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Article

Risk Factors Associated with the Carriage of Pathogenic Escherichia coli in Healthy Commercial Meat Chickens in Queensland, Australia † †

by
Leena Awawdeh
1,2,*,
Rachel Forrest
2,*,
Conny Turni
3,
Rowland Cobbold
1,
Joerg Henning
1,‡ and
Justine Gibson
1,‡
1
School of Veterinary Science, The University of Queensland, Gatton, QLD 4343, Australia
2
Eastern Institute of Technology, Hawke’s Bay, 501 Gloucester Street, Taradale, Napier 4112, New Zealand
3
Queensland Alliance for Agriculture and Food Innovation, Centre for Animal Science, The University of Queensland, Dutton Park, QLD 4102, Australia
*
Authors to whom correspondence should be addressed.
†
This paper is part of Leena Awawdeh ’s doctor thesis.
‡
These authors contributed equally to this work.
Poultry 2022, 1(2), 94-110; https://doi.org/10.3390/poultry1020009
Submission received: 14 March 2022 / Revised: 7 April 2022 / Accepted: 18 April 2022 / Published: 17 May 2022
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Abstract

:

Simple Summary

At the farm-level, all 40 farms sampled were positive for avian pathogenic E. coli (APEC), and the mean within-farm prevalence was 63%. Higher APEC within-farm bird-level prevalence was significantly associated with the usage of well water as a source of drinking water, failure to disinfect the waterline after each flock, farm visitors not showering before entering the shed, distances greater than 20 m between the car park and the poultry shed, and the presence of wild birds within 50 m of the shed. Chlorinating the drinking water combined with automatic water filtration reduced within-farm bird-level APEC prevalence. Based on the results concluded from the multivariable model, improving biosecurity and water treatments might reduce APEC prevalence, decrease the risk of colibacillosis, reduce the use of antimicrobials, improve food safety, and positively influence poultry and public health.

Abstract

Avian pathogenic E. coli (APEC) can cause avian colibacillosis, an economically important disease that contributes to bird mortality and the high costs associated with prevention and treatment. Little is known about APEC in the context of Australian conditions. The current study aimed to estimate the prevalence of APEC and determine the risk factors associated with cloacal carriage of APEC among commercial healthy meat chickens in Queensland. Cloacal swabs were collected at slaughter from 400 healthy meat chickens (ten per farm) originating from 40 farms. A total of 2200 E. coli isolates were selected from cultured swabs and screened for the presence of five APEC-associated virulence genes (VGs). Farm-level data were collected using a questionnaire. Binominal general linear models were used to identify farm-level risk factors associated with bird-level APEC prevalence. Thirty-four per cent of the cultured E. coli isolates (n = 751) were classified as APEC, with all farms testing positive for APEC, and the overall bird-level prevalence of APEC was 63.0%. Higher APEC within-farm bird-level prevalence was positively associated with the usage of well water as a source of drinking water (OR = 6.2, 95% CI: 2.3, 16.5, p < 0.001); not having shower facilities available for farm visitors (OR = 3.6, 95% CI: 1.8, 7.1, p < 0.001); distances greater than 20 m between the car park and the poultry shed (OR = 2.2, 95% CI: 1.4, 3.4, p = 0.001); not applying water line disinfection after each flock cycle (OR = 2.2, 95% CI: 1.4, 3.5, p = 0.001); the presence of wild birds within 50 m of the poultry shed (OR = 2.3, 95% CI: 1.4, 3.7, p = 0.001). Chlorine combined with automatic drinking water filtration reduced within-farm bird-level APEC prevalence (OR = 0.07, 95% CI: 0.02, 0.34, p = 0.001). This study identified a number of important factors associated with APEC and showed that improving biosecurity and water treatments might reduce the prevalence of APEC. The notable high APEC prevalence on all farms requires further epidemiological investigations.

1. Introduction

Avian colibacillosis is considered one of the most common diseases that affect the poultry industry and results in significant economic losses and increased welfare concerns [1,2,3,4,5,6,7]. Despite the improvements and modernisation in poultry production systems and the fact that avian pathogenic Escherichia coli (APEC) has been a recognised cause of avian colibacillosis, APEC remains one of the most significant pathogens, posing a considerable challenge to the global poultry industry [1,3,5,6]. In addition, the genetic overlap between APEC and other extraintestinal pathogenic E. coli (ExPEC) that cause neonatal meningitis, septicaemia and urinary tract infections in humans suggests that APEC is a zoonotic pathogen [3,8,9,10,11,12,13,14].
APEC can act as a primary or secondary pathogen [6,15,16,17,18] and can result in localised and/or systemic infections in birds [5,19,20]. The severity of the disease depends on the virulence of APEC strains, chicken age and immune status, and the presence of predisposing risk factors [1,20,21]. Healthy chickens can harbour APEC and avian faecal E. coli (AFEC) in their gut flora, which may harbour various virulence genes [7,19]. Hence, healthy chickens can act as a reservoir for disseminating APEC to other more susceptible chickens (due to age and or immune status) and their surrounding environment, potentially causing recurring infections in new flocks [19,20].
A number of studies have indicated that various virulence genes (VGs) are useful markers for identifying APEC and that they can be used to differentiate between APEC and AFEC [9,12,22,23,24]. The combinations of different VGs are likely associated with APEC pathogenicity [9,22,25]. Thus, Johnson et al., (2008) [26] developed a PCR targeting five VGs, namely, (haemolysin gene (hlyF), increased serum survival gene (iss), outer membrane protease gene (ompT), and two iron acquisition system genes (iutA and iroN), which have been used as a tool for the identification of APEC [26,27,28,29,30,31,32].
A range of risk factors are associated with likelihood of APEC infection [26,27,28,29,30]. Kemmett et al., (2013) reported a higher APEC prevalence in the intestinal.
Flora of one-day-old healthy chicks compared to adult chickens at slaughter-age [25]. Contrarily, Kwon et al., (2008) [33] found a higher APEC prevalence (31%) in layer birds (approximately 21 to 70 weeks of age) compared to slaughter-age meat chickens (up to 12 weeks of age, APEC prevalence 14%) in Korea. However, these differences might be related to farming practices rather than age, as layer and meat management are very different.
Farm-level risk factors associated with a high prevalence of avian colibacillosis relate to poultry management practices [5,21]. Impaired biosecurity protocols, for example, might result in APEC entry into the chicken sheds and contribute to increased APEC prevalence [34]. On the other hand, good biosecurity practices, such as frequent carcass removal and the use of disinfectants for cleaning, decreased the prevalence and the spread of avian colibacillosis [21].
A positive association between the accumulation of the E. coli pathogen in the faeces and the surrounding environment with an increase in the birds’ susceptibility to APEC infection among meat chickens has been found [20,34]. The main risk factors associated with the bird’s susceptibility were the duration of exposure, the virulence of the APEC strain, breed, and the immune status of the bird [34]. There were positive associations between an increased risk of avian colibacillosis and increased environmental infection pressure [5]. Such environmental pressures can result from unfavourable husbandry management, poor biosecurity protocols, and seasonal changes [5,34,35,36,37].
Farm-level risk factors for APEC among commercial meat chicken flocks in Australia are unknown. Therefore, the current study aimed to: (i) determine the farm-level and bird-level prevalence of the gastroenteric carriage of APEC and (ii) investigate the associations between management risk factors and the within-farm APEC prevalence among healthy commercial meat chicken flocks to identify potential farm-level risk factors for avian colibacillosis.

2. Materials and Methods

2.1. Study Design

A cross-sectional study was conducted to estimate APEC prevalence and identify farm-level risk factors associated with APEC prevalence.

2.2. Sample Collection

Assuming a high farm-level APEC prevalence of 90%, with a 95% confidence interval (CI) and a precision of 10%, a sample size of 40 farms was required. The required sample size for bird-level prevalence was calculated to be 400 based on an unknown prevalence of birds carrying APEC (the assumed prevalence was set to 50%), a precision of 5% for the prevalence estimate, and a 95% CI. Thus, we sampled ten birds from each of 40 commercial meat farms. Also, a sample size of about 380 birds is needed to achieve 80% power for detecting an OR of 2 for the risk of APEC, if the expected exposure to the risk factor in the group of birds without APEC is about 20%.
The chicken meat farms included in the study belonged to the same commercial company and were randomly selected by the company. The selected company was willing to participate in this research project and provided access to their farm premises. The 40 commercial chicken meat farms were operating in different geographical locations.
Samples were collected at slaughter between October 2013 and July 2014 in Queensland, Australia (animal ethics approval number: SVS /323/13/ POULTRY CRC).
The commercial chicken meat company owned one slaughterhouse, and chickens were sampled at that location to reduce the disturbance of on-farm production. The slaughterhouse processed up to 15 commercial chicken meat flocks from different farms within a day. The slaughterhouse was visited every Monday for eight consecutive weeks, and birds from four to six farms were sampled at each visit. The sampling of birds from a particular farm was completed within a day, i.e., birds from the same farm were not sampled across days.
Chickens were submitted to the slaughterhouse in flocks, with chickens from each flock kept together in cages (up to 20 chickens per cage). Only one bird was selected and restrained from each cage whilst a cloacal swab (Sarstedt Australia Pty. Ltd., Technology Park, Mawson Lakes, South Australia, Australia) was collected. In this way, a total of ten chickens from ten cages representing one meat farm were sampled. The swabs were transported on ice to the School of Veterinary Science laboratory at the University of Queensland within two hours of collection.

