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. 2013 Nov 29;8(11):e82269. doi: 10.1371/journal.pone.0082269

Putative Panmixia in Restricted Populations of Trypanosoma cruzi Isolated from Wild Triatoma infestans in Bolivia

Christian Barnabe 1,2,*, Rosio Buitrago 1,2, Philippe Bremond 1, Claudia Aliaga 1,2, Renata Salas 1,2, Pablo Vidaurre 3, Claudia Herrera 4, Frédérique Cerqueira 5, Marie-France Bosseno 1,2, Etienne Waleckx 1,2, Simone Frédérique Breniere 1,2
Editor: Érika Martins Braga6
PMCID: PMC3843716  PMID: 24312410

Abstract

Trypanosoma cruzi, the causative agent of Chagas disease, is subdivided into six discrete typing units (DTUs; TcI–TcVI) of which TcI is ubiquitous and genetically highly variable. While clonality is the dominant mode of propagation, recombinant events play a significant evolutive role. Recently, foci of wild Triatoma infestans have been described in Bolivia, mainly infected by TcI. Hence, for the first time, we evaluated the level of genetic exchange within TcI natural potentially panmictic populations (single DTU, host, area and sampling time).

Seventy-nine TcI stocks from wild T. infestans, belonging to six populations were characterized at eight microsatellite loci. For each population, Hardy-Weinberg equilibrium (HWE), linkage disequilibrium (LD), and presence of repeated multilocus genotypes (MLG) were analyzed by using a total of seven statistics, to test the null hypothesis of panmixia (H0).

For three populations, none of the seven statistics allowed to rejecting H0; for another one the low size did not allow us to conclude, and for the two others the tests have given contradictory results. Interestingly, apparent panmixia was only observed in very restricted areas, and was not observed when grouping populations distant of only two kilometers or more. Nevertheless it is worth stressing that for the statistic tests of "HWE", in order to minimize the type I error (i. e. incorrect rejection of a true H0), we used the Bonferroni correction (BC) known to considerably increase the type II error ( i. e. failure to reject a false H0). For the other tests (LD and MLG), we did not use BC and the risk of type II error in these cases was acceptable. Thus, these results should be considered as a good indicator of the existence of panmixia in wild environment but this must be confirmed on larger samples to reduce the risk of type II error.

Introduction

Trypanosoma cruzi is the causative agent of Chagas disease, which affects about eight million people in Latin America, of whom 30–40% either suffers or will develop cardiomyopathy, digestive megasyndromes, or both. Moreover, Chagas disease is becoming an emerging health problem in nonendemic areas because of the increasing number of migrants from endemic areas [1]. The T. cruzi species exhibits a very high genetic variability similar to that observed within different species of other kinetoplastidae such as Leishmania [2]. Consensual taxonomy recognized six discrete typing units (DTUs named TcI–TcVI) [3] and one additional group only found in bats (Tcbat) [4] within T. cruzi [5]; TcI is the most genetically diversified and ubiquitous of them, spreading from the United States to Argentina, and present in both sylvatic and domestic biotopes. As a result of the dominant clonal multiplication, identical multilocus genotypes (MLGs) have been sampled over several years and over large geographical distances, leading to considering the species as multiclonal [6]. The long-term clonal evolution is involved in the current important genetic diversity of the species, but more and more “genetic exchange” events are being described. Scarce hybridization events are the source of two hybrid DTUs [7–9], mitochondrial introgression events have been detected [10,11], and different levels of gene recombination have been described [12–14]. In addition, high genome plasticity is also a source of variability. Aneuploidy is suspected [15], occurrence of allele loss is possible during genetic exchanges, the mitochondrial genome is probably more complex than previously described, and maxicircle gene recombination occurs as well as intragenic recombination [14]; heteroplasmy has also been reported [16]. Several of these genetic exchange mechanisms have been triggered in vitro [17] and are still hotly debated in the field. As previously stated [18]: “From an epidemiological and medical point of view, the important parameter to evaluate is the stability of the genetic clones in space and time.” This stability directly depends on the level of genetic exchanges (in the broad sense). Indeed, within a strict clonal framework the clones are stable in space and time, and they convey similar biological characteristics that can be crucial for epidemiological and medical features generation after generation. In contrast, with more or less frequent recombination, such correlations are not necessarily expected, hence the importance of studying genetic exchanges between stocks.

In general terms, to test panmixia, two prerequisites are needed: (i) the use of an appropriate genetic marker not subjected to selection and with a sufficient level of polymorphism and (ii) populations isolated in restricted areas where parasites are assumed to be in sympatry. Our previous work showed that microsatellite markers are relevant for studying the population genetics of T. cruzi at the DTU level [19]. Moreover, abundant and accessible foci of wild Triatoma infestans vectors mainly infected by TcI have been recently described in Bolivia [20,21]; hence, in the present work it was possible to evaluate the level of genetic exchanges in potentially panmictic T. cruzi TcI populations isolated from sylvatic T. infestans in Bolivia.

Materials and Methods

Parasite stocks and multilocus microsatellite typing (MLMT)

