The most common spoligotype of Mycobacterium bovis isolated in the world and the recommended loci for VNTR typing; A systematic review

Ghavidel, Mahdis; Mansury, Davood; Nourian, Kimiya; Ghazvini, Kiarash

doi:10.1016/j.micpath.2018.03.036

Cited by 34 publications

(39 citation statements)

References 44 publications

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“…To get more insights into the geographical ranges of the different M. bovis clades, we used the spoligotype patterns inferred from the WGS data and searched for references describing the prevalence of those in different regions of the world (Table S3). Patterns SB0120 and SB0134, known as “BCG-like” and reported to be relatively prevalent [9], as well as SB0944, are phylogenetically uninformative; SB0120 is present in several clades probably by common ancestry given that it contains the spacers deleted in most other spoligotypes and SB0134 and SB0944 have evolved independently in two different M. bovis populations (Fig. 2, Table S3).…”

Section: Resultsmentioning

confidence: 99%

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An African origin forMycobacterium bovis

Loiseau

Menardo

Aseffa

et al. 2019

Preprint

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Lay Summary: Mycobacterium bovis and M. caprae are both the most important agents 37 of tuberculosis in livestock and zoonotic tuberculosis in humans. Using phylogenetic and 38 molecular clock inferences based on an extensive collection of whole-genome sequences 39 we provide new insights into the global population structure, phylogeography and 40 evolutionary history of these pathogens. 41 42 Word count abstract: 180 43 Word count main text: 4366 44 Number of Figures: 3 45 46 ABSTRACT 47 48 Background and objectives 49 Mycobacterium bovis and Mycobacterium caprae are the two most important agents of 50 tuberculosis (TB) in livestock and the most important causes of zoonotic TB in humans. 51However, little is known about the global population structure, phylogeography and 52 evolutionary history of these pathogens. 53 Methodology 54We compiled a global collection of 3364 whole-genome sequences from M. bovis and M. 55 caprae originating from 35 countries and inferred their phylogenetic relationships, geographic 56 origins and age. 57 Results 58Our results resolve the phylogenetic relationship among the four previously defined clonal 59 complexes of M. bovis, and another eight newly described here. Our inferences indicate that 60 M. bovis emerged in East Africa likely between the 4 th and 10 th century. While some M. bovis 61 groups remained restricted to East-and West Africa, others have subsequently dispersed to 62 different parts of the world. 63 Conclusions and implications 64Our results allow a better understanding of the global population structure of M. bovis and its 65 evolutionary history. This knowledge can be used to define better molecular markers for 66 epidemiological investigations in settings where whole genome sequencing cannot easily be 67 implemented. 68 69 70 BACKGROUND AND OBJECTIVES 71 Tuberculosis (TB) remains an important burden for global health and the economy [1]. TB is 72 the number one cause of human death due to infection globally, with an estimated 10.0 73 million new cases and 1.6 million deaths occurring every year [1]. TB is caused by members 74 of the Mycobacterium tuberculosis complex (MTBC), which includes seven human-adapted 75 lineages, and several animal-adapted ecotypes including M. bovis and M. caprae. Animal TB 76 complicates the control of human TB due to the zoonotic transfer of TB bacilli from infected 77 animals to exposed human populations through e.g. the consumption of unpasteurized milk or 78 handling of contaminated meat [2]. M. bovis and M. caprae are the most important agents of 79 TB in livestock and the most important agents of zoonotic TB in humans, causing at least 147 80 000 new human cases and 12 500 deaths yearly [1, 3]. Zoonotic TB caused by M. bovis also 81 poses a challenge for patient treatment, due to its natural resistance to pyrazinamide (PZA), 82 one of the four first-line drugs used in the treatment of TB. In addition, TB in livestock 83 accounts for an estimated loss of three billion US dollars per year [4]. In Africa its prevalence 84 is highes...

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Section: Resultsmentioning

confidence: 99%

“…Current knowledge about global M. bovis populations stems mostly from spoligotyping [8, 9]. This method has been highly valuable for showing that M. bovis populations vary by geography, and defining strain families based on the presence or absence of spacers in the Direct Repeat region of the MTBC genome [8].…”

Section: Background and Objectivesmentioning

confidence: 99%

An African origin forMycobacterium bovis

Loiseau

Menardo

Aseffa

et al. 2019

Preprint

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“…Additionally, a recent publication by Ghavidel, Mansury, Nourian, and Ghazvini (2018) combined spoligotyping data of bovine isolates from different geographic locations and evaluated the most common spoligotype signature in each continent (Ghavidel et al, 2018). The most predominant were spoligotype SB0120, found in Asia (Iran), Europe (France and Italy) and Africa (Zambia and Algeria); spoligotype SB0121 in Europe (Spain, Portugal), Africa (Algeria) and America (Mexico and Brazil); and SB0140 in Asia (China), Europe (Ireland) and America (Mexico).…”

Section: Drivers Of Animal Tb Heterogeneitymentioning

confidence: 99%

“…The most predominant were spoligotype SB0120, found in Asia (Iran), Europe (France and Italy) and Africa (Zambia and Algeria); spoligotype SB0121 in Europe (Spain, Portugal), Africa (Algeria) and America (Mexico and Brazil); and SB0140 in Asia (China), Europe (Ireland) and America (Mexico). Spoligotype SB0121 isolates belong to Eu2 clonal complex, SB0140 to Eu1, and SB0120 to BCG‐like (Ghavidel et al, 2018). Also, a group of strains enclosed in the F4 family, defined by a specific spoligotype and MIRU‐VNTR profile, has been found mainly in southern France (Hauer et al, 2015).…”

Section: Drivers Of Animal Tb Heterogeneitymentioning

confidence: 99%

“…As described up above, the heterogeneity of the causative agents of animal TB is highly dependent on their genetic heterogeneity, introduced by SNPs, IS regions and RDs. These, along with clustering by WGS, spoligotyping and MIRU‐VNTR, are now starting to be related to host range, geographical distribution and differential virulence (Garbaccio et al, 2014; Ghavidel et al, 2018; Hauer et al, 2015, 2019; Zimpel et al, 2019). So, although many descriptive molecular epidemiology studies have been performed so far, a more complex understanding of the connection between genetic markers and their phenotypical consequence needs to be developed, as it may greatly help epidemiological tracking, the prognosis of disease outcome and transmission risk prediction.…”

Section: Drivers Of Animal Tb Heterogeneitymentioning

confidence: 99%

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Animal tuberculosis: impact of disease heterogeneity in transmission, diagnosis, and control

Pereira

Reis

Ramos

et al. 2020

Transbound Emerg Dis

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Animal tuberculosis (TB) in terrestrial mammals is mainly caused by Mycobacterium bovis. This pathogen is adapted to a wide range of host species, representing a threat to livestock, wildlife and human health. Disease heterogeneity is a hallmark of multi‐host TB and a challenge for control. Drivers of animal TB heterogeneity are very diverse and may act at the level of the causative agent, the host species, the interface between mycobacteria and the host, community of hosts, the environment and even policy behind control programmes. In this paper, we examine the drivers that seem to contribute to this phenomenon. We begin by reviewing evidence accumulated to date supporting the consensus that a complex range of genetic, biological and socio‐environmental factors contribute to the establishment and maintenance of animal TB, setting the grounds for heterogeneity. We then highlight the complex interplay between individual, species‐specific and community protective factors with risk/maintenance variables that include animal movements and densities, co‐infection and super‐shedders. We finally consider how current interventions should seek to consider and explore heterogeneity in order to tackle potential limitations for diagnosis and control programmes, simultaneously increasing their efficacy.

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