Abstract

Multi-drug resistance traits of Staphylococcus species especially methicillin-resistant Staphylococcus aureus (MRSA) in the clinical settings are well established. Of environmental concern is hospital effluents discharging into wastewaters. This article investigated the prevalence and detection of antibiotic resistance genes in Staphylococcus species from clinical and environmental sources in Ile-Ife, Nigeria. Standard culture-based and molecular protocols were used. Seventy-six (27 clinical, 14 hospital effluent and 35 environmental) Staphylococcus isolates were recovered: 56.58% were coagulase-negative and 43.42% coagulase-positive (S. aureus). For the clinical isolates, 10, 6, 4, 4 and 1 were isolated from urine, skin, wounds, blood and pus, respectively. Isolates were resistant to methicillin and amoxycillin (91.7%), cloxacillin (88.0%), ciprofloxacin (84.0%), ofloxacin (83.3%), azithromycin (78.0%), ceftazidime (76.0%), gentamycin (75.0%), cefuroxime (75.0%) and erythromycin (72.0%). Nearly, all isolates (90.8%) had multiple antibiotic resistance (MAR) index >0.2. Overall MAR indices for Staphylococcus species isolated from the clinical, hospital effluent and environmental wastewaters were relatively similar (0.482; 0.500; 0.435). mecA, nuc and luk-pvl genes were detected in S. aureus, while mecA was detected in S. arlettae, S. sciuri, S. cohnii, S. epidermidis and S. saprophyticus. This study informs on the potential contamination of environmental waters downstream from hospitals and possible impacts that this could have on human and animal health.

INTRODUCTION

Currently in human medicine, antibiotics are the most effective antimicrobials used for combatting bacterial infections. However, the uncontrolled, excessive and misuse of antibiotics has played a key role in the selection of antibiotic-resistant bacteria (ARB) (Finley et al. 2013; Tripathi & Tripathi 2017; Jensen et al. 2019).

Hospital effluents have been identified as a major reservoir for pollutants such as pharmaceutical wastes (antibiotics) and pathogenic microorganisms (Huang et al. 2019). Studies have reported that the discharge of hospital wastewaters is a highly selective route for the dissemination of ARB into natural environments (receiving water bodies) (Yilmaz et al. 2017; Kumar et al. 2019). However, the effect of antibiotics as environmental pollutants has been largely overlooked (Moges et al. 2014; Sabri et al. 2018). According to Finley et al. (2013) and Burgmann et al. (2018), there are no regulations guiding the release of antibiotic residues into wastewaters from hospital effluents. It is documented that only a few countries recommend the pre-treatment of hospital effluents before they are discharged into receiving water bodies (Szekeres et al. 2017).

Staphylococcus species are among the most frequently encountered bacteria in hospital settings and have been incriminated for many infections in humans such as skin and soft tissue infections, surgical site/wound infections, pneumonia, septicaemia and bone infections (Nanoukona et al. 2017). The detection of Staphylococcus species in hospital wastewaters had been reported by various authors (Gómez et al. 2017; Tripathi & Tripathi 2017). It has been demonstrated that pathogenic Staphylococcus species could be resistant to a wide array of antibiotics (WHO 2017). Staphylococcus spp. comprise of two major groups – coagulase-positive Staphylococci (CoPS) and coagulase-negative Staphylococci (CoNS) (Casey et al. 2009). The CoPS include Staphylococcus aureus as the major pathogen. There is now increasing evidence that some of the CoNS species (S. cohnii, S. epidermidis, S. haemolyticus, S. warneri and S. xylosus) could also be pathogenic and cause nosocomial infections (Tayyar et al. 2015; Hitzenbichler et al. 2017).

S. aureus and specifically methicillin-resistant S. aureus (MRSA) have been isolated from wastewater effluent (Börjesson et al. 2009, 2010; Rosenberg Goldstein et al. 2012; Ekwanzala et al. 2018). In addition, the presence and multi-drug resistance of CoNS in reclaimed water had also been confirmed (Goldstein et al. 2017). Among the antibiotics to which Staphylococcus species exhibit resistance are ampicillin and methicillin (Moges et al. 2014; Delorme et al. 2017). Susceptibility/sensitive to vancomycin and imipenem is still being recorded among large numbers of isolates (Tayyar et al. 2015; Hitzenbichler et al. 2017; Premanadham et al. 2017).

Antibiotic resistance could be the result of mutations or the acquisition of antibiotic resistance genes (ARGs) due to horizontal gene transfer (HGT) (Calero-Caceres et al. 2017). HGT, thus, facilitates the inter- and intraspecies transfer of antibiotic resistance and virulence genes (Tripathi & Tripathi 2017; Lerminiaux & Cameron 2019).

The detection of these Staphylococcus species in wastewaters is an important environmental risk which may result in the contamination of natural water reservoirs (groundwaters) and may eventually lead to public health challenges. In West Africa and particularly Nigeria, there is a paucity of data on the detection of Staphylococcus species in hospital effluents and the interplay with receiving wastewaters.

The aim of this study was therefore to investigate the prevalence of MRSA in clinical and environmental (hospital effluents and surrounding receiving wastewaters) sources in the South-western region of Nigeria and to determine antibiotic resistance profiles and mecA, nuc and luk-pvl genes in Staphylococcus species.

MATERIALS AND METHODS

Study location

This study was carried out at a hospital in Ile-Ife (7°16′48′′N, 4°20′24′′E), Osun State, South-western Nigeria. The medical institution provides health care services to about two million inhabitants in Ile-Ife and Southwest Nigeria.

