Novel insights into serodiagnosis and epidemiology of Erysipelothrix rhusiopathiae, a newly recognized pathogen in muskoxen (Ovibos moschatus).

BACKGROUND: Muskoxen are a key species of Arctic ecosystems and are important for food security and socio-economic well-being of many Indigenous communities in the Arctic and Subarctic. Between 2009 and 2014, the bacterium Erysipelothrix rhusiopathiae was isolated for the first time in this species in association with multiple mortality events in Canada and Alaska, raising questions regarding the spatiotemporal occurrence of the pathogen and its potential impact on muskox populations.
MATERIALS AND METHODS: We adapted a commercial porcine E. rhusiopathiae enzyme-linked immunosorbent assay to test 958 blood samples that were collected from muskoxen from seven regions in Alaska and the Canadian Arctic between 1976 and 2017. The cut-off between negative and positive results was established using mixture-distribution analysis, a data-driven approach. Based on 818 samples for which a serological status could be determined and with complete information, we calculated trends in sample seroprevalences in population time-series and compared them with population trends in the investigated regions.
RESULTS: Overall, 219/818 (27.8%, 95% Confidence Interval: 24.7-31.0) samples were classified as positive for exposure to E. rhusiopathiae. There were large variations between years and regions. Seropositive animals were found among the earliest serum samples tested; 1976 in Alaska and 1991 in Canada. In Alaskan muskoxen, sample seroprevalence increased after 2000 and, in two regions, peak seroprevalences occurred simultaneously with population declines. In one of these regions, concurrent unusual mortalities were observed and E. rhusiopathiae was isolated from muskox carcasses. In Canada, there was an increase in sample seroprevalence in two muskox populations following known mortality events that had been attributed to E. rhusiopathiae.
CONCLUSION: Our results indicate widespread exposure of muskoxen to E. rhusiopathiae in western Canada and Alaska. Although not new to the Arctic, we documented an increased exposure to the pathogen in several regions concurrent with population declines. Understanding causes for the apparent increased occurrence of this pathogen and its association with large scale mortality events for muskoxen is critical to evaluate the implications for wildlife and wildlife-dependent human populations in the Arctic.

Introduction

Muskoxen (Ovibos moschatus) are distributed across the circumarctic regions of the world [1]. They play an important role in Arctic ecosystems [2-4], are a major source of food and income, and a part of the cultural heritage for many northern Indigenous peoples [5,6]. Nearly extirpated across most of their historical range in the early 20th century, drastic conservation measures, including hunting moratorium and bans, as well as translocations, resulted in widespread population recovery by the end of the century [7,8]. In recent years, however, the two largest populations, those on Banks and Victoria Islands, Northwest Territories and Nunavut, Canada, have undergone substantial population declines. The Banks Island population declined from 69,000 to 14,000 between 2001 and 2014 [9]. On northwest Victoria Island, the population dropped from 19,000 in 2001 to 11,000 in 2015 [10]. On the rest of the island, estimates indicated a decrease from 24,000 animals in 1992–94 to 10,000 in 2013–14 [11,12].

Infectious diseases have been identified as a potential threat to wildlife populations globally [13-15]. In muskoxen, multifactorial causes, including diseases and mineral deficiencies, were implicated as causes for the decline of a reintroduced Alaskan population [16]. On Victoria Island, the ongoing decline of muskoxen is concomitant to the apparent emergence or increased occurrence of multiple pathogens and disease syndromes [17-20]. Given the taxonomic uniqueness of muskoxen, and their limited genetic diversity [21,22], which may influence their resilience to diseases [23], it is important to understand the potential role of infectious diseases in their population dynamics and conservation.

Erysipelothrix rhusiopathiae is a gram-positive, opportunistic and zoonotic bacterium commonly identified in domestic pigs and poultry, but which can infect a wide range of species, including wild animals [24]. In North American wildlife, sporadic isolation of the bacterium has been previously reported in American bison (Bison bison), moose (Alces alces), pronghorn antelope (Antilocapra americana), white-tailed deer (Odocoileus virginianus), and wolf (Canis lupus) [25,26]. More recently, E. rhusiopathiae has been reported for the first time as a mortality cause in muskoxen between 2010–2013 [27], and has subsequentially been considered as a potential public health concern in the area [28]. A single genotype of E. rhusiopathiae was implicated as the cause of death during multiple muskoxen die-offs in the declining populations of Banks and Victoria Islands in the Northwest Territories and Nunavut, Canada [24]. Subsequently, multiple different genotypes were isolated from carcasses of muskoxen in Alaska, as well as woodland caribou (Rangifer tarandus caribou) and moose in Canada, during periods of unusually high mortality of these species [24]. The bacterium has also recently been implicated as the causative agent of a disease syndrome in Pribilof arctic foxes (Alopex lagopus pribilofensis) in Alaska [29]. The apparent emergence of E. rhusiopathiae as an etiological agent of disease or mortality across a broad host range and spatial scale in temperate and Arctic North America raised questions regarding its historical occurrence and its possible role in the declining health of several muskox populations documented in Canada and Alaska [1,16,19].

The objectives of this study were to develop a species-specific diagnostic serological tool to detect exposure to E. rhusiopathiae in muskoxen, describe spatiotemporal trends of seroprevalence to E. rhusiopathiae in different muskox populations, and assess seroprevalence relative to known mortality events and population trends in North American muskoxen.

