Characterization of multidrug and heavy metal resistance of carbapenemases producing Klebsiella pneumoniae from poultry samples in Bangladesh

Abstract

Background

Resistance to multiple drugs in Klebsiella pneumoniae (KPN) is an important issue in human and animal medicine. KPN phenotypic and genotypic aspects in poultry samples have not been comprehensively explored in Bangladesh.

Methods

This research focused on the prevalence of antibiotic resistance and the characterization of KPN in Bangladeshi poultry isolates using both phenotypic and genotypic approaches.

Results

A total of 32 poultry samples were randomly obtained from a commercial poultry farm in Narsingdi, Bangladesh, and 43.90% (18/41) of the isolates were confirmed to be KPN, whereas all isolates were biofilm producers. The antibiotic sensitivity test revealed the most remarkable (100%) antibiotic resistance level against Ampicillin, Doxycycline and Tetracycline while remaining susceptible to Doripenem, Meropenem, Cefoxitin and Polymyxin B. Resistance to Nalidixic acid, Nitrofurantoin, Trimethoprim, Levofloxacin, Ciprofloxacin, Cefuroxime and Chloramphenicol ranges from 18% to 70%. Minimum inhibitory concentrations for carbapenem‐resistant KPN ranged from 128 to 512 mg/mL for Meropenem, Imipenem, Gentamycin and Ciprofloxacin, respectively. [Correction added on 15 June 2023, after first online publication: 512 g/mL was corrected to 512 mg/mL in the preceding sentence]. Carbapenemase‐producing KPN isolates harboured a single or multiple β‐lactamase genes, bla _SIM‐1, bla _IMP‐4 and bla _OXA‐48 as well as one ESBL gene (bla _TEM) and plasmid‐mediated quinolone resistance gene (qnrB). Furthermore, Cr and Co outperformed Cu and Zn in antibacterial effectiveness.

Conclusions

The results of this investigation showed that the high prevalence of multidrug‐resistant pathogenic KPN in our chosen geographic location had displayed sensitivity to FOX/PB/Cr/Co, which might be regarded as an alternate treatment to reduce pressure of use on carbapenems.

Increasing numbers of carbapenemase‐producing, multidrug‐resistant, highly pathogenic Klebsiella pneumoniae pose a serious risk to the health of people and poultry in Bangladesh. To reduce the prevalence Klebsiella pneumoniae isolates in poultry which have harbored beta‐lactamase genes and quinolone resistance genes, a combination of antibiotics such as doripenem, meropenem, cefoxitin, and polymyxin B is recommended, followed by the use of readily available heavy metals Cr>Co>Cu>Zn beyond their toxic metal. Antibiotics such as ampicillin, doxycycline, tetracycline, gentamycin, and ciprofloxacin have already lost their typical efficacy against the isolates examined, therefore we must be cautious when using them to treat bacterial diseases in poultry.

1. INTRODUCTION

Klebsiella pneumoniae (KPN) has been recognized as a significant foodborne pathogen due to its frequent appearance in various foods such as fresh vegetables, meat and street foods (Kim et al., 2015; Overdevest et al., 2014). As a category ‘B’ pathogen (Sultana et al., 2021), an overwhelming number of foodborne outbreaks caused by KPN have been documented in various countries in recent years (Calbo et al., 2011; Saha, Hoque, et al., 2020; Saha, Rakhi, et al., 2020). Among all other sources, poultry has been considered the top source of these outbreaks (Aly et al., 2014), as documented in prior studies (Aly et al., 2014; Guo et al., 2016; Yang et al., 2019). Along with the pathogenicity of KPN in poultry, antibiotic resistance has recently emerged as a significant public health concern (Guo et al., 2016; Hamza et al., 2016; Saud et al., 2019; Yang et al., 2019). Antimicrobial drugs are routinely utilized to promote growth in food animals (Schroeder et al., 2002). The latter is accomplished by diminishing the animals’ sensitivity to bacterial infections and promoting sustainable absorption in the gut. The fact that these bioactive components are the same or similarly related to antimicrobials used in human medicine is cause for serious worry (Schroeder et al., 2002).

Furthermore, due to the widespread usage of these antimicrobial drugs, bacteria have evolved ways to avoid their effects through evolutionary adaptations (Wright et al., 2005). Most notably, the onset of β‐lactamase‐producing and carbapenem‐resistant KPN has piqued the interest of both veterinary and human medicine for years (Elmonir et al., 2021; Wu et al., 2016) because they can be virtually resistant to all presently offered antimicrobial agents and have been linked to high rates of morbidity and mortality in poultry (Munoz‐Price et al., 2013). On the other hand, antimicrobial agents other than antibiotics have been shown to stimulate a co‐selection process. A well‐known example of such selection methods is heavy metal resistance (Baker‐Austin et al., 2006). Heavy metals (Ni, As, Fe, Zn, Cr) are required for various physiological processes and are components of DNA‐ and RNA‐polymerases, urease and cytochrome C oxidase (Seiler & Berendonk, 2012). The toxicity of such micronutrients is substantially commensurate to their concentration. The use of heavy metal‐containing drugs for growth promotion and treatment of intestinal illness, notably in poultry production, may select for microorganisms with lower sensitivity to heavy metals and co‐select for reduced susceptibility to other antimicrobials (Islam et al., 2017).

Furthermore, they may have many metal tolerance genes (Fang et al., 2016). Several AMR genes have been identified in KPN, including the IMP, VIM, ESBL‐encoding genes, TE, KPC, SIM and NDM. Many rules have been put in place in industrialized nations to reduce antibiotic resistance in poultry (Cogliani et al., 2011). These strategies primarily focus on limiting antimicrobial usage and building robust antimicrobial resistance surveillance and monitoring systems inside farms (Cogliani et al., 2011). However, the situation is exacerbated in impoverished nations such as Bangladesh (Sarker et al., 2019), where poultry is reared near people (Sarker et al., 2019). These antibiotic‐resistant bacteria can transmit directly to people from chickens or indirectly through contaminated eggs, water, feed and meat, for example, through the food chain, causing serious health concerns (Azad et al., 2019; Mahmud et al., 2018). This suggests that the danger of antibiotic resistance in Bangladesh chicken farms is quite significant, necessitating more research. However, there has been little information available on the properties of multidrug‐resistant (MDR) KPN isolated from poultry until today. This study aimed to examine the incidence and pathogenicity of KPN isolated along with their antibiotic/metal resistance pattern from chicken farms in the Narsingdi districts of Bangladesh.

