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Identification of eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula) infection levels in Northern bobwhite quail (Colinus virginianus) of the Rolling Plains, TX using a mobile research laboratory: Implications for regional surveillance

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Over the last few decades, there has been a decline in Northern bobwhite quail (Colinus virginianus) throughout their native range. While there are various factors that may be influencing this decline, it is suggested that parasites should be taken into consideration as a potential contributor in the Rolling Plains Ecoregion. High prevalence of the eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula) in bobwhite of this region, coupled with a continuous decline, creates a need to assess infection through alternative methods for regional surveillance. Previous studies have developed a qPCR method and mobile research laboratory as an option for nonlethal procedures. However, there is still a need for standardization of these techniques. Therefore, this study builds on previous protocols to develop an application that considers factors that may influence qPCR results. In this study, cloacal swabs are collected from bobwhite in three locations throughout the Rolling Plains and scaled based on amount of feces present on the swab. This data is compared to qPCR standards as a limit of quantification for both eyeworm and caecal worm to define parasitic infection levels. Binary logistic regressions confirm that the probability of detection increases for both eyeworm (Odds Ratio: 2.3738; 95% Confidence Interval: [1.7804, 3.1649]) and caecal worm (Odds Ratio: 2.8516; 95% Confidence Interval: [2.2235, 3.6570]) as swab score increases. Infection levels for eyeworm and caecal worm are based on the generated cycle threshold value averages of qPCR standards. Based on the results of this study, this method can be applied in the mobile research laboratory to quantitatively assess regional parasitic infection in bobwhite throughout the Rolling Plains.
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Biomolecular Detection and Quantication
journal homepage: www.elsevier.com/locate/bdq
Identication of eyeworm (Oxyspirura petrowi) and caecal worm
(Aulonocephalus pennula) infection levels in Northern bobwhite quail
(Colinus virginianus) of the Rolling Plains, TX using a mobile research
laboratory: Implications for regional surveillance
Kendall R. Blanchard
a
, Aravindan Kalyanasundaram
a
, Cassandra Henry
a
, Kelly A. Commons
a
,
Matthew Z. Brym
a
, Kalin Skinner
a
, James G. Surles
b
, Ronald J. Kendall
a,
a
The Wildlife Toxicology Laboratory, Texas Tech University, P.O. Box 43290, Lubbock, TX, 79409-3290, USA
b
The Department of Mathematics and Statistics, P.O. Box 41042, Texas Tech University, Lubbock, TX, 79409-1042, USA
ARTICLE INFO
Handled by: Jim Huggett
Keywords:
Bobwhite
Caecal
Eyeworm
Rolling plains
Surveillance
qPCR
ABSTRACT
Over the last few decades, there has been a decline in Northern bobwhite quail (Colinus virginianus) throughout
their native range. While there are various factors that may be inuencing this decline, it is suggested that
parasites should be taken into consideration as a potential contributor in the Rolling Plains Ecoregion. High
prevalence of the eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula) in bobwhite of this
region, coupled with a continuous decline, creates a need to assess infection through alternative methods for
regional surveillance. Previous studies have developed a qPCR method and mobile research laboratory as an
option for nonlethal procedures. However, there is still a need for standardization of these techniques. Therefore,
this study builds on previous protocols to develop an application that considers factors that may inuence qPCR
results. In this study, cloacal swabs are collected from bobwhite in three locations throughout the Rolling Plains
and scaled based on amount of feces present on the swab. This data is compared to qPCR standards as a limit of
quantication for both eyeworm and caecal worm to dene parasitic infection levels. Binary logistic regressions
conrm that the probability of detection increases for both eyeworm (Odds Ratio: 2.3738; 95% Condence
Interval: [1.7804, 3.1649]) and caecal worm (Odds Ratio: 2.8516; 95% Condence Interval: [2.2235, 3.6570])
as swab score increases. Infection levels for eyeworm and caecal worm are based on the generated cycle
threshold value averages of qPCR standards. Based on the results of this study, this method can be applied in the
mobile research laboratory to quantitatively assess regional parasitic infection in bobwhite throughout the
Rolling Plains.
1. Introduction
Since the 1960s, there has been an annual decline of over 4% in
Northern bobwhite quail (Colinus virginianus Linnaeus, 1758; hereafter
bobwhite) throughout their native range [1]. This decline has received
increasing attention in the Rolling Plains Ecoregion of West Texas,
considered one of the last strongholds of this popular gamebird [2]. In
this region, parasites have been an especially notable concern due to
the prevalence of two heteroxenous nematodes, the eyeworm (Oxy-
spirura petrowi Skrjabin, 1929) and caecal worm (Aulonocephalus pen-
nula Chandler, 1935), infecting bobwhite [36].
