Staphylococci are the bacteria most commonly isolated from bovine mastitis [13]. The discussions and comparisons between CNS and SA have often been reported [6, 14]. Although SA causes more server mastitis than CNS, CNS are now predominant over SA in most countries [6]. Staphylococcus aureus mastitis easily remains persistent [15], but CNS are more able to persist in the mammary gland with causing a moderate increase of milk SCC [16]. In this study, 168 isolates of SA were recovered from subclinical cases in the 6 farms. For 225 CNS isolates, Staphylococcus sciuri (22.67%) and Staphylococcus xylosus (17.33%) are identified most frequently. Staphylococcus sciuri is also reported as the commonest CNS species isolated from cows in Poland [17, 18]; Staphylococcus chromogenes, however, is typically the most commonly identified species in Columbus (USA) or Helsinki (Finland) [14, 19].
On the other hand, vitro drug sensitivity tests were conducted on staphylococcal isolates. We found that the most effective antibiotics against CNS and SA were different. Most SA strains were susceptible to clarithromycin (92.26%), followed by nitrofurantoin (88.69%) and chloramphenicol (85.71%). The majority of CNS were sensitive to chloramphenicol (86.67%), co-trimoxazole (83.56%) and nitrofurantoin (82.22%). Therefore, chloramphenicol can defend against most staphylococci; this might due to that the use of chloramphenicol has been banned in food animals in China because of its inhibition of bone marrow hematopoietic function [20]. Fortunately, chloramphenicol now can be replaced by florfenicol, which is also a member of the amide alcohols. Florfenicol was developed in the late 1980s as a new kind of broad-spectrum antibiotic for veterinary use.
The concepts of MDR, XDR and PDR are very important, characterizing the different patterns of resistance found in bacteria. But there were many different definitions for them until 2012, Magiorakos reported and defined them [21]. According to the report, we exercised statistic data; from Table 2 and Table 3, it can be seen that most of SA were quadruple-drug resistances, and most CNS resist double. However, CNS seem to outperform SA in resisting six or more classes of drugs; there were even 4 strains of CNS are PDR strains that were non-susceptible to all of the 15 kinds of antibiotics used in this study. This point agrees with the view that CNS tend to be more resistant to antimicrobials than SA and easily develop multiresistance [11]. Therefore, CNS are more likely represented as a reservoir which transmitted antibiotic-resistance to other staphylococci like SA [11].
According to the chi-square test results, we summary and find that quinolones (ciprofloxacin, levofloxacin, and norfloxacin) and co-trimoxazole antibiotics, both interfere with the metabolism of nucleotides. They affected CNS significantly more than SA. Quinolones antibiotics can trap the bacterial topoisomerases on DNA [22] and co-trimoxazole includes trimethoprim work as a tetrahydrofolate reductase inhibitor, and sulfamethoxazole provides a second blockage of the folate biosynthetic pathway [23]. Therefore, whatever the results in Jiangsu, Finland [13], or Portuguese [24], there might be mechanisms or compounds that tend to protect nucleotide metabolism in SA from these antibiotics under pressure from these kinds of antibiotics. Proctor proposes that the special thermonuclease in SA could release extra thymidine from bacterial inoculum and mammalian tissues, so they can bypass the metabolic blockades caused by co-trimoxazole [25]. We remained unknown whether this release process could also affect the working mechanism of quinolones or there are other defense mechanisms in SA.
Equally, We also compare the resistance of CNS and SA to lincomycins (clindamycin), macrolides (including erythromycin and clarithromycin), tetracycline, and nitrofurantoin antibiotics; those antibiotics all interfere the bacterial protein synthesis by inhibiting the prolonging of peptide chains [26–28]. We summary and found that the antimicrobial resistance rates of CNS to them were significantly higher than that of SA; that is to say, they affected CNS significantly less than SA in general. Moreover, it can be found that resistance genes were detected much more frequently in CNS than SA, which means resistance genes may have more contribution in CNS than SA. Taponen also reported that CNS were more resistant to macrolides, lincosamides, oxytetracycline and fusidic acid in Finland [29]. These are partly in line with the view CNS tend to be more resistant to antimicrobials than SA [6, 11].
Macrolides (MLS) and lincomycin antibiotics have similar binding sites in the 50S ribosomal subunit. It can irreversibly bind to bacterial ribosomal 23SrRNA and selectively inhibit protein synthesis by blocking tranlspeptide action and mRNA shift [26]. The erm gene can methylate specific nucleotide residues of 23SrRNA, resulting in their resistance to macrolides, lincosamide, and streptomycin B with the same target position, clinically known as MLS resistance. Chi-square test results show that CNS were significantly more resistant to macrolides (erythromycin and clarithromycin) or lincomycin (clindamycin) than SA in this area. At the genetic level, the detection rate of ermC in the CNS is also higher than that of SA. MLS resistance can be divided into constitutive (cMLS) and induced (iMLS) resistance [30]. The resistance of cMLS type could resist erythromycin and clindamycin, which could be detected routinely in vitro drug sensitivity tests. However, iMLS resistance means that erythromycin, as an inducer, can induce erm gene expression through the attenuating mechanism to produce resistance toward clindamycin; hence some bacteria with iMLS could be resistant to erythromycin and sensitive to clindamycin in vitro drug sensitivity assay, but clindamycin might be ineffective to them in clinical treatment [31]. Therefore, ermC is often added to the drug sensitivity test to prevent clinical drug failure. The detection rate of ermC in this study was 3.1% in CNS and 1.2% in SA; both were low, indicating that the most clinical susceptibility results should be valid and the probability of clinical clindamycin failure is low. It also shows that the resistant models of CNS and SA to macrolides and lincomycin drugs were little dominated by the ermC mechanism in Jiangsu province. The resistance rate of staphylococci to erythromycin in Jiangsu area (15.78%) is still somewhat high, and CNS were significantly more resistant to macrolides (erythromycin and clarithromycin) or lincomycin (clindamycin) than SA
Besides, tetK, tetM, tetL and tetO, the major resistance genes that defend against tetracycline antibiotics in staphylococci, were detected in this study. We found that staphylococcal resistance to tetracycline is mainly mediated by energy-dependent efflux of tetracycline in this area; the tetK and tetL genes encode proteins that pump out tetracycline, but this cannot remove minocycline [32]. Another resistance mechanism, ribosomal protection proteins (RPPs), plays a minor role in this area. RPPs are encoded by tetO and tetM; together of them were only detected out a tiny proportion, 1.2%, in all isolated staphylococci. RPPs result in an allosteric disruption of primary tetracycline binding and consequently release of the drug. This mechanism confers resistance to tetracyclines and minocycline [33]. Therefore, although 26.6% of CNS can resist tetracycline theoretically due to the energy-dependent efflux of tetracycline, most of them should be susceptible to minocycline. Phenotypic antimicrobial-resistant observations of this study were also supported this hypothetical pattern.
A related point to consider is that, for minocycline and chloramphenicol, they are not used in these 6 farms and chloramphenicol is forbidden to be used in China. Few CNS and SA isolates were resistant to these two in this study, and the chi-square test results of them didn’t show a significant difference between SA and CNS. Therefore, we speculate that only after its involvement, the stress of antibiotics interfering with protein synthesis, CNS strains might be more likely to become the mutations to survive than SA. Interestingly, recently Fernando also makes a very similar interpretation on another kind of bacteria; he assumed that the evolutionary landscapes of Pseudomonas aeruginosa towards ribosome-targeting antibiotic resistance depend on selection strength [34]. We further proposed that this evolutionary also relies on the classes of antibiotics and the species of bacteria.