Abstract
Background and Objectives:
Antibiotic resistance is an indicator of the passively acquired and circulating resistance genes. Salmonella Gallinarum significantly affects the poultry food industry. The present study is the first study of the S. Gallinarum biofilm in Iran, which is focused on the characterization of the S. Gallinarum serovars and their acquired antibiotic resistance genes circulating in poultry fields in central and northwestern Iran.
Materials and Methods:
Sixty isolates of S. Gallinarum serovar were collected from feces of live poultry. The bacteria were isolated using biochemical tests and confirmed by Multiplex PCR. Biofilm formation ability and the antibacterial resistance were evaluated using both phenotypic and genotypic methods. The data were analyzed using SPSS software.
Results:
According to Multiplex PCR for ratA, SteB, and rhs genes, all 60 S. Gallinarum serovars were Gallinarum biovars. In our study, the antibiotic resistance rate among isolated strains was as follows: Penicillin (100%), nitrofurantoin (80%), nalidixic acid (45%), cefoxitin (35%), neomycin sulfate (30%), chloramphenicol (20%), and ciprofloxacin (5%). All isolates were susceptible to imipenem, ertapenem, ceftriaxone, ceftazidime, and ceftazidime+clavulanic acid. All sixty isolates did not express the resistance genes IMP, VIM, NDM, DHA, blaOXA48, and qnrA. On the other hand, they expressed GES (85%), qnrB (75%), Fox M (70%), SHV (60%), CITM (20%), KPC (15%), FOX (10%), MOXM (5%), and qnrS (5%). All S. Gallinarum isolates formed biofilm and expressed sdiA gene.
Conclusion:
Considering that the presence of this bacteria is equal to the death penalty to the herd, the distribution of resistance genes could be a critical alarm for pathogen monitoring programs in the region. This study showed a positive correlation between biofilm formation and 50% of tested resistance genes. Also, it was found that the most common circulating S. gallinarum biovars are multidrug-resistant.
Keywords: Salmonella, Poultry disease, Antibiotic resistance
INTRODUCTION
Salmonella contamination is a major expense in the poultry industry. Contamination with S. gallinarum serotypes causes host death or reduced chicken production. Close monitoring to eliminate Salmonella serovars (such as Typhi, Typhimurium and Enteritidis) from food are needed (1). Also, some Salmonella serovars such as S. Enteritidis, S. Heidelberg, S. Kentucky and S. Gallinarum, which could spread to the reproductive organs and contaminate the next generation, must be omitted (2).
Presently, Gallinarum and Pullorum are categorized as biotypes of Salmonella Gallinarum serovar (3). S. enterica serotype Gallinarum is responsible for fowl typhoid (1), affecting the mature chicken and spreading horizontally (4). Fundamentally, in such infections, the herd should be destroyed, all the rodents and insects should be eradicated, and the cages should be kept empty for some time. Therefore, Gallinarum biovars lead to considerable economic losses in the poultry industry worldwide. Moreover, since they are found in other farm animals, the chickens are considered as a source of transmitting the microbiota to a variety of hosts.
Both Salmonella biovar Gallinarum and biovar Pullorum are non-motile bacteria with shared biochemical traits and somatic antigens (1). The results of various studies on the worldwide prevalence of S. Gallinarum between the years 1981 and 2020 showed that the prevalence of S. Gallinarum decreased until 2006, but from that year, there was an increasing prevalence rate of S. Gallinarum worldwide (5). Thus, the identification of biovar is vital due to the mentioned consequences for the poultry industry.
Biofilm is a biologically active matrix composed of persistent cells and extracellular substances formed on surfaces inside and outside the host body (6). The ability of bacteria to form biofilms and also the frequency of transferred genetic material encoding multidrug resistance (MDR) traits among biofilm-forming bacteria are important (7–10). The correlation between antibiotic resistance and severity of biofilm formation is an interesting field of study.
Administration of antibiotics and food containing antibiotics are the main causes of antibiotic resistance in poultry. These antibiotics promote biofilm formation and prevent bacterial eradication by conventional antibiotics (11). Diagnosis of Salmonella serovars in the field and information on their antibiotic resistance could define the protocol for administering the antibiotics in the poultry industry (12).
