Drivers of microbial community composition in mesophilic and thermophilic temperature-phased anaerobic digestion pre-treatment reactors

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    Drivers of microbial community composition inmesophilic and thermophilic temperature-phasedanaerobic digestion pre-treatment reactors

    Hasina M. Pervin a, Paul G. Dennis a,b, Hui J. Lim a, Gene W. Tyson a,b,Damien J. Batstone a, Philip L. Bond a,*aAdvanced Water Management Centre, The University of Queensland, Brisbane, Queensland 4072, AustraliabAustralian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland,

    Brisbane, Queensland 4072, Australia

    a r t i c l e i n f o

    Article history:

    Received 8 April 2013

    Received in revised form

    2 July 2013

    Accepted 4 July 2013

    Available online 23 October 2013


    Temperature-phased anaerobic


    Molecular microbial ecology

    Thermophilic pre-treatment


    Abbreviations: AD, Anaerobic Digestion;Hydraulic Retention Time; MP, Mesophilic Pmorphism; TP, Thermophilic Pre-treatment;RFLP, Terminal Restriction Fragment Length* Corresponding author. Advanced Water Ma

    Research Rd., St. Lucia, Queensland 4072, AuE-mail address:

    0043-1354/$ e see front matter 2013 Elsev

    a b s t r a c t

    Temperature-phased anaerobic digestion (TPAD) is an emerging technology that facilitates

    improved performance and pathogen destruction in anaerobic sewage sludge digestion by

    optimising conditions for 1) hydrolytic and acidogenic organisms in a first-stage/pre-

    treatment reactor and then 2) methogenic populations in a second stage reactor. Pre-

    treatment reactors are typically operated at 55e65 C and as such select for thermophilic

    bacterial communities. However, details of key microbial populations in hydrolytic com-

    munities and links to functionality are very limited. In this study, experimental thermophilic

    pre-treatment (TP) andcontrolmesophilic pre-treatment (MP) reactorswereoperatedasfirst-

    stages of TPAD systems treating activated sludge for 340 days. The TP system was operated

    sequentially at 50, 60 and 65 C,while theMP rectorwasheld at 35 C for the entireperiod. The

    compositionofmicrobial communities associatedwith theMPandTPpre-treatment reactors

    was characterised weekly using terminal-restriction fragment length polymorphism (T-

    RFLP) supported by clone library sequencing of 16S rRNA gene amplicons. The outcomes of

    this approachwere confirmedusing 454 pyrosequencing of gene amplicons andfluorescence

    in-situ hybridisation (FISH). TP associated bacterial communities were dominated by pop-

    ulations affiliated to the Firmicutes, Thermotogae, Proteobacteria and Chloroflexi. In particular

    there was a progression from Thermotogae to Lutispora and Coprothermobacter and diversity

    decreased as temperature and hydrolysis performance increased. While change in the

    composition of TP associated bacterial communities was attributable to temperature, that of

    MP associated bacterial communities was related to the composition of the incoming feed.

    This study determined processes driving the dynamics of keymicrobial populations that are

    correlated with an enhanced hydrolytic functionality of the TPAD system.

    2013 Elsevier Ltd. All rights reserved.

    BLAST, Basic Local Alignment Search Tool; FISH, Fluorescent In situ Hybridization; HRT,re-treatment; OTU, Operational Taxonomic Unit; RFLP, Restriction Fragment Length Poly-TPAD, Temperature-Phased Anaerobic Digestion; T-RF, Terminal Restriction Fragment; T-Polymorphism.nagement Centre (AWMC), The University of Queensland, Level 6 Gehrmann Building (60),stralia. Tel.: 61 (0)7 3446 3226; fax: 61 (0)7 3365 (P.L. Bond).

    ier Ltd. All rights reserved.

  • wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 7 0 9 8e7 1 0 8 7099

    1. Introduction

    observed to be both stable (Weiss et al., 2008) and variable

    Anaerobic digestion (AD) is an economically and environ-

    mental attractive microbially driven process that can be used

    to generatemethane from biosolids. AD comprises hydrolysis,

    fermentation, acetogenesis and methanogenesis (Weiland,

    2010). Bacteria generally dominate the first three stages;

    however, archaea drive methanogenesis and this latter stage

    is generally well characterised (Amani et al., 2010). In com-

    parison, detailed knowledge of the populations responsible for

    hydrolysis and fermentation is lacking. Hydrolysis is a key

    rateelimiting step as the products are rapidly consumed by

    methanogens (Li and Noike, 1992; Rittmann, 2008). Greater

    insight into the key microorganisms involved, their dynamics

    and details of their activities can provide opportunities for

    manipulation of populations and functions for enhancing

    process performance, reactor efficiency and troubleshooting

    management of AD.

