- Record: found
- Abstract: found
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International Study to Evaluate PCR Methods for Detection of Trypanosoma cruzi DNA in Blood Samples from Chagas Disease Patients
research-article
Author(s):
Alejandro G. Schijman
1
,
* ,
Margarita Bisio
1 ,
Liliana Orellana
2 ,
Mariela Sued
2 ,
Tomás Duffy
1 ,
Ana M. Mejia Jaramillo
3 ,
Carolina Cura
1 ,
Frederic Auter
4 ,
Vincent Veron
5 ,
Yvonne Qvarnstrom
6 ,
Stijn Deborggraeve
7 ,
Gisely Hijar
8 ,
Inés Zulantay
9 ,
Raúl Horacio Lucero
10 ,
Elsa Velazquez
11 ,
Tatiana Tellez
12 ,
Zunilda Sanchez Leon
13 ,
Lucia Galvão
14 ,
Debbie Nolder
15 ,
María Monje Rumi
16 ,
José E. Levi
17 ,
Juan D. Ramirez
18 ,
Pilar Zorrilla
19 ,
María Flores
20 ,
Maria I. Jercic
21 ,
Gladys Crisante
22 ,
Néstor Añez
22 ,
Ana M. De Castro
23 ,
Clara I. Gonzalez
24 ,
Karla Acosta Viana
25 ,
Pedro Yachelini
26 ,
Faustino Torrico
12 ,
Carlos Robello
19 ,
Patricio Diosque
16 ,
Omar Triana Chavez
3 ,
Christine Aznar
5 ,
Graciela Russomando
13 ,
Philippe Büscher
7 ,
Azzedine Assal
4 ,
Felipe Guhl
18 ,
Sergio Sosa Estani
27 ,
Alexandre DaSilva
6 ,
Constança Britto
28 ,
Alejandro Luquetti
29 ,
Janis Ladzins
30
Publication date (Electronic):
11 January 2011
Journal:
PLoS Neglected Tropical Diseases
Publisher:
Public Library of Science
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Abstract
Background
A century after its discovery, Chagas disease still represents a major neglected tropical threat. Accurate diagnostics tools as well as surrogate markers of parasitological response to treatment are research priorities in the field. The purpose of this study was to evaluate the performance of PCR methods in detection of Trypanosoma cruzi DNA by an external quality evaluation.
Methodology/Findings
An international collaborative study was launched by expert PCR laboratories from 16 countries. Currently used strategies were challenged against serial dilutions of purified DNA from stocks representing T. cruzi discrete typing units (DTU) I, IV and VI (set A), human blood spiked with parasite cells (set B) and Guanidine Hidrochloride-EDTA blood samples from 32 seropositive and 10 seronegative patients from Southern Cone countries (set C). Forty eight PCR tests were reported for set A and 44 for sets B and C; 28 targeted minicircle DNA (kDNA), 13 satellite DNA (Sat-DNA) and the remainder low copy number sequences. In set A, commercial master mixes and Sat-DNA Real Time PCR showed better specificity, but kDNA-PCR was more sensitive to detect DTU I DNA. In set B, commercial DNA extraction kits presented better specificity than solvent extraction protocols. Sat-DNA PCR tests had higher specificity, with sensitivities of 0.05–0.5 parasites/mL whereas specific kDNA tests detected 5.10 −3 par/mL. Sixteen specific and coherent methods had a Good Performance in both sets A and B (10 fg/µl of DNA from all stocks, 5 par/mL spiked blood). The median values of sensitivities, specificities and accuracies obtained in testing the Set C samples with the 16 tests determined to be good performing by analyzing Sets A and B samples varied considerably. Out of them, four methods depicted the best performing parameters in all three sets of samples, detecting at least 10 fg/µl for each DNA stock, 0.5 par/mL and a sensitivity between 83.3–94.4%, specificity of 85–95%, accuracy of 86.8–89.5% and kappa index of 0.7–0.8 compared to consensus PCR reports of the 16 good performing tests and 63–69%, 100%, 71.4–76.2% and 0.4–0.5, respectively compared to serodiagnosis. Method LbD2 used solvent extraction followed by Sybr-Green based Real time PCR targeted to Sat-DNA; method LbD3 used solvent DNA extraction followed by conventional PCR targeted to Sat-DNA. The third method (LbF1) used glass fiber column based DNA extraction followed by TaqMan Real Time PCR targeted to Sat-DNA (cruzi 1/cruzi 2 and cruzi 3 TaqMan probe) and the fourth method (LbQ) used solvent DNA extraction followed by conventional hot-start PCR targeted to kDNA (primer pairs 121/122). These four methods were further evaluated at the coordinating laboratory in a subset of human blood samples, confirming the performance obtained by the participating laboratories.
Author Summary
A century after its discovery, Chagas disease, caused by the parasite Trypanosoma cruzi, still represents a major neglected tropical threat. Accurate diagnostics tools as well as surrogate markers of parasitological response to treatment are research priorities in the field. The polymerase chain reaction (PCR) has been proposed as a sensitive laboratory tool for detection of T. cruzi infection and monitoring of parasitological treatment outcome. However, high variation in accuracy and lack of international quality controls has precluded reliable applications in the clinical practice and comparisons of data among cohorts and geographical regions. In an effort towards harmonization of PCR strategies, 26 expert laboratories from 16 countries evaluated their current PCR procedures against sets of control samples, composed by serial dilutions of T.cruzi DNA from culture stocks belonging to different lineages, human blood spiked with parasite cells and blood samples from Chagas disease patients. A high variability in sensitivities and specificities was found among the 48 reported PCR tests. Out of them, four tests with best performance were selected and further evaluated. This study represents a crucial first step towards device of a standardized operative procedure for T. cruzi PCR.
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Most cited references41
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Development of a real-time PCR assay for Trypanosoma cruzi detection in blood samples.
Jordi i Prat, Roser Fisa, Natalia Casamitjana … (2007)
The aim of this study was to develop a real-time PCR technique to detect Trypanosoma cruzi DNA in blood of chagasic patients. Analytical sensitivity of the real-time PCR was assessed by two-fold serial dilutions of T. cruzi epimastigotes in seronegative blood (7.8 down to 0.06 epimastigotes/mL). Clinical sensitivity was tested in 38 blood samples from adult chronic chagasic patients and 1 blood sample from a child with an acute congenital infection. Specificity was assessed with 100 seronegative subjects from endemic areas, 24 seronegative subjects from non-endemic area and 20 patients with Leishmania infantum-visceral leishmaniosis. Real-time PCR was designed to amplify a fragment of 166 bp in the satellite DNA of T. cruzi. As internal control of amplification human RNase P gene was coamplified, and uracil-N-glycosylase (UNG) was added to the reaction to avoid false positives due to PCR contamination. Samples were also analysed by a previously described nested PCR (N-PCR) that amplifies the same DNA region as the real-time PCR. Sensitivity of the real-time PCR was 0.8 parasites/mL (50% positive hit rate) and 2 parasites/mL (95% positive hit rate). None of the seronegative samples was positive by real-time PCR, resulting in 100% specificity. Sixteen out of 39 patients were positive by real-time PCR (41%). Concordance of results with the N-PCR was 90%. In conclusion, real-time PCR provides an optimal alternative to N-PCR, with similar sensitivity and higher throughput, and could help determine ongoing parasitaemia in chagasic patients.
