Biomass and Bioenergy 85 (2016) 84e93
lable at ScienceDirectContents lists avaiBiomass and Bioenergy
journal homepage: http : / /www.elsevier .com/locate/biombioeResearch paperResponses of anaerobic microorganisms to different culture conditions
and corresponding effects on biogas production and solid digestate
quality
Rui Chen a, Mariana Murillo Roos g, Yuan Zhong a, Terence Marsh b,
Mauricio Bustamante Roman a, Walter Hernandez Ascencio c, Lidieth Uribe f,
Lorena Uribe Lorio c, Dana Kirk a, Dawn Marie Reinhold a,
Jose Alberto Miranda Chavarria d, Daniel Baudrit Ruiz d, Jose Francisco Aguilar Pereira d,
Werner Rodriguez Montero e, Ajit Srivastava a, Wei Liao a, *
a Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI, USA
b Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
c Research Center for Cellular and Molecular Biology, University of Costa Rica, San Jose, Costa Rica
d Agricultural Engineering, University of Costa Rica, San Jose, Costa Rica
e Fabio Baudrit Experimental Station, University of Costa Rica, San Jose, Costa Rica
f Agronomy Research Center, University of Costa Rica, San Jose, Costa Rica
g National Institute for Innovation and Transfer of Agricultural Technology, Ministry of Agriculture, San Jose, Costa Ricaa r t i c l e i n f o
Article history:
Received 15 April 2015
Accepted 27 November 2015
Available online 17 December 2015
Keywords:
Anaerobic microbes
Co-digestion
Biorefining feedstock
Biogas
Solid digestate* Corresponding author. Michigan State University
East Lansing, MI 48824, USA.
E-mail address: liaow@msu.edu (W. Liao).
http://dx.doi.org/10.1016/j.biombioe.2015.11.028
0961-9534/© 2015 Elsevier Ltd. All rights reserved.a b s t r a c t
Microbial communities of anaerobic digestion have been intensively investigated in the past decades.
Majority of these studies focused on correlating microbial diversity with biogas production. The rela-
tionship between microbial communities and compositional changes of the solid digestate (AD fiber) has
not been comprehensively studied to date. Therefore, the objective of this study was to understand the
responses of microbial communities to different operational conditions of anaerobic co-digestion and
their influences on biogas production and solid digestate quality. Two temperatures and three manure-
to-food waste ratios were investigated by a completely randomized design. Molecular analyses
demonstrate that both temperature and manure-to-food waste ratio greatly influenced the bacterial
communities, while archaeal communities were mainly influenced by temperature. The digestion per-
formance showed that biogas productivity increased with the increase of supplemental food wastes, and
there were no significant differences on carbohydrate contents among different digestions. The statistical
analyses conclude that microbes changed their community configuration under different conditions to
enhance digestion performance for biogas and homogenized solid digestate production.
© 2015 Elsevier Ltd. All rights reserved.1. Introduction
Anaerobic digestion (AD) is one of the oldest biotechnologies
that mankind has practiced to treat organic wastes for several
centuries. A complex anaerobic microbial consortium converts
organic matter in thewastes intomethane biogas - a carbon neutral
and renewable energy source, and correspondingly alleviates the, 524 S. Shaw Ln, Room 202,odor and pathogen problems. The classic AD systems often used
animal manure or sewage sludge as feedstock to provide nutrients
and inoculate anaerobic microorganisms [1]. However, due to the
structural and nutritional limitation of manure and sludge, single-
sourced AD systems have been described as “not energy efficient
nor cost effective” [2]. Co-digestion of multiple feedstocks was
hence introduced to enhance AD performance of biogas production
and total solids (TS) reduction [3e5]. In addition, the overall per-
formance of an AD system depends on not only the composition of
feedstock, but also operational parameters such as temperature [6].
Conventional operational temperatures range from mesophilic
(30e38 C) to thermophilic (49e57 C), and it has been proven that
R. Chen et al. / Biomass and Bioenergy 85 (2016) 84e93 85operational temperature is one of themost important determinants
of the microbial community structure in an AD system [6,7].
Numerous studies have been conducted on the microbiology of
anaerobic co-digestion system to correlate biogas production with
microbial diversity [8e12]. However, the relationship between
microbial communities and compositional changes of the solid
digestate (AD fiber) has not been widely reported [13]. Several
recent studies have discovered that solid digestate has a similar
cellulose conversion potential with other energy crops and residues
such as switchgrass and corn stover, and it can be used as a cellu-
losic feedstock for biorefining of fuel and chemical production
[14e18]. Therefore, a clear understanding on the relationship be-
tween mixed feedstock, microbial communities, biogas production,
and solid digestate quality should be achieved in order to advance
AD technology into a pretreatment unit operation for the next-
generation fuel and chemical biorefining.
