Consistent 1,3-propanediol Production From Glycerol In Mixed ...

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Moscoviz et al. Biotechnol Biofuels (2016) 9:32
DOI 10.1186/s13068-016-0447-8
Consistent 1,3-propanediol production
from glycerol in mixed culture fermentation
over a wide range of pH
Roman Moscoviz, Eric Trably* and Nicolas Bernet
Background: Glycerol is currently an over-produced chemical that can be used as substrate for the production of
high value products such as 1,3-propanediol (1,3-PDO) in fermentation processes. The aim of this study was to investigate the effect of initial pH on a batch mixed culture fermentation of glycerol, considering both the bacterial community composition and the fermentation patterns.
Results: For pH values between 5 and 9, 1,3-PDO production yields ranged from 0.52 ± 0.01 to 0.64 ± 0.00
glycerol, with the highest values obtained at pH 7 and 8. An Enterobacteriaceae member closely related
to Citrobacter freundii was strongly enriched at all pH values. Within the less dominant bacterial species, two different
microbial community structures were found, one at acid pH values and another at neutral to basic pH values.
Conclusions: 1,3-PDO production was improved at pH values over 7. It was anti-correlated with lactate and ethanol
production but positively correlated with acetate production. No direct correlation between 1,3-PDO production and
a specific family of bacteria was found, suggesting functional redundancies in the microbial community. However,
1,3-PDO production yield remained high over the range of pH studied and was comparable to the best obtained in
the same conditions in the literature.
Keywords: 1,3-PDO, Metabolic patterns, Microbial consortia, Dark fermentation, Biodiesel
© 2016 Moscoviz et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License
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In order to reduce their fossil fuel dependency, several
countries have favored the production of biofuels such
as bioethanol or biodiesel. The European Union voted
in 2009 a resolution to raise the share of EU energy consumption produced from renewable resources to 20  %,
while reaching a 10  % share of renewable energy in the
transport sector. Biodiesel is currently produced from
transesterification of animal or vegetal oils. However,
approximately 100  kg of glycerol are co-produced per
ton of biodiesel produced [1]. This has led to an increase
in world glycerol production over the last decade. This
production reached about 3 million tons in 2011 and
4.7 million tons are expected to be produced in 2020 [2].
Therefore, it is a major issue to find a recycling solution
for this glycerol to make the biodiesel production more
Glycerol can be used as an inexpensive carbon substrate
for fermentation to produce many economically interesting chemicals including 1,3-propanediol (1,3-PDO).
1,3-PDO is used for the production of solvents, cleaners, adhesives, resins, and cosmetics. It can also be used
as a monomer for the production of polytrimethylene
terephthalate (PTT) further used in textile industry [3].
Many micro-organisms from the Enterobacteriaceae and
Clostridiaceae families are known as natural producers
of 1,3-PDO from glycerol. So far, most studies about 1,3PDO production from glycerol fermentation have focused
on the use of pure cultures such as Clostridium butyricum
[4] or Klebsiella pneumoniae [5]. High yields, productivities, and final 1,3-PDO concentrations have been achieved
with pure cultures which require sterile conditions and
the use of yeast or meat extract in the culture medium.
Open Access
Biotechnology for Biofuels
INRA, UR0050, Laboratoire de Biotechnologie de L’Environnement (LBE),
Avenue des étangs, 11100 Narbonne, France
Page 2 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
To reduce the production costs, only few articles have
reported the use of mixed cultures to convert crude glycerol from biodiesel production into 1,3-PDO under nonsterile conditions. Dietz et al. [6] successfully used mixed
cultures from municipal wastewater treatment plant and
reached yields between 0.56 and 0.76 mol1,3-PDO mol
with a minimal culture medium containing crude glycerol. These production yields were slightly higher than the
theoretical maximum yield of 0.72 mol1,3-PDO mol
[6] because of the impurities contained in crude glycerol
that could be used as additional substrates. Selembo et al.
[7] and Liu et al. [8] achieved 1,3-PDO production yields
close to the theoretical maximum (resp. 0.69 and 0.65
mol1,3-PDO mol
glycerol) when using mixed culture on glycerol fermentation.
Previous reported results using mixed cultures were
obtained in different experimental conditions and, in
particular, with pH values ranging from 5.5 to 8 and with
different sources of glycerol [6–10], making difficult to
outline the effects of pH. As reported by Samul et al. [11],
the effects of crude glycerol impurities on the fermentation patterns can substantially vary, depending on their
composition and the source of micro-organisms. The aim
of this work was to investigate the effect of initial pH on
batch production of 1,3-PDO under non-sterile conditions using a mixed culture as inoculum. Hence a minimal culture medium containing only pure glycerol with
no additives such as yeast extract was used in order to
reduce the sources of variability other than pH.