2. MATERIALS AND METHODS

2.1. Considering area for research

The investigation was performed in Dhaka's districts: Narsingdi (23.92°N, 90.73°E) (Figure S1). The region was chosen deliberately even though it has a considerable hen population and many reports of poultry diseases. More than 700 poultry farms operate in the Narsingdi region (DLS (Department of Livestock Services), 2016).

2.2. Phenotypic characterization of KPN isolates from poultry samples

In November 2017, 32 poultry samples were randomly collected from a commercial poultry farm in one of Bangladesh's Narsingdi districts, encompassing droppings (n = 8), cloacal swabs (n = 8), poultry feed (n = 4), handler's swab (n = 4), egg surface swab (n = 4) and feeding water (n = 4). The materials were placed into sterile containers and promptly transferred to the laboratory in a refrigerator with icepacks and processed within 4–6 h. First, 20 g of each sample was enhanced in 20 mL nutrient broth (Oxoid, USA). The enrichment was then streaked over eosin methylene blue (EMB) (Oxoid, USA) and MacConkey agar (Oxoid, USA) and incubated at 37°C. Next, pink, mucoid colonies and big, pink to purple colonies with no metallic green sheen were picked up from MacConkey agar and EMB agar plates, respectively, and subcultured into nutrient agar (NA) at 37°C for 24 h. There Gram‐negative bacteria was further confirmed by Gram‐staining (Hoque et al., 2020) (Figure S2). Colonies that resembled Gram‐negative KPN were chosen for further biochemical tests (indole, methyl red, Voges–Proskauer, catalase, oxidase, urease and triple sugar iron tests, motility test, sugar [glucose, lactose, sucrose] fermentation test) as previously mentioned by Hoque et al. (2020) and Permatasari et al. (2020). All biochemical findings were summarized using the internet tool Microrao (http://www.microrao.com/index.html) and Bio Cluster, which forecast potential organisms based on biochemical results (Abdullah et al., 2015).

2.3. Pathogenicity assay of KPN

Biofilm propagation was approximated on 24‐well polystyrene plates (Corning, Costar), as recently demonstrated by Saha, Islam et al. (2021); Saha, Rakhi et al. (2021). In brief, all (18) KPN strains were cultivated in Luria‐Bertani (LB) medium for 24 h at 37°C with shaking, followed by a 1:1000 dilution in LB. Twenty five microliters were introduced in each well containing 1.5 mL of culture medium. In static circumstances, the plates were incubated for 48 h at 37°C. Planktonic cells were removed, and biofilm‐containing wells were rinsed three times with distilled water before staining the remaining adherent bacteria with 2 mL/well of CV (0.7% [wt/vol] solution; Sigma‐Aldrich) for 12 min. Washes with distilled water were used to remove excess discoloration. CV was extracted using acetic acid, and the plates were incubated at room temperature to allow the dye to dissolve. After transferring two samples of 100 mL from each well to a 96‐well flat‐bottom plate, the dye concentration was quantified at 600 nm using a microplate reader. The tests were performed four times for each isolate, and the mean SD was calculated. Strains were categorized as non, feeble, intermediate or robust biofilm producers (Singh et al., 2017). The biofilm surfaces were then examined using an Olympus BX51 upright microscope (40× objectives), 5% TSB as nutrient‐rich media and FilmTracer LIVE/DEAD Biofilm Viability Kit (Thermo Fisher Scientific, Waltham, MA, USA) as staining materials to determine the proportion of live or active cells (fluorescent green). Finally, pictures were acquired with an Olympus DP73 camera and displayed with ImageJ, a Java‐based image processing application (Murray et al., 2017).

2.4. Genomic DNA extraction of KPN

Genomic DNA was extracted from each isolated KPN using the boiling DNA method to follow the overnight culture. In a nutshell, the samples were centrifuged for 15 min at 15,000g then removed the supernatant. The pellet was then resuspended in 40 mL of molecular biology grade water, boiled in a water bath for 10 min, cooled on ice and centrifuged for 10 s at 15,000g (Queipo‐Ortuo et al., 2008; Sultana et al., 2018). Finally, a NanoDrop ND‐2000 spectrophotometer was used to quantify the isolated DNA.

2.5. Molecular fingerprinting and evolutionary analysis of KPN isolates

As previously reported, all isolates were subjected to random amplification of polymorphic DNA (RAPD PCR) typing (Yoon et al., 2016). For RAPD PCR, the primer 1283 (5′‐GCGATCCCCA‐3′) was used, and similar protocol was followed described by Momtaz et al. (2018). Furthermore, two KPN isolates with distinct RAPD groups were recruited for 16S rRNA gene PCR and sequencing using primers 27F 5′‐AGAGTTTGATCMTGGCTCAG‐3′ and 1492R 5′‐TACGGYTACCTTGTTACGACTT‐3′. The raw sequences were subsequently quality assured using SeqMan software before aligning with appropriate reference sequences downloaded from the NCBI database with Molecular Evolutionary Genetics Analysis (MEGA) version 7.0 for more enormous datasets (Kumar et al., 2016). Finally, the evolutionary distances were calculated using the Kimura‐Nei approach, and the phylogenetic tree was constructed using the neighbour‐joining method (Saitou, 1987).

For the bigger datasets, the nucleotide sequence of the relevant isolates was viewed using MEGA version 7.0 (Kumar et al., 2016). Nucleotide BLAST (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi) is an online tool that searches GenBank databases for comparable nucleotide sequences (Hoque et al., 2022). The ClustalW tool was used to do multiple sequence alignment on a set of sequences obtained from NCBI that are very similar to one another (Hoque et al., 2022). Sequence quality was estimated using the Trimmomatic tool (version 0.39), which was also utilized to improve low‐quality sequences (Sultana et al., 2021). With the default settings of the MEGA 7.0 program, a maximum‐likelihood tree was constructed. The bootstrap test was used to determine the reliability of each node in the final phylogenetic tree (1000 replicates). Accessions numbers OP850272 and OP850273 have been assigned to the sequences in NCBI (https://www.ncbi.nlm.nih.gov).

