Study on the prevalence and genetic diversity of Eimeria species from broilers and free-range chickens in KwaZulu-Natal province, South Africa

Abstract

This study was conducted from January to October 2018 with the objective to determine the prevalence and genetic diversity of Eimeria species in broiler and free-range chickens in KwaZulu-Natal province, South Africa. A total of 342 faecal samples were collected from 12 randomly selected healthy broiler chicken farms and 40 free-range chickens from 10 different locations. Faecal samples were screened for the presence of Eimeria oocysts using a standard flotation method. The species of Eimeria isolates were confirmed by amplification of the internal transcribed spacer 1 (ITS-1) partial region and sequences analysis. Among broiler and free-ranging chickens, 19 out of 41 pens (46.3%) and 25 out of 42 faecal samples (59.5%) were positive for Eimeria infection. Molecular detection revealed the following species: Eimeria maxima, Eimeria tenella, Eimeria acervulina, Eimeria brunetti and Eimeria mitis in all the samples screened. Similarly, polymerase chain reaction assays specific for three cryptic Eimeria operational taxonomic units were negative for all the samples. Phylogenetic analysis of the ITS-1 sequences supported species identity with the greatest variation detected for E. mitis. This study provides information on the range and identity of Eimeria species, and their genetic relatedness, circulating in commercially reared broilers and free-ranging chickens from different locations in KwaZulu-Natal province.

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Onderstepoort Journal of Veterinary Research
ISSN: (Online) 2219-0635, (Print) 0030-2465
Page 1 of 10 Original Research
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Authors:
Abiodun J. Fatoba1
Oliver T. Zishiri1
Damer P. Blake2
Sunday O. Peters3
Jerey Lebepe4
Samson Mukararwa5
Mahew A. Adeleke1
Aliaons:
1Discipline of Genecs,
School of Life Sciences,
College of Agriculture,
Engineering and Sciences,
University of KwaZulu-Natal,
Westville, South Africa
2Department of Pathobiology
and Populaon Sciences,
The Royal Veterinary College,
Hawkshead Lane,
Herordshire,
United Kingdom
3Department of Animal
Science, Berry College,
Mount Berry, Georgia,
United States
4Department of Biodiversity
and Evoluonary Biology,
School of Life Sciences,
College of Agriculture,
Engineering and Sciences,
University of KwaZulu-Natal,
Durban, South Africa
5Department of Biological
Sciences, School of Life
Sciences, College of
Agriculture, Engineering and
Sciences, University of
KwaZulu-Natal, Durban,
South Africa
Corresponding author:
Mahew Adeleke
adelekem@ukzn.ac.za
Introducon
Poultry production has become a major driving force in the economy of many developing
countries, which are countries characterised by low income and gross domestic product
per capita (Alders & Pym 2009). South Africa produced 129.3 million chickens
throughout the nine provinces in 2017, of which 7% were from KwaZulu-Natal (South African
Poultry Association 2017). The vulnerability of chickens under commercial production to
parasitic diseases such as coccidiosis is a major threat to the productivity and viability of
the South African poultry industry.
Coccidiosis is an enteric disease that reduces performance and affects the welfare of chickens,
leading to high morbidity and mortality in the absence of effective control (Blake & Tomley
2014). Globally, the annual burden of preventing/controlling coccidiosis has been estimated
to exceed $3 billion (Blake & Tomley 2014). Eimeria, a parasite of the phylum Apicomplexa,
is the causative agent of this disease, and its species such as Eimeria necatrix, Eimeria
maxima, Eimeria acervulina, Eimeria praecox, Eimeria mitis, Eimeria brunetti and Eimeria tenella
are also known to infect chickens (Nematollahi, Moghaddam & Niyazpour 2008). Mixed
infections are common (Haug et al. 2008; Jenkins et al. 2008), thereby complicating diagnosis
and effective control. The emergence of three cryptic Eimeria genotypes, referred to as
operational taxonomic units (OTUs) x, y and z, has added further complexity. These were
first detected circulating among commercial chickens reared in Australia (Cantacessi et al.
2008). The three OTU genotypes have since been reported in several African countries, such
as Nigeria, Tanzania, Ghana, Uganda and Zambia (Clark et al. 2016; Jatau et al. 2016).
The widespread occurrence of these cryptic genotypes could pose a significant risk to
vaccine development and application (Clark et al. 2016).
This study was conducted from January to October 2018 with the objective to determine the
prevalence and genetic diversity of Eimeria species in broiler and free-range chickens in
KwaZulu-Natal province, South Africa. A total of 342 faecal samples were collected from
12 randomly selected healthy broiler chicken farms and 40 free-range chickens from
10 different locations. Faecal samples were screened for the presence of Eimeria oocysts
using a standard flotation method. The species of Eimeria isolates were confirmed by
amplification of the internal transcribed spacer 1 (ITS-1) partial region and sequences
analysis. Among broiler and free-ranging chickens, 19 out of 41 pens (46.3%) and 25 out of
42 faecal samples (59.5%) were positive for Eimeria infection. Molecular detection revealed
the following species: Eimeria maxima, Eimeria tenella, Eimeria acervulina, Eimeria brunetti
and Eimeria mitis in all the samples screened. Similarly, polymerase chain reaction assays
specific for three cryptic Eimeria operational taxonomic units were negative for all the
samples. Phylogenetic analysis of the ITS-1 sequences supported species identity with
the greatest variation detected for E. mitis. This study provides information on the range and
identity of Eimeria species, and their genetic relatedness, circulating in commercially reared
broilers and free-ranging chickens from different locations in KwaZulu-Natal province.
