Supporting Information

Efficient reduction of antibiotic residues and associated resistance genes in

tylosin antibiotic fermentation waste using hyperthermophilic composting

Hanpeng Liao1, Qian Zhao1, Peng Cui1, Zhi Chen1, Zhen Yu2, Stefan Geisen3, Ville-

Petri Friman4, Shungui Zhou1

Author affiliation:

1 Fujian Provincial Key Laboratory of Soil Environmental Health and Regulation,

College of Resources and Environment, Fujian Agriculture and Forestry University,

Fuzhou, China;

2 Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and

Management, Guangdong Institute of Eco-environmental Science & Technology,

Guangzhou 510650, China;

3 Department of Terrestrial Ecology, Netherlands Institute of Ecology, Wageningen,

Netherlands;

4 Department of Biology, Wentworth Way, YO10 5DD, University of York, York,

UK;

Supplementary Materials and Methods

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2.1 The analysis of bio-available heavy metals

The bio-available concentration of heavy metals (Ni2+, Cu2+, Co2+, Zn2+, and Pb2+) was

extracted using diethylenetriaminepentaacetic acid (DTPA)- triethanolamine (TEA)

solution consisting of 0.005 M DTPA with 0.01 M CaCl2 and 0.1 M triethanolamine

(Guo et al. 2018). Briefly, metals were extracted from a 10-gram air-dried sample in

50 ml of extracting solution for 30 mins (in triplicates). Each sample was then filtrated

through a 0.45 μm filter and metal concentrations measured using inductively coupled

plasma atomic emission spectroscopy (ICP-AES; Varian, Vista Pro).

2.2 The quantitative PCR (qPCR) for determining abundances of ARGs and

MGEs

The primers, annealing temperatures, and amplification protocols for all gene targets

are listed in the supplementary table (Table S2). The qPCR and plasmid constructions

were designed according to a previous protocol (Li et al. 2017) by using the

LightCycler 96 System (Roche, Mannheim, Germany). Briefly, the plasmids carrying

target genes were obtained from TA clones and extracted by using a TIAN pure Mini

Plasmid kit (Tiangen, Beijing, China). The standard plasmid concentrations (ng/mL)

were determined with the Nanodrop ND-2000 (Thermo Fisher Scientific,

Wilmington, USA) to calculate gene copy concentrations (copies/mL). The qPCR was

carried out in 96-well plates containing 10 μL of GoTaq qPCR Master Mix (Promega,

Madison, USA), 1.5 μL each of forward and reverse primers (4 mmol/L), 1 μL of

template genomic DNA and 6 μL of nuclease-free water. Each qPCR run began with

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2 min of initial denaturation at 95 °C, followed by 40 cycles of denaturation at 95 °C

for 30 s, annealing for 30 or 45 s according to the length of target at the primer-

specific annealing temperature, and extension for 30 s at 72 °C. For each qPCR run

conducted in 96-well plates, two blanks including negative and positive control

(without DNA template and with primers in DNA-free water, respectively) were

included. The amplification efficiencies of different PCR reactions ranged from 90%

to 110% with R2 values higher than 0.99 for all standard curves. Each reaction was

run in triplicate along with standard curves and controls.

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Fig. S1 Changes in the absolute and relative abundances of different ARGs and MGEs during

hyperthermophilic composting of TFR waste. Panels in column (a): absolute target gene

abundances based on gene copy numbers per gram of dry sample; Panels in column (b):

relative target gene abundances standardized with 16S rRNA gene copy numbers. In all

4

panels, bars denote for 1 standard error of mean.

Fig. S2 Relationships between MGE and total ARG abundances. All target gene abundances

are shows as absolute abundances after logarithmic (Log10) transformation.

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Fig. S3 Changes in bacterial community composition, total bacterial abundances and diversity

during the early and late phases of hyperthermophilic composting based on OTUs. Panel (a):

PCoA analysis showing differences in bacterial community composition between initial TFR and

early and late phase composting samples. Panel (b-d): The abundance, richness and diversity of

bacterial communities between initial TFR and early and late phase composting samples. One star

(*): significant at P < 0.05, Two star (**): significant at P < 0.01.

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Fig. S4 Taxonomic cladogram based on linear discriminant analysis (LDA-score > 3.5)

combined with effect size measurements (LEfSe) classifying discriminative taxonomic

differences between early (red symbols) and late (green symbols) phases of

hyperthermophilic composting. Moving from the inside outwards, cladograms depict taxa at

domain, phylum, class, order, family, and genus levels. Taxa with non-significant differences

are represented in yellow and the diameter of symbols is proportional to their relative

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abundances.

