The present study was undertaken to evaluate the prevalence, underlying resistance mechanism, and virulence involved in Pseudomonas aeruginosa (n = 35) isolated from freshwater fishes in Andhra Pradesh, India. Antibiogram studies revealed that 68.5, 62.8, 37.1, 11.4, 8.5, 57.1, 54.2, and 48.5% of isolates had resistance to oxytetracycline, co-trimoxazole, doxycycline, enrofloxacin, ciprofloxacin, cefotaxime, ceftazidime, and ampicillin, respectively. The resistant isolates harboured the tetA (85.7%), tetD (71.4%), tetM (91.4%), sul1 (80%), blaCTX-M (57.1%), blaTEM (42.8%), and blaSHV (48.5%) genes. In total, 50% of the isolates were altered as multi-drug resistant, and the multiple antibiotic resistance index was calculated as 0.4. Furthermore, 37.3, 48.5, and 14.2% of isolates were categorized as strong, moderate, and weak biofilm formers, possessing pslA (91.5%) and pslD (88.6%) biofilm encoding genes. In total, 82.8% of the isolates exhibited efflux pump activity and harboured the mexA (74.2%), mexB (77.1%), and oprM (37.1%) genes. Virulent genes oprL, toxA, exoS, and phzM were detected in 68.5, 68.5, 100, and 17.1% of isolates, respectively. The data suggested that P. aeruginosa harbours multiple resistance mechanisms and virulence factors that may contribute to antibiotic resistance and pathogenicity, and their distribution in fish culture facilities highlights the public health hazards of the food chain.

  • Multi-drug-resistant P. aeruginosa strains were identified and characterized from freshwater fishes in Andhra Pradesh, India.

  • Improper farm management and disease outbreaks are the major risk factors associated with antimicrobial use.

  • Different antibiotic resistance mechanisms and virulence gene determinants were identified using the polymerase chain reaction.

Aquaculture is a rapidly growing fisheries sector in India with an annual growth of 10.34%, and contributing about 1.24% to national gross value added (GVA) and 7.28% to agricultural GVA. Freshwater aquaculture contributes over 95% of the total aquaculture production (Mishra et al. 2017b). Techniques like polyculture, induced carp breeding, composite carp culture on Indian major carps, and exotic carps led to the development of freshwater aquaculture. Intensification of aquaculture has, however, increased the risk of disease outbreaks. Disease outbreaks are seen as significant barriers to aquaculture production and sustainability, and contribute between 10 and 15% of the cost of production (Mishra et al. 2017b). Bacterial pathogens are opportunistic in nature and closely related to physiologically unbalanced, nutritionally deficient conditions, poor water quality, and high stocking densities (Tavares-Dias & Martins 2017). Aeromonas hydrophila, A. caviae, Edwardsiella tarda, Pseudomonas aeruginosa, P. putida, P. fluorescens, P. putrefaciens, Flexibacter columnar, Vibrio alginolyticus, Streptococcus iniae, and S. agalactiae are the common fish bacterial pathogens responsible for disease outbreaks (Mishra et al. 2017a). This has led to a rise in the use of antimicrobials, which are now frequently utilized, sometimes excessively, and inappropriately in a wide range of farming areas (Page & Gautier 2012).

P. aeruginosa is a common bacterial pathogen that can survive in a variety of habitats in the environment. It is a common hospital-acquired pathogen that causes severe nosocomial infections, cystic fibrosis, respiratory and urinary tract infections, and wound and soft tissue infections in immune-compromised patients. Furthermore, P. aeruginosa is one of the primary global causes of septicaemia in both freshwater and marine water fishes with severe economic losses in fish farms (Algammal et al. 2020). It is a part of normal fish microbiota, but under stressful conditions, the bacteria may become pathogenic, which can lead to acute haemorrhagic septicaemia, gill necrosis, abdominal distension, splenomegaly, a friable liver, and a congested kidney (Ardura et al. 2013). There are reports of P. aeruginosa infections in Labeo rohita, Catla catla, and Pangasianodon hypophthalmus causing haemorrhages, eye opacity, tail and fin rot, abdominal dropsy, paleness, an enlarged liver, congested kidneys, and spleen (Yaseen et al. 2020; Beulah et al. 2022).

