1

Supporting Information

For

Dynamics of the Physiochemical and Community Structures of Biofilms under

the Influence of Algal Organic Matter and Humic Substances

Lei Li1, Youchul Jeon1,†, Sang-Hoon Lee1,†, Hodon Ryu2, Jorge W. Santo Domingo2, and

Youngwoo Seo1,3*

1 Department of Civil and Environmental Engineering, University of Toledo, Mail Stop 307,

3048 Nitschke Hall, Toledo, OH, USA

2 Water Systems Division, National Risk Management Research Laboratory, U.S. Environmental

Protection Agency, Cincinnati, Ohio 45268, United States

3 Department of Chemical Engineering, University of Toledo, Mail Stop 307, 3048 Nitschke Hall,

Toledo, OH, USA

† These authors (alphabetical order) contributed equally to this work.

* Corresponding author’s mailing address: 3006 Nitschke Hall, Mail Stop 307, 2801 W. Bancroft

St., Toledo, OH 43606-3390; Phone: (419) 530-8131; Fax: (419) 530-8116; Email:

Youngwoo.Seo@utoledo.edu

2

Summary:

Text S1. Preparations of HS- and AOM-impacted bulk waters (reactor influents)

Text S2. EEM analysis

Text S3. Biofilm staining and CLSM imaging

Text S4. Statistical analyses

Fig. S1. A schematic diagram of the experimental setup for three biofilm CDC reactors.

Fig. S2. Fluorescence fingerprints of the five EEM-PARAFAC components identified by

PARAFAC analyses.

Fig. S3. PCA plot of EEM-PARAFAC components (organic matter compositions) of HS-,

AOM-, and R2A-impacted bulk water as determined by the Fmax percentage values. PC1 and

PC2 explained 86.79% and 12.46% variances, respectively.

Fig. S4. Venn diagrams of the core OTUs for BFHS, BFAOM, and BFR2A.

Fig. S5. Representative CLSM images for (A) BFHS, (B) BFAOM, and (C) BFR2A at day 168.

Blue pixel: protein; Green pixel: cell biomass; Red pixel: polysaccharide.

Table S1. Description of identified components through the EEM-PARAFAC model.

Table S2. The effects of operational factors on the biofilm community structures along PCoA

axes for all the samples ((envfit) function, {Vegan} package, RStudio software).

Table S3. The universal cores which were shared among all biofilm samples. Taxonomy is listed

for the further classification.

Table S4. Relative abundance and taxonomic affiliation of top 10 OTUs responsible for the

dissimilarities among BFHS, BFAOM, and BFR2A through SIMPER analysis.

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Text S1. Preparations of HS- and AOM-impacted bulk waters (reactor influents)

The concentrated HS stock solution was prepared by dissolving 1 gram of humic acid

(Sigma Aldrich, MO, USA) into 50 mL DI water. The concentrated AOM stock solution was

prepared using concentrated cyanobacteria-laden water samples from Lake Erie with five cycles

of freeze-thaw steps to obtain AOM according to the USEPA Method 545. AOM and HS stock

solutions were added into jar test beakers which contained 2 L of filtrated tap water (TOC ~0

mg/L) collected from a GAC (Calgon Carbon, PA, USA) column. Next, 8 mL of aluminum

sulfate stock solution (10,000 mg/L) was added as a coagulant to each beaker. Then, jar tests

were conducted following the steps: rapid mixing at 200 rpm for 1 minutes, slow mixing at 25

rpm for 30 minutes, and no mixing for 1 hour to simulate the coagulation, flocculation, and

sedimentation processes. The supernatants were then collected from each beaker, and 2 mg/L of

ozone were applied for 5 minutes using a lab-scale ozonator (OZOTECH, CA, USA). Then,

TOC concentrations were measured for the ozonated water samples and the final concentration

was adjusted to 1.5 mg/L.

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Text S2. EEM analysis

The collected water samples were filtered through 0.45 µm hydrophilic polyethersulfone

membrane filters (EMD Millipore, MA, USA). Fluorescence excitation-emission matrix (EEM)

spectra were recorded in triplicates using a spectrofluorophotometer (RF-6000, Shimadzu,

Japan). Excitation wavelengths were scanned from 200 nm to 500 nm at 5-nm increments;

Emission wavelengths were scanned from 220 nm to 560 nm at 2-nm increments. The obtained

fluorescence EEM spectra were processed by parallel factor (PARAFAC) analyses using a

drEEM 4.0 toolbox (Murphy et al. 2013) built in MATLAB (MathWorks, Natick, MA) with the

non-negativity constrains method. For PARAFAC analyses, the wavelength ranges were

restricted from 250 nm to 450 nm for excitations and from 270 nm to 560 nm for emissions.

