This study analyzed 164 Toxoplasma gondii isolates from chickens and cats across 9 countries in Central and South America. Multilocus PCR-RFLP genotyping of 11 genetic markers identified 42 distinct genotypes. There was high genetic diversity within and between populations. The major lineages identified were ToxoDB PCR-RFLP #7, Type III, and Type II. Linkage disequilibrium analysis found evidence of frequent genetic recombination in some populations. Bayesian and phylogenetic network analyses identified at least three main genetic clusters. Overall, the study demonstrated high genetic diversity of T. gondii in Central and South America, with dominance of the Type III and closely related ToxoDB PCR-RFLP #7
1. Molecular genotyping of Toxoplasma gondii from Central and South America
revealed high diversity within and between populations
C. Rajendran a
, C. Su b
, J.P. Dubey a,⇑
a
United States Department of Agriculture, Agricultural Research Service, Animal and Natural Resources Institute, Animal Parasitic Diseases Laboratory, Building 1001, Beltsville,
MD 20705-2350, USA
b
Department of Microbiology, The University of Tennessee, Knoxville, TN 37996-0845, USA
a r t i c l e i n f o
Article history:
Received 12 July 2011
Received in revised form 14 December 2011
Accepted 16 December 2011
Available online 29 December 2011
Keywords:
Toxoplasma gondii
Chicken (Gallus domesticus)
Cat (Felis catus)
Genetic characterization
Genetic diversity
Population genetics
a b s t r a c t
Recent population studies revealed that a few major clonal lineages of Toxoplasma gondii dominate in
different geographical regions. The Type II and III lineages are widespread in all continents and dominate
in Europe, Africa and North America. In addition, the type 12 lineage is the most common type in wildlife
in North America, the Africa 1 and 3 are among the major types in Africa, and ToxoDB PCR–RFLP #9 is the
major type in China. Overall the T. gondii strains are more diverse in South America than any other
regions. Here, we analyzed 164 T. gondii isolates from three countries in Central America (Guatemala,
Nicaragua, Costa Rica), from one country in Caribbean (Grenada) and five countries from South America
(Venezuela, Colombia, Peru, Chile, and Argentina). The multilocous polymerase chain reaction–restriction
fragment length polymorphism (PCR–RFLP) based genotyping of 11 polymorphic markers (SAG1, SAG2,
alt.SAG2, SAG3, BTUB, GRA6, L358, PK1, C22-8, C29-2 and Apico) were applied to 148 free-range chicken
(Gallus domesticus) isolates and 16 isolates from domestic cats (Felis catus) in Colombia; 42 genotypes
were identified. Linkage disequilibrium analysis indicated more frequent genetic recombination in pop-
ulations of Nicaragua and Colombia, and to a lesser degree in populations of Costa Rica and Argentina.
Bayesian structural analysis identified at least three genetic clusters, and phylogenetic network analysis
identified four major groups. The ToxoDB PCR–RFLP #7, Type III and II were major lineages identified
from Central and South America, with high frequencies of the closely related ToxoDB PCR–RFLP #7
and Type III lineages. Taken together, this study revealed high diversity within and between T. gondii
populations in Central and South America, and the dominance of Type III and its closely related ToxoDB
PCR–RFLP #7 lineages.
Ó 2011 Elsevier B.V. All rights reserved.
1. Introduction
Toxoplasma gondii is an intracellular protozoan parasite that
infects most warm blooded vertebrates including birds and mam-
mals. Cats play an important role in the transmission of T. gondii to
humans and animals because they are the only hosts that excrete
the environmentally resistant oocysts in their feces (Dubey,
2010a). Human become infected by ingesting tissue cysts from
undercooked meat, food or water contaminated with oocysts or
by accidental ingestion of oocysts from the environment. In
general, T. gondii isolates were considered a single species without
geographical boundaries, and with little genetic diversity
(Dubey and Beattie, 1988; Dardé et al., 1992; Sibley and Boothroyd,
1992; Howe and Sibley, 1995; Dardé, 1996; Ajzenberg et al.,
2002a). Based on early molecular genotyping studies, T. gondii iso-
lates in North America and Europe have been classified into three
genetic types (I, II, III) (Dardé et al., 1992; Howe and Sibley,
1995; Dardé, 1996; Howe et al., 1997; Lehmann et al., 2000; Su
et al., 2003). Phenotypically, Type I strains are uniformly lethal to
out-bred mice and Type II and III strains are significantly less
virulent (Sibley and Boothroyd, 1992; Howe and Sibley, 1995).
Studies of human toxoplasmosis in France showed the dominance
of Type II strains and Type I infection was rare (Ajzenberg et al.,
2002b, 2009; Ajzenberg 2010). Recent studies of T. gondii in human
and animals in South America suggested that this parasite is genet-
ically diverse (Lehmann et al., 2004, 2006; Dubey et al., 2007a,b,
2008a,b,c; Demar et al., 2007; Pena et al., 2008), and severe toxo-
plasmosis in immunocompetent human patients often was associ-
ated with atypical genotypes (non-Type I, II and III) in South
America (Carme et al., 2002; Delhaes et al., 2010). Other studies
showed the dominance of genotype ToxoDB PCR–RFLP #9 (also
known as China 1) in China (Dubey et al., 2007c; Zhou et al.,
2009; Chen et al., 2011), and high prevalence of Type II, III, Africa
1 and Africa 3 genotypes in Africa (Velmurugan et al., 2008;
Mercier et al., 2010; Al-Kappany et al., 2010).
