Quantifying electron fluxes in
methanogenic microbial communities
Junicke, H., 2015
Quantifying electron fluxes in methanogenic microbial communities
Cover image: Illustration of the electron transfer between an acetogenic bacterium (electron source) and a methane-producing archaeon (electron sink).
Quantifying electron fluxes in
methanogenic microbial communities
PROEFSCHRIFT
ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,
op gezag van de Rector Magnificus Prof. Ir. K.Ch.A.M. Luyben, voorzitter van het College voor Promoties,
in het openbaar te verdedigen op dinsdag 8 december 2015 om 10:00 uur
door
Helena JUNICKE
Diplom-Biochemikerin, Freie Universität Berlin, Duitsland, geboren te Solikamsk, Rusland
This dissertation has been approved by the
promotor: Prof. Dr. Dr. h.c. Ir. M.C.M. van Loosdrecht and copromotor: Dr. Ir. R. Kleerebezem
Composition of the doctoral committee:
Rector Magnificus chairperson
Prof. Dr. Dr. h.c. Ir. M.C.M. van Loosdrecht promotor
Dr. Ir. R. Kleerebezem copromotor
Independent members:
Prof. Dr. Ir. J.B. van Lier Faculty of Applied Science, TU Delft Prof. Dr. Ir. A.J.M. Stams Wageningen University, The Netherlands Prof. Dr. rer. nat. B. Schink Konstanz University, Germany
Dr. W.F.M. Roeling VU Amsterdam, The Netherlands
Prof. Dr. Ir. J.J. Heijnen TU Delft, reserve member
This research is supported by the Dutch Technology Foundation STW, which is part of the Netherlands Organisation for Scientific Research (NWO) and partly funded by the Ministry of Economic Affairs (project number 11603).
ISBN: 978-94-6186-533-5 © 2015 Helena Junicke
Table of contents
Summary/Samenvatting i
Chapter 1 Introduction and thesis outline 1
Chapter 2 Absolute quantification of individual biomass concentrations in a methanogenic coculture
19
Chapter 3 Impact of the hydrogen partial pressure on lactate degradation in a coculture of Desulfovibrio sp. G11 and Methanobrevibacter arboriphilus DH1
37
Chapter 4 Limitation of syntrophic coculture growth by the acetogen 59
Chapter 5 Kinetic and thermodynamic control of butyrate conversion in non-defined methanogenic communities
81
Chapter 6 Outlook 109
Acknowledgements 120
Curriculum Vitae 123
Summary/Samenvatting
i
Summary
Anaerobic digestion is a widely applied process in which close interactions between different microbial groups result in the formation of renewable energy in the form of biogas. Nevertheless, the regulatory mechanisms of the electron transfer between acetogenic bacteria and methanogenic archaea in the final steps of the anaerobic digestion process are not fully understood. The electron flux of each syntrophic partner is defined as the product of the biomass-specific electron transfer rate and the individual biomass concentration. Therefore, to investigate how these biomass-specific electron fluxes are regulated, individual biomass concentrations need to be determined. So far, the lack of experimental techniques has posed a major obstacle to measuring individual biomass concentrations and thus our quantitative understanding of interspecies electron transfer in methanogenic environments remained limited. Novel molecular tools hold the promise for an accurate determination of individual biomass concentrations.
This thesis aimed to elucidate the kinetic and thermodynamic control mechanisms of interspecies hydrogen transfer in defined and non-defined methanogenic communities. For this to achieve, interspecies electron fluxes were quantified by a combination of direct measurement and modelling. The chapters of this thesis present advances in the measurement of individual biomass concentrations and address important questions on energy sharing in syntrophic communities and the principles of microbial survival at the thermodynamic limits of life.
Chapter 2 describes a novel qPCR method to quantify individual biomass concentrations in a syntrophic methanogenic coculture of Desulfovibrio sp. G11 and Methanospirillum hungatei JF1. Existing qPCR methods usually rely on several conversion factors such as gene copy numbers of the cell and cell concentrations, introducing potential error sources and inaccuracies. The presented qPCR approach, in contrast, benefits from the direct correlation of the qPCR signal to the individual biomass concentrations and thus from higher accuracy. The accurate measurement of individual biomass concentrations in syntrophic methanogenic communities finally allows to validate biomass-specific conversion rates and to improve the description of anaerobic systems. In Chapter 3, the kinetic and thermodynamic effect of an imposed change in the hydrogen partial pressure on lactate conversion was studied using the syntrophic coculture of Desulfovibrio sp. G11 and Methanobrevibacter arboriphilus DH1. The biomass-specific lactate consumption rate increased three-fold as the hydrogen partial pressures decreased from 1200 ppm to 250 ppm. Since all partial reactions were exergonic, the observed inhibitory effect of hydrogen on lactate conversion was not due to thermodynamics but was rather an effect of reaction kinetics. An
adequate consideration of mass-transfer phenomena allowed for the determination of several kinetic parameters including the 50 % hydrogen inhibition constant of lactate conversion (KiH2,Lacox), the maximum biomass-specific lactate consumption rate of Desulfovibrio sp. G11 (qLac,max) and the affinity constant for hydrogen uptake of Methanobrevibacter arboriphilus DH1 (KS,H2). Both, the KS,H2 and KiH2,Lacox,were considerably higher than the hydrogen partial pressure prevailing during syntrophic lactate degradation. These results demonstrate that the acetogen was operating at qLac,max whereas the hydrogenotrophic methanogen was working far below its maximum capacity due to hydrogen limitation. The tight coupling of syntrophic partner organisms suggests that these microbial consortia are susceptible to small environmental changes. However, the overcapacity of hydrogenotrophic methanogens reflects the actual robustness of methanogenic ecosystems and shows first indication that coculture growth is rather restricted by the acetogen and not the methanogen.
In Chapter 4, the novel qPCR approach described in Chapter 2 was applied for the direct measurement of individual biomass concentrations in the syntrophic coculture of Desulfovibrio sp. G11 and Methanospirillum hungatei JF1 grown on lactate and formate. This methodology enabled not only to accurately validate model-derived biomass-specific rates and growth yields, but also to prove that the acetogen is the growth-limiting partner during syntrophic lactate conversion. The observed overcapacity of hydrogenotrophic methanogens reflects the robustness of syntrophic methanogenic communities which is in contrast to the expectation that these consortia are susceptible even to slight imbalances. In addition, the measurement of biomass-specific rates revealed different growth strategies of the syntrophic partners during syntrophic lactate conversion. The biomass-specific electron transfer rate of the hydrogenotrophic methanogen was three-fold higher compared to its acetogenic partner. This is due to the low methanogenic biomass yield per electron mole of substrate which is determined by thermodynamics.
