International Journal for Parasitology 39 (2009) 1475–1483

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International Journal for Parasitology

journal homepage: www.elsevier .com/locate / i jpara

Trypanosoma vivax displays a clonal population structure

Craig W. Duffy a,b, Liam J. Morrison a, Alana Black b, Gina L. Pinchbeck c, Robert M. Christley c,Andreas Schoenefeld d, Andy Tait a, C. Michael R. Turner b, Annette MacLeod a,*

a Wellcome Centre for Molecular Parasitology, Glasgow Biomedical Research Centre, Faculty of Veterinary Medicine, University of Glasgow,120 University Place, Glasgow G12 8TA, United Kingdomb Division of Infection and Immunity, Faculty of Biomedical and Life Sciences, University of Glasgow, Glasgow Biomedical Research Centre,120 University Place, Glasgow G12 8TA, United Kingdomc Faculty of Veterinary Science, University of Liverpool, Leahurst, Neston CH64 7TE, United Kingdomd International Trypanotolerance Centre, PMB 14, Banjul, Gambia

a r t i c l e i n f o

Article history:Received 21 March 2009Received in revised form 21 May 2009Accepted 22 May 2009

Keywords:Trypanosoma vivaxPopulation geneticsMatingMicrosatellitesMultilocus genotypes

0020-7519/$36.00 Crown Copyright � 2009 Publishedoi:10.1016/j.ijpara.2009.05.012

* Corresponding author. Tel.: +44 141 3303650; faxE-mail address: gvwa08@udcf.gla.ac.uk (A. MacLeo

a b s t r a c t

African animal trypanosomiasis, or Nagana, is a debilitating and economically costly disease with a majorimpact on animal health in sub-Saharan Africa. Trypanosoma vivax, one of the principal trypanosome spe-cies responsible for the disease, infects a wide host range including cattle, goats, horses and donkeys andis transmitted both cyclically by tsetse flies and mechanically by other biting flies, resulting in a distribu-tion covering large swathes of South America and much of sub-Saharan Africa. While there is evidence formating in some of the related trypanosome species, Trypanosoma brucei, Trypanosoma congolense and Try-panosoma cruzi, very little work has been carried out to examine this question in T. vivax. Understandingwhether mating occurs in T. vivax will provide insight into the dynamics of trait inheritance, for examplethe spread of drug resistance, as well as examining the origins of meiosis in the order Kinetoplastida.With this in mind we have identified orthologues of eight core meiotic genes within the genome, thepresence of which imply that the potential for mating exists in this species. In order to address whethermating occurs, we have investigated a sympatric field population of T. vivax collected from livestock inThe Gambia, using microsatellite markers developed for this species. Our analysis has identified a clonalpopulation structure showing significant linkage disequilibrium, homozygote deficits and disagreementwith Hardy–Weinberg predictions at six microsatellite loci, indicative of a lack of mating in this popula-tion of T. vivax.

Crown Copyright � 2009 Published by Elsevier Ltd. All rights reserved.

1. Introduction

African trypanosomes cause debilitating diseases in humansand domestic animals in sub-Saharan Africa. Animal African try-panosomiasis, more commonly known as Nagana, remains a seri-ous problem for livestock and is caused by Trypanosomacongolense, Trypanosoma vivax, and to a lesser extent by Trypano-soma brucei, with mixed species infections being common (Hoare,1972; Auty et al., 2008; Pinchbeck et al., 2008). This livestock dis-ease has an important impact on human welfare, resulting in in-come loss in very resource-poor settings, with an estimated costof US $1300 million per year (Shaw, 2004). Despite the consider-able impact on animal health and the subsequent downstreameffects on human populations, many aspects of the disease remainpoorly understood.

The host range of the animal infective trypanosomes is exten-sive, predominantly encompassing ungulates, with infection most

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: +44 141 3305422.d).

commonly reported in domestic livestock such as bovines, equinesand caprines (Hoare, 1972; Gardiner and Wilson, 1987). Naganaresulting from infection with T. vivax is typically debilitating, withanaemia, weight loss and reduced work capacity common in live-stock (Hoare, 1972; Silva et al., 1998; Osório et al., 2008). Infectionsin West Africa are commonly associated with an acute diseasecompared to the chronic infections of East Africa (Fasogbon et al.,1990; Magona et al., 2008), although severity and length of infec-tion may vary significantly depending on parasite strain, endemic-ity and host species (Taylor and Mertens, 1999; Batista et al., 2007;Rodrigues et al., 2008). Relatively infrequent severe haemorrhagicoutbreaks, with high mortality levels, have been periodically re-ported in East Africa (Catley et al., 2002; Magona et al., 2008). Incommon with the other Salivarian trypanosomes, T. vivax is trans-mitted by a diverse range of Glossina spp., and thus is primarilyfound within the tsetse belt of sub-Saharan Africa. Trypanosoma vi-vax may also be efficiently transmitted mechanically by a numberof biting flies, (Desquesnes and Dia, 2004; Cherenet et al., 2006;Delafosse et al., 2006; Sinshaw et al., 2006) which has allowed itto become established outside the tsetse belt of Africa and in large

d.

