Journal Pre-proof Autoinducer-2 influences tetracycline resistance in Streptococcus suis by regulating the tet(M) gene via transposon Tn916
Baobao Liu, Li Yi, Jinpeng Li, Yuxin Wang, Chenlong Mao, Yang Wang PII:
S0034-5288(19)30488-6
DOI:
https://doi.org/10.1016/j.rvsc.2019.12.007
Reference:
YRVSC 3936
To appear in:
Research in Veterinary Science
Received date:
14 May 2019
Revised date:
31 October 2019
Accepted date:
3 December 2019
Please cite this article as: B. Liu, L. Yi, J. Li, et al., Autoinducer-2 influences tetracycline resistance in Streptococcus suis by regulating the tet(M) gene via transposon Tn916, Research in Veterinary Science (2019), https://doi.org/10.1016/j.rvsc.2019.12.007
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© 2019 Published by Elsevier.
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Autoinducer-2 influences tetracycline resistance in Streptococcus suis by regulating the tet(M) gene via transposon Tn916 Baobao Liua,b#, Li Yic#, Jinpeng Lia,b, Yuxin Wanga,b, Chenlong Maoa,b, Yang Wanga,b,* a
College of Animal Science and Technology, Henan University of Science and
Technology, Luoyang 471003, China Key Laboratory of Molecular Pathogen and Immunology of Animal of Luoyang,
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b
Luoyang 471003, China
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College of Life Science, Luoyang Normal University, Luoyang 471023, China
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#These authors contributed equally to this study
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c
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Running title: Autoinducer-2 influences tetracycline resistance
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Corresponding author at: College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China E-mail addresses:
[email protected](Yang Wang)
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Abstract The concern over increasing resistance to tetracyclines (TCs), such as tetracycline and chlortetracycline, necessitates exploration of new approaches to combating infection in antimicrobial therapy. Given that bacteria use the chemical language of autoinducer 2 (AI-2) signalling molecules in order to communicate and
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regulate group behaviors, we asked whether the AI-2 signalling influence the tetracyclines antibiotics susceptibility in S. suis. Our present work demonstrated that
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MIC increased when exogenous AI-2 was added, when compared to the wild type
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strain. When grown in the presence of sub-MIC of antibiotics, it has been shown that
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exogenous AI-2 increases growth rate and biofilm formation. These results suggest
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that the TCs resistance in S. suis could involve a signaling mechanism. Base on the
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above observations, transcriptomic analyses showed significant differences in the expression of tet(M) of tetracyclines resistance genes, as well as differences in Tn916
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transposon related genes transcription, as judged by RT-PCR. Our results provide strong evidence that AI-2 signalling molecules is may involve in TCs antibiotic resistance in S. suis by regulating tet(M) gene via Tn916 transposon. This study may suggest that targeting AI-2 signaling in bacteria could represent an alternative approach in antimicrobial therapy. Keywords: Autoinducer-2; tetracyclines antibiotic; resistance; tet(M) gene; Tn916 transposon; Streptococcus suis
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1. Introduction Streptococcus suis is a zoonotic pathogen affecting pigs and people exposed to/infected by pigs or contaminated pork products and the numbers of human S. suis infections worldwide has significantly increased in recent years (Kerdsin et al., 2018; Lun et al., 2007; Rajahram et al., 2017; Tsai et al., 2005). The tetracycline group of
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antibiotics, such as tetracycline and chlortetracycline, are among the most effective antibiotics to treat of S. suis infections, consequently, this has contributed to the
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increase in TCs resistance in S. suis (Hendriksen et al., 2008; Oh et al., 2017).
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Antimicrobial resistance is a major threat for the effective control of infectious
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diseases. Tetracyclines (TCs) are broad-spectrum alkaline antibiotics which inhibit
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protein synthesis by their effect on the 30S ribosomal subunit (Rose and Rybak, 2006).