2.6. Phenotypic antibiotic susceptibility test and carbapenemase production

To examine the antimicrobial sensitivity of prospective isolates on MHA, the disk diffusion method (Saha, Islam, et al., 2021; Saha, Rakhi, et al., 2021) was employed (Oxoid, UK). Antibiotic testing was performed on each isolate using a panel of antimicrobial agents, including Cefoxitin (Fox) (30 mg), Chloramphenicol (C) (30 mg), Aztreonam (ATM) (30 mg), Ampicillin (AMP) (10 mg), Doxycycline (DTX) (30 mg), Nitrofurantoin (F) (300 mg), Levofloxacin (LEV) (5 mg), Trimethoprim (Tm) (5 mg), Tetracycline (TE) (30 mg), Meropenem (MEM) (10 mg), Cefuroxime (CXM) (30 mg), nalidixic acid (NA) (30 mg), Gentamycin (CN) (10 mg), Ciprofloxacin (CIP) (5 mg), Imipenem (IMP) (10 μg), Doripenem (DOR) (10 mg) and Polymyxin B (PB) (10 mg). The minimum inhibitory concentrations (MICs) of IMP, MEM, CIP and CN were measured using the broth microdilution technique with twofold dilution in a range of 2–512 g/mL incubation at 37°C. These antibiotics represent the principal antimicrobial medicines used in veterinary and human medicine. Using the CLSI breakpoints, isolates were classed as susceptible, moderately resistant or resistant. The production of carbapenemase was determined using the modified Hodge test (MHT) according to the CLSI guidelines (Clinical and Laboratory Standards Institute (CLSI, 2016) and as described elsewhere (Okoche et al., 2015) with some modifications (not using Escherichia coli ATCC 25922 but using E. coli‐DH5 isolate that is susceptible to carbapenem antibiotics). A sterile cotton swab was used to distribute sensitive E. coli on Mueller–Hinton agar plates. Excess moisture is removed by pushing on the inside walls of the tube, followed by the dispersion of E. coli on all sections of the plates. Allow the plates to sit at room temperature for 3–10 min before placing them on the central MEM or IMP antibiotic. Next, 3–4 colonies of each KPN isolate were extracted with a sterile lobe and cultivated in a straight line from the antithesis to the plate's periphery, with a length of no less than 20–25 mm – incubate the plates for 19 h at 37°C (Kim et al., 2005). MDR KPN isolates were distinguished by their resistance to at least three drugs (Magiorakos et al., 2012).

2.7. Determination of multiple antibiotic resistance (MAR) indexing

The multiple antibiotic resistance (MAR) was determined using the following formula: MAR index = The percentage of antibiotics to which the isolate shows resistance/the total number of antibiotics exposed to the isolate, as estimated utilizing previously described criteria (Nandi & Mandal, 2016). An MAR score of ≤0.2 suggested a low risk of antibiotic contamination, whereas an MAR rating of ≥0.2 indicated a high risk of antibiotic contamination.

2.8. Molecular characterization of antibiotics resistance genes

To uncover resistance genes patterns, PCR was conducted. Class A β‐lactamase genes (bla _TEM, bla _SHV, bla _CTX), carbapenemase genes (bla _KPC, bla _SIM‐1, bla _VIM‐1, bla _IMP‐3/4, bla _NDM‐1 and bla _OXA‐48) and plasmid‐mediated quinolone resistance genes (qnrB) were identified using PCR amplification with specific primers (Marhova et al., 2010). The same primers were used, and the lengths of the expected PCR products are shown in Table 1. Amplicons were separated using 1.5% agarose gel electrophoresis and photographed using a Bio‐Rad ChemiDoc Imaging System (Knöbl et al., 2012).

TABLE 1.

Primers used for carbapenemase detection and corresponding annealing time and temperature used for PCR.

Name of primer	Primer sequence	Ta (°C)	Targeted gene	Size (bp)	References
OXA‐F	5′‐GCGTGGTTAAGGATGAACAC‐3′	54	bla OXA‐48	438	Rakhi et al. (2019)
OXA‐R	5′‐CATCAAGTTCAACCCAACCG‐3′
SIM1‐F	5′‐TACAAGGGATTCGGCATCG‐3′	56	bla SIM‐1	551	Lee et al. (2005)
SIM1‐R	5′‐TAATGGCCTGTTCCCATGTG‐3′
IMP4F	5′‐ATGAGCAAGTTATCTGTATTCT‐3′	58	bla IMP‐4	474	Rakhi et al. (2019)
IMP4R	5′‐AGTGTGTCCCGGGCCACC‐3′
TEM‐F	5′‐CATTTCCGTGTCGCCCTTATTC‐3′	55	bla TEM	438	Dallenne et al. (2010)
TEM‐R	5′‐CGTTCATCCATAGTTGCCTGAC‐3′
qnrBF	5′‐GGMATHGAAATTCGCCACTG‐3′	56	qnrB		Datta et al. (2004)
qnrBR	5′‐TTTGCYGYYCGCCAGTCGAA‐3′			264
NDM‐F	5′‐CTTCCAACGGTTTGATCGTC‐3′	58	bla NDM‐1	238	Rakhi et al. (2019)
NDM‐R	5′‐TAGTGCTCAGTGTCGGCATC‐3′
VIM1‐F	5′‐TTATGGAGCAGCAACCGATGT‐3′	60	bla VIM‐1	801
VIM1‐R	5′‐CAAAAGTCCCGCTCCAACGA‐3′
KPC5F	5′‐TGTCACTGTATCGCCGTC‐3′	58	bla KPC‐1	900
KPC10R	5′‐CTCAGTGCTCTACAGAAAACC‐3′
blaSHV‐R	5′‐GGTTAGCGTTGCCAGTGCT‐3′	59	blaSHV	861	Luo et al. (2011)
blaSHV‐F	5′‐TCGTTATGCGTTATATTCGCC‐3′
blaCTX‐1	5′‐TTAGGAARTGTGCCGCTGYA‐3′	55	blaCTX	688
blaCTX‐2	5′‐CGATATCGTTGGTGGTRCCAT‐3′
qnrAF	5′‐TCAGCAAGAGGATTTCTC‐3′	58	qnrA	627	Robicsek et al. (2005)
qnrAR	5′‐GGCAGCACTATTACTCCCA‐3′

2.9. Zone of inhibition (ZoI) assays for metal susceptibility testing

Heavy metals’ antimicrobial property against isolated microorganisms was investigated in vitro using agar well diffusion (Saha, Hoque, et al., 2020; Saha, Rakhi, et al., 2020; Vaidya et al., 2017). Four heavy metal salts were investigated to examine the magnitude of the zone of inhibition (ZoI): CuSO4.5H2O, ZnSO4.7H2O, K2Cr2O7 and CoCl2.6H2O for copper (Cu), zinc (Zn), chromium (Cr) and cobalt (Co) (ZoI). In summary, isolated pathogens from nutrient agar (NA) plates were subcultured into Mueller–Hinton agar (Oxoid, UK) plates, and four equal wells (7 mm diameter) were cut out of each agar plate with a sterile cork borer and stainless‐steel needle. Each well delivered 50–100 mL of the metal ion solution. The plates were incubated according to the directions in the cultures and medium sections. The ZoI was measured using metal ion solution concentrations of 50, 100, 500 and 1000 mg/L. Following incubation, the ZoI was measured in millimetres (mm) from each well's four corners to establish an average mean value.

