Effects of glucose overloading on microbial community structure and biogas production in a laboratory-scale anaerobic digester

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  • Eects of glucose overloading on microbial community structureand biogas production in a laboratory-scale anaerobic digester

    Ingvar Sundh a,*, Helena Carlsson a, AAke Nordberg b, Mikael Hansson b, Berit Mathisen b

    a Department of Microbiology, Swedish University of Agricultural Sciences, P.O. Box 7025, SE-750 07 Uppsala, Swedenb Swedish Institute of Agricultural and Environmental Engineering, P.O. Box 7033, SE-750 07 Uppsala, Sweden

    Received 8 October 2002; received in revised form 10 February 2003; accepted 25 February 2003

    Abstract

    This study characterizes the response of the microbial communities of a laboratory-scale mesophilic biogas process, fed with a

    synthetic substrate based on cellulose and egg albumin, to single pulses of glucose overloading (15 or 25 times the daily feed based on

    VS). The microbial biomass and community structure were determined from analyses of membrane phospholipids. The ratio be-

    tween phospholipid fatty acids (PLFAs; eubacteria and eucaryotes) and di-ethers (PLEL; archaea) suggested that methanogens

    constituted 48% of the microbial biomass. The glucose addition resulted in transient increases in the total biomass of eubacteria

    while there were only small changes in community structure. The total gas production rate increased, while the relative methane

    content of the biogas and the alkalinity decreased. However, the biomass of methanogens was not aected by the glucose addition.

    The results show that the microbial communities of biogas processes can respond quickly to changes in the feeding rate. The glucose

    overload resulted in a transient general stimulation of degradation rates and almost a doubling of eubacterial biomass, although the

    biomass increase corresponded to only 7% of the glucose C added.

    2003 Elsevier Science Ltd. All rights reserved.

    Keywords: Biogas; Microbial community structure; PLFA; Substrate overload; Methanogenesis; Di-ether lipid

    1. Introduction

    In biogas production from organic materials, the in-

    tegrated action of several types of microorganisms,

    which perform dierent degradation steps, results in the

    sequential degradation of polymeric carbohydrates,

    proteins and fats (Gujer and Zehnder, 1983; Schink,

    1988). Functionally, the organisms can be broadly

    classied into hydrolytic, fermentative organic acid-producing, acetate-producing and, in the terminal step,

    methane-producing, organisms.

    Due to low energy yields, many anaerobic microor-

    ganisms grow slowly, the methanogens in particular.

    Therefore, in completely mixed systems with relatively

    short retention times, disturbance due to, for example,

    poor composition or overloading of the substrate, ac-

    cumulation of inhibitory substances, or presence of an-thropogenic contaminants, may inhibit the active

    organisms and result in serious malfunctioning of the

    process. However, knowledge of the response of themicrobial communities to dierent kinds of disturbance

    is still meagre, particularly regarding the communitiesstructural characteristics.

    In the present study, we investigated the eects of

    substrate overload, with a single dose of glucose, on the

    size and structure of the microbial community and on

    the biogas production in a laboratory scale biogas pro-

    cess fed with a synthetic substrate. The microbial bio-mass and community structure were determined from

    analysis of membrane phospholipids. In addition, the

    fate of the added glucose was determined by construc-

    tion of a C budget.

    2. Methods

    2.1. Reactor system

    The reactor was a continuously mixed glass tank of8 l active volume, operated under mesophilic condi-

    tions (37 C). It was started with digester contents froma larger reactor which had operated with the same

    *Corresponding author. Tel.: +46-18-673210; fax: +46-18-673392.

    E-mail address: ingvar.sundh@mikrob.slu.se (I. Sundh).

    0960-8524/03/$ - see front matter 2003 Elsevier Science Ltd. All rights reserved.doi:10.1016/S0960-8524(03)00075-0

    Bioresource Technology 89 (2003) 237243

  • substrate for three years. The substrate consisted of a

    mixture of microcrystalline cellulose, egg albumin and

    vitamins in a mineral medium (Nordberg et al., 2000).