Keywords: chickens; coccidiosis; Eimeria; genetic diversity; molecular diagnosis; prevalence.
Study on the prevalence and genec diversity of
Eimeria species from broilers and free-range chickens in
KwaZulu-Natal province, South Africa
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Dates : Received: 27 Nov. 2019 | Accepted: 25 June 2020 | Published: 17 Sept. 2020
How to cite this arcle: Fatoba, A.J., Zishiri, O.T., Blake, D.P., Peters, S.O., Lebepe, J., Mukararwa, S., et al. 2020, ‘Study on the prevalence
and genec diversity of Eimeria species from broilers and free-range chickens in KwaZulu-Natal province, South Africa’, Onderstepoort
Journal of Veterinary Research 87(1), a1837. hps://doi.org/10.4102/ojvr.v87i1.1837
Copyright: © 2020. The Authors. Licensee: AOSIS. This work is licensed under the Creave Commons Aribuon License.

Page 2 of 10 Original Research
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Effective control of coccidiosis in chickens relies on strict
management practices, supplemented by timely application
of anticoccidial drugs and/or vaccines (Godwin & Morgan
2015) underpinned by proper diagnosis and identification.
Traditional diagnostic methods include evaluation of the
location and the characteristics of gross pathology (lesion
scoring) and microscopic analysis of oocyst morphology
(Kumar et al. 2014). However, the relative complexity and
requirement of expertise for these methods necessitated
the development of molecular alternatives, including
genus- and species-specific polymerase chain reaction
(PCR) assays (Lew et al. 2003). The use of nuclear and
mitochondrial genetic markers (e.g. internal transcribed
spacer [ITS] sequences, 18S ribosomal RNA, cytochrome
oxidase subunit I [COI]) has proven effective in the
identification and taxonomic classification of protozoan
parasites, including Eimeria (Kumar et al. 2015a; Ogedengbe
et al. 2018; Tan et al. 2017).
Thus, ITS-1 sequences have served as genetic markers to
identify Eimeria species (Cook et al. 2010; Oliveira et al.
2011). Based on the observed diversity, ITS-based species-
specific primers have been developed for use in the
identification of Eimeria species (Lew et al. 2003). However,
studies from various countries have reported nucleotide
variations in the ITS-1 region within Eimeria species isolates
(Bhaskaran et al. 2010; Kumar et al. 2015a; Lew et al. 2003).
Genetic diversity among species and strains of Eimeria
could pose a major risk to the control of coccidiosis in the
future. As such, knowledge defining naturally occurring
genetic diversity becomes imperative to understand the
pathogenicity and epidemiology of Eimeria that infect
chickens (Morris & Gasser 2006).
There is a dearth of information on Eimeria occurrence
and diversity in South Africa. As such, reports on circulating
Eimeria species in KwaZulu-Natal province together with
information on their occurrence in commercial chickens are
not available. This study, therefore, aimed to determine
prevalence and genetic diversity of Eimeria species in
both broiler and free-range chickens in KwaZulu-Natal
province.
Materials and methods
Study area
KwaZulu-Natal is the second most populous province
among the nine provinces in South Africa. It has a
population of approximately 10 million people and land
size of 94 000 km2 located between latitude 28°99’S and
longitude 30°97’E. The capital city of Pietermaritzburg has
a warm and subtropical climate throughout the year,
especially around the coastline, but gets colder in the
inland areas. The poultry industry in KwaZulu-Natal
province is one of the producers of broiler birds in South
Africa with a total of 6.7 million broiler birds in 2017,
contributing 6.4% to the national broiler production (South
African Poultry Association 2017).
Sample collecon
A total of 342 chicken faecal samples were collected from 12
broiler farms consisting of 41 pens (1–5 pens per farm) and
free-range chickens. The age of broiler chickens at the time of
sampling ranged from 3 to 10 weeks, with the exception of a
single farm consisting of 12-week-old chickens. In addition,
42 faecal samples of 40 free-ranging 3-week-old village
chickens were randomly collected from four localities. The
342 samples were collected randomly once from the following
locations: Pietermaritzburg, Phoenix, Scottburg, Stanger,
Chatsworth, Westville, Maphumulo, Umvoti, Port
Sherpstone and Shongweni of KwaZulu-Natal province from
January to October 2018. Detailed information on the number
of pens per farm, number of samples per pen, number of farms
per location and number of chickens per location is shown in
Appendix 1 Tables 1-A1 and 2-A1. There were no clinical signs
of coccidiosis among the chickens on any of the farms sampled.
Samples were collected following the procedure described by
Kumar et al. (2014). Briefly, in the broiler farms, faecal samples
were collected following a pre-determined ‘W’ pathway in
each pen to allow random sampling. Fifty-millilitre conical
tubes containing 10 mL of 2% potassium dichromate were
used to collect faeces up to 20 mL of the tube and stored at
4 °C until further use. Depending on the size of the pen, four
to eight 50-mL conical tubes of faecal samples were collected
per pen and the content was mixed together vigorously.
