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Epidemiological analysis of Leishmania tropica strains and giemsa-stained smears from Syrian and Turkish leishmaniasis patients using multilocus microsatellite typing (MLMT).

ABSTRACT: Turkey is located in an important geographical location, in terms of the epidemiology of vector-borne diseases, linking Asia and Europe. Cutaneous leishmaniasis (CL) is one of the endemic diseases in a Turkey and according to the Ministry Health of Turkey, 45% of CL patients originate from Şanlıurfa province located in southeastern Turkey. Herein, the epidemiological status of CL, caused by L. tropica, in Turkey was examined using multilocus microsatellite typing (MLMT) of strains obtained from Turkish and Syrian patients. A total of 38 cryopreserved strains and 20 Giemsa-stained smears were included in the present study. MLMT was performed using 12 highly specific microsatellite markers. Delta K (ΔK) calculation and Bayesian statistics were used to determine the population structure. Three main populations (POP A, B and C) were identified and further examination revealed the presence of three subpopulations for POP B and C. Combined analysis was performed using the data of previously typed L. tropica strains and Mediterranean and Şanlıurfa populations were identified. This finding suggests that the epidemiological status of L. tropica is more complicated than expected when compared to previous studies. A new population, comprised of Syrian L. tropica samples, was reported for the first time in Turkey, and the data presented here will provide new epidemiological information for further studies.

SUBMITTER: Karakus M

PROVIDER: S-EPMC5402985 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundLeishmaniases are divided into cutaneous (CL) and visceral leishmaniasis (VL). In the Old World, CL is caused by Leishmania (L.) major, L. tropica and L. aethiopica. L. tropica can also visceralize and cause VL. In India, the large epidemics of VL are caused by L. donovani and cases of CL are caused by L. major and L. tropica. However, strains of L. tropica have also been isolated from Indian cases of VL.This study was done to see if Indian strains of L. tropica isolated from human cases of CL are genetically identical to or different from Indian strains of L. tropica isolated from human cases of VL and to see if any genetic differences found correlated with clinical outcome presenting as either CL or VL.MethodsMultilocus microsatellite typing (MLMT), employing 12 independent genetic markers specific to L. tropica, was used to characterize and identify eight strains of L. tropica isolated from human cases of CL examined in clinics in Bikaner City, Rajasthan State, north-west India. Their microsatellite profiles were compared to those of 156 previously typed strains of L. tropica from various geographical locations that were isolated from human cases of CL and VL, hyraxes and sand fly vectors.ResultsBayesian, distance-based and factorial correspondence analyses revealed two confirmed populations: India/Asia and Israel/Palestine that subdivided, respectively, into two and three subpopulations. A third population, Africa/Galilee, as proposed by Bayesian analysis was not supported by the other applied methods. The strains of L. tropica from Bikaner isolated from human cases of CL fell into one of the subpopulations in the population India/Asia together with strains from other Asian foci. Indian strains isolated from human cases of VL fell into the same sub-population but were not genetically identical to the Bikaner strains of L. tropica.ConclusionsIt seems that the genetic diversity encountered between the two groups of Indian strains is mainly owing to their geographical origins rather than their different times of isolation. Also, the genetic differences seen between the dermatotropic and viscerotropic strains might be connected with the difference in pathogenicity.

Project description:BackgroundMalaria parasitemia is commonly used as a measurement of the amount of parasites in the patient's blood and a crucial indicator for the degree of infection. Manual evaluation of Giemsa-stained thin blood smears under the microscope is onerous, time consuming and subject to human error. Although automatic assessments can overcome some of these problems the available methods are currently limited by their inability to evaluate cases that deviate from a chosen "standard" model.ResultsIn this study reliable parasitemia counts were achieved even for sub-standard smear and image quality. The outcome was assessed through comparisons with manual evaluations of more than 200 sample smears and related to the complexity of cell overlaps. On average an estimation error of less than 1% with respect to the average of manually obtained parasitemia counts was achieved. In particular the results from the proposed approach are generally within one standard deviation of the counts provided by a comparison group of malariologists yielding a correlation of 0.97. Variations occur mainly for blurred out-of-focus imagery exhibiting larger degrees of cell overlaps in clusters of erythrocytes. The assessment was also carried out in terms of precision and recall and combined in the F-measure providing results generally in the range of 92% to 97% for a variety of smears. In this context the observed trade-off relation between precision and recall guaranteed stable results. Finally, relating the F-measure with the degree of cell overlaps, showed that up to 50% total cell overlap can be tolerated if the smear image is well-focused and the smear itself adequately stained.ConclusionThe automatic analysis has proven to be comparable with manual evaluations in terms of accuracy. Moreover, the test results have shown that the proposed comparison-based approach, by exploiting the interrelation between different images and color channels, has successfully overcome most of the inherent limitations possibly occurring during the sample preparation and image acquisition phase. Eventually, this can be seen as an opportunity for developing low-cost solutions for mass screening.

