Antibiotic resistance in bacteria is now a major global health challenge. The increase and indiscriminate use of antibiotics is pivotal in the selection of resistant bacteria strains and the spread of resistance genes and resistance determining factors. The occurrence of Pseudomonas aeruginosa, a commonly implicated organism in nosocomial infections as well as poultry diseases has been found to be on the increase in samples in Ghana. This study therefore sought to determine the prevalence, susceptibility pattern, resistance mechanisms, resistance determining factors and the clonal relatedness of P. aeruginosa isolates obtained from stool, urine, blood, poultry litter and the environment in the Ashanti Region of Ghana. The P. aeruginosa isolates were identified using their biochemical characteristics and genotypically confirmed through PCR amplification of specific outer membrane lipoprotein (oprL) genes. Kirby-Bauer disc diffusion method was used to determine the susceptibility of the isolates to commonly used antipseudomonal agents. Plasmid sizes and resistance determining factors present in the isolates were detected using alkaline lysis method and PCR, respectively. Out of 900 samples screened, 87(9.7%) P. aeruginosa isolates were obtained. 75% of the P. aeruginosa isolates from the various sources were identified to be resistant to more than a single antipseudomonal agent and 38(43.6%) of the isolates were multidrug resistant (resistant to antibiotics from three or more antipseudomonal classes). The most common resistance pattern was observed with ciprofloxacin (62%), gentamicin (69%) and ticarcillin (56%).
High prevalence of extended spectrum β-lactamases (84.2%), metallo- β-lactamases (34.1%) and AmpC inducible cephalosporinases (50%) were observed in the MDR isolates. However, no strain produced KPC type carbapenemase. Among the MDR strains, 57.8% displayed moderate to very high efflux capacity and 65.7% of the MDR isolates haboured one to five plasmids with sizes ranging from 2.0kb to 116.8kb. While common β- lactamase encoding genes (blaSHV, blaTEM, blaCTX-M, blaVIM and blaIMP) were not detected in any MDR isolates, class 1 integrons were detected in 89.4% of the MDR isolates with 15.7% and 13.1% respectively carrying quinolone resistance gene mutations in gyrA and parC subunits of DNA gyrase and topoisomerase IV. Antibiogram typing was found to be discriminatory (D=0.9502), differentiating the MDR isolates into 24 antibiogram types with 19 distinct susceptibility patterns and 5 antibiogroups. Genotypic relatedness of the strains from the various sources generated through ERIC-PCR identified all the P. aeruginosa isolates to belong to two groups at a similarity of 62%. Dendrogram generated using Pearson coefficient as a similarity index and UPGMA as a distance measure revealed 27 P. aeruginosa genotypes. All the clinical strains of P. aeruginosa were closely related. From this study, there is the possibility of MDR P. aeruginosa transfer from the environment to patients as well as among patients in the same hospital. P. aeruginosa strains in humans and poultry may develop extensive antipseudomonal resistance which could be disseminated between patients and the environment.

1.0 Introduction
The emergence and dissemination of antibiotic resistant bacteria is considered globally as a threat to antibacterial therapy (WHO, 2014). The revolutionary development of antibacterial agents was envisioned to bring a halt to the clinical difficulties posed by infectious bacteria in the pre-antibiotic era. The use of antibiotics in the treatment of infectious diseases resulted in a drastic decrease in mortality and morbidity (WHO, 2000). With the view that the battle against infectious bacteria had been won, most drug manufacturers refocused their attention on finding remedies to metabolic or non-communicable diseases. However, within a few years after the introduction of penicillin, penicillin resistant strains of Staphylococcus aureus began to emerge. Since then, there has been a global surge of antibiotic resistance, resulting in serious global public health concern with economic, social and political implications (WHO, 2014).

Extended spectrum β-lactamases (ESBL) producing and carbapenem resistant Enterobacteriacae (CRE), vancomycin-resistant Enterococcus (VRE), Methicillin-resistant Staphylococcus aureus (MRSA), multidrug-resistant Pseudomonas aeruginosa and Acinetobacter, drug-resistant Campylobacter, Shigella, typhoidal and non-typhoidal Salmonella are now widespread globally (Center for Disease Control (CDC), 2013).