The objective of this study was to delineate the responses of
microbial communities to changes in substrate composition and
reaction temperature of anaerobic co-digestion. Dairy manure was
mixed with food waste as the substrates to feed anaerobic di-
gesters. The 16S rRNA gene-based 454 pyrosequencing, Terminal
Restriction Fragment Length Polymorphism (T-RFLP) and clone li-
brary were used to investigate the communities. Microbial com-
munities was also statistically correlated with performance
parameters such as TS reduction, biogas production, and AD fiber
quality (cellulose, xylan, and lignin).
2. Materials and methods
2.1. Feedstock
Fresh dairy manure was collected from the Michigan State
University dairy farm (4241053.8000N, 842908.6300W), and stored
at 20 C prior to use. Dairy cows were fed on an alfalfa and corn
silage blend diet formulated according to the standard Total Mixed
Rations (TMRs) [19]. Food waste collected from cafeterias on
campus was homogenized using a commercial immersion blender
(Waring WSB70, Waring, Stamford, CT) and stored at 20 C prior
to use.
2.2. Anaerobic digestion systems
A completely stirred tank reactor (CSTR) was used as the
anaerobic digester in this study. Three different weight ratios of
dairy manure to food waste were used as feeds for the anaerobic
digesters: 100:0, 90:10 and 80:20 (based on dry weight). Each
digester contained 5% TS. Two culture temperatures of 35 and 50 C
were tested. The hydraulic retention time (HRT) was 20 days. A
completely randomized design (CRD) was applied on both factors
of manure-to-food waste ratio and temperature. Six treatments
with replicates were cultured on New Brunswick shakers (Eppen-
dorf, Enfield, CT) at 150 rpm for 4 full HRTs (80 days). All digesters
had a working volume of 0.50 L with 0.25 L headspace. The di-
gesters were first purged with nitrogen gas for 30 s and then sealed
with rubber septum caps. Daily biogas accumulationwas measured
using a water displacement system. Biogas sample from the di-
gesters was collected for gas composition analysis. All digesters
were fed every other day with 50 mL of afore mentioned feed. Feed
was prepared a few days before the feeding according to the
manure-to-food waste ratios, and stored at 4 C. Prior to the
feeding, an equal volume (50 mL) of digestate was removed from
the digesters as the digestate samples: 40 mL of the digestate
samples were stored at 20 C for TS, cellulose, xylan, and lignin
analyses. 10 mL of the digestate samples were stored at 80 C for
microbial community analysis. The pH of all digesters wascontrolled above 6.70 by dosing 20% sodium hydroxide (NaOH) at
the start-up stage of digestion (first one to two weeks). The oper-
ations of sampling, feeding, and pH adjustment were carried on
using a Simplicity 888 automatic anaerobic chamber (PLAS Lab,
Lansing, MI) purged with a medical grade specialty gas (85% ni-
trogen, 10% hydrogen and 5% carbon dioxide).
2.3. Analytical methods
Methane and carbon dioxide content were quantified using a
SRI 8610c gas chromatograph (Torrance, CA). The system was
equipped with a thermal conductivity detector. The detector was
kept at 150 C during the analysis. Hydrogen and helium were
carrier gases, and maintained at 21 psi. The biogas sample volume
was 100 mL, and the syringe was purged three times before sample
injection. Fiber composition of the digestate was analyzed accord-
ing to the National Renewable Energy Laboratory (NREL) Analytical
Procedure (LAP) [20]. The free sugars and starchwas analyzed using
a commercial starch assay kit (Catalog No. SA20. SigmaeAldrich Co.
LLC, St. Louis, MO).
2.4. Bacterial community analysis
A Power-Soil DNA isolation kit (MO BIO Laboratories, Carlsbad,
CA) was utilized to extract community genomic DNA from digestate
samples, and a NanoDrop™ Lite spectrophotometer (Thermo Fisher
Scientific Inc., Waltham, MA) was applied to quantify the DNA
extraction. Polymerase Chain Reactions (PCR) were conducted to
amplify the bacterial 16S rRNA gene sequences using a forward
primer 357F (50-CCTACGGGAGGCAGCAG-30) and a reverse primer
926R (50-CCGTCAATTCMTTTRAGT-30) which targeted on the hy-
pervariable V3eV5 region of rRNA genes [21e23]. A 454 “A”
adapter and unique barcode sequences were incorporated in the
reverse primer, and a “B” adapter was incorporated in the forward
primer. A 15 mL reaction solution contained 0.33 mM primer,
0.125 U mL1 high fidelity Taq polymerase (Life Technologies™,
Grand Island, NY), 1X Taq reaction buffer, 0.2 mM of each dNTP,
2 mM MgSO4, 0.1 mg mL1 BSA, and 10 ng DNA template. The re-
action solutionwasmixedwith DNase and RNase freewater for PCR
reaction. The amplification included an initial denaturing step at
95 C for 5 min, followed by 30 cycles of 3 temperature steps
(denaturing at 95 C for 45 s, annealing at 50 C for 45 s, and
elongation at 72 C for 90 s), and a final extension at 72 C for 5min.