Antimicrobial resistance (AMR) is undoubtedly a public health concern due to antibiotic misuse and overuse in humans and farm animals, which has changed the natural bacterial population and increased AMR levels (Schar et al. 2020). High levels of antibiotic dependency in animal food production threaten both the food system and wildlife through AMR and the release of antibiotic-resistant bacteria (ARBs) and antibiotic-resistant genes into the environment (Lulijwa et al. 2020). ARBs accumulate in water, sediment, farm and wild animals, and in and around the farms, which limit the effective treatment options, undermining the sustainability of aquatic food production and animal welfare (Cabello et al. 2013). It is well known that P. aeruginosa displays resistance to a wide variety of antibiotics (Curran et al. 2018). Generally, the major mechanism of P. aeruginosa used to counter antibiotic attacks can be classified into intrinsic and acquired or adaptive resistance (Soto 2013). The intrinsic resistance of P. aeruginosa includes low outer membrane permeability, expression of efflux pumps that expel antibiotics out of the cell and production of antibiotic-inactivating enzymes. The acquired resistance of P. aeruginosa can be achieved by either horizontal transfer of resistance genes or mutational genes. The adoptive resistance of P. aeruginosa involves biofilm formation where the biofilm serves as a diffusion barrier to limit antibiotic access to the bacterial cell (Streeter & Katouli 2016). The prophylactic and therapeutic use of tetracycline and sulphonamides in aquaculture has led to the emergence of tetracycline and sulphonamides resistance in aquatic-borne bacteria (Aminov 2013). The resistance of P. aeruginosa to the β-lactam antibiotics is mainly attributed to the extended spectrum beta-lactamases (ESBLs). blaCTX-M, blaTEM, and blaSHV are the most prevalent ESBL encoding genes and have been described in P. aeruginosa strains (Algammal et al. 2020). Besides, this bacterium possesses many virulence-related determinants, including cell-mediated and secreted virulence types. The cell-mediated types include pilli, flagella, and lipopolysaccharide, which are commonly involved in bacterial colonization and motility, the delivery of active proteins into the host cells, and the establishment of persistent infections. Likewise, the secreted virulence factors fortify the inflammatory processes, induce severe tissue damage, facilitate bacterial invasion and dissemination, and accelerate the progression of diseases (Mesquita et al. 2013).

There have been several reports on the AMR and virulence of P. aeruginosa isolated from fishes around the world (Algammal et al. 2020). Andhra Pradesh has become a real contender in fish and shrimp production, contributing 50% to the country's total production. Semi-intensive and intensive farming facilities are vulnerable to disease outbreaks. Based on the initial survey and interactions with local diagnostic laboratories and experts in the field, P. aeruginosa is opportunistically present in the aquatic environment, contributing to disease and AMR. Indeed, the identification of P. aeruginosa is essential for accurate diagnosis, outbreak prediction, and preventive and/or prophylactic measure implementation in aquaculture. Therefore, this study aimed to identify the prevalence, antibiogram, and underlying resistance mechanisms and virulence involved in the emergence and spread of multi-drug-resistant P. aeruginosa in freshwater finfish aquaculture.

Sample collection

In the present study, data from 110 freshwater finfish farms were collected to better understand management practices adopted within the system for aquaculture production. A total of 310 fishes were collected, representing 140 L. rohita (Rohu), 109 C. catla (Catla), and 61 P. hypophthalmus (Pangasius) were randomly from 110 freshwater farms in Krishna (16°36′21.22″N, 80°42′56.39″E) and West Godavari (16°53′55.65″N, 81°18′9.30″E) districts of Andhra Pradesh, India, from June 2021 to October 2022 (Figure 1). A prescribed questionnaire under the All India Network Project on Fish Health was used to collect data regarding culture type, size of the farm, culture species, stocking densities, and aquaculture inputs for water, soil, feed, health management, and routine disease testing to better understand the daily practices followed in fish farms and to identify risks and challenges for farmers within the systems. Fresh specimens of apparently healthy fish were transferred alive in aerated plastic bags to the microbiology laboratory, Department of Fisheries, Kaikaluru, Andhra Pradesh for further bacteriological examination. Samples from the gill, liver, kidney, and spleen were collected and processed aseptically following the protocols of Austin & Austin (2007). For selective enrichment, 1 g of sample was transferred into 9 ml of sterile malachite green broth (HiMedia, India) and incubated at 37°C for 18–24 h. To isolate the P. aeruginosa strains, a loopful of enriched culture was streaked onto cetrimide agar (HiMedia, India) and incubated at 37°C for 18–24 h. The yellowish-green colonies are suspected to be pseudomonads, as per Lamont & Martin (2003). The suspected Pseudomonas isolates were preserved in 20% glycerol-containing tryptic soy broth (HiMedia, India) and transported to the Department of Aquatic Animal Health Management, Faculty of Fisheries Science, Kerala University of Fisheries and Ocean Studies, Kerala, India, for further analysis.
Figure 1

Map of the study region showing the locations of sampling sites (Adobe® Photoshop® 7.0).

Figure 1

Map of the study region showing the locations of sampling sites (Adobe® Photoshop® 7.0).

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Identification of P. aeruginosa

The BD Phoenix™ M50 automated system was used to identify P. aeruginosa isolated from fish samples (BD Diagnostics, USA). In this study, an ID-AST combo panel, NMIC/ID55, which is designed for bacterial identification and susceptibility testing, was used. The panels were only used for bacterial identification since the antibiotics selected for testing were not available on the panel's antibiotic list provided by manufacturers. All the steps were carried out in accordance with the manufacturer's instructions. Pure bacterial cultures were transferred into ID broth, and cells were adjusted by 0.5 McFarland with the help of a BD Phoenix Spec nephelometer. Then, the panels were sealed and put into the instrument for incubation at 35°C for 10–12 h. P. aeruginosa ATCC 27853 were used as quality control. The data management programme EpiCentre linked to the BD Phoenix system was used to analyse test results.