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parts of South America (Jones and Dávila, 2001; Cherenet et al.,2006; Cortez et al., 2006; Osório et al., 2008).

The reported prevalence of T. vivax shows considerable varia-tion, with geography, abundance of tsetse or biting flies and hostspecies all important variables. Within the tsetse belt overallT. vivax prevalence is typically reported within the 5–15% range,and will often account for up to half of total trypanosome preva-lence (Kalu et al., 2001; Njiokou et al., 2004; Waiswa andKatunguka-Rwakishaya, 2004). Outside of the tsetse belt T. vivaxprevalence, where present, is typically lower, in the range of2–10% (Delafosse et al., 2006; Sinshaw et al., 2006) and dependentupon local and seasonal variation in fly abundance. When tsetseflies are absent T. vivax typically accounts for all but a smallminority of observed trypanosome infections in African livestock(Cherenet et al., 2006; Delafosse et al., 2006).

True prevalence rates may however be much higher than thesecommonly reported values due to the limited sensitivity of themicroscopy based techniques typically utilised (Delafosse et al.,2006). Faye et al. (2001) observed an approximately seven timeshigher prevalence of bovine trypanosomiasis when comparingPCR-based identification with the traditional microscopy tech-nique in an analysis of herds in regions of high and low tsetse chal-lenge in The Gambia. Similarly, Pinchbeck et al. (2008) recentlyreported a significantly higher detection of prevalence in clinicalequine samples from The Gambia when comparing PCR detectionwith microscopy, reporting a T. vivax prevalence of 87% from PCRidentification, compared with a total trypanosome prevalence(T. vivax, T. congolense and T. brucei) of only 18% with microscopy.

In order to fully understand and manage the disease caused by T.vivax and other trypanosomes, we must develop a better under-standing of the parasite’s basic biology and population dynamics,in particular the mode of reproduction. Understanding how the spe-cies may exchange genetic material will allow predictions of its abil-ity to adapt to environmental changes and to develop and spreadtraits, such as drug resistance, that are important for understandingboth the epidemiology of the disease and its control. Evidence formating has been obtained for three species of kinetoplastid, Trypan-osoma cruzi, T. congolense and T. brucei, that are phylogenetically re-lated to T. vivax (Stevens et al., 1999). Trypanosoma cruzi, endemic toSouth America, appears to have a system of inheritance involvingrare fusion events and random chromosome loss (Gaunt et al.,2003) generating stable and essentially clonal lineages. A numberof candidate hybrid lineages have been identified within the naturalpopulations (Brisse et al., 2003; Westenberger et al., 2005; de Freitaset al., 2006). Population studies of T. congolense, one of the Africantrypanosomes responsible for Nagana, have revealed a considerabledegree of genetic heterogeneity with three distinct clades, Savannah,Forest and Kilifi, being identified (Young and Godfrey, 1983; Gash-umba et al., 1988). For the Savannah clade a recent study has re-vealed evidence for mating in this species (Morrison et al., 2009).

Trypanosoma brucei is the only member of the Trypanosomati-dae that has been directly shown by laboratory crosses to have afunctional Mendelian system of inheritance (Turner et al., 1990;MacLeod et al., 2005). Mating is not obligatory however and the ex-tent of mating in natural populations of T. brucei has been the sub-ject of much controversy (Tibayrenc et al., 1990; Maynard-Smithet al., 1993; MacLeod et al., 2000). Some of these studies revealedhigh levels of linkage disequilibrium between alleles at pairs of lociwith the data interpreted as indicating that mating plays only aminor role in natural populations (Tibayrenc et al., 1990; May-nard-Smith et al., 1993). However, apparent linkage disequilibriumcan result from a sub-structured population, due to geography,host or cryptic speciation (MacLeod et al., 2001) or from samplingbias, by non-random selective amplification of trypanosomeseither through growth in rodents or in vitro culture (McNamaraet al., 1995; Jamonneau et al., 2003). Analysis of data from the most

intensively studied trypanosome population in South-East Uganda,which took many of these confounding factors into account, hassuggested that mating occurs in the field in Trypanosoma bruceibrucei, but infrequently in Trypanosoma brucei rhodesiense (MacLe-od et al., 2000). Similar analysis of Trypanosoma brucei gambiensepopulations have indicated that mating is rare or absent in popula-tions of this subspecies (Koffi et al., 2007; Simo et al., 2007; Morri-son et al., 2008; Koffi et al., 2009).

To date there have been few population studies to assess thediversity and population dynamics of T. vivax. Here, we have there-fore analysed the population structure of this economically impor-tant species to address the question of mating in a sympatricpopulation of T. vivax from livestock in The Gambia, in an area wherethe cyclical vector (Glossina spp.) is highly prevalent. Our analysishas identified the presence of a high prevalence T. vivax populationwith characteristically low parasitaemia. Using species-specificmicrosatellite markers developed specifically for this study, we de-scribe the population structure and potential for mating in T. vivax.