Salmonella serovars are differentiated by cultural, biochemical, and molecular techniques. These techniques have been used to distinguish S. entrrica serovar Gallinarum from other Salmonella species (13, 14). Although Salmonella biovar Gallinarum and Pullorum are distinguished primarily on the basis of biochemical tests, including tests for ornithine and dulcite decarboxylase, it is widely believed that some atypical biovars are difficult to distinguish. Recent molecular techniques have suggested some genes for the differentiation of these two biovars. ratA and SteB represent hypothetical proteins and fimbrial usher genes respectively. ratA is a pseudogene without a premature stop codon in open reading frames in each of the biovars. The RHS family (rhs) pseudogenes encode type II toxin-antitoxins. Hq703462 is a partial coding sequence for the putative RHS protein. The amplification result differs between the biovars Gallinarum and Pullorum. Although the rhs gene is shared by these two biovars, SteB is unique to biovar Gallinarum (15).
Due to the importance of S. Gallinarum contamination in the poultry industry and increasing antibiotic resistance, we decided to assess the prevalence of S. Gallinarum and also the pattern of antibiotic resistance of S. Gallinarum in samples collected from different farms. Furthermore, since bacteria in the biofilm are more resistant to antibiotics, we estimated the relationship between the ability to form biofilms and the pattern of antibiotic resistance. We hope that the results of our study can help expose the misuse of antibiotics in the poultry industry. According to these results, the urgent need for appropriate antimicrobial regimen surveillance programs can be highlighted in order to prevent the increasing rate of antimicrobial resistance.
MATERIALS AND METHODS
Isolation, diagnosis of Salmonella from feces samples.
Feces samples were collected from 18 farms of different provinces of Iran, including Tehran, Qom, Qazvin, Fars, West Azerbaijan, and East Azerbaijan from 2012 to 2017 based on the A Laboratory Manual for the Isolation, Identification, and Characterization of Avian Pathogens, fifth Edition, Salmonellosis. Then the group D non-motile Salmonella (60 samples (was isolated. The bacteria were confirmed by microbiological analysis based on (ISO6579), including culture on xylose lysine desoxycholate agar (XLD) (Merck, germany) and RVS broth (Rappaport-Vasiliadis Soy Peptone) (Merck, germany). Then, biochemical analysis, including Lysine decarboxylase, Voges-Proskauer, indole reaction, beta-galactosidase reaction, urease, and H2S production, was performed. Subsequently, the isolates were serotyped with specific O and H Salmonella antisera (Mast, UK) and classified based on the Kauffman White scheme.
Extraction of DNA.
The genomic DNAs of the 60 S. Gallinarum serovar isolates were extracted using the kit (Roch life science Cat. No. 11796828001).
Differentiation of Salmonella gallinarum biovars.
To differentiate between Salmonella enetrica biovar Gallinarum from Pullorum, ratA, steB, and rhs genes were amplified by Multiplex PCR (16). The amplified Hq703462 gene was used as an internal control to confirm the isolated S. Gallinarum serotype by PCR. The standard strains of both biovars were obtained from the OIE (World Organization for Animal Health, Padua, Italy). PCR was performed in a 25 μl of the reaction mixture using primer pairs shown in Table 1; the following PCR program was used: 1 cycle for initial denaturation at 95°C for 5 minutes, 40 cycles for denaturation at 94°C for 40 seconds, annealing stage at 56°C (or 60 for Hq703462) for 30 seconds, elongation step at 72°C for 40 seconds, and final elongation cycle at 72°C for 7 minutes. A PCR reaction without the template was used as a negative control.
Table 1.