1567-1348/$ - see front matter Ó 2011 Elsevier B.V. All rights reserved.
doi:10.1016/j.meegid.2011.12.010
⇑ Corresponding author. Tel.: +1 301 504 8128; fax: +1 301 504 9222.
E-mail address: jitender.dubey@ars.usda.gov (J.P. Dubey).
Infection, Genetics and Evolution 12 (2012) 359–368
Contents lists available at SciVerse ScienceDirect
Infection, Genetics and Evolution
journal homepage: www.elsevier.com/locate/meegid
2. Table 1
Summary of genotyping results by countries.
SAG1 50
-
30
SAG2
alt.SAG2 SAG3 BTUB GRA6 c22-
8
c29-
2
L358 PK1 Apico ID n = ToxoDB PCR–
RFLP
genotype#
Comments
Reference I I I I I I I I I I I RH88 10 Type I
Reference II or
III
II II II II II II II II II II PTG 1 Type II
Reference II or
III
III III III III III III III III III III CTG 2 Type III
Reference I II II III II II II u-1 I u-2 I TgCgCa1 66 Atypical
Reference u-1 I II III III III u-1 I I III I MAS 17 Atypical
Reference I III III III III III I I I u-1 I TgCatBr5 19 Atypical
Chile
chickens
n = 22
I III III III III III III I III III III TgCkCh1 1 14 Genotype previously reported (Pena et al., 2008).
II or
III
II II II II II II II II II I TgCkCh2, 4, 5, 7, 8, 9, 12, 13, 14, 17,
19, 21, 22
13 3 Genotype previously reported (Pena et al., 2008).
II or
III
III III III III III III III III III III TgCkCh3, 15, 18, 20 4 2 Type III
II or
III
II II II II II II II II II II TgCkCh6, 10, 11, 16 4 1 Type II
Colombia
cats n = 16
I I I I I I II I III I III TgCtCo1 1 28 Genotype previously reported (Dubey et al., 2008c).
I I I I I I I I I I I TgCtCo2, 7 2 10 Genotype previously reported (Pena et al., 2008).
I III III III I I I III I I III TgCtCo4, 10, 11 3 38 Genotype previously reported (Dubey et al.,
2007b).
u-1 I II III III III III III I III I TgCtCo5x 1 40 Genotype previously reported (Dubey et al., 2008c).
I I II III I III II III III III I TgCtCo3, 9 2 62 This study
I I II III I III II III I u-2 I TgCtCo5, 6 2 61 This study
I I II III I III II I I u-2 I TgCtCo15 1 101 This study
I III III III III III III I III III III TgCtCo14 1 14 Genotype previously reported (Pena et al., 2008).
II or
III
II II II II II II III II II I TgCtCo8 1 128 This study
I I I III I III II I III III I TgCtCo12, 13 2 18 Genotype previously reported (Dubey et al., 2007c).
Costa Rica
chickens
n = 32
I I I I I I I III I I III TgCkCr3, 4, 5, 6 4 35 This study
I I II I II I I I I u-1 I TgCkCr7, 9, 10 3 43 This study
II or
III
III III III III III III III III III III TgCkCr11 1 2 Type III
I I II I I I II I I I I TgCkCr1 1 91 This study
I III III III III III III III III III I TgCkCr8, 12, 13, 14, 15, 16, 17, 18,
19, 20, 21, 22, 23, 24, 25, 26, 27
17 7 Genotype previously reported (Dubey et al., 2008c).
I I I I III I I I I I III TgCkCr2, 28, 29, 30, 31, 32 6 24 This study
Nicaragua
chickens
n = 44
I I II III III I III I III III I TgCkNi1, 11, 22, 23, 26, 29, 33, 36,
38, 46, 47y
11 16 This study
II or
III
III III III III III III III III III III TgCkNi3, 8, 13, 44, 48, 2x 6 2 Type III
II or
III
III III III III III II III III I III TgCkNi27 1 140 This study
I I II III I III II I III u-1 I TgCkNi4, 6, 10, 17, 21, 34, 37 7 23 This study
I I II III I III II I III u-1 III TgCkNi35 1 102 This study
u-1 I II III I III u-2 I I III I TgCkNi12, 32 2 52 Genotype previously reported (Dubey et al., 2009).
I III III III III III III III III III I TgCkNi14, 15, 20, 25, 30 5 7 Genotype previously reported (Dubey et al., 2008c).
II or
III
II II II II II II II I II I TgCkNi18, 39, 42 3 4 Genotype previously reported (Velmurugan et al.,
2009; Dubey et al., 2008a; Sundar et al., 2008).
II or
III
III III I III I III III III III III TgCkNi16, 45, 7x 3 50 This study
I I I I I I I III I I I TgCkNi7, 9, 40, 41, 43 5 27 This study
Grenada II or III III III III III III III III III III TgCkGr12, 16, 23, 24, 29 5 2 Type III
360C.Rajendranetal./Infection,GeneticsandEvolution12(2012)359–368
3. chickens
n = 9
III
I I I I I III II III III I III TgCkGr25, 26 2 13 Genotype previously reported (Dubey et al., 2008c).