Seventy-nine T. cruzi stocks, previously assigned to the DTU TcI using the multiplex miniexon PCR method [22] and isolated from six potentially panmictic Bolivian sylvatic T. infestans populations (see Figure 1) were compared to 21 TcI sylvatic reference stocks ranging from the United States to South America (see Table 1). These populations were defined in small geographic areas in which we believe that the T. infestans vector can move freely (maximum distance between two stocks less than five hundred meters). Four of them are located in La Paz department (namely, Luribay, central sampling point at 17°3'54.90"S / 67°39'53.85"W; Mecapaca, 16°42'45.90"S / 67°59'27.13"W; Sap-Sap, 16°48'47.23"S / 67°42'9.83"W; and Sap-Cosi, 16°49'50.00"S / 67°42'22.20"W), while the other two populations are located in Cochabamba department (namely, Qui-Urk, 17°25'29.00"S / 66°17'45.20"W and Qui-Bsia, 17°25'28.81"S / 66°15'52.75"W). The distances between the populations are given in Figure 1. The stocks directly isolated from wild triatomines, all captured with mice bait Noireau’s traps, were cultured in LIT medium supplemented with 10% fetal calf serum. DNA was extracted with a conventional CTBA 2% method and the solutions diluted to 20 ng/µl before use. Eight previously described microsatellite loci were used, namely MCLE01, SCLE10, SCLE11, MCLF10, A427, MCLG10, C875, and MCLE08 [17,23] using the same PCR conditions [19]. Electrophoreses of fluorescent-labeled PCR products, diluted and denatured in 20 µl of HiDi formamide, were carried out on a ABI3130xL Genetic Analyzer (Applied Biosystems, Carlsbad, CA, USA), with Genescan 500 LIZ as the internal size standard. GeneMapper® software (Applied Biosystems, Carlsbad, CA, USA) was used to characterize the alleles.

Figure 1. Map of Bolivia: localization of the six populations of Trypanosoma cruzi under study isolated from sylvatic Triatoma infestans and distances between populations.

Figure 1

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Table 1. Codes, locations, genotypes at each locus and reference numbers of each multilocus genotype (MLG) of the 79 Trypanosoma cruzi TcI stocks isolated from six potentially panmictic populations and of the 21 T. cruzi TcI reference strains.

