Prevalence, Genetic Heterogeneity, and Antibiotic Resistance Profile of<i> Listeria</i> spp. and<i> Listeria monocytogenes</i> at Farm Level: A Highlight of ERIC- and BOX-PCR to Reveal Genetic Diversity

Maurice Bilung, Lesley; Sin Chai, Lai; Tahar, Ahmad Syatir; Ted, Chong Kian; Apun, Kasing

doi:https://doi.org/10.1155/2018/3067494

BioMed Research International

On this page

Abstract Introduction Materials and Methods Results Discussion Conclusion Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments References Copyright Related Articles

Special Issue

Food Microbiology

View this Special Issue

Research Article | Open Access

Volume 2018 | Article ID 3067494 | https://doi.org/10.1155/2018/3067494

Prevalence, Genetic Heterogeneity, and Antibiotic Resistance Profile of Listeria spp. and Listeria monocytogenes at Farm Level: A Highlight of ERIC- and BOX-PCR to Reveal Genetic Diversity

Lesley Maurice Bilung,¹Lai Sin Chai,¹Ahmad Syatir Tahar,¹Chong Kian Ted,²and Kasing Apun¹

Academic Editor: Marta Laranjo

Received16 Mar 2018

Revised02 May 2018

Accepted03 Jun 2018

Published03 Jul 2018

Abstract

This study aimed to identify Listeria spp. and L. monocytogenes, characterize the isolates, and determine the antibiotic resistance profiles of the isolates Listeria spp. and L. monocytogenes in fresh produce, fertilizer, and environmental samples from vegetable farms (organic and conventional farms). A total of 386 samples (vegetables, soil, water, and fertilizer with manure) were examined. The identification of bacterial isolates was performed using PCR and characterized using ERIC-PCR and BOX-PCR. The discriminating power of the typing method was analyzed using Simpson’s Index of Diversity. Thirty-four (n=34) Listeria isolates were subjected to antimicrobial susceptibility test using the disc-diffusion technique. The PCR analysis revealed that Listeria spp. were present in 7.51% (29/386) of all the samples (vegetable, soil, fertilizer, and water). None of the samples examined were positive for the presence of L. monocytogenes. Percentages of 100% (15/15) and 73.30% (11/15) of the Listeria spp. isolated from vegetables, fertilizer, and soil from organic farm B had indistinguishable DNA fingerprints by using ERIC-PCR and BOX-PCR, respectively. Listeria spp. isolated from 86 samples of vegetable, fertilizer, and environment of organic farm A and conventional farm C had distinct DNA fingerprints. Simpson’s Index of Diversity, D, of ERIC-PCR and BOX-PCR is 0.604 and 0.888, respectively. Antibiotic susceptibility test revealed that most of the Listeria spp. in this study were found to be resistant to ampicillin, rifampin, penicillin G, tetracycline, clindamycin, cephalothin, and ceftriaxone. The isolates had MAR index ranging between 0.31 and 0.85. In conclusion, hygienic measures at farm level are crucial to the reduction of Listeria transmission along the food chain.

1. Introduction

Listeria is a gram-positive, rod-shaped, and non-spore-forming bacterium [1]. Genus of Listeria is classified into 17 species including Listeria monocytogenes that is a common causative agent of human foodborne infection, listeriosis [2]. Listeriosis is usually treated with antibiotic therapy involving the use of penicillin, ampicillin, rifampin, gentamicin, tetracycline, erythromycin, chloramphenicol, or trimethoprim with sulfamethoxazole alone or in combination [3, 4]. Previous researches have shown that Listeria spp. may be resistant to several antibiotics such as clindamycin, daptomycin, oxacillin, tetracycline, and nalidixic acid [5, 6]. Therefore, it is important to monitor the antibiotic susceptibility of Listeria spp. and L. monocytogenes to ensure the effectiveness of listeriosis treatment.

Repetitive sequence-based PCR (Rep-PCR) is a DNA amplification technique for bacterial genomic fingerprinting by using repetitive DNA elements present within bacterial genome. There are four main types of repetitive sequences used for molecular typing which include enterobacterial repetitive intergenic consensus (ERIC) sequence, BOX elements, repetitive extragenic palindromic sequences (REP elements), and (GTG)₅ [7]. Utilization interspersed repetitive sequence-based tools can be used in bacterial fingerprinting since the distance between each of the sequences varies among strains [8] and have been used to type wide range of gram-negative and several gram-positive bacteria [7]. ERIC-PCR has been used for intraspecies fingerprinting of Bacillus anthracis and Bacillus cereus [9], Enterobacter sakazakii [10], Lactobacillus [11], Listeria monocytogenes [12], and Salmonella Enteritidis [13, 14]. Meanwhile, BOX-PCR has been well used in typing of Escherichia coli [15–17], Bifidobacterium [7], Streptomyces [18], Aeromonas spp. [19], Burkholderia pseudomallei [20], and Bacillus anthracis [21]. Nonetheless, ERIC sequence-based PCR (ERIC-PCR) and BOX-PCR were used in this study as they are rapid subtyping methods and have high discrimination power [2, 22, 23].

According to Strawn et al. [24], agricultural practices (irrigation with contaminated water, fertilization with contaminated manure and contaminated soil) could increase the risk of bacterial contamination of vegetables. Therefore, this study was carried out to assess the contamination levels of Listeria spp. and L. monocytogenes in vegetables, fertilizer, and environmental samples (soil and water) at farm level practicing organic and conventional farming in Sarawak, to obtain information on the genetic diversity of the Listeria spp. isolates using Repetitive Intergenic Consensus Polymerase Chain Reaction (ERIC-PCR) and BOX-PCR. Further, the study aimed to compare the effectiveness of ERIC-PCR and BOX-PCR for genetic diversity of Listeria spp. and determine antibiotic resistance profiles of the Listeria spp. isolates.