2.3. Collection of Risk Factor Data

A questionnaire was used to collect data on potential risk factors associated with intestinal/cloacal carriage of APEC in the sampled meat chickens (human ethics approval number: SVS/2014000327/POULTRY CRC).
The questionnaire focussed on risk factors previously reported to be associated with APEC in commercial meat chickens [5,21,34] and included questions on the number of sheds and chickens kept on the farm, the farm’s location concerning other livestock farms, specific management practices and biosecurity measures on the farm, and general flock health. Management risk factors evaluated included the following: the age structure of meat flocks; restocking practices; sources of drinking water used; number of workers on the farm; type of visitors; reasons for visits and frequency of their visit(s) to the farm; the presence and the frequency of unwanted animals (rats, mice, wild birds, domestic animals such as dogs, cats, cattle or pigs, stray/feral animals, amphibians, reptiles, kangaroos, possums) inside or outside the chicken shed within a categorised distance (less than and equal to 50 m and greater than 50 m); the frequency of litter removal. Biosecurity measures were assessed in terms of the following: routine cleaning practices (bird disposal, shed and equipment cleaning); precautionary measures used by farmworkers and/or visitors before and after entering the chicken sheds; the frequency of using foot baths; use of protective clothing; use of showers and hand sanitisers; cleaning and disinfecting protocols used; the distance between the meat shed and the car park; the frequency of cleaning and disinfection of the tyres of transport vehicles and of equipment (feeder, drinker, ladder, fixing tools, etc.) before entering the farm; ownership of livestock or pets by the farm manager and workers. Potential flock health data collected comprised information on previous colibacillosis infections and other diseases on the farm, mortality rates per shed, frequency of removing dead bird carcasses from the sheds, and the administration of antimicrobial drugs.
The questionnaire was piloted in February 2014 in face-to-face interviews with three individual meat farm managers, and five questions were revised to increase their clarity. The final questionnaire contained 52 binary, ordinal, and open-ended questions (Supplementary Table S1).
The questionnaire, information on the background and purpose of the research study, a consent form, and a pre-addressed stamped envelope for posting the completed questionnaire to the first author of this paper were mailed out to the managers of the chicken meat farms in April 2014. In June 2014, a reminder was posted followed by a phone call to remind the farm managers to complete the questionnaire. The managers of ten chicken meat farms were contacted either face-to-face or by phone to clarify some responses after receiving the completed questionnaires.

2.4. Bacterial Culture of Samples, Identification and DNA Extraction

All samples were processed within 24 h of collection. Each cloacal swab was cultured on BrillianceTM E. coli coliform selective agar (BECS; Oxoid, Thebarton, South Australia, Australia) [38] and incubated aerobically overnight at 37 °C. From each agar plate, five or ten presumptive E. coli colonies (for each farm, five colonies were selected from nine chickens and ten colonies from one chicken) were collected. If the selected isolate was not confirmed as E. coli, further isolates were selected from the BECS plate until 2200 E. coli isolates were collected from the 40 farms.
Presumptive E. coli isolates were subcultured on sheep blood agar (SBA; Oxoid) and incubated aerobically at 37 °C overnight. Isolates that were indole positive and pyrrolidonyl arylamidase negative were presumed to be E. coli and DNA was extracted [39]. An E. coli-specific PCR targeting the uspA gene [40] was performed to confirm E. coli identification. All E. coli isolates were stored at −80 °C in brain heart infusion (BHI) broth (Oxoid) containing 20% glycerol until further analysis. The extracted DNA (100 µL) was stored at −20 °C until further analysis.

2.5. Molecular Detection of Virulence Genes

All 2200 E. coli isolates were screened for the presence of five APEC-related VGs (iroN, iutA, iss, hlyF, and ompT) using the pentaplex-PCR [26] Escherichia coli STJ-1 [41] and E. coli ATCC 8739 were used as positive and negative controls, respectively. The E. coli isolate selected to represent each bird was the E. coli cultured from that bird that contained the most VGs to increase the sensitivity of identifying APEC positive birds. If more than one E. coli isolate from the same chicken carried the same number of VGs, random selection was applied using a random number generator by Excel Microsoft (Microsoft Corporation, Sydney, NSW, Australia, www.microsoft.com (accessed on 11 February 2014).).

2.6. Case Definition

For the purpose of this study, APEC were defined as an E. coli isolate that was cultured from cloacal swabs and harboured four or more of the five selected APEC-related VGs (iutA, iss, ompT, hlyF, and iroN) [26]. AFEC was defined as an isolate that was cultured from the cloacal swab of a healthy chicken and harboured less than four of the five selected APEC related VGs.
A chicken was considered APEC positive at the bird-level if at least one of its E. coli harboured four or more of the selected APEC-associated VGs. The farm was considered APEC positive if at least one bird on that farm was APEC positive.

2.7. Validation of the Number of E. coli Colonies That Need to Be Screened to Detect APEC VGs

To identify the number of E. coli colonies that needed to be screened to detect four or more of the five selected APEC-related VGs, five colonies (obtained from nine chickens within a single farm) and ten colonies (obtained from one chicken within a single farm) were selected from BrillianceTM E. coli coliform selective agar (BECS; Oxoid). The E. coli colony selected to represent each bird was the E. coli colony containing the most VGs. This E. coli isolate (and the individual bird) was classified as either APEC positive or negative. We used the kappa statistic to evaluate the agreement in classifying an isolate APEC positive or negative when either five or ten colonies were selected from the agar plates [42].

2.8. Virulence Gene Prevalence in APEC Positive and Negative Birds

The prevalence of the five VGs (with 95% CI) among APEC positive and negative birds was summarised. As samples were clustered within meat farms, survey estimation commands were used, with the farm being defined as the primary sampling unit [43,44]. Hence, the standard error and CI estimation accounted for the clustering. The prevalence of each VG was compared between APEC positive and negative birds using the Pearson chi-square statistic with Rao and Scott second-order correction [43,44]. Thus the Pearson chi-square statistic was converted into a survey-design adjusted F statistic [43,44].

2.9. Farm-Level, Bird-Level and within-Farm APEC Prevalence

Overall farm-level prevalence was the proportion of farms that had at least one bird that was APEC positive. Overall bird-level prevalence was calculated as the number of APEC positive birds out of the total number of birds (n = 400) sampled in this study. Within-farm prevalence was calculated as the number of APEC positive birds out of the ten birds sampled per farm.

2.10. Risk Factors for APEC within-Farm Prevalence

Questionnaire data were entered into a Microsoft Access 2013 database (Microsoft Corporation) and examined for errors and missing values. Data analyses were performed using Stata (13th edition, Blackburn North Victoria, Australia, www.stata.com (accessed on 20 October 2014).
A total of 120 individual risk factors were derived from the 52 questions in the questionnaire. Logistic regression models were used to investigate the association of APEC within-farm prevalence and potential APEC farm-level risk factors [45,46]. Risk factors with p < 0.15 in the univariate analysis were included in the multivariable model. A forward stepwise model building strategy was used to develop the final model. The analysis was continued by successively re-fitting models with explanatory variables that were not significant at p < 0.15 in the univariate analysis until all remaining variables in the final model were statistically significant at p < 0.05 [47,48,49,50]. In addition, potential confounding variables were explored by identifying if adding or removing a variable would result in at least a 20% relative change in the coefficients of variables in the multivariable model [50]. Interactions between the different explanatory variables in the final model were also tested. For variables with more than two levels, the overall significance of the categorical variable levels was evaluated using the Wald test [47]. Models were compared using the Akaike information criterion (AIC) [48,49,50]. Overall assessment of how well the final multivariable model fitted the observed data was conducted by exploring residuals and covariate patterns and by calculating Pearson X2, deviance, and conducting the Hosmer–Lemeshow tests [51].

