S rrna sequences to the cellulolytic biofilm and 88% to the methanogenic biofilm sample. Archaea were classified with 2% and 12%, respectively. The phyla Firmicutes (36% and 25% of assigned reads) and Bacteroidetes (3% and 5%) were most prevalent among the Bacteria identified in the cellulolytic and methanogenic biofilm samples, respectively. In addition, Euryarchaeota were enriched in the methanogenic biofilm with 12% instead of 2% within the cellulolytic biofilm. The phyla Thermotogae and Proteobacteria were identified with a frequency below 2% in both samples. Clostridia (27%), followed by Methanomicrobia (2%) and Thermotogae (1%), were the most detected classes in the cellulolytic biofilm sample (Fig. 2). In contrast, the methanogenic biofilm revealed that Clostridia (18%) were less represented, followed by Methanomicrobia (7%) and Methanobacteria (4%) (Fig. 2). At the genus rank, Ruminococcaceae, which could not be assigned to a genus, were dominantly classified with 7% within the cellulolytic biofilm (Table 3). Notably, members of the genus Clostridium were not identified in both samples. Focusing on the methanogenic biofilm, two genera were prevalently detected: Methanosarcina and Methanobacterium (both 4%). Additionally, Thermacetogenium was identified with an abundance of 2% (Table 3). Microbial community structure analyzed by Pfam protein families A phylogenetic characterization of EGTs identified on reads matching Pfam protein family members was applied using the CARMA software. A number of (cellulolytic biofilm sample) and reads (methanogenic biofilm sample) were identified as EGTs representing 29.8% of all reads (Table 2). Focusing on the cellulolytic biofilm sample, most EGTs were assigned to Bacteria (83% of EGTs), followed by Archaea (4%). In contrast, the methanogenic biofilm revealed a lower proportion of Bacteria (62%) and a higher contribution of Archaea with 22% of all identified EGTs. The proportion of Eukaryota was consistent with 4% in both samples. A total of 9 12% of EGTs could not be classified to a superkingdom. At the phylum level, Firmicutes was prevalently classified with 51% (cellulolytic biofilm) and 30% (methanogenic biofilm) of the prokaryotic EGTs (pegts). Furthermore, Proteobacteria (12 13% of pegts) and Bacteroidetes (3 4% of pegts) were also detected among the Bacteria in both samples. On the contrary, Euryarchaeota were classified with 24% within the methanogenic biofilm compared to 4% in the cellulolytic biofilm sample. Clostridia (39%), Bacilli (6%), Gammaproteobacteria (4%), and Methanomicrobia (3%) were identified as most prevalent classes in the cellulolytic biofilm (Fig. 2). The methanogenic sample showed a different ranking with Clostridia (21%), Methanomicrobia (11%), Methanobacteria (7%), and Bacilli (5%) (Fig. 2). Members of the classes Cytophaga, Flavobacteria, and Bacteroidia occurred with a proportion of % in both samples. At the genus level, we identified Clostridium (17%) followed by Bacillus (2%), Thermoanaerobacter (1.5%), and Petrotoga (1%) as dominant within the cellulolytic biofilm sample (Table 3). Herein, Clostridium thermocellum (7%),

6 790 A. Rademacher et al. Archaea Bacteria Class Thermoprotei Halobacteria Methanobacteria Methanococci Methanomicrobia Thermococci Actinobacteria Bacteroidia Cytophagia Flavobacteria Chlorobia Anaerolineae Chloroflexi Dehalococcoidetes Deinococci Bacilli Clostridia Planctomycetacia Alphaproteobacteria Betaproteobacteria Deltaproteobacteria Epsilonproteobacteria Gammaproteobacteria Spirochaetes Synergistia Mollicutes Thermotogae Verrucomicrobiae (a) (b) (c) % of assigned reads % of pegts % of assigned reads Fig. 2. Phylogenetic classification using RDP classifier (a), CARMA software (b), and LCA analysis (c) showing the prevalent classes; gray bar, cellulolytic biofilm sample; black bar, methanogenic biofilm sample; pegts, prokaryotic EGTs; abundance < 0.1% of assigned reads. Table 3. List of dominant genera in both the cellulolytic and the methanogenic biofilm samples as revealed by phylogenetic classification Distribution in percentage Cellulolytic biofilm Methanogenic biofilm RDP