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TCs resistance in bacteria, both Gram-negative and -positive, is mostly caused by a large group of efflux proteins, e.g. TetA to TetL and by another group of proteins,
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including TetM to TetW, which are responsible for actively blocking the tetracycline target site in the 30S ribosomal subunit (Lopez et al., 2008; Wang et al., 2016). There is little study so far on the tetracycline resistance mechanism of S. suis, and when taking into account TCs resistance is getting more common and more serious infections are caused by S. suis, it is something that needs to be addressed in order to explore alternative approaches in antimicrobial therapy. The recognition that bacteria use a chemical language of signaling molecules in a process called quorum-sensing (QS), has led to a new understanding of bacterial behavior in response to their environment (Diggle et al., 2007; E et al., 2018). Many
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QS signals are species specific, however, production of, and responses to one molecule, autoinducer-2, are observed throughout the bacterial kingdom suggesting that it may mediate communication among and between species (Brackman et al., 2009; Wang et al., 2018). Our research shows that exogenous AI-2 acts as a concentration-dependent signaling molecule to regulate S. suis biofilm formation,
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host-cell adherence, and transcription levels of many virulence genes (Wang et al., 2013, 2014; Wang et al., 2011a; Wang et al., 2011c). Recently, the presence of AI-2
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has been associated with antibiotic resistance (Evans et al., 2018; Kroger et al., 2016;
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Lai et al., 2017; Schroeder et al., 2017). Inactivation or denaturation of the signal
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molecule itself is the most basic way to prevent bacterial resistance and to study new
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antibacterial strategies. Yu (Yu et al., 2018) and others reported that exogenous
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imidazole, a furan carbocyclic analogue of AI-2, reduced the antibiotic resistance of clinical E. coli strains to β-lactam antibiotics by inhibiting the function of AI-2.
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Ahmed et al indicate that AI-2 communication is associated with erythromycin and ampicillin susceptibility in S. anginosus, which may present a novel approach in antimicrobial therapy (Ahmed et al., 2007). Our overall goal is to investigate whether AI-2 signaling can influence antibiotic resistance of S. suis. Here, we show that a signaling mechanism associated with the AI-2 molecule may be able to influence TCs resistance in S. suis. 2. Materials and methods 2.1 Bacterial strains and antibiotics The wild-type strain of S. suis was isolated from S. suis infected pigs in the
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Jiangsu Province and was confirmed as a virulent strain (Yao et al., 1999). The bacterial cells were stored at -20℃. Before each experiment, the bacteria were cultured overnight in Tryptone Soya Broth (Soybean-Casein Digest Medium U.S.P). The AI-2 precursor molecule, DPD, was purchased from Omm Scientific Inc. (Dallas, TX) and performed at 3.9 µM (Our previous research data) (Xue et al., 2013). Tetracycline and chlortetracycline bulk drugs were purchased from the China Institute
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2.2 MIC and MBC determinations
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were prepared in advance and stored at −20℃.
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of Veterinary Drugs Control (Beijing, China). Antibiotic stock solutions (1280 μg/ml)
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The MICs of tetracycline and chlortetracycline were determined using the
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two-fold dilution method according to the Clinical and Laboratory Standards
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Institutes guidelines (CLSI, 2015). The MICs of antibiotics were performed in 96-well microplates (Costar 3599, Corning, NY, USA). Briefly, overnight cultures of
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S. suis were adjusted to 105 CFU/ml and 100 µl was added to each well. Serial dilutions of antibiotics were prepared in culture medium at a volume of 100 μl. To verify the association with AI-2 signaling and altered antibiotic resistance, the WT strain was supplemented with exogenous AI-2. The plates were incubated at 37 °C for 24 h. The MIC was defined as the lowest concentration of antibiotic that had no visible bacterial growth after overnight incubation. Minimum bactericidal concentrations (MBC) were determined at the end of the incubation period by removing 10 μL samples from each well without visible bacterial growth and putting them in TSB and after incubating for 24 h at 37°C, the MBC was defined as the
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lowest concentration of antibiotic required to kill 100% of the bacteria. 2.3 Growth Kinetics A single colony was used for subcultivation in TSB overnight at 37°C. The initial culture was diluted 100-fold in fresh TSB medium with no antibiotics, and then the TSB was supplemented with 5 μg/ml and 10 μg/ml of tetracycline or 2.5 μg/ml and 5
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μg/ml chlortetracycline. To examine the effect of AI-2, the WT strain was supplemented with exogenous AI-2. At the time points indicated, 1 ml samples were
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taken and the turbidity was measured at OD600 using a spectrophotometer (Multiskan
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FC, Thermo, China) with fresh TSB used as a blank.