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- Abstract: found
- Article: not found
Accurate Real-Time PCR Strategy for Monitoring Bloodstream Parasitic Loads in Chagas Disease Patients
Tomas Duffy, Margarita Bisio, Jaime Altcheh … (2009)
Introduction Infection with the parasite Trypanosoma cruzi (T. cruzi) remains a major concern in 21 endemic countries of America, with an estimated prevalence of almost 8 million infected people [1]. The infection may be acquired mainly through the triatomid insect vector, blood transfusion or the trans-placental route. Furthermore, in areas under vector control, cases of congenital and transfusional transmission are relatively emerging [2]. This parasitic disease shows a variable clinical course, which ranges from asymptomatic cases, to severe chronic stages characterized by low parasitaemia and cardiac and/or gastrointestinal disorders [1]. Individuals from different endemic regions are infected with distinct parasite populations that may play a role in pathogenesis, clinical forms and severity of the disease [3]. Parasite populations are classified into two main phylogenetic lineages, T. cruzi I (TcI) and T. cruzi II (TcII) [4]; the later composed by five subdivisions designated as TcIIa to TcIIe [5]. Current chemotherapies based on the nitrofuran nifurtimox, and the nitroimidazole benznidazole, are unsatisfactory since these compounds are almost exclusively effective in recent infections and frequently have toxic side effects [6]. In this context, the development of novel drugs is necessary [6]. After etiological treatment (tmt), the criterion of cure relies on serological conversion to negative of the anti- T. cruzi antibody response [2], but in patients initiating therapy at the indeterminate phase, seroconversion usually occurs several years after treatment, requiring long-term follow-up [7]. Moreover, parasitological response to treatment is usually monitored by means of traditional methods such as Strout, hemoculture or xenodiagnoses, which lack sensitivity, and therefore are also inadequate for these purposes [2]. In this context, quantitative real-time PCR (Q-PCR) has the potential to become a novel parasitological tool for prompt evaluation of trypanocidal treatment. As a target for amplification, the nuclear satellite DNA, represented in 104 to 105 copies in the parasite genome is highly conserved [8]–[11] and therefore may provide accurate Q-PCR based measurements. Proper Q-PCR performance also requires high quality DNA extraction procedures from blood samples, which in most cases are collected in guanidine hydrochloride and EDTA buffer (GEB) [12]. The co-purification of trace PCR inhibitors may not impede amplification but may reduce its efficiency resulting in erroneous quantification of the parasitic load. Accordingly, we aimed to develop a satellite-DNA based Q-PCR strategy for accurate quantification of T. cruzi loads in peripheral blood samples along with an adequate DNA extraction protocol. The following features have been regarded: A commercial DNA purification protocol based on silica-membrane technology was adapted for GEB samples, providing DNA lysates without PCR interfering substances. A heterologous internal standard (IS) was incorporated to each GEB sample to follow-up the yield and quality of DNA extraction and PCR amplification. The relative copy number of satellite repeats per genome, according to the parasite lineage, was assessed for a more accurate quantification of the parasitic load, by means of a real-time PCR melting curve analysis (Lg-PCR). Finally, we applied this Q-PCR strategy to: (1) calculate the basal T .cruzi loads in blood specimens collected from Chagas disease pediatric patients, (2) follow-up their parasitological response to treatment with benznidazole, and (3) monitor T. cruzi recrudescence and parasitological response to treatment in chronic Chagas heart disease patients undergoing heart-transplantation and receiving immunosuppressive therapy. Materials and Methods Ethics statement This study was conducted according to the principles expressed in the Declaration of Helsinki. The study was approved by the Institutional Review Boards of the “Ricardo Gutierrez” Children's Hospital and of the Fundacion “Rene Favaloro”. All patients or responsible adults provided written informed consent for the collection of samples and subsequent analysis. Parasite stocks T. cruzi epimastigotes were grown in liver infusion tryptose (LIT) medium containing 10% calf serum at 27–28°C. The parasites were harvested and stored at −70°C. T. cruzi DNA was purified after Phenol-Chloroform extraction and ethanol precipitation. Reference T. cruzi stocks used as controls were: TcI (Silvio X10 cl1, SN3, HA, Pal V2-2, Pav 00, G); TcIIa (CanIII); TcIIb: (Tu18, JG, Gilmar, Y, Basileu, Mas cl1); TcIIc: (M5631, Cu-Tom-229, Cu-Yaya-211), TcIId (Mn cl2, Bug 2148 cl1, SO3 cl5, PAH 265, Tev 41), TcIIe (Cl Brener, Tul 77, Tep 6, Tep 7, MC). They were kindly provided by Patricio Diosque (Universidad Nacional de Salta, Salta, Argentina), Andrea M. Macedo (University Federal of Minas Gerais, Belo Horizonte, Brasil), and Michel Tibayrenc (UR62 “Genetics of Infectious Diseases”, IRD Centre, Montpellier, France). Some T. cruzi I strains were provided by Omar Triana Chavez (University of Antioquia, Medellín, Colombia). Argentinean T. cruzi IIc isolates were provided by Ricardo Gurtler (Universidad de Buenos Aires, Argentina). Chagas disease patients Peripheral blood samples collected from a cohort of 43 T. cruzi-seropositive pediatric patients (mean age: 7.13 years; 15 days–18 years old) admitted between 2005 and 2006 at the Parasitology Unit of the “Ricardo Gutierrez” Children's Hospital, a reference centre for diagnosis and treatment of Chagas disease pediatric patients (Government of Buenos Aires, Argentina). These patients were treated during 60 days with benznidazole (5 to 8 mg/kg/day) [13]. Parasitic loads were determined by Q-PCR at time of diagnosis (t1), at 7 (t2), 30 (t3) and 60 (t4) days of treatment. After t4, patients were followed-up by qualitative kDNA-PCR at 6, 12 and 18 months post-tmt. Blood samples from three chronic Chagas heart disease patients undergoing orthotopic heart transplantation (Tx) in 2003–2005 were provided by the Transplant Unit of the Instituto de Cardiología y Cirugía Cardiovascular, Fundación “René Favaloro”, Buenos Aires, Argentina. [14]. All these protocols were approved by the ethical committees of the corresponding institutions and written informed consents were required from each patient or a responsible adult. DNA extraction from peripheral human blood samples Ten mL or 2 mL blood samples collected from T. cruzi infected adults or infants, respectively, were immediately mixed with one volume of 2× lysis buffer containing 6 M guanidine hydrochloride (Sigma, St Louis, USA) and 200 mM EDTA, pH 8.0 (GE) [12]. QIAmp DNA Mini Kit (Qiagen, Valencia, CA) based extraction was carried out from 400 µl of GEB and eluted with 200 µl of water according to the manufacturer's instructions using the Blood and Body Fluid Spin Protocol, with slight modifications. Briefly, since blood samples were initially mixed with one volume of GE lysis buffer, treatment with proteinase K and “AL” lysis buffer (which contains guanidine hydrocloride) were omitted. The following steps were carried out following the manufacturer's instructions. Phenol-chloroform based DNA extraction was carried out from 100 µl of GEB aliquots and resuspended in 50 µl water as reported [15]. T. cruzi standard calibration curve Cl Brener epimastigotes were added to non-infected human blood to result in a concentration of 105 p/mL of reconstituted blood and immediately mixed with one volume of 2× lysis GE buffer. The resulting GEB was serially diluted 10-fold with non-infected GEB to cover a range between 105 and 0.001 parasite equivalents/mL. Total DNA was purified using the QiAmp DNA Mini Kit based extraction method, as above described. T. cruzi satellite DNA Q-PCR An MJR-Opticon II device (Promega, USA) was used for amplification and detection. The 20 µL reaction tube contained 0.5 µM of novel primers Sat Fw (5′-GCAGTCGGCKGATCGTTTTCG-3′) and Sat Rv (5′-TTCAGRGTTGTTTGGTGTCCAGTG-3′), 3 mM MgCl2, 250 µM of each dNTP, 0.5 U of Platinum Taq polymerase, (Invitrogen, Life Technologies, USA) SYBR Green (Invitrogen, Life Technologies, USA) at a final concentration of 0.5× and 2 µL of sample DNA. After 5 min of pre-incubation at 95°C, PCR amplification was carried out for 40 cycles (94°C for 10 s, 65°C for 10 s and 72°C for 10 s). The plate was read at 72°C at the end of each cycle. Internal standards of Q-PCR A linearized p-ZErO plasmid containing a sequence of Arabidopsis thaliana was used as a heterologous internal standard (IS). All clinical samples were co-extracted with 200 pg of recombinant plasmid, which was assumed as 1 arbitrary unit (AU) of IS. This amount of IS input was chosen because the amplicons are detected at approximately the Cycle threshold (Ct) number 20, the mid point of the dynamic range of the PCR. For each Q-PCR test, the IS was added to 400 µl of GEB lysate, immediately before the DNA extraction procedure. The standard calibration curve for the IS was carried out using the same reconstituted blood samples as for the T. cruzi calibration curve: those samples containing 105, 104 and 103 p/mL were spiked