Dynamics of Salmonella Shedding andWelfare of Hens in Free-Range EggProduction Systems

Vaibhav C. Gole,a Rebecca Woodhouse,b Charles Caraguel,a Talia Moyle,a

Jean-Loup Rault,b Margaret Sexton,c Kapil Chousalkara

School of Animal and Veterinary Science, University of Adelaide, Roseworthy, South Australia, Australiaa;Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, Victoria, Australiab;Biosecurity SA, Primary Industries and Regions SA, Adelaide, South Australia, Australiac

ABSTRACT The current study investigated the effect of environmental stressors (i.e.,weather changes) on Salmonella shedding in free-range production systems and thecorrelations with behavioral and physiological measures (i.e., fecal glucocorticoidmetabolites). This involved longitudinal and point-in-time surveys of Salmonellashedding and environmental contamination on four commercial free-range layerfarms. The shedding of Salmonella was variable across free-range farms and in differ-ent seasons. There was no significant effect of season on the Salmonella prevalenceduring this investigation. In this study, the combined Salmonella most probablenumber (MPN) counts in environmental (including feces, egg belt, dust, nest box,and ramp) samples were highest in samples collected during the summer season(4th sampling, performed in February). The predominant serovars isolated duringthis study were Salmonella enterica serovar Mbandaka and Salmonella enterica sero-var Typhimurium phage types 135 and 135a. These two phage types were involvedin several egg product-related Salmonella outbreaks in humans. Multilocus variable-number tandem-repeat analysis (MLVA) results indicated that MLVA types detectedfrom human food poisoning cases exhibited MLVA patterns similar to the strains iso-lated during this study. All Salmonella isolates (n � 209) were tested for 15 differentgenes involved in adhesion, invasion, and survival of Salmonella spp. We also ob-served variations for sopA, ironA, and misL. There were no positive correlationsbetween fecal corticosterone metabolite (FCM) and Salmonella prevalence and/orshedding in feces. Also, there were no positive correlations between Salmonella preva-lence and Salmonella count (log MPN) and any of the other welfare parameters.

IMPORTANCE In this study, the welfare of laying hens and Salmonella sheddingwere compared over a prolonged period of time in field conditions. This study in-vestigated the long-term shedding of Salmonella serovars in a free-range egg pro-duction system. Given that there is increasing demand for free-range eggs, it is es-sential to understand the risks associated with such a production system.

KEYWORDS eggs, free range, hens, Salmonella, welfare

In Australia and the rest of the world, there has been an increase in egg productionover the last decade. The Australian egg industry produced 421.3 million dozen eggs

in 2015, and per capita consumption of the eggs increased to 226 eggs (1). Consumerpreferences focus on perceived animal welfare and the environmentally friendly pro-duction of eggs. As a result, the free-range production system is becoming a majorsource of egg production in Australia and in other parts of the world. In Australia,free-range and conventional cage eggs have a market share of 49% and 39% by value(39% and 51% by volume), respectively (1). Challenging aspects of the free-rangeproduction system involve implementing biosecurity and controlling environmental

Received 6 December 2016 Accepted 13December 2016

Accepted manuscript posted online 30December 2016

Citation Gole VC, Woodhouse R, Caraguel C,Moyle T, Rault J-L, Sexton M, Chousalkar K.2017. Dynamics of Salmonella shedding andwelfare of hens in free-range egg productionsystems. Appl Environ Microbiol 83:e03313-16.https://doi.org/10.1128/AEM.03313-16.

Editor Edward G. Dudley, The PennsylvaniaState University

Copyright © 2017 American Society forMicrobiology. All Rights Reserved.

Address correspondence to Kapil Chousalkar,kapil.chousalkar@adelaide.edu.au.

V.C.G., R.W., C.C., T.M., J.-L.R., M.S., and K.C.contributed equally to this article.

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stressors. Free-range hens are exposed to more environmental stressors, such asextreme weather conditions, predation, exposure to wild birds, and aggression, incomparison with hens from barn and cage systems (2–4). The findings from a recentAustralian survey revealed that free-range egg producers imputed financial losses toheat stress, cannibalism, grass impaction, diseases, and malnutrition (5). According tothis free-range survey, Australian free-range hens face extremely hot (�40°C, 16% ofrespondents) or cold (�0 to 10°C, 64% of respondents) temperatures on the range (6).

The exposure to extreme weather conditions might be stressful for birds and mayincrease the environmental shedding of bacteria. These factors may result in anincreasing bacterial contamination of eggs. Higher bacterial loads on eggs may lead toincreases in food poisoning outbreaks. Earlier studies reported increasing humanSalmonella enterica serovar Typhimurium notifications with increasing temperaturesduring the warm season (7). In recent decades, foodborne illness has emerged as aserious problem throughout the world. In 2015, in Australia and the United States, theincidences of Salmonella notifications were 72.6 and 15.8 per 100,000 people, respec-tively (8, 9). Although there was a decreasing incidence of salmonellosis from 2008 to2014 in the European Union, there was a 15.3% increase in the rate of Salmonellainfections in 2014 compared with that in 2013 (10). Many salmonellosis outbreaks weretraced back to raw egg products contaminated with Salmonella.

A previous epidemiology study in cage production systems found that the odds ofan eggshell testing positive for Salmonella were higher when the environmentalsamples, such as fecal, egg belt, and dust samples, tested positive for Salmonella (11).However, little attention has been given to estimating the prevalence of Salmonella oneggs collected from free-range production systems or to determining the factorsresponsible for contamination. To maintain body temperature, birds maintain homeo-stasis through behavioral and physiological changes. High environmental stressorsaffect the neuroendocrine system of poultry, ultimately increasing plasma corticoste-rone levels (12). Hence, the current study investigated the effect of environmentalstressors (i.e., weather changes) on Salmonella shedding in free-range productionsystems and the correlations with behavioral (i.e., panting and ranging activity) andphysiological measures (i.e., fecal glucocorticoid metabolites).