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2.4 Biofilm Formation
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Biofilm formation under static conditions was measured using the microtiter
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plate assay based on the standard crystal violet method described in our previous report (Wang et al., 2011c). Briefly, 100 µl of fresh TSB with or without various
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concentrations of tetracycline (1.25, 2.5, 5, and 10 μg/ml) and chlortetracycline (0.625, 1.25, 2.5, and 5 μg/ml) were dispensed into 96-well microtiter plates. Overnight cultures of WT were diluted to an OD600 of 0.1 and inoculated into the plates with 100µl added to each well and incubated for 24h at 37℃. To investigate the effect of AI-2, the WT strain was supplemented with exogenous AI-2. After incubation, the supernatant and any unadhered bacteria were aspirated and the wells washed three times with 200 µl PBS. Adherent bacterial cells were stained with 200 µl crystal violet solution for 10min, washed with distilled water then dried at 37℃ for 30 min. The stain was then released by adding 200 µl of ethanol to each well. The absorbance
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of each well at 570nm was determined using a spectrophotometer (Multiskan FC, Thermo, China). All assays were performed in triplicate and repeated three times. 2.5 Time-kill curve assay The time-kill kinetics were determined for S. suis at 2×MBC and 4×MBC of Tetracycline and chlortetracycline for 24h. Antibiotic free cultures were used as a control. To assess the impact of AI-2, the WT strain was supplemented with
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exogenous addition of AI-2. The bacteria were added to each solution (1×107 CFU/ml,
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3ml), and incubated at 37°C with shaking. At predetermined time points (0, 2, 4, 6, 8,
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10, 12 and 14h), 10 μL of the samples were taken for bacteria counts. The colonies
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were counted only on plates that had between 30 and 300 colonies growing on them.
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2.6 RNA-seq analysis
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Three independent experiments were performed.
S. suis was grown for 8 h without or with exogenous AI-2. A total amount of 3µg
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RNA per sample was used as input material for the RNA sample preparations. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and paired-end reads were generated. The reference genome and gene model annotation files were downloaded from the genome website directly. Both building the index of the reference genome and aligning clean reads to the reference genome were performed using Bowtie2-2.2.3. HTSeqv0.6.1 was used to count read numbers mapped to each gene. Differential expression
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analysis of two conditions/groups (two biological replicates per condition) was performed using the DESeq R package (1.18.0). 2.7 Quantitative real-time reverse transcription PCR qRT-PCR was performed to validate the results of the RNA-seq. The specific primers used for the various genes are listed in Table 1, with 16S rRNA used as an
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internal control (Wang et al., 2011b). S. suis were grown in TSB for 8 h with or without AI-2. Total RNA was extracted using the TRIzol (CoWin Biosciences Co.,
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Ltd, Biejing, china) method and treated with DNase I (Promega, Madison, USA) to
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remove DNA contamination. cDNA synthesis was performed using the PrimeScript™
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Reagent kit (CoWin Biosciences Co., Ltd, Biejing, china) following the
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manufacturer’s directions. The real-time cycler conditions used have been described
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previously (Wang et al., 2011c). Amplification data were analyzed by the comparative critical threshold (2-ΔΔCT) method and are presented as total expression relative to that
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of the 16S rRNA gene. 2.8 Statistical analysis
The data were analyzed using the Graphpad Software package (GraphPad Software, La Jolla, CA). One-way analysis of variance (ANOVA) followed by the Dunnett’s multiple comparison test was used for biofilm formation and CFU count. Student t-tests were used for both biomass and RT-PCR analysis. Significance was accepted when the P value was <0.05.