with 2 AU of IS, those containing 100, 10 and 1 p/mL were spiked with 0.2 AU of IS, and those containing 0.1, 0.01 and 0.001 p/mL were spiked with 0.02 AU of IS. Two non-infected blood samples with and without IS DNA were used as negative controls of the extraction procedure. The IS was quantified using 1 µM of primers, IS Fw (5′-AACCGTCATG GAACAGCACGTAC-3′) and IS Rv (5′-CTAGAACATTGGCTCCCGCAACA-3′). All other PCR reagents and cycling conditions were identical to those used for T. cruzi Q-PCR. Qualitative PCR detection of T. cruzi kDNA Post-treatment follow-up of parasitological response to benznidazole in pediatric and heart transplanted patients was conducted by means of kDNA-PCR as previously reported [14],[16]. Determination of the satellite/P2α ratio In order to analyze the variability in the number of satellite sequences detected by Q-PCR, comparative quantification was performed using as a normalizer the single copy ribosomal protein P2α gene (GenBank accession number XM_800089). Assays for quantification of P2α gene were performed using 1 µM of primers P2α Fw (5′-ATGTCCATGAAGTACCTCGCC-3′) and P2α Rv (5′-GCGAATTCTTACGCGCCCTCCGCCACG-3′). All other PCR reagents were used at the same concentrations as for T. cruzi Q-PCR. After 5 min of pre-incubation at 95°C, PCR amplification was carried out for 40 cycles (94°C for 10 s, 60°C for 15 s and 72°C for 10 s). The plate was read at 72°C at the end of each cycle. Identification of parasites according to the number of satellite sequences detected per genome by Lg-PCR Since TcI and TcIIa parasites have a lower number of satellite sequences than TcIIb/c/d/e parasites, we have developed a method to distinguish between both groups according to the melting temperatures (Tm) of their corresponding amplicons to enable more precise parasitic load assessments. The identification of the type of satellite sequence was performed using 0.5 µM of primers TcZ1 (5′-CGAGCTCTTGCCCACACGGGTGCT-3′) and Sat Rv (5′-TTCAGRGTTGTTTGGTGTCC AGTG-3′). All other PCR reagents were used at the same concentrations as for T. cruzi Q-PCR. The PCR conditions consisted of an initial denaturation at 95°C for 5 min, followed by 40 cycles of 94°C for 10 s, 65°C for 10 s and 72°C for 10 s with fluorescence acquisition at 81.5°C and a final step of 2 min at 72°C. Amplification was immediately followed by a melt program with an initial denaturation of 5 s at 95°C and then a stepwise temperature increase of 0.1°C /s from 72–90°C. Since satellite DNA is arranged in tandem repeats, if more than 0.05 parasites (equivalent to approximately 10 p/mL) are loaded in the reaction tube, a satellite sequence dimer is amplified giving place to a melting temperature peak typically above 86°C for both lineage groups. Satellite sequences were obtained by direct sequencing of satellite DNA amplicons obtained with TcZ1 and TcZ2 primers (GenBank Accession numbers EU728662-EU728667). Sequence alignment was conducted using MEGA version 4 [17]. Normalization of parasite loads according to the internal standard and parasite satellite sequence group The parasite load in the clinical sample was normalized respect to the standard curve according to (1) the efficiency of the DNA extraction procedure measured by the amplification of the IS, and (2) the parasite lineage group. The following equation was used: Np/mL = (Np/well ×LF / AU) / V, where Np/mL is the number of parasites per millilitre of blood, Np/well is the number of parasites per well, LF is the lineage factor, AU are the arbitrary units of IS quantified and V is the volume of extracted DNA sample used per reaction. Results Analytical sensitivity and reproducibility of Q-PCR with purified DNA and reconstituted blood samples The analytical sensitivity of the Q-PCR was tested by using serial dilutions of purified T. cruzi DNAs from TcI (Silvio X10 cl1) and TcIIe (Cl Brener) reference stocks. The detection limits were 2 fg and 0.2 fg DNA per reaction tube with a dynamic range of 107 and 108 for Silvio X10 cl1 and Cl Brener stocks, respectively (data not shown). These detection limits correspond to 0.01 and 0.001 parasite genomic equivalents considering that one parasite cell harbors approximately 200 fg of DNA. Furthermore, we tested the operational parameters of Q-PCR in reconstituted - blood samples spiked with known quantities of Cl Brener and Silvio X10 cl1 cultured epimastigote cells. The dynamic range of Q-PCR performed with samples reconstituted with Silvio X-10 was 0.1–105 p/mL and with those spiked with Cl Brener was 0.01–105 p/mL (Figure 1). 10.1371/journal.pntd.0000419.g001 Figure 1 Dynamic range of the T. cruzi satellite DNA based Q-PCR. Results are expressed as the number of parasites per milliliter of blood and represent the average of 5 independent experiments. Slope = −3.35. Efficiency = 99%. Dynamic range: 0.01–105 p/mL. R square: 0.998. C(t): cycle threshold. The reproducibility of the Q-PCR assay at 100 p/mL and 1 p/mL was estimated by testing each reconstituted sample 15 times in the same PCR run. The coefficients of variation of the Ct values were 1.27% and 2.30%, respectively for Cl Brener and 1.60% and 5.42%, respectively for Silvio X10 cl1. The reproducibility of the DNA extraction was also characterised: aliquots from the same GEB-reconstituted samples containing 10 Cl Brener p/mL were processed in twenty independent DNA purification experiments. For each of the 20 DNA lysates, the p/mL were measured in triplicate PCR runs and a mean value was calculated. The coefficient of variation of the Ct values among the 20 mean values was 1.69%. Estimation of the relative numbers of satellite DNA copies per genome for different Trypanosoma cruzi lineages In order to evaluate if the differences in the detection limits of the Q-PCR obtained from Cl Brener or Silvio X10 cl1 samples were related to a different copy number of satellite repeats in their respective genomes, the amounts of satellite sequences, relative to the single copy gene encoding the ribosomal-P2α protein, were estimated for parasite stocks belonging to the 6 lineages (Table 1). The stocks belonging to TcIIb/d/e lineages showed similar amounts of satellite repeats (Table 1A), the M5631 stock (TcIIc) harbored 2-fold less repeats than the aforementioned stocks (Table 1A), whereas Can III stock (TcIIa) and six stocks belonging to T. cruzi I from Argentina, Colombia and Brazil, harbored a 10-fold lower number of satellite repeats (Table 1A and 1B). This is in agreement with the analytical sensitivities obtained with purified DNA and reconstituted samples of the reference stocks. 10.1371/journal.pntd.0000419.t001 Table 1 Variation in the relative numbers of satellite DNA copies per genome. A. Cultured T. cruzi stocks representing each of the phylogenetic lineages Lineage T.cruzi Reference Stocks Sat/P2α Tc I Silvio X-10 cl1 0.08 Tc IIa Can lll 0.08 Tc IIb Tu18 0.95 Tc IIc M5631 0.47 Tc IId Mn cl2 1.1 Tc IIe Cl Brener 1 B. T. cruzi I stocks from different endemic countries T. cruzi I Stocks Country of Origin Sat/P2a Silvio X-10 cl1 Brasil 0.08 G Brasil 0,13 HA Colombia 0,11 SN3 Colombia 0,13 Pav 00 Argentina 0,09 Pal V2-2 Argentina 0,12 Results are expressed as arbitrary units, obtained calculating the ratio of copy numbers of Cl Brener satellite/ ribosomal-P2α gene DNA targets. Distinction by Lg-PCR of T. cruzi groups according to the relative number of satellite repeats Two groups of lineages, T. cruzi I/IIa (group I) and T. cruzi II (IIb,c,d,e) (group II) were clearly distinguished due to the differential melting temperatures of their corresponding satellite sequence amplicons, above or below 85°C, respectively (Figure 2). 10.1371/journal.pntd.0000419.g002 Figure 2 Melting curve analysis of satellite amplicons from reference stocks. Group I satellite amplicons show melting temperatures above 85°C, whereas Group II render amplification products with melting temperatures below 85°C. The Lg-PCR was validated using a panel of 25 characterised stocks (Table 2): five stocks belonging to TcI, one to TcIIa, six to TcIIb, three to TcIIc, five to TcIId and the remaining five to TcIIe. 