3. Results

3.1. Overview of Meat Farm Management and Biosecurity Practices

The majority (97.5%) of the questionnaires (n = 39) were completed by farm managers and 2.5% by a farm owner (n = 1). Variation in shed numbers among the participating farms was noted, with the smallest farm consisting of only two sheds that produced up to 50,000 chickens per meat growing cycle (range 30 to 60 days). The largest farm was composed of 19 sheds producing up to 180,000 chickens per meat growing cycle. Half (50%) of the surveyed farms were composed of five to eight sheds.
The integrated company livestock manager (independent from the farm manager and/or owner) visited each farm weekly to check on-farm management, health of the bird, and progress of the meat chickens. The livestock manager supported and supervised all of the participating 40 farms, all of which followed the same biosecurity protocols that the integrated company had developed.
A quarter (25%, n = 10) of the farms housed chicken meat flocks of the same age (range 1–50 days-old) in the same shed at the same time using an all-out all-in system of rearing. Sixty-five per cent (n = 26) of the farms housed flocks of different ages within the same shed. Ten per cent of the farms (n = 4) housed single and multiple aged birds in different sheds at one time.
Fifty percent of the sampled farms used tunnel ventilation (n = 20), 47.5% used natural ventilation (n = 19) and 2.5% (n = 1) used negative pressure ventilation. About 63% of farms (n = 25) used fans as a second source of ventilation.
All farm workers (including the manager/owner) and visitors on all farms (n = 40) used footbaths. Hand sanitisers were used by 42.5% of farmworkers (n = 17) and 55% of farm visitors (n = 22). Most farm workers (97.5%, n = 39) and farm visitors (80%, n = 32) did not wear protective overalls when entering the chicken sheds. Only one farm failed to disinfect equipment such as repaired tools or ladders used by farmworkers and visitors prior to the equipment re-entering the sheds.
Seventy-five per cent of farms (n = 30) used reticulated water as the only source of drinking water for chickens, 7.5% of the farms (n = 3) used a well as the only source of drinking water, and 17.5% of farms (n = 7) used a combination of reticulated and dam water as the source of drinking water. Seventy-five per cent (n = 30) of the farms treated the drinking water with either chlorine alone or in combination with other treatment methods such as automatic filtration.
Every farm removed used litter after each batch of chickens and the sheds were cleaned with a pressure hose using a mild detergent before they were restocked. Most of the farms (97.5%, n = 39) washed the walls as part of the shed cleaning protocol, and shed sanitisation was conducted by 80% of the farms (n = 32). As part of their cleaning protocols, all farms used insecticides inside the shed after cleaning.
Thirteen farms (33%) were located within 500 m of other farms housing animals (nine cattle, two horse and two camel farms). Only 10% (n = 4) of farm managers/owners owned a dog and/or a cat. However, no contact between their pet(s) and the meat chickens was reported.
Avian colibacillosis had been diagnosed in the last year for 40% (n = 16) of the surveyed farms based on clinical signs, post-mortem examination, and the isolation of E. coli from the affected lesions. Antimicrobial treatment (trimethoprim-sulfamethoxazole) had been administered to bird flocks on four of these 16 farms. Furthermore, no other respiratory or any other diseases had been diagnosed on any of the farms within the period the sampled flock was kept on the farm.

3.2. Validation of the Number of E. coli Colonies That Need to Be Screened to Detect APEC VGs

Of the 2200 E. coli isolates cultured, 34% (n = 751) carried four or more VGs (mean = 4.9 VGs) and were classified as APEC positive. In contrast, 66% (n = 1449) were classified as AFEC positive with a mean of 2.2 VGs per isolate.
The kappa statistics data on the agreement of using five or ten E. coli colonies for classifying a chicken as APEC positive or negative are shown in Table 1. The agreement varied between almost perfect and moderate [42] and provided confidence that five colonies were sufficient for classifying birds as APEC positive or negative correctly.

3.3. Virulence Gene Prevalence in APEC Positive and Negative Birds

The prevalence of individual VGs in the 400 bird-level isolates (each isolate representing one sampled chicken) is shown in Table 2. Overall, the prevalence of APEC related VGs was significantly higher in APEC positive birds in comparison to APEC negative chickens. The iutA VG was the most frequently occurring VG in APEC negative chickens with a 75.7% prevalence.

3.4. Prevalence of Avian Pathogenic E. coli

All of the 40 farms were positive for APEC (i.e., at least one bird per farm was APEC positive). At the bird-level, the overall prevalence of APEC in commercial meat chickens (n = 400) was 63.0% (95% CI: 55.8, 70.2). The frequency of APEC positive birds sampled per farm across the 40 commercial farms is shown in Figure 1. More than half (58%) of the farms (n = 23) had six or more APEC positive birds (of 10 sampled birds). Only one farm had one bird (of 10 sampled birds) identified as APEC positive, and four farms had all ten sampled chickens identified as APEC positive.

3.5. Risk Factors for APEC Bird-Level Prevalence

The univariate analysis showed that four risk factor variables were associated with decreased APEC within-farm prevalence (p < 0.15) (Table 3), and eight risk factors were associated with increased APEC farm prevalence (p < 0.15) (Table 4).
The final multivariable model describing the association between the farm-level risk factors and within-farm APEC prevalence is shown in Table 5. Higher APEC within-farm bird-level prevalence was positively associated with the following: usage of well water as a source of drinking water (OR 6.2, 95% CI: 2.3, 16.5, p < 0.001); not having shower facilities available for farm visitor (OR = 3.6, 95% CI: 1.8, 7.1, p < 0.001); distances greater than 20 m between the car park and the poultry shed (OR = 2.2, 95% CI: 1.4, 3.4, p = 0.001); failure to disinfect the waterline after each flock (OR = 2.2, 95% CI: 1.4, 3.5, p = 0.001); presence of wild birds within 50 m of the poultry shed (OR = 2.3, 95% CI: 1.4, 3.7, p = 0.001). The use of chlorine combined with automatic drinking water filtration reduced within-farm bird-level APEC prevalence (OR = 0.07, 95% CI: 0.02, 0.34, p = 0.001).