Sample collection

Isolates from clinical samples

Isolates from various clinical samples were used and included wounds, skin, pus, urine, bones and blood. These were samples from different wards in the hospital submitted to the Microbiology Laboratory Unit for analysis. Clinical isolates were obtained from the Laboratory over a period of 6 months between May and October 2017. The clinical isolates were aseptically cultured on appropriate MacConkay agar (Difco MacConkey Agar, New Brunswick, NJ, USA) and blood agar (Blood agar base, Oxoid Ltd, Hampshire, UK) to select for the growth of staphylococci. Purification and growth on Mannitol salt (Biotec Laboratories, Kentford, UK) and MRSA CHROMagar base (CHROMagar MRSA-ITK Diagnostics BV, Uithoorn, The Netherlands) agars were to enhance the growth of S. aureus and MRSA, respectively. Isolates were incubated on the two media at 33 and 37 °C, respectively, for 24–48 h following standard protocols (Cheesbrough 2006; Igbinosa et al. 2016).

Processing of water samples

Environmental samples were collected from wastewater generated within the hospital facility (hospital effluents). Water samples were also collected downstream at three receiving wastewater bodies within proximity (2 km) of the hospital. Each receiving wastewater body was approximately 750 m from each other. Sampling was done weekly over a period of 6 months for the sole purpose of collecting as many Staphylococcus isolates as possible. The water samples were collected in sterile bottles, preserved in cooler boxes and stored at 4 °C until analysed (within 24 h). Once at the laboratory, the water samples were filtered using sterile 0.45 μm membrane filters. These filters were enriched within Bacto tryptic soy broth (soybean-casein digest medium) (Becton Dickinson, USA). They were then placed on Mannitol salt agar (Biotec Laboratories, Kentford, UK) and incubated for 24 h at 33 °C. Resulting yellow colonies were presumptively considered as S. aureus. The yellow colonies were further plated on MRSA CHROMagar base (CHROMagar MRSA-ITK Diagnostics BV, Uithoorn, The Netherlands) to obtain pure isolates. These were at 37 °C for 48 h.

Isolation of Staphylococcus species

Clinical and environmental isolates were grown on Mannitol salt agar and chromogenic agars. Those that provided both the characteristic yellow and purple colours, respectively, were included in further analyses. These were subjected to Gram stain and identified as Gram-positive cocci with grape-like clusters under a microscope. S. aureus including MRSA and other Staphylococcus species were confirmed with the coagulase and catalase tests using standard protocols (Cheesbrough 2006; Igbinosa et al. 2016).

Antimicrobial susceptibility testing

All isolated and identified Staphylococcus species were then subjected to antibiotic susceptibility testing using the standard Kirby-Bauer's disk diffusion technique (CLSI 2014).

Partial 16S rRNA gene-based identification of isolates

Extraction of genomic DNA

The Nucleospin® tissue extraction kit (Macherey-Nagel, Düren, Germany) was used to extract genomic DNA from the isolates following the manufacturer's instructions. Briefly, pure isolates were incubated overnight in Nutrient Broth (Biolab Diagnostics, RSA) at 37 °C. About 2 mL of samples from the broth cultures were dispensed into a 2 mL microfuge tube and centrifuged at 8,000 rpm for 5 min at room temperature, the supernatant discarded, and the pellet treated, following the Macherey-Nagel Nucleospin® tissue extraction kit instructions. The quality and integrity of extracted DNA products were verified on 1% agarose gels, and images were captured using a GeneGenius Bioimaging system (Syngene, Cambridge, UK) and GeneSnap software V. 2.2.2 (Syngene, Cambridge, UK). DNA purity and concentration were verified using NanoDrop spectrophotometer (ND-1000, NanoDrop Technologies Inc., Wilmington, DE, USA).

PCR amplification

Polymerase chain reaction (PCR) was performed in a C1000TM thermal cycler (Bio-Rad, Hercules, CA, USA), and amplification of the 16S rRNA gene was done using universal primer sets 27F and 1492R with PCR conditions (Table 1), as previously described (Lane 1991). Each PCR reaction including positive and negative controls contained 12.5 μL of 2x PCR Master mix (Thermos Scientific Technologies, Waltham, MA, USA), 50 ng DNA template, 5 μM each of forward (27F) and reverse (1492R) primers and nuclease-free water to a final volume of 25 μL.

Table 1

Primers used for the identification of Staphylococcus species and the detection of marker genes