CARMA LCA RDP CARMA LCA Methanobacterium ND ND ND 3.8 ND ND Methanoculleus Methanosaeta ND < 0.1 < Methanosarcina Methanothermobacter ND Alkaliphilus ND ND Bacillus ND Bacteroides ND ND Caldicellulosiruptor ND ND Clostridium ND ND Desulfotomaculum ND ND Flavobacterium ND ND < 0.1 < 0.1 Moorella ND ND Pelotomaculum ND Petrotoga Ruminococcaceae 7.0 ND ND 0.2 ND ND inc. sed. Syntrophomonas ND Thermacetogenium 0.1 ND ND 2.3 ND ND Thermoanaerobacter ND ND Thermotoga ND 0.4 < 0.1 ND ND, not detected. Clostridium cellulolyticum (2%), and Petrotoga mobilis (1%) appeared to be the prevalent species. On the contrary, the genera Methanosarcina (6%), followed by Clostridium (4%) and Methanothermobacter (4%), were detected in the methanogenic biofilm (Table 3). Here, Methanothermobacter thermautotrophicus (4%), Methanosarcina barkeri (2%), and Methanoculleus marisnigri (2%) were most prevalent. Microbial community structure determined by LCA analysis The LCA analysis is a naïve method. Firstly, reads were searched for matches to the NCBI NR database. Subsequently, the LCA of every metagenome read was calculated and assigned to it. A number of (cellulolytic biofilm) and reads (methanogenic biofilm) were assigned to taxonomic ranks representing 10% of all 454-reads (Table 2). The results of this profiling mainly confirmed the results of the previous phylogenetic classification applying RDP and CARMA. Only few differences were observed, for instance at the class level. Here, members of the classes Bacilli and Gammaproteobacteria appeared to be less abundant in comparison with the CARMA results, whereas those of the Thermotogae (4 6%) showed a higher proportion in comparison with the RDP and CARMA analysis (Fig. 2). Apart from that, Clostridia and Methanomicrobia were also most

7 Microbial biofilms in thermophilic biogas systems 791 prevalent in LCA profiles of the cellulolytic and methanogenic biofilm samples, respectively. Enzymatic capacity of the microbial community revealed by COG and GO analyses Functional analysis allowed a snapshot insight into the genetic potential of the biofilm-based microbial communities residing in different compartments of the investigated biogas system. A number of (cellulolytic biofilm) and (methanogenic biofilm) 454-reads were assigned to GO terms. The Gene Ontology project is a bioinformatic initiative, which provides defined terms (GO terms) for describing genes and their gene products (Harris et al., 2004). Additionally, (cellulolytic biofilm) and reads (methanogenic biofilm) could be assigned to COG. The COG database includes proteins, which are grouped in 2791 COG categories (Tatusov et al., 2001). The results of the GO and COG classification showed strong differences between the cellulolytic and the methanogenic biofilm sample. Enzymes involved in carbohydrate degradation were profoundly enriched in the cellulolytic biofilm, whereas the methanogenic enzymes were predominant in the methanogenic biofilm sample. Digestion of celluloses and hemicelluloses such as xylan is one of the first steps in the breakdown of plant material. Enzymes degrading xylan, a heteropolysaccharide of plant cell walls, were overrepresented in the cellulolytic biofilm sample. The COG categories beta-1,4- xylanase (COG3693), beta-xylosidase (COG3664), xylose isomerase (COG2115), ABC-type xylose transport system (COG4213), and the GO term xylan catabolic process (GO: ) were increased by a factor of up to 7 in comparison with the methanogenic biofilm sample (Table 4). Enzymes catalyzing further degradation steps of polysaccharides and oligosaccharides were also predominant in the cellulolytic biofilm sample. Hence, Table 4. List of identified biomass degrading GO and COG categories and their cellulolytic increase factor in the cellulolytic biofilm GO/COG accession GO/COG category GO/COG hits Cellulolytic biofilm Methanogenic biofilm Degradation of xylan COG4213 ABC-type xylose transport system COG3693 Beta-1,4-xylanase COG3664 Beta-xylosidase GO: Xylan catabolic process COG2115 Xylose isomerase Degradation of polysaccharides and oligosaccharides GO: Cellulase activity COG1363 Cellulase M