2. Materials and methods

2.1. Identification of meiotic genes

Orthologues of a core set of eight genes associated with meiosis(spo11, dmc1, mnd1, msh4, msh5, hop1, hop2 and rec8 (Schurko andLogsdon, 2008)) were identified using BLASTP searches of the con-tigs of the T. vivax geneDB database (http://www.genedb.org/genedb/tvivax/). Several of these genes have orthologues that havebeen previously identified in the T. brucei genome (spo11, dmc1,msh4, msh5 and hop1), and these were used to search for T. vivaxorthologues in these cases (El-Sayed et al., 2005; Ramesh et al.,2005). Conserved domains and motifs were identified in T. bruceiand T. vivax orthologues by NCBI Conserved Domain Databasev2.14 (http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml).GeneDB accession numbers are given in Supplementary Table S1.

2.2. Study area and sample collection

Five hundred and thirty-one samples were collected in March2006, August 2006 and January 2007 from donkeys (72 samples),horses (251 samples) and cattle (208 samples) from locationswithin a 50 km radius in the Central River District of The Gambia.The equine samples from March and August 2006 (Table 1) werepreviously described by Pinchbeck et al. (2008). These 241 sampleswere primarily collected from sick animals brought by owners toclinics run by the Gambian Horse and Donkey Trust (GHDT). TheGHDT is based at Sambel Kunda in Niamina East District with clin-ics held in the surrounding villages and markets. Seventy-three ofthese 241 samples were collected by random sampling of animalsfrom 15 of the nearby villages. An additional 82 equine samples,not described by Pinchbeck et al. (2008), were collected by theGHDT in January 2007 by further passive sampling at clinics. Inaddition, 208 bovine samples (Table 2) were collected by randomsampling of herds at the International Trypanotolerance Centre(ITC) field station at Bansang, The Gambia. Both equine and bovinesamples were from within an estimated 50 km radius of SambelKunda. For each sample approximately 200 lL of venous bloodwas spotted onto FTA� filter cards (Whatman) with subsequentair-drying. Parasitaemia was scored as positive or negative bymicroscopic examination of the buffy coat.

2.3. Diagnostic PCR

All field samples were initially tested by PCR with species-spe-cific primers directed against multicopy satellite repeats of each

Table 1Prevalence in equines of Trypanosoma vivax infections as determined by species-specific PCR. All samples were collected from animals brought to clinics run by the GambianHorse and Donkey Trust, The Gambia.

Species present March 2006(n = 154)

August 2006(n = 87)

January 2007(n = 82)

Horse(n = 251)

Donkey(n = 72)

Overall prevalence(n = 323)

N P % N P % N P % N P % N P % N P %

T. vivax only 71 46 40 46 34 41 125 50 20 28 145 45T. vivax + Trypanosoma congolense mixed infection 30 19 19 22 21 26 52 20 18 25 70 22T. vivax + Trypanosoma brucei mixed infection 23 15 10 11 3 4 25 10 11 15 36 11T. vivax + T. congolense + T. brucei mixed infection 7 5 10 11 2 2 14 6 5 7 19 6

Total T. vivax 131 85 79 91 60 73 216 86 54 75 270 84

n, number of samples; N, number of trypanosome-positive samples; P %, percentage of positive samples.

Table 2Prevalence in bovines of Trypanosoma vivax infections as determined by species-specific PCR. Samples were collected by random sampling of herds owned by the InternationalTrypanotolerance Centre (ITC), The Gambia.

Species present August 2006 (n = 15) January 2007 (n = 193) Total bovine (n = 208)

N P % N P % N P %

T. vivax only 7 na 16 8 23 11T. vivax + Trypanosoma congolense mixed infection 1 na 0 0 1 1T. vivax + Trypanosoma brucei mixed infection 5 na 4 2 9 4T. vivax + T. congolense + T. brucei mixed infection 0 na 1 7 1 1

Total T. vivax 13 na 21 11 34 16

n, number of samples; N, number of trypanosome-positive samples; P %, percentage of positive samples; Na, not applicable, as only microscopically positive samples wereexamined.

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respective species or subgroup; T. vivax, T. congolense Savannah, T.congolense Forest, T. congolense Kilifi and T. brucei (Masiga et al.,1992). All T. congolense-positive samples were of the Savannahclade, so T. congolense in this current study refers to T. congolenseSavannah. Whole genome amplification (WGA) reactions were car-ried out on all T. vivax-positive samples as described previously(Morrison et al., 2007), with two FTA discs used as substrate ineach reaction, and pooling of three independent reactions to min-imise allele dropout.