In Chapter 5, the kinetic and thermodynamic control mechanisms of electron transfer were investigated using chemostat grown non-defined methanogenic enrichments on butyrate and ethanol. It was shown that elevated hydrogen partial pressures have an inhibitory effect on butyrate and ethanol conversion. Compared to the Anaerobic Digestion Model No. 1, a ten times lower hydrogen inhibition constant on butyrate conversion was found in this study, indicating a much stronger inhibition by hydrogen. The distinct microbial groups of the enrichment followed different growth strategies during syntrophic butyrate and ethanol conversion, which is in line with previous studies in a syntrophic coculture on lactate (Chapter 4). The hydrogenotrophic methanogens exhibited a 2-fold higher biomass-specific electron transfer rate compared to the
Summary/Samenvatting
iii butyrate-utilizing acetogen. The overcapacity of hydrogenotrophic methanogens previously observed in defined cocultures on lactate (Chapter 3 and 4), was also noted in the non-defined enrichments on butyrate and ethanol (Chapter 5). These results significantly contribute to a better understanding of the regulatory mechanisms in anaerobic digestion processes, implying that syntrophic methanogenic ecosystems are not as easily affected by environmental perturbations as previously believed.
In addition to these kinetic limitations, Chapter 5 demonstrated the need to consider thermodynamic restrictions during syntrophic butyrate conversion, since the biomass-specific butyrate consumption rate (qBut) decreased significantly and remained close to zero when anaerobic butyrate conversion became endergonic. More insight was gained on how the syntrophic partner organisms share the little energy available in anaerobic methanogenic ecosystems. During syntrophic butyrate conversion, an unequal energy distribution between the butyrate-utilizing species (17 %), the hydrogenotrophic methanogens (9 – 10 %) and the acetoclastic methanogens (73 – 74 %) was found. These findings are consistent with previous coculture studies on lactate where the smallest fraction of the total energy (17 – 21 %) was attributed to the hydrogenotrophic methanogen (Chapter 3 and 4). As a result, hydrogenotrophic methanogens showed a low biomass yield that requires a large qe to equalize specific growth rates in the coculture. The observed growth strategies are a direct consequence of energy disproportion and illustrate the impact of thermodynamics on growth kinetics.
As another interesting observation, butanol was formed at bicarbonate limiting conditions of hydrogenotrophic methanogenesis and increasing hydrogen partial pressures (> 390 ppm). These observations indicate that the hydrogen partial pressure may not only play a key role in the kinetic and thermodynamic regulation of syntrophic methanogenic conversions, but is also of great importance for shifting the electron fluxes towards reduced product formation.
Samenvatting
Anaerobe vergisting is een alom toegepast proces waarbij nauwe interacties tussen verschillende microbiële groepen resulteren in de vorming van hernieuwbare energie in de vorm van biogas. Desalniettemin zijn de regulerende mechanismen achter de elektronenoverdracht tussen acetogene bacteriën en methanogene archaea in de laatste stappen van het anaerobe vergistingsproces niet volledig bekend. De elektronenflux van elk van de syntrofe partners is gedefinieerd als het product van de biomassa-specifieke elektronenoverdrachtssnelheid en de individuele biomassaconcentratie. Om te onderzoeken hoe deze biomassa-specifieke elektronenfluxen zijn gereguleerd, dienen de individuele biomassaconcentraties te worden bepaald. Tot nu toe heeft het gebrek aan experimentele technieken een belangrijk obstakel gevormd bij het meten van individuele biomassaconcentraties en bleef zodoende ons kwantitatieve begrip van intersoortelijke elektronenoverdracht in methanogene milieus beperkt. Nieuwe moleculaire tools beloven een nauwkeurige bepaling van individuele biomassaconcentraties.
Dit proefschrift beoogde de kinetische en thermodynamische controlemechanismen van intersoortelijke waterstofoverdracht in gedefinieerde en niet-gedefinieerde methanogene gemeenschappen te verhelderen. Om dit te bereiken werden intersoortelijke elektronenfluxen gekwantificeerd door een combinatie van directe metingen en modellering. De hoofdstukken in dit proefschrift presenteren de vorderingen bij het meten van individuele biomassaconcentraties en beantwoorden belangrijke vragen over de deling van energie in syntrofe gemeenschappen en de principes van microbieel voortbestaan aan de thermodynamische grenzen van het leven. Hoofdstuk 2 beschrijft een nieuwe qPCR-methode om individuele biomassaconcentraties in een syntrofe methanogene co-cultuur van Desulfovibrio sp. G11 en Methanospirillum hungatei JF1 te kwantificeren. Bestaande qPCR-methoden zijn doorgaans afhankelijk van verscheidene omrekeningsfactoren, zoals genkopieaantallen van de cel en celconcentraties, die mogelijke fouten en onnauwkeurigheden introduceren. De voorgestelde qPCR-aanpak maakt daarentegen gebruik van de directe correlatie tussen het qPCR-signaal en de individuele biomassaconcentraties en biedt daardoor een hogere nauwkeurigheid. De accurate bepaling van individuele biomassaconcentraties in syntrofe methanogene gemeenschappen maakt het uiteindelijk mogelijk biomassa-specifieke omzettingssnelheden te valideren en de beschrijving van anaerobe systemen te verbeteren.
In Hoofdstuk 3 werd het kinetische en thermodynamische effect van een opgelegde verandering van de partiële waterstofspanning op de omzetting van lactaat bestudeerd met behulp van de syntrofe co-cultuur van Desulfovibrio sp. G11 en Methanobrevibacter arboriphilus DH1. De
Summary/Samenvatting
v biomassa-specifieke lactaatopnamesnelheid verdrievoudigde wanneer de partiële waterstofspanning afnam van 1200 ppm naar 250 ppm. Aangezien alle deelreacties exergoon waren, was het waargenomen remmende effect van waterstof op de omzetting van lactaat niet te wijten aan de thermodynamica, maar eerder een gevolg van de reactiekinetiek. Een adequate afweging van stofoverdrachtsverschijnselen maakte de bepaling van verscheidene kinetische parameters mogelijk, waaronder de 50% inhibitieconstante van waterstof op de omzetting van lactaat (KiH2,Lacox), de maximale biomassa-specifieke lactaatopnamesnelheid van Desulfovibrio sp. G11 (qLac,max) en de affiniteitsconstante voor waterstofopname van Methanobrevibacter arboriphilus DH1 (KS,H2). Zowel de KS,H2 als de KiH2,Lacox was aanzienlijk hoger dan de heersende partiële waterstofspanning tijdens syntrofe lactaatafbraak. Deze resultaten laten zien dat de acetogeen opereerde bij qLac,max terwijl de hydrogenotrofe methanogeen ver onder zijn maximale capaciteit werkte als gevolg van waterstoflimitatie. De nauwe koppeling tussen syntrofe partnerorganismen suggereert dat deze microbiële consortia gevoelig zijn voor kleine omgevingsveranderingen. Echter, de overcapaciteit van de hydrogenotrofe methanogenen weerspiegelt de werkelijke robuustheid van methanogene ecosystemen en geeft een eerste indicatie dat groei van de co-cultuur eerder beperkt wordt door de acetogeen dan door de methanogeen.