Stock code Location* MCLE01
 SCLE10
 SCLE11
 MCLF10
 A427
 MCLG10
 C875
 MCLE08
 MLG
LaPaz / Mecapaca / Tun1 / Mecapaca
MEC095 id. 128 128 250 254 138 138 188 188 185 185 155 155 191 191 117 117 66
MEC099 id. 128 128 250 254 138 138 188 188 186 186 155 155 183 187 117 117 74
MEC101 id. 128 128 250 254 138 138 188 188 186 186 155 155 183 187 117 119 73
MEC102 id. 128 128 250 254 138 138 184 188 186 186 155 155 183 187 117 119 71
MEC103 id. 128 129 250 254 139 139 184 188 186 186 155 155 191 191 117 117 76
MEC107 id. 128 128 254 254 138 138 184 188 186 186 155 155 191 191 117 119 70
MEC161 id. 128 128 250 254 139 139 188 188 186 186 155 155 187 191 119 119 86
MEC166 id. 128 128 250 254 139 139 188 188 186 186 155 155 187 191 119 119 86
MEC170 id. 128 128 250 254 139 139 188 188 186 186 155 155 183 187 119 119 85
MEC171 id. 127 127 250 250 138 138 184 188 178 184 155 155 183 191 117 119 58
MEC173 id. 128 128 250 250 139 141 184 188 177 184 155 155 183 191 119 119 59
LaPaz / Luribay / Luribay / Luribay
LUR229 id. 128 128 238 250 138 138 184 184 178 186 155 155 189 189 117 117 67
LUR237 id. 128 128 250 250 138 138 184 184 185 185 155 155 189 189 117 117 68
LUR245 id. 120 128 250 254 138 138 184 188 186 186 146 155 189 189 117 117 64
LUR250 id. 128 128 250 254 138 138 184 188 185 185 155 155 189 189 0 0 65
LUR258 id. 128 128 250 250 138 140 184 184 179 186 155 155 189 189 117 117 69
LUR265 id. 128 128 250 250 138 138 184 184 177 187 155 155 187 187 0 0 60
LaPaz / Murillo / Sapini / Sap-Sap
SAP203 id. 129 129 250 254 138 138 184 188 175 178 155 155 187 189 117 119 21
SAP207 id. 128 128 250 254 138 138 188 188 178 178 155 155 187 189 117 119 48
SAP223 id. 120 128 250 254 138 138 184 188 175 178 155 155 187 189 117 119 53
SAP233 id. 129 129 250 254 138 138 184 188 175 178 155 155 189 191 117 119 22
SAP241 id. 117 128 250 254 138 138 184 188 177 177 146 146 187 189 117 119 50
SAP242 id. 129 129 250 254 138 138 184 188 175 178 155 155 187 189 117 119 21
SAP242b id. 129 129 250 254 138 138 184 188 178 178 146 155 187 189 117 119 24
SAP243 id. 129 129 250 250 138 140 188 188 178 178 155 155 187 189 117 119 35
SAP256 id. 128 128 250 254 138 138 182 186 175 178 146 146 187 189 117 119 51
SAP259 id. 128 128 250 254 139 139 184 188 175 178 146 155 187 189 117 119 52
SAP260 id. 129 129 250 254 138 138 184 188 175 175 146 146 187 189 117 119 26
SAP261 id. 129 129 250 254 138 138 184 188 175 175 146 155 187 189 117 119 25
SAP263 id. 129 129 250 254 138 138 184 188 175 175 155 155 189 191 117 119 23
SAP264 id. 129 129 250 254 138 138 184 184 178 178 155 155 189 189 119 119 19
SAP265 id. 129 129 250 254 138 138 184 188 175 184 155 155 187 187 117 119 30
SAP266 id. 129 129 254 254 138 138 188 188 178 178 155 155 189 189 117 119 17
SAP267 id. 120 128 250 254 138 138 184 188 175 178 146 155 187 189 117 119 54
SAP270 id. 128 128 250 254 138 138 184 188 175 178 155 155 187 189 117 119 55
SAP271 id. 129 129 250 250 138 140 184 188 186 186 146 155 187 189 117 119 39
SAP272 id. 129 129 250 254 138 138 184 188 175 186 146 146 187 189 117 119 27
SAP391 id. 120 128 250 250 138 138 184 184 177 177 155 155 187 187 119 119 62
SAP404 id. 128 128 250 254 138 138 184 188 175 175 155 155 187 189 117 119 56
SAP405 id. 117 128 250 250 138 138 184 184 177 177 155 155 187 187 119 119 63
SAP445 id. 120 128 250 254 138 138 184 184 177 177 155 155 187 187 119 119 61
SAP491 id. 120 128 250 254 138 138 184 188 175 175 155 155 187 189 117 119 57
SAP492 id. 120 128 250 254 138 138 184 188 175 175 155 155 187 189 117 119 57
SAP500 id. 128 128 250 254 138 138 184 188 175 175 155 155 187 189 117 119 56
LaPaz / Loayza / Cosiraya / Sap-Cosi
SAP302 id. 129 129 250 250 137 137 188 188 178 186 155 155 187 187 117 119 37
SAP303 id. 128 128 250 254 137 137 188 188 178 178 155 155 187 187 117 119 49
SAP304 id. 129 129 250 250 138 138 184 188 178 186 155 155 187 189 117 119 34
SAP310 id. 129 129 250 254 138 138 184 188 186 186 146 155 187 187 117 119 28
SAP312 id. 129 129 254 254 138 138 188 188 186 186 146 146 189 189 117 119 18
SAP313 id. 129 129 250 254 138 138 184 188 178 186 155 155 187 187 117 119 31
SAP318 id. 129 129 250 250 138 138 188 188 178 186 146 146 187 187 117 119 46
SAP319 id. 129 129 250 250 138 138 188 188 178 178 146 146 187 187 117 119 45
SAP321 id. 129 129 250 250 138 140 178 188 179 186 146 155 187 187 117 119 40
SAP323 id. 129 129 250 254 138 138 184 188 179 186 155 155 187 187 117 117 32
SAP334 id. 129 129 250 250 138 140 178 178 186 186 155 155 187 187 111 117 41
SAP336 id. 129 129 250 250 138 138 178 178 178 186 146 155 187 187 117 119 43
SAP337 id. 129 129 250 250 138 138 178 178 178 186 146 146 187 187 117 119 44
SAP346 id. 129 129 250 250 138 138 184 188 179 186 155 155 187 187 117 117 33
SAP347 id. 129 129 250 250 138 138 188 188 178 186 155 155 187 189 117 119 36
SAP348 id. 129 129 250 250 137 137 188 188 178 186 146 155 187 189 117 119 38
SAP349 id. 129 129 250 250 138 138 188 188 178 186 146 146 187 187 117 117 47
SAP372 id. 129 129 250 250 138 138 184 184 178 186 146 155 189 189 117 119 20
SAP374 id. 129 129 250 250 138 138 184 188 179 179 146 155 187 187 117 119 42
Cochabamba / Quillacollo / VillaUrkipiña / Qui-Urk
QUI755 id. 129 129 250 254 138 138 188 188 186 186 155 155 187 187 117 119 29
QUI757 id. 129 129 250 254 139 139 188 188 186 186 155 155 187 187 119 119 88
QUI762 id. 120 128 250 254 139 139 188 188 186 186 155 155 187 187 119 119 84
QUI763 id. 129 129 250 254 139 139 188 188 186 186 155 155 187 187 117 119 89
QUI766 id. 129 129 250 254 139 139 188 188 186 186 155 155 187 187 117 119 89
QUI768 id. 129 129 250 254 138 138 188 188 186 186 155 155 187 187 117 119 29
QUI769 id. 120 128 250 250 139 139 188 188 186 186 155 155 187 187 117 119 83
QUI774 id. 129 129 250 254 139 139 188 188 186 186 155 155 187 187 117 119 89
QUI775 id. 129 129 250 254 139 139 188 188 186 186 155 155 187 187 117 119 89
QUI907 id. 129 129 250 254 139 139 188 188 186 186 155 155 187 187 117 119 89
QUI913 id. 129 129 250 254 139 139 188 188 186 186 155 155 187 187 119 119 88
QUI916 id. 129 129 250 254 139 139 188 188 186 186 155 155 187 187 117 117 87
Cochabamba / Quillacollo / BSIA14T1 / Qui-Bsia
QUI026 id. 128 128 250 254 138 138 188 188 186 186 155 155 187 187 117 117 75
QUI027 id. 128 128 250 254 138 138 188 188 186 186 155 155 187 187 117 117 75
QUI053 id. 131 131 250 254 136 136 188 188 186 186 146 155 187 187 117 117 80
QUI054 id. 117 125 250 254 130 140 188 188 186 186 155 155 187 187 117 117 81
Countries of reference strains
361-TA Colombia 131 133 252 254 135 138 186 186 174 174 157 157 176 182 119 119 7
458 Colombia 131 131 248 251 138 140 186 186 178 178 153 155 172 176 114 119 2
85/818 Bolivia 123 141 251 251 138 138 174 174 177 181 146 155 174 174 119 119 1
93041401P USA 135 141 255 255 135 135 174 184 188 188 157 157 165 165 114 114 11
93070103P USA 135 141 255 255 135 135 174 174 188 188 157 157 165 165 114 117 12
A269 Guiana 143 145 251 251 140 140 184 184 179 179 155 157 178 184 114 114 4
Cuicacl1 Brazil 128 128 250 254 139 139 188 188 186 186 146 155 187 187 117 119 82
Cutiacl1 Brazil 129 129 254 254 139 139 178 188 173 186 155 155 165 165 117 117 77
FX18 Colombia 127 131 255 255 136 136 178 178 173 173 159 161 166 185 114 114 5
G-38-1 Brazil 129 129 254 254 138 138 182 182 177 177 153 153 172 172 117 117 15
H10 Mexico 135 137 252 255 135 135 176 176 173 173 157 157 165 165 117 119 9
OPS21cl11 Venezuela 135 135 252 255 135 135 184 186 173 186 157 157 165 165 117 119 10
P209cl93 Bolivia 129 129 238 254 138 138 178 178 186 186 155 155 165 165 117 119 16
PB3cl2 Bolivia 127 155 252 254 138 140 186 188 178 178 155 155 170 170 114 117 3
PERU Peru 127 127 252 255 128 128 184 186 182 182 149 157 165 165 114 119 8
SABP3 Peru 128 128 250 254 138 138 188 188 186 186 155 155 187 187 119 119 72
Saimiri4A Venezuela 142 144 251 251 136 136 191 191 178 178 157 157 185 189 111 117 6
SP31 Chile 128 128 254 254 139 139 184 188 173 186 155 155 165 165 119 119 78
T.cruzi#1 Honduras 134 134 252 252 135 135 184 184 0 0 157 157 165 165 119 119 13
V120 Chile 128 128 254 254 139 139 188 188 173 186 155 155 165 169 114 119 79
Z17 Mexico 137 137 255 255 135 135 184 184 175 175 157 157 165 165 119 119 14
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* Department / Municipality / Area / Population

