Supporting information
Membrane bioreactors fed with different COD/N ratio wastewater:
impacts on microbial community and microbial products
Xiaomeng Han1, Zhiwei Wang1,*, Jinxing Ma1, Chaowei Zhu2, Yaxin Li1, Zhichao Wu1
1
State Key Laboratory of Pollution Control and Resource Reuse, School of Environmental
Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, P.R. China
2
Chinese Research Academy of Environmental Sciences, Beijing 100012, P.R. China
* Corresponding
author. Tel./fax: +86-21-65980400. E-mail address: zwwang@tongji.edu.cn
S1
Contents
Microbial diversity analysis procedure
Fig. S1 Schematic diagram of M1 and M2
Fig. S2 Venn diagram of the bacterial communities of M1 and M2 based on OTU (3% distance),
and the taxonomic identities at the phylum level. M1-U and M2-U represent the unique M1 and M2
communities, and M1-M2 refers to shared communities
Fig. S3 Variations of relative abundances of the predominant phylogenetic group at the phylum
level in MBRs; (a) the relative abundance, (b) statistical analysis of the difference; relative
abundance is defined as the number of sequences affiliated with that taxon divided by the total
number of sequences per sample; “No_Rank” are defined as the sequences that are embodied in
the database but without taxonomic classification; phyla making up less than 0.5 % are defined as
“others”
Fig. S4 EEM fluorescence spectra of (a) SMP of M1, (b) SMP of M2, (c) LB-EPS of M1, (d)
LB-EPS of M2, (e) TB-EPS of M1, (f) TB-EPS of M2; Peak A indicates aromatic protein-like
substances, Peak B indicates tryptophan protein-like substances and Peak C indicates visible
humic acid-like substances
Fig. S5 Comparison of the fluidity of SMP and bound EPS extracted from M1 and M2: Dissipation
shift (△D) versus frequency shift (△f) during adsorption stage
Fig. S6 Component percentage changing of SMP and bound EPS excreted in the batch tests; (a)
SMP in M1 sludge, (b) SMP in M2 sludge, (c) LB-EPS in M1 sludge, (d) LB-EPS in M2 sludge, (e)
TB-EPS in M1 sludge, (f) TB-EPS in M2 sludge
Table S1 Richness and diversity estimators of the bacteria phylotypes in MBRs
S2
Microbial diversity analysis procedure
Based on the manufacturer’s protocols, DNA extraction was conducted by FastDNA®SPIN
Kit for Soil (MP Biomedicals, Solon, OH, USA). Afterwards, the quality of the DNA fragments
was measured via a Nano-drop® ND-1000 spectrophotometer (Labtech International, UK). DNA
were
amplified
by
PCR
with
thermocycling
steps
using
primer
set
27F
(5’-AGAGTTTGATCCTGGCTCAG-3’) and 533R (5’-TTACCGCGGCTGCTGGCAC-3’) with
the aim of the V1-V3 region of the 16S rRNA gene. 0.4 μL of FastPfu Polymerase, 4 μL of
5×FastPfu Buffer, 0.4 μL of each primer (5 μM), 2 μL of 2.5 mM dNTPs and 0.5 μL of DNA were
included in the PCR mixture of 20 μL. During the thermocycling steps, denaturation at 95°C for 2
min was first employed. Then 25 cycles of 95°C for 30 sec, 55°C for 30 sec, 72°C for 30 sec were
applied, followed by a final extension step at 72°C for 5 min. A 10-nucleotide barcode, which was
inserted between the Life Science primer A and the 27F primer, was incorporated in the fused
forward primer. During pyrosequencing in a single 454 GS-FLX run, these barcodes enabled
samples to multiplex.
The mixture of amplicons was purified with the UNIQ-10 PCR Purification Kit (Sangon,
Shanghai, China) and quantified with a TBS-380 (Turner BioSystems, Inc., USA). Then the
amplicons were used for pyrosequencing on a Roche 454 GS-FLX Titanium platform (Roche 454
Life Sciences, Branford, CT, USA) according to the method reported by Margulies et al. (2005).
