Non-clinical isolates as potential reservoirs of antibiotic resistance in Port Harcourt, Nigeria

Introduction Multidrug resistance (MDR) is a growing problem worldwide. This type resistance often arises due to the sequential acquisition of drug resistance determinants and subsequent clonal spread. It is therefore important to determine possible reservoirs of these MDR gene to help set out control strategies. This study was aimed at analysing susceptibility patterns of various non-clinical Gram negative bacterial strains to determine their potential as reservoirs of MDR. Methods Thirty-five non-clinical Gram negative bacteria were identified and susceptibility profile determined using standard methodologies. Results Findings showed a preponderance of Pseudomonas aeruginosa and Escherichia Coli. Resistance rates of above 80% were noted in 50% of antibiotics, though none of the isolates were resistant to Ofloxacin. Majority of isolates (68.6%) had a multiple antibiotic resistance (MAR) index greater than 0.5, but only 20% of Escherichia Eoli. were found in this category. A high level of MDR was noted in this study (71.4%), but again only 20% of these were Escherichia Coli. Conclusion Gram negative bacteria are the most common group of bacteria frequently encountered in clinical microbiology. In more recent years, infections with these organisms have been further complicated by the phenomenon of drug resistance. Non-clinical isolates have been postulated as possible reservoirs. Findings from this study of widespread multidrug resistance support this idea. This study however highlights the lack of MDR in Escherichia Coli, which is promising. More extensive studies will need to be carried out to properly assess the role of non-clinical isolates as reservoirs of MDR determinants.


Introduction
The problem of multidrug antibiotic resistance is an ever growing one, with increasing reports on 'superbugs' made worldwide [1].
Multidrug resistance (MDR) has been defined as resistance or nonsusceptibility of an organism to at least one drug from 3 or more defined classes of antibiotics [2]. This phenomenon is commonly thought to result from the sequential acquisition of drug resistance determinants and clonal dissemination following an index case of point mutation rather than from widespread random point Aminoglycosides, Macrolides and Quinolones [5]. A recent report on a pandrug resistant isolate with resistance to Colistin even noted that this resistance was caused by the functional inactivation of a gene due to the insertion of a MGE that encodes resistance to Carbapenem [3]. Similarly, strains of VRE were shown to be resistant to a number of other antibiotics (Tetracycline, Erythromycin, Streptomycin and Gentamicin). The genes for these were carried on two conjugative transposons [6]. A similar trend has also been reported for MRSA [7]. High level MDR has been reported in several non-clinical isolates, with some studies suggesting that these isolates could act as sources of antimicrobial resistance (AMR) determinants to clinical strains [8][9][10]. This level of resistance, sometimes to the last line drugs effective against a group of microorganisms, has raised fears of a return to the pre-antibiotic era and the associated high mortality rates. While the development of resistance definitely appears to be driven by the selective pressure of antibiotic used in clinical settings, there is still a significant role for traffic of MGE even across species boundaries outside of clinical settings. In order to curb the development of drug resistance, it has become essential to properly assess possible reservoirs of MDR determinants. Over the years numerous reservoirs of drug resistance have been reported elsewhere [8,11]. Few studies have been carried out in Nigeria focused on assessing the role of nonclinical isolates to serve as reservoirs of multidrug resistance. This study therefore set out to analyse the susceptibility patterns of various non-clinical Gram negative bacteria in order to determine the potential of these bacteria as reservoirs of MDR.

Methods
Bacterial isolation and characterisation: Thirty-five Gram negative bacteria were isolated from various non-clinical sources affected by human interaction. These sources included, surface water (7), slaughter houses (9), cloak rooms of male and female hostels (19). These organisms were characterised using standard biochemical tests to determine their identities [12,13].
Antibiotic resistance testing: Resistance profile of each organism was determined using the Kirby Bauer disc diffusion technique [14]. This method involves first plating out a 0. Resistance profile was then generated for each organism from a standard [15] based on the zones of inhibition observed following a 24 hour incubation at 37οC.

Determination of MAR index and multidrug resistance:
The MAR index points at the level of resistance exhibited by each organism. This was calculated as a/b where "a" is the total number of antibiotic to which the organism was resistant and "b" is the total number of antibiotics against which the organisms were tested [16].
Multidrug resistance was then determined by ascertaining the drug class of each test antibiotic and noting those organisms with resistance to three or more classes. Antibiotic susceptibility profile: An analysis of the susceptibility profile of the test organisms revealed a high degree of resistance to antibacterial agents ( Figure 1). Of the 8 antibiotics tested, Page number not for citation purposes 3 resistance rates of above 80% were noted in 50% of antibiotics.

Results
The lowest level of resistance was noted with Ofloxacin (0%). In total, 13 antibiotic resistance profiles were observed (Table 1). Majority of test isolates (68.6%) had a MAR index above 0.5 ( Figure   2). An analysis of the data however, shows that the higher MAR index values were mainly found with P. aeruginosa, K. pneumoniae,  with Escherichia Coli being the more common member of the family detected, followed by K. pneumoniae and then Salmonella sp [17].
An assessment of all test isolates revealed high rates of resistance to 5 out of the 8 antibiotics tested. These 5 antibiotics represent 3 broad drug classes, the aminoglycosides, penicillins and cephalosporins. Both penicillins and cephalosporins are traditional first-line therapy drug options for treating Gram negative bacteria in general and enterobacteriaceae in particular [18]. Several studies have reported high rates of resistance to these drugs worldwide, often resulting in therapy failure and a worse prognosis for the patients [17,19]. This same trend is reflected in this current study where resistance rates of greater than 80% was noted for these two first line drugs. This high level resistance to first line drugs in nonclinical isolates should pose a major public health concern. Even more worrying is the high level resistance noted in this study against Gentamicin, an aminoglycoside. Though an older antibiotic, in more recent times there has been a tendency to use this drug to treat more serious Gram negative infections [20]. Therefore, high resistance rates in this class of drugs will further reduce available treatment options. One striking finding of this study was the 0% resistance to Ofloxacin reported. Despite some report of high level resistance to this drug [21,22], similar low levels of resistance against Ofloxacin have been widely reported in Nigeria and elsewhere [23][24][25]. Ofloxacin a second generation quinolone antibiotic belongs to one of the most prescribed group of antibiotics worldwide. Like other quinolones, Ofloxacin acts on gyrase and topoisomerase IV enzymes, making them toxic with the ability to fragment bacterial chromosome [26]. Unlike the other quinonlones however, Ofloxacin is unique in that it lacks plasmid-borne resistance [27].

Competing interests
The authors declare no competing interests.

Authors' contributions
Kome Otokunefor and Tosanwumi Vincent Otokunefor designed the study. Paul Agbude carried out most of the benchwork, Kome Otokunefor wrote the initial draft of the article. All authors read and approved of the final article. Table 1: Antibiotic resistance profile of bacterial isolates