Supplementary material for “Journal of Hazardous Materials”

Co-occurrence of microplastics and triclosan inhibited nitrification function and

enriched antibiotic resistance genes in nitrifying sludge

Zhiqi Wang, Jingfeng Gao*, Dingchang Li, Huihui Dai, Yifan Zhao

National Engineering Laboratory for Advanced Municipal Wastewater Treatment

and Reuse Technology, Beijing University of Technology, Beijing 100124, China

*Corresponding author: Dr. Jing-Feng Gao, E-mail: gao.jingfeng@bjut.edu.cn or

gao158@gmail.com, Tel.: 0086-10-67392627; Fax: 0086-10-67391983.

Summary

1. Methods

Method S1 The properties of MPs.

Method S2 Preparation of MPs suspensions.

Method S3 The repeated experiment.

Method S4 TCS mass balance experiments.

2. Tables

Table S1 Primers used in this study.

Table S2 SRCC analysis of the addition of PE, PS, PVC, PA and concentrations of

effluent SS and MLSS (* represents p < 0.05. P values < 0.05 combined with the SRCC

were marked in blue).

Table S3 SRCC analysis of contents of LB-proteins, LB-polysaccharides, LB-EPS,

TB-proteins, TB-polysaccharides, TB-EPS and concentrations of SS in effluent and

1

MLSS (* represents p < 0.05. P values < 0.05 combined with the SRCC were marked in

blue).

Table S4 Summaries of the results of high-throughput sequencing and alpha diversity

of bacterial 16S rRNA gene based on 97% similarity.

3. Figures

Fig. S1 The concentrations of NH4+-N, NO2

--N, NO3--N, the removal rate of NH4

+-N in

R-PVC (a) and R-PA (b).The effluent concentration of SS in R-PVC and R-PA (c). The

MLSS concentration in R-PVC and R-PA at the 0th, 7th, 14th, and 21th day (d).

Fig. S2 SEM photos of four types of fresh MPs. PE (a), PS (b), PVC (c) and PA (d).

Fig. S3 SEM photos of four types of MPs in the SBRs for 28 days. PE (a), PS (b), PVC

(c) and PA (d).

Fig. S4 SEM photos of nitrifying sludge after adding 1 mg/L MPs in four SBRs and

undosing control SBR for 28 days. SBR-CK (a), SBR-PE (b), SBR-PS (c), SBR-PVC

(d) and SBR-PA (e).

Fig. S5 Microbial morphology of nitrifying sludge after adding 1 mg/L MPs in four

SBRs for 28 days. SBR-PE (a), SBR-PS (b), SBR-PVC (c) and SBR-PA (d).

Fig. S6 The adsorption capacity of TCS on PA, PS, PVC and PE.

Fig. S7 Network analysis showing the relationships among environmental variables

and ARGs-MGEs in five SBRs. Solid and dotted lines represent the positive and

negative correlations, respectively.

2

Method S1 The properties of MPs.

In this study, PE, PS, PVC and PA were selected. Among them, PE is used in

pharmaceutical and personal care products (PPCPs) (with TCS), including body and

facial scrubs as well as food packaging films and water bottles (Cheung & Fok, 2017;

Lares et al., 2018; Ziajahromi et al., 2017). Meanwhile, PVC and PS, which have a lot

of usage in daily life, have been reported in the literature as the plastic materials used in

PPCPs (with TCS) (Fendall & Sewell, 2009; Programme, 2015; Zitko & Hanlon, 1991).

In addition, PS is widely used in protective packaging, containers, bottles and lids

(Sussarellu et al., 2016),which could be used as a box for PPCPs (containing TCS). And

PA is all widely used in synthetic clothes (Ziajahromi et al., 2017), which may come

into contact with laundry liquid (containing TCS) when washing clothes. PE, PS, PVC

and PA had frequent contacted with TCS. As manufactured microbeads (primary MPs)

or small plastic fragments derived from the breakdown of plastics (secondary MPs), PE,

PS, PVC and PA were widely used in life and discharged into WWTPs with TCS. Thus,

it was urgent to explore the co-effects of MPs (PE, PS, PVC and PA) and TCS on

nitrifying sludge in WWTPs.