Antimicrobial susceptibility test

The antibiotic susceptibility testing (AST) was performed on Muller-Hinton agar (HiMedia, India) by the disc diffusion method in accordance with the Clinical and Laboratory Standards Institute guidelines (CLSI 2022). Antibiotic discs used for AST were based on the data obtained in the survey. The selected farms routinely used different antibacterial agents such as oxytetracycline, doxycycline, ciprofloxacin, enrofloxacin, and co-trimoxazole (combination of trimethoprim and sulphamethoxazole) for regular prophylactic and treatment protocol. The antibiotic discs used for AST included oxytetracycline (30 μg), doxycycline (30 μg), ciprofloxacin (5 μg), enrofloxacin (10 μg), co-trimoxazole (25 μg), imipenem (10 μg), meropenem (10 μg), cefotaxime (30 μg), ceftazidime (30 μg), amikacin (30 μg), and ampicillin (10 μg). All the antibiotic discs were purchased from HiMedia, India. Exponential-phase bacterial cultures were adjusted to 0.5 McFarland standard, and 100 μL was plated onto MHA and incubated at 37°C for 18–24 h. P. aeruginosa ATCC 27853 and Escherichia coli ATCC 25922 were used as quality control isolates. The zones of inhibition were recorded and categorized as susceptible, intermediate, and total resistance according to the zone diameter interpretation standard described in the CLSI (2022). Isolates that exhibited resistance to three or more classes of antibiotics were categorized as multi-drug-resistant (Magiorakos et al. 2012). The multiple antibiotic resistance (MAR) index was calculated as per Krumpermann (1983). All the resistant P. aeruginosa isolates were examined for antibiotic resistance genes, biofilm development, efflux pump activity, and virulent profiles.

Phenotypic detection of biofilm formation and efflux pump activity

The biofilm formation assay was performed using the tissue culture plate method (Mathur et al. 2006). Individual colonies of P. aeruginosa isolates were inoculated into Brain Heart Infusion (BHI) broth (HiMedia, India) and supplemented with 2% sucrose. In total, 200 μL of bacterial suspension was added to a 96-well microtiter plate and incubated at 37°C for 18–24 h. As a negative control, 200 μL of sterile BHI broth was poured into a well. After incubation, the contents of each well were removed and washed three times with sterile deionized water to eliminate non-adherent bacteria. After 45 min of air drying, each well was filled with 200 μL of 0.2% (v/v) crystal violet (HiMedia, India) and incubated for 45 min at room temperature. The wells were then washed four times with sterile, deionized water. The dye was solubilized in each well with 200 μL of 33% glacial acetic acid (HiMedia, India), and the optical density (OD) was measured at 650 nm using the iMark™ Microplate Reader (Bio-Rad, USA). The mean OD values classified as strong (>0.108), moderate (0.108–0.083), and weak (0.083), and biofilm formers were used to quantify the biofilm-forming potential as per Hassan et al. (2011).

The efflux pump activities of isolates were assessed using the ethidium bromide agar cartwheel (EtBrCW) method (Martins et al. 2013). Bacterial suspensions having a 0.5 McFarland standard of turbidity were swabbed on tryptic soy agar with EtBr concentrations of 0, 0.5, 1, 1.5, and 2 mg/L and incubated at 37°C for 18–24 h. After incubation, the plates were examined for fluorescence under UV light in a gel documentation system (Bio-Rad, USA). Those plates lacking fluorescence indicated the presence of active efflux pumps, while those that fluoresced indicated the absence of efflux pumps.

Molecular characterization of biofilm formation, efflux pump activity, and virulence-encoding genes in P. aeruginosa

The genomic DNA of P. aeruginosa isolates was extracted according to the method of Kpoda et al. (2018). About three to four colonies of overnight-grown cultures were suspended in 200 μL of TE buffer and kept at 95°C for 10 min in a dry bath (IKA®, Dry Block Heater, India). The cell culture suspension was allowed to cool down and centrifuged at 12,000 rpm at 4°C for 10 min. The supernatant containing DNA was collected and kept at −20°C until use. The polymerase chain reaction (PCR) was carried out in a 25 μL reaction volume, targeting genes encoding for antibiotic resistance (tetA, tetD, tetM, sul1, blaCTX-M, blaTEM, and blaSHV), biofilm formation (pslA, pslD), efflux pump activity (mexA, mexB, and oprM), and virulence (oprL, toxA, exoS, and phzM) with specific primers using EmeraldAmp GT PCR Master Mix (Takara, India) in the Applied Biosystems™ Proflex™ (Thermo Fisher Scientific, USA) thermocycler. DNA template from P. aeruginosa ATCC 27853 was used as a positive control for pslA, pslD, mexA, mexB, oprM, oprL, toxA, exoS, and phzM genes, and nuclease-free water was used as a negative control. The primer sequences, PCR conditions, and expected amplicon size are depicted in Table 1. The PCR products were electrophoresed on 1.5% agarose at 80 V for 45 min, visualized, and photographed in a gel documentation system (Bio-Rad, USA).