    The experimental reactor was automatically fed every

    12th h and the hydraulic retention time was 20 d. The

    regular feeding corresponded to 1.0 gVS l1 d1.Two experiments with glucose additions were carried

    out, separated by ve months, where extra glucose wasadded representing approximately 15 (Experiment B)

    and 25 (Experiment C) times (in gVS l1 d1) the normaldaily feeding rate, with cellulose and albumin. The

    glucose was added as a single dose, which replaced one

    regular feeding, after which normal feeding rates were

    resumed. A second reactor operated in an identical

    manner served as a control and did not receive glucose

    at any stage.

    2.2. Microbial biomass and community structure

    The microbial communities were characterized fromanalyses of normal phospholipid fatty acids (PLFAs)

    from eucaryotes and bacteria, and of phospholipid die-

    ther lipids (PLELs) from methanogenic archae. Samples

    for lipid analysis were collected immediately before and

    after the glucose addition, after 4 h, and then at intervals

    during a 20 day period. 2-ml aliquots of the reactor

    contents were immediately frozen in extraction tubes

    and stored at )20 C until analysis. Detailed descri-ptions of the lipid extractions have been given previously

    (Sundh et al., 1997). Briey, the total lipid fraction of

    the reactor contents was extracted in a one-phase chlo-

    roform/methanol/water extraction. The lipids were then

    fractionated with silicic acid chromatography. The polar

    fraction (containing the phospholipids) was subjected to

    an alkaline methanolysis, after which the normal fatty

    acids were recovered as methyl esters. The subsequentderivatizations of the intact diether lipids with

    bis(trimethylsilyl)triuoroacetamide (BSTFA), quanti-

    cations of the lipid components with gas chromato-

    graphy (GC) with a ame ionization detector, and

    identications with a GC with a mass selective detector

    were made according to Virtue et al. (1996). However, in

    contrast to them, we used helium as the carrier gas and a

    30 m HP1-MS column. The quantications were madeby using the methyl ester of the fatty acid 19:0 as in-

    ternal standard and identications were facilitated by

    comparisons with standard mixtures (standards were

    obtained from Larodan Fine Chemicals AB, Lim-

    hamnsgaardens allee 9, SE-216 16 Malmoo, Sweden). Therelative amounts of cis and trans isomers of monoun-

    saturated PLFAs were determined after dimethyldisul-

    phide (DMDS) derivatizations followed by GC-MSanalysis (Nichols et al., 1986).

    The coecient of variation (CV) for PLFA determi-

    nations in replicate samples from the reactor was 19%,

    both for the total concentration and the mean for indi-

    vidual PLFAs. For the diether PLEL the CV was 42%.

    2.3. Analytical methods for gas and glucose

    The total gas ow from the reactor was continously

    registered using a gas meter with a volume of 50 ml percycle, calibrated against a wet gas meter (Schlumberger

    Industries, Meterfabriek B.V.). Methane and carbon

    dioxide concentrations in the reactor gas were measured

    with gas chromatography, and as the gas volume ab-

    sorbed in 7 M NaOH, respectively (Jarvis et al., 1995).

    The glucose concentration was measured with HPLC

    (Schnuurer et al., 1996) and alkalinity with acid titration(APHA, 1985).

    2.4. Fate of added glucose

    A carbon budget for the added glucose was con-

    structed for the total duration of Experiment B, i.e. one

    hydraulic retention time. The following sinks for the

    added glucose were considered: 1. Total amounts ofmethane and carbon dioxide leaving the reactor (also

    corrected for gas produced from the regular substrate).

    2. Glucose passing the reactor without being metabo-

    lized. 3. Increase in microbial biomass in the reactor

    contents. 4. Microbial biomass washed out of reactor.

    5. Propionate and acetate washed out of reactor.

    We did not correct the ow of carbon dioxide for

    losses of bicarbonate from the reactor uid due to dropsin pH and alkalinity, since both parameters returned to

    initial values well before the end of the experiment.

    2.5. Data analysis

    In order to detect general, systematic variation in thefatty acid composition, the PLFA data were treated with

    principal component analysis (PCA), performed with

    the JMP software. Standardized principal compo-

    nents calculations were used, where the principal

    component scores were scaled to have unit instead of

    canonical variance. By investigating two-dimensional

    plots of the principal components (PCs), general dier-

    ences among samples could be detected.

