Bioenergy production from agricultural, municipal, and industrial waste is efficiently accomplished through anaerobic digestion to biogas. Biogas produced usually contains 55 – 70% of methane (CH4) and 30 – 45% of carbon dioxide (CO2) and it is stored in gas holders and subsequently used as a potential source of energy [1-4].
Anaerobic fermentation is a natural process in which microorganisms convert biodegradable substrate into biogas. It occurs in marshes, wetlands, river sediments, and also in the digestive tract of ruminants [5,6]. The microorganisms are also active in landfills where they are responsible for biodegradable waste decomposition [2,5,7]. Biogas is the final product of anaerobic metabolism. The process occurs in an anaerobic environment through the consecutive biochemical breakdown of polymers to methane and carbon dioxide [8, 9]. This is a result of the metabolism of different microorganisms which include fermentative microbes (acidogens); hydrogen-producing, acetate-forming microbes (acetogens); and methane-producing microbes (methanogens) [10-13].
On the basis of homologous sequence analysis of 16S rRNAs, methanogens have been classified into one of the three primary kingdoms of living organisms: the Archaea [10, 14, 17]. Recombinant DNA technology is one of the most powerful techniques for characterizing the biochemical and genetic regulation of methanogenesis . This necessitates the selection of genetic markers, an efficient genetic transformation system, and a vector system for genetic recombination as prerequisites . Anaerobic methane generation systems are known as methane bioreactors. The production of methane and growth of methanogenic microorganisms in the bioreactors depend on many factors, including temperature, pH, substrate quality, composition of specific groups of microorganisms and their accumulation of the toxic metabolic products. One of such final products of sulfate-reducing bacteria metabolism is hydrogen sulfide produced in the process of dissimilatory sulfate reduction [6, 7, 20-22].
It is known that hydrogen sulfide is toxic for living organisms and can inhibit enzymes of different groups of microorganisms [6, 20]. The sulfate-reducing bacteria can compete with the methanogens for substrate components, in this case for molecular hydrogen, and produce hydrogen sulfide in high concentration in bioreactors. It, in turn, can inhibit the growth of methanogenic microorganisms and their process of methanogenesis.
Recent progress in the molecular biology of methanogens is reviewed, new digesters are described and improvements in the operation of various types of bioreactors are also discussed. However, the prevalence of the methanogenic populations and sulfate-reducing bacteria in methane bioreactors, their diversity and relationship has never been studied properly.
The aim of this research was to characterize the diversity of the methanogenic microorganisms and sulfate-reducing bacteria using amplification of gene fragments and Illumina sequencing, and to study their relationship and production biogas in the experimental bioreactors.
2 Materials and methods
2.1 Batch anaerobic fermentation tests
A total of six laboratory batch fermenters of volume 120 liters each were used. Fermenters were equipped with a low speed agitator (operated at 60 rpm, 1 min agitation time, 60 min rest), temperature control, monitoring of pH, and sampling valve. On the first day of experiments, all fermenters were filled up with inoculum substrate and maize silage, in ratio 35:65% (v/v). Inoculum and maize silage was collected at a full scale biogas plant in Čejč, Czech Republic. This biogas plant processes as feedstock maize silage and liquid pig manure and it is operated in the mesophilic temperature regime (39°C). Inoculum characteristics were pH=7.3±0.1; DM 3.84%±0.3%; ODM 72.71%±0.4%. For maize silage, dry matter (DM) was 39.15%±0.5 and organic dry matter (ODM) was 99.21%±0.6%. Fermenters were set to 39°C ± 0.1°C. The hydraulic retention time was 26 days. During the fermentation, the quality of biogas was determined daily using X-am® 7000 gas analyzer (Drägerwerk AG & Co. KGaA Germany). Concentration of CH4, CO2, H2S and H2 in the biogas produced was determined. Quantity of biogas produced was measured by the gasometer PREMGAS BK G4 (Elster, Germany) and converted to standard conditions (T0 = 273 K, p0 = 101325 Pa).