In addition, the MPs (the size of MPs > 100 μm) in the influent of WWTPs varied

from 1 to 293 particles/L (approximately 0.004 to 1.23 mg/L) (Carr et al., 2016; Dris et

al., 2015). Furthermore, the MPs (the size of MPs > 10 μm) in the influent of WWTPs

varied from 2223 to 18285 particles/L (approximately 0.09-0.84 mg/L) (Simon et al.,

2018). Notably, Ziajahromi et al. (Ziajahromi et al., 2017) quantified MPs in

wastewater, including 3.1 particles/L (approximately 0.012 mg/L) PE, 1.4 particles/L

(approximately 0.006 mg/L) PS, 1.0 particles/L PA (approximately 0.004 mg/L), and a

small number of PVC. PE is one of the most abundant type MPs. Furthermore,

3

Ziajahromi et al. (Ziajahromi et al., 2016) expected the concentration of PE in UK

wastewater is 0.27-1.4 mg/L. Thus, in this study, 1 mg/L MPs, which might be an

environmental concentration of MPs in WWTPs, were selected to study their effect on

activated sludge. Meanwhile, the size of the activated sludge in this study was about 110

m, so the MPs with a size slightly larger than the sludge was selected to study their

impact on sludge.

4

Method S2 Preparation of MPs suspensions.

PE, PS, PVC and PA were dispersed into water by magnetic stirring in four bottles

at a concentration of 100 mg/L, respectively. Before feeding stage, the magnetic

stirrings worked to make the suspensions in bottles sufficiently mixed for 30 min. And

then, the 30 mL MPs dispersions were added into the SBRs during feeding stage.

5

Method S3 The repeated experiment.

In this study, the inhibition on nitrification of “TCS and PVC” or “TCS and PA”

co-loading, were found during 14 days. Thus, the experiment, which co-added TCS and

PVC (named as R-PVC), TCS and PA (named as R-PA), respectively, was repeated by

simulating the same experimental conditions as before. Because the experiment used

domestic sewage as the influent, and formal experiment was completed in summer,

while repeated experiment was conducted in winter, the concentration of NH4+-N and

COD in the sewage in winter is slightly higher than that in summer. The influent

concentration of NH4+-N and COD fluctuated between 58-79 mg/L and 110-150 mg/L,

respectively. Each SBR ran four cycles per day. Each cycle included 0.1 h feed, 3 h

aerobic reaction, 0.15 h settling, 0.15 h decant and 2.6 h idle. The other parameters were

same with before. Among them, 0.5 mg/L TCS and 1 mg/L PVC, 0.5 mg/L TCS and 1

mg/L PA, respectively, were fed to the SBRs. The concentrations of TCS, PVC and PA

were exactly the same as before. Due to the decrease of temperature in winter, the heater

band was used to maintain the temperature in each reactor at 25 ± 2 oC. Meanwhile, the

SBRs were started up with the MLSS concentration of 2000 mg/L, and the seed sludge

was collected from a lab-scale SBR which was dosed with TCS under stable operation.

The repeated experiment ran 24 days.

6

Method S4 TCS mass balance experiments.

The analysis of TCS was made by UV detection at 230  nm, using a Waters X-

bridge C18 Column (250 mm × 4.5 mm, 5 μm). The injected volume was 10 μL with the

flow rate of 1 mL/min. The TCS removal by nitrifying activated sludge may be

contributed by adsorption and degradation (Eq. (1)). The removal TCS mass and

removal efficiency during MPs loading at the14th and 28th day were tracked using the

following Eqs. (1) - (2), where Mlost is the removal mass of TCS (g); Madsorption is the

mass of adsorbed TCS (g); Mdegration is the mass of degraded TCS (g); MTCS is the mass of

total TCS (g); Mresidue is the residual mass of TCS (g); V inf is the volume of influent (L);