Data analysis

“For a majority of pathogens, including the Trypanosomatidae family, the reproductive strategy was mainly deduced from population genetics analysis” [24]. Here, the analyses were focused on two kinds of events involved in sexual exchanges: allelic segregation and genetic recombination. Allelic segregation was explored through Hardy-Weinberg equilibrium (HWE) or F is, while genetic recombination was explored through linkage disequilibrium analysis (LD, nonrandom association between genotypes at independent loci) and the presence / absence of repeated multilocus genotypes (MLG). A previous study, based on simulations and aiming to estimate the level of clonal reproduction in diploids [25] advised the simultaneous use of F is (mean and variance) and LD estimators.

F is is a measure of inbreeding of individuals within a subsample; it also represents the deviation from random union of gametes and varies from −1 (fixed heterozygous) to +1 (fixed homozygous) via F is = 0 (Hardy-Weinberg equilibrium). This Wright F-statistic [26] was estimated with Weir and Cockerham’s unbiased estimators [27] called f. Negative values of F is (excess heterozygosity) can be caused by accumulation of mutations in an ancient clonal lineage, a phenomenon called the Meselson effect [28], and are generally regarded as a mark of clonality as observed in Bdelloid rotifers [29]. Positive values of F is correspond to inbreeding within the sample, a particular case being the Wahlund effect, when the sample comes from heterogeneous and structured populations. It is worth noting that if the mean F is values are good estimators of HWE, low F is values associated with substantial variance of F is among loci (with some loci displaying an extreme heterozygote deficit and others an extreme excess) can reveal very low levels of sex (cryptic sex) [30]. All statistical tests were based on randomization: data sets fitting the null hypothesis (H0 = panmixia) were generated by randomizing the relevant unit (allele, genotype, etc.). Here, to test HWE within the subsamples, the alleles were permuted among individuals within each subsample and F is was used as a HWE estimator, while for testing the overall HWE, alleles were permuted among subsamples and F it was used as an estimator. Moreover, since the presence of null alleles artificially increases F is estimations, we tested the impact of null alleles on the increased F is values.

Linkage disequilibrium (LD) is another measure of deviation from panmixia. Here it was estimated in three different ways: (i) by the classical index IA [31], which has the disadvantage of increasing with the number of loci, so we also used a slightly modified index (ȓd) which is independent of the number of loci [32]; (ii) by the log-likelihood ratio G-statistics [33]; the P-value of this test is obtained as follows: genotypes at the 2 loci are associated at random a number of times and the statistic is recalculated on the randomized data set; the P-value is estimated as the proportion of statistics from randomized data sets that are larger or equal to the observed and (iii) by comparing the observed number of MLGs and the frequency of the most frequent MLG to the expected ones in simulated panmixia. As for F is, all the LD statistical tests are based on H0 = panmixia (i.e., the genotypes at the two loci are associated at random a number of times depending on the sample size and the statistics are recalculated on the randomized data set).

LD and HWE tests are based on multiple comparisons, so the Bonferroni corrections should be applied; this consists in dividing the p-value (or α, generally 5%), which is the threshold for rejecting H0, by the number of comparisons. For example, testing eight loci within seven different populations leads to 56 comparisons and theoretically α (0.05) would become α′ = α / 56 = 0.00089. Nevertheless, the Bonferroni correction entails a high risk of falsely accepting H0 (bias towards Type II error) and therefore masking real deviations from panmixia. Teriokhin et al. [34] suggested that a high test power can be preserved by using the binomial test instead of the Bonferroni correction in order to check whether the proportion of tests found significant at the 5% level was significantly above 0.05: if this is true, the test is significant and H0 is rejected, and if it is not true, H0 is not rejected ; for example here with 8 loci, to test the genotype association at two loci by using G-statistics there are 26 comparisons and hence 26 values of G-Statistics: if 3 of them are below 0.05 the binomial test (written in R “binom.test (3, 26, p=0.05)”) give a no significant P-value of 0.1386, meaning that 3 values under 0.05 out of 26 are not sufficient to reject Ho; in reality we need 4 values below 0.05 out of 26 to reject significantly H0 (P-value of the binomial test in this case is 0.03874). Because rejecting or accepting the null hypothesis is crucial here, we chose to use and discuss all the p-values (with or without the Bonferroni corrections and the p-values given by the exact binomial tests).

To test F is, LD, and MLG, we examined nine subsamples: the six populations under study (Luribay, Mecapaca, Sap-Sap, Sap-Cosi, Qui-Urk, and Qui-Bsia); the subsample “overall Sapini,” which clusters the two populations from Sapini (Sap-Sap + Sap-Cosi); the subsample “overall Quillacollo,” which clusters the two populations from Quillacollo (Qui-Urk + Qui-Bsia); and the “overall” sample including all stocks (N = 79). The different indices and p-values were associated with their level of significance (NS, not significant; * significant at 5% and ** significant at 1%). As several tests were applied for F is, LD, and repeated MLG, a decision about accepting or rejecting H0 is proposed in each case, namely “reject H0” or “not reject H0” when all tests are congruent, and “ambiguous” when at least one of the tests gave a discordant result.