10.1371/journal.pntd.0000419.t002 Table 2 Melting temperatures of satellite fragments amplified from T. cruzi stocks belonging to the 6 phylogenetic lineages. Stock Tm (°C) Lineage Tm (°C)±SD Silvio X-10 cl1 85.7 Tc I 85.34±0.15 Pal v2-2 85.4 G 85.5 SN3 85.3 HA 85.4 Can lll 85.7 Tc lla 85.70±0.30 Tu18 84.6 Tc llb 84.60±0.18 JG 84.8 Gilmar 84.8 Y 84.6 Basileu 84.4 Mas cl1 84.4 M5631 83.9 Tc llc 84.03±0.45 Cu-TOM-229 84.5 Cu-Yaya-211 83.6 Mn cl2 84.4 Tc lld 84.44±0.30 Bug 2148 cl1 84.8 SO3 cl5 84.7 PAH265 84.1 Tev 41 84.2 Cl Brener 84.2 Tc lle 84.42±0.33 Tul77 84.7 Tep7 84.3 MC 84.0 Tep6 84.9 The 99% confidence interval of the melting temperatures depicted by the T.cruzi strains from group I (mean: 85.5°C; CI 99% 85.2–85.8) and II (mean: 84.4°C; CI 99% 84.2–84.7) did not overlap. This distinction allows a more accurate parasite load quantification by incorporating a correction factor (Lineage Factor LF), according to the number of target sequences, when the parasitic load is calculated. Comparison of PCR inhibition using two extraction methods in human samples We extracted 55 GEB samples from Chagas disease patients with the QIAmp DNA Mini Kit adapted protocol as well as with a Ph-Chl based method. Using the Ph-Chl based method, we detected traces of PCR inhibitors in 16 (29%) samples, whereas for the commercial kit we did not detect PCR inhibitors in any of the samples. The presence of PCR inhibitors was assessed by (1) the low yield of IS amplification, giving rise to less than 0.1 AU of the IS and (2) the improved yield of IS amplification when the DNA lysate was diluted 1/100 prior to the Q-PCR run. Out of the 16 samples that presented traces of PCR inhibitors when extracted with the Ph-Chl based method, 4 were negative for T. cruzi by both extraction methods, 3 rendered similar parasite loads by both methods, 8 rendered higher parasite loads when extracted with the commercial kit, and one rendered a positive result only when extracted with the commercial kit. For the 39 samples extracted by Ph:Chl that did not contain PCR inhibitors, similar results of T. cruzi quantification were obtained with both methods of extraction. On the basis of these data, the QIAmp DNA Mini Kit extraction protocol was selected for Q-PCR in clinical samples. Application of the Q-PCR assay to clinical specimens A panel of human blood samples was analyzed using the Q-PCR strategy, namely samples from seropositive pediatric patients and chronic Chagas heart disease adults presenting clinical reactivation after heart transplantation. Table 3 describes the necessary steps for calculating the parasitic loads, considering the lineage factor (LF), the AU of the IS and the input volume of DNA sample. For example, in case Tx1c, the Q-PCR alone quantified 0.39 p/mL, but the AU of the IS was 0.43, and the LF was 10 (T. cruzi I), giving a final result of 9.07 p/mL, which is 23 times higher than if the quantification had been made based only on the Q-PCR crude measurement. In case Pd6, a pediatric patient with very low parasitemia, the lineage could not be determined since the low concentration of amplicons gave rise to non-reliable melting temperature peaks and therefore the parasitic load could only be expressed within a range of 10-fold. In cases Tx1a and Tx2c, also with low levels of parasitemia, the lineage was presumed from previous data obtained from genotyped samples of the same patients, because it was demonstrated that the T. cruzi lineages were persistent during recrudescence leading to clinical reactivation in these patients [14]. Cases Pd2a and Tx2b presented high parasitic loads, 512 and 468 p/mL, respectively. In both of them, dimers of the satellite repeats were preferentially amplified when Lg-PCR was performed, giving melting temperatures above 86°C (Table 3). Thus, when the non-corrected Q-PCR results are above 10 p/mL, the DNA lysate should be diluted to approximately 1 p/mL before performing Lg-PCR. 10.1371/journal.pntd.0000419.t003 Table 3 Examples of the calculation of parasitic loads in pediatric and transplanted patients. Case Age/Gender Clinical Diagnosis Sample Q-PCR Np/well / V IS-PCR AU Lg-PCR Tm (°C) Lineage LF Parasitic Load Np/mL = (Np/well ×LF / AU) / V Pd 1a 7 y / M Congenital ChD Pre-tmt 7.20 0.87 84.6 2 1 8.28 1b 7 days of tmt 0.1 0.97 84.6 2 1 0.1 1c 30 days of tmt 0.76 1.21 84.4 2 1 0.63 1d 60 days of tmt 0.95 0.82 84.6 2 1 1.16 Pd 2a 3 m / M Congenital ChD Pre-tmt 527 1.03 84.5‡ 2 1 512 2b 30 days of tmt 0.29 0.67 84.8 2 1 0.43 2c 60 days of tmt 1.01 1.34 84.4 2 1 0.75 Pd 3 1 y / F Congenital ChD Pre-tmt 14.69 1.27 84.4 2 1 11.57 Pd 4 2 y / M Congenital ChD Pre-tmt 0.34 0.49 84.6 2 1 0.69 Pd 5 3 y / F Congenital ChD Pre-tmt 0.54 1.18 84.6 2 1 0.46 Pd 6 10 y / F Indeterminate ChD Pre-tmt 0.04 0.74 ND ND# ND# 0.05–0.5 Tx 1a 46 y / M Chronic Cardiomyopathy with Heart Transplantation 5 days pre-Tx 0.03 1.26 ND 1* 10* 0.22 1b 29 days post-Tx 0.59 1.53 85.2 1 10 3.85 1c reactivation 78 days post-Tx 0.39 0.43 85.3 1 10 9.07 Tx 2a 61 y / F Chronic Cardiomyopathy with Heart Transplantation 7 days post-Tx 2.23 0.84 84.5 2 1 2.66 2b reactivation 92 days post-Tx 342 0.73 84.6‡ 2 1 468 2c 12 days post-tmt 0.13 1.84 ND 2* 1* 0.07 In the samples from transplanted patients (Tx) whose infecting lineages could not be determined, they were presumed from the data obtained from other samples of the same patient, assuming that the lineage is persistent during reactivation [13]. ND: Not determined. # In case Pd6 no presumption could be made about the parasite lineage. ‡ Samples diluted before Lg-PCR. The reproducibility of the whole Q-PCR assay was evaluated in 5 clinical samples from different Chagas disease patients covering a range of 3 logarithms of parasitic loads (0.06 to 70.29 p/mL, Table 4). For each peripheral blood sample (A to E, Table 4), the entire protocol was carried out in 5 independent replicates. The coefficients of variation of the Ct values and p/mL for the T.cruzi Q-PCRs ranged from 1.30 to 5.49% and from 25.19 to 137,95%, respectively, and those for the IS-PCRs ranged from 0.66 to 2.28% and from 9.56 to 29.51%, respectively (Table 4). The final parasitic load measurements were inversely correlated with their coefficients of variation, which ranged from 32.43 to 114.20% (Table 4). 10.1371/journal.pntd.0000419.t004 Table 4 Reproducibility of the Q-PCR and IS-PCR assays in clinical samples of Chagas disease patients. Patient Replicates Q-PCR Cv % IS-PCR Cv% Parasitic Load Ct p/mL Ct p/mL Ct AU Ct AU p/mL Mean p/mL Cv% A 1 neg 0.00 5.49 137.95 20.83 1.37 1.54 22.66 0.00 0.06 114.2 2 30.29 0.29 20.40 1.83 0.16 3 31.95 0.09 21.23 1.05 0.09 4 34.31 0.02 20.91 1.30 0.01 5 33.56 0.03 21.12 1.13 0.03 B 6 30.83 0.20 2.83 66.52 23.08 0.30 2.28 29.51 0.65 0.33 72.39 7 31,70 0.11 22.48 0.46 0.24 8 30.08 0.33 21.97 0.64 0.51 9 32.13 0.08 22.00 0.63 0.13 10 32.09 0.08 21.86 0.69 0.12 C 11 30.16 0.31 3.20 69.45 21.64 0.80 1.51 21.96 0.39 0.50 88.15 12 30.29 0.29 20.94 1.28 0.22 13 31.19 0.15 21.31 1.00 0.15 14 28.59 0.92 21.76 0.74 1.24 15 29.59 0.46 21.31 1.00 0.46 D 16 26.08 5.16 1.30 25.19 20.97 1.25 0.66 9.56 4.13 4.87 32.43 17 25.93 5.72 21.03 1.20 4.75 18 25.36 8.47 21.11 1.14 7.41 19 26.26 4.56 20.75 1.45 3.15 20 25.91 5.80 21.05 1.18 4,90 E 21 22.89 46.25 2.44 40.68 21.36 0.96 1.42 19.05 47.99 70.29 33.45 22 22,80 49.20 21.95 0.65 76.01 23 23,00 42.88 21.32 0.99 43.32 24 21.72 103.38 21.16 1.10 93.84 25 22.17 75.87 21.56 0.84 90.28 The T.cruzi lineage group was assessed by Lg-PCR as T.cruzi II in all tested patients. Parasitic Loads were calculated as shown in Table 3. Follow-up of pediatric patients under treatment with benznidazole The pre-treatment parasitic loads were assessed in 43 children with Chagas disease. Basal parasitic loads ranged from 640 to 0.01 p/mL, and were correlated to the patients' ages at the time of diagnosis (coefficient of Spearman: −0.5832, P<0.05) (Figure 3A). Thirty eight of these patients were monitored by Q-PCR during 60 days of etiological treatment with benznidazole. Parasitic loads were determined at time of diagnosis (t1) in 38 cases, at 7 (t2), 30 (t3) and 60 (t4) days of treatment in 31 cases. 10.1371/journal.pntd.0000419.g003 Figure 3 Parasitic loads in peripheral blood samples from pediatric patients. (A) Association between basal parasitic loads and patients' ages in 43 pediatric cases. Coefficient of correlation: −0.5832; P<0.05. (B) Monitoring of parasitological response to benznidazole therapy in 38 pediatric patients. The evolution of the parasitic loads for patients with more then one positive sample are depicted. Samples were withdrawn at time of diagnosis (t1), after 7 (t2) and 30 (t3) days of treatment, as well as at the end of treatment (t4, 60 days). Only the PCR positive samples are shown. The horizontal line represents the lower limit of the dynamic range of Q-PCR. Figure 3B and Table 3 show the parasitic response of these patients during treatment monitoring. Q-PCR results at t2 were negative in 24 out of 31 patients (77%), at t3 in 27 out of 31 patients (87%) and at t4 in 29 out of 31 patients (94%). One of the Q-PCR positive patients at t4 was a 7 year-old boy whose parasite load declined from 8.28 p/mL at t1 (Pd1a) to 0.1 p/mL at t2 (Pd1b), relapsing to 0.63 p/mL at t3 (Pd1c) and 1.16 p/mL at t4 (Pd1d) (Figure 3B, red triangle, Table 3). The other Q-PCR positive patient at t4 was a 3 month old infant who displayed detectable parasitic loads in the three analysed samples; 512 p/mL at t1 (Pd2a), 0.43 p/mL at t3 (Pd2b) and 0.75 p/mL at t4 (Pd2c) (Figure 3B, green triangle, Table 3). Both patients were followed-up by kDNA-PCR with persistently positive results at 6, 12 and 18 months post-tmt suggesting treatment failure (data not shown). Q-PCR based monitoring of Chagas disease reactivation in heart-transplanted patients Stored peripheral blood samples from three heart transplanted patients infected with different parasite lineages and presenting different patterns of clinical reactivation were retrospectively analyzed using the Q-PCR strategy (Figure 4). 