Materials and methods

Sample collection

We obtained frozen serum samples or blood on Nobuto filter paper (FP) strips (Toyo Roshi Kaisha, Ltd., Tokyo; Japan; Advantec MFS Inc., Dublin, California, USA distributor) collected between 1976 and 2017 from muskoxen in four regions in Alaska and three regions in Canada (Fig 1 and Table 1). Regions were determined by topographic features for Canada (islands versus mainland) and, for Alaska, by adapting the official Game Management Unit delimitation [30]. For sera, samples were collected during translocation and radio-collaring programs. Whole blood was collected in serum tubes and was kept cool until the serum could be separated from the blood clot by centrifugation within 24 hours of collection. The FP samples were collected as part of hunter-based sampling programs or commercial muskox harvests in Canada [31]. Filter papers were dipped in blood (typically from the jugular or femoral veins or heart) of recently deceased animals, frozen immediately after collection and sent to the University of Calgary where they were processed following the protocol described by Curry et al. [32] to obtain eluates with an estimated dilution of 1:10. All serum and FP samples were stored at -20°C until testing. All sampled muskoxen were free-ranging animals living in remote habitat with no contact with domestic animals. Details on sample collected and their serostatus are given in the supplementary material.

Fig 1

Study area and origin of samples.

Regions of origin of 818 muskoxen sampled between 1976 and 2017 and serologically tested for exposure to Erysipelothrix rhusiopathiae. For each region, the number of seropositive/number of tested individuals and the percentage of positives are indicated. A: Nunivak Island; B: Game Management Unit (GMU) 22; C: GMU 23; D: GMU 26; E: Banks Island; F: Victoria Island; G: Kitikmeot Mainland. The map was created using country and province boundaries from naturalearthdata.com.

Table 1

Seroprevalences to Erysipelothrix rhusiopathiae in North American muskoxen.

Region	Time period	Positive/total	Sample prevalence (%)	95% Confidence interval	Population information	Sources
Nunivak Island	1976–1986	10/57	17.5	9.2–30.4	Introduced in 1935. Stable, managed, population since the mid 70’s.	[33,34]
GMU 22	1978–1989	9/68	13.2	6.6–24.1	Introduced in 1970. Growing population in the 70’s and 80’s.	[33,34]
GMU 22	2007–2015	89/150	59.3	51–67.2	Growing in the early 2000s. Population decline in part of the region (North Seward Peninsula) in 2007–2012. Unusually high mortality in radio-collared adults between 2009–2012. E. rhusiopathiae isolated from dead animals in 2011–2012.	[1,24,33]
GMU 23	2009–2012	20/61	32.8	21.6–46.1	Introduced in 1970. Rapidly growing until 1998 then stagnant and decreasing in 2007–2012. E. rhusiopathiae isolated from dead animals in 2012.	[1,24,33]
GMU 26	1984–1992	4/36	11.1	3.6–27	Introduced in 1970. Growing population until the mid-90’s.	[33]
GMU 26	2000–2014	15/75	20	12–31.1	Declining between 2000 and 2007. Since 2007 stabilized at a lower number.	[16,33]
Banks Island	1991–2012	36/153	23.5	17.2–31.2	Population growing until early 2000's, decline of over 80% between 2000 and 2015 (attributed first to starvation caused by a severe and widespread winter icing event in 2003/2004 and then to unusually high mortality rates associated with E. rhusiopathiae in 2012–2013).	[1,9,27]
Victoria Island	2011–2017	37/181	20.4	15–27.2	Population growing until early 2000's followed by a decline between 2000–2015. Unusually high mortality rates associated with E. rhusiopathiae between 2009–2013.	[1,10,12,19,27]
Kitikmeot mainland	2011–2017	4/37	10.8	3.5–26.4	Recolonization and expansion after near extirpation in the early 1900’s.	[1,35]

Summary of seroprevalences and population information in seven regions of Alaska and Canada investigated for exposure to Erysipelothrix rhusiopathiae between 1976 and 2017.

The following wildlife sampling permits and ethic approvals were obtained for this study:

For Alaska: “ADF&G ACUC Approved Protocols: 04–011, 06–08, 08–02, 2010–03, 2010-10R, 2011–012, 2012–04, 2013–18 and US Geological Survey Approved Protocol: 2009–01”

For Canada: “Department of Environment of the Government of Nunavut: 2013–035, 2014–053, 2015–068 and 2016–058” and “Department of Natural Resources of the Government of the Northwest Territories: WL002097, WL002112, WL002853, WL003091, WL500098, WL500158, WL500257,WL005627, WL005761, WL500018, WL 5004469”.

For all samples: “University of Calgary Animal Care and Use Permit (AC13-0121).”