Fig. S5 Procrustes analysis showing relationships between ARGs, MGEs and their associated

bacterial abundances. Panel (a): correlations between ARGs (relative abundance) and their

associated bacterial taxon abundances (M2= 0.5537, R = 0.6681, P = 0.0017, 999

permutations). (b): correlations between MGEs (relative abundance) and their associated

bacterial taxon abundances (M2= 0.6940, R = 0.5531, P = 0.0185, 999 permutations).

Different colors and numbers (D0-D31) represent different sampling days during the

composting.

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Fig. S6 Procrustes analysis showing relationships between different individual ARGs, MGEs

and their associated bacterial abundances. Panel (a): the correlation between four ARGs

(tetracycline, sulfonamide, aminoglycoside and macrolide) and their associated bacterial

taxon abundances (all P < 0.05, 999 permutations). (b): Correlation analysis between different

types of MGEs (plasmids, integrons and transposon) and their associated bacterial taxon

abundances (all P < 0.05, 999 permutations). All panels are based on relative target genes

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abundances.

Fig. S7 The abundance of potential ARG hosts (left side of the panel) at genus level during

hyperthermophilic composting. The legend at the right side of the panel indicate the relative

taxa abundances associated with ARGs based on total bacterial 16S rRNA gene sequences.

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Fig. S8 Number of total culturable resistant bacterial strains isolated from early and late phase

composting samples.

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Fig. S9 Canonical correspondence analysis (CCA) showing the effect of different factors on

the absolute ARG abundances. Different symbols denote for composting properties (blue

arrows), MGEs (red arrows), heavy metals (green arrows) and bacterial community

composition (asterisk). The percentage of variation explained by each axis is shown in

parentheses on both axes. All relationships are significant (P < 0.05) based on 999

permutations used the Mantel test (Table S5). Abbreviations next to arrows denote for: TN:

total nitrogen; TC: total carbon; C/N: the ratio of total carbon and total nitrogen; WC: water

content; EC: electrical conductivity; Tylosin: the concentration of residual tylosin. D0-D31

refer to different sampling days during the composting.

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Table S1 Physico-chemical properties of raw materials used for composting (OM: organic matter;

TN: total nitrogen; TP: total phosphorus; TK: total potassium; carbon; C/N: the ratio of total

carbon and total nitrogen)

Parameters Raw materials Compost

Tylosin fermentation waste Rice husk mixture

Weight (t) 17 4 21

Moisture (%) 70.20 15.00 55.40

pH 8.50 - 7.90

OM (%) 64.70 72.80 59.30

TN (%) 6.40 0.84 5.60

TP (%) 2.60 0.23 2.15

TK (%) 1.10 1.30 1.20

C/N 10.52 56.21 19.35

Tylosin content (mg/kg) 113.20 - 85.0

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Table S2. PCR primers used for targeting the antibiotic resistance genes (ARGs), mobile genetic elements (MGEs) and bacterial 16s rRNA gene.

Antibiotic GeneAnnealing

temp. (°C)

Annealing

time (s)

Amplicon

length (bp)Forward Primers (5'-3') Reverse Primers (5'-3')

