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Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review
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Tuberculosis journal homepage: http://intl.elsevierhealth.com/journals/tube
REVIEW
Q10 Q9
Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review Vlad Nikolayevskyy a, b, *, 1, Katharina Kranzer a, c, d, 1, Stefan Niemann d, e, Francis Drobniewski a, b a
PHE National Mycobacterium Reference Unit, 2 Newark Street, E1 2AT London, United Kingdom Department of Medicine, Imperial College London, Du Cane Road, W12 0NN London, United Kingdom London School of Hygiene and Tropical Medicine, London, UK d National Reference Center for Mycobacteria, Forschungszentrum Borstel, Leibniz-Zentrum für Medizin und Biowissenschaften, D-23845 Borstel, Germany e German Center for Infection Research (DZIF), Partner Site Hamburg-Borstel-Lübeck, D-23845 Borstel, Germany b c
a r t i c l e i n f o
s u m m a r y
Article history: Received 22 November 2015 Received in revised form 22 February 2016 Accepted 29 February 2016
Contact tracing complemented with genotyping is considered an important means of understanding person-to-person transmission of tuberculosis (TB). It still remains unclear whether Whole Genome Sequencing (WGS) of Mycobacterium tuberculosis can rule in transmission and how it performs in different human populations, risk groups and across TB lineages. This systematic review aimed to determine the sensitivity and specificity of WGS for detection of recent transmission using conventional epidemiology as the gold standard and investigate if WGS identifies previously undetected transmission events. Systematic review was conducted according to the criteria of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses group. A compound search strategy was developed to identify all relevant studies published between 01/01/2005 and 30/11/2014 using three online databases. Publications satisfying specific criteria have been identified and data extracted. A total of 12 publications were included. We established that WGS has a higher discriminatory power compared to conventional genotyping and detects transmission events missed by epidemiological investigations. A cut-off value of <6 SNPs between isolates may predict recent transmission. None of the studies performed a head-to-head comparison between WGS and conventional genotyping using unselected prospectively collected isolates. Minimum reporting criteria for WGS studies have been proposed and quality control parameters considered. Crown Copyright © 2016 Published by Elsevier Ltd. All rights reserved.
Keywords: Tuberculosis Epidemiology Transmission Next generation sequencing
1. Background Tuberculosis (TB) remains a serious public health problem killing more than 1.7 million people annually [1]. The varying impact of control measures in different settings highlights the need for better diagnostics, treatment, preventive strategies and improved understanding of transmission at the population level.
* Corresponding author. PHE National Mycobacterium Reference Unit, 2 Newark Street, E1 2AT London, United Kingdom. Tel.: þ44 207 3775895. E-mail address: [email protected] (V. Nikolayevskyy). 1 These authors contributed equally to the study.
Since the 1990s molecular epidemiological studies have provided valuable insights into the phylogeography of Mycobacterium tuberculosis complex (MTBC), its evolutionary pathways and population and nosocomial transmission helping to distinguish between reinfection and re-activation and detect laboratory crosscontamination [2e5]. Contact tracing complemented with MTBC genotyping is considered an important means of understanding person-to-person transmission. However, due to competing priorities and limited resources, nation-wide prospective genotyping has only been implemented in few high income countries such as the United Kingdom, the Netherlands, Finland and the United States [6e9]. It is less clear whether genotyping itself is cost-
http://dx.doi.org/10.1016/j.tube.2016.02.009 1472-9792/Crown Copyright © 2016 Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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effective and has any added value beyond contact tracing from an immediate public health point of view [6]. Over the past two decades, methods in MTBC genotyping have evolved from non-PCR based methods to more reproducible and less cumbersome methods such as spoligotyping and 24-lociMIRU-VNTR typing (Mycobacterial Interspersed Repetitive UnitsVariable Number of Tandem Repeats). These methods utilize variations in repetitive sequences in MTBC strains and produce results in digital format enabling portability of results and creation of national and international databases for routine and research purposes [10]. MIRU-VNTR genotyping using a standardised set of 24 loci is currently in use for routine MTBC genotyping in many European countries and globally [11,12]. Online analysis tools for lineages identification are