4. Discussion

The current study estimated APEC prevalence in commercial broiler chickens and investigated the possible associations between the detected APEC prevalence and biosecurity measures, flock health, and management practices. A cross-sectional study involving healthy commercial broiler chickens simultaneously allowed the comparison and identification of many potential risk factors. The current study has revealed a high APEC prevalence in healthy commercial meat chickens in Queensland. All of the tested farms (n = 40) were APEC positive and 63% (252 of 400) of birds were identified as APEC positive. APEC-associated VGs (iss, hlyF, ompT, iroN, and hlyF) were commonly detected in E. coli cultured from the faeces of healthy commercial broiler chickens. Therefore, healthy birds may be a reservoir for APEC-associated genes.
The analysis of risk factors revealed many similar contributors associated with APEC carriage in Australia compared to studies conducted in China and Belgium [21,52]. The risk factors that were significantly associated with higher APEC prevalence in Australia included using water wells as a source of drinking water, not having shower facilities available for farm visitors, distances greater than 20 m between the car park and the poultry shed, not applying water line disinfections after each flock cycle, and the presence of wild birds within 50 m of the poultry shed. The use of chlorine combined with automatic filtration of drinking water was identified as a protective factor and reduced farm-level APEC prevalence.
The VGs that were proposed by Johnson et al., (2008) [26] as an APEC marker were based on the significant association between these VGs and APEC [27,53,54]. These genes (iutA, hlyF, iss, iroN, and ompT) are carried by plasmids that typify the APEC pathotype [23,26]. The current study reported an average number of 2.2 genes in E. coli cultured from the faeces of healthy meat chickens in Australia compared to 1.3 genes found in faecal E. coli in the United States of America [26].
The current study reported that the most prevalent of the tested VGs was ompT (100%) followed by iss, hylF, iroN, and iutA, which were all detected in more than 94% of the 252 E. coli isolates from APEC positive chickens. Johnson et al., (2008) reported a lower prevalence of these five VGs ranging between 21 to 36% in 200 E. coli isolates sourced from the faecal samples of healthy meat chickens in the United States of America (USA) [26]. A higher prevalence of ompT (42.5%) and a lower prevalence of iss (18.3%) and iroN (13.5%) were found by Rodriguez-Siek et al., (2005) in E. coli isolates from faecal samples of healthy birds from the USA [23].
This study showed that the selection of five colonies was sufficient to identify the strains of E. coli carried by the birds with the maximum number of VGs and allow them to be correctly identified as APEC positive or negative. Additionally, only one E. coli isolate, with the highest number of VGs, was chosen to identify APEC status per bird, which may explain the high prevalence of APEC found at the farm-level in the current study compared with other studies. No data were collected regarding the whole genomic sequence and phylogenic groups in the current study, so these molecular comparisons between poultry and human isolates should be the focus of future research.
Despite the age of the birds, there was a similarity between the current study and Kemmett et al., (2013), where considerable APEC prevalence variations were found [25]. A lower APEC prevalence of 1% was reported by Kemmett et al., (2013) [25] in 160 E. coli isolates sourced from meat chickens in the United Kingdom. However, the usage of a larger number and a different range of VGs (astA (heat-stable cytotoxin), iss, irp2 (iron-repressible protein), iucD (aerobactin), papC (fimbriae), tsh (temperature-sensitive hemagglutinin), vat (vacuolating autotransporter toxin), cvi (colicin V plasmid operon), sitA, and ibeA (invasion of brain endothelium)) could explain the lower APEC prevalence they reported. The same authors identified a higher bird-level prevalence of APEC (that harboured five or more of the ten VGs) of 24.1% in one-day-old chickens compared to 1% prevalence at slaughter-age [25]. At the bird-level, a 14% APEC prevalence was reported in a Korean study where they used a different set of eight APEC VGs (astA, iss, irp2, papC, iucD, tsh, vat, and cva/cvi) to screen 216 E. coli isolates sourced from chickens and environmental samples at the hatcheries [33]. Thus, studies that screen for a larger number of VGs and define APEC with more VGs generally identify a lower prevalence of APEC than those studies using fewer VGs. The development of a defined set of VGs for the definition of APEC would aid in the direct comparison of multiple studies.
Understanding the risk factors associated with the increased prevalence of APEC can assist managers to implement strategies to minimise the presence of the pathogen on the farm. Previous studies have suggested that good biosecurity and management protocols are crucial in controlling and reducing environmental contamination by APEC and preventing colibacillosis [1,6,20,34]. The current study identified risk factors in line with the results of several studies described in various countries, such as poor-quality water sources, no treatment of drinking water, and direct and/or indirect contact of wild birds with the meat chickens [37,55,56].
The ability of bacteria to survive in water makes the drinking water used on meat farms a potential source of infection [57]. Droppings and secretions of wild birds and other animals could contaminate water sources on poultry farms. It is common on poultry farms for a single water source to supply many birds [57]. Applying essential biosecurity to the drinking water source, such as chlorinated water mains, covered water tanks, cleaning and disinfection of tanks, and water lines between flocks, are essential practices to assist in reducing the presence of APEC and/or other pathogens in the drinking water [58].
Water wells have previously been linked to the carriage of APEC [59] and Campylobacter coli [60]. The use of water wells as a source of drinking water in three farms in the current study was associated with a higher prevalence of APEC (OR = 6.2) compared to farms that used chlorinated mains water and/or dam water. Interestingly, one of the three farms that used a well did not use any treatment of the drinking water, and the other two farms treated the water with chlorine only. The combination of using a water well and the absence of water treatment may have contributed to the observed high APEC prevalence. Although there were only three farms involved, the current study highlights the benefit of using a combination of water treatment by chlorination and filtration to reduce the prevalence of APEC carriage in meat chickens. Arsenault et al., (2007) also reported that the addition of chlorine to the drinking water helped reduce the risk of Campylobacter and Salmonella colonisation of intestinal flora [61].
Similarly, other studies have also reported the benefits of chlorination in reducing the prevalence of E. coli and/or other pathogens and/or decreasing mortality associated with disease [58,62,63,64]. In this study, not disinfecting the water line between each flock increased APEC prevalence by 2.2-fold. This reflects the role of appropriate infection control measures for drinking water in reducing the prevalence of APEC as well as other infectious agents [63,65]. Hence, untreated water usage can be considered a potential risk factor for meat flock carriage of APEC, and potentially, other infectious agents. It can be recommended that farms that utilise a well as a source of drinking water should disinfect the water with chlorine and use automatic filtration to reduce the prevalence of APEC carriage. After each flock, disinfection of the water lines should also be included as a best practice management technique on farms.
One concerning finding of the current study was that most farm workers and/or visitors did not implement appropriate on-farm biosecurity measures whilst conducting daily work. For example, the same pair of overalls and gumboots were utilised across sheds on the same farm. It has been shown that this can facilitate the spread of E. coli as well as other infectious agents from one shed to another or introduce agents to the shed from the surrounding environment [66].
The current study identified that a distance greater than 20 m between car parks and sheds was associated with a 2.2-fold increase in APEC prevalence. This finding relates not so much to the proximity of the car park to the sheds but more to how much farm personnel need to move around the farm before undertaking biosecurity procedures (e.g., showering, use of dedicated clothing) and entering the sheds. A number of studies showed that APEC is found in the surrounding environment around farms [67,68,69]. The reported overlap between APEC strains isolated from farmworkers clothes, hands and boots, and poultry farms suggests that people may act as a significant vehicle for introducing and spreading APEC and other pathogens to the poultry farms from the external environment [26,70,71,72,73]. Essentially, parking should be close to the changing area, and stringently imposed requirements for changing protective overalls and boots is imperative for infection control [52,55].
In addition to this, procedures for all staff and visitors to shower in and out of the facilities can reduce the presence of APEC on farms. This study found that not having a shower facility on the farm premises was associated with a 3.6-fold increase in APEC carriage prevalence on seven farms. Hence, this is a management procedure that can be implemented on all farms to reduce the presence of pathogens, such as APEC, within the poultry farm boundaries.
Wild birds present a source of contamination for the poultry flock environment. The presence of wild birds within 50 m of the meat sheds in this study was significantly associated with increased APEC prevalence. A previous Australian study investigating Newcastle virus, and overseas studies on APEC and other infectious agents, also identified wild birds as an important biosecurity risk [52,74,75]. Wild birds can directly or indirectly encounter meat flocks in their sheds, and they can function as mechanical and/or biological vectors for introducing and/or spreading APEC and other avian diseases. The similarity between APEC strains that are extracted from the faeces of wild birds and meat flocks may implicate wild birds as a potential source of risk [70,76]. Furthermore, the presence of wild birds can induce stress, which is a known predisposing factor for APEC [5]. Therefore, there is a need to control the presence of wild birds near meat sheds. This can be achieved by applying restricted biosecurity measures, such as cleaning feed spills and minimising the amount of surface water on the farm, to discourage the presence of wild birds [77].
All farms that were surveyed in this research tested positive for APEC, providing further evidence that APEC is common even in the gut of healthy meat chickens. Exposure to APEC might be a contributing factor in cases of avian colibacillosis [34]. Thus, there is a need to implement strict biosecurity to reduce APEC exposure on farms and decrease the prevalence of APEC. It is known that the occurrence and severity of avian colibacillosis depends on the pathogenicity of the APEC strain, the immune status of the chicken, and the presence of predisposing risk factors [34]. This study has highlighted some of these risk factors, including management practices that could contribute to an increased carriage of APEC in healthy chickens.
Nevertheless, this study has not taken into consideration that there might be some interplay between farm management and the immune status of the birds. Further research might look at farm management practices to prevent damaging the immune system of the birds and mitigate the negative effects of APEC risk. It is also recommended that further investigation should seek to identify how the potential risk factors identified in this study contribute to APEC prevalence. Other biosecurity questions, such as farm infrastructure, location, and the surrounding environment, could also be further investigated.
The current study was able to overcome some of the difficulties associated with self-reporting questionnaires by conducting piloted face-to-face interviews with three individual meat farm managers to help simplify any unclear questions. As a result, five questions were revised to increase their clarity. Face-to-face interviews took place on all farms that did not respond to overcome the low response rate associated with self-reporting questionnaires. By doing this, we achieved a 100% response rate from all the sampled commercial meat farms. The main limitation of this study is that only one integrated large commercial meat company participated. The sampled chicken meat farms belonged to the same company and had implemented the biosecurity practices recommended by that company. Future research could compare biosecurity practices with APEC prevalence across different companies. Another limitation of this study is that it was conducted as a cross-sectional study, and causal associations are difficult to detect with this study type (e.g., whether management interventions lead to increased/decreased APEC prevalence, or whether management interventions were implemented in response to increased/decreased APEC prevalence). Furthermore, it is difficult to accurately compare the prevalence findings between studies based on a cross-sectional research design because there are too many uncontrolled variables. Future investigations could use longitudinal or cohort approaches to explore APEC prevalence and associated risk factor temporal patterns.

5. Conclusions

In summary, the current study identified a high prevalence of APEC carriage in healthy meat chickens in Queensland. The current study suggests that practices such as the availability of a shower facility on the farm, a decreased distance between the car park and the sheds, and/or providing a buffer area close to each shed where visitors or workers can change into protective clothing will decrease the risk of APEC carriage and potential infection. Furthermore, our study identified drinking water as a significant risk factor for contamination highlighting the need for water management mechanisms to be put in place in order to reduce the prevalence of APEC. These include chlorination and filtration of drinking water, covering water wells and all water sources, as well as cleaning and disinfecting tanks and water lines between each flock. Particular attention is needed to control risk factors related to impaired biosecurity protocols on the farm, such as direct and indirect contact between chickens and wild birds (for example, through access to the same drinking water).
While this study has identified a high prevalence of APEC at both the bird and farm level in Queensland, longitudinal investigations are needed to estimate the carriage of APEC in one-day-old chickens through to slaughter (or death prior to slaughter), track the associated APEC prevention and treatment costs (and effectiveness/efficacies), and determine the extent of carcass rejections in the same flocks at the abattoirs to ascertain the economic cost of APEC to the chicken meat industry in Australia.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/poultry1020009/s1: Risk Factors Associated with the Carriage of Pathogenic Escherichia coli in Healthy Commercial Meat Chickens in Queensland, Australia; Table S1: Questionnaire for the cross-sectional study to identify risk factors associated with avian pathogenetic E.coli on commercial meat chicken farms in Queensland.