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3. Results 3.1 Antibiotic Susceptibility The in vitro activities of tetracycline and chlortetracycline against S. suis with AI-2 are shown in table 2. MIC of leaves extract shows antimicrobial activity of tetracycline and chlortetracycline at 20 μg/ml and 10 μg/ml respectively against S.
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suis, however, MIC leaves increased when compared to the WT with the addition of exogenous AI-2. MBC values of tetracycline and chlortetracycline were generally
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3.2 Antibiotic effects on growth rate
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equal to, or two times greater than, the MIC values.
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To examine the effect of tetracycline and chlortetracycline on the growth of S.
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suis with and without AI-2 at sub-MIC levels, the bacterial growth rate was
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determined. According to the figure 1, the growth rate of S. suis strain with AI-2 was greater than of the S. suis cultured at the same concentration of tetracycline and
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chlortetracycline. The growth of S. suis was inhibited by 10 μg/ml of tetracycline (Fig. 1a) and 5 μg/ml of chlortetracycline (Fig. 1b), but cultures with AI-2 were not affected.
3.3 Antibiotics at sub-MICs increased biofilm formation by S. suis In the absence of antibiotics, the bacteria displayed an approximately 34% reduction in the level of biofilm formation compared to that of the S. suis with exogenous AI-2 (Fig. 2). The level of biofilm formation by the S. suis significantly increased in the presence of 1.25 to 10 μg/ml tetracycline and 0.625 to 5 μg/ml chlortetracycline (Fig. 2a and 2b).
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3.4 Time-kill curve studies Fig. 3 shows the viable bacteria counts after exposure to TSB with or without antibiotics for different timepoints at 37℃. In the absence of antibiotics, S. suis with and without exogenous AI-2 showed similar growths after incubation. However, following exposure to the antibiotics tetracycline and chlortetracycline, the S. suis
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without exogenous AI-2 displayed higher viable counts than those with it at 4 MBC for 4 h to 10 h (Fig. 3a and 3b). Viable counts indicated that S. suis were more likely
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to be killed at the same antibiotic concentration and time.
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3.5 Global gene expression analysis of AI-2-treated cells
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We performed transcriptomic analysis to examine the global effect of exogenous
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AI-2 on gene expression patterns in S. suis. AI-2 addition induced significant
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differences in the expression of four genes/operons in S. suis; a tetracyclines resistance gene tet(M), tetracyclines transposons gene Tn916, tetracyclines resistance
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relevant gene SSU05_0045, and SSU05_1355 (Table. 3). The differential expression of these genes was confirmed by qRT-PCR analysis and it was found that the transcription levels of all four genes was lower in S. suis with exogenous AI-2 (Fig. 4). 4. Discussion The autoinducer-2 has been proposed to be an interspecies metabolic-status signaling mechanism in bacteria which allows for adaptive regulation in response to environmental conditions (Galloway et al., 2011; Yadav et al., 2018). AI-2 controls a diverse array of traits in both nonpathogenic and pathogenic bacteria (Ascenso et al.,
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2011). In the previously study, we proposed that exogenous AI-2 acted as a concentration-dependent signaling molecule to regulate S. suis biofilm formation, host-cell adherence, and the transcription levels of many virulence genes (Wang et al., 2013, 2014). These findings confirm that AI-2 regulates bacterial function in S. suis, however, the precise link between this signaling molecule and antimicrobial resistance
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is not yet clear (Wang et al., 2018). Our work demonstrates that exogenous AI-2 increased S. suis resistance to tetracycline and chlortetracycline. Sub-MIC levels of
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antibiotics causes a significant increase in growth rate and biofilm formation when
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exogenous AI-2. This is in agreement with Xue et al (Xue et al., 2016). We also found
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that exogenous AI-2 resulted in an increase of the bactericidal effects of tetracycline
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and chlortetracycline compared to samples taken at the same concentration. These
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results suggest that antibiotic resistance could be attributed to a signaling mechanism associated with the AI-2 molecule.