and related proteins COG2730 Endoglucanase COG3405 Endoglucanase Y COG0366 Glycosidases GO: Hydrolase activity COG5520 O-glycosyl hydrolase GO: Polysaccharide catabolic process Processing of disaccharides and monosaccharides COG3345 Alpha-galactosidase COG1874 Beta-galactosidase GO: Beta-galactosidase activity COG1472 Beta-glucosidase-related glycosidases COG3459 Cellobiose phosphorylase COG0153 Galactokinase GO: Glucose catabolic process GO: Glucosidase activity GO: Glucuronate catabolic process COG1904 Glucuronate isomerase COG2160 L-arabinose isomerase Cellulolytic increase factor Cellulolytic increase factor was calculated as follows: (number of GO or COG hits of the cellulolytic biofilm/all obtained 454-reads of the cellulolytic biofilm)/(number of GO or COG hits of the methanogenic biofilm/all obtained 454-reads of the methanogenic biofilm).

8 792 A. Rademacher et al. the GO terms cellulase activity (GO: ) and hydrolase activity (GO: ) and the COG category cellulase M and related proteins (COG1363) were raised by an average factor of 3. Additionally, the GO term polysaccharide catabolic process (GO: ) was enriched 12-fold (Table 4). Similarly, O-glycosyl hydrolase (COG5520) and endoglucanase (COG2730), which are involved in polysaccharide degradation, were increased 15-fold and 30-fold, respectively (Table 4). One of the last steps in the breakdown of plant material is the processing of disaccharides and monosaccharides, which is carried out by certain enzymes such as alphaand beta-galactosidase, glucosidase, glucuronate isomerase, galactokinase, and L-arabinose isomerase (Table 4). These enzymes were also enriched by a factor of 2 10, supporting the conclusion that enzymes with carbohydratedegrading activity were prevalent in the cellulolytic biofilm sample. Altogether, we determined the terms hydrolase activity (GO: , 1950 hits), cellobiose phosphorylase (COG3459, 868 hits), beta-glucosidase related glycosidases (COG1472, 849 hits), beta-1,4-xylanase (COG3693, 323 hits), glycosidases (COG0366, 322 hits), and cellulase M (COG1363, 315 hits) as most dominant COG and GO terms in the cellulolytic biofilm (Table 4). By contrast, enzymes characterized by the GO term methanogenesis (GO: ) were enriched sixfold in the methanogenic biofilm sample. A closer look on enzymes required for the hydrogenotrophic and the aceticlastic methanogenesis pathways supported this finding. The hydrogenotrophic pathway is represented by different enzymes such as formylmethanofuran dehydrogenase (subunits A E), formylmethanofuran tetrahydromethanopterin (H 4 MP) formyltransferase, methenyl-h 4 MP cyclohydrolase, H 2 -forming methylene-h 4 MP dehydrogenase, coenzyme F 420 -dependent methylene-h 4 MP reductase, and H 4 MP S-methyltransferase (subunits A H). These enzymes catalyze the whole conversion process of CO 2 to methyl coenzyme-m. All of them could be identified by COG and GO analyses and were distinctly enriched by an average factor of 10 in the methanogenic biofilm sample (Table 5). For instance, the COG and GO category methenyl-h 4 MP cyclohydrolase (COG3252, GO: ) was enriched by a factor of 19 and 24, respectively. Enzymes involved in the aceticlastic pathway were also identified to a higher amount within the methanogenic biofilm. Despite the fact that the CO dehydrogenase/acetyl-coa synthase is also involved in the Wood-Ljungdahl pathway, this enzyme complex also converts acetyl-coa to methyl-tetrahydrosarcinopterin (H 4 SP), forming an intermediate step of the aceticlastic methanogenesis. Therefore, corresponding COG categories of this complex (with subunits a, b, c, d, and e) and the GO term CO dehydrogenase activity (GO: ) were strongly enriched up to a factor of 14 in the methanogenic biofilm sample (Table 5). The last step of methane formation, the reductive demethylation of methyl-com, is identical in both the hydrogenotrophic and the aceticlastic pathways. The catalyzing enzyme involved in this step is methyl coenzyme- M reductase (MCR, subunits a, b, c, C, D). All COG categories, assigned to the methyl-com reductase, were strongly overrepresented in the methanogenic biofilm sample (Table 5) notably, the MCR subunit a (COG4058) by a factor of 22. Enzymatic capacity of the microbial community resulting from Pfam analysis The Pfam database (Pfam 24.0) provides a broad range of protein families (11 912). Each of these protein families is represented by multiple-sequence alignments and hidden Markov models (Finn et al., 2008). Using Pfam classification, we identified carbohydrate-degrading and methanogenic enzymes in both samples, which were subsequently assigned to taxonomic groups. Focusing on the carbohydrate-degrading enzymes, we selected several protein families representing glycosyl hydrolases, for example glycosyl hydrolase family 5 (cellulase, PF00150) and glycosyl hydrolase family 10 (e.g. xylanase, PF00331), for our analysis (Supporting Information, Table S1). The assignment of carbohydrate-degrading Pfam categories to taxonomic groups revealed Clostridia, Bacilli, Flavobacteria, and Gammaproteobacteria as prevalent bacteria. Thermotogae, Actinobacteria, and Bacteroidia were less represented in this functional analysis (Fig. 3), although the phylogenetic classification (RDP and LCA) revealed a high abundance of at least Thermotogae. At the genus level, Clostridium was most abundant. In addition, the genera Flavobacterium, Bacillus, and Caldicellulosiruptor also showed carbohydrate-degrading potential (Fig. 3). Further, the Pfam analysis revealed glycosyl families 36 (PF06165, 380 EGTs), 9 (PF00759, 277 EGTs), 10 (PF00331, 256 EGTs), and 3C (PF01915, 235 EGTs) as most prevalent, representing, for example, cellobiose phosphorylase, endoglucanase, xylanase, and betaglucosidase (Table S1). In addition, several enzymes covering the hydrogenotrophic (e.g. formylmethanofuran/h 4 MP formyltransferase, PF01913) and the aceticlastic (e.g. CO dehydrogenase/ acetyl-coa synthase subunit b, PF03598) pathway of methanogenesis were analyzed to receive data about the biofilm-based methanogenesis (Table S2). At the class level, Methanomicrobia, followed by Methanobacteria, were frequently detected as revealed by the results of the phylogenetic classification in both samples. Further, Methanothermobacter, followed by Methanosarcina and

9 Microbial biofilms in thermophilic biogas systems 793 Table 5. List of identified methanogenic GO and COG categories and their methanogenic increase factor in the methanogenic biofilm GO/COG accession GO/COG category GO/COG hits Cellulolytic biofilm Methanogenic biofilm Methanogenic increase factor Methanogenesis (both pathways) GO: Methanogenesis COG4058 Methyl coenzyme-m reductase subunit a COG4054 Methyl coenzyme-m reductase subunit b COG4057 Methyl coenzyme-m reductase subunit c COG4056 Methyl coenzyme-m reductase subunit C COG4055 Methyl coenzyme-m reductase subunit D Hydrogenotrophic methanogenesis COG1229 Formylmethanofuran dehydrogenase subunit A COG1029 Formylmethanofuran dehydrogenase subunit B COG2218 Formylmethanofuran dehydrogenase subunit C COG1153 Formylmethanofuran dehydrogenase subunit D COG2191 Formylmethanofuran dehydrogenase subunit E COG2037 Formylmethanofuran H 4 MP formyltransferase COG3252 Methenyl-H 4 MP cyclohydrolase GO: Methenyl-H 4 MP cyclohydrolase activity COG4074 H 2 -forming N5, N10-methylene-H 4 MP dehydrogenase 0 4 NC GO: Coenzyme F420-dependent N5, N10-methenyl H 4 MP 0 6 NC reductase activity COG2141 Coenzyme F420-dependent N5, N10-methylene H 4 MP reductase COG4063 H 4 MP S-methyltransferase subunit A COG4062 H 4 MP S-methyltransferase subunit B COG4061 H 4 MP S-methyltransferase subunit C COG4060 H 4 MP S-methyltransferase subunit D COG4059 H 4 MP S-methyltransferase subunit E COG4218 H 4 MP S-methyltransferase subunit F COG4064 H 4 MP S-methyltransferase subunit G COG1962 H 4 MP S-methyltransferase subunit H GO: H 4 MP S-methyltransferase activity Aceticlastic methanogenesis COG1152 CO dehydrogenase/acetyl-coa synthase subunit a COG1614 CO dehydrogenase/acetyl-coa synthase subunit b COG1456 CO dehydrogenase/acetyl-coa synthase subunit c COG2069 CO dehydrogenase/acetyl-coa synthase subunit d COG1880 CO dehydrogenase/acetyl-coa synthase subunit e GO: Carbon-monoxide dehydrogenase activity NC, not