3. RESULTS

3.1. Isolation and characterization of pathogenic KPN from poultry samples

First, 32 individual poultry samples were obtained from all poultry farms under assessment (Figure 1). Forty‐one isolates with typical KPN‐like colonies were first confirmed as positive premised on EMB and MC agar colony morphology. Then, KPN was supposed to be recognized using a set of biochemical tests and Gram‐staining (Figure S2). The biochemical analysis revealed that KPN was present in the isolates’ 43.90% (18/41). Furthermore, 38.89% of KPN isolated from droppings, 33.33% isolated from cloacal swab, 22.22% isolated from handler swab and 5.56% isolated from feeds were isolated, respectively (Figure 2). All biochemical findings were summarized using the web tool (Table 2). Moreover, the RAPD patterns revealed a definite trend among the isolates, signifying no wide variation among the KPN isolates. Repeated testing was used to verify the dependability of the RAPD approach (Figure S3).

FIGURE 1.

Schematic representation of bacterial poultry diseases studies in poultry caused by Klebsiella pneumonia (KPN). The research works include both phenotypic (selective culture and biochemical tests) identification, biofilm formation assay, antibiogram and heavy metals sensitivity profiling and molecular (16S rRNA gene sequencing, RPAD, marker specific multiplex PCR) characterization of KPN AMR gene(s) in poultry samples of diseases chickens. Phylogenetically similar, virulent, multidrug‐resistant (MDR) carbapenemases producing KPN strains are the predominant aetiology of poultry farms in Bangladesh.

FIGURE 2.

Genera/species‐level prevalence and distribution of Klebsiella pneumonia (KPN) species isolated from different poultry samples from studied poultry farms. Microorganisms identified in four different poultry samples (denoted by different colours). We have not found any positive isolates from feeding water and egg surface swab samples.

TABLE 2.

Summarization of biochemical results along with a Microrao tool for presumptive identification of isolates.

SL. no	Biochemical test	Results	Likelihood of the isolates by Microrao tool a (%‐confidence level)
1.	Indole test	Negative	Klebsiella pneumoniae (99.11)
2.	Methyl red test	Negative
3.	Voges–Proskauer test	Positive
4.	Citrate utilization test	Positive
5.	Hydrogen sulphide test	Negative
6.	Urea hydrolysis test	Positive
7.	Lysine decarboxylase test	Positive
8.	Motility test	Negative
9.	Gas from glucose	Positive
10.	Lactose fermentation test	Positive
11.	Sucrose fermentation test	Positive

^a http://www.microrao.com/index.html and BioCluster.

3.2. Biofilm‐forming (BF) capacity of KPN

In this biofilm‐forming (BF) investigation, the average OD of the negative control was 0.0280, and the threshold OD value was set at 0.045. The NBF isolates had an OD value of less than 0.045. All bacterial species developed biofilms in this study, with substantial biofilm formation accounting for 50.00%, intermediate biofilm formation accounting for 33.33% and feeble biofilm formation accounting for 16.67% (Figure 3 and Table 3).

FIGURE 3.

Klebsiella pneumonia (KPN) isolates with high, moderate and poor biofilm formation abilities. (a) Mean optical density at 600 nm of the 12 isolates after 48 h of growth at 37°C. Scan acoustic microscopy was used to examine the biofilms of three strong biofilm‐producing isolates (b) SK4, (c) SK23 and (d) SK29. The SAM micrographs showed colonizing bacterial cells after 48 h of incubation, as well as how the bacteria develop in clumps (micro‐colonies) and the exopolysaccharide that covers the bacterium. The standard deviation is shown by the error bars. The red bars indicate strong biofilm formation ability, whereas the yellow and green bars indicate moderate and poor biofilm formation capacity, respectively.

TABLE 3.

Relative comparison among isolated Pathogenic Klebsiella pneumonia (KPN) from poultry farm in Narsingdi, Bangladesh.

