Universal genotyping reveals province-level differences in the molecular epidemiology of tuberculosis
Universal genotyping reveals province-level differences in the molecular epidemiology of tuberculosis
Jennifer L. GuthrieID 0 1
Alex Marchand-Austin 1
Kirby Cronin 1
Karen Lam 1
Daria Pyskir 1
Clare Kong 1
Danielle Jorgensen 1
Mabel Rodrigues 1
David Roth 1
Patrick Tang 1
Victoria J. Cook 1
James Johnston 1
Frances B. Jamieson 1
Jennifer L. Gardy 0 1
0 School of Population and Public Health, University of British Columbia , Vancouver , Canada , 2 Public Health Ontario , Toronto , Canada , 3 National Microbiology Laboratory, Public Health Agency of Canada , Winnipeg , Canada , 4 British Columbia Centre for Disease Control, Public Health Laboratory , Vancouver , Canada , 5 British Columbia Centre for Disease Control , Vancouver , Canada , 6 Department of Pathology and Laboratory Medicine, University of British Columbia , Vancouver , Canada , 7 Respiratory Medicine, University of British Columbia , Vancouver , Canada , 8 Department of Laboratory Medicine and Pathobiology, University of Toronto , Toronto , Canada
1 Editor: Igor Mokrousov, St Petersburg Pasteur Institute, RUSSIAN FEDERATION
consumer-services) grant number 08507, and the
British Columbia Centre for Disease Control
Foundation for Population and Public Health (http://
bccdcfoundation.org/), and the British Columbia
Lung Association (https://bc.lung.ca/). Financial
support was obtained from the University of British
Columbia (https://www.ubc.ca/) 4-year doctoral
fellowship to J. L. Guthrie, the Canadian Institutes
of Health Research (http://www.cihr-irsc.gc.ca/e/
193.html) doctoral research award to J. L. Guthrie,
Killam Trusts (http://www.killamlaureates.ca/)
doctoral scholarship to J. L. Guthrie, the Michael
Smith Foundation (https://www.msfhr.org/)
scholar awards to J. J. and J. L. Gardy, and the
Canada Research Chairs Program (http://www.
chairs-chaires.gc.ca/) to J. L. Gardy. The funders
had no role in study design, data collection and
analysis, decision to publish, or preparation of the
Competing interests: The authors have declared
that no competing interests exist.
We recommend expanding analysis of shared genotypes to include neighbouring
jurisdictions, and implementing whole genome sequencing to improve identification of TB
transmission, recognize outbreaks, and monitor changing trends in TB epidemiology.
Tuberculosis (TB) remains a major public health issue in Canada. Molecular techniques, such
as 24-locus Mycobacterial Interspersed Repetitive Units?Variable Number Tandem Repeat
(MIRU-VNTR) genotyping, have improved understanding of TB epidemiology, and many
jurisdictions are adopting routine genotyping of all Mycobacterium tuberculosis (Mtb) isolates
]. Within Canada, the province of Ontario?which has the largest number of TB cases of
any Canadian province [
]?was an early adopter of universal genotyping, using MIRU-VNTR
to genotype the first culture-positive isolate for each case since mid-2007 [
these data in the context of linked clinical and demographic information has facilitated both
contact tracing and outbreak detection in the province [
]. More recently, British Columbia
(BC) retrospectively genotyped all first culture-positive isolates since 2005 [
implemented universal genotyping in 2015.