Sample analyses

We modified an ELISA developed by Giménez-Lirola et al. [36]. This ELISA is based on a recombinant polypeptide antigen SpaA (rSpaA415), which has been shown to give reliable results and to be specific to the bacterium E. rhusiopathiae with no cross-reaction documented with antibodies directed against closely related bacteria or similar cell surface proteins [36,37]. The rSpaA415 gene was recloned to a different vector to increase expression and solubility [38]. In short, the ELISA protocol was optimized as follows: coating 96 well Maxisorp (Nunc) plates with 50 μL of 1 μg/ml SpaA415 in Phosphate Buffered Saline (PBS), incubating overnight at 4°C; washing (all washing steps were done by adding 350 μL/well with 0.1% Tween 20 in PBS three times); adding 300 μL/well of blocking solution (1% Casein, 0.1% bovine serum albumin, 1% Tween 20 in PBS) for 2hrs at room temperature; washing; adding 50 μL/well of sample (serum or FP eluate) in blocking solution diluted 1/10 in PBS (for serum diluent) or in undiluted blocking solution (for FP samples); incubating one hour at 37°C; washing; adding 50 μL/well of Protein A/G-HRP enzyme conjugate (Pierce/Thermo Fisher, Mississauga) diluted to 1/50,000 in serum diluent; incubating one hour at 37°C; washing; adding 100 μL enhanced tetramethylbenzidine-hydrogen peroxide substrate (Pierce/Thermo Fisher, Mississauga) at room temperature for 15–25 minutes; finally, stopping the reaction by adding 100 μL/well 1.00 Normal Sulfuric Acid at room temperature.

All plates were read immediately at 450nm and sample results expressed as optical density (OD) values. Samples were tested in duplicate and the average OD was recorded for each sample. Samples with an average OD value >0.2 and a discrepancy of >20% between duplicates were repeated.

To standardize ELISA results across different plates, we expressed the result of each sample as the percent positivity (PP) of a benchmark positive control, following the formula PP = (ODsample—ODblank)/(ODcont—ODblank); where ODsample is the optical density value of the sample, ODcont is the value of the positive control of the plate and ODblank is the value of the blank well of the plate. The positive control used across all plates was a pool of five muskox serum samples from our sample set with OD values close to 1.

Cut-off determination

To estimate the optimal cut-off value of PP to discriminate between negative and positive samples, we used a mixture-distribution modelling (MDM) approach. This method is commonly used to estimate cut-offs for diagnostic tests both in animals [39-41] and in humans [42,43]. Briefly, we assumed that the test results from our sampled population could be represented as a mixture of two underlying subpopulations, corresponding to negative and positive samples, with Gaussian distributions and distinct parameters (mean and standard deviation). Using maximum likelihood estimation, we determined the parameters of each distribution as well as the optimal cut-off (defined as the intersection between the distributions of negative and positive samples) and used 1,000 bootstrapping iterations to compute confidence intervals (CI) around the cut-off. We considered serum and FP samples as two different sets and thus, two separate cut-offs were determined. The R-code we developed to estimate cut-offs and conduct bootstrapping iterations is provided in the supplementary material (S1 File).

Sample seroprevalences and population trends

We calculated sample seroprevalences (and binomial proportion confidence intervals) for the entire sample set and for the different muskox populations and time periods. In addition, we used general linear modelling (GLM) to construct trends in seroprevalences. For each region and time period, the probability of a sample to be seropositive was modelled as a binomial outcome using the year as a predictive variable. Since the trend could be non-linear, different polynomial degrees of the predictive variable were used in the models. Akaike Information’s Criterion was used for model selection. By small (<2) Criterion differences between models, the less complex one (i.e. smaller polynomial degree) was selected. Trends were not computed between data points more than four years apart or for time periods with less than four consecutive years.

Additionally, we reviewed the available literature on muskox population estimates and status in all the investigated populations and presented existing abundance estimates together with seroprevalences.

All statistical analyses were conducted with R [44] using the package mixtools [45] for MD analysis. The map in Fig 1 was created with QGIS [46] using publicly available shapefiles from naturalearthdata.com for the boundaries of North-America.

Results

Samples collected and cut-off determination

A total of 958 individual animals (695 sera and 263 FP) were tested for antibodies to E. rhusiopathiae and used to run the MDM models and estimate the cut-offs. Values of PP values ranged from < 0.001 to 3.45 (median = 0.14) for serum samples and from < 0.001 to 4.96 (median = 0.20) for FP samples (Fig 2). Estimated distribution parameters of PP values for serum samples, were mean = 0.09 ± SD 0.07 and mean = 1.04 ±SD 0.82 for the populations of negative and positive individuals, respectively. Estimated distribution parameters for FP samples were mean = 0.20 ± SD 0.13 and mean = 1.38± SD 1.00 for the populations of negative and positive individuals, respectively. Optimal cut-offs were estimated at 0.25 (95% CI = 0.23–0.28) and 0.44 (95% CI = 0.31–0.60) for serum and FP samples, respectively. Among the samples, sixty-eight samples (7.8%) had PP values within the confidence intervals surrounding the cut-off values, and were considered inconclusive, and excluded from further analysis.

Fig 2

Mixture distribution model results.

Mixture distribution models for ELISA results of serum and filter paper samples from free-ranging muskoxen tested against Erysipelothrix rhusiopathiae. Black curve: frequency distribution of the ELISA results (Percent Positivity) for the datasets (serum or filter paper samples). Blue and red curves: estimated underlying distributions of negative and positive samples, respectively. Dotted vertical lines: cut-off value obtained through mixture distribution analysis. Grey area: 95% Confidence Intervals (CI) computed through 1,000 bootstrap iterations. Optimal cut-offs were estimated at 0.25 (95% CI = 0.23–0.28) and 0.48 (95% CI = 0.35–0.59) for serum and filter paper samples, respectively.