    Temperature-phased anaerobic digestion (TPAD) is an

    emerging process, in which enhanced hydrolysis, facilitated

    by a pre-treatment reactor operated at 50e70 C, can becombined with enhanced stability of the overall process (Paul

    et al., 2012). A TPAD system may typically comprise of a

    thermophilic pre-treatment reactor with a short (2e4 days)

    hydraulic retention time (HRT) followed by the main reactor

    operating at mesophilic temperatures with a 10e15 day HRT

    (Ge et al., 2011). The functionality of the pre-treatment stage is

    mainly associated with hydrolysis and acidogenesis, which

    are mediated by bacteria. The second stage function is pri-

    marily acetogenesis and methanogenesis, and this will

    comprise a mix of bacteria and archaea. TPAD is particularly

    applicable to AD of activated sludge, as it allows increased

    performance regarding hydrolysis of organic solids and

    methane production at a moderate energy input, as well as

    full pathogen removal (Paul et al., 2012).

    There have been limited molecular-based studies of mi-

    crobial communities in AD systems. These studies largely

    focus on the methanogenic communities (Kobayashi et al.,

    2009) although those that include analyses of bacterial com-

    munities reveal mostly novel phylotypes (Chouari et al., 2005).

    For example, in a survey of publically available 16S rRNA gene

    amplicon sequences associated with anaerobic digesters,

    Nelson et al. (2011) found that ca. 60% of bacteria could not be

    assigned to any established genus (Nelson et al., 2011). Mi-

    crobial communities of seven mesophilic full scale digesters

    have been examined and, bacteria of the Chloroflexi, Betapro-

    teobacteria, Bacteridetes and Synergistetes were observed as core

    groups (Riviere et al., 2009). However, details of the bacterial

    populations within those phyla and the ecological role of

    those are yet to be determined. The compositions of AD-

    associated bacterial communities are seen to be influenced

    by reactor parameters. For example, pH fluctuations have

    been observed to correlate with changes in bacterial com-

    munitieswithin a thermophilic AD over time (Hori et al., 2006),

    and similarly, pH changes in a mesophilic multistage AD

    system were implicated in bacterial community differences

    between phases of the reactor (Supaphol et al., 2011). In AD

    systems run with the same operational conditions over time,

    however, the composition of bacterial communities has been

    (Fernandez et al., 1999; Pycke et al., 2011). A recent study

    compared bacterial communities of seven full scale anaerobic

    reactors having a temperature range of 35e52 C (Lee et al.,2012). It was found that temperature was a major factor

    affectingmicrobial community compositions, and some of the

    phylotypes could be weakly linked with some process per-

    formance parameters (Lee et al., 2012). In a recent study of a

    TPAD pre-treatment stage treating primary sludge, over 90%

    of the sequences were from previously undetected bacteria

    (Pervin et al., 2013). This study identified specific thermophilic

    populations, but could not link performance to community

    changes. Additionally, the treated waste was primary sludge,

    and although feed communities were not determined, the

    variable nature of the feed was implied to influence the pre-

    treatment bacterial communities. It is evident that studies of

    these bacterial communities are limited and knowledge of the

    ecology and how that may be related to the system operation

    is just beginning to develop. In particular, the pre-treatment

    stage in a temperature-phased anaerobic process is

    appealing from a microbial perspective, since it is novel in

    temperature and performance, and studies comparing ther-

    mophilic and mesophilic systems would be revealing.

    Consequently, there are limitations with previous studies

    with respect to determining hydrolytic communities, aswell as

    with identification of dynamics of key microbial populations.

    Additionally, insight is required as towhether functionality is a

    general community characteristic, or whether it can be linked

    to key populations. It is very difficult to address this fully, but

    examination of TPAD operating at different temperatures, and

    on a feed more consistent than primary sludge, such as acti-

    vated sludge, offers the opportunity to associate microorgan-

    isms with reactor performance. In this study we attempt to

    address this gap through multiple molecular approaches

    including high analytical frequency through T-RFLP, objective

    identification through 16S rRNA gene clone-libraries and

    pyrotag sequencing, as well as PCR-independent analysis

    through fluorescence in-situ hybridisation. The overall objec-

    tivewas to identify community populations thatmay be linked

    to increased temperature and performance.