TB incidence rates in Ontario and BC are nearly identical, with 4.5 and 4.6 cases per
100,000 population respectively [
]. Together, these two provinces represent a substantial
burden of disease in Canada, accounting for >50% of the nation?s TB cases, with rates in both
settings largely driven by reactivation of latent TB infection (LTBI) in persons born outside
]. Both provinces are popular destinations for immigrants, with the multi-cultural
cities of Toronto and Vancouver attracting many newcomers [
]. Vancouver has a high
proportion of immigrants from Asia whereas Toronto is more diverse and, in addition to people
from Asia, also has many immigrants from Africa, the Caribbean, and Latin America [
Furthermore, despite the distance between these provinces, there is substantial interprovincial
travel and migration, with ~15,000 individuals reportedly migrating from Ontario to BC and
vice-versa in 2016/17 [
]. Migrants of all types frequently lack support networks and are at
greater risk for homelessness and other factors associated with increased risk of TB
reactivation or infection [
]. This is particularly true in BC, where under-housed migrants from
other provinces?some of whom are experiencing mental illness, addictions, and/or chronic
health conditions [
]?are thought to be attracted to Vancouver by the temperate climate.
Each Canadian province/territory works independently towards TB prevention and care
and contributes data towards national TB surveillance programs; however, there is currently
no national-level TB molecular surveillance program. Although not unique to Canada,
crossjurisdictional issues, including funding, privacy, platforms for disseminating information, and
necessary support personnel, as well as questions surrounding the benefits that such a program
would offer, have prevented implementation thus far. Having completed universal
MIRU-VNTR genotyping dating back over a decade, Ontario and BC have the most extensive
collections of MIRU-VNTR genotyped isolates in Canada. This provides a unique opportunity to
compare the molecular epidemiology of TB between these large immigrant-receiving
provinces and demonstrate the added value of genotype data shared between different jurisdictions
by providing context to the genotypes observed within each region. The resulting insights are
key to understanding genotypic clustering as it relates to local spread of TB, and establishing
proof of concept for a national genotyping program.
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Study setting and design
Ontario and BC are the first and third most populous Canadian provinces, respectively, with
14.2 and 4.8 million inhabitants [
], and rank first and second for the highest population
proportion of immigrants, at 28.5% for Ontario and 27.6% for BC [
]. All Mycobacterium
tuberculosis (Mtb) isolates are either identified in culture at the provincial reference laboratories?
Public Health Ontario Laboratory (PHOL) and British Columbia Centre for Disease Control
Public Health Laboratory (BCPHL), or submitted for reference testing from other laboratories.
The study population included all culture-positive TB cases residing in Ontario or BC at TB
treatment initiation, with a first Mtb sensu stricto isolate received from 2008 through 2014.
Therefore, 3,314 Ontario and 1,602 BC isolates, representing 75.2% and 79.7% of all notified
TB diagnoses during this time period in the respective provinces were included. For
individuals with a reoccurrence during the study period indicative of relapse?successful completion of
treatment and identical MIRU-VNTR results for both episodes (Ontario: n = 5, BC: n = 9)?
only data from the first episode was included.
Ethics approval was granted by Public Health Ontario (#2016?058.0), and the University of
British Columbia (certificate #H12-00910).
Diagnosis and case information
All provinces/territories follow the Canadian Tuberculosis Standards [
] for investigation,
management and reporting of active TB. Case-level clinical and demographic data, including
age, sex, birthplace, and disease site were extracted from each province?s independently held
reportable disease registry?the integrated Provincial Health Information System (iPHIS) in
Ontario and Panorama in BC?and were linked to the genotype results in their respective
provinces. To assess genotyping in the context of urban/rural regions, community type was
determined using Statistics Canada-defined health region Peer Groups (A?I) to effectively compare
health regions with similar characteristics across provinces/territories [
]. We grouped these
into four higher-level categories: Metro (G), Urban, high-density (A, H), Urban,
moderatedensity (B), Rural/Remote (C?E, I). A description of each peer group is provided by Statistic
Genotyping by 24-locus MIRU-VNTR
Using standard methods [
], we successfully MIRU-VNTR genotyped 97.8% (3,314/3,388) of
Ontario isolates and 99.8% (1,602/1,605) of BC. Isolates lacking an amplicon peak at any locus
had MIRU-VNTR repeated with newly extracted DNA, and where there remained no peak at
a single locus?excluding loci 2163 and 2165, which are known to be absent in some strains
]?the locus was coded as missing data and the isolate included in the analyses. Major
lineage (L) was predicted using the TB-Insight webtool [
], and categorized as Indo-Oceanic
(L1), East-Asian (L2), East-African-Indian (L3) or Euro-American (L4). Sub-lineage was
determined using TBminer [
] for isolates in which the major lineage predicted was
concordant with TB-Insight. In cases where the major lineage was discordant between these
prediction tools the TB-Insight lineage was used. We defined an intraprovincial cluster as 2 isolates
with an identical MIRU-VNTR pattern within a province, and an interprovincial cluster as
one or more isolates sharing an identical genotype across the two provinces. Genotypic
clusters within each major lineage were visualized using a Minimum Spanning Tree (MST) created
in PHYLOViZ 2.0 [
] and coloured by province. To graphically represent the relationship
between the number of isolates contributing to a genotype match between the provinces, we
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displayed interprovincial clusters using a circular chord diagram according to the number of
isolates contributing to an interprovincial genotype cluster: single (1 isolate), small (2?9
isolates), large ( 10 isolates).
