Analytical Performance of a Multiplex Real-Time PCR Assay Using TaqMan Probes for Quantification of Trypanosoma cruzi Satellite DNA in Blood Samples

Background: The analytical validation of sensitive, accurate and standardized Real-Time PCR methods for Trypanosoma cruzi quantification is crucial to provide a reliable laboratory tool for diagnosis of recent infections as well as for monitoring treatment efficacy. Methods/Principal Findings: We have standardized and validated a multiplex Real-Time quantitative PCR assay (qPCR) based on TaqMan technology, aiming to quantify T. cruzi satellite DNA as well as an internal amplification control (IAC) in a single-tube reaction. IAC amplification allows rule out false negative PCR results due to inhibitory substances or loss of DNA during sample processing. The assay has a limit of detection (LOD) of 0.70 parasite equivalents/mL and a limit of quantification (LOQ) of 1.53 parasite equivalents/mL starting from non-boiled Guanidine EDTA blood spiked with T. cruzi CLBrener stock. The method was evaluated with blood samples collected from Chagas disease patients experiencing different clinical stages and epidemiological scenarios: 1- Sixteen Venezuelan patients from an outbreak of oral transmission, 2- Sixty three Bolivian patients suffering chronic Chagas disease, 3- Thirty four Argentinean cases with chronic Chagas disease, 4- Twenty seven newborns to seropositive mothers, 5- A seronegative receptor who got infected after transplantation with a cadaveric kidney explanted from an infected subject. Conclusions/Significance: The performing parameters of this assay encourage its application to early assessment of T. cruzi infection in cases in which serological methods are not informative, such as recent infections by oral contamination or congenital transmission or after transplantation with organs from seropositive donors, as well as for monitoring Chagas disease patients under etiological treatment.Fil: Duffy, Tomas. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones En Ingeniería Genética y Biología Molecular; ArgentinaFil: Cura, Carolina Inés. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular; ArgentinaFil: Ramírez, Juan C.. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular; ArgentinaFil: Abate, Teresa. Universidad Central de Venezuela. Instituto de Medicina Tropical; VenezuelaFil: Cayo, Nelly M.. Universidad Nacional de Jujuy. Instituto de Biologia de la Altura; ArgentinaFil: Parrado, Rudy. Universidad San Simón; BoliviaFil: Diaz Bello, Zoraida. Universidad Central de Venezuela. Instituto de Medicina Tropical; VenezuelaFil: Velazquez, Elsa Beatriz. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorio e Instituto de Salud. Instituto Nacional de Parasitología; ArgentinaFil: Muñoz Calderón, Arturo. Universidad Central de Venezuela. Instituto de Medicina Tropical; VenezuelaFil: Juiz, Natalia Anahí. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular; ArgentinaFil: Basile, Joaquín. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular; ArgentinaFil: Garcia, Lineth. Universidad San Simón; BoliviaFil: Riarte, Adelina. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorio e Instituto de Salud. Instituto Nacional de Parasitología; ArgentinaFil: Nasser, Julio Rubén. Universidad Nacional de Salta. Facultad de Ciencias Naturales; ArgentinaFil: Ocampo, Susana B.. Universidad Nacional de Jujuy. Instituto de Biologia de la Altura; ArgentinaFil: Yadon, Zaida E.. Pan-American Health Organization; Estados UnidosFil: Torrico, Faustino. Universidad San Simón; BoliviaFil: Alarcón de Noya, Belkisyole. Universidad Central de Venezuela. Instituto de Medicina Tropical; VenezuelaFil: Ribeiro, Isabela. Drugs and Neglected Diseases Initiative; SuizaFil: Schijman, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular; Argentin

Multiplex Real-Time PCR Assay Using TaqMan Probes for the Identification of Trypanosoma cruzi DTUs in Biological and Clinical Samples

