Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1(−) strains and the ancestry of the Amazonian group

International Journal for Parasitology xxx (2015) xxx–xxx

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Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1() strains and the ancestry of the Amazonian group q Thaís Cristine Marques Sincero a,⇑, Patricia Hermes Stoco b, Mário Steindel b, Gustavo Adolfo Vallejo c, Edmundo Carlos Grisard b,⇑ a

Universidade Federal de Santa Catarina (UFSC), Centro de Ciências da Saúde (CCS), Departamento de Análises Clínicas (ACL), Setor E, Bloco K, Florianópolis, SC 88.040-970, Brazil Universidade Federal de Santa Catarina (UFSC), Centro de Ciências Biológicas (CCB), Departamento de Microbiologia, Imunologia e Parasitologia (MIP), Setor F, Bloco A, Florianópolis, SC 88.040-970, Brazil c Laboratorio de Investigaciones en Parasitología Tropical, Universidad del Tolima, Altos de Santa Helena, A.A. 546, Ibagué, Colombia b

a r t i c l e

i n f o

Article history: Received 3 July 2014 Received in revised form 12 November 2014 Accepted 24 November 2014 Available online xxxx Keywords: Genetic polymorphism Vector–parasite coevolution Parasite ancestry Intra-specific variability Microsatellite and SNP analysis

a b s t r a c t Assessment of the genetic variability and population structure of Trypanosoma rangeli, a non-pathogenic American trypanosome, was carried out through microsatellite and single-nucleotide polymorphism analyses. Two approaches were used for microsatellite typing: data mining in expressed sequence tag /open reading frame expressed sequence tags libraries and PCR-based Isolation of Microsatellite Arrays from genomic libraries. All microsatellites found were evaluated for their abundance, frequency and usefulness as markers. Genotyping of T. rangeli strains and clones was performed for 18 loci amplified by PCR from expressed sequence tag/open reading frame expressed sequence tags libraries. The presence of single-nucleotide polymorphisms in the nuclear, multi-copy, spliced leader gene was assessed in 18 T. rangeli strains, and the results show that T. rangeli has a predominantly clonal population structure, allowing a robust phylogenetic analysis. Microsatellite typing revealed a subdivision of the KP1() genetic group, which may be influenced by geographical location and/or by the co-evolution of parasite and vectors occurring within the same geographical areas. The hypothesis of parasite–vector co-evolution was corroborated by single-nucleotide polymorphism analysis of the spliced leader gene. Taken together, the results suggest three T. rangeli groups: (i) the T. rangeli Amazonian group; (ii) the T. rangeli KP1() group; and (iii) the T. rangeli KP1(+) group. The latter two groups possibly evolved from the Amazonian group to produce KP1(+) and KP1() strains. Ó 2015 The Authors. Published by Elsevier Ltd. on behalf of Australian Society for Parasitology Inc. This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/4.0/).

1. Introduction Trypanosoma rangeli and Trypanosoma cruzi are kinetoplastid protozoan parasites infecting humans and a variety of wild and domestic mammals in South and Central America. Due to the non-pathogenic nature of T. rangeli to its mammalian hosts, this parasite is a unique and interesting biological model for addressing host–parasite interactions, and the genome has been recently unveiled (Snoeijer et al., 2004; Grisard et al., 2010; Stoco et al., 2014). Furthermore, considering the wide and superimposed geographical distribution and sharing of reservoirs, vectors and

q Sequence data reported in this paper are available in GenBank under accession numbers KJ525754–KJ525771. ⇑ Corresponding author at: Universidade Federal de Santa Catarina, Cx. Postal 476, Florianópolis, SC 88.040-970, Brazil. Tel.: +55 (48) 3721 2955. E-mail addresses: [email protected] (T.C.M. Sincero), edmundo.grisard@ufsc. br (E.C. Grisard).

soluble antigens with T. cruzi, the etiological agent of Chagas disease, T. rangeli is of epidemiological and medical importance, often leading to a misdiagnosis of South American trypanosomiasis and resulting in social and economic losses (Stevens et al., 2001; Guhl and Vallejo, 2003; Grisard et al., 2010). Polymorphism among the T. rangeli strains isolated from mammals and triatomines from different geographical regions has been demonstrated by molecular and biochemical methods. Two main genetic lineages based on kinetoplast DNA (kDNA) mini-circle typing have been described: KP1(+) and KP1() (Vallejo et al., 2002, 2003, 2009). Comparative sequence analysis of the ssrDNA, internal transcribed spacer 1 (ITS-1) and spliced leader intergenic regions (SL-IRs) noted increased variability within this taxon and resulted in the proposal of the existence of five lineages (A–E) (Maia da Silva et al., 2004, 2007, 2009). The distinct molecular markers and methods used to assess DNA polymorphisms must consider (i) the expected level of variability, (ii) the rate of mutation, (iii) the mode of inheritance

http://dx.doi.org/10.1016/j.ijpara.2014.11.004 0020-7519/Ó 2015 The Authors. Published by Elsevier Ltd. on behalf of Australian Society for Parasitology Inc. This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/4.0/).

