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Updated: May 29, 2026
Identification of Mycobacterium Species by DNA Microarray Chip Method
Published on: June 24, 2025
Effectiveness of combination of Mini-and Microsatellite loci to sub-type Mycobacterium avium subsp. paratuberculosis
Matteo Ricchi1, Gianluca Barbieri, Roberta Taddei
1Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna, National Reference Centre for Paratuberculosis, Strada Faggiola 1, 29027 Gariga di Podenzano, Piacenza, Italy. matteo.ricchi@izsler.it
Background:
Mycobacterium avium subsp. paratuberculosis (Map) is the etiological agent of paratuberculosis. The aim of our study was to combine Mini-and Microsatellite loci analysis in order to explore the effectiveness of this sub-typing method in a group of Map isolates. For this purpose, 84 Italian Type C Map isolates, each from a different cattle herd, were submitted to MIRU-Variable-Number Tandem-Repeats (VNTRs) typing and Short Sequence repeats (SSRs) sequencing. Moreover, the method was used to analyse the variability inside 10 herds (from three to 50 isolates per herd).
Results:
The molecular sub-typing, carried out using three SSR and 10 MIRU-VNTR loci, differentiated the 84 isolates into 33 clusters, reaching a Simpson's Discriminatory Index (SID) value of 0.952 (0.933 to 0.972, 95% confidence intervals). Among all considered loci, six (SSR2, MIRU2, SSR1, SSR8, VNTR3527 and VNTR1067) showed relevant allelic variability. Thirty-eight% of the isolates were clustered into four genotypes, differing from each other for the SSR2 locus. The other isolates, characterised by differences in two or more loci, were spread among the rest of the clusters. The intra-herd analysis revealed more than one genotype in most herds with a similar distribution of clusters.
Conclusions:
Our results revealed the advantage of using both Mini-and Microsatellite approaches for successfully discriminating among Map Type C isolates from the same geographic area, host species and herd. These data suggest that the combination of loci here proposed could be a useful molecular tool for regional epidemiological studies.
