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Leishmaniasis, Leishmania tropica, Leishmania major, Metabolomics, Proton magnetic resonance spectroscopy, What&,rsquo s Known Leishmania tropica and Leishmania major cause cutaneous leishmaniasis in Iran and many other countries. Metabolomics is a powerful tool to identify the metabolite profile and differentially expressed metabolites and can help gain further information on the metabolic pathways between species, the presentation of potential drug targets, and host-pathogen interactions. No data exist on comparative metabolomics between the Iranian clinical isolates of Leishmania tropica and Leishmania major. What&,rsquo s New Our data showed markedly different metabolic patterns and their biochemical pathways for Leishmania tropica and Leishmania major. Betaine metabolism, ammonia recycling, and the metabolism of methionine, asparagine, and aspartate were the most important metabolomic pathways between the two species. Significant metabolites confer greater insights into novel potential drug targets and how pathogens adapt to their hosts. IntroductionLeishmaniasis is a parasitic and vector-borne disease created by various Leishmania species (L. spp). Cutaneous leishmaniasis (CL) is regarded as a major public health concern in the Middle East, including Iran. 1, The Leishmania parasite has different two stages including infective metacyclic promastigote forms inside the sand fly midgut, which is transmitted during the blood feeding, by the bite of phlebotomine sand flies into a vertebrate (mammalian) host. In the vertebrate hosts, metacyclic promastigotes are rapidly swallowed by macrophages and converted to amastigotes. 2,, 3, CL is the most common form of leishmaniasis it is endemic in more than half of the provinces of Iran. 1,, 4, Leishmania tropica (L. tropica) and Leishmania major (L. major) cause CL in Iran they represent the two main forms of CL, anthroponotic (dry) CL and zoonotic (wet) CL, respectively. 1, The recent years have witnessed a rise in the number of CL cases in different parts of Iran. 1, &,ldquo Omics&,rdquo approaches, including proteomics and metabolomics, have gained much attention in the recent years. 3,, 5, Metabolomics is an instance of such modern technologies and is capable of detecting and quantifying metabolites in specific samples. Thus, it provides a global picture in time of the metabolic changes that occur during the course of a disease. 3, Metabolomics enjoys better dynamism than both genomics and proteomics, which enables to detect metabolic changes associated with different physiological sates in a shorter time frame. 6, There are multiple changes in biochemical and metabolite pathways in the different stages of L. spp, 3, including L. tropica and L. major, which are responsible for the creation of the two different clinical forms of cutaneous ulcer. A thorough understanding of these differences in the life cycle of the parasite and the identification of the metabolites related to these biochemical dissimilarities that play an important role not only in the prevention and treatment of leishmaniasis but also in the prediction of new potential drugs against it. For all the metabolomics-based studies performed on L. spp to assess their drug resistance mechanisms, metabolomics, and stage-specific metabolic profiling, 3,, 7, there is a dearth of data on comparative metabolomics between the Iranian clinical field isolates of the parasites. We, accordingly, performed the present study to identify differentially expressed metabolites between the Iranian isolates of L. major and L. tropica via the analytical platform of proton nuclear magnetic resonance (1H-NMR). Materials and MethodsPatients and Parasite Species IdentificationIranian clinical field isolates were obtained from the cutaneous lesions of seven patients infected with L. major and nine patients infected with L. tropica who referred to laboratories in Gonbad, Golestan Province, and Bam, Kerman Province, for parasitological diagnoses between 2017 and 2018. All the subjects were new cases, and had not been on medication. The study protocol was approved by the Ethics Committee of Shahid Beheshti University of Medical Sciences (Code No, IR.SBMU.REC.1398.086), and written informed consent was obtained from all the participants.Samples (smears) were prepared through sampling the border of the skin lesions of each case with clinically suspected CL. The samples were then stained with Giemsa stain and examined for the amastigote stage by light microscope (ZEISS, Germany). Positive skin scrapings were aseptically inoculated into tubes containing the Novy-MacNeal-Nicolle medium (NNN). The isolates were identified via the polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) technique, in which the internal transcribed-spacer-1 (ITS1) region of the parasites&,rsquo ribosomal-RNA gene was amplified, followed by the resulting amplicons digested by the HaeIII enzyme (Fermentas, Leon-Rot, Germany). PCR was conducted through the use of a forward primer (5&,rsquo -CTGGATCATTTTCCGATG-3&,rsquo ), and a reverse primer (5&,rsquo -TGATACCACTTATCGCACTT-3&,rsquo ). After the use of the restriction enzyme, the banding patterns