PrimersPrimer sequence (5′–3′)PCR conditionsSize (bp)References
27F 1492R 5′GAGTTTGATCATGGCTCAG3′ 5′GGTTACCTTGTTACGACTT3′ 1 cycle of 2 min at 95 °C; 35 cycles of 30 s at 94 °C; 30 s at 53 °C; 1 min at 72 °C; 1 cycle of 10 min at 72 °C 1,500 Lane (1991)  
mecA-F mecA-R 5′AACGATTGTGACACGATAGCC3′ 5′GGGATCATAGCGTCATTATC3′ 1 cycle of 5 min at 94 °C; 30 cycles of 30 s at 94 °C; 30 s at 55 °C; 1 min at 72 °C; 1 cycle of 10 min at 72 °C 527 Kumar et al. (2016)  
nuc-1 nuc-2 5′TCAGCAAATGCATCACAAACAG3′ 5′CGTAAATGCACTTGCTTCAGG3′ 1 cycle of 5 min at 94 °C; 35 cycles of 30 s at 94 °C; 30 s at 55 °C; 1 min at 72 °C 255 Othman et al. (2014)  
luk-F luk-R 5′ATCATTAGGTAAATGTCTGGCA TGATCC3′ 5′AGCATCAAGTGTATTGGATAGC AAAAGC3′ 1 cycle of 4 min at 94 °C; 30 cycles of 45 s at 94 °C; 1 min at 72 °C; 1 cycle of 2 min at 72 °C 433 McClure et al. (2006)  
PrimersPrimer sequence (5′–3′)PCR conditionsSize (bp)References
27F 1492R 5′GAGTTTGATCATGGCTCAG3′ 5′GGTTACCTTGTTACGACTT3′ 1 cycle of 2 min at 95 °C; 35 cycles of 30 s at 94 °C; 30 s at 53 °C; 1 min at 72 °C; 1 cycle of 10 min at 72 °C 1,500 Lane (1991)  
mecA-F mecA-R 5′AACGATTGTGACACGATAGCC3′ 5′GGGATCATAGCGTCATTATC3′ 1 cycle of 5 min at 94 °C; 30 cycles of 30 s at 94 °C; 30 s at 55 °C; 1 min at 72 °C; 1 cycle of 10 min at 72 °C 527 Kumar et al. (2016)  
nuc-1 nuc-2 5′TCAGCAAATGCATCACAAACAG3′ 5′CGTAAATGCACTTGCTTCAGG3′ 1 cycle of 5 min at 94 °C; 35 cycles of 30 s at 94 °C; 30 s at 55 °C; 1 min at 72 °C 255 Othman et al. (2014)  
luk-F luk-R 5′ATCATTAGGTAAATGTCTGGCA TGATCC3′ 5′AGCATCAAGTGTATTGGATAGC AAAAGC3′ 1 cycle of 4 min at 94 °C; 30 cycles of 45 s at 94 °C; 1 min at 72 °C; 1 cycle of 2 min at 72 °C 433 McClure et al. (2006)  

Sequencing of 16S rRNA genes

Sequencing of purified PCR products was carried out using the Big Dye terminator V. 3.1 cycle sequencing kit (Applied Biosystems, Warrington, UK) on a 3130 Genetic analyzer (Applied Biosystems/Hitachi, Tokyo, Japan). Generated sequence electropherograms were then manually edited after inspection using Finch TV 1.4.0 (http://www.geospiza.com/Products/finchtv.shtml). Edited sequences were aligned against other sequences for comparison with the Basic Local Alignment Search Tool (BLAST) program alignment tool of the GenBank on the National Centre for Biotechnology Information (NCBI) database (https://www.ncbi.nlm.nih.gov/). Multiple sequence alignment was performed using MUSCLE (Edgar 2004) integrated into MEGA V. 7.0 (http://www.megasoftware.net/; Kumar et al. 2016). Phylogenetic sequence dendrograms with closely related sequences in GenBank were constructed with the neighbor-joining tree method using the substitution model. The partial 16S rRNA sequences from this study are available in the GenBank under the accession numbers: KY290702-KY290711; KY290719-KY290745 and MK208534-MK208572.

PCR amplification of mecA, nuc and luk-pvl genes

For MRSA differentiation, PCR amplification of the mecA gene (that encodes for methicillin resistance), the thermonuclease (nuc) gene and the luk-pvl gene that encodes for virulence * in S. aureus species was performed. Each PCR reaction contained 12.5 μL of 2x PCR Master mix (Thermos Scientific Technologies, Waltham, MA, USA), 50 ng DNA template, 5 μM each of forward and reverse primers and nuclease-free water to a final volume of 25 μL. Information on the primers and conditions are detailed in Table 1. DNA amplification was performed in a C1000 thermocycler (Bio-Rad, Hercules, USA). Electrophoresis of the amplicons were performed with 1% w/v agarose gel and visualized with GelRed staining under a UV transilluminator.

Statistical analyses

Antimicrobial resistance data were analysed using WHONET 2017 software V. 5.6 (WHO; http://www.whonet.org/software.html). The multiple antibiotic resistance (MAR) index for individual isolates was calculated and interpreted according to Krumperman (1983) using the formula:
formula
MAR index values greater than 0.2 indicate high-risk source of contamination where antibiotics are often used (Krumperman 1983). The MAR index for each of the three compartments (clinical, hospital wastewater and environmental water) was determined using the method of Krumperman (1983) using the formula:
formula
Multiple sequence alignment was performed using MUSCLE (Edgar 2004) integrated into Molecular Evolutionary Genetics Analysis (MEGA) V. 7.0 (Kumar et al. 2016).

RESULTS

Prevalence of Staphylococcus strains isolated from clinical and environmental samples

Over the sampling period, a total of 360 bacterial isolates were obtained, of which 140 isolates were presumptively and phenotypically identified as Gram positive. Further biochemical testing confirmed 76 of the total number of samples collected both clinical and environmental isolates were Staphylococcus species.

Phenotypic and taxonomic identification of Staphylococcus strains

This study further confirmed the identities of the Staphylococcus species obtained from the clinical and environmental sources by 16S rRNA gene sequencing analysis. Of Staphylococcus species (n = 76), 56.58% were coagulase-negative (CoNS) and 43.42% coagulase-positive (S. aureus). Twenty-seven of these were from clinical sources, 14 from hospital effluents and 35 isolates originated from environmental (wastewater) sources. Among the clinical isolates, 10 were from urine, 4 from wounds, 6 from skin, 4 from blood and 1 isolate from pus. Environmental samples constituted 40% (n = 14) from the hospital generated wastewaters (effluents) and 60% (n = 21) from surrounding wastewater bodies at proximity to the hospital.