A total of 818 samples (622 sera and 196 FP) with complete information on sampling year and location and which could be classified as positive or negative were included in the analysis. The overall seroprevalence was 227/818 (27.8%, 95% CI = 24.7–31.0). Results from the sample analyses and literature search on muskox population trends are presented in Table 1 and Fig 3. In Alaska, seroprevalence in GMU 22 was higher between 2007–2015 when compared to 1978–1989 (Fisher exact test, p<0.001). A similar but not significant trend was observed in GMU 26 when comparing seroprevalence estimates for 2000–2014 to 1984–1992 (Table 1). In GMU 22 and 26, the highest seroprevalence recorded corresponded to periods just before or during population declines. Additionally, in GMU 22, the peak seroprevalence was concomitant with unusual mortalities and the detection of E. rhusiopathiae in muskox carcasses [1,24]. For Victoria Island, although qualitative data on muskox population trends were available in the literature and presented in Table 1, no accurate island-wide estimates were available and thus no population trend was represented for this region in Fig 3

Fig 3

Time plots of seroprevalences to Erysipelothrix rhusiopathiae in North American muskoxen.

Time plots of seroprevalences (black dots) to Erysipelothrix rhusiopathiae from a set of 781 muskoxen sampled in six regions of Alaska and Canada. Dotted vertical lines represent exact binomial confidence intervals. Red curves represent trend lines for regions and time periods (see text for the calculations of trends in seroprevalences). Population trends as estimated through aerial surveys are indicated in green in the top part of each plot (with 95% Confidence Intervals represented by green dotted lines) and documented mortality events with detection of E. rhusiopathiae are depicted with an X (see Table 1 for references).

In Canada, Banks Island muskoxen were sampled irregularly between 1991 and 2012. Seroprevalences fluctuated between 2.3% and 41%. The highest seroprevalence occurred concomitantly with a known outbreak of E. rhusiopathiae-associated mortalities documented on the island in 2012 [27]. On Victoria Island, where similar E. rhusiopathiae-associated mortalities were observed in 2009–2013 [19,27], the sample seroprevalence increased through 2011–2015 from 4.3 to 41.7%. The small sample size and the limited number of sampling years for the Kitikmeot mainland population did not allow for inference on temporal patterns.

Discussion

In 2009–2013, E. rhusiopathiae was for the first time discovered and associated with high mortality rates in muskoxen in the Canadian Arctic Archipelago [27]. Our first step was to assess if the bacterium was new to the Arctic or had historically been present. An important challenge was to ensure that an appropriate diagnostic test was available. Often in wildlife health monitoring, diagnostic tests are adapted from domestic species without calibrating the tests to free-ranging species [47]. Here, we used MDM as a data-driven statistical approach to calibrate our ELISA. This method is widely recognized as a reliable tool to produce cut-offs for diagnostic tests in the absence of a well-established benchmark (e.g. experimental trials) [40-42,48]. However, to effectively use a MDM approach, the investigated dataset must contain both negative and positive samples in sufficient quantities to allow the estimation of the two subpopulations [39]. We assumed that there were seropositive muskoxen in our sample set as samples originated from the same populations where the bacterium E. rhusiopathiae had recently been detected [1,27]. Further, the distribution of the PP values was skewed to the right with a long tail, suggesting negative and positive subpopulations [39].

There was a large difference between the means of the distributions of negative and positive samples in our dataset which allowed for a clear determination of cut-offs and indicate that muskoxen can display a strong antibody response to the pathogen (the maximum PP in our set of samples was over 20 times the median value of all tested samples). For both serum and FP samples, the estimated distribution of PP values for positive samples was much wider (larger standard deviation) compared to negative samples (Fig 2). This large standard deviation in the distribution of positive samples was previously described by Garnier et al. [39] in a similar study on ELISA calibration for free-ranging birds. This wider distribution may be explained by the high variability in IgG levels from positive animals corresponding to different immune function and infection history status [49].

Sample seroprevalence and population trends

Once the cut-offs for our diagnostic tests were estimated, we could effectively classify 818 samples in our dataset as either positive or negative and assess trends in seroprevalences in muskoxen from seven North American regions over more than 40 years. Our results indicate that E. rhusiopathiae has been circulating in muskox populations since at least 1976 in Alaska and 1991 in Canada, corresponding to the earliest year for which samples were available. In Canada, the increase in seroprevalence between 2011 and 2015 on Victoria Island, and the high seroprevalence in 2012 on Banks Island, coincided with unusually high mortality rates associated with E. rhusiopathiae infection and population declines [1,19]. The severity of the reported mortalities [19,27], the large-scale spread of a unique genotype over a range of 800 km and two islands [24], and the increase in seroprevalence documented on Victoria Island subsequent to the mortalities, suggest an emerging highly infective E. rhusiopathiae genotype that caused a widespread seroconversion within a susceptible population. Whether the genotype circulating on these islands in recent years is the same as the one detected serologically in 1991–92 on Banks Island is not known.

On Banks Island, seroprevalence alternated between years with higher values (1991, 2001, 2012) and years with lower values (1992, 2007) The small sample size and the gaps in the time series warrant a cautious interpretation of those results. However, this periodic increase in seroprevalence may suggest a cyclical pattern of outbreaks of E. rhusiopathiae similar to those described in other pathogens of free-ranging species [50,51].

