Microbial management of anaerobic digestion:exploiting the microbiome-functionality nexusMarta Carballa, Leticia Regueiro and Juan M Lema

Available online at www.sciencedirect.com

ScienceDirect

Anaerobic reactors are mostly operated based on the

monitoring of process parameters and empirical expert

knowledge due to the limitations of microbial-based

management. This review analyzes the requirements to

conduct microbial management in anaerobic digestion,

emphasizing the importance of understanding the anaerobic

microbiome and the need of establishing microbial indicators of

optimal performance. The strategies currently applied to shape

the reactor microbiome are explored and we assess critically

the different types of management (retrospective, prospective

and proactive). We conclude that future research should lead to

more useful data or insights to accomplish proactive

management, seen as stimulation and anticipation rather than

remediation.

Addresses

Department of Chemical Engineering, Institute of Technology, University

of Santiago de Compostela, E-15782 Santiago de Compostela, Spain

Corresponding author: Carballa, Marta (marta.carballa@usc.es,

marta.carballa@gmail.com)

Current Opinion in Biotechnology 2015, 33:103–111

This review comes from a themed issue on Environmental

biotechnology

Edited by Spiros N Agathos and Nico Boon

For a complete overview see the Issue and the Editorial

Available online 13th February 2015

http://dx.doi.org/10.1016/j.copbio.2015.01.008

0958-1669/# 2015 Elsevier Ltd. All rights reserved.

IntroductionThe human society is claiming for a renewable energy

supply and anaerobic digestion (AD) can make a substan-

tial sustainable contribution since it simultaneously solves

the problem of organic waste management, reducing its

deposition in landfills. AD consists of liquefaction and

hydrolysis of insoluble organic compounds and gasification

of intermediates, accompanied by a partial or complete

mineralization and humification of the organic matter.

Although AD is a well-known and consolidated technolo-

gy, the key players of anaerobiosis and their associations

and functioning are not completely understood yet. The

* Microbiome is defined as a group of microorganisms cooperating and inter

organization [1, 2��].

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complexity of the anaerobic microbiome* and the high

number of uncharacterized microorganisms [3��], the high

specialized functioning due to thermodynamic constrains

[4], the limitations of the frequently used DNA-based

methods [2��] and the continuous entrance of microorgan-

isms with the feedstock in open systems [5] are some of the

reasons of this gap. Additionally, the higher phylogenetic

diversity, multiple microbial interactions and the redun-

dant microbial functions hampers the microbial-based

management of anaerobic reactors. Yet, some efforts have

been made in the past years for monitoring complex

microbial communities and to set the standard character-

istics of an anaerobic microbiome for an optimal perfor-

mance, that is, successful (high efficiency at high rate)

methane production and process stability. In this review,

the requirements to conduct microbial management in

anaerobic digestion are analyzed. The combination of

fundamental knowledge about the anaerobic microbiome

with microbial indicators of optimal performance should

enable the development of microbial-based management.

In addition, the strategies currently applied to shape the

reactor microbiome are described and a critical and com-

parative assessment of the different types of management

(retrospective, prospective and proactive) is performed.

Needs for microbial management in anaerobicdigestionTwo needs for microbial management of anaerobic reac-

tors were identified: to understand the anaerobic micro-

biome, that is, fundamental knowledge about microbial

communities, including how they behave against envi-

ronmental and process disturbances, and to set microbial

indicators of optimal performance, that is, benchmark

values for well-performing reactors as well as warning

indicators of process failure.

Understanding the anaerobic microbiome:hydrolytic versus methanogenic functionThe conversion of complex organic compounds to CH4 and

CO2 is possible due to the cooperation of different micro-

organisms, that are clustered in two main domains: Bacteria,

in charge of decomposing the organic matter into volatile

fatty acids (VFAs), CO2 and H2, and Archaea, responsible of

CH4 formation [6�]. Moreover, the syntrophic relationship

between microorganisms producing and consuming hydro-

gen is necessary to guarantee efficient and stable operation.

acting among them, showing a higher resilience level of functionality and

Current Opinion in Biotechnology 2015, 33:103–111

104 Environmental biotechnology

y PCA: principle component analysis; PCoA: principle coordinate

analysis; RDA: redundancy analysis, NMDS: nonmetric multidimen-

sional scaling.