Tetracycline

tetA 61 30 210 GCTACATCCTGCTTGCCTTC CATAGATCGCCGTGAAGAGG

tet B 63 30 151 GGCAGGAAGAATAGCCACTAA AGCGATCCCACCACCAG

tetC 68 30 207 GCGGGATATCGTCCATTCCG GCGTAGAGGATCCACAGGACG

tetG 60 45 468 GCTCGGTGGTATCTCTGCTC AGCAACAGAATCGGGAACAC

tetL 55 30 267 TCGTTAGCGTGCTGTCATTC GTATCCCACCAATGTAGCCG

tetM 55 30 171 ACAGAAAGCTTATTATATAAC TGGCGTGTCTATGATGTTCAC

tetQ 63 30 169 AGAATCTGCTGTTTGCCAGTG CGGAGTGTCAATGATATTGCA

tetO 60 45 515 GATGGCATACAGGCACAGACC GCCCAACCTTTTGCTTCACTA

tetM 55 30 171 ACAGAAAGCTTATTATATAAC TGGCGTGTCTATGATGTTCAC

tetW 64 30 168 GAGAGCCTGCTATATGCCAGC GGGCGTATCCACAATGTTAAC

tetX 55 45 468 CAATAATTGGTGGTGGACCC TTCTTACCTTGGACATCCCG

Macrolide

ermB 58 30 364 GATACCGTTTACGAAATTGG GAATCGAGACTTGAGTGTGC

ermF 50 45 465 CGGGTCAGCACTTTACTATTG GGACCTACCTCATAGACAAG

ermT 51 30 369 CATATAAATGAAATTTTGAG ACGATTTGTATTTAGCAACC

ermM 56 30 306 TCTAGCAATGAGAATGAAGGT ACTATAACGTGATGGTTGGGAGGGA

ermX 61 45 488 GAGATCGGRCCAGGAAGC GTGTGCACCATCGCCTGA

mefA 54 30 348 AGTATCATTAATCACTAGTGC TTCTTCTGGTACTAAAAGTGG

ereA 56 45 466 AACACCCTGAACCCAAGGGACG CTTCACATCCGGATTCGCTCGA

Aminoglycosid

e

aacA4 65 45 482 TTGCGATGCTCTATGAGTGGCTA CTCGAATGCCTGGCGTGTTT

aadA 58 30 276 AAATTCTTCCAACTGATCTGCG CCTGAACAGGATCTATTTGAGGC

aadB 58 30 175 TGGTGGTACTTCATCGGCATA GTTACTTGACTGCGAACCTGCT

aadE 58 30 143 GATCTTACCTTATTGCCCTTGGA GCGCTTGGCTTTCTTACATG

aphA1 55 45 500 AAACGTCTTGCTCGAGGC CAAACCGTTATTCATTCGTGA

strA 55 45 546 CCTGGTGATAACGGCAATTC CCAATCGCAGATAGAAGGC

strB 56 45 509 ATCGTCAAGGGATTGAAACC GGATCGTAGAACATATTGGC

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Sulfonamide

sul1 55 30 158 CACCGGAAACATCGCTGCA AAGTTCCGCCGCAAGGCT

sul2 60 30 190 CTCCGATGGAGGCCGGTAT GGGAATGCCATCTGCCTTGA

sul3 58 30 143 CCCATACCCGGATCAAGAATAA CAGCGAATTGGTGCAGCTACTA

Mobile genetic

element

Inti1 55 30 280 CCTCCCGCACGATGATC TCCACGCATCGTCAGGC

intI2 56.5 30 164 GTTATTTTATTGCTGGGATTAGGC TTTTACGCTGCTGTATGGTGC

ISCR1 60 45 475 ATGGTTTCATGCGGGTT CTGAGGGTGTGAGCGAG

IncQ oriV 57 45 436 CTCCCGTACTAACTGTCACG ATCGACCGAGACAGGCCCTGC

Tn916/154

550 30 142 GACAGTATTAAGCCATCAGAC TCTTCCGAACACAATCATCT

16S rRNA gene 16S 55 30 193 CCTACGGGAGGCAGCAG TTACCGCGGCTGCTGGCAC

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Table S3. The occurrence of ARGs and MGEs on plasmid DNA among culturable resistant isolates

　 Isolate Identification tetA tetL tetX sul1 aacA4 aadA aadB aadE aphA1 ermB ermF ermM ermT intI1 ISCR1 IncQNo.of ARGs

and MGEsNo.of ARGs

Detection

rates (%)