Sample processing and microscopic
oocyst idencaon
Samples were processed based on the procedures described
by Kumar et al. (2014), with minor modifications. Two grams
of faecal samples were weighed into a beaker and mixed with
100 mL of distilled water. This was stirred with a glass rod
and later filtered through a gauze. The filtrate was transferred
into a new 50-mL conical tube and filled to the brim with
saturated salt solution. This was then centrifuged at 800 × g
for 10 minutes. The supernatant was decanted and the
sediment was transferred into a new 50-mL tube and then
later pelleted at 14 000 × g for 3 min. Oocysts per gram (OPG)
were counted using a McMaster counting chamber following
a standard protocol (Haug, Williams & Larsen 2006). Samples
with OPG greater or equal to 250 OPG were selected for
deoxyribonucleic acid (DNA) extraction. Photomicrograph
images of unsporulated oocysts were taken randomly from
each farm sampled using an OMAX compound microscope
containing a 5 MP camera at 400×.
DNA extracon
Total genomic DNA was extracted using a Quick-DNATM
Fecal/Soil Microbe Miniprep Kit (Zymo Research, United
States [US]) based on the manufacturer’s protocol with
minor modifications. Faecal samples in the Bashing BeadsTM
lysis tube (0.1 mm and 0.5 mm) were processed on a Vortex
Genie at maximum speed for 25 min, instead of 20 min as
recommended by the manufacturer’s protocol. DNA quality
and concentration were checked on an agarose gel (1.5%) and
NanodropTM 1000 spectrophotometer (Thermo Scientific, US)
at 260 nm absorbance.

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Polymerase chain reacon amplicaon
A nested PCR protocol targeting the genomic ITS-1 region
was used to detect each Eimeria species. Genus- and species-
specific primers were used as described by Lew et al.
(2003). Each 25 µL PCR contained 12.5 µL 2X DreamTaq
Green PCR Master Mix (Thermo Scientific, US), 1 µL of
each forward and reverse primer (10 µM of stock solution;
Table 1), 5.5 µL nuclease free water and 5 µL DNA template.
Thermal cycling was done as follows: initial denaturation
at 94 °C for 3 min, 30 cycles of 94 °C for 30 s, 56 °C for 30
seconds and 72 °C for 90 s and a final extension at 72 °C for
15 min. The primary PCR product (1 µL of the 25 µL) was
used as template for the nested PCR containing species-
specific primers in each tube. The same thermal cycling
conditions were used for the species with varying annealing
temperature as follows: 55 °C for E. mitis, 56.7 °C for
E. tenella, 61 °C for E. acervulina, 62 °C for E. maxima, 61 °C
for E. necatrix, 61 °C for E. praecox and 61 °C for E. brunetti.
Nuclease-free water replaced the DNA template for the
negative control. Amplification of nested PCR products
was checked on 1.5% (w/v) agarose gel at 100 V for 30 min
and visualised under ultraviolet light using a Bio-Rad
ChemiDocTM MP System (Bio-Rad, US). Similarly, the
samples were also screened for the presence of three cryptic
Eimeria OTUs by targeting the ITS-2 genomic region using
the primers and thermal cycling procedure described by
Fornace et al. (2013), as shown in Table 2. The PCR products
were sent for sequencing at Inqaba Biotech (South Africa).
Sequencing was done with both forward and reverse
primers using Big Dye chemistries in an ABI 3500XL
Genetic Analyzer, POP-7TM (Thermo Scientific, US).
Sequence analysis
A total of 28 ITS-1 sequences were viewed, edited and
trimmed. Consensus sequences were generated from both
forward and reverse sequences using BioEdit version 7.0.5.3
software (Hall 1999). The sequences were submitted to
National Center Biotechnology Information and assigned
accession numbers (Appendix 1 Table 3-A1). Also, the
sequences were compared with selected published sequences
from the GenBank. Sequence alignment was performed using
the ClustalW programme. Pairwise percentage identity
(Appendix 1 Figure 1-A1) was carried using Sequence
Demarcation Tool (SDT) version 1.2 software (Muhire, Varsani
& Martin 2014). Genetic distance within Eimeria species
isolates from this study was calculated with MEGA version
6.0 (Tamura et al. 2013) using the Tamura 3-parameter model.
Phylogenec analysis of internal transcribed
spacer-1 sequences
The genetic diversity that exists between the ITS-1 sequences
generated in this study (n = 28) and those of American,
Chinese, Indian, Australian, Egypt, Sudan and Swedish
TABLE 2: Primers used for the detecon of three crypc Eimeria operaonal taxonomic units.
Species Primer ref Primer sequences Annealing temperature (°C) Size (bp)
OTUx OTU_X_f1 GTGGTGTCGTCTGCGCGT 56 133
OTU_X_r1 ACCACCGTATCTCTTTCGTGA
OTUy OTU_Y_f1 CAAGAAGTACACTACCACAGCATG 56 346
OTU_Y_r1 ACTGATTTCAGGTCTAAAACGAAT
OTUz OTU_Z_f1 TATAGTTTCTTTTGCGCGTTGC 56 147
OTU_Z_r1 CATATCTCTT TCATGAACGAAAGG
Source: Lew, A.E., Anderson, G.R., Minchin, C.M., Jeston, P.J. & Jorgensen, W.K., 2003, ‘Inter-and intra-strain variaon and PCR detecon of the internal transcribed spacer 1 (ITS-1) sequences of
Australian isolates of Eimeria species from chickens’, Veterinary Parasitology 112(1–2), 33–50. hps://doi.org/10.1016/S0304-4017 (02)00393-X
Primers were all designed by Fornace et al. (2013).
