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
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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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