2. Materials and Methods

2.1. Sampling Sites and Sample Collection

A total of 206 vegetable samples, 60 fertilizer samples, 60 soil samples, and 60 water samples were collected from two organic farms (organic farm A and organic farm B) and one conventional farm (conventional farm C) in Kuching, Sarawak. As shown in Table 1, the organic farms practice crop rotations, application of composted chicken waste and plant waste as fertilizer, mechanical methods to control weeds, and restricted use of pesticides. The conventional farm also practices the use of composted animal manures and plant waste as fertilizer; however, it does not practice crop rotation and synthetic chemical pesticides are applied to the produce biweekly.

The vegetable samples and soil samples were collected from the fields while the fertilizer samples were collected from the fertilizer storage places. Water samples were collected from the respective water sources (pond or rainwater). All samples were kept in ice box and transported to the Molecular Microbiology Laboratory at Universiti Malaysia Sarawak.

2.2. Sample Processing and Listeria Enrichment

Sample processing was done as described in Ozbey et al. [25]. First, 25 g (or 25 ml) of each sample (soil, fertilizer, and water) was weighed or measured and then transferred into conical flasks containing 225 ml of Listeria Enrichment Broth (LEB) (Oxoid, United States). After that, the flasks were incubated at 30°C for 48 hr. Vegetable samples were weighed (25 g) and cut into pieces before being transferred into the conical flasks containing 225 ml of LEB followed by incubation at 30°C for 48 hr.

2.3. Enumeration of Listeria spp.

The enriched bacterial cultures (100 μl) from the samples were transferred and spread on PALCAM agar (Merck, Germany). The PALCAM agar plates were incubated at 37°C for 48 hr. Listeria spp. colonies appeared to be greyish-green or black in color and surrounded by black halo on PALCAM agar [26]. These colonies were observed, counted, and recorded.

2.4. DNA Extraction

Prior to amplification, genomic DNA was extracted using GF-1 Nucleic Acid Extraction Kits (Vivantis, United States) according to manufacturer’s guide. DNA template was further subjected to PCR-based analysis.

2.5. Identification of Listeria spp. and Listeria monocytogenes

2.5.1. DNA Extraction

Presumptive Listeria spp. colonies were selected from PALCAM agar and subjected to DNA extraction using GF-1 Nucleic Acid Extraction Kits (Vivantis, United States) according to the manufacturer’s guide. DNA template was further subjected to PCR-based analysis.

2.5.2. Polymerase Chain Reaction (PCR) for Listeria spp.

PCR detection of Listeria spp. was carried out as described by Jeyaletchumi et al. [27] and Wong et al. [28] with slight modification in the concentration of reagents. The primer pairs used for the detection of Listeria spp. (genus specific) were 5′-CTC CAT AAA GGT GAT CCT-3′ and 5′-CAG CAG CCG CGG TAA TAC-3′. These primers were designed to amplify a 938 bp region in the 16S rRNA gene. To prepare 25 μl of PCR mixture, 0.2 M of forward primer, 0.2 M of reverse primer, 5.5 μl of DNA template, 1.5 μl of 10× Taq PCR buffer, 0.2 μl dNTP, 1.5 mM MgCl₂, and 1.5 unit of Taq DNA polymerase were mixed together. Lastly, the PCR products were separated on 1% agarose gel with 100 kb DNA ladder for 75 min, stained with ethidium bromide, and viewed under a UV transilluminator (Maestrogen, Taiwan).

2.5.3. Polymerase Chain Reaction (PCR) for Listeria monocytogenes

PCR detection of L. monocytogenes was carried out as described by Awaisheh [29] with a modification in the concentration of reagents. The primer pairs used for the detection of L. monocytogenes were 5′-CAT TAG TGG AAA GAT GGA ATG-3′ and 5′-GTA TCC TCC AGA GTG ATC GA-3′ which amplify 730 bp region of the listeriolysin (hlyA) gene. To prepare 25 μl of PCR mixture, 0.4 M of hlyA forward primer, 0.4 M of hlyA reverse primer, 5 μl of DNA template, 2.5 μl of 10× Taq PCR buffer, 0.2 mM dNTP, 0.8 mM MgCl₂, and 2.5 units of Taq DNA polymerase were mixed together. Lastly, the PCR products were separated on 1% agarose gel with 100 kb DNA ladder for 75 min. The gel was stained with ethidium bromide and viewed under a UV transilluminator (Maestrogen, Taiwan).

2.6. Genetic Diversity Analysis Using ERIC and BOX-PCR

The ERIC-PCR condition for this method was in accordance with Indrawattana et al. [30] and Laciar et al. [31]. Meanwhile, the BOX-PCR condition followed Jamali and Thong [32] and Versalovic et al. [8] with slight modifications on the reagent concentration and reaction condition. In ERIC-PCR, the primer pairs used were 5′-ATGTAAGCTCCTGGGGATTCAC-3′ and 5′-AAGTAAGTGACTGGGGTGAGCG-3′. To prepare 25 μl of PCR mixture, 1.0 M of forward primer, 1.0 M of reverse primer, 3.0 l of DNA template, 5.0 μl of 5×Taq PCR buffer, 0.2 mM dNTP, 2.0 mM MgCl₂, and 1.0 unit of Taq DNA polymerase were mixed together. The PCR reaction was carried out according to the condition in Table 2. In BOX-PCR, the primer used was BOX A1R (5′-CTACGG CAA GGC GAC GCT GAC G-3′). To prepare 25 μl of PCR mixture, 400 μM of each dNTPs, 1×PCR buffer, 3 mM MgCl₂, 4 μM of primer, and 2.5 U Taq DNA polymerase (Promega) were mixed together. The PCR reaction was carried out according to the condition in Table 3.

