Multidrug Efflux System-mediated resistance in Staphylococcus aureus under a One Health approach

doi:10.21203/rs.3.rs-2375347/v1

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Multidrug Efflux System-mediated resistance in Staphylococcus aureus under a One Health approach

https://doi.org/10.21203/rs.3.rs-2375347/v1

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published 08 Nov, 2023

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The aim of the study was to track the spread of antimicrobial resistance among the different sectors of One Health through the detection of Multidrug-Efflux-System in multidrug-resistant Staphylococcus aureus isolates. Multidrug-resistant (MDR) and methicillin-resistant (MRSA) S. aureus isolates were selected: 25 of human, one of animal and eight of food origin. The efflux system genes norA, norB, norC, LmrS, tet38 and msrA were screened by PCR. The activity of the efflux systems was determined by the minimum inhibitory concentration (MIC) of tetracycline and ciprofloxacin in the presence and absence of CCCP and in the quantification of ethidium bromide efflux. Furthermore, biofilm formation was determined in the presence and absence of the CCCP. The molecular epidemiology of the isolates was traced with the aid of PFGE. The gene norC was the most prevalent, detected in all isolates and msrA was the least prevalent, detected in only two isolates from humans. There was no difference in the MICs of tetracycline and ciprofloxacin in the presence of CCCP, but 55.9% of isolates showed ethidium bromide efflux. The presence of CCCP decreased the biofilm formation. Regarding the molecular epidemiology, in three clusters was a mixture of the isolates from different origins. Therefore, S. aureus MDR with active multidrug efflux systems are circulating between One Health domains and it is necessary to consider strategies to decrease this circulation in order to prevent the dissemination of resistance mediated by MES.

antibiotic resistance

genetic characterization

Gram-positive

One Medicine

It is well known that antimicrobial resistance (AMR) threatens the environment, animal health and public health (Council of Canadian Academies 2019). Resistant microorganisms can be transmitted between animals and humans through direct contact or contaminated food; therefore, to contain them effectively, a well-coordinated approach is needed in humans and animals (WHO 2017). In this regard, the One Health approach, defined as “an integrated and unifying approach that aims to sustainably balance and optimize the health of people, animals and ecosystems, recognizing that the health of humans, domestic and wild animals, plants and the environment are closely linked” (WHO 2021), is essential to investigate mechanisms for the spread of antimicrobial resistance.

Staphylococcus aureus is an important opportunistic pathogen in humans and one of the most important pathogenic species of Staphylococcus in veterinary medicine. Still, S. aureus is one of the main causal agents of food poisoning associated with the consumption of raw milk cheese (Castro et al. 2020). S. aureus develops resistance to antimicrobials by different mechanisms. These mechanisms include drug absorption limitation, drug target modification, drug enzymatic inactivation, and active efflux (Yılmaz and Özcengiz 2017). Thus, diseases associated with this bacterium continue to be a threat to human and animal health (Antiabong et al. 2017).

Multidrug efflux systems (MES) prevent the accumulation of drugs within the bacterium through active transport systems that transport toxic substances, such as antimicrobials, to the extracellular medium (Li and Nikaido 2009). According to Shamkhi et al. (2019), SEM plays a vital role in antimicrobial multidrug resistance (MDR) in S. aureus., with MDR defined as non-susceptibility to at least one agent in three or more antimicrobial categories (Magiorakos et al. 2012). Evidence suggests that MES also play a role in biofilm formation (Alav et al. 2018), which is a sessile community characterized by cells that are irreversibly attached to a substrate, interface or to each other and are embedded in a matrix of substances and self-produced extracellular polymers. Biofilms exhibit an altered phenotype in relation to growth rate and gene transcription (Soto 2013).

The study of resistant microorganisms must encompass a range of factors, including the evolution of resistance at the molecular level within a given organism, transmission mechanisms and pathways between organisms, and spread between human and animal hosts and throughout the environment (Samreen et al. 2021).

Thus, the objective of the study was to track the spread of antimicrobial resistance among the different sectors of One Health through the detection of MES in Staphylococcus aureus isolated from animals, food, humans and the environment.

Selection of bacterial isolates and multiplication conditions

Multidrug-resistant Staphylococcus aureus isolates obtained from humans, food and animals belonging to different bacterial libraries of partner research laboratories were selected (Table 1). Information on the antimicrobial resistance of human and food isolates is summarized in Fig. 1. The animal isolate (St 754) was resistant to oxacillin, ciprofloxacin, erythromycin and tetracycline. All isolates selected for the study are methicillin resistant (MRSA).