Table 1

List of primers, expected amplicon size, and annealing temperatures used in the present study

Target genePrimer sequence (5′–3′)Amplicon (bp)PCR conditions
Reference
DenaturationAnnealingExtensionCyclesFinal Extension
tetA F- GGCGGTCTTCTTCATCATGC
R-CGGCAGGCAGAGCAAGTAGA 
502 94°C for 1 min 58°C for 30 s 72°C for 1 min 35 72°C for 7 min Lanz et al. (2003)  
tetD F-GAGCGTACCGCCTGGTTC
R- TCTGATCAGCAGACAGATTGC 
780 94°C for 30 s 55°C for 30 s 72°C for 30 s 35 72°C for 5 min Koo & Woo (2011)  
tetM ACACGCCAGGACATATGGAT
ATTTCCGCAAAGTTCAGACG 
536 96°C for 30 s 53°C for 30 s 72°C for 1 min 35 72°C for 5 min Call et al. (2003)  
Sul1 F-CGGCGTGGGCTACCTGAACG
R-GCCGATCGCGTGAAGTTCCG 
433 94°C for 15 s 69°C for 30 s 72°C for 1 min 30 72°C for 7 min Karczmarczyk et al. (2011)  
pslA F-TGGGTCTTCAAGTTCCGCTC
R-ATGCTGGTCTTGCGGATGAA 
119 95°C for 30 s 57°C for 40 s 72°C for 1 min 30 72°C for 10 min Maita & Boonbumrung (2014)  
pslD F-CTCATGAAACGCACCCTCCT
R-TGCGACCGATGAACGGATAG 
295 
mexA F-ACCTACGAGGCCGACTACCAGA
R-GTTGGTCACCAGGGCGCCTTC 
179 59°C for 40 s 72°C for 1 min 72°C for 10 min Pourakbari et al. (2016)  
mexB F-GTGTTCGGCTCGCAGTACTC
R-AACCGTCGGGATTGACCTTG 
244 58°C for 40 s 
oprM F-CCATGAGCCGCCAACTGTC
R-CCTGGAACGCCGTCTGGAT 
205 59°C for 40 s 
oprL F-ATGGAAATGCTGAAATTCGGC
R-CTTCTTCAGCTCGACGCGACG 
504 96°C for 1 min 58°C for 1 min 72°C for 1 min 40 72°C for 10 min Algammal et al. (2020)  
toxA F-GACAACGCCCTCAGCATCACC
R-AGCCGCTGGCCCATTCGCTCCAGCGCT 
396 94°C for 1 min 59°C for 1 min 30 
exoS F-GCGAGGTCAGCAGAGTATCGTTC
R-GGCGTCACTGTGGATGC 
118 94°C for 30 s 58°C for 30 s 36 
phzM F-ATGGAGAGCGGGATCGACAGATG
R- CGGGTTTCCATCGGCAG 
875 94°C for 30 s 59°C for 30 s 30 
blaCTX-M F- CGCTTTGCGATGTGCAG
R- ACCGCGATATCGTTGGT 
550 94°C for 1 min 55°C for 30 s 72°C for 1 min 30 72°C for 7 min 
blaTEM F- ATAAAATTCTTGAAGACGAAA
R- GACAGTTACCAATGCTTAATC 
1,080 94°C for 1 min 50°C for 40 s 72°C for 1 min 32 72°C for 10 min 
blaSHV F- TTAACTCCCTGTTAGCCA
R- GATTTGCTGATTTCGCCC 
795 95°C for 1 min 52°C for 30 s 72°C for 1 min 32 72°C for 7 min 
Target genePrimer sequence (5′–3′)Amplicon (bp)PCR conditions
Reference
DenaturationAnnealingExtensionCyclesFinal Extension
tetA F- GGCGGTCTTCTTCATCATGC
R-CGGCAGGCAGAGCAAGTAGA 
502 94°C for 1 min 58°C for 30 s 72°C for 1 min 35 72°C for 7 min Lanz et al. (2003)  
tetD F-GAGCGTACCGCCTGGTTC
R- TCTGATCAGCAGACAGATTGC 
780 94°C for 30 s 55°C for 30 s 72°C for 30 s 35 72°C for 5 min Koo & Woo (2011)  
tetM ACACGCCAGGACATATGGAT
ATTTCCGCAAAGTTCAGACG 
536 96°C for 30 s 53°C for 30 s 72°C for 1 min 35 72°C for 5 min Call et al. (2003)  
Sul1 F-CGGCGTGGGCTACCTGAACG
R-GCCGATCGCGTGAAGTTCCG 
433 94°C for 15 s 69°C for 30 s 72°C for 1 min 30 72°C for 7 min Karczmarczyk et al. (2011)  
pslA F-TGGGTCTTCAAGTTCCGCTC
R-ATGCTGGTCTTGCGGATGAA 
119 95°C for 30 s 57°C for 40 s 72°C for 1 min 30 72°C for 10 min Maita & Boonbumrung (2014)  
pslD F-CTCATGAAACGCACCCTCCT
R-TGCGACCGATGAACGGATAG 
295 
mexA F-ACCTACGAGGCCGACTACCAGA
R-GTTGGTCACCAGGGCGCCTTC 
179 59°C for 40 s 72°C for 1 min 72°C for 10 min Pourakbari et al. (2016)  
mexB F-GTGTTCGGCTCGCAGTACTC
R-AACCGTCGGGATTGACCTTG 
244 58°C for 40 s 
oprM F-CCATGAGCCGCCAACTGTC
R-CCTGGAACGCCGTCTGGAT 
205 59°C for 40 s 
oprL F-ATGGAAATGCTGAAATTCGGC
R-CTTCTTCAGCTCGACGCGACG 
504 96°C for 1 min 58°C for 1 min 72°C for 1 min 40 72°C for 10 min Algammal et al. (2020)  
toxA F-GACAACGCCCTCAGCATCACC
R-AGCCGCTGGCCCATTCGCTCCAGCGCT 
396 94°C for 1 min 59°C for 1 min 30 
exoS F-GCGAGGTCAGCAGAGTATCGTTC
R-GGCGTCACTGTGGATGC 
118 94°C for 30 s 58°C for 30 s 36 
phzM F-ATGGAGAGCGGGATCGACAGATG
R- CGGGTTTCCATCGGCAG 
875 94°C for 30 s 59°C for 30 s 30 
blaCTX-M F- CGCTTTGCGATGTGCAG
R- ACCGCGATATCGTTGGT 
550 94°C for 1 min 55°C for 30 s 72°C for 1 min 30 72°C for 7 min 
blaTEM F- ATAAAATTCTTGAAGACGAAA
R- GACAGTTACCAATGCTTAATC 
1,080 94°C for 1 min 50°C for 40 s 72°C for 1 min 32 72°C for 10 min 
blaSHV F- TTAACTCCCTGTTAGCCA
R- GATTTGCTGATTTCGCCC 
795 95°C for 1 min 52°C for 30 s 72°C for 1 min 32 72°C for 7 min 

