New approach for serological testing for leptospirosis by using detection of leptospira agglutination by flow...

Leptospirosis is considered an important reemerging infectious disease worldwide. The standard and most widespread method for the diagnosis of leptospirosis is the microscopic agglutination test (MAT). This test is laborious and time-consuming, and the interpretation of the results is subjective. In the present work we describe an application of flow cytometry (FCM) as a tool for the serological diagnosis of leptospirosis. The analysis is based on the sensitivity of FCM to the size and shape of the bacteria analyzed by measurement of light scatter parameters: forward scatter (FSC) and side scatter (SSC). The addition of positive serum to an infecting leptospiral serovar results in a shift of the light scatter parameter to a different location with higher FSC and SSC values, indicating the formation of leptospiral aggregates. By using immunofluorescent staining, we have shown that the large particles formed are the agglutinated leptospires. Quantification of the agglutination process has been achieved by calculating an agglutination factor (Af), based on changes in the light scatter parameters measured by FCM. Af enables us to determine the specificity of the serological reaction of the patient serum with each leptospiral serovar. In this work, 27 serum samples from 18 leptospirosis patients were tested by both the MAT and the FCM techniques, in which each serum sample was tested against 13 serovars. Twenty-six human serum samples derived from patients with a variety of other defined illnesses were used as negative controls and enabled us to define the Af threshold value as < 9.3 for negative patients, while any value higher than that would be a positive result for leptospirosis. Compared to MAT, the FCM technique was found to be more specific and sensitive, especially in identifying the serogroup in the acute phase of the disease. The whole process was found to be rapid and took less than 1.5 h. Moreover, FCM analysis is objective and can be automated for the handling of large numbers of samples.