II or
III
III III III III III II III III III III TgCkGr17, 18 2 187 This study
Argentina
chickens
n = 10
II or
III
III III III III III III III III III III TgCkAr2, 6, 24 3 2 Type III
I III III III III III III III III III I TgCkAr16, 18 2 7 Genotype previously reported (Pena et al., 2008).
I I II III III III I III I II III TgCkAr1 1 11 Genotype previously reported (Pena et al., 2008).
I III III III III III III III III III III TgCkAr7 1 48 Genotype previously reported (Dubey et al.,
2007a,b,c,d)
u-1 I II III III III u-1 I I III I TgCkAr27, 28 2 17 Genotype previously reported (Pena et al., 2008).
u-1 I II III III III III I I III I TgCkAr25 1 15 Genotype previously reported (Dubey et al.,
2008a,b,c,d)
Guatemala
chickens
n = 3
I III III III III III III III III III I TgCkGa6 1 7 Genotype previously reported (Pena et al., 2008).
I III III III I I II III III I III TgCkGa01 1 190 This study
I I I I I I II III III I III TgCkGa04 1 191 This study
Venezuela
chickens
n = 7
I III III III III III II III III III III TgCkVe1 1 8 Genotype previously reported (Pena et al., 2008).
I III III III III III III III III III III TgCkVe 4, 5, 10 3 48 Genotype previously reported (Dubey et al.,
2007a,b,c,d)
I III III III III III III I III III III TgCkVe3 1 14 Genotype previously reported (Pena et al., 2008).
I III III III I III II III III III III TgCkVe11, 1 116 Genotype previously reported (Dubey et al., 2008c).
II or
III
II II III III II III III III u-2 III TgCkVe6 1 185 This study
Colombia
chickens
n = 16
I III III III I I I III I I III TgCkCo6, 10, 12, 13, 21, 23, 24, 8,
15
9 38 Genotype previously reported (Dubey et al.,
2007b).
I I II III I III II I III III I TgCkCo20 1 29 Genotype previously reported (Dubey et al., 2007a).
I I I I I I II I III I III TgCkCo5 1 28 Genotype previously reported (Pena et al., 2008).
I III III III III III III I III III III TgCkCo2 1 14 Genotype previously reported (Pena et al., 2008).
I I II III I III I III III III III TgCkCo17, 22 2 179 This study
II or
III
III III III III III III III I I III TgCkCo9 1 188 This study
I I I III I III II I I III I TgCkCo4 1 178 This study
Peru
chickens
n = 5
II or
III
III III III III III III III III III III TgCkPe2 1 2 Type III
u-1 I II III III III u-1 I I III I TgCkPe4, 6 2 17 Genotype previously reported (Pena et al., 2008).
I III III III I III II III III III III TgCkPe3 1 116 Genotype previously reported (Dubey et al., 2008c).
u-1 I II I I I I I I III I TgCkPe5 1 189 This study
C.Rajendranetal./Infection,GeneticsandEvolution12(2012)359–368361
4. Existing data suggest T. gondii populations are highly different
between North and South America, with a few dominant genotypes
in the North, and highly diverse population in the South (Velmur-
ugan et al., 2009; Dubey et al., 2008c, 2011; Pena et al., 2008; Khan
et al., 2011). At present, there are limited data regarding T. gondii
diversity from Central America. In this study we identified 42
genotypes from 164 T. gondii isolates from selected countries from
Central America and South America using 11 polymerase chain
reaction–restriction fragment length polymorphism (PCR–RFLP)
markers. The results showed that populations in Central and South
America are diverse except Chile where the Type II and III strains
are dominant.
2. Materials and methods
2.1. Revival of T. gondii strains
The cryopreserved infected mouse brains or lung tissues from
previous studies in our laboratory (Lehmann et al., 2006; Dubey,
2010b) were collected from liquid nitrogen and thawed at 37 °C
water bath for few min and an aliquot was seeded onto CV1 cell
culture flask (25 cm2
) and an aliquot was inoculated subcutane-
ously into 1–2 gamma interferon gene knock out (KO) mice for
the isolation of viable tachyzoites (Dubey, 2010a). Lung tissue of
KO mice that died were homogenized in 1 ml of RPMI 1640
medium containing 3% fetal bovine serum and then seeded onto
new CV1 cell culture. The expanded tachyzoites from cell cultures
were cryopreserved in liquid nitrogen and used to isolate T. gondii
genomic DNA for multilocus genotyping studies.
A total of 50 T. gondii isolates from previous studies were
revived. In brief, nine isolates were isolated from chickens in Gre-
nada (Dubey et al., 2005a), three isolates from Guatemala (Dubey
et al., 2005b), 10 isolates from chickens in Argentina (Dubey et al.,
2003), seven isolates from Venezuela (Dubey et al., 2005c), five
isolates from chickens in Peru (Dubey et al., 2004) and 16 isolates
from chickens in Colombia (Dubey et al., 2005a,b,c). In addition,
DNA samples from previous studies that were genotyped by six of
the 11 markers were used to generate complete typing results in
this experiment. These samples included 22 isolates from chickens
in Chile (Dubey et al., 2006b), 32 isolates from chickens in Costa
Rica (Dubey et al., 2006a), 44 isolates from chickens in Nicaragua
(Dubey et al., 2006d) and 16 cat isolates from Colombia (Dubey
et al., 2006c). A total of 164 T. gondii isolates were analyzed in this
study, including 148 chicken and 16 cat isolates.