2.2 Determination of the physical and chemical characteristics
The physical and chemical characteristics of fermenter content at each bioreactor, including temperature, pH, redox potential, dry matter content, organic dry matter content, biogas composition, sulfate content and acetate content were determined. DM content was determined by oven drying at 105±5°C followed by cooling in a desiccator and weighing until a constant weight. EcoCELL 111 (BMT Medical Technology Ltd., Czech Republic) was used in accordance with the Czech Standard Method (CSN EN 14346 2007) . ODM content was determined by incineration of the samples in a muffle furnace at 550°C ± 5°C in accordance with the Czech Standard Method (CSN EN 15169 2007) , using a muffle furnace LMH 11/12 (LAC, Ltd., Czech Republic). The pH, and redox potential were determined by using pH/Cond meter 3320 (WTW GmbH, Germany) in accordance with the standard (CSN EN 12176 1999) . Temperature of samples was determined by using the high accuracy PT100 RTD thermometer HH804U (OMEGA Engineering, INC., USA). Acetate content was determined using capillary electrophoresis Ionosep 2005 (RECMAN, Czech Republic). For determination of sulfate concentration, the spectrophotometer DR 3800 (Hach Lange GmbH, Germany) was used.
2.3 Isolation of DNA from collected samples
For DNA isolation samples from all 6 reactors were taken. These samples were combined and then examined. The QIAamp Fast DNA Stool Mini Kit (QIAGEN GmbH, Germany) is designed for rapid purification of total DNA from stool samples and was used for DNA extraction from biogas digester samples. DNA extraction was performed in accordance to the manufacturers’ instructions, with minor adjustments as described below. Briefly, 100 mg of sample was washed with 1.4 mL of ASL buffer (QIAGEN GmbH, Germany), heated at 95°C for 10 minutes. After centrifugation, an InhibitEX tablet was put in the supernatant to remove impurities and PCR inhibitors. After thorough centrifugation, 200 μL of the supernatant was added to 15 μL of proteinase K, and 200 μL of buffer AL (QIAGEN GmbH, Germany) was added. The mixture was heated to 70°C for 10 minutes and 200 μL of absolute ethanol was added. The sample mixture was then passed through the QIAamp kit column, followed by two washes with buffers AW1 and AW2 (QIAGEN GmbH, Germany). The DNA was eluted in a volume of 200 μL of elution buffer.
2.4 Amplification of gene fragments and Illumina sequencing
Amplification of 16S rRNA gene fragments was carried out using universal primers for amplification of the V3 and V4 variable regions of the 16S rRNA . The primers were flanked by molecular barcodes for sample identification. The PCR reaction was prepared using Maxima™ Probe qPCR Master Mix (Thermo Fisher Scientific, USA) with cycling conditions as follows: 95°C for 10 min. followed by 30 cycles of incubation at 94°C for 30 s, 60°C for 30 s and 72°C for 120 s, and a final extension step at 72°C for 2 min. PCR products were visualized using electrophoresis on 1.5% agarose gels and purified from the gel using the QIAquick Gel Extraction Kit (QIAGEN GmbH, Germany). DNA was quantified using the Quant-iTPicoGreen dsDNA Assay (Thermo Fisher Scientific, USA) and equimolar amounts of the PCR products were pooled together.
Purified amplicons were paired-end sequenced on an Illumina Mi-Seq platform. QIIME data analysis package was used for 16S rRNA data analysis . Quality filtering on raw sequences was performed in accordance to base quality score distributions, average base content per read and GC distribution in the reads. Chimeras and reads that did not cluster with other sequences were removed. The obtained sequences with qual scores higher than 20 were shortened to the same length of 350 bp and classified with RDP Seqmatch with an operational taxonomic unit (OTU) discrimination level set to 97%. The relative abundance of the taxonomic groups was calculated to the microorganisms detected in this study.
Sequences were compared using the BLAST feature of the National Center for Biotechnology Information (NCBI) . The sequences were uploaded to Mega7 for comparative genomic analyses . Alignments of sequences were performed in Mega7 using Clustal W and clustering was performed by the neighbor-joining method .
The research results were analyzed using software packages Statistica12 (www.statistica.software.informer.com) and Origin7.0 (www.originlab.com). The basic statistic parameters (arithmetic average (M) and standard error (m) of the arithmetic average, M ± m) were calculated using the experimental data. For estimation of the validity of difference between the statistical characteristics of the data, Student’s index was calculated. The difference was valid when P<0.05 [31, 32].