available via online databases e.g. MIRUVNTRplus (www.miru-vntrplus.org) or SITVIT-WEB (www.pasteurguadeloupe.fr:8081/SITVIT_ONLINE/) [13]. Although introduction of MIRU-VNTR genotyping has significantly enhanced our knowledge in MTBC phylogeny and global transmission, its discriminatory power for prospective epidemiological investigations might be limited in some circumstances. It is an established method to rule out transmission in epidemiologically linked cases but ruling in transmission events is more problematic especially in endemic regions and/or where highly conserved genotypes (e.g. Beijing) prevail [14e16]. Although the VNTR molecular clock is considered to be relatively slow, there is some evidence suggesting that VNTR profiles evolve both within individuals and across transmission events as shown during longterm outbreaks [16,17]. High throughput whole genome sequencing (WGS) based on Next Generation Sequencing (NGS) technologies offers new opportunities both in research and public health including TB laboratory diagnosis and molecular epidemiology [2,5,18]. NGS allows sequencing nearly full genomes of multiple strains simultaneously saving time, simplifying the workflow and providing considerably more information compared to traditional methods with unprecedented accuracy [18,19]. WGS resequencing allows one to assemble a genome against a known reference and identify various polymorphisms, including SNPs and indels potentially important for epidemiology, diagnosis, drug resistance detection and phylogenetic investigations [2,20]. The past decade has seen a considerable expansion of sequencing capacity improving its availability for routine laboratories in high-income countries. Template amplification platforms with a variety of chemistries, both high-end and bench-top instruments are currently in use with single molecule sequencing technologies being under development [20,21]. Following the first outbreak investigation using WGS [22], several studies have shown the utility of WGS in the context of epidemiological investigations [16,23,24]. These studies suggest that WGS provides better discriminatory power than VNTR typing improving accuracy, resolving false clusters and, importantly, potentially saving money and resources of public health teams by preventing unnecessary actions [16]. The M. tuberculosis genome mutation rates were estimated at 0.5 single nucleotide polymorphisms (SNPs) per genome per year and a threshold of genetic distance of less than 6 SNP for strains from direct human to human transmission (suggesting recent transmission) was proposed [16,25]. Importantly, data obtained through WGS is of dual use also providing a crucial information on the mutations associated with drug resistance potentially making it a versatile tool in TB laboratory diagnosis [2,5,18]. It remains unclear whether WGS can more reliably rule in transmission and whether it is specific enough to identify cases truly involved in recent transmission chains. The value of classical genotyping techniques in TB-related epidemiological investigations
is well established while the role of WGS has not been accurately defined. Whether NGS genotyping has a variable performance in different human populations, risk groups and across TB lineages is yet to be investigated. To address these issues, we conducted a systematic review to determine the sensitivity and specificity of WGS for detection of recent transmission chains using conventional epidemiological data as a gold standard. We further investigated if WGS provides any additional information compared to classical genotyping and or conventional epidemiology with regards to identification of previously undetected transmission events and/or ruling out person-to-person transmission. 2. Methods This systematic review was conducted according to the criteria of the Preferred Reporting Items for Systematic Reviews and MetaAnalyses group [26]. The protocol was registered with PROSPERO (registration number CRD42015023675). 2.1. Inclusion and exclusion criteria Cross-sectional and cohort studies published between 1st January 2005 and 30th November 2014 were eligible for inclusion if they reported on individuals with culture positive TB disease. No geographical or language restriction was applied. Studies were included if WGS, molecular fingerprinting of M. tuberculosis complex isolates (IS6110 RFLP and/or multilocus VNTR typing) and conventional epidemiology data determining transmission chains, events and outbreaks were available. Review papers and studies with incomplete data sets were excluded. 2.2. Outcome measures The following types of outcome measures were recorded: - Number of transmission events detected by WGS and/or genotyping confirmed by conventional epidemiological data; - WGS performance characteristics (sensitivity, specificity, PPV, NPV) compared to conventional epidemiological data; - Number of subclusters/transmission chains identified using WGS within original RFLP- and/or VNTR-determined clusters.
