Using FT-IR spectroscopy for the identification of the T. cruzi, T. rangeli, and the L. chagasi species

Aguiar, Josafá Carvalho; Mittmann, Josane; Júnior, P.C. Caetano; Raniero, Leandro

doi:10.1016/j.exppara.2018.07.008

Cited by 5 publications

(7 citation statements)

References 42 publications

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“…There are only a small number of studies that have applied infrared spectroscopy to investigate Leishmania parasites. One study focused on differentiating different Leishmania species. , Aguiar et al applied FTIR as a tool to investigate the promastigotes of Leishmania amazonensis, Leishmania chagasi, and L. major species.…”

Section: Introductionmentioning

confidence: 99%

“…One study focused on differentiating different Leishmania species. 33,34 36 In this study, for the first time, we are incorporating the synchrotron infrared spectroscopic approach to characterize isolated promastigotes, amastigotes along with infected and uninfected macrophages. To date no spectroscopic studies investigating biochemical fingerprints of the intra and extra cellular Leishmania parasitic forms have been performed.…”

Section: ■ Introductionmentioning

confidence: 99%

“…major, Leishmania tropica, Leishmania infantum, and Leishmania donovani) by means of variance-based principal component analysis and distance-based hierarchical cluster analysis . By exploiting Gaussian curve fitting and multivariate statistical analysis approaches, Aguiar et al were able to spectroscopically differentiate Trypanosoma rangeli and Trypanosoma cruzi from Leishmania chagasi parasites . However, none of those studies characterized the intracellular Leishmania form (i.e., amastigote) and the infected and uninfected macrophages.…”

Section: Introductionmentioning

confidence: 99%

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Synchrotron-Infrared Microspectroscopy of Live Leishmania major Infected Macrophages and Isolated Promastigotes and Amastigotes

et al. 2023

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The prevalence of neglected tropical diseases (NTDs) is advancing at an alarming rate. The NTD leishmaniasis is now endemic in over 90 tropical and sub-tropical low socioeconomic countries. Current diagnosis for this disease involves serological assessment of infected tissue by either light microscopy, antibody tests, or culturing with in vitro or in vivo animal inoculation. Furthermore, co-infection by other pathogens can make it difficult to accurately determine Leishmania infection with light microscopy. Herein, for the first time, we demonstrate the potential of combining synchrotron Fouriertransform infrared (FTIR) microspectroscopy with powerful discrimination tools, such as partial least squares-discriminant analysis (PLS-DA), support vector machine-discriminant analysis (SVM-DA), and k-nearest neighbors (KNN), to characterize the parasitic forms of Leishmania major both isolated and within infected macrophages. For measurements performed on functional infected and uninfected macrophages in physiological solutions, the sensitivities from PLS-DA, SVM-DA, and KNN classification methods were found to be 0.923, 0.981, and 0.989, while the specificities were 0.897, 1.00, and 0.975, respectively. Cross-validated PLS-DA models on live amastigotes and promastigotes showed a sensitivity and specificity of 0.98 in the lipid region, while a specificity and sensitivity of 1.00 was achieved in the fingerprint region. The study demonstrates the potential of the FTIR technique to identify unique diagnostic bands and utilize them to generate machine learning models to predict Leishmania infection. For the first time, we examine the potential of infrared spectroscopy to study the molecular structure of parasitic forms in their native aqueous functional state, laying the groundwork for future clinical studies using more portable devices.

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Section: Introductionmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Synchrotron-Infrared Microspectroscopy of Live Leishmania major Infected Macrophages and Isolated Promastigotes and Amastigotes

et al. 2023

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“…Studies based on molecular spectroscopy diagnosis related to the Trypanosomatidae family are limited to an investigation of L. chagasi (sin. = L. infantum), Trigonoscuta cruzi, and T. rangeli strain discrimination [29], and Phlebotomine sandflies specimen's classification based on FTIR spectroscopy [30]. This is the first report about canine blood serum evaluated by FTIR spectroscopy and machine learning algorithms for the Leishmania infection diagnosis.…”

Section: Introductionmentioning

confidence: 99%

A new strategy for canine visceral leishmaniasis diagnosis based on FTIR spectroscopy and machine learning

Larios

Ribeiro

Arruda

et al. 2021

Journal of Biophotonics

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“…Studies based on molecular spectroscopy diagnosis related to Trypanosomatidae family are limited to an investigation of L. chagasi (sin.=L. infantum), T. cruzi and T. rangeli strain discrimination (29), and Phlebotomine sand ies specimen's classi cation based on FTIR spectroscopy (30). This is the rst report about canine blood serum evaluated by FTIR spectroscopy and machine learning algorithms for the Leishmania infection diagnosis.…”

Section: Introductionmentioning

confidence: 99%

A New Strategy for Canine Visceral Leishmaniasis Diagnosis Based on Molecular Spectroscopy and Machine Learning

Larios

Ribeiro

Arruda

et al. 2021

Preprint

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Visceral leishmaniasis is a neglected disease caused by protozoan parasites of the genus Leishmania. The successful control of the disease depends on its accurate and early diagnosis, which is usually made by combining clinical symptoms with laboratory tests such as serological, parasitological, and molecular tests. However, early diagnosis based on serological tests may exhibit low accuracy due to lack of specificity caused by cross-reactivities with other pathogens, and sensitivity issues related, among other reasons, to disease stage, leading to misdiagnosis. In this work was investigated the use of mid-infrared spectroscopy and multivariate analysis to perform a fast, accurate and easy canine visceral leishmaniasis diagnosis. Canine blood sera of non-infected, Leishmania infantum, and Trypanosoma evansi infected groups were studied. The data demonstrate that principal component analysis with machine learning algorithms achieved an overall accuracy above 85% in the diagnosis.

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Using FT-IR spectroscopy for the identification of the T. cruzi, T. rangeli, and the L. chagasi species

Cited by 5 publications

References 42 publications

Synchrotron-Infrared Microspectroscopy of Live Leishmania major Infected Macrophages and Isolated Promastigotes and Amastigotes

Synchrotron-Infrared Microspectroscopy of Live Leishmania major Infected Macrophages and Isolated Promastigotes and Amastigotes

A new strategy for canine visceral leishmaniasis diagnosis based on FTIR spectroscopy and machine learning

A New Strategy for Canine Visceral Leishmaniasis Diagnosis Based on Molecular Spectroscopy and Machine Learning

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