In Hoofdstuk 4 werd de nieuwe qPCR-aanpak, beschreven in Hoofdstuk 2, toegepast voor de directe meting van individuele biomassaconcentraties in de syntrofe co-cultuur van Desulfovibrio sp. G11 en Methanospirillum hungatei JF1 gekweekt op lactaat en formaat. Deze methodologie maakte het niet alleen mogelijk om nauwkeurig de met een model afgeleide biomassa-specifieke snelheden en biomassaopbrengsten te valideren, maar ook om te bewijzen dat de acetogeen de groeibeperkende partner is tijdens syntrofe lactaatomzetting. De waargenomen overcapaciteit van hydrogenotrofe methanogenen reflecteert de robuustheid van syntrofe methanogene gemeenschappen, hetgeen in contrast staat met de verwachting dat deze consortia gevoelig zijn voor zelfs geringe onevenwichtigheden. Daarnaast onthulde de meting van biomassa-specifieke snelheden verschillende groeistrategieën van de syntrofe partners tijdens de syntrofe omzetting van lactaat. De biomassa-specifieke elektronenoverdrachtssnelheid van de hydrogenotrofe methanogeen was driemaal zo hoog als dat van zijn acetogene partner. Dit is het gevolg van de lage methanogene biomassaopbrengst per elektron-mol substraat die bepaald wordt door de thermodynamica.
In Hoofdstuk 5 werden de kinetische en thermodynamische controlemechanismen van elektronenoverdracht onderzocht met behulp van niet-gedefinieerde methanogene verrijkingscultures, gekweekt in een chemostaat gevoed met butyraat en ethanol. Er werd
aangetoond dat verhoogde partiële waterstofspanningen een remmend effect hebben op de omzetting van butyraat en ethanol. In vergelijking met het Anaerobic Digestion Model No. 1 werd in deze studie een tienmaal lagere inhibitieconstante van waterstof op de omzetting van butyraat gevonden, wat wijst op een veel sterkere remming door waterstof. De verschillende microbiële groepen in de verrijkingscultuur volgden verschillende groeistrategieën tijdens de syntrofe omzetting van butyraat en ethanol, hetgeen in lijn is met eerdere studies in een syntrofe co-cultuur op lactaat (Hoofdstuk 4). De hydrogenotrofe methanogenen vertoonden een tweemaal hogere biomassa-specifieke elektronenoverdrachtssnelheid dan de butyraat-consumerende acetogeen. De overcapaciteit van hydrogenotrofe methanogenen, eerder waargenomen in gedefinieerde co-cultures gevoed met lactaat (Hoofdstuk 3 en 4), werd ook waargenomen in de niet-gedefinieerde verrijkingscultures op butyraat en ethanol (Hoofdstuk 5). Deze resultaten dragen significant bij aan een beter begrip van de regulerende mechanismen in anaerobe vergistingsprocessen en impliceren dat syntrofe methanogene ecosystemen niet zo gemakkelijk beïnvloed worden door omgevingsveranderingen als eerder aangenomen.
Behalve deze kinetische beperkingen, liet Hoofdstuk 5 de noodzaak zien om rekening te houden met thermodynamische beperkingen tijdens syntrofe butyraatomzetting, aangezien de biomassa-specifieke butyraatopnamesnelheid (qBut) significant afnam en nagenoeg nul bleef wanneer de anaerobe omzetting van butyraat endergoon werd. Meer inzicht werd verkregen in hoe de syntrofe partnerorganismen de beperkte energie beschikbaar in anaerobe methanogene ecosystemen delen. Tijdens de syntrofe omzetting van butyraat, werd een ongelijke energieverdeling geconstateerd tussen de butyraat-consumerende soorten (17%), de hydrogenotrofe methanogenen (9-10%) en de acetoclastische methanogenen (73-74%). Deze bevindingen zijn consistent met eerdere co-cultuur studies met lactaat waar de kleinste fractie van de totale energie (17-21%) werd toebedeeld aan de hydrogenotrofe methanogenen (Hoofdstuk 3 en 4). Als gevolg hiervan vertoonden de hydrogenotrofe methanogenen een lage biomassaopbrengst die een hoge qe vereist om de specifieke groeisnelheden in de co-cultuur te vereffenen. De waargenomen groeistrategieën komen direct voort uit de energetische onbalans en illustreren de invloed van thermodynamica op de groeikinetiek.
Een andere interessante observatie was de vorming van butanol onder de bicarbonaat-gelimiteerde omstandigheden van hydrogenotrofe methanogenese en toenemende partiële waterstofspanningen (>390 ppm). Deze waarnemingen wijzen erop dat de partiële waterstofspanning mogelijk niet alleen een sleutelrol speelt in de kinetische en thermodynamische regulatie van syntrofe methanogene omzettingen, maar ook van groot belang is voor het verschuiven van de elektronenfluxen in de richting van verminderde productvorming.
Summary/Samenvatting
CHAPTER 1
Introduction
Anaerobic digestion is the bioconversion of organic matter to carbon dioxide and methane, a gas mixture commonly referred to as biogas. This process involves the interaction of distinct microbial groups and encompasses four major steps: hydrolysis, acidogenesis, acetogenesis and methanogenesis (Christy et al. 2014; McCarty and Smith 1986; McInerney et al. 2008; Schink 1997; Shrestha and Rotaru 2014; Sieber et al. 2012) (Figure 1.1). In the first two steps organic polymers are hydrolysed into monomeric building blocks that are further converted to organic acids, including short-chain fatty acids, alcohols and lactate. The two subsequent steps comprise the conversion of these organic molecules to acetate, CO2 and reducing equivalents in the form of hydrogen, formate or electrons which serve as substrate for methane-producing archaea.