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Based on these results, we want to further explore the specific mechanism of AI-2’s action on S. suis. We found changes in expression levels of tetracycline related resistance genes (SSU05_0045, tet(M), Tn916, and SSU05_1355) through transcriptomic analysis, which may also have an effect on tetracycline resistance. Xue et al. found that the addition of AI-2 affects tetracycline susceptibility, which may be mediated by a tetracycline resistance gene tet(M) (Xue et al., 2016). On this basis, we analyzed changes in expression of tetracycline resistance genes in S. suis after adding AI-2. We found that when AI-2 was added, the tetracycline resistance gene tet(M) was down-regulated, this was quantitatively verified by fluorescence.
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The AI-2 plays an important role in bacteria as a signal molecule, and the luxS gene is a gene for the production of AI-2 precursors, which involves the regulation of the LuxS/AI-2 quorum-sensing system. Our previous studies have shown that LuxS/AI-2 system is involved in fluoroquinolones susceptibility in S. suis (Wang et al., 2019). The WT strain was also less susceptible to enrofloxacin and norfloxacin in
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the presence of AI-2. This is consistented with the findings of this paper and proved in Streptococcus intermedius by Ahmed et al. (Ahmed et al., 2009). Our research shows
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that bacteria with AI-2 are more likely to be killed after the addition of high
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concentrations of antibiotics, which has been studied with Xue et al (Xue et al., 2013)
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(Lu et al., 2005). Our transcriptome analyses found that when it was added to AI-2 for
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8 hours, the expression of its resistance gene was down-regulated, which is similar to
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the study of Zhang et al (Xue et al., 2013; Zhang et al., 2018). Our Previous studies have shown that AI-2 produces different levels at different culture times (Wang et al.,
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2013), which contribute to this results. In addition to, bacterial resistance is produced, which is manifested by increased MIC value, including specific resistance with drug resistance gene expression and efflux pump activity, and non-specific drug resistance factors, with biofilm formation ability and cell permeability increase. These complex factors contribute to bacterial resistance. The AI-2, as a signal molecule, is affected by concentration and environment. We focus on the possible regulation mechanisms of this signal molecule and antibiotic resistance and provide a better direction for its regulation function. In Tn916, tetracycline activate the transfer of the element through an
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anti-attenuation mechanism that relies on the Tet(M) resistance protein, itself encoded by the element (Scornec et al., 2017). AI-2 signal molecules can interfere with Tn916 regulation. These events may affect the number of tet(M) copies, contributing tetracycline resistance (Leon-Sampedro et al., 2019). In addition, proposed model for the involvement of autoinducer-2 system in tetracyclines antibiotic resistance by regulating tet(M) gene via Tn916 transposon in S. suis was shown Figure 5.
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In conclusion, our findings provide strong evidence that AI-2 signalling
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molecules is may involve in TCs antibiotic resistance in S. suis by regulating tet(M)
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gene via Tn916 transposon. This study may suggest that targeting AI-2 signaling in
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bacteria could represent an alternative approach in antimicrobial therapy.
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Conflicts of interest No conflict of interest declared
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Acknowledgments
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Figure Legends.