2.4. Identification of microsatellite markers

Trypanosoma vivax sequence data was obtained from The San-ger Institute website at http://www.sanger.ac.uk/Projects/T_vi-vax/. Microsatellite markers were identified by screening of theTviv2Kb.cons20Mar06 release file using Tandem Repeats Findersoftware (http://tandem.bu.edu/trf/trf.html) (Benson, 1999) withcandidates selected based on their repeat copy number and thefidelity of the repeats. All microsatellites selected are located onseparate contigs to minimise the chance of close physical linkage.Nested oligonucleotide primer sets were designed to the uniqueflanking sequence of the selected microsatellite loci with the aidof PRIDE 2.1 (http://www.dkfz-heidelberg.de/tbi_old/services/Pride/search_primer) (Haas et al., 1998). All PCR amplificationswere carried out using the previously described reaction buffer(MacLeod et al., 1999). One microlitre of a 1/100 dilution of firstround product was used as a template in the second round ofnested PCRs. All nested reactions for genotyping were carried outunder the same conditions: 50 s at 95�C, 50 s at 55�C and 50 s at65�C for 28 cycles for both rounds.

2.5. Allele size determination and multilocus genotype (MLG)determination

One internal primer for each marker included a 50 FAM or HEXmodification to allow the detection of size-separated products(Supplementary Table S2) using a capillary-based sequencer (ABI3100 Genetic Analyser; Applied Biosystems; Dundee Sequencing

Service http://www.dnaseq.co.uk/) alongside a set of ROX labelledsize standards (GS400HD markers, Applied Biosystems). This al-lowed for the determination of DNA fragment length using PeakScanner v1.0 software (Applied Biosystems). Microsatellite alleleswere defined as individual peaks on the Peak Scanner trace witheach allele designated a unique identifier. The specific allele com-binations across the six markers allowed for generation of a MLGfor each isolate, with each unique MLG assigned an ID number.

2.6. Population analysis

MLGs were analysed using Clustering Calculator (http://www2.biology.ualberta.ca/jbrzusto/cluster.php), generating a Phy-lip Drawtree string and bootstrap values (unweighted arithmeticaverage clustering method, Jaccard’s similarity coefficient). PhylipDrawtree data was entered into Treeview (http://taxonomy.zoology.gla.ac.uk/rod/treeview.html) (Page, 1996) to generatedendrograms of similarity. Hardy–Weinberg equilibrium and link-age disequilibrium between paired loci were examined using Ge-netic Distance Analysis program (GDA; http://hydrodictyon.eeb.uconn.edu/people/plewis/software.php). GenAlEx (http://www.anu.edu.au/BoZo/GenAlEx/) (Peakall and Smouse, 2006) was uti-lised for FIT determination. The program MLGism (Stenberg et al.,2003) was used to determine the probability of replicatedgenotypes occurring due to sexual recombination. Psex values werecalculated for each replicated MLG and compared with values gen-erated by 106 simulated populations.

3. Results

3.1. Identification of meiosis-associated genes

To assess the potential for meiosis in T. vivax, we have examinedthe genome reference sequence for evidence of conserved meiosis-associated genes. Using the orthologous T. brucei putative proteinsequences, the eight genes spo11, dmc1, mnd1, msh4, msh5, hop1,hop2 and rec8 (Schurko and Logsdon, 2008) were putatively iden-

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tified within the T. vivax genome (Supplementary Table S1). Formnd1and msh5 the annotated genes lack start codons, although itis possible that these genes use start codons 400 and 232 bp up-stream, respectively. For the purpose of the alignment we havechosen to include only the annotated sequences of both genes.

The level of identity between T. vivax and T. brucei ranges be-tween 44% and 86% at the protein level with recognisable super-family motifs conserved, suggesting a possible retention offunction following the divergence of these two species. While themeiotic functions of these genes have yet to be characterised inT. brucei, the presence of mating in this species implies that theyare functional. The fact that these genes are retained in T. vivaxsuggests that the machinery required for, and therefore potentialto undergo, mating remains in this species.

3.2. Prevalence of T. vivax, T. congolense and T. brucei in The Gambia

A total of 531 equine and bovine samples collected from TheGambia were examined to determine the total prevalence of T. vi-vax and the frequency of mixed infections with T. congolense orT. brucei. The equine data are shown in Table 1. The trypanosomeprevalence of the March and August samples, determined by bothmicroscopy and PCR, has been previously described by Pinchbecket al. (2008). The values reported for these samples in Table 1 differslightly from those reported by Pinchbeck et al. (2008), as a resultof re-examination of the species identification tests. Trypanosomavivax prevalence in equines was 85% in March 2006, 91% in August2006 and 73% in January 2007. Mixed species infections of T. vivaxwith T. brucei, T. congolense or both were common, and occurred in46% of T. vivax-infected animals.