Figure 1

Distribution of Staphylococcus isolates obtained from clinical and wastewater samples.

Figure 1

Distribution of Staphylococcus isolates obtained from clinical and wastewater samples.

Figure 2

Antibiotic resistance profile of Staphylococcus isolates. Key: R indicates ‘resistant’ and S ‘susceptible’. FOX (Methicillin) (30 μg), OFX (Ofloxacin) (5 μg), ERY (Erythromycin) (15 μg), CLO (Cloxacillin) (5 μg), CRM (Cefuroxime) (30 μg), GEN (Gentamycin) (10 μg), IPM (Imipenem) (10 μg), AZM (Azithromycin) (15 μg), CAZ (Ceftazidime) (30 μg), AMC (Amoxycillin) (2 μg), AUG (Augmentin) (30 μg), CIP (Ciprofloxacin) (5 μg) and VAN (Vancomycin) (30 μg).

Figure 2

Antibiotic resistance profile of Staphylococcus isolates. Key: R indicates ‘resistant’ and S ‘susceptible’. FOX (Methicillin) (30 μg), OFX (Ofloxacin) (5 μg), ERY (Erythromycin) (15 μg), CLO (Cloxacillin) (5 μg), CRM (Cefuroxime) (30 μg), GEN (Gentamycin) (10 μg), IPM (Imipenem) (10 μg), AZM (Azithromycin) (15 μg), CAZ (Ceftazidime) (30 μg), AMC (Amoxycillin) (2 μg), AUG (Augmentin) (30 μg), CIP (Ciprofloxacin) (5 μg) and VAN (Vancomycin) (30 μg).

Distribution of Staphylococcal species

A total of 11 different Staphylococcus species were obtained in this study (Figure 1). Forty-three percent of the isolates were identified as S. aureus. Other species included S. sciuri (17.1%) and S. cohnii (11.8%) as well as S. arlettae, S. epidermidis and S. saprophyticus (6.5%). There were single representatives of S. equorum, S. warneri, S. xylosus and S. kloosii.

In terms of species distribution, 78.87% of the Staphylococcus strains obtained were found in both clinical and environmental sources (Figure 1). These were S. aureus, S. cohnii, S. sciuri, S. haemolyticus, S. arlettae, S. saprophyticus and S. epidermidis. On the other hand, S. sciuri and S. haemolyticus were isolated more frequently from environmental water sources. It was observed that four of the species were found either in the clinical or environmental source but not in both. Among these species were S. equorum (found only in clinical sources) and S. warneri, S. kloosii and S. xylosus occurring only in environmental samples. Furthermore, three Staphylococcus species exclusively found in environmental sources were isolated from the hospital effluents (Table 2). These observations are not absolute and could be biased since the isolation process was a culture-based selective process. Nonetheless, it provided some insights into culturable staphylococci associated with hospital effluent, environmental water and a potential link to clinical staphylococci.

Table 2

Identification, source, antibiotic resistance pattern and MAR indices of Staphylococcus species isolated from clinical and environmental samples