Figure 1.1: Schematic overview of the anaerobic digestion process
Since methanogenic archaea can utilize only a limited range of substrates they strongly depend on acetogenic bacteria for substrate supply. Acetogens in turn depend on methanogens for product removal as product accumulation would render the acetogenic reaction energetically unfavorable. The strong mutual dependency observed in these microbial communities is referred to as syntrophy and the transfer of reducing equivalents is denoted as interspecies electron transfer (Kleerebezem and Stams 2000; Schink 1997; Schink and Friedrich 1994; Sieber et al. 2014; Stams 1994; Stams and Plugge 2009). The two most important mechanisms of interspecies electron transfer in methanogenic ecosystems include the indirect interspecies electron transfer
Chapter 1
3 (IIET) via hydrogen or formate and the direct interspecies electron transfer (DIET) via conductive connections between cells.
Indirect interspecies electron transfer
Interspecies hydrogen transfer was first observed in the Methanobacillus omelianskii culture converting ethanol to acetate and methane (Bryant et al. 1967). This culture, initially believed to constitute a single species, was shown to consist of two syntrophic partner organisms, strain S and strain M.o.H, neither of which being capable to catalyse the reaction without the other. However, interspecies hydrogen transfer is not restricted to methanogenic systems where CO2 serves as final electron acceptor. Figure 1.2 gives an example of a non-methanogenic coculture with fumarate as the final electron acceptor (Rotaru et al. 2012).
Figure 1.2: Example of interspecies hydrogen and formate transfer in a syntrophic coculture of
Pelobacter carbinolicus and Geobacter sulfurreducens.
Besides hydrogen, which was regarded the prime electron transfer molecule for long time, formate is an accepted alternative interspecies electron shuttle (Boone et al. 1989; De Bok et al. 2004; Stams and Plugge 2009; Thiele and Zeikus 1988). Interspecies formate transfer was frequently demonstrated in syntrophic cocultures on butyrate or propionate (De Bok et al. 2004; Dong and Stams 1995; Sousa et al. 2007; Stams and Dong 1995). In practice, the contribution of either hydrogen or formate in interspecies electron transfer is often difficult to unravel. This is due to the low concentrations of these electron carriers in syntrophic environments and the dual ability of many species for hydrogen and formate transfer (Stams 1994). Studies on a syntrophic coculture of Pelobacter carbinolicus and a hydrogenase deletion mutant (∆hybL) of Geobacter sulfurreducens revealed an overexpression of the formate dehydrogenase (∆fdnG) gene of Geobacter sulfurreducens, demonstrating the occurrence of interspecies formate transfer when hydrogen transfer was inhibited (Rotaru et al. 2012). Figure 1.2 illustrates the mechanism of interspecies formate transfer, together with hydrogen transfer, in the syntrophic coculture of Pelobacter carbinolicus and Geobacter sulfurreducens.
Apart from interspecies hydrogen and formate transfer, several redox shuttles have been recognized to be involved in IIET. These mediators include but are not limited to humic substances (Lovley and Blunt-Harris 1999; Lovley et al. 1996; Newman and Kolter 2000), sulphur compounds (Biebl and Pfennig 1978; Kaden et al. 2002; Milucka et al. 2012; Straub and Schink 2004) and flavins (Brutinel and Gralnick 2012; Marsili et al. 2008; von Canstein et al. 2008). For a more extensive review on the role of redox mediators in exocellular electron transfer, the reader is referred to (Shrestha and Rotaru 2014; Stams et al. 2006).
Direct interspecies electron transfer
DIET is a more recently discovered mechanism where electrons are exchanged through conductive connections between syntrophic partners (Reguera et al. 2005). The two most common DIET processes include the electron transfer via conductive biological contacts (pili and cytochromes) and the conductive mineral mediated electron transfer (Shrestha and Rotaru 2014). Since the first discovery of pili-mediated DIET in cocultures of Geobacter metallireducens and Geobacter sulfurreducens much attention was given to the phenotypic and molecular analysis of Geobacter species (Shrestha et al. 2013a; Shrestha et al. 2013b; Summers et al. 2010). Rotaru et al. (2012) observed successful syntrophy between G. metallireducens and the double mutant of G. sulfurreducens (∆hybL∆fdnG) deficient in hydrogen and formate uptake. Formation of close associations between the syntrophic partners seems to be a prerequisite for pili-mediated transfer and was consistently reported, in contrast to IIET where close contact between the syntrophic partners is not essentially required (Shrestha et al. 2013a; Summers et al. 2010). Most recently, G. metallireducens was also shown to operate syntrophically with two acetoclastic methanogens via DIET (Rotaru et al. 2014a; Rotaru et al. 2014b). The released electrons served for the direct reduction of CO2 to CH4.
Besides pili, cytochromes were shown to be essential for DIET (Ding et al. 2008; Qian et al. 2011). During syntrophic cooperation of G. sulfurreducens with G. metallireducens via DIET, high expression levels of OmcS, an extracellular c-type cytochrome surrounding the pili of G. sulfurreducens, were detected (Leang et al. 2010; Shrestha et al. 2013a; Shrestha et al. 2013b; Summers et al. 2010). However, the specific function of extracellular cytochromes towards DIET in G. metallireducens is not yet fully understood. Figure 1.3a illustrates the mechanism of pili-mediated and cytochrome-assisted DIET in a methanogenic coculture (Rotaru et al. 2014b).
Chapter 1
5
Figure 1.3: Example of DIET mediated by (a) electrically conductive pili and cytochromes in the methanogenic coculture of Geobacter metallireducens and Methanosaeta harudinacea, and (b) conductive minerals in the syntrophic coculture of Geobacter metallireducens and Geobacter
sulfurreducens.
Externally supplied conductive minerals such as nano-magnetite (Kato et al. 2012a, b; Liu et al. 2015), biochar (Chen et al. 2014) or granulated activated carbon (Liu et al. 2012) provide alternative electrical connections between cells as a substitute or in addition to biological connections. The energy investment of syntrophic communities to establish biological cell connections can therefore be reduced (Shrestha and Rotaru 2014). Kato et al. (2012b) showed that the addition of magnetite nano-particles facilitated the electron transfer between G. sulfurreducens and Thiobacillus denitrificans. Furthermore, Liu et al. (2015) demonstrated that magnetite may serve as substitute for OmcS in OmcS-deficient mutants of G. sulfurreducens in coculture with G. metallireducens (Figure 1.3b). Syntrophic growth of cocultures deficient in cytochromes or pili was resumed following addition of granulated activated carbon (Liu et al. 2012).
Energetic constraints in syntrophic methanogenic ecosystems
Interspecies electron transfer and syntrophy are the results of energetic limitations which are often encountered in anaerobic conversions and less frequently in aerobic processes. Table 1.1 shows
Table 1.1: Gibbs energy change under standard conditions (pH 7.0 and 298.15 K), ΔG01, for different
aerobic and anaerobic catabolic reactions.