Please cite this article in press as: Sincero, T.C.M., et al. Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1() strains and the ancestry of the Amazonian group. Int. J. Parasitol. (2015), http://dx.doi.org/10.1016/j.ijpara.2014.11.004

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T.C.M. Sincero et al. / International Journal for Parasitology xxx (2015) xxx–xxx

(segregation during cell division), and (iv) the cost, time and need for specialised equipment and practices. Based on the type of information generated by various loci, we may group these methods into three categories as follows: dominant bi-allelic (e.g., random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), bi-allelic co-dominant (e.g., single-nucleotide polymorphism (SNP), restriction fragment length polymorphism (RFLP), and multi-allelic co-dominant (e.g., microsatellites (MSs) (Vignal et al., 2002). Despite the description of several MS loci for T. cruzi (Oliveira et al., 1998, 1999; Macedo et al., 2001; Koffi et al., 2007; Njiru et al., 2007; Lewis et al., 2009; Llewellyn et al., 2009; Venegas et al., 2009; Simo et al., 2010), Trypanosoma brucei (Kanmogne et al., 1997; Jamonneau et al., 2002, 2004; Truc et al., 2002; Koffi et al., 2007; Cabrine-Santos et al., 2010; McInnes et al., 2012), and Trypanosoma evansi (Botero et al., 2010; McInnes et al., 2012), the number of these markers described for trypanosomatids is still small. Similarly, the number of SNP markers in kinetoplastida has revealed a few loci, but only data for T. cruzi are available at dbSNP (http://www.ncbi.nlm.nih.gov/snp/) and TcSNP (http:// snps.tcruzi.org/) (Ackermann et al., 2009). Because the number of both MS and SNP markers is relatively small for T. rangeli (Grisard et al., 1999; Urrea et al., 2011), we searched for and used MS and SNP markers to assess the genetic variability and population structure of T. rangeli strains isolated from distinct geographical regions, hosts and vectors.

2. Materials and methods 2.1. Parasites and DNA extraction All parasites and strains used in this study are shown in Table 1. Except for T. rangeli strains C23, TRE and 5048, which were kindly provided by Dr. Concepción Puerta from Pontifícia Universidad Javeriana, Colombia, all other parasite strains were obtained from our laboratory cryobank (Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina – UFSC, Brazil). Trypanosoma rangeli and T. cruzi strains were previously

subjected to cyclic mouse-triatomine-mouse passaging and were re-isolated by hemoculture of infected mice in liver infusion tryptose (LIT) medium supplemented with 10% FCS at 27 °C. Parasite DNA was obtained by standard phenol–chloroform extraction (Sambrook and Russel, 2001). All primers used in this study are described in Supplementary Table S1. All procedures involving animals were previously approved by the UFSC Ethics Committee on Animal Use – CEUA (Reference number: 23080.025618/2009-81) and were carried out according to the guidelines of the Brazilian National Authority (Colégio Brasileiro de Experimentação Animal – COBEA). 2.2. Identification and characterisation of MSs 2.2.1. MS identification from cDNA libraries The transcriptomic library used in this study (2.45 Mb) was formerly generated using cDNA from epimastigote and trypomastigote forms from both T. rangeli Choachí and SC-58 strains, resulting in 2,230 and 2,127 sequences, respectively (Grisard et al., 2010). The search for tandem repeats and the analysis of the satellite repeat contents was carried out using Tandem Repeats Finder (TRF) (Benson, 1999) and the Tandem Repeats Analysis Program (TRAP) (Sobreira et al., 2006), respectively. 2.2.2. MS identification from genomic libraries Genomic libraries were constructed for this study according to PIMA methodology (PCR-based isolation of microsatellite arrays) (Lunt et al., 1999). Briefly, RAPD profiles were obtained using 10 ng of DNA from each strain and the Ready-To-Go RAPD Analysis Beads™ (GE Healthcare, UK), according to the manufacturer´s instructions. Amplification was performed in a Mastercycler Gradient™ thermocycler (Eppendorf, Germany) under the following conditions: initial denaturation at 95 °C for 5 min, followed by 45 cycles of denaturation at 95 °C for 1 min, primer annealing at 36 °C for 1 min, and extension at 72 °C for 2 min. All PCR products were cloned into the pGEM T easy™ vector (Promega, USA), resulting in approximately 40–50 positive clones/strain. The detection of MS repeats in each obtained clone was carried out by multiplex

Table 1 List of species, strains and clones of Trypanosoma rangeli and Trypanosoma cruzi used in this study including original host, geographical origin and classification based on the absence () or presence (+) of KP1 mini-circles. Species

Strain

Original host

Geographical origin

KP1 typing

T. rangeli

SC-58 SC-58 clone 1 SC-58 clone 11 SC-61 SC-68 SC-74 SC-75 SC-76 PIT-10 TRE C23 5048 Choachí D3493 B450 H8GS R1625 Macias San Agustín H9 H14 1545 Palma-2 Y

Echimys dasythrix – – E. dasythrix Panstrongylus megistus P. megistus P. megistus P. megistus P. megistus ND Aotus sp. Homo sapiens Rhodnius prolixus R. prolixus Rhodnius brethesi Homo sapiens H. sapiens H. sapiens H. sapiens H. sapiens H. sapiens R. prolixus R. prolixus H. sapiens

Brazil – – Brazil Brazil Brazil Brazil Brazil Brazil Colombia Colombia Colombia Colombia Colombia Brazil Honduras El Salvador Venezuela Colombia Honduras Honduras Colombia Venezuela Brazil

            + + + + + + + + + + + NA

T. cruzi

NA, not applicable; ND, not determined.

Please cite this article in press as: Sincero, T.C.M., et al. Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1() strains and the ancestry of the Amazonian group. Int. J. Parasitol. (2015), http://dx.doi.org/10.1016/j.ijpara.2014.11.004

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PCR using primers specific to the cloning vector (EXCEL-R and PGEM-F, Supplementary Table S1) and an additional primer directed to CA motif repeats, as described for T. cruzi (Oliveira et al., 1998). The 10 lL reactions comprised 1 U of Taq DNA polymerase (LGC Biotechnology, Brazil), 0.2 mM of each dNTP (GE Healthcare), 10 pmol of each primer in a buffer containing 10 mM Tris–HCl (pH 8.5), 50 mM KCl and 1.5 mM MgCl2. The amplification was performed in a Mastercycler Gradient™ Thermocycler with an initial denaturation at 94 °C for 3 min, followed by 35 cycles at 94 °C for 45 s, primer annealing at 55 °C for 30 s, and extension at 72 °C for 1 min followed by final extension at 72 °C for 10 min. DNA sequencing of both strands from all positive clones was carried out using the DYEnamic™ ET Dye Terminator kit (GE Healthcare) on a MegaBACE 1000™ DNA Analysis System (GE Healthcare). Briefly, each sequencing reaction used 5 pmol of each oligonucleotide, pGEM-F or EXCEL-R, and 800 ng of plasmid DNA under the following thermal conditions: 95 °C for 25 s, 35 cycles of 95 °C for 15 s, 50 °C for 20 s, and 60 °C for 90 s. After the labelling reaction, the products were precipitated in 70% isopropanol, injected at 2 kV for 100 s, and electrophoresed for 140 min at 8 kV. The resulting contigs were then analysed using the TRAP and TRF software, as described in Section 2.4.2.