The PCR products from ERIC- and BOX-PCR were separated in 2% agarose gel with 100 kb DNA ladder for 90 min. Then, the gel was stained with ethidium bromide and viewed under a UV transilluminator (Maestrogen, Taiwan). The DNA band patterns were analyzed and a dendrogram was generated for the Listeria isolates by using BioNumerics 7.5 software program (Applied Maths, Sint-Martens-Latem, Belgium) using Dice coefficient and the unweighted pair group method (UPGMA) [33]. Simpson’s Index of Diversity, D, was also calculated.

The discriminating power of this typing method was calculated by using Simpson’s Index of Diversity, D [34]. The higher the discriminatory index, the greater the effectiveness of a particular fingerprinting method to discriminate different strains [35]. This index was given by the following equation:

“N” denotes the total number of strains in the sample population, “s” denotes the total number of types described, “n_j” denotes the number of strains belonging to the jth type.

2.7. Antibiotic Susceptibility Test

Antibiotic susceptibility of isolated Listeria spp. was carried out with the disc-diffusion method by Chen et al. [5] and Morobe et al. [36] with a slight modification. The antibiotic discs (Oxoid, the United States) used were ampicillin (10 μg), cephalothin (30 μg), chloramphenicol (30 μg), clindamycin (2 μg), erythromycin (15 μg), gentamycin (10 μg), penicillin G (10 μg), rifampin (5 μg), streptomycin (10 μg), tetracycline (30 μg), sulfamethoxazole/trimethoprim (23.75 μg/1.25 μg), novobiocin (30 μg), nitrofurantoin (10 μg), and ceftriaxone. First, the overnight culture grown in Mueller-Hinton broth was spread uniformly onto the Mueller-Hinton agar plate. Antibiotic discs were then placed onto the surface of each plate (4 antibiotics/Petri dish) using antibiotic-disc dispenser (Oxoid, United States). After incubation at 37°C for 24 hr, the diameter of growth inhibition zone surrounding each disc was measured and interpreted according to the CLSI (Clinical and Laboratory Standards Institute) 2014 recommendation. Evaluation of the Listeria as resistant, susceptible, and intermediate toward the antibiotics was conducted by referring to the Zone Diameter Interpretive Criteria (nearest whole mm) of a particular antibiotic of CLSI. The CLSI criteria for staphylococci were referred to in this study because interpretative criteria for Listeria are not available from CLSI with the exception of susceptibility breakpoints for ampicillin and penicillin. Multiple antibiotic resistance (MAR) index of an isolate was calculated as defined by Krumperman [37]:

“a” denotes number of antibiotics to which the particular isolate was resistant and “b” denotes number of antibiotics to which the particular isolate was exposed.

3. Results

3.1. Prevalence of Listeria spp. Based on PCR Analysis

Analysis using PCR assay revealed that Listeria spp. were present in 7.51% (29/386) of all the samples (vegetable, soil, fertilizer, and water) collected. It was present in 9.10% (6/66), 8.13% (13/160), and 6.25% (10/160) of the samples collected from organic farm A, organic farm B, and conventional farm C, respectively. The prevalence of Listeria spp. from all the samples was shown in Table 4. The gel picture for PCR amplification of 16S rRNA gene of Listeria spp. was shown in Figure 1.

3.2. Enumeration of Listeria spp. in the Vegetables, Soil, Water, and Fertilizer

The standard plate count (in CFU/g) of Listeria spp. in all the samples is also shown in Table 2. Listeria spp. were present in 6.70% (2/30) and 8.00% (7/88) of vegetable samples from organic farm A and organic farm B, respectively. Vegetable samples from organic farm B had the highest prevalence of Listeria spp. among the three farms, while soil samples from organic farm A have the highest prevalence of Listeria spp. Listeria spp. were not present in vegetables and soil samples from conventional farm C. For fertilizer samples, organic farms A and B had the highest prevalence of Listeria spp. among the three farms. For water samples, Listeria spp. were only present in 33.30% (8/24) of water samples from conventional farm C.

3.3. Prevalence of Listeria monocytogenes Based on PCR Analysis

PCR detection of L. monocytogenes in the samples was carried out by using primer pairs which amplified 730 bp region of the listeriolysin (hlyA) gene. However, L. monocytogenes was absent in all the samples analyzed.

3.4. Genetic Diversity of Listeria Isolates Using ERIC-PCR

The electrophoretic profile of DNA fragments obtained after ERIC-PCR amplification yielded 1-5 bands with size approximately 120 bp to 1450 bp. A common band with molecular size of approximately 520 bp was observed in the electrophoretic profile from most of the isolates. Based on the ERIC-PCR dendrogram shown in Figure 2, the Listeria spp. isolated from organic farm A, organic farm B, and conventional farm C were genetically diverse and heterogeneous as they were not classified into specific cluster by either sampling area or the type of samples. ERIC-PCR analysis produced 11 different DNA fingerprint profiles. Simpson’s Index of Diversity, D, was calculated for ERIC-PCR based on Hunter and Gaston [34]. The D value of this technique was calculated to be 0.604.