10.1371/journal.pntd.0000419.g004 Figure 4 Follow-up of Chronic Chagas heart disease patients after heart transplantation. Parasitic loads in peripheral blood samples of Chronic Chagas heart disease patients with clinical reactivation due to immunosupression after heart transplantation. * Time of diagnosis of clinical reactivation and etiological treatment. Case Tx1 presented positive Q-PCR results (0.22 p/mL) prior to heart transplantation. Clinical reactivation was diagnosed at day 78 post-Tx by a skin chagoma biopsy and a positive Strout result. The parasite population was characterized as group I by Lg-PCR. Case Tx2 did not present positive PCR results before heart Tx, but parasitemia became detectable 7 days post-Tx (2.66 p/mL). Clinical reactivation was diagnosed at 92 days post-Tx due to positive Strout findings. Upon etiological tmt, the parasitic load decreased reaching undetectable levels at 21 days post-tmt. The T. cruzi population was identified as group II. Case Tx3 presented a parasite load of 0.02 p/mL 30 days before Tx, showing a 10-fold increase (0.2 p/mL) 7 days after Tx. The parasite load continued to rise until clinical reactivation was diagnosed 38 days after Tx based on positive Strout findings. Accordingly, the patient was treated with benznidazole and the parasite load dropped rapidly, with negative Q-PCR findings at 14 days post-tmt, persisting PCR negative for 53 days. However, 70 days after tmt Q-PCR monitoring revealed detectable loads (0.01 p/mL) (Figure 4). The bloodstream T. cruzi population was identified as group II. Discussion Herein we report a highly sensitive, reproducible, accurate and rapid real-time Q-PCR strategy for quantification of the T. cruzi parasitic load in human blood samples. Indeed, this is a first attempt to develop a real-time Q-PCR strategy for reliable T. cruzi quantification, because it incorporates: (1) a commercial kit for sample processing which minimizes carry-over of PCR inhibitors and standardizes the yield and quality of DNA extraction, (2) a closed-tube single-round PCR reaction which minimizes carry-over contamination, (3) an appropriate internal quality control and (4) a correction of the parasitic load, according to the variation in the number of target sequences between the different lineage groups. This is a key step towards the standardization and validation of in-house Q-PCR tests for application to routine laboratory practice. Although studies showing the advantages of real-time PCR for screening and quantification of T. cruzi have recently appeared, none have implemented procedures to normalize the DNA extraction yield and the representativity of the PCR target according to the lineage group. Some studies [18]–[20] have chosen as an internal control a host DNA sequence, but the human DNA content in blood can be highly variable, especially in immunosupressed patients. In this work, the addition of a standardized amount of a plasmid containing a heterologous sequence, allows normalization of the DNA extraction yields and detection of false negatives due to inhibition under any clinical situation. Regarding the selected molecular target of amplification, Elias et al. [8],[11] and Vargas et al. [10] demonstrated that satellite DNA is 4 to 9 times more abundant in TcIIb/d/e than in TcI stocks. Herein, we have extended this analysis to all 6 T. cruzi lineages, describing for the first time the satellite repeats of T. cruzi IIa, IIc and IId representative stocks (GenBank Accession numbers EU728662-EU728667). Indeed, we detected a 5 to 10-fold variation in the satellite DNA content between group I (TcI/IIa) and group II (TcIIb/c/d/e) parasite stocks (Table 1). Therefore, this variability must be taken into account in order to calculate accurately the parasitic loads. Accordingly, we have also designed a highly sensitive real-time PCR procedure (Lg-PCR) to distinguish T. cruzi group I (with lower satellite sequence copy number and higher melting temperature) from group II lineages (with higher satellite sequences copy number and lower melting temperature). All the analyzed stocks rendered only one temperature melting peak, including hybrid stocks like Cl Brener although harboring both types of satellite sequences. This can be explained by the fact that Cl Brener (Tc IIe) harbors ten times more type II than type I satellite repeats [10] and due to exponential amplification, only the predominant sequence type is detected. The high analytical sensitivity of Lg-PCR makes it useful for direct lineage group characterization in biological samples that may not be typed using other typing methods [16],[21],[22]. Alternatively, a recently reported multiplex PCR strategy might be useful for typing T.cruzi groups in clinical specimens [23] when a Q-PCR test targeted to satellite sequences is carried out. Sample processing and DNA extraction must also be optimized for reliable quantification. In this direction, we adapted a commercial kit, based on silica-membrane technology (QIAmp DNA Mini Kit) for processing GEB samples. Phenol-chloroform DNA extraction is a cost-effective method for qualitative PCR, but traces of PCR inhibitors may be co-purified [24],[25]. These interfering substances may not impede Q-PCR amplification, but could affect its efficiency leading to inaccurate results. In fact, we detected traces of PCR inhibitors in 29% of the samples extracted with Ph-Chl. When present, these inhibitors underestimated the parasite loads in 67% of the positive samples, although they did not seriously affect the positivity of the PCR. These results suggest that Ph-Chl based extraction of GEB samples is not suitable for Q-PCR but can be used for qualitative purposes. In this report, we applied the Q-PCR strategy to blood samples collected from patients under different clinical scenarios. Its wide dynamic range allowed direct measurements in cases with high parasitic loads such as immunosuppressed Chagas disease patients and congenitally infected newborns, as well as in cases with low parasitemias, such as patients at the indeterminate phase or under etiological treatment. In this sense, the coefficients of variation of the Q-PCR measurements obtained from clinical samples were similar to those obtained from reconstituted blood samples (Table 4). When applied to newborns, infants and children with T. cruzi infection, Q-PCR estimated their basal parasitic loads in a vast range, between 0.01 and 640 p/mL of blood (Figure 3A). The highest parasitic loads observed in the younger pediatric population are in agreement with the results obtained by conventional parasitological and kDNA-PCR analysis [15],[26]. Moreover, the lower parasitic loads detected in the older pediatric patients reflect their evolution to the indeterminate phase of congenital infection [15]. Furthermore, we were able to follow-up their parasitological responses to treatment with benznidazole (Figure 3B) with a favorable outcome in 94.7% (36/38) cases. It is worth to note that at t3, under 30 days of tmt, 4 patients still showed detectable parasitic loads. At the end of tmt (t4) 2 of them became Q-PCR negative and remained negative during 18 months of post-tmt follow-up. This observation emphasizes the importance of a treatment regimen of 60 days. Interviews with the mothers of the two patients who persisted Q-PCR positive at t4 revealed the non-adherence in one of them (Pd2, Table 3 and Figure 3B, green triangle), whereas in the other case (Pd1, Table 3 and Figure 3B, red triangle) persistence of parasitemia indicated lack of parasitological response to benznidazole. These cases demonstrate the usefulness of the Q-PCR assay as surrogate marker for early detection of treatment failure. Two pediatric patients (Figure 3B, pink and yellow squares) presented an increase of their parasitic loads from t1 to t2, showing a favorable parasitological response to treatment in the samples collected at t3 and t4, fact that was confirmed by means of kDNA-PCR in the successive post-tmt controls (data not shown). The lower parasitic loads detected at t1, before initiation of tmt, compared with t2, might be due to natural fluctuations of the parasitemia in chronic Chagas disease patients [27]. In this context, it is important to analyze serial blood samples to be able to observe an increasing or decreasing tendency in the parasitic loads in chronic patients under treatment. The Q-PCR test was also used for early detection of T. cruzi reactivation after heart transplantation. This was visualized through the increment of the parasitic loads in all patients who presented clinical manifestations of reactivation [14]. In case Tx1, the patient is infected with T. cruzi I, and the number of parasites increased from 0.22 p/mL (5 days pre-Tx) to 9.07 p/mL (78 days post-Tx) when the patient presented signs and symptoms of skin reactivation and patent parasitemia [14]. In the other two tested cases, Tx2 and Tx3, who were infected with group II populations, the parasitic loads increments were notably higher (Table 3 and Figure 4). In Tx3, treatment with benznidazole after reactivation achieved transitory parasitological response because samples collected at 44 and 70 days after tmt were Q-PCR positive (Figure 4). Parasite relapse was confirmed by means of kDNA-PCR in successive samples until a second episode of clinical reactivation was diagnosed [14]. In Tx cases, the Q-PCR allowed to detect parasitic load increase, previous to diagnosis of reactivation, as well as to follow-up parasitological response during treatment with benznidazole. All together, the high analytical sensitivity of the Q-PCR strategy, the low levels of intra- and inter-assay variation, as well as the accuracy provided by the Lg-PCR correction, promotes this method as a key laboratory tool to follow-up patients under etiological treatment or at risk of clinical reactivation. This will be of particular significance for future drug trials in which an early assessment of efficacy or failure is mandatory [28].