We compared case-level characteristics using a Chi-square test for categorical variables
(Fisher?s Exact test where appropriate), and a t-test for continuous variables. Intraprovincial
clustering proportions were compared using Chi-square. To calculate the clustered proportion
potentially attributable to local transmission, we used the ?n?1? method in which the first case
of each cluster is assumed to have initiated the cluster and is subtracted from the total number
of clustered isolates [
]. We used logistic regression to examine factors associated with
interprovincial clustering, calculating the odds ratio (OR), adjusted OR (aOR), and 95% confidence
interval (CI). A complete-case analysis strategy (excluded records with missing data: n = 109
[2.2%]) was used, with stepwise backward selection of variables following Akaike Information
Criterion minimization. All statistical analyses were conducted using R statistical software
The study population included a total of 4,916 cases (3,314 in Ontario and 1,602 in BC) with a
diagnosis of culture-positive TB from 2008?2014. The median age was 46 in Ontario with an
interquartile range (IQR) of 30?67 ?significantly lower than in BC (53 years, IQR: 37?72),
p<0.001. Case distribution by community type varied between the provinces (Table 1), with
many Ontario cases residing in Metro areas (47.0%) and most BC cases in high-density urban
areas (55.7%). Notably, a higher proportion of BC cases resided in rural/remote regions
(11.8% versus 4.1%). Country of birth was available for 97.5% of individuals, the majority of
whom were born outside Canada (Table 1); however, the proportion varied significantly
between Ontario (91.3%) and BC (73.5%). Furthermore, Ontario had a higher proportion of
recent immigrants?those arriving within the last five years?(n = 1,024; 35.5%) compared to
BC (n = 309; 27.8%). BC had a higher proportion of persons with respiratory disease (85.1%)
versus Ontario (74.9%).
TB isolates in BC are more likely to be clustered by MIRU-VNTR
To understand the patterns of clustering, we examined the number and size distribution of
genotypic clusters. MIRU-VNTR genotyping grouped the Ontario Mtb isolates into 290
clusters, with a mean cluster size of four isolates (size range: 2?49), yielding a clustered proportion
of 31.8% (S1 Table). In BC, we identified 134 clusters, with an average cluster size of five
isolates (size range: 2?68) and an overall clustered proportion of 40.5%?significantly higher than
found in Ontario (p<0.001). Using the ?n?1? method, [
] the number of infections
potentially attributable to local transmission was 1,053 (23.0%) in Ontario and 649 (32.1%) in BC,
indicating that while the overall number of cases in BC is lower, the proportion of TB
diagnoses that may be the result of local transmission is higher.
In both provinces, more than half the clusters? 56.7% in Ontario and 54.9% in
BC?contained only two individuals, likely representing single transmission events for which there is
little opportunity for intervention. In contrast, large clusters may represent ongoing
transmission where there is more opportunity for preventive measures. Only a few large clusters of
10 individuals were present in either province (Ontario: n = 11 [3.8%], BC: n = 10 [7.5%]).