To process the data, different programs were used: (i) the HierFstat package [35] in R [36] to compute the 95% confidence intervals of F is, (ii) the “binom.test” function in R to test the null hypothesis about the probability of success in Bernoulli’s experiments, (iii) MicroChecker v.2.2.3 [37] to test the load of null alleles, (iv) Multilocus v1.3b [32] for IA and ȓd indices and to test the probabilities of repeated MLG and different MLG, (v) Populations (v.1.2.30© 1999, Olivier Langella, CNRS UPR9034) to build a general clustering analysis between all stocks using the Cavalli-Sforza and Edwards’ chord genetic distances [38], and (vi) Fstat [39] for all other tests.

Results

Genetic diversity of the six populations under study

Genetic diversity was explored within the six local wild T. cruzi TcI populations (79 stocks) and within the 21 reference strains. Details of the origin and allelic microsatellite composition of each stock studied are listed in Table 1.

Null alleles: Only two stocks from the Luribay population did not amplify at locus MCL08 and one reference stock at locus A427. Analyzing the six potentially panmictic populations with MicroChecker, 43 null alleles were expected at loci presenting high F is over 1264 alleles, hence 3.40%, which is already very low. The proportion of observed null alleles in this sample (n = 4, hence 0.32%) is lower than expected (exact binomial test, p = 4e-14). Thus, the role of null alleles in inflated F is may be considered here as negligible.

Overall polymorphism: The main indices of genetic diversity as well as observed and expected heterozygotes and F is by locus and by population are listed in Table 2. It is worth noting that, as expected, the subsample of the reference strains (n = 21) is by far the most polymorphic. Moreover, 42 alleles out of 82 (51.2% of the total number of alleles) were specific to reference strains (see Table 1). Eighty-nine different multilocus genotypes (MLGs) were observed among the 100 stocks (including references) versus only 68 MLGs among the 79 stocks under study (without references). The most repeated MLG (no. 89, repeated five times) was identified in a single population, Qui-Urk, in the Cochabamba valley (Table 1). The number of alleles per locus ranged from 4 to 18 and from 2 to 8 with and without references, respectively. Similarly, the mean allelic richness by locus systematically decreased when reference strains were removed. For the six local populations, the F is values per locus and per population showed high variance, ranging from −1.00 (fixed heterozygosity for locus SCLE10 in Qui-Bsia population) to 1.00 (fixed homozygosity for loci MCLE01 in Sap-Cosi, SCLE11 in Qui-Urk, and C875 in Luribay), while only positive F is values were observed for the reference population (ranging from 0.30 to 0.82) as is expected when pooling differentiated reproductive units within a single subpopulation [25]. The mean allelic richness in local populations was weakly variable, ranging from 1.49 (Qui-Urk) to 2.27 (Sap-Sap) and higher within the reference strains (4.49). The clustering analysis (NJ tree not shown) of all the stocks using the Cavalli-Sforza and Edwards distance method showed that six of the reference strains, namely P209cl93, SABP3, Cutiacl1, SP31, V120, and Cuicacl1, were closely related to some of the wild stocks under study, the other reference strains forming a separate group not supported by a significant bootstrap value. The analysis of genetic distances between each of the 21 reference strains and the 79 wild stocks (mean of pairwise distances) showed that the three reference strains closest to the Bolivian wild stocks were SABP3 from Peru, Cuicacl1 from Brazil, and P209cl93 from Bolivia, with genetic distances of 0.36, 0.41, and 0.50, respectively; the three reference strains farthest from the wild stocks were FX18 from Colombia and 93041401P and 93070103P from the US, with mean genetic distances of 0.89, 0.88, and 0.87, respectively.

Table 2. Main indices of genetic diversity and Hardy-Weinberg equilibrium by locus (vertical) and by population (horizontal) of the 79 Trypanosoma cruzi TcI stocks isolated from six potentially panmictic populations and of the 21 T. cruzi TcI reference strains.