S No.IsolatesAccession numberSourcesSample typeAntibiotics
FOXOFXERYCLOCRMGENIPMAZMCAZAMCAUGCIPVANRMAR per isolate
1. S. cohnii KY290719 Clinical Wound 0.7 
2. S. arlettae KY290720 Clinical Skin 0.6 
3. S. equorum KY290721 Clinical Pus 0.6 
4. S. aureus KY290722 Clinical Wound 0.5 
5. S. aureus KY290723 Clinical Skin 0.4 
6. S. cohnii KY290724 Clinical Wound 0.5 
7. S. arlettae KY290725 Clinical Urine 0.3 
8. S. cohnii KY290726 Clinical Wound 0.3 
9. S. epidermidis KY290727 Clinical Skin 0.6 
10. S. sciuri KY290728 Clinical Urine 0.6 
11. S. saprophyicus KY290729 Clinical Urine 0.5 
12. S. aureus KY290730 Clinical Urine 0.5 
13. S. cohnii KY290731 Clinical Urine 0.5 
14. S. aureus KY290732 Clinical Blood 0.2 
15. S. arlettae KY290733 Clinical Urine 0.5 
16. S. cohnii KY290734 Clinical Skin 11 0.8 
17. S. aureus KY290735 Clinical Bone 0.2 
18. S. cohnii KY290736 Clinical Blood 0.4 
19. S. sciuri KY290737 Clinical Urine 0.3 
20. S. haemolyticus KY290738 Clinical Skin 0.5 
21. S. sciuri KY290739 Clinical Urine 0.3 
22. S. sciuri KY290740 Clinical Urine 0.5 
23. S. aureus KY290741 Clinical Bone 0.7 
24. S. cohnii KY290742 Clinical Urine 12 0.9 
25. S. cohnii KY290743 Clinical Blood 0.4 
26. S. epidermidis KY290744 Clinical Skin 0.4 
27. S. arlettae KY290745 Clinical Blood 0.3 
MAR index for clinical isolates = 0.482 
28. S. aureus KY290702 Hospital wastewater Effluent 0.5 
29. S. sciuri KY290703 Hospital wastewater Effluent 0.5 
30. S. haemolyticus KY290704 Hospital wastewater Effluent 0.5 
31. S. arlettae KY290705 Hospital wastewater Effluent 0.5 
32. S. saprophyticus KY290706 Hospital wastewater Effluent 0.6 
33. S. epidermidis KY290707 Hospital wastewater Effluent 0.6 
34. S. epidermidis KY290708 Hospital wastewater Effluent 0.5 
35. S. warneri KY290709 Hospital wastewater Effluent 0.4 
36. S. Kloosi KY290710 Hospital wastewater Effluent 0.3 
37. S. xylosus KY290711 Hospital wastewater Effluent 0.6 
38. S. aureus MK208534 Hospital wastewater Effluent 0.5 
39. S. aureus MK208535 Hospital wastewater Effluent 10 0.8 
40. S. aureus MK208536 Hospital wastewater Effluent 12 0.9 
41. S. aureus MK208537 Hospital wastewater Effluent 0.1 
MAR index for hospital wastewater = 0.500 
42. S. aureus MK208538 Environmental Water 0.7 
43. S. aureus MK208539 Environmental Water 0.3 
44. S. aureus MK208540 Environmental Water 10 0.8 
45. S. aureus MK208568 Environmental Water 0.5 
46. S. aureus MK208568 Environmental Water 0.6 
47. S. aureus MK208568 Environmental Water 0.6 
48. S. aureus MK208568 Environmental Water 0.3 
49. S. aureus MK208545 Environmental Water 0.1 
50. S. aureus MK208546 Environmental Water 0.7 
51. S. aureus MK208547 Environmental Water 0.4 
52. S. aureus MK208548 Environmental Water 0.7 
53. S. aureus MK208549 Environmental Water 0.6 
54. S. aureus MK208550 Environmental Water 0.5 
55. S. aureus MK208551 Environmental Water 0.2 
56. S. aureus MK208552 Environmental Water 0.1 
57. S. haemolyticus MK208553 Environmental Water 0.3 
58. S. aureus MK208554 Environmental Water 0.1 
59. S. aureus MK208555 Environmental Water 0.1 
60. S. cohnii MK208556 Environmental Water 10 0.8 
61. S. epidermidis MK208557 Environmental Water 0.4 
62. S. epidermidis MK208558 Environmental Water 0.5 
63. S. aureus MK208559 Environmental Water 0.5 
64. S. epidermidis MK208560 Environmental Water 0.1 
65. S. epidermidis MK208561 Environmental Water 0.1 
66. S. epidermidis MK208562 Environmental Water 0.3 
67. S. epidermidis MK208563 Environmental Water 0.3 
68. S. aureus MK208564 Environmental Water 11 0.8 
69. S. epidermidis MK208565 Environmental Water 0.6 
70. S. haemolyticus MK208566 Environmental Water 0.6 
71. S. epidermidis MK208567 Environmental Water 0.4 
72. S. aureus MK208568 Environmental Water 0.5 
73. S. aureus MK208569 Environmental Water 0.3 
74. S. epidermidis MK208570 Environmental Water 0.4 
75. S. haemolyticus MK208571 Environmental Water 0.5 
76. S. aureus MK208572 Environmental Water 0.6 
MAR index for environmental receiving water = 0.435 
S No.IsolatesAccession numberSourcesSample typeAntibiotics
FOXOFXERYCLOCRMGENIPMAZMCAZAMCAUGCIPVANRMAR per isolate
1. S. cohnii KY290719 Clinical Wound 0.7 
2. S. arlettae KY290720 Clinical Skin 0.6 
3. S. equorum KY290721 Clinical Pus 0.6 
4. S. aureus KY290722 Clinical Wound 0.5 
5. S. aureus KY290723 Clinical Skin 0.4 
6. S. cohnii KY290724 Clinical Wound 0.5 
7. S. arlettae KY290725 Clinical Urine 0.3 
8. S. cohnii KY290726 Clinical Wound 0.3 
9. S. epidermidis KY290727 Clinical Skin 0.6 
10. S. sciuri KY290728 Clinical Urine 0.6 
11. S. saprophyicus KY290729 Clinical Urine 0.5 
12. S. aureus KY290730 Clinical Urine 0.5 
13. S. cohnii KY290731 Clinical Urine 0.5 
14. S. aureus KY290732 Clinical Blood 0.2 
15. S. arlettae KY290733 Clinical Urine 0.5 
16. S. cohnii KY290734 Clinical Skin 11 0.8 
17. S. aureus KY290735 Clinical Bone 0.2 
18. S. cohnii KY290736 Clinical Blood 0.4 
19. S. sciuri KY290737 Clinical Urine 0.3 
20. S. haemolyticus KY290738 Clinical Skin 0.5 
21. S. sciuri KY290739 Clinical Urine 0.3 
22. S. sciuri KY290740 Clinical Urine 0.5 
23. S. aureus KY290741 Clinical Bone 0.7 
24. S. cohnii KY290742 Clinical Urine 12 0.9 
25. S. cohnii KY290743 Clinical Blood 0.4 
26. S. epidermidis KY290744 Clinical Skin 0.4 
27. S. arlettae KY290745 Clinical Blood 0.3 
MAR index for clinical isolates = 0.482 
28. S. aureus KY290702 Hospital wastewater Effluent 0.5 
29. S. sciuri KY290703 Hospital wastewater Effluent 0.5 
30. S. haemolyticus KY290704 Hospital wastewater Effluent 0.5 
31. S. arlettae KY290705 Hospital wastewater Effluent 0.5 
32. S. saprophyticus KY290706 Hospital wastewater Effluent 0.6 
33. S. epidermidis KY290707 Hospital wastewater Effluent 0.6 
34. S. epidermidis KY290708 Hospital wastewater Effluent 0.5 
35. S. warneri KY290709 Hospital wastewater Effluent 0.4 
36. S. Kloosi KY290710 Hospital wastewater Effluent 0.3 
37. S. xylosus KY290711 Hospital wastewater Effluent 0.6 
38. S. aureus MK208534 Hospital wastewater Effluent 0.5 
39. S. aureus MK208535 Hospital wastewater Effluent 10 0.8 
40. S. aureus MK208536 Hospital wastewater Effluent 12 0.9 
41. S. aureus MK208537 Hospital wastewater Effluent 0.1 
MAR index for hospital wastewater = 0.500 
42. S. aureus MK208538 Environmental Water 0.7 
43. S. aureus MK208539 Environmental Water 0.3 
44. S. aureus MK208540 Environmental Water 10 0.8 
45. S. aureus MK208568 Environmental Water 0.5 
46. S. aureus MK208568 Environmental Water 0.6 
47. S. aureus MK208568 Environmental Water 0.6 
48. S. aureus MK208568 Environmental Water 0.3 
49. S. aureus MK208545 Environmental Water 0.1 
50. S. aureus MK208546 Environmental Water 0.7 
51. S. aureus MK208547 Environmental Water 0.4 
52. S. aureus MK208548 Environmental Water 0.7 
53. S. aureus MK208549 Environmental Water 0.6 
54. S. aureus MK208550 Environmental Water 0.5 
55. S. aureus MK208551 Environmental Water 0.2 
56. S. aureus MK208552 Environmental Water 0.1 
57. S. haemolyticus MK208553 Environmental Water 0.3 
58. S. aureus MK208554 Environmental Water 0.1 
59. S. aureus MK208555 Environmental Water 0.1 
60. S. cohnii MK208556 Environmental Water 10 0.8 
61. S. epidermidis MK208557 Environmental Water 0.4 
62. S. epidermidis MK208558 Environmental Water 0.5 
63. S. aureus MK208559 Environmental Water 0.5 
64. S. epidermidis MK208560 Environmental Water 0.1 
65. S. epidermidis MK208561 Environmental Water 0.1 
66. S. epidermidis MK208562 Environmental Water 0.3 
67. S. epidermidis MK208563 Environmental Water 0.3 
68. S. aureus MK208564 Environmental Water 11 0.8 
69. S. epidermidis MK208565 Environmental Water 0.6 
70. S. haemolyticus MK208566 Environmental Water 0.6 
71. S. epidermidis MK208567 Environmental Water 0.4 
72. S. aureus MK208568 Environmental Water 0.5 
73. S. aureus MK208569 Environmental Water 0.3 
74. S. epidermidis MK208570 Environmental Water 0.4 
75. S. haemolyticus MK208571 Environmental Water 0.5 
76. S. aureus MK208572 Environmental Water 0.6 
MAR index for environmental receiving water = 0.435 