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Differences in the clustered proportion between the two provinces was largely driven by
clustering amongst Canadian-born persons (Ontario: n = 142 [50.0%], BC: n = 312 [75.7%]), as
the clustered proportion was similar for persons born outside Canada (Ontario: n = 892
[30.0%], BC: n = 322 [28.1%]), a finding that suggests BC experiences more local TB
Interprovincial clustering occurs frequently between Ontario and BC
In total, we observed 3,461 distinct MIRU-VNTR patterns (S2 Table) across both provinces.
Although only 175 of these patterns were detected in both Ontario and BC (S1 Fig), this
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constituted 22.4% (1,102/4,916) of all study isolates sharing a genotype pattern across both
provinces? 595 (18.0%) Ontario isolates and 507 (31.6%) BC isolates. To determine whether
the isolates with MIRU-VNTR matches across the two provinces represented unique
genotypes or common clusters within a province, we examined MIRU-VNTR clustering in each
province. We found that the majority of these interprovincially matched isolates were also
clustered within their respective provinces? 85.5% (509/595) in Ontario and 79.1% (401/507)
in BC (Fig 1). The considerable number of interprovincial matches that also clustered with
isolates within their respective provinces demonstrates that common genotypes occur frequently
across geographically disparate regions.
We used multivariable logistic regression to investigate independent factors associated with
interprovincial genotype matches (Table 2). We found increased odds of interprovincial
matching for BC isolates (aOR 2.1, 95%CI: 1.8?2.5) compared to Ontario isolates?indicating
Ontario had considerably more unique MIRU-VNTR patterns. Additionally, the odds of
matching were higher for Canadian-born persons (aOR 2.5, 95%CI: 1.9?3.2), and those with a
non-L4 Mtb isolate (aOR range: 1.9?4.7). Individuals residing in a Metro area had 1.8 times
the odds of their isolate belonging to an interprovincial cluster (95%CI: 1.2?2.5) compared to
those residing in a rural/remote region. From a public health perspective, understanding the
discriminatory power of MIRU-VNTR for investigating potential transmission is key.
Comparing genotypic matches across the provinces?particularly those representing intraprovincial
clusters?can reveal whether these clusters represent a common genotype circulating in a
specific region of the world or are instead the result of local transmission; the former scenario is
more likely when the same genotype is also common in a distant province. To examine factors
that could be related to cluster size and MIRU-VNTR matches between the provinces we
restricted the sample to include only isolates contributing to an interprovincial genotypic
cluster and compared single versus multiple contributors to a cluster. We observed very similar
trends to the factors associated with overall interprovincial clustering (S3 Table). Furthermore,
upon examination of cluster composition (Fig 2), we found 68 of the 175 interprovincial
clusters were comprised solely of a single isolate detected in each province? 80.9% were L1, L2, or
L3 clusters and 93.9% of these isolates were identified in persons born outside Canada (S2
Fig). This suggests that genotypic matching between the provinces is often the result of strains
with MIRU-VNTR patterns common to the place of origin in persons born outside Canada
and likely representing LTBI reactivation?key information for understanding clustering
Differentiating strains by lineage and sub-lineage revealed dominant sub-lineages?L1_EA2,
L2_Beijing, and L3_CAS which were associated with particular geographic regions (S3 Fig)?
most notably, 93.3% of individuals born in Philippines had an L1_EA2 isolate. Two
MIRU-VNTR patterns (ON253/BC011: 5224341442218A7263223363, ON267/BC021:
5224341442219A7263223363) within this sub-lineage were commonly seen in both Ontario
Mtb population structure reveals large BC-based Lineage 4 clusters
We visualized the 1,894 isolates that were intra- and/or interprovincially clustered using a
minimum spanning tree (Fig 3), revealing 17 large clusters ( 10 persons), many of which
were observed in both Ontario and BC. Recognizing that MIRU-VNTR overestimates
transmission in non-L4, [
] and that local transmission is more likely to occur amongst
Canadianborn persons, we examined these clusters in the context of lineage and birthplace (Table 3).
