| Literature DB >> 27680169 |
Tülin Güven Gökmen1, Ayben Soyal2, Yıldız Kalayci2, Cansu Önlen2, Fatih Köksal2.
Abstract
Leptospirosis is still one of the most important health problems in developing countries located in humid tropical and subtropical regions. Human infections are generally caused by exposure to water, soil or food contaminated with the urine of infected wild and domestic animals such as rodents and dogs. The clinical course of leptospirosis is variable and may be difficult to distinguish from many other infectious diseases. The dark-field microscopy (DFM), serology and nucleic acid amplification techniques are used to diagnose leptospirosis, however, a distinctive standard reference method is still lacking. Therefore, in this study, we aimed to determine the presence of Leptospira spp., to differentiate the pathogenic L. interrogans and the non-pathogenic L. biflexa, and also to determine the sensitivity and specificity values of molecular methods as an alternative to conventional ones. A total of 133 serum samples, from 47 humans and 86 cattle were evaluated by two conventional tests: the Microagglutination Test (MAT) and the DFM, as well as three molecular methods, the 16S rRNA-PCR followed by Restriction Fragment Lenght Polymorphism (RFLP) of the amplification products 16S rRNA-PCR-RFLP, LipL32-PCR and OmpL1-PCR. In this study, for L. interrogans, the specificity and sensitivity rates of the 16S rRNA-PCR and the LipL32-PCR were considered similar (100% versus 98.25% and 100% versus 98.68%, respectively). The OmpL1-PCR was able to classify L. interrogans into two intergroups, but this PCR was less sensitive (87.01%) than the other two PCR methods. The 16S rRNA-PCR-RFLP could detect L. biflexa DNA, but LipL32-PCR and OmpL1-PCR could not. The 16S rRNA-PCR-RFLP provided an early and accurate diagnosis and was able to distinguish pathogenic and non-pathogenic Leptospira species, hence it may be used as an alternative method to the conventional gold standard techniques for the rapid disgnosis of leptospirosis.Entities:
Year: 2016 PMID: 27680169 PMCID: PMC5048635 DOI: 10.1590/S1678-9946201658064
Source DB: PubMed Journal: Rev Inst Med Trop Sao Paulo ISSN: 0036-4665 Impact factor: 1.846
Determination of Leptospira spp. and positive values over total samples (n = 133), according to the microagglutination test (MAT)
| Microaggltination Test (MAT) | ||
|---|---|---|
| Positive samples/Total | (%) | |
|
| 26/133 | 19.55 |
|
| 30/133 | 22.55 |
|
| 2/133 | 1.50 |
|
| 6/133 | 4.51 |
|
| 1/133 | 0.75 |
|
| 5/133 | 3.76 |
|
| 14/133 | 10.53 |
|
| 6/133 | 4.51 |
| TOTAL | 90/133 | 67.66 |
Fig.1(A) 16S rRNA-PCR products. Lane 6: 100 bp DNA ladder; Lane 1-10: 289 bp product. (B) 16S rRNA-PCR-RFLP products. Lane 5: 100 bp DNA ladder; Lane 1-2-4-6-8: RFLP with ApoI for L. interrogans (289 bp); Lane 3-7-9-10: RFLP with ApoI for reference L. biflexa (200 bp and 89 bp products). (C) LipL32-PCR products. Lane 7: 100 bp DNA ladder; Lane 1-12: 497 bp product. (D) OmpL1-PCR products. Lane 6: 100 bp DNA ladder; Lane 1-10: 406 bp product.
Positive values over total samples (133) according to the tested methods
| DFM * | MAT | 16S rRNA | LipL32 | OmpL1 | |
|
| 21/133 | 64/133 | 77/133 | 77/133 | 67/133 |
|
| 14/133 | 26/133 | 15/133 | - | - |
| TOTAL | 35/133 | 90/133 | 92/133 | 77/133 | 67/133 |
*Spirochetes determined by dark field microscopy (DFM) were identified and distinguished as serovars by the microagglutination test (MAT). 16S rRNA, LipL32 and OmpL32 are PCR techniques.
Sensitivity and specificity values of all the methods used in this study
| Positive samples | Sensitivity | 95% CI | Specificity | 95% CI* | PPV** | NPV*** | |
| DFM | 21 | 27.27% | 17.75-38.62 | 100% | 93.56-100 | 100% | 50% |
| MAT | 64 | 82.43% | 71.83-90.29 | 94.92% | 85.83-98.88 | 95.31% | 81.16% |
| 16S rRNA-PCR | 77 | 100% | 95.28-100 | 100% | 93.56-100 | 100% | 100% |
| LipL32-PCR | 77 | 98.68% | 92.86-99.78 | 98.25% | 90.57-99.71 | 98.68% | 98.25% |
| OmpL1-PCR | 67 | 87.01% | 77.41-93.58 | 100% | 93.56-100 | 100% | 84.85% |
*: Confidence interval, **: Positive Predictive Value, ***: Negative Predictive Value