TABLE 1 HERE

All isolates were reactivated in Brain Heart Infusion broth (BHI, Himedia) and then frozen using 20% glycerol as cryoprotectant. All isolates were stored at -80ºC and reactivated in broth by overnight incubation at 37ºC before testing.

FIGURE 1 HERE

Species confirmation was performed by PCR for the nuc gene, using the primers nuc–1 5'-GCGATTGATGGTGATACGGTT-3' and nuc–2 5'-AGCCAAGCCTTGACGAACTAAAGC-3' (Yang et al. 2007).

Chemical reagents

The proton decoupler carbonyl cyanide m-chlorophenylhydrazone (CCCP), the ethidium bromide dye and the antimicrobials ciprofloxacin and tetracycline were purchased from Sigma-Aldrich Brazil.

Molecular detection of multidrug efflux systems

The PCR technique was used to confirm the species of the isolates and detect the genes of the multidrug efflux systems. Genomic DNA extraction was performed using the Wizard® Genomic DNA Purification Kit (Promega) following the manufacturer's instructions. Amplification reactions were conducted for each isolate in a 25 µL reaction mixture containing 12.5 µL of GoTaq® Green Master Mix (Promega), 20 µmol of each primer, 2 µL of genetic material and 6.5 µL of nuclease free water. The reaction mixture was subjected to thermocycling. At the end, the reaction product was separated via electrophoresis run at 75 V on a 1% agarose gel stained with UniSafe Dye® (Uniscience). The gels were visualized under UV light and photodocumented using the L-Pix EX. The size of the amplicons was estimated by comparison to a 50 bp molecular weight standard.

The genes researched, primers used, product size, controls used and references are specified in Table 2. The control used in the norA, norC, lmrS and tet38 reactions was the isolate S. aureus 4c (Lima et al. 2020). For norB and msrA genes, the size of the amplicon formed was used as a control.

TABLE 2 HERE

Phenotypic detection of multidrug efflux systems

The isolates confirmed as S. aureus and which presented genes related to the MES were phenotypically characterized through evaluation of the minimum inhibitory concentration in the absence and presence of CCCP and through the quantification of the ethidium bromide efflux to verify the SEM activity by the isolates.

Minimum Inhibitory Concentration (MIC)

Minimum Inhibitory Concentrations (MICs) of ciprofloxacin and tetracycline were determined in the presence and absence of CCCP (efflux system inhibitor). These antimicrobials were chosen because of the large number of isolates that are resistant to them and which had SEM genes related to their efflux (Fig. 1 and 3). MICs were determined in a 96-well microtiter plate by broth microdilution as per CLSI guidelines (2018) using a final inoculum of 5x10⁵ CFU/mL after the overnight reactivation of isolates at 37 °C. The MIC test was performed in duplicate and repeated three times, with the MIC being considered the lowest concentration capable of inhibiting bacterial multiplication, comparing the results to the controls.

Efflux quantification

Ethidium bromide dye was used according to the protocol described by Kaatz et al. (2000) with some modifications. For the assay, S. aureus isolates were cultured overnight in BHI broth. The culture was diluted to an OD₆₆₀ of 0.7 to 0.8 and allowed to stand at room temperature for 20 minutes. Then the OD₆₆₀ was adjusted to 0.4 with BHI broth containing CCCP (100 µM) and ethidium bromide (10 µg/mL). The cultures were left to rest for one hour at room temperature to allow loading of the bacteria with ethidium bromide. After incubation, 400 µL of the culture was pelleted (4000 rpm/5 min), the supernatant discarded, and then resuspended in 400 µL of phosphate-buffered saline (PBS) pH 7.2. Subsequently, 50 µL of the culture was distributed in 500 µL microtubes that already contained 50 µL of PBS, 50 µL of BHI with CCCP or 50 µL of glucose (1M), with one duplicate per treatment. The fluorescence of the suspension was monitored by acquisition for 60 cycles of 10 seconds in a Rotor-Gene Q thermocycler (Qiagen), using the excitation and emission wavelengths of 530 and 610 nm, respectively.