No. Designation Catabolic reactions ΔG01 [kJ/mol]
1 Aerobic glucose conversion C6H12O6+ 6 O2→ 6 HCO3−+ 6 H++ 6 H2O -2843.1 2 Aerobic ethanol conversion C2H5OH + 3 O2→ 2 HCO3−+ 2 H++ H2O -1308.9 3 Anaerobic glucose conversion C6H12O6+ 4 H2O → 2 C2H3O2−+ 2 HCO3−+ 4 H++ 4 H2 -206.3 4 Anaerobic ethanol conversion C2H5OH + H2O → C2H3O2−+ H++ 2 H2 +2.7 5 Anaerobic lactate conversion C3H5O3−+ 2 H2O → C2H3O2−+ HCO3−+ H++ 2 H2 -7.7 6 Anaerobic butyrate conversion C4H7O2−+ 2 H2O → 2 C2H3O2−+ H++ 2 H2 +48.2 7 Anaerobic propionate conversion C3H5O2−+ 3 H2O → C2H3O2−+ HCO3−+ H++ 3 H2 +76.4 8 Acetoclastic methanogenesis C2H3O−2+ H2O → HCO3−+ CH4 -31.2 9 Hydrogenotrophic methanogenesis H2+ 0.25 HCO3−+ 0.25 H+→ 0.25 CH4+ 0.75 H2O -33.9
the Gibbs energy change for a set of aerobic and anaerobic reactions under standard conditions, pH 7 and 298.15 K. Most of the anaerobic conversions proceed close to thermodynamic equilibrium with only a fraction of the Gibbs energy change observed in aerobic processes (Heijnen and Kleerebezem 2010; Kleerebezem and Stams 2000; Schink 1997; Thauer et al. 1977).
Some of these anaerobic conversions were even reported to occur at Gibbs energy changes much closer to zero than the postulated minimum energy of -20 kJ/mol (Conrad et al. 1986; Dwyer et al. 1988; Hickey and Switzenbaum 1991; Kleerebezem and Stams 2000; Schink 1997; Seitz et al. 1990a; Smith and McCarty 1989). To date, only few studies have experimentally addressed the question how microorganisms can survive at the thermodynamic boundaries of life and how the syntrophic partners share the little amount of energy available (Dwyer et al. 1988; Seitz et al. 1988; Seitz et al. 1990a, b).
A small window of opportunity exists for syntrophic anaerobic cooperation. Taking the example of syntrophic butyrate conversion, Figure 1.4 shows the Gibbs energy change of anaerobic butyrate conversion (Reaction 6, Table 1.1) and hydrogenotrophic methanogenesis (Reaction 9, Table 1.1) as a function of the hydrogen partial pressure.
Syntrophic cooperation is possible only when both partial reactions remain exergonic and the situation of equal energy sharing is often assumed the optimal working condition for syntrophy (Schink 1997; Schink and Friedrich 1994).
Chapter 1
7
Figure 1.4: Dependence of the Gibbs energy change of anaerobic butyrate conversion (dashed) and hydrogenotrophic methanogenesis (solid) on the hydrogen partial pressure.
Microbial metabolism
In the ideal picture, microbial metabolism can be defined as the sum of catabolic and anabolic reactions (Figure 1.5) (Heijnen and Kleerebezem 2010; Kleerebezem and Stams 2000; Kleerebezem and Van Loosdrecht 2010). During catabolism, substrates are converted into products and energy is stored in the form of ATP. In the anabolic reaction, a fraction of the energy obtained from the catabolic reaction serves for biomass formation from a carbon source (C-source) and a nitrogen source (N-source). Another fraction of the stored energy is used for maintenance purposes of the cell (mATP). In both, catabolism and anabolism, a certain amount of the energy generated cannot be harvested by the cell, neither for growth nor for maintenance. This energy is denoted as the driving force of the respective reaction (ΔGDF).
If the catabolic reaction is highly exergonic and a major fraction of the energy generated is invested into biomass formation, the biomass yield on substrate (YX/S) is high, which holds for many aerobic conversions. In most anaerobic processes, however, the Gibbs energy change of the catabolic reaction (∆GCAT) is rather low, leaving only a minor energy fraction to biomass production and hence leading to a comparably low YX/S. Apart from the illustrated impact of the thermodynamics on YX/S, the ΔGDF may also affect the reaction rate of the conversion in question. This is the case when the ΔGDF approaches zero as will be explained in the following section.
Figure 1.5: A simplified picture of microbial cell metabolism. ΔGDF: driving force of the underlying
reaction, C (N) source: carbon (nitrogen) source, mATP: the fraction of ATP invested in non-growth
related maintenance of the cell. Modified after Kleerebezem and Van Loosdrecht (2010).
Flux-force relationships
Flux-force relationships describe the dependence of the metabolic flux on ΔGDF. In many aerobic conversions, ΔGDF is relatively high and the thermodynamic impact on the metabolic flux is often negligible. Therefore, far from thermodynamic equilibrium, biomass-specific substrate consumption rates, q [mol-S∙(mol-X)-1∙h-1], are typically described independent of thermodynamics
𝑞 = 𝑞max 𝑆
𝑆 + 𝐾S (1.1)
in close resemblance of classical Monod kinetics (Monod 1949)
𝜇 = 𝜇max 𝑆 + 𝐾𝑆
S (1.2)
when assuming a constant YX/S [mol-X/mol-S](Heijnen and Kleerebezem 2010; Kleerebezem and Stams 2000). Here, qmax [mol-S∙(mol-X)-1∙h-1] is the maximum biomass-specific substrate consumption rate, S [mM] the substrate concentration, KS [mM] the affinity constant for substrate
Chapter 1
9 uptake, µ [h-1] the biomass-specific growth rate, and µmax [h-1] the maximum biomass-specific growth rate.