The pattern of seropositivity in Alaskan muskoxen differed somewhat from the one documented in Canada. Forde et al. [24] suggested an endemic presence of E. rhusiopathiae in Alaskan muskoxen based on phylogenetic analyses that demonstrated multiple different genotypes isolated from the bone marrow of deceased muskoxen in GMU 22 and 23. The hypothesis of endemicity seems to be confirmed by the recurrent low seroprevalence between 1976–1992 in the three Alaskan populations for which archived samples were available prior to 2000. However, in two regions (GMU 22 and 26), yearly seroprevalences over 50% documented after 2000 indicate a possible increase inexposure to E. rhusiopathiae in these regions.

Although historically present in muskox populations since at least the 1970s, our results suggest that the seroprevalence of E. rhusiopathiae. has increased in some North American muskox populations coincident with observed mortality events and population level declines. The emergence or invasion of new, more pathogenic genotypes could explain this increase. However, while this hypothesis may hold for Victoria and Banks Islands, whole genome sequencing by Forde et al. [24] refutes a hypothesis of a single emerging genotype of E. rhusiopathiae in Alaska. In this latter case, mechanisms such as host density-dependent pathogen abundance [52] and stress [53-55] may facilitate negative outcomes of infections with E. rhusiopathiae, and could be a contributing factor for muskoxen as well. The Arctic is experiencing rapid changes [56-58], which may increase stress on muskoxen through a variety of biotic and abiotic mechanisms. Possible stressors include extreme weather, changes in predator numbers and occurrence, human disturbance, alterations in plant diversity and phenology, or in mineral availability, and the emergence of other pathogens [59]. Changes in the environment may also modify the ability of pathogens to survive and persist outside the host [27].

Finally, the impact of E. rhusiopathiae at the population level remains to be assessed. Here, the documented association between an increase in seroprevalence and population declines/die-offs alone does not establish causality. Additionally, in our dataset, high seroprevalence against E. rhusiopathiae did not always fit known mortality events or population declines. This can be explained by low observation pressure and underreporting of mortalities [19], and also by the fact that the drivers of muskox population dynamics are likely to be more complex Furthermore, the regions used in this study were delimited as epidemiological units consistent with the current knowledge on muskox populations but are nonetheless wide and do not take into account possible subpopulations and heterogeneity in sample collection within each region (e.g. hunter-collected samples clustered around communities). Although not feasible with the data presented here, an analysis of seroprevalences and population trends at a finer spatial resolution might might provide new insights on the association between E. rhusiopathiae and muskox population dynamics. Nevertheless, the extent of the 2009–2013 outbreaks on Banks and Victoria Islands and the high number of reported mortalities [27], given that muskox mortalities are substantially under-reported [19], highlight the potential high death toll that E. rhusiopathiae can exert on muskox populations. Moreover, diseases might have more pernicious effects on a host population than just direct mortality. Preece et al. [60] noted that pathogens can also have bottom-up negative effects (e.g. reduced fertility) or indirect negative effects such as changes in the population structure, which are more difficult to measure and contribute to the frequent underestimation of the true impact of diseases on wildlife populations. This, together with the data presented here raises the question of whether E. rhusiopathiae is not a contributor in the decline of some muskox populations in Canada and Alaska.

Conclusion

We successfully adapted an ELISA to test for exposure to E. rhusiopathiae in free-ranging muskoxen and used it to document the widespread historical exposure in several North American populations toa pathogen that was until recently not known to infect this species. The MDM approach allowed us to estimate an optimal cut-off value for the ELISA without using a set of known-positive and known-negative animals. As species-specific cut-offs are increasingly recognized as necessary in diagnostic testing, this statistical approach is of particular interest to improve diagnostic test accuracy in free ranging-species for which experimental infection trials are not easily feasible. Archival samples were critical for these analyses to understand historical seroprevalence. Our data suggest that in some populations, exposure to E. rhusiopathiae has increased concomitantly with observed population declines. Our data also highlight different epidemiological patterns across the investigated regions. Data limitations include many factors such as the lack of knowledge on antibody persistence, small sample sizes, bias due to opportunistic sampling, and missing information on the age and sex of exposed animals. The novel knowledge presented here will be enhanced through further monitoring efforts and the use of complementary, multidisciplinary techniques are warranted to overcome the many limitations linked with health surveillance efforts conducted in remote free-ranging animal populations (Given the need to understand mechanisms that may drive population trends of muskoxen in the Arctic, the importance of muskoxen as a source of food and income for Indigenous communities, as well as the zoonotic potential of E. rhusiopathiae documented for other animal species, an enhanced understanding of the epidemiology of this pathogen in a rapidly changing Arctic ecosystem is needed.

R-code for mixture distribution modeling and bootstrapping to determine optimal cut-off in a set of ELISA results.

(TXT)

Click here for additional data file.

Csv file with the percent positivity values used to run the mixture distribution modeling and bootstrapping R-code.

(CSV)

Click here for additional data file.

Excel file with information (location, year, serological status) on all sampled animals included in the study results.

(XLSX)

Click here for additional data file.