2.2.3. Selection and genotyping of MS loci and phylogenetic inferences Following size (P24 bp) and quality assessment (Phred >20) and the TRF and TRAP analyses, high-quality sequences were selected according to the criteria described by Subirana and Messeguer (2008), whereby a given sequence of 24 bp has a very low chance of occurring randomly (105) and is unlikely to generate a coding sequence (Subirana and Messeguer, 2008). Primers for each selected MS locus were designed based on the obtained sequences, and the sense oligonucleotide of each primer pair was 50 -labelled with fluorescein (FAM) (Supplementary Table S1). These defined MS loci were then used in genotyping assays of all T. rangeli strains and the control T. cruzi strain (Table 1). PCR was performed using the GoTaq™ Green Master Mix (Promega) in a final volume of 12.5 lL containing GoTaq™ DNA polymerase, 1 lM of each primer, 50 ng of template DNA in a buffer containing 200 lM dNTPs and 1.5 mM MgCl2 (pH 8.5). Amplification was performed in a Mastercycler Gradient™ Thermocycler with an initial denaturation at 94 °C for 3 min, followed by 35 cycles at 94 °C for 45 s, primer annealing at 55 °C for 30 s, extension at 72 °C for 1 min, and a final extension at 72 °C for 10 min. The amplicons were precipitated in 70% isopropanol and eluted in 10 lL of ultrapure water. The genotyping reaction was set up using 7.75 lL of 0.1% Tween, 0.25 lL of ET-ROX™ 400 or 900 (GE Healthcare), and 2 lL of diluted PCR product (1:5–1:15 in water), as instructed by the manufacturer. The samples were gently homogenised, denatured at 95 °C for 1 min, and kept on ice until genotyping using a MegaBace 1000™ DNA Analysis System (GE Healthcare). The samples were injected for 80 s at 3 kV and electrophoresed for 80 min at 10 kV. Determination of the allele size and quality, as well as the genotypes of the strains for each marker, was performed by analysis of the obtained electropherograms using the Fragment Profiler software (GE Healthcare). Phylogenetic inferences from the obtained MS data were based on the Stepwise Mutation Model (SMM) (Kimura and Ohta, 1978). The MS multilocus genotypes were analysed using the Factor, Mix and Seqboot software of the Phylip package (v. 3.69) (Felsenstein, 2005). Briefly, binary characters (0/1) generated by Factor were loaded into Mix and analysed by the Wagner Parsimony Method, allowing a Seqboot bootstrap (1,000 bootstraps) estimation of the evolutionary relationships among the strains expressed as a Wagner network tree.

3

2.3. Population analysis A number of metrics were used to test for population genetic structure such as MS allelic frequencies, Nei’s unbiased measures of genetic distance, Wright’s fixation index (FST) and heterozygosity were calculated with GENEPOP (V. 3.4) (http://genepop.curtin. edu.au). An Analysis of Molecular Variance (AMOVA) and the probability of occurrence of subpopulations or genetic subdivisions were carried out using ARLEQUIN (v. 3.1) (Excoffier et al., 2005) using the original haplotype definition with the following settings: Deletion Weight = 1, Transition Weight = 1, Transversion Weight = 1, Epsilon Value = 1e-07, Significant digits for output = 5 and Allowed Level of Missing Data = 0.05. 2.4. SNP analysis of the SL gene 2.4.1. PCR, cloning and sequencing Amplification of the SL gene for all strains was performed using primers ME-L (50 -TTC GAA CCC ATA ACT TGT TTG GT-30 ) and ME-R (50 -AGC CAT TGT TTC AAA GTA CTC AAT CAG AAA CTG-30 ), as described by Fernandes et al. (1997), generating an amplicon of approximately 900 bp. The reaction was performed using the Qiagen HotStar HiFidelity™ system, with HiFi buffer (Tris–HCl, pH 8.7), 300 lM dNTP ultrapure, BSA, Triton X-100™, and 1.5 mM MgSO4), 1 lM of each primer, 50 ng of DNA and 1 U of HotStar HiFidelity DNA polymerase (Qiagen, USA) in a total volume of 25 lL. The amplification was performed in a Mastercycler Gradient Thermocycler™ (Eppendorf) under the following thermal conditions: denaturation at 95 °C for 5 min, followed by five cycles at 95 °C for 20 s, primer annealing at 60 °C for 30 s, and extension at 72 °C for 30 s, 30 cycles of 95 °C for 20 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s, and a final extension step of 72 °C for 5 min. The expected bands were purified using GFX PCR DNA and a Gel Band Purification Kit™ (GE Healthcare), cloned into the pGEM™ T Easy vector (Promega), and transformed by electroporation in Escherichia coli DH5a cells. After transformation, recombinant clones were obtained by selective growth on Luria–Bertani (LB) medium supplemented with 100 g/mL of ampicillin and checked for the presence of the inserts with PCR using primers pGEM-F (50 -ACG CCA AGC TAT TTA GGT GAC ACT ATA-30 ) and EXCEL-R (50 -GTT GTA AAA CGA CGG CCA GTG AAT-30 ). For sequencing, five positive clones of each strain were grown in LB medium supplemented with 100 lg/mL of ampicillin for 20 h at 37 °C with shaking. Plasmid DNA was recovered by alkaline lysis according to standard protocols (Sambrook and Russel, 2001). Both DNA strands were sequenced for all clones as described in Section 2.2.2. 2.4.2. SL gene sequence analysis After quality analysis using the Phred/Phrap/Consed package (http://www.phrap.org) (Ewing and Green, 1998; Ewing et al., 1998), high quality sequences (Phred P30) were checked for their identity using a BLAST search (www.ncbi.nlm.nih.gov/BLAST) and then aligned using ClustalW (Thompson et al., 1994). Phylogenetic reconstructions using the SL gene sequences were obtained for all T. rangeli strains using the bootstrapped Maximum Parsimony (1,000 replicates) and Kimura 2 parameter (K2P) models in MEGA software (v. 5) (Tamura et al., 2011). 2.4.3. Network analysis A reconstruction of the phylogenetic relationship among T. rangeli strains was carried out as formerly described by Herrera et al. (2013) for T. cruzi strains. For that, the intergenic region of 63 gene