			Antibiotics profile	MIC interpretive criteria				MHT			MAR index
Isolates	Sources	BF		IMP	MEM	CN	CIP	IMP	MEM	Genotype
SK1	DR	0.195	AMP, C, DTX, F, Tm, Te, NA, ATM, IMP	>512	NA	NA	NA	+	NT	bla OXA‐48+, bla SIM‐1+, blaTEM+, qnrB+, bla IMP‐+4	0.53
SK2	DR	0.334	AMP, C, DTX, F, Tm, Te, CXM, NA, CIP, LEV, IMP, MEM	256	128	NA	>512	+	+	blaTEM+, bla SIM‐1−, bla IMP‐4+, bla OXA‐48−, qnrB−	0.71
SK3	CS	0.14	AMP, DTX, CN, Te, CXM, NA, ATM	NA	NA	>512	NA	−	NT	blaTEM+, qnrB+	0.41
SK4	CS	0.34	AMP, C, DTX, F, Tm, Te, CXM, NA, CIP, LEV, ATM, IMP, MEM, Fox	256	>512	NA	>512	+	+	bla OXA‐48+, bla SIM‐1+, blaTEM+, qnrB+, bla IMP‐4+	0.82
SK5	F	0.133	AMP, DTX, F, Te, C	NA	NA	NA	NA	NA	NA	Nil	0.29
SK6	DR	0.081	AMP, DTX, Te, NA	NA	NA	NA	NA	NA	NA	Nil	0.2
SK9	DR	0.066	AMP, DTX, F, Te	NA	NA	NA	NA	NA	NA	Nil	0.2
SK10	H	0.056	AMP, DTX, Te, NA, CIP	NA	NA	NA	>512	NA	NA	qnrB+	0.3
SK16	CS	0.152	AMP, DTX, F, Tm, Te, CXM	NA	NA	NA	NA	−	NT	blaTEM+	0.35
SK17	CS	0.102	AMP, DTX, F, Tm, Te, LEV	NA	NA	NA	NA	NA	NA	Nil	0.35
SK18	CS	0.192	AMP, DTX, F, CN, Tm, Te, NA, CIP, LEV, IMP	>512	NA	>512	>512	+	NT	bla OXA48+, bla SIM‐1+, blaTEM+, bla IMP‐4+, qnrB+	0.58
SK21	DR	0.102	AMP, DTX, F, CN, Tm, Te, NA, CIP, LEV	NA	NA	>512	256	NA	NA	qnrB+, blaTEM+	0.53
SK23	DR	0.31	AMP, C, DTX, F, CN, Tm, Te, NA, ATM	NA	NA	>512	NA	NA	NA	qnrB+, blaTEM+	0.53
SK24	DR	0.152	AMP, C, DTX, F, Te, LEV	NA	NA	NA	NA	NA	NA	Nil	0.3
SK29	F	0.23	AMP, DTX, Te, Fox, CXM	NA	NA	NA	NA	NA	NA	Nil	0.2
SK30	F	0.121	AMP, DTX, F, Tm, Te, NA, LEV, IMP	256	NA	NA	NA	+	NA	blaTEM+, bla SIM‐1−, bla IMP‐4+, bla OXA48+	0.53
SK33	F	0.197	AMP, DTX, Te, NA, ATM	NA	NA	NA	NA	NA	NA	qnrB+	0.2
SK35	CS	0.074	AMP, C, DTX, F, Te, ATM	NA	NA	NA	NA	NA	NT	blaTEM+	0.2

Abbreviations: −, negative; +, positive; AMP, Ampicillin; BF, biofilm formation; C, Chloramphenicol; CIP, Ciprofloxacin; CN, Gentamycin; CS, cloacal samples; CXM, Cefuroxime; DR, dropping; DTX, Doxycycline; F, Nitrofurantoin; F, feed; Fox, Cefoxitin; H, handler swab; IMP, Imipenem; LEV, Levofloxacin; MAR, multiple antibiotic resistances; MEM, Meropenem; MHT, modified Hodge test; MIC, minimum inhibitory concentration; NA, nalidixic acid; NA, not applicable; ND, not done; Nil, no tested antibiotics gene present; NT, not tested; PB, polymyxin B; Te, Tetracycline; Tm, Trimethoprim; W, feeding water.

3.3. Genetic evolutionary analysis of KPN

A phylogenetic tree was constructed using nucleotide sequences acquired from 2 KPN isolates and 12 previously reported reference sequences collected from the NCBI database. The phylogenetic study of ribosomal gene sequencing showed a single clade, KPN. KPN strains examined in clade KPN were 98%–100% identical to KPN (NR114506) (Figure 4).

FIGURE 4.

The 16S rRNA gene sequences isolated from poultry samples in Bangladesh are used for the phylogenetic characterization of poultry microbial strains (OP850272 and OP850273). Treponema denticola is included in the out group. The sequences were built using Molecular Evolutionary Genetics Analysis (MEGA) 7.0's maximum‐likelihood technique and the Kimura 2‐parameter model (Saitou, 1987), and they were aligned using the ClustalW software. After each species name, you will find the related sequencing strain(s) (n = 14) and GenBank accession number(s). Next to the tree, the Bootstrap values are shown for reference.

3.4. Assessment of the KPN's phenomenological antimicrobial resistance

The Kirby–Bauer disk diffusion test was being used in the investigation to evaluate the resistance of this KPN to 17 drugs. Figure 5 and Table 3 show the outcomes of assessing the resistance patterns to 17 antibiotics in the 18 isolates. The isolates screened exhibited differing levels of resistance to these medicines. The total antimicrobial susceptibility demonstrated PB (100%), DOR (100%), MEM (88.89%), Fox (77.78%) and CN (55.56%) to be the most effective medications against KPN infections, whereas other antimicrobials tested showed substantial resistance. Astonishingly, 100% of the MDR isolates were resistant to AMP/DXT/TE, 61.11% to NA, 66.67% to F, 50% to Tm, 38.89% to LEV/C, 33.33% to ATM and 27.78% to IMP/CIP (Figure 5 and Table 4). The antibiotic coding profiles revealed that 100% of the isolated isolates had MAR to four or more antibiotics. Thirteen isolates (72.22%) were identified with an MAR index of more than 0.2, whereas five isolates (27.78%) were less than 0.2. No isolates, however, had an MAR index of 1 (i.e. resistant to all the antimicrobials tested). Meanwhile, seven isolates had an MAR index of 0.5, with four retrieved from droppings samples, two from cloacal swab samples and one from feed sample (Table 3).

FIGURE 5.

Antibiotic sensitivity and resistance pattern chart of isolated Klebsiella pneumonia (KPN) against different antibiotics. Here, (a) red bars are showing resistant percentages, orange and green colours indicating moderate and sensitive percentages, respectively. (b) Here, changing pattern of resistant and sensitivity are shown in term of antibiotics class.

TABLE 4.

Antimicrobial resistance patterns of Klebsiella pneumonia (KPN) isolates from informal settlement.

Antibiotic used	Disc potency (μg)	Breakpoint to declare resistance (≤mm)	Breakpoint to declare moderately resistance (≤mm)	Breakpoint to declare sensitive (≤mm)	Percentage of resistant isolates (n = 18)
Ampicilin (AMP)	30	≤13	14–16	≥17	100 (18)
Chloramphenicol (C)	30	≤12	13–17	≥18	38.89 (7)
Doxycycline (DTX)	30	≤10	11–13	≥14	100 (18)
Trimethoprim (Tm)	5	≤10	11–15	≥16	50 (9)
Gentamycin (CN)	10	≤12	13–14	≥15	22.22 (4)
Tetracycline (TE)	30	≤11	12–14	≥15	100 (18)
Cefuroxime (CXM)	30	≤14	15–17	≥18	27.78 (5)
Nitrofurantoin (F)	300	≤14	15–16	≥17	66.67 (12)
Nalidixic acid (NA)	30	≤13	14–18	≥19	61.11 (11)
Ciprofloxacin (CIP)	5	≤21	22–25	≥26	27.78 (5)
Levofloxacin (LEV)	5	≤16	17–20	≥21	38.89 (7)
Aztreonam (ATM)	30	≤17	18–20	≥21	33.33 (6)
Imipenem (IMP)	10	≤19	20–22	≥23	27.78 (5)
Meropenem (MEM)	10	≤19	20–22	≥23	11.11 (2)
Polymyxin B (PB)	10	≤10	–	≥11	0 (0)
Doripenem (DOR)	10	≤19	20–22	≥23	0 (0)
Cefoxitin (Fox)	30	≤14	15–17	≥18	11.11 (2)