OTUs, operaonal taxonomic units; bp, base pair.
TABLE 1: Genus- and species-specic internal transcribed spacer-1 primers used in the study.
Genus-species Primer strand Primers Annealing temperature (°C) Length (bp)
Eimeria genus Forward AAGTTGCGTAAATAG AGCCCTC 56.0 Variable
Reverse AGACATCCATTGCTG AAAG
Eimeria tenella Forward AATTTAGTCCATCGC AACCCT 56.7 278
Reverse CGAGCGCTCTGCATA CGACA
Eimeria acervulina Forward GGC TTGGATGATGTT TGCTG 61.0 321
Reverse CGAACGCAATAACAC ACGCT
Eimeria brune Forward GATCAG TTTGAGCAA ACCTTCG 61.0 311
Reverse TGGTCT TCCGTACGT CGGAT
Eimeria maxima Forward CTACACCACTCAC AATGAGGCAC 62.0 145
Reverse GTGATATCGTTCTG GAGAAGTT TGC
Eimeria mis Forward GGGTTTATTTCCTGT CCGTCGTCTC 55.0 328
Reverse GCAAGAGAGAATCGG AATGCC
Eimeria praecox Forward CCAAGCGATTTCATC ATTCGGGGAG 61.0 116
Reverse AAAAGCAACAGCGA TTCAAG
Eimeria necatrix Forward TACATCCCAATCTTT GAATCG 61.0 383
Reverse GGCATACTAGCTTCG AGCAAC
Source: Lew, A.E., Anderson, G.R., Minchin, C.M., Jeston, P.J. & Jorgensen, W.K., 2003, ‘Inter-and intra-strain variaon and PCR detecon of the internal transcribed spacer 1 (ITS-1) sequences of
Australian isolates of Eimeria species from chickens’, Veterinary Parasitology 112(1–2), 33–50. hps://doi.org/10.1016/S0304-4017 (02)00393-X
Primers were all designed by Lew et al. (2003).

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Eimeria species isolates published in GenBank (Appendix 1
Table 4-A1) were analysed. Phylogenetic analyses using the
maximum likelihood (ML) method were carried out with
MEGA version 6.0 (Tamura et al. 2013). The nucleotide
substitution model that best fitted the data set was identified
using Model-Test in MEGA6. Based on the Akaike
Information Criterion, the Jukes–Cantor model was
identified as the best model. Gaps in the alignment were
treated as missing characters. Bootstrap iteration was based
on 1000 replicates and the percentage value was indicated at
each node. Neospora caninum (GenBank accession number:
AF038860.1) and Toxoplasma gondii (EU025025.1) were used
as out-group species to root the tree.
Stascal analysis
Data generated were analysed using the Statistical Package
for the Social Sciences (SPSS) software version 25.0.
Descriptive statistics were used to determine the prevalence
of detected Eimeria species.
Ethical consideraon
The protocol for this study was approved by the University
of KwaZulu-Natal Animal Research Ethics Committee and
assigned the reference number AREC/058/017D.
Results
Polymerase chain reacon amplicaon and
microscopic unsporulated oocyst detecon
Among broiler and free-ranging chickens, 19 out of 41 pens
(46.3%) and 25 out of 42 samples (59.5%) were positive for
Eimeria infection (Figure 1). The highest level of Eimeria
infection was observed in the following locations in both
broiler and free-ranging chickens as shown in Figure 2:
Phoenix (7/41; 17.1%), Scottburg (4/41; 9.8%), Shongweni
(8/42; 19%), Port Sherpstone (7/42; 16.7%) and Maphumulo
(7/42; 16.7%).
Using the species-specific nested PCR assay, five Eimeria
species were identified (E. tenella, E. maxima, E. acervulina,
E. brunetti and E. mitis) in all screened samples (Figure 3).
In broiler farms, E. tenella had the highest prevalence (13/19;
68.4%), followed by E. maxima (9/19; 47.4%) based on pens
which were positive. However, in free-ranging chickens,
E. mitis (24/25; 96%) and E. maxima (23/25; 92%) had the
FIGURE 1: Images of unsporulated Eimeria oocysts detected in faecal samples
from infected farms.
100 μm 100 μm
FIGURE 2: Occurrence of Eimeria infecon in dierent locaons in KwaZulu-Natal.
0
2
4
6
8
10
Location
12
Occurrence of Eimeria infection
14
16
18
20
Maphumulo
Umvoti
Port Sherpstone
Shongweni
Pietermaritzburg
Phoenix
Scottburg
Stangers
Chatworth
Westville
Broiler chickens
Indigenous chickens
bp, base pairs.