    3. Results

    3.1. Eects on microbial communities

    During the two sampling periods, a total of 22 die-

    rent PLFAs and one PLEL were quantied in the re-

    actor contents (Table 1). There were traces of otherdiethers that could not be quantied. Nineteen of the

    normal fatty acids were common to both experiments.

    Branched-chain and saturated PLFAs with uneven

    238 I. Sundh et al. / Bioresource Technology 89 (2003) 237243

  • numbers of carbons were most prominent, showing that

    gram-positive and anaerobic gram-negative eubacteria

    dominated the community. With the exception of small

    amounts of 18:2, polyunsaturated fatty acids were

    missing, demonstrating a lack of eucaryotic microor-

    ganisms. The ratio of PLEL to PLFAs is an estimate ofthe relative contribution of methanogens to the micro-

    bial biomass. With respect to complete phospholipid

    molecules, the average amount of PLEL was 3.5% and

    8.3% of the PLFAs in the two experiments.

    In both experiments, the total PLFA concentration

    roughly doubled in response to glucose addition,

    showing that the eubacterial biomass increased sub-

    stantially (Fig. 1). On the other hand, there was noobvious change in PLELs (Fig. 1), and hence not in

    methanogenic biomass. However, the latter diered by a

    factor of two between the two overloading experiments.

    Total PLFA concentration peaked after 34 days and

    then gradually declined, returning to its initial level

    approximately three weeks after glucose addition.

    The glucose overloadings resulted in time-dependent

    changes in the PLFA composition in the reactor. Whenthe PLFA data from the two experiments were separately

    treated by PCA, regular changes with time were evident

    (Fig. 2).Most of the quantitatively dominating fatty acids

    were high in PC1, i.e. they had a peak in concentration 2

    4 days after the glucose addition. Most of the fatty acids

    responsible for the separation of early and late samples in

    the PCA (e.g. 16:1x7, 18:1x9, 18:0) had overall lowconcentrations (Table 1). Thus, the time-dependent

    changes demonstrated by the PCA are caused both by an

    increase in total PLFA concentration and by changes in

    the relative contributions of individual fatty acids.

    In a simultaneous PCA with all samples, the generalpattern of movement with time in the score plot, was

    similar in both experiments, showing that the eect of

    the glucose on the microbial community structure was

    similar. However, the two overloading experiments were

    clearly separated in the score plot, showing that they

    had slightly dierent PLFA composition overall. The

    main causes for this separation were the three fatty acids

    occurring in only one of the experiments (i17:1, 20:0,cy21:0), and the overall dierent concentrations of 18:2,

    i16:0 and PLEL.

    The abundances of the trans isomers of the mono-

    unsaturated PLFAs were determined in Experiment C.

    The average trans/cis ratio of 16:1x7, 18:1x7 and18:1x9 was generally low (0.61.6%) and did not changesignicantly during the course of the experiment. These

    low ratios show that the nutrient supply to the microbialcommunity was generally high.

    3.2. Process parameters

    During normal feeding rates with cellulose and al-

    bumin, glucose was below the detection limit (0.2 g l1).

    Table 1

    Average concentrations of normal phospholipid fatty acids (PLFAs; in mol % for the individual fatty acids) and archaeal diether lipids (PLEL; in

    nmolml1) in a mesophilic biogas reactor fed a synthetic substrate mixture and receiving instant overloadings with glucose

    PLFA 15 Times overloading (B) 25 Times overloading (C)

    Normal After overload Normal After overload

    i13:0 0.81 (0.010) 1.05 (0.35) 1.47 (0.11) 1.33 (0.19)

    a13:0 0.51 (0.027) 0.74 (0.13) 0.70 (0.093) 0.90 (0.12)

    i14:0 4.9 (0.069) 5.5 (0.61) 4.4 (0.16) 5.5 (0.77)

    14:0 2.9 (0.11) 2.3 (0.61) 2.2 (0.097) 3.2 (1.1)

    i15:0 20.6 (0.17) 22.9 (4.1) 25.4 (0.29) 26.4 (3.9)

    a15:0 28.3 (0.059) 30.5 (2.0) 25.8 (0.30) 24.6 (1.5)

    15:0 2.9 (0.072) 7.2 (2.2) 6.6 (0.46) 11.1 (2.6)

    i16:0 11.1 (0.064) 7.4 (2.4) 4.5 (0.075) 3.6 (0.60)