3.5. Determination of MIC of resistant antibiotics of KPN

In CIP, five isolates of KPN had MICs ranging from >512 to 256 mg/mL (Table 3). In particular, four isolates showed gentamicin MICs higher than 512 mg/mL. Furthermore, three of the five IMP‐resistant isolates (60%) had a high Imipenem MIC of 256 mg/mL, with the other two isolates having an MIC of >512 mg/mL. Two MEM resistant isolates, on the other hand, showed MEM MICs of 128 (SK2) and >512 (SK4) mg/mL (Table 3).

3.6. Phenotypic detection of carbapenemase‐producing KPN

The MHT was used to explore KPN isolates’ capacity to synthesize carbapenemase enzymes. The results of this study revealed that five (SK1, SK2, SK4, SK18 and SK30) isolates out of nine (five resistant and four mild sensitives) tested isolates resistant to carbapenem antibiotics (55.56%) produced a positive result, whereas four isolates (44.44%) gave a negative result (Table 3).

3.7. Molecular detection of antimicrobial resistance genes in KPN

According to PCR recognition of ESBL genotypes, 10 (55.56%) KPN isolates carried 1 ESBL gene (bla _TEM) investigated in the current study. Likewise, pool‐1 (bla _SIM‐1, bla _IMP‐4 and bla _OXA‐48) was detected in three carbapenem‐resistant isolates (60%) and pool‐2 (bla _IMP‐4 and bla _OXA‐48) in one isolate. The presence of the qnrB gene was detected by electrophoresis in 8 (44.44%) of the isolates. Rather than a single antibiotic resistance gene, eight isolates (44.44%) possessed several genes, with bla _TEM + bla _IMP‐4 + qnrB being the most prevalent combination. The carbapenemase bla _IMP‐4 (5) was found to be the most often found, followed by bla _OXA‐48 (4) and bla _SIM‐1 (3). Furthermore, four isolates (22.22%) had just one tested gene (bla _TEM/qnrB), and six MDR isolates (33.33%) had no tested antibiotic resistance genes. No qnrA, bla _CTX, bla _SHV, bla _KPC‐1, bla _VIM‐1 or bla _NDM‐1 genes were detected in any of the tested strains (Figure 6 and Table 3).

FIGURE 6.

ARGs analysis of representative isolates. White box is indicating the appropriate position of the bands. Here (a) Lanes 2, 6, 10 and 15 are blank negative controls. Lanes 3–5, 7–9, 11–14, 16–19 to Klebsiella pneumonia (KPN) isolates positive for bla _OXA‐48, bla _SIM‐1, bla _TEM, bla _IMP‐4, respectively. Lanes 1 and 20 are molecular makers (100 bp and 1 KB, respectively). (b) Lane 2 is blank negative controls. Lane 3–5 to KPN isolates positive for qnrB. Lane 1 is molecular makers (100 bp).

3.8. Determination of zone of inhibition (ZoI) of heavy metals

In the ZoI test, all isolated KPN was classified into three categories based on MAR index values: Category A (MAR index 0.5), Category B (0.3 but 0.5) and Category C (0.2 but 0.3). In this ZoI assay, four isolates were chosen for examination based on the following three categories. ZoI experiments utilizing individual metal solutions revealed an increase in antibacterial activity proportional to the concentration of metal ions in the solution (Figure S4). At 1000 mg/L concentration, Cu, Zn, Cr and Co displayed the highest ZoIs against all tested microorganisms (>5 and 24 mm). At 1000 mg/L, copper displayed the lowest antibacterial efficacies (>5 and 8 mm ZoI) (Figure 7). At 1000 mg/L concentration, Cr displayed the highest antibacterial efficacies (>17 and 24 mm ZoI), followed by Co (>15 and 22 mm ZoI). Only Cr and Co displayed antibacterial efficacy at lower doses (50 mgL/) (>2 and 4 mm ZoI) against all three tested isolates (Figures 7 and 8). There were no significant variations among the three groups mentioned.

FIGURE 7.

Antibacterial activity of heavy metals: Cu (CuSO₄), Zn (ZnO), Cr (K₂Cr2O₇), Co (CoCl₂) against poultry pathogen Klebsiella pneumonia (KPN). Zone of inhibition (ZOI, mm) for four poultry diseases causing KPN, each colour representing the each concentration of metals for each bacterium.

FIGURE 8.

Zone of inhibition values for four metals at different concentrations against tested four pathogens demonstrating that at higher concentrations, chromium (Cr) and cobalt (Co) were the most effective antimicrobials, whereas at lower concentrations (50 mgL⁻¹), copper and zinc demonstrated no antimicrobial activity (p < 0.001). Black error indicates the increasing trend of the sensitivity zone.

4. DISCUSSION

With an annual frequency of 10%–80%, bacterial poultry infections are among the most contagious illnesses poultry may get (Saha, Hoque, et al., 2020; Saha, Rakhi, et al., 2020). There has been little to no research done in Bangladesh (Hasan et al., 2012; Rahman et al., 2017, 2018) on the heavy metal resistance of carbapenemases producing MDR KPN in poultry, despite the fact that the epidemiological prevalence of KPN and its antimicrobial resistance pattern has been studied at length in farm animals in other countries (Fielding et al., 2012; Kowalczyk et al., 2022). Therefore, in light of the current farming situation in Bangladesh, the purpose of this study was to characterize KPN isolates in poultry samples collected from chickens with poultry bacterial diseases with regard to their antimicrobial resistance and molecular identification of carbapenemases gene(s). Moreover, the susceptibility to heavy metals, pathogenicity and evolutionary connection was also studied (Figure 1).