    2. Materials and methods

    2.1. Reactor operation and performance

    Two TPAD systems, each consisting of two stages: 1) a 0.6 L

    pre-treatment reactor with a hydraulic retention time (HRT) of

    two days and 2) a 4 L main reactor (methanogenic) with a 14

    day HRT, were operated for 340 days. In one system, the pre-

    treatment was performed under mesophilic conditions at

    35 C (MP), while the other was operated under thermophilicconditions at 50 C for 186 days, 60 C for 100 days and 65 C for60 days (TP). In both systems the second-stage reactor was

    operated at 35 C. Details of the reactor operations aredescribed in Ge et al. (2011). The reactors were inoculatedwith

    sludge from another lab-scale mesophilic TPAD system, this

    provided a relevant and common starting point for both re-

    actors. The TPADs were fed 0.3 L per day of activated sludge

  • wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 7 0 9 8e7 1 0 87100

    collected from a wastewater treatment plant in Gold Coast

    city, Australia. The activated sludge feed was collected

    monthly and stored at below 4 C. The reactors were mixedusingmagnetic stirrer bars. The performance of each reactor was

    characterised by measuring quantities of total solids (TS),

    volatile solids (VS), volatile fatty acid (VFA), chemical oxygen

    demand (COD), total Kjeldahl nitrogen (TKN), ammo-

    niumenitrogen (NH4 N) and methane gas as described in

    Ge et al. (2011).

    2.2. Characterisation of microbial communities

    2.2.1. Sample collection and DNA extractionEffluent sludge samples were collected at regular intervals

    from both pre-treatment reactors during the operation of the

    TPAD systems (Figure S1), these samples were immediately

    frozen at 20 C for DNA extraction. Additional sludge sam-ples were collected from the feed reservoir, which was

    replenished daily with waste activated sludge (WAS), and are

    denoted as Feed in this study. Genomic DNA was extracted

    using the Fast DNA SPIN Kit for soil according to the manu-

    facturers instructions (Q-Bio gene, Australia).

    2.2.2. Microbial community fingerprinting by T-RFLPBacterial community structure was assessed using terminal

    restriction fragment length polymorphism fingerprinting (T-

    RFLP; Supplementary information). Briefly, PCR was per-

    formed using the 63F (50-AGTTTGATCCTGGCTCAG-30) and1389R (50-ACGGGCGGTGTRC-30) primers (Marchesi et al., 1998)followed by purification and restriction enzyme digestion in

    duplicates usingMSPI andHaeIII (Fermentas Inc., Hanover,MD,

    USA). Terminal restriction fragments (T-RFs) were analysed

    using an automated DNA sequencer (ABI Prism TM 3730). T-RF

    sizes and their corresponding areas were measured using

    GeneMarker (version 1.75; SoftGenetics, LLC., State College,

    PA, USA). Data were standardised by expressing each T-RF

    peak area as a percentage of the total population for that

    profile and normalised using a constant percentage threshold

    method as previously described (Sait et al., 2003).

    The likely origin of T-RF peaks was identified by producing

    in-silico profiles of cloned genes (see Section 2.2.3) using the T-

    RFLPMAP software (NERC environmental bioinformatics

    centre, UK). Although the T-RFs identities are putative, the

    confidence of the suggested identifications was increased by

    using two enzyme digestions and coinciding T-RFLP abun-

    dance patterns of the two digestions during the reactor

    operation (Figure S3). The TAP t-RFLP tool (Marsh et al., 2000)

    of the Ribosomal Database Project was used to verify the

    affiliation of peaks and to infer matches when those were not

    available from the clone library database. Both the MSPI and

    HaeIII digest results were used for identifications, and the T-

    RFLP profiles of the different digestions were in good agree-

    ment (Fig. S3). However, as MSPI generated the more detailed

    T-RFLP profiles, further analysis and results presented in this

    study are based on those.

    2.2.3. 16S rRNA gene amplicon cloning and sequencingBacterial and archaeal 16S rRNA genes of the communities

    were determined by PCR, cloning and sequencing at 100 days

    operation for MP and TP, and also at 240 days operation for TP.