The PCR products were purified using QiaQuick PCR Product Puri-
fication kit (Qiagen, Valencia, CA). Purified amplicons were diluted
to 0.5 ng dsDNA mL1 and sequenced using a Roche 454 GSFLX Ti-
tanium Sequencer at the Research Technology Support Facility of
Michigan State University. All bacterial 16S rRNA amplicon se-
quences were trimmed, screened and analyzed using Ribosomal
Database Project (RDP) Pyrosequencing Pipeline Initial Process
tools with a minimum sequence length of 300 bp and no ambig-
uous bases [24]. Chimeras were identified using USEARCH imple-
mented UCHIME algorithm in reference mode with Silva Gold
Alignment database [25]. Sequences were assigned with genus
names at 80% confidence level by RDP Multi-Classifier and clus-
tered at 97% similarity by Complete Linkage Clustering [13].
2.5. Archaeal community analysis
DNA extracts from the previous step were also used for archaeal
community analysis. The archaeal communities were examined
using 16S rRNA gene-based Terminal Restriction Fragment Length
Polymorphism (T-RFLP). The 16S rRNA gene was amplified with
archaeal domain-specific primers 344 aF-FAM (FAM-50-
CGGGGYGCASCAGGCGCGAA-30) and 1119aR (50-
86 R. Chen et al. / Biomass and Bioenergy 85 (2016) 84e93GGYRSGGGTCTCGCTCGTT-30) [13,26]. A 100 mL reaction solution
containing 20e40 ng DNA template, 90 mL Platinum® PCR Super-
Mix (Invitrogen, Life Technologies Corporation, Carlsbad, CA),
0.25 mM primer, and 0.1 mg mL1 bovine serum albumin (BSA) was
prepared for PCR reaction. The amplification included an initial
denaturing step at 94 C for 5 min, followed by 25 cycles of 3
temperature steps (denaturing at 94 C for 1min, annealing at 50 C
for 45 s, and elongation at 71 C for 100 s), and a final extension at
72 C for 5 min. The PCR products were then purified using Qia-
Quick PCR Product Purification kit (Qiagen, Valencia, CA). The pu-
rified PCR products were subjected to restriction enzyme digestion
with MspI (New England Biolabs Inc., Ipswich, MA). A 15 mL
digestion mixture contained 300e400 ng of purified PCR product,
1.5 mL 10X enzyme buffer, 0.5 mL enzyme (20 U mL1), and
0.1 mg mL1 BSA. The digestion mixture was incubated at 37 C for
3 h and deactivated at 65 C for 10 min. The digested DNA samples
(7 mL) were analyzed at the Research Technology Support Facility at
Michigan State University.
In order to construct archaeal clone libraries, the 16S rRNA genes
of four representative samples were amplified with archaea
domain-specific primers of 344 aF and 1119aR. Unlike the forward
primer 344 aF-FAM used in previous T-RFLP experiment, 344 aF
does not contain any fluorescent label (FAM). TOPO TA cloning kit
(Invitrogen, Life Technologies Corporation, Carlsbad, CA) with One
Shot® TOP10 Chemically Competent Escherichia coli was used for
cloning. A total of 192 clones were picked and screened for each
sample, and 96 clones with correct inserts were sequenced at the
Research Technology Support Facility of Michigan State University.
Archaeal 16S rRNA gene sequences obtained from clone libraries
were processed using RDP. Phylogenetic affiliations were analyzed
using the RDP Classifier at an 80% confidence threshold at genus
level.
2.6. Statistical analysis
Two-way analysis of variance (ANOVA) and pair-wise compari-
son using Statistical Analysis System program9.0 (SAS Institute Inc.,
Cary, NC) were conducted on biogas production, TS reduction, and
AD fiber composition to compare the AD characteristics and per-
formance among six experimental treatments.