For comparison, one T. gondii population from chickens in Africa
(Velmurugan et al., 2008) and two populations from chickens in
Brazil (Dubey et al., 2007a) were included as reference populations
for analysis.
2.2. DNA extraction and purification
Culture-derived tachyzoites of T. gondii isolates were processed
for the collection of DNA using the Qiagen DNeasy blood and tissue
kit (Qiagen, USA) and with proteinase K to have the final concen-
tration of 1 mg/ml. The samples were then incubated at 56 °C in
water bath for 3 h and vortexed several times during incubation.
Genomic DNA was extracted using elution buffer provided with
the kit and the genomic DNA was eluted in 40 ll of elution buffer
and stored at À20 °C until use.
2.3. Multilocus PCR–RFLP genotyping
The parasite genomic DNA samples were subjected to multilo-
cus PCR–RFLP genotyping using 11 molecular markers including
SAG1, 50
-30
SAG2, alt.SAG2, SAG3, GRA6, BTUB, C22-8, C29-2,
L358, PK1 and Apico (Table 1) with two rounds of amplification.
The first round of amplification consisted of external forward and
reverse primers of all markers together followed by second round
of amplification carried out separately with individual forward and
reverses primers (nested PCR) of the particular markers (Su et al.,
Fig. 1. Map of countries where Toxoplasma gondii isolates were collected. Black dots represent approximate location for sampling. Number of samples collected is listed for
each location.
362 C. Rajendran et al. / Infection, Genetics and Evolution 12 (2012) 359–368
5. 2010). The reaction volume consisted of 25 ll containing 100 ng
genomic DNA with positive control samples. Eight T. gondii strains
were included as the positive controls including GT1, PTG, CTG,
TgCgCa1, MAS TgCtBr5, TgCtBr64 and TgRsCr1 (Table 1). The PCR
reaction composed of 1Â PCR buffer, 0.2 mM of each primer,
200 lM dNTPs, 2 mM MgCl2, 0.2 U of FastStart Taq DNA polymer-
ase (Roche-Applied Science, USA). The PCR amplification was per-
formed using thermal cycler (PTC 200, Bio-RAD). All samples
were incubated at 95 °C for 5 min to activate the DNA polymerase,
then 30 cycles of PCR at 95 °C for 30 s, 55 °C for 60 s and 72 °C for
90 s. Similar program was used for the nested PCR. The nested PCR
were carried out with the annealing temperature at 60 °C for 60 s
for all the markers except Apico, which was amplified at 55 °C
for 60 s. Further, the amplified PCR products were subjected to
RFLP analysis with suitable restriction enzymes for the analysis
of genotyping results. Restriction enzyme digested PCR products
were analysed using 2.5% agarose gel for all markers and 3% for
Apico and 2% for C29-2 marker, respectively. The gel was run at
100 V for 80 min prior to staining by ethidium bromide (1 mg/
ml) and the gel was observed under ultraviolet light and
documented the image for the interpretation of genotyping data.
2.4. Data analysis
Multilocus PCR–RFLP typing data was analyzed using several
population genetic softwares. Basic statistics, within and between
Table 2
Summary of typing results by genotypes.
SAG1 50
-30
SAG2
alt.SAG2 SAG3 BTUB GRA6 c22-
8
c29-
2
L358 PK1 Apico n = ToxoDB PCR–
RFLP
genotype#
II II II II II II II II II II II TgCkCh6, 10, 11, 16 4 1 (Type II)
II or
III
III III III III III III III III III III TgCkCh3, 15, 18, 20, TgCkCr11, TgCkNi3, 8, 13, 44, 48,
2x, TgCkGr12, 16, 23, 24, 29, TgCkAr2, 6, 24, TgCkPe2
20 2 (Type III)
II or
III
II II II II II II II II II I TgCkCh2, 4, 5, 7, 8, 9, 12, 13, 14, 17, 19, 21, 22 13 3 (Type II
variant)
II or
III
II II II II II II II I II I TgCkNi18, 39, 42 3 4
I III III III III III III III III III I TgCkCr8, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
24, 25, 26, 27, TgCkNi14, 15, 20, 25, 30, TgCkAr16, 18,
TgCkGa6
25 7
I III III III III III II III III III III TgCkVe1 1 8
I I I I I I I I I I I TgCtCo2, 7 2 10
I I II III III III I III I II III TgCkAr1 1 11
I I I I I III II III III I III TgCkGr25, 26 2 13
I III III III III III III I III III III TgCkCh1, TgCtCo14, TgCkCo2, TgCkVe3 4 14
u-1 I II III III III III I I III I TgCkAr 25 1 15
I I II III III I III I III III I TgCkNi1, 11, 22, 23, 26, 29, 33, 36, 38, 46, 47y 11 16
u-1 I II III III III u-1 I I III I TgCkAr27, 28, TgCkPe4, 6 4 17
I I I III I III II I III III I TgCtCo12, 13 2 18
I I II III I III II I III u-1 I TgCkNi4, 6, 10, 17, 21, 34, 37 7 23
I I I I III I I I I I III TgCkCr2, 28, 29, 30, 31, 32 6 24
I I I I I I I III I I I TgCkNi7, 9, 40, 41, 43 5 27
I I I I I I II I III I III TgCtCo1, TgCkCo 5 2 28
I I II III I III II I III III I TgCkCo20 1 29