    16:1x7 0.81 (0.005) 0.67 (0.17) 1.1 (0.24) 0.99 (0.32)16:0 5.9 (0.051) 4.4 (1.2) 5.9 (0.13) 4.9 (0.91)

    i17:1 0.81 (0.26) 0.51 (0.18)

    i17:0 5.4 (0.011) 4.0 (0.64) 5.8 (0.11) 4.8 (1.5)

    a17:0 5.0 (0.004) 3.9 (0.62) 5.1 (0.12) 3.7 (0.68)

    17:0 1.6 (0.011) 2.6 (1.09) 1.5 (0.050) 2.0 (0.58)

    18:2 2.4 (0.055) 1.6 (0.43) 1.4 (0.31) 0.84 (0.23)

    18:1x9 2.8 (0.031) 2.0 (0.30) 4.4 (0.16) 2.7 (0.54)18:1x7 0.54 (0.001) 0.42 (0.11) 0.47 (0.026) 0.39 (0.056)18:0 2.1 (0.072) 1.5 (0.31) 2.6 (0.12) 1.6 (0.26)

    10Me18:0 0.38 (0.085) 0.23 (0.029) 0.24 (0.12)

    20:1 0.62 (0.010) 0.46 (0.082) 0.50 (0.051) 0.47 (0.079)

    20:0 0.37 (0.042) 0.33 (0.17)

    cy21:0 0.21 (0.11)

    Total PLFAs (nmolml1) 160 (2.7) 212 (39.9) 121 (2.7) 182 (40.3)PLEL (nmolml1) 3.86 (0.98) 3.42 (0.98) 7.33 (0.26) 7.62 (0.73)

    Data are given separately for normal, pre-overload, conditions and for a three-week period following overload. SD is shown within parenthesis.

    I. Sundh et al. / Bioresource Technology 89 (2003) 237243 239

  • The added glucose was rapidly consumed and the con-

    centration had returned to non-detectable levels after 2

    3 days (Fig. 3). Simultaneously, the alkalinity droppedfrom roughly 7, to 5 and 4 g CaCO3 l1, after 15 and 25times overloading, respectively. The alkalinity gradually

    returned to initial values after the glucose was consumed

    (Fig. 3).

    The ow of biogas increased substantially as an im-

    mediate result of the glucose addition. The ow of car-

    bon dioxide returned to pre-glucose rates sooner than

    the ow of methane. As long as free glucose was avail-able, carbon dioxide ow exceeded methane production.

    Thereafter, the biogas composition changed back to

    dominance by methane. The regular feeding occasions

    were evident as regular cycles of increased production of

    methane and carbon dioxide.

    The sum of the glucose sinks considered amounted to

    3.17 mol C (Table 2). This is 56% of the glucose carbon

    in the reactor immediately after the addition (the rstsamples were taken approximately 5 min after addition).

    The calculation assumes that the degradation of the

    regular substrate was not aected by the addition. This

    is not likely, and on the converse assumption, that there

    was no degradation of regular feed after the addition,

    the total recovery was 6.90 mol C, equivalent to 121% of

    the glucose carbon (Table 2).

    4. Discussion

    Comparatively short and saturated, branched- or

    straight-chain fatty acids with up to 17 carbons domi-

    nated among the normal ester-linked fatty acids in the

    reactor. These fatty acids are dominant in many gram-

    positive and anaerobic gram-negative eubacteria. Otherstudies have suggested that members of Clostridium,

    other low GC gram-positive eubacteria, Spirochaeta,

    Bacteroides, and Cytophaga can be prominent in the

    eubacterial community in biogas processes (Godon

    et al., 1997; Sekiguchi et al., 1998; Fernandez et al.,

    1999, 2000; Delbees et al., 2001; Dollhopf et al., 2001).The fatty acid compositions of Spirochaeta and Bacte-

    roides, which are common sugar fermenters in anaerobic

    Fig. 1. (a) Total PLFA and (b) total PLEL concentrations in a biogas

    reactor after instant glucose overloading. Experiment B, 15 times the

    normal daily feed (diamonds); Experiment C, 25 times the normal

    daily feed (triangles).

    Fig. 2. PCA of PLFA and PLEL data from a biogas reactor after

    receiving an instant glucose overloading of 25 times the daily feed. (a)

    scores; (b) loadings. Numbers in the score plot denote days after glu-

    cose addition.