The wide-spread prevalence of the eyeworm and caecal worm in
bobwhite of the Rolling Plains has led to a necessity for regional
surveillance. Common methods of assessing parasite prevalence in
bobwhite have largely consisted of necropsies (e.g. [3,4,6,7]) which can
involve time, money, and intense labor. Similar problems arise when
using fecal oats as a nonlethal alternative, with the additional risk of
potentially misidentifying parasite specieseggs [8]. Nonlethal proce-
dures are made even more dicult given no reported evidence of
eyeworm or caecal worm expulsion in the feces of bobwhite for mor-
phological identication. Consequently, Kalyanasundaram et al. [9]
successfully developed an accurate and precise multiplex quantitative
PCR (qPCR) method to detect eyeworm and caecal worm egg presence
in bobwhite feces, which has been utilized in a mobile research la-
boratory [10]. This progress has provided an opportunity to nonlethally
assess parasitic infection in bobwhite and also provides a platform for
https://doi.org/10.1016/j.bdq.2019.100092
Received 28 February 2019; Received in revised form 3 June 2019; Accepted 18 June 2019
Corresponding author.
E-mail address: ron.kendall@ttu.edu (R.J. Kendall).
Biomolecular Detection and Quantification 17 (2019) 100092
2214-7535/ © 2019 Published by Elsevier GmbH. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T
widespread parasite surveillance in bobwhite populations throughout
the Rolling Plains Ecoregion.
Regular surveillance of parasitic infection is vital as it can track the
eciency of mitigation eorts after rounds of treatment [11,12]. Ad-
ditionally, surveillance may be especially important when considering
that these nematodes are thought to enter diapause, a state of halted
growth and development, when environmental conditions are poor
[13]. Diapause has even been suggested to hinder the eectiveness of
anthelmintic treatments due to parasitic inactivity at this time [14,15].
To prevent this, Easton et al. [16] suggests that qPCR assays may be
useful in monitoring the intensity of parasitic infections in areas where
multiple treatments have occurred to trace re-infections or low intensity
infections.
While feces is the best sample type when using qPCR to detect
eyeworms and caecal worms, it has been suggested that cloacal swabs
are more ecient to collect in eld applications [9,10,17]. However,
cloacal swab eciency in determining infection may be dependent on
the amount of feces present in the swab and thus, may aect the out-
come of qPCR results. This issue presents a need to standardize tech-
niques that can be eectively communicated to landowners, hunters,
and others in the Rolling Plains who may be interested in mitigation
opportunities. Therefore, this study expands on the protocols outlined
in Blanchard et al. [10], where cloacal swabs will be scaled based on the
presence of feces on the swab in order to identify if scaling is an e-
cient method for determining infection. This study also examines ap-
propriate ways for identifying low, moderate, and high infection based
on cycle threshold (C
t
) values in qPCR. Lastly, this study will also
present a method for handling non-detects for eyeworm and caecal
worm qPCR detection.
2. Materials and Methods
2.1. Ethics statement
This experiment was approved by Texas Tech University Animal
Care and Use Committee under protocol 16071-08. All bobwhites were
trapped and handled according to Texas Parks and Wildlife permit SPR-
0715-095.
2.2. Sample collection and processing
The mobile research laboratory was deployed to three locations in
the Rolling Plains Ecoregion including Cottle, Garza, and Mitchell
Counties. Bobwhite sample collection occurred between March and
October of 2018 following the procedures described in Dunham et al.
[7] with an additional trap check in the afternoon for a total of 3 trap
checks per day. Upon collection, bobwhites were banded, aged, sexed,
weighed, given a body condition score, and a cloacal swab was taken.
Birds that were collected and transported to The Institute of Environ-
mental and Human Health Aviary were re-swabbed and had feces col-
lected within 13 days of their arrival. Samples were processed in the
mobile laboratory as described by Blanchard et al. [10]. Samples that
were not immediately extracted upon collection were stored at 20 °C
until extraction.
2.3. DNA extraction and qPCR
DNA extraction protocols followed procedures outlined in
Kalyanasundaram et al. [9] and Kistler et al. [17]. Fecal samples were
weighed to 180220 mg prior to extraction. Every 12th sample in a
DNA extraction was used as a control for contamination. Quantitative
PCR protocols used Taqman Fast Advanced Mastermix (Applied Bio-
systems, 4,444,557) with a nal mastermix volume of 20 μL as de-
scribed in Kalyanasundaram et al. [9] following the same qPCR running
conditions. All samples were run in duplicates. Primer and probe se-
quences used (Sigma Aldrich, USA) in this study are presented in
Table 1. A negative control was used in each qPCR run on a 96-well
plate (Applied Biosystems, 4,346,907). There was no evidence of con-
tamination in the DNA extraction controls and qPCR controls.