In contrast, many anaerobic conversions proceed close to thermodynamic equilibrium, which can lead to a ΔGDF considerably closer to zero and may therefore affect reaction kinetics. Additions to Monod kinetics have been proposed to properly account for thermodynamic restrictions in kinetic system description (Hoh and Cord-Ruwisch 1996; Kleerebezem and Stams 2000; Kleerebezem and van Loosdrecht 2006). As a first approximation, the biomass-specific flux may be described by a conditional Monod-like equation
𝑞 = {𝑞max 𝑆
𝑆 + 𝐾S, ∆𝐺 < 0
0, ∆𝐺 ≥ 0
(1.3)
which, in agreement with the laws of thermodynamics, states that no reaction may occur under endergonic conditions. Hoh and Cord-Ruwisch (1996) proposed to include ∆GCAT [kJ/mol] explicitly in the rate equation:
𝑞 = 𝑞max
𝑆 (1 − e∆𝐺CAT⁄R𝑇) 𝐾S+ 𝑆 (1 + e∆𝐺CAT⁄R𝑇)
(1.4)
where R [kJ∙K-1∙mol-1
] is the gas constant and T [K] the temperature. Equation 1.4 provides an improved thermodynamic description and implies an equalization of biomass-specific growth rates during syntrophic growth as proposed by Powell (1984, 1985). Furthermore, threshold substrate concentrations follow naturally from this equation as they are implied in reaction thermodynamics. However, the use of ∆GCAT as driving force does not reflect reality in the picture of cell metabolism since only a fraction of ∆GCAT represents ∆GDF while the remainder is used for maintenance and growth (Kleerebezem and Stams 2000; Kleerebezem and van Loosdrecht 2006). Therefore, a more realistic description of the flux-force relationship is given by
𝑞 = {𝑞max 𝑆 𝑆 + 𝐾S (1 − e ∆𝐺DF⁄R𝑇), ∆𝐺DF< 0 0, ∆𝐺DF≥ 0 (1.5)
Apart from thermodynamic restrictions, product inhibition by hydrogen may be another factor limiting reaction kinetics. Effects of product inhibition have been repeatedly reported for anaerobic conversions and various attempts aimed to describe product inhibition by competitive (Labib et al. 1993), non-competitive (Dolfing and Tiedje 1988; Labib et al. 1993; Mosey 1983; Siegrist et al. 1993), and uncompetitive (Warikoo et al. 1996) inhibition models.
Mosey (1983) proposed a hydrogen inhibition term to describe the inhibitory effect of hydrogen on anaerobic butyrate and propionate conversion:
𝑞 = 𝑞max 𝑆 + 𝐾𝑆 S
𝐾iH2
𝐾iH2+ H2 (1.6)
where KiH2 is the hydrogen inhibition constant. Assuming thermodynamic equilibrium between the hydrogen partial pressure and the NAD+/NADH redox couple, Mosey (1983) suggested a KiH2 of 150 Pa (1500 ppm). Kleerebezem and Stams (2000) emphasized that the KiH2 in microbial systems should not be regarded fixed but rather dependent on intracellular metabolite and carrier concentrations. The hydrogen inhibition term is used by anaerobic digestion models such as the Anaerobic Digestion Model No. 1 (ADM1) which has been developed by the IWA expert task group to establish a general description of anaerobic processes (Batstone et al. 2002). ADM1 provides several kinetic and stoichiometric parameters including the KiH2 for anaerobic propionate and butyrate conversion, 296 ppm and 847 ppm, respectively.
Besides inhibition terms in analogy to enzyme kinetics, there have been arguments in favour of a powered hydrogen inhibition term for microbial conversions that proceed close to thermodynamic equilibrium (Kleerebezem and van Loosdrecht 2006). Both, the hydrogen concentration and the hydrogen inhibition constant are powered by the stoichiometric coefficient of hydrogen on substrate, YH2/S [mol-H2/mol-S]
𝑞 = 𝑞max 𝑆 𝑆 + 𝐾S 𝐾iH2Y 𝐾iH2Y + H2Y (1.7)
The dependence of the biomass-specific conversion rates on the Gibbs energy change is illustrated in Figure 1.6 using the examples of anaerobic lactate, butyrate and propionate conversion. The powered hydrogen inhibition term (Equation 1.7) shows a much stronger inhibitory effect on the reaction rate when compared to the standard non-competitive hydrogen inhibition model (Equation 1.6). For lactate (Figure 1.6a), which is the most energy-rich substrate under investigation, it is furthermore apparent that thermodynamics hardly affect the reaction rate. For butyrate and propionate in contrast (Figure 1.6b,c), a thermodynamic description is obviously required as, according to ADM1, these reactions would still occur at positive Gibbs energy changes. In the case of anaerobic propionate conversion either ADM1 or powered hydrogen inhibition alone fail to meet thermodynamic laws, unless combined with thermodynamic restrictions.
Chapter 1
11 To date, validation of the proposed theoretical models is still hampered by a lack of data and experimental tools for the quantification of biomass-specific fluxes. While many studies make use of thermodynamic analysis, the quantification of biomass-specific fluxes is the missing link to establish flux-force relationships in methanogenic ecosystems. Emerging quantitative molecular methods such as quantitative FISH (qFISH) and PCR (qPCR) may open up the opportunity for a more accurate determination of individual biomass concentrations and therefore a deeper understanding of flux-force relationships in anaerobic ecosystems.
Figure 1.6: Biomass-specific lactate (a), butyrate (b) and propionate (c) consumption rates as a function of the Gibbs energy change of the catabolic reaction. Calculations according to (I) ADM1, (II) ADM1 with thermodynamic limitation, (III) powered hydrogen inhibition, and (IV) powered hydrogen inhibition with thermodynamic limitation. The concentrations of all aqueous species were assumed 1 mM except for HCO3- (50 mM), H+ (10-7 M) and the hydrogen partial pressure was varied. For the
sake of simplicity ∆GCAT was used instead of ∆GDF. The KiH2 were taken from ADM1, except for lactate
Outline
Despite the widespread application of anaerobic digestion in wastewater treatment processes, our current fundamental knowledge of the involved microbial interactions is limited. In particular, little is known about the exchange of reducing equivalents between the syntrophic partner organisms in the final steps of the process and how these partners share the typically low energy budget. This lack of insight is attributed to several factors but most prominently to a lack of experimental tools for the accurate determination of individual biomass concentrations in methanogenic ecosystems. The quantification of individual biomass concentrations is a prerequisite for the study of control and regulatory mechanisms of electron transfer in syntrophic methanogenic communities. Since the metabolic flux of each syntrophic partner is given by the product of the individual biomass concentration and the biomass-specific electron transfer rate, biomass-specific electron fluxes can only be determined when the individual biomass concentrations are known. Due to the lacking information on individual biomass concentrations, many anaerobic digestion models have not been fully validated and consequently treat the anaerobic digestion process only semi-quantitatively or as a black box.
This thesis aims to establish an improved quantitative understanding of the anaerobic digestion process by providing detailed insights into the mechanisms of interspecies electron transfer and syntrophy in general. As a major improvement over existing models, the implementation of thermodynamic restrictions shall provide a more realistic model description that opens up the opportunity for enhanced process operation, process control and failure prediction. For this to achieve, kinetic and thermodynamic control of electron fluxes has been studied in defined and non-defined microbial communities with advanced process monitoring tools including online gas analysis and qPCR-based quantification of individual biomass concentrations.
