from low endemic settings where the difference between clustered
and unclustered is often a bimodal distribution of SNP distances
and therefore easy to separate. Further research is required to
determine whether these cutoffs are applicable to settings in
which TB is endemic [166, 195].
Genomic epidemiology has also been used to study the historic
spread of M. tuberculosis, including dating its emergence from
Africa [196, 197], its appearance in mummies [198, 199], and
multihost transmission of animal variants such as M. tuberculosis
variant bovis [200, 201]. Dating such events requires the combination of genomic information and Bayesian phylogenetic analyses,
termed phylodynamics. These approaches also allow for additional
epidemiological parameters to be estimated, such as the population
size of the bacterium in a given outbreak [202, 203], the molecular
clock [204] (number of mutations accumulated on average per
year), and even the basic reproductive number [205]. Additionally,
Bayesian approaches can begin to estimate transmission trees,
including how many unsampled cases and missed transmission
links were present in a population [206], and to replace hard-line
SNP cutoffs for transmission clustering, which in turn can provide
better guidance to public health initiatives.
For other mycobacteria, genomic epidemiology at the level of
between-host transmission is more complex, primarily because the
mode of transmission of the more common pathogens
(M. ulcerans, M. leprae, M. avium, and M. abscessus) is not fully
known. WGS data have primarily been used for within-host population dynamics, source tracking, or ruling out human to human
transmission in many of these pathogens [207–211]. It has also
been used to look at more long-term or historic epidemiology, such
as spread between countries or continents, using phylodynamics to
determine the date of introduction into different settings [212–
214]. However, WGS-based molecular epidemiology of NTMs is
still in its infancy compared to M. tuberculosis and requires much
more concerted effort to establish transmission routes and transmission clustering criteria.
6 Conclusion
The advent of whole-genome sequencing and its steadily declining
price have allowed the biological world to be examined at both
previously unprecedented breadth and depth. The slow growth rate
for mycobacteria makes WGS an extremely valuable molecular tool
for their identification and characterization. Finally, WGS provides
an unequivocal and reproducible way for mycobacteriologists to
identify and characterize mycobacteria.
444
Marco A. Riojas et al.
and unclustered is often a bimodal distribution of SNP distances
and therefore easy to separate. Further research is required to
determine whether these cutoffs are applicable to settings in
which TB is endemic [166, 195].
Genomic epidemiology has also been used to study the historic
spread of M. tuberculosis, including dating its emergence from
Africa [196, 197], its appearance in mummies [198, 199], and
multihost transmission of animal variants such as M. tuberculosis
variant bovis [200, 201]. Dating such events requires the combination of genomic information and Bayesian phylogenetic analyses,
termed phylodynamics. These approaches also allow for additional
epidemiological parameters to be estimated, such as the population
size of the bacterium in a given outbreak [202, 203], the molecular
clock [204] (number of mutations accumulated on average per
year), and even the basic reproductive number [205]. Additionally,
Bayesian approaches can begin to estimate transmission trees,
including how many unsampled cases and missed transmission
links were present in a population [206], and to replace hard-line
SNP cutoffs for transmission clustering, which in turn can provide
better guidance to public health initiatives.
For other mycobacteria, genomic epidemiology at the level of
between-host transmission is more complex, primarily because the
mode of transmission of the more common pathogens
(M. ulcerans, M. leprae, M. avium, and M. abscessus) is not fully
known. WGS data have primarily been used for within-host population dynamics, source tracking, or ruling out human to human
transmission in many of these pathogens [207–211]. It has also
been used to look at more long-term or historic epidemiology, such
as spread between countries or continents, using phylodynamics to
determine the date of introduction into different settings [212–
214]. However, WGS-based molecular epidemiology of NTMs is
still in its infancy compared to M. tuberculosis and requires much
more concerted effort to establish transmission routes and transmission clustering criteria.
6 Conclusion
The advent of whole-genome sequencing and its steadily declining
price have allowed the biological world to be examined at both
previously unprecedented breadth and depth. The slow growth rate
for mycobacteria makes WGS an extremely valuable molecular tool
for their identification and characterization. Finally, WGS provides
an unequivocal and reproducible way for mycobacteriologists to
identify and characterize mycobacteria.
444
Marco A. Riojas et al.