computable. Methanogenic increase factor was calculated as follows: (number of GO or COG hits of the methanogenic biofilm/all obtained 454-reads of the methanogenic biofilm)/(number of GO or COG hits of the cellulolytic biofilm/all obtained 454-reads of the cellulolytic biofilm). Methanoculleus were classified as the most dominant genera within the methanogenic biofilm, whereas Methanosarcina, followed by Methanothermobacter, were prevalent in the cellulolytic biofilm (Fig. 3). Discussion Methodical aspects and bioinformatic analysis As the main part of microorganisms is not cultivable yet, culture-independent methods are of major importance for gaining insights into different microbial habitats. One crucial point of DNA-based molecular analysis is an effective DNA extraction. However, a commonly known problem is the variable lysis efficiency of microbial cells. In this approach, we amended to the recently published protocol (Rheims & Stackebrandt, 1999; Klocke et al., 2008; Nettmann et al., 2010) consisting of an enzymatic and chemical lysis step an additional mechanical step for an improved lysis of microbial cells. A further problem is the DNA extraction from biofilms attached to heterogenic crop material. Several studies have been applied for

10 794 A. Rademacher et al. (a) (b) EGTs Actinobacteria Bacteroidia Flavobacteria Bacilli Clostridia Class Gammaproteobacteria Thermotogae Bacteroides Flavobacterium Bacillus Caldicellulosiruptor Clostridium Genus Shewanella Thermotoga Methanobacteria Methanomicrobia Methanococci Class Methanosphaera Methanothermobacter Methanococcus Methanoculleus Methanospirillum Genus Methanosarcina Fig. 3. Pfam characterization of carbohydrate-degrading (a) and methanogenic (b) enzymes and subsequent assignment at class and genus rank; gray bar, cellulolytic biofilm sample; black bar, methanogenic biofilm sample; only prevalent groups with 20 EGTs (a) and 10 EGTs (b) are shown. detaching biofilms with chemical (e.g. Chen & Stewart, 2000), enzymatic (e.g. Johansen et al., 1997; Böckelmann et al., 2003), or physical (e.g. Mott et al., 1998; Rochex et al., 2009) treatment. However, using the whole plant material for DNA extraction minimizes a potential loss of microbial cells, which is in accordance with other studies (McEniry et al., 2008; Wang et al., 2010). Another point is the assignment of the obtained 454- reads to taxonomic groups, which remains a sophisticated effort owing to bioinformatic challenges and a high rate of unknown species. In our approach, only a minor number of reads could be classified with the applied phylogenetic classification. Therefore, approximately 70% of reads remained unexplored, indicating that additionally a certain number of species might be involved in the biogas fermentation process. The assignment of metagenomic reads by comparison with different databases is influenced by the content of the database, for example the number and origin of stored nucleotide and protein sequences, respectively. Sequences with a high abundance in databases from, for example, cultivable microorganisms could distort the obtained results. Moreover, the assignment of reads also comprises some drawbacks concerning overestimation of specific taxa. Krause et al. (2008b) assumed that Proteobacteria were incorrectly assigned by a rate of 3.8% using the CARMA software. Likewise, our CARMA results showed a high rate of Proteobacteria (12 13%), suggesting a certain rate of false-positive classified reads. In addition, the assignment of reads down to the species level is enabled by the presence of highly related species in databases. Therefore, especially at the species level, the microorganisms residing in the studied system may only be related and not identical to reference species stored in databases. These drawbacks in assignment of reads lead to limitations in comparative analyses. However, a comparative analysis is applicable as a first insight, owing to the fact that the assignment to the same taxonomic groups is affected by the same bias. A further point to note is that the applied phylogenetic classifications are based on two different