RESULTSSelection of sampling areas for cross-sectional study. Culture isolation results

indicated that, in all four flocks, 51 samples (32.28%; confidence interval [CI], 25.47 to39.93) were positive for Salmonella spp. (Fig. 1). Flock B had the highest prevalence ofSalmonella-positive samples (75.00%; CI, 61.67 to 84.89) followed by flock C (21.15%, CI,12.08 to 34.20). On other hand, only one sample in flock A was Salmonella positive, andall samples collected from flock D were negative.

For each positive sample, three colonies were isolated and sent for serotyping. AllSalmonella isolates from flock A were Salmonella enterica serovar Mbandaka. Serovarsisolated from flock B were serovars Mbandaka and Agona, whereas flock C sampleswere positive for serovars Mbandaka, Anatum, and Worthington. Based on the preva-lence result from the cross-sectional study (Fig. 1), different areas of the sheds wereselected for longitudinal sampling.

Salmonella prevalence in flock A, B, C and D in longitudinal study. In thelongitudinal study during the period of samplings, the highest prevalence of Salmonellawas observed in flock C (environmental samples: 29.89%, CI, 25.50 to 34.70; egg shells:5%, CI, 2.93 to 8.29), followed by flock D (environmental samples: 3.97%, CI, 2.37 to 6.50;egg shells: 0%, CI, 0 to 1.63), flock A (environmental samples: 1.85%, CI, 0.82 to 3.85; eggshells: 0.36%, CI, 0 to 2.20), and flock B (environmental samples: 1.85%, CI, 0.82 to 3.85;egg shells: 0%, CI, 0 to 1.63). The overall prevalence of Salmonella in environmentalsamples was 9.39% with a CI of 8.02 to 10.97. The overall prevalence of Salmonella onegg shells (including clean and floor eggs) was 1.34% with a CI of 0.79 to 2.22. Overall(all flocks combined), the Salmonella prevalence was higher in dust samples (14.19%, CI,10.64 to 18.90) than in shoe covers out on ranges (12.50%, CI, 5.88 to 23.93), feces

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(11.79%, CI, 8.48 to 16.12), ramps (8.21% CI, 5.49 to 12.07), nest boxes (7.86%, CI, 5.20to 11.66), egg belts (5.36%, CI, 3.21 to 8.72), shoe covers inside sheds (3.57%, CI, 0.28to 12.82), floor eggshells (3.57%, CI, 1.87 to 6.53), and eggshells (0.6%, CI, 0.21 to 1.43).All internal content samples from table and floor eggs were Salmonella negative. Theprevalences of Salmonella in different types of samples from flocks A, B, C, and D areshown in Tables S1, S2, S3, and S4 in the supplemental material.

In flock A, the prevalences of Salmonella were similar in dust, feces, and nest boxsamples (2.85%), followed by egg belts (1.42%). In this flock, only one eggshell wasSalmonella positive. All other samples, such as ramps, shoe covers inside sheds and outon ranges, and floor eggshells, were Salmonella negative. The log most probablenumber (MPN) values for dust (0.36 � 0.1 per/m2 of swab) and feces (0.3 � 0.1 per g)were highest during the 5th sample collection (performed in March 2015) (Fig. 2).

In flock B, the highest prevalence of Salmonella was in shoe covers out on the ranges(7.41%), followed by feces (5.71%), nest boxes, and ramps (1.43%). All eggshells andfloor eggshells were Salmonella negative. The log MPN values for feces (0.77 � 0.1 perg) and shoe cover samples collected from ranging areas (0.68 � 0.1 per pair of shoecovers) were highest during the 2nd sample collection (performed in November 2014)(Fig. 3).

The highest numbers of samples that were Salmonella positive were from flock C.From the 4th sampling, there was an increasing prevalence of Salmonella in all types ofsamples, but it was highest in dust samples (48.57%). This was followed by feces(35.71%), shoe covers outside ranges (28.57%), ramps (25.71%), nest boxes (25.71%),egg belts (17.14%), and shoe covers inside sheds (14.28%). Flock C had the highestnumber of floor eggshells (14.28%) that were Salmonella positive compared with thosefrom the other flocks. Of all the table eggs collected during sampling periods from flockC, 1.90% (4/840) were Salmonella positive. The log MPN values for dust (5.8 � 0.1

FIG 1 Percentages of various locations within the sheds that were positive for Salmonella spp. during thecross-sectional sampling.

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per/m2 of swab) and nest boxes (3.7 � 0.1 per g of feces) were highest during the 4thsample collection (performed in February 2015) (Fig. 4). During the 5th sample collec-tion (performed in March 2015), the level of Salmonella was highest in swabs collectedfrom ramps (4.8 � 0.1 per/m2 of swab). The level of Salmonella on egg shells during thissample collection was 1.71 � 0.1 per egg.

In contrast, in flock D, all eggshells, floor eggshells, and ramp samples wereSalmonella negative. The highest prevalence was observed in shoe covers from ranges(14.28%), followed by dust (5.71%), ramp (5.71%), feces (2.85%), egg belt (2.85%), andnest box (1.43) samples. The level of Salmonella was highest (log MPN 0.70 � 0.1) at the5th sampling point (conducted in March 2015) in swabs collected from ramps (Fig. 5).

Overall, the Salmonella MPN values were highest for swabs collected from ramps atthe 3rd and 5th sampling points, whereas the Salmonella MPN was highest for dustswabs collected at the 5th sampling point (see Fig. S1).