    Amplicons were generated by PCR, as described previously

    (Bond et al., 1995), using the primer pairs 27F (50eTTTGATCCTGGCTCAGe30) and 1492R (50eGGTTACCTTGTACGACTTe30) forbacteria, and Arc8F (50eTCCGGTTGATCCTGCCe30) andArc927R (50e CCCGCCAATTCCTTTAAGTTTCe30) for archaea(Singh et al., 2006). Clone librarieswere constructed based on a

    total of 187 positive clones (Supplementary information). The

    full length clone sequences were phylogenetically analysed

    using representative bacterial sequences (ARB database, and evolutionary distance analysis in

    the ARB software package (Ludwig et al., 2004). The topology of

    the phylogenetic tree was used to aid probe design (Section


    2.2.4. 16S rRNA gene amplicon pyrosequencingBacterial and archaeal 16S rRNA gene amplicons were exam-

    ined by pyrosequencing from MP and TP reactor samples at

    days 240 and 324, this was when TP was operated at 60 C and65 C respectively. Gene amplicons were generated by PCR withprimers 926F and 1392R (Engelbrektson et al., 2010) that were

    modified on the 50 end to contain the 454 FLX Titanium Lib Ladapters B and A, respectively. The reverse primers also

    contained a 5-6 base barcode sequence positioned between

    the primer sequence and the adapter. A unique barcode was

    used for each sample. Following amplification (see Supple-

    mentary Information) purified and normalised amplicons

    were submitted to Macrogen (South Korea) for 454 pyrose-

    quencing (Supplementary information). Sequence analysis

    was performed as described previously (Dennis et al., 2013)

    using QIIME (Caporaso et al., 2010) and UCHIME (Edgar et al.,


    2.2.5. Fluorescence in situ hybridization (FISH)Probes for FISH for each of the three major OTUs in the clone

    library were designed as previously described using ARB

    (Hugenholtz et al., 2002), and then checked for specificity

    using BLAST ( and

    probeCheck (Loy et al., 2008). Probes were synthesised and

    labelled at the 50 end with either Cy3, Cy5 or FITC (Gene-Works, Australia). FISH was performed using previously re-

    ported phylogenetic group specific probes and newly

    designed species specific probes (Table S1) on reactor sam-

    ples fixed in either 4% paraformaldehyde (Gram negatives) or

    ethanol (Gram positives) according to established procedures

    (Amann et al., 1995). To assess probe specificities FISH was

    performed on fixed reactor samples with those probes at

    different stringencies by increasing the formamide concen-

    tration in the hybridization buffer in 5% intervals and

    decreasing the NaCl concentration in the respective wash

    buffers accordingly. The most stringent conditions that gave

    the brightest signal with the presumed target cells were

    considered as optimal for subsequent quantification. Micro-

    bial cells hybridising to the fluorescently labelled probes were

    observed with a Zeiss Axioplan LSM510 confocal laser-

    scanning microscope (CLSM) using standard excitation and

    emission wavelengths. FISH images were used for quanti-

    fying the population of target microbe using the DAIME

    version 1.3.1 software (Daims et al., 2006). The images were

    optimised by adjusting the pixel level to reduce background

    noise and to achieve a good contrast of the target organism


  • Table 1 e Reactor performance parameters as determined by Ge et al. (2011).

    Parameter 35 Ca 50 Cb 60 Cb 65 Cb

    Hydrolysis speed khyd (d1) 0.2 0.1 0.12 0.06 0.5 0.1 0.7 0.2

    Hydrolysis extent fd 0.4 0.1 0.4 0.1 0.41 0.04 0.51 0.04a Measured in MP system.b Measured in TP system.

    wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 7 0 9 8e7 1 0 8 7101

    over the general population. At least 25 images were used to

    obtain an accurate biovolume fraction of the target microbe.

    All biovolume fractions obtained have a minimum congru-

    ency level of 90% to ensure that the quantification values

    obtained were reliable.

    2.3. Statistical analyses

    Turnover in the composition of T-RFs between samples was

    visualised using Principle Component Analysis (PCA). Data

    were Hellinger transformed prior to analysis. The effect of

    treatment parameters on the composition of microbial com-

    munities was determined using permutational multivariate

    analysis of variance (PERMANOVA). Statistical analyses were

    conducted using R statistical package (R Development Core

    Team, 2004).