Figure 2

Dendrogram constructed for ERIC-PCR of Listeria spp. in vegetable, fertilizer, and environmental samples collected from organic farm A, organic farm B, and conventional farm. “A” denotes organic farm A, “B” denotes organic farm B, “C” denotes organic farm C, “(a)” denotes Listeria spp. isolated from vegetables, soil, fertilizer, and water from organic farm A, organic farm B, and conventional farm C, “(b)” denotes Listeria spp. isolated from soil and water from organic farm A and conventional farm C, “(c)” denotes Listeria spp. isolated from vegetable and water from organic farm B and conventional farm C, and “(d)” denotes Listeria spp. isolated from soil from organic farm A.

3.5. Genetic Diversity of Listeria Isolates Using BOX-PCR

The electrophoretic band pattern of BOX-PCR amplification yielded 2-13 bands with size approximately 120 bp to 1550 bp. Based on the BOX-PCR dendrogram shown in Figure 3, Listeria spp. isolated from all the three farms were not classified according to the types of sample or sampling area. Therefore, these Listeria spp. isolates were genetically diverse and heterogeneous. BOX-PCR analysis produced 14 different fingerprint profiles. Simpson’s Index of Diversity, D, was calculated for BOX-PCR based on Hunter and Gaston [34]. The D value of this technique was calculated to be 0.888.

Figure 3

Dendrogram constructed for BOX-PCR of Listeria spp. in vegetable, fertilizer, and environmental samples collected from organic farm A, organic farm B, and conventional farm C. “A” denotes organic farm A, “B” denotes organic farm B, “C” denotes organic farm C, “(a)” denotes Listeria spp. isolated from vegetables, soil, and fertilizer from organic farm A and organic farm B, “(b)” denotes Listeria spp. isolated from vegetable, soil, and water from organic farm A and conventional farm C, “(c)” denotes Listeria spp. isolated from vegetables, fertilizer, and water from organic farm A, organic farm B, and conventional farm C, and “(d)” denotes Listeria spp. isolated from water from conventional farm C.

3.6. Antibiotic Susceptibility Test

Thirty-four (n=34) Listeria spp. isolated from 29 samples (vegetable, soil, fertilizer, and water) collected from all the three farms were subjected to antibiotic susceptibility testing. Listeria spp. isolates were most resistant to clindamycin 97.06% (33/34) and least resistant to gentamicin 17.65% (6/34).

Listeria spp. were isolated from 11 vegetable samples, 2 (Chinese mustard and cucumber) from organic farm A and 9 (Chinese cabbage, romaine/cos lettuce, and Chinese white cabbage) from organic farm B. Antibiotic resistance graph of vegetable samples from the three farms is shown in Figure 4.

All Listeria spp. isolated from vegetable samples from organic farms A and B were resistant to penicillin G, tetracycline, and clindamycin. For soil samples, Listeria spp. were isolated from 6 soil samples, 4 from organic farm A and 2 from organic farm B. Antibiotic resistance graph of soil samples from the three farms is shown in Figure 5.

In this study, all Listeria spp. isolated from soil samples from organic farms A and B were resistant to clindamycin, cephalothin, and ceftriaxone. Two Listeria spp., 4 Listeria spp., and 2 Listeria spp. were isolated from the fertilizer samples collected from organic farm A, organic farm B, and conventional farm C, respectively. Antibiotic resistance graph of fertilizer samples from the three farms is shown in Figure 6.

The results revealed that all Listeria spp. isolated from fertilizer samples were resistant to clindamycin and ceftriaxone. Conventional farm C was the only farm where the water samples were detected with Listeria spp., with 9 Listeria spp. isolated. Antibiotic resistance graph of water samples from the 3 farms is shown in Figure 5. All (100%) (9/9) of the Listeria spp. were resistant to penicillin G. MAR index defined by Krumperman [37] was evaluated for all the isolates. In this study, Listeria spp. isolates demonstrated MAR; they were resistant to at least four of the thirteen antibiotics tested. The MAR indexes for all the isolates are recorded in Table 5. For vegetable samples, Listeria spp. in Chinese mustard from organic farm A and romaine/cos lettuce from organic farm B had the highest MAR index of 0.85. For soil samples, Listeria spp. from organic farm A had the highest MAR index of 0.69. For fertilizer samples, Listeria spp. from organic farm A had the highest MAR index of 0.85. For water samples, Listeria spp. were isolated only from conventional farm C, and the highest MAR index was 0.77.