Increasing trends of antimicrobial resistance in Gram-negative bacteria has been observed in Europe, illustrating the continuous loss of effective antimicrobial therapy (European Antibiotic Resistance surveillance network (EARS-Net, 2012). Within the African region, the true extent of antibiotic resistance is limited. This is because surveillance of drug  resistance is carried out in a few countries (EARS-Net, 2012). There is also scarcity of accurate and reliable data on antibiotic resistance for common infectious conditions of public health significance such as meningitis, pneumonia and bloodstream infections. The few available data however, indicates that, the African region shares the worldwide trend of increasing drug resistance (WHO, 2014).

Newman et al. (2015) reported high prevalence and resistance of common pathogenic bacteria from both the northern and southern sectors of Ghana. In the study, common antibacterial agents like ampicillin, tetracycline, chloramphenicol, trimethoprim and sulfamethoxazole were found to be ineffective in about 80% of the frequently isolated pathogenic bacteria. Most of the isolates were multidrug-resistant (MDR) with over 50% producing β-lactamase. Almost 90% of the isolates sampled produced ESBLS (Newman et al., 2015). There have also been previous reports of high levels of resistant bacterial isolates in both teaching and regional hospitals in Ghana (Newman et al., 2006; Bieranye, 2011).

The global rise in the trends of antibiotic resistant bacteria has resulted in a corresponding increase in the amount and frequency of antibacterial use (Levy and Marshall, 2004). As a result, treatment costs for previously easily treatable infections are now high, due to treatment failures. It is estimated that drug resistant infections could cause 100 million deaths and cost approximately US $100 trillion a year by 2050 (O’Neill, 2014).

The evolution and spread of resistant bacteria can be attributed to both natural phenomena as well as human practices in the area of antibiotic use (WHO, 2015). Antibiotics either provide selective pressure that results in the acquisition of resistance through mutation or 2 transfer of resistance determining factors such as conjugable plasmids, transposons, integrons and antibiotic resistance genes (Davies and Davies, 2010). Resistance to antibiotics can be intrinsic or acquired. Naturally, genetic determinants of defense mechanisms may originate from bacteria such as antibiotic producing bacteria (Dantas and Sommer, 2014). As a defense against their own antibiotics produced, these bacteria may carry genes responsible for antibiotic resistance. These genes may be integrated into mobile genetic elements such as plasmids, transposons and integrons which could be passed on through horizontal transfer to other bacteria (Dantas and Sommer, 2014). The overuse and misuse of antibiotics in the treatment of human illness, animal husbandry and agriculture leaves residual traces of these antibiotics in the respective environments, enabling the population of bacteria to adapt and acquire resistance (Joanne et al., 2009).

The existence and growing concern of the problem of antibiotic resistance has called for global efforts to protect the few effective antibiotics. Surveillance of antibiotic resistance is an essential part of an effective response to the global threat of antibiotic resistance (Laxminarayan et al., 2013). Surveillance results provide information on the magnitude and the trends of resistance. The World Health Organization’s (WHO) Global Action Plan against antimicrobial resistance has also identified surveillance as one of the key pillars to combating this problem (WHO, 2014). In light of this, WHO first attempted in 2013, to assemble information on national antibiotic surveillance in order to present a global picture of the problem. Extensive national and regional programmes have been instituted to monitor antibiotic resistance patterns in high income countries. Thus, in resource-limited countries like Ghana, which are also stricken with a high burden of infectious diseases, the need arises for extensive surveillance of antibiotic use and resistance patterns of common pathogens. This will augment the global efforts to monitor and curb the problem of antibiotic resistance.