Biofilm in the presence of CCCP

Biofilm formation by S. aureus isolates in the presence and absence of CCCP was evaluated to verify the influence of MES on its formation. Biofilms were evaluated for the amount of biomass formed and the viability. The planktonic growth of the isolates submitted to the same treatments was also analyzed. Furthermore, the isolates were classified according to biofilm formation.

To represent planktonic growth, the isolates were cultured with Tryptic Soy Broth (TSB) with or without CCCP (0.78 µL/mL). Single colonies were cultured at 37 °C overnight (18-20 h) to prepare a standard inoculum of 10⁸ CFU/mL. Then, the cultures were diluted 1/20 in 3 mL of TSB, and 100 µL of the dilutions were distributed in 96-well microtiter plates, where the wells were made up to 200 µL with sterile TSB (107 CFU/mL/ pit). An uninoculated well served as a sterile control. The isolates were inoculated in triplicate, and incubated under shaking (100-150 rpm) at 37 °C. After 24 hours, optical density measurements were performed at 550 nm in a plate reader spectrophotometer.

For biofilm cell viability tests and biofilm biomass quantification, the plates were incubated at 37 °C without shaking for 24h. Biofilms grown for 24 h were stained using the Crystal Violet staining method, as described by Stepanovic et al. (2000), to quantify the biomass. Briefly, after the incubation period, the wells were rinsed with 200 μL sterile PBS buffer and air dried for 10 minutes. Biofilms were fixed by adding 150 μL/well of 99% methanol for 15 minutes. Staining was performed with 150 μL/well of 2% CV (w/v) for 15 minutes. The wells were rinsed in running water until all of the free dye was removed and then destained for 30 minutes with 200 μL of 95% ethanol. The OD₅₅₀ was then measured.

To verify the viability of biofilms, after the incubation period, the wells were washed twice with 200 µL/well of sterile 0.9% (w/v) saline. Surviving biofilms were dislodged by sonication for 10 min with 200 µL/well of sterile recovery medium (TSB with 1% (v/v) Tween 80). Recovered biofilms were inoculated (10 µL/inoculum) onto BHI agar plates and incubated at 37 °C for 24 h to determine the viability of biofilm cells according to their CFU/well.

To verify the viability of biofilms, the wells were washed twice after the incubation period with 200 µL/well of sterile 0.9% (w/v) saline. Surviving biofilms were dislodged by sonication for 10 min with 200 µL/well of sterile recovery medium (TSB with 1% (v/v) Tween 80). Recovered biofilms were inoculated (10 µL/inoculum) onto BHI agar plates and incubated at 37 °C for 24 h to determine the viability of biofilm cells according to their CFU/well.

The results obtained in TSB were compared to the negative control (non-inoculated medium) to classify the isolates in terms of biofilm production, using the criteria proposed by Stepanovic et al. (2000): OD ≤ ODc = non-producer; ODc < OD ≤ 2×ODc = poor producer; 2×ODc < OD ≤ 4×ODc = moderate producer and 4×ODc < OD = strong producer, where OD is the mean of the optical densities obtained for the evaluated isolate and ODc is the mean of the optical densities of the negative control.

Molecular Typing

To establish the epidemiology and trace the phylogenetic relationship between the isolates, the pulsed field gel electrophoresis (PFGE) technique was used. Through the use of restriction enzymes, variations were detected between isolates. The fragments obtained after the enzymatic cuts were separated on an agarose gel where the standards were compared (Cooper and Feil 2004).