The sequences of paired primers used in this study
| Target gene | Primer name | Oligonucleotide sequences (5′ to 3′) | Biovar | Annealing temperature (°C) | PCR product size (bp) | Reference |
|---|---|---|---|---|---|---|
| steB | steB-F | TGTCGACTGGGACCCGCCCGCCCGC | Gallinarum (D1) | 56 | 636 | (17) |
| steB-R | CCATCTTGTAGCGCACCAT | the gene is absent in pullorum | ||||
| rhs locus | rhs-F | TCGTTTACGGCATTACACAAGTA | Gallinarum +Pullorum | 56 | 402 | (15) |
| rhs-R | CAAACCCAGAGCCAATCTTATCT | |||||
| ratA | ratA-f | GACGTCGCTGCCGTCGTACC | Gallinarum +Pullorum | 56 | SG:1047 | (18) |
| ratA-r | TACAGCGAACATGCGGGCGG | SP:243 | ||||
| Hq703462 | Hq-f | CGATATAGCTTACTGTGTCCCG | Gallinarum | 60 | 145 | (13) |
| Hq-r | TCATGCACTACCACCATAACG |
SG is Salmonella Gallinarum and SP: Salmonella Pullorum
Antibacterial susceptibility testing.
Antibiotic susceptibility test was performed using the disk diffusion method on Muller-Hinton Agar media with various antibiotics of different classes based on CLSI 2022 guidelines suggestions (19). The antibiotics were purchased from Mast Company (UK), including penicillin (10 μg), nitrofurantoin (50 μg), nalidixic acid, (30 μg), amoxicillin (25 μg) amoxicillin (20 μg) + clavulanic acid (10 μg), cefoxitin (30 μg), colistin sulfate (10 μg) chloramphenicol (30 μg), ciprofloxacin (5 μg), ceftazidime (30 μg), ceftazidime (30 μg) + clavulanic acid (10 μg), ceftriaxone (30 μg), cefepime (30 μg) ertapenem (10 μg), kanamycin (30 μg), trimethoprim (1.25 μg) + sulfamethoxazole (23.7 μg), and imipenem (10 μg).
Determination of antimicrobial resistance genes.
In this study, the frequency of 14 antimicrobial resistance genes was evaluated. Salmonella isolates underwent a PCR test to detect the presence of reistance genes mentioned in Table 2. PCR was accomplished in a 25 μl final volume with a reaction mixture containing 1 μl of each primer using primer sequences presented in Table 2. The following PCR program was used: one cycle for initial denaturation at 95°C for 5 minutes, 30 cycles with denaturation at 94°C for 40 seconds, annealing step at 56°C for 30 seconds, extension stage at 72°C for 50 seconds, and final extension stage in 72°C for 10 minutes.
Table 2.
Oligonucleotide primers used for detection of antimicrobial resistance and biofilm genes
| Primers | Sequences | Amber classification | Genes | Size of PCR-amplified product (bp) | Annealing temperature (°C) | References |
|---|---|---|---|---|---|---|
| IMP-F | GGAATAGAGTGGCTTAATTCTC | B | IMP | 232 | 56 | (20) |
| IMP-R | GGTTTAACAAAACAACCACC | |||||
| VIM-F | GTTTGGTCGCATATCGCAAC | B | VIM | 389 | 56 | (21) |
| VIM-R | AATGCGCAGCACCAGGATAG | |||||
| GES-F | ATGCGCTTCATTCACGCAC | - | GES | 591 | 56 | (22) |
| GES-R | CTATTTGTCCGTGCTCAGG | |||||
| NDM-F | GGTTTGGCGATCTGGTTTTC | B | NDM | 621 | 56 | (20) |
| NDM-R | CGGAATGGCTCATCACGATC | |||||
| blaOXA48 -F | GCGTGGTTAAGGATGAACAC | D | bla OXA48 | 438 | 56 | (20) |
| blaOXA48 -R | CATCAAGTTCAACCCAACCG | |||||
| SHV-F | ATGCGTTATATTCGCCTGTG | A | SHV | 896 | 56 | (22) |
| SHV-R | AGATAAATCACCACAATGCGC | |||||
| KPC-F | CGTCTAGTTCTGCTGTCTTG | A | KPC | 798 | 50 | (Saffar et al., 2016) |
| KPC-R | CTTGTCATCCTTGTTAGGCG | |||||
| qnrB-F | GATCGTGAAAGCCAGAAAGG | - | qnrB | 469 | 50 | (23) |
| qnrB-R | ACGATGCCTGGTAGTTGTCC | |||||