In order to improve the veracity of data, the low-quality sequences shorter than 200 bp which
could not match the forward primer or possessed an unrecognizable reverse primer or contained
any ambiguous base calls, were removed (Lu et al. 2012). After eliminating the low-quality
sequences and stripping barcodes and primers, 6940 (R1) and 6867 (R2) high-quality V1-V3 tags
of the 16S rRNA-gene were produced with an average length was 473 bp.
S3
Finally, a kmer searching (http://www.mothur.org/wiki/Align.seqs) was performed to analyze
the resulting sequences based on the silva database ( http://www.arb-silva.de ). The uniform length
was 200 bp. According to the furthest neighbor method in MOTHUR program
(http://www.mothur.org/wiki/Cluster), the high-quality reads were clustered into operational
taxonomic units (OTUs) with a 0.03 or 0.05 distance limit (corresponding to 97% or 95%
similarity). Taxonomic classification was assigned down to the phylum and genus level using
Naïve Bayesian Classifier method (http://www.mothur.org/wiki/Classify.seqs ) with a set
confidence threshold of 80%.
Effluent
Carbon source added
Influent coming from a
dynamic membrane separation
reactor with carbon source
added
A/O MBR, M1
Effluent
Influent coming from a
dynamic membrane separation
reactor
A/O MBR, M2
Fig. S1 Schematic diagram of M1 and M2
S4
2500
No_Rank
Acidobacteria
Actinobacteria
Bacteroidetes
2000
Chlorobi
Chloroflexi
Cyanobacteria
1500
OTUs
Elusimicrobia
Firmicutes
Fusobacteria
Gemmatimonadetes
1000
Lentisphaerae
Nitrospirae
Planctomycetes
500
Proteobacteria
Spirochaetes
Tenericutes
Verrucomicrobia
0
M₁-U
M₁-M₂
M₂-U
M1-U
1581
OTUs
M2-U
M1-M2
526
OTUs
2246
OTUs
Fig. S2 Venn diagram of the bacterial communities of M1 and M2 based on OTU (3% distance),
and the taxonomic identities at the phylum level. M1-U and M2-U represent the unique M1 and M2
communities, and M1-M2 refers to shared communities
S5
M1
M2
Bacteroidetes
Proteobacteria
Nitrospirae
No_Rank
Chloroflexi
others
Planctomycetes
Acidobacteria
Gemmatimonadetes
Chlorobi
Candidate_division_TM7
Verrucomicrobia
Lentisphaerae
(a)
(b)
Fig. S3 Variations of relative abundances of the predominant phylogenetic group at the phylum
level in MBRs; (a) the relative abundance, (b) statistical analysis of the difference; relative
abundance is defined as the number of sequences affiliated with that taxon divided by the total
number of sequences per sample; “No_Rank” are defined as the sequences that are embodied in
the database but without taxonomic classification; phyla making up less than 0.5 % are defined as
“others”
S6
0
550
(a)
3.467E4
(b)
3.467E4
1.040E5
6.933E4
500
1.387E5
450
1.040E5
1.733E5
1.387E5
450
2.080E5
400
1.733E5
2.427E5
2.600E5
2.080E5
Ex (nm)
Ex (nm)
0
550
6.933E4
500
350
400
2.427E5
2.600E5
350
300
300
250
250
300
350
400
450
500
250
550
Em (nm)
250
300
350
400
450
500
550
Em (nm)
-6.000E4
550
(c)
5.467E4
(d)
Peak C