Statistical software R with package Vegan was used to perform
the operational taxonomic unit (OTU)- and phylotype-based ana-
lyses of both bacterial and archaeal communities. Specifically, non-
metric multidimensional scaling analysis (NMDS) was used to
correlate the dissimilarities between samples and the variations in
phylotype abundance. The R package Vegan was also applied to
estimate the diversity index (Shannon's H), community evenness
(Pielou's J) and rarefaction curve for each sample based on clustered
sequences. The sampling coverage (C) of each bacterial sample was
calculated based on Good's method, C ¼ 1-n1/N, where n1 repre-
sents number of OTUs, and N is the total number of sequences in
the sample [27].
Peak Scanner™ Software v1.0 (Applied Biosystems®, Life Tech-
nologies Corporation, Carlsbad, CA) was applied to perform DNA
fragment analysis. Peaks below 50 fluorescence units were filtered
out to eliminate the background noise. Comparisons of T-RFLP re-
sults among samples were conducted by T-Align [28].
3. Results and discussion
3.1. Characteristics of feedstocks
Table 1 presents the characteristics of dairy manure and food
waste, which includes total carbon (C), total nitrogen (N), free
sugars and starch, structural carbohydrates (cellulose and xylan), aswell as lignin. It is noticeable that even though food waste con-
tained a similar amount of total carbon (47.8%) with dairy manure
(43.7%), it had significantly more available carbon (p ¼ 0.001) but
less cellulose (p ¼ 0.05) and xylan (p ¼ 0.007). This is due to the
difference in diets between ruminant and human: dairy cows were
fed on alfalfa and corn silage, both of which are fibrous lignocel-
luloses; while food waste from the university cafeterias contained
less fiber but more free sugars and starch (Table 1). In addition, high
total nitrogen content in food waste also attributes to human's high
protein diet (meat and dairy). C/N ratio in the organicmaterial plays
a crucial role in the anaerobic digestion. A high C/N ratio indicates a
rapid consumption of nitrogen by the microbes, which could result
in a reduction of biogas productivity [29]. While, a lower C/N ratio
leads to carbon deficiency, ammonia accumulation and pH increase,
all of which inhibit reproduction and metabolism of the metha-
nogens [30,31]. Therefore, mixing food waste with dairy manure
could provide a balanced C/N for a healthy and efficient AD process
[32e34].3.2. Effects of feedstock composition and culture temperature on
digestion performance
Fig. 1 and Table 2 illustrate the performance of digesters under
six different conditions. In general, methane content in biogas
ranged from 58.3 to 67.6% without significant difference among all
experimental runs (p ¼ 0.117). Daily biogas production and carbon
removed from the feed were significantly correlated to supple-
mental food waste (p ¼ 0.001 and 0.004, respectively) and reac-
tion temperature (p ¼ 0.001 and 0.005, respectively). The
interactions between these two factors also had significant im-
pacts (p ¼ 0.001 and 0.041, respectively) on the daily biogas
production and carbon removal from the feed. With the increase
of the food waste percentage, both mean biogas production and
carbon removal were significantly improved. On the contrary, fiber
analysis demonstrates that neither reaction temperature nor
supplemental food waste had impacts on cellulose (p ¼ 0.632 and
0.522, respectively), xylan (p ¼ 0.478 and 0.253, respectively), and
lignin (p ¼ 0.998 and 0.165, respectively) contents in the solid
digestate. In other words, this study demonstrates that within a
certain range of variation in feedstock composition (mainly
controlled by available C/N ratio), AD system could adjust itself in
order to maximize carbon utilization for biogas production and
generate homogenized solid digestate with similar carbohydrate
content. Considering the potential application of solid digestate as
a feedstock for biorefining of biofuel and chemical production
[14e18], the AD function of homogenizing carbohydrate compo-
nents in the solid digestate from different feeds might provide a
solution to address the compositional diversity the issue of
different lignocellulosic feedstock that lignocellulosic biorefining
processes encounter.
In order to further evaluate the AD performance between
different combination of temperature and feed ratio, daily biogas
productivity was introduced to conduct the comparison. The daily
biogas productivity [mL g1 TS reduction L1 digestion] was
calculated by dividing the daily biogas accumulation [mL L1
digestion day1] by daily TS reduction [g TS reduction day1]. The
biogas productivity data present that within the boundary of the
experimental conditions temperature had no significant influence
(p ¼ 0.206) on biogas production (Fig. 2). While, increasing the
percentage of food waste in the feed significantly increased the
biogas productivity (p ¼ 0.002). It is apparent that easy-
hydrolyzing carbon sources of free sugars and starch in food
waste enhanced the AD performance to produce biogas, homoge-
nized fiber quality of the solid digestate.
R. Chen et al. / Biomass and Bioenergy 85 (2016) 84e93 87
Table 1
Characteristics of feedstocka.
