TY - JOUR
T1 - Genetic Characterization of Brucella spp.
T2 - Whole Genome Sequencing-Based Approach for the Determination of Multiple Locus Variable Number Tandem Repeat Profiles
AU - Pelerito, Ana
AU - Nunes, Alexandra
AU - Grilo, Teresa
AU - Isidro, Joana
AU - Silva, Catarina
AU - Ferreira, Ana Cristina
AU - Valdezate, Sylvia
AU - Núncio, Maria Sofia
AU - Georgi, Enrico
AU - Gomes, João Paulo
N1 - Publisher Copyright:
Copyright © 2021 Pelerito, Nunes, Grilo, Isidro, Silva, Ferreira, Valdezate, Núncio, Georgi and Gomes.
PY - 2021/11/12
Y1 - 2021/11/12
N2 - Brucellosis is an important zoonosis that is emerging in some regions of the world, gaining increased relevance with the inclusion of the causing agent Brucella spp. in the class B bioterrorism group. Until now, multi-locus VNTR Analysis (MLVA) based on 16 loci has been considered as the gold standard for Brucella typing. However, this methodology is laborious, and, with the rampant release of Brucella genomes, the transition from the traditional MLVA to whole genome sequencing (WGS)-based typing is on course. Nevertheless, in order to avoid a disruptive transition with the loss of massive genetic data obtained throughout the last decade and considering that the transition timings will vary considerably among different countries, it is important to determine WGS-based MLVA alleles of the nowadays sequenced genomes. On this regard, we aimed to evaluate the performance of a Python script that had been previously developed for the rapid in silico extraction of the MLVA alleles, by comparing it to the PCR-based MLVA procedure over 83 strains from different Brucella species. The WGS-based MLVA approach detected 95.3% of all possible 1,328 hits (83 strains×16 loci) and showed an agreement rate with the PCR-based MLVA procedure of 96.4% for MLVA-16. According to our dataset, we suggest the use of a minimal depth of coverage of ~50x and a maximum number of ~200 contigs as guiding “boundaries” for the future application of the script. In conclusion, the evaluated script seems to be a very useful and robust tool for the in silico determination of MLVA profiles of Brucella strains, allowing retrospective and prospective molecular epidemiological studies, which are important for maintaining an active epidemiological surveillance of brucellosis.
AB - Brucellosis is an important zoonosis that is emerging in some regions of the world, gaining increased relevance with the inclusion of the causing agent Brucella spp. in the class B bioterrorism group. Until now, multi-locus VNTR Analysis (MLVA) based on 16 loci has been considered as the gold standard for Brucella typing. However, this methodology is laborious, and, with the rampant release of Brucella genomes, the transition from the traditional MLVA to whole genome sequencing (WGS)-based typing is on course. Nevertheless, in order to avoid a disruptive transition with the loss of massive genetic data obtained throughout the last decade and considering that the transition timings will vary considerably among different countries, it is important to determine WGS-based MLVA alleles of the nowadays sequenced genomes. On this regard, we aimed to evaluate the performance of a Python script that had been previously developed for the rapid in silico extraction of the MLVA alleles, by comparing it to the PCR-based MLVA procedure over 83 strains from different Brucella species. The WGS-based MLVA approach detected 95.3% of all possible 1,328 hits (83 strains×16 loci) and showed an agreement rate with the PCR-based MLVA procedure of 96.4% for MLVA-16. According to our dataset, we suggest the use of a minimal depth of coverage of ~50x and a maximum number of ~200 contigs as guiding “boundaries” for the future application of the script. In conclusion, the evaluated script seems to be a very useful and robust tool for the in silico determination of MLVA profiles of Brucella strains, allowing retrospective and prospective molecular epidemiological studies, which are important for maintaining an active epidemiological surveillance of brucellosis.
KW - Brucellaspp
KW - MLVA
KW - Python script
KW - genotyping
KW - whole-genome sequencing
KW - zoonosis
UR - http://www.scopus.com/inward/record.url?scp=85120423297&partnerID=8YFLogxK
U2 - 10.3389/fmicb.2021.740068
DO - 10.3389/fmicb.2021.740068
M3 - Article
AN - SCOPUS:85120423297
SN - 1664-302X
VL - 12
JO - Frontiers in Microbiology
JF - Frontiers in Microbiology
M1 - 740068
ER -