DNA macrorestriction analyses were performed following the protocol described by André et al. (2008), with some modifications. To make the plugs, the isolates were inoculated in BHI broth and incubated at 37ºC for 16 to 18 hours until an optical density of 0.8-1 (OD₅₉₀) was obtained. After adjusting the OD, 200 μl of the bacterial suspension was transferred to 1.5 mL microtubes and centrifuged at 15000 rpm for 5 minutes. The supernatant was discarded and the pellet resuspended in 150 µl of cell suspension buffer solution (10 mM Tris-HCl pH 7.2, 20 mM NaCl, 50 mM EDTA). Then, 7 µl of lysostaphin (1 mg/ml) and 7 µl of lysozyme (10 mg/ml) were added. After homogenization, 150 μl of 2% low melting point agarose was added to the solution, and the mixture was transferred to the plug mold, filling two wells per isolate. The mold was kept at 4 °C for 5 minutes for solidification. Then, the plugs were transferred to 2.0 mL microtubes containing 1.0 mL of Lysis Buffer (10 mM Tris-HCl pH 7.2, 50 mM NaCl, 50 mM EDTA, 0.2% deoxycholate, 0.5% sarkosyl) and incubated for 1 h at 37 °C in a water bath. After incubation, the lysis buffer was removed and 500 µL of PK-PK Buffer (60 U/mL - 250 mM EDTA pH 9.0, 1% sarkosyl) was added. This was followed by a 30 min incubation at 50 °C. Then, the PK-PK Buffer was discarded and the plugs rinsed with 1.4 mL of wash buffer (10 mM Tris-HCl pH 7.6, 0.1 mM EDTA), followed by three washes with 1.4 mL of Wash Buffer at 50 °C for 30 min. At the end of the washes, 1.4 mL of Wash Buffer was added to the microtubes for storage at 4 °C. For enzyme restriction, about 1/3 of the original plug was sectioned and added to properly labeled 1.5 mL microtubes. The plugs were initially equilibrated in 300 μL of enzyme buffer (MultiCore®, Promega) 1X for 10 min at room temperature. After discarding the equilibration buffer, 150 μL of the 1X buffer plus 25 U restriction enzyme SmaI (Promega Corporation, Madison, USA) was transferred to the microtubes. The plugs were incubated at 25 °C for 4 h in a dry bath. The DNA present in the plugs was separated using the CHEF-DRIII apparatus (Bio-Rad Laboratories, Hercules, CA, USA), following the running protocol: 5.3 to 34.9 seconds, for 18 hours, at an angle of 120°, 6V/cm, in 0.5x TBE buffer kept at 14 °C. Salmonella enterica serotype Braenderup H9812 (CDC) was used as a marker, restricted with 20 IU of XbaI (Hunter et al. 2005) and added to three channels per gel. The obtained gels were developed in an immersion bath with 1% ethidium bromide and visualized in a transilluminator under ultraviolet light and photographed for further analysis (L-PIX EX). The bands obtained were analyzed using BioNumerics v.6.6.4 software (Applied Maths, Kortrijk, Belgium). For the analysis and interpretation of the results, a dendrogram was constructed, using the dice coefficient of similarity and the unweighted pair group method with arithmetic mean (UPGMA) using a tolerance degree of 1.5% and optimization of 5%. To group the isolates, 80% similarity was adopted as the cut-off point.

Statistical Analysis

The prevalence of genes and the simultaneous number of genes were compared for the One Health sector by Fisher's Exact Test. The classification of biofilm production was compared in relation to the number of resistance genes and number of classes of resistant antimicrobials, while the One Health sector was also assessed using Fisher's Exact Test.

The means of planktonic growth and biofilm biomass data were submitted to the Kolmogorov-Smirnov normality test and then compared by the Kruskal-Wallis test, followed by the Dunn test. 95% significance was always adopted.

Molecular detection of efflux systems

The genes detected in each isolate are shown in Fig. 4. The most prevalent gene was norC, detected in all 34 isolates, followed by norA in 33 and lmrS in 32. The least prevalent gene was msrA, found in two isolates, both of human origin. The norB gene was the only one to show a difference in prevalence regarding origin, having been more frequently detected among human isolates (p<0.05).

Regarding the number of genes carried at the same time by the isolates, approximately 41% carried five genes and 47% carried four. One isolate was positive for a single gene and one isolate was positive for all genes surveyed. There was no difference regarding the simultaneous number of genes carried in relation to the One Health origin of the isolates (p>0.05).

Phenotypic detection of efflux systems

Ciprofloxacin and tetracycline MICs were compared in the absence and presence of CCCP. With ciprofloxacin, 21 isolates were tested (one from food, 19 from humans and one isolate of animal origin). With tetracycline, seven isolates of food origin, 20 from humans and the single animal isolate were tested, totaling 28 isolates. There was no reduction in the MIC of any of them, either for ciprofloxacin or tetracycline.

Using ethidium bromide efflux, 19 (55.9%) isolates showed SEM activity, with three (37.5%) being of food origin, 15 (60%) of human origin and one (100%) of animal origin. Fig. 2 shows representative curves of isolates without efflux and isolates with ethidium bromide efflux.