Notes: R is the number of antibiotics an isolate was resistant to. FOX (Methicillin) (30 μg), OFX (Ofloxacin) (5 μg), ERY (Erythromycin) (15 μg), CLO (Cloxacillin) (5 μg), CRM (Cefuroxime) (30 μg), GEN (Gentamycin) (10 μg), IPM (Imipenem) (10 μg), AZM (Azithromycin) (15 μg), CAZ (Ceftazidime) (30 μg), AMC (Amoxycillin) (2 μg), AUG (Augmentin) (30 μg), CIP (Ciprofloxacin) (5 μg) and VAN (Vancomycin) (30 μg).

Antibiotic resistance patterns of Staphylococcus species

Many of Staphylococcus species were resistant to several classes of antibiotics (Table 2). The antibiotic(s) to which the highest number of isolates were resistant to included methicillin (the antibiotic of interest) and amoxycillin (91.7%). More than 80% were also resistant to cloxacillin, ciprofloxacin, ofloxacin and more than 70% to azithromycin, ceftazidime, gentamycin, cefuroxime and erythromycin (Figure 2). Forty-two percent were resistant to ceftriaxone. Among all these isolates, 90% and 84% were susceptible to imipenem and vancomycin, respectively. This implies that these antibiotics were still effective against the staphylococci from this region.

About 60% of the isolates were resistant to at least 6 of the 13 antibiotics (Table 2). Over 50% of the S. aureus isolates were methicillin-resistant (thus MRSA), while the others were susceptible to methicillin (MSSA).

Multiple antibiotic resistance

In this study, nearly all the isolates (69 of 76; 90.8%) had an MAR index higher than 0.2 while only 7 (9.2%) had an MAR index <0.2. The Staphylococcus isolates with an MAR index greater than 0.2 were mainly clinical isolates (Table 2). Furthermore, the mean overall MAR values of clinical, hospital wastewater effluents and environmental water were calculated and compared. The overall MAR index values for Staphylococcus species isolated from the clinical, hospital effluent and environmental wastewaters were 0.482, 0.500 and 0.435, respectively (Table 2). These MAR index values were relatively similar.

Detection of resistance and virulence genes in Staphylococcus species

The detection of resistance and virulence genes among the Staphylococcus species varied. It was observed that of the 11 different species, six (54.5%) tested positive for the resistance gene – mecA. Of all 11 species, S. aureus was the only strain that was positive for all three genes. S. sciuri and S. cohnii (six isolates each), S. arlettae and S. epidermidis (five isolates each) and a single isolate of S. saprophyticus were positive for only the mecA gene but neither nuc nor luk-pvl genes. Overall, approximately 55.3% (42 out of 76) of the isolates analysed in this study were positive for the ARG – mecA. Neither resistance nor virulence genes were detected in S. haemolyticus, S. equorum, S. warnerii, S. kloosii and S. xylosus species.