2.840E5
5.133E5
3.987E5
450
6.280E5
Peak B
400
1.693E5
500
3.987E5
5.133E5
7.427E5
8.000E5
6.280E5
Ex (nm)
Ex (nm)
5.467E4
2.840E5
450
350
300
-6.000E4
550
1.693E5
500
Peak A
400
7.427E5
8.000E5
350
300
250
250
300
350
400
450
500
250
550
Em (nm)
250
300
350
400
450
500
550
Em (nm)
-2.000E5
550
(e)
1.200E5
(f)
1.200E5
7.600E5
4.400E5
500
1.080E6
450
7.600E5
1.400E6
1.080E6
450
1.720E6
400
1.400E6
2.040E6
2.200E6
1.720E6
Ex (nm)
Ex (nm)
-2.000E5
550
4.400E5
500
350
400
2.040E6
2.200E6
350
300
300
250
250
300
350
400
450
500
250
550
Em (nm)
250
300
350
400
450
500
550
Em (nm)
Fig. S4 EEM fluorescence spectra of (a) SMP of M1, (b) SMP of M2, (c) LB-EPS of M1, (d)
LB-EPS of M2, (e) TB-EPS of M1, (f) TB-EPS of M2; Peak A indicates aromatic protein-like
substances, Peak B indicates tryptophan protein-like substances and Peak C indicates visible
humic acid-like substances
S7
15
M₁:SMP
Dissipation shift, △D (10 -6 )
12
9
y = -0.4028x - 0.0148 R² = 0.9888
M₂:SMP
y = -0.2228x + 0.0079 R² = 0.9472
M₁:LB-EPS
y = -0.3590x - 1.2737 R² = 0.9977
M₂:LB-EPS
y = -0.3369x - 0.7880 R² = 0.9973
M₁:TB-EPS
y = -0.3114x + 0.8377 R² = 0.9986
M₂:TB-EPS
y = -0.2882x + 1.0710 R² = 0.998
6
3
0
0
-5
-10
-15
-20
-25
-30
-35
-40
-45
-50
Frequency shift, △f (Hz)
Fig. S5 Comparison of the fluidity of SMP and bound EPS extracted from M1 and M2: Dissipation
shift (△D) versus frequency shift (△f) during adsorption stage
S8
Humic acids
Carbohydrates
Proteins
100%
80%
80%
Percentage
Percentage
Proteins
100%
60%
40%
Humic acids
60%
40%
20%
20%
0%
0%
0
1
2
3
4
5
0
6
1
2
(a)
4
5
6
(b)
Humic acids
Carbohydrates
Proteins
100%
100%
80%
80%
Percentage
Percentage
Proteins
3
Time (h)
Time (h)
60%
40%
20%
Humic acids
Carbohydrates
60%
40%
20%
0%
0%
0
1
2
3
4
5
6
0
1
2
Time (h)
Proteins
3
4
5
6
Time (h)
(c)
(d)
Humic acids
Carbohydrates
Proteins
100%
100%
80%
80%
Percentage
Percentage
Carbohydrates
60%
40%
20%
Humic acids
Carbohydrates
60%
40%
20%
0%
0%
0
1
2
3
4
5
6
0
1
2
Time (h)
3
4
5
6
Time (h)
(e)
(f)
Fig. S6 Component percentage changing of SMP and bound EPS excreted in the batch tests; (a)
SMP in M1 sludge, (b) SMP in M2 sludge, (c) LB-EPS in M1 sludge, (d) LB-EPS in M2 sludge, (e)
TB-EPS in M1 sludge, (f) TB-EPS in M2 sludge
S9
Table S1 Richness and diversity estimators of the bacteria phylotypes in MBRs
α=0.03
Sample
OTU
Chao1a
M1
2107
6460
5.45
M2
2772
8908
6.82
α=0.05
Shannon b Coverage c
OTU
Chao1a
Shannon b Coverage c
0.78
1796
4891
5.19
0.82
0.70
2371
6594
6.56
0.76
References:
Lu L, Xing D, Ren N (2012) Pyrosequencing reveals highly diverse microbial communities in
microbial electrolysis cells involved in enhanced H2 production from waste activated sludge.
Water Res 46: 2425-2434
Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS,
Chen YJ, Chen ZT (2005) Genome sequencing in microfabricated high-density picolitre reactors.
Nature 437: 376-380
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