10 Jan 2020

PONE-D-19-30167

Novel insights into serodiagnosis and epidemiology of Erysipelothrix rhusiopathiae, a newly recognized pathogen in muskoxen (Ovibos moschatus)

PLOS ONE

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Reviewers' comments:

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: The study addresses an important issue, as muskoxen are an important species for many indigenous communities of the Arctic ecosystem and there has been a large population decline observed since 2001 due to Erysipelothrix rhgusiopahiae, having serious impact. The aim of developing a specific diagnostic serological test is of particular importance not only for the present study, but also for its future use in monitoring animal exposure to the pathogen. In addition, the experimental approach may serve as a model for many other species of wildlife that do not have standard diagnostic tests. Hence, the originality of the approach is something important.

Title is specific, the abstract is accurate, the methodology is fully explained and possible to replicate it. Discussion fully explains the results and especially the ones from Banks Island, where a change in pattern is observed, attributed to a cyclical pattern of outbreaks, a well documented view.

I would suggest to add in your conclusions that your approach could be used in oher wildlife species as well in which a large number of samples is available, and there is an aitiological agent recognized to affect the specific population.

Reviewer #2: This is an important paper that pursued the authors’ previous research papers dealing with large scale mortalities caused by infection with Erysipelothrix rhusiopathiae. In this study, the authors investigated seropositivity for E. rhusiopathiae of blood samples that collected from muskoxen from regions in Alaska and Canada during the past 40 years. They concluded that 227 samples (28%) of 818 tested were positive, indicating widespread historical exposure of the pathogen to the animals in the North American populations.

Overall, I agree to the authors’ conclusion and have minor comments.

Comments are as follows:

1. The authors’ conclusion and interpretation of data is based on that like in pigs, humoral immune responses in muskoxen are well induced by infection of E. rhusiopathiae. However, with experimental infections in cattle, I observed that E. rhusiopathiae does not induce strong humoral immune responses and the immunity does not last long. It may be possible in muskoxen as well. The authors should take it into consideration and can discuss this.

2. Do the authors have any information regarding the animals’ habitat environments? Were all the animals completely in the wild or could they get close to humans, or some farmed? This information is important, if the authors have that, please discuss in detail.

3. L55: “Cl” should be spelled out on first appearance.

4. SpaA is not a membrane protein. So, “membrane proteins” should read “cell-wall-associated proteins” or “cell surface-located proteins” or “cell surface proteins”.

5. Please check whether SpaA415 was coated on ELISA plate in PBS? Not in alkaline buffer?

6. Page 14 Discussion L1 and L3: E. rhusiopathiae is not a syndrome or disease. Please correct them.

7. Page 16, second paragraph can be “On Banks Island, several muskox die-offs were attributed to Yersinia pseudotuberculosis in the 1980’s and 1990’s, but in some cases, despite intensive investigation of Y. pseudotuberculosis at the time, macroscopic lesions were not consistent with yersiniosis (pulmonary edema rather than intestinal lesions [46]) and/or Y. pseudotuberculosis was not isolated from carcasses (1996 die-off [47]). As E. rhusiopathiae was, at that time unknown to affect muskoxen and not specifically looked for, this raises the question of whether those cases were, in fact, unrecognized E. rhusiopathiae infections. On Banks Island, seroprevalence alternated between years with higher values (1991, 2001, 2012) and years with lower values (1992, 2007), and the high seroprevalence documented in 1991 was not associated with any visible population decline or mortality events. The reason for the disassociation is unclear. However, this periodic increase in seroprevalence may suggest a cyclical pattern of outbreaks of E. rhusiopathiae similar to those described in other pathogens of free-ranging species [48,49]."

8. Figure 3: Prevalence (%)

9. Figure 3: Please add Population trend data for Victoria Island. If there is no data, it should be clarified in the text.

**********

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Reviewer #1: No

Reviewer #2: Yes: Yoshihiro Shimoji

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27 Mar 2020

Please find below our responses to the comments of the academic editor and the reviewers.

Academic Editor comments:

1.Please ensure that your manuscript meets PLOS ONE’s style requirements, including those for file naming.

We changed the file names to comply with the journal quidelines and adapted the text accordingly at lines 708-713

2. Thank you very much for including the following ethics statement on the submission details page: “The following wildlife sampling permits and ethic approvals were obtained for this study:

ADF&G ACUC Approved Protocols : 04-011, 06-08, 08-02, 2010-03, 2010-10R, 2011-012, 2012-04, 2013-18;

US Geological Survey Approved Protocol: 2009-01

Department of Environment of the Government of Nunavut: 2013-035, 2014-053, 2015-068 and 2016-058

Department of Natural Resources of the Government of the Northwest Territories: WL002097, WL002112, WL002853, WL003091, WL500098, WL500158,

WL500257,WL005627, WL005761, WL500018, WL 5004469

University of Calgary Animal Care and Use Permit (AC13-0121).” Please also include this ethics statement in the Methods section and clarify which permits or approvals are obtained for which samples from which countries.

We have added the information at line 120-130

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The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

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Natural Earth (public domain): http://www.naturalearthdata.com/

Figure 1 is not a copy of an existing map and was created for the purpose of this publication. The GIS shapefile used to represent the sampling regions was done by the first author with the software QGIS using the free-hand polygon layer creation tool. The shapefiles used to represent the borders of Alaska and northern Canada were obtained from the website https://mapcruzin.com/ and are publicly available under the Creative Commons Attribution Share-Alike 2.0 license. We modified the Material and Method section at line 190-191 to clarify this and we referenced https://mapcruzin.com/ as the source of the layers for the borders.