FIGURE 3: Amplicaon of Eimeria species by polymerase chain reacon. M:
100 bp DNA marker; L2: negave control; L3–7: samples. (a) Eimeria mis
328 bp; (b) Eimeria tenella 278 bp; (c) Eimeria maxima 145 bp; (d) Eimeria
acervulina 321 bp; (e) Eimeria brune 311 bp.
ab
cd
e

Page 5 of 10 Original Research
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highest prevalence. The lowest prevalence was observed for
E. acervulina (5/19; 26.3%) and E. brunetti (3/25; 12%) in
broiler and free-ranging chickens, respectively (Figure 4).
DNA amplicaon of Eimeria species
The most common mixed species combinations detected in
broiler and free-ranging chicken faecal samples were
E. tenella + E. maxima (4/19; 21.1%) and E. mitis + E. maxima +
E. acervulina (11/25; 44%), respectively. Other combinations
were E. mitis + E. maxima (2/19; 10.5%), E. tenella + E. mitis
(1/25; 4%), E. acervulina + E. maxima (1/25; 4%), E. acervulina +
E. tenella (2/19; 10.5%), E. mitis + E. tenella (3/19; 15.8%),
E. acervulina + E. tenella + E. maxima (1/19; 5.3%), E. acervulina +
E. mitis + E. tenella (2/19; 10.5%), E. tenella + E. acervulina + E.
mitis + E. maxima (7/25; 28%), E. tenella + E. mitis + E. brunetti +
E. maxima (1/25; 4%), E. acervulina + E. mitis + E. tenella +
E. maxima (3/19; 15.8%) and E. tenella + E. acervulina + E. mitis +
E. maxima + E. brunetti (2/25; 8%). Overall, among the broiler
farms, Scottburg farm had the highest prevalence level of
mixed species (E. acervulina + E. mitis + E. tenella + E. maxima;
75%), whilst mixed species (E. acervulina + E. mitis + E. maxima)
with a prevalence of 44% was the highest among all locations
with the free-range chickens. Cryptic Eimeria OTUs were not
detected in all the samples screened.
Internal transcribed spacer-1 sequence analysis
Internal transcribed spacer-1 sequences of E. mitis, E. maxima,
E. tenella, E. acervulina and E. brunetti from this study showed
high homology with sequences from Eimeria species present
in the GenBank as follow: 90% – 93% identity for E. mitis,
99.31% for E. maxima, 99% – 100% for E. tenella, 99.38% for
E. acervulina and 100% for E. brunetti. The overall mean
genetic distance within Eimeria species isolates from
KwaZulu-Natal in South Africa calculated by ML (Tamura
3-parameter model) with 1000 bootstrap replicates was 1.14 ±
0.08. Mean genetic distance per species was as follows: E. mitis
(0.13 ± 0.014), E. maxima (0.09 ± 0.020), E. tenella (0.09 ± 0.012),
E. acervulina (0.02 ± 0.005) and E. brunetti (0.02 ± 0.006).
Phylogenec analysis of internal transcribed
spacer-1 sequences
Maximum likelihood with the Jukes–Cantor model was used
to create the phylogenetic tree (Figure 5) of the 28 ITS-1
sequences generated in this study, together with reference
Eimeria ITS-1 sequences of American, Chinese, Indian,
Australian and Swedish isolates. Irrespective of their
geographical locations, the ITS-1 sequences of all five species
clustered in distinct clades. Among the E. tenella clade, all the
seven E. tenella sequences from this study clustered with
E. tenella sequences from China, Egypt and India with a very
strong support. Similarly, all the five and eight sequences of
E. acervulina and E. mitis from this study, respectively,
clustered with E. acervulina and E. mitis sequences of America,
E. maxima, Eimeria maxima; E. acervulina, Eimeria acervulina; E. mis, Eimeria mis;
E. brunee, Eimeria brunee; E. tenella, Eimeria tenella.
FIGURE 4: Prevalence of Eimeria species in both broilers and free-range chickens
in KwaZulu-Natal.
0
20
Eimeria species
Prevalence rate
40
60
80
100
120
E. tenella E. mis E. maxima E. acervulina E. brune
Indigenous Chickens
Broilers Chickens
E. maxima, Eimeria maxima; E. acervulina, Eimeria acervulina; E. mis, Eimeria mis;
E. brunee, Eimeria brunee; E. tenella, Eimeria tenella; US, United States.
FIGURE 5: Maximum likelihood tree (Tamura-3 model) of internal transcribed
spacer-1 sequences of Eimeria species. Percentage of bootstrap (1000 replicate)
values is indicated in each node. The scale bar indicates sequence substuon
per site. Sequences in this study are in dierent colours and shapes.