of the isolates were obtained in comparison with the molecular profiles of the World Health Organization (WHO) reference strains of L. tropica (MHOM/IR/02/MHOM/R), and L. major (MRHO/IR/75/ER). Preparation of Metacyclic Promastigotes The promastigotes were initially grown on the NNN medium and for mass culture. The parasites were prepared in the RPMI 1640 medium (Gibco, Germany), supplemented with 10% (v/v) heat-inactivated fetal bovine serum (Gibco, Germany), and Pen-Strep (100 U/mL of penicillin and 100 &,mu g/mL of streptomycin Gibco, Germany) at 24 to 25 &,deg C. The promastigotes were cultured with repeated medium refreshment every three to five days until the number of parasites reached approximately 2&,times 107 cells/mL by Neubauer chamber counting (Marienfeld, Germany). The culture was incubated without adding the fresh medium for 10 (range=8&,ndash 12) days, and then the metacyclic promastigotes (the stationary phase) were evaluated using both the morphometric analysis and the agglutination assay by lectin. 8,, 9, The cell body size and flagellum lengths for 300 parasites in each day were measured, and the percentage of metacyclic forms was calculated. (The promastigotes whose flagellum/body length ratio was &,ge 2 were considered metacyclic forms, as described by da Silva and colleagues. 8, ) To ensure the collection of purified metacyclic promastigotes, we also performed the agglutination assay with peanut agglutinin (PNA) (Sigma, CA, USA). 9, Briefly, we added PNA to phosphate-buffered saline (PBS)-washed metacyclic promastigotes to a final concentration of 30 &,micro g/mL for 2&,times 107 cells/mL. After 30 minutes at room temperature, the separation of PNA- cells (metacyclic promastigotes) from PNA+ cells (procyclic promastigotes) was performed by centrifugation at 200 g for five minutes. The non-agglutinated metacyclic promastigotes were then harvested from the supernatants. Stationary phase L. major and L. tropica promastigotes were washed at least three successive times in sterile PBS (pH 7.4) to remove the culture medium compounds, and collected by centrifugation at 3500 g at 4 &,deg C for 20 minutes. The practical conditions and processes/steps for both parasite species examined were thoroughly identical.Cell Extraction and Proton Nuclear Magnetic Resonance (1H-NMR) SpectroscopyCell disruption and metabolite extraction were performed according to Gupta and others, 10, with slight modifications. Child 1.8 M perchloric acid, Merck, Germany, (800 &,mu L) was added to the cell suspension, and then each sample was vortexed and sonicated for five minutes at 4 &,deg C. The lysed cells were centrifuged at 12000g for 10 minutes at 4 &,deg C, and the pH of each supernatant was adjusted to 6.8 with potassium hydroxide (Merck, Germany). The supernatant was kept on ice for one hour to allow the precipitation of potassium perchlorate and centrifuged again as above. The lysate supernatant was transferred into new Eppendorf tubes (Sigma Aldrich, Germany). For 1H-NMR spectroscopy, D2O (20%) with trimethylsilyl propionate (TSP, 0.25 mM) (Sigma, CA, USA), as the NMR chemical shift reference (as an internal standard), was added to each sample, and mixed by vortexing. The samples were spun down at 12000g for 15 minutes at 4 &,deg C, and then 550 &,mu L of the supernatant was transferred into 5-mm NMR tubes (Sigma Aldrich, Germany). All the experiments were performed using a Bruker AVANCE 400 MHz (Bruker, Germany), equipped with a 5-mm probe at 298 K. The Carr-Purcell Meiboom-Gill (CPMG) spin-echo pulse sequencing was used to remove macromolecule signals. The water impact on the baseline was minimized by irradiating the water frequency during the relaxation delay of two seconds and a mixing time of 0.1 seconds. 1H-NMR spectra were acquired in 150 scans per sample, at 298 K, with an acquisition time of 3.0 seconds and a spectral width of 8389.26 Hz. Data Processing and Statistical AnalysisThe 1H-NMR spectra were processed using ProMatab in the MATLAB (version 7.8.0.347) environment, and necessary corrections were made on the spectra. The spectra were referenced to the TSP standard at 0.0 ppm. Chemical shifts between 0.2 and 10 ppm were normalized and subjected to spectral binning in 0.01 ppm. The spectral region affected by the water-related signal was removed in the range of 4.54 to 5.0 ppm. The 2D data matrix obtained from 1H-NMR was 16 at 813, comprising the number of the studied samples (nine samples of L. tropica and seven samples of L. major) and bins, respectively.Multivariate statistical analyses, including the unsupervised principal component analysis (PCA) and the supervised orthogonal projections to latent structures (OPLS) discriminant analysis, were applied to identify the most significant relevant metabolites between L. tropica and L. major. PCA was applied to detect similarities or trends in different samples, as well as to reveal the outliers and relationships that existed between the observations. The OPLS discriminant analysis was employed to maximize the covariance between the measured data and to compare the two classes of samples. The PCA and OPLS diagrams were plotted in the R software (Version 3.3.2). In each comparison, the variable