Please cite this article in press as: Sincero, T.C.M., et al. Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1() strains and the ancestry of the Amazonian group. Int. J. Parasitol. (2015), http://dx.doi.org/10.1016/j.ijpara.2014.11.004

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sequences from the T. rangeli SL-IR, corresponding to 18 new sequences obtained in this study and 45 non-redundant sequences retrieved from GenBank, were comparatively analysed (Supplementary Table S2, Supplementary Fig. S1). The detailed characteristics of these strains, including their genetic lineages (KP1+/KP1 or A–E groups), are presented in Supplementary Table S3 (Vallejo et al., 2002; Maia Da Silva et al., 2007, 2009; Urrea et al., 2011). Sequences ranging from 230 to 311 bp were aligned and edited manually using BioEdit (v. 7.0.90) (http://www.mbio.ncsu.edu/bioedit/bioedit.html) and MEGA (v. 5) (Tamura et al., 2011); the 5.8S rRNA gene was removed, generating two distinct regions of SL-IR that were separately analysed as proposed by Herrera et al. (2013). An analysis of the first region, named the SNP region, was performed by deleting the beginning of the sequence alignment, the entire MS region, and one site where two sequences presented a position annotated ‘‘S’’ (C/G). After trimming, alignment of the 173 bp-long SNP-enriched fraction revealed 24 polymorphic sites, of which 14 was parsimony informative. The analysis of the second region, named the MS region, was carried out by selecting the sites corresponding to the MS region (CA)n (TA)n (TG)n (TATG)n (TA)n in the alignment. Because the T. rangeli SL gene is far more conserved than that in T. cruzi, gaps were retained to allow analysis using the Single Mutation Model. Haplotype reconstruction was performed using the algorithm PHASE (Stephens et al., 2001, 2003) of DnaSP (v. 5) (Librado and Rozas, 2009) using default parameters. The phylogenetic relationship was built using the median-joining (MJ) network method in Network version 4.5.1.6 (Bandelt et al., 1999) (http://www.fluxus-engineering.com). As recommended by Herrera et al. (2013), the network approach is preferable to conventional phylogenetic methods for intraspecific phylogeny. The network was obtained after haplotype reconstruction using DnaSP. After star contraction (pre-processing), with default parameters and epsilon 10, postprocessing was used to remove unnecessary median vectors and links (cleaning procedure). Network diagrams of haplotypes were manually arranged considering geographical and host origin, cycle and subgroup classification (Supplementary Table S4).

3. Results 3.1. Search for MS repeats in T. rangeli genomic and cDNA libraries The search for MS repeats on T. rangeli genomic and transcriptomic libraries by TRF revealed seven and 2,138 potential MS markers, respectively, which after analysis by TRAP resulted in two genome and 36 transcriptome-derived sequences. Among these, a single genomic sequence (Tr_Di-05) and 18 cDNA sequences (Table 2) were in accordance with formerly established criteria (Subirana and Messeguer, 2008) and submitted to experimental validation. PCR amplification of these markers was achieved for 16 out of the 18 pre-selected repeats (88.9%), including MCLE-03 previously described for T. cruzi (Oliveira et al., 1998). A total of 2,127 contigs clustered from 2.45 Mb of sequence from the T. rangeli transcriptome (Grisard et al., 2010) were used for MS mining. The TRF analysis revealed 2,132 simple-sequence repeats (SSRs) distributed in 418 non-redundant classes at a frequency of one repeat every 1.24 Kb. The ratio of various classes of MSs (dimers to hexamers) is not equally distributed throughout the sequences. Hexameric repeats were the most abundant class of MSs, with an average of 37.2% of all loci, followed by trimers (18.5%), pentamers (11.1%), dimers (10.4%), and tetramers (7.7%). The TRAP analysis revealed that a majority of the 2,132 contigs revealed by TRF were not suitable for MS typing due to either (i) reduced size of the regions flanking the repeat motifs did not allow the design of PCR primers or (ii) the MS size was less than 24 bp in length, which could have an increased chance of occurring randomly and thus did not represent a robust locus. The selected markers found in both the SC-58 and Choachí strains are shown in Table 2 and reveal simple and composed repeats, perfect or imperfect, formed by two to six nucleotides. The efficiency of the transcriptome mining approach is indicated by the successful amplification of 18 of the 23 loci tested. All the T. rangeli MS loci described in the present study were revealed to be specific because attempts to amplify these loci from T. cruzi (Y strain), Leishmania infantum and Leishmania braziliensis were unsuccessful (data not shown). Furthermore, the stability of