In total, 209 Salmonella isolates were obtained from all samples types during thislongitudinal study. Salmonella serotyping suggested that the four farms selected in thisstudy were positive for S. Mbandaka (64.5%), Typhimurium phage type 135 (24.4%),Agona (5.7%), Infantis (1.4%), Anatum (0.95%), Worthington (0.95%), Singapore (0.47%),subspecies 1 serovar 4,5,12:i:� (0.47%), and subspecies 1 serovar rough:f,g,s:� (0.47%).

FIG 2 Log MPN values in different samples collected at different sampling points in Flock A.

FIG 3 Log MPN values in different samples collected at different sampling points in Flock B.

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Figure 6 provides the percentage of various Salmonella serovars isolated from differenttype of samples.

Salmonella Typhimurium MLVA typing. S. Typhimurium strains were isolated fromflocks C and D. In flock C, S. Typhimurium was detected in all shoe covers collected fromoutdoor ranges. At the 6th sampling point, out of all Salmonella-positive dust and fecalsamples, 70% and 60%, respectively, were S. Typhimurium (see Fig. S2). In flock D, S.Typhimurium was isolated from all shoe covers collected from outdoor ranges duringthe 6th and 7th sample collections (see Fig. S3l). Multilocus variable-number tandem-repeat analysis (MLVA) indicated that S. Typhimurium strains isolated from flocks C andD were genetically different. In flock C, the S. Typhimurium phage type 135 possessedthree different MLVA patterns (03 13 10 12 523, 03 14 10 12 523, and 03 14 11 12 523),whereas S. Typhimurium phage type 135a isolated from flock D exhibited two differentMLVA patterns (03 12 09 10 523 and 03 12 09 11 523).

Sampling time and Salmonella shedding. Salmonella shedding was highest indust samples collected during the 4th collection (conducted in February 15) (log MPN,

FIG 4 Log MPN values in different samples collected at different sampling points in Flock C.

FIG 5 Log MPN values in different samples collected at different sampling points in Flock D.

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1.4 � 0.83). The overall Salmonella count was lowest in fecal samples collected duringthe 3rd collection (performed in December 2014/January 2015) (log MPN, 0.0 � 0.0).There was a significant difference between Salmonella counts in fecal samples from the1st and 4th sample collections. There was also a significant difference in SalmonellaMPN values for the 1st and 5th sample collections. S. Typhimurium was isolated fromdifferent samples collected in all seasons.

Fecal glucocorticoid metabolites and relationship with Salmonella shedding.Results showed that fecal glucocorticoid concentrations as measured by the selectedassay increased significantly by 1 h after adrenocorticotropin (ACTH) administration(analysis of variance [ANOVA], time � treatment interaction, P � 0.001, with all post hoccomparisons at P values of �0.01), and returned to concentrations that were notsignificantly different from control hens by 6.5 h after the administration. Hence, thisassay provides valid measurements of glucocorticoid metabolites.

The highest concentration of fecal glucocorticoid metabolites was found in the 1stsampling (268.5 � 22.3 ng/ml). Fecal glucocorticoid metabolite concentrationsdropped significantly in the 2nd (232.2 � 19.3 ng/ml) and 3rd (225.9 � 18.7) samplecollections, and were lowest (186.6 � 15.1 ng/ml) in the last sampling. There was noassociation between fecal glucocorticoid metabolite concentrations and the loads ofSalmonella in feces (Fig. 7).

Other hen welfare parameters and Salmonella shedding. There were no corre-lations between Salmonella shedding or prevalences and comb colors, panting, plum-

FIG 6 Distributions of Salmonella serovars isolated from the current epidemiological investigation.

FIG 7 Levels of fecal corticosterone metabolites at different sampling points.

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age damage, noise levels, novel object tests, distance avoidance tests, or social inter-actions between birds (Table 1).

Presence of virulence genes in different Salmonella serovars. Salmonella sero-vars were screened for different virulence genes that are involved in adhesion, colo-nization, and survival in eggs. The results from PCRs for the presence of various genesare presented in Fig. 8. The majority of the selected virulence genes were detected inmost of the serovars tested. All isolates of S. Mbandaka and S. Worthington werenegative for sptP. sopA was not detected in one isolate of S. Typhimurium, one isolateof S. Infantis, or two isolates of S. Mbandaka (from flock C). One isolate of S. Mbandakawas also negative for iroN and misL.

DISCUSSION

The prevalences and shedding of Salmonella on four commercial free-range farmsacross various seasons were variable. The first cross-sectional study was conducted forselecting sampling sites in the free-range layer sheds. The results of the cross-sectionalstudy performed on four different flocks indicated variable and mixed results fordifferent sites in each flock across the sheds (Fig. 1). Hence, the longitudinal studyinvolved all sites that were sampled during the cross-sectional study.

The shedding of Salmonella varied across free-range farms and during differentseasons. This finding contrasts with an earlier study that found increasing Salmonellashedding over the sampling period (13). There was no significant effect of season onSalmonella prevalence during this study. There was no increase in Salmonella sheddingin the summer season. Earlier, Traub-Dargatz et al. (14) reported that, under experi-mental conditions, heat stress did not influence the levels of Salmonella TyphimuriumDT 104. Previous studies found increasing S. Typhimurium 135- and 135a-relatedhuman cases in the summer (7). These two phage types were isolated predominantlyfrom free-range farms during this study. Our finding regarding high Salmonella shed-ding in summer is in agreement with that of a previous report that detected increasinglevels of Salmonella on farms in the summer (15). During our study, variabilitiesbetween the detected prevalence and shedding were observed between flocks andfarms. This observation is in agreement with previous reports (13, 16). There arenumerous reports on the effects of the housing system on the shedding of Salmonellaspp. (17). In Australia between 2012 and 2014, 213 Salmonella outbreaks were recorded.Of 213 outbreaks, 102 (47%) were attributed to the consumption of egg products.Twenty of 102 (19%) outbreaks were caused by S. Typhimurium phage types 135 and135a (Fig. 9). MLVA results from S. Typhimurium strains isolated from flock C weredistinct from and unrelated to those from flock D. The MLVA pattern of S. Typhimurium(both phage types 135 and 135a) evolved during the sample collection period. Earlier,we found that vectors, such as wild birds and foxes in the close vicinity of free-rangefarms, might play a major role in S. Typhimurium evolution (18). S. Typhimurium strainsdetected from human food poisoning cases exhibited MLVA patterns similar to thestrains isolated from flocks C and D (19, 20) (Table 2). It is not clear why MLVA type 0312 09 11 523 was isolated more frequently (from 59 human cases from 2013 to 2015)