Clusters of non-L4 isolates were observed in persons born outside Canada, and all but one of
these clusters spanned both provinces, suggesting that rather than local transmission, these
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Fig 1. Intra- and interprovincial 24-locus MIRU-VNTR genotypic clustering, Ontario and British Columbia (2008?2014). Each pie represents the proportion of
isolates within the province that have a genotype match in the other. For the group that does have an interprovincial match, the stacked bar graphs show the relative
frequency of isolates that are clustered or unique within the province.
clusters may reflect reactivation of strains acquired overseas. Clusters involving predominantly
Canadian-born persons tended to occur exclusively within one province or the other and in
different community types?Metro and high-density urban in Ontario, largely rural/remote in
BC. However, seven isolates with genotypes matching two large BC outbreaks (BC002 and
BC012)?one of which has been previously described [
]?appeared in Ontario. Cases in these
two BC-based clusters arose throughout the study period, whereas those with matching
MIRU-VNTR genotypes in Ontario were seen sporadically (S4 Fig), with the first case matching
the BC002 genotype diagnosed in 2011, and the initial Ontario case matching BC012
diagnosed in 2008. The large number of BC cases diagnosed in 2008 suggests these two strains
were present in BC prior to the study period and that the individuals in Ontario potentially
acquired their infections through travel to BC or contact with an individual that had spent
time in BC.
This study describes the first comprehensive interprovincial comparison of MIRU-VNTR
genotyping in Canada using >4,900 Mtb isolates collected in Ontario and BC over a seven-year
period. This represents >50% of culture-positive TB cases diagnosed in Canada during this
period, and provides new insights into the comparative epidemiology of TB in two of Canada?s
largest provinces. Although both provinces have large, diverse populations, there were
significant differences in the epidemiology and the Mtb population structure between the two
provinces. Ontario had more unique genotypes, primarily in persons born outside Canada, and
more cases occurring in large urban areas.
Despite the high strain diversity, the clustered proportion differed significantly between
Ontario and BC?similar to findings in a Western Canada study using restriction fragment
length polymorphism (RFLP) genotyping where clustering varied (9%?64%) across the
provinces studied [
]. In our study, BC cases were more frequently clustered than those in
Ontario, consistent with BC?s higher proportion of TB in Canadian-born persons, amongst
whom local transmission is likely to drive TB rates. This was further supported by the higher
proportion of respiratory disease seen in BC, which is more common in those with L4 strains
]?the lineage which was commonly associated with the large predominantly
Canadianborn clusters. Encouragingly, most clusters were small, with only seven large outbreaks
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consistent with local transmission?most of which have been previously described [
Thus, despite different models of TB management and care between the provinces?Ontario
follows a decentralized model and BC a largely centralized system?common practices and
national guidelines [
] result in consistently effective public health responses in most cases.
When we examined genotypes present in both provinces, we found that most genotype
matches were due to a single individual in either province?the vast majority were born outside
Canada which is consistent with the notion that these represent LTBI reactivation [
appears to be little interprovincial transmission between Ontario and BC, and the seven cases
detected are genotypic matches to two strains endemic to BC circulating within vulnerable
populations with known risk factors, including under-housing [
]. It is possible that
these Ontario residents had travelled to or had prior residence in BC, with social/behavioural
risk factors linked to a higher risk of exposure and infection?something that has been observed
in other cross-jurisdictional studies [
]. Interestingly, Ontario?s large clusters (ON219,
ON22) circulating amongst under-housed individuals in a Metro area of Ontario [
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Fig 2. Interprovincial genotype matches by cluster size within a province. A circular chord diagram visualizing the
number (indicated by tick marks) of interprovincial 24-locus MIRU-VNTR genotype matches between Ontario (left)
and British Columbia (right) from 2008?2014, grouped by the number of isolates within each province sharing the
matched genotype: single (1 isolate), small (2?9 isolates), large ( 10 isolates). Flow width indicates the number of
genotypes. For example 20 single isolates each with a different MIRU-VNTR pattern in Ontario are genotype matches
to 20 different small British Columbia MIRU-VNTR clusters.