I I I I I I I III I I III TgCkCr3, 4, 5, 6 4 35
I III III III I I I III I I III TgCtCo4, 10, 11, TgCkCo6, 8, 10, 12, 13, 15, 21, 23, 24 12 38
u-1 I II III III III III III I III I TgCtCo5x 1 40
I I II I II I I I I u-1 I TgCkCr7, 9, 10 3 43
I III III III III III III III III III III TgCkAr7, TgCkVe4, 5, 10 4 48
II or
III
III III I III I III III III III III TgCkNi16, 45, 7x 3 50
u-1 I II III I III u-2 I I III I TgCkNi12, 32 2 52
I I II III I III II III I u-2 I TgCtCo5, 6 2 61
I I II III I III II III III III I TgCtCo3, 9 2 62
I I II I I I II I I I I TgCkCr1 1 91
I I II III I III II I I u-2 I TgCtCo15 1 101
I I II III I III II I III u-1 III TgCkNi35 1 102
I III III III I III II III III III III TgCkVe11, TgCkPe3 2 116
II or
III
II II II II II II III II II I TgCtCo8 1 128
II or
III
III III III III III II III III I III TgCkNi27 1 140
I I I III I III II I I III I TgCkCo4 1 178
I I II III I III I III III III III TgCkCo17, 22 2 179
II or
III
II II III III II III III III u-2 III TgCkVe6 1 185
II or
III
III III III III III II III III III III TgCkGr17, 18 2 187
II or
III
III III III III III III III I I III TgCkCo9 1 188
u-1 I II I I I I I I III I TgCkPe5 1 189
I III III III I I II III III I III TgCkGa1 1 190
I I I I I I II III III I III TgCkGa4 1 191
164 Isolates.
C. Rajendran et al. / Infection, Genetics and Evolution 12 (2012) 359–368 363
6. population diversity, linkage disequilibrium were analyzed by
Arlequin v3.5 (Excoffier and Lischer, 2010). For these analyses,
multilocus PCR–RFLP typing data was coded for all genetic loci.
For a given locus, presence or absence of DNA restriction
fragments were coded with 1s and 0s, respectively. Therefore, a
string of 1s and 0s were used to represent DNA banding pattern
of an allele for a locus. For example, at locus PK1, alleles I, II,
III, u-1, u-2 and u-3 were coded as 1001000101, 0000111101,
1000010101, 0100000110, 0100010101 and 0010010110, respec-
tively. To analyze by Arlequin, the data type was set as ‘‘haplo-
typic’’ data, and the data form was set as ‘‘Standard’’ which
compares the data for their content at each locus without taking
special consideration about the nature of the alleles. Phylogenetic
network of all unique genotypes were inferred by SplitsTree v4.4
(Huson and Bryant, 2006) using the genotyping data coded as
above.
Standardized index of association IsA
for each population was
calculated by LIAN v. 3.5 (Haubold and Hudson, 2000). Clustering
analysis was carried out using STRUCTRURE v2.3.3 (Pritchard
et al., 2000). Ten replicate simulations were conducted for each
of K = 1 to K = 10 using a length of burn-in of 104
and 104
replicates
of Markov Chain Monte Carlo simulation. The simulation was
conducted using the linkage model for estimating the ancestral
populations. The natural log probability of data under a given mod-
el was estimated for ln P(D/K). The DK value for clustering was
determined to infer the best K value for clustering using
CorrSieve (Campana et al., 2010), the result was processed by
CLUMPP v1.1.2 (Jakobsson and Rosenberg, 2007) and the graph
was generated by Distruct v1.1 (Rosenberg, 2004).
3. Results
The 164 samples analyzed here were divided into 10 populations
based on countries and animal hosts in Central and South America
(Fig. 1, Table 1) and were identified by PCR–RFLP typing (Table 2).
Each genotype was compared to ToxoDB genotyping database
(ToxoDB.org), and designated with the matching ToxoDB PCR–RFLP
genotype # (Tables 1 and 2). New genotypes are assigned to new
ToxoDB genotype # and deposited to the database for future
Table3
BasicstatisticsofToxoplasmapopulationsfromCentralandSouthAmerica.
Argentina
Cks
ChileCksPeruCksColombia
Cats
Colombia
Cks
Venezuela
Cks
Costa
RicaCks
Nicaragua
Cks
Guatemala
Cks
Grenada
Cks
Brazil
PACksa
Brazil
RSCksa
AfricaCksb
No.ofisolates1022516167324439151919
No.ofhaplotypes6441075610331174
No.ofloci10101010101010101010101010
No.ofpolym.loci710910107101076101010
Genediversity(haplotype)0.889±0.0750.610±0.0930.900±0.1610.942±0.0360.692±0.1240.857±0.1370.677±0.0740.875±0.0241.000±0.2720.667±0.1320.952±0.0400.819±0.0630.509±0.117
Meannumberofpairwise
differenceoverloci
3.533±1.9473.645±1.9125.400±3.0815.217±2.6513.550±1.8952.191±1.3584.611±2.3185.163±2.5444.667±3.0492.500±1.4720.554±0.3150.424±0.2450.409±0.238
IsA
0.2130.8170.2900.1530.2520.1350.5440.251nd0.4310.1190.3430.784
P-valueofIsA
<0.001<<0.0010.002<0.001<0.0010.02<0.001<0.001nd<0.001<0.001<0.001<<0.001
IsA
foreachpopulationisdeterminedbyLIANv3.5.
a
Datafrompreviouslypublishedreport(Dubeyetal.,2007a).
b
Datafrompreviouslypublishedreport(Velmuruganetal.,2008).