E. tenella JX853831.1 (India)
JQ061003.1 E. tenella (Egypt)
E. tenella GQ153635.1 (China)
MV E. tenella MN727042
MP E. tenella MN727041
PS E. tenella MN727040
CH2 E. tenella MK404745
SG1 E. tenella MK404742
ST3 E. tenella MK404743
PX2 E. tenella MK404744
SH E. brune MN727047
JX853835.1 E. brunne (India)
PS E. brune MN727048
MP E. brune MN727049
AF446058.1 E. brune (Australia)
GQ856314.1 E. brune (India)
E. maxima JX853828.1 (India)
E. maxima FJ230340.1 (US)
PX1 E. maxima MK404734
MP E. maxima MN727039
WS1 E. maxima MK404736
SH E. maxima MN727037
PS E. maxima MN727038
PM2 E. mis MK404739
E. mis AF065093.1 (Sweden)
MV E. mis MN727036
WS2 E. mis MK404737
CH1 E. mis MK404741
SH E. mis MN727032
PS E. mis MN727033
MP1 E. mis MN727034
MP2 E. mis MN727035
E. mis FJ230372.1 (US)
E. mis JX853834.1 (India)
ST4 E. acervulina MK404748
SH E. acervulina MN727043
PS E. acervulina MN727044
MV E. acervulina MN727045
MP E. acervulina MN727046
E. acervulina AY779487.1 (US)
E. acervulina GQ856312.1 (India)
KY639280.1 E. acervulina (Sudan)
AF038860.1 Neospora caninum
EU025025.1 Toxoplasma gondii
99
94
64
51
85
99
94
76
91

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India, Sudan and Sweden with a very strong support. All the
E. maxima sequences from this study clustered with E. maxima
sequences from America and India with low support. Within
the E. brunetti clade, all the three sequences from this study
clustered with E. brunetti sequences from India and Australia
with a very strong support. Genetic distances between ITS-1
sequences of Eimeria isolates in this study and those of a
public database were as follow: E. mitis (0.12 ± 0.013),
E. acervulina (0.02 ± 0.005), E. maxima (0.07 ± 0.016), E. tenella
(0.07 ± 0.010) and E. brunetti (0.01 ± 0.004).
Discussion
Coccidiosis is an enteric disease that poses a threat to efficient
poultry production (Ogedengbe, Hanner & Barta 2011),
compromising economic productivity and chicken welfare.
For effective diagnosis, control and epidemiology of the
disease, the identification of specific species of Eimeria is
essential. Understanding the occurrence of genetic diversity
and regional population structure are important (Hamza,
Al-Massodi & Jeddoa 2015; Morris & Gasser 2006).
In this study, Eimeria infection had an overall prevalence of
46.3% (19 out of 41 pens) and 59.5% (25 out of 42 samples)
across different farms and locations, which was higher than
the 29.4% found among Eimeria parasites from KwaZulu-
Natal and Limpopo (Malatji et al. 2016). However, it was
lower than previous reports from other regions including
Ethiopia (56%; Luu et al. 2013), Romania (91%; Gyorke et al.
2013), Anhui Province, China (87.75%; Huang et al. 2017) and
two north Indian states (81.3%; Kumar et al. 2015b).
Molecular diagnosis using nested species-specific ITS-1
primers was used to identify five species of Eimeria (E. tenella,
E.maxima, E. acervulina, E. brunetti and E. mitis) circulating in
both commercial broiler and free-range chickens in KwaZulu-
Natal province. This is similar to the study of Debbou-
Iouknane, Benbarek and Ayad (2018), who reported the same
five species of Eimeria among broilers farms in Bejaia region
of Algeria. The prevalence of one or more species of Eimeria
in broiler farms in this study could be influenced by the
different anticoccidial used in various farms (Carvalho et al.
2011), although our study did not document anticoccidial use
in the farms.
The most prevalent species among broiler farms in this study
was E. tenella (68.4%), which is in agreement with other
studies that have reported a high prevalence that ranges from
80.67% to 100% in Anhui Province, China, Trinadad and
Indonesia (Brown et al. 2018; Hamid et al. 2018; Huang et al.
2017). The high prevalence of E. tenella poses a major concern
to the health status of chickens because it is associated with
caecal lesions causing haemorrhage, oedema and anaemia
(Iacob & Duma 2009). However, E. mitis (96%) had the highest
prevalence among free-ranging village chickens in this study.
The reason for this is unclear as it is contrary to reports of
most studies where E. acervulina and E. tenella are known to
be highly prevalent in most farms because of their high
reproductive potentials (Williams 2001).
Co-infection with multiple Eimeria species is a common
finding in many poultry farms (Aarthi et al. 2010; Haug
et al. 2008). We also found multiple infections (57.9% and
100%) to be common in both chicken types, with two or
more species among the samples examined. Eimeria tenella +
E. maxima (21.1%) and E. mitis + E. maxima + E. acervulina
(44%) were the most common co-infections. This is in line
with different studies which reported the frequency of
E. maxima in most mixed species infection (Kaboudi, Umar &
Munir, 2016).
Mixed infections among Eimeria species poses a challenge to
the control of coccidiosis in chickens as it can increase
pathogenicity of the disease among birds (Jekins et al. 2008).
It could also serve as a potential threat to the effectiveness of
anticoccidial vaccine, and this has warranted the combination
of different Eimeria strains in some species, such as E. maxima,
in the design of anticoccidial vaccines.