    240 I. Sundh et al. / Bioresource Technology 89 (2003) 237243

  • systems, show a high resemblance to that in the reactor

    (Lechevalier and Lechevalier, 1988), indicating that

    these bacterial groups were dominants in the commu-

    nity. Members of Clostridium, other low GC gram-positives and Cytophaga, on the other hand, all have

    mainly 14:0, 16:0, 16:1, and 18:1 (Lechevalier and

    Lechevalier, 1988). These PLFAs occurred in much

    lower concentrations, showing that the latter eubacterial

    groups possibly formed sub-dominant populations.

    Eucaryotes were principally absent, as 18:2 was the only

    polyunsaturated PLFA detected, making up 12% of the

    PLFAs.

    The diether lipids from methanogens corresponded to

    48% of the PLFAs, based on moles of complete

    phospholipid molecules. This means that assuming that

    the ratio of phospholipid to biomass is the same in the

    eubacteria and the methanogens, the methanogenic

    biomass was roughly 48% of the eubacterial. This iswithin the range of biomass ratios reported in other

    studies employing lipid analysis (Schropp et al., 1988;

    Hedrick et al., 1991, 1992). Similarly, in a pilot-scale

    reactor system treating brewery wastewater, direct mi-

    croscopic cell counts gave a methanogenic to eubacterial

    cell number ratio of 78% (Ince et al., 1997). Analyses of

    relative amounts of small subunit (SSU) rRNA have

    yielded ratios of methanogens/eubacteria of 510% inanaerobic reactors treating sludge from wastewater

    treatment plants (Raskin et al., 1995) and during treat-

    ment of a simulated organic fraction of municipal solid

    waste (Grin et al., 1998). Although conversion factors

    that are necessary to convert amounts of membrane

    lipids or SSU rRNA to actual biomass may vary con-

    siderably, estimates of the relative methanogenic bio-

    mass in biogas reactors based on completely dierentmethods seem to converge around a value of 10%.

    Apart from the few weeks immediately following the

    glucose addition, the reactor maintained a quite stable

    performance with respect to chemical parameters, both

    before and after the glucose additions (data not shown).

    Despite a stable performance, the PCA analysis of the

    fatty acid data revealed that there were general dier-

    ences in the microbial community structure between thetwo experiments. This dierence was smaller, but per-

    sisted, if the PLFAs that were detected in only one of the

    experiments were excluded in the PCA (data not

    shown). Additionally, slow and gradual changes in

    Fig. 3. Glucose concentrations (diamonds) and alkalinity (triangles) in

    a biogas reactor after glucose overloading. (a) Experiment B,15 times

    the normal daily feed; (b) Experiment C, 25 times the daily feed.

    Table 2

    Recovery of glucose carbon (mol C) after a single pulse of glucose overloading (15 times daily feed) of a mesophilic biogas reactor fed with a synthetic

    liquid substrate

    Glucose in reactor immediately (5 min) after addition 5.68CO2 leaving reactor

    a 2.75

    CO2 production from regular feed )1.55CH4 leaving reactor

    a 3.46

    CH4 production from regular feed )2.18Glucose passing the reactorb 0.19

    Incorporated into microbial biomassc 0.20

    Flushed out as microbial biomassd 0.20

    Flushed out as propionate+ acetateb ;e 0.10

    Total C recovery, assuming unchanged utilization of regular feed 3.17

    Total C recovery, assuming no utilization of regular feed 6.90

    The calculations take one hydraulic retention time into account.a Estimated as the sum of hourly ow rates for gas leaving the reactor.b The time-weighted average concentration multiplied by total volume washed out.c Estimated from the increase in PLFA content, assuming 100 lmol PLFA g1 dw of cells and that C makes up 50% of the dw (White et al., 1979).d Calculated as for glucose passing reactor, but only for increase compared to the initial background biomass.e Calculated from data presented in Nordberg et al. (2000).