The microbial inoculum used in this work was a mixed
culture issued from a long-term continuous dark fermentation lab-scale reactor operated at pH 6.5 under microaerobic conditions for the production of H2 from glycerol
[12]. It was stored at 4 °C for 1 month before use.
Fermentation medium
The composition of the fermentation medium (per
liter of water) was modified from Dietz et  al.’s as follows: 1.66  g glycerol, 1  g NH4Cl, and 0.5  g NaCl for
pH-buffered experiments or 23.50  g glycerol, 2.5  g
NH4Cl and 1.0  g NaCl for pH-regulated experiments
(Sigma-Aldrich,  ≥99  %). In all experiments, 20  mL of
a trace element solution (1.5  g/L nitrilotriacetic acid;
3.0  g/L MgSO4·7H2O; 0.50  g/L MnSO4·H2O; 1.0  g/L
NaCl; 0.10  g/L FeSO4·7H2O; 0.18  g/L CoSO4·7H2O;
0.10  g/L CaCl2·2H2O; 0.18  g/L ZnSO4·7H2O; 0.01  g/L
CuSO4·5H2O; 0.02  g/L KAl(SO4)2·12H2O; 0.01  g/L
H3BO3; 0.01  g/L Na2MoO4·2H2O; 0.03  g/L NiCl2·6H2O;
0.30  mg/L Na2SeO3·5H2O; 0.40  mg/L Na2WO4·2H2O)
and 150 mM phosphate buffer were added.
pH‑buffered fermentation set‑up
Batch experiments were performed in triplicates in
glass bottles containing 200 mL of solution and around
300  mL of headspace. Bottles were sealed with butyl
rubber septa and aluminum caps. Initial biomass was
obtained after centrifugation of 33  mL of the inoculum (volatile solids =  0.40 ±  0.01  %total mass) at 12,000g
for 15  min. The pellet was then suspended in the culture medium. Anoxic conditions were assured just after
inoculation by flushing the media with high-purity N2
(>99.995  %) for at least 30  min. The temperature was
controlled at 37 °C. Initial pH was adjusted at 4, 5, 6, 7, 8,
9, or 10 using 150 mM phosphate buffer and hydrochloric acid. Final pH values were, respectively, 3.9  ±  0.2,
4.2 ± 0.2, 5.7 ± 0.2, 6.9 ± 0.1, 7.7 ± 0.2, 8.0 ± 0.2, and
9.9 ± 0.2.
pH‑regulated fermentation set‑up
Glycerol fermentations under pH regulation were conducted in four replicates in glass reactors containing 1 L
of solution and about 500 mL of headspace. The temperature was controlled at 37 °C and the pH was regulated at
7.0 by adding 2  M NaOH (pH probe InPro 4260i, Mettler Toledo). Bottles containing pH 7 from the pH-buffered experiments were used as inoculum after storage at
4 °C. Initial biomass was obtained after centrifugation of
100 mL of the inoculum at 12,000g for 15 min. The pellet
was then suspended in the culture medium. Anaerobic
conditions were assured just after inoculation by flushing the media with high-purity N2 (>99.995 %) for at least
30 min.
Analytical methods
Concentrations of glucose, glycerol, 1,3-PDO, and
organic acids were measured by HPLC with a refractive
index detector (Waters R410). Samples were first centrifuged at 12,000g for 15 min and then supernatants were
filtered with 0.2  µm syringe filters. HPLC analysis was
performed at a flow rate of 0.4  mL/min on an Aminex
HPX-87H, 300  ×  7.8  mm (Bio-Rad) column at a temperature of 35 °C. H2SO4, 4 mM was used as the mobile
phase. Biogas composition was determined using a gas
chromatograph (Clarus 580, Perkin Elmer) equipped
with a thermal conductivity detector. The columns used
were a RtQbond column (for H2, O2, N2, and CH4) and
a RtMolsieve column (for CO2), and the gas vector was
argon at a pressure of 3.5 bar.
The COD balances were established based on the number of electrons per mol of each fermentation product
and for microbial biomass, assuming an elemental composition of C4H7O2N [13]. Biomass was estimated from
the metabolites produced considering a YX/ATP of 10.5 g/
mol [14].