FIGURE 2 HERE

Biofilms in the presence of CCCP

The 19 S. aureus isolates that showed ethidium bromide efflux activity were evaluated for biofilm formation. In the presence of CCCP, the planktonic growth of the isolates was lower than that of the positive control and higher than that of the negative control (p<0.05). Regarding the quantification of biofilm biomass, when submitted to CCCP, the isolates produced less biofilm than the positive control (p<0.05), with results similar to those obtained in the negative control (Fig. 3).

FIGURE 3 HERE

Molecular Typing

A dendrogram was created using the BioNumerics program version 6.6. A total of 26 pulsotypes were obtained, forming 8 clusters based on genetic similarity (80% cutoff) designated from A to H. The PFGE pattern of the isolates and the comparison between the patterns associated with the One Health sector and the presence of genes from SEM are illustrated in Fig. 4.

FIGURE 4 HERE

The largest cluster was H, formed by 14 isolates of human origin with more than 90% homology and then cluster E, which comprised six isolates of human origin. Clusters C and F had a mixture of isolates of food and human origin, while cluster D was composed of isolates of food and animal origin.

The reckless and excessive use of antimicrobials in the agricultural, veterinary and medical sectors contributes to the global epidemic increase in antimicrobial resistance (AMR). According to Samreen et al. (2021), there is growing concern that the environment acts as a reservoir of AMR and plays a key role in the spread of antimicrobial resistance genes (ARGs).

Since antimicrobials used in human and animal health largely comprise the same or very similar molecules, the transmission of resistance between animals and people can occur, either directly or through the environment (Robinson et al. 2016). Thus, adopting the One Health approach to the study of AMR is fundamental. With this premise in mind, we tried to obtain isolates recovered from the three domains of One Health for this study: humans, animals and the environment. However, we did not obtain any from the environment among the S. aureus isolates selected with the desired profile in this study.

Among the selected isolates, there was high resistance (94.1%) to erythromycin, an antimicrobial of the macrolide class (Fig. 1), one of the classes of choice for the treatment of S. aureus infections due to its pharmacokinetic properties and its antimicrobial profile. According to Fiebelkorn et al. (2003), in Staphylococci, macrolide resistance may be due to active efflux (msrA encoded) or ribosomal target modification (macrolide-lincosamide-streptogramin B [MLSB] resistance; usually encoded by ermA or ermC). In our study, only two (5.9%) isolates had the msrA gene. Evidence shows that target modification encoded by ermA, ermB and ermC is the main mechanism in S. aureus for cross-resistance to MLSB antibiotics, including resistance to erythromycin and cross-resistance to lincosamide clindamycin (Sun et al. 2018). Thus, it is believed that the resistance of most of the isolates in the present study was due to target modification, since the percentage of resistance to clindamycin by the isolates was also high (Fig. 1).

As for ciprofloxacin, whose percentage of resistance among the isolates was 76.5%, one of the resistance mechanisms in S. aureus is the presence of efflux pumps (Rajabi et al. 2020) and the MES NorA, NorB and NorC have the ability to expel this fluoroquinolone (Truong-Bolduc et al. 2006a; Bambeke et al. 2010). The detection of the norA, norB and norC genes was 97.1, 76.5 and 100%, respectively, and at least one of these genes was detected in all of the study isolates (Fig. 4), which may explain the high resistance to ciprofloxacin (Fig. 1). Another mechanism that causes fluoroquinolone resistance are mutations that occur in the quinolone resistance-determining region (QRDR) of topoisomerase IV encoded by grlA/grlB and DNA gyrase encoded by gyrA/gyrB; these mutations decrease drug affinity (Hassanzadeh et al. 2017) and may be present in the studied isolates.

In relation to tetracycline, 44.1% of the S. aureus studied showed resistance (Fig. 1). According to Wendlandt et al. (2013), two mechanisms of resistance to tetracyclines were identified among staphylococci: active efflux and ribosomal protection. The MES Tet38 of the MFS family confers, among others, resistance to tetracycline (Truong-Bolduc et al. 2021). NorB is also capable of effluxing tetracyclines (Bambeke et al. 2010). However, as with ciprofloxacin, the use of CCCP was not able to reduce the MIC of tetracycline in any of the isolates evaluated. Thus, ribosomal protection may be the strategy used by these isolates.

Also, in S. aureus, MgrA acts as an indirect regulator of norA, norB, norC and tet38 expression, negatively regulating the transcription of these genes (Truong-Bolduc et al. 2006a). Thus, the difficulty in reducing the MICs of resistant and positive isolates for efflux system genes may have also occurred due to their low transcription, which would imply in few active efflux systems that could be inhibited.