Most studies target Archaea [7,8], as methanogenesis is

usually the rate-limiting step and the low diversity of

archaeal population hinders the functional redundancy

[9]. However, the monitoring of bacterial populations

becomes essential in anaerobic reactors treating solid waste,

in which the hydrolytic phase is often the bottleneck.

As functioning and stability of an anaerobic reactor rely on

microbial community structure, understanding anaerobic

microbiome composition and interactions is crucial. The

biodiversity of the anaerobic microbiome is not only

influenced by the environment (especially temperature

[10] or the type of substrate (which also determines the

rate-limiting step), but also by the arrival and quantity of

new species [11]. Proteobacteria, Firmicutes, Bacteroidetesand Chloroflexi are the four major phyla in the bacterial

domain [12,13��], whose diversity is mainly driven by the

use of different substrates [5,14,15] and the operational

conditions, such as temperature [16,17] or organic loading

rate (OLR) [18]. For instance, lipid-rich substrates pro-

mote Thermosediminibacter litoperuensis presence [14],

higher OLRs favor the dominance of Firmicutes species

[18] and Bacteroidetes and Chloroflexi predominate at meso-

philic temperature [17]. On the contrary, the archaeal

population is steered by the reactor environment, mainly

the concentrations of volatile fatty acids (VFAs) [19,20],

ammonium [20] and temperature [16], as well as by

reactor configuration [19,21], with Methanosaeta and the

uncharacterized WSA2 group [12,22] as dominant species.

Recently, a clear relationship between operation and

microbiome was detected and three clusters based on

the operational conditions (easy, harsh and very harsh)

were proposed [23].

However, to design microbial-based strategies to manage

anaerobic reactors, not only the microbial community

structure during steady-state performance is required,

but also how they react to operational or environmental

disturbances. Some information is available about the

response of the archaeal domain, but these patterns are

poorly understood for bacterial populations. Overall,

stressful conditions, such as loading shock events, de-

creased hydraulic retention times (HRTs), temperature

variations, increased ammonium or long chain fatty acid

(LCFA) concentrations, promote the dominance of

Methanobacteriaceae, Methanomicrobiaceae and Methanosar-cina and a likely shift from aceticlastic methanogenesis to

syntrophic acetate oxidation followed by hydrogeno-

trophic methanogenesis [24–27,28��].

Certainly, the rapid development in culture-independent

techniques over the last decade has generated a lot of data

about the anaerobic microbiome, but the link between

microbial community structure with reactor functioning is

still unclear [3��]. Future research should focus not only on

the simultaneous identification of phylogeny, interrela-

tionships and function, but also on microbial population

Current Opinion in Biotechnology 2015, 33:103–111

dynamics during transitional periods caused by environ-

mental stresses or operational disturbances, particularly

the bacterial domain.

Microbial indicators for optimal performanceBenchmark values based on microbial community struc-

ture associated to optimal reactor performance (microbial

indicators) are needed for microbial management of an-

aerobic digestion. By contrast to process performance

indicators (VFA levels, Ripley index, hydrogen concen-

tration, among others), no much information is available

about microbial indicators. In this section, besides review-

ing the published data and speculating on the reasoning

behind each indicator, we will try to distinguish between

monitoring indicators (those associated to good steady-

state performance) and warning indicators (those pointing

out a process disturbance that might end in process

failure).

Firstly, phylogeny-based indicators, that is, presence or

variation on specific microorganism(s), are described. The

importance of Clostridia class, which contribute to degrad-

ing both protein and cellulose, and Bacilli class, responsi-

ble of decomposing fat and carbohydrate, of the phylum

Firmicutes and the phyla Bacteroidetes and Proteobacteriahave been stand out by many authors in solid-based

reactors [13��,16,29–31]. The main explanation lies in

the capacity of these fermentative Bacteria to process a

wide range of substrates [32,33]. The presence of Syn-trophomonas (propionate and butyrate degraders) and