Page 3 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
Microbial community analysis
DNA was extracted with the QIAamp fast DNA stool
mini kit in accordance with the manufacturer’s instructions (Qiagen, Hilden, Germany). Extractions were confirmed using Infinite 200 PRO NanoQuant (Tecan Group
Ltd., Männedorf, Switzerland). The V4 and V5 regions
of the 16S rRNA genes were amplified using the primers 515F (5′-GTGYCAGCMGCCGCGGTA-3′) and 928R
(5′-CCCCGYCAATTCMTTTRAGT-3′), which captures
most of the bacterial and archaeal diversity [15]. Adapters
were added for multiplexing samples during the second
amplification step of the sequencing. The PCR mixtures
(50  µl) contained 0.5 U of Pfu Turbo DNA polymerase
(Stratagene) with its corresponding buffer, 200  mM of
each dNTP, 0.5 mM of each primer, and 10 ng of genomic
DNA. Reactions were performed in a Mastercycler thermal
cycler (Eppendorf) as follows: 94  °C for 2  min, followed
by 35 cycles of 94 °C for 1 min, 65 °C for 1 min, and 72 °C
for 1 min, with a final extension at 72  °C for 10 min. The
amount and size of PCR products were determined using
a Bioanalyzer 2100 (Agilent). A capillary electrophoresis single-strand conformation polymorphism (CE-SSCP)
method was used for PCR product’s diversity characterization. Samples were heat-denatured at 95 °C for 5 min and
re-cooled directly in ice for 5 min. CE-SSCP electrophoresis was performed in an ABI Prism 3130 genetic analyzer
(Applied Biosystems) in 50  cm capillary tubes filled with
10  % glycerol, conformation analysis polymer and corresponding buffer (Applied Biosystems). Samples were eluted
at 12 kV and 32 °C for 30 min, as described elsewhere [16].
CE-SSCP profiles were aligned with an internal standard
(ROX) to consider the inter-sample electrophoretic variability. CE-SSCP profiles were normalized using the StatFingerprints library [17] in R software version 2.9.2 (R.
Development Core Team 2010). The community composition was also evaluated using the MiSeq v3 chemistry (Illumina) with 2 × 300 bp paired-end reads at the GenoToul
platform ( Sequences were retrieved after
demultiplexing, cleaning, and affiliating sequences using
mothur [18]. Sequences have been submitted to GenBank
with accession No. KT287117–KT288056.
Quantitative PCR (qPCR)
PCRs were prepared using 96-well real-time PCR plates
(Eppendorf, Hamburg, Germany) and Mastercycler ep
gradient S (Eppendorf, Hamburg, Germany). Then, 6.5 μl
of Express qPCR supermix with premixed ROX (Invitrogen, France), 2 μl of DNA extract with three appropriate
dilutions, 100 nM forward primer F338-354 (5′-ACTCC
TACGG GAGGC AG-3′), 250 nM reverse primers R805785 (5′-GACTA CCAGG GTATC TAATC C-3′), 50 nM
TaqMan probe, and water were added to obtain a final
volume of 12.5 μl for all analyses.
An initial incubation of 2  min at 95  °C and 40 cycles
of denaturation (95 °C, 7 s; 60 °C, 25 s) were performed.
One standard curve was generated from each assay by
using tenfold dilutions in sterilized water (Aguettant
Laboratory, Lyon, France) of a target plasmid (Eurofins
Genomics, Germany). The initial DNA concentrations
were quantified using the Infinite 200 PRO NanoQuant
(Tecan, France). The average number of bacterial cells
was estimated by dividing the average number of 16S
rRNA gene copies per cell by a factor 4.1 [19].
Theoretical yield calculations
Metabolic pathways of glycerol fermentation were
assumed to be similar as in [20]. In particular, the biochemical routes leading to lactate, acetate, and ethanol
without formate production were written as follows:
The conversion of formate into hydrogen was assumed
as follows:
The elemental constitution of biomass was assumed to
be C4H7O2N with a biomass production yield of 10.5 g/
molATP [14], leading to the following equation:
Pearson correlation matrix
A Pearson correlation matrix was calculated from metabolite profiles after 3 days of fermentation (n =  15) and
the bacterial community composition obtained after
sequencing (n = 5, only one per triplicate). The correlation and significance calculations were made with the R
3.1.3 software (R Development Core Team 2010) and the
function “rcorr” of the package Hmisc. The hierarchical
clustering was made with the function “corrplot” of the
package corrplot using the centroid method.