not found in BC, suggesting differences in the epidemiology or movements of the
underhoused populations between the provinces. However, because TB case management occurs at
the provincial/territorial level, sharing of patient-level data across jurisdictions is challenging,
and a limited data-sharing agreement with stringent privacy requirements prevented
comparison of risk factor and epidemiological data to explore this further. We also assumed that
identical genotypes amongst Canadian-born individuals with L4 Mtb strains represented local
transmission. This observation is supported by recent work in the English Midlands,  but
whether this is the case here remains to be seen; it is possible these interprovincial clusters
represent a common strain circulating in Canada amongst vulnerable populations. We similarly
assumed that persons born outside Canada having Mtb isolates with lineages commonly
associated with their birthplace and genotypically clustering across the two provinces were likely to
represent LTBI reactivations with a genotype common to their country of origin.
The strong phylogeographic structure of Mtb [
] was apparent in our study. Lineages were
consistent with birthplace and mirrored Canada?s demographics, where the top three countries
of origin of immigrants to Canada are Philippines, India, and China [
]. These were reflected
in the considerable number of L1_EA2, L3_CAS, and L2_Beijing strains and large
MIRU-VNTR clusters within these lineages. It has previously been determined that the
discriminatory power of MIRU-VNTR is reduced in non-L4 strains [
], and several studies have found
that MIRU-VNTR overestimates transmission [
]. Our findings support this,
particularly amongst persons from the Philippines?nearly all Mtb isolates from Filipino-born
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Fig 3. Minimum spanning tree analysis of 24-locus MIRU-VNTR of the 1,894 intra- and interprovincially clustered isolates with lineage indicated, Ontario
and British Columbia (2008?2014). The size of each circle is proportional to the number of isolates. Classification of genotypes by province is visualized by colour
individuals belonged to sub-lineage L1_EA2, which is in line with recent studies [
same two MIRU-VNTR patterns dominated within L1_EA2 in both provinces, and
understanding that these represented common genotypes in persons from the Philippines could
have prevented a significant amount of public health resources used within each province to
investigate these clusters?investigations which to date have not yielded epidemiological
connections supporting local transmission.
Currently, there is no coordinated national molecular surveillance program for tuberculosis
in Canada and genotyping data are not routinely shared across all provinces, precluding a
nationwide molecular surveillance program of the type implemented in the United Kingdom,
the Netherlands, and other comparable low-incidence settings [
]. While our analyses
suggest minimal TB transmission between BC and Ontario, these are two geographically distant
provinces?a similar study using geographically closer jurisdictions may tell a different story. A
national molecular surveillance program is a complex undertaking, requiring coordinated and
collaborative efforts by all provinces/territories for implementation, maintenance, support,
and evaluation. Perhaps the largest challenge is acquiring funding to support a national
program, particularly the necessary personnel required to carry out such an effort, as provincial
public health budgets are already limited. Additional issues complicate the ability to access and
analyze health data across provincial/territorial borders?data ownership, legal, ethical, and
privacy concerns limit what jurisdictions may be willing or able to share, yet clinical and
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R (100) L2_Beijing
Predominant ( 50%) birthplace country or region. Birthplace was unknown for 10 individuals; percentage represents those with complete data.
?Predominant ( 50%) community type.
?All individuals were male.
?Not available, data suppressed due to small cell size.
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epidemiological data are required for meaningful interpretation of genotypic data [
Interpretation of these data requires molecular epidemiologists with a regional- and national-level
understanding of TB epidemiology, and a suitable information technology platform to link
genotyping and administrative data. Integration of data sources, even within provinces,
requires significant resources for creating and curating databases and routinely linking data.