Synergistetes (syntrophic acetate oxidizers) might be a sign

of well acetogenic [11,12] and acetotrophic performance

[34], respectively. The order Methanosarcinales and in a

lesser extent Methanomicrobiales are the dominant Archaea

in stable reactors [9,19], with the genus Methanosaeta as

the main acetate-degrader [19]. The combination of

phylogenetic data with operational/environmental vari-

ables by using computational ecology methods (PCA,

PCoA, RDA, NMDS)y has been widely used in the last

years in order to reinforce the link between microbiome

structure and function. Zingashin [9], for instance, found

a strong correlation between Methanoculleus and ammonia

concentration using NMDS, and Sundberg [13��] corre-

lated higher numbers of Thermotogae and Sphingobacteriawith thermophilic temperatures applying PCA. The lack

of studies assessing Bacteria response to disturbances and

the functional redundancy and resilience of bacterial

populations hampers the selection of a warning bacterial

indicator. On the contrary, Methanosaeta decrease can be

used as warning indicator in Methanosaeta-dominated

reactors [22], while a decrease in the active archaeal

community can be selected for those well-performing

reactors with no presence of this genus [10] (e.g. dry

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Microbial management of anaerobic digestion Carballa, Regueiro and Lema 105

anaerobic digesters or thermophilic digesters with rela-

tively high ammonium).

The huge amount of data derived from the molecular

techniques, particularly the high-throughput methods, calls

for a universal platform to interpret and compare them.

Consequently, a set of tools (here called numerical indica-

tors) have been proposed [1,35], which also incorporates

information about microbiological interactions. To main-

tain functional stability and robustness, three ecological

parameters play an important role: microbial community

diversity, evenness of microbial community structure and

microbial community dynamics over time [1,35–37,38�].

Although there are reactors with low diversity indexes

operating in stable conditions (e.g. those treating simple

substrates [5] or working at high temperature [39]), a

functional diverse microbial community provides a suite

of parallel pathways for each trophic step [37], and thus, a

higher diversity is often correlated with good-performing

anaerobic reactors [5,27,36,40�]. The explanation lies

behind the resistance, resilience and functional redun-

dancy of the anaerobic microbiome (Box 1). The combi-

nation of these three types of populations ensures the

overall functional stability and qualifies the microbial

community to face environmental stresses or process

perturbations [37,41], as shown in Figure 1. However,

the use of diversity as warning indicator is not clear yet.

The technique-dependence of most diversity indexes

and the calculation methods used are the likely argu-

ments for the discrepancy among studies [28��,36].

Evenness in the structure of the microbial diversity

ensures an adequate distribution of dominant microor-

ganisms and resilient ones [35], thereby the community

Box 1 Resistance, resilience and functional redundancy of

anaerobic microbiome

There are three basic mechanisms to maintain microbial community

function over time, regardless a disturbance [37,41]: resistance

(populations able to withstand changes without variations in

composition), resilience (populations with the ability to rebound

following a disturbance) and redundancy (a disturbed population is

replaced by a new population whose function is redundant with the

original, thus not affecting system performance). Applying these

concepts to anaerobic microbiome, the ‘core microbiome’ contains

the resistant populations, but as their contribution to the overall

system functioning is poorly understood, they can only be used as

fingerprint of specific reactor environments. Hydrolytic-fermentative

bacteria are functionally redundant, whereas syntrophic commu-

nities tend to be more resilient [3��]. The latter are usually minority

community members, but extremely function-specialized (only they

can perform the task). Therefore, their upturn following a disturbance

is crucial to preserve or recover the overall system performance.

Archaea are less diverse, metabolically slower and less resilient to

stress than Bacteria [6�]. Therefore, methanogenesis is more

susceptible to stress and instability. We speculate Methanobacter-

iales as resistant, Methanosaeta as redundant and Methanosarci-

na and Methanomicrobiales as resilient and redundant.

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has more capacity to use its varied array of metabolic

pathways [37]. Consequently, microbial communities

with intermediate evenness have a more robust function

[28��,35,37,40�,42]. More important, a decrease in bacte-

rial evenness can be used as warning indicator, as dem-

onstrated by different perturbations (loading shock,

temperature, ammonia) [28��,36]. This is explained by

the fact that anaerobic process requires both key (impor-

tant as they are responsible of a big fraction of the

functioning) and team players (equilibrium approach to

fully exploit all metabolic pathways) in the microbial

community to guarantee well-performance.

The dynamics of populations over time allows the com-

munity to adjust following disturbances, providing the

system with access to the total functional diversity and

environmental specificity available in the community [37].