Author Contributions

Conceptualisation, J.G., C.T., J.H., R.C. and L.A.; methodology, J.G., C.T., J.H., R.C. and L.A.; data curation and formal analysis, J.H., L.A. and R.F.; interpretation of data, J.H., L.A. and R.F.; writing—original draft preparation, J.G., C.T., J.H., R.C., R.F. and L.A.; writing—review and editing, J.G., C.T., J.H., R.C., R.F. and L.A.; supervision, J.G., C.T., J.H., R.C., R.F. and L.A.; project administration, J.G., C.T. and L.A.; funding acquisition, J.G., C.T. and L.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Poultry Cooperative Research.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the University of Queensland Ethics Committee (human ethics approval number: SVS/2014000327/POULTRY CRC) and (animal ethics approval number: SVS /323/13/ POULTRY CRC).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We like to thank the poultry farmers, slaughterhouse and the manager for allowing us to sample their sheds.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Dho-Moulin, M.; Fairbrother, J.M. Avian pathogenic Escherichia coli (APEC). Vet. Res. 1999, 30, 299–316. [Google Scholar] [PubMed]
  2. Arné, P.; Marc, D.; Brée, A.; Schouler, C.; Dho-Moulin, M. Increased Tracheal Colonization in Chickens without Impairing Pathogenic Properties of Avian Pathogenic Escherichia coli MT78 with a fimH Deletion. Avian Dis. 2000, 44, 343–355. [Google Scholar] [CrossRef] [PubMed]
  3. Johnson, J.R.; Russo, T.A. Extraintestinal pathogenic Escherichia coli: “The other bad E. coli”. J. Lab. Clin. Med. 2002, 139, 155–162. [Google Scholar] [CrossRef] [PubMed]
  4. Ewers, C.; Janssen, T.; Kiessling, S.; Philipp, H.C.; Wieler, L.H. Molecular epidemiology of avian pathogenic Escherichia coli (APEC) isolated from colisepticemia in poultry. Vet. Microbiol. 2004, 104, 91–101. [Google Scholar] [CrossRef]
  5. Nolan, L.K.; Barnes, H.; Jean Pirre, V.; Abdul-Aziz, T.; Louge, C.M. Colibacillosis. In Diseases of Poultry, 13th ed.; Swayne, D.E., Glisson, J.R., McDougald, L.R., Nolan, L.K., Suarez, D.L., Nair, V.L., Eds.; John Wiley and Sons: Ames, IA, USA, 2013; pp. 751–785. [Google Scholar]
  6. Collingwood, C.; Kemmett, K.; Williams, N.; Wigley, P. Is the concept of avian pathogenic Escherichia coli as a single pathotype fundamentally flawed? Front. Vet. Sci. 2014, 1, 5. [Google Scholar] [CrossRef] [Green Version]
  7. Braga, J.F.V.; Chanteloup, N.K.; Trotereau, A.; Baucheron, S.; Guabiraba, R.; Ecco, R.; Schouler, C. Diversity of Escherichia coli strains involved in vertebral osteomyelitis and arthritis in broilers in Brazil. BMC Vet. Res. 2016, 12, 140. [Google Scholar] [CrossRef]
  8. Ewers, C.; Li, G.W.; Wilking, H.; Kiessling, S.; Alt, K.; Antao, E.M.; Laturnus, C.; Diehl, I.; Glodde, S.; Homeier, T.; et al. Avian pathogenic, uropathogenic, and newborn meningitis-causing Escherichia coli: How closely related are they? Int. J. Med. Microbiol. 2007, 297, 163–176. [Google Scholar] [CrossRef]
  9. Johnson, J.R.; Johnston, B.; Clabots, C.R.; Kuskowski, M.A.; Roberts, E.; DebRoy, C. Virulence genotypes and phylogenetic background of Escherichia coli serogroup O6 isolates from humans, dogs, and cats. J. Clin. Microbiol. 2008, 46, 417–422. [Google Scholar] [CrossRef] [Green Version]
  10. Ewers, C.; Antao, E.M.; Diehl, I.; Philipp, H.C.; Wieler, L.H. Intestine and environment of the chicken as reservoirs for extraintestinal pathogenic Escherichia coli strains with zoonotic potential. Appl. Environ. Microbiol. 2009, 75, 184–192. [Google Scholar] [CrossRef] [Green Version]
  11. Zhao, L.; Gao, S.; Huan, H.; Xu, X.; Zhu, X.; Yang, W.; Gao, Q.; Liu, X. Comparison of virulence factors and expression of specific genes between uropathogenic Escherichia coli and avian pathogenic E. coli in a murine urinary tract infection model and a chicken challenge model. Microbiology 2009, 155, 1634–1644. [Google Scholar] [CrossRef] [Green Version]
  12. Thomrongsuwannakij, T.; Blackall, P.J.; Djordjevic, S.P.; Cummins, M.L.; Chansiripornchai, N. A comparison of virulence genes, antimicrobial resistance profiles and genetic diversity of avian pathogenic Escherichia coli (APEC) isolates from broilers and broiler breeders in Thailand and Australia. Avian Pathol. 2020, 49, 457–466. [Google Scholar] [CrossRef] [PubMed]
  13. Tivendale, K.A.; Logue, C.M.; Kariyawasam, S.; Jordan, D.; Hussein, A.; Li, G.W.; Wannemuehler, Y.; Nolan, L.K. Avian-pathogenic Escherichia coli strains are similar to neonatal meningitis E. coli strains and are able to cause meningitis in the rat model of human disease. Infect. Immun. 2010, 78, 3412–3419. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Manges, A.R.; Johnson, J.R. Food-borne origins of Escherichia coli causing extraintestinal infections. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 2012, 55, 712–719. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Antao, E.M.; Glodde, S.; Li, G.; Sharifi, R.; Homeier, T.; Laturnus, C.; Diehl, I.; Bethe, A.; Philipp, H.C.; Preisinger, R.; et al. The chicken as a natural model for extraintestinal infections caused by avian pathogenic Escherichia coli (APEC). Microb. Pathog. 2008, 45, 361–369. [Google Scholar] [CrossRef] [PubMed]
  16. Maluta, R.P.; Logue, C.M.; Casas, M.R.; Meng, T.; Guastalli, E.A.; Rojas, T.C.; Montelli, A.C.; Sadatsune, T.; de Carvalho Ramos, M.; Nolan, L.K.; et al. Overlapped sequence types (STs) and serogroups of avian pathogenic (APEC) and human extra-intestinal pathogenic (ExPEC) Escherichia coli isolated in Brazil. PLoS ONE 2014, 9, e105016. [Google Scholar] [CrossRef]
  17. Kohler, C.D.; Dobrindt, U. What defines extraintestinal pathogenic Escherichia coli? Int. J. Med. Microbiol. 2011, 301, 642–647. [Google Scholar] [CrossRef]
  18. Bauchart, P.; Germon, P.; Bree, A.; Oswald, E.; Hacker, J.; Dobrindt, U. Pathogenomic comparison of human extraintestinal and avian pathogenic Escherichia coli search for factors involved in host specificity or zoonotic potential. Microb. Pathog. 2010, 49, 105–115. [Google Scholar] [CrossRef]
  19. Rodriguez-Siek, K.E.; Giddings, C.W.; Doetkott, C.; Johnson, T.J.; Nolan, L.K. Characterizing the APEC pathotype. Vet. Res. 2005, 36, 241–256. [Google Scholar] [CrossRef] [Green Version]
  20. Guabiraba, R.; Schouler, C. Avian colibacillosis: Still many black holes. FEMS Microbiol. Lett. 2015, 362, 23–30. [Google Scholar] [CrossRef]
  21. Vandekerchove, D.; De Herdt, P.; Laevens, H.; Pasmans, F. Risk factors associated with colibacillosis outbreaks in caged layer flocks. Avian Pathol. 2004, 33, 337–342. [Google Scholar] [CrossRef] [Green Version]
  22. Ewers, C.; Janssen, T.; Kiessling, S.; Philipp, H.C.; Wieler, L.H. Rapid detection of virulence-associated genes in avian pathogenic Escherichia coli by multiplex polymerase chain reaction. Avian Dis. 2005, 49, 269–273. [Google Scholar] [CrossRef] [PubMed]
  23. Rodriguez-Siek, K.E.; Giddings, C.W.; Doetkott, C.; Johnson, T.J.; Fakhr, M.K.; Nolan, L.K. Comparison of Escherichia coli isolates implicated in human urinary tract infection and avian colibacillosis. Microbiology 2005, 151, 2097–2110. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Circella, E.; Pennelli, D.; Tagliabue, S.; Camarda, A. Virulence-associated genes in avian pathogenic Escherichia coli from laying hens in Apulia, southern Italy. Br. Poult. Sci. 2012, 53, 465–470. [Google Scholar] [CrossRef] [PubMed]
  25. Kemmett, K.; Humphrey, T.; Rushton, S.; Close, A.; Wigley, P.; Williams, N.J. A longitudinal study simultaneously exploring the carriage of APEC virulence associated genes and the molecular epidemiology of faecal and systemic E. coli in commercial broiler chickens. PLoS ONE 2013, 8, e67749. [Google Scholar] [CrossRef] [Green Version]