TABLE 1 Comparisons of welfare parameters with Salmonella shedding and prevalence

Welfare measure

P value for Salmonella measure

Prevalencea Count

Panting 0.918 0.057Noise level 0.153 0.567Comb color 0.463 0.057Plumage damage 0.459 0.588Interaction 0.162 0.773Novel object test 0.244 0.364Avoidance distance test 0.968 0.744Pariah N/A 0.762aMeasured by the MPN method. N/A, not available.

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than MLVA type 03 12 09 10 523 isolated from the same flock. Our previous reportsuggested that MLVA profiles of S. Typhimurium isolated from cage farms and humanSalmonellosis cases were similar (11). Although a majority of the previous studies werefocused on S. enterica serovar Enteritidis, the results of these studies were highlyvariable. The contamination of eggs with Salmonella from production to plate is acomplex issue and influenced by different variables, such as flock size, stocking density,flock age, stress, feed, the quality of eggs, disinfection procedures on the farm, thehandling of eggs, storage temperature, the kitchen environment, and kitchen hygiene(21). Jones et al. (22) reported no significant differences in the prevalence of Salmonellabetween free-range and cage production systems. Findings from our study also rein-force the hypothesis that the level of egg contamination may be attributed largely toindividual flock management and/or farm management. There are several possiblesources of Salmonella contamination and/or infection from day-old hens to laying hensat the end of their commercial life span (23). In this study, sampling was conductedfrom week 24 onwards. Hence, further research is required to investigate the longitu-dinal epidemiology of S. Typhimurium from day-old hens to those at the end of their

FIG 8 Distributions of genes tested in different Salmonella serovars isolated in this study. (A) sopA, sopB, sitC, spiC, misL, orfL, pipD; (B) iroN,sipB, sipC, avrA, sptP, hilA, xthA, and yafD.

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commercial life (75 to 80 weeks) in laying flocks on caged and free-range farms.Although such longitudinal investigations are valuable for understanding Salmonella-shedding dynamics, the successes of such studies also depend on the willingness ofproducers to participate.

Currently, there is no nationwide prevalence database of S. Typhimurium on eggfarms. A cross-sectional microbiological survey conducted by New South Wales FoodAuthority on 49 egg farms showed that 28% of the commercial free-range farms werepositive for S. Typhimurium (24), whereas a survey conducted on 21 egg farms by SafeFood Queensland reported that 13.5% of farms were positive for S. Typhimurium (25).Current data suggest that shedding of S. Typhimurium from known-positive hens inboth field conditions is highly variable and can be influenced by the stress experiencedby hens. Cross-sectional sampling may not be sufficient for determining the trueprevalence. Therefore, longitudinal sampling of flocks is essential.

During this study, the prevalence of Salmonella was highest in dust samplesfollowed by those from shoe covers from outdoor ranging areas and in fecal samples.Our results regarding the persistence of Salmonella in dust samples from free-rangeproduction systems are in agreement with those of a previous study (26). The removalof dust by effective cleaning and disinfection of poultry sheds might reduce the levels

FIG 9 Salmonella outbreaks reported in Australia between 2012 and 2014. This information was obtained from OzFoodNet quarterlyreports (2012 to June 2014) (19, 47–55) http://health.gov.au/internet/main/publishing.nsf/Content/cdna-ozfoodnet-reports.htm.

TABLE 2 MLVA types isolated from human cases over three periods in Australiaa

MLVA type

No. of cases

2013 2014 2015 (Jan–June)

03 13 10 12 523 0 0 003 14 10 12 523 0 0 203 14 11 12 523 0 0 1103 12 09 10 523 0 0 103 12 09 11 523 30 17 12aThese MLVA types of S. Typhimurium were also isolated from free-range farms sampled in this study. ThreeMLVA types (03 14 10 12 523, 03 14 11 12 523, and 03 12 09 10 523) were not isolated from human casesin 2013 or 2014. However, these MLVA types started to appear in humans in 2015. This underlines theconnection between the free-range layer industry and the potential threat of Salmonella to public health.Data are from quarterly reports of the Australian Salmonella Reference Centre (2013, 2014, and 2015),Institute of Medical and Veterinary Sciences, SA Pathology, Adelaide, Australia.

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of Salmonella contamination, although the recovery of Salmonella spp. from surfacessuch as floors and dropping boards in cleaned and disinfected houses was variable (27).Salmonella spp., including S. Typhimurium, persisted in ranging areas. In practice, it isdifficult to clean and disinfect ranging areas.

The predominant Salmonella serovars isolated during this study were S. Mbandakaand S. Typhimurium phage type 135. S. Mbandaka was the predominant pathogen inour previous longitudinal study conducted on cage farms (11, 28). S. Mbandaka has notbeen associated with egg-related Salmonella outbreaks in Australia. S. Typhimuriumwas the second most prevalent serovar in this study. This serovar has gained significantpublic attention over the last decade in Australia, as the majority of egg-relatedSalmonella outbreaks are associated with S. Typhimurium and its phage types (29). S.Typhimurium was isolated from all sample types, including egg shell wash, although itspersistence was variable. It has been hypothesized that birds reared on the floor are lesslikely to harbor Salmonella spp. and that microorganisms present in the litter could playa role in competitive exclusion (30). Data from this field study do not support thehypothesis. However, further experimental studies are essential to confirm whethersome Salmonella serovars act as seeding agents for the competitive exclusion of S.Typhimurium. Although the MLVA profiles of S. Typhimurium isolated in this study andfrom egg human outbreaks were similar, further studies are required for understandingthe invasion potential of these isolates. It was demonstrated that the invasive potentialof S. Typhimurium increased after enrichment (31). A hypothesis might be that theinvasive potential of S. Typhimurium is influenced by the available favorable environ-ment at the time of invasion.

The 15 genes analyzed in this study were tested because they are known to beinvolved in adhesion, invasion, and survival of Salmonella spp. The detection ofthese genes by PCR has been widely used as a predictive measure for Salmonellavirulence (32, 33). sptP was not amplified among S. Mbandaka and Worthingtonisolates. We observed variability in the detections of sopA, ironA, and misL. Althoughthe PCR results indicated that some of the Salmonella serovars were negative forthese genes, it is possible that there was sufficient genetic variability preventingprimer annealing and subsequent amplification. Full genome-sequence analysisstudies are essential to investigate genetic variability. Although the health author-ities in Australia are moving toward the whole-genome sequencing approach, PCRtyping of virulence genes can still be used as a preliminary screening tool to selectisolates for whole-genome sequencing. All but two S. Mbandaka isolates recoveredfrom flock C tested positive for sopA. Also, three different MLVA types of S.Typhimurium were detected from flock C during the study period. It is possible thatsome Salmonella isolates either acquired virulence genes or evolved from a morevirulent type (S. Typhimurium, in this case). Previous studies detected virulencegenes in various Salmonella isolates collected from cage farms (31, 34). However,there is limited information on virulence typing of Salmonella serovars collectedfrom free-range environments.

In this study, Salmonella MPN values for environmental (feces, egg belt, dust, nestbox, and ramp) samples were highest in specimens collected during the summerseason (4th sampling, performed in February). A recent study found an increase in casesof human S. Typhimurium phage types 9 and 108 during the warm season (7). It isimportant to note that none of these phage types were isolated in this study. Ourprevious study also indicated high Salmonella counts in feces in summer, with S.Typhimurium phage type 9 as a predominant serovar (18). Human gastrointestinalinfections with Salmonella have been positively correlated with warmer temperatures(35, 36), as warmer temperatures can enhance the replication of bacteria. In this study,S. Typhimurium was detected in environmental samples and egg shell wash. However,their presence did not depend on the time of sampling and/or season. Earlier, Schulzet al. (37) reported that the probability of finding Salmonella spp. on farms did notdepend on the time of sampling or season.

Other serovars, such as Singapore, Anatum, Agona, and Infantis, have also been

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associated with sporadic egg-related Salmonella cases in humans in Australia (38). Theprevalence of these serovars was low in this study. Our previous study indicated thatthe presence of virulence genes may not necessarily dictate the virulence/invasiveability of Salmonella (31). The PCR results indicated that most of the above-listedserovars harbored virulence genes, but in vivo studies are required to study theirvirulence potential.

In this study, there were no correlations between fecal corticosterone metabolite(FCM) and Salmonella prevalence and/or shedding in feces. This observation is consis-tent with our previous finding (18). There are limited reports of FCM levels andSalmonella shedding in laying hens. The measurement of FCM is an establishednoninvasive method for measuring adrenocortical activity in chickens (39) as an indi-cation of the hypothalamic-pituitary-adrenal axis component of the stress response.Borsoi et al. (40) reported high plasma corticosterone levels in cold-stressed andSalmonella-infected specific-pathogen-free broilers. A previous study found more pecksat waxworms (dummy worms) from Salmonella-infected birds than from uninfectedbirds (37). There were no correlations between the prevalence or shedding of Salmo-nella and any of the hen welfare measures, including social interaction, plumagedamage (which may indicate occurrence of plumage damage), flock noise, fear tests(novel object and avoidance distance), comb colors, ranging activity, panting, or theprevalence of pariah birds. The breed of laying hens might influence their behavior (37).However, in this study, all birds were of the same breed. In Australia, free-range birdshave a minimum of 8 h of range access, except during adverse weather conditions (41).Although flocks sampled during this study did not have access to ranging areas duringadverse weather conditions, birds enclosed in the shed would have been exposed toheat. It is worth noting that, although Salmonella counts were high in fecal samplescollected during the summer, the FCM levels were not high, and FCMs decreased fromthe first to the last visits, likely as a result of aging. During high temperatures, pantingis one of the thermoregulatory mechanisms for laying hens (42). In this study, there wasno correlation between panting and Salmonella shedding. The results from our studyregarding high Salmonella shedding in warm seasons are in agreement with thosereported by Wales et al. (13), but could not be linked with physiological stress based onFCM levels. It is important to note that corticosterone metabolites in fecal samplesreflect the corticosterone production after a species-specific time period (43), and thedetection of short peaks requires frequent sampling. In this study, hen welfare assess-ments were conducted at six weekly intervals, so it is possible that short-lastingdeviations from these welfare states may have been missed. Further experiments arenecessary to study the relationship between hen welfare and Salmonella shedding in acontrolled environment.

The data provide important information for the egg industry regarding the dynam-ics of Salmonella shedding and the possible links between environment/bird/eggtransmissions of Salmonella serovars of public health significance on free-range layerfarms. This field study compared the shedding of Salmonella spp. with flock welfare ina free-range environment. The study highlights the challenges of implementing Sal-monella control strategies in a free-range production system, because shedding andpersistence varied across different farms and seasons. Some reports have indicated thepossibility of increased human Salmonella cases in warmer months due to increases inSalmonella shedding on farms (7, 15). However, factors such as the handling of eggproducts or food handling practices in general, kitchen hygiene, changes in human lifestyles, and eating habits cannot be ignored. Salmonella organisms survived in variousenvironmental samples (inside and outdoor environments), and their detection wasvariable. This finding highlights the challenge for establishing Salmonella prevalencebased on single time point sampling. The incidences of Salmonella spp. need to bemonitored regularly in the Australian egg industry. Regulatory authorities are involvedin the testing of poultry farms in Australia. This study provides useful information forpublic health authorities, veterinarians, and regulators to design sampling strategies onfree-range egg farms.

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MATERIALS AND METHODSSelection of farms. Four commercial free-range flocks (A, B, C, and D) from four different farms were

selected for this study on the basis of the willingness of egg producers to participate in the study. Allfarms had multiage flocks housed in separate sheds. The youngest flocks (ages ranged from 23 to 24weeks) on each farm were selected for this study. All flocks had at least 8 h of outdoor range access.Flocks A and B had 10,000 birds each, whereas flocks C and D had 18,000 and 8,000 Hy-Line brown birds,respectively. To identify Salmonella serovars and determine the best sampling sites within the shed andrange areas, a cross-sectional study was conducted on all four free-range flocks. This was followed by thelongitudinal study to investigate the shedding of Salmonella in the free-range production systems. Thestocking densities in the ranges were between 1,500 and 10,000 birds per hectare.

Cross-sectional study. During this cross-sectional sampling, to identify areas of higher Salmonellaprevalence and infection spread within a flock, 10 swabs (Whirl-Pak speci-sponge bags; Thermo FisherScientific, Australia) were collected from floor areas near pop holes (small openings from which birdswent out to range), floor areas near drinker lines, nest boxes, and dust and ramps near pop holes (total50 samples/flock) (Fig. 10). In addition, samples from shoe covers (n � 2) worn while collecting samplesfrom the left and right sides of the sheds were also collected. At the end of the sampling, shoe coverswere removed and placed in a 250-ml sterile plastic container (Pacific Laboratory Products, Australia).

Longitudinal sampling for investigating the dynamics of Salmonella shedding. Based on theprevalence results from the cross-sectional study (Fig. 1), different areas of the sheds were selected forlongitudinal sampling. Samplings were conducted from 2014 to 2015 during different seasons.

From each flock, samples were collected at 6-week intervals from October 2014 to July 2015. Duringthe longitudinal sampling on each farm, 10 fecal samples were collected (five from each side) in a sterileWhirl-pak plastic bag (150 by 230 mm; Thermo Fisher Scientific, Australia). A clean and disinfected plastictray was placed under the slats/flooring on the day before sampling for collecting fresh feces. Fresh feceswere collected in a sterile plastic bag on the day of sampling, and stored at �20°C within 6 h. Swabs(Whirl-Pak Speci-sponge bags, 115 by 134 mm; Thermo Fisher Scientific, Australia) from egg belts, dust,nest boxes, and ramps near pop holes (n � 10 each) were collected at each sampling point. Samples fromshoe covers (n � 4) worn while collecting samples from inside and outside (range area) of the sheds werecollected from the left and right sides. Thirty visibly clean eggs, as well as 10 floor eggs, were collectedat each sampling point.

Isolation and enumeration of Salmonella. Salmonella organisms were isolated from egg belt, dust,nest box, ramp, swab, and shoe cover samples. The swabs were premoistened using 20 ml of bufferedpeptone water (BPW; Oxoid, Australia) and were dragged to cover 1 square meter of floor area. ForSalmonella isolation, 10 g of feces was inoculated into 90 ml of BPW and further enriched. Shoe coverswere placed in 100 ml of BPW and processed for further enrichment and isolation.

FIG 10 Graphical representation of sampling performed during the current study. The swabs from nestboxes (NB), ramps (L, R), and dust (D) were collected during each sampling. Fecal samples (FS) werecollected during each sampling point.

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Each sample inoculated in BPW was incubated at 37°C overnight, and 100 �l of inoculated BPW wastransferred to Rappaport Vassiliadis soya peptone (RVS) broth (Oxoid, Australia), which was thenincubated at 42°C for 24 h. A loopful of the same sample was streaked on Brilliance Salmonella (OxoidAustralia) and xylose lysine deoxycholate (XLD; Oxoid, Australia) agar plates. The presumptive Salmonellacolonies were also tested for ortho-nitrophenyl-�-D-galactopyranoside (Oxoid, Australia), lysine decar-boxylase (LDC), and urease (Oxoid, Australia) activities. The suspected Salmonella cultures were sent forserotyping to the Salmonella Reference Laboratory, Adelaide, Australia. Salmonella organisms wereisolated from shoe covers placed in 100 ml BPW as mentioned above.

Individual eggs were placed in 10 ml of sterile BPW in Whirl-Pak bags. To recover bacteria fromeggshell surfaces, eggs were massaged out of Whirl-pak bags for 2 min. Before rinsing, BPW wasprewarmed to 37°C to facilitate bacterial recovery. After a rinse sample was obtained, each egg wasremoved and transferred to a new sterile bag. The BPW samples were incubated at 37°C overnight, and100 �l of this sample was inoculated into RVS broth (Oxoid, Australia), which was then incubated at 42°Cfor 24 h. The incubated RVS broths were further processed for Salmonella isolation as mentioned above.After eggshell surface processing, each egg was dipped into 70% alcohol for 60 s to eliminate anybacteria present on the outside of the shell and was allowed to air dry in a biosafety cabinet. After drying,

TABLE 3 Procedures and scoring system for hen welfare assessment

Measure Scoring method Definition

Panting (adapted from 41) Ten birds from four different areas were observed for panting.Numbers of panting birds in each section were recorded.

Breathing respiration in short gasps; visiblesigns are birds that sit upright, opentheir beaks, and often make visiblerespiratory movements; wings may beheld out from the side of the body

Comb color (56) Ten birds from each area were randomly selected and scoredas follows: pale � 1–3, normal � 4–5, dark red � 6–7.

See comb color scale from the BristolWelfare Assurance Programme henassessment (56)

Noise (adapted from 57) Each flock was observed inside the shed for 30 s and scoredas follows for the noise level: quiet � 1, steady murmur �2, loud chatter � 3, loud gakel calling � 4.

Self-explainable; see scoring method

Plumage damage (adaptedfrom 58)

Ten birds were randomly selected in four different areas ofthe shed. Head/neck, back, and ventral area of each bird(without handling birds) was visibly assessed. No/minimalfeather loss: no bare skin visible, no or slight wear, onlysingle feathers missing � 0; moderate feather loss:moderate wear, i.e., damaged feathers or 1 or morefeatherless areas, bare skin visible �5 cm maximumdimension � 1; Severe feather loss: at least one area withbare skin visible �5 cm maximum dimension � 2.

Relates to plumage condition; see scoringmethod

Social interactions (adaptedfrom 57)

Birds within an area of 1 m2 were observed for 3 min. No. ofbirds interacting with each other were measured (not theno. of interactions), accounting for the no. of hens in thearea at the end of observation minus no. at the start.

Physical interactions between two or morehens, such as pecking or grooming

Novel object test (adaptedfrom 57)

Red (comb color) sheet was placed on the floor in fourdifferent areas of sheds 2 m in front of the observer.Latency for 10 different birds to touch the paper wasrecorded or the no. of birds that have touched in 2 min,whichever came first.

Touching: physical contact (beak, foot)with novel object

Avoidance distance test(adapted from 58)

The assessor stops, turns around, and focuses on a randombird approx 2 m in front of him/her. The assessor holds his/her hand in a fixed position against the abdomen andwalks slowly at one step per second toward the focal bird,looking at the bird’s feet. When the bird turns away orretreats (both feet step aside or away), the distance (in mm)between the assessor’s hand and where the bird’s feet wereoriginally is estimated. If the hen retreated for a reasonother than the approach, another hen was selected.

Self-explainable; see scoring method

Pariah birds (adaptedfrom 59)

No. of victimized birds within a 5 m radius in each of theeight areas of the sheds were counted.

Hyperactive individual that alternativelywithdraws from or makes a frenzieddash through the body of the flock

Ranging activity assessment(adapted from 57)

No. of hens counted inside the veranda area, close to theveranda/pop holes, is within 2 m ranging, ranging awayfrom the veranda/pop holes is 5–10 m, or more thanhalfway down the range is �20 m. This assessment wasconducted outside the sheds on both the left and rightsides of the ranges.

Self-explainable; see scoring method

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the eggs were cracked open and the internal egg contents were collected in sterile containers, werethoroughly mixed, and 2 ml was inoculated into 8 ml of BPW. The inoculated BPW samples were furtherprocessed for Salmonella isolation as mentioned above. The miniaturized most probable number (MPN)method as described previously (44) was used for determining the loads of Salmonella in samples thattested positive by culture techniques. The results were interpreted as log MPN/g feces or m2 of areasampled.

Multilocus-variable tandem-repeat analysis of S. Typhimurium isolates. After serotyping, allSalmonella strains that were identified as a Typhimurium were further analyzed by MLVA, as describedpreviously by Ross et al. (45) at the Salmonella Reference Laboratory, Adelaide, Australia.

Assessment of bird welfare. Hen welfare was measured on each visit to investigate the relationshipbetween hen welfare and Salmonella shedding (Table 3). The sheds were sectioned into four quarters: 1,the front right corner; 2, the back right corner; 3, the back left corner, and 4, the front left corner. Eachquarter was subdivided into two areas, with one area between the shed wall and the feeder and drinkerline and the other area between the feeder and drinker line and the nest area in the center of the shed.Assessments were carried out in the middles of each of these areas. Observations were made between11:00 AM and 02:30 PM, when hens are expected to be most active. Some measures were taken on 80individual hens during each visit, with 10 birds in each of the 8 areas: panting, comb colors, plumagedamage, and avoidance distance tests. Other measures were collected for each of the 8 areas: socialinteractions, novel object tests, pariah birds, and fecal sampling for glucocorticoid metabolite measure-ment. Finally, the last set of welfare measures was collected at flock level, including noise and rangingactivity assessment.

Measurement of fecal glucocorticoid metabolites. Glucocorticoid metabolites were extractedfrom all fecal samples (n � 280) as described earlier (18). All fecal samples were homogenized and driedat 103°C overnight. After cooling at room temperature, the dried samples were milled to a fine powder.Fecal samples (0.2 g) were mixed with ethanol, vortexed for 30 min, and centrifuged at 10,000 � g for15 min. The supernatants were dried using a nitrogen dryer, and the dried extracted samples were storedat �20°C. Immediately before the immunoassay, the extracts were dissolved in ethanol. Samples wereanalyzed for glucocorticoid metabolite concentrations by a radioimmunoassay (RIA) (ImmuChem doubleantibody corticosterone 125I RIA kit; MP Biomedicals LLC, Orangeburg, NY, USA) in accordance with themanufacturer’s instructions using a 1:100 dilution. A preliminary validation was conducted by adminis-trating 12.5 IU adrenocorticotropin (ACTH) subcutaneously in three laying hens, with two other hensadministered saline as a control, followed by repeated fecal samplings every 30 min for 8 h. Samples weresuccessfully obtained in 82% of the time points for all hens. Samples giving results with a coefficient ofvariation greater than 5% between duplicates were rerun. The results were interpreted as ng/ml.

DNA extraction and PCR. Overnight cultures of the Salmonella serovars selected for this study weregrown at 37°C in 4 ml Luria Bertani (LB) broth. DNA was purified from 109 bacteria/ml using the Promegagenomic DNA kit (Promega, USA). Purified DNA was quantified using a NanoDrop spectrophotometer(Thermo Fisher Scientific, Australia). Working DNA solutions were prepared by diluting stock solutions to5 ng/�l. Primers for each gene were designed using the primer design feature in GenBank or wereobtained from Hughes et al. (46). Primers were obtained from GeneWorks (Adelaide, South Australia)(Table 4). The PCR mix comprised 1� Taq polymerase buffer (Fisher Biotech, Australia), 1.0 mM MgCl2,0.5 �M forward and reverse primers, 0.2 �M deoxynucleoside triphosphates (dNTPs), 0.3 U Taq poly-merase (Fisher Biotech, Australia), and 10 ng Salmonella DNA.

TABLE 4 Details of the virulence genes used for Salmonella typing

Virulencegene Function

Primer sequence (5= to 3=)Annealingtemp (°C) ReferenceForward Reverse

sitC Iron transporter CAGTATATGCTCAACGCGATGTGGGTCTCC CGGGGCGAAAATAAAGGCTGTGATGAAC 64 60spiC Disrupts Golgi apparatus

and lysosomesCCTGGATAATGACTATTGAT AGTTTATGGTGATTGCGTAT 56 60

misL Adhesin GTCGGCGAATGCCGCGAATA GCGCTGTTAACGCTAATAGT 58 60orfL Survival within

macrophagesGGAGTATCGATAAAGATGTT GCGCGTAACGTCAGAATCAA 56 60

pipD Colonization CGGCGATTCATGACTTTGAT CGTTATCATTCGGATCGTAA 58 60iroN Iron transport ACTGGCACGGCTCGCTGTCGCTCTAT CGCTTTACCGCCGTTCTGCCACTGC 60 60sipB Invasion protein TGGCAGGCGATGATTGAGTC CCCATAATGCGGTTCGTTTC 58 31sipC Invasion protein TGCCCTGGCAAATAATGTCA CATCGATTCGGGTCATATCC 58 61sopA Induces proinflammatory

responseGCCCACGGTTTCTGAAGGTA AAGAGTCCGCTGTGAGTGG 60 31

avrA Modulates host immuneresponse

ATACTGCTTCCCGCCGC ACACCGAAGCATTGACCTGT 58 31

sptP Disrupts actincytoskeleton

TTCACCCTATCCGCCAGGTA GTGTAGCCCGGTTCTCACAA 58 46

hilA Activates expression ofinvasion genes

CACCAACCCGCTTCTCTCTT ATTGTGGTCCAGCTCTGTCG 58 62

xth-a Survival in egg CGAAAAACACCAGCCCGATG CCGGCAGGAAGGAGCATTTA 55 62yafD Survival in egg CGGATCCGTATCCTCGTGTG ATCGTCAGTGAAACGCACCT 55 46

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The product sizes for each of the genes were relatively similar. Therefore, the PCR conditions weresimilar, with differences only in the primer annealing temperatures (listed in Table 4). The generalreaction protocol was 95°C for 5 min, 30 cycles of 95°C for 30 s (melt), annealing temperature (see Table4) for 45 s, and 72°C for 1 min (extension), and then 72°C for 4 min and holding at 8°C. For data analysis,a positive PCR result was scored as 1 and a negative results was scored as 0.

Statistical analysis. Descriptive and inference statistics were run using STATA v13.1 (StataCorp LP,Texas, USA). The apparent prevalences of Salmonella were compared at various time points using amixed multifactorial logistic regression with a two-way cross-random effect for “sampling number” and“sample type” to account for nonindependent observations. For studying the relationship between fecalglucocorticoid metabolites and Salmonella shedding, for each fecal sample, the probability of isolatingSalmonella spp. was compared to the measured concentration of fecal corticosterone using a mixed-effect logistic regression with “farm” and “sampling time” within farm as random effects. For fecalsamples where Salmonella was detected (n � 33), the Salmonella cell count (log scaled) was comparedto the fecal corticosterone concentration using a mixed-effect linear regression with “farm” and “sam-pling time” within farm as random effects. To study the relationships between hen welfare parametersand Salmonella prevalence and shedding for each flock at each sampling time, the means of each henwelfare parameter were collated with the mean Salmonella prevalences and counts (log scaled) from allsamples but egg shells. Correlations between prevalence/shedding and hen welfare were estimatedusing mixed-effect regression models, where flock was included as a random effect to account forrepeated measures across time within a flock. The relationship between prevalence/shedding and henwelfare was also explored using standard scatter plots.

SUPPLEMENTAL MATERIAL

Supplemental material for this article may be found at https://doi.org/10.1128/AEM.03313-16.

TEXT S1, PDF file, 0.2 MB.

ACKNOWLEDGMENTSThis research was conducted within the Poultry CRC, established and supported

under the Australian Government’s Cooperative Research Centres Program (numberPoultry CRC 3.2.6).

We thank A. McWhorter and V. Pande for their valuable technical help during thisstudy.

The authors have no conflicts of interest.K.C., J.-L.R., and M.S. designed and developed the concept of the work, V.G., T.M.,

K.C., M.S., and R.W. performed the samplings on various farms, J.-L.R. and R.W. devel-oped the welfare parameters, T.M. performed the PCRs, and C.C. and K.C. performed thestatistical analyses.

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