Once upon a time, it was believed that antibiotic resistance emerged only in health care settings like hospitals. New research, however, shows that the animals used to grow fresh produce are a major source of MDR microorganisms (Bachiri et al., 2017; Belmahdi et al., 2016). The widespread use of antibiotics in livestock production for the purposes of curing diseases, promoting growth and warding off infection was largely to blame (Economou & Gousia, 2015). There is strong evidence from several research studies linking close contact with farm animals to an increased risk of contracting antibiotic‐resistant bacteria (Huijbers et al., 2014). By considering all of the above circumstances, in this study, antimicrobial‐resistant Gram‐negative carbapenemases generating KPN in poultry farms were quantified in Narsingdi, Bangladesh. The incidence is far higher than that previously observed from the chicken feed in Bangladesh (Rahaman et al., 2021; Roy et al., 2017). On a global scale, the prevalence found in our study is similar to that reported in South Africa (40%) (Fielding et al., 2012) and Egypt (35%) (Hamza et al., 2016), but higher than that described in Egypt (22.2%) (Hoelzer et al., 2017), Nepal (30.4%) (Saud et al., 2019), Nigeria (7%) (Akinbami et al., 2018) and China (9.9%) (Guo et al., 2016). Differences in screening methodologies, sampling methods and antibiotic consumption levels in each region might explain these discrepancies (Rhouma et al., 2016). Going to follow the inspection for the occurrence of KPN, the next most essential question is whether it is pathogenic? May have any connection to pathogenicity and antibiotic resistance? Biofilm would be the greatest response to the question (Singh et al., 2017). Bacterial biofilm is an essential virulence factor that promotes the first phase of pathogenesis by allowing bacteria to attach to diverse cell/tissue surfaces (Singh et al., 2017). However, the link between KPN BF and antibiotic resistance is unknown. All 18 MDR KPN isolates formed biofilm to varying degrees in this investigation. The present investigation found a substantial relationship between BF and resistance, particularly carbapenemases producers, corroborated by two earlier publications by Yang and Zhang (2008) and Subramanian et al. (2012). Several writers have also observed a link between biofilm development and antibiotic resistance (Ito et al., 2009; Marhova et al., 2010). As a result, there may be a link between KPN BF and antibiotic resistance to be investigated further. Following that, the most worrisome issue is antibiotic resistance. Antimicrobial therapy in chicken businesses is an effective control method for avoiding KPN infection. Unfortunately, the growth of MDR bacteria and the spread of resistance genes have made it difficult to reduce the incidence of these infections (Saud et al., 2019). In this investigation, all examined isolates exhibited MDR phenotypes, with MDR to four or more drugs. Similar resistance characteristics have been observed in KPN isolated from sick chickens in numerous countries (Guo et al., 2016; Saha, Islam, et al., 2021; Saha, Rakhi, et al., 2021), and more recently in MDR KPN isolated from animal samples in China (Guo et al., 2016; Yang et al., 2019). Antibiotics such as DTX, NA, E and PEN are commonly used in chicken disease management and treatment (Fielding et al., 2012). When these medicines are given to birds for a lengthy period, especially at low doses, some bacteria grow resistant (Kilonzo‐Nthenge et al., 2008). Worryingly, increasing scientific data indicates that these resistant microorganisms, including diseases, can be transmitted to people via the food chain (Fielding et al., 2012). Resistance to the multidrug AMP, DTX, TE, NA, F, LEV, Tm, IMP, CIP, CXM and C was found in KPN isolates in this investigation. This finding was consistent with earlier studies (Kim et al., 2005) of MDR KPN being isolated in agricultural settings and retail chicken and beef products. Several drugs, including AMP, S3, CN, C and TE, are resistant to KPN (Rasool et al., 2003). Antibiotic‐resistant bacteria are a major problem in hospitals, making KPN an increasingly urgent issue. Contradicting our results is a research by Zhang et al. (2018), which found that more than 90% of KPN isolates from retail foods in China are susceptible to quinolone antibiotics, including CIP. Although antibiotics play an important role in current livestock production systems, the use of some of the more costly and freshly manufactured antibiotics for treating infections and stimulating animal development is very limited (Yang et al., 2019). Thus, bacteria exhibit less drug resistance against these antibiotics than against traditional antibiotics. IMP and MEM, for example, are rarely used to treat animal illnesses. However, in the current analysis, we discovered that certain KPN isolates were resistant to IMP and MEM, which contradicts a prior result by Davis and Price (2016) but corresponds with Yang et al. (2019). The most worrisome finding in this study was KPN resistance to MEM, CIP, CN and IMP, which are widely used to treat KPN infection in humans (Ryanto et al., 2019; Nekidy et al., 2017). Such pathogens in food may provide a major risk to consumers, as these viruses have been linked to persistent infections with higher morbidity and death (Warjri et al., 2015; Zhang et al., 2018). The most encouraging aspect of this study is that the isolates were susceptible to PB, DOR and Fox. Furthermore, 10 (55.56%) of those with ESBLs carried just one ESBL gene (bla_TEM). Our findings differ significantly from a prior study, which discovered all three ESBL gene‐carrying isolates (Wu et al., 2016). On the other hand, Elmonir et al. (2021) recently found that both chicken and human KPN isolates had β‐lactamase genes (bla _SHV, bla _TEM, bla _CTX‐1 and bla _OXA‐1). Our observations, however, clearly suggest that the antimicrobial resistance of the isolates from the commercial broiler factory is severe, particularly resistance to β‐lactam antibiotics. This high percentage of MDR bacteria of food origin might be ascribed to antibiotic misuses, such as β‐lactams, in the commercial broiler slaughter facility, and this is likely true for the whole poultry business (Guo et al., 2016). Second, 27.78% of the KPN isolates from poultry samples were carbapenem‐resistant, with MIC values ranging from 128 to more than 512, and they were all positive for bla _IMP‐4 which was similarly reported by two previous studies by Hamza et al. (2016) and Abdallah et al. (2015). Davis and Price (2016) predicted the risk of KPN transmission between poultry and people after discovering a close phylogenetic link between chicken meat and human clinical isolates. This begged the issue of how such strains may have emerged in poultry farms. Although carbapenems are not often used in chicken farming, the extensive use of other antibiotic classes such as Tetracyclines, quinolones and cephalosporins may co‐select for the presence of KPN (EFSA Panel on Biological Hazards (BIOHAZ), 2013). Consequently, chicken carcasses and droppings might be a possible source of KPN strains spreading to the surrounding environment, either via direct contact or through insects (Marshall et al., 2009). On the other hand, human‐to‐animal transmission is plausible as carbapenems producing KPN bla _KPC, bla _OXA‐48 and bla _NDM were previously identified from hospitalized patients (Gamal et al., 2016; Hamza et al., 2016). This shows that the resistance genes were acquired in hospitals and spread to fields via diseased human carriers or sewage discharge. Water has been proposed as a source for the interchange of resistance determinants and the establishment of novel resistant strains in another study (Marshall et al., 2009). Quinolones are broad‐spectrum antibacterial medicines widely employed in clinical care and food‐producing animals (Wu et al., 2016). This study confirms previous findings that a high proportion (75%) of ESBL and carbapenemase‐producing isolates also have the PMQR gene (qnrB) (Wu et al., 2016). It is past time that we do something about this dire predicament. Novel biocidal and antibacterial formulations are needed due to the rise of MDR bacteria in the poultry environment (Vaidya et al., 2017). Metal compounds and complexes, including copper, zinc, chromium and cobalt, have been shown to be very effective antibacterial agents against a diverse range of antimicrobial‐resistant microorganisms (Sair & Khan, 2018; Yazdankhah et al., 2018; Vaidya et al., 2017). Seven very MDR isolates were also teMetal resistance trends vary significantly depending on concentration (Vaidya et al., 2017), verified by the current investigation. The following trends were at the four concentrations studied: Cr > Co > Zn > Cu. Others found similar findings for copper, zinc, cobalt and nickel, with antibacterial activity increasing with increasing concentrations (from 5 to 20 mg/L) (Etaiw et al., 2011). Copper, nickel and cobalt coupled with coumarin‐8‐yl ligands have similarly shown better bacterial suppression against KPN at 100 mg/L compared to 25 or 50 mg/L (Sair & Khan, 2018; Vaidya et al., 2017). Thus, combining antimicrobial drugs may boost their antibacterial activity by providing a synergistic effect (Vaidya et al., 2017). Others’ work has shown that silver ions have a lower MBC value for E. coli planktonic cells than biofilm, which is consistent with our findings (Choi et al., 2010). Bacterial resistance to various antibiotics and heavy metals (Cu and Zn) in chicken samples, on the other hand, strongly implies that resistance to both antibiotics and metals may be genetically connected. For several decades, it has been recognized that antibiotic–metal resistance genes are connected, particularly on plasmids, with evidence for co‐selection coming from research that employed plasma curing, transformation and plasma sequencing techniques (Ramos‐Vivas et al., 2019; Sair & Khan, 2018). The cohabitation of antibiotics and metals may significantly impact the development and spread of MDR (Sair & Khan, 2018; Vaidya et al., 2017; Yazdankhah et al., 2018). Some questions arise as a result of the coexistence phenomenon; for example, how this bacterium could have achieved antibiotic and metal cross resistances in its natural aquatic environment, how these two resistances might interact with each other, and whether one resistance has an impact on the regulation of the other. Thus, it is possible that the presence of both metal and antibiotic resistance exists because metal exerts a selective pressure in the environment that indirectly induces the selection of antibiotic resistance, especially in environments contaminated with these two elements (McIntosh et al., 2008), or because antibiotics exert positive selective pressure on bacteria to acquire metal resistance (Baker‐Austin et al., 2006). There are certain flaws in this research. To begin, we did not collect information on the prevalence of antimicrobial use in agriculture in the areas that supplied the farms, stores and restaurants where we conducted our analyses. The second was that no clinical isolates from the same geographic region had been linked to these KPN isolates that had been found in contaminated food. In addition, data from only one site was utilized in this study, and few antimicrobial‐resistant gen primers were employed. As a last caveat, a major limitation is the very limited sample size of isolated organisms.