2.4. Swab scoring
Swabs were scaled between 04 at the time of extraction. Fecal
samples were also included in statistical analyses and denoted with a
score of 5. The cloacal swab scaling is as follows: a 0 is scored when
there is no visible fecal matter on the swab; a 1 has small ecks of feces
on the swab to indicate the presence of feces; a 2 has small clumps of
feces on the swab; a 3 has smears and clumps of fecal matter on the
swab; and a 4 was used when excessively large clumps of feces were
present and the swab was saturated in fecal matter (Fig. 1).
2.5. Infection level classication
Infection levels were classied by comparing C
t
values generated for
swabs to C
t
values generated by the standards as a limit of quantica-
tion (LOQ). Standards in this study consist of serially diluted plasmid
DNA collected from eyeworm and caecal worm and are the same
standards outlined in Kalyanasundaram et al. [9] and Kistler et al. [17].
Concentrations for the standards ranged from 10
1
to 10
5
copy numbers.
2.6. Data analysis
Statistical applications were run in Minitab (v18). A total of 234
samples each for eyeworm and caecal worm were used in binary logistic
regression analyses for the swab scoring data analysis. Probability
distributions for the predicted probability of detection were generated
from the binary logistic regression analyses.
3. Results and Discussion
Scoring as a method of health assessment has risen in popularity
over the past several decades. This has been practiced in both terrestrial
species [18,19] and marine mammals [20]. Swab scoring was adopted
based on this concept in order to determine the eciency of scoring in
relation to the probability of detection of eyeworm and caecal worm
infection by qPCR. Here, it is demonstrated that as the swab score in-
creases from 0 to 5, the probability of detection for both eyeworm
(Odds Ratio: 2.3738; 95% Condence Interval: [1.7804, 3.1649];
Fig. 2A) and caecal worm (Odds Ratio: 2.8516; 95% Condence In-
terval: [2.2235, 3.6570]; Fig. 2B) also increases. These statistical ana-
lyses conrm earlier conclusions of feces samples as the best method for
identifying parasitic infection in bobwhite by qPCR [9,17]. While fecal
samples have a higher likelihood of producing positive results, cloacal
swabs are easier to collect in the eld and reduce stress on the bird
[17]. For this reason, when cloacal swabs are collected in the eld,
scores of 3 and 4 will be considered as more reliable data to represent
infection in a population
However, LOQs in qPCR should also be taken into consideration in
determining cut-ovalues for positive results as well. Determining the
LOQ should rely on DNA of a known concentration, like qPCR standards
[21]. Therefore, the C
t
value average of the lowest detected copy
numbers of qPCR standards for each parasite should be considered as
the LOQ, with any potentially positive result to be considered negative
if above those C
t
value averages. Based on this proposition and the
standards represented in Fig. 3, infection levels for eyeworm are as
follows: low infection is < 10 copy numbers, moderate infection at 10
copy numbers to 1,000 copy numbers, and high infection at > 1,000
copy numbers. For caecal worm, low infection is < 100 copy numbers,
moderate infection at 100 copy numbers to 10,000 copy numbers, and
high infection at > 10,000 copy numbers. These results are outlined
with corresponding C
t
value ranges in Table 2. In addition to the pro-
posed LOQ and infection levels, previous cut-ovalues between a
K.R. Blanchard, et al. Biomolecular Detection and Quantification 17 (2019) 100092
2
positive and negative result for this qPCR method suggested in Blan-
chard et al. [10] should still be upheld.
Nevertheless, the issue remains that samples that are generated
outside the threshold of detection in qPCR, or non-detects, need to be
considered in order to appropriately assess overall infection regionally.