Dairy manure Food waste Comparison
Total carbon (wt%, dry basis) 43.7 47.8 p ¼ 0.061
Total available carbon (wt%, dry basis) 24.8 39.9 p ¼ 0.001
Free sugars and starch (wt%, dry basis) Not detectable 34.6 p < 0.001
Cellulose (wt%, dry basis) 22.7 16.5 p ¼ 0.005
Xylan (wt%, dry basis) 13.9 4.9 p ¼ 0.007
Lignin (wt%, dry basis) 28.4 11.9 p ¼ 0.009
Total nitrogen (wt%, dry basis) 2.1 5.3 p ¼ 0.005
C:N ratio, total C 20.6 9.0 e
C:N ratio, available Cb 11.8 7.5 e
a Data listed represent the average of two biological replicates.
b Available carbon excludes organic matters (i.e. lignin) that are not able to be utilized by anaerobic microbes.
Fig. 2. Daily biogas productivity (daily biogas accumulation vs TS reduction). Daily
biogas productivity is calculated using daily biogas accumulation divided by TS
reduction. Data are average of two replicates.
Fig. 1. Effects of feedstock composition and culture temperature on digestion perfor-
mance. Top bars with red color are TS reduction, bottom bars with blue color are biogas
production. Data are average of two replicates. (For interpretation of the references to
colour in this figure legend, the reader is referred to the web version of this article.)
Table 2
Performance of anaerobic digestiona.
Daily biogas (mL L1 AD day1) CH4 (%) Carbon removal from the feedb (%) Cellulose in residue (%) Xylan in residue (%) Lignin in residue (%)
35 C 100/0 558.9 58.3 27.4 23.1 14.3 36.4
90/10 499.1 65.2 24.2 22.3 13.5 36.4
80/20 626.5 60.1 30.2 23.9 13.6 34.4
50 C 100/0 554.4 59.0 27.2 25.3 14.8 38.0
90/10 642.1 58.6 31.2 22.4 13.8 35.0
80/20 848.8 67.6 40.9 23.4 13.7 34.3
a Data listed represent the average of two biological replicates.
b Carbon removed from the feed means that the percentage of carbon in the feed has been consumed for biogas production.3.3. Effects of feedstock composition and culture temperature on
anaerobic microbes
The afore mentioned performance results demonstrate that AD
can efficiently adjust itself to adapt into different nutrient condi-
tions to maintain the performance of digestion. Considering that
anaerobic microbes are the powerhouse of AD, the relationship
between microbial communities, digestion conditions, biogas
production, and digestate composition should be delineated in
order to better understand microbial responses to digestion con-
ditions, and enable engineering of anaerobic microbial commu-
nities to fulfill both biogas production and lignocellulose
pretreatment. Metagenomic analysis was carried on to elucidate
such relationship. The bacterial and archaeal communities were
separately discussed in this section.3.3.1. Anaerobic bacterial community
The pyrosequencing results demonstrate that the total bacterial
16S rRNA gene sequences in a sample ranged from 1594 to 30,295
among 12 digestate samples (Table 3). Although rarefaction curves
(Fig. S1) demonstrate a great unsampled diversity across all 12 di-
gesters, especially in those who had fewer sequences, the Good's
coverage (C) ranged from 89.0% to 98.8% with an average of 94.5%.
Allers et al. [35] used Good's numbers to indicate the diversity of an
environmental microbial community and they found that most of
the gammaproteobacteria were covered with the Good's numbers
fell between 70% and 80%. Therefore, the Good's numbers from all
12 AD samples indicated a high sampling coverage of bacterial
community.
Based on bacterial 16S rRNA gene targeted sequencing, bacterial
diversities (Hbact) of mesophilic digesters were significantly higher
88 R. Chen et al. / Biomass and Bioenergy 85 (2016) 84e93
Table 3
The diversity and evenness of bacterial and archaeal communities calculated based
on their 16S rRNA gene targeted sequencing.
Temp Ratio ID Bacteria Archaea
N a OTU b C (%)c H d J e d ebact obs bact bact Harch Jarch
35 C 100:0 MI1 30,295 368 98.79 2.67 0.55 1.67 0.80
MI2 13,987 227 98.38 2.78 0.59 1.85 0.77
90:10 MI3 13,589 224 98.35 3.08 0.64 2.06 0.83
MI4 3492 282 91.92 3.07 0.71 1.98 0.77
80:20 MI5 4126 277 93.29 3.25 0.73 1.84 0.77
MI6 4116 301 92.69 3.46 0.75 1.74 0.76
50 C 100:0 MI7 3770 328 91.30 2.52 0.58 1.80 0.72
MI8 10,416 220 97.89 2.73 0.58 1.52 0.85
90:10 MI9 10,849 213 98.04 2.23 0.43 1.59 0.82
MI10 1594 176 88.96 2.81 0.66 1.66 0.80
80:20 MI11 2988 247 91.73 2.65 0.62 1.63 0.84
MI12 2689 204 92.41 2.62 0.59 1.60 0.82
a Nbact is the total bacterial 16S rRNA gene sequences in the sample.