The population dynamics in anaerobic reactors are quite

unclear, since some researchers observed community shifts

in functionally stable [43,44] and unstable reactors [31,37],

while others observed stable communities in functionally

stable systems [5]. Moreover, some authors suggest a high

population dynamics, mainly bacterial, as a well-function-

ing symptom [36,40�], while others described a stable

community in well-performing reactors [5]. These contro-

versial results are likely due to the functional redundancy

and resilience of the anaerobic microbiome, but hinder the

use of dynamics as microbial indicator.

From the abovementioned results, we propose interme-

diate bacterial evenness and a minimum active archaeal

population as monitoring indicators and a decrease in

bacterial evenness, in Methanosaeta or in the active ar-

chaeal population as warning indicators (Table 1). Yet,

further research is required to establish the optimal values

of these parameters, ideally independent of the molecular

technique used.

Management strategies in anaerobicdigestionDespite the hurdles for microbial-based management,

several strategies are applied to shape the reactor micro-

biome with the ultimate goal to increase methane pro-

ductivity. Current management strategies can be divided

into two groups: microbial-based strategies, those target-

ing directly the microbial community, and operational-

based strategies, those relying on a process parameter

variation, which indirectly affects the microbial commu-

nity. Moreover, a differentiation between boosting (aim-

ing at enhancing reactor performance) and remediation

(aiming at recovering a deteriorated performance) strate-

gies was done (Figure 2).

Microbial-based strategiesAn inoculum with high activity levels and balanced

anaerobic microbial communities plays an important role

in anaerobic reactor start up [6�,45]. Furthermore, the use

Current Opinion in Biotechnology 2015, 33:103–111

106 Environmental biotechnology

Figure 1

REACTOR PERFORMANCE

CH4 PRODUCTION

% VS DESTRUCTION

ACETIC ACID

MICROBIAL COMMUNITY STRUCTURE

Time

REDUNDANT

REDUNDANT

RESISTANT

RESISTANT

RESISTANT

RESILIENT

RESILIENT

DISTURBANCEMICROBIOME LEGEND

COLOUR: mechanisms tomaintain microbial community

function over time.

SHAPE: Microorganism type

RED -> RESISTANTGREEN -> RESILIENT

MULT IPL ECOLOURS -> REDUND ANT

Hydrolytic-fermentative

Acetogenic-Syntrophic

Methanosaeta

Methanobacteriales

Methanomicrobiales

Methanosarcina

Current Opinion in Biotechnology

Understanding the response of anaerobic microbiome to disturbances based on resistance, resilience and redundancy. Left: the legend (shape:

type of microorganism; color: behavior (resistant, resilient or redundant)). Right: the response of the different microbial communities (bottom)

against a process disturbance (up). Hydrolysis-fermentation is not affected (VS destruction is constant) due to functional redundancy.

Acetogenesis-syntrophy is affected (acetate accumulation), but recovered, due to resilience. Methanogenesis is affected (methane yield

decreased), but recovered, due to resilience and functional redundancy. Resistant microorganisms are assumed to be present in all stages.

of an acclimated microbial consortium is a promising

boosting strategy to accelerate the start-up of the diges-

tion process [46,47]. For example, around 5-fold faster

start-up was attained in a reactor treating olive mill

wastewater using an adapted consortium to lipids degra-

dation (Figure 2a, [46]).

Stimulation of microbial growth by trace elements addition

improved the performance of the anaerobic process (higher

methane yields and low levels of VFA) not only during

start-up [48,49], but also during steady-state operation

(Figure 2b, [48]). Furthermore, supplementation of trace

elements resulted to be a successful remediation strategy

to overcome a propionic acid accumulation event ([50],

Figure 2c, [51�]). Different combinations of trace metal

supplementations can have synergistic or antagonistic

Current Opinion in Biotechnology 2015, 33:103–111

effects [52,53], thereby the elements to be supplied and

the dosages are not clear yet. As a consequence, this

strategy is still quite empirical and more research on the

relationship between microbial populations and trace

metals is needed.