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Ancestral Genomes, Sex, and the Population Structure of Trypanosoma cruzi
Introduction The parasite protozoan Trypanosoma cruzi causes Chagas disease, a malady that afflicts almost 20 million people in South America and Central America, with more than 20,000 deaths reported each year [1,2]. Two different ecosystems exist for T. cruzi: one related to wild hemiptera and generally involving wild mammals (the “sylvatic” cycle), and another dependent on home-dwelling hemiptera and primarily involving humans and household animals (the so-called “domestic” cycle). The connection between the two ecosystems is made by infected rats, mice, bats, marsupials, and other feral mammals. It is estimated that the parasite emerged as a species well over 150 million years ago, originally infecting primitive mammals dispersed throughout Laurasia and Gondwanaland, regions that originated North and South America, respectively [3]. The first contact with humans occurred much more recently, in the late Pleistocene, 15,000–20,000 years ago, when humans first peopled the Americas—thus, Homo sapiens is a very recent new host for T. cruzi. There is convincing molecular evidence for the presence of T. cruzi DNA in mummies exhumed in Northern Chile and Southern Peru and dating as far back as 9,000 years before the present day. [4]. The conventional mode of transmission of T. cruzi to humans is by the feces of infected hematophagous triatomine bugs. Alternative modes of infection include blood transfusion, congenital transmission from infected mothers, and ingestion of contaminated foods. Thanks to intensive programs of triatomine control, vectorial infection has been virtually abolished in Brazil, Chile, Uruguay, and Argentina [5]. Moreover, improved screening of blood donors to reduce the likelihood of transfusional transmission and early detection and treatment of congenital cases have added to this success. It would be, however, a mistake to think that Chagas disease has been controlled. High levels of vector-borne transmission are still apparent in many areas, and several of the endemic countries have yet to develop serious large-scale surveillance and intervention programs [5]. Also, migrations of infected individuals offer a risk of new transmission in previously nonendemic regions, such as the United States [6]. Furthermore, the ancient and wide-ranging sylvatic cycle constitutes an enormous reservoir of parasites that represents a threat for humans. Recent studies have shown that in a nonendemic area of the Brazilian Atlantic coastal rainforest 50% of the triatomine vectors and of the marsupials Didelphis marsupialis and Philander opossum [7] as well as 52% of the golden lion tamarins and several other species of New World primates [8] were naturally infected with T. cruzi. Moreover, in the United States T. cruzi has been found in 11.4% of opossums and 22% of the raccoons, together with infected triatomine bugs in the state of Georgia [9]. In certain areas of that state 43% of the raccoons were infected [10]. Closer to the human domestic environment, Bradley et al. [11] have shown that 3.6% of the rural hunting dogs in Oklahoma were seropositive for T. cruzi. Human infection from the sylvatic environment can occur either from sudden migration of hemiptera to the human environment, forced by the destruction of forests [12] or by the ingestion of foods contaminated by the feces of hemipterae or by crushed insects [13,14]. Thus, a complete understanding of the population structure of T. cruzi, especially the sylvatic cycle, will be indispensable for controlling the disease. T. cruzi is diploid, with different-sized homologous chromosome pairs [15]. Its genome has been recently sequenced [16], and its size (diploid) has been estimated between 106.4 and 110.7 Mb. At least 50% of the T. cruzi genome is made up of repetitive sequences, consisting of large gene families of surface proteins, retrotransposons, and subtelomeric repeats. There is extensive and well-characterized intraspecific genetic diversity in T. cruzi (reviewed in [17,18]). Two major evolutionary lineages of the parasite, named T. cruzi I and T. cruzi II, have been identified [19]. These lineages are very divergent as revealed by several biological and molecular markers, including isozymes, 24Sα rDNA, and mini-exon gene polymorphisms [20]. T. cruzi I and T. cruzi II strains belong predominantly to distinct ecological environments: respectively, the sylvatic and domestic transmission cycles of Chagas disease [3,21]. T. cruzi I strains are characterized by zymodeme Z1 (a zymodeme is a group of strains that have the same isozyme profile), 24Sα rDNA group 2, and mini-exon group 2, and induce low parasitism in human chagasic patients. In contrast, T. cruzi II strains are characterized by zymodeme Z2, 24Sα rDNA and mini-exon group 1, and cause human infections with high parasitemia in classic endemic areas [21]. At least in Brazil, T. cruzi II strains appear to be exclusively responsible for tissue lesions in Chagas disease [22]. Additionally, there are some parasite strains that cannot be properly grouped into any one of these two major lineages. Among these unclassified strains are those identified as belonging to zymodeme Z3 [23] and other hybrid strains characterized as rDNA group 1/2 [24,25]. Using isozymes and random amplified polymorphic DNA (RAPD) typing, Brisse et al. [26] proposed that T. cruzi II strains could be partitioned into five phylogenetic sublineages (IIa-e), each comprising one of the following reference strains: CanIII cl1 (IIa), Esmeraldo cl3 (IIb), M5631 cl5 (IIc), MN cl2 (IId), and CLBrener (IIe). In contrast, T. cruzi I strains could not be further subdivided. Within each of these clades or sublineages, there is extensive genetic diversity that can be unraveled by analyses with microsatellites and several other genomic markers (reviewed in [27]). Although capable of recombination in vitro [28], T. cruzi reproduces predominantly by binary fission and consequently its diploid nuclear genotype is transmitted en bloc to the progeny. Thus, the parasite presents extreme degrees of linkage disequilibrium, as shown through isozymes [29] and microsatellites [30], and exhibits a predominantly clonal population structure. Indeed, T. cruzi still has been considered the paradigm for clonal eukaryotic pathogenic microorganisms [31]. The occurrence of hybrid strains in natural populations of T. cruzi was suggested by isozyme analyses [32,33], restriction fragment-length polymorphism (RFLP) of housekeeping genes [34], RAPD [35], and genotype variations observed at chromosomal level [15,35,36], and has been confirmed using nucleotide sequences [37,38]. Their discovery proved that sexual events definitely have taken place in the past and have shaped the genetical structure of current T. cruzi populations. However, such genetic exchange events seem to have been rare enough to allow the propagation of clonal genotypes over long periods of time and wide geographical regions [35]. Because of the linkage disequilibrium, genotyping of nuclear markers in T. cruzi has thus far been limited to characterization of multilocus genotypes. Therefore, to understand the evolutionary history of the species it would be desirable to dissect the multilocus genotypes into their constituent haploid genome blocks. We wish to report that we have achieved this, revealing the existence of ancestral haplogroups and repeated hybridization events in T. cruzi. Results We have typed 75 strains of T. cruzi (Table 1) with five nuclear CA-repeat microsatellites (Table S1). We assumed a stepwise mutation model for the evolution of microsatellites and used the minimum number of mutational steps necessary to transform one strain microsatellite profile into another to build a genetic distance matrix. The multidimensional scaling (MDS) plot shown in Figure 1 provided, with excellent fit (stress = 0.08), a visual representation of the distance matrix. Four clusters are clearly visible and identified by ellipsoids in the MDS plot. The identity of the clusters is revealed by the presence of the prototypical strains of Brisse et al. [26]: MDS-cluster A corresponds to T. cruzi I, MDS-cluster C to T. cruzi IIb, MDS-cluster B to T. cruzi IIc, and MDS-cluster BH to the IId and IIe sublineages. Only three strains fell outside the four clusters: CanIII (sub-lineage IIa), Dog Theis, and 402. In 41 of the 75 strains we sequenced a 290–base pair region of the maxicircle-encoded cytochrome oxidase subunit II (COII) gene encompassing 44 variable positions (Figure 2). The sequenced data were used to generate a neighbor-joining (NJ) tree that is shown in Figure 