The mecA gene was detected among 83.3% of the Staphylococcus species originated from clinical sources, while it was detected in 16.7% environmental samples. These were mainly from the hospital wastewater. Similarly, for the nuc gene, 54.5% of the strains that were positive for this gene were isolated from clinical sources, while 45.5% were isolated from wastewater sources. However, with the luk-pvl virulence gene, all the isolates were S. aureus from clinical sources. Largely, 63% of the isolates which were positive for the resistance and virulence genes originated from clinical samples while 37% were from environmental sources.

DISCUSSION

Studies have focussed on S. aureus and CoNS from clinical sources in West Africa (Nanoukona et al. 2017) and Nigeria (Shittu et al. 2012; Vitali et al. 2014). However, there is a paucity of data regarding these species in environmental sources (wastewater effluents and water bodies). In the present study, we found that 43.42% of isolates were coagulase-positive (S. aureus) and 56.58% coagulase-negative (CoNS). These isolates were from clinical, wastewater and environmental water samples. The 10 different CoNS species identified included – S. cohnii, S. epidermidis, S. saprophyticus, S. haemolyticus, S. arlettae, S. scuiri, S. xylosus, S. warneri, S. equorum and S. kloosii. Similar observations were made in previous studies. A study conducted by Gómez et al. (2017) on wastewaters in Spain demonstrated the occurrence of 16.67% S. aureus and 83.33% CoNS species. These authors observed 12 different species. Furthermore, Shittu et al. (2012) and Tayyar et al. (2015) found S. haemolyticus, S. epidermidis, S. saprophyticus and S. xylosus in clinical samples. Similarly, Nanoukona et al. (2017) identified S. cohnii, S. sciuri, S. arlettae, S. warneri and S. kloosii also in clinical samples. Gómez et al. (2017) found S. epidermidis, S. sciuri, S. xylosus, S. equorum and S. warneri in wastewater samples.

The present study demonstrated the occurrence of S. cohnii and S. equorum in clinical samples and S. xylosus, S. warneri and S. kloosii in wastewater sources. These results are corroborated by previous studies. Both Chen et al. (2015) and Gómez et al. (2016) suggested that the reason few studies have reported S. cohnii in wastewater is because they are mainly associated with nosocomial infections. Therefore, finding them in wastewater may suggest that their origin is from a clinical setting (Vitali et al. 2014; Hitzenbichler et al. 2017; Nanoukona et al. 2017). A study by Gómez et al. (2017) demonstrated that S. xylosus and S. warneri to occur in wastewaters. This is consistent with the findings from the present study. These observations confirmed that the S. warneri and S. kloosii could be present in hospital effluents. This may possibly suggest that they are likely to originate from clinical sources and then could be transported to environmental water bodies where they could be a potential health threat. Staphylococcus equorum, a very rare species could be present in wastewaters (Gómez et al. 2017). It had earlier been reported to also be associated with clinical scenarios (Nováková et al. 2006). S. kloosii isolated from wastewaters in this study was also previously isolated from clinical sources (Nanoukona et al. 2017). In the present study, various Staphylococcus sp. had been isolated from clinical samples, hospital effluent and receiving environmental waters. These findings were supported by previous studies showing similar trends. The prevalence of the nine different species found in these aquatic environmental habitats may be ascribed to their capability to survive under the existing conditions for extended periods (Šolić & Krustulović 1994; Tolba et al. 2008; Abulreesh 2011).

With respect to antimicrobial resistance, almost all the Staphylococcus species were resistant to several classes of antibiotics. Isolates were defined as multi-resistant based on resistance to methicillin and at least two other classes of antibiotics (Magiorakos et al. 2012). Specifically, over 50% of S. aureus isolates from both clinical and environmental sources were methicillin-resistant (MRSA), while the others were susceptible to methicillin (MSSA). S. saprophyticus isolates were all resistant to methicillin. Furthermore, a strain of S. cohnii was resistant to 12 of the 13 antibiotics tested. This finding is supported by Delorme et al. (2017) and Nanoukona et al. (2017) that found S. chonii resistant to a large number of antibiotics. In the present study, it was demonstrated that most of the isolates (91.7%) were resistant to methicillin and amoxycillin. This trend had also been confirmed by previous studies (Moges et al. 2014; Tayyar et al. 2015; Premanadham et al. 2017). On the contrary, most of the Staphylococcus species were susceptible to vancomycin (84.0%) and imipenem (90.0%) demonstrating that these antibiotics are still useful in clinical settings. A similar trend of antibiotic susceptibility of Staphylococcus spp. had been documented in previous studies (Thomas et al. 2016; Hitzenbichler et al. 2017). The high susceptibility rate recorded for vancomycin and imipenem had been ascribed to the fact that these drugs are usually not commonly prescribed in the hospital settings (Thomas et al. 2016). This demonstrates that antibiotic stewardship and regulation may still delay the onset of antibiotic resistance, even in developing regions of the world. Vancomycin is a glycopeptide antibiotic that is seen as a drug of choice and a good therapeutic option for treating severe bacterial infections, especially multi-drug resistance MRSA strains (Hitzenbichler et al. 2017). Although the efficacy of vancomycin may be reduced when administered intravenously as a single dose, its combination with other antibacterial agents, such as imipenem, has given better treatment outcomes (Erjavec et al. 1994; Courvalin 2006).