| FOX-F | CACCACGAGAATAACC | - | bla FOX | 1184 | 50 | (24) |
| FOX-R | GCCTTGAACTCGACCG | |||||
| QnrA-F | ATTTCTCACGCCAGGATTTG | - | qnrA | 516 | 52 | (23) |
| QnrA-R | GATCGGCAAAGGTTAGGTCA | |||||
| QnrS-F | ACGACATTCGTCAACTGCAA | - | qnrS | 417 | 52 | (23) |
| QnrS-R | TAAATTGGCACCCTGTAGGC | |||||
| CITMF | TGG CCA GAA CTG ACA GGC AAA | Amp C | LAT-1TOLAT-4,CYM-2 | 462 | 55 | (25) |
| CITMR | TTT CTC CTG AAC GTG GCT GGC | TO CYM-7, BIL-1 | ||||
| MOXMF | GCT GCT CAA GGA GCA CAG GAT | Amp C | MOX1,2 | 520 | 55 | (25) |
| MOXMR | CAC ATT GAC ATA GGT GTG GTG C | CYM1, 8 to 11 | ||||
| DHAMF | AAC TTT CAC AGG TGT GCT GGG T | Amp C | DHA1,2 | 405 | 55 | (25) |
| DHAMR | CCG TAC GCA TAC TGG CTT TGC | |||||
| FOXMF | AACATGGGGTATCAGGGAGATG | Amp C | FOX-1 TO FOX-5b | 190 | 55 | (25) |
| FOXMR | CAAAGCGCGTAACCGGATTGG | |||||
| sdiA-for | AATATCGCTTCGTACCAC | - | sdiA | 274 | 53 | (26) |
Biofilm formation.
Biofilm formation was inspected phenotypically by microplate assay. Briefly, 230 μl of fresh Tryptic soy broth (TSB) (Merck, Germany) was poured into each well of a polystyrene plate in triplicate. Non-cultured media was used for negative control. 20 μl of the freshly cultured bacteria was added to each of the wells and incubated overnight at 37°C. The wells were washed three times using 300 μl of PBS. Then, 250 μl of methanol was added to each well and kept for 15 minutes at ambient temperature for air-drying. Next, wells were incubated with 250 μl of crystal violet 2% for 5 minutes (24).
The content of plates was removed and rinsed three times with distilled water and further air-dried. Following the addition of 250 μl of acetic acid 33% to each well, the absorbance of supernatants was measured at 570 nm (23, 24).
The ODt, which represents the mean OD of the three wells for each isolates, and the ODc, which represents the mean OD of the three wells for the control, were recorded. Biofilm formation levels were classified based on the OD as follows (27).
ODt < ODc Non-biofilm
ODc < ODt < 2× ODc Weak biofilm
2× ODc < ODt < 4×ODc Moderate biofilm
ODt ≥ 4×ODc Strong biofilm
The genotype of the bacteria for biofilm production was assessed by the PCR using two sdi primers to explore the presence of the SDI gene (Table 2).
Statistical analysis.
The data were analyzed using SPSS software (version 22.0; Chicago, Illinois, USA). Consensus tables and chi-square tests have been used to investigate the correlation. The P-values <0.05 were considered statistically significant.
Ethical consideration.
Chickens were not manipulated for sampling. Samples were collected from yards as a random surveillance program done by the National Veterinary Reference Laboratory.
RESULTS
Differentiation of Salmonella entrica biovar Gallinarum from Pullorum.
As shown in Fig. 1, ratA and stepB were used to differentiate between S. Gallinarum biovars of Gallinarum and Pullorum according to PCR. S. Gallinarum produces 1047 bp band; however, S. Pullorum produces 243 bp band for ratA gene (Fig.1A). Moreover, S. Gallinarum produces 402 bp for steB gene and 636 bp for the rhs gene; however, in S. Pullorum, only 402 bp fragments for the step B gene were amplified using the respective primers shown in Fig. 1B. The present study showed that all 60 S. Gallinarum isolates were S. Gallinarum biovar.
Fig. 1.