4. Discussion

4.1. Prevalence of Listeria spp. from the Vegetables, Soil, Water, and Fertilizer

As shown in Table 4, a total of five vegetables from organic farms A and B had high concentration of Listeria spp. in the vegetables (ranging from 9.50 × 10² to 2.10 × 10⁵ CFU/g). However, none of vegetables from conventional farm C was positive. According to the Public Health England [38], samples consisting of more than 100 CFU/g of Listeria spp. are considered unsatisfactory and investigation is required. Therefore, the vegetable samples collected from organic farms A and B were considered unsatisfactory and this represents the risk of contracting listeriosis associated with fresh produce consumption. Listeria spp. were present in 16.70% (2/12) and 8.30% (2/24) of soil from organic farms A and B. Listeria spp. are widely distributed in the environment including soil, vegetation, surface water, sewage, animal feeds, farm environments, and food-processing environments [39]. According to Vackachan et al. [40], contaminated fertilizer and humidity of the soil may increase the risk of soil contamination. Therefore, measures should be taken for the use of contaminated soil to reduce the presence of the bacteria. The fertilizer used by the three farms in the present study was animal waste compost (chicken litter) and plant waste. Such fertilizers are usually used as they are of low cost, organic, and containing notable amount of nutrients. Normally, composting of animal waste can inactivate large populations of human pathogens but improper composting or cross-contamination results in the high survival rate of these pathogens. Improper composting may also result in the regrowth of the pathogens in the finished compost products under a range of favorable conditions [41]. Listeria spp. were absent in the water samples from organic farms A and B. However, Listeria spp. were detected in 33.30% (8/24) of the water from conventional farm C. According to Galvez et al. [42] and Chitarra et al. [43], pathogenic bacteria such as Salmonella, pathogenic E. coli, and L. monocytogenes can be found in irrigation water for fresh produce. These pathogenic bacteria can internalize crops through the roots and survive in them. This study also revealed no presence of L. monocytogenes in all the samples (vegetable, soil, water, and fertilizer) from all farms which could indicate lower potential of disease burden as the species is commonly causing human infections [2].

4.2. Genetic Heterogeneity of Listeria spp. Based on ERIC- and BOX-PCR Analysis

The findings from both ERIC-PCR and BOX-PCR analysis in the present study showed that the Listeria spp. isolates were not grouped together based on the types of samples and the source of isolation. They were not classified into specific cluster by either sampling area or the type of samples. In the present study, the Listeria spp. isolated from organic farm A, organic farm B, and conventional farm C were genetically diverse and heterogeneous. The heterogeneity was expected as the isolates were collected from different types of sample (vegetable, soil, fertilizer, and water) and sampling locations (organic farm A, organic farm B, and conventional farm C). In this study, Simpson’s Index of Diversity, D, value for ERIC- and BOX-PCR was 0.604 and 0.888, respectively. According to Kqueen et al. [35], the higher the discriminatory index, the greater the effectiveness of a particular fingerprinting method to discriminate different strains. Thus, it was shown that BOX-PCR had greater discriminatory power than ERIC-PCR for fingerprinting Listeria spp. isolates of this study. In comparison, the discriminatory power for both BOX-PCR and ERIC-PCR analysis was lower as compared to the finding by Jersek et al. [44] which revealed ERIC-PCR was suitable for the typing of L. monocytogenes isolates as the index of discrimination was high (0.98). Another study conducted by Jamali and Thong [32] reported that the discrimination indexes for REP-PCR, BOX-PCR, RAPD, and PFGE were 0.992, 0.998, 1, and 0.916, respectively. They suggested that different subtyping methods often give different discriminatory powers. Therefore, it is necessary to use more than one subtyping approach to provide a more accurate description of the genetic diversity of microorganisms in the study. On the other hand, other fingerprinting tools such as REP-PCR and (GTG)₅ are well employed in bacterial typing [8] which can be tested in further study.

4.3. Antibiotic Susceptibility of the Listeria Isolates

This present study revealed that 97.06% (33/34) of Listeria spp. isolated from vegetables, soil, fertilizer, and water from organic farm A, organic farm B, and conventional farm C were resistant to clindamycin. Chen et al. [5] found that all Listeria spp. isolates in catfish fillets and processing environment were resistant to clindamycin. Gamboa-Marin et al. [45] also revealed that L. monocytogenes, Listeria spp., and L. ivanovii from swine processing facilities in Colombia had major resistance and intermediate susceptibility to clindamycin. In the present study, Listeria spp. from the three farms showed the lowest resistance against gentamicin. This is comparable to a study by Li et al. [46] which revealed gentamicin exhibited good activity against Listeria spp. from processed bison in the USA.

This study showed that all the Listeria spp. isolates were resistant to more than one antibiotic and therefore demonstrated MAR. According to Krumperman [37], MAR index value lower than 0.20 indicates that the organism originated from a lower risk source in which the antibiotics are seldom or never used. MAR index value higher than 0.20 indicates that they are originated from a higher risk source which is greatly exposed to antibiotics. A study conducted by Jamali et al. [47] reported that 8.40% of Listeria spp. isolated from raw milk in Iran showed multiple antibiotic resistances. In the present study, all Listeria spp. had MAR index higher than 0.20, suggesting that the Listeria spp. isolates from the three farms were originated from a higher risk source in which they had been constantly exposed to antibiotics. MAR of Listeria spp. in vegetables, soil, and irrigation water could be a result of the usage of animal waste as fertilizer which might contain antibiotics used to prevent or treat animal diseases and promote animal growth. Hu et al. [48] conducted a study on the migration of antibiotics from manure to soil and from soil to vegetables and groundwater. In the study, they applied manure containing antibiotics to organic vegetable bases and revealed that the soil, vegetables, and water were detected with antibiotic residues. Some antibiotics are still biologically active despite being in environment. This eventually can initiate development of antibiotics resistance genes in microorganisms. The findings in the present study showed that Listeria spp. isolated from the samples from all the three farms were multiresistant to the antibiotics tested. The presence of Listeria spp. that were resistant to antibiotics commonly used to treat human listeriosis (including ampicillin, chloramphenicol, erythromycin, gentamicin, penicillin G, rifampin, tetracycline, and sulfamethoxazole/trimethoprim) raises the possibility of future acquisition of resistance by L. monocytogenes and Listeria spp.