The efficacy of anticoccidial vaccines is under threat,
especially with the recent upsurge of new Eimeria variants
(OTUs), which was first detected circulating among
commercial birds in Australia (Cantacessi et al. 2008). The
presence of these OTUs (OTUx, OTUy and OTUz) has also
been reported across much of the Southern Hemisphere
(Clark et al. 2016; Fornace et al. 2013; Jatau et al. 2016). In this
study, none of the samples was positive for any of the three
OTUs. This could be because of the geographical location of
our study sample, which is on latitude 28°S. Although a
study has reported the distribution of these cryptic species
(OTUs) in the northern hemisphere (Jatau et al. 2016), a more
elaborate study by Clark et al. (2016) in 20 different countries
from five continents has opined that these OTUs are
distributed towards the south of the 30°N latitude. The study
reported eight different countries to be populated with OTUs
with the following distribution: OTUz was found in all the
eight countries south of the 30°N latitude and OTUx was
detected south of 30°N in six out of the eight countries, whilst
OTUx, OTUy and OTUz were only detected in Nigeria
among all the African countries at the same geographical
location (Clark et al. 2016).
Similarly, ITS-1 sequences belonging to five different
Eimeria species were generated in this study. The similarity
of the sequences generated in this study when compared
with published Eimeria species sequences ranged from
90% to 93% in E. mitis, 99.31% in E. maxima, 99% to 100% in
E. tenella, 100% in E. brunetti and 99.38% in E. acervulina.
Although the ML tree, as shown in Figure 5, grouped all five
species of Eimeria into five distinct clades, some level of
variation existed within species of Eimeria in this study and
that of the public database, as indicated by their mean genetic
distances. The lowest genetic distance of 0.01 was observed
among E. brunetti isolates. Similar ITS-1 sequence variations
among E. mitis, E. tenella and E. maxima have also been
reported by different authors (Bhaskaran et al. 2010; Kumar
et al. 2015a; Lew et al. 2003; Thenmozhi, Veerakumari &
Raman 2014).

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hp://www.ojvr.org Open Access
In conclusion, this study characterised Eimeria species in
broiler and free-range chickens based on molecular diagnostic
techniques and determined their diversity in KwaZulu-Natal
province. The study reports the presence of five Eimeria
species (E. tenella, E. maxima, E. acervulina, E. brunetti and
E. mitis), all of which are regarded as pathogenic. Although
none of the chickens showed clinical signs of coccidiosis
during sampling, the high prevalence of these pathogenic
parasites in the study area suggests that subclinical infection
is common in all infected chickens. Thus, effective control
strategies remain imperative to curtail coccidial infection in
poultry farms in the study areas. A survey on the types of
anticoccidial used among commercial farms and their efficacy
should be conducted to understand the impact of this disease.
This will also help in the implementation of policies for the
control of this disease in KwaZulu-Natal province.
Acknowledgements
Financial support by the National Research Foundation of
South Africa (Grant numbers: 112886 and 112768) is gratefully
acknowledged.
Compeng interests
The authors have declared that no competing interest exists.
Authors’ contribuons
A.J.F. was involved in design, collection of samples,
laboratory work, result analysis and manuscript writing.
O.TZ. co-supervised the research and corrected the
manuscripts. D.P.B. and S.O.P. were involved in grant writing
for the research and correcting the manuscript. J.L. provided
technical support and corrected the manuscript. S.M.
provided guide for sample processing, assisted with sample
collection and corrected the manuscript. M.A.A. conceived
the idea, acquired funding for the research, supervised the
research and corrected the manuscript.
Funding informaon
This research received no specific grant from any funding
agency in the public, commercial or not-for-profit sectors.
Data availability statement
Data sharing is not applicable to this article as no new data
was created or analysed in this study.
Disclaimer
The views and opinions expressed in this article are those of
the authors and do not necessarily reflect the official policy or
position of any affiliated agency of the authors.
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Appendix start on the next page →

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Appendix 1
TABLE 1–A1: Summary of samples collected in broiler farms and the outcome of Eimeria detecon.
Locaon Farms No of pen per farm No of sample per farm Age (Weeks) Posive pen
Pietermaritzburg A 540 30
B341 4 3
Phoenix C 4 20 3 4
D 3 15 4 2
E 3 15 41
Scoburgh F 4 25 4 4
Stanger G 548 9 0
H 4 22 10 1
I315 9 1
Chatsworth J 328 10 1
K 1 7 9 1
Westville L 3 24 12 1
Total 12 41 300 19
TABLE 2–A1: Summary of samples collected in free-range chickens and the outcome of Eimeria infecon.
Locaon No of chicken No of sample per locaon No of posive samples
Maphumulo 10 10 7
Umvo 10 10 3
Port Sherpstone 10 9 7
Shongweni 10 13 8
Total 40 42 25
TABLE 3–A1: ITS-1 sequences of Eimeria species generated from this study.
Serial No Sequence ID Species GenBank accession no.
1PX1 Eimeria maxima MK404734
2WS1 Eimeria maxima MK404736
3WS2 Eimeria mis MK404737
4PM2 Eimeria mis MK404739
5CH1 Eimeria mis MK404741
6SG1 Eimeria tenella MK404742
7ST3 Eimeria tenella MK404743
8PX2 Eimeria tenella MK404744
9CH2 Eimeria tenella MK404745
10 ST4 Eimeria acervulina MK404748
11 SH Eimeria mis MN727032
12 PS Eimeria mis MN727033
13 MP1 Eimeria mis MN727034
14 MP2 Eimeria mis MN727035
15 MV Eimeria mis MN727036
16 SH Eimeria maxima MN727037
17 PS Eimeria maxima MN727038
18 MP Eimeria maxima MN727039
19 PS Eimeria tenella MN727040
20 MP Eimeria tenella MN727041
21 MV Eimeria tenella MN727042
22 SH Eimeria acervulina MN727043
23 PS Eimeria acervulina MN727044
24 MV Eimeria acervulina MN727045
25 MP Eimeria acervulina MN727046
26 SH Eimeria brune MN727047
27 PS Eimeria brune MN727048
28 MP Eimeria brune MN727049
PX, Phoenix; WS, Westville; PMB, Pietermaritzburg; CH, Chatsworth; SG, Stanger; ST, Scoburg; PS, Port Sherpstone; MV, Umvo; MP, Maphumulo; SH, Shongweni.