Project description:BackgroundCandida tropicalis is considered to be the leading pathogen causing nosocomial fungemia and hepatosplenic fungal infections in patients with cancer, particularly those with leukemia. Microsatellite-based typing methods using sets of genetic markers have been developed and reported for population structure analysis of C. albicans, C. glabrata, and C. parapsilosis, but no studies have been published for genetic analysis of C. tropicalis. The objective of this study was to develop new microsatellite loci that have the ability to distinguish among C. tropicalis isolates.ResultsDNA sequences containing over 10 bi- or tri-nucleotide repeats were selected from the C. tropicalis genome database. Thirty PCR primers sets specific for the microsatellite loci were designed and tested using eight clinically independent isolates. According to the amplification efficiency, specificity, and observed polymorphisms, eight markers were selected for further population structure analysis and molecular typing. Sixty-five independent C. tropicalis isolates were genotyped using these 8 markers. Based on these analyses, six microsatellite loci were confirmed, although two loci were found to be with unstable flanking areas. The six polymorphic loci displayed 4-22 alleles and 7-27 genotypes. The discriminatory power of the six loci ranged from 0.70 to 0.95. Genotyping results obtained by microsatellite analysis were compared to PCR-fingerprinting and multi-locus sequence typing (MLST). The comparisons showed that microsatellite analysis and MLST had the similar discriminatory power for C. tropicalis, which were more powerful than PCR-fingerprinting.ConclusionsThis is the first attempt to develop new microsatellite loci for C. tropicalis. These newly developed markers will be a valuable resource for the differentiation of C. tropicalis isolates. More C. tropicalis isolates will need to be sequenced and analyzed in order to fully show the potential of these newly developed microsatellite markers.

Project description:Leishmania infantum is the main etiological agent of both visceral and cutaneous clinical forms of leishmaniasis in the Mediterranean area. Leishmania/HIV coinfection in this area is characterized by a chronic course and frequent recurrences of clinical episodes. The present study using Multilocus Microsatellite Typing (MLMT) analysis, a highly discriminative tool, aimed to genetically characterize L. infantum isolates taken from monitored Leishmania/HIV coinfected patients presenting successive clinical episodes.In this study, by the analysis of 20 microsatellite loci, we studied the MLMT profiles of 25?L. infantum isolates from 8 Leishmania/HIV coinfected patients who had experienced several clinical episodes. Two to seven isolates per patient were taken before and after treatment, during clinical and non-clinical episodes, with time intervals of 6 days to 29 months. Genetic diversity, clustering and phenetic analyses were performed.MLMT enabled us to study the genetic characteristics of the 25?L. infantum isolates, differentiating 18 genotypes, corresponding to a genotypic diversity of 0.72. Fifteen genotypes were unique in the total sample set and only 3 were repeated, 2 of which were detected in different patients. Both clustering and phylogenetic analyses provided insights into the genetic links between the isolates; in five patients isolates showed clear genetic links: either the genotype was exactly the same or only slightly different. In contrast, the isolates of the other three patients were dispersed in different clusters and some could be the result of mixing between populations.Our data indicated a great MLMT variability between isolates from coinfected patients and no predominant genotype was observed. Despite this, almost all clinical episodes could be interpreted as a relapse rather than a reinfection. The results showed that diverse factors like an intrapatient evolution over time or culture bias could influence the parasite population detected in the patient, making it difficult to differentiate between relapse and reinfection.

Dataset Information

Epidemiological analysis of Leishmania tropica strains and giemsa-stained smears from Syrian and Turkish leishmaniasis patients using multilocus microsatellite typing (MLMT).

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