Principal component analysis (PCA)
In order to analyze and compare the microbial consortia,
a principal component analysis (PCA) was performed on
the microbial community compositions obtained from
Glycerol+ ADP+ Pi +NAD
→ Lactate+ ATP+H2O+NADH2
Glycerol+ 2(ADP+ Pi)+ 3NAD
→ Acetate+ CO2 + 2ATP+H2O+ 3NADH2
Glycerol+ ADP+ Pi +NAD
→ Ethanol+ CO2 + ATP+H2O+NADH2
Glycerol + NADH2
→ 1, 3-propanediol +NAD+ + H2O.
Formate+H2O → HCO

3 + H2
4Glycerol+ 3NH3 + 30ATP+ 24H2O+ 4NAD
→ 3 C4H7O2N+ 4NADH2 + 30(ADP+ Pi)
Page 4 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
CE–SSCP with the R 2.12 software (R Development Core
Team 2010), the vegan 2.12.2 package.
Effect of pH on fermentation products
To evaluate the effect of initial pH on glycerol fermentation by a mixed culture, a range of initial pH values
between 4 and 10 was investigated in batch reactors. A low
initial concentration of 1.66 g of glycerol was used to avoid
a pH drop during fermentation. COD mass balances are
shown in Fig. 1 (more details on COD mass balances are
presented in Additional file 1). COD mass balance closed
between 93 and 102 %, indicating that no major metabolic
by-product was missed during the batch fermentation.
After 3 days of fermentation, glycerol was depleted in most
of the reactors except those running at the extreme pH 4,
5, and 10 with 95.4, 8.1, and 93.0 % of the initial glycerol
remaining, respectively. It was assumed that no fermentation occurred at pH 4 and 10. For all other pH values,
the main metabolite produced was 1,3-PDO (60–74 %total
COD) with acetate as major by-product (11–17 %total COD).
The 1,3-PDO production yields ranged from 0.52 ±  0.01
to 0.64 ± 0.00 mol1,3-PDO mol−1glycerol. The best values were
obtained at pH 7 and 8 and corresponded to 90 % of the
maximum theoretical yield of 0.72 mol1,3-PDO mol
[6] with a final concentration of 0.86 ± 0.00 g/L. Ethanol
was only produced for pH values below 6 (6–9 %total COD),
while acetate production decreased. At pH values over 7,
formate production increased from 0 to 9  %total COD. H2
was only detected for pH values below 7 and represented
less than 1 % of the total COD. Methane was not detected
in any condition, which was not surprising since the initial inoculum originated from an output of a continuous
reactor in which methanogenesis did not occur (low HRT).
Although basic pH around 7–8 may favor the emergence
of methanogens in long-term operation of the reactor, several studies reported that high 1,3-PDO final titers were
obtained at pH between 5 and 6 [21], and pH 8 [7] without
methane production.
Comparison with theoretical yields
Metabolic pathways of glycerol fermentation are well
known and have been described in many studies. A
simplified representation is provided in Fig.  2. In order
to find the global reactions leading to (i) maximal 1,3PDO production (ii) maximal biomass growth, and (iii)
minimal biomass growth, the following redox and ATP
balanced reactions were calculated by aggregating the
equations of glycerol metabolism as provided in the
material and method section and presented in Fig. 3:
68 Glycerol+ 3 NH3 → 3 C4H7O2N+ 15 Acetate
+ 15 CO2 + 49 1, 3-PDO+ 40 H2O
53 Glycerol+ 3 NH3 → 3 C4H7O2N+ 15 Acetate
+ 15 Formate+ 34 1, 3-PDO+ 25 H2O
38 Glycerol+ 3 NH3 → 3 C4H7O2N+ 30 Ethanol
+ 30 Formate+ 4 1, 3-PDO+ 10 H2O
68 Glycerol+ 3 NH3 → 3 C4H7O2N+ 30 Lactate
+ 34 1, 3-PDO+ 40 H2O
Fig. 1 COD balances calculated from the metabolites measured after 3 days of fermentation in triplicate experiments in pH-buffered reactors.
Results are normalized on initial COD. The biomass was estimated from the ATP production associated to the different metabolites production
Page 5 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
The maximal theoretical production yield of 1,3-PDO
(0.72 mol/mol) could be obtained when only acetate was
produced, according to Eq.  (1). The theoretical maximal growth was reached when ethanol was produced
together with formate as in the Eq. (3), leading to a minimal 1,3-PDO yield of 0.11 mol/mol. The theoretical biomass growth was minimal if only lactate and acetate were
produced (Eqs.  (1) and (4)) but the production of lactate had a negative impact on 1,3-PDO production. The
production of formate together with acetate had also a
negative impact on 1,3-PDO (Eq.  (2)). These theoretical
values have been compared to the actual values obtained
at different pH values and are shown in Table  1. The
best 1,3-PDO production values were obtained at pH 7
and 8 and were close to those obtained with Eq. (4) (i.e.,
YAcetate/S = 0.28 mol/mol and YPDO/S = 0.64 mol/mol) but
with much less formate or hydrogen produced, maybe
due to measurement errors in hydrogen production.