There is much debate in how to treat these non-detects in quantitative
analyses, with the aim to reduce bias where possible [2224]. At pre-
sent, there is not a singularly accepted method for handling non-detects
in qPCR [25]. In order to maintain minimal bias in this study, it is
proposed that non-detects could be substituted with the generated C
t
value average of the lowest copy number. For example, based on values
presented in this study, C
t
value averages of 36 for caecal worm and
35.5 for eyeworm can be considered limits of quantication for either
parasite and substitute non-detects. By substituting these values, an
overall infection level could be determined for a location by averaging
all C
t
values for that site. This method likely reduces bias because the
limit of detection is based on quantiable data. It may also reduce bias
as McCall et al. [25] revealed that replacing non-detects with 35, in-
stead of 0 or 40, reduced bias and suggested that non-detects may
sometimes signify a failure to detect a true C
t
value < 40. Finally, the
process of substituting non-detects becomes especially helpful with
swab scores of 02 that generate non-detects but may not necessarily
mean the bobwhite is uninfected. These individuals can be considered
to have low infection to decrease the risk of a false negative, particu-
larly when considering if other factors that facilitate infection spread
may be present in the tested area.
Eyeworm and caecal worm infection levels of low, moderate, and
high could also be used as an index of parasite prevalence in a
Table 1
Primer and probe sequences used in multiplex qPCR of parasitic infection in bobwhite.
Primer/Probe Sequence Target Product Size
Oxy2448F GTTTCCTCATGTGATTTCATTTTGT Eyeworm ITS2 [17] 149 bp
Oxy2597R ATAAACGTTATTGTTGCCATATGCT
Oxy_Probe_1 FAM-AAAGAAAGGTAATTCATCTGGT-MGB
Apen F1 GGGTTGTGGTACTAGGTGGGT Caecal Worm COX1 [9] 120 bp
Apen R1 GCACCCAAAATAGAACTCACCCC
Apen_Probe_1 VIC-GGTCATCCTGGTAGAAGCGTTG-MGB
ND2_70F CAACCACTGAATCATAGCCTGAAC Northern Bobwhite NADH2 [17] 79bp
ND2_149R GGTGGTGGGATTTTGAAATGAG
Quail_ND2_Probe1 NED-AGGAACCACAATCAC-MGB
Fig. 1. Illustration of cloacal swab scores based on feces present on the swab.
Fig. 2. Scatterplots of swab score and the predicted probability of detection of eyeworm (A) and caecal worm (B) by qPCR produced from binary logistic regressions.
Solid lines depict estimated probability and dotted lines depict 95% condence intervals.
K.R. Blanchard, et al. Biomolecular Detection and Quantification 17 (2019) 100092
3
population. Often times, these assessments can be combined with a
variety of factors to comprise the overall health of a population. The
index of biological integrity (IBI), for example, using sh assemblages is
a popular method for regional assessments of aquatic environment
health [26,27]. This index scores various physical, chemical, and bio-
logical conditions to rate water quality and aquatic communities. Si-
milarly, in human medicine, the Braden scale is used often for accu-
rately predicting the likelihood of elderly patients developing pressure
ulcers based on scored evaluations [28]. A similar type of index as-
sessment could be applied to bobwhite in the Rolling Plains. This could
include a collaborative eort of analyzing and scoring factors like insect
intermediate host diversity, habitat quality, eyeworm and caecal worm
infection levels in the mobile laboratory, and nesting success to assess
bobwhite population health in the Rolling Plains Ecoregion.
4. Conclusions
Overall, we conclude that assigning a scale to cloacal swabs col-
lected in the eld will help in accurately identifying eyeworm and
caecal worm infection levels. Based on this data, scaling swabs in ac-
cordance with fecal material can aid in determining the probability of
detection in qPCR, where higher swab scores lessen the likelihood of a
false negative in bobwhite. These methods also provide a quantiable
estimate using the established LOQ to properly assess and compare
infection levels across the Rolling Plains Ecoregion in addition to a level
of infection that can be clearly communicated to stakeholders during
the judgement and recommendation of mitigation procedures.
Furthermore, with the application of these methods, the mobile re-
search laboratory can perform consistent surveillance in areas receiving
regular anthelmintic treatment while also comparing levels of infection
regionally in relation to spatial and temporal factors that may inuence
eyeworm and caecal worm infection in bobwhite.
Funding
We thank Rolling Plains Quail Research Foundation (23A470) and
Park Cities Quail Coalition (23A540) for their nancial support of our
quail research.
Declaration of Competing Interest
The authors declare that there are no conicts of interest in this
study.
Acknowledgements
We thank our sponsors for providing the nancial means to make
this study possible. We also thank the employees and volunteers of
Matador Wildlife Management Area and Dalby Ranch in aiding our
research eorts where possible. We also thank each of our study sites
for providing us accommodations to perform this study. Finally, we
thank all the laboratory members for their eld and laboratory assis-
tance.
Appendix A. Supplementary data
Supplementary material related to this article can be found, in the
online version, at doi:https://doi.org/10.1016/j.bdq.2019.100092.
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