Population MCLE01 SCLE10 SCLE11 MCLF10 A427 MCLG10 C875 MCLE08 Overall
Luribay N/no. all/all. rich. 6/2/1.67 6/3/2.58 6/2/1.67 6/2/1.91 6/6/4.66 6/2/1.67 6/2/1.91 4/1/1.00 2.13*
Ho/He/F is 0.17/0.17/0.00 0.50/0.44/-0.15 0.17/0.17/0.00 0.33/0.30/-0.11 0.50/0.82/0.41 0.17/0.17/0.00 0.00/0.30/1.00 NA 0.23/0.30/0.24
MLG - - - - - - - - 6
Mecapaca N/no. all/all. rich. 11/3/1.97 11/2/2.00 11/3/2.36 11/2/1.92 11/5/2.94 11/1/1.00 11/3/2.92 11/2/2.00 2.14*
Ho/He/F is 0.09/0.25/0.65 0.73/0.52/-0.43 0.09/0.56/0.84 0.45/0.37/-0.25 0.18/0.47/0.63 NA 0.73/0.67/-0.08 0.36/0.52/0.31 0.33/0.42/0.23
MLG - - - - - - - - 10
Qui-Urk N/no. all/all. rich. 12/3/2.13 12/2/2.00 12/2/1.83 12/1/1.00 12/1/1.00 12/1/1.00 12/1/1.00 12/2/1.97 1.49*
Ho/He/F is 0.17/0.30/0.46 0.92/0.52/-0.83 0.00/0.29/1.00 NA NA NA NA 0.67/0.50/-0.33 0.22/0.20/-0.08
MLG - - - - - - - - 6
Qui-BSIA N/no. all/all. rich. 4/4/4.00 4/2/2.00 4/4/4.00 4/1/1.00 4/1/1.00 4/2/2.00 4/1/1.00 4/1/1.00 2.00*
Ho/He/F is 0.25/0.75/0.70 1.00/0.57/-1.00 0.25/0.75/0.70 NA NA 0.25/0.25/0.00 NA NA 0.22/0.29/0.28
MLG - - - - - - - - 3
Sap-Sap N/no. all/all. rich. 27/4/2.89 27/2/1.99 27/3/1.55 27/4/2.29 27/5/3.25 27/2/1.91 27/3/2.27 27/2/1.99 2.27*
Ho/He/F is 0.30/0.63/0.53 0.81/0.50/-0.64 0.07/0.14/0.48 0.74/0.54/-0.37 0.37/0.68/0.46 0.18/0.37/0.51 0.78/0.54/-0.44 0.85/0.50/-0.73 0.51/0.49/-0.05
MLG - - - - - - - - 24
Sap-Cosi N/no. all/all. rich. 19/2/1.38 19/2/1.78 19/3/2.17 19/3/2.72 19/3/2.70 19/2/1.99 19/2/1.84 19/3/2.20 2.10*
Ho/He/F is 0.00/0.10/1.00 0.21/0.27/0.23 0.10/0.36/0.71 0.37/0.57/0.36 0.68/0.61/-0.12 0.31/0.50/0.38 0.16/0.31/0.49 0.84/0.52/-0.64 0.33/0.41/0.18
MLG - - - - - - - - 19
REF N/no. all/all. rich. 21/15/6.07 21/7/4.23 21/6/4.26 21/8/4.98 20/10/5.31 21/7/3.38 21/13/4.60 21/4/3.05 4.49*
Ho/He/F is 0.43/0.91/0.54 0.43/0.80/0.47 0.14/0.80/0.82 0.29/0.85/0.67 0.25/0.87/0.72 0.29/0.68/0.58 0.29/0.74/0.62 0.48/0.67/0.30 0.32/0.79/0.60
MLG - - - - - - - - 21
Overall with reference strains (N = 100) / without reference strains (N = 79)
no. all 18/7 7/3 9/7 8/5 13/8 7/2 15/4 4/3 -
Size range** 117-155 238-255 128-141 174-191 173-188 146-161 165-191 111-119 -
mean all. rich. 3.64/2.75 2.96/2.02 3.19/2.58 3.08/2.37 4.24/3.75 2.54/1.83 3.70/2.67 2.44/2.04 -
F is 0.56/0.57 -0.17/-0.49 0.76/0.72 0.20/-0.07 0.44/0.31 0.48/0.41 0.17/-0.07 -0.24/-0.46 -
Hs 0.46/0.38 0.51/0.45 0.45/0.39 0.39/0.30 0.51/0.44 0.29/0.22 0.38/0.31 0.39/0.34 -
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N, size of the sample; no. all, number of alleles; all. rich., allelic richness; Ho, observed heterozygotes; He, expected heterozygotes; MLG, number of different multilocus genotypes in the subsample; REF, reference stocks; Hs, Nei's gene diversity; *, mean allelic richness; **Size range of alleles calculated with all stocks (including references); NA, not available because the locus is monomorphic.

Panmixia tests within the six populations under study

F is among populations: F is values per population and their 95% confidence intervals are shown in Figure 2. The F is values were also examined by grouping the most adjacent populations, Sap-Sap with Sap-Cosi (1.9 km apart), Qui-Urk with Qui-Bsia (3.3 km apart), and all the populations (overall). F is varied from −0.08 (Qui-Urk population) to 0.29 (overall). Considering the significance using the Bonferroni correction (BC), none of the F is were significant (H0 not rejected, see Table 3) except for the overall sample. As we know that BC may falsely accept H0, we also considered the p-values without BC: here H0 is rejected with α = 1% within the “overall” sample and for only one sample grouping two local populations “overall Sapini” and was not rejected in all the local populations. Consequently, the decisions about panmixia were rejection for the “overall” sample, ambiguous for “overall Sapini,” and no rejection for all local populations (Table 3).

Figure 2. Observed F is of the six Trypanosoma cruzi populations under study and three artificial clusters (all stocks from Sapini, all stocks from Quillacollo, and all TcI Bolivian stocks) and their 95% confidence intervals.

Figure 2

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Table 3. Analysis of F is, disequilibrium linkage (LD) and repeated multilocus genotypes (MLGs) of the 79 Trypanosoma cruzi strains isolated from six potentially panmictic populations.

Populations Overall Luribay Mecapaca Overall Sapini Sap-Sap Sap-Cosi Overall Quillacollo Qui-Urk Qui-Bsia
Sample size 79 6 11 46 27 19 16 12 4
Statistical tests of HWE based on Fis statistics
Real p-value without BC(1) 0.006** 0.0371* 0.0182* 0.0075** 0.2243NS 0.0148* 0.0178* 0.3954NS 0.1096NS
Signification with BC(2) ** NS NS NS NS NS NS NS NS
Decision about H0 reject H0 no reject H0 no reject H0 ambiguous no reject H0 no reject H0 no reject H0 no reject H0 no reject H0
Statistical tests of LD
Ratio signif. / total(3) 16/28** 0/21NS 2/21NS 11/28** 7/28** 1/28NS 1/10NS 0/6NS 0/3NS
IA (4) 0.25** -0.05NS 0.39* 0.31** 0.56** 0.002NS 0.63** -0.08NS 1.31NS
ȓd (5) 0.04** -0.009NS 0.07* 0.05** 0.08** 0.0003NS 0.20** -0.03NS 0.68NS
Decision about H0 reject H0 no reject H0 ambiguous reject H0 reject H0 no reject H0 ambiguous no reject H0 no reject H0
Statistical tests of repeated MLG
No. of different MLGs 68** 6NS 10NS 43* 24* 19NS 9** 6NS 3NS
Maximum frequency of MLG 5** 1NS 2NS 2NS 2NS 1NS 5NS 5NS 2NS
Decision about H0 reject H0 no reject H0 no reject H0 ambiguous ambiguous no reject H0 ambiguous no reject H0 no reject H0
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Results of statistical tests and decisions about H0 (reject or not reject panmixia). For all tests: NS or NS = not significant; * = significant at 5% risk; ** = significant at 1% risk (1) p-value for F is within samples without Bonferroni correction (BC); (2) significance of the test with BC; (3) Ratio: significant loci pairwise comparisons / total comparisons, tested by the binomial test with R program; (4) Value of index of association; (5) Value of ȓd index.