Bacterial identification

The bacteriological examination revealed that the isolates were motile and Gram-negative bacilli, and arranged in double or short chains. The typical isolates of P. aeruginosa displayed large irregular colonies with a fruity odour and produced a yellowish-green fluorescent pigment on cetrimide agar (HiMedia, India). Among the 82 suspected isolates, 35 isolates were confirmed to be P. aeruginosa by the BD Phoenix™ M50 automated system. Only P. aeruginosa strains were included in this study. The total prevalence (Table 2) of P. aeruginosa was found to be 11.2% (n = 35/310), comprising L. rohita (9.56%; 11/115), C. catla (10%; 10/100), and P. hypophthalmus (14.7%; 14/95). Molecular characterization of virulence profiles showed that 68.5% (24/35), 68.5% (24/35), 100% (35/35), and 17.1% (6/35) of the isolates had oprL, toxA, exoS, and phzM virulence-encoding genes (Table 3).

Table 2

Showing the sampling site, species collected, and prevalence of P. aeruginosa

Sampling siteNumber of fishesL. rohitaC. catlaP. hypophthalmus
Krishna 170 60 55 55 
West Godavari 140 55 45 45 
Number of P. aeruginosa isolates 35 11 10 14 
Mean 155 ± 21 57.5 ± 3.5 50 ± 7.0 50 ± 7.0 
Prevalence (%) 11.2 9.56 10 14.7 
Sampling siteNumber of fishesL. rohitaC. catlaP. hypophthalmus
Krishna 170 60 55 55 
West Godavari 140 55 45 45 
Number of P. aeruginosa isolates 35 11 10 14 
Mean 155 ± 21 57.5 ± 3.5 50 ± 7.0 50 ± 7.0 
Prevalence (%) 11.2 9.56 10 14.7 
Table 3

AMR, biofilm formation, efflux pump activity, and virulence gene determinants of P. aeruginosa from fish samples