MES LmrS also belongs to the MFS family and has linezolid, chloramphenicol, florfenicol, trimethoprim, erythromycin, kanamycin, fusidic acid, lincomycin, streptomycin, tetraphenylphosphonium and ethidium bromide as substrates. The lmrS gene encoding this protein is located on the bacterial chromosome and was detected in 94.1% of the MDR S. aureus selected for this study (Fig. 4).

Ethidium bromide is a substrate for different SEM; among those researched in the present work, it is effluxed by NorA and LmrS (Hassanzadeh et al. 2017). Comparing their efflux in the presence and absence of CCCP, 55.9% of the isolates exhibited SEM activity. Ethidium bromide is particularly suitable for use as a probe for these studies because it emits weak fluorescence in aqueous solution and becomes strongly fluorescent in nonpolar and hydrophobic environments, especially when it penetrates the bacterial cell wall and accumulates in the cytoplasm (Viveiros et al. 2010).

We are not aware of the use of this tool as a screening tool to detect efflux activity in S. aureus, being most commonly used to compare SEM activity in isolates that are genetically altered to overexpress or knockout SEM genes. There are also reports of its use in comparing emitted fluorescence to determine the activity of new compounds such as EPI (Espinoza et al. 2019; de Sousa Andrade et al. 2020). However, using the efflux of EtBr in our bacterial library allowed us to evidence SEM activity, even when we were not able to do so through the use of MIC, the most traditionally used technique. Therefore, we describe here a new application of the technique that can be used to support traditional techniques for the detection of SEM activity.

To determine the effect of efflux inhibition on biofilm formation, we used CCCP. Compared to the control, the presence of CCCP decreased the biofilm formation of the isolates that had SEM activity (Fig. 3). Decreased S. aureus biofilm formation using CCCP has been reported previously (Baugh et al. 2014; Garrison et al. 2015). The inhibition of biofilm formation was not the result of antibacterial action, since the isolates were able to multiply in the presence of CCCP. Thus, efflux inhibition is a promising antibiofilm strategy.

Regarding the molecular epidemiology of the isolates, the restriction pattern obtained with SmaI submitted to PFGE revealed the existence of eight clusters, with the H cluster being dominant (n=14) and formed only by isolates of human origin with a similarity greater than 90%. Cluster E (n=6) was also formed by only human isolates. Small differences in restriction patterns may be the result of genetic rearrangements that allow the isolates to adapt to the host and increase its pathogenicity. However, three clusters were obtained (C, D and F) where there was a mixture of the origin of isolates. In these, the isolates seem to have evolved in ways that are adapted to the different domains studied: humans, animals and food. New omics studies are needed to better assess this dispersion.

All isolates of human origin were recovered from the same hospital, within an intensive care environment. In view of the great similarity found in the restriction patterns of these isolates, it is believed that they are residents of the environment and capable of causing nosocomial infections. In addition, one can think about the adoption of a sessile way of life (biofilm) by these isolates, which makes it difficult to eliminate them from the environment, even using correct disinfection and asepsis techniques. Medical devices are excellent support for bacterial adhesion and biofilm formation (Ribeiro et al., 2012). The combinational therapies show great potential to biofilm combat, which is reinforced by the inhibitory effect of CCCP among the S. aureus isolates tested in the present work (Kranjec et al., 2021).

Analyzing the food source isolates, the pattern was quite heterogeneous, with the isolates being distributed in five clusters, mixed with other sources or not. This diversity probably reflects the multiple sources of contamination by S. aureus: animals and their raw milk, the processing environment and the personnel involved in the production chain (Loncarevic et al. 2005).

Thus, multidrug-resistant S. aureus isolates from humans, animals and foods carry distinct MES genes, and their activity was detected through ethidium bromide efflux. The inhibition of this activity did not change resistance to the antimicrobials ciprofloxacin and tetracycline, but resulted in a decrease in biofilm formation by these isolates. This may be a strategy adopted in an attempt to reduce nosocomial infections caused by this bacterium, which may remain in the environment through biofilms. Still, S. aureus MDR with active multidrug efflux systems are circulating between One Health domains and it is necessary to think of strategies to decrease this circulation in order to prevent the dissemination of resistance mediated by MES. Finally, we highlight the use of ethidium bromide efflux quantification as a screening tool for the detection of SEM activity in S. aureus.