Linkage disequilibrium (LD): three parameters were tested: (i) the proportion of significant LD tests over the total number of comparisons by pairs of loci, using the binomial test, (ii) the association index (IA), a direct measure of LD, and (iii) a special index (ȓd) derived from IA. These indices and their associated significance are given in Table 3. Of the six local populations under study, H0 was not rejected in four of them (Luribay, Sap-Cosi, Qui-Urk and Qui-Bsia); two results were ambiguous (Mecapaca and overall Quillacollo) and three rejected H0 (Overall, Overall Sapini and Sap-Sap).

Repeated multilocus genotypes: We tested two parameters, the number of different MLGs and the maximum frequency of the most repeated MLG. The results showed (Table 3) that H0 is rejected in only one sample (Overall), not rejected in five populations (Luribay, Mecapaca, Sap-Cosi, Qui-Urk, and Qui-Bsia) and ambiguous in three populations (Overall Sapini, Sap-Sap, and Overall Quillacollo).

Considering only the six potentially panmictic populations under study, in four of them (Luribay, Sap-Cosi, Qui-Urk, and Qui-Bsia) the decisions for F is, LD, and MLG were “no rejecting H0” , while in the two others (Mecapaca and Sap-Sap) contradictory results were observed between the different tests of panmixia. Nevertheless, for the only F is tests within the populations from Luribay and Sap-Cosi, there is a potential risk of type II error

Discussion

Likely panmixia in several T. cruzi populations isolated from wild T. infestans

As previously recommended [25], we used three classes of classical population genetics parameters to study the mode of reproduction (i.e., Hardy-Weinberg equilibrium, linkage equilibrium, and presence of repeated MLG) and we showed that in four out of six potentially panmictic T. cruzi populations (Luribay, Sap-Cosi, Qui-Urk, and Qui-Bsia) sampled in restricted areas, true panmixia cannot be excluded. In the case of Luribay and Sap-Cosi, the F IS tests required the Bonferroni correction to lead to the decision “no rejecting Ho”, carrying a high risk of Type II error. However, as Qui-Bsia has a small size (N = 4) and that we cannot rule out a statistical type II error in this case, we must consider only three panmictic populations Luribay, Sap-Cosi, and Qui-Urk. For the two other populations, the tests gave contradictory results in Sap-Sap and ambiguous results for LD tests in Mecapaca, which appears “more panmictic” than Sap-Sap. In this case we could infer a lack of power of the tests to explain these results; nevertheless, and except for Qui-Bsia where the sample size is very small, a high β error value (type II error) is unlikely because for comparable population sizes the tests can reject or not reject H0. Moreover, multiplying the tests decreases the probability of type II error and increases the power of the test. Hence we can consider that no rejection of H0 is equivalent to accepting panmixia, possibly except for Qui-Bsia. Moreover, it is interesting to note that the tests were very sensitive to the Wahlund effect (sampling from heterogeneous populations): when we grouped all six populations (overall), all the tests became highly significant, proving the heterogeneity between populations at the regional level. This was true to a lesser extent for overall Sapini and overall Quillacollo, showing a genetic structure at a very low geographic scale (a few kilometers).

Role of sympatry and sampling design

To test panmixia, the first condition is natural sympatry; indeed, a nonsympatric sample may lead to genetic structuring and generate a Wahlund effect and consequently a false rejection of H0. As nobody knows precisely what sympatry means for this parasite, we picked up the populations within a very small area, not more than 1 ha, in which the triatomes and mammal hosts are assumed to move enough to allow parasite transmission from one host to another and hence generate opportunities for genetic exchanges; we named these populations “potentially panmictic” and tested them. Consequently, in such populations, when H0 is not rejected, and excluding a type II error discussed above, we can consider, a posteriori, that these populations were truly sympatric. Inversely, when H0 is rejected by some tests, as is the case for the Sap-Sap population and to a lesser extent for Mecapaca, a Wahlund effect due to a hidden genetic structure (itself possibly due to a lack of sympatry) could be inferred. Interestingly, when we analyzed the microsatellite data by the software Structure [40], we showed the presence of two distinct genomes in only Sap-Sap and Mecapaca, hence a hidden genetic structure, which can explain the rejection of H0 for some tests within these two populations (data not shown). Meanwhile for these two populations, choosing between the two alternative hypotheses (i.e., lack of sympatry or presence of some extent of clonality) is almost impossible. Sampling in areas that are not actually sympatric may therefore result in falsely rejecting H0. Inversely, as previously stated by others [41], selecting only one individual per subpopulation and pooling each of them into an artificial population generates misleading patterns and false conclusions regarding the mode of reproduction, in particular a significant reduction of LD and modified HW equilibrium, sometimes giving an erroneous picture of the recombining organism despite a high level of clonality. Obviously, our sampling method did not fit this pattern and consequently absence of H0 rejection cannot be attributed to this sampling bias. All these remarks emphasize the importance of sampling design to test the hypothesis under study, for example here, to test panmixia, we need potential sympatric areas, not allopatric areas.