IsolateSourceAMR genes
Biofilm formation
Efflux pump genes
Virulence profiles
tetAtetDtetMsul1blaCTX-MblaTEMblaSHVpslApslDmexAmexBoprMoprLtoxAexoSphzM
PA01 Kidney − − − − − 
PA02 Spleen − − − 
PA03 Kidney − − − − 
PA04 Gill − − − − − − − 
PA05 Kidney − − − − − 
PA06 Kidney − − − − − − − 
PA07 Kidney − − − − − − 
PA08 Kidney − − − − − − − 
PA09 Liver − − − − − − − 
PA10 Liver − − − − 
PA11 Spleen − − − − − − − 
PA12 Spleen − − − − − 
PA13 Liver − − − − 
PA14 Liver − − − − 
PA15 Gill − − − − 
PA16 Gill − − − − − 
PA17 Kidney − − − − − 
PA18 Kidney − − − − 
PA19 Liver − − − − − − 
PA20 Spleen − − − − − 
PA21 Spleen − − − 
PA22 Liver − − − − − − 
PA23 Gill − − − − − − − 
PA24 Gill − − − − − − − − − 
PA25 Gill − − − − − 
PA26 Liver − − − − − 
PA27 Kidney − − − − − 
PA28 Liver − − − 
PA29 Spleen − − 
PA30 Liver − − − − 
PA31 Gill − 
PA32 Liver − − − 
PA33 Kidney − − − − − 
PA34 Kidney − − − − 
PA35 Spleen − − − − − − − − − 
IsolateSourceAMR genes
Biofilm formation
Efflux pump genes
Virulence profiles
tetAtetDtetMsul1blaCTX-MblaTEMblaSHVpslApslDmexAmexBoprMoprLtoxAexoSphzM
PA01 Kidney − − − − − 
PA02 Spleen − − − 
PA03 Kidney − − − − 
PA04 Gill − − − − − − − 
PA05 Kidney − − − − − 
PA06 Kidney − − − − − − − 
PA07 Kidney − − − − − − 
PA08 Kidney − − − − − − − 
PA09 Liver − − − − − − − 
PA10 Liver − − − − 
PA11 Spleen − − − − − − − 
PA12 Spleen − − − − − 
PA13 Liver − − − − 
PA14 Liver − − − − 
PA15 Gill − − − − 
PA16 Gill − − − − − 
PA17 Kidney − − − − − 
PA18 Kidney − − − − 
PA19 Liver − − − − − − 
PA20 Spleen − − − − − 
PA21 Spleen − − − 
PA22 Liver − − − − − − 
PA23 Gill − − − − − − − 
PA24 Gill − − − − − − − − − 
PA25 Gill − − − − − 
PA26 Liver − − − − − 
PA27 Kidney − − − − − 
PA28 Liver − − − 
PA29 Spleen − − 
PA30 Liver − − − − 
PA31 Gill − 
PA32 Liver − − − 
PA33 Kidney − − − − − 
PA34 Kidney − − − − 
PA35 Spleen − − − − − − − − − 

Antibiogram study

All (n = 35) isolates were screened for antibiogram, which displayed variable resistance patterns to the panel of antibiotics tested. Sixty-eight percent (24/35), 62.8% (22/35), 37.1% (13/35), 11.4% (4/35), 8.5% (3/35), 57.1% (20/35), 54.2% (19/35), and 48.5% (17/35) of isolates had resistance to oxytetracycline, co-trimoxazole, doxycycline, enrofloxacin, ciprofloxacin, cefotaxime, ceftazidime, and ampicillin, respectively. None of the isolates were found resistant to imipenem, amikacin, and meropenem. The isolates from P. hypophthalmus showed high resistance in comparison to the isolates from C. catla and L. rohita. In order to correlate AST findings with antibiotic-resistant determinants, the isolates were screened for specific antibiotic-resistant gene fragments harbouring tetA, tetD, tetM, sul1, blaCTX-M, blaTEM, and blaSHV genes. They were prevalent in 85.7% (30/35), 71.4% (25/35), 91.4% (32/35), 80% (28/35), 57.1% (20/35), 42.8% (15/35), and 48.5% (17/35) of the P. aeruginosa isolates, respectively. Furthermore, 50% of the P. aeruginosa isolates were altered as multi-drug-resistant, having resistance to more than three antibacterial agents. The MAR index was found to be 0.4.

Biofilm formation

Pseudomonas aeruginosa strains were categorized as strong, moderate, and weak biofilm formers (WBF). Around 37.3% (13/35), 48.5% (17/35), and 14.2% (5/35) of biofilm formers were identified as strong biofilm formers (SBF), moderate biofilm formers (MBF), and WBF, respectively. All SBF isolates carried the pslA and pslD genes, whereas 62 and 79% of MBF carried pslA and pslD, respectively. Sixty-five percent of WBF possessed only the pslA gene, while none of the WBF carried the pslD gene. The overall prevalence of the pslA and pslD genes in all biofilm formers was 91.5% (32/35) and 88.6% (31/35), respectively.

Evaluation of efflux pump activity in P. aeruginosa

The efflux pump activity was detected in all concentrations of EtBr-coated agar plates. At EtBr concentrations of 1 and 2 mg/L, a unique efflux pump activity was detected (Figure 2). Overall, 82.8% (29/35) of P. aeruginosa isolates exhibited efflux pump activity, and 6 isolates did not. The isolates having active efflux pumps possessed mexA (74.2%; 26/35), mexB (77.1%; 27/35), and oprM (37.1%; 13/35) genes, which belong to the resistance-nodulation-division family. MexA and mexB were detected in 10 isolates, and mexA and oprM were detected in 13 isolates, while 16 isolates possessed all three genes (mexA, mexB, and oprM).
Figure 2

Efflux pump activity of P. aeruginosa determined by the EtBrCW method (2 mg/L). Isolates 1, 3, 4, 5, 6, 7, 8, and 9 were positive for efflux pump activity as they did not fluoresce under UV light. Isolates 2, 10, 11, and 12 lack efflux pump activity and fluoresced because of EtBr retention.