In addition to the equine samples, sympatric bovine sampleswere collected through a random sampling of herds maintainedby the ITC, with the data summarised in Table 2. Trypanosoma vivaxprevalence in bovines was 11% in 2007 (n = 193). An additional setof 15 samples collected in 2006, which were identified as being po-sitive by microscopy, were also included in this analysis. Of the 34bovines infected with T. vivax, 11 were also positive for T. brucei orT. congolense. The difference in prevalence compared with theequines is likely due to the random sampling employed and thusmay be more indicative of the true prevalence. We cannot howeverrule out other factors such as local variation or differing hostsusceptibilities.

3.3. Development of T. vivax-specific microsatellite markers

In order to assess the genetic diversity and potential frequencyof mating in T. vivax we have developed a panel of eight microsat-ellites markers (TV3, TV4, TV6, TV14, TV17, TV24, TV31 and TV49;for primer sequences and microsatellite details see SupplementaryTable S2) for use in this study. All eight markers are specific forT. vivax, amplifying from the T. vivax ILRAD V34 DNA used as a po-sitive control, while no amplification products were observed withT. b. brucei TREU 927 or T. congolense KETRI 2885.

3.4. Genetic analysis

Three hundred and four of the 531 samples were identified aspositive for T. vivax using PCR amplification of a species-specificsatellite repeat (Masiga et al., 1992). We attempted to genotypeall T. vivax-positive samples using the panel of eight single-locusmicrosatellite markers. However the majority of samples failed toamplify for any single-locus marker (Supplementary Fig. S1), thusfull MLGs (positive allele identification for all eight markers) weresuccessfully obtained for only 31 samples (Table 3), 10% of the totalT. vivax infections identified. This low amplification rate with thesingle copy microsatellite markers is suggestive of a population

where the majority of infections are present at parasitaemias be-low the threshold for detection by single-locus PCR but within thatof the more sensitive multicopy satellite marker.

While two alleles were identified for both TV3 and TV4 thesemarkers were largely monoallelic in the study population, with asingle allele present at a frequency above 0.8, rendering themuninformative for much of the genetic analysis. The remainingsix markers had between two and four alleles per locus (Fig. 1and Table 3). Of the 31 samples for which full MLGs were obtainedno mixed T. vivax genotype infections were identified, as definedby the presence of three or more alleles for any single marker.The large differences in allele sizes, up to 63 bp, and lack of inter-mediate alleles in the population suggest the microsatellites maybe following a non-stepwise mutation model or the sample sizeis too small to detect a full range of allele sizes.

From the 31 fully genotyped samples nine unique MLGs wereidentified, four of which were represented by multiple samples(Table 3 and Fig. 2). MLG 8 was detected 15 times, constituting al-most half of the genotyped samples. The control sample, T. vivax IL-RAD V34 (MLG 1), originating from Kenya, had unique alleles atthree of the six loci (Table 3). Jaccard’s coefficient of similarity be-tween MLGs is displayed as a dendrogram of similarity (Fig. 2). All31 field samples are significantly different from the Kenyan T. vivaxILRAD V34 control by clustering analysis (bootstrap = 100).

To further our understanding of the T. vivax population struc-ture, allele frequencies were examined for deviation from Hardy–Weinberg equilibrium and for the presence of linkage disequilib-rium between the six loci. These tests indicate whether the ob-served allele combinations between loci or the genotypefrequencies resemble those expected in a randomly mating popu-lation. Significant disagreement (P < 0.05) with Hardy–Weinbergequilibrium predictions is present in five of the six loci (TV6,TV24, TV17, TV31 and TV49) (Table 4). This disagreement withHardy–Weinberg predictions is due to the global heterozygote ex-cess observed at all loci, with TV24 and TV17 at, or close to, hetero-zygote fixation. No homozygotes were identified for marker TV24despite the presence of four alleles at this locus. The population-wide heterozygote excess is reflected in the FIT values, rangingfrom �0.38 to �0.94 across the six markers (Table 4). To test forevidence of genome re-assortment and recombination, linkage dis-equilibrium between alleles at all pairwise combinations of lociwere examined. Significant levels of linkage disequilibrium(P < 0.02 and below) (Table 5) were observed between all pairwisecombinations, in line with expectations for a population resultingfrom clonal expansion.

As a final test to examine the role of mating in the population,samples were analysed with MLGsim, which simulates randomlymating populations from known allele frequencies in order to pre-dict MLG frequencies. It is then possible to determine whether ob-served MLG frequencies are higher than expected, indicating a lackof random mating. MLGsim identified three of the four repeatedMLGs (MLGs 4, 8 and 9) as having frequencies significantly(P < 0.01) higher than expected in a randomly mating population.MLG 10, present twice in the sample set, did not differ significantly(P > 0.05) in frequency from that expected in a randomly matingpopulation (data not shown).

4. Discussion

Despite the extensive distribution and considerable impact ofNagana, T. vivax, one of the principal agents of the disease, remainshighly neglected in the scientific literature. A major factor for thisis that the species is notoriously difficult to work with as isolatesare not easily adapted to culture or grown in standard laboratoryanimals (Gardiner, 1989). The few studies that have investigated

Table 3Collection details (sampling date and host species) and genotypes of the 31 fully genotyped Trypanosoma vivax samples plus the control sample, ILRAD V34. Samples weregenotyped at six microsatellite loci specific to T. vivax and allele sizes determined by comparison to labelled size standards following size-separation on a capillary-basedsequencer.