- A: Amplification of ratA gene for S. Gallinarum biovars as 1047 bp band for S. Gallinarum and 243 for S. Pullorum: lane 1, standard strain 2, 3, are isolated S. Gallinrum, lanes 4, 5, 6; three standard S. Pullorum and number 7 is negative control with no DNA template
- B: Amplification of steB and rhs genes as 636 bp and 402 bp bands, respectively for detection and confirmation of S. Gallinarum. Lane number 1 is standard S. Gallinarum, 2, 3 are the isolated ones. The lanes 4, 5, 6 are three standard S. Pullorum, that only rhs gene is amplified and the lane number 7 is a negative control.
Antimicrobial resistance.
Antimicrobial resistance genes Amplification in S. Gallinarum and the presence of resistance genes are shown in Fig. 2. The Distribution of resistance genes in 60 isolated S. Gallinarum from different provinces of Iran is shown in Fig. 3.
Fig. 2.
Result of detection of resistance genes using Multiplex PCR. From the left: M: marker 100 bp, lane 1; GES gene (591 bp) and IMP (232 bp), lane 2; Ges gene (591 bp) and VIM (389 bp), lanes 4, 9, 13 (T0) are negative control, lanes 6 and 7 are related with SHV (896 bp) and blaOXA48 (438 bp), lane 8; blaOXA48 (438 bp), lanes 10 and 11; show the qnrA (516 bp), lane 12; products with size 568 bp, 264 bp and 516 bp are related with marR, parC and gyrA genes, respectively. lanes 14, 18 and 19; show the band 798 bp of KPC, lane 15; corresponds with FOX (1184 bp), qnrB (469 bp) and lanes 16 and 17; show the qnrB (469 bp).
Fig. 3.
Distribution of resistance genes in 60 isolated S. Gallinarum from different provinces of Iran. (A) distribution of resistance genes in collected samples. (B) distribution of resistance genes based on the samples collected from each province.
Antibacterial susceptibility assay.
In our study, the pattern of susceptibility to selected antibiotics for the collected S. Gallinarum strains is as follows: penicillin (100%), nitrofurantoin (80%), and amoxicillin (75%), amoxicillin+clavulanic acid (50%), nalidixic acid (45%), neomycin sulfate (30%), chloramphenicol (20%), and ciprofloxacin (5%). On the contrary, all bacteria were susceptible to imipenem, ertapenem, ceftriaxone, ceftazidime, and ceftazidime+ clavulanic acid (Table 3).
Table 3.
Antimicrobial resistance frequency of S. Gallinarum against different classes of antibiotics (different shadings).
| Antibiotic name | Susceptible N (%) | Intermediate N (%) | Resistant N (%) | |
|---|---|---|---|---|
| B-lactamse | Penicilin 10 μg (P10C) | 0 | 0 | 60 (100) |
| Amoxicilin 25 μg (A25c) | 12 (20) | 3 (5) | 45 (75) | |
| Amoxicilin 20 μg+ Clavulanic acid 10 μg (Aug) | 30 (50) | 0 | 30 (50) | |
| Ceftazidime 30 μg (CAZ30c) | 60 (100) | 0 | 0 | |
| Ceftazidime 30 μg+ Clavulanic acid (CAZ+Clave) | 60 (100) | 0 | 0 | |
| Ceftriaxone 30 μg (CRO 30c) | 60 (100) | 0 | 0 | |
| Cefepime 30 μg (CPM30c) | 51 (85) | 9 (15) | 0 | |
| Carbapenemase | Imipenem 10 μg (IMI10c) | 60 (100) | 0 | 0 |
| Ertapenem 10 μg (ETP10c) | 60 (100) | 0 | 0 | |
| Nitrofurantoein 50 μg (FM50) | 6 (10) | 6 (10) | 48 (80) | |
| Quinolones | Nalidxic acid 30 μg (NA30c) | 27 (45) | 6 (10) | 27 (45) |
| Ciprofloxacin 5 μg (CIP 5c) | 6 (10) | 51 (85) | 3 (5) | |
| Chloramphenicol 30 μg (C30c) | 27 (45) | 21 (35) | 12 (20) | |
| Aminoglycoside | Neomycin sulphate 10 μg (KF30c) | 33 (55) | 9 (15) | 18 (30) |
| Kanamycin 30 μg (K30c) | 51 (85) | 9 (15) | 0 | |
| Trimethoprim 1.25 μg+ Sulfametoxazole 23.7 μg (TS 25c) | 54 (90) | 6 (10) | 0 | |
| Colistin sulphate 10 μg (CO 10c) | 48 (80) | 12 (20) | 0 |
As shown in Table 4, the resistant phenotype (+ve) was observed in 12 of 17 antibiotics tested. For cefepime, kanamycin, trimerhoprime, sulfamethoxazole, and colistin sulfate antibiotics, only intermediate resistance was observed. 85% of S. Gallinarum isolates showed intermediate resistance for ciprofloxacin, and only 5% were highly resistant.
