Expression of genes encoding resistance in Staphylococcus spp. isolated from bovine subclinical mastitis in Brazil

Abstract

Introduction: Staphylococci are the most important agents associated with bovine mastitis. This study aimed at characterizing resistance factors to antimicrobials in Staphylococcus spp. isolated from the milk of cows with subclinical mastitis.
 Methodology: In vitro resistance of 243 Staphylococcus spp. isolates to antimicrobials commonly used in clinical practice was evaluated. The detection and expression of genes encoding resistance mecA (gene encoding penicillin binding protein 2a) mecALGA251 (mecA homologue), blaZ (gene encoding penicillin resistance), femA and femB (genes encoding essential factors - A and B - for the expression of methicillin resistance) and aacA-aphD (gene encoding for a bifunctional enzyme that confers resistance to gentamicin) using PCR and RT-PCR was investigated.
 Results: One or more genes encoding resistance to different antimicrobials were detected in 184 Staphylococcus spp. samples. The femA and femB genes were the most frequent. Regarding the variables’ detection (N = number of strains) and expression (% of strains), the following results were obtained: blaZ (N = 40 – 82.5%), femA (N = 147 – 47.6%), aacAaphD (N = 30 – 43.3%), femB (N = 138 – 29.7%), mecA (N = 33 – 27.3%), mecALGA251 (N = 01 – 0.0%). There was a higher occurrence of phenotypic resistant strains for amoxicillin, ampicillin and penicillin in isolates positive for detection and/or expression of blaZ gene when compared with the other genes.
 Conclusions: The present study provides new information on genotypic traits of Staphylococcus isolates from bovine subclinical mastitis especially regarding the evaluation of expression of genes associated with antimicrobial resistance in Staphylococcus spp. using molecular tools.

A meta‐analysis of the global prevalence of methicillin‐resistantStaphylococcus aureus(MRSA) isolated from clinical and subclinical bovine mastitis

“…Sizes of squares indicate the weight of each study based on sample size. The diamond indicates the estimated pooled effect size; CI = confidence interval Overall (I^2 = 97•48%, p = 0•00) Buyukcangaz et al, 2013 Zayda et al, 2020 Kwon et al, 2005 Zaatout et al, 2020 Awad et al, 2017 Guimarães et al, 2017 Elhaig and Selim, 2015 El-Ashker et al, 2015 Akkou et al, 2018 Algammal et al, 2020 Tavakol et al, 2012 Oreiby et al, 2019 Chandrasekaran et al, 2014 Rossi et al, 2019 Pu et al, 2014 Yang et al, 2020 Dan et al, 2019 Sayed, 2016 Klibi et al, 2018 Study Havaei et al, 2015 Enany et al, 2013 Elkenany, 2018 Nazir et al, 2017 Hamid et al, 2017 Girmay et al, 2020 Kutar et al, 2015 Jamali et al, 2014 Wang et al, 2018 Yi et al, 2018 Pehlivanoglu and Yardımcı, 2012 El-Ashker et al, 2020 Zhang et al, 2016Gindonis et al, 2013Käppeli et al, 2019Schabauer et al, 2018Benhamed and Kihal, 2013Mistry et al, 2016Abed et al, 2018Zuniga et al, 2020Shah et al, 2019Khan et al, 2020 Haveri et al, 2008Song et al, 2016Silva et al, 2014Heidari et al, 2011Ismail, 2017 Shrivastava et al, 2016Ganai et al, 2016Srednik et al, 2018Hanon, 2016Mahanti et al, 2020Kaszanyitzky et al, 2007Abd El-Tawab et al, 2016Suleiman et al, 2012Asfour, 2011 Abd Al-Azeem et al, 2013Sheela et al, 2016Hoque et al, 2018Srednik et al, 2019Kumar et al, 2011Kumar et al, 2010 Schmidt et al, 2015Moon et al, 2007Kumari et al, 2020Patel et al, 2017Salam, 2015Li et al, 2015…”

“…Akkou et al, 2018Silva et al, 2014Kumar et al, 2011Guimarães et al, 2017Zayda et al, 2020Girmay et al, 2020Kumar et al, 2010 Shrivastava et al, 2016 Algammal et al, 2020 Subtotal (I^2 = 97•13%, p = 0•00)Patel et al, 2017Havaei et al, 2015Mistry et al, 2016Abed et al, 2018Kutar et al, 2015Elhaig and Selim, 2015El-Ashker et al, 2020Yi et al, 2018Kwon et al, 2005 al., 2018 Abd El-Tawab et al, 2016 El-Ashker et al, 2015 Mahanti et al, 2020 Asfour, 2011 Africa Salam, 2015 Ganai et al, 2016 Käppeli et al, 2019 Srednik et al, 2019 Gindonis et al, 2013 Suleiman et al, 2012 Shah et al, 2019 Enany et al, 2013 Dan et al, 2019 Hamid et al, 2017 Europe Pu et al, 2014Kaszanyitzky et al, 2007Zhang et al, 2016Klibi et al, 2018Sheela et al, 2016 Pehlivanoglu and Yardımcı, 2012Tavakol et al, 2012Kumari et al, 2020Awad et al, 2017Wang et al, 2018 America Oreiby et al, 2019 Subtotal (I^2 = 97•00%, p = 0•00)Haveri et al, 2008 Study Jamali et al, 2014Zuniga et al, 2020Chandrasekaran et al, 2014Hanon, 2016Khan et al, 2020Li et al, 2015Benhamed and Kihal, 2013Ismail, 2017Song et al, 2016Schabauer et al, 2018Yang et al, 2020 Abd Al-Azeem et al, 2013Sayed, 2016Heidari et al, 2011Moon et al, 2007 …”

Detection of Genes Encoding Microbial Surface Component Recognizing Adhesive Matrix Molecules in Methicillin-Resistant Staphylococcus aureus Isolated from Pyoderma Patients

“…The level of methicillin resistance is mainly influenced by the Fem (factor essential for methicillin resistance) proteins encoded by femA and femB [ 28 ]. Both genes are essential for the formation of pentaglycine, which is required for the formation of peptidoglycan.…”

“…Both genes are essential for the formation of pentaglycine, which is required for the formation of peptidoglycan. The absence of these genes results in greater susceptibility to β–lactam antibiotics [ 28 ]. In this study, all the MSSA and MRSA isolates (116) were found positive for the femA gene.…”

Antibacterial Resistance Pattern in Clinical and Non-clinical Bacteria by Phenotypic and Genotypic Assessment

“…9 Lately, the bacterial RNAs have emerged as regulating keys of post-transcriptional regulators during the gene expression process, in addition, the bacterial RNAs were involved in several cellular processes, including bacterial virulence. 10 MecA is a chromosomal gene on S. aureus that clarifies methicillin-resistant S. aureus (MRSA), 11 while femA and femB genes encode proteins that affect the level of methicillin resistance of S. aureus. 12 TEM is the major gene determinant of the resistance to amino-penicillin in E. coli, and the most common β-lactamaseencoded plasmid, 13 TEM is frequently encoded by Gram-negative bacteria.…”