Sample Date Speciesa Locus and allele sizesb MLGc

TV6 TV14 TV17 TV24 TV31 TV49

59 Mar 06 D 279 293 211 229 143 206 122 140 476 506 103 138 872 Mar 06 D 279 302 211 211 143 206 140 157 476 476 103 103 9102 Mar 06 H 279 279 211 211 143 206 140 152 476 506 103 138 4103 Mar 06 H 279 279 211 229 143 206 122 140 476 506 103 138 7148 Mar 06 H 279 302 211 211 143 206 140 157 476 476 103 103 91067 Aug 06 H 279 302 211 229 143 143 140 152 476 506 103 138 21068 Aug 06 D 279 279 211 211 143 206 140 152 476 506 103 138 41081 Aug 06 H 279 293 211 229 143 206 122 140 476 506 103 138 81096 Aug 06 H 279 279 211 211 143 206 140 152 476 506 103 138 41100 Aug 06 D 279 279 211 211 143 206 140 152 476 506 103 138 4c2 Aug 06 C 279 293 211 229 143 206 122 140 476 506 103 138 82002 Jan 07 D 279 293 211 229 143 206 122 140 476 506 103 138 82005 Jan 07 H 279 293 211 229 143 206 122 140 476 506 103 138 82029 Jan 07 H 279 293 211 229 143 206 122 140 476 506 103 138 82037 Jan 07 H 279 302 211 211 143 206 140 157 476 476 103 103 92047 Jan 07 H 279 293 211 211 143 206 152 157 476 506 103 138 52058 Jan 07 H 279 279 211 211 143 206 140 157 476 476 103 103 102062 Jan 07 H 279 279 211 211 143 206 140 152 476 506 103 138 42069 Jan 07 H 279 293 211 229 143 206 122 140 476 506 103 138 82078 Jan 07 H 279 279 211 211 143 206 140 152 506 506 103 138 32081 Jan 07 D 279 293 211 229 143 206 122 140 476 506 103 138 83003 Jan 07 C 279 293 211 229 143 206 122 140 476 506 103 138 83035 Jan 07 C 279 279 211 211 143 206 152 157 476 506 103 138 63036 Jan 07 C 279 293 211 229 143 206 122 140 476 506 103 138 83037 Jan 07 C 279 293 211 229 143 206 122 140 476 506 103 138 83038 Jan 07 C 279 302 211 211 143 206 140 157 476 476 103 103 93039 Jan 07 C 279 293 211 229 143 206 122 140 476 506 103 138 83040 Jan 07 C 279 293 211 229 143 206 122 140 476 506 103 138 83041 Jan 07 C 279 279 211 211 143 206 140 157 476 476 103 103 103042 Jan 07 C 279 293 211 229 143 206 122 140 476 506 103 138 83043 Jan 07 C 279 293 211 229 143 206 122 140 476 506 103 138 8ILRAD V34 – – 279 293 211 211 160 185 140 136 476 476 138 117 1

a Species: D, donkey; H, Horse; C, cattle.b Allele size given in bp.c MLG, multilocus genotype, where each multilocus genotype represents a unique combination of microsatellite alleles across the six loci examined for this study.

Fig. 1. Distribution of allele frequency for the 31 fully genotyped samples collected from horses, donkeys and cattle in The Gambia using six Trypanosoma vivax-specificmicrosatellite markers. Alleles are grouped by locus and listed as their bp size.

C.W. Duffy et al. / International Journal for Parasitology 39 (2009) 1475–1483 1479

the genetic diversity in T. vivax have typically focused on compar-ison between isolates from across Africa and South America(Allsopp and Newton, 1985; Dirie et al., 1993). These studies haveshown that T. vivax can be loosely separated on the basis of an Eastor West African origin, with those from South America groupingwith West African isolates (Allsopp and Newton, 1985; Fasogbonet al., 1990; Cortez et al., 2006). Many of the isolates utilised in

these studies had, however, been previously adapted to laboratoryuse and may not therefore reflect the actual genetic diversity infield populations, due to the possible selection of genotypes duringisolation and adaptation to laboratory conditions (McNamara et al.,1995; Jamonneau et al., 2003). The studies of Kilgour et al. (1975)and Kilgour and Godfrey (1977) addressed the diversity of T. vivaxusing samples collected from a single geographic location and time

Fig. 2. Dendrogram of Trypanosoma vivax multilocus genotypes (MLGs) for the 31 fully genotyped samples collected from horses, donkeys and cattle in The Gambia. Thedendrogram was generated by Treeview from Clustering Calculator. Bootstrap values generated from 100 reiterations are shown for the major nodes. Scale bar representsdissimilarity.