Figure 2

Efflux pump activity of P. aeruginosa determined by the EtBrCW method (2 mg/L). Isolates 1, 3, 4, 5, 6, 7, 8, and 9 were positive for efflux pump activity as they did not fluoresce under UV light. Isolates 2, 10, 11, and 12 lack efflux pump activity and fluoresced because of EtBr retention.

Close modal

AMR is detrimental to human and animal health and has been widely acknowledged and addressed in recent years (Schar et al. 2020). Antibiotic-resistant organisms cause infections that are more challenging to treat, as they necessitate medications that are often more difficult to obtain, more expensive, and even more toxic (Lulijwa et al. 2020). Bacterial, mycotic, and parasitic diseases have been identified as substantial risk factors in fish farms in Andhra Pradesh, India (Mishra et al. 2017a). P. aeruginosa is a normal component of the fish microbiota, but under stressed conditions, the bacteria may become pathogenic to fish (Ardura et al. 2013). It is interesting to note that P. aeruginosa isolated from apparently healthy fish, indicating opportunistic distribution in the aquatic environment, can cause disease in stressed animals. In the present study, the total prevalence of P. aeruginosa was found to be 11.2%, comprising L. rohita (9.56%), C. catla (10%), and P. hypophthalmus (14.7%). This is in agreement with previous reports, where P. aeruginosa is highly prevalent in freshwater fishes (Ardura et al. 2013; Algammal et al. 2020). The prevalence of P. aeruginosa was found to be high in P. hypophthalmus due to the high-density culture with ineffective farm management. The dissimilarity of pathogen distribution in aquaculture is closely associated with species, stocking density, and farming activities leading to stress (Mishra et al. 2017a; Lulijwa et al. 2020). According to the findings of the current study, the majority of fish farms hold high stocking densities (8,000–10,000 fish/acre) with ineffective farm management, poor biosecurity, and continuous cultures with partial harvesting. Furthermore, it was observed that all (100%) of the farms had been in operation for at least 3 years at the time of sampling. This likely indicates that several factors contribute to the emergence and spread of bacterial pathogens in the aquatic environment (Ali et al. 2020).

Diseases are substantial risk factors associated with morbidity and mortality, leading to economic losses. This may lead to the use of chemical and biological compounds for water quality management, pathogen prevention, and control (Mishra et al. 2017b). Imprudent use of antibiotics and the emergence of antibiotic resistance genes could result in the occurrence of multi-drug resistant (MDR) strains (Reverter et al. 2020). It is well known that P. aeruginosa has strong intrinsic and acquired resistance to a broad range of antibiotics (Horna et al. 2018). In the present study, 50% of isolates altered as MDR and were resistant to oxytetracycline, co-trimoxazole, doxycycline, enrofloxacin, ciprofloxacin, cefotaxime, ceftazidime, and ampicillin. The isolates possessed tetA, tetD, tetM, sul1, blaCTX-M, blaTEM, and blaSHV genes. The MAR index was found to be high, indicating that all the isolates are originating from high-risk sources where the use of antibiotics is rampant. These findings closely resemble those of research on aquaculture-derived Klebsiella pneumoniae and P. aeruginosa from fish and shrimp farms in India (Das et al. 2018; Algammal et al. 2020). Previous studies reported that a strong relationship exists between trends in AMR isolates and antibiotic use, environmental factors, season, water quality, stocking density, pollution and global warming, and disease incidence (Mishra et al. 2017b; Reverter et al. 2020). Earlier studies investigated a link between pesticide use and AMR to commonly used antibiotics, which could be conferred by a plasmid that contributes to cross-resistance, namely, an unspecific organophosphorus hydrolase that degrades antibiotic derivatives (Rangasamy et al. 2017). Baseline data found during sampling indicate that pesticides (diclorvos, cypermethrin, amitraz, ivermectin, albendazole, emamectin benzoate, deltamethrin) and herbicides (glyphosate) were commonly used in fish culture. A sub-lethal effect of pesticides and herbicides is related to an adaptive MAR phenotype associated with an increased expression of efflux pumps and is responsible for MDR bacteria proliferation (Malagon-Rojas et al. 2020). This could be the situation with cross-resistance, where natural selection may be involved in multi-drug resistance resulting from horizontal gene transfer (Tincher et al. 2017; Malagon-Rojas et al. 2020). The use of cephalosporin antibiotics in aquaculture practices is unlikely. However, 57.1, 42.8, and 48.5% of the isolates possessed cephalosporin resistance genes blaCTX-M, blaTEM, and blaSHV genes. Thus, our findings are in line with those of Malagon-Rojas et al. (2020) and Tincher et al. (2017) who opined that cross-resistance with other antimicrobials may be involved in the emergence and spread of MDR pathogens in aquaculture settings.

