Distribution of Antibiotic Resistant Bacteria in Selected Aquaculture Farms in Sarawak

There is a growing awareness on the importance of aquaculture for the social-economical livelihood for low- and mid-income community. Due to the domestic and global demand for fish meat as a preferred source of protein, this had generated a rampant growth of the aquaculture industry seen across the globe alongside a heavy use of antibiotics. These activities pose a risk of spreading antibiotic resistant bacteria (ARB) to the aquaculture environment, which tends to develop among environmental bacteria that is exposed to antibiotics. This study aimed to detect the distribution of ARB from five selected aquaculture farms in Sarawak. A total of 350 samples consisted of fish (108 samples), sediment (113 samples) and water (129 samples) were collected from five selected aquaculture farms within Sarawak. The samples were kept and transported immediately to the laboratory in an ice box. Upon arrival in the laboratory, the samples were plated on trypticase soy agar and incubated at 28 ℃ for 24 hours. After incubation, a few colonies were randomly picked, purified and stocked in glycerol. (GTG)5-fingerprinting were employed to analyse the genetic differences of the bacterial isolates. A dendrogram was constructed based on the (GTG)5-PCR patterns with similarity index ranged from 50% to 74% similarity. Based on the dendrogram, 50 isolates were chosen for species identification using 16S rRNA sequencing. These isolates were then tested with 25 antibiotics using a standard disk diffusion method. The degree of resistance of the isolates were categorised based on their area of inhibition zones whether they are resistant, intermediate and susceptible. About two hundred and four bacterial isolates were isolated and after species identification, 50 of these isolates constitute of 14 genera of bacteria including Bacillus (38%), Exiguobacterium (16%), Enterobacter (14%), Aeromonas (6%), Acinetobacter (4%), Citrobacter (4%), Staphylococcus (4%), Achromobacter (2%), Chitinophaga (2%), Fictibacillus (2%), Plesiomonas (2%), Pseudomonas (2%) and Pseudoxanthomonas (2%) and Stenotrophomonas (2%). The antibiotic resistance analysis revealed that the highest percentage resistance recorded were against streptomycin (75.0%), followed by ampicillin (66.0%), ceftriaxone (50.0%), rifampin (43.3%), aztreonam (36.8%) and ceftazidime (31.6%). Resistance to more than two antibiotics was seen in 40.0% of the isolates with Multiple Antibiotic Resistant (MAR) index ranged from 0 to 0.79. Interestingly, all five farms have an MAR of more than 0.2, which suggested that the occurrence of MAR bacteria might originate from high-risk sources in all five aquaculture farms. Similar MAR patterns were observed in farm 4 and farm 5, suggesting that the distributions of ARB were dependent on the selective pressure of geographical location. A plethora of resistance patterns seen across these five farms warrants a careful examination on the dissemination of MAR in aquaculture farms. This should be of concerns for fish farmers, local communities and environmental authorities as the spreading of ARB would render the antibiotic helpless