Population pairwise Fst
Fst
0.5
0.4
0.3
0.2
0.1
0.0
Costa Rica cks
Nicaragua cks
Guatemala cks
Colombia cats
Colombia cks
Venezuela cks
Grenada cks
Chile cks
Argentina cks
Peru cks
Brazil PA cks
Brazil RS cks
Africa cks
Costa Rica cks
Nicaragua cks
Guatemala cks
Colombia cats
Colombia cks
Venezuela cks
Grenada cks
Chile cks
Argentina cks
Peru cks
Brazil PA cks
Brazil RS cks
Africa cks
CostaRicacks
Nicaraguacks
Guatemalacks
Colombiacats
Colombiacks
Venezuelacks
Grenadacks
Chilecks
Argentinacks
Perucks
BrazilPAcks
BrazilRScks
Africacks
CostaRicacks
Nicaraguacks
Guatemalacks
Colombiacats
Colombiacks
Venezuelacks
Grenadacks
Chilecks
Argentinacks
Perucks
BrazilPAcks
BrazilRScks
Africacks
Fig. 2. Pairwise Fst of 10 sample populations and three reference populations.
Comparison of populations were conducted using Arlequin ver 3.5. The heat map
indicates the Fst value.
364 C. Rajendran et al. / Infection, Genetics and Evolution 12 (2012) 359–368
7. reference. Of these 164 isolates, 42 different genotypes were identi-
fied. Among these 42 different genotypes, ToxoDB #7 (n = 25),
ToxoDB #2 (Type III, n = 20), and ToxoDB #3 (variant of Type II,
n = 13) are the three most prevalent genotypes.
1.5 1.5
Colombia cats,
n 16 haplotypes 10
Nicaragua cks,
44 h l t 10
1.5
Colombia cks
16 h l t 7
1.0 1.0
n=16, haplotypes=10 n=44, haplotypes=10
1 0
1.5
n=16, haplotypes=7
0.5 0 50 5
1.0
ax
0.0 0 0
0.5
0 0
0.5
Dma
-0.5 0 5
0.0
0 5
0.0
’=D/D
-1.0
1 0
-0.5
1 0
-0.5
D’
-1.5
0
-1.0-1.0
1.5
0 200 400
-1.5
0 200 400
-1.5
0 200 400 0 200 400
A i k
0 200 400
Chil kC Ri k 1.5 Argentina cks,
n=10 haplotypes=6
1.5 Chile cks,
n=22 haplotypes=4
1.5 Costa Rica cks
n=32 haplotypes=6
1.0
n=10, haplotypes=6
1.0
n=22, haplotypes=4
1.0
n=32, haplotypes=6
0.50.50.5
max
0.00.00.0
D/Dm
-0.5-0.5-0.5
D’=D
-1.0-1.0-1.0
D
-1.5-1.5-1.5
0 200 4000 200 4000 200 400
1.5 1.5
1 5 Africa cks,Brazil RS cks,Brazil PA cks,
h l
1.0 1.0 1 0
1.5 ,
n=19, haplotypes=4n=19, haplotypes=7n=15, haplotypes=11
0.5 0.5 0 5
1.0
max
0 0
0.5
0.0 0 0
0.5
/Dm
-0 5
0.0
-0.5 -0 5
0.0
D’=D/
1 0
-0.5
-1.0 -1 0
-0.5
D
1 5
-1.0
-1.5 -1 5
-1.0
-1.5
0 200 400
0 200 400
-1.5
0 200 4000 200 400
Fig. 3. Distribution of D0
= D/Dmax within populations. Populations that have 10 or more Toxoplasma gondii isolates were analyzed for linkage disequilibrium D0
. D0
= À1 or 1
suggests strong disequilibrium, whereas D0
= 0 suggests complete equilibrium. X-axis represents the number of comparisons among alleles between polymorphic loci.
K
Mean lnP(D/K)
ΔK
/K)P(D/
K
lnP
ΔK
eanMe
Argentina
Chile
Peru
Colombiacats
ColombiaCks
Venezuela
CostaRica
Nicaragua
Guatemala
Grenada
A
B
Fig. 4. Clustering analysis of Toxoplasma populations. (A) Analysis of ln P(D/K) and DK. At K = 3, the mean posterior probability of data ln P(D/K) approaches the plateau, the
rate of change in the log probability of data between successive K values (DK) also reaches the peak point. Taken together, K = 3 is the best estimation of ancestral clusters for
the populations studied. (B) Structures of the 10 Toxoplasma populations. It is shown that Chile chicken population is different from all other populations.
C. Rajendran et al. / Infection, Genetics and Evolution 12 (2012) 359–368 365
8. Basic statistics, within and between population diversity, link-
age disequilibrium were analyzed on haplotype data by Arlequin
v3.5 (Excoffier and Lischer, 2010). Analyses of the 10 sample popu-
lations and three reference populations are summarized in Table 3.
