| Literature DB >> 36080480 |
Alba L Montoya1, Elisa G Carvajal1, Uriel Ortega-Rodriguez2, Igor L Estevao2, Roger A Ashmus1, Sohan R Jankuru1, Susana Portillo2, Cameron C Ellis2, Colin D Knight2, Julio Alonso-Padilla3,4, Luis Izquierdo3,4, Maria-Jesus Pinazo3,4,5, Joaquim Gascon3,4,5, Veronica Suarez2, Douglas M Watts2, Iliana R Malo6, Janine M Ramsey6, Belkisyolé Alarcón De Noya7, Oscar Noya8, Igor C Almeida2, Katja Michael1.
Abstract
Chagas disease (CD) is caused by the parasite Trypanosoma cruzi and affects 6-7 million people worldwide. The diagnosis is still challenging, due to extensive parasite diversity encompassing seven genotypes (TcI-VI and Tcbat) with diverse ecoepidemiological, biological, and pathological traits. Chemotherapeutic intervention is usually effective but associated with severe adverse events. The development of safer, more effective therapies is hampered by the lack of biomarker(s) (BMKs) for the early assessment of therapeutic outcomes. The mammal-dwelling trypomastigote parasite stage expresses glycosylphosphatidylinositol-anchored mucins (tGPI-MUC), whose O-glycans are mostly branched with terminal, nonreducing α-galactopyranosyl (α-Gal) glycotopes. These are absent in humans, and thus highly immunogenic and inducers of specific CD anti-α-Gal antibodies. In search for α-Gal-based BMKs, here we describe the synthesis of neoglycoprotein NGP11b, comprised of a carrier protein decorated with the branched trisaccharide Galα(1,2)[Galα(1,6)]Galβ. By chemiluminescent immunoassay using sera/plasma from chronic CD (CCD) patients from Venezuela and Mexico and healthy controls, NGP11b exhibited sensitivity and specificity similar to that of tGPI-MUC from genotype TcI, predominant in those countries. Preliminary evaluation of CCD patients subjected to chemotherapy showed a significant reduction in anti-α-Gal antibody reactivity to NGP11b. Our data indicated that NGP11b is a potential BMK for diagnosis and treatment assessment in CCD patients.Entities:
Keywords: Chagas disease; Trypanosoma cruzi; anti-α-Gal antibodies; biomarker; chemotherapy; oligosaccharide synthesis; α-Gal-containing neoglycoprotein
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Year: 2022 PMID: 36080480 PMCID: PMC9457857 DOI: 10.3390/molecules27175714
Source DB: PubMed Journal: Molecules ISSN: 1420-3049 Impact factor: 4.927
Figure 1(A) Synthesis of the trisaccharide 3-thiopropyl α-D-galactosyl-(1,2)-[α-D-galactosyl-(1,6)]-β-D-galactoside (G11) and its conjugation with maleimide-derivatized BSA to afford NGP11b. (a) TMSOTf, DCM; (b) HF-pyr, THF; (c) DCM, TFA, H2O; (d) AcSH, AIBN, THF, UV light (350 nm); (e) NaOMe, MeOH; (f) TCEP-HCl, pH 7.2. (B) Overlaid MALDI-TOF mass spectra of singly charged molecular ions of BSA ([BSA + H]+), maleimide-BSA ([Mal-BSA + H]+), and NGP11b ([NGP11b + H]+) are indicated. GU, glycan unit; m/z, mass to charge ratio.
Figure 2Serological evaluation of NGP11b, TcI tGPI-MUC, and TcII tGPI-MUC by CL-ELISA. (A) Cross-titration of varying concentrations (50, 25, 12.5, 6.2, 3.1, and 1.6 ng/well) of synthetic NGP11b (top panel), and purified TcI tGPI-MUC (from Colombiana strain, 40-2 ng/well) (middle panel) and TcII tGPI-MUC (from Y strain, 40–2.5 ng/well) (bottom panel) at 1:400 and 1:800 serum dilutions. The CCD serum pool (CCDSP) (n = 10) was obtained from CCD patients from Venezuela. The normal human serum pool (NHSP) (n = 10) was obtained from healthy donors from the U.S.A. (B) CL-ELISA titers of sera (at 1:800 dilution) of individual CCD patients (n = 58), from Venezuela (n = 42) and Mexico (n = 16), and umbilical cord plasma (at 1:400 dilution) samples of healthy individuals, negative control (NC) (n = 27) from the U.S.A. to NGP11b, TcI tGPI-MUC, and TcII tGPI-MUC. Serum samples from Mexico (Mex) with a confirmed CD diagnosis by positive PCR (+PCR), and from Venezuela (Ven) with a confirmed CD diagnosis by positive conventional serology (+CS), are indicated by different symbols. Green line, cutoff value (CL-ELISA titer = 1.000), calculated as described in Materials and Methods. (C) ROC curves for NGP11b, TcI tGPI-MUC, and TcII tGPI-MUC comparing the reactivity of sera from CCD patients vs. healthy individuals, using the data depicted in the truncated violin scatterplot (B). Statistical analysis: Kruskal–Wallis test with Dunn’s multiple comparison test with Geisser–Greenhouse correction. * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. The area under the curve (AUC) (gray area) and its value are indicated. The 95% confidence interval (CI) values are shown in brackets. (D) CL-ELISA titers of CCD patients before treatment (day 0) and after treatment (24 months) with the standard of care of benznidazole (150 mg twice a day, for 60 days). Statistical analysis: mixed-effects model with Geisser–Greenhouse correction. * p < 0.05; ** p < 0.01; *** p < 0.001.
Immunoreactivity of sera of CCD patients and plasma of negative controls with TcI tGPI-MUC, TcII tGPI-MUC, and NGP11b.
| Disease/Control |
| NGP11b | TcI tGPI-MUC | TcII tGPI-MUC | |||
|---|---|---|---|---|---|---|---|
| Positive | Negative | Positive | Negative | Positive | Negative | ||
| Chronic Chagas disease | 58 | 55 (95.8%) | 3 (5.2%) | 51 (87.9%) | 7 (12.1%) | 32 (55.2%) | 26 (44.8%) |
| Healthy control a | 27 | 0 | 27 (100%) | 0 | 27 (100%) | 0 | 27 (100%) |
a Plasma from umbilical cord samples with negative real-time PCR and non-conventional serology (with nine in-house T. cruzi antigens) for CCD.
Sensitivity, specificity, and other diagnostic parameters of NGP11b, TcI tGPI-MUC, and TcII tGPI-MUC, in the comparison of CCD vs. healthy individuals.
| Parameter a,b | NGP11b | TcI tGPI-MUC | TcII tGPI-MUC |
|---|---|---|---|
|
| |||
| Sensitivity | 94.8 | 87.9 | 55.2 |
| Specificity | 100.0 | 100.0 | 100.0 |
| FPR | 0.0 | 0.0 | 0.0 |
| PPV | 100.0 | 100.0 | 100.0 |
| NPV | 90.0 | 79.4 | 50.9 |
| Accuracy | 96.6 | 92.4 | 76.6 |
a Calculated based on CCD (n = 58) and NC (n = 27) immunoreactivity with NGP11b, TcI tGPI-MUC, and TcII tGPI-MUC (Figure 2B). b Sensitivity = [true positive (TP)/TP + false negative (FN)] × 100. Specificity = [true negative (TN)/TN + false positive (FP)] × 100. False-positive rate (FPR) = 100 − specificity. Positive predictive value (PPV) = TP/TP + FP. Negative predictive value (NPV) = TN/TN + FN; Accuracy = (TN + TP)/(TN + TP + FN + FP).