In Ontario, the OUT-TB Web online platform is used to communicate case-level genotyping
data across the province and could provide a template for a national system [
While there was minimal evidence of cross-jurisdictional transmission in the present study,
the comparison of TB molecular epidemiology between Ontario and BC furthered our
understanding of local transmission and LTBI reactivation by providing context to the genotypes
observed in each province. This information strengthens the collective understanding of
genotypic clustering and how it can be used to support public health efforts in TB prevention?
essential for program management and resource allocation, as local molecular epidemiology
often informs contact investigation and other TB program activities. Our study contributes to
the understanding of LTBI reactivation of infections acquired abroad, providing further
evidence that genotyping does not always provide sufficient discriminatory power to exclude
local transmission?information necessary for determining appropriate TB prevention
strategies. Next steps could include expanding the analyses to other Canadian jurisdictions, and
incorporating whole genome sequencing data?used prospectively and combined with
epidemiological data, this technology will most certainly provide the clearest picture of TB
epidemiology and more accurately quantify transmission versus LTBI reactivation, for which different
preventative measures are needed.
S1 Table. Genotype (24-locus MIRU-VNTR) results, including intraprovincial genotype
clustering by size and frequency in Ontario and British Columbia, 2008?2014.
S2 Table. 24-locus MIRU-VNTR patterns for study isolates.
S3 Table. Multivariable analysis of factors associated with single and multi ( 2 isolates)
contributors to an interprovincial 24-MIRU-VNTR cluster, Ontario and British Columbia
S1 Fig. Venn diagram representing the number of unique and shared 24-locus
MIRU-VNTR genotypes between Ontario and British Columbia, 2008?2014.
S2 Fig. Proportion of single contributors to an interprovincial cluster by province and
S3 Fig. Distribution of Mycobacterium tuberculosis sub-lineages in Ontario and British
Columbia (2008?2014) by patient continent or region of birth. Pies are scaled to the total
number of isolates represented by each sub-lineage.
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S4 Fig. Epidemiological curve of two MIRU-VNTR genotype clusters known to represent
local transmission in British Columbia.
Special thanks to the PHO Laboratory (TB/Mycobacteriology) and BCCDC Public Health
Laboratory (TB/Mycobacteriology) staff for providing the TB isolates for this study, and to Fay
Hutton of BCCDC TB Services and Michael Whelan of Public Health Ontario for their
assistance with Panorama and iPHIS data extraction.
Conceptualization: Jennifer L. Guthrie, Karen Lam, Daria Pyskir.
Data curation: Jennifer L. Guthrie, Alex Marchand-Austin, Kirby Cronin, David Roth.
Formal analysis: Jennifer L. Guthrie.
Funding acquisition: Patrick Tang, Victoria J. Cook, James Johnston, Frances B. Jamieson,
Jennifer L. Gardy.
Investigation: Jennifer L. Guthrie, Karen Lam, Daria Pyskir, Clare Kong, Danielle Jorgensen.
Project administration: Jennifer L. Guthrie, Alex Marchand-Austin, Frances B. Jamieson,
Methodology: Jennifer L. Guthrie.
Jennifer L. Gardy.
Resources: Alex Marchand-Austin.
Jamieson, Jennifer L. Gardy.
Visualization: Jennifer L. Guthrie.
Writing ? original draft: Jennifer L. Guthrie.
Supervision: Mabel Rodrigues, Patrick Tang, Victoria J. Cook, James Johnston, Frances B.
Writing ? review & editing: Jennifer L. Guthrie, Alex Marchand-Austin, Kirby Cronin, Karen
Lam, Daria Pyskir, Clare Kong, Danielle Jorgensen, Mabel Rodrigues, David Roth, Patrick
Tang, Victoria J. Cook, James Johnston, Frances B. Jamieson, Jennifer L. Gardy.
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