Antibiotic Exposure in a Low-Income Country: Screening Urine Samples for Presence of Antibiotics and Antibiotic Resistance in Coagulase Negative Staphylococcal Contaminants

Lerbech, Anne Mette; Opintan, Japheth A.; Bekoe, Samuel Oppong; Ahiabu, Mary‐Anne; Tersbøl, Britt Pinkowski; Hansen, Martin; Brightson, Kennedy; Ametepeh, Samuel; Frimodt‐Møller, Niels; Styrishave, Bjarne

doi:10.1371/journal.pone.0113055

Cited by 35 publications

(44 citation statements)

References 49 publications

(56 reference statements)

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“…equally showed a high level of resistance mostly to tetracycline (57%), doxycycline (44%), and penicillin (28%). However, the resistance observed toward penicillin was less than the number Lerbech et al29 reported, with 98% CoNS isolates from humans being resistant to penicillin. The high resistance of CoNS to penicillin reported by Lerbech et al29 could be due to the fact that all the isolates were obtained from patients, and such isolates have been found to be highly resistant to beta-lactams 30.…”

Section: Discussionmentioning

confidence: 76%

“…However, the resistance observed toward penicillin was less than the number Lerbech et al29 reported, with 98% CoNS isolates from humans being resistant to penicillin. The high resistance of CoNS to penicillin reported by Lerbech et al29 could be due to the fact that all the isolates were obtained from patients, and such isolates have been found to be highly resistant to beta-lactams 30. Resistance of the isolates to tetracycline (57%) was almost similar to the 63% reported by Lerbech et al29…”

Section: Discussionmentioning

confidence: 76%

“…to several essential antibiotics over the past 30 years26–28 in different countries including Ghana 29. In this study, coagulase-negative Staphylococcus spp.…”

Section: Discussionmentioning

confidence: 89%

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Prevalence and antibiotic resistance of coagulase-negative <em>Staphylococci</em> isolated from poultry farms in three regions of Ghana

Boamah¹,

Agyare²,

Odoi³

et al. 2017

IDR

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The use of antibiotics in animal production has been associated with the development and spread of antibiotic-resistant organisms including commensals. Coagulase-negative Staphylococcus (CoNS) species, which were until recently considered non-pathogenic, have been associated with opportunistic infections and high resistance to several antibiotics. This study sought to determine the prevalence, identity, and phenotypic resistance of coagulase-negative Staphylococcus spp. isolated from some selected poultry farms and farm workers in the Ashanti, Brong Ahafo, and Greater Accra regions of Ghana. Poultry litter samples and oral swabs of poultry farm workers were collected, from which bacterial species were isolated, identified, and analyzed. Various selective media were used for the presumptive identification of the different species. Confirmation of bacterial identity was done using matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry. Antibiotic susceptibility testing of the isolates was performed using the Kirby-Bauer disk diffusion method. Zones of growth inhibition were interpreted based on the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines. Two hundred and fifty-six coagulase-negative Staphylococcus spp., comprising S. sciuri (42.97%), S. lentus (35.94%), S. gallinarum (6.64%), S. xylosus (4.30%), S. haemolyticus (3.91%), S. saprophyticus (1.95%), and S. cohnii (0.39%) were confirmed by MALDI-TOF. CoNS were isolated from samples from the Brong Ahafo (48.83%), Ashanti (33.59%), and Greater Accra (17.78%) regions. Isolates from poultry litter constituted 55.47%, and farm workers 44.53%. All the isolates were susceptible to amoxicillin/clavulanic acid and amikacin. The isolates exhibited high resistance toward tetracycline (57.03%), doxycycline (43.75%), and oxacillin (43.36%). Multi-drug resistance (MDR) was observed in 19.14% of the isolates. MDR was higher in isolates obtained from poultry farm workers (61.22%) than isolates from poultry litter (38.78%). The above findings call for stricter monitoring of antibiotic usage in both animal production and in humans.

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Section: Discussionmentioning

confidence: 76%

Section: Discussionmentioning

confidence: 76%

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Prevalence and antibiotic resistance of coagulase-negative <em>Staphylococci</em> isolated from poultry farms in three regions of Ghana

Boamah¹,

Agyare²,

Odoi³

et al. 2017

IDR

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“…Sample preparation was a critical procedure to determine analytes in complex matrix. It was a difficult extraction and cleanup process for many different classes compounds due to their different physicochemical properties . Methods reported to determine veterinary antimicrobial drugs in urine, faces, and water were LLE and SPE .…”