    3. Results

    3.1. Reactor operation and performance

    A detailed report and comparison of the performance of the

    TPADs is presented in Ge et al. (2011). Briefly, both TPAD sys-

    tems successfully produced methane throughout the 340 day

    operation and the thermophilic pre-treatment (TP) reactor

    demonstrated significantly enhanced AD performance.

    Increased volatile solids destruction, solubilisation and pro-

    duction of volatile fatty acids was evident in the TP reactor in

    Table 2 e Putative identification of the most abundant T-RFs inphylogenetic analysis of cloned sequences. TP 50, TP 60, TP 65microorganisms during the periods of the TP reactor operationreactor operation (at 35 C throughout the experiment).

    T-Rf length asper MspI (bp)

    Putative identification determinedfrom clone sequence affiliation

    56 Comamonas sp.

    102 Uncultured Betaproteobacterium

    103 Uncultured Gammaproteobacterium

    112 Novosphingobium mathurense

    236 Uncultured Thermotogae sp.

    256 Coprothermobacter sp.a

    271 Lutispora thermophila

    450 Pseudomonas meridian

    451 Zoogloea resiniphila

    454 Thauera sp.

    480 Clostridium cellulovorans

    482 Uncultured Chloroflexi

    489 Clostridium sp.

    a Obtained from 100% matching fullelength representative sequence to

    comparison to the mesophilic pre-treatment (MP) reactor (Ge

    et al., 2011). The solubilisation of organic solids during the

    operationof theTP reactor increased from15%at50 Cto27%at60 C and 65 C. In comparison, solubilisation of organic solidsin the MP reactor was only 7% (based on the chemical oxygen

    demandbalance).Additionally, theammoniaenitrogenrelease

    in the TP reactor was constantly higher than that in the MP

    reactor (Ge et al., 2011). Model based analysis determined key

    kinetic parameters related to the extent (fd) and speed (khyd) of

    organic solid degradation (Table 1). Both the speed and amount

    of hydrolysis increased with increasing temperature in the TP

    reactor, but these parameters did not differ between the MP

    reactor at 35 C and the TP reactor at 50 C.

    3.2. Identification of key populations

    Sequencing of 16S rRNA amplicons from the clone library

    revealed a range of organisms that were associated with the

    pre-treatment reactors (Table 2 and Fig. 1). These sequences

    were subjected to in-silico restriction enzyme digests which

    facilitated their association with peaks from the T-RFLP anal-

    ysis (Fig. 2). The composition of microbial communities asso-

    ciated with the MP and TP reactors differed significantly

    (PERMANOVA, P < 0.001), with the TP reactor (50e65 C) beingassociated with members of the Thermotogae, Lutispora and

    Coprothermobacter (Fig. 3). The TP reactor communities were

    dominated by these key populations, particularly at the higher

    temperatures of 60 C and 65 C (Fig. 2). In comparison, the MPreactor (35 C) communities were not dominated by particular

    the pre-treatment reactors as determined from theand MP 35 indicate average abundance of particularat 50 C, 60 C, and 65 C respectively, and during the MP

    Average abundance (%) as per MSPI

    TP 50 TP 60 TP 65 MP 35

    0.28 0.02 0.06 1.06

    1.40 5.79 2.60 2.21

    3.58 1.65 2.33 5.21

    3.67 1.63 1.35 4.20

    12.18 28.58 3.77 0.73

    0.15 3.92 10.45 0.35

    3.94 17.23 21.46 0.68

    5.15 2.64 3.42 2.14

    0.41 3.33 2.02 3.67

    4.37 1.85 1.81 6.58

    3.30 0.33 0.81 1.79

    4.91 1.91 2.79 2.01

    0.00 0.03 0.02 3.57

    respective pyrotag sequence analysis.

  • Fig. 1 eMicrobial community analysis of TP samples by FISH, T-RFLP, and 16S rRNA gene pyrotag sequencing, including; (A)

    organisms identified by the THERMO846 probe as Thermotogae sp. at day 240 (60 C) (magenta) against other bacteria in blue(EUB338), (B) organisms identified by the LUTI1250 probe as Lutispora thermophile at day 294 (65 C) (magenta) against otherbacteria in blue; (C)Methanosarcina thermophila as identified by the SARC1645 (orange) with other Archaea (ARC915) in green

    and bacteria in blue; and (D) comparison of community analyses by pyrotag sequencing (Pyro 240, Pyro 325) and T-RFLP at

    days 240 (60 C) and 325 (65 C). Abundant populations detected are highlighted by arrows. (For interpretation of thereferences to colour in this figure legend, the reader is referred to the web version of this article.)

    wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 7 0 9 8e7 1 0 87102

    bacterial populations, but were associated with representa-

    tives ofGammaproteobacteria,Clostridium and Zoogloea.Archaeal

    populations related to the Methanosarcinaceae represented

    approximately 10% of the total population in the TP reactor at

    60 C (Figure S4). This findingwas in agreementwith the resultsof FISH analyses using the probe SARC1645 which specifically

    targetsMethanosarcina thermophila (Fig. 1). Only lownumbers of

    archaea were detected by FISH (

  • Fig. 2 e Abundance patterns of bacteria in (A) TP and (B) MP as revealed by T-RFLP with MspI enzyme; T-RFs having


  • Fig. 3 e PCA ordination representing variation in the composition of bacterial communities detected using T-RFLP

    fingerprinting of 16S rRNA gene amplicons. Samples are represented by circles; the size of which represents the number of

    weeks since the start of the experiment and the colour represents the temperature of the reactor at any given time. Samples

    from the same reactor are joined by arrows that indicate the progression of time. The crosses represent T-RFs, of which the

    most discriminating are labelled. T-RF labelled in bold font represent those with a corresponding taxonomic affiliation from

    in-silico restriction enzyme digests of 16S rRNA gene amplicon sequences (Table 2). The red text highlights the time periods

    of samples that are discussed in the main text. (For interpretation of the references to colour in this figure legend, the reader

    is referred to the web version of this article.)

    wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 7 0 9 8e7 1 0 87104

    occurred in the TP pre-treatment reactor during operation at

    50 C, 60 C and 65 C were related to populations that wereinfluenced by the temperature changes. For example, at 50 Cthe community differed over time due to a gradual increase in

    the abundance of the Thermotogae population (T-RF 236),

    whereas at 65 C the community differed over time due to thesame population gradually decreasing (Fig. 3).

    Changes that occurred in the MP pre-treatment reactor,

    however, appear to have been related to changes in the

    composition of the microbial communities associated with

    the feed (Fig. 3). Feed-associated microbial communities

    differed significantly over time, with feed samples becoming

    more enrichedwith three populations (T-RFs 396, 450 and 489)

    as the experiment progressed. These populations included

    Pseudomonas meridiana and a representative of the Clostridium

    (PERMANOVA, P < 0.001; Fig. 4). The largest change in the

    composition of the MP reactor associated bacteria community

    was apparent after 208 days andwas related to an enrichment

    of the P. meridiana and Clostridium populations (T-RFs 450 and

    489) also observed to vary in the feed. Another obvious change

    in the composition of the MP reactor associated bacteria

    community was apparent after 255 days (Figs. 3 and 4). The

    change was related to an enrichment of the P. meridiana pop-

    ulation which was also more abundant in feed from days

    250e280 relative to previous feed-stocks (Fig. 4). Feed com-

    munity composition is further implicated as a driver of MP

    pre-treatment reactor associated microbial community

    composition by a PERMANOVA analysis, which demonstrated

    that the primary axis scores from the PCA of the feed associ-

    atedmicrobial communities (Fig. 4) were significant predictors

    of variation in the composition of the MP pre-treatment

    reactor associated communities (P 0.016).

    4. Discussion

    4.1. Dynamic nature of microbial communities andcorrelation to reactor conditions

    We were interested to detect differences in the communities

    of the two pre-treatment reactors and correlate those to the

    operating conditions and performance of the reactors. The

    importance of temperature for methanogenic archaeal spe-

    cies composition has been shown previously (Karakashev

    et al., 2005), however, the influence of temperature driving

    bacterial species composition is yet to be established in AD.

    The communities in both TP and MP were dynamic as

    revealed by T-RFLP, FISH and pyrosequencing. The thermo-

    philic system was clearly dynamic in response to operating

    temperature. The largest variations in the TP reactor bacterial

    communities coincided with the changes in operation tem-

    perature (Fig. 3). Consequently this study successfully

  • Fig. 4 e PCA ordination representing variation in the composition of feed-associated bacterial communities. Samples are

    represented by circles. The size of the circles is proportional to the number of weeks since the start of the experiment.