2.3. Search strategy A compound search strategy was developed to identify all relevant studies regardless of language or publication status using MEDLINE (OVID), EMBASE (OVID), and Web of Science electronic databases (see Supplementary Tables 1 and 2). All references identified by the compound search strategy were imported into EndNote. Duplicates were removed. Titles and abstracts were examined in duplicate by two reviewers (VN and KK) and irrelevant studies were excluded. Full texts of all potentially relevant studies were obtained and inclusion criteria applied using a standardised eligibility form. Reference lists of all studies identified by the above methods and bibliographies of reviews and editorials were examined and additional references were identified satisfying original eligibility criteria [27]. Final agreement on study inclusion was determined through consensus between the two reviewers (VN and KK). 2.4. Data extraction and management Data extraction was performed independently, in duplicate, using a standardized data extraction form. The following data was
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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extracted: year, setting (country, city), duration of sampling, number of isolates included, risk group/population status and genetic lineages, primary and secondary (if available) genotyping method used, outcome measures. Additionally, relevant technical details such as WGS platform, SNPs genetic distances within epidemiologically linked and genotypically linked subjects, genome coverage/sequencing depth, quality control criteria and the exclusion/inclusion criteria which were applied to call polymorphisms were extracted. 2.5. Analysis A PRISMA diagram was constructed. The sensitivity and the specificity of MIRU-VNTR and WGS compared with conventional epidemiology were calculated using the following assumptions and definitions: - Number of links identified by genotyping: although some patients may be linked to more than one patient, and number of pairwise combinations within larger RFLP/VNTR clusters with identical profiles could be in theory hundreds or thousands, for the purposes of the current review we adopted a previously described approach [16], and assumed that the number of links identified by genotyping was equal to the number of strains within a cluster minus one and applied this definition to all studies for sensitivity and specificity calculations. - Number of links identified by WGS: unlike genotyping, WGS may allow to determine the direction of transmission. Even closely genomically related strains (i.e. within 0…5 SNPs genetic distance) may not represent actual direct transmission events. For the purposes of the current review, we assumed that any two strains within 5 SNP genetic distances (termed genomically linked) could be involved in direct transmission. Therefore in the current review the number of links identified by WGS is equal to the number of genomically linked strains. The number of transmission chains/subclusters identified using WGS within genotyping clusters was determined. 2.6. Quality assessment Currently there are no formally recognised criteria to assess the quality of WGS based studies. With regards to quality assessment of individual studies conventional criteria such as sampling frame and completeness were determined to assess selection bias. Reported quality criteria for the method itself, including genome coverage and sequencing depth, as well as specific cut-off values and reading consensus rates for valid SNP calls were derived from all studies. 3. Results
3
M. africanum isolates were sequenced. Two studies conducted social network analysis [22,29]. Only one study was conducted in a high TB incidence setting in China [29], the others were conducted in the Netherlands (n ¼ 3), United Kingdom (n ¼ 3), Germany (n ¼ 2), Canada (n ¼ 2), and USA (n ¼ 1). Methods used for genotyping varied across studies. PCR-based methods (MIRU-VNTR typing and spoligotyping) and non PCR-based methods (IS6110 RFLP) were utilised in 5 and 4 studies, respectively. In three studies both PCR- and non-PCR based methods were used in parallel. In a proportion of studies non-standard and/or incomplete sets of VNTR loci (12, 15, or 16 loci plus hypervariable loci) were used [16,29,31,36]. 