Fst values of pairwise comparison of the 13 populations were
summarized in Fig. 2. The results showed high diversity within
and between populations. Haplotype diversity within the popula-
tions from the order of high to low is: Guatemala > Brazil PA >
Colombia cat > Peru > Argentina > Nicaragua > Venezuela > Brazil
RS > Colombia chickens > Costa Rica > Grenada > Chile > Africa. The
mean number of pairwise difference among loci within population
from high to low is: Brazil PA > Peru > Colombia cat > Nicara-
gua > Guatemala > Costa Rica > Brazil RS > Africa > Chile > Colom-
bia chicken > Argentina > Grenada > Venezuela. Fst values of
pairwise comparison of the 13 populations (Fig. 2) showed that
Chile chicken population is highly different from all other popula-
tions. The two Colombia populations (chicken and cat) do not show
statistic difference (at P = 0.01).
To determine allelic linkage disequilibrium among different
loci, distribution of D0
= D/Dmax within populations that have 10
or more isolates was analyzed by Arlequin v3.5 (Fig. 3). Populations
with less than 10 isolates were not used because small sample size
maybe more sensitive to variation and less meaningful. Linkage
disequilibrium among multiple loci was also analyzed using stan-
dardized index of association (IsA
) (Haubold and Hudson, 2000),
the results are summarized in Table 3. Linkage disequilibrium
analysis of D0
values and IsA
showed comparable results among
the populations. IsA
quantifies the strength of linkage disequilib-
rium among different genetic loci. IsA
= 1 indicates complete link-
age disequilibrium, whereas IsA
= 0 indicates complete linkage
equilibrium (Haubold and Hudson, 2000). Both methods identified
strong linkage disequilibrium in Chile chicken isolates (D0
= À1 or
1, IsA
= 0.817), followed by Africa chicken isolates (IsA
= 0.784)
(Fig. 3. Table 3), suggesting both have a clonal population struc-
ture. Both methods also identified low linkage disequilibrium in
Colombia cat isolates, Nicaragua and Brazil PA chicken isolates
(D0
with high frequency of values close to 0, IsA
with low values,
Fig. 3, Table 3), indicating high frequency of genetic recombination
in these populations. Colombia, Argentina and Brazil RS chicken
isolates have medium to high frequency of low D0
values among
polymorphic loci of RFLP markers (Fig. 3), and medium to low IsA
values (0.252, 0.213 and 0.343, respectively, Table 3) indicating
frequent genetic recombination within these populations. Costa
Rica chicken population has medium level of low D0
values, and
relatively high IsA
(0.544), indicate relatively infrequent genetic
exchange within its population. Due to small sample sizes (less
than 10 isolates) in Grenada, Guatemala, Venezuela and Peru, link-
age equilibrium analysis of these locations may not be informative.
Structure analysis identified K = 3 to be the best estimation of
ancestral populations from these 164 T. gondii samples (Fig. 4A).
At K = 3, the mean posterior probability of data ln P(D/K) approxi-
mately reaches the plateau, whereas the DK, the rate of change in
the log probability of data between successive K values, also
reaches the peak point. Using K = 3 for the estimation of ancestral
clusters, genetic structure for each population is inferred and pre-
sented in Fig. 4B. It is shown that most of these populations are
made of two of the three clusters (represented by red and blue
clusters). However, the Chile chicken population is unique in that
the third cluster (green) dominates. This cluster is represented by
the clonal Type II strains.
Phylogenetic network of all unique genotypes were inferred by
SplitsTree v4.4 (Huson and Bryant, 2006). The network analysis of
#1, PTG, TgCkCh6,
10, 11, 16
#3, TgCkCh2 , 4, 5,
7, 8, 9, 12, 13, 14, 17,
19, 21, 22
#128, TgCtCo8
#4, TgCkNi18, 39, 42
#66, TgCgCa1
#185, TgCkVe6
#11
(BrII), TgCkAr1
#40, TgCtCo5x
#15, TgCkAr25
#17,
M
AS,TgC
kAr27,28,
TgC
kPe4,6
#52,TgCkNi12,32
#61,TgCtCo5,6
#101,TgCtCo15#23,TgCkNi4,6,
10,17,21,34,37
#102,TgCkNi35
#179,TgCkCo17,22
#62,TgCtCo3,9
#29,TgCkCo20
#18,TgCtCo12,13
#178,TgCkCo4
#19, TgCatBr5
#38, TgCtCo4, 10, 11,
TgCkCo6, 8, 10, 12, 13,
15, 21, 23, 24
#190, TgCkGa1
#116, TgCkVe11, TgCkPe3
#8 (BrIII), TgCkVe1
#7
#7: TgCkCr8, 12, 13, 14, 15, 16, 17,
18, 19, 20, 21, 22, 23, 24, 25, 26, 27,
TgCkNi14, 15, 20, 25, 30,
TgCkAr16, 18, TgCkGa6
#48, TgCkAr7,
TgCkVe4, 5, 10
#14
#188,
TgCkCo9#2
#2: CTG, TgCkCh3, 15, 18, 20,
TgCkCr11, TgCkNi3, 8, 13, 44, 48,
2x, TgCkGr12, 16, 23, 24, 29,
TgCkAr2, 6, 24, TgCkPe2
#187, TgCkG
r17, 18
#140,TgCkNi27
#50,
TgCkNi16,45,7x
#13, TgCkG
r25, 26
#191,TgCkG
a4
#28,TgCtCo1,
TgCkCo5
#10,RH88,TgCtCo2,7
#27, TgCkNi7, 9, 40, 41, 43
#35, TgCkCr3, 4, 5, 6
#91, TgCkCr1
#189, TgCkPe5
#43, TgCkCr7, 9, 10
#16, TgCkNi1, 11, 22, 23,
26, 29, 33, 36, 38, 46, 47y
#14, TgCkCh1, TgCtCo14,
TgCkCo2, TgCkVe3
#24,TgCkCr2,28,
29,30,31,32
Group 1
n=27
Group 3
n=76Group 2
n=22
Group 4
n=28
Fig. 5. Phylogenetic network analysis of Toxoplasma from Central and South America. From the 164 samples, 42 genotypes were identified. These genotypes are divided into
four major groups. Populations with n P 10 are color coded: Nicaragua Cks – red; Chile Cks – green; Costa Rica Cks – blue; Colombia Cks – magenta; Colombia Cats –purple;
Argentina Cks – brown. Reference strains were underlined. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this
article.)