Emerging molecular techniques such as qFISH and qPCR might hold potential use in the quantification of individual biomass concentrations with unprecedented accuracy. Nevertheless, existing qPCR methods for individual biomass quantification often rely on error-prone factors used for the conversion of gene copy numbers or cell concentrations into actual biomass concentrations. In Chapter 2 it was aimed to develop a novel qPCR approach that relates the native qPCR signal directly to the individual biomass concentration. The improved technique permits the calculation of biomass-specific conversion rates based on individual biomass concentrations. The developed qPCR approach may fill the missing link for the study of flux-force relationships in methanogenic ecosystems.
Chapter 1
13 In Chapter 3 the thermodynamic and kinetic impact of the hydrogen partial pressure on lactate degradation was investigated using the syntrophic coculture of Desulfovibrio sp. G11 and Methanobrevibacter arboriphilus DH1. Addition of formate besides lactate served to control the hydrogen partial pressure. Hydrogen resulted from the bioconversion of lactate and formate in the liquid phase which was mediated by the acetogen. A large portion of work was devoted to the implementation of a descriptive model system which aims to elucidate the regulatory mechanisms in syntrophic methanogenic communities.
Chapter 4 deals with the regulation and control of syntrophic growth in a coculture of Desulfovibrio sp. G11 and Methanospirillum hungatei JF1 when cultivated on lactate, formate or both. A particular focus lies on the regulatory factors that govern a common biomass-specific growth rate in syntrophy and the potential role of the reaction thermodynamics therein. The qPCR approach developed in Chapter 2 was applied for validation of the biomass concentrations of both bacteria and archaea.
In Chapter 5 the kinetic and thermodynamic control mechanisms of electron transfer have been studied in non-defined methanogenic communities using butyrate and ethanol-fed continuously stirred tank reactors (CSTR). A special interest of this study was to investigate the energy sharing between syntrophic partners in energy-limited anaerobic ecosystems. Furthermore, the role of the hydrogen partial pressure in the kinetic and thermodynamic control of reduced product formation was investigated.
Chapter 6 evaluates the main findings and conclusions of this thesis in relation to the body of literature and the latest research on the topic. An outlook into novel research themes is provided.
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CHAPTER 2
Absolute quantification of individual biomass
concentrations in a methanogenic coculture
This Chapter is published as: Junicke, H., Abbas, B., Oentoro, J., van Loosdrecht, M.C.M., and Kleerebezem, R. (2014). Absolute quantification of individual biomass concentrations in a methanogenic coculture. AMB Express, 4(1), 35.
Abstract
Identification of individual biomass concentrations is a crucial step towards an improved understanding of anaerobic digestion processes and mixed microbial conversions in general. The knowledge of individual biomass concentrations allows for the calculation of biomass-specific conversion rates which form the basis of anaerobic digestion models. Only few attempts addressed the absolute quantification of individual biomass concentrations in methanogenic microbial ecosystems which has so far impaired the calculation of biomass-specific conversion rates and thus model validation. This study proposes a quantitative PCR (qPCR) approach for the direct determination of individual biomass concentrations in methanogenic microbial associations by correlating the native qPCR signal (cycle threshold, Ct) to individual biomass concentrations (mg dry matter/L). Unlike existing methods, the proposed approach circumvents error-prone conversion factors that are typically used to convert gene copy numbers or cell concentrations into actual biomass concentrations. The newly developed method was assessed and deemed suitable for the determination of individual biomass concentrations in a defined coculture of Desulfovibrio sp. G11 and Methanospirillum hungatei JF1. The obtained calibration curves showed high accuracy, indicating that the new approach is well suited for any engineering applications where the knowledge of individual biomass concentrations is required.
Chapter 2
21
Introduction
Many biotechnological processes rely on the combined action of complex microbial consortia (Kleerebezem and van Loosdrecht 2007). An important example is the anaerobic digestion process which converts organic residues into biogas, a renewable form of energy containing methane as the primary energy carrier (Chen et al. 2008; Gujer and Zehnder 1983).
Anaerobic digestion comprises a series of reaction steps each performed by a specific microbial group of the anaerobic ecosystem (Gavala et al. 2003; Stams and Plugge 2009). Due to the interdependence of involved reactions, the overall mechanism is kinetically controlled by the rate limiting reaction step (Griffin et al. 1998; Lyberatos and Skiadas 1999; Yu et al. 2005). Therefore, to improve conversion performance and process control major importance lies in the identification of the factors that govern a well-balanced reaction mechanism (Chen et al. 2008; Griffin et al. 1998; Rittmann and McCarty 2001). To investigate these factors mathematical models such as the Anaerobic Digestion Model No.1 (ADM1) have been developed (Batstone et al. 2002; Gavala et al. 2003). Unfortunately, validation of ADM1 and similar models is yet hampered by the lacking information on individual biomass concentrations i.e., the biomass concentrations of individual species or different functional groups contained in the microbial community. Only by knowing individual biomass concentrations it is possible to calculate biomass-specific rates which form the basis of these models and whose determination is hence required for their evaluation.
In mixed microbial conversions any rate should be normalized to the individual biomass that is associated with it, giving rise to a biomass-specific rate, q, defined as
𝑞 = 𝑅 𝑁x=
𝑅
𝑐x∙ 𝑉R (2.1)
where R denotes the net reaction rate in question, Nx the specific biomass amount, cx the specific biomass concentration and VR the reactor volume (Heijnen 2010). In the general case, dividing by the lumped instead of the individual biomass provides an incorrect description of experimental conditions as certain reactions are performed by specific organisms only and not by the total biomass. A failure to implement this logic into mixed microbial conversion models may result in inaccurate and even false predictions. The measurement of individual biomass is therefore an important step towards an improved theoretical understanding of the anaerobic digestion process and mixed microbial conversions in general.
Only limited research has focused on the determination of individual biomass concentrations in mixed microbial communities. Seitz et al. (1990) determined individual biomass concentrations of an anaerobic coculture by phase-contrast microscopy assisted manual cell counting. Nevertheless, this approach is time-intensive and suffers from low accuracy since morphologically similar microorganisms and aggregated cells can hardly be distinguished (Manz et al. 1994; Wagner et al. 2003). Emerging molecular techniques such as qPCR, quantitative fluorescence in situ hybridization (qFISH) or pyrosequencing promise to be much faster and more accurate (Coskuner et al. 2005; Ronaghi and Elahi 2002; Wagner et al. 2003; Zhang and Fang 2006).