Clonality versus recombination in T. cruzi species

Since the pioneering studies using isoenzymes [6], T. cruzi has been considered by most authors to have a basically clonal population structure, with occasional bouts of genetic exchange or hybridization. These facts were confirmed on many occasions with other genetic markers and a clonal theory of parasitic protozoa was proposed [2,42] with the notable exception of Plasmodium falciparum in which sex occurs [43]; the theory was reaffirmed with both Trypanosoma and Leishmania genera [44] and extended to fungi bacteria and viruses in a recent review [45]. The question of determining whether sex occurs or not in T. cruzi is not trivial, nor needless. Because of a reduced or absent gene flow, clonality must have a major impact on the biological and medical properties of the parasites, which has been explored [46,47]. On the other hand, genetic exchanges can take different forms, the best known being hybridization that has been provoked in vitro [17] and has naturally occurred, playing a crucial role in T. cruzi evolution (generating new DTUs). It is generally admitted that two hybridization events have defined the population structure of T. cruzi [7], the first one very ancient, between TcI and TcII, leading to TcIII and TcIV, and the second one, recent, between TcII and TcIII, leading to TcV and TcVI. The in vitro hybrids showed a fusion of parental genotypes, loss of alleles, homologous recombination, and uniparental inheritance of kinetoplast maxicircle DNA [17], and it is accepted that natural hybridization might occur in a similar but contrasted way [48]. In addition to hybridization, many authors have reported incongruence between phylogenetic trees, which is generally a sign of recombination: for example 13,49, mitochondrial introgression [10,11] and even mitochondrial heteroplasmy (heterogeneous mitochondrial genomes in an individual cell) was demonstrated recently [16] using the promising mtMLST method (mitochondrial multilocus sequence typing), itself derived from the MLST method using nuclear genes [50]. The last way of genetic exchanges might be conventional recombination mechanisms, as in sexual diploids, which can be detected by the usual tools of population genetics (F IS, LD, etc., like here). Because we do not know the cytological mechanisms involved, we named these events “recombination-like” in order to differentiate them from the known genetic exchanges involving meiosis in sexual diploids. One of the first studies regarding this event [51], reported at one isoenzyme locus (phosphoglucomutase), observed homozygous and heterozygous frequencies almost identical to those predicted by the theoretical Hardy-Weinberg distribution in sylvatic TcI. Later, using microsatellites, some recombinations were suggested in a general clonal framework in sylvatic TcI over the endemic area [52], TcI in Ecuador [53], and TcIII [54]: in the latter, the authors could not effectively discriminate a recombination from a high genome-wide frequency of gene conversion. Finally, three recent studies emphasize the role of genetic exchanges and the extraordinary genome plasticity of T. cruzi, (i) using genomic CNV (copy number variation) [15]; (ii) another team [14] reported gross incongruence in Colombian TcI between nuclear and mitochondrial markers, mosaic maxicircle sequences, and the genetic resorting mechanism; (iii) other authors [55] showed that hybrid stocks contain haplotypes that are mosaics probably originating from intragenic recombination. In all these examples, it is worth noting that hybridization or introgression may occur between distant DTUs, whereas “recombination-like” events generally are intra-DTU, as shown in the present study. The “clonality or genetic exchanges” duality for T. cruzi has definitively became obsolete; this species obviously has used both mechanisms to evolve and probably to adapt to its multiple hosts, associated with an extraordinarily plastic genome shaped by clonal evolution and several kinds of genetic exchanges. The mode of reproduction of T. cruzi could oscillate between clonality and sexuality and the true questions are why, when, how, and to what extent T. cruzi recombines? Nevertheless, we agree with Tibayrenc and Ayala’s [45] definition of clonality as “restrained recombination on an evolutionary scale,” which has already been observed in T. cruzi since the same MLGs can be sampled at different times and in distant regions. The same authors stated that “recombination seems easier between closely related genotypes pertaining to the same near-clade in both fungi and parasitic protozoa”; this probably constitutes the most parsimonious explanation for the co-occurrence of recombination at restricted space / time levels and of clonality at larger space / time scales. Interestingly, in bacteria “the probability of acceptance of a recombination event decreases exponentially with genetic distance between the donor and recipient DNA” [56], which is an effect of sexual isolation in bacteria [57]; this could be true for T. cruzi and should be further investigated.

Conclusion, limitations and warning

For the first time we report panmixia, notably through linkage disequilibrium statistics, in T. cruzi TcI populations isolated from wild T. infestans in Bolivia. In absence of additional studies involving other sylvatic vectors, it is not possible to associate panmixia with the sylvatic biotopes; further studies of panmixia should be conducted in other biotopes where parasites should be sympatric. As previously mentioned, “mixed clonal / sexual reproduction is nearly indistinguishable from strict sexual reproduction as long as the proportion of clonal reproduction is not strongly predominant” [30], so, although unlikely, we cannot exclude a certain level of clonality in these populations, even when all tests did not reject the panmixia hypothesis. Moreover, it is worth noting that the parasite strains used here were not cloned and some artifacts due to multiple infections could be a possible explanation for some contradictory results between the different tests. The Leishmania genome is aneuploid [58], every chromosome in every cell may be present in different ploidy states (monosomic, disomic, or trisomic). If this is the case for T. cruzi, as suspected [15], there could be a serious bias with all the codominant nuclear markers, particularly in the studies involving microsatellites: artificially decreasing F is in the trisomic state (excess heterozygosity) and artificially increasing F is in the monosomic state (excess homozygosity). Hence, all the F is results should be interpreted with caution, especially when there is a substantial variance of F is between loci. Moreover, F is is not linearly related to the rate of clonal reproduction [59]. As stated above, the sampling strategy is crucial to confirm or reject these results in other natural contexts, avoiding sampling stocks that have a foreign origin because of passive transport by humans. For this purpose (to specify the mating system at the local scale), we recommend starting with a reduced time and space scale in order to avoid the Wahlund bias as much as possible, which does not hamper the opposite strategy previously proposed [45], “taking a birds-eye view of genetic variability over years and continents, from different hosts and ecosystems” to look at the evolution of the species over space and time.

Acknowledgments

We are particularly grateful to the leaders of the Inlasa (Instituto de Laboratorios de Salud, La Paz Bolivia), Dr. Walter Agreda for having hosted this work in the Department of Entomology directed by Dr. Tamara Chavez.

Funding Statement

This work was funded by the IRD, the National Agency for Research (ANR No 3624, France) and the European Commission Framework Program Project “Comparative epidemiology of genetic lineages of Trypanosoma cruzi” ChagasEpiNet, Contract No. 223034. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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