  26. Johnson, T.J.; Wannemuehler, Y.; Doetkott, C.; Johnson, S.J.; Rosenberger, S.C.; Nolan, L.K. Identification of minimal predictors of avian pathogenic Escherichia coli virulence for use as a rapid diagnostic tool. J. Clin. Microbiol. 2008, 46, 3987–3996. [Google Scholar] [CrossRef] [Green Version]
  27. Kobayashi, R.K.; Aquino, I.; Ferreira, A.L.; Vidotto, M. ECOR phylogenetic analysis and virulence genotyping of avian pathogenic Escherichia coli strains and Escherichia coli isolates from commercial chicken carcasses in Southern Brazil. Foodborne Pathog. Dis. 2011, 8, 631–634. [Google Scholar] [CrossRef]
  28. Hussein, A.H.; Ghanem, I.A.; Eid, A.A.; Ali, M.A.; Sherwood, J.S.; Li, G.; Nolan, L.K.; Logue, C.M. Molecular and phenotypic characterization of Escherichia coli isolated from broiler chicken flocks in Egypt. Avian Dis. 2013, 57, 602–611. [Google Scholar] [CrossRef]
  29. Dissanayake, D.R.; Octavia, S.; Lan, R. Population structure and virulence content of avian pathogenic Escherichia coli isolated from outbreaks in Sri Lanka. Vet. Microbiol. 2014, 168, 403–412. [Google Scholar] [CrossRef]
  30. De Oliveira, A.L.; Rocha, D.A.; Finkler, F.; de Moraes, L.B.; Barbieri, N.L.; Pavanelo, D.B.; Winkler, C.; Grassotti, T.T.; de Brito, K.C.; de Brito, B.G.; et al. Prevalence of ColV plasmid-linked genes and in vivo pathogenicity of avian strains of Escherichia coli. Foodborne Pathog. Dis. 2015, 12, 679–685. [Google Scholar] [CrossRef]
  31. McPeake, S.J.; Smyth, J.A.; Ball, H.J. Characterisation of avian pathogenic Escherichia coli (APEC) associated with colisepticaemia compared to faecal isolates from healthy birds. Vet. Microbiol. 2005, 110, 245–253. [Google Scholar] [CrossRef]
  32. Schouler, C.; Schaeffer, B.; Bree, A.; Mora, A.; Dahbi, G.; Biet, F.; Oswald, E.; Mainil, J.; Blanco, J.; Moulin-Schouleur, M. Diagnostic strategy for identifying avian pathogenic Escherichia coli based on four patterns of virulence genes. J. Clin. Microbiol. 2012, 50, 1673–1678. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Kwon, S.-G.; Cha, S.-Y.; Choi, E.-J.; Kim, B.; Song, H.-J.; Jang, H.-K. Epidemiological prevalence of avian pathogenic Escherichia coli differentiated by multiplex PCR from commercial chickens and hatchery in Korea. J. Bacteriol. Virol. 2008, 38, 179–188. [Google Scholar] [CrossRef] [Green Version]
  34. Kabir, S.M.L. Avian colibacillosis and salmonellosis: A closer look at epidemiology, pathogenesis, diagnosis, control and public health concerns. Int. J. Environ. Res. Public Health 2010, 7, 89–114. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Leitner, G.; Heller, E.D. Colonization of Escherichia coli in young turkeys and chickens. Avian Dis. 1992, 36, 211–220. [Google Scholar] [CrossRef]
  36. Gross, W.B.; Siegel, P.B. Why some get sick. J. Appl. Poult. Res. 1997, 6, 453–460. [Google Scholar] [CrossRef]
  37. Ibrahim, R.A.; Cryer, T.L.; Lafi, S.Q.; Basha, E.-A.; Good, L.; Tarazi, Y.H. Identification of Escherichia coli from broiler chickens in Jordan, their antimicrobial resistance, gene characterization and the associated risk factors. Vet. Res. BMC 2019, 15, 159. [Google Scholar] [CrossRef]
  38. Wohlsen, T.D. Comparative evaluation of chromogenic agar CM1046 and mFC agar for detection of E. coli and thermotolerant coliform bacteria from water samples. Lett. Appl. Microbiol. 2011, 53, 155–160. [Google Scholar] [CrossRef]
  39. Abraham, S.; Chin, J.; Brouwers, H.J.; Zhang, R.; Chapman, T.A. Molecular serogrouping of porcine enterotoxigenic Escherichia coli from Australia. J. Microbiol. Methods 2012, 88, 73–76. [Google Scholar] [CrossRef]
  40. Chen, J.; Griffiths, M.W. PCR differentiation of Escherichia coli from other gram-negative bacteria using primers derived from the nucleotide sequences flanking the gene encoding the universal stress protein. Lett. Appl. Microbiol. 1998, 27, 369–371. [Google Scholar] [CrossRef]
  41. Fagan, P.K.; Hornitzky, M.A.; Bettelheim, K.A.; Djordjevic, S.P. Detection of shiga-like toxin (stx(1) and stx(2)), intimin (eaeA), and enterohemorrhagic Escherichia coli (EHEC) hemolysin (EHEC hlyA) genes in animal feces by multiplex PCR. Appl. Environ. Microbiol. 1999, 65, 868–872. [Google Scholar] [CrossRef] [Green Version]
  42. Landis, J.R.; Koch, G.G. The Measurement of Observer Agreement for Categorical Data. Biometrics 1977, 33, 159–174. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Rao, J.N.K.; Scott, A.J. The analysis of categorical data from complex surveys: Chi-squared tests for goodness of t and independence in two-way tables. J. Am. Stat. Assoc. 1981, 76, 221–230. [Google Scholar] [CrossRef]
  44. Rao, J.; Scott, A. On simple adjustments to chi-square tests with sample survey data. Ann. Stat. 1987, 15, 385–397. [Google Scholar] [CrossRef]
  45. Skov, T.; Deddens, J.; Petersen, M.; Endahl, L. Prevalence proportion ratios: Estimation and hypothesis testing. Int. J. Epidemiol. 1998, 27, 91–95. [Google Scholar] [CrossRef] [PubMed]
  46. Barros, A.; Hirakata, V. Alternatives for logical regression in cross-sectional studies: An empirical comparison of models that directly estimate tthe prevalence ratio. BMC Med. Res. Methodol. 2003, 3, 21. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Steyerberg, E.W.; Eijkemans, M.J.; Harrell, F.E., Jr.; Habbema, J.D.F. Prognostic modeling with logistic regression analysis: In search of a sensible strategy in small data sets. Med. Decis. Mak. 2001, 21, 45–56. [Google Scholar] [CrossRef]
  48. Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 1974, 19, 716–723. [Google Scholar] [CrossRef]
  49. Akaike, H. Information theory and an extension of the maximum likelihood principle. In Proceedings of the Second International Symposium on Information Theory, Tsahkadsor, Armenia, 2–8 September 1971; Akademiai Kiado: Budapest, Hungary, 1973; pp. 267–281. [Google Scholar]
  50. Dohoo, I.; Martin, S.W.; Stryhn, H. Veterinary Epidemiologic Research/Ian Dohoo, Wayne Martin, Henrik Stryhn, 2nd ed.; Charlotte, P.E.I., Ed.; VER, Inc.: Charlottetown, PE, Canada, 2009. [Google Scholar]
  51. Hosmer, J.M.; Steiner, A.A.; Lopes, L.B. Lamellar liquid crystalline phases for cutaneous delivery of paclitaxel: Impact of the monoglyceride. Pharm. Res. 2013, 30, 694–706. [Google Scholar] [CrossRef]
  52. Wang, Y.; Jiang, Z.; Jin, Z.; Tan, H.; Xu, B. Risk factors for infectious diseases in backyard poultry farms in the Poyang Lake area, China. PLoS ONE 2013, 8, e67366. [Google Scholar] [CrossRef]
  53. Mbanga, J.; Nyararai, Y.O. Virulence gene profiles of avian pathogenic Escherichia coli isolated from chickens with colibacillosis in Bulawayo, Zimbabwe. Onderstepoort J. Vet. Res. 2015, 82, 840–850. [Google Scholar] [CrossRef] [Green Version]
  54. Hasan, B.; Faruque, R.; Drobni, M.; Waldenstrom, J.; Sadique, A.; Ahmed, K.U.; Islam, Z.; Parvez, M.B.H.; Olsen, B.; Alam, M. High prevalence of antibiotic resistance in pathogenic Escherichia coli from large- and small-scale poultry farms in Bangladesh. Avian Dis. 2011, 55, 689–692. [Google Scholar] [CrossRef] [PubMed]
  55. Vandekerchove, D.; Herdt, P.D.; Laevens, H.; Butaye, P.; Meulemans, G.; Pasmans, F. Significance of interactions between Escherichia coli and respiratory pathogens in layer hen flocks suffering from colibacillosis-associated mortality. Avian Pathol. 2004, 33, 298–302. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Shobrak, M.Y.; Abo-Amer, A.E. Role of wild birds as carriers of multi-drug resistant Escherichia coli and Escherichia vulneris. Braz. J. Microbiol. Publ. Braz. Soc. Microbiol. 2014, 45, 1199–1209. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Amaral, L.D. Drinking water as a risk factor to poultry health. Rev. Bras. Ciência Avícola 2004, 6, 191–199. [Google Scholar] [CrossRef]