5. Conclusion

The findings of this study show current occurrence of Listeria spp. at farm level of selected organic and conventional vegetable farms in Sarawak, Malaysia. Personal hygiene and good manufacturing practice at farm level are essential for prevention of the transmission of the organism along the food chain. Based on the genotyping analysis, all Listeria spp. isolates were heterogenous. Nonetheless, BOX-PCR was shown to be better in discriminatory power than ERIC-PCR and can be utilized in Listeria typing. This study also presented high occurrence of multiple antibiotic resistant strains in the fresh produce and farm environment which could be an indicator of the excessive use of antibiotics in the agriculture field.

Data Availability

Data generated in this study are included in this article.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

Lesley Maurice Bilung conceived the study and was involved in the design and coordination of the study and manuscript drafting. Lai Sin Chai and Ahmad Syatir Tahar were involved in the manuscript drafting and editing. Lai Sin Chai was involved in the sampling collection, processing, and data analysis. Kasing Apun and Lesley Maurice Bilung were involved in the final editing of the manuscript. All authors read and approved the final manuscript.

Funding

This research is supported by Research Grant no. FRGS/SG03(01)/970/2013(11).

Acknowledgments

The authors acknowledge Ministry of Higher Education, Malaysia (MOHE), for funding the project.

References

K. Todar, Listeria monocytogenes. Todar’s Online Textbook of Bacteriology, Department of Bacteriology, University of Wisconsin, 2012.
P. Jeyaletchumi, R. Tunung, S. P. Margaret, R. Son, M. G. Farinazleen, and Y. K. Cheah, “Review article: detection of Listeria monocytogenes in foods,” International Food Research Journal, vol. 17, no. 1, pp. 1–11, 2010.
View at: Google Scholar
D. F. Maffei, N. F. D. A. Silveira, and M. D. P. L. M. Catanozi, “Microbiological quality of organic and conventional vegetables sold in Brazil,” Food Control, vol. 29, no. 1, pp. 226–230, 2013.
View at: Publisher Site | Google Scholar
D. Walsh, G. Duffy, J. J. Sheridan, I. S. Blair, and D. A. McDowell, “Antibiotic resistance among Listeria, including Listeria monocytogenes, in retail foods,” Journal of Applied Microbiology, vol. 90, no. 4, pp. 517–522, 2001.
View at: Publisher Site | Google Scholar
B.-Y. Chen, R. Pyla, T.-J. Kim, J. L. Silva, and Y.-S. Jung, “Antibiotic resistance in Listeria species isolated from catfish fillets and processing environment,” Letters in Applied Microbiology, vol. 50, no. 6, pp. 626–632, 2010.
View at: Publisher Site | Google Scholar
L. Z. Moreno, R. Paixao, D. D. S. Gobbi et al., “Characterization of antibiotic resistance in Listeria spp. isolated from slaughterhouse environments, pork and human infections,” The Journal of Infection in Developing Countries, vol. 8, no. 4, pp. 416–423, 2014.
View at: Google Scholar
L. Masco, G. Huys, D. Gevers, L. Verbrugghen, and J. Swings, “Identification of Bifidobacterium species using rep-PCR fingerprinting,” Systematic and Applied Microbiology, vol. 26, no. 4, pp. 557–563, 2003.
View at: Publisher Site | Google Scholar
J. Versalovic, M. Schneider, F. J. De Bruijn, and J. R. Lupski, “Genomic fingerprinting of bacteria using repetitive sequence-based polymerase chain reaction,” Methods in Molecular and Cellular Biology, vol. 5, no. 1, pp. 25–40, 1994.
View at: Google Scholar
Y.-H. Shangkuan, J.-F. Yang, H.-C. Lin, and M.-F. Shaio, “Comparison of PCR–RFLP, ribotyping and ERIC–PCR for typing Bacillus anthracis and Bacillus cereus strains,” Journal of Applied Microbiology, vol. 89, no. 3, pp. 452–462, 2000.
View at: Publisher Site | Google Scholar
Y. Ye, Q. Wu, L. Yao, X. Dong, K. Wu, and J. Zhang, “Analysis of a consensus fragment in ERIC-PCR fingerprinting of Enterobacter sakazakii,” International Journal of Food Microbiology, vol. 132, no. 2-3, pp. 172–175, 2009.
View at: Publisher Site | Google Scholar
D. P. Stephenson, R. J. Moore, and G. E. Allison, “Comparison and utilization of repetitive-element PCR techniques for typing Lactobacillus isolates from the chicken gastrointestinal tract,” Applied and Environmental Microbiology, vol. 75, no. 21, pp. 6764–6776, 2009.
View at: Publisher Site | Google Scholar
Z. Ruiz-Bolivar, A. K. Carrascal-Camacho, M. C. Neuque-Rico et al., “Enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) fingerprinting reveals intra-serotype variations among circulating Listeria monocytogenes strains,” Journal of Microbiology Research, vol. 5, no. 13, pp. 1586–1598, 2011.
View at: Google Scholar
S. Y. Cao, M. S. Wang, A. C. Cheng et al., “Comparative analysis of intestinal microbial community diversity between healthy and orally infected ducklings with Salmonella enteritidis by ERIC-PCR,” World Journal of Gastroenterology, vol. 14, no. 7, p. 1120, 2008.