Table 4.
Multi drug resistance patterns of the 60 isolated S. Gallinarum between 2012–2017.
| Antibiotic resistance Patterns | Antibiotics categories | MDR | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
| ||||||||||
| ß-lactamase inhibitors | Aminoglycosides | Fluoroquinolones | Polymyxins | Antimetabolite (nitrofuran) | Quinolone | Chloramphenicol | ||||
|
| ||||||||||
| Penicillin | Amoxicillin | Cefoxitin | Neomycin | Ciprofloxacin | Colistin | Nitrofurantoin | Nalidixic acid | Chloramphenicol | ||
| 1 | R | − | ||||||||
| 2 | R | R | − | |||||||
| 3 | R | R | R | + | ||||||
| 4 | R | R | + | |||||||
| 5 | R | R | R | R | − | |||||
| 6 | R | R | R | + | ||||||
| 7 | R | R | R | R | R | + | ||||
| 8 | R | R | R | R | R | R | + | |||
| 9 | R | R | R | R | + | |||||
| 10 | R | R | R | R | + | |||||
| 11 | R | R | R | R | R | R | + | |||
| 12 | R | R | R | R | R | R | + | |||
| 13 | R | R | R | R | R | R | R | + | ||
| 14 | R | R | R | R | R | R | R | + | ||
*Resistance
In this study, all isolates were susceptible to imipenem, ertapenem, and extended-spectrum of cephalosporins, 3rd, and 4th generation cephalosporins, including ceftriaxone, ceftazidime, and ceftazidime+clavulanic acid, except cefepime which showed intermediate resistance in 15% of the isolates.
The rate of multidrug resistance is presented in Table 4. Twenty-four S. Gallinarum serovars were resistant to less than two classes of antibiotics (pattern 1, 2, 5); however, most of the biovars 36/60 (60%) were multidrug-resistant (MDR), in 7 categories, with different patterns as presented in Table 4.
Statistical analysis.
Results showed that all 60 S. Gallinarum isolates produced biofilm according to amplification of the sdiA gene. As shown in Table 5, biofilm formation were reported as strong (n=21 isolates or 35%), intermediate (n=24 or 40%), weak (n=15 or 25%). The results showed that the isolates with higher biofilm production are more antibiotic-resistant than weak biofilm producers in a planktonic form (shaded area). Moreover, a positive correlation is shown between some resistance genes such as FOX M, GES, Fox, KPC, and qnrB and the severity of biofilm formation. However, no correlations were found for the SHV gene, blaOXA48, MOXM (Ampc), and CITM (AmpC).
Table 5.
Correlation between the strength of biofilm formation and the presence of antibiotic resistance genes in 60 Salmonella SPP.