Section: Introductionmentioning

confidence: 99%

Multiclass method for the quantification of 92 veterinary antimicrobial drugs in livestock excreta, wastewater, and surface water by liquid chromatography with tandem mass spectrometry

et al. 2016

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A simple multiresidue method was developed for detecting and quantifying 92 veterinary antimicrobial drugs from eight classes (β-lactams, quinolones, sulfonamides, tetracyclines, lincomycins, macrolides, chloramphenicols, and pleuromutilin) in livestock excreta and water by liquid chromatography with tandem mass spectrometry. The feces samples were extracted by ultrasound-assisted extraction with a mixture of acetonitrile/water (80:20, v/v) and edetate disodium, followed by a cleanup using solid-phase extraction with an amino cartridge. Water samples were purified with hydrophilic-lipophilic balance solid-phase extraction column. Urine samples were extracted with acetonitrile and edetate disodium. Detection of veterinary antimicrobial drugs was achieved by liquid chromatography with tandem mass spectrometry using both positive and negative electrospray ionization mode. The recovery values of veterinary antimicrobial drugs in feces, urine, and water samples were 75-99, 85-110, and 85-101% and associated relative standard deviations were less than 15, 10, and 8%, respectively. The limits of quantification in feces, urine, and water samples were 0.5-1, 0.5-1, and 0.01-0.05 μg/L, respectively. This method was applied to determine real samples obtained from local farms and provides reliable quantification and identification results of 92 veterinary antimicrobial drugs in livestock excreta and water.

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“…␤-Lactamases are a major concern in modern health care due to their efficient inactivation of many ␤-lactams and their high variability in biochemical properties. The selective pressure by the widespread use of antibiotics has been assumed to lead to the development of new variants and to allow existing variants to surface (3,4). Even though the currently known sequences often vary by only a few amino acids, the minor changes allow for a variety of different substrate spectra and resistances and can be broadly classified into four phenotypes.…”

mentioning

confidence: 99%

Network Analysis of Sequence-Function Relationships and Exploration of Sequence Space of TEM β-Lactamases

Zeil

Widmann

Fademrecht

et al. 2016

Antimicrob Agents Chemother

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The Lactamase Engineering Database (www.LacED.uni-stuttgart.de) was developed to facilitate the classification and analysis of TEM ␤-lactamases. The current version contains 474 TEM variants. Two hundred fifty-nine variants form a large scale-free network of highly connected point mutants. The network was divided into three subnetworks which were enriched by single phenotypes: one network with predominantly 2be and two networks with 2br phenotypes. Fifteen positions were found to be highly variable, contributing to the majority of the observed variants. Since it is expected that a considerable fraction of the theoretical sequence space is functional, the currently sequenced 474 variants represent only the tip of the iceberg of functional TEM ␤-lactamase variants which form a huge natural reservoir of highly interconnected variants. Almost 50% of the variants are part of a quartet. Thus, two single mutations that result in functional enzymes can be combined into a functional protein. Most of these quartets consist of the same phenotype, or the mutations are additive with respect to the phenotype. By predicting quartets from triplets, 3,916 unknown variants were constructed. Eighty-seven variants complement multiple quartets and therefore have a high probability of being functional. The construction of a TEM ␤-lactamase network and subsequent analyses by clustering and quartet prediction are valuable tools to gain new insights into the viable sequence space of TEM ␤-lactamases and to predict their phenotype. The highly connected sequence space of TEM ␤-lactamases is ideally suited to network analysis and demonstrates the strengths of network analysis over tree reconstruction methods.T EM ␤-lactamases cause resistance of their host organisms against ␤-lactam based antibiotics, such as penicillin, by catalyzing the hydrolysis of the ␤-lactam ring. Since the discovery of the first TEM ␤-lactamase, TEM-1, in 1963, over 200 variants have been found (1). An annotated library of these sequences, further referenced as the TEM mutation table, is maintained by the Lahey clinic (2). ␤-Lactamases are a major concern in modern health care due to their efficient inactivation of many ␤-lactams and their high variability in biochemical properties. The selective pressure by the widespread use of antibiotics has been assumed to lead to the development of new variants and to allow existing variants to surface (3, 4). Even though the currently known sequences often vary by only a few amino acids, the minor changes allow for a variety of different substrate spectra and resistances and can be broadly classified into four phenotypes. According to the classification of ␤-lactamases done by Bush and Jacoby, the TEM family contains proteins that confer broad-or extended-spectrum activity (phenotypes 2b and 2be, respectively), inhibitor resistance (2br), or a combination of extended-spectrum activity and inhibitor resistance (2ber) (5, 23). Sequences at the TEM mutation table are classified mostly according to these categories. This makes t...

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Antibiotic Exposure in a Low-Income Country: Screening Urine Samples for Presence of Antibiotics and Antibiotic Resistance in Coagulase Negative Staphylococcal Contaminants

Cited by 35 publications

References 49 publications

Prevalence and antibiotic resistance of coagulase-negative <em>Staphylococci</em> isolated from poultry farms in three regions of Ghana

Prevalence and antibiotic resistance of coagulase-negative <em>Staphylococci</em> isolated from poultry farms in three regions of Ghana

Multiclass method for the quantification of 92 veterinary antimicrobial drugs in livestock excreta, wastewater, and surface water by liquid chromatography with tandem mass spectrometry

Network Analysis of Sequence-Function Relationships and Exploration of Sequence Space of TEM β-Lactamases

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