Blank corrections, Raman and Rayleigh scattering removals, inner-filter corrections were

finished following the preprocessing steps implemented in the drEEM. A final of five

components model was developed as illustrated in Fig. S2 and Table S1. The model was

validated using split-half method (Murphy et al. 2013, Stedmon and Bro 2008). The Fmax value

calculated by the component maximum fluorescence intensity multiplied by its score (Murphy et

al. 2013) was assumed to be proportional to the real concentrations of the corresponding

component (Borisover et al. 2009).

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Text S3. Biofilm staining and CLSM imaging

Bacterial cells in the biofilm matrix were stained with SYTO 9. Protein contents in the

biofilm EPS were labeled with SYPRO orange. Polysaccharide contents in the biofilm EPS were

visualized by applying a mixture of ConA Alexa 633 and WGA Alexa 633 (Thermo Fisher

Scientific Inc., MA, USA) stains, which specifically targets the polysaccharides (α-

mannopyranosyl and α-glucopyranosyl residues, and N-acetyl-D-glucosamine and N-

acetylneuraminic acids) in biofilms (Marchal et al. 2011). The stained biofilms were incubated in

the dark room for 20 minutes. Then, biofilm images were collected using a CLSM at 20X

magnification with a scan speed of 600 Hz (Xue et al. 2014). The image collection gates were set

at the 488 nm excitation wavelength and recorded at 551-602 nm for SYPRO orange and 504-

547 nm for SYTO 9, respectively. ConA and WGA stains were excited at 633 nm and recorded at

646-704 nm. Z-stacks were acquired in the 512 × 512 format with 2 μm z-step size.

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Text S4. Statistical analyses

Principle coordinate analysis (PCoA) based on the weighted UniFrac distance matrix was

applied to compare the bacterial community compositions among samples. The significant

factors ((envfit) function, {Vegan} package, RStudio software) were later added to PCoA plot to

visualize the impacts of bulk water characteristics on the bacterial community changes (Oksanen

et al. 2015). Analysis of Similarity (ANOSIM) test based on the weighted UniFrac distance

matrix was performed to evaluate the significant differences among sample groups (permutation

= 999). The ANOSIM statistic R is a value ranged from -1 to 1 and the closer to 1 indicates a

higher degree of separation between groups (Ramette 2007). Similarity Percentage analysis

(SIMPER) based on the Bray-Curtis distance matrix was conducted to identify the OTUs

primarily contributing to the dissimilarities between sampling groups (PAST 3). The Spearman’s

rank correlation coefficient (ρ) ranged from -1 to 1 was used to evaluate the correlations between

two biofilm structural parameters. The correlations between two parameters are high when the ρ

closed to -1 or 1.

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Fig. S1. A schematic diagram of the experimental setup for three biofilm CDC reactors.

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Fig. S2. Fluorescence fingerprints of the five EEM-PARAFAC components identified by PARAFAC analyses.

9

Fig. S3. PCA plot of EEM-PARAFAC components (organic matter compositions) of HS, AOM,

and R2A-impacted bulk water as determined by the Fmax percentage values. PC1 and PC2

explained 86.79% and 12.46% variances, respectively.

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Fig. S4. Venn diagrams of the core OTUs for BFHS, BFAOM, and BFR2A.

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Fig. S5. Representative CLSM images for (A) BFHS, (B) BFAOM, and (C) BFR2A at day 168. Blue pixel: proteins; Green pixel: cell

biomass; Red pixel: polysaccharides.

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Table S1. Description of identified components through the EEM-PARAFAC model.

Component Exmax(nm)a Emmax(nm)b Descriptions from previous studies References

C1 275 314 Tyrosine-like materials (Mermillod-Blondin et al. 2015, Murphy et al. 2011)

C2 265(285)c 288 Soluble microbial product-like materials (Chen et al. 2003)

C3 255(280)c 326 Tryptophan-like materials (Coble 2007)

C4 300 420 Low molecular weight humic-like substances (Fellman et al. 2010)

C5 275(320)c 462 High molecular weight humic-like substances (Fellman et al. 2010) aMaximum excitation wavelength. bMaximum emission wavelength. cSecondary fluorescence peaks.

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Table S2. The effects of operational factors on the biofilm community structures along PCoA

axes for all the samples ((envfit) function, {Vegan} package, RStudio software).

PCoA1 PCoA2 R2

P value

(> r) % explanation 36.800 24.700

Turbidity 0.538 -0.843 0.441 0.012 *

pH 0.611 -0.791 0.227 0.092 .

PO43- (mg/L) -0.079 0.997 0.171 0.113

AOC (µg/L) -0.018 0.998 0.111 0.358

TOC (mg/L) 0.022 0.998 0.100 0.506 TN (mg/L) -0.427 0.904 0.679 0.001 ***

TOC/TN 0.612 -0.791 0.245 0.092 .

