antibiotics and toxic compounds), Subsystem Name (e.g., Arsenic
resistance), and the functional role of each of the included genes.
Clicking on the subsystems tab for any genome provides three
different views. The Subsystems Overview shows a pie chart that
displays the percent of the genes that are in a particular Superclass.
The Subsystems tab includes the number of genes found in a
particular Superclass. The Genes tab includes a list of all the genes
across all the subsystems. Subsystem information is not only available for individual genomes but also summed for each taxonomic
level, all the way up to Superkingdom using the NCBI taxonomy
[142]. A heatmap view showing the presence and absence of specific proteins per selected subsystem across a taxon or a specific
genome group is also available.
5.2 M. tuberculosis
Molecular Markers
(SITVITWEB)
Epidemiological studies of tuberculosis rely on genetic markers.
Traditionally, most studies done for tuberculosis were performed
using IS6110-RFLP, a labor-intensive technique that has been
replaced by newer PCR-based assays. Using mainly two of these
techniques, large genotyping databases have been developed. These
techniques are spoligotyping and mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR)
[143]. Spoligotypes are patterns displaying the presence/absence
of 43 spacers in the direct repeat (DR) locus, and these can be
represented as 43 digits or under a reduced octal form of only
15 numbers. MIRU-VNTR are represented as a variable number
of repeats present [144]. Both techniques yield genotypes that are
relatively easy to achieve and digitize, allowing the creation of
databases useful in enabling the epidemiological correlation of
clinical isolates at a global scale. SITVIT2 (http://www.pasteurguadeloupe.fr:8081/SITVIT2/) is a database that contains the
genotypes of more than 100,000 M. tuberculosis isolates, which
also provides epidemiologic, demographic, and genetic data and
allows an exhaustive overview of worldwide distribution of
M. tuberculosis complex [145, 146]. When available, the genotyping data are also analyzed as a function of bacterial drug resistance
and demographic, clinical, and geographical characteristics [147].
SITVIT2 also provides SpoTyping, a tool that analyzes and
determines the spoligotype from the WGS. This allows researchers
to identify their lineage and compare them with isolates at a global
scale [147, 148].
5.3 Antimicrobial
Resistance
Antimicrobial resistance (AMR) is widely recognized as one of the
most serious threats to public health across the globe
[149, 150]. However, WGS holds significant promise as a tool to
help combat AMR. WGS can allow us to develop new antimicrobial
drugs, improve surveillance, research AMR emergence, develop
new diagnostic tests, detect AMR in clinical environments, and
440
Marco A. Riojas et al.
resistance), and the functional role of each of the included genes.
Clicking on the subsystems tab for any genome provides three
different views. The Subsystems Overview shows a pie chart that
displays the percent of the genes that are in a particular Superclass.
The Subsystems tab includes the number of genes found in a
particular Superclass. The Genes tab includes a list of all the genes
across all the subsystems. Subsystem information is not only available for individual genomes but also summed for each taxonomic
level, all the way up to Superkingdom using the NCBI taxonomy
[142]. A heatmap view showing the presence and absence of specific proteins per selected subsystem across a taxon or a specific
genome group is also available.
5.2 M. tuberculosis
Molecular Markers
(SITVITWEB)
Epidemiological studies of tuberculosis rely on genetic markers.
Traditionally, most studies done for tuberculosis were performed
using IS6110-RFLP, a labor-intensive technique that has been
replaced by newer PCR-based assays. Using mainly two of these
techniques, large genotyping databases have been developed. These
techniques are spoligotyping and mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR)
[143]. Spoligotypes are patterns displaying the presence/absence
of 43 spacers in the direct repeat (DR) locus, and these can be
represented as 43 digits or under a reduced octal form of only
15 numbers. MIRU-VNTR are represented as a variable number
of repeats present [144]. Both techniques yield genotypes that are
relatively easy to achieve and digitize, allowing the creation of
databases useful in enabling the epidemiological correlation of
clinical isolates at a global scale. SITVIT2 (http://www.pasteurguadeloupe.fr:8081/SITVIT2/) is a database that contains the
genotypes of more than 100,000 M. tuberculosis isolates, which
also provides epidemiologic, demographic, and genetic data and
allows an exhaustive overview of worldwide distribution of
M. tuberculosis complex [145, 146]. When available, the genotyping data are also analyzed as a function of bacterial drug resistance
and demographic, clinical, and geographical characteristics [147].
SITVIT2 also provides SpoTyping, a tool that analyzes and
determines the spoligotype from the WGS. This allows researchers
to identify their lineage and compare them with isolates at a global
scale [147, 148].
5.3 Antimicrobial
Resistance
Antimicrobial resistance (AMR) is widely recognized as one of the
most serious threats to public health across the globe
[149, 150]. However, WGS holds significant promise as a tool to
help combat AMR. WGS can allow us to develop new antimicrobial
drugs, improve surveillance, research AMR emergence, develop
new diagnostic tests, detect AMR in clinical environments, and
440
Marco A. Riojas et al.