Cinf is the total concentration of TCS in influent (g/L); Veff is the volume of effluent (L);

Ceff is the total concentration of TCS in effluent (g/L) (Heidler & Halden, 2007):

(1)

(2)

The adsorbed TCS mass, adsorption efficiency and degradation efficiency are

calculated as Eqs. (3) - (5), respectively, where Vsludge is the volume of sludge in SBR

(L); Csludge, before is the total concentration of TCS in sludge before influent (g/L); Csludge, after

is the total concentration of TCS in sludge after effluent (g/L).

(3)

(4)

(5)

7

Table S1 Primers used in this study.

Gene Name Forward Primer (5’-3’) Reverse Primer (5’-3’) Source

16S rRNA ATGGCTGTCGTCAGCT ACGGGCGGTGTGTAC(Ferris et al.,

1996)

AOA amoA ATAGAGCCTCAAGTAGGAAAGTTCTA CCAAGCGGCCATCCAGCTGTATGTCC(Meinhardt et

al., 2015)

AOB amoA GGGGTTTCTACTGGTGGT CCCCTCKGSAAAGCCTTCTTC(Rotthauwe

et al., 1997)

NOB CCTGCTTTCAGTTGCTACCG GTTTGCAGCGCTTTGTACCG(Liu &

Wang, 2013)

acrA-03 CAGACCCGCATCGCATATT CGACAATTTCGCGCTCATG

(Zhu et al.,

2013)

acrB-01 AGTCGGTGTTCGCCGTTAAC CAAGGAAACGAACGCAATACC

adeA CAGTTCGAGCGCCTATTTCTG CGCCCTGACCGACCAAT

mexF CCGCGAGAAGGCCAAGA TTGAGTTCGGCGGTGATGA

fabI AGGCATAACGCGCTCAGAAC GCACACGCTTGATGGTGACT (Chen et al.,

8

2009)

fabI1 GGCGATTTCCGCTATATCCT CAGCAGATACAAGCCCGAAT(Pycke et al.,

2010)

PafabVACCGAGGTTCATATGATGATCATCAAAC

CGCGCAGGCAAGCTTGTCGCTGAAAACGCGAAC

(Zhu et al.,

2010)

intI1 CGAACGAGTGGCGGAGGGTG TACCCGAGAGCTTGGCACCCA(Gillings et

al., 2015)

intI3 GCCACCACTTGTTTGAGGA GGATGTCTGTGCCTGCTTG(Barraud et

al., 2010)

IS613 AGGTTCGGACTCAATGCAACA TTCAGCACATACCGCCTTGAT(Zhu et al.,

2013)

9

SS MLSS

PESRCC -0.282 0.491

P values 0.498 0.217

PSSRCC -0.282 0.000

P values 0.498 1.000

PVCSRCC 0.773 -0.525

P values 0.039* 0.182

PASRCC 0.800 -0.659

P values 0.017* 0.075

Table S2 SRCC analysis of the addition of PE, PS, PVC, PA and concentrations of

effluent SS and MLSS (* represents p < 0.05. P values < 0.05 combined with the SRCC

were marked in blue).

10

Table S3 SRCC analysis of contents of LB-proteins, LB-polysaccharides, LB-EPS,

TB-proteins, TB-polysaccharides, TB-EPS and concentrations of SS in effluent and

MLSS (* represents p < 0.05. P values < 0.05 combined with the SRCC were marked in

blue).

SS MLSS

LB-proteinsSRCC 0.735 -0.810

P values 0.038* 0.015*

LB-

polysaccharides

SRCC 0.181 -0.500

P values 0.668 0.207

LB-EPSSRCC 0.759 -0.810

P values 0.029* 0.015*

TB-proteinsSRCC 0.566 -0.667

P values 0.143 0.071

TB-

polysaccharides

SRCC 0.458 -0.571

P values 0.254 0.139

TB-EPSSRCC 0.482 -0.619

P values 0.227 0.102

11

Table S4 Summaries of the results of high-throughput sequencing and alpha diversity of bacterial 16S rRNA gene based on 97%

similarity.