    I. Sundh et al. / Bioresource Technology 89 (2003) 237243 241

  • community structure are illustrated by a general decline

    in the concentration of i16:0 during Experiment B, and

    the general dierence in diethers between the experi-

    ments. Along the same line, recent studies based on

    molecular inventories of biogas reactors indicate that

    there may be substantial changes in the microbial

    communities despite a rather stable process performance

    (Fernandez et al., 1999, 2000; Zumstein et al., 2000).In this study, the responses to glucose overloading

    were similar to those found in other studies in similar

    systems (Xing et al., 1997; Hashsham et al., 2000).

    However, in our experiments, the general microbial re-

    sponse was a stimulation of degradation. For example,

    all glucose was taken up by microorganisms in only 23

    days, and with regard to the entire Experiment B, most

    of the glucose carbon was recovered as raised produc-tion rates of methane and carbon dioxide (Table 2).

    Additionally, the biomass of eubacteria increased, as

    evidenced by a peak in total PLFA concentration after

    34 days. However, since only a very small part of the

    energy was available for growth, the total eubacterial

    biomass increase corresponded to not more than 7.0%

    of the glucose C (Table 2). Along the same lines, the

    trans/cis ratios of the monounsaturated PLFAs werequite low (1.6% at most), suggesting that the microbial

    community experienced good nutritional conditions

    (Guckert et al., 1986; Hedrick et al., 1992).

    It is a bit surprising that while there was an obvious

    increase in eubacterial biomass, there was no clear

    change in methanogenic biomass (Fig. 1). In an eective

    biogas process like this reactor, most of the carbon

    mineralization is channelled through methanogenesis.Indeed, the total increase in gas production over the

    length of the experiment was represented by almost

    equimolar amounts of methane and carbon dioxide,

    which is expected for carbohydrate degradation in a

    biogas reactor (Gujer and Zehnder, 1983). In part, the

    lack of methanogenic biomass increase can be explained

    by the comparably low energy yield for methanogenesis,

    and the low growth rates of methanogens in general(Vogels et al., 1988). In any case, the diether data must

    be interpreted with care, since the diether content varies

    among methanogens (Koga et al., 1998), implying that a

    species shift may potentially mask a biomass increase. In

    addition, the coecient of variation for the diether data

    was high (42%).

    Our budget calculations did not account for all the

    added glucose. This was not unexpected, for at least fourreasons: 1. Flush-out of intermediates other than acetate

    and propionate was not considered. 2. Some of the

    glucose carbon may have ended up in biomass growing

    on the walls of the reactor. This was hardly a major sink,

    however, since there was no visible growth on the walls.

    3. The conversion factor for calculation of dry weight of

    biomass from PLFA concentration is uncertain. 4. The

    background gas production from the regular feed may

    have been overestimated, since the daily peaks in gas

    ow were smaller during the rst week after the glucose

    addition, indicating that the regular feed may have been

    utilized at lower rates for a period after the glucose

    shock. A slower degradation of the regular feed in this

    period also complies well with the fact that when the

    assumption was made that the regular feed was not used

    at all, this resulted in an obvious overestimate in re-covery (126%).

    The lipid analyses used in this study monitored major

    changes in the microbial community, especially in the

    eubacterial biomass, but also in the community structure.

    By comparisonwith the chemical parameters, the changes

    in the community could be explained in the perspective of

    process dynamics. However, the PLFA analysis would

    not be a suitable parameter for monitoring the state ofbiogas processes. Therefore, the glucose overloading ex-

    periments also included on-line measurements of the near

    infrared reectance (NIR) spectra of the process slurry. A

    NIR spectrum can be used as a ngerprint of the chemical

    composition of the process slurry, and NIR spectroscopy

    has a big potential for on-line monitoring and regulation

    of biogas production processes. Correlations ofNIR data

    with total PLFA concentrations using partial least square(PLS) modelling gave strong relationships (Nordberg

    et al., 2000). This shows that the changes in the biological

    components of the biogas process studied here can be

    detected by NIR. Such sensitivity to biological compo-

    nents is a good characteristic of parameters used to con-

    trol the performance and health of biogas processes.

    Acknowledgements

    We are grateful for the excellent technical assistance

    of Anette Levin, Gunnel Fransson and Sylvia Roonn. Wealso thank Anna Schnuurer for constructive comments onthe manuscript. Financial support was given by The

    Swedish National Energy Administration (Contract

    P10545-1).

