Elsevier

Anaerobe

Volume 46, August 2017, Pages 56-68
Anaerobe

Proteotyping of laboratory-scale biogas plants reveals multiple steady-states in community composition

https://doi.org/10.1016/j.anaerobe.2017.02.005Get rights and content

Highlights

  • Proteotyping is a sensitive tool for analysis of microbiomes from biogas plants.

  • Enrichment of microbial communities resulted in multiple steady-states.

  • Thermophilic reactors showed increased abundance of cellulose-degrading proteins.

  • Gap between laboratory and full-scale biogas reactors should be carefully considered.

Abstract

Complex microbial communities are the functional core of anaerobic digestion processes taking place in biogas plants (BGP). So far, however, a comprehensive characterization of the microbiomes involved in methane formation is technically challenging. As an alternative, enriched communities from laboratory-scale experiments can be investigated that have a reduced number of organisms and are easier to characterize by state of the art mass spectrometric-based (MS) metaproteomic workflows.

Six parallel laboratory digesters were inoculated with sludge from a full-scale BGP to study the development of enriched microbial communities under defined conditions. During the first three month of cultivation, all reactors (R1-R6) were functionally comparable regarding biogas productions (375–625 NL Lreactor volume−1 d−1), methane yields (50–60%), pH values (7.1–7.3), and volatile fatty acids (VFA, <5 mM). Nevertheless, a clear impact of the temperature (R3, R4) and ammonia (R5, R6) shifts was observed for the respective reactors. In both reactors operated under thermophilic regime, acetic and propionic acid (10–20 mM) began to accumulate. While R4 recovered quickly from acidification, the levels of VFA remained to be high in R3 resulting in low pH values of 6.5–6.9. The digesters R5 and R6 operated under the high ammonia regime (>1 gNH3 L−1) showed an increase to pH 7.5–8.0, accumulation of acetate (>10 mM), and decreasing biogas production (<125 NL Lreactor volume−1 d−1).

Tandem MS (MS/MS)-based proteotyping allowed the identification of taxonomic abundances and biological processes. Although all reactors showed similar performances, proteotyping and terminal restriction fragment length polymorphisms (T-RFLP) fingerprinting revealed significant differences in the composition of individual microbial communities, indicating multiple steady-states. Furthermore, cellulolytic enzymes and cellulosomal proteins of Clostridium thermocellum were identified to be specific markers for the thermophilic reactors (R3, R4). Metaproteins found in R3 indicated hydrogenothrophic methanogenesis, whereas metaproteins of acetoclastic methanogenesis were identified in R4. This suggests not only an individual evolution of microbial communities even for the case that BGPs are started at the same initial conditions under well controlled environmental conditions, but also a high compositional variance of microbiomes under extreme conditions.

Introduction

Conversion of agricultural waste into biogas is a sustainable source of renewable energy. The so called anaerobic digestion (AD) is performed in large parallel or serial digester systems of different sizes and designs, commonly referred to as biogas plants (BGP). Additional classifications are made depending on the process temperature [1], the type (e.g. silage and/or manure and dung) and consistency (e.g. moisture content) of the used substrate [2], [3], and the ammonium or ammonia concentrations [4]. Independent from these conditions, AD process is subdivided into the four steps hydrolysis, fermentation, acetogenesis and methanogenesis [3], which are executed by different groups of microorganisms forming complex microbial communities — the microbiome [5].

Laboratory-scale digester systems (ranging from a few hundred milliliters to several liters working volume) are commonly used as a scale-down model to investigate AD [6], [7], [8]. These systems benefit from a better control over the cultivation parameters, and allow well-directed disturbances without risking costly malfunction of full-scale BGP. In a highly controlled process, the substrate is fully defined and continuous stirring enables homogeneous mixing and representative sampling. This is in contrast to full-scale BGP with occasional dead zones or floating layers [3], [9], and varying and non-sterile substrates [10]. However, microbial communities evolving in laboratory bioreactors operating under well-defined process conditions loose part of their complexity [11]. While this facilitates analytics, the question arises to what extent results can be transferred to the optimization of full-scale BGP.

Many different analytical methods are routinely applied to study microbial communities in BGP. Genomic approaches, like cloning and sequencing of microbial DNA [12] or fingerprinting of 16S rRNA genes (e.g. T-RFLP — terminal restriction fragment length polymorphisms [13]), allow to explore the diversity of Archaea and Bacteria of microbial communities. As a complementary approach, metaproteomics turned out to be well suited to capture the physiological state and functions of a microbial population [14]. State of the art methods rely on gel-free approaches [15] pushed by the rapid development of high resolving mass spectrometers (MS) for protein identification, and powerful tools for data analysis [16]. Their application revealed great potential for the characterization of mixed microbial communities, which was referred recently as proteotyping [17]. So far, this term was only used for the identification of single microorganisms by characteristic protein mass spectra derived from Matrix-Assisted Laser Desorption/Ionization-Time-Of-Flight MS analysis (MALDI-TOF-MS) [18]. In a recent review, however, the term proteotyping was extended to cover classification, characterization and identification of microorganisms as well as microbial communities by tandem MS and MS/MS-based shotgun proteomics [19]. The first comprehensive proteotyping of microbial communities in technical biocoenoses aimed at the correlation of biological processes of the microbiome in BGP with respective process parameters [17]. Applications of biostatistics and data mining tools (e.g. principal component analysis or clustering) allowed identifying correlations of taxonomies, functions and metaproteins with process parameters (e.g. temperature, substrate, reactor design or nitrogen content) from extensive lists of identified proteins — without laborious hit-by-hit evaluation.

In this study six parallel digesters were inoculated with sludge from a full-scale BGP to enrich microbial communities under defined conditions. After three month of cultivation, steady-state operation was achieved for all digesters. Subsequently, the temperature and the ammonia concentration were increased for two reactors each. Based on metaproteomics the following questions were addressed: how similar are stable microbial communities operating under exactly the same environmental conditions? Can marker species or functions be determined representing the different process regimes using proteotyping?

Section snippets

Reactor setup

For enrichment, a Sixfors multi bioreactor system (INFORS AG, Bottmingen, Switzerland) with six parallel 500 mL glass vessels was used (R1-R6; 400 mL working volume). Each reactor was equipped with an integrated Pt100 temperature probe, a pH electrode (Type 405-DPAS-SC-K8S, Mettler-Toledo GmbH, Gieβen, Germany), and gastight tubing (Santoprene® LEZ-SAN, ID 1.6 mm, thickness 1.6 mm, Medorex, Nörten-Hardenberg, Germany) connected to a Luer/Lock sampling valve (Eppendorf AG, Hamburg, Germany).

Abiotic process data

After a short delay during the first two weeks of enrichment (start-up phase) the daily biogas production increased to 0.481 ± 0.09 NL Lreactor volume−1 d−1 for R1, 0.500 ± 0.09 NL Lreactor volume−1 d−1 for R2, 0.538 ± 0.105 NL Lreactor volume−1 d−1 for R3, 0.548 ± 0.096 NL Lreactor volume−1 d−1 for R4, 0.502 ± 0.102 NL Lreactor volume−1 d−1 for R5, and 0.500 ± 0.098 NL Lreactor volume−1 d−1 for R6. The high-N regimes R5 and R6 showed decreasing gas productions to less than 125 NL Lreactor

Reactor performance

Methane contents for all cultivation regimes monitored were stable with means of 53.2–54.5% and maximum fluctuations below ±8% (Fig. 1, Fig. 2, Fig. 3). Except for the later cultivation phases of R5 and R6, the corresponding biogas productions were also at steady-state (Fig. 3). To evaluate the production of biogas, the theoretical methane content was estimated using the empirical formula of Boyle et al. [40] for the media supplied (Table 1) as 48.7% (R1-R4; R5 and R6 until day 93) and 43.3%

Conclusions

Proteotyping is a sensitive tool for characterization of microbial communities in laboratory-scale reactors and full-scale BGP. In addition, proteotyping provides valuable taxonomic and functional data. However, even for parallel cultivations in well controlled cultivations using the same inoculum, the high compositional and functional variances of microbiomes after enrichment did not enable the identification of specific markers for very different process conditions. Interestingly, besides all

Funding

R. Heyer was supported by a grant of the Federal Ministry of Food, Agriculture and Consumer Protection (BMELV) communicated by the Agency for Renewable Resources (FNR), grant no. 22404115 (Biogas-Messprogramm III). R. Kottler and E. Rapp acknowledge support by the European Union (EC) under the project “HighGlycan” (grant no. 278535).

Acknowledgment

The authors acknowledge excellent support of C. Siewert, S. Fischer (both Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany) and C. Best (Otto von Guericke University, Magdeburg, Germany) in the laboratory. Furthermore the support of S. Theuerl (Leibniz Institute for Agricultural Engineering Potsdam-Bornim, Potsdam, Germany) was very valuable for setting up the T-RFLP methods. Finally, the authors want to thank M. Leifheit and J. Greiser (Gesellschaft zur

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