Figure 5.11: Approach for the construction of a profile hidden Markov model (HMM) representing a target enzymes: An initial set of described protein sequences is used to search for similar proteins. The hits serve for building an initial profile HMM, which is refined with further sequences and rebuilt from improved alignments.
as a basis for building an initial profile HMM by applying the HMMER3 package [Eddy, 2011].
Second, the initial profile HMM modeling the target enzyme is retrained. Therefore, an HMM-based search is applied to identify additional enzymes in a public protein database that match the initial profile HMM. The sequences with a hit are extracted and aligned using HMMER3. The alignment is verified by removing duplicates or invalid sequences. The remaining sequences are aligned to the initial profile HMM with HMMER3, and a final profile HMM is constructed.
CHAPTER
6
Application examples
This chapter describes the outcomes of the analyses of whole metagenome shotgun, 16S rDNA amplicon and metatranscriptome tags obtained from a biogas plant. For a better understanding of the results, the process of biogas production is introduced in the first section. Thereafter, the taxonomic and functional results deduced by means of MetaSAMS are reported for the metagenome of the biogas-producing community. Next, a deeper resolution of the taxonomic composition of the underlying community is described based on 16S rDNA amplicon analysis in AMPLA. Additionally, active members and functions of the biogas-producing community are presented by applying the developed MeTra pipeline on the corresponding metatranscriptome dataset. Finally, the results of a search for laccases encoded in genomes and metagenomes are reported.
6.1 Introduction to biogas
The dwindling of fossil fuel supplies and the worldwide growing demand for energy are the driving forces to find sustainable energy sources. Simultaneously, burning of fossil fuels is associated with the increase in atmospheric carbon dioxide, which is considered to affect global warming. In this context, biogas from renewable resources or organic waste is a promising carrier of bioenergy [Weiland, 2010]. Methane, the energy-rich molecule in biogas, can be converted to electric energy or heat in an ecologically- friendly way. The conversion of organic material to biogas is a complex process, which is composed of four successive steps, namely hydrolysis, acidogenesis, acetogenesis and methanogenesis (Fig. 6.1) [Deublein and Steinhauser, 2008]. The processes are
Figure 6.1: The process of anaerobic digestion in biogas plants (modified from Deublein and Steinhauser, 2008): The anaerobic decomposition of biomass consists basically of four stages, namely hydrolysis, acidogenesis, acetogenesis and methanogenesis. In addition, homoacetogenesis and syntrophic acetate oxidation are coupled to the basic stages.
accomplished by certain groups of microorganisms under anaerobic conditions. Some of them partly stand in syntrophic associations, i.e. their growth relies on the metabolisms of other microorganisms.
In the first step, the hydrolysis, anaerobic bacteria cleave polymers, like polysaccha- rides, proteins and lipids, into monomers by hydrolytic enzymes [Cirne et al., 2007]. The products of this reaction are short compounds such as short-chain sugars, amino acids, fatty acids and glycerin. Frequently, species being relevant for the hydrolytic cleavage belong to the class Bacteroides and Clostridia [Jaenicke et al., 2011].
Under anaerobic conditions, the short compounds are taken up by bacteria and trans- formed into short-chain organic acids (e.g., butyric acid, propionic acid, acetic acid), alcohols, carbon dioxide and hydrogen (Fig. 6.1) [Deublein and Steinhauser, 2008]. This step of microbial degradation is called acidogenesis. The degradation of sugars can
6.1 Introduction to biogas
be catalyzed in different pathways. In the succinate and acrylic pathways, sugars are converted to propionic acid. Another pathway is the butyric acid pathway, in which butyric acid is formed from sugar by acidogenic Clostridium species. A degradation pathway for fatty acids is β-oxidation.
The products of the acidogenic step are converted into acetate during acetogenesis (Fig. 6.1). In addition, acetate production is carried out by homoacetogenic microorganisms, which transform carbon dioxide and hydrogen to acetic acid.
The final step is methanogenesis (Fig. 6.1), which is conducted by methanogenic Ar- chaea under strictly anaerobic conditions. Aceticlastic methanogens convert acetate to methane, whereas hydrogenotrophic methanogens use carbon dioxide and hydrogen to produce methane [Demirel and Scherer, 2008]. Aceticlastic methanogens include the genera Methanosaeta and Methanosarcina. Hydrogenotrophic methanogens are a diverse group. Species of Methanobacterium, Methanospirillum, Methanomicrobium and Methanothermobacter are capable of carrying out hydrogenotrophic methanogenesis [Demirel and Scherer, 2008]. Some of them are described to be in association with syntrophic acetate-oxidizing bacteria, which convert acetate into carbon dioxide and hydrogen [Ahring, 2003, Hattori, 2008].
The process of anaerobic degradation is well described but the knowledge about the taxonomic composition is still limited. To optimize the yield and efficiency of the biogas production process, a better understanding of the underlying taxonomic structure and metabolic properties of the biogas-producing microbes is essential. The first metagen- ome of a microbial community of a continuously stirred tank reactor (CSTR) fed with maize silage provided information about the taxonomic composition and the functional capabilities [Krause et al., 2008b, Schlüter et al., 2008, Jaenicke et al., 2011]. The analy- ses revealed Clostridia from the phylum Firmicutes as the most prevalent bacterial class, whereas species of the order Methanomicrobiales were shown to be dominant among Archaea.
In this thesis, the metagenome of a microbial community from a biogas reactor an- alyzed previously [Jaenicke et al., 2011] was used to illustrate the capabilities of the novel system MetaSAMS. Moreover, 16S rDNA and metatranscriptome datasets were generated to deepen the knowledge about the biogas-producing microbial community. The first 16S rDNA amplicon and metatranscriptome approaches were carried out for a microbial community residing in a biogas plant. For this purpose, a fermentation sample was taken from the standard sampling device installed at the main fermenter of the same biogas plant for which the metagenome sequencing project was carried out. Sequences were generated by means of the 454 pyrosequencing technique. Both datasets were processed and analyzed by performing the pipelines MeTra and AMPLA. The aim of this analysis is to shed more light on the processes and organisms relevant for the anaerobic digestion in the studied biogas plant.