    Arrows indicate the progression of time. The crosses represent T-RFs of which the most discriminating are labelled. T-RF

    labelled in bold font represents those with a corresponding taxonomic affiliation from in-silico restriction enzyme digests of

    16S rRNA gene amplicon sequences (Table 2). The first feed sample was characterised 100 days into the experiment after

    that each new batch of feed was subjected to T-RFLP fingerprinting. The temperature in the thermophilic reactor was 50 Con days 35e186, 60 C on days 187e287, and 65 C on days 288e340. The temperature in the mesophilic reactor was 35 Cthroughout the experiment.

    wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 7 0 9 8e7 1 0 8 7105

    correlated microbial community changes, particularly those

    of the bacteria, to operating conditions of increased temper-

    ature in anaerobic digestion.

    The TP reactor communities were dominated by particular

    bacteria at the different stages of temperature operation. This

    is likely to be related to the different temperature optimums of

    the bacteria. For example, at 65 C Thermotogae sp. was outcompeted in the TP reactor by Lutispora thermophila and other

    thermophiles; possibly this temperature being above the or-

    ganisms optimal range. Another possibility was the Thermo-

    togae sp. abundance was not favoured by the high

    concentrations of ammonium or organic acids, since the total

    VFA concentration increased three foldwhen the temperature

    increased from 60 to 65 C in the TP reactor (Ge et al., 2011).Thus, reactor conditions influenced the presence and domi-

    nance of specific populations resulting in the community dy-

    namics at various temperatures.

    The Feed community was seen to significantly affect the

    bacterial community structure in the MP reactor. Correla-

    tion of variation of Feed communities with that in MP

    reactor communities was evident by PCA ordination (Fig. 3).

    Likely, contributing to the MP communities were: survival of

    facultative anaerobic Feed populations due to the similar

    temperature conditions of the MP reactor and WAS, changes

    in the batches of Feed community composition and dead

    cell DNA from the Feed. Contributions of the Feed commu-

    nities were not so evident in the TP reactor communities

    and this could be explained by the selection pressure of

    temperature in TP having a stronger influence on microbial

    community composition in comparison with the feed


    Some variation in the TP reactor bacterial communities

    were detected within periods of constant operating tempera-

    ture. Variation in bacterial communities has been detected

    during the stable operation of AD reactors (Fernandez et al.,

    1999; Pycke et al., 2011). However, this variation in TP could

    be attributed to adjustment of population abundance

    following reactor temperature changes and consequential

    performance changes, such as changing VFA levels, occurring

    through the periods of constant temperature operation.

    4.2. Microbial community composition and reactorperformance

    The principal parameters for performance of anaerobic

    digestion are stated in Section 3.1. However, it is important

    that hydrolysis in TP at 50 C was similar to that in MP, andonly increased once temperature increased to 60 C, and thekey dominating populations shifted frommixed communities

    and Thermotogae to Lutispora thermophila and Coprothermobacter

  • wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 7 0 9 8e7 1 0 87106

    as the temperature increased to 65 C. This indicates thatwhile at 50 C the community was strongly directed by tem-perature (to Thermotogae), it was only once temperature

    increased and caused a population shift particularly to Lutis-

    pora thermophila and Coprothermobacter that performance in

    terms of hydrolysis increased substantially. While the com-

    munity changes could be related to increased hydrolysis,

    these changes also coincided with other changes, including

    increases in ammonia and organic acid concentrations (Ge

    et al., 2011). It should be noted also that these increases in

    digestion performance were related to increased protein hy-

    drolysis, a particularly important feature for WAS digestion.

    In the TP reactor methane production was significantly

    higher than in the MP reactor. This coincided with the pres-

    ence ofMethanosarcina thermophilawhich was abundant in TP.

    In contrast, FISH (results not shown) and pyrosequencing

    indicated that archaea were in very low abundance in MP.

    4.3. Possible functions of key organisms in thepre-treatment reactors

    We assume the abundant organisms in the pre-treatment

    reactors were playing important roles in the AD perfor-

    mance. While detection of particular 16S rRNA genes is not

    proof of phenotype activity, it is possible to suggest potential

    functions of the abundant microorganisms in the pre-

    treatment reactors. Thermotogae has been previously detec-

    ted in thermophilic anaerobic digesters (Chen et al., 2004;

    Leven et al., 2007), and in mesophilic AD (Nesbo et al., 2006),

    however, on this occasion they were not detected in the MP

    reactor. Members of the Thermotogae are thermophilic anaer-

    obes that excrete hydrolytic enzymes to catalyse a wide range

    of polysaccharides to acetate, carbon dioxide and hydrogen as

    the main fermentation products (Huber and Hanning, 2007).