3.3. Study design, human populations and M. tuberculosis genetic lineages In all but one study [35], historical TB outbreaks were analysed. In five studies genotyped isolates belonged to long-term TB outbreaks lasting from 18 months to 17 years confined to specific geographical settings (towns, provinces or metropolitan areas). One population-based study conducted in the UK utilised a nondiscriminatory sampling strategy and WGS was performed on strains isolated from patients with and without confirmed epidemiological links [35]. In the majority of studies (n ¼ 10) selection of MTBC isolates for sequencing was based on availability of conventional genotyping results so only strains clustered using molecular genotyping methods (IS6110 RFLP and/or multilocus VNTR) and therefore considered part of TB outbreaks were sequenced; no strains outside those clusters were included. The total number of IS6110 RFLP or multilocus VNTR clusters within a given study varied from 1 to 42; in two studies original clusters formed by a primary genotyping method were further split into smaller groups using secondary methods [32,33]. Information on M. tuberculosis genetic groups and lineages was derived from VNTR genotyping, spoligotyping and/or WGS data and reported in nine studies. Two more studies reported VNTR codes, but those could not be unambiguously assigned to any known family using international databases [22,32]. Two studies included exclusively East Asian (Beijing family) strains (N ¼ 34) [29,37], three more studies e Euro-American (Haarlem family) strains (N ¼ 121) [24,31,33], and two small studies included a total of three EuroAmerican strains belonging to the T family [23,30]. Two larger studies included strains from all major lineages (N ¼ 416) [16,28]. None of the studies specifically focused on high-risk groups; some studies included high-risk, foreign-born patients or ethnic minorities. Individuals belonging to high-risk groups such as the homeless, recreational drug users, and people living with HIV comprised over 60% of individuals in two Canadian studies [22,32]. The studies conducted in the UK and Germany included a significant (although unspecified) proportion of foreign-born individuals.
3.1. Study selection A total of 2085 publications were identified; 59 studies were selected for full text review, 47 of those were excluded leaving 12 studies being included in the current systematic review [16,22e24,28e35]. PRISMA diagram is depicted on Figure 1. 3.2. General characteristics of included studies
Q1
The characteristics of included studies and relevant outcome data are summarised in Tables 1 and 2. WGS data was available for 1088 MTBC isolates. The number of isolates included in each study varied from 2 to 390. All but one report included M. tuberculosis isolates only; in one study [16] a small number of M. bovis and
3.4. Relevant technical data, quality control and polymorphisms calling criteria WGS is a novel method that has emerged over the last few years. Commercial kits covering all stages of analysis are not available so ‘wet’ laboratory technology and data processing pipelines have not been fully standardised. Data summarizing the technical details are presented in Table 3. All studies reported the sequencing chemistry platform and hardware used for sample analysis. Two studies used 454 technology, and the rest used various versions of Illumina including GeneAnalyser (n ¼ 2), Hi Seq (n ¼ 3), and MiSeq (n ¼ 2). Genome coverage and average sequencing depth were reported in 8 of the
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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Figure 1. PRISMA study selection flow diagram.
12 studies and varied from 88.5% to 99.2% and from 50.9 to 174, respectively. Principal QC criteria applied at analytical stages included minimum depth for valid single nucleotide polymorphisms (SNP) call, minimum consensus rate for valid call and exclusion of certain types of polymorphisms depending on their nature and location. SNPs associated with drug resistance and indels were not included in any studies while SNPs located in repetitive and high GC-rich regions (including PE/PPE and ESX genes) were included in one study [22], and not reported in two. Exclusion criteria and rules applied to polymorphisms located within 12 bp of each other, as well as information on whether DNA was extracted from single colonies, was not systematically reported. Minimum depth for valid
SNP call and minimum consensus rate for valid SNP calls were reported in 5 and 8 studies and ranged from 10 to 20 and from 75% to 90%, respectively. There was no clarity whether these criteria were applied to each DNA strand separately. 3.5. Genetic distances between M. tuberculosis strains isolated from patients with confirmed epidemiological links Genetic distances between strains isolated from patients with confirmed epidemiological links were reported in all but two studies and ranged from 0 to 1746; in the majority of studies (N ¼ 7), they did not exceed 5 SNPs. There was a total of 23 epidemiological links (7.4% of the total number of transmission
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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Table 1 General characteristics of the studies. Publication
Primary genotyping method used
Epi data
Country
Settings
Risk groups
M. tuberculosis lineages