Previous studies have used qPCR to analyze microbial community structures and population dynamics in a range of samples from wastewater treatment plants (Hall et al. 2002; Harms et al. 2003; Winkler et al. 2012), anaerobic bioreactors (Shin et al. 2011; Yu et al. 2006), activated sludge processes (Hall et al. 2002; Kim et al. 2011) and natural habitats (Schippers and Neretin 2006). Similar applications were covered by qFISH (Albertsen et al. 2012; Egli et al. 2003; Juretschko et al. 2002; Kragelund et al. 2011) and pyrosequencing (Jaenicke et al. 2011; Kröber et al. 2009; Kwon et al. 2010; Schlüter et al. 2008; Zhang et al. 2012). However, only a few attempts addressed the absolute quantification of individual biomass concentrations or the calculation of biomass-specific conversion rates.
Harms et al. (2003) quantified nitrite-oxidizing bacteria (NOB) and ammonia-oxidizing bacteria (AOB) by means of qPCR and derived cell-specific conversion rates in activated sludge. The native qPCR results (DNA copies/L) were converted to cells/L, cells/g, and percent of biomass using several assumptions. Ahn et al. (2008), Cho et al. (2013) and Kindaichi et al. (2006) used qPCR to determine maximum biomass-specific growth rates in nitrifying communities based on the abundance of DNA copy numbers, and assuming a constant correlation factor between DNA content and biomass. Cho et al. (2013) determined DNA specific growth yields (DNA copy numbers/mg-N) but did not express results in terms of biomass. Ahn et al. (2008) used additional conversion factors to derive biomass growth yields (mg-COD biomass/mg-N) from growth yields expressed in terms of DNA. The prevalent use of DNA copy numbers (Cheng et al. 2011; Chon et al. 2011) or cell numbers (Coskuner et al. 2005), rather than actual biomass, renders these results inconvenient for most engineering purposes. Error-prone conversion factors (e.g. gene copies/genome, genomes/cell, cells/g dry matter, DNA extraction efficiency) add to the problematic of this approach.
Several studies employed FISH to quantify cells of AOB and NOB, and to determine cell-specific ammonium and nitrite oxidation rates (Altmann et al. 2003; Daims et al. 2001; Gieseke et al. 2005; Wagner et al. 1995). In a direct comparison of FISH and qPCR for the quantification of
Chapter 2
23 cells in nitrifying biofilms Kindaichi et al. (2006) found that both methods yielded comparable results but qPCR was more favorable due to higher sensitivity and faster handling. Low sample concentrations (< 105 cells/mL), autofluorescence, non-specific binding and low signal intensity can become limiting factors for FISH analysis (Kindaichi et al. 2006; Konuma et al. 2000; Rittmann et al. 1999; Zhang and Fang 2006). The quantification of individual biomass concentrations by means of pyrosequencing remains challenging due to the semi-quantitative nature of the method (Amend et al. 2010). Purely quantitative applications of pyrosequencing remain scarce as of yet. Lastly, biomass concentrations were estimated from observed substrate transformation rates, metabolite ratios and individual biomass growth yields (Jiang et al. 2011; Lopez-Vazquez et al. 2007; Rittmann et al. 1999). These indirect methods are based on the measurement of commonly used analytical variables (e.g. substrate and product concentrations, lumped biomass concentration) without requiring molecular techniques (Lopez-Vazquez et al. 2007). However, assumptions of reaction stoichiometry or maximum biomass-specific conversion rates are inherent to these indirect methods and pose a major source of inaccuracy. In view of the previous, qPCR is regarded the most suited molecular method for the quantification of individual biomass concentrations in complex microbial ecosystems, and it stands out due to its high sensitivity (< 5 gene copies), high reproducibility (standard deviation < 2%) and high specificity (Kim et al. 2013).
Here it is aimed to derive individual biomass concentrations, expressed in gram dry matter per liter, directly from the qPCR signal of a given sample. No such approach has been reported so far, despite a few key advantages: Firstly, the result can readily be used in mathematical models and engineering applications. Secondly, several limitations of existing methods can be avoided, including unnecessary assumptions or erroneous conversion factors.
Material and Methods
A defined coculture of Desulfovibrio sp. G11 and Methanospirillum hungatei JF1 was used to evaluate the applicability of a qPCR approach for the determination of specific biomass concentrations.
Cultivation of microorganisms
Pure cultures of Desulfovibrio sp. strain G11 (DSM 7057) and Methanospirillum hungatei type strain JF1 (DSM 864) were obtained from the Laboratory of Microbiology, Wageningen University, The Netherlands, and cultivated in 2 L Schott bottles in the absence of oxygen and
under sterile conditions. The basic medium was prepared according to Plugge (2005). Culture medium for Desulfovibrio sp. G11 contained 20 mM sodium lactate, as the sole carbon source, and 10 mM sodium sulphate as electron acceptor. Basic medium for Methanospirillum hungatei JF1 was supplemented with 2 mM sodium acetate and 4 mM cysteine hydrochloride. While Desulfovibrio sp. G11 was kept under 80%/20% N2/CO2 atmosphere, Methanospirillum hungatei JF1 was grown under 80%/20% H2/CO2. The headspace of the methanogenic culture was exchanged every other day. The pH was maintained between 7.0 and 7.2. All cultures were incubated at a temperature of 37ºC and constantly shaken at 150 rpm.
Centrifugation efficiency test
The centrifugation efficiency was tested for a biomass concentration of 21.0 mg/L (Desulfovibrio sp. G11) and 179.9 mg/L (Methanospirillum hungatei JF1) and four further two-fold dilutions, respectively. A three-step centrifugation procedure using a cell suspension volume of 2 mL (13000 rpm, 21000×g, 4ºC, Heraeus, Biofuge fresco) was used. The duration of the first step amounted to 5 min. The resulting supernatant was again centrifuged for 3 min. Supernatant of the second step was centrifuged for 10 min. Three pellets resulting from the previous centrifugation steps were combined for DNA extraction.
DNA extraction
The UltraClean microbial DNA isolation kit (Mo Bio, Carlsbad, USA) was used for DNA extraction in triplicates. Instead of horizontal vortex mixing for 10 min, the Mini Bead Beater 16 (BioSpec Products, Bartlesville, USA) was used for 5 min. In order to improve DNA elution efficiency herring-sperm DNA (HS-DNA) was added prior to the bead-beating step.
Quantitative PCR
Quantitative PCR was performed using an iQ5 system (Bio-Rad Laboratories B.V., Veenedaal, The Netherlands). The primer sets used for the amplification of the partial 16S rDNA sequences by qPCR are shown in Table 2.1. Both primer sets are highly specific to amplify only the DNA of the target microorganism in the coculture.