Table 2 Characteristics of microsatellite markers identified and selected from Trypanosoma rangeli genomic and/or transcriptomic sequences from Choachí and SC-58 strains. Marker

Motif

Size range alleles (bp)

No. of alleles

Ho

He

Strain

Sequence Origina

Reference

TR_Di-01 TR_Di-03 TR_Di-04 TR_Di-05 TR_Di-06 TR_Di-07 TR_Di-09 TR_Tri-01 TR_Tri-01b TR_Tetra-02b TR_Hexa-01 TR_Hexa-01b TR_Hexa-02 TR_Hexa-03 TR_Hexa-04 TR_Hexa-05 TR_Hexa-06

(CA)21 (CT)10(GT)10 (AC)14AG(AC)6 (AC)13 (AC)17 (GT)15 (CT)13 (GCC)10 (GCC)10 (TTTG)8 (TGTGCG)4 (TGTGCG)4 (CTCCTT)4 (TGTGCG)4 (ATCCGC)4 (CCTTTT)4 (ATAAAT)4

174–247 313–321 195–241 366–374 165–183 266–288 109–129 221–242 316–364 108–230 379–396 334–347 229–260 307–388 358–376 359–366 205–235

11 4 9 3 3 7 7 3 4 5 3 3 3 7 4 2 3

0.5556 0.0000 0.8500 0.0000 0.0000 0.8500 0.6842 0.0000 0.0000 0.4118 0.0000 0.0000 0.0500 0.1500 0.6000 0.0667 0.2308

0.8222 0.7100 0.8282 0.6694 0.6205 0.8462 0.7838 0.2495 0.3256 0.7522 0.5947 0.6032 0.5141 0.7179 0.6564 0.0667 0.4400

Choachí Choachí Choachí Choachí Choachí Choachí SC-58 SC-58 SC-58 Choachí SC-58 SC-58 Choachí SC-58 Choachí Choachí Choachí

t t t g/t t t t t t t t t t t t t t

CHEG204007B06.b CHEG202001E11.b CHEG203001A03.b CHEG205001C03.b CHEG205003A01.b CHEG205005A10.b SCEG216003B10.b SCEG216009G07.b SCEG216009G07.b CHEG004010A02.b SCEG212007E09.b SCEG212007E09.b CHEG201009E03.b SCEG212007E09.b CHEG204015E05.b CHEG203003A12.b CHEG204001A07.b

MCLE-03

(CT)4(GT)2CTAT(GT)15

408–418

5

0.2000

0.5244

CL Brenerb

g

Oliveira et al. (1998)

Ho, observed heterozygosity; He, expected heterozygosity. a Sequence origin as genome (g) and/or transcriptome (t). b Trypanosoma cruzi strain.

Please cite this article in press as: Sincero, T.C.M., et al. Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1() strains and the ancestry of the Amazonian group. Int. J. Parasitol. (2015), http://dx.doi.org/10.1016/j.ijpara.2014.11.004

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these loci as MS markers was assessed by the PCR amplification of each MS repeat after 70 passages of the studied strains in axenic culture, revealing no size or sequence changes (data not shown). 3.2. Genotyping of T. rangeli strains The 18 polymorphic MS markers were successfully amplified from 22 of the 23 T. rangeli strains (except strain 5048) (Supplementary Table S5). It is noteworthy to mention that the amplification of a single allele for all markers in both SC-58 strain clones (1 and 11) could be the result of monosomic chromosomes. Trypanosoma rangeli is considered a diploid parasite as is also assumed for other trypanosomatids such as T. cruzi, T. brucei, Leishmania major, Leishmania amazonensis and L. braziliensis (Stoco et al., 2014). Although the T. rangeli population structure was analysed while assuming such a premise, we cannot rule out the possibility of aneuploidy since this phenomenon has been described in these phylogenetically related parasites, especially for the genus Leishmania (Gaunt et al., 2003; Minning et al., 2011; Rogers et al., 2011; Mannaert et al., 2012). Complete data of the MS genotyping are shown in Supplementary Table S5. The number of alleles per studied locus is shown in Table 3. All loci showed a variable number of alleles, ranging from two to 11. Table 2 also shows the observed (Ho) and expected (He) heterozygosity obtained for each locus, confirming the expected deficiency in heterozygosity for organisms lacking sexual reproduction, such as T. rangeli. An analysis of the unrooted Wagner network based on the MS genotyping of 18 T. rangeli polymorphic loci (Fig. 1) using the SMM (Kimura and Ohta, 1978) supports the clustering of three populations: (i) KP1(+) strains, (ii) Colombian KP1() strains, and (iii) Brazilian KP1() strains. 3.3. Population structure of T. rangeli The level of population subdivision was estimated using FST (Wright’s fixation index) between population pairs. The likelihood of this subdivision was evaluated using STRUCTURE software with 100,000 interactions of the Markov chain algorithm and consider-