3. It is clear that there are three tightly clustered sets of strains, separated by very large genetic distances, permitting straightforward allocation of T. cruzi strains into three mitochondrial clades that can also be simply identified by variation in just two AluI RFLP sites (Figure 2), which were then scored for all 75 strains (Table 2). Our MDS clusters corresponded perfectly to these mitochondrial clades, with the exceptions of MDS-clusters B (sublineage IIc) and BH (thus called because it contains the hybrid sublineages IId and IIe), both of which fall within mitochondrial clade B. To confirm our finding, we also built NJ trees for sequences obtained from GenBank of two other mitochondrial genes, cytochrome b (CYb) [35] and NADH dehydrogenase subunit 1 (ND1) [37]. The CYb and ND1 trees had very similar topology to that of the COII tree (all with extremely high bootstrap values for the three main branches), confirming that sublineages IIc, IId, and IIe indeed belong to the same mitochondrial clade (Figure 3). We tested this notion further using analysis of molecular variance [39]. By partitioning the variability within and between mitochondrial clades we found that for COII, CYb, and ND1, respectively, 97%, 91%, and 68% of the genetic variability was found among clades. We also typed all strains for the polymorphism of the D7 divergent domain of the 24Sα rRNA gene (Table S1) and combined the results with the microsatellites into multilocus genotypes that were analyzed with the PHASE software [40]. We identified 141 different haplotypes corresponding to a haplotypic diversity of 0.993. The identified haplotypes were then subjected to a median joining analysis using the NETWORK 3.1 software [41]. The resulting multitude of plausible trees is best expressed by a network that displays alternative potential evolutionary paths (Figure 4). Three haplotypic clusters are clearly identifiable: we called them haplogroups X, Y, and Z. Within these haplotypic clusters there is extensive reticulation because of the stepwise recurrent nature of microsatellite mutations [42]. However, the three haplogroups are connected by long and unique paths, emphasizing the great genetic distance between them. Seven haplotypes (numbers 33, 35, 58, 59, 60, 61, and 63) belong to these “bridges” and hence could not be assigned to any of the haplogroups—they were lumped into a haplogroup “I” (for indeterminate). We could then assign to each of the 75 strains a haplogroup genotype (Table 2). All strains belonging to the T. cruzi I lineage (MDS-cluster A in Figure 1) proved to be Z/Z (i.e., had two haplotypes belonging to haplogroup Z). Likewise, all the strains in MDS-cluster C (Figure 1) had Y/Y genotypes and those in MDS-cluster B had X/X genotypes. The strains in cluster BH all had X/Y genotypes confirming their hybrid nature. Strains Can III (genotype I/I, COII B), Dog Theis (genotype I/I, COII C), 402, and Mas1cl1 (both genotype I/Y, COII C), and M6241cl16 (genotype I/X, COII B) presented haplotypes of haplogroup I. It is noteworthy that three of these five strains are the ones outside MDS clusters in Figure 1A. Discussion The population structure of T. cruzi is far from being completely understood. Although the existence of two major lineages in this species is well accepted, uncertainties about the existence or not of a third major ancestral group have been raised [15,35,36]. For instance, strains belonging to zymodeme Z3 or to rDNA group 1/2 could not be classified into either T. cruzi I or T. cruzi II [19]. Likewise, other strains (such as SC43) that present incongruities between the rDNA (group 2) and mini-exon (group 1) typing cannot be allocated into any of the two major lineages [24]. One of the major goals of this work was to investigate the genetic relationships among these “unclassifiable” strains. Our first strategy was to perform the phylogenetic analysis of T. cruzi populations by using microsatellite data. Albeit extremely variable, these DNA markers allowed us to reliably identify four significant major clusters of strains (MDS clusters A, B, C, and BH in Figure 1). MDS-cluster A corresponds to T cruzi I and MDS-cluster C to classical T. cruzi II or T. cruzi IIb as named by Brisse et al. [26]. MDS-cluster B contains strains classified as Z3 and assigned to the IIc sublineage [26]. Finally, the strains within MDS-cluster BH were known to belong to the putative hybrid isozyme clonets 39 or 43 as proposed by Tibayrenc [43] and later classified as IId and IIe sublineages by Brisse et al. [26] (see Table 1). Nucleotide sequencing and AluI RFLP analysis of a 290-bp stretch of the mitochondrial COII gene demonstrated that all strains enclosed in our microsatellite clusters B and BH (Z3 and hybrid strains) belonged to the same mitochondrial clade B. Sequences of two other mitochondrial genes, CYb [35] and ND1 [37], obtained from GenBank, amply confirmed this observation by showing that indeed hybrid strains (sublineages IId and IIe) and Z3 strains (sublineage IIc) were grouped together into the same mitochondrial clade B. This same conclusion had been reached earlier [35,37]. Gaunt et al. [28] have shown that the hybridization of T. cruzi strains involves only nuclear genomes, without mitochondrial fusion. Here, we clearly demonstrated that the mitochondrial clade B is a third major phylogenetic division of T. cruzi, distinct from T. cruzi I (mitochondrial clade A) and T. cruzi II (mitochondrial clade C) major lineages. We have also shown that the strains with hybrid molecular markers in their nuclear genomes have a distinct mitochondrial genome (genotype B). The analyses with all studied nuclear markers identified 141 different haplotypes that could be clustered into three haplogroups. All strains belonging to the T. cruzi I major lineage (MDS-cluster A in Figure 1) proved to be Z/Z (i.e., had two haplotypes belonging to haplogroup Z). Likewise, all the strains in MDS-cluster C (Figure 1) had Y/Y genotypes and those in MDS-cluster B had X/X genotypes. Thus, our data do not corroborate the suggestion made by Sturm et al. [36] that sublineage IIc (MDS-cluster B) is a hybrid. In contrast, the strains in MDS-cluster BH all had X/Y genotypes, confirming their hybrid character. Because of the way that PHASE identifies haplotypes, proximity of haplotype numbers is highly correlated with genetic proximity. Hybrid strains 167, 1022, 182, CLBrener, and Tulacl2 have, respectively, genotypes 4/99, 2/102, 5/108, 5/100, and 3/103, forming one group, while strains MNcl2, NR, SC43cl1, and SO3 have genotypes 52/133, 55/130, 54/129, and 54/130, and form another (notice equivalence with sublineages IIe and IId of Brisse et al. [26]). This indicates that at least two independent hybridizations occurred, presumably followed by clonal microdifferentiation. Based on these results we propose the following minimal scenario for the evolution of T. cruzi populations (Figure 5). In the distant past there were at least three ancestral clades (MDS clusters A, C, and B in Figure 1) that we may call, respectively, T. cruzi I, T. cruzi II, and T. cruzi III. It is interesting to note that this proposal matches the initial suggestion made by Miles et al. [23] almost 30 years ago on the basis of isozyme studies. Most likely, T. cruzi II and T. cruzi III had overlapping ecological niches, and thus the conditions necessary for hybridization were in place. At least two hybridization events produced evolutionarily viable progeny. In both events, the cytoplasmic donor for the resulting offspring (as identified by the mitochondrial clade of the hybrid strains) was T. cruzi III. From the haplotype reconstitutions we can estimate the parentage of a hybrid strain. For instance, CLBrener, the reference strain for the recently completed T. cruzi genome sequencing [16], has genotype 5/100. Its most likely mitochondrial recipient was a strain proximate to 1005 (genotype 100/106), while the most likely mitochondrial donor was a close relative of strains 222 and 115, which are very near each other in Figure 1 (arrowheads). The existence of strains that cannot be accommodated into this scenario (i.e., CanIII [sublineage IIa of Brisse et al. [26]] and Dog Theis) indicates that the evolutionary history had additional complexities. However, our simple model (depicted in Figure 5) should be useful for proposing and testing evolutionary and pathogenetic hypotheses. The fact that the same population structure of T. cruzi can be envisaged with different molecular markers, such as isozymes [23], RAPD [26,35], microsatellites [30], and several sequence-based nuclear [20,21,37,38] and mitochondrial ([35,37], this study) markers, bears witness to its extreme stability. Although, as