Table 4Polymorphism, heterozygosity and agreement with Hardy–Weinberg equilibriumbased on allele frequencies observed in 31 Trypanosoma vivax-positive samplescollected from horses, donkeys and cattle in The Gambia following genotyping at sixT. vivax-specific microsatellite markers.

Locus Na Ho He FIT P

TV6 3 0.68 0.49 �0.38 0.04TV14 2 0.55 0.40 �0.39 0.07TV17 2 0.97 0.50 �0.94 <0.001TV24 4 1.00 0.68 �0.48 <0.001TV31 2 0.77 0.49 �0.59 <0.001TV49 2 0.81 0.48 �0.68 <0.001

Na, no. alleles; Ho, observed heterozygosity; He, expected heterozygosity; FIT,inbreeding coefficient; P, probability of agreement with Hardy–Weinberg Equilib-rium (P > 0.05 = agreement with Hardy-Weinberg equilibrium).

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point, which were later analysed by Tibayrenc et al. (1991). Sam-pling directly from Zebu cattle in Nigeria these studies identified

61 and 31 T. vivax-positive animals and with the use of two isoen-zyme markers demonstrated the presence of three main T. vivaxisotypes, which were maintained as the dominant isotypes withinthe population during the 3 year period between the studies. Whilethese studies were limited by the use of only two isoenzymes to as-say diversity, together with the nine isolates from Allsopp andNewton (1985) they provided the first evidence for clonality inthe species based on the criteria outlined by Tibayrenc et al.(1991), namely an over-representation of a small number of geno-types, an absence of recombinant genotypes and significant levelsof linkage disequilibrium between markers. For our study wetherefore aimed to further examine the prevalence, genetic diver-sity and mating system of T. vivax utilising samples collected overthe period of one year and from a localised geographic area. Ouranalysis suggests a high prevalence of T. vivax in The Gambia, char-acterised by low parasitaemic infections, limited genetic diversityand the clonal expansion of particular genotypes.

Table 5Linkage disequilibrium between all pairwise combinations of six Trypanosoma vivax-specific microsatellite markers in 31 T. vivax-positive samples collected from horses,donkeys and cattle in The Gambia.

Locus 1 Locus 2 P

TV6 TV14 0.02TV6 TV17 <0.001TV6 TV24 0.02TV6 TV31 0.01TV6 TV49 0.01TV14 TV17 <0.001TV14 TV24 <0.001TV14 TV31 <0.001TV14 TV49 <0.001TV17 TV24 <0.001TV17 TV31 <0.001TV17 TV49 <0.001TV24 TV31 <0.001TV24 TV49 <0.001TV31 TV49 <0.001

P, Probability of agreement with Hardy–Weinberg Equilibrium (P > 0.05 = agree-ment with Hardy-Weinberg equilibrium).

C.W. Duffy et al. / International Journal for Parasitology 39 (2009) 1475–1483 1481

Compared directly with T. brucei, clonality in T. vivax would atfirst glance appear to fit with expectations. Trypanosoma brucei isthe only member of the Salivarian trypanosomes for which matinghas been unequivocally demonstrated and displays a classical Men-delian pattern of inheritance. While the exact mechanism andrequirements remain elusive, mating in T. brucei is known to occurwithin the salivary glands of the tsetse fly vector. However in T. vivaxcyclical development in the tsetse is simpler in nature, being local-ised solely in the proboscis of the fly, possibly accounting for the easewith which this species can be mechanically transmitted. Despitethe apparent dominance of clonality, our results suggest that matingmay not be absent altogether. Examination of the genome sequenceallowed us to identify eight meiosis-associated genes (El-Sayedet al., 2005; Ramesh et al., 2005; Schurko and Logsdon, 2008) thatdemonstrate conservation of protein features between T. bruceiand T. vivax despite the early divergence of these lineages withinthe Salivarian clade (Stevens et al., 1999). The presence of the mei-otic machinery therefore appears to be ancestral in nature with theretention of these genes in T. vivax suggesting a potential continuedrole. The expression, functionality and in particular the meiotic rolesof these genes, however, are as yet undetermined, even in T. brucei.This is an area of research that deserves further scrutiny in all ofthe Salivarian trypanosomes. In contrast to the suggestion of extantmeiotic machinery, our microsatellite analysis has identified the keyfeatures of clonality (Tibayrenc et al., 1990; Maynard-Smith et al.,1993; Halkett et al., 2005; De Meeûs et al., 2006) namely excess het-erozygosity at all loci, significant disagreement with Hardy–Wein-berg predictions, significant levels of linkage disequilibriumbetween all loci combinations, an absence of recombinant genotypesand a limited number of unique genotypes, with one genotype dom-inating the population. These results show clear similarities with theanalysis by Tibayrenc et al. (1991), supporting the idea of clonality inT. vivax and suggesting that it may be the primary, if not only, modeof reproduction.