To determine each region, we used the exact locations of the sampled animals (not shown in the publication) and for Alaska, we additionally used the Game Management Units map described (among others) in Miller et al. 2017. For clarity purpose, we added a description on how regions were made at line 111-113 and added the relevant reference from Miller et al., 2017.

Reviewer 1:

I would suggest to add in your conclusions that your approach could be used in other wildlife species as well in which a large number of samples is available, and there is an etiological agent recognized to affect the specific population

We adapted the text as requested at lines 353-357

Reviewer 2:

1. The authors’ conclusion and interpretation of data is based on that like in pigs, humoral immune responses in muskoxen are well induced by infection of E. rhusiopathiae. However, with experimental infections in cattle, I observed that E. rhusiopathiae does not induce strong humoral immune responses and the immunity does not last long. It may be possible in muskoxen as well. The authors should take it into consideration and can discuss this.

We added some discussion points on those topics at lines 265-267 :

“There was a large difference between the means of the distributions of negative and positive samples in our dataset which allowed for a clear determination of cut-offs and indicate that muskoxen can display a strong immune response to the pathogen (the maximum PP in our set of sample was over 20 times the median value of all tested samples).”

and at lines 361-364:

“It must however be noted that the data presented here only reflects apparent seroprevalence in the investigated populations and is limited by many factors such as the lack of knowledge on antibody persistence, small sample sizes, bias due to opportunistic sampling, or missing information on the age and sex of exposed animals.”

2. Do the authors have any information regarding the animals’ habitat environments? Were all the animals completely in the wild or could they get close to humans, or some farmed? This information is important, if the authors have that, please discuss in detail.

We modified the text at line 120 to clarify that the animals are free-ranging and living in remote areas with no contact with domestic animals.

3. L55: “Cl” should be spelled out on first appearance.

Corrected as requested

4. SpaA is not a membrane protein. So, “membrane proteins” should read “cell-wall-associated proteins” or “cell surface-located proteins” or “cell surface proteins”.

Changed membrane protein to cell surface protein (line 144)

5. Please check whether SpaA415 was coated on ELISA plate in PBS? Not in alkaline buffer?

Indeed, we used a PBS buffer. The PBS recipe we use gives a final pH of 7.4 which is deemed sufficient for efficiently binding the antigen to Maxisorp plates. This part of the protocol follows exactly the instructions described in Gimenez-Lirola (2012) from which we adapted our ELISA. The ELISA protocol was modified in our study only to extend the range of species that can be tested, we saw no reason to change the buffer used for coating the plates.

6. Page 14 Discussion L1 and L3: E. rhusiopathiae is not a syndrome or disease. Please correct them.

We modified the text at line 250-252.

“In 2009-2013, E. rhusiopathiae was for the first time discovered and associated with high mortality rates in muskoxen in the Canadian Arctic Archipelago. Our first step was to assess if the bacterium was new to the Arctic or had historically been present.”

We also modified the text at line 89-92 to avoid the incorrect use of the term “disease syndrome”

“More recently, E. rhusiopathiae has been reported for the first time as a mortality cause in muskoxen between 2010-2013 [27], and has subsequentially been considered as a potential public health concern in the area [28]”

7. Page 16, second paragraph can be “On Banks Island, several muskox die-offs were attributed to Yersinia pseudotuberculosis in the 1980’s and 1990’s, but in some cases, despite intensive investigation of Y. pseudotuberculosis at the time, macroscopic lesions were not consistent with yersiniosis (pulmonary edema rather than intestinal lesions [46]) and/or Y. pseudotuberculosis was not isolated from carcasses (1996 die-off [47]). As E. rhusiopathiae was, at that time unknown to affect muskoxen and not specifically looked for, this raises the question of whether those cases were, in fact, unrecognized E. rhusiopathiae infections. On Banks Island, seroprevalence alternated between years with higher values (1991, 2001, 2012) and years with lower values (1992, 2007), and the high seroprevalence documented in 1991 was not associated with any visible population decline or mortality events. The reason for the disassociation is unclear. However, this periodic increase in seroprevalence may suggest a cyclical pattern of outbreaks of E. rhusiopathiae similar to those described in other pathogens of free-ranging species [48,49]."

We are grateful to reviewer#2 for bringing this part of the text to our attention. After reflecting on the changes proposed by reviewer#2 and discussing it with one of our co-authors (J. Blake) who was involved in the die-off investigation on Banks Island in the 1980s and 1990s, we have decided to remove the first half of the paragraph. (line 287-294).

“On Banks Island, seroprevalence alternated between years with higher values (1991, 2001, 2012) and years with lower values (1992, 2007). The small sample size and the gaps in the time series warrant a cautious interpretation of those results. However, this periodic increase in seroprevalence may suggest a cyclical pattern of outbreaks of E. rhusiopathiae similar to those described in other pathogens of free-ranging species [51,52]. “

8. Figure 3: Prevalence (%)

Corrected as requested

9. Figure 3: Please add Population trend data for Victoria Island. If there is no data, it should be clarified in the text.

Indeed, no reliable trend data are available for Victoria Island. We clarified this at line 227-229.