ing a model of mixed ancestry (admixture model) and correlated allelic frequencies. Assessment of the population structure of all T. rangeli strains (Table 1) revealed an FST value of 0.30380 (P = 0.00293), indicating a moderate subdivision of this taxon (Porter, 1990). A separate analysis of the genetic diversity of the KP1() and KP1(+) strains revealed FST values of 0.4718 (± 0.2652) and 0.2572 (± 0.1981), respectively, indicating an effective isolation for KP1() strains and a moderate subdivision for KP1(+) strains (Porter, 1990; Hey and Pinho, 2012). As expected for asexual and clonal organisms, the Ho values were lower than the He (Table 2). 3.4. SNP analysis of the T. rangeli SL gene Cloning and high quality sequencing (Phred quality P90) of the SL gene was achieved for 18 of the 23 T. rangeli strains (except for SC-74, SC-61, SC-68 and both SC-58 strain clones). A discrete size polymorphism was observed among the strains, as formerly reported (Grisard et al., 1999), varying from 904 bp for strain 5048 to 1,022 bp for the PIT10 strain. All obtained sequences are available in GenBank under accession numbers KJ525754–KJ525771. All parsimonious sites are shown in Supplementary Table S6. A phylogram resulting from the Maximum Parsimony analysis of the SL gene from the 18 T. rangeli strains is shown in Fig. 2. Using almost the same strains, the clustering obtained by this method corroborates the genotyping results shown in Fig. 1 and reinforces the classical KP1(+)/KP1() mini-circle classification (Vallejo et al., 1994, 2002, 2003, 2009). A further assessment of these differences was carried out by analysing the MS region of the SL-IR (Supplementary Fig. S1) of the 18 T. rangeli strains cited above, aggregating 23 non-redundant sequences described by Urrea et al. (2011) and 22 sequences described by Maia da Silva et al. (2007, 2009) which were retrieved from GenBank. The haplotype analysis of all 63 non-redundant sequences is shown in Fig. 3. Despite the lack of resolution for some branches, especially among KP1(+) strains, the tree topology corroborates the results shown in Figs. 1 and 2, emphasising with high bootstrap support the existence of a third group formed exclusively by T. rangeli strains isolated from the Brazilian Amazon region.

Table 3 Distribution of Trypanosoma rangeli strains according to genotypes identified by microsatellite (MS) region analysis of the spliced leader intergenic region (SL-IR), their KP1(+/) lineage classification and the frequency of repeats per genotype.

a

T. rangeli strains

MS Genotypes

No. of sequences attributed

Repeats frequency

KP1(+)

KP1()

CA

TA

TG

TATG

TA

Legeri, 4176 AM80, AAA, AAB, Saimiri, Preguici Choachí, B450, D3493, H8GS, H14, H9, Macias, Palma2, San_Agustin, R1625, 1545, SC75, SC58, P19, Duran, 444, 3123, Rp500, Rp528, D99, VE00, Lobita, AEI, ROma01, P21, VE9, VE3, ROR20, ROR62, ROR85 Tra643 R.col, P53, 44, 43, 201 2715 55 LDG RGB SC76, PIT10 G5 401, 1141 TRE PG 5048 C23 GAL 47, SO 29, SO 48 Peru1, Peru1A, Peru2

G1 G2 G3

2 6 29

0 0 0

1 2 3

0 0 0

0 0 1

0 0 0

0 0 2

G4 G5 G6 G7 G8 G9 G10 G11 G12 G13 G14 G15 G16 G17 G18

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 5 1 1 1 1 2 1 2 1 1 1 1 3 3

6 6 6 6 7 7 7 8 9 9 9 10 10 11 12

6 9 9 10 4 8 14a 5 4 5 13 4 4 7 9

1 9 9 9 1 1 1 1 1 1 1 1 1 1 2

1 3 3 3 5 3 8a 4 3 4 6 3 5 1 2

2 0 0 0 2 2 1a 2 2 2 2 2 2 2 2

Imperfect repeats.

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4. Discussion The search for SSRs in T. rangeli expressed sequence tag (EST)/ open reading frame expressed sequence tags (ORESTES) libraries proved to be an efficient method for selecting MS markers, also allowing the assessment of repetitive content within the coding regions of the T. rangeli genome. Although less polymorphic than the MSs found within non-coding regions (Li et al., 2004), the repeats found in coding regions are abundant, easily detectable by computational screening, with no bias concerning the types of repetition (except A/T monomers), and allow the direct mapping of genes representing the transcribed part of the genome. The assessment of the MS polymorphism in T. rangeli, as defined by the number of alleles per locus, revealed that 18 out of the 20 loci tested (Table 3) showed polymorphism that is comparable with other MS genotyping of phylogenetically related organisms such as T. cruzi and Leishmania spp. (Oliveira et al., 1999; Fakhar et al., 2008), and a consequent reduction in Ho of the studied strains. Our studies of T. rangeli population structure were based on MS genotyping. In general, the Ho values were lower than the He values (Table 2), a result that is consistent with other MS-based studies of L. infantum (Ferreira et al., 2012) and T. cruzi populations (Oliveira et al., 1998, 1999). Assessment of a given population structure, which varies according to the species studied, may be influenced by the numbers and types of markers used. For T. rangeli, as few as three hypervariable MS loci (TR_Di-04, TR_Di-07, TR_Di-09) were sufficient to distinguish the populations according to the KP1(+) and KP1() genetic groups. FST is calculated as the variance that distinguishes a population over the total variation present. Porter (1990) suggested the following: FST < 0.2 indicates a negligible population subdivision; 0.2 < FST < 0.3 indicates a moderate subdivision; FST values >0.3 are indicative of effective isolation. More recently, Hey and Pinho (2012) suggested an FST value >0.35 to identify a distinct or isolated population. With regard to the question of whether FST tends to reflect mostly gene flow or the time since population separation, the studies compiled by Hey and Pinho (2012) suggest a fairly even balance between the two. Considering all T. rangeli strains in a single analysis, a moderate subdivision is shown (FST = 0.30380 ± 0.00203, P = 0.00293), in accordance with the KP1() and KP1(+) lineages. However, considering strains from each group in a separate analysis, the KP1() strains show a genetic diversity almost two times higher (0.4718 ± 0.2652) than the KP1(+) strains (0.2572 ± 0.1981), indicating a further subdivision of the KP1() strains (FST > 0.35). These data are consistent with those observed in the phylogenetic trees (Figs. 1 and 2) and are in accordance with the geographical distribution of the strains, whereby the KP1() strains are grouped into two branches: the strains isolated in Colombia and the strains isolated in Brazil. The KP1(+) population appears to have some degree of subdivision but at a more subtle level (0.2 < FST > 0.3). These results reinforce the classification of T. rangeli strains into distinct genetic groups according to the presence/absence of the KP1 kDNA mini-circle as well as the vector–parasite co-evolution theory that proposes the isolation of vectors in nature, thus preventing gene flow between the KP1(+) and KP1() strains (Steindel et al., 1994; Vallejo et al., 2007; Urrea et al., 2011). The phylogenetic analyses (Fig. 1) suggest that the population structure of T. rangeli can be partly explained by classification based on the presence or absence of the KP1 mini-circle. However, two highly significant branches were observed among the KP1() strains, one comprising strains from southern Brazil (PIT10, SC58, SC-61, SC-68, SC-74, SC-75, and SC-76) and another with strains from Colombia (C23, 5048, and TRE), corroborating the results of a