View at: Google Scholar
R. Chmielewski, A. Wieliczko, M. Kuczkowski, M. Mazurkiewicz, and M. Ugorski, “Comparison of ITS Profiling, REP‐and ERIC‐PCR of Salmonella enteritidis isolates from Poland,” Zoonoses and Public Health, vol. 49, no. 4, pp. 163–168, 2002.
View at: Publisher Site | Google Scholar
P. E. Dombek, L. K. Johnson, S. T. Zimmerley, and M. J. Sadowsky, “Use of repetitive DNA sequences and the PCR to differentiate Escherichia coli isolates from human and animal sources,” Applied and Environmental Microbiology, vol. 66, no. 6, pp. 2572–2577, 2000.
View at: Publisher Site | Google Scholar
B.-K. Hahm, Y. Maldonado, E. Schreiber, A. K. Bhunia, and C. H. Nakatsu, “Subtyping of foodborne and environmental isolates of Escherichia coli by multiplex-PCR, rep-PCR, PFGE, ribotyping and AFLP,” Journal of Microbiological Methods, vol. 53, no. 3, pp. 387–399, 2003.
View at: Publisher Site | Google Scholar
B. R. Mohapatra and A. Mazumder, “Comparative efficacy of five different rep-PCR methods to discriminate Escherichia coli populations in aquatic environments,” Water Science and Technology, vol. 58, no. 3, pp. 537–547, 2008.
View at: Publisher Site | Google Scholar
B. Lanoot, M. Vancanneyt, P. Dawyndt et al., “BOX-PCR fingerprinting as a powerful tool to reveal synonymous names in the genus Streptomyces. Emended descriptions are proposed for the species Streptomyces cinereorectus, S. fradiae, S. tricolor, S. colombiensis, S. filamentosus, S. vinaceus and S. phaeopurpureus,” Systematic and Applied Microbiology, vol. 27, no. 1, pp. 84–92, 2004.
View at: Publisher Site | Google Scholar
M. Tacão, A. Alves, M. J. Saavedra, and A. Correia, “BOX-PCR is an adequate tool for typing Aeromonas spp,” Antonie van Leeuwenhoek-Journal of Microbiology, vol. 88, no. 2, pp. 173–179, 2005.
View at: Publisher Site | Google Scholar
B. J. Currie, D. Gal, M. Mayo et al., “Using BOX-PCR to exclude a clonal outbreak of melioidosis,” BMC Infectious Diseases, vol. 7, article no. 68, 2007.
View at: Publisher Site | Google Scholar
W. Kim, Y.-P. Hong, J.-H. Yoo, W.-B. Lee, C.-S. Choi, and S.-I. Chung, “Genetic relationships of Bacillus anthracis and closely related species based on variable-number tandem repeat analysis and BOX-PCR genomic fingerprinting,” FEMS Microbiology Letters, vol. 207, no. 1, pp. 21–27, 2002.
View at: Publisher Site | Google Scholar
D. M. Olive and P. Bean, “Principles and applications of methods for DNA-based typing of microbial organisms,” Journal of Clinical Microbiology, vol. 37, no. 6, pp. 1661–1669, 1999.
View at: Google Scholar
M. Fakruddin, K. S. Bin Mannan, R. Mohammad Mazumdar, A. Chowdhury, and M. Nur Hossain, “Identification and characterization of microorganisms: DNA-fingerprinting methods,” Songklanakarin Journal of Science and Technology, vol. 35, no. 4, pp. 397–404, 2013.
View at: Google Scholar
L. K. Strawn, Y. T. Gröhn, S. Warchocki, R. W. Worobo, E. A. Bihn, and M. Wiedmann, “Risk factors associated with Salmonellaand Listeria monocytogenes contamination of produce fields,” Applied and Environmental Microbiology, vol. 79, no. 24, pp. 7618–7627, 2013.
View at: Publisher Site | Google Scholar
G. Ozbey, H. B. Ertas, and F. Kok, “Prevalence of Listeria species in camel sausages from retail markets in Aydin province in Turkey and RAPD analysis of Listeria monocytogenes isolates,” Irish Veterinary Journal, vol. 59, no. 6, pp. 342–344, 2006.
View at: Publisher Site | Google Scholar
M. J. Zimbro, D. A. Power, S. M. Miller, G. E. Wilson, and J. A. Johnson, Difco & BBL Manual: Manual of Microbiological Culture Media-Second Edition, Becton, Dickinson and Company, 2009.
P. Jeyaletchumi, R. Tunung, P. M. Selina et al., “Evaluation of Listeria spp. and Listeria monocytogenes in selected vegetable farms,” Journal of Tropical Agricultural and Food Science, vol. 39, no. 2, pp. 255–266, 2011.
View at: Google Scholar
W. C. Wong, C. F. Pui, R. Tunung et al., “Prevalence of Listeria monocytogenes in frozen burger patties in Malaysia,” International Food Research Journal, vol. 19, no. 4, pp. 1751–1756, 2012.
View at: Google Scholar
S. S. Awaisheh, “Survey of Listeria monocytogenes and other Listeria sp. contamination in different common ready-to-eat food products in Jordan,” Pakistan Journal of Biological Sciences, vol. 12, no. 23, pp. 1491–1497, 2009.
View at: Publisher Site | Google Scholar
N. Indrawattana, T. Nibaddhasobon, N. Sookrung et al., “Prevalence of Listeria monocytogenes in raw meats marketed in Bangkok and characterization of the isolates by phenotypic and molecular methods,” Journal of Health, Population and Nutrition, vol. 29, no. 1, pp. 26–38, 2011.
View at: Google Scholar
A. Laciar, L. Vaca, R. Lopresti, A. Vega, C. Mattana, and O. N. P. De Centorbi, “DNA fingerprinting by ERIC-PCR for comparing Listeria spp. strains isolated from different sources in San Luis, Argentina,” Revista Argentina de Microbiología, vol. 38, no. 2, pp. 55–60, 2006.