SampleEffective

readsobserved_species

Good’s

coveragePD_whole_tree Chao1 Shannon Simpson

Control-14d

35470

1491 0.99 169.92 2095.16 7.38 0.98

PE-14d 1517 0.98 107.27 2189.88 7.44 0.99

PS-14d 1447 0.99 117.84 2063.13 7.29 0.99

PVC-14d 1440 0.98 99.60 2053.21 6.92 0.98

PA-14d 1300 0.99 78.93 1906.00 6.57 0.97

Control-28d 1558 0.99 122.40 2043.03 7.89 0.99

PE-28d 1590 0.98 94.89 2224.28 7.97 0.99

PS-28d 1668 0.98 110.72 2293.29 7.89 0.99

12

Fig. S1 The concentrations of NH4+-N, NO2

--N, NO3--N, the removal rate of NH4

+-N in

R-PVC (a) and R-PA (b).The effluent concentration of SS in R-PVC and R-PA (c). The

MLSS concentration in R-PVC and R-PA at the 0th, 7th, 14th and 21th day (d).

13

Fig. S2 SEM photos of four types of fresh MPs. PE (a), PS (b), PVC (c) and PA (d).

14

Fig. S3 SEM photos of four types of MPs in the SBRs for 28 days. PE (a), PS (b), PVC

(c) and PA (d).

15

Fig. S4 SEM photos of nitrifying sludge after adding 1 mg/L MPs in four SBRs and

undosing control SBR for 28 days. SBR-CK (a), SBR-PE (b), SBR-PS (c), SBR-PVC

(d) and SBR-PA (e).

16

Fig. S5 Microbial morphology of nitrifying sludge after adding 1 mg/L MPs in four

SBRs for 28 days. SBR-PE (a), SBR-PS (b), SBR-PVC (c) and SBR-PA (d).

17

Fig. S6 The adsorption capacity of TCS on PE, PS, PVC and PA.

18

Fig. S7 Network analysis showing the relationships among environmental variables

and ARGs-MGEs in five SBRs. Solid and dotted lines represent the positive and

negative correlations, respectively.

19

References

Barraud, O., Baclet, M.C., Denis, F., Ploy, M.C. 2010. Quantitative multiplex real-time

PCR for detecting class 1, 2 and 3 integrons. J. Antimicrob. Chemother., 65(8),

1642-5.

Carr, S.A., Liu, J., Tesoro, A.G. 2016. Transport and fate of microplastic particles in

wastewater treatment plants. Water Res., 91, 174-82.

Chen, Y., Pi, B., Zhou, H., Yu, Y., Li, L. 2009. Triclosan resistance in clinical isolates of

Acinetobacter baumannii. J. Med. Microbiol., 58(Pt 8), 1086-91.

Cheung, P.K., Fok, L. 2017. Characterisation of plastic microbeads in facial scrubs and

their estimated emissions in Mainland China. Water Res., 122, 53-61.

Dris, R., Gasperi, J., Rocher, V., Saad, M., Renault, N., Tassin, B. 2015. Microplastic

contamination in an urban area: a case study in Greater Paris. Environ. Chem.,

12(5), 592.

Fendall, L.S., Sewell, M.A. 2009. Contributing to marine pollution by washing your

face: microplastics in facial cleansers. Mar. Pollut. Bull., 58(8), 1225-1228.

Ferris, M.J., Muyzer, G., Ward, D.M. 1996. Denaturing gradient gel electrophoresis

profiles of 16S rRNA-defined populations inhabiting a hot spring microbial mat

community. Appl. Environ. Microbiol., 62(2), 340-346.