Microbial communities and growth
Biomass was estimated after 3 days of fermentation from
qPCR on total bacterial DNA. The low initial biomass
concentration of 5.9 ± 1.7 × 105 bact/mL after inoculation could explain the long lag phase observed at all pH
values. The final biomass concentration ranged between
108 and 109 bact/mL in all reactors in which glycerol fermentation occurred, except for the reactors running at
pH 9 (7.4 ±  1.3 × 106 bact/mL). This value obtained at
pH 9 is very low compared to the biomass estimated with
ATP production. This could be due to ATP dissipation for
maintaining intracellular pH at 7. Therefore, it was clear
that bacterial growth was strongly inhibited at extreme
pH values lower than 5 and above 8.
To observe the effect of pH on microbial communities, MiSeq sequencing was performed on the inoculum
and on samples after 3 days of fermentation (Fig. 4). The
inoculum was mainly composed of bacteria from the
Clostridiaceae and Enterococcaceae families (resp. 50
and 18 % of 82,243 sequences). Two OTUs were dominant, one in each family, and represented 46 % and 18 %
of the total bacterial community. Nucleotide sequence
analyses of their 16S rRNA genes revealed resp. 99 and
100  % of sequence homology with Clostridium intestinale and Enterococcus cecorum. C. intestinale is known
to be an aerotolerant species, able to grow on glycerol
and to produce H2 [22–24], which is consistent with
the inoculum origin. After 3 days of fermentation, the
bacterial community observed at pH 9 was very close
Fig. 2 Simplified catabolic pathways of glycerol fermentation. Fdox and Fdred stand for the oxidized and reduced form of ferredoxin, respectively.
Adapted from [20]
Page 6 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
to the inoculum, probably because there was practically no bacterial growth. For every other pH condition,
an Enterobacteriaceae species was enriched whose 16S
rRNA gene had 100 % of sequence homology with Citrobacter freundii, a species studied for 1,3-PDO production from glycerol [25, 26]. A Brucellaceae species which
had 100  % similarity with Ochrobactrum anthropi was
also favored at pH 5.
Correlations between microbial community
and fermentation patterns
In order to highlight correlations between the composition of microbial communities and fermentation
patterns, a Pearson correlation matrix was calculated
with the bacterial families and metabolites produced as
variables (Fig.  5). 1,3-PDO was found to be positively
correlated to acetate (r = 0.64, p ≤ 0.01) and negatively
correlated to lactate (r  =  –0.78, p  ≤  0.001), ethanol
(r = –0.65, p ≤ 0.01), and hydrogen (r = –0.60, p ≤ 0.05).
It was also negatively correlated to the emergence of bacteria from the Pseudomonadaceae (r = –0.85, p ≤ 0.05),
Ruminococcaceae (r  =  –0.92, p  ≤  0.05), and Bacteroidaceae (r  =  –0.96, p  ≤  0.01) families. A hierarchical
cluster analysis on the Pearson correlation matrix also
highlighted two groups of bacteria. The first one was
composed of bacteria from Veillonellaceae, Clostridiaceae, Lachnospiraceae, and Enterococcaceae families and
was linked with formate production. The second one was
composed of bacteria from Pseudomonadaceae, Ruminococcaceae, Bacteroidaceae, and Brucellaceae and linked
with ethanol and hydrogen production. There was a high
positive correlation between ethanol and the presence of
Fig. 3 Carbon flux trees according to theoretical pathways. a Maximal 1,3-propanediol production. b Acetate and Formate pathways. c Maximal
growth yield. d Minimal growth yield. The values in percentage represent the proportion of initial carbon that is found in the final products
Table 1 Comparison of  the experimental yields obtained in  this study with  theoretical yields calculated considering
anabolism and catabolism
a The biomass yield was calculated assuming an elemental composition of C4H7O2N [14] and that all the ATP produced was used for biomass production
b The ATP yield was calculated from the metabolites measured after 3 day of fermentation: YATP/Acetate = 2; YATP/Ethanol = 1; YATP/Lactate = 1; YATP/PDO = 0
Theoretical values Experimental values
growth yield
and formate
pH 5 pH 6 pH 7 pH 8 pH 9
YX/S (g/mol)
a 4.45 4.45 7.97 5.72 5.39 ± 0.25 6.18 ± 0.62 5.90 ± 0.14 6.15 ± 0.41 5.87 ± 0.80
YATP/S (mol/mol)
b 0.44 0.44 0.79 0.57 0.51 ± 0.02 0.59 ± 0.06 0.56 ± 0.01 0.59 ± 0.04 0.56 ± 0.07
YPDO/S (mol/mol) 0.72 0.50 0.11 0.64 0.61 ± 0.04 0.52 ± 0.01 0.64 ± 0.00 0.63 ± 0.01 0.58 ± 0.01
YAcetate/S (mol/mol) 0.22 0 0 0.28 0.21 ± 0.02 0.21 ± 0.01 0.27 ± 0.01 0.29 ± 0.02 0.25 ± 0.04
YEthanol/S (mol/mol) 0 0 0.79 0 0.07 ± 0.05 0.11 ± 0.07 0 0 0
YLactate/S (mol/mol) 0 0.44 0 0 0 0.06 ± 0.01 0.01 ± 0.01 0 0.07 ± 0.00
Y(Formate+H2)/S (mol/mol) 0 0 0.79 0.28 0.06 ± 0.01 0.07 ± 0.00 0.01 ± 0.01 0.17 ± 0.01 0.26 ± 0.02
Page 7 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
Brucellaceae bacteria (r =  0.99, p ≤  0.001), and hydrogen production and the presence of Pseudomonadaceae
bacteria (r = 0.93, p ≤ 0.05). Lactate was not found to be
correlated to a specific group of bacteria.
pH‑regulated fermentations
To see whether the performances obtained with a low
substrate concentration were still valid at higher substrate load, assays were carried out in batch mode in
pH-regulated reactors at an initial glycerol concentration of 23.5 g/L. A pH of 7.0 was selected to regulate the
fermenters since it was the condition that led to the best
1,3-PDO yield during the pH-buffered assays. The fermentation started after a 19  h lag phase, probably due
to the inoculum storage and all the substrates were then
depleted within 11.5 h. The COD mass balance was close
at 95 % with 1,3-PDO as the major product (61 %total COD)
(more details on metabolites distribution are presented
in Additional file  2). The 1,3-PDO yield and productivity were, respectively, 0.53  ±  0.02 mol1,3-PDO mol−1glycerol
and 0.89  ±  0.02  g/L  h, and a final concentration of
10.3  ±  0.3  g/L was achieved. Major by-products were
ethanol (11  %total COD), acetate (7  %total COD), and lactate
(7  %total COD). Ethanol was mainly produced within the
first 4 hours of fermentation. Formate and succinate were
also produced in small quantities (resp. 2  %total COD and
1 %total COD).
Effect of pH on microbial populations
In order to compare the bacterial populations obtained at
the end of the fermentation with the different pH values,
a PCA was performed (Fig. 6). Most of the total variance
(67.1 %) was explained by the principal compound 1 (PC
1) that was able to discriminate samples between neutral
pH from 6 to 8 and extreme pH values of 5 and 9. This
PC was supported by the emergence of the Enterobacteriaceae species and the decrease of the Clostridiaceae
species that were predominant in the inoculum. Surprisingly, these two predominant families were found to have
non-significant and low correlations with the metabolites
produced suggesting that the differences found in the fermentation patterns were more related to less dominant
species. It was shown that sub-dominant species in mixed
culture fermentations can have significant effect on fermentation patterns and therefore have to be considered
even at low abundance [27]. The PC 2 (16.4  % of total
variance) separated the bacterial population observed
at low pH (≤6) and neutral to basic pH (≥7). This PC
separated the two groups highlighted by the hierarchical clustering of the correlation matrix. The growth of
Pseudomonadaceae, Ruminococcaceae, Bacteroidaceae,
and Brucellaceae species together with ethanol and
H2 production was then found to occur at low pH (<6).
On the other hand, the growth of the species from the
Fig. 4 Bacterial population distribution within the taxonomic families of the inoculum and after 3 days of fermentation in pH-buffered reactors
at different pH values. This distribution is based on 16S rRNA genes identification retrieved from MiSeq sequencing. Other stand for the families
containing less than 2 % of the total bacterial populations
Page 8 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
Enterococcaceae, Clostridiaceae, Lachnospiraceae, and
Veillonellaceae families, associated to formate production, was favored at high pH (≥7). The high pH microbial
community was more favorable for 1,3-PDO than the one
found for pH values below 6 in which many micro-organisms were strongly anti-correlated with 1,3-PDO production. However, no significant and direct link between a
specific bacterial family and a better 1,3-PDO has been
found. It was also found that lactate was neither correlated to a specific bacterial family nor to pH conditions.
pH‑induced H2/formate shift
It is usual to observe H2 production from glycerol or glucose fermentation depending strongly on the initial pH.
The shift from formate to H2 production observed in this
study when pH decreased was previously described by
Temudo et al. [28] who used a mixed culture for glucose
fermentation. It was observed during this study that the
hydrogen/formate molar ratio decreased concomitantly
with the increase initial pH values. Considering the following equation and its Gibbs free energy [28]:
The observed shift from formate to H2 could be
explained by thermodynamic considerations. This reaction is very close to the thermodynamic equilibrium and
is catalyzed by the formate hydrogen lyase complex that
is reversible. As the pKa value of carbonate is 6.37 (at
25  °C), a pH increase above this value would favor carbonate accumulation in the bulk and therefore inhibit
formate splitting into carbonate and H2. Considering that
neither methanogenesis nor acetogenesis is occurring, a
low H2 production could mean that formate is produced
and/or NADH2 is formed from ferredoxin (see Fig.  2).
However, it is very likely that hydrogen was underestimated during this study when comparing the metabolic
Formate+H2O → HCO

3 +H2 G
= 1.3 kJ/mol
Fig. 5 Pearson correlation matrix calculated from metabolite production profiles and sequencing results after 3 days of fermentation. The hatched
squares correspond to negative correlations and the full squares to positive correlations. The black outlines are the result of hierarchical clustering for
n = 5 groups. p-values: ** ≤0.001; *≤0.01; •≤0.05
Page 9 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
profiles obtained for pH values between 5 and 7 and theoretical values (see Table 1).
Ethanol production
From a theoretical analysis of all the possible glycerol fermentation pathways, it is clear that the acetate pathway
leads to the highest 1,3-PDO production. In this study, a
shift in acetyl-CoA derived product was observed from
acetate to ethanol at pH values below 6 with an expected
decrease of the 1,3-PDO production yields. From a thermodynamic point of view, Rodriguez et  al. [29] showed
in their metabolic-based model that for pH values below
5.6, ethanol is the metabolite that is generating the maximum energy for growth. Their calculation considers the
energetic cost of acid transportation through the cellular membrane. At pH lower than 5.6, the energetic cost
becomes more important than the energy supplied to the
metabolism by the extra ATP produced during acetate
production. Therefore, ethanol is energetically favored
over acetate at low pH values. However, the ethanol shift
cannot be only explained by energetic reasons and seems
to be also strain-dependent. Klebsiella variicola has been
reported to produce ethanol from glycerol with high
yields at pH values ranging from 8 to 9 [30]. Temudo et al.
[9] also showed ethanol production from glycerol at pH
8 from a mixed culture dominated by an Enterobacteria
species close to Klebsiella oxytoca. In addition, Clostridium acetobutylicum, a bacterium used for acetone–
butanol–ethanol production, is known for switching its
metabolism from acidogenesis to solventogenesis when
external pH drops under 5 [31]. In this study, ethanol
production was highly correlated with Brucellaceae species and was only found when pH was below 6.
Towards high 1,3‑PDO concentrations
Initial high 1,3-PDO production yields were obtained
at low glycerol concentration with a low impact of the
pH. To determine whether such performances could be
reached at higher substrate concentration, an assay was
performed in pH-regulated batch reactors with an initial
glycerol concentration of 23.5 g/L at pH 7. In this experiment, a 1,3-PDO yield of 0.53 ± 0.02 mol1,3-PDO mol−1glycerol
was obtained, which is slightly lower but still consistent
with the one obtained with the reactors buffered at pH
7 and with an initial substrate concentration of 1.66 g/L
(0.64  ±  0.00 mol1,3-PDO mol−1glycerol). Nevertheless, this
yield is still high considering that a minimal medium with
no vitamins or yeast extract was used. It is consistent with
the results obtained by Dietz et al. in similar conditions
with crude glycerol (yield of  ~0.60 mol1,3-PDO mol
and productivity of ~1 g/L h) and by Kanjilal et al. with
pure glycerol (0.52 mol1,3-PDO mol
glycerol) [6, 10]. These
different results tend to show that mixed culture can be
a viable option for 1,3-PDO production from pure or
crude glycerol, even though two major challenges remain
to sustain an efficient production of high concentration
of 1,3-PDO. The first one is the use of crude glycerol
issued from biodiesel production, which contains various
impurities such as methanol and KOH at high concentrations [8, 10, 11, 32]. These impurities may have positive
effects through the addition of carbon sources and nutriments that can be used by the micro-organisms and thus
increase the 1,3-PDO production [6, 10, 11]. But methanol that is always present in these impurities can also
inhibit the microbial growth, even at low concentration,
and therefore decrease 1,3-PDO productivity and glycerol consumption [8, 32]. As crude glycerol composition
may vary from a source to another, it is rather difficult to
extend our conclusions when considering the combined
effect of the impurities on glycerol fermentation. For that
reason, mixed culture fermentation has the advantage to
be more robust to environmental changes. The second
challenge is to increase the final 1,3-PDO concentration, while keeping high productivities and production
yields. A substrate inhibition has been reported at initial
concentration higher than 70 g/L of crude glycerol for C.
butyricum [33, 34]. This inhibition was also observed by
Dietz et al. when mixed cultures were used [6]. Therefore,
fed-batch process seems to be the best way to increase
final 1,3-PDO concentration, while avoiding substrate
inhibition. Using a fed-batch reactor with a continuous
feed, mixed cultures and minimal medium, Dietz et  al.
obtained a final concentration of 70 g/L of 1,3-PDO with
Fig. 6 PCA performed on the composition of bacterial communities
obtained with CE-SSCP after 3 days of fermentation in pH-buffered
Page 10 of 11Moscoviz et al. Biotechnol Biofuels (2016) 9:32
a yield of 0.56 mol1,3-PDO mol
glycerol and a productivity of
2.60  g/L  h [6]. Another interesting process named electro-fermentation showed promising results by reaching a
final 1,3-PDO concentration of 42 g/L [35]. These results
are outstanding considering that non-sterile conditions
and minimal medium were used and are compared with
the best performances obtained with pure culture [25].
When considering the Pearson correlation matrix (Fig. 5)
and the PCA results (Fig. 6), it appeared in this study that
pH had a significant impact on both bacterial growth, the
composition of the bacterial community and metabolic
profiles. The predominant bacteria from Clostridiaceae
and Enterobacteriaceae families could not explain alone
the changes in metabolic profiles. Within the less dominant species, two different communities were found, one
at acid pH values and another at neutral to basic pH values. The latter one was favorable to 1,3-PDO yield even
if no significant correlation between a specific bacterial
family of this community and a good 1,3-PDO yield was
found. It was likely that there were a functional redundancy within this community. From the theoretical analysis of the metabolic pathways of glycerol fermentation
(Table 1) and the correlation matrix (Fig. 5), it was clear
that 1,3-PDO was favored when produced together with
acetate, which was mostly the case in this study. Even if
strong changes occurred in the microbial community
structure over the pH range studied, high 1,3-PDO production yields were obtained and were comparable to the
best yield obtained in similar conditions (i.e., mixed culture, pure glycerin, and no additive such as yeast extract)
of 0.69 mol/mol [7].
1,3-PDO: 1,3-propanediol; ADP/ATP: adenosine di/triphosphate; HRT: hydraulic
retention time; NADH2/NAD
+: nicotinamide adenine dinucleotide reduced/
oxidized; PCA: principal component analysis; PTT: polytrimethylene terephthalate; qPCR: quantitative real-time polymerase chain reaction.
Authors’ contributions
RM designed the study and carried out the fermentation experiments, the
statistical analysis, and drafted the manuscript. ET designed and coordinated
Additional files
Additional file 1. COD mass balance of batch tests operated at variable
initial pH. Detailed COD mass balances of each batch test are presented
in this additional table. COD mass balances were calculated from the
metabolites composition measured after 3 days of fermentation (triplicate
Additional file 2. Metabolites distribution (expressed in COD equivalent)
measured after total substrate depletion in pH-controlled reactors (four
replicates). Detailed final COD distributions as assessed through metabolites production are presented in this Figure. Results are normalized by the
initial COD contained in the medium.
the study and helped to draft the manuscript. NB designed and coordinated
the study and helped to draft the manuscript. All authors read and approved
the final manuscript.
This work was supported by the French National Research Agency (BIORARE
Project: ANR-10-BTBR-02).
Competing interests
The authors declare that they have no competing interests.
Received: 2 November 2015 Accepted: 20 January 2016
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