SUVA254 (L/mg C-m) 0.505 -0.863 0.447 0.011 **

Tyrosine-like materials (%) -0.697 0.717 0.821 0.001 ***

SMP-like materials (%) -0.674 0.739 0.813 0.001 ***

Tryptophan-like materials (%) 0.088 0.996 0.594 0.001 ***

LMW humic-like substances (%) 0.883 -0.468 0.514 0.003 **

HWW humic-like substances (%) 0.481 -0.877 0.543 0.002 **

Significant codes: '***' 0.001;'**' 0.01;'*' 0.05;'.'0.1

Number of permutations: n = 999

R2 represents a coefficient of determination ranged from 0 to 1 indicating how much variation in

biofilm communities can be explained by the bulk water characteristic parameters.

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Table S3. The universal cores which were shared among all biofilm samples. Taxonomy is listed for the further classification.

OTU number

709657 k__Bacteria; p__Proteobacteria; c__Alphaproteobacteria; o__Rhodospirillales; f__Rhodospirillaceae; g__; s__

4329000 k__Bacteria; p__Nitrospirae; c__Nitrospira; o__Nitrospirales; f__Nitrospiraceae; g__Nitrospira; s__

1491 k__Bacteria; p__Nitrospirae; c__Nitrospira; o__Nitrospirales; f__Nitrospiraceae; g__Nitrospira; s__

4390108 k__Bacteria; p__Proteobacteria; c__Alphaproteobacteria; o__Rhodobacterales; f__Rhodobacteraceae; g__Rhodobacter; s__

850135 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae

539570 k__Bacteria; p__Acidobacteria; c__Acidobacteria-6; o__iii1-15; f__mb2424; g__; s__

1125869 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae; g__; s__

4406766 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae; g__; s__

4424415 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Rhodocyclales; f__Rhodocyclaceae; g__Methyloversatilis; s__

2655357 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae; g__; s__

New.ReferenceOTU126 k__Bacteria; p__Proteobacteria; c__Alphaproteobacteria; o__Rhizobiales; f__; g__; s__

New.ReferenceOTU85 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae

Taxon (phylum, class, order, family, genus,species)

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Table S4. Relative abundance and taxonomic affiliation of top 10 OTUs responsible for the dissimilarities among BFHS, BFAOM,

and BFR2A through SIMPER analysis*.

* SIMPER analysis based on the Bray-Curtis distance matrix indicated that the dissimilarity among BFHS, BFAOM, and BFR2A was

80.97%.

OUT number

Contrib.

%

Cumulativ

e %

Mean

abund.% SD

Mean

abund.% SD

Mean

abund.% SD

850135 16.47 16.47 40.93 15.58 9.72 20.58 13.19 5.04 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae

New.ReferenceOTU17 2.68 19.15 0.01 0.02 0.02 0.02 6.35 3.98 k__Bacteria; p__Bacteroidetes; c__Cytophagia; o__Cytophagales; f__Cytophagaceae; g__; s__

2655357 2.35 21.50 3.02 1.40 1.13 1.39 3.96 7.90 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae; g__; s__

4424415 1.83 23.32 0.17 0.13 0.43 0.40 4.39 4.33 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Rhodocyclales; f__Rhodocyclaceae; g__Methyloversatilis; s__

4390108 1.76 25.08 0.23 0.45 3.68 1.71 2.12 3.05 k__Bacteria; p__Proteobacteria; c__Alphaproteobacteria; o__Rhodobacterales; f__Rhodobacteraceae; g__Rhodobacter; s__

New.ReferenceOTU86 1.74 26.81 0.47 0.57 0.48 0.29 4.19 6.59 k__Bacteria; p__Proteobacteria; c__Alphaproteobacteria; o__Rhodospirillales; f__Rhodospirillaceae; g__; s__

New.ReferenceOTU97 1.50 28.31 0.01 0.02 0.08 0.20 3.52 7.91 k__Bacteria; p__Bacteroidetes; c__[Saprospirae]; o__[Saprospirales]; f__Saprospiraceae; g__; s__

4426766 1.44 29.75 0.20 0.24 0.38 0.35 3.55 1.46 k__Bacteria; p__Bacteroidetes; c__[Saprospirae]; o__[Saprospirales]; f__Chitinophagaceae; g__; s__

New.ReferenceOTU126 1.10 30.86 0.20 0.09 2.91 1.69 0.21 0.14 k__Bacteria; p__Proteobacteria; c__Alphaproteobacteria; o__Rhizobiales; f__; g__; s__

611360 1.04 31.90 1.13 2.28 0.02 0.02 1.72 2.80 k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales; f__Comamonadaceae; g__; s__

BFHS BFAOM BFR2A

Taxon (phylum,class,order, family, genus,species)

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