Gillings, M.R., Gaze, W.H., Pruden, A., Smalla, K., Tiedje, J.M., Zhu, Y.G. 2015. Using

the class 1 integron-integrase gene as a proxy for anthropogenic pollution. ISME J,

9(6), 1269-79.

Heidler, J., Halden, R.U. 2007. Mass balance assessment of triclosan removal during

conventional sewage treatment. Chemosphere, 66(2), 362-9.

Lares, M., Ncibi, M.C., Sillanpää, M., Sillanpää, M. 2018. Occurrence, identification

20

and removal of microplastic particles and fibers in conventional activated sludge

process and advanced MBR technology. Water Res., 133, 236-246.

Liu, G., Wang, J. 2013. Long-term low DO enriches and shifts nitrifier community in

activated sludge. Environ. Sci. Technol., 47(10), 5109-17.

Meinhardt, K.A., Bertagnolli, A., Pannu, M.W., Strand, S.E., Brown, S.L., Stahl, D.A.

2015. Evaluation of revised polymerase chain reaction primers for more inclusive

quantification of ammonia-oxidizing archaea and bacteria. Environ. Microbiol.

Rep., 7(2), 354-63.

Programme, U.N.E. 2015. Plastic in cosmetics, UNEP Nairobi.

Pycke, B.F., Crabbe, A., Verstraete, W., Leys, N. 2010. Characterization of triclosan-

resistant mutants reveals multiple antimicrobial resistance mechanisms in

Rhodospirillum rubrum S1H. Appl. Environ. Microbiol., 76(10), 3116-23.

Rotthauwe, J.H., Witzel, K.P., Liesack, W. 1997. The ammonia monooxygenase

structural gene amoa as a functional marker: Molecular fine-scale analysis of

natural ammonia-oxidizing populations. Appl. Environ. Microbiol., 63(12), 4704-

4712.

Simon, M., van Alst, N., Vollertsen, J. 2018. Quantification of microplastic mass and

removal rates at wastewater treatment plants applying Focal Plane Array (FPA)-

based Fourier Transform Infrared (FT-IR) imaging. Water Res., 142, 1-9.

Sun, J., Dai, X., Wang, Q., van Loosdrecht, M.C.M., Ni, B.J. 2019. Microplastics in

wastewater treatment plants: Detection, occurrence and removal. Water Res., 152,

21-37.

Sussarellu, R., Suquet, M., Thomas, Y., Lambert, C., Fabioux, C., Pernet, M.E.J., Le

Goïc, N., Quillien, V., Mingant, C., Epelboin, Y. 2016. Oyster reproduction is

21

affected by exposure to polystyrene microplastics. Proceedings of the National

Academy of Sciences, 113(9), 2430-2435.

Zhu, L., Lin, J., Ma, J., Cronan, J.E., Wang, H. 2010. Triclosan resistance of

Pseudomonas aeruginosa PAO1 is due to FabV, a triclosan-resistant enoyl-acyl

carrier protein reductase. Antimicrob. Agents Chemother., 54(2), 689-98.

Zhu, Y.G., Johnson, T.A., Su, J.Q., Qiao, M., Guo, G.X., Stedtfeld, R.D., Hashsham,

S.A., Tiedje, J.M. 2013. Diverse and abundant antibiotic resistance genes in

Chinese swine farms. Proc Natl Acad Sci U S A, 110(9), 3435-40.

Ziajahromi, S., Neale, P.A., Leusch, F.D. 2016. Wastewater treatment plant effluent as a

source of microplastics: review of the fate, chemical interactions and potential risks

to aquatic organisms. Water Sci. Technol., 74(10), 2253-2269.

Ziajahromi, S., Neale, P.A., Rintoul, L., Leusch, F.D. 2017. Wastewater treatment plants

as a pathway for microplastics: Development of a new approach to sample

wastewater-based microplastics. Water Res., 112, 93-99.

Zitko, V., Hanlon, M. 1991. Another source of pollution by plastics: skin cleaners with

plastic scrubbers. Mar. Pollut. Bull., 22(1), 41-42.

22