More studies are needed to determine the prevalence of this mechanism in isolates of environmental origin and to enrich the information on its dispersion. This study brings relevant and unpublished data on the dispersion of S. aureus MDR in the context of One Health.

ACKNOWLEDGMENTS

The authors thanks to CAPES (this study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001), CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and FAPEMIG (Fundação de Amparo à Pesquisa do Estado de Minas Gerais) by financial support.

Funding

This work was supported by CAPES, CNPq and Fapemig. Authors M.M.C, R.A.M, L.A.N. and M.A.S.M are supported by CNPq.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose

Author Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Mariana de Barros, Ilderlane Silva Lopes, Ana Júlia Moreira and Raquel dos Santos Oliveira Almeida. The first draft of the manuscript was written by Mariana de Barros and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Ethics approval

This study was performed in line with the ethics principles. Approval was granted by the Comitê de Ética em Pesquisa com Seres Humanos (November 12^th, 2018, 3.014.634) and by Comissão de Ética no Uso de Animais (79/2018) both of Universidade Federal de Viçosa.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Table 1 Multidrug-resistant Staphylococcus aureus isolates selected for the study.

Identification	Laboratory	Source	Origin
St 05	A	Wound secretion	Human
St 08	A	Bone tissue	Human
St 09	A	Bone tissue	Human
St 10	A	Orthopedic screw	Human
St 14	A	Bone fragment	Human
St 18	A	Blood culture	Human
St 30	A	Surveillance Culture - Nasal Swab	Human
St 33	A	Subdural secretion	Human
St 37	A	Synthesis	Human
St 38	A	Soft parts	Human
St 39	A	Surveillance Culture - Nasal Swab	Human
St 67	A	Blood culture	Human
St 74	A	Tracheal secretion	Human
St 77	A	Blood culture	Human
St 78	A	Blood culture	Human
St 80	A	Surveillance Culture - Nasal Swab	Human
St 82	A	Tracheal secretion	Human
St 92	A	Surveillance Culture - Retal Swab	Human
St 104	A	Surveillance Culture - Nasal Swab	Human
St 112	A	Tracheal secretion	Human
St 261	A	Skull bone	Human
St 262	A	Secretion	Human
St 282	A	Wound fragment	Human
St 319	A	Fistulous tissue	Human
St 331	A	Tracheal secretion	Human
St 574	A	Nasal swab	Animal
RP 01	B	Goat cheese	Food
RP 03	B	Goat cheese	Food
RP 05	B	Goat cheese	Food
RP 06	B	Goat cheese	Food
RP 07	B	Goat cheese	Food
RP 09	B	Goat cheese	Food
RP 27	B	Goat cheese	Food
RP 28	B	Goat cheese	Food

Table 2 Primers for detection of Staphylococcus aureus multidrug efflux system genes using the PCR technique

Gene	Family	Primer	Sequence (5’-3’)	Amplicon (pb)	Reference
tet38	MFS	tet38 - 1	TTCAGTTTGGTTATAGACAA	400	(Truong-Bolduc et al. 2005)
		tet38 - 2	CGTAGAAATAAATCCACCTG
norA	MFS	norA1	TGCAATTTCATATGATCAATCCC	150	(Truong-Bolduc et al. 2003)
		norA2	AGATTGCAATTCATGCTAAATATT
norB	MFS	norB1	GAAGATAGTTTCAATACAGA	400	(Truong-Bolduc et al. 2005)
		norB2	ATTATAAATGATAGGATGAA
norC	MFS	norC - f	AAATGGTTCTAAGCGACCAA	200	(Truong-Bolduc et al. 2006b)
		norC - r	ATAAATACCTGAAGCAACGCCAAC
LmrS	MFS	LmrS - f	GCAAGCTTATGGCTAAAGTTGAATTAACAAC	1400	(Floyd et al. 2010)
		LmrS - r	GCGGATCCTTAAAATTTCCTTCTATTACTTT
msrA	ABC	msrA - f	TCCAATCATTGCACAAAATC	163	(Martineau et al. 2000)
		msrA - r	AATTCCCTCTATTTGGTGGT

ABC: ATP-Binding Cassette; MFS: Major Facilitator Superfamily

No competing interests reported.

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Multidrug Efflux System-mediated resistance in Staphylococcus aureus under a One Health approach

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