Early

phase

e1 Staphylococcus lentus 　 1 　 1 　 　 　 1 　 1 　 　 1 　 1 1 7 5 15.15

e2 Bacillus sp. 1 　 1 　 　 　 　 1 　 　 1 　 　 　 　 　 4 4 12.12

e3 Bacillus flexus 1 　 　 　 1 1 　 　 1 　 1 　 1 　 1 1 8 6 18.18

e5 Bacillus sp. 　 　 1 　 　 　 　 　 　 　 　 1 　 　 　 　 2 2 6.06

s1 Bacillus cereus 1 1 　 　 1 　 　 　 　 1 1 　 　 　 　 　 5 5 15.15

s4 Bacillus anthracis 1 　 1 　 　 　 　 　 　 1 　 1 　 　 1 1 6 4 12.12

g2 Alcaligenes sp. 　 　 　 　 　 1 1 　 1 　 1 　 　 　 1 　 5 4 12.12

g5 Vagococcus sp. 1 1 1 1 1 　 1 1 　 1 1 　 1 1 　 1 12 10 30.30

g7Saccharopolyspora

hordei 1 　 　 1 1 1 1 1 　 1 1 　 　 　 1 1 10 8 24.24

t1 Paenibacillus cineris 　 　 　 　 1 　 　 　 　 　 　 　 1 　 　 　 2 2 6.06

Late

phase

s1 Staphylococcus lentus 1 　 　 　 　 　 　 　 　 　 　 　 　 　 　 　 1 1 3.03

s2 Staphylococcus lentus 　 　 1 　 　 　 　 　 　 　 　 　 1 1 　 　 3 2 6.06

e2 Staphylococcus lentus 　 1 1 1 1 　 　 1 　 　 　 　 　 　 　 　 5 5 15.15

t1 Staphylococcus lentus 　 　 　 　 　 　 　 1 　 　 1 　 　 　 　 　 2 2 6.06

t2 Alcaligenes faecalis 　 1 　 　 　 1 　 　 　 　 　 　 1 1 　 1 5 3 9.09

t3 Alcaligenes faecalis 1 1 　 1 　 　 　 　 　 　 　 　 　 　 1 　 4 3 9.09

g1 Staphylococcus lentus 　 　 　 1 　 　 　 　 　 　 　 　 　 　 　 　 1 1 3.03

g3 Alcaligenes faecalis 　 　 　 1 　 1 　 　 　 　 　 　 　 　 　 　 2 2 6.06

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Table S4. Detection the ARGs and MGEs occurrence on the genomic DNA among culturable resistant isolates

　 Isolate

Identification

tetA tetG tetL tetM tetX sul1 sul2 aacA4 aadA aadB aadE aphA1 ermB ermT ermX intI1 Tn916

No. of

ARGs and

MGEs

No. of

ARGs

Detection

rates

(%)

Early

phase

e1 Staphylococcus lentu 　 　 　 　 　 　 　 1 　 　 　 1 1 　 　 　 　 3 3 9.1

e2 Bacillus sp. 　 　 　 　 　 1 1 1 1 　 1 　 1 　 1 1 　 8 7 21.2

e3 Bacillus flexus 1 　 　 　 　 1 　 　 1 　 　 1 1 　 1 1 1 8 6 18.2

e5 Bacillus sp. 　 　 　 　 　 　 　 　 　 1 　 　 　 　 　 1 　 2 1 3.0

s1 Bacillus cereus 　 1 　 　 　 1 1 　 1 　 　 1 1 1 1 1 　 9 8 24.2

s4 Bacillus anthracis 　 　 　 　 　 　 　 1 　 　 　 　 　 　 　 　 1 2 1 3.0

g2 Alcaligenes sp. 　 　 1 　 　 　 　 　 　 　 　 1 　 1 　 　 　 3 3 9.1

g5 Vagococcus sp. 1 　 1 　 1 1 　 　 1 　 1 　 　 　 1 1 　 8 7 21.2

g7 Saccharopolyspora hordei 　 　 　 　 　 　 1 　 　 1 　 　 　 　 　 　 　 2 2 6.1

t1 Paenibacillus cineris 1 　 　 　 　 1 　 　 　 　 　 1 1 　 　 1 　 5 4 12.1

Late

phase

s1 Staphylococcus lentus 　 　 　 　 　 　 　 　 　 　 1 　 1 　 　 　 　 2 2 6.1

s2 Staphylococcus lentus 　 　 　 　 　 　 　 　 　 　 　 1 　 　 　 1 　 2 1 3.0

e2 Staphylococcus lentus 　 　 　 　 　 　 　 　 　 　 　 　 　 1 　 　 1 2 1 3.0

t1 Staphylococcus lentus 1 　 　 　 　 　 1 　 　 　 　 1 　 　 　 　 　 3 3 9.1

t2 Alcaligenes faecalis 　 　 1 　 　 　 　 1 1 1 　 　 　 　 　 　 　 4 4 12.1

t3 Alcaligenes faecalis 　 　 　 1 　 　 　 　 1 　 1 　 1 1 　 　 1 6 5 15.2

g1 Staphylococcus lentus 　 1 　 　 　 　 　 　 　 　 　 1 　 　 　 　 　 2 2 6.1

g3 Alcaligenes faecalis 　 　 　 　 　 　 　 　 1 　 　 1 　 　 　 　 1 3 2 6.1

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Table S5. Mantel test for significant relationships between different factors

Factors R2 P-avlue Signif. CodesTylosin 0.9578 0.001 ***MGEs 0.8745 0.001 ***TOC 0.6042 0.002 **NO3

- 0.5248 0.004 **EC 0.8618 0.001 ***WC 0.8732 0.001 ***TN 0.4338 0.016 *TC 0.4393 0.008 **C/N 0.8005 0.001 ***Ni2+ 0.642 0.002 **Cu2+ 0.7715 0.001 ***Co2+ 0.6572 0.001 ***Zn2+ 0.7528 0.001 ***Pb2+ 0.7482 0.001 ***

Euryarchaeota 0.5027 0.015 *Chloroflexi 0.7786 0.002 **Firmicutes 0.9061 0.001 ***

Proteobacteria 0.6973 0.002 **Thermi 0.7041 0.005 **

Signif. codes: ***<0.001; **<0.01 and *<0.05. TOC: total organic carbon content; EC:

electrical conductivity; WC: water content; TN: total nitrogen; TC: total carbon; C/N: the ratio of total carbon and total nitrogen

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