    Thermotogae are also implicated with interspecies hydrogen

    transfer (Johnson et al., 2006), and the presence of Meth-

    anosarcina thermophila, implicates a possible syntrophy

    contributing to the methane production in TP.

    Lutispora thermophila were originally isolated from an

    anaerobic bioreactor operating at 55 C (Shiratori et al., 2008),and is a fermentater that strictly utilises amino acids for

    growth. Coprothermobacter, like Lutispora are within the Clos-

    trida subphylum of the Firmicutes. Also, similar to Lutispora,

    Coprothermobacter are detected in thermophilic andmesophilic

    anaerobic digestionand theyhavepreference for fermentation

    of protein and amino acids as opposed to carbohydrate

    fermentation (Etchebehere et al., 1998). This function of these

    organisms coincides with the abundance of these sequences

    detected with the higher levels of NH4 and VFA in the TP

    reactor at higher temperatures. Additionally, it highlights the

    importance of protein degradation and fermentation for the

    performance of AD systems.Coprothermobacter also produceH2and improved growth of these is detected in the presence of H2utilising methanogens (Sasaki et al., 2011).

    Methanosarcina thermophila, the primary archaeon in the TP

    reactor, are detected in previous studies of thermophilic

    anaerobic digestion systems (Kobayashi et al., 2008; Leven

    et al., 2007). In general, Methanosarcina are thought respon-

    sible for methane production in anaerobic digestion systems

    when acetate concentrations are high (Jetten et al., 1990;

    McMahon et al., 2001). However, Methanosarcina thermophila

    is capable of H2/CO2 conversion tomethane (Mladenovska and

    Ahring, 2000), and consequently the nature of this methano-

    genesis is of interest in terms of the metabolic pathway uti-

    lised. Additionally, the growth rates of organisms in the TP

    reactor (HRT of 2 days) would be faster than typically expected

    for methanogens. However, high growth rates, such as a 12 h

    doubling time on acetate, are reported for various Meth-

    anosarcina spp. (Mladenovska and Ahring, 2000).

    5. Conclusion

    The mesophilic pre-treatment reactor bacterial communities

    were heavily influenced by the feed, while the thermophilic

    reactor was less diverse, and had dominant populations of

    Thermotogae sp., Lutispora thermophila, and Coprothermobacter,

    shifting progressively from the first to the last as temperature

    was increased from 50 C to 65 C. Functionality was higher at60 C and 65 C, when the process wasmore dominated by thelatter two organisms, indicating that while temperature can

    direct community, there will be optimums related to the

    emergence of key populations that we suggest are implicated

    for the enhanced hydrolytic ability. A particularly important

    outcome was the consistency in outputs from the multiple

    methods applied, with key populations being quantified

    consistently by FISH, T-RFLP (full 16S rRNA gene sequence)

    and 454 pyrosequencing (partial 16S rRNA gene sequence).


    We thank the Queensland Government and Environmental

    Biotechnology Cooperative Research Centre (EBCRC),

    Australia for supporting this work as a sub-project of Small-

    medium scale organic solids stabilization. The authors

    gratefully acknowledge the contributions of Dr. Frances

    Slater, Dr. Huoqing Ge, and Dr. Paul Jensen.

    Appendix A. Supplementary data

    Supplementary data related to this article can be found at

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    Drivers of microbial community composition in mesophilic and thermophilic temperature-phased anaerobic digestion pre-treatm ...1 Introduction2 Materials and methods2.1 Reactor operation and performance2.2 Characterisation of microbial communities2.2.1 Sample collection and DNA extraction2.2.2 Microbial community fingerprinting by T-RFLP2.2.3 16S rRNA gene amplicon cloning and sequencing2.2.4 16S rRNA gene amplicon pyrosequencing2.2.5 Fluorescence in situ hybridization (FISH)

    2.3 Statistical analyses

    3 Results3.1 Reactor operation and performance3.2 Identification of key populations3.3 The effect of temperature of bacterial community composition3.4 Changes in bacterial community composition over time

    4 Discussion4.1 Dynamic nature of microbial communities and correlation to reactor conditions4.2 Microbial community composition and reactor performance4.3 Possible functions of key organisms in the pre-treatment reactors

    5 ConclusionAcknowledgementsAppendix A Supplementary dataReferences


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