    References

    APHA, 1985. Standard Methods for the Examination of Water and

    Waste Water, 16th ed. APHA, AWWA, WPCF. American Public

    Health Association, Washington, DC.

    Delbees, C., Moletta, R., Godon, J.-J., 2001. Bacterial and archaeal 16S

    rDNA and 16S rRNA dynamics during an acetate crisis in an

    anaerobic digestor ecosystem. FEMS Microbiol Ecol. 35, 1926.

    Dollhopf, S.L., Hashsham, S.A., Dazzo, F.B., Hickey, R.F., Criddle,

    C.S., Tiedje, J.M., 2001. The impact of fermentative organisms on

    carbon ow in methanogenic systems under constant low-substrate

    conditions. Appl. Microbiol. Biotechnol. 56, 531538.

    Fernandez, A., Huang, S., Seston, S., Xing, J., Hickey, R., Criddle, C.,

    Tiedje, J., 1999. How stable is stable? Function versus community

    composition. Appl. Environ. Microbiol. 65, 36973704.

    Fernandez, A., Hashsham, S.A., Dollhopf, S.L., Raskin, L., Glagol-

    eva, O., Dazzo, F.B., Hickey, R.F., Criddle, C.S., Tiedje, J.M.,

    242 I. Sundh et al. / Bioresource Technology 89 (2003) 237243

  • 2000. Flexible community structure correlates with stable commu-

    nity function in methanogenic bioreactor communities perturbed

    by glucose. Appl. Environ. Microbiol. 66, 40584067.

    Godon, J.-J., Zumstein, E., Dabert, P., Habouzit, F., Moletta, R.,

    1997. Molecular microbial diversity of an anaerobic digestor as

    determined by small-subunit rDNA sequence analysis. Appl.

    Environ. Microbiol. 63, 28022813.

    Grin, M.E., McMahon, K.D., Mackie, R.I., Raskin, L., 1998.

    Methanogenic population dynamics during start-up of anaerobic

    digesters treating municipal solid waste and biosolids. Biotechnol.

    Bioeng. 57, 342355.

    Guckert, J.B., Hood, M.A., White, D.C., 1986. Phospholipid ester-

    linked fatty acid prole changes during nutrient deprivation of

    Vibrio cholerae: Increases in the trans/cis ratio and proportions of

    cyclopropyl fatty acids. Appl. Environ. Microbiol. 52, 794801.

    Gujer, W., Zehnder, A.J.B., 1983. Conversion processes in anaerobic

    digestion. Water Sci. Technol. 15, 127167.

    Hashsham, S.A., Fernandez, A.S., Dollhopf, S.L., Dazzo, F.B.,

    Hickey, R.F., Tiedje, J.M., Criddle, C.S., 2000. Parallel processing

    of substrate correlates with greater functional stability in metha-

    nogenic bioreactor communities perturbed by glucose. Appl.

    Environ. Microbiol. 66, 40504057.

    Hedrick, D.B., Richards, B., Jewell, W., Guckert, J.B., White, D.C.,

    1991. Disturbance, starvation, and overfeeding stresses detected by

    microbial lipid biomarkers in high-solids high-yield methanogenic

    reactors. J. Ind. Microbiol. 8, 9198.

    Hedrick, D.B., White, T., Guckert, J.B., Jewell, W.J., White, D.C.,

    1992. Microbial biomass and community structure of a phase-

    separated methanogenic reactor determined by lipid analysis. J.

    Ind. Microbiol. 9, 193199.

    Ince, O., Anderson, G.K., Kasapgil, B., 1997. Composition of the

    microbial population in a membrane anaerobic reactor system

    during start-up. Water Res. 31, 110.

    Jarvis, AA., Nordberg, AA., Mathisen, B., Svensson, B.H., 1995.Stimulation of conversion rates and bacterial, activity in a silage-

    fed two-phase biogas process by initiating liquid recirculation.

    Antonie van Leeuwenhoek 68, 317327.

    Koga, Y., Morii, H., Akagawa-Matsushita, M., Ohga, M., 1998.

    Correlation of polar lipid composition with 16S rRNA phylogeny

    in methanogens. Further analysis of lipid component parts. Biosci.

    Biotechnol. Biochem. 62, 230236.