  58. Dhillon, A.S.; Jack, O.K. Two outbreaks of colibacillosis in commercial caged layers. Avian Dis. 1996, 40, 742–746. [Google Scholar] [CrossRef]
  59. Coleman, B.L.; Salvadori, M.I.; McGeer, A.J.; Sibley, K.A.; Neumann, N.F.; Bondy, S.J.; Gutmanis, I.A.; McEwen, S.A.; Lavoie, M.; Strong, D.; et al. The role of drinking water in the transmission of antimicrobial-resistant E. coli. Epidemiol. Infect. 2012, 140, 633–642. [Google Scholar] [CrossRef] [Green Version]
  60. Whiley, H.; van den Akker, B.; Giglio, S.; Bentham, R. The role of environmental reservoirs in human campylobacteriosis. Int. J. Environ. Res. Public Health 2013, 10, 5886–5907. [Google Scholar] [CrossRef] [Green Version]
  61. Arsenault, J.; Letellier, A.; Quessy, S.; Normand, V.; Boulianne, M. Prevalence and risk factors for Salmonella spp. and Campylobacter spp. caecal colonization in broiler chicken and turkey flocks slaughtered in Quebec, Canada. Prev. Vet. Med. 2007, 81, 250–264. [Google Scholar] [CrossRef]
  62. El Houadfi, M.; Fellahi, S.; Nassik, S.; Guerin, J.L.; Ducatez, M.F. First outbreaks and phylogenetic analyses of avian influenza H9N2 viruses isolated from poultry flocks in Morocco. Virol. J. 2016, 13, 140–147. [Google Scholar] [CrossRef] [Green Version]
  63. Nather, G.; Alter, T.; Martin, A.; Ellerbroek, L. Analysis of risk factors for Campylobacter species infection in broiler flocks. Poult. Sci. 2009, 88, 1299–1305. [Google Scholar] [CrossRef]
  64. Vandeplas, S.; Dubois Dauphin, R.; Beckers, Y.; Thonart, P.; Thewis, A. Salmonella in chicken: Current and developing strategies to reduce contamination at farm level. J. Food Prot. 2010, 73, 774–785. [Google Scholar] [CrossRef] [PubMed]
  65. Henry, I.; Reichardt, J.; Denis, M.; Cardinale, E. Prevalence and risk factors for Campylobacter spp. in chicken broiler flocks in Reunion Island (Indian Ocean). Prev. Vet. Med. 2011, 100, 64–70. [Google Scholar] [CrossRef] [PubMed]
  66. Newell, D.; Elvers, K.; Dopfer, D.; Hansson, I.; Jones, P.; James, S.; Gittins, J.; Stern, N.; Davies, R.; Connerton, I. Biosecurity-based interventions and strategies to reduce Campylobacter spp. on poultry farms. Appl. Environ. Microbiol. 2011, 77, 8605–8614. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Cortes, P.; Blanc, V.; Mora, A.; Dahbi, G.; Blanco, J.E.; Blanco, M.; Lopez, C.; Andreu, A.; Navarro, F.; Alonso, M.P.; et al. Isolation and characterization of potentially pathogenic antimicrobial-resistant Escherichia coli strains from chicken and pig farms in Spain. Appl. Environ. Microbiol. 2010, 76, 2799–2805. [Google Scholar] [CrossRef] [Green Version]
  68. Anza, I.; Vidal, D.; Laguna, C.; Diaz-Sanchez, S.; Sanchez, S.; Chicote, A.; Florin, M.; Mateo, R. Eutrophication and bacterial pathogens as risk factors for avian botulism outbreaks in wetlands receiving effluents from urban wastewater treatment plants. Appl. Environ. Microbiol. 2014, 80, 4251–4259. [Google Scholar] [CrossRef] [Green Version]
  69. Sola-Gines, M.; Cameron-Veas, K.; Badiola, I.; Dolz, R.; Majo, N.; Dahbi, G.; Viso, S.; Mora, A.; Blanco, J.; Piedra-Carrasco, N.; et al. Diversity of multi-drug resistant avian pathogenic Escherichia coli (APEC) causing outbreaks of colibacillosis in broilers during 2012 in Spain. PLoS ONE 2015, 10, e0143191. [Google Scholar] [CrossRef] [Green Version]
  70. Belanger, L.; Garenaux, A.; Harel, J.; Boulianne, M.; Nadeau, E.; Dozois, C.M. Escherichia coli from animal reservoirs as a potential source of human extraintestinal pathogenic E. coli. Fems Immunol. Med. Microbiol. 2011, 62, 1–10. [Google Scholar] [CrossRef] [Green Version]
  71. Cho, S.H.; Lim, Y.S.; Kang, Y.H. Comparison of Antimicrobial Resistance in Escherichia coli Strains Isolated From Healthy Poultry and Swine Farm Workers Using Antibiotics in Korea. Osong Public Health Res. Perspect. 2012, 3, 151–155. [Google Scholar] [CrossRef] [Green Version]
  72. Lynne, A.M.; Kariyawasam, S.; Wannemuehler, Y.; Johnson, T.J.; Johnson, S.J.; Sinha, A.S.; Lynne, D.K.; Moon, H.W.; Jordan, D.M.; Logue, C.M.; et al. Recombinant Iss as a potential vaccine for avian colibacillosis. Avian Dis. 2012, 56, 192–199. [Google Scholar] [CrossRef] [Green Version]
  73. Ge, X.Z.; Jiang, J.; Pan, Z.; Hu, L.; Wang, S.; Wang, H.; Leung, F.C.; Dai, J.; Fan, H. Comparative genomic analysis shows that avian pathogenic Escherichia coli isolate IMT5155 (O2:K1:H5; ST complex 95, ST140) shares close relationship with ST95 APEC O1:K1 and human ExPEC O18:K1 strains. PLoS ONE 2014, 9, e112048. [Google Scholar] [CrossRef] [Green Version]
  74. East, I.J. Adoption of biosecurity practices in the Australian poultry industries. Aust. Vet. J. 2007, 85, 107–112. [Google Scholar] [CrossRef] [PubMed]
  75. Keawcharoen, J.; van Riel, D.; van Amerongen, G.; Bestebroer, T.; Beyer, W.E.; van Lavieren, R.; Osterhaus, A.D.; Fouchier, R.A.; Kuiken, T. Wild ducks as long-distance vectors of highly pathogenic avian influenza virus (H5N1). Emerg. Infect. Dis. 2008, 14, 600–607. [Google Scholar] [CrossRef] [PubMed]
  76. Oh, J.Y.; Kwon, Y.K.; Tamang, M.D.; Jang, H.K.; Jeong, O.M.; Lee, H.S.; Kang, M.S. Plasmid-mediated quinolone resistance in isolates from wild birds and chickens in South Korea. Microb. Drug Resist. 2016, 22, 69–79. [Google Scholar] [CrossRef] [PubMed]
  77. Darrell, W.T. Integrated farm management to prevent Salmonella Enteritidis contamination of eggs. J. Appl. Poult. Res. 2014, 23, 353–365. [Google Scholar] [CrossRef]
Poultry 01 00009 g001 550
Figure 1. Frequency of meat farms with the number of meat chickens that tested as avian pathogenic E. coli (APEC) positive (out of 10 birds sampled per farm) in Queensland.
Figure 1. Frequency of meat farms with the number of meat chickens that tested as avian pathogenic E. coli (APEC) positive (out of 10 birds sampled per farm) in Queensland.
Poultry 01 00009 g001
Table
Table 1. Agreement, kappa statistics and p-value for the detection of APEC virulence genes after selecting five or ten E. coli colonies cultured from meat chickens from Queensland.
Table 1. Agreement, kappa statistics and p-value for the detection of APEC virulence genes after selecting five or ten E. coli colonies cultured from meat chickens from Queensland.
Virulence GenesObserved
Agreement %		Expected
Agreement %		Kappap-Value
iutA97.588.250.787<0.001
Iss97.569.50.918<0.001
hlyF92.579.750.629<0.001
ompT92.583.750.539<0.001
iroN97.572.750.908<0.001
Table
Table 2. The prevalence of five virulence genes (VGs) with 95% confidence interval (CI) among 252 avian pathogenic Escherichia coli (APEC) positive chickens and 148 APEC negative chickens that were sampled between October 2013 and July 2014 from commercial meat chicken farms in Queensland.
Table 2. The prevalence of five virulence genes (VGs) with 95% confidence interval (CI) among 252 avian pathogenic Escherichia coli (APEC) positive chickens and 148 APEC negative chickens that were sampled between October 2013 and July 2014 from commercial meat chicken farms in Queensland.
Virulence
Gene		Number of
E. coli Isolates with VG.		Number of APEC with VG.Number of AFEC with VG.Prevalence of VG in APEC Positive Chickens
(95% Cl)		Prevalence of VG in APEC Negative Chickens
(95% Cl)		p-Value
iss269250 19 99.2 (0.97, 0.99)12.8 (7.52, 20.1)<0.001
iroN259248 11 98.4 (0.95, 0.99)7.4 (3.52, 14.3)<0.001
ompT322252 70 10047.3 (0.34, 0.58)<0.001
hlyF31825167 99.6 (0.97, 0.99)45.3 (31.4, 57.6)<0.001
iutA351237 114 94.1 (0.90, 0.97)77.0 (63.9, 84.5)<0.001