influence in projection (VIP) was used to find the most significant discriminating metabolites. Metabolites with a VIP of greater than 1 and a P value of less than 0.05 were marked as significant variables. Metabolite Identification and Pathway AnalysisThe metabolites were identified using metabolite validated databases such as the Biological Magnetic Resonance Data Bank (BMRB)11 and the Human Metabolome Database (HMDB).12 Finally, the significantly changed metabolites were used to determine the most important pathway differences between the two L. spp. The pathway enrichment analysis was performed using the MetaboAnalyst server.13 MetaboAnalyst (www.metaboanalyst.ca,) is a web server for metabolomic data analysis and interpretation.ResultsDiagnosis of Parasite Species The PCR products of both positive specimens and standard strains with approximately 350 bp were digested by the HaeIII enzyme. The reference strain on agarose gel exhibited two bands (135 bp and 215 bp) that corresponded to L. major and two bands (57bp and 185bp) corresponded to L. tropica (figure 1,).Figure 1. Results of the restriction fragment length polymorphism patterns of ITS1-rDNA amplicons digestion with the HaeIII (BsuRI) enzyme for the Leishmania isolates are illustrated. Lane 1 and 2, Leishmania tropica sample Lane 3 and 4, Leishmania major sample Lane 5, standard strain of Leishmania major (MHOM/IR/75/ER) Lane 6, standard strain of Leishmania tropica (MHOM/IR/02/MHOM/R) Lane 7, marker 50 bpDiscrimination between L. major and L. tropica Using Multivariate AnalysisMultivariate analyses were performed on the result matrix to find metabolites, that mostly discriminated L. major from L. tropica. The values of the first two components in the PCA with the highest role in separating the two groups (L. major and L. tropica) in in vitro conditions were 92.9% (PC1) and 4% (PC2) (figure 2,). The score plot based on the PCA analysis showed that the two groups were well-separated based on the first two dimensions of the analysis. Additionally, all the data were within the 95% confidence interval, and no outlier data were observed. The OPLS discriminant analysis is a supervised method for finding a combination based on existing variables with the most variance between the groups. The OPLS discriminant analysis separated L. major and L. tropica clusters, which is visualized in score plots in figure 3,.Figure 2. Scatter score plot of the principal component analysis displays the discrimination between the Iranian isolates of Leishmania major (&,#9675 ) and Leishmania tropica (&,#8710 ). Principal component 1 (Dim1) and principal component 2 (Dim2) explain 92.9% and 4.0% of the total variance, respectively. Figure 3. Leishmania tropicaThe OPLS model is validated by R2 (coefficient of determination) and Q2 (cross-validated R2), which was performed in the present study via the seven-fold cross-validation measure. All the models had Q2 values of greater than 0.4 with the intercept of less than zero, which demonstrated that the models were validated. The R2X, R2Y, Q2Y, and RMSE values of the OPLS model were 0.983, 0.595, 0.566, and 0.355, respectively (figure 3,), which demonstrated the model&,rsquo s good predictive ability.Metabolite Identification of Two Leishmania Species and Pathway AnalysisThe differentially expressed metabolites were determined among the metacyclic promastigotes of the Iranian isolates of L. major and L. tropica, and the spectral bins of the highest importance according to VIP values were selected. Twenty-four significantly differentially expressed metabolites were identified among the metacyclic promastigotes of the L. major and L. tropica samples (P&,le 0.0152). The details of the metabolite alterations that reached statistical significance are indicated in table 1,.Metabolite*HMDB IDKEGG IDbinVIPP valueL.t/ L.m3-hydroxybutyrateHMDB0000357C010894.1752.090.0050.79PhosphoserineHMDB0000272C010054.1652.050.0050.822L-prolineHMDB0000162C001484.1252.030.0060.801kynurenineHMDB0000684C003284.1451.990.0050.813LactateHMDB0000190C001864.1051.860.0050.838CholineHMDB0000097C001144.0551.850.0050.89CreatinineHMDB0000562C007914.0451.670.0041.35GalactoseHMDB0000143C001244.0851.650.0041.515TryptophanHMDB0000929C000784.0351.590.0041.7HistidineHMDB0000177C001353.9851.550.0040.88AsparagineHMDB0000168C001523.9951.550.0050.75PhenylalanineHMDB0000159C000793.9751.520.0030.91TyrosineHMDB0000158C000823.9351.500.0020.88L-serineHMDB0000187C000653.9551.500.0041.5HippurateHMDB0000714C015863.9451.490.0031.965PantothenateHMDB0000210C008643.9651.450.0041.45BetaineHMDB0000043C007193.8951.450.0022.87CreatineHMDB0000064C003003.9151.360.0012.35MannoseHMDB0000169C001593.9251.300.0012. 216AspartateHMDB0000191C000493.8851.300.0023.48MethionineHMDB0000696C000733.8551.220.0023.45HomocitrullineHMDB0000679C024273.7251.200.0151.3LeucineHMDB0000687C001233.7151.180.0100.8AcetylcarnitineHMDB0000201C025713.8451.010.0022.85 HMDB, Human Metabolome Database KEEG, Kyoto Encyclopedia of Genes and Genomes VIP, Variable importance in projection L.m, Leishmania major L.t, Leishmania tropica *Independent t-test were applied and Metabolites with VIP values of more than 1 and P values of less than 0.05 were considered significant |