Duration of sampling (longest time interval(s) between isolates within suspected outbreaks)
Schurch et al., 2010a Schurch et al., 2010b
Contact tracing, interviews Contact tracing, interviews
Netherlands Netherlands
Low incidence Low incidence
Not reported Not reported
Not reported Not reported
13 years 13 years
Gardy et al., 2011
IS6110 RFLP IS6110 RFLP, 24 VNTR, spoligotyping 24 VNTR
Canada
Low incidence
No HIV infected
Not reported
30 months
Bryant et al., 2013
IS6110 RFLP
Contact tracing, interviews, social network analysis Contact tracing, interviews, stone-in-the-pond principle
Netherlands
Low incidence
Not reported
16 years
Luo et al., 2013
16 þ 2 VNTR, 6 SNPs
Contact tracing, interviews, social network analysis
China
High incidence
Not reported
Kato-Maeda et al., 2013
Contact tracing, interviews
USA
Low incidence
Roetzer et al., 2013
IS6110 RFLP, 12 VNTR, spoligotyping IS6110 RFLP
Contact tracing, interviews
Germany
Low incidence
Euro-American (Haarlem family)
13 years
Torok et al., 2013
24 VNTR
Contact tracing, interviews
United Kingdom
Low incidence
15 or 24 VNTR
Contact tracing, interviews
United Kingdom
Low incidence
Kohl et al., 2014
IS6110 RFLP, spoligotyping 24 VNTR, spoligotyping
Contact tracing, interviews
Germany
Low incidence
Not reported
Contact tracing, interviews
Canada
Low incidence
17 years
e
Contact tracing, interviews
United Kingdom
Low incidence
Outbreak associated with high risk populations (homeless/HIV infected and drug abusers) Not reported
East Asian (Beijing family) All major lineages, M. bovis and M. africanum Euro-American (Haarlem family) Not reported
e
Walker et al., 2013
Foreign-born individuals, ethnic minority Outbreak associated with high risk populations (homeless and alcohol abusers) Foreign-born individuals Not reported
Euro-American, East Asian, East-African Indian, Indo-Oceanic East Asian (Beijing family modern sublineage) Euro-American (Haarlem family)
All major lineages
e
Q8
Mehaffy et al., 2014
Walker et al., 2014
events across all studies) where genetic distances between isolates were over 12 SNPs; eighteen of those (>100 SNPs, exact distances not specified) occurred in a Chinese study where epidemiological investigations were challenging [29]. Applying more stringent criteria for epidemiological linkage (<6 SNPs) only marginally increased the proportion of genomically unconfirmed links (29 links, 9.4%). 3.6. Sensitivity and specificity of WGS and genotyping using epidemiological data as a gold standard Performance characteristics of WGS and genotyping (sensitivity, specificity, PPV and NPV) were not systematically reported in the reviewed papers and were calculated as described in the Methods section. All studies reporting conventional genotyping data selected isolates on the basis that they were indistinguishable by IS6110 RFLP and/or VNTR typing so sensitivity and specificity of conventional genotyping data could not be determined. The only study performing non-discriminatory testing reported on WGS data only and did not include any genotyping data [35]. WGS performance characteristics had to be interpreted in the context of the sampling frame. Within VNTR/RFLP clusters, nearly all transmission events identified by conventional epidemiology were confirmed by WGS resulting in high sensitivity (100% in 8 out of 12 studies). Data to calculate specificity was available in five
18 months
22 months
12 years
10 years
studies [16,24,29,32,35]. Within RFLP/VNTR-defined clusters, WGS identified a significant number of isolates with less than 5 SNP difference (suggesting transmission) despite non-established epidemiological links resulting in specificity ranging from 17 to 95% using conventional epidemiology as a gold standard. 100% sensitivity rates were reported for different lineages including East Asian (Beijing family) and Euro-American (Haarlem family). Two studies did not stratify transmission events by lineage [16,28]. 3.7. Identification of transmission chains using WGS and overall comparison with conventional genotyping WGS had a higher discriminatory power compared to IS6110 RFLP and/or VNTR to identify separate transmission chains within RFLP/VNTR clusters. WGS allowed the identification of two independent transmission chains within two clusters defined by indistinguishable IS6110 RFLP/VNTR profiles in Canada. These results were in agreement with contact tracing data and geographical distribution of isolates [22,32,33]. One of the subclusters identified using WGS in the Canadian study was comprised of strains harbouring a 15 kB deletion which was not detected by MIRU-VNTR typing [32]. In another study conducted in Germany two additional clusters were identified within a cluster defined by IS6110 RFLP [33]. In a small study conducted in the UK WGS allowed the identification of a previously missed transmission event [37].