Fig. 1 The growth curves (measured as optical density at 600 nm, OD 600) of WT and strain S. suis cultured with 3.9 µM autoinducer 2 (AI-2) under different antibiotic conditions: (a) tetracycline, (b) chlortetracycline. Error bars indicate standard deviations. The results represent a mean of 3 independent experiments; *P <
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0.05, indicating a difference between antibiotic alone and antibiotic + AI-2.
Fig. 2 Biofilm formation in the presence of (a) tetracycline, (b) chlortetracycline. The wild-type (WT) and the wild-type with exogenous 3.9 µM AI-2 (WT + AI-2) following 24h of incubation in the presence of tetracycline and chlortetracycline. The
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Fig. 3 Time-kill kinetics of S. suis in TSB broth supplemented with (a)
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tetracycline and (b) chlortetracycline at given concentrations. Colony counts
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AI-2) following 24 h of incubation at 37 ℃. The data points represent mean values
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Fig. 4 Relative expression of SSU05_0045, tet(M), Tn916, and SSU05_1355 by WT and S. suis with or without AI-2 was quantitated by qRT-PCR. The 16S rRNA as an internal standard. Data are total expression relative to 16S rRNA (mean ± the standard deviation of three independent experiments). *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001 (Student’s unpaired t test).
Fig. 5 Proposed model for the involvement of autoinducer-2 system in tetracyclines antibiotic resistance by regulating tet(M) gene via Tn916 transposon in S. suis. (a) In the presence of high concentrations of AI-2, a product of the luxS
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gene, the binding of AI-2 to its cell surface receptors (unknow in S. suis) is followed by signaling cascades resulting in the regulation of tet(M) gene. Tetracyclines antibiotic resistance mechanism in S. suis (a: Ribosomal protection protein). (b) A
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schematic representation of Tn916.
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Table 1. Primers used for the quantitative RT-PCR analysis Genes Primer sequence tet(M)-1 GGGGA TTCCC ACAAT CTTTT tet(M)-2 ACATC CCATG CTCAG GTTC Tn916-1 TATCT CCGTC TTCCG CAGTT Tn916-2 CTGCA TAATA GGCAC GCTCA SSU05_0045-1 TCGGT ATGAA ACAAC GGACA SSU05_0045-2 TGGAA ATTTG TCGCT CACTG SSU05_1355-1 GCGAT AAGGC TCAGC AGAAG SSU05_1355-2 TCAAG GGGAC ACTTC CTTCA 16sRNA-1 GTTGC GAACG GGTGA GTAA 16sRNA-2 TCTCA GGTCG GCTAT GTATC G
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Table 2. Susceptibility of S. suis to tetracycline and chlortetracycline. MIC(μg/ml ) MBC(μg/ml ) Antibiotic a b WT WT+AI-2 WT a WT+AI-2 b tetracycline 20 40 40 40 chlortetracycline 10 20 20 20 a WT = wild-type strain b WT + AI-2 = wild-type strain with exogenous 3.9 µM AI-2
Table 3. Differential gene expression in S. suis relative to that in S. suis with AI-2. Gene ID and name SSU05_0045
Description log2 (fold change) P-value multidrug ABC transporter -1.5204 0.00059314 ATPase SSU05_0922 tet(M) translation elongation -0.66924 0.00011413 factor (GTPases) SSU05_0930 Tn916 Tn916%2C transcriptional -1.9481 0.00065636 regulator SSU05_1355 ABC transporter ATPase -1.0611 0.002259 Differential gene expression was determined by RNA-seq analysis as described in Materials and Methods. Data shown are fold changes in gene expression for the comparisons indicated. Only genes with statistically significant differential expression (adjusted P ≤ 0.05) are shown, except where indicated otherwise.
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Highlights Bacteria use autoinducer 2 (AI-2) signalling molecules regulate bacteria behaviors
AI-2 signalling molecules influences tetracyclines resistance in Streptococcus suis
This regulation mechanism achieved by regulating tet(M) gene via Tn916 transposon
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