Overall, all the species from Staphylococcus sp. displayed multiple resistance traits towards antibiotics. The CoNS in this study were resistant to a higher number of antibiotics compared with S. aureus. This result confirms the multi-resistance potential of S. aureus and CoNS to antibiotics used in clinical settings. Our finding is corroborated by Center et al. (2003) who reported that CoNS species generally have decreased susceptibilities to various antibiotics.

It was confirmed that strains of the same Staphylococcus species demonstrated similar antibiotic resistance/susceptibility patterns regardless of their isolation sources (clinical or environmental). Of note is the very high number of Staphylococcus species that had an MAR index greater than 0.2. Furthermore, the overall MAR values of clinical, hospital wastewater effluents and environmental water numerically relatively quite similar. These similar MAR indices may indirectly suggest that all the isolates were from the sources where antibiotics are often used. This also implies that the strains from the clinical/hospital wastewater effluent and environmental water might have a common origin (Krumperman 1983; Riaz et al. 2011). Furthermore, this index demonstrates frequent exposure of the bacteria to antibiotics of various classes (Krumperman 1983; Riaz et al. 2011). It could also indicate that ARGs may be well distributed among the bacteria in environmental wastewaters where there is the interphase of the clinical and environmental strains (Rosenberg Goldstein et al. 2012; Gómez et al. 2017). MAR in bacteria is most commonly associated with the presence of plasmids or other mobile elements which contain one or more resistance genes, each encoding a single antibiotic resistance phenotype (Riaz et al. 2011).

The detection of multi-drug resistance phenotype, with mecA (54.5%) and nuc (100%) resistance and virulence genes, respectively, were confirmed in S. aureus isolates. Only the mecA gene was detected in S. arlettae, S. scuiri, S. cohnii, S. epidermidis and S. saprophyticus. The detection of the mecA resistance gene in CoNS species had been reported by previous studies (Shittu et al. 2012; Vitali et al. 2014; Gómez et al. 2017). The mecA gene allows a bacterium to be resistant to antibiotics such as methicillin and penicillin. The most commonly known carrier of the mecA gene is the bacterium known as MRSA (Igbinosa et al. 2016). In addition, the detection of the virulence gene, luk-pvl was confirmed in the six S. aureus representatives isolated from clinical samples only. Panton–Valentine leukocidin (PVL) is considered one of the important virulence factors responsible for white cell destruction and as a marker of community-acquired MRSA (Yang et al. 2009; Igbinosa et al. 2016).

All Staphylococcus species isolated from wastewater sources were negative for the luk-pvl virulence gene. This trend has been confirmed in a previous study (Gómez et al. 2017). The detection of mecA resistance gene in CoNS had been ascribed to possible HGT by mobile genetic components (such as plasmids, intergrons and transposons) from S. aureus species, which could facilitate the environmental dissemination of the ARGs to CoNS (Calero-Caceres et al. 2017; Tripathi & Tripathi 2017; Jensen et al. 2019). This scenario may be the case in the present study, where the hospital wastewater could be the source of mecA and HGT could be responsible for the dispersal of this gene to other staphylococci.

CONCLUSION

This study highlighted the prevalence and diversity of Staphylococcus spp. in both clinical and environmental sources. Staphylococcus spp. containing the mecA gene was detected in the water body receiving hospital wastewaters. Among the mecA positive isolates were S. cohnii a coagulase-negative staphylococci normally not considered as a pathogen in the clinical settings. All strains of the same Staphylococcus species displayed the same antibiotic resistance/susceptibility trend regardless of their isolation sources (clinical or environmental). This potentially shows that there may be a link between the various habitats. These findings on prevalence, diversity and multi-drug resistance staphylococci, particularly CoNS in wastewater and receiving water sources, are worrisome. Environmental water sources are used for agricultural, direct exposure (recreational) and drinking water production purposes. Finding these Staphylococcus species potentially from the clinical origin in environmental water is cause for concern. These bacterial species are normally not tested for in microbiological water quality analyses. This raises the issue of regulations and testing regimes of environmental water that receives hospital wastewater. It calls for stringent regulations and proper treatment of hospital effluents before disposal to receiving wastewaters. This would reduce the risks posed to human and animal health and safety and may as well also play an important role in mitigation of global antibiotic resistance, particularly of mecA associated resistance.

ACKNOWLEDGEMENTS

The authors sincerely appreciate Messrs Abram Mahlatsi, Michael Adebowale, Sipho Ndhlovu, Israel Ojo and Mrs Lee Chenhaka for their assistance during this study.

FUNDING

The authors acknowledge the financial support of the North-West University, Potchefstroom, South Africa. Also, this work is based on research supported in part by the National Research Foundation (NRF) of South Africa for Grant Nos. 113824 and 109207 and the Water Research Commission (WRC) of South Africa (project K5/2347//3). Views expressed are those of the authors and not of the funders.

ETHICAL STATEMENT

This study was approved by the ethics committee of the hospital used in Ile-Ife, Nigeria, under protocol number: SERC-2016-001-NWU-SA and Health Research Ethics Committee (HREC) of the Faculty of Health Sciences, North-West University, Potchefstroom, South Africa, under ethics number: NWU-00122-17-S1. All clinical staphylococcal isolates evaluated in this study were obtained from the Microbiology Laboratory of the Medical Institution, Ile-Ife, Nigeria, and were anonymized.

HEALTH AND SAFETY

The authors declare that all mandatory laboratory health and safety procedures and protocols were complied with while conducting the experimental work reported in this study.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

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