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
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Table 2 Principal findings. Publication
No of isolates sequenced
Schurch et al., 2010a Schurch et al., 2010b
3 (One RFLP cluster) 2 (One RFLP/VNTR/spoligo cluster)
Gardy et al., 2011
No of epi links
No of links identified by WGS (<6 SNPs genetic distance)
No of links identified by genotyping*
2 1
2 1
2 1
36 (One VNTR/RFLP cluster)
19
e
35
Bryant et al., 2013
199 (42 RFLP clusters)
97
149y,¶
Luo et al., 2013
32 (3 16VNTR clusters)
24
Kato-Maeda et al., 2013
9 (One genotyping cluster)
Roetzer et al., 2013
Torok et al., 2013 Walker et al., 2013
Kohl et al., 2014 Mehaffy et al., 2014
Walker et al., 2014
No of links identified by WGS (<6 SNPs genetic distance) and confirmed by epidemiology 2 1 e
157
89¶
10
29
10
7
10
8
7
86 (One RFLP cluster; VNTR further subdivided into five groups) 2 (One 24 VNTR cluster)
31
85
85
31
0
1
1
217 from 168 patients within 11 VNTR clusters (6…47 cases) 26 (One RFLP/spoligo cluster)
69
142
157
69
14
22
25
14
18
39
55
18
28x
26¶
56 (One VNTR/spoligo genotyping cluster further split into three “pseudo clusters” using RFLP) 247
e
11
WGS sensitivityz and specificity (<6 SNPs genetic distance) 100% 100% e e e 91.8% e 100% 95.0% 100% e 100% e e e 100.0% 17.0% 100% 27.2% 100% 29.2% 78.5% 93.5%
*
Number of links identified by genotyping ¼ number of strains within an RFLP/VNTR cluster minus one. Values calculated using the data available in the publications and Supplementary data. In all but one study (Walker et al., 2014), only isolates clustered based on genotypical investigations (VNTR and/or RFLP) were included which introduced significant bias into calculations of WGS sensitivity and made impossible to calculate genotyping sensitivities and specificities x Including 12 culture-negative cases and two isolates with no WGS data ¶ Identified using <12 SNPs criteria y z
Overall, in most studies only a proportion of strains within clusters defined by indistinguishable IS6110 RFLP and/or VNTR were genomically linked (using both <6 and <12 SNP criteria). This confirms the limited discriminatory power of conventional genotyping methods for prospective epidemiological investigations. 4. Discussion Previous studies indicated that WGS sequencing provides a higher discrimination of clinical MTBC isolates compared to classical genotyping e.g. based on MIRU-VNTR typing but this has not been investigated systematically to date. By performing a systematic analysis of 12 studies, this review confirms the notion that WGS has a higher discriminatory power and is able to subdivide clusters defined by classical genotyping. Studies included in this review have shown that the proposed cut-off value of <6 SNPs could be used for identification of isolates involved in direct human-tohuman TB transmission [16]. No study has yet performed a head-to-head comparison between WGS and conventional genotyping using unselected prospectively collected isolates. All studies except one included in this review have used a selective sampling strategy, where isolates found to be identical by conventional genotypic methods were then retested using WGS. It was therefore impossible to evaluate sensitivity and specificity of different genotyping methods compared to conventional epidemiological investigations. Performance characteristics of WGS described in this review are subject to selection bias due to the particular strategies used in the original studies. Hence, sensitivity and specificity estimates need to be