    Lechevalier, H., Lechevalier, M.P., 1988. Chemotaxonomic use of

    lipidsan overview. In: Ratledge, C., Wilkinson, S.G. (Eds.),

    Microbial Lipids, Vol. 1. Academic Press, London (Chapter 12).

    Nichols, P.D., Guckert, J.B., White, D.C., 1986. Determination of

    monounsaturated fatty acid double-bond position and geometry

    for microbial monocultures and complex consortia by capillary

    GC-MS of their dimethyl disulphide adducts. J. Microbiol.

    Methods 5, 4955.

    Nordberg, AA., Hansson, M., Sundh, I., Nordkvist, E., Carlsson, H.,

    Mathisen, B., 2000. Monitoring of a biogas process using electronic

    gas sensors and near-infrared spectroscopy (NIR). Water Sci.

    Technol. 41, 18.

    Raskin, L., Zheng, D., Grin, M.E., Stroot, P.G., Misra, P., 1995.

    Characterization of microbial communities in anaerobic bioreac-

    tors using molecular probes. Antonie van Leeuwenhoek 68, 297

    308.

    Schink, B., 1988. Principles and limits of anaerobic degradation:

    Environmental and technological aspects. In: Zehnder, A.J.B.

    (Ed.), Biology of Anaerobic Microorganisms. John Wiley & Sons,

    New York (Chapter 14).

    Schnuurer, A., Schink, B., Svensson, B.H., 1996. Clostridium ultunense

    sp. nov, a mesophilic bacterium oxidizing acetate in syntrophic

    association with a hydrogenotrophic methanogenic bacterium. Int.

    J. Syst. Bacteriol. 46, 11451152.

    Schropp, S.J., Phelps, T.J., Mikell, A.T., White, D.C., 1988. The

    relationship of eubacterial and methanogenic community structure

    in anaerobic digesters. In: Klass, D.L. (Ed.), Energy From Biomass

    and Wastes X. Elsevier Applied Science Publishers, London, pp.

    10351043.

    Sekiguchi, Y., Kamagata, Y., Syutsubo, K., Ohashi, A., Harada, H.,

    Nakamura, K., 1998. Phylogenetic diversity of mesophilic and

    thermophilic granular sludges determined by 16S rRNA gene

    analysis. Microbiology 144, 26552665.

    Sundh, I., Nilsson, M., Borgaa, P., 1997. Variation in microbialcommunity structure in two boreal peatlands as determined by

    analysis of phospholipid fatty acid proles. Appl. Environ.

    Microbiol. 63, 14761482.

    Virtue, P., Nichols, P.D., Boon, P.I., 1996. Simultaneous estimation of

    microbial phospholipid fatty acids and diether lipids by capillary

    gas chromatography. J. Microbiol. Methods 25, 177185.

    Vogels, G.D., Keltjens, J.T., Drift, C., 1988. Biochemistry of methane

    production. In: Zehnder, A.J.B. (Ed.), Biology of Anaerobic

    Microorganisms. John Wiley & Sons, New York (Chapter 13).

    White, D.C., Bobbie, R.J., Herron, J.S., King, J.D., Morrison, S.J.,

    1979. Biochemical measurements of microbial mass and activity

    from environmental samples. In: Costerton, J.W., Colwell, R.R.

    (Eds.), Native Aquatic Bacteria: Enumeration, Activity, and

    Ecology, ASTM STP 695. American Society for Testing and

    Materials, pp. 6981.

    Xing, J., Criddle, C., Hickey, R., 1997. Long-term adaptive shifts in

    anaerobic community structure in response to a sustained cyclic

    substrate perturbation. Microb. Ecol. 33, 5058.

    Zumstein, E., Moletta, R., Godon, J.-J., 2000. Examination of

    two years of community dynamics in an anaerobic bioreactor

    using uorescence polymerase chain reaction (PCR) single-strand

    conformation polymorphism analysis. Environ. Microbiol. 2, 69

    78.

    I. Sundh et al. / Bioresource Technology 89 (2003) 237243 243

    Effects of glucose overloading on microbial community structure and biogas production in a laboratory-scale anaerobic digesterIntroductionMethodsReactor systemMicrobial biomass and community structureAnalytical methods for gas and glucoseFate of added glucoseData analysis

    ResultsEffects on microbial communitiesProcess parameters

    DiscussionAcknowledgementsReferences

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