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TABLE 4–A1: ITS-1 sequences of Eimeria species downloaded from GenBank.
No Species GenBank accession number Origin of isolates
1E. mis FJ230372.1 America
2E. mis JX853834.1 India
3E. mis AF065093.1 Sweden
4E. maxima JX853828.1 India
5E. maxima FJ230340.1 America
6E. tenella GQ153635.1 China
7E. tenella JX853831.1 India
8E. tenella JQ061003.1 Egypt
9E. acervulina AY779487.1 America
10 E. acervulina GQ856312.1 India
11 E. acervulina KY639280.1 Sudan
12 E. brunee AF446058.1 Australia
13 E. brune GQ856314.1 India
14 E. brune JX853835.1 India
E. maxima, Eimeria maxima; E. acervulina, Eimeria acervulina; E. mis, Eimeria mis; E. brunee, Eimeria brunee; E. tenella, Eimeria tenella; US, United States.
E. maxima, Eimeria maxima; E. acervulina, Eimeria acervulina; E. mis, Eimeria mis; E. brunee, Eimeria brunee; E. tenella, Eimeria tenella; US, United States.
FIGURE 1–A1: Pairwise percentage identy of ITS-1 sequences of dierent Eimeria species.
CH1_E._mis__MK404741
E._mis_FJ230372.1__US_
E._mis_JX853834.1__lndia_
E._mis_AF065093.1__Sweden_
SH_E._mis_MN727032
PS_E._mis__MN727033
MV_E._mis__MN727036
MP1_E._mis__MN727034
MP2_E._mis_MN727035
WS2_E._mis__MK404737
PM2_E._mis__MK404739
WS1_E._maxima__MK404736
SH_E._maxima_MN727037
E._maxima_JX853828.1_lndia_
E._maxima_FJ230340.1_US_
PX1_E._maxima__MK404734
PS_E._maxima__MN727038
MP_E._maxima__MN727039
SH_E._brune__MN727047
PS_E._brune__MN727048
MP_E._brune__MN727049
GQ856314.1_E._brune__India_
JX853835.1_E._brunne__lndia_
AF446058.1_E._brune__Australia_
ST4_E.__acervulina___MK404748
SH_E.acervulina__MN727043
PS_E._acervulina_MN727044
MP_E._acervulina__MN727046
MV_E._acervulina__MN727045
E._acervulina_GQ856312.1__India_
E._acervulina_AY779487.1__US_
ST3_E._tenella_MK404743
PS_E._tenella__MN727040
MP_E._tenella___MN727041__
E._tenella_JX853831.1 __lndia_
E._tenella_GQ153635.1__China_
SG1_E._tenella__MK404742
MV_E._tenella__MN727042
PX2_E._tenella__MK404744
CH2_E._tenella__MK404745
AF038860.1_Neospora_caninum
EU025025.1_Toxoplasma_gondii
CH1_E._mis__MK404741
E._mis_FJ230372.1_US_
E.mis_JX853834.1__lndia_
E._mis_AF065093.1__Sweden_
SH_E._mis_MN727032
PS_E._mis__MN727033
MV_E._mis__MN727036
MP1_E._mis__MN727034
MP2_E._mis__MN727035
WS2_E._mis__MK404737
PM2_E._mis_MK404739
WS1_E._maxima___MK404736
SH_E._maxima_MN727037
E._maxima_JX853828.1__India_
GQ856314.1_E._brune__India_
JX853835.1_E._brune__India_
AF446058.1_E._brune__Australia_
SH_E.__acervulina_MN727043
PS_E.__acervulina_MN727044
MP_E.__acervulina_MN727046
MV_E.__acervulina_MN727045
E._acervulina_GQ856312.1__India_
E._acervulina_AY779487.1__US_
ST3_E._tenella__MK404743
PS_E._tenella__MN727040
MP_E._tenella___MN727041__
E._tenella_JX853831.1__India_
E._tenella_GQ153635.1__China_
SG1_E._tenella__MK404742
MV_E._tenella__MN727042
PX2_E._tenella__MK404744
CH2_E._tenella__MK404745
AF038860.1_Neospora_caninum
EU025025.1_Toxoplasma_gondii
ST4_E.__acervulina_MK404748
E._maxima_FJ230340.1__US_
PX1_E._maxima__MK404734
PS_E._maxima__MN727038
MP_E._maxima__MN727039
SH_E._brune__MN727047
PS_E._brune__MN727048
MP_E._brune__MN727049
100
94
88
82
76
70
64
58
52
46
40
Pairwise identy (%)