interpreted with caution, and should be confirmed in future studies utilising non-discriminatory sampling of specimens. Overall sensitivity of WGS to identify epidemiologically linked isolates was high. WGS allowed one to distinguish between isolates sharing identical genotyping patterns potentially separating transmission chains within RFLP/VNTR clusters. WGS identified false clustering ruling out false transmission events. Some studies showed that WGS was in better agreement with contact tracing data and geographical distribution of isolates. Specificity of WGS for detection of recent transmission chains using conventional epidemiology as a gold standard varied across studies (17.0e95.0%). A high number of “false positive” results might raise concerns about its applicability to ruling in transmission; however, these results may actually represent transmission events missed by conventional epidemiology or linked to other problems with the conventional epidemiology data collection, interpretation and quality. Conventional epidemiology is an imperfect gold standard itself especially in high TB incidence settings and is influenced by the method used and resources available [29,38]. This review has several strengths and limitations. The review used an extensive search strategy applying international criteria of the Preferred Reporting Items for Systematic Reviews and MetaAnalyses group. Due to heterogeneity of data a meta-analysis was not possible and lack of internationally agreed quality criteria for WGS studies in the context of TB epidemiology and laboratory diagnosis made quality assessment challenging. Limitations of studies included in this review included the retrospective nature of the study design, selection bias, small sample sizes in some studies,
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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Table 3 WGS technical data. Publication
WGS genome WGS average Platform/methodology used coverage depth
PE/PPE/PGRS Minimum Minimum and repetitive depth for consensus valid call rate threshold sequences for valid call
No of SNPs between isolates with confirmed epi links, range
No of SNPs between isolates clustered using genotyping
Schurch et al., 2010a Schurch et al., 2010b Gardy et al., 2011 Bryant et al., 2013
95.4% 97.0% 99.2% 95.6%
50.9 e 174 100
e e Included Excluded
e e e e
e e 70% 75% on each strand
4 4 e 0…149 SNP
Luo et al., 2013 Kato-Maeda et al., 2013 Roetzer et al., 2013 Torok et al., 2013 Walker et al., 2013
e 95.7% 96.4% e 88.5%
100 Illumina HiSeq 300 bp reads 73 Illumina GA 36 bp reads e 454 (one strain) and Illumina 82 to 102 Illumina MiSeq 150 bp reads e Illumina HiSeq 75 bp reads
Excluded Excluded Excluded e Excluded
10 12 10 e e
e 85% 80% 75% 75%
>100 0…2 0…3 n/a 0…5
Kohl et al., 2014 Mehaffy et al., 2014 Walker et al., 2014
e e 92%
84 e 106
Excluded Excluded Excluded
10 20 e
75% 75% 90%
0…5 0…4 0…1746
8 4 204 95% of RFLP-linked isolates had SNP distances <11 SNPs 108 7 85 0 0…150 (up to two mismatches in VNTR clusters) 322 81 n/a
454 Platform 454 Platform 250 bp reads Illumina 50 bp reads Illumina GAIIx 76e108 bp reads
Illumina MiSeq Illumina Illumina HiSeq
lack of data related to specific M. tuberculosis lineages and populations such as high risk groups. This review was unable to assess the difference of performance of WGS for different lineages of M. tuberculosis, as only few studies stratified their analysis by lineage. In future studies using WGS methodology are likely to become prolific. Developing minimal criteria for reporting and assessment of quality is important as such criteria have been agreed for other studies such as observational studies and clinical trials [39,40]. We take the opportunity to introduce minimum list of technical parameters, as well as outcomes and performance characteristics for studies using WGS technology that should be included in future reports to ensure comparability of studies and improve quality (Table 4). Consensus on cut-off values and thresholds for certain technical parameters including minimum depth for a valid SNP call and criteria for minor alleles is yet to be reached and applied in future studies. