bit25320-sm-0001-SupInfo-S1

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Multilevel correlations in the biological phosphorus removal process: from
bacterial enrichment to conductivity-based metabolic batch tests and
polyphosphatase assays
SUPPLEMENTARY MATERIAL
David G. Weissbrodt1,a,b, Julien Maillard1, Alessandro Brovelli2, Alexandre Chabrelie1,
Jonathan May1, Christof Holliger1,*
1
Ecole Polytechnique Fédérale de Lausanne, School for Architecture, Civil and
Environmental Engineering, Laboratory for Environmental Biotechnology, Switzerland
2
Ecole Polytechnique Fédérale de Lausanne, School for Architecture, Civil and
Environmental Engineering, Ecological Engineering Laboratory, Switzerland
*Corresponding author: Prof. Christof Holliger, EPFL ENAC IIE LBE, Station 6, CH-1015
Lausanne, Switzerland; Tel +41-21-6934724, Fax +41-21-6934722, e-mail:
christof.holliger@epfl.ch
a
Current address: ETH Zürich, Institute of Environmental Engineering, Chair of Process
Engineering in Urban Water Management, Zürich, Switzerland
b
Current address: Eawag – Swiss Federal Institute of Aquatic Science and Technology,
Department of Process Engineering, Dübendorf, Switzerland
1
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
Supplementary material 1
Table SM1.1 Optimal composition of nutritive media used for the cultivation of stable PAO- and GAOenrichments in the present study.
Compound
CAS no.
Molecular
formula
Molecular
weight
(g mol-1)
Concentrations
in influent wastewater
PAO-SBR
GAO-SBR
C-source medium1
Sodium acetate2
Sodium propionate2
Magnesium sulfate
Calcium chloride
127-09-3
137-40-6
7487-88-9
10043-52-4
C2H3O2Na·3H2O
C3H5O2Na
MgSO4·7H2O
CaCl2·2H2O
136.09
96.06
246.51
147.02
3.57 mmol L-1
0.37
0.10
6.25 mmol L-1
0.37
0.10
12125-02-9
7778-77-0
109-57-9
8013-01-2
91079-38-8
65072-00-6
-
NH4Cl
KH2PO4
C4H8N2S
n.a.
n.a.
n.a.
-
53.49
136.09
116.18
n.a.
n.a.
n.a.
-
1.43 mmol L-1
1.61
2.00 mg L-1
0.80
0.80
0.80
0.30 mL L-1
1.43 mmol L-1
0.07
2.00 mg L-1
0.30 mL L-1
N-source and P-source medium1
Ammonium chloride
Potassium dihydrogen phosphate3
Allyl-N-thiourea4
Yeast extract5
Peptone5
Casamino acids5
Trace element solution
Compound
CAS no.
Molecular
formula
Molecular
weight
Concentrations
in stock solution
(g mol-1)
(g per 5 L)
(mmol L-1)
372.25
287.59
197.92
270.30
205.92
249.71
237.96
61.83
166.00
50.00
0.60
0.60
7.50
0.30
0.15
0.75
0.75
0.90
26.86
0.42
0.61
5.55
0.29
0.12
0.63
2.43
1.08
Trace element stock solution1,6
Disodium EDTA
Zinc sulfate
Manganese chloride
Iron(III) chloride
Sodium molybdate
Copper(II) sulfate
Cobalt(II) chloride
Boric acid
Potassium iodide
139-33-3
7733-02-0
7773-01-5
7705-08-0
7631-95-0
7758-98-7
7646-79-9
11113-50-1
7681-11-0
C10H14N2O8Na2·2H2O
ZnSO4·7H2O
MnCl2·4H2O
FeCl3·6H2O
Na2MnO4·2H2O
CuSO4·5H2O
CoCl2·6H2O
H3BO3
KI
1
All solutions were prepared in demineralized water. The synthetic wastewater was prepared by 1:1 mixing of 2times concentrated C-source medium, and N-source and P-source medium.
2
The final concentrations of acetate and propionate in the influent corresponded to 12.5 C-mmolAc L-1 and 10.7
C-mmolPr L-1, respectively, and to 400 mgCOD L-1. Optimal SBR start-up was operated with stepwise increase of
the organic concentration. At steady state, the SBRs were thus fed with volumetric organic loading rates (OLR)
of 200 mgCODs cycle-1 LR-1.
3
At steady state, the COD/P ratio of the influent wastewaters amounted to 8 and 200 g COD gP-PO4-1, respectively.
4
Allyl-N-thiourea was added to inhibit nitrification.
5
Protein complements were added in the PAO-SBR to sustain the enrichment of Accumulibacter, according to
the media composition used by different authors (Hesselmann et al. 1999; Hollender et al. 2002; Lopez-Vazquez
et al. 2009; Lu et al. 2006; Marcelino et al. 2009; Schuler and Jenkins 2003; Smolders et al. 1994; Zeng et al.
2003). COD conversion factors: 1.4 gCOD gyeast extract-1, 1.4 gCOD gcasamino acids-1, 1.2 gCOD gpeptone-1.
6
The composition of the trace element solution was taken from Lopez-Vazquez et al. (2009).
2
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
Supplementary material 2
Table SM2.1 Stoichiometric and composition matrix formulation of the PAO and GAO processes occuring under anaerobic and standardized conditions (20°C, pH 7.0). The
main participating ionic species were integrated for modeling of electrical conductivity evolution in PHREEQC. The descriptions of PAO/GAO processes of Smolders et al.
(1995), Manga et al. (2001), Zeng et al. (2003), Siegrist et al. (2002), and Lopez-Vazquez et al. (2009) were adapted by integration of the main participating charged ions
according to Serralta et al. (2004), Seco et al. (2004), and Aguado et al. (2006). This matrix considers the conversion of soluble components and of intracellular storage
compounds (hereafter refered as to particulate components). Stoichiometric coefficients (υij) were calculated by sastisfying balances of theoretical oxygen demand (ThOD),
charge, and materials, and were expressed in moles as prerequisite for implementation in PHREEQC. Maintenance processes of PAO and GAO under anaerobic conditions
were specified in the matrix, but were not taken into consideration in the modelling investigations. Aguado et al. (2006) reported a model-based calibrated composition of
polyphosphate of (K0.28Mg0.36PO3)n instead of the traditionally used compositions (K0.34Mg0.33PO3)n.
i
1
2
3
4
5
6
7
8
9
10
11
12
Components
Soluble
in PHREEQC
Acetate
P
K
Mg
C
H
O
XGly
XPP
XPHB
XPHV
XPH2MV
C2H4O2
PO43-
K+
Mg2+
CO32-
H+
H2O
(C6H10O5)n
(K0.28Mg0.36PO3)n
(C4H6O2)n
(C5H8O2)n
(C6H10O2)n
m-3)
m-3)
Molecular formula
m-3)
Particulate
m-3)
j
Processes
1
PAO: Anaerobic PHA storage
2
PAO: Anaerobic maintenance
3
GAO: Anaerobic PHA storage
4
GAO: Anaerobic maintenance
k
Composition
1
ThOD (gCOD/moli)
2
Charge + (mol+/moli)
-3
3
P
1
4
K
5
Mg
6
C
2
7
H
4
8
O
2
units
(mol
-1
(mol
(mol
m-3)
(mol
m-3)
26/30
0.28·26/30
0.36·26/30
1
0.28
0.36
-1
(mol
m-3)
2/6
(mol
m-3)
(mol
m-3)
72/30
-11/30
2
-1
0.54
1.08
0.5
1
2
64
+1
+2
-2
(mol
m-3)
-1/6
-26/30
(mol
(mol
(mol m-3)
4/6
-1
-0.3733
0.6789
0.1822
0.0122
-1
1/4
1/2
1/4
192
144
192
240
4
5
6
6
8
10
2
2
2
+1
1
1
0.28
1
0.36
1
6
1
4
(mol
m-3)
3
3
2
10
1
5
3
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
Table SM2.2 Biokinetic model of PAO and GAO processes under anaerobic conditions under standardized
conditions (20°C, pH 7.0). Adpated from Smolders et al. (1995), Zeng et al. (2003), Siegrist et al. (2002), de
Kreuk et al. (2007), and Lopez-Vazquez et al. (2009). All coefficients were expressed in molar forms as
prerequisite for implementation in PHREEQC. The kinetic coefficients were taken from Siegrist et al. (2002) and
de Kreuk et al. (2007). The affinity constants used as first approximations by Lopez-Vazquez et al. (2009) were
indeed overestimated compared to the values provided by the two previous studies, and led to limited volumetric
kinetics for the anaerobic metabolic batches modeled at biomass concentrations below 1 g CODx L-1. Another
difference with Lopez-Vazquez et al. (2009) was that the switching functions related to the consumed particulate
components (polyphosphate and glycogen) were expressed with Xi/Xbiomass ratios according to Siegrist et al.
(2002).
j
Processes
Process rates, ρi
1
PAO: Anaerobic acetate uptake
qPAO,Ac_PHA,Max · MAc · XPAO
· MPAO,PP · MPAO,Gly · SATPAO,PHA
2
PAO: Anaerobic maintenance
mPAO,An · XPAO
· MPAO,PP
3
GAO: Anaerobic acetate uptake
qGAO,Ac_PHA,Max · MAc · XGAO
· MGAO,Gly · SATGAO,PHA
4
GAO: Anaerobic maintenance
mGAO,An · XGAO
· MGAO,Gly
Kinetic coefficients:
KAc = 1/2·0.001 molAc m-3
KGly = 1/6·0.01 molGly molXbio-1
KPP = 0.01 molPP molXbio-1
KfPHA = 1/4·0.01 molPHA molXbio-1
Switching functions (Monod terms):
MAc = SAc·(KAc+SAc)-1
MPAO,PP = (XPP,PAO/XPAO)·(KPP+(XPP,PAO/XPAO))-1
MPAO,Gly = (XGly,PAO/XPAO)·(KGly+(XGly,PAO/XPAO))-1
MGAO,Gly = (XGly,GAO/XGAO)·(KGly+(XGly,GAO/XGAO))-1
molPHA molXbio-1
fPHA,Max = 1/4·1
fPP_PAO,Max = 0.30 molPP molXpao-1
fGly_PAO,Max = 1/6·0.27 molPP molXpao-1
fGly_GAO,Max = 1/6·0.30 molPP molXgao-1
PHA-related cell saturation term:
SATPAO,PHA = (fPHA,Max – fPHA,PAO)·(fPHA,Max – fPHA,PAO + KfPHA)-1
SATGAO,PHA = (fPHA,Max – fPHA,GAO)·(fPHA,Max – fPHA,GAO + KfPHA)-1
Kinetic parameters:
qPAO,Ac_PHA,Max (20°C) = 1/2 · 0.20 molAc molPAO-1
qGAO,Ac_PHA,Max (20°C) = 1/2 · 0.22 molAc molGAO-1
mPAO,An (20°C) = 2.35·10-3 molPP h-1 molPAO-1
mGAO,An (20°C) = 1/6 · 4.70·10-3 molGly h-1 molGAO-1
4
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
Table SM2.3 Composition of the medium of anaerobic metabolic batch tests. For simplified modeling in
PHREEQC, only the highlighted main substrates were taken into consideration.
MM
(g/mol)
Component
m(stock)
(mg /1 L)
c(batch) c(batch)
(mol/L) (mmol/L)
c(stock)
(mg/L)
c(batch)
(mg/L)
214
180
28
4
107
90
14
2
2.0E-03
3.7E-04
9.5E-05
1.7E-05
2.000
0.365
0.095
0.017
8.0 mgN/L
1700
151
2
850
75.5
1
6.2E-03
4.8E-04
6.246
0.484
399.7 mgCOD/L
15.0 mgP/L
Mineral solution (2x conc)
NH4Cl
MgSO4.2H2O
CaCl2.2H2O
Allyl-N-thiourea C4H8N2S
Trace element solution**
53.49
246.51
147.02
116.18
214
180
28
4
0.6 mL
Substrate solution (2x conc)
C2H3O2Na.3H2O
NaH2PO4.2H2O
Yeast extract
136.09
156.01
1700
151
2
26.6 gCOD/gP
50.0 gCOD/gN
Component
MM
(g/mol)
m(stock)
(g /5 L)
c(stock)
(g/L)
c(stock)
(mol/L)
c(min. sol.)
(mol/L)
c(batch)
(mol/L)
c(batch)
(mmol/L)
372.25
287.59
197.92
270.30
205.92
249.71
237.96
61.83
166.00
50
0.6
0.6
7.5
0.3
0.15
0.75
0.75
0.9
10
0.12
0.12
1.5
0.06
0.03
0.15
0.15
0.18
0.0269
0.0004
0.0006
0.0055
0.0003
0.0001
0.0006
0.0024
0.0011
1.6E-05
2.5E-07
3.6E-07
3.3E-06
1.7E-07
7.2E-08
3.8E-07
1.5E-06
6.5E-07
8.1E-06
1.3E-07
1.8E-07
1.7E-06
8.7E-08
3.6E-08
1.9E-07
7.3E-07
3.3E-07
8.1E-03
1.3E-04
1.8E-04
1.7E-03
8.7E-05
3.6E-05
1.9E-04
7.3E-04
3.3E-04
**Trace element solution
C10H14N2O8Na2·2H2O
ZnSO4·7H2O
MnCl2·4H2O
FeCl3·6H2O
Na2MnO4·2H2O
CuSO4·5H2O
CoCl2·6H2O
H3BO3
KI
Table SM2.4 Charge matrix of the medium of anaerobic metabolic batch tests. The total concentrations of the
main ionic species displayed in bold characters were used as input data in PHREEQC. According to the
definition of chemical components in PHREEQC, the medium was adapted for ensuring adequate charge
balance, e.g. for the orthophosphate source (highlighted).
Concentration (mmol/L)
PHREEQC
Ionic
Charge
ionic species species i
(mol+/mol i)
Main cations N(-3)
NH4 +
1
Mg
Mg 2+
2
Ca
Ca 2+
2
Na
Na +
1
Main anions Cl
Cl -1
S(6)
SO4 2-2
Acetate
C3H3O2 -1
P
PO4 3-3
Charged components j
NH4Cl
MgSO4
CaCl2 C2H3O2Na
2.000
0.365
0.095
6.246
Moles of ionic species i per mol of component j
(mol i/mol j)
1
1
1
1
1
2
1
1
Na3PO4
0.484
3
1
c_tot(i)
c_tot(+)
Sum(+)
(mmol i /L) (mmol + /L) (mmol + /L)
2.000
2.000
10.619
0.365
0.730
0.095
0.190
7.698
7.698
2.191
-2.191
-10.619
0.365
-0.730
6.246
-6.246
0.484
-1.452
Balance
0.00000
Table SM2.5 Concentrations of PAO and GAO in the anaerobic metabolic batch tests calculated from the
measured average biomass concentration of 1 gVSS L-1 and the relative abundances of PAO and GAO obtained by
T-RFLP. The average biomass formula C1H1.8O0.5N0.2 was considered here. For more precision one could use the
specific biomass formula given by Lopez-Vazquez et al. (2007) and Zeng et al. (2003) for PAO
(C1H2.09O0.54N0.20P0.015) and GAO (C1H1.84O0.5N0.19).
c(biomass) c(biomass) c(biomass) F(PAO) F(GAO)
c(PAO)
c(GAO)
c(others)
(gVSS/L) (C-molX/L) (C-mmolX/L)
(%)
(%) (C-mmolX/L) (C-mmolX/L) (C-mmolX/L)
1.0
0.04065
41
0
60
0
24
16
12
46
5
19
17
24
32
10
13
18
37
16
15
7
19
51
0
21
0
20
5
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
Supplementary material 3
Anaerobic
400
350
Aerobic
Total COD
Acetate
Propionate
Ammonium
300
B
Ammonium
(mgN.-NH4 L-1)
25
Orthophosphate, Potassium, Magnesium
(mgP-PO4, mgK and mgMg L-1)
Anaerobic
200
Aerobic
Phosphate
Potassium
Magnesium
20
150
250
Settling
Volatile fatty acids
(gCOD L-1)
Settling
A
15
200
100
10
150
100
50
5
50
0
60
120
180
240
C
300
0
360
0
0
60
120
180
240
300
360
Electrical conductivity
(μS cm-1)
Anaerobic
1500
Aerobic
Settling
0
1400
1300
1200
1100
1000
0
60
120
180
240
300
360
x-axes = SBR cycle time (min)
Fig. SM3.1 Typical profiles of anaerobic VFA uptake and ammonium assimilation (A), of orthophosphate,
potassium and magnesium cycling (B), and of electrical conductivity (C) recorded in the PAO-SBR for an
enrichment trial with a mixture of acetate and propionate 75:25%COD as carbon source. Legend: concentrations
in the influent wastewater (red points) and in the treated effluent (blue points).
6
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
A
100
PAO-SBR – Unfavorable conditions
Exp. 5
OTUs and affiliations
Other OTUs (< 2%)
393/400 Bdellovibrio
298 Herpetosiphon
294 Ruminococcus
Exp. 7
259/260 Nitrospira / Sphingobacteriales
252/253/252/256/308/318/321/323 Sphingobacteriales (Cytophaga)
251/276/277 Spirochaetes
250 Acinetobacter
239/303/304 Gammaproteobacteria (Competibacter)
50
233/198 TM7
227 Microbiaceae
223/224/229 Intrasporangiaceae (Tetrasphaera)
216 Methyloversatillis
214/215/217 Rhodocyclus (Accumulibacter)
211 Armatimonadetes
200/209 Acidobacteriaceae
193/207/211/212/213/ Comamonadaceae (Acidovorax)
1
4
10
25
53
69
84
98
2
10
13
14
20
31
36
0
185/188/189/190/220/286 Rhizobiales (Aminobacter, Mezorhizobium, Bradyrhizobiaceae)
71/195 Zoogloea
B
PAO-SBR – Optimal conditions
100
50
0
BNR
C
1
5
7
9
17
30
42
51
58
64
73
84
95
99
105
109
116
119
133
147
161
171
186
269
289
315
y-axes = Relative abundances of OTUs (%)
178/193/290 Rhodospirillaceae
GAO-SBR – Optimal conditions
100
50
1
6
14
20
34
50
62
73
95
129
162
199
233
239
258
264
272
290
296
314
325
335
357
377
388
392
398
402
412
426
433
440
454
458
463
471
485
611
0
x-axes = Time (days)
Fig. SM3.2 Bacterial community dynamics during the enrichment of PAO under unfavorable (A) and optimal
(B) start-up conditions, and during the enrichment of GAO (C). The bacterial community dynamics in the PAOSBR and GAO-SBR under optimal conditions (B-C) have previoulsy been presented in Weissbrodt et al. (2013).
7
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
Supplementary material 4
A
B
Normalized electrical conductivity σ
(μS cm-1 gCODx-1)
1000
Normalized orthophosphate concentration
(mgP-PO4 gCODx-1)
100
PAO and GAO
abundances (%)
900
700
600
Normalized acetate concentration
(mgCOD,Ac gCODx-1)
0
90
80
51 : 0
37 : 16
24 : 32
12 : 46
0 : 60
800
C
-100
70
60
50
500
-200
40
400
30
300
20
200
-300
10
100
0
0
-10
0
1
2
3
4
5
-400
0
1
2
3
4
5
0
1
2
3
4
5
x-axes (A-C) = Batch time (h)
D
E
Normalized electrical conductivity σ
(μS cm-1 gCODx-1)
250
Normalized acetate concentration
(mgCOD,Ac gCODx-1)
0
20
51 : 0
37 : 16
24 : 32
12 : 46
0 : 60
150
F
25
PAO and GAO
abundances (%)
200
Normalized orthophosphate concentration
(mgP-PO4 gCODx-1)
-100
15
10
-200
100
5
-300
50
0
0
-5
0
10
20
30
-400
0
10
20
30
0
10
20
30
x-axes (D-F) = Batch time (h)
Maximum biomass specific rates
H
I
Conductivity qσ
Orthophosphate qPO4
(μS cm-1 h-1 gCODx-1) (mgP-PO4 h-1 gCODx-1)
400
y = 663.1x + 80.868
R2 = 0.9933
y = 87.351x
R2 = 0.9834
300
30
250
200
20
150
100
50
qσ
qPO4
0
10
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Relative abundance of PAO
in total biomass (%)
0.5
FGAO = GAO/(PAO+GAO) (-)
0
1
500
50
40
350
1
qσ (μS cm-1 h-1 gCODx-1)
450
FGAO = GAO/(PAO+GAO) (-)
0.5
0
0.5
YPO4/Ac (mgP-PO4 mgCOD,Ac-1)
G
400
300
200
100
qσ = 337 FPAO + 91
R2 = 0.9877
0
0.4
0.3
0.2
0.1
YPO4/Ac = 0.507 FPAO
R2 = 0.9951
0.0
0
0.5
FPAO = PAO/(PAO+GAO) (-)
1
0
0.5
1
FPAO = PAO/(PAO+GAO) (-)
Fig. SM4.1 Evolution of conductivity (A), orthophosphate (B), and acetate (C) recorded during 5 h in anaerobic
metabolic batch tests in function of the experimental relative abundance of PAO and GAO measured by TRFLP. Each variable was normalized by the biomass concentration expressed as COD equivalents. Zooms over
the data collected during the first 30 min that were used to compute initial maximum rates (D-F). Linear trends
were obtained between the maximum biomass specific rates of conductivity evolution (q σ) and of orthophosphate
release (qPO4), and the relative abundance of PAO present in the total biomass (G). The maximum biomass
specific rates of conductivity evolution (qσ) (H) and the yield of orthophosphate release to acetate uptake (I) also
correlated linearily with the PAO/GAO ratio.
8
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
Supplementary material 5
A
B
Electrical conductivity σ
(μS cm-1)
1100
C
Orthophosphate concentration
(mgP-PO4 L-1)
200
PAO (C-mmolX L-1)
Acetate concentration
(mgCOD,Ac L-1)
450
0
400
1000
250 100 50
25
150 250 100 50
350
25
900
300
10
800
100
5
250
10
10
200
700
150
5
5
50
100
250 100 50
600
0
500
0
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
25
50
0
0
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
x-axes (A-C) = Batch time (h)
D
E
Electrical conductivity σ
(μS cm-1)
1100
Maximum biomass specific rate of
conductivity evolution qσ (μS cm-1 h-1 gCODx-1)
250
Slope = 2.8103 (μS/cm) (mgP/L)-1
R2 = 0.9987
1000
F
Yσ/Ac (μS cm-1 mgCOD,Ac-1)
YPO4/Ac (mgP-PO4 mgCOD,Ac-1)
1.5
200
900
1
150
800
100
700
0.5
50
600
500
qσ = 195 μS cm-1 h-1 gCODx-1
Yσ/Ac
YPO4/Ac
0
0
50
100
150
200
Orthophosphate concentration (mgP-PO4 L-1)
= 1.18 μS cm-1 gCOD,Ac-1
= 0.42 gP-PO4 gCOD,Ac-1
0
0
50
100
150
200
250
PAO concentration (C-mmolX L-1)
0
50
100
150
200
250
PAO concentration (C-mmolX L-1)
Fig. SM5.1 Evolutions of conductivity (A), orthophosphate (B), and acetate (C) during anaerobic metabolic
batch tests simulated in PHREEQC in function of the concentration of PAO when only PAO are present in the
sludge. A single linear trend was satisfactorily describing the correlation between all conductivity and
orthophosphate profiles (D). The maximum biomass specific rate of conductivity evolution amounted to 195 μS
cm-1 h-1 gCODx-1 independently from the PAO concentration (E). Yields of conductivity evolution (Yσ/Ac) and of
orthophosphate release (YP-PO4/Ac) to acetate uptake amounted to 1.18 μS cm-1 gCOD,Ac-1 and 0.42 gP-PO4 gCOD,Ac-1,
respectively (F).
9
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
A
B
Electrical conductivity σ
(μS cm-1)
1100
C
Orthophosphate concentration
(mgP-PO4 L-1)
200
450
400
PAO/GAO (%)
1000
100:0
150
100:0
900
350
300
75:25
75:25
800
250
100
50:50
200
50:50
25:75
700
Acetate concentration
(mgCOD,Ac L-1)
150
25:75
50
0:100
0:100
100
100:0
600
50
0:100
500
0
0.0
0.5
1.0
1.5
2.0
0
0.0
0.5
1.0
1.5
2.0
0.0
0.5
1.0
1.5
2.0
x-axes (A-C) = Batch time (h)
Slopes (μS/cm) (mgP/L)-1
R2 > 0.9990
1100
1000
0
200
900
3.8
800
5.2
∞
700
600
0
1
0.5
0.5
0:100
y = 142x + 55
50
150
100
100
150
50
y = 142x + 55
R2 = 0.9951
200
0
500
0
50
100
150
1
0
R2 = 0.9951
2.9
3.3
100:0
F
FGAO = GAO/(PAO+GAO) (-)
200
Orthophosphate concentration (mgP-PO4 L-1)
0
0.5
FPAO = PAO/(PAO+GAO) (-)
FGAO = GAO/(PAO+GAO) (-)
0
0 1
1.5
Yσ/Ac (μS cm-1 mgCOD,Ac-1)
YPO4/Ac (mgP-PO4 mgCOD,Ac-1)
E
Electrical conductivity σ
(μS cm-1)
qσ (μS cm-1 h-1 gCODX-1)
D
0.5
0.5
Yσ/Ac
YPO4/Ac
1
0
R2 = 0.9951
y = 0.9341x
+ 0.2849
y = 142x
+ 55
R2 = 0.995
50
1
100
y = 0.4094x
0.5
150
2
R = 0.9971
200
0
1
0
0.5
1
FPAO = PAO/(PAO+GAO) (-)
Fig. SM5.2 Evolutions of conductivity (A), orthophosphate (B), and acetate (C) during anaerobic metabolic
batch tests simulated in PHREEQC in function of the PAO/GAO ratio. Different linear correlations were
obtained between conductivity and orthophosphate profiles in function of the PAO/GAO ratio (D). The biomass
specific rate of conductivity evolution (qσ) (E), and the yields of conductivity evolution (Yσ/Ac) and of
orthophosphate release (YP-PO4/Ac) to acetate uptake can be related in a linear way to the PAO/GAO ratio (F).
10
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
Supplementary material 6
B
Normalized polyphosphate hydrolysis
(μmolPi-PP45 mgProteins-1)
0
5
10
15
20
40
-5
-10
-15
-20
30
20
PAO and GAO
relative abundances
51 : 0 %
37 : 16 %
24 : 32 %
12 : 46 %
0 : 60 %
-45
-50
-55
10
y = 91.089x
2
R = 0.9914
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Relative abundance of PAO
in total biomass (-)
E
Rate of conductivity evolution
qσ (μS cm-1 h-1 gCODx-1)
1000
450
900
400
800
350
700
300
600
250
500
200
400
150
300
y = 7.2255x + 81.754
50
R2 = 0.9794
0
0
40
30
20
10
qlys,PP = 48.2 FPAO
R2 = 0.990
0
0.5
1
FPAO = PAO/(PAO+GAO) (-)
Polyphosphatase activity qlys,PP
(in equivalent units: mgP-PP h-1 gCODx-1)
500
100
0.5
50
0
0
Enzymatic reaction time (min)
D
FGAO = GAO/(PAO+GAO) (-)
1
50
5
0
-25
-30
-35
-40
C
Polyphosphatase activity
qlys,PP (nkatPi-PP45 mgProteins-1)
Polyphosphatase activity qlys,PP
(nkatPi-PP mgProteins-1)
A
200
y = 21.17x
100
R = 0.9727
2
0
0
10
20
30
40
Polyphosphatase activity
qlys,PP (nkatPi-PP45 mgProteins-1)
50
0
10
20
30
40
50
Anaerobic metabolic activity
qPO4 (mgP-PO4 h-1 gCODx-1)
Fig. SM6.1 Evolution of the hydrolysis of commercial polyphosphate 45 during enzymatic reactions with cell
extracts from different mixtures of PAO and GAO biomass (A). Linear relation between the polyphosphatase
activity and the T-RFLP-based relative abundance of PAO present in the total biomass of mixtures of PAO and
GAO enrichments (B). Linear relation between the polyphosphatase activity and the fraction of PAO calculated
based on the sum of PAO and GAO only (C). Comparison of the biomass specific rate of conductivity evolution
and the polyphosphatase activity of PAO/GAO mixtures (D). Comparison of the rate of polyphosphate
hydrolysis in the enzymatic assay and the rate of orthophosphate release in anaerobic metabolic batch tests (E).
The polyphosphatase activity in nkatPi-PP45 mgProteins-1 was converted in mgP-PP h-1 gCODx-1 in order to allow
comparing the two types of polyphosphate hydrolysis activity measured. The average measured fraction of
proteins present in cell extracts (0.250 gPrtoeins gVSS-1) and the VSS→CODx conversion factor of 1.366 gCODx gVSS1
for a standard biomass composition of C1H1.8O0.5N0.2 were taken into account, to this end.
11
Weissbrodt D.G. et al., Supplementary material, Multilevel correlations in the EBPR process
References
Aguado D, Montoya T, Ferrer J, Seco A. 2006. Relating ions concentration variations to conductivity variations
in a sequencing batch reactor operated for enhanced biological phosphorus removal. Environmental
Modelling & Software 21(6):845-851.
de Kreuk MK, Picioreanu C, Hosseini M, Xavier JB, van Loosdrecht MCM. 2007. Kinetic model of a granular
sludge SBR: Influences on nutrient removal. Biotechnology and Bioengineering 97(4):801-815.
Hesselmann RPX, Werlen C, Hahn D, van der Meer JR, Zehnder AJB. 1999. Enrichment, phylogenetic analysis
and detection of a bacterium that performs enhanced biological phosphate removal in activated sludge.
Systematic and Applied Microbiology 22(3):454-465.
Hollender J, Dreyer U, Kornberger L, Kämpfer P, Dott W. 2002. Selective enrichment and characterization of a
phosphorus-removing bacterial consortium from activated sludge. Applied Microbiology and
Biotechnology 58(1):106-111.
Lopez-Vazquez CM, Hooijmans CM, Brdjanovic D, Gijzen HJ, van Loosdrecht MCM. 2007. A practical method
for quantification of phosphorus- and glycogen-accumulating organism populations in activated sludge
systems. Water Environment Research 79(13):2487-2498.
Lopez-Vazquez CM, Oehmen A, Hooijmans CM, Brdjanovic D, Gijzen HJ, Yuan Z, van Loosdrecht MCM.
2009. Modeling the PAO-GAO competition: Effects of carbon source, pH and temperature. Water
Research 43(2):450-462.
Lu H, Oehmen A, Virdis B, Keller J, Yuan Z. 2006. Obtaining highly enriched cultures of "Candidatus
Accumulibacter phosphates" through alternating carbon sources. Water Research 40(20):3838-3848.
Manga J, Ferrer J, Garcia-Usach F, Seco A. 2001. A modification to the Activated Sludge Model No. 2 based on
the competition between phosphorus-accumulating organisms and glycogen-accumulating organisms.
Water Science and Technology 43(11):161-171.
Marcelino M, Guisasola A, Baeza JA. 2009. Experimental assessment and modelling of the proton production
linked to phosphorus release and uptake in EBPR systems. Water Research 43(9):2431-2440.
Schuler AJ, Jenkins D. 2003. Enhanced biological phosphorus removal from wastewater by biomass with
different phosphorus contents, part I: Experimental results and comparison with metabolic models.
Water Environment Research 75(6):485-498.
Seco A, Ribes J, Serralta J, Ferrer J. 2004. Biological nutrient removal model No. 1 (BNRM1). Water Science
and Technology 50(6):69-78.
Serralta J, Borras L, Blanco C, Barat R, Seco A. 2004. Monitoring pH and electric conductivity in an EBPR
sequencing batch reactor. Water Science and Technology 50(10):145-152.
Siegrist H, Rieger L, Koch G, Kuhni M, Gujer W. 2002. The EAWAG Bio-P module for activated sludge model
No. 3. Water Science and Technology 45(6):61-76.
Smolders GJF, van der Meij J, van Loosdrecht MCM, Heijnen JJ. 1994. Model of the anaerobic metabolism of
the biological phosphorus removal process - Stoichiometry and pH influence. Biotechnology and
Bioengineering 43(6):461-470.
Smolders GJF, van der Meij J, van Loosdrecht MCM, Heijnen JJ. 1995. A structured metabolic model for
anaerobic and aerobic stoichiometry and kinetics of the biological phosphorus removal process.
Biotechnology and Bioengineering 47(3):277-287.
Weissbrodt DG, Neu TR, Kuhlicke U, Rappaz Y, Holliger C. 2013. Assessment of bacterial and structural
dynamics in aerobic granular biofilms. Frontiers in Microbiology 4:175.
Zeng RJ, van Loosdrecht MCM, Yuan ZG, Keller J. 2003. Metabolic model for glycogen-accumulating
organisms in anaerobic/aerobic activated sludge systems. Biotechnology and Bioengineering 81(1):92105.
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