The concerted efforts of the European Antimicrobial Resistance Surveillance System (EARSS), now the European Antimicrobial Resistance Surveillance Network (EARS-Net), the Swedish Strategic Programme for the Rational Use of Antimicrobial Agents and Surveillance of Resistance, and the Action on Antibiotic Resistance (ReAct), through their vision of a world free from fear of untreatable infections, have empowered many countries including Ghana to take up the fight against antibiotic resistance. This is evident in the support offered Ghana through the Antibiotic Drug use Monitoring and Evaluation of Resistance (ADMER) project, for a six month nationwide surveillance of antimicrobial resistance (Newman et al., 2015). Reports from this study indicated occurrence of Escherichia coli (27.5%), Pseudomonas species (14%), Staphylococcus aureus (11.5%), Enterobacter species (9.3%), Citrobacter (9.1%), Streptococcus species (2.3%) and Salmonella enterica serovar typhi (0.6%) in about 1,598 clinical samples collected nationwide.

The primary source of most of the collected samples used for the routine surveillance of antibiotic resistance were in and out-patients who presented to the various regional and district hospitals in the country (Newman et al., 2015). Likewise, routine surveillance in most countries employs samples from critically infected patients with less samples taken from the community (WHO, 2014). This presents a limitation to the nationwide prevalence picture and the resistance profiles of the important pathogenic bacteria being monitored.

Local surveillance of the resistance profiles and characterization of prevalent resistant bacteria in selection prone areas like animal husbandry, aquaculture and agriculture are vital to the fight against antibiotic resistance (Centre for Disease Dynamics, Economics and Policy (CDDEP), 2015). Wide surveillance studies fail to fully characterize and identify the spread of particular resistant strains of bacteria. However, determining the selection, evolution, source, spread, resistance profile and mechanism of resistance are epidemiologically relevant and key to gaining control of the problem of antibiotic resistance (EARS-Net, 2012). A particular resistance strain that evolves in an environment highly selective of resistance may have its resistance determining factors shared within the surrounding bacteria population. Dissemination of this resistant strain through human contact, food, water, animal waste, wind or any other natural phenomena will ensure acquisition of the resistant traits by commensal pathogenic and non-pathogenic bacteria (Dantas and Sommer, 2014).

Monitoring and characterizing bacteria such as Pseudomonas aeruginosa, Escherichia coli and Staphylococcus aureus in different environments, makes it possible to compare the prevalence of resistance, and detect possible transfer of resistant bacteria and resistance genes between animals, humans and the environment. It also helps to identify any rising antibiotic resistance selective factors as well as resistance selective environments (Bogaard and Stobberingh, 2000).

Particularly, high prevalence of Pseudomonas species in clinical samples is worrying, owing to its intrinsic resistance and the therapeutic challenges it poses. It is ubiquitous in moist environments like water, soils, plants and animals. It can colonize human body sites, with preference for moist areas such as skin (0-2%), nasal mucosa (0-3.3%), throat (0-6.6%), faecal samples (2.6-24%), ear and perineum (Mena and Gerba, 2009). Among poultry, diseases of Pseudomonas occurs in chickens, ducks, geese and ostriches (Patttison et al., 2008). This bacteria presents a great therapeutic challenge due to the complexity of mechanisms which confer resistance both intrinsically and extrinsically (Lister et al., 2009). Its intrinsic resistance is to a wide range of antibiotics including ampicillin, amoxicillin, ceftriaxone, tetracyclines, trimethoprim, chloramphenicol and ertapenem, with a few antibiotics like piperacillin, ticarcillin, ceftazidime, cefepime, meropenem, imipenem, aztreonam and polymyxin B remaining effective (EUCAST, 2015; Mesaros et al., 2007).

The therapeutic difficulty posed by P. aeruginosa is worsened by its ability to develop resistance to multiple classes of antibacterial agents during the course of therapy. This makes selection of antibiotics for management of related infection difficult, doubling the length of hospitalization and the overall cost of patient care (Hancock and Speert, 2000). The prevalence and spread of multidrug resistant strains of this bacteria in flagged areas of high antibiotic use such as animal husbandary and human medicine in the country is of great concern. This study thus seeks to identify and characterize resistance profiles and resistance determining factors in multidrug-resistant strains of Pseudomonas aeruginosa from poultry farms, patients and the environment.

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Item Type: Ghanaian Topic  |  Size: 127 pages  |  Chapters: 1-5
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