taxonomies. The RDP classifier relies on the Bergey s taxonomy (Garrity et al., 2004; Wang et al., 2007), whereas CARMA and the LCA analysis use the NCBI taxonomy (Wheeler et al., 2007; Krause et al., 2008a). For instance, C. thermocellum was classified to Ruminococcaceae by means of the RDP classifier (Bergey s taxonomy), although the NCBI taxonomy assigned it to Clostridiaceae. Therefore, the unclassified members of the family Ruminococcaceae, identified by means of the RDP classifier, most probably correspond to Clostridium species as revealed by CARMA and the LCA analysis using the NCBI taxonomy. Spatial distribution of the analyzed microbial community The analyzed biofilms of the two-phase leach-bed system revealed strong differences in their microbial community structure. Bacteria and their plant-degrading enzymes were increased in the HR (cellulolytic biofilm) according to their role in biomass degradation. Furthermore, methanogenic enzymes present in Euryarchaeota occurred predominantly in the AF (methanogenic biofilm) as identified with COG and GO analyses. Hence, the methane content of the AF was strongly enhanced with 71% in comparison with the HR with 45%. Nevertheless, the total methane yield obtained for the HR (CH 4 : L kg 1 VS) was twice as high as for the AF (CH 4 : L kg 1 VS). In contrast to the results of the phylogenetic classification, the functional Pfam analysis revealed a spatial distribution of archaea between both samples (Fig. 3). Whereas Methanosarcina was dominantly classified in the

11 Microbial biofilms in thermophilic biogas systems 795 HR, Methanothermobacter was prevalent in the AF. These findings confirm results obtained recently by Talbot et al. (2010) analyzing the microbial consortium in a plugflow-type anaerobic bioreactor. Their study showed that acid-producing bacteria and aceticlastic methanogens are mainly located in the hydrolysis/acidification stage, suggesting that hydrogenotrophic archaea residing in further reactor stages are dominantly involved in methane production (Talbot et al., 2010). However, our results revealed that Methanosarcina is associated with the reactor (HR) that achieved the highest total methane yield, suggesting that Methanosarcina was dominantly involved in the methane production within the HR. The downstream AF appeared to have a postfermentation role in our system, where all residual precursors were utilized for the production of biogas with high methane content, for instance, by Methanothermobacter as revealed by functional Pfam analysis. Genetic potential for anaerobic biomass degradation In general, thermophilic biogas systems are known to operate with lower retention times of raw material achieving a higher productiveness. Dugba & Zhang (1999) measured a higher methane production and VS removal for a thermophilic two-stage anaerobic batch system digesting wastewater. A higher productiveness and therefore an elevated turnover may be reflected in an adapted enzymatic capacity of the inherent microbial community. Functional analyses of enzymes (by Pfam, COG, or GO) involved in biomass degradation identified a strong prevalence of carbohydrate-degrading enzymes in the cellulolytic biofilm sample. Further, we identified an ascertained hierarchy of enzymes suggesting a defined anaerobic degradation potential. Using COG and GO analyses and Pfam analysis, enzymes such as hydrolases, cellobiose phosphorylases, xylanases, beta-glucosidases, endoglucanases, and cellulases (Table 4, Table S1) were most prevalent. These enzymes are involved in the breakdown of both polysaccharides, and di- and monosaccharides. Therefore, the whole degradation process beginning with the breakdown of xylan, hemicellulose, and cellulose and other polysaccharides down to the formation of disaccharides and monosaccharides can be reconstructed by those enzymes as revealed by functional analyses. This implies a wide-ranged degradation potential for plantderived heteropolysaccharides down to monosaccharides, which was also confirmed by the calculated degradation rate of organic dry matter (without lignin fraction) of 74% in our thermophilic biogas