ABSTRACT
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.
CHAPTER ONE
GENERAL INTRODUCTION
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.
For more Pharmaceutics Projects Click here
===================================================================
Item Type: Ghanaian Topic | Size: 127 pages | Chapters: 1-5
Format: MS Word | Delivery: Within 30Mins.
===================================================================
No comments:
Post a Comment
Note: Only a member of this blog may post a comment.