Bioaugmentation has been applied to enhance the deg-

radation of problematic substrates, such as lipid-rich feed-

stocks [54,55], or to recover digester performance after

perturbation [56,57]. Increased methane yield (10–24%,

Figure 2d, [54]) and shorter recovery period (70–80 days

earlier, Figure 2e, [56]) were observed after bioaugmen-

tation. Bacterial-based bioaugmentation is mostly used to

enhance solids anaerobic digestion, with the typical used

strains belonging to Pseudomonas, Bacillus and Actinomyces[58]. Archaeal-based bioaugmentation is not often

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Microbial management of anaerobic digestion Carballa, Regueiro and Lema 107

Table 1

Proposed microbial indicators. Phylogeny-based indicators are proposed for Archaea due to its low diversity: a minimum active Archaea

population and a decrease in Methanosaeta or in the active archaeal community as monitoring and warning indicator, respectively. The

high diversity and functional redundancy of bacterial communities hinder the definition of phylogeny-based indicators for Bacteria;

thereby numerical indicators are more appropriate. Among them, evenness is suggested as both monitoring and warning indicator,

supported by several studies. Diversity might also become a monitoring indicator once overcome its technique-dependence.

Monitoring Warning

Phylogenetic

Numerical

Indicator typeBacteria Archaea ArchaeaBacteria

Diversity

Evenness

Dynamics

High

Intermediate Decrease

Stable activearchaeal

population

Mathanosaetaand/or

active archaealpopulation decrease

X X

X

X X

X

XX

X

XX

employed, but recently bioaugmentation of ammonia

tolerant methanogenic consortia has been successfully

applied [59�]. However, bioaugmentation failure cases

have been also reported [60], pointing out that bioaug-

mentation potential is still lacking.

Operational-based strategiesA regular step-wise adaptation of the community to stress-

ful conditions has been used to strengthen the microbiome

against future disturbances (named here as endurance

development). In this way, a higher degree of functional

stability in the anaerobic digester is fostered [28��,38�,61].

For example, a regular application of organic material pulse

rather than continuous feeding allowed the microbial

community to be more tolerant to ammonium levels

(Figure 2f, [38�]). However, the most typical strategy

applied to manage the microbiome is the manipulation

of a process variable. Ho [16] improved the methane yield

by varying temperature and HRT (Figure 2g) and Schmidt

[62] dropped the OLR for few days to surpass a VFA

accumulation event (Figure 2h).

Retrospective versus prospective versusproactive managementThere is a high potential for microbial-based management

in anaerobic digestion with the final goal of initiate a

change in the microbial community to improve methane

production and process stability. But, this is not enough,

because the type of management conducted is also impor-

tant. If we simply evaluate reactor (well or deteriorated)

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functioning and then look backwards to assess microbial

community shifts explaining such performance (here

called retrospective management), the results would be

highly biased because of the several changes taken place

simultaneously and the lack of a comprehensive monitor-

ing. Accordingly learning from such experiments is ex-

tremely difficult. Most of the studies available in literature

performed retrospective management.

On the contrary, if we plan carefully a controlled pertur-

bation experiment with a detailed monitoring scheme

(here called prospective management), we will be able to

gather data to establish trustworthy patterns of microbial

community structure versus functionality. This informa-

tion is scarce in literature, although recently it has been

demonstrated that structural and functional changes can

be reliably predicted under controlled conditions [31] as

deterministic rather than stochastic processes guide mi-

crobial community dynamics.

More interestingly and desirable is the proactive man-

agement, seen as the trend to initiate a change rather than

react to changes. In other words, proactive management

implies stimulating and anticipating rather than remediat-

ing. To be predictive and avoid process failure, an addi-

tional condition is needed: the change at microbial

community level should occur before the change at

macroscopic level (here called as early microbial indica-

tor). Therefore, to accomplish proactive management: (i)

routine analysis of reactor microbiomes should become

Current Opinion in Biotechnology 2015, 33:103–111

108 Environmental biotechnology

Figure 2

Strategy

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(b)

40

30

20

10

0

30

20

10

0

504540353025201510

50

140

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40

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0

0 1 2 3 4

55 °C 60 °C 65 °C

5

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10

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6

2

4

00 100 200 300 400 500 600 700 800

0 10 20 30 40 50

50 60 70 80

5 10 15Time (days)

mg

CO

D_C

H4

Time (days) Time (days)

Time (days) SCOD<2 g L–1

Rec

ove

ry p

erio

d (

day

s)

Propionic<200 mg L–1

Time (days)

Time (d)

OL

R (

g L

–1 d

–1)

AC

(g

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)

Pro

pio

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Non-acclimatedbiomass

Acclimatedbiomass

Bioaugmentation

Endured reactor

No-endured reactor

Trace elements added

No trace elements

5-fold faster start-up

Improved stability

IncreaseCH4 yield

Endured biomassmore resistant toammonia levels

Immediatepropionatedegradation

Shorter recovery period

Methane yield can be improvedby varying temperature & HRT

OLR drop surpassed acidaccumulation

20

4d_HRT 3d_HRT 2d_HRT

Met

han

e (L

kg

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add

ed–1

)

2500

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)

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Control

500 600

Trace elementsand lime addition

OLR AC

(d)

(f)

(g) (h)

(e)

(c)

Current Opinion in Biotechnology

(a) Cumulative methane production in batch assays using olive mil wastewater and acetate as substrates with acclimated and non-acclimated

biomass [46]. (b) Propionate levels in reactors with and without trace elements addition [48]. (c) Effect of trace elements supplementation on

propionic acid degradation [51�]. (d) Methane yield in a reactor bioaugmented with Caldicellulosiruptor lactoaceticus at day 28 [54]. (e) Recovery

periods to reach soluble COD and propionic acid concentrations below 1 g/L and 200 mg/L, respectively [56]. (f) Response of endured and non-

endured biomass to high ammonia concentrations [38�]. (g) Variation of methane yield with temperature and HRT [16]. (h) Organic loading rate

(OLR) and acid capacity (AC), calculated as the sum of organic acid concentrations, during the digestion of grain stillage in a CSTR reactor [62].

Current Opinion in Biotechnology 2015, 33:103–111 www.sciencedirect.com

Microbial management of anaerobic digestion Carballa, Regueiro and Lema 109

more feasible (the requirements to fulfill this have already

been reviewed, [2��]), (ii) the large amount of data result-

ing from high-throughput sequencing should be con-

verted into meaningful microbial patterns by using, for

example, data mining, and (iii) robust microbial indicators

and early microbial indicators should be set down. We are

still on the road.

Acknowledgements

This research was supported by the Ministry of Economy andCompetitiveness through (CTM2010-17196) project and the Ramon y Cajalcontract (RYC-2012-10397) and by the Xunta de Galicia throughMicroDAN (EM2012/087) project. The authors belong to the GalicianCompetitive Research Group GRC 2013-032, programme co-funded byFEDER.

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110 Environmental biotechnology

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Authors observed a clear shift from acetoclastic methanogenesis to analternative acetate-consuming pathway of syntrophic acetate oxidation(SAO) as a response to an increase in the ammonia loading. Bacterialphylotypes became more uneven after perturbation, but they returned tomore even communities once SAO bacteria allowed reactors maintainstable performance.

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This study demonstrates how the feeding pattern (continuous vs. pulsefeeding) affects functional stability in anaerobic digesters, showing thatpulse-feeding promotes higher capacity to confront perturbations.

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This study monitors microbial community richness, dynamics and orga-nization in four full-scale anaerobic digesters over 45 days, highlighting

Current Opinion in Biotechnology 2015, 33:103–111

that communities in full-scale anaerobic digesters are unique to theinstallation and that community properties are dynamic.

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In this study, a full-scale reactor exhibited a highly dynamic environment(methanogenic populations changed constantly due to substrates avail-ability and inhibitors), but control actions such as organic loadingdecrease, addition of trace elements or alkalinity allowed maintenanceof digester stability.

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Microbial management of anaerobic digestion Carballa, Regueiro and Lema 111

bioaugmentation of overloaded anaerobic digesters. WaterRes 2011, 45:5249-5256.

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Fotidis IA, Wang H, Fiedel NR, Luo G, Karakashev DB, Angelidaki I:Bioaugmentation as a solution to increase methaneproduction from an ammonia-rich substrate. Environ SciTechnol 2014, 48:7669-7676.

One of the very few studies about bioaugmentation with Archaea. A fastgrowing hydrogenotrophic methanogen (Methanoculleus bourgensis)was bioaugmented in reactor with high ammonia levels (5 g/L), which

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resulted in an increased methane production of 31% respect to thecontrol.

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