Table
Table 3. Univariate analysis of possible farm-level risk factors associated (p-value < 0.15) with decreased within-farm prevalence of avian pathogenic E. coli (APEC). Data were collected from commercial meat chicken farms in Queensland between October 2013 and July 2014. Risk factor coefficients are presented as odds ratios (OR) with 95% confidence intervals (CI). The number (N) of farms represents the number of meat farms that possess or do not possess the risk factor of interest. APEC prevalence represents the mean number of APEC positive birds within the farms that have or do not have the risk factor of interest.
Table 3. Univariate analysis of possible farm-level risk factors associated (p-value < 0.15) with decreased within-farm prevalence of avian pathogenic E. coli (APEC). Data were collected from commercial meat chicken farms in Queensland between October 2013 and July 2014. Risk factor coefficients are presented as odds ratios (OR) with 95% confidence intervals (CI). The number (N) of farms represents the number of meat farms that possess or do not possess the risk factor of interest. APEC prevalence represents the mean number of APEC positive birds within the farms that have or do not have the risk factor of interest.
Risk Factor GroupNumber (%)APEC PrevalenceOR (95% CI)p-ValueWald Test
p-Value
Separate age groups of birds housed in a farm at the same time
No10 (25)0.62Reference
Yes30 (75)0.460.52 (0.32–0.82)0.005
Drinking water treatment 0.01
None10 (25)0.53Reference
Chlorine28 (70)0.510.94 (0.44–1.99)0.87
Chlorine and automatic water filtration2 (5)0.100.09 (0.05–0.19)0.01
Number of days per week external (casual) farmworkers were present on the farm 0.01
None16 (40)0.59Reference
Category 1 ≤ 5 days9 (22.5)0.430.52 (0.31–0.88)0.02
Category 2 > 5 days15 (37.5)0.430.52 (0.33–0.82)0.01
Use of protective overalls by farmworkers
Never39 (97.5)0.50Reference
Always1 (2.5)0.400.67 (0.48–0.93)0.02
Table
Table 4. Univariate analysis of possible farm-level risk factors associated (p-value < 0.15) with an increased within-farm prevalence of avian pathogenic E. coli (APEC). Data were collected from commercial meat chicken farms in Queensland between October 2013 and July 2014. Risk factor coefficients are presented as odds ratios (OR) with 95% confidence intervals (CI). The number (N) of farms represents the number of meat farms that possess or do not possess the risk factor of interest. APEC prevalence represents the mean number of APEC positive birds within the farms that have or do have not the risk factor of interest.
Table 4. Univariate analysis of possible farm-level risk factors associated (p-value < 0.15) with an increased within-farm prevalence of avian pathogenic E. coli (APEC). Data were collected from commercial meat chicken farms in Queensland between October 2013 and July 2014. Risk factor coefficients are presented as odds ratios (OR) with 95% confidence intervals (CI). The number (N) of farms represents the number of meat farms that possess or do not possess the risk factor of interest. APEC prevalence represents the mean number of APEC positive birds within the farms that have or do have not the risk factor of interest.
Risk FactorsNumber of Farms (%)APEC PrevalenceOR (95% CI)p-ValueWald Test
p-Value
The usage of water well as a source of drinking water
No37 (92.5)0.48Reference
Yes3 (7.5)0.661.81 (1.19, 2.74)0.005
The animal species found outside the shed
None39 (97.5)0.49Reference
Horses1 (2.5)0.899.47 (6.88, 13.0)0.03
Availability of a shower facility on the farm
Yes7 (17.5)0.37Reference
No33 (82.5)0.521.86 (1.09, 3.17)<0.001
Frequency of water line disinfection after each flock
Always21 (52.5)0.43Reference
Often19 (47.5)0.571.72 (1.16, 2.56)0.007
The mortality variations between the sheds within the last 12 months
No9 (22.5)0.39Reference
Yes31 (77.5)0.531.77 (0.88, 3.55)0.10
Presence of wild birds within 50 m of the meat shed(s)
No17 (42.5)0.49 Reference
Yes23 (57.5)0.511.15 (0.63, 1.45)0.11
Number of rats outside the shed within 50 m
None8 (20)0.33Reference 0.01
Category 1 ≤ 56 (15)0.461.27 (0.85, 1.91)0.24
Category 2 > 526 (65)0.563.39 (2.26, 5.10)0.01
Distance between the car park and the shed
Category 1 ≤ 20 m23 (57.5)0.44Reference0.007
Category 2 > 20 m17 (42.5)0.581.73 (1.16, 2.59)
Table
Table 5. Final multivariable model of possible farm-level risk factors associated (p-value < 0.05) with a within-farm prevalence of avian pathogenic E. coli (APEC). Data were collected from commercial meat chicken farms in Queensland between October 2013 and July 2014. Risk factor coefficients are presented as odds ratios (OR) with 95% confidence intervals (CI). The number (N) of farms represents the number of meat farms that possess or do not possess the risk factor of interest. APEC prevalence represents the mean number of APEC positive birds within the farms that do not have the risk factor of interest.
Table 5. Final multivariable model of possible farm-level risk factors associated (p-value < 0.05) with a within-farm prevalence of avian pathogenic E. coli (APEC). Data were collected from commercial meat chicken farms in Queensland between October 2013 and July 2014. Risk factor coefficients are presented as odds ratios (OR) with 95% confidence intervals (CI). The number (N) of farms represents the number of meat farms that possess or do not possess the risk factor of interest. APEC prevalence represents the mean number of APEC positive birds within the farms that do not have the risk factor of interest.
Risk FactorsNumber of Farms (%)APEC PrevalenceOR (95% CI)p-ValueWald Test
p-Value
The usage of a water well as a source of drinking water
No 37 (92.5)0.48
Yes3 (7.5)0.666.20 (2.32, 16.5)<0.001
Drinking water treatment 0.01
None10 (25)0.53
Chlorine only28 (70)0.510.77 (0.46, 1.26)0.317
Chlorine and automatic water filtration 2 (5)0.100.07 (0.02, 0.34)0.001
Distance between the car park and the shed
Category 1 ≤ 20 m23 (57.50)0.44
Category 2 > 20 m17 (42.5)0.582.16 (1.38, 3.38)0.001
Availability of a shower facility on the farm
Yes7 (17.5)0.37
No33 (82.5)0.523.59 (1.75, 7.11)<0.001
Frequency of water line disinfection after each flock
Always21 (52.5)0.43
Often19 (47.5)0.572.21 (1.41, 3.47)0.001
Presence of wild birds within 50 m of the broiler shed(s)
No17 (42.5)0.49
Yes23 (57.5)0.512.28 (1.39, 3.72)0.001
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Awawdeh, L.; Forrest, R.; Turni, C.; Cobbold, R.; Henning, J.; Gibson, J. Risk Factors Associated with the Carriage of Pathogenic Escherichia coli in Healthy Commercial Meat Chickens in Queensland, Australia †. Poultry 2022, 1, 94-110. https://doi.org/10.3390/poultry1020009

AMA Style

Awawdeh L, Forrest R, Turni C, Cobbold R, Henning J, Gibson J. Risk Factors Associated with the Carriage of Pathogenic Escherichia coli in Healthy Commercial Meat Chickens in Queensland, Australia †. Poultry. 2022; 1(2):94-110. https://doi.org/10.3390/poultry1020009

Chicago/Turabian Style

Awawdeh, Leena, Rachel Forrest, Conny Turni, Rowland Cobbold, Joerg Henning, and Justine Gibson. 2022. "Risk Factors Associated with the Carriage of Pathogenic Escherichia coli in Healthy Commercial Meat Chickens in Queensland, Australia †" Poultry 1, no. 2: 94-110. https://doi.org/10.3390/poultry1020009

APA Style

Awawdeh, L., Forrest, R., Turni, C., Cobbold, R., Henning, J., & Gibson, J. (2022). Risk Factors Associated with the Carriage of Pathogenic Escherichia coli in Healthy Commercial Meat Chickens in Queensland, Australia †. Poultry, 1(2), 94-110. https://doi.org/10.3390/poultry1020009

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