5. CONCLUSION

Our results show that MDR Gram‐negative KPN is present in a poultry farm in Narsingdi, Bangladesh. Poultry illnesses in chickens caused by KPN are more common (>43.0%) in Bangladesh, which is a major public health concern. Throughout the sample area, bacteria are producing strains of MDR, carbapenemases and ESBL that are resistant to many classes of antibiotics often employed in the treatment of humans. Antibiotic susceptibility testing identified KPN as a MDR pathogen owing to the presence of bla _SIM‐1, bla _IMP‐4 and bla _OXA‐48 genes, as well as an extended‐spectrum β‐lactamase gene (bla _TEM) and a plasmid‐mediated quinolone resistance gene. Our findings, based on the existing available molecular data, suggest that chicken farms in Narsingdi are significant reservoirs of antibiotic resistance. Although just a small number of investigations have shown carbapenemase producers in Bangladesh livestock (Ahmed et al., 2019; Azad et al., 2019), these organisms will soon become widespread in Bangladesh animal farms. Even more so if strict rules are not enacted to restrict the abuse and misuse of antibiotics in Bangladesh agriculture for treatment, growth augmentation and prophylaxis. Based on our research, we know that there needs to be a greater emphasis on KPN monitoring of the poultry industry and chicken‐derived goods.

AUTHOR CONTRIBUTIONS

Otun Saha carried out the studies (sampling, sequencing, molecular and data analysis) and participated in drafting the manuscript. Otun Saha and Rabeya Basri visualized figures, interpreted data and results, critically reviewed and edited the manuscript. Munawar Sultana and M. Anwar Hossain developed the hypothesis, supervised the whole work and helped to prepare and critically revise the manuscript. All authors read and approved the final manuscript.

CONFLICT OF INTEREST STATEMENT

The authors declare that they have no conflict of interests.

ETHICS STATEMENT

Ethics approval and consent to participate Ethical approval were granted from the Ethics Committee of the Faculty of Biological Sciences, University of Dhaka, Bangladesh who has approved the procedure under the Reference 71/Biol.Scs./2018‐2019.

PEER REVIEW

The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer‐review/10.1002/vms3.1168.

Supporting information

Supporting Information

Saha, O. , Basri, R. , Hossain, M. A. , & Sultana, M. (2023). Characterization of multidrug and heavy metal resistance of carbapenemases producing Klebsiella pneumoniae from poultry samples in Bangladesh. Veterinary Medicine and Science, 9, 1685–1701. 10.1002/vms3.1168

DATA AVAILABILITY STATEMENT

The data that supports the findings of this study is available in the Supporting Information section of this article.