system. To assess potential differences between the enzymatic capacity of a thermophilic and a mesophilic biogas system, we compared our findings with the COG and Pfam results of a recently published metagenome (Tables S3 and S4) obtained from a mesophilic (41 C) full-scale biogas system supplied with maize silage, green silage, and manure (Jaenicke et al., 2011). Their system showed a different enzymatic capacity with a modified order of frequent enzymes such as beta-glucosidase-related glycosidases (COG1472), glycosidases (COG0366), cellulase M (COG1363), cellobiose phosphorylase (COG3459), and beta-galactosidase/beta-glucuronidase (COG3250) (Table S3). The Pfam analysis revealed glycosyl families 43 (PF04616), 3C (PF01915), 2N (PF02837), and 4 (PF02056) (Table S4) with enzyme activities of, for example, beta-xylosidase, beta-glucosidase, beta-galactosidase, and 6-phospho-beta-glucosidase also supporting the COG results. However, although both profiles are different, they both revealed enzymes involved in the processing of polysaccharides and oligosaccharides as well as disaccharides and monosaccharides. Nevertheless, the comparison of Pfam results revealed that Pfam families representing enzymes involved in polysaccharide degradation such as xylanase (PF00457) or cellobiohydrolase (PF00759 and PF02011) were increased up to a factor of 22 (Table S4) within our thermophilic cellulolytic biofilm sample. Additionally, we detected a higher abundance of almost all Pfam accessions and all identified COG accessions involved in carbohydrate degradation (Tables S3 and S4) within our sample. These findings indicate a higher genetic potential, in particular for polysaccharide degradation, in our thermophilic two-phase biogas system, which may lead to a more efficient turnover in the thermophilic biogas system. However, this tendency has to be verified in further approaches. Bacteria involved in thermophilic anaerobic degradation Regarding the whole process of biomass conversion to methane, the degradation of cellulosic material conducted by certain bacteria is the time-determining step and therefore still needs to be improved. Analyzing the metagenome reads, we identified predicted Firmicutes (e.g. Clostridia and Bacilli) as the most dominant bacterial phylum. Members of the genus Clostridia were classified more prevalently than those of the genus Bacilli in the cellulolytic biofilm sample. Several genera belonging to the class Clostridia were identified, indicating a high diversity within this class. Numerous Clostridium species are known for their cellulolytic activity such as C. thermocellum and C. cellulolyticum. Both species, prevalent in our analysis, have a cellulose-binding, multi-enzyme complex, the so-called cellulosome, for

12 796 A. Rademacher et al. degradation of cellulosic material (Felix & Ljungdahl, 1993; Bayer et al., 2004). Despite the high number of unknown sequence reads, members of the genus Clostridium may play a key role in the digestion of crop biomass, as mentioned in previous studies (Klocke et al., 2007; Krause et al., 2008a; Schlüter et al., 2008; Liu et al., 2009). Nevertheless, Thermoanaerobacter and Caldicellulosiruptor, also prevalent in this study, are capable to degrade cellulosic substrates. For instance, Caldicellulosiruptor increases the yield of methane by inoculation to a thermophilic biogas fermenter as indicated by Nielsen et al. (2007). The degradation of crop biomass leads to fermentation end products such as lactate, ethanol, acetate, H 2, and CO 2. Further detected species such as members of the genus Pelotomaculum are capable to oxidize lactate or several alcohols in syntrophy with H 2 -scavenging methanogens (Imachi et al., 2002), indicating a syntrophic cooperation in the HR. Other degradation steps during biogas formation including b-oxidation of fatty acids or degradation of proteins may be conducted by Syntrophomonas and Alkaliphilus, respectively (McInerney et al., 1981; Takai et al., 2001). Besides the class Clostridia, the class Bacilli appeared to be less abundant. Bacillus, the dominantly identified genus among the Bacilli, is