366 C. Rajendran et al. / Infection, Genetics and Evolution 12 (2012) 359–368
9. the 164 isolates is summarized in Fig. 5. A total of 42 genoytpes
were identified and these genotypes are divided into four major
groups (Fig. 5). This result indicated high diversity of T. gondii
strains. Groups 1, 2, 3 and 4 have 27, 22, 76 and 28 isolates, respec-
tively. The clonal Type I, II and III lineages are associated with
Groups 1, 2 and 3, respectively. Analysis of the data revealed no
association of genotypes with geographical locations in the popu-
lations investigated.
4. Discussion
This study revealed high diversity within and between T. gondii
populations and the dominance of Type III and its closely related
ToxoDB PCR–RFLP #7 lineages in Central and South America. The
diversity of T. gondii in this region might have been generated by
frequent genetic recombination among these populations. This is
supported by linkage disequilibrium analysis which showed low
levels of IsA
and D0
values in several populations studied, and lim-
ited ancestral clusters identified by STRUCTURE analysis.
Though the Type II strains were identified, it was mainly con-
centrated in Chile and absent from other populations in Central
and South American countries included in this study (Table 1,
Fig. 4). The lack of Type II strain was previously reported in a large
collection of T. gondii strains from mainland Brazil (Pena et al.,
2008; Dubey et al., 2008c). A more recent study reported Type II
strains (Type II at all loci but Type I alllele at Apico) in sheep from
the state in the south of Brazil, but this Type II lineage was possibly
imported from other country (da Silva et al., 2011). The prevalence
of genetic types of T. gondii in all hosts studied is different from the
results obtained from chickens from Fernando de Noronha, an is-
land 350 km northeast to the mainland of Brazil where clonal Type
II predominated (Dubey et al., 2010). Because Fernando de Noro-
nha was occupied by Europeans, it is likely that the Type II strain
in Fernando de Noronha spread from Europe. In summary, existing
data indicated that Type II strain is absent or rare in the inland of
South America continent. This data suggest that Type II could have
originated outside of South America. The high frequency of Type II
strain in Chile is interesting. Chile is a long and narrow coastal
country located on the west side of the Andes Mountains which
separate it from most of the countries in South America. To its west
is the Pacific Ocean, which provides ports and harbors convenient
to maritime transportation to other countries. The unique geo-
graphical location of Chile may limit migration of animals to and
from surrounding countries in South America, which can explain
why its T. gondii population is different. In addition, trading with
countries in other regions (North America, Europe, Asia etc.) might
bring in the Type II strains which eventually expanded and become
dominant in Chile.
Type III strains were frequently identified from Central and
South America in this study. Several genotypes identical or closely
related to Type III lineage are identified, including ToxoDB #2, Tox-
oDB #7, ToxoDB #8, ToxoDB #14, ToxoDB #48, ToxoDB #140, Tox-
oDB #187 and ToxoDB #188 (Fig. 5), similar data were reported in
chickens and cats in Brazil (Pena et al., 2008). Clonal Type I strains
were also rare in the populations studied. However, identical and
closely related genotypes of Type I lineages are identified from this
study (ToxoDB #10, ToxoDB #27 and ToxoDB #35) and from chick-
ens and cats in Brazil (Pena et al., 2008). Taken together, these data
suggest that, in contrast to Type II lineage, clonal Type I and III lin-
eages might have a South America origin (Lehmann et al., 2006).
However, this need to be confirmed by sampling more T. gondii iso-
lates from wild animals in other continents such as Africa and Asia,
from which only limited typing data is available for comparison at
present. Overall, there are genetic substructures in several T. gondii
populations from Central and South America. Currently sampling
of population genetic studies only revealed a small proportion of
diversity which warrants more in depth study in the future.
5. Conclusion
This study of 164 T. gondi isolates revealed high diversity within
and between T. gondii populations in Central and South America.
However, the T. gondii population in Chile is unique in that it is lar-
gely represented by the Type II lineage. Our data clearly revealed
the lack of Type II strain in Central and South America. Previous
studies using microsatellite and intron sequence data suggested
four clusters of ancestral populations (Lehmann et al., 2006; Khan
et al., 2007). Since different T. gondii isolates and markers were
analyzed in these studies, direct comparison of data is difficult.
However, it is apparent that all methods have come to a similar
conclusion that there is very limited number of ancestral genomes
contributed the makeup of modern data population structure of T.
gondii.
Acknowledgements
The authors thank Leandra Ferreira, Juliana Martins for their
help in revival of T. gondii strains.
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