possible population subdivision among KP1() strains as evidenced by FST discussed above. Analyses of SNPs are accurate but require high quality sequencing from well-characterised biological material. For this study, we initially subjected all T. rangeli strains to a cyclical mouse-triatomine-mouse passage to assure the biological characteristics of T. rangeli (anterior transmission). After amplification of the SL gene using a high fidelity proof-reading Taq DNA polymerase, all high quality reads (Phred P30) were considered for clustering, which resulted in a majority of sequences with Phred quality P90 (1 error/109 bases). MEGA 4.0 analysis revealed a total of 77 parsimony informative sites based on the alignment of the 18 sequences of the T. rangeli SL gene by ClustalW (Supplementary Table S6). A phylogram based on the SNPs found within the SL gene allowed interspecific clustering, clearly separating T. rangeli from T. cruzi and T. vivax (Fig. 2). Even with no resolution for intraspecific clustering, the T. rangeli KP1() strains isolated in Brazil remained clustered closer to the Colombian strains and outside the main KP1(+) clade of strains, as was also observed in former studies using the same strains but distinct markers such as the Histone H2A intergenic region (Puerta et al., 2009) and PTP2 gene (phosphotyrosine phosphatase) (Prestes et al., 2012). In contrast to the SNP analysis of the SL-IR gene, the analysis of MS repeats allowed a clear assembly of T. rangeli strains according to the KP1(+) and KP1() genetic groups, with high bootstrap support (Fig. 1), as previously reported by other groups (Cuervo et al., 2006; Suarez et al., 2007). These results indicate a recent divergence between the strains due to the high mutation rate of MS markers (Wilson and Balding, 1998), in contrast to SNPs. The separate clustering of the Brazilian and Colombian KP1() strains also reinforces the vector–parasite co-evolution theory and indicates that the T. rangeli population structure should be more complex than the classification according to the type of kDNA mini-circle, as proposed by Maia da Silva et al. (2007, 2009). These authors suggest the existence of at least five genetic groups for T. rangeli (A–E). Group A is composed of isolates from Colombia, Venezuela, Honduras and Brazil (Rondônia and Marajó Island), group B of Brazilian isolates from Acre, Amazonas and Pará States, and group C of strains isolated in Panama, El Salvador and Colombia. Group D is composed exclusively of strain SC-58 isolated from southern Brazil and group E of isolates from bats (Platyrrhinus lineatus) from central Brazil. Using RAPD and sequencing analyses of the SL-IR from 25 T. rangeli strains, Urrea et al. (2011) recently reported results that support a strict association of T. rangeli genotypes and Rhodnius spp., suggesting a possible co-evolutionary association between parasites and their vectors. The authors suggested associations between T. rangeli KP1(+) strains and Rhodnius prolixus, Rhodnius robustus and Rhodnius neglectus, and between T. rangeli KP1() strains and Rhodnius pallescens, Rhodnius colombiensis and Rhodnius ecuadoriensis. Considering this vector–parasite clustering and aiming to assess the evolutionary history of T. rangeli, we performed a comparative analysis including the 18 sequences of the SL-IR generated in the present study and formerly described sequences (Maia Da Silva et al., 2007, 2009; Urrea et al., 2011) (Fig. 3). It is worth mentioning that despite the lack of resolution for some branches, the clustering of the strains was maintained and corroborated the analysis using complete sequences (Fig. 2), showing the robustness of this approach and reinforcing the KP1(+/) classification, which appears to be more general than proposed by Maia da Silva et al. (2007, 2009). This analysis also revealed a distinct and interesting group composed of T. rangeli strains isolated in the Brazilian Amazon region (related to Rhodnius brethesi), which clustered separately from all

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Fig. 1. Unrooted Wagner network of Trypanosoma rangeli strains based on the genotyping of 18 polymorphic loci. Each microsatellite allele was considered one state from a multistate character; the genetic distance between any two strains was estimated as the number of mutational steps necessary to transform one into the other. Numbers on the nodes represent the bootstrap values based on 1,000 replications. Bootstrap values not shown were all below 600 and are not given individually. Bar indicates KP1 (+/) classification.

Fig. 2. Phylogram resulting from maximum parsimony analysis (1,000 replicates) (Kimura 2 parameter model using MEGA software) of the spliced leader gene from Trypanosoma rangeli strains. The tree was rooted using Trypanosoma cruzi (Tc CL, U57984.1) and Trypanosoma vivax (Tv Desowitz, AJ250749.1) sequences. Bootstrap values are shown in each tree node.

other KP1(+) and KP1() strains, with a high bootstrap value (Fig. 3). Because the Amazon region is considered the origin of Rhodnius spp. (Hiraki et al., 1978) and the fact that T. rangeli evolved together with its invertebrate hosts (Kimura and Ohta, 1978; Urrea et al., 2011), it would be reasonable to speculate that this group represents the ancestral genotype of T. rangeli strains. This hypothesis

was further addressed through a network analysis for intraspecific variability using two regions of SL-IR (SNP and MS regions), as described in Section 2.4.3 (Table 3, Fig. 4, Supplementary Table S4). The analysis of the MS region of SL-IR (Table 3, Supplementary Table S4) shows a progressive increase in repeat number, especially for the CA motif, starting with one and two for the