Background: Trypanosoma cruzi has been classified into six Discrete Typing Units (DTUs), designated as TcI–TcVI. In order to effectively use this standardized nomenclature, a reproducible genotyping strategy is imperative. Several typing schemes have been developed with variable levels of complexity, selectivity and analytical sensitivity. Most of them can be only applied to cultured stocks. In this context, we aimed to develop a multiplex Real-Time PCR method to identify the six T. cruzi DTUs using TaqMan probes (MTq-PCR).Methods/Principal Findings: The MTq-PCR has been evaluated in 39 cultured stocks and 307 biological samples from vectors, reservoirs and patients from different geographical regions and transmission cycles in comparison with a multi-locus conventional PCR algorithm. The MTq-PCR was inclusive for laboratory stocks and natural isolates and sensitive for direct typing of different biological samples from vectors, reservoirs and patients with acute, congenital infection or Chagas reactivation. The first round SL-IR MTq-PCR detected 1 fg DNA/reaction tube of TcI, TcII and TcIII and 1 pg DNA/reaction tube of TcIV, TcV and TcVI reference strains. The MTq-PCR was able to characterize DTUs in 83% of triatomine and 96% of reservoir samples that had been typed by conventional PCR methods. Regarding clinical samples, 100% of those derived from acute infected patients, 62.5% from congenitally infected children and 50% from patients with clinical reactivation could be genotyped. Sensitivity for direct typing of blood samples from chronic Chagas disease patients (32.8% from asymptomatic and 22.2% from symptomatic patients) and mixed infections was lower than that of the conventional PCR algorithm.Conclusions/Significance: Typing is resolved after a single or a second round of Real-Time PCR, depending on the DTU. This format reduces carryover contamination and is amenable to quantification, automation and kit production.This work received financial support from the Ministry of Science and Technology of Argentina [PICT 2011-0207 to AGS] and the National Scientific and Technical Research Council in Argentina (CONICET) [PIP 112 2011-010-0974 to AGS]. Work related to evaluation of biological samples was partially sponsored by the Pan-American Health Organization (PAHO) [Small Grants Program PAHO-TDR]; the Drugs and Neglected Diseases Initiative (DNDi, Geneva, Switzerland), Wellcome Trust (London, United Kingdom), SANOFI-AVENTIS (Buenos Aires, Argentina) and the National Council for Science and Technology in Mexico (CONACYT) [FONSEC 161405 to JMR]

Human Polymorphisms in Placentally Expressed Genes and Their Association With Susceptibility to Congenital Trypanosoma cruzi Infection

Background. It is currently unclear why only a proportion of children born to Trypanosoma cruzi?infected mothers acquire the infection. We have examined the association of 11 single-nucleotide polymorphisms (SNPs) located in genes coding for placental expression enzymes as genetic markers of susceptibility to congenital T. cruzi infection (hereafter, ?congenital infection?): rs2014683and rs1048988 in ALPP; rs11244787 and rs1871054 in ADAM12; rs243866, rs243865, rs17859821, rs243864, and rs2285053 in MMP2; and rs3918242 and rs2234681 in MMP9.Methods. Two groups of children born to mothers seropositive for T. cruzi were compared: 101 had congenital infection, and 116 were uninfected. Novel high-resolution melting and capillary electrophoresis genotyping techniques were designed and used.Results. Logistic regression analysis showed that mutations in rs11244787 and rs1871054 (in ADAM12) and rs243866, rs17859821, and rs2285053 (in MMP2) were associated with susceptibility to congenital infection. Multifactor dimensionality reduction revealed that genotyping results for rs11244787, rs1871054, rs243866, rs17859821 and rs243864 sites would be a good predictorof congenital infection.Conclusions. Our results suggest an important role of human polymorphisms in proteins involved in extracellular matrix remodeling and the immune response during congenital infection. To our knowledge, this is the first study demonstrating the association between mutations in placentally expressed genes and susceptibility to congenital infection.Fil: Juiz, Natalia Anahí. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular ; ArgentinaFil: Cayo, Nelly M.. Universidad Nacional de Jujuy. Instituto de Biología de la Altura; ArgentinaFil: Burgos, Marianela. Hospital Nacional Prof. Alejandro Posadas; ArgentinaFil: Salvo, Miriam E.. Hospital Nacional Prof. Alejandro Posadas; ArgentinaFil: Nasser, Julio Rubén. Universidad Nacional de Salta; ArgentinaFil: Bua, Jacqueline Elena. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorio e Instituto de Salud “Dr. C. G. Malbrán”. Instituto Nacional de Parasitología ; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Longhi, Silvia Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular ; ArgentinaFil: Schijman, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular ; Argentin