Additional changes:

During the revision process, there was an additional internal review required by our USGS colleagues. This, and our final review of the manuscript, has led to some additional minor edits for clarity. None of these edits have changed the findings or interpretations of the manuscript. These include:

Changed ‘strain’ to genotype for consistency throughout the text.

Line 65: changed “human population in the Arctic” to “wildlife-dependent human populations in the Arctic”

Line 130: added: “Details on sample collected and their serostatus are given in the supplementary material.”

Lines 165 and 167: replaced “determine” with “estimate”

Line 221: added “when comparing seroprevalence estimates for 2000-2014 to 1984-1992” to clarify which trend we are referring to.

Line 222-224 : replaced: ”In GMU 22 and 26, the highest seroprevalence corresponded to the muskox population peak just before they started to decline and, in GMU 22, was concomitant with unusual mortalities and the detection of E. rhusiopathiae in muskox carcasses [1,24]” with ” In GMU 22 and 26, the highest seroprevalence recorded corresponded to periods just before or during population declines. Additionally, in GMU 22, the peak seroprevalence was concomitant with unusual mortalities and the detection of E. rhusiopathiae in muskox carcasses [1,24]”.

Line 244: In the revision we realized that the phrase ‘’ the sampling period of 2011-2017 from 4.3 to 25%’ was a carry over from a much earlier draft of the manuscript and previous analysis where multiple locations had been combined. We had subsequently organized the data in more refined geographic units which made much more biological sense and this is how all the data have been presented throughout, with the exception of this one oversight. The phrase has now been replaced with “2011-2015 from 4.3 to 41.7%”. This correction does not affect the results nor interpretation of the data.

Line 274: Changed “established” to “estimated” and removed “effectively”. This was done for clarity.

Line 275: added ”as either positive or negative“.

Line 282: Replaced “and the increase in seroprevalence on these islands documented in this work” with “and the increase in seroprevalence documented on Victoria Island subsequent to the mortalities”. This was done as the data for Banks Island is not sufficient to make the statement for both islands.

Line 304-306: Replaced ”However, in two regions (GMU 22 and 26), the increase in seroprevalence since 2000, with the highest seroprevalence occurring concurrently with a peak in the muskox population, suggests that the epidemiology of the pathogen may have changed.” with “However, in two regions (GMU 22 and 26), yearly seroprevalences over 50% documented after 2000 indicate a possible increase in the presence of the pathogen in these regions.” This was done to simplify and clarify the text.

Line 312-313: Replaced: “has increased in some North American muskox populations in recent years” with “has increased in some North American muskox populations coincident with observed mortality events and population level declines”

Line 316: To improve clarity, we shortened the section “In this latter case, other mechanisms such as host density-dependent pathogen abundance [53] may play a role in the documented increase in E. rhusiopathiae occurrence. Furthermore, stress has been implicated in facilitating infections with E. rhusiopathiae in multiple species [54-56] and could be a contributing factor for muskoxen as well.” with “In this latter case, mechanisms such as host density-dependent pathogen abundance [53] and stress[54-56] may facilitate negative outcomes of infections with E. rhusiopathiae [54-56] and could be a contributing factor for muskoxen as well.”

Line 329-332: Added “Additionally, in our dataset, high seroprevalence against E. rhusiopathiae did not always fit known mortality events or population declines. This can be explained by low observation pressure and underreporting of mortalities [19] but also by the fact that the drivers of muskox population dynamics are likely to be more complex.”

Line 331: Replaced “and, in all likelihood, the drivers of muskox population dynamics are more complex.” with “but also by the fact that the drivers of muskox population dynamics are likely to be more complex.”

Line 339: removed “wide”

Line 346: removed “at least”

Line 350: To improve clarity, we replaced “…to establish the widespread historical exposure to a previously unknown Arctic pathogen in several North American populations” with “…to document the widespread historical exposure in several North American populations of a pathogen that was until recently not known to infect this species.”

Line 357: Replaced “the historical occurrence” with “historical seroprevalence”

Line 370: added: “documented for other animal species,” because, as of yet, there are no documented cases of transmission of E. rhusiopathiae from muskoxen to people.

References:

Giménez-Lirola, L. G., Xiao, C. T., Halbur, P. G. & Opriessnig, T. Development of a novel fluorescent microbead-based immunoassay and comparison with three enzyme-linked immunoassays for detection of anti-Erysipelothrix spp. IgG antibodies in pigs with known and unknown exposure. Journal of Microbiological Methods 91, 73–79 (2012).

Miller, S. D., Schoen, J. W. & Schwartz, C. C. Trends in brown bear reduction efforts in Alaska, 1980–2017. ursu 28, 135–149 (2017).

Submitted filename: Response to Reviewers_Mavrot_et_al.docx

Click here for additional data file.

31 Mar 2020

Novel insights into serodiagnosis and epidemiology of Erysipelothrix rhusiopathiae, a newly recognized pathogen in muskoxen (Ovibos moschatus)

PONE-D-19-30167R1

Dear Dr. Mavrot,

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Additional Editor Comments (optional):

My congratulations!

Emmanuel

Reviewers' comments:

6 Apr 2020

PONE-D-19-30167R1

Novel insights into serodiagnosis and epidemiology of Erysipelothrix rhusiopathiae, a newly recognized pathogen in muskoxen (Ovibos moschatus)

Dear Dr. Mavrot:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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