The main restriction on analysing the current population set isthe low parasitaemia leading to non-amplification of single-locusmicrosatellite markers for most T. vivax-positive samples. Para-sitaemia levels are known to vary considerably depending on par-asite strain, species, breed of host, geographic origin and presenceof other infections (Fasogbon et al., 1990; Batista et al., 2007;Magona et al., 2008; Pinchbeck et al., 2008). Identification ofinfections has conventionally been by microscopy following prep-aration of a buffy coat, estimated by Faye et al., 2001 to be seventimes less sensitive than the PCR technique we have employed

here. Our results, of a high prevalence of low parasitaemia infec-tions, reinforce these observations and suggest that T. vivax maybe more endemic than previously believed. There remains thepossibility that low parasitaemia infections might act as a reser-voir of genetic diversity with observed outbreaks of disease aris-ing from a limited number of virulent clones best adapted to thelocal environment. It may be, therefore, that we need to examinethe parasites from animals with subpatent levels of T. vivax par-asitaemia in order to uncover the true dynamics of the populationstructure. Given the already high sensitivity of the WGA and PCRtechniques employed in the current study, we will require meth-ods to concentrate trypanosome DNA by extraction from largervolumes of infected blood if we wish to characterise these cur-rently elusive populations.

Although there are suggestions from our data that mating mayoccur rarely, the predominance of clonal expansion is a feature thatT. vivax shares, among the Salivarian trypanosomes, with theagents of Human African Trypanosomiasis, T. b. rhodesiense(MacLeod et al., 2000) and T. b. gambiense (Koffi et al., 2007; Mor-rison et al., 2008; Koffi et al., 2009). While all of the available evi-dence supports clonality in T. b. gambiense, it is possible thatmating does occur in T. b. rhodesiense, as previous studies into thissubspecies have centred around foci of human infection, where vir-ulent strains may dominate. Other examples of trypanosomes thatare likely to propagate clonally include Trypanosoma evansi andTrypanosoma equiperdum, although in these cases the predictedclonality is due to their modes of transmission, mechanical andvenereal, respectively. These trypanosome species are essentiallyvariants of T. brucei (Gibson, 2007; Lai et al., 2008), that have lostthe ability to undergo cyclical transmission. They are thereforelikely to expand solely by asexual replication with the eventualloss of the potential for mating. As mentioned previously, endemicfield populations of those trypanosomes not under similar con-straints (T. b. brucei and T. congolense) have been shown to undergofrequent mating. The T. vivax population in the present study issampled from ‘typical’ host species (i.e. there are not specific ge-netic mutations in T. vivax, as far as we are aware, that confer sur-vival in cattle and equines), and are sampled from a region wherethe predominant vector is that in which cyclical development oc-curs. The strong evidence for linkage disequilibrium in the T. vivaxsamples is interpreted as reflecting a clonal population and con-trasts sharply with the evidence for mating in sympatric T. congo-lense subpopulations, where there is far less deviation from linkageequilibrium (Morrison et al., 2009). The discovery of evidence formating in T. congolense but not in T. vivax, from the same host sam-ples suggests that asexual reproduction is the de facto mode ofreproduction in this population of T. vivax, despite there beingapparent conditions conducive to mating. However it is possiblethat mating could occur in other T. vivax populations under differ-ent conditions and a detailed analysis of further disease foci is nec-essary to address this.

As described above, T. vivax is the most ancient of the Salivar-ian trypanosomes, and has possibly lost the ability to mate, ratherthan T. brucei and T. congolense gaining this feature. However thepresence of meiotic gene orthologues that have not been dis-rupted by internal stop codons could be explained by insufficienttime for such mutations to accumulate, that these genes havenon-meiotic functions in T. vivax, or that mating does occur inother epidemiological situations. The Salivarian trypanosomes,therefore, represent a group of related eukaryotes that providean intriguing perspective on the evolution and loss of sexualrecombination. In conclusion, we describe here an examinationof the population structure of the animal pathogen T. vivax andhave identified the predominance of clonality. This is an impor-tant step in expanding our understanding of this major, yet ne-glected, animal pathogen.

1482 C.W. Duffy et al. / International Journal for Parasitology 39 (2009) 1475–1483

Acknowledgements

Craig Duffy, Liam Morrison, Alana Black, Mike Turner, Andy Taitand Annette MacLeod are funded by the Wellcome Trust. AnnetteMacLeod is a Wellcome Trust Career Development Research Fel-low. Annette MacLeod also acknowledges financial support fromTenovus Scotland. We would also like to acknowledge studentsfrom the University of Liverpool, UK (Lucinda Meehan, JoannaLangford and Joanne Ireland), and the assistance of staff of theInternational Trypanotolerance Centre in Banjul, The Gambia (M.Mbacke, M.A. Bojang, A. Jallow, K. Mboge, A. Jarju, A.A. Bankole)and the Gambian Horse and Donkey Trust (in particular, HeatherArmstrong, Saloum Jallow, Jibril Jallow and Amadou Jallow) fortheir efforts in sample collection.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.ijpara.2009.05.012.

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