shown conclusively in our study and also by others [35,37], hybridization events clearly did occur in the evolutionary history of T. cruzi, they seem to have been only occasional and to have been subsequently stabilized by strong clonal propagation (reviewed in [17,18]). Materials and Methods T. cruzi isolates. T. cruzi stocks (75) isolated from both domestic and sylvatic transmission cycles were analyzed (Table 1). DNA from the parasites were kindly provided by Dr. Égler Chiari from the Departamento of Parasitologia, Universidade Federal de Minas Gerais (Belo Horizonte, Brazil); Dr. José Rodrigues Coura and Dr. Ana Maria Jansen-Franken, from the Departamento de Medicina Tropical and the Departamento de Protozoologia, Fundação Oswaldo Cruz (Rio de Janeiro, Brazil), respectively; and Dr. M. Tibayrenc from the Centre d'Études sur le Polymorphisme des Microorganismes (Montpellier, France). Nuclear genetic typing. Amplification of five previously described microsatellite loci, denominated SCLE10, SCLE11, MCLE01, MCLF10, and MCLG10, was performed as previously described [30]. After the PCR, the amplified microsatellites were loaded on a 6% denaturing polyacrylamide gel and analyzed on an ALF sequencer (GE Healthcare, Milwaukee, Wisconsin, United States) using the Allelinks software (GE Healthcare). To determine the allele size the samples were directly compared with the band sizes from an allelic ladder prepared by amplification of an artificial mixture of DNA from 60 T. cruzi strains. Amplification of the D7 divergent domain of the 24Sα rRNA gene was achieved by PCR with D71 fluorescent (5′-AAGGTGCGTCGACAGTGTGG-3′) and D72 (5′-TTTTCAGAATGGCCGAACAGT-3′) primers following protocols described previously [24]. The amplification products were also analyzed in ALF sequencer and allele sizes determined by the Allelinks software. Mitochondrial genetic typing. Amplification of the mitochondrial COII gene [37] was performed using the primers TcMit31 (5′-TAAATAATATATATTGTACATGAG-3′) and TcMit40 (5′-CTRCATTGYCCATATATTGT-3′). Total DNA (1–10 ng) were used in each PCR reaction in the following condition: 30 s denaturation at 94 °, primer annealing for 2 min at 48 °, and primer extension for 2 min at 72 °, in a total of 30 cycles. The amplified products were purified and sequenced using primer TcMit31 and the cycle sequencing with Thermo-Sequenase (ETKit; GE Healthcare) using the thermal cycling program recommended in the kit. The sequencing products were purified and run on a MegaBACE capillary sequencer (GE Healthcare). After Phred, Phrap, and Consed analyses, the sequences were trimmed to have equal length (290 base pairs). All bases sequenced had Phred values above 30 [44]. Based on the restriction map of COII sequences, the AluI restriction endonuclease was chosen to perform RFLP analyses in the mitochondrial COII gene. After PCR amplification, the amplicons were submitted to enzyme digestion for 16 hours according to instructions provided by the manufacturer (Promega, Madison, Wisconsin, United States). Digested products were analyzed on polyacrylamide gel electrophoresis and silver stained. Sequences for the mitochondrial CYb gene [35] and the ND1 (37) were obtained from GenBank. Construction of distance matrices, multidimensional scaling, and NJ trees. Based on the microsatellite results, a distance matrix between the strains was constructed as described previously [30]. In order to provide a visual representation of the distance matrix we used the multidimensional scaling plot using the software Statistica Version 6.0 [45]. Analyses of molecular variance for the mitochondrial sequences were performed using the Arlequin v.2.0 software using 1,000 permutations [46]. NJ trees were obtained separately for the COII, CYb, and ND1 sequences with the MEGA v. 3.1 software [47] using the Kimura 2 parameter and 500 replications for the bootstrap statistics. Haplotype inference and network construction. Haplotypes were reconstructed from the 75 T. cruzi populations by using a Bayesian coalescent theory-based method contained in PHASE software (Version 2.0.2 for Linux) [40]. The type of polymorphism (SNP or multiallelic with stepwise mutation mechanism for rDNA and microsatellite data, respectively) is taken into account in PHASE. For the analyses the default parameters of the program were used, with additional runs up to 10,000 permutations. These were the best-tested conditions, giving highly reproducible results. The resultant haplotypes were then arranged in a network by using the Median Joining analysis [41], available in NETWORK 3.1 software provided by Fluxus Technology (http://www.fluxus-engineering.com). Supporting Information Table S1 Typing of rDNA Group and Allele Sizes (in bp) of Five Microsatellite Loci (105 KB DOC) Click here for additional data file. Accession numbers The GenBank (http://www.ncbi.nlm.nih.gov/Genbank) accession numbers for the genes and gene products discussed in this paper are 24S rDNA (L19411), mini-exon gene (X62674), COII (AF359041 and DQ343715–DQ343753), CYb (AJ130921, AJ130931–AJ130938, AJ439719–AJ439727), and ND1 (AF359009, AF359011–AF359029, AF359031–AF359053).
Author and article information
Contributors
: Role: Editor
Journal
Journal ID (nlm-ta): PLoS Negl Trop Dis
Journal ID (publisher-id): plos
Journal ID (pmc): plosntds
Title:
PLoS Neglected Tropical Diseases
Publisher:
Public Library of Science
(San Francisco, USA
)
ISSN
(Print):
1935-2727
ISSN
(Electronic):
1935-2735
Publication date Collection:
January
2011
Publication date
(Electronic):
11
January
2011
Volume: 5
Issue: 1
Electronic Location Identifier: e931
Affiliations
[1
]Laboratorio de Biología Molecular de la Enfermedad de Chagas (LabMECh), Instituto
de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI-CONICET), Buenos
Aires, Argentina
[6
]Department of Parasitic Diseases, Centers for Disease Control, Atlanta, Georgia, United
States of America
[12
]Centro Universitario de Medicina Tropical, Facultad de Medicina, Universidad Mayor
de San Simon, Cochabamba, Bolivia
[13
]Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asunción,
Asunción del Paraguay, Paraguay
[15
]London School of Tropical Medicine and Hygiene Department of Clinical Parasitology,
Hospital for Tropical Diseases, London, United Kingdom
[18
]Centro de Investigaciones en Microbiología y Parasitología Tropical, Universidad de
los Andes, Bogotá, Colombia
[20
]Centro de Mahahonda, Centro Nacional de Microbiologia, Instituto de Salud Carlos III,
Madrid, España
[22
]Centro de Investigaciones Parasitológicas “J.F. Torrealba,” Universidad de los Andes,
Mérida, Venezuela
[23
]Instituto de Patologia Tropical e Saúde Pública (IPTSP), Universidade Federal de Goiás,
Goiânia, Brazil
[24
]Grupo de Inmunología y Epidemiología Molecular (GIEM), Facultad de Salud, Universidad
Industrial de Santander, Bucaramanga, Colombia
[25
]Departamento de Biomedicina de Enfermedades Infecciosas y Parasitarias Laboratorio
de Biología Celular, Centro de Investigaciones Regionales (CIR) “Dr Hideyo Noguchi,”
Universidad Autónoma de Yucatán, Yucatán, México
[26
]Instituto de Biomedicina, Universidad Católica de Santiago del Estero, Santiago del
Estero, Argentina
[27
]Centro Nacional de Diagnóstico e Investigación de Endemoepidemias (CeNDIE) ANLIS Dr.
Carlos G. Malbrán, Buenos Aires, Argentina
[28
]Laboratório de Biologia Molecular e Doenças Endêmicas, Instituto Oswaldo Cruz/FIOCRUZ,
Rio de Janeiro, Brazil
Author notes
* E-mail:
schijman@
123456dna.uba.ar
Conceived and designed the experiments: AGS MB LO MS TD FG SSE CB AL JL. Performed the experiments: MB TD AMMJ CC FA VV YQ SD GH IZ RHL EV TT ZSL LG DN MMR JEL JDR PZ MF MIJ GC CB. Analyzed the data: AGS MB LO MS TD AMMJ CC YQ SD GH IZ RHL EV TT ZSL LG DN MMR JEL JDR MF MIJ GC NA AMDC CIG KAV PY FT CR PD OTC CA GR PB AA FG AD CB AL. Contributed reagents/materials/analysis tools: AGS GH RHL AA AD AL JL. Wrote the paper: AGS MB LO MS TD SD CA PB CB AL. Organized and coordinated the multicentric study: AGS.
Article
Publisher ID: 10-PNTD-RA-1183R2DOI: 10.1371/journal.pntd.0000931
PMC ID: 3019106
PubMed ID: 21264349
SO-VID: 83a8c2ee-df8d-40e2-b50c-24b1afc875d6
Copyright © This is an open-access article distributed under the terms of the Creative Commons
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History
Date
received
: 20
May
2010
Date
accepted
: 1
December
2010
Page count
Pages: 13
Categories
Subject:
Research Article
Subject:
Infectious Diseases/Neglected Tropical Diseases
Subject:
Infectious Diseases/Protozoal Infections
Subject:
Microbiology/Parasitology
Subject:
Molecular Biology
ScienceOpen disciplines: Infectious disease & Microbiology
Data availability:
ScienceOpen disciplines: Infectious disease & Microbiology