b OTUobs is the number of observed OTUs for an OTU definition.
c C is the sample/Good's coverage for an OTU definition.
d H is the Shannon's index which indicates the diversity of the microbial com-
munity; the subscript bact represents bacteria and arch represents archaea.
e J is the Pielou's index which indicates the evenness of the microbial community;
the subscript bact represents bacteria and arch represents archaea.than thermophilic digesters (p ¼ 0.006). Several previous studies
on anaerobic digestive microbial community also revealed similar
trend [36e38], which could be the reason why mesophilic AD is
more robust to environmental changes than thermophilic process.
However, the Pielou's evenness (Jbact) indices did not show any
significant difference among treatments (p  0.084), which means
that different bacterial communities had similar variations be-
tween OTUs. In addition, a combined dendrogram and heat map
was generated to demonstrate the similarity of bacterial commu-
nities across all samples (Fig. 3a). From the top of the dendrogram
(left-side of the figure), the first separation of clades shows a
community shift caused by reaction temperature. The cluster with
samples MI7-MI12 is thermophilic digesters (50 C) and the one
with samples MI1-MI6 is mesophilic digesters (35 C). At both
temperatures, the digesters fed on dairy manure only (MI1&2 at
35 C, and MI7&8 at 50 C) were significantly differentiated from
the ones fed on the mixture feed with 80:20 ratio (MI5&6 at 35 C,
and MI11&12 at 50 C). Meanwhile, the bacterial communities in
90:10 digesters (MI3&4 at 35 C, andMI9&10 at 50 C) behaved like
an intermediate state between the other two feed ratios, and their
replicates illustrated closeness to either 100% dairy manure or
80:20 ratio digesters. This result indicates that bacterial community
of an AD system gradually shifted its structure with the change of
the feedstock. Yue et al. [13] also observed a bacterial community
shift by supplementing corn stover into a dairy manure AD system.
A heat map of the most abundant bacterial genera in 12 samples
(Fig. 3a) demonstrates a higher microbial density and diversity in
mesophilic digesters (MI1-6). Moreover, digesters had higher
manure in the feedstock generally had higher microbial density.
Ribosomal Database Project's Multi-Classifier with a minimal
bootstrap value of 80 was used to determine the bacterial taxa. A
total of 23 phyla were assigned and overall 8.6% of total sequence
was categorized as unclassified bacteria. At genus level, a total of
363 bacterial groups (275 classified and 88 unclassified) were
identified. Bacteroidetes (46e69% at 35 C, 16e28% at 50 C), Fir-
micutes (20e45% at 35 C, 45e62% at 50 C), Proteobacteria (2e5% at
35 C, 4e7% at 50 C) and Spirochaetes (1e8% at 35 C) were the
most abundant phyla in all 6 treatments (12 digesters) (Fig. 4a). In
addition, Thermotogae (18%) was only observed in thermophilic
digesters with the 80:20 ratio. Synergistetes (1e2%) in mesophilic
digesters and Chloroflexi (8e14%) in thermophilic digesters werealso major components of their microbial communities (Fig. 4a,
wide columns). Within these phyla, Clostridia (19e41% at 35 C,
44e61% at 50 C), unclassified Bacteroidetes (30e38% at 35 C, 2e4%
at 50 C), Petrimonas (4e7% at 35 C, 6e8% at 50 C) and Bacteroides
(1% at 35 C, 1e2% at 50 C) were highly abundant (Fig. 4a, thin
columns). Thermophilic digesters tended to accumulate more Fir-
micuteswhile mesophilic ones had significantly more Bacteroidetes.
Class Clostridia comprised 91e98% of the phylum Firmicutes across
6 runs (12 digesters). Within phylum Bacteroidetes, unclassified
Bacteroideteswas a significant component (p < 0.001) inmesophilic
digesters. In addition, the fractions of Petrimonas in all 6 runs were
similar (5e8%), but total amount of Bacteroides in the AD treat-
ments was significantly lower than that in original dairy manure.
Phylum Bacteroidetes as one of the major bacterial groups in AD
include several strains such as Flavobacterium johnsoniae, Spor-
ocytophaga myxococcoides, and Cytophaga sp. that have been
repeatedly reported as degraders of structural carbohydrates of
plants [39e41]. A recent study on bacterial community in anaerobic
digesters [13] also showed that unclassified Bacteroidetes was one
of dominant taxa in lignocellulose-rich co-digestion systems. Be-
sides cellulose/hemicellulose degradation, it has also been reported
that many members of Bacteroidetes are proteolytic bacteria which
can degrade protein and convert amino acids to acetate [43,44].
Class Clostridia was another major bacterial group in anaerobic
digestion. As saprophytic bacteria, they commonly show high
cellulolytic activity as well as capability of degrading volatile fatty
acids such as butyrate and its analog compounds [43,45]. Moreover,
some strains of Clostridia can also utilize cellobiose and glucose
generated from carbohydrate degradation to produce proton and
hydrogen gas.
Chlorflexi, Synergistetes, Spirochaetes and Thermotogae are other
phyla that have been detected in the digesters. It has been reported
that Chloroflexi have potential to treat wastes in anaerobic envi-
ronment, such as thriving in naturally anaerobic dechlorination
[46], wastewater treatment processes [47], and degrading carbo-
hydrates [43,48]. Synergistetes are able to consume amino acids and
produce short chain fatty acids as well as sulphate for methano-
genic archaea and sulphate-reducing bacteria [49]. They prefer
mesophilic environment [50] as shown in this study. Spirochaetes
can break down cellulose and other plant polysaccharides, and
their optimum living temperature is also mesophilic [51]. Notice-
ably, Thermotogae only appeared in thermophilic digesters with
80:20 ratio that had the highest biogas productivity among all
treatments, which may be related to their capability of degrading
different complex-carbohydrates and producing acetic acid, carbon
dioxide and hydrogen gas [52].
Non-metric multidimentional scaling (NMDS) analysis was
performed based on the complete linkage clustering of 16S rRNA
gene sequences of all 12 digesters (6 treatments with duplicates)
(Fig. 5a). The differences of bacterial communities between two
reaction temperatures were significant (p ¼ 0.001), though, the
supplemental food waste did not have significant impact on the
community shift (p ¼ 0.148). The biogas productivities were
significantly different among treatments (p ¼ 0.012), and the di-
rection of its arrow indicates that digesters with 80:20 feed ratio
had the highest biogas productivity (Fig. 5a). Similarly, the arrow of
TS reduction shows an improved performance trend with elevated
temperature and no-supplemental food wastes, even though the
difference was not significant (p ¼ 0.453). Fitting the dominant
bacetrial taxa to the community distances reveals that phyla Bac-
teroidetes (p < 0.001), Synergistetes (p ¼ 0.038) and Spirochaetes
(p ¼ 0.028) preferred mesophilic AD condition, while phyla Chlor-
oflexi (p < 0.001), Thermotogae (p ¼ 0.019) and Firmicutes
(p ¼ 0.004) tended to acccumulate more at thermophilic condition
(50 C). In addition, Firmicutes (p ¼ 0.035) preferred the increased
Fig. 3. Dendrograms and heat map of the microbial community, MI1-12 are the sample IDs for different digestion conditions that are described in Table 3. A. Dendrogram and heat
map of bacterial community (based on the most common genera from 454 pyrosequencing). B. Dendrogram and heat map of archaeal community (based on T-RFLP results).
90 R. Chen et al. / Biomass and Bioenergy 85 (2016) 84e93
Fig. 4. Abundance of bacterial and archaeal communities. A. Assembly of dominant
bacteria (wide columns indicate dominant bacterial phyla and thin columns indicate
dominant bacterial classes). B. Distribution of dominant archaea under different cul-
ture conditions (based on T-RFLP results). C. Main archaea from the digestions under
different temperatures (based on clone library).amount of supplemental food waste, while Bacteroidetes
(p ¼ 0.003) had higher abundance in 100% dairy manure digesters.
Although both phyla Firmicutes (especially class Clostridia) and
Bacteroidetes were reported to be able to degrade crystalline fiber
into organic acids [13,53,54], Sundberg et al. [55] reported that
Bacteroidetes were more susceptible to the environmental change
caused by additional food waste, such as ammonia accumulation
and pH fluctuation. The correlation between AD performance and
bacterial community change also becomes obvious on this NMDS
diagram. Bacterial communities tended to adapt themselves into
different culture conditions and maximize their capability to
convert all available carbon sources (free sugar, starch, protein, fat,
hemicellulose, and easy-degradable cellulose) into biogas (Fig. 1
and Table 2). As a result, differences in compositional cellulose
(p ¼ 0.626), xylan (p ¼ 0.128) and lignin (p ¼ 0.113) of the solid
digestates among all six treatments were not significant, whichmeans the bacterial metabolism reached an equilibrium for each
treatment and relatively homogenized carbohydrate composition
in the solid digestate.