Biofilm development enhances antibiotic resistance and pathogenicity, resulting in persistent infections (Kamali et al. 2020). In the present study, all resistant isolates had the ability to produce biofilm with varying capabilities. Previous studies have described that the association between antibiotic resistance and biofilm production in P. aeruginosa strongly supports our findings (Cepas et al. 2019). The polysaccharide synthesis locus (psl), which regulates the secretion of biofilm in P. aeruginosa, is largely composed of the pslA and pslD genes. In the present study, 91.5 and 88.6% of isolates were found to be positive pslA and pslD genes, respectively. Our research findings have been supported by Ugwuanyi et al. (2021) who reported the presence of pslA and pslD biofilm encoding genes in antibiotic-resistant P. aeruginosa from clinical isolates in Nigeria. In addition, active efflux pumps play a significant role in mediating bacterial multi-drug resistance. According to previous reports, P. aeruginosa has been found to express a high level of the mexAB–OprM efflux pump, which concurrently promotes resistance to multiple antibiotics (Pan et al. 2016). The prevalence of the mexA, mexB, and oprM genes was found to be 74.2, 77.1, and 37.1% of the isolates, respectively. Previous studies have reported that mexAB-R and mexAB–oprM efflux pumps were dominant in P. aeruginosa isolated from urinary tract infections in Egypt and Nigeria, and is lending support to our findings (Pan et al. 2016; Ugwuanyi et al. 2021). All active efflux pump-positive isolates were resistant to oxytetracycline and doxycycline and harboured the tetA, tetD, tetM, and sul1 genes. Tetracycline resistance in bacteria is mediated by ribosomal protection and tetracycline-specific efflux via the presence of major facilitator superfamily transporters (Kobayashi et al. 2007; Aminov 2013). The findings of the current study clearly demonstrate that tetracycline resistance in aquatic foodborne bacteria is caused by major facilitator superfamily transporters.

P. aeruginosa can adapt to a hostile environment in the host by secreting a number of virulence factors that lead to infection and disease (Qin et al. 2022). In the present study, PCR results revealed that all the tested isolates were positive for oprL, toxA, exoS, and phzM genes in agreement with previous reports (Mesquita et al. 2013; Horna et al. 2018; Algammal et al. 2020). L-lipoproteins (oprL), which belong to outer membrane proteins present in P. aeruginosa, are responsible for antibiotic resistance and pathogenicity. These are highly prominent in Pseudomonads, so they would be a good target for identifying and determining the pathogenicity of clinical and environmental specimens (Remans et al. 2010). ExotoxinA is an extracellular substance that inhibits protein biosynthesis via the toxA gene on their chromosome (Lee et al. 2005). ExoS is a bifunctional toxin that activates both GTPases and ADP-ribosyltransferases. Similarly, pyocyanin is a major virulence factor expressed by the phzM gene, which aids in survival and colonization in hosts (Bradbury et al. 2010). Due to its zoonotic nature, P. aeruginosa has been identified as a possible hazard to both human and animal health, inevitably resulting in morbidity and mortality (Milivojevic et al. 2018). This could harm fish handlers' well-being and may have serious health consequences. Therefore, care must always be taken when handling the animals for regular health monitoring and disease diagnosis.

P. aeruginosa is a common bacterial pathogen that affects both humans and animals. The emergence of multi-drug-resistant pathogens in aquaculture settings in this region raises concerns about antibiotic misuse. Multiple factors play crucial roles in the AMR of P. aeruginosa. These findings highlight the need for a multifaceted approach from all the stakeholders in the sector to tackle the disease and AMR issues. Regular disease surveillance, identification of causative agents, and AST are all prerequisites to minimizing the emergence of antibiotic-resistant bacterial strains of potential public health concern. Also, routine surveillance and effective policies with proper guidelines have to be practiced to minimize the need for antibiotics. The presence of virulence genes in the isolates highlights the potential risk in causing diseases when prevailing conditions become favourable for them. Particularly, the higher prevalence of AMR P. aeruginosa in Pangasius farms where management practices are sub-optimal. As a result, maintaining biosecurity and good aquaculture practices (GAPs) addressing breed, seed, and feed selection are the only ways forward for disease control and prevention. If diseases are reduced through GAPs, then the use of antimicrobials and the resultant emergence of MDR bugs can be significantly controlled. Furthermore, the current study findings provide promising insights into the distribution of P. aeruginosa in freshwater aquaculture settings, resistance patterns, underlying mechanisms, and virulence profiles for future research.

The authors are grateful to the authorities of the Kerala University of Fisheries and Ocean Studies, Kochi, India, for providing all the necessary infrastructure facilities and scientific support for carrying out the Ph.D. research work. The authors are thankful to the Rajiv Gandhi Centre for Aquaculture, Tamilnadu, India, for providing laboratory facilities. The authors also acknowledge the fish farmers of Andhra Pradesh, India, for providing information and samples for this research.

This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

K.S. conceptualized the work, performed methodology, investigated the work, carried out data curation, and wrote the original draft. A.S. found resources and did data analysis. M.S. and R.P. reviewed and edited the manuscript. D.P. supervised and conceptualized the work, performed methodology, did critical review, and edited the original draft.

The guidelines of the Committee for the Purpose of Control and Supervision of Experiments on Animals (CPCSEA) registration number: 1174/ac/08/CPCSEA were properly followed in the execution of all the experiments.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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