Follow-up of <i>T. cruzi</i> infected patients using qPCR.

<p>A. Follow-up of orally infected cases from Chacao, Caracas, Venezuela. Years pos-treatment (ys pos-T) are represented in the <i>x</i>-axis. Parasite equivalents (par. eq.) were estimated using a Silvio X-10 (TcI) calibration curve. Case 1- Pre-T: 5.23 log₁₀ par. eq./10 mL; 2 ys pos-T: 1.88 log₁₀ par. eq./10 mL. Case 2- Pre-T: 3.78 log₁₀ par. eq./10 mL; 2 ys pos-T: 1.83 log₁₀ par. eq./10 mL. Case 3- Pre-T: 2.94 log₁₀ par. eq./10 mL; 2 ys pos-T: 1.88 log₁₀ par. eq./10 mL. B. A 42 year-old seronegative man received kidney transplantation from a seropositive cadaveric donor. Progression of parasitic load after transplantation is shown as well as post-treatment follow-up. The quantification was estimated using a Cl-Brener (TcVI) calibration curve. Days pos-Transplantation (Tx) are represented in the <i>x</i>-axis. The number of par. eq./10 mL of blood is represented in the <i>y-</i>axis, in a log-scale. Arrow marks initiation of Benznidazole treatment. ND: not detectable. The line indicates LOQ (1.185 log₁₀ par. eq./10 mL) derived from analysis of CL-Brener (TcVI) spiked samples. Discontinued line: parasitic loads in Chacao patients were estimated with Silvio X-10 (TcI) calibration curves.</p

Parasitic loads in Chagas disease clinical groups.

<p>CD: Chagas disease; Cong: Congenital; Pos: Positivity; Per: Percentile; par. eq./10 mL: parasite equivalents in 10 mL of blood.</p>a<p>Three out of 27 newborns to seropositive mothers were diagnosed as congenitally infected by means of conventional diagnosis.</p

Estimation of Precision of the qPCR assay.

<p>S_r: estimate of repeatability standard deviation (within-run precision); B: standard deviation of the daily means; N: number of replicate analyses per run; S_t: estimate of within-device or within-laboratory precision standard deviations (S_t = [B²+(N−1)/N*S_r²]^1/2); CV: coefficient of variation; log₁₀ par. eq./10 mL: logarithmic values of parasite equivalents in 10 mL of blood.</p

Estimation of IAC amplification in blood specimens from different clinical groups.

a<p>Sample PCC 331: qPCR positive, 0.69 log₁₀ par. eq./mL, IAC Ct 19.20.</p><p>Nb: Newborn; UCB, umbilical cord blood; PB: peripheral blood.</p

Anticipated reportable range and linearity of qPCR method.

<p>Multiplex TaqMan qPCR strategy was carried out with spiked GEB samples containing parasite stocks belonging to TcI and TcVI in ten concentrations spanning 10⁶ to 0.625 par. eq./10 mL, tested in triplicate. Assigned values were plotted on the <i>x</i> axis versus measured values (converted to log₁₀) on the <i>y</i> axis using SigmaPlot 10.0 for Windows (SPSS, Chicago, IL). Linear regression analysis rendered the equation y = 1.013x+0.058 (R² = 0.992) for TcI, and y = 1.001x+0.005 (R² = 0.998) for TcVI.</p