predicted to degrade carbohydrates as assumed by other authors investigating mesophilic biogas systems supplied with fodder beet silage or maize silage (Klocke et al., 2007; Krause et al., 2008a). Likewise, it must be mentioned that the classes Thermotogae (Thermotogae), Bacteroidia, and Flavobacteria (Bacteroidetes) were also identified but with minor prevalence compared to Clostridia. Petrotoga (Thermotogae), such as P. mobilis, was identified in all phylogenetic classifications. Petrotoga mobilis is a fermentative bacterium possessing xylanase activity (Lien et al., 1998). In contrast, the functional analysis revealed Thermotoga as predominant genus among the Thermotogae. Species of this genus also possess carbohydrate-degrading activity (Huber et al., 1986). The phylum Bacteroidetes is well known to be part of microbial biogas consortia. However, in contrast to its genus Bacteroides, its genus Flavobacterium has been rarely identified in biogas communities (Godon et al., 1997; Klocke et al., 2007; Krause et al., 2008a). A strong presence of Flavobacterium and Bacteroides, as deduced from our phylogenetic classification of EGTs having a predicted function in carbohydrate degradation indicates that these genera are also involved in the breakdown of plant biomass. These findings confirm results obtained by McBride et al. (2009), who predicted that Flavobacterium johnsoniae should be able to degrade hemicellulose. Methanogenesis and syntrophic interactions at thermophilic conditions The production of methane is carried out by the hydrogenotrophic and the aceticlastic pathway. A predominance of one of these pathways in biogas-producing reactors is still discussed. Our results obtained from both biofilms showed that Methanomicrobia, followed by Methanobacteria, were identified as the most common archaeal classes. The genera Methanosarcina, Methanothermobacter, and Methanoculleus were identified as prevalent. Although only very few thermophilic biogas reactors were analyzed so far, some studies revealed a high abundance of Methanosarcina in systems supplied with manure as main component (e.g. Karakashev et al., 2005). Furthermore, Methanobacteria were also predicted to be dominant in thermophilic methane-producing communities digesting maize or beet silage (Bauer et al., 2008; Krakat et al., 2010). Notably, we identified Methanoculleus (Methanomicrobia) in a higher number in our thermophilic system, although some other studies showed that these archaea were less abundant (Krakat et al., 2010) or not detected in thermophilic biogas systems (Karakashev et al., 2005). Moreover, the strict aceticlastic archaea Methanosaeta were less detected in both samples. Methanosaeta was found as predominant archaea at total ammonia concentrations of up to 1.5 g L 1 (Karakashev et al., 2005; Nettmann et al., 2010). Our system showed a total ammonia concentration of 1.33 g L 1, but the apparent concentration of free ammonia (NH 3 -N = 0.31 ± 0.07 g L 1 ) was proportionally high owing to the high temperature (55.41 ± 3.32 C) and the ph (7.88 ± 0.19). In full-scale biogas plants with a concentration of free ammonia above 0.20 g L 1, Methanosaeta did not occur (Nettmann et al., 2010). In contrast, for instance, Methanosarcina tolerated a free ammonia concentration of 0.45 g L 1 (Nettmann et al., 2010). Further, an acetic acid concentration of up to 92.8 mm and a VFA concentration of up to 7.1 g L 1, which can also restrict Methanosaeta (Karakashev et al., 2005), favor the apparent prevalence of other methanogenic archaea. Methanosarcina, Methanothermobacter, and Methanoculleus, which were also classified in our results, are able to cope with higher acid and ammonia concentrations as indicated by previous analyses (Karakashev et al., 2005; Nettmann et al., 2010). Because of the fact that both Methanosarcina and strict hydrogenotrophic archaea were identified in our system, the question which pathway was mainly utilized for methane production is still unanswered. The results of the COG and GO analyses identified enzymes for both the hydrogenotrophic and the aceticlastic methanogenesis. However, the study of