View at: Google Scholar
H. Jamali and K. L. Thong, “Genotypic characterization and antimicrobial resistance of Listeria monocytogenes from ready-to-eat foods,” Food Control, vol. 44, pp. 1–6, 2014.
View at: Publisher Site | Google Scholar
C. R. Jackson, L. M. Spicer, J. B. Barrett, and L. M. Hiott, “Application of multiplex PCR, Pulsed-Field Gel Electrophoresis (PFGE), and BOX-PCR for molecular analysis of Enterococci,” in Gel Electrophoresis-Principles and Basics, S. Magdeldin, Ed., InTech, 2012.
View at: Google Scholar
P. R. Hunter and M. A. Gaston, “Numerical index of the discriminatory ability of typing systems: an application of Simpson's index of diversity,” Journal of Clinical Microbiology, vol. 26, no. 11, pp. 2465-2466, 1988.
View at: Google Scholar
C. Yoke-Kqueen, K. Teck-Ee, R. Son, N. Yoshitsugu, and N. Mitsuaki, “Molecular characterisation of Vibrio parahaemolyticus carrying tdh and trh genes using ERIC-, RAPD- and BOX-PCR on local Malaysia bloody clam and Lala,” International Food Research Journal, vol. 20, no. 6, pp. 3299–3305, 2013.
View at: Google Scholar
I. C. Morobe, C. L. Obi, M. A. Nyila, B. A. Gashe, and M. I. Matsheka, “Molecular characterization and serotyping of Listeria monocytogenes with a focus on food safety and disease prevention,” in Biochemical Testing, J. C. Jimenez-Lopez, Ed., InTech, 2012, Retrieved November 8, 2012, http://www.intechopen.com/books/biochemical-testing/molecularcharacterization-and-serotyping-of-listeriamonocytogenes-isolates-from-various-foods-in-g.
View at: Google Scholar
P. H. Krumperman, “Multiple antibiotic resistance indexing of Escherichia coli to identify high-risk sources of fecal contamination of foods,” Applied and Environmental Microbiology, vol. 46, no. 1, pp. 165–170, 1983.
View at: Google Scholar
Public Health England, “Detection and enumeration of Listeria monocytogenes and other Listeria species. Microbiology: Services Food, Water and Environmental Microbiology Standard Method. Crown,” 2014.
View at: Google Scholar
B. D. Sauders, J. Overdevest, E. Fortes et al., “Diversity of Listeriaspecies in urban and natural environments,” Applied and Environmental Microbiology, vol. 78, no. 12, pp. 4420–4433, 2012.
View at: Publisher Site | Google Scholar
M. B. Vackachan, C. Latha, B. Sunil, and V. K. Menon, “Prevalence of Listeria spp. in soils of central Kerala, India,” International Journal of Current Microbiology and Applied Sciences, vol. 4, no. 1, pp. 938–943, 2015.
View at: Google Scholar
Z. Chen and X. Jiang, “Microbiological safety of chicken litter or chicken litter-based organic fertilizers: a review,” Agriculture, vol. 4, no. 1, pp. 1–29, 2014.
View at: Publisher Site | Google Scholar
F. Lopez-Galvez, A. Allende, F. Pedrero-Salcedo, J. J. Alarcon, and M. I. Gil, “Safety assessment of greenhouse hydroponic tomatoes irrigated with reclaimed and surface water,” International Journal of Food Microbiology, vol. 191, pp. 97–102, 2014.
View at: Publisher Site | Google Scholar
W. Chitarra, L. Decastelli, A. Garibaldi, and M. L. Gullino, “Potential uptake of Escherichia coli O157:H7 and Listeria monocytogenes from growth substrate into leaves of salad plants and basil grown in soil irrigated with contaminated water,” International Journal of Food Microbiology, vol. 189, pp. 139–145, 2014.
View at: Publisher Site | Google Scholar
B. Jeršek, P. Gilot, M. Gubina et al., “Typing of Listeria monocytogenesstrains by repetitive Element sequence-based PCR,” Journal of Clinical Microbiology, vol. 37, no. 1, pp. 103–109, 1999.
View at: Google Scholar
A. Gamboa-Marín, D. C. Mejía-Wagner, P. A. Moreno-Ocampo et al., “Antimicrobial susceptibility of Listeria monocytogenes, Listeria ivanovii and Listeria species isolated from swine processing facilities in Colombia,” Journal of Swine Health and Production, vol. 21, no. 1, pp. 10–21, 2013.
View at: Google Scholar
Q. Li, J. S. Sherwood, and C. M. Logue, “Antimicrobial resistance of Listeria spp. recovered from processed bison,” Letters in Applied Microbiology, vol. 44, no. 1, pp. 86–91, 2007.
View at: Publisher Site | Google Scholar
H. Jamali, L. C. Chai, and K. L. Thong, “Detection and isolation of Listeria spp. and Listeria monocytogenes in ready-to-eat foods with various selective culture media,” Food Control, vol. 32, no. 1, pp. 19–24, 2013.
View at: Publisher Site | Google Scholar
X. Hu, Q. Zhou, and Y. Luo, “Occurrence and source analysis of typical veterinary antibiotics in manure, soil, vegetables and groundwater from organic vegetable bases, northern China,” Environmental Pollution, vol. 158, no. 9, pp. 2992–2998, 2010.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2018 Lesley Maurice Bilung et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

2260

Downloads

1459

Citations