Please cite this article in press as: Sincero, T.C.M., et al. Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1() strains and the ancestry of the Amazonian group. Int. J. Parasitol. (2015), http://dx.doi.org/10.1016/j.ijpara.2014.11.004

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Fig. 3. Phylogram obtained with spliced leader intergenic region sequences from Trypanosoma rangeli strains described in this study (denoted by Tr prefix) and from all nonredundant sequences obtained in GenBank (Maia da Silva et al., 2007, 2009; Urrea et al., 2011). The two main branches separated the Robustus genotype from Pallescens II, Colombiensis and Ecuadoriensis II genotypes. KP1 mini-circle classifications are also indicated. The bootstrap values obtained by maximum likelihood analysis are shown on tree nodes (1,000 replicates).

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KP1(+)

G03

KP1(-) G17 G09 G08, 11, 12, 13, 15 G04 G14, 16

G18

N1 G17

N2

N3

G10 Colombiensis genotype G05, 06, 07 Ecuadoriensis II genotype Pallescens II genotype

G01 e 02

Robustus genotype Amazonian strains Santa Catarina strains

KP1? Fig. 4. Distribution of Trypanosoma rangeli strains according to the single nucleotide polymorphism region analysis of the spliced-leader intergenic region. Haplotype (H_1– H_23) median network trees are resolved from 63 sequences of T. rangeli. A network program was used for the reconstruction of the trees, applying the star contraction option before construction with the median-joining option. A cleaning procedure was done with the post-processing option. Black circles are median vectors that are hypothesised sequences not found in the sample and required to connect the existing haplotypes. The other circles are nodes corresponding to one haplotype or contracted haplotypes found in the current data set; their size is proportional to the number of haplotypes that form each node. Sco is the result of a star contraction of haplotypes 3 and 4. The torso of analysis is represented by N1, N2 and N3, and partitioned haplotypes into three main branches. The different colours represent triatomine genotypes described by Urrea et al. (2011). Localisation of genotypes obtained from microsatellite region analysis (Table 3, G01–G18) are also indicated.

Amazonian group (G1, G2) and up to 12 for the Peruvian strains (G18). The motifs TA and TATG were absent in the first three genotypes, with the TG and final TA dinucleotides starting to appear in the KP1(+) strains (G3). The most heterogeneous group was formed by KP1() strains (G4–G18), revealing a variable number of repeats. The SMM used to analyse all the data indicated that the MS regions showing lower numbers of repeats could be considered ancestral markers, thus indicating that T. rangeli strains evolved from the Amazonian group to the KP1(+) and KP1() strains. Fig. 4 shows the analysis of the SNP region (Haplotypes 1–23) median network trees resolved from 63 sequences of T. rangeli SL-IR, reinforcing the observations discussed above. The trunk of the analysis is represented by N1, N2 and N3, partitioning haplotypes into three main branches: the Amazonian group, which is more distant from the other strains; the KP1(+) strains isolated from Robustus group triatomines, which are more similar to each other; and the more diverse KP1() strains isolated from Colombiensis, Pallescens and Ecuadoriensis group triatomines. The data also reveal no apparent geographical structure except for the Amazonian group. As expected there was no specific association of the T. rangeli haplotypes with a given vertebrate host but a more visible association with the triatomine vectors (Urrea et al., 2011). While the KP1(+) group is exclusively associated with the Robustus genotype, the KP1() group is associated with the Pallescens, Ecuadoriensis and Colombiensis groups of triatomines (Fig. 4, Supplementary Tables S3, S4). The Amazonian haplotype (KP1?) was not clustered along the established triatomine groups. In conclusion, our results characterised MS markers found within coding sequences of the T. rangeli genome, allowing an understanding of the population structure of this parasite and sup-

porting the clonal structure of this species. Additionally, such markers reinforce the robustness of the two major groups circulating in central/South America, KP1(+) and KP1() and their intrinsic relationship with triatomine groups, highlighting variability within the KP1() group composed of strains from southern Brazil and the possibility of the ancestry of this taxon based on Amazonian strains. Taken together, the analysis of MS genotyping and SL sequences suggests the following three T. rangeli groups: (i) the Amazonian group, which is related to R. brethesi and some vertebrates; (ii) the T. rangeli KP1() group, which is related to R. pallescens, R. colombiensis, R. ecuadoriensis, Panstrongylus megistus and some vertebrates (although strains from Santa Catarina remain between other KP1() and KP1(+) strains); and (iii) the T. rangeli KP1(+) group, which is related to R. prolixus, R. robustus, R. neglectus and some vertebrates (Vallejo et al., 2003; Urrea et al., 2011). The analysis of the T. rangeli population structure reinforces its use as a model organism to study the genomic organisation and evolution of trypanosomatids. Also, the present study points out the influence of vector species on the clonality of these parasite strains, which is not well understood for most of the vector-borne human or animal trypanosomatid-related diseases. Acknowledgments We are grateful to Dr. LDP Rona for critical reading of the manuscript. TCMS and PHS were recipients of Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Brazil) scholarships. This study was supported by grants from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq,

Please cite this article in press as: Sincero, T.C.M., et al. Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1() strains and the ancestry of the Amazonian group. Int. J. Parasitol. (2015), http://dx.doi.org/10.1016/j.ijpara.2014.11.004

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Please cite this article in press as: Sincero, T.C.M., et al. Trypanosoma rangeli displays a clonal population structure, revealing a subdivision of KP1() strains and the ancestry of the Amazonian group. Int. J. Parasitol. (2015), http://dx.doi.org/10.1016/j.ijpara.2014.11.004