3.3.2. Anaerobic archaeal community
TheShannon's diversity indices of archaea (Harch) calculated from
the aligned and clustered (0.03% cutoff) sequences were relatively
low (Table 3), which indicated a low diversity within archaeal
communities of all treatments. The Pielou's evenness indices (Jarch)
of archaea also show that archaeal communities had less variation.
In Fig. 3b, the archaeal dendrogram demonstrates community sim-
ilarity across all treatments, and the heat map presents that several
archaeal OTUs had higher density within mesophilic digesters.
When temperature increased, archaea in the co-digestion systems
also shifted accordingly, though, the ones in 100%manure digesters
were relatively consistent regardless of temperature change. Sta-
tistically, reaction temperature (p ¼ 0.001) had significant impacts
on the change of archaeal community while the amount of supple-
mental foodwastedidnot (p¼0.441). The communityabundance of
archaea based on T-RFLP test (Fig. 4b) shows a relatively uniform
assembly across all treatments. However, they were all significantly
different from the archaea community in the original dairy manure.
Moreover, similar to bacteria, archaeal communities in mesophilic
digesters were more diverse than thermophilic digesters. Further
phylogenetic affiliations based on clone library illustrated four
genera of methanogenic archaea were detected in the digesters
(Fig. 4c). In details, the abundance ofMethanosarcina increased from
70% to 90% when reaction temperature was raised from 35 C to
50 C, while Methanobrevibacter reduced from 20% to non-
detectable. Results also demonstrate a higher hydrogentrophic
methanogen assembly (i.e. Methanobrevibacter, Methanobacterium
and Methanoculleus) in mesophilic digeseters. The abundance
change of Methanobrevibacter due to temperature was expected
since the optimum temperature for both genera was 37e38 C
[56,57].Methanocarsina is a genus that uses aceticlastic pathway to
generate methane [13]; therefore, its dominance in the clone li-
braries illustrates that aceticlastic reactions of methanogensis were
the dominant route to methane in all digesters.
The NMDS analysis of archaeal community (Fig. 5b) shows the
methane content in biogas was similar among all treatments
(p ¼ 0.117). The direction of the arrow illustrates that digesters at
35 C had relatively higher methane content. Similar observation
was reported previously [58e60]. The biogas productivities and TS
reduction were discussed in previous bacterial NMDS section.
Fitting the dominant archaeal genera to the community distances
demonstrated that increasing the reaction temperature had sig-
nificant impact on Methanosarcina (p ¼ 0.001) positively, but
negatively on Methanobrevibacter (p ¼ 0.031).
4. Conclusion
A variety of molecular and statistical approaches were applied
to examine the responses of microbial communities to the
changes of digestion conditions and their impacts on biogas
production and solid digestate quality. The biogas productivity
increased significantly with the increase of supplemental food
waste. Reaction temperature did not show any significant effect on
biogas production within the experimental conditions. There
were no significant differences on carbohydrate contents of solid
digestate among six treatments. The alikeness of methane content
among all six treatments and the analysis of archaea community
both proved that methanogens were lack of diversity and they
only varied with reaction temperature. Analysis of bacterial
community revealed that even though each treatment had its
distinct bacterial composition, the community changed their
R. Chen et al. / Biomass and Bioenergy 85 (2016) 84e93 91
Fig. 5. Nonmetric Multidimensional Scaling (NMDS) of bacterial and archaeal communities. The blue solid arrows demonstrate dominant phyla; the blue dashed arrows
demonstrate dominant classes or genera; the ellipses demonstrate the dispersion of each factor using standard error of the weighted average scores. A. NMDS diagram of bacteria. B.
NMDS diagram of archaea. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)configuration to adapt the environment, enhanced the utilization
of available carbon for biogas production, and homogenized car-
bohydrate components in the solid digestate. In-depth studies onthe AD function of homogenizing solid digestate are urgently
needed in order to develop an AD-based pretreatment method for
lignocellulosic biorefining of biofuel and chemical production.
92 R. Chen et al. / Biomass and Bioenergy 85 (2016) 84e93Acknowledgment
This research has been supported by the U.S. Department of
StateWest Hemisphere Affairs (S-LMAQM-11-GR-075). The authors
thank the Research Technology Support Facility of Michigan State
University for their help on gene sequencing.Appendix A. Supplementary data
Supplementary data related to this article can be found at http://
dx.doi.org/10.1016/j.biombioe.2015.11.028.References
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