The physical and chemical characteristics of samples taken on the 14th day from the experimental bioreactors, operated at temperature 39°C±0.5, were pH (7.2±0.1), redox (-5.6±0.2), total solids (3.76%±0.3), volatile solids (70.85%±0.9). Biogas composition during the tests is shown in figure 1. Concentration of acetic acid ranged from 460 to 490 mg/L and concentration of sulfate ranged from 305 to 333 mg/L, while the sulfate concentration in fermenters on the first day of experiment ranged from 380 to 450 mg/L. The results of our research show that methane was intensively produced for the first 12 days, after this time, the methane production achieved plateau and was almost unchanged (Fig. 1). This can be explained by the fact that the methanogenic microorganisms can achieve the stationary growth phase after 12 days. As growth slowed, methane production (concentration) achieved a stable level (46.2–49.3%vol) during the 15–26 day period. An interesting pattern was observed in the production of hydrogen and hydrogen sulfide. The level of hydrogen rapidly grew the first 5 days and after that it was reduced. This can be explained by the fact that both hydrogenotrophic methanogens and sulfate-reducing bacteria consume this simple molecule. This is also evident when isolated microorganisms are examined and compared. Both acetotrophic and hydrogenotrophic metanogens were isolated. Sulfate-reducing bacteria can use hydrogen as an electron donor in the process of dissimilatory sulfate reduction. The final product of this process is hydrogen sulfide. The highest concentration of hydrogen sulfide was achieved on the 14th day, which can confirm the high number of sulfate-reducing bacteria (1050 OUT·mL-1) in the bioreactor. Different studies have found both unionized and total hydrogen sulfide concentrations important in inhibition of the SRB bacteria and methanogens. However, our results do not confirm the inhibitory effect of H2S at maximal concentration 390 ppm, as evident by the biogas production trend. The distribution of main genera in the bioreactor was investigated using amplification of 16S rRNA gene and Illumina sequencing. To clarify the genetic relationship of the methanogenic and sulfate-reducing populations of microorganisms in the bioreactor, sample of 16S rRNA gene sequences were compared with sequences of different strains from GenBank. The genomic sequences of the microorganisms are available in GenBank under accession no. KY172649, KY172662, KY172650, KY194790, KY172816, KY172822, KY172821, KY172646, KY172643, KY172641, KY172640, KY172645, KY172824, KY172823, KY126837. The obtained sequences were compared with reference strains using nucleotide Blast:Search. The sequences of the 16S rRNA gene of the methanogens were homologous (98– 99%) to genera of Methanosarcina, Thermogymnomonas, Methanoculleus, and Archaeon (Table 1). The sequences of sulfate-reducing bacteria were homologous (98–99%) to the genera of Desulfomicrobium, Desulfobulbus and Desulfovibrio (Table 2). It should be noted that most described sequences of the methanogenic strains and sulfate-reducing bacteria in GenBank are identified only to the domain, kingdom, family or genus and, in some cases, to species. Most of them are uncultured (www.ncbi.nlm.nih.gov/genbank).
Based on all of the 16S rRNA gene sequences of methanogens and sulfate-reducing bacteria from the bioreactor, a phylogenetic tree demonstrating their genetic relationship was built (Fig. 2, 3). The detected genera of methanogens were homologous with Methanosarcina mazei strain GS14-2aM, uncultured archaeon clone g10-56, uncultured hermogymnomonas p. isolate OTU_11, ncultured hermoplasmatales rchaeon isolate OTU_9, Methanoculleus sp. strain Biowerk_c-HAW (Fig. 2). Another phylogenetic tree was built for 16S rRNA gene sequences of sulfate-reducing bacteria which were homologous with Desulfovibrio desulfuricans strain E4 16S, uncultured Desulfovibrio sp. clone MFC-2-L19, Desulfobulbus propionicus strain DSM 2032, Desulfobulbus sp. clone OC011, uncultured esulfomicrobium p. clone: 3CP(-)_3, Desulfobulbus sp. Prop6, uncultured esulfobulbus p. isolate OTU 265, uncultured sulfate-reducing bacterium clone 2R1V11, uncultured Desulfovibrionales bacterium clone Flu2_26 (Fig. 3).
Percentage ratio of methanogenic and sulfate-reducing microorganisms was calculated by OUT·mL-1 determined from Illumina sequencing (Fig. 4). Results indicate that three genera of both physiological groups of microorganisms were detected in the experimental bioreactors. The dominant genus of methanogens was Methanosarcina, which was 62% of all detected methanogens. Two other genera, Thermogymnomonas and Methanoculleus, were 16 and 2%, respectively, as well as other Archaeons which were not identified to the genus (20%). For sulfate-reducing bacteria, three genera were identified: Desulfomicrobium, Desulfobulbus and Desulfovibrio in percentage ratios of 48, 39.8, and 12%, respectively. Other sulfate-reducing bacteria (0.19%) were not identified to the genus.
Methane is the final product of anaerobic metabolism carried out by communities of hydrolytic bacteria and fungi, acid-producing intermediary organisms, and finally, methanogenic microorganisms . Methane-producing communities are very stable and resilient, but they are also complex and largely undefined. The results of our studies are consistent to other research described in literature [5, 14, 33, 34]. Production of methane depends on many factors, including physical (temperature) and chemical (pH), type of substrate, its concentration and accessibility for microorganisms, composition and the ratio of the microorganisms and their metabolic compounds in the bioreactors. Therefore, bioreactors are a complex fermentative system which includes various oxidations and reduction processes with changes in redox potential. Our research demonstrates that the intensive production of methane in the experimental bioreactor lasts the first 12 days and correlates with the accumulation of hydrogen sulfide. The highest concentration of hydrogen sulfide (390 ppm) was detected on the 14th day and it correlates with the titer of sulfate-reducing bacteria (1050 OUT·mL-1). The sulfate-reducing bacteria (SRB) are a heterogeneous group of microorganisms which use sulfate as an electron acceptor in the process of dissimilatory sulfate reduction [35, 36]. The final product of this process is hydrogen sulfide [6, 20, 22, 37]. For sulfate reduction, SRB need exogenous electron donors, such as: organic compounds (e.g., lactate, propionate, butyrate, ethanol, etc.) and molecular hydrogen. Organic compounds for SRB can be simultaneously electron donors and carbon sources and oxidized completely (to CO2) or incompletely (to acetate and CO2) [6, 7]. SRB, oxidizing organic compounds incompletely, belong to the group called “Acetogenic sulfate-reducing bacteria” . Detected SRB, Desulfovibrio(48%), Desulfomicrobium(39.8%), and Desulfobulbus (12%) genera, are acetogenic microorganisms which oxidize organic compounds, incompletely, to acetate and CO2. Produced acetate is consumed by methanogens e.g., species of the Methanosarcina genus, which are dominant microorganisms (62%) in the bioreactor (see Fig. 4). Our results demonstrated the presence of acetotrophic and hydrogenotrophic methanogenic archaea. The species of the Methanosarcina genus can form multicellular colonies and are anaerobic methanogens. They are widespread in the rumen of cows, sheep, goats, deer, and the large intestine of humans . Recently, there has been a study on M. barkeri, because this species has the enzyme methylamine methyltransferase, which catabolizes methylamines leading to methane production. Methanosarcina sp. possess all three known pathways for methanogenesis, and can utilize a broad spectrum of substrates, including hydrogen. All the other methanogens can utilize no more than two methanogenic substrates and possess a single pathway for methanogenesis . It also has a number of distinct morphological forms, including single cells with and without a cell envelope, as well as multicellular packets and lamina .
The other dominant genus of microbial methanogens in the studied bioreactor was Thermogymnomonas (16%) . The species of this genus were also isolated as a novel thermoacidophilic, cell wall-less archaeon from a solfataric field in Ohwaku-dani, Hakone, Japan. The cells were irregular cocci, sometimes lobed, club-shaped or catenated, and were highly variable in size, ranging from 0.8 to 8.0 µm in diameter . Itoh et al. (2007) identified this strain as Thermogymnomonas acidicola. The strain grew at temperatures in the range 38–68°C (optimally at 60°C) and at pH 1.8–4.0 (optimally at around pH 3.0). Strain IC-189T was an obligate anaerobic and heterotrophic microorganism, requiring yeast extract for growth. Yeast extract, glucose and mannose served as carbon and energy sources. Therefore, strain IC-189T represents a novel genus (order Thermoplasmatales) and species .
The Methanoculleus genus was found in the lowest number among all detected methanogens. The species of the genus were frequently described as playing an important role in different biogas reactor systems [34, 40, 41]. Methanoculleus bourgensis was always detected as the dominant in biogas systems. The prevalence of M. bourgensis in reactors performing syntrophic acetate oxidation under high ammonium concentrations [42, 43, 44], indicates the importance of this methanogen in corresponding communities. Isolation and/or cultivation of M. bourgensis, together with acetate-oxidizing bacteria  such as Clostridium ultunense , led to the assumption that syntrophic association may play an important role for members of the Methanoculleus genus [42, 47]. The 16S rRNA gene sequence analysis classified the isolate as a member of the species M. bourgensis with 99% sequence identity to the 16S rRNA gene of strain MS2T [48, 49]. Genomic DNA of strain BA1 was isolated and sequenced, applying the paired-end protocol on an Illumina MiSeq system [34, 48]. In our studies, using Illumina sequencing, the sequences belonging to this genus were the most often detected in all bioreactors.
The detected genera of methanogens and SRB described can compete by molecular hydrogen (Fig. 5). Hydrogen and CO2 can be used by the methanogens for their growth and methane production and, simultaneously, SRB can also use H2 as a simple electron donor. Therefore, competition for molecular hydrogen may occur between methanogens and SRB. Accordingly, decrease of H2 was observed after the 6th day. Perhaps, the highest consumption of hydrogen by both microorganism groups occurred during this period because afterwards hydrogen levels stabilized. However, SRB produce hydrogen sulfide which can be toxic for methanogens, and may inhibit methanogenesis.
We conclude that studies of the diversity of methanogenic microorganisms under the influence of various factors in the bioreactors require further understanding of the process of biogas production. The sulfate-reducing bacteria can compete with the hydrogenotrophic methanogens for substrate components, in this case molecular hydrogen, and produce hydrogen sulfide in high concentrations in the bioreactors. This, in turn, can inhibit the growth of methanogenic microorganisms and their process of methanogenesis. It can cause unbalance of other microbial communities and instability of the fermentation process. However, this was not tested in our experiments at a maximum concentration of H2S (390 ppm). The study of new isolates is still important for selecting the optimal conditions for methane production process.
This study was supported by Masaryk University (project TAČR GAMA – internal project CTT MU “Technology for qualitative biogas treatment” Registration Project ID: 51047). The authors wish to acknowledge the institutional support of the Faculty of AgriSciences, Mendel University in Brno funded by the Ministry of Education, Youth and Sports of the Czech Republic. The authors express their gratitude to Igor Starunko, Head of Editorial Office of Studia Biologica Journal at Ivan Franko National University of Lviv for his help in the preparation of graphic material.
Scherer P.A., Vollmer G.R., Fakhouri T., Martensen S., Development of methanogenic process to degrade exhaustively the organic fraction of municipal grey waste under thermophilic and hyperthermophilic conditions, Water Sci. Technol., 2000, 41, 83-91 PubMedGoogle Scholar
Schink B., Energetics of syntrophic cooperation in methanogenic degradation, Microb. Mol. Biol. Rev., 1997, 61, 262-280 Google Scholar
Wilkie A., Biomethane from Biomass, Biowaste, and Biofuels, 195-205. In Wall J., Harwood C., Demain A. (ed.), Bioenergy. ASM Press, Washington, 2008 Google Scholar
Krich K., Augenstein D., Batmale J.P., Benemann J., Rutledge B., Salour D., Biomethane from Dairy Waste. A Sourcebook for the Production and Use of Renewable Natural Gas in California. USDA Rural Development, 2005 Google Scholar
Kushkevych I., Dissimilatory sulfate reduction in the intestinal sulfate-reducing bacteria, Studia Biologica, 2016, 10(1), 197-228 Google Scholar
Ahring B., Ibrahim A.A., Mladenovska Z., Effect of temperature increase from 55 to 65°C on performance and microbial population dynamics of an anaerobic reactor treating cattle manure. Water Resour., 2001, 35, 2446-2452 Google Scholar
Ziemiński K., Frąc M., Methane fermentation process as anaerobic digestion of biomass: Transformations, stages and microorganisms. African J. Biotech., 2012, 11(18), 4127-4139 Google Scholar
Demirel B., Scherer P., The roles of acetotrophic and hydrogenotrophic methanogens during anaerobic conversion of biomass to methane: a review. Rev. Environ. Sci. Biotechnol., 2008, 7, 173-190CrossrefGoogle Scholar
Santosh Y., Sreekrishnan T.R., Kohli S., Rana V., Enhancement of biogas production from solid substrates using different techniques,Bioresour. Technol., 2004, 95, 1-10 Google Scholar
Griffin M.E., McMahon K.D., Mackie R.I., Raskin L., Methanogenic population dynamics during start-up of anaerobic digesters treating municipal soild waste and biosolids. Biotechnol. Eng., 2000, 57, 342-355 Google Scholar
Grothenhuis J.T., Smith M., Plugge C.M., Yuansheng X., Lammeren A.A., Stams A.J., et al., Bacteriological composition and structure of granular sludge adapted to different substrates. Appl. Environ. Microbiol., 1991, 57, 1942-1949PubMedGoogle Scholar
Ilyin V.K., Korniushenkova I.N., Starkova L.V., Lauriniavichius K.S., Study of methanogenesis during bioutilization of plant residuals. Acta Astronautica, 2005, 56, 465-470 CrossrefPubMedGoogle Scholar
Zeikus J.G., The biology of methanogenic bacteria, Bact. Rev., 1977, 41, 514-541 Google Scholar
Amon T., Amon B., Kryvoruchko V., Zollitsch W., Mayer K., Gruber L., Biogas production from maize and dairy cattlemanure – influence of biomass composition on the methane yield, Agric. Ecosys.Environ.,2007,118, 173-182 CrossrefGoogle Scholar
Kushkevych I.V., Effect of hydrogen sulfide at differential concentrations on the process of dissimilatory sulfate reduction by the bacteria Desulfovibrio piger, Sci Notes of Ternopil Nat. Ped. Univ. Series Biol, 2013, 4(57), 74-80 Google Scholar
Kushkevych I.V., Dissimilatory sulfate reduction by various Desulfovibrio sp. strains of the human intestine, Microbiol. and Biotechnol., 2013, 3(23): 50-63Google Scholar
Kushkevych I.V., Dissimilatory sulfate reduction in bacterium Desulfovibrio piger Vib-7 under the effect of medium with differential acidity, American J. Microbiol. & Biotechnol, 2014, 1(2), 49-55. Google Scholar
Czech Standards Institute. Characterization of waste – Determination of loss on ignition in waste, sludge and sediments ČSN EN 15169, 2007 Google Scholar
Czech Standards Institute. Characterization of sludge – Determination of pH-value ČSN EN 12176, 1999 Google Scholar
Nossa C.W., Oberdorf W.E., Yang L., Aas J.A., Paster B.J., Desantis T.Z., et al., Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome, World J. Gastroenterol., 2010, 16(33), 4135-4144 Web of ScienceCrossrefPubMedGoogle Scholar
Caporaso J.G., Kuczynski J., Stombaugh J., Bittinger K., Bushman F.D., Costello E.K., et al., QIIME allows analysis of high-throughput community sequencing data. Nat. Methods, 2010, 7(5), 335-336 Web of SciencePubMedCrossrefGoogle Scholar
Kearse M., Moir R., Wilson A., Stones-Havas S., Cheung M., Sturrock S., et al., Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics, 2012, 28(12), 1647-9 PubMedWeb of ScienceCrossrefGoogle Scholar
Chen P.Y., Popovich P.M., Correlation: Parametric and Nonparametric Measures. Sage University Papers Series on Quantitative Applications in the Social Sciences, 2002 Google Scholar
Bailey N.T.J., Statistical Methods in Biology, third ed. Cambridge University Press, Cambridge, 1995 Google Scholar
Itoh T., Yoshikawa N., Takashina T., Thermogymnomonasacidicola gen. nov., sp. nov., a novel thermoacidophilic, cell wall-less archaeon in the order Thermoplasmatales, isolated from a solfataric soil in Hakone, Japan, Int. J. Syst. Evol. Microbiol., 2007, 57(11), 2557-61 CrossrefPubMedGoogle Scholar
Maus I., Wibberg D., Winkler A., Pühler A., Schnürer A., Schlütera A., Complete Genome Sequence of the Methanogen Methanoculleus bourgensis BA1 Isolated from a Biogas Reactor Genome, Announcements, 2016, 4(3) e00568-16 Google Scholar
Kushkevych I.V., Dose-dependent effect of electron acceptor and donor on dissimilatory sulfate reduction by bacteria Desulfovibrio piger Vib-7 of human intestine, Studia Biologica, 2014, 8(1), 103-116 Google Scholar
Kushkevych I.V., Growth of the Desulfomicrobium sp. strains, their sulfate- and lactate usage,production of sulfide and acetate by the strains isolated from the human large intestine, Microbiol. Discovery, 2014, 2, 1-8 CrossrefGoogle Scholar
Kushkevych I., Bolis M., Bartoš M., Model-based characterization of the kinetic parameters of dissimilatory sulfate reduction under the effect of different initial density of Desulfovibrio piger Vib-7 bacterial cells, The Open Microbiol. J., 2015, 9, 55-69 Google Scholar
Ferry J., Methanogenesis: Ecology, Physiology, Biochemistry & Genetics, Chapman & Hall Inc, New York, 1993 Google Scholar
Conway de Macario E., Maeder D. L., Macario A.J.L., Breaking the mould: archaea with all four chaperoning systems, Biochem. and Biophys. Res. Commun., 2003, 301, 811-812 Google Scholar
Jaenicke S., Ander C., Bekel T., Bisdorf R., Dröge M., Gartemann K.H. et al., Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing, PLoS One, 2011, 6, e14519 PubMedCrossrefWeb of ScienceGoogle Scholar
Stolze Y., Zakrzewski M., Maus I., Eikmeyer F., Jaenicke S., Rottmann N.,et al., Comparative metagenomics of biogas-producing microbial communities from production-scale biogas plants operating under wet or dry fermentation conditions, Biotechnol. Biofuels, 2015, 8, 14 CrossrefGoogle Scholar
Westerholm M., Levén L., Schnürer A., Bioaugmentation of syntrophic acetate-oxidizing culture in biogas reactors exposed to increasing levels of ammonia, Appl. Environ. Microbiol., 2012, 78, 7619-7625 Web of SciencePubMedCrossrefGoogle Scholar
Westerholm M., Müller B., Isaksson S., Schnürer A., Trace element and temperature effects on microbial communities and links to biogas digester performance at high ammonia levels, Biotechnol. Biofuels, 2015, 8, 154 CrossrefPubMedWeb of ScienceGoogle Scholar
Moestedt J., Müller B., Westerholm M., Schnürer A., Ammoniathreshold for inhibition of anaerobic digestion of thin stillage and the importance of organic loading rate, Microb. Biotechnol., 2016, 9, 180-194 CrossrefPubMedGoogle Scholar
Fotidis I.A., Karakashev D., Angelidaki I., Bioaugmentation with anacetate-oxidising consortium as a tool to tackle ammonia inhibition ofanaerobic digestion, Bioresour Technol., 2013, 146, 57-62 CrossrefGoogle Scholar
Schnürer A., Schink B.H., Svensson B.H., Clostridium ultunense sp. nov., a mesophilic bacterium oxidizing acetate in syntrophic association with a hydrogenotrophic methanogenic bacterium, Int. J. Syst. Bacteriol., 1996, 46, 1145-1152 CrossrefPubMedGoogle Scholar
Fotidis I.A., Wang H., Fiedel N.R., Luo G., Karakashev D.B., Angelidaki I., Bioaugmentation as a solution to increase methane production from an ammonia-rich substrate, Environ. Sci. Technol., 2014, 48, 7669-7676 CrossrefWeb of SciencePubMedGoogle Scholar
Maus I., Wibberg D., Stantscheff R., Stolze Y., Blom J., EikmeyerF.G.,et al., Insights into the annotated genome sequence of Methanoculleus bourgensis MS2 (T), related to dominant methanogens in biogas-producing plants, J. Biotechnol., 2014, 201, 43-53 Web of ScienceGoogle Scholar
Wibberg D., Blom J., Jaenicke S., Kollin F., Rupp O., Scharf B., et al., Complete genome sequencing of Agrobacterium sp.H13-3, the former Rhizobium lupine H13-3, reveals a tripartite genome consisting of a circular and a linear chromosome and an accessory plasmid but lacking a tumor-inducing Ti-plasmid, J. Biotechnol., 2011, 155, 50-62 CrossrefGoogle Scholar
About the article
Published Online: 2017-04-20
Conflict of Interest: Authors state no conflict of interest
Citation Information: Open Life Sciences, Volume 12, Issue 1, Pages 82–91, ISSN (Online) 2391-5412, DOI: https://doi.org/10.1515/biol-2017-0009.
© 2017 Ivan Kushkevych et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0