| Antibiotic resistance gene | Number of Isolates (%) | Strong Biofilm Formation (%) | Weak and moderate Biofilm Formation (%) | P-value |
|---|---|---|---|---|
| GES gene (bla) | 51 (85) | 15 (29.4) | 36 (70.6) | 0.054 |
| Positive | 9 (15) | 6 (66.7) | 3 (33.3) | |
| Negative | ||||
| Fox gene (bla) | 6 (10) | 6 (100) | 0 (0) | 0.001 |
| Positive | 54 (90) | 15 (27.8) | 39 (72.2) | |
| Negative | ||||
| Kpc gene (bla) | 9 (15) | 69 (66.7) | 3 (33.3) | 0.054 |
| Positive | 51 (85) | 15 (29.4) | 36 (70.6) | |
| Negative | ||||
| FoxM (Ampc) | 42 (70) | 9 (21.4) | 33 (78.6) | 0.001 |
| Positive | 18 (30) | 12 (66.7) | 6 (33.3) | |
| Negative | ||||
| qnrB | 45 (75) | 12 (26.7) | 33 (73.3) | 0.022 |
| Positive | 15 (25) | 9 (60) | 6 (40) | |
| Negative | ||||
| qnrS | 36 (60) | 12 (33.3) | 24 (66.7) | 0.039 |
| Positive | 24 (40) | 9 (37.5) | 15 (62.5) | |
| Negative | ||||
| SHV gene | 36 (60) | 12 (33.3) | 24 (66.7) | 0.476 |
| Positive | 24 (40) | 9 (37.5) | 15 (62.5) | |
| Negative | ||||
| blaOXA48 Positive | 36 (60) | 12 (33.3) | 24 (66.7) | 0.476 |
| Negative | 24 (40) | 9 (37.5) | 15 (62.5) | |
| MOXM (Ampc) | 57 (95) | 21 (36.8) | 36 (63.2) | |
| Positive | 3 (5) | 0 (0) | 3 (100) | 0.545 |
| Negative | ||||
| CITM (AmpC) | 12 (20) | 6 (50) | 6 (50) | 0.312 |
| Positive | 48 (80) | 15 (31.2) | 33 (68.8) | |
| Negative |
DISCUSSION
Monitoring for Salmonella infections is vital to the poultry industry. They are responsible for economic losses by harming the industry worldwide. In addition, they are a source of diseases transmitted to humans through diet and the environment. For economic and pathogenetic reasons, detection of S. Gallinarum in older birds and S. Pollurum in chickens is crucial (13). In this study, 60 isolates of S. Gallinarum were confirmed by biochemical test. PCR-based detection of Salmonella biovars is sensitive, easy, and rapid (28, 29). Up to now, Xiong et al. have detected several genes; they have amplified ratA (ROD) gene that shows a deletion in biovar Pullorum compared with Gallinarum. They showed that the combined amplification of stn, I137_08605, and ratA ROD could be 100% specific for each biovar (30, 31). In our study, the ratA that is common between two biovars showed different sizes; however, the rhs and SteB genes were used for biovar classification. All 60 S. Gallinarum were identified as Gallinarum; therefore, the following results of our study are beneficial to the industry of mature or growing chickens, ducks, and turkeys of farms in Iran.
To confirm the identification of S. Gallinarum biovars, Paiva et al. employed the RFLP-based amplification of the Flic gene of flagellar antigen and digestion with a restriction enzyme (Hinp1l) followed by running on the agarose gel. The technique is a two-step process that is expensive and time-consuming compared to standard PCR (32).
All Salmonella strains were S. Gallinarum. S. Pullorum was not detected; the reason could be related to the community of collected samples, i.e., adult farm chickens, and not the young ones, which are more susceptible to S. Pullorum.
A variety of bacteria is present in the gastrointestinal tract of poultry, such as Enterobacteriaceae, that exchange the genetic materials, including resistance genes (21, 33).
Inappropriate antibiotic use in poultry has led to the emergence of resistant bacteria and horizontal resistant gene transfer to environmental and transient Salmonella (34).
Studies have shown that the GES and KPC genes are detected in Klebsiella, with the respective prevalence of 11% and 23% (35). However, our results showed the respective prevalence of 15% and 85% for KPC and GES genes. Moreover, the S. Gallinarum with KPC resistance gene does not contain GES and vice versa, which has not been reported up to now.
The existence of a variety of β-lactam genes such as KPC, SHV, GES, Fox, qnrB, and qnrS in S. Gallinarum, could be a significant warning due to their transmissibility to other bacteria of the ecosystem, arising a dilemma in the treatment of pathogenic bacteria in the poultry industry which would finally contaminate human (36–38).
Our result on the origin of resistance contrasts with the study conducted in Brazil from 2006 to 2013. They found no PMQR gene in 17 isolates of S. Gallinarum or S. Pullorum isolates. However, they reported resistance to quinolones (nalidixic acid) and fluoroquinolones (ciprofloxacin) (39).
The high prevalence of multidrug-resistant Salmonella in poultry may increase the rate of MDR Salmonella in humans (40). In our study, all the isolates were susceptible to imipenem, ertapenem, ceftriaxone, ceftazidime, and ceftazidime + clavulanic acid supported by the previous studies conducted in Vietnam (41). To the best of our knowledge, the fluoroquinolones and third-generation of cephalosporins are relatively effective for the treatment of salmonellosis (22), though in recent years, the resistance to routine antibiotics has increased (41). The absence of resistance against cephalosporins antibiotics in the present study possibly shows restricted use in poultry (41, 42). As mentioned above, 45 (75%) of our isolates were resistant to amoxicillin, and 30 (50%) of the isolates were resistant to amoxicillin-clavulanic acid, which is an indicator of the presence of ESBLs genes in the isolates. Moreover, the results are warning for the possible increase in the prevalence of ESBLs genes in human populations. The previous studies have also shown an increase in resistance for S. Pullorum/Gallinarum over time (12). In contrast to our study, Ramya et al. showed that the susceptibility of Salmonella spp. for ciprofloxacin and amoxicillin were 100% and 82%, respectively (43). Furthermore, studies in geographical areas such as Bangladesh have also shown approximately 50% resistance to five antibiotics among 16 Salmonella spps. isolates in 2016 (44). Results from another study in Bangladesh from 2021 showed an increase in the frequency of antibiotic resistance: This study reports high levels of resistance to penicillin and nalidixic acid, sulfometaxazole trimethoprim , ampicillin and amoxicillin (45).
A total of 130 S. Gallinarum isolates from chickens were collected in a study conducted in Korea from 2014 to 2018. In general, these isolates showed higher resistance to nalidixic acid, gentamicin, ciprofloxacin and ampicillin (46). The antimicrobial susceptibility profiles of Salmonella isolated from poultry in Pakistan were as follows: highest resistance to nalidixic acid, ampicillin, amoxicillin, moderate resistanceto gentamicin, chloramphenicol, tetracycline, ciprofloxacin, ceftazidime and low resistance to cefotaxime, ceftriaxone, sulfamethoxazole and cefixime (45). Studies of resistance gene in S. Gallinarum in India in 2016 have shown that the 25.6% are resistant to ciprofloxacin 81.81% to amoxicillin, doxycycline, kanamycin, gentamycin, and tetracycline (44).
In many countries, control and prevention programs to eradicate salmonellosis are ineffective due to the use of antibiotics as growth factors in poultry (47). In the present study, the high antibiotic resistance could result from the same process and lead to a disastrous outcome.
The production of bacterial biofilms enhances the ability of bacteria to endure harsh environmental conditions and sanitation procedures (48). Therefore, the prevalence of biofilm formation and the level of biofilm production are essential parameters for biofilm eradication (13, 16). The biofilm formation was studied using both molecular and phenotypic techniques in the present study. This study confirmed the variable biofilm formation; however, a relation was found between biofilm formation and antibiotic resistance. Our results also showed that biofilm formation is significantly related to the prevalence of antibiotic resistance genes for Fox, GES, KPC, qnrB, and FOXM (P<0.05) and could be considered a factor that increases the virulence of S. Gallinarum.
The present study is the first study on S. Gallinarum biofilm in Iran focusing on the characterization of S. Gallinarum biovar and their acquired antibiotic resistance genes circulating in poultry farms in central and northwestern of Iran. Furthermore, our results demonstrated the association between biofilm production ability and resistance to commonly administered antibiotics.
CONCLUSION
Considering that the presence of this bacteria is equal to the death penalty to the herd, the distribution of resistance genes could be a critical alarm for pathogen monitoring programs in the region. This study showed a positive correlation between biofilm formation and 50% of tested resistance genes. Also, it was found that the most common circulating S. Gallinarum biovars are multidrug-resistant.
ACKNOWLEDGEMENTS
The authors wish to express their deep gratitude to all who provided support during the course. This is from a PhD student project and the authors received no specific funding for this work.
Authors’ contributions: PE conceived and designed the study. RKF performed experiments and writing the manuscript. MER and NS checking data analysis. AHKF data analysis. SAG validation and visualization, MR data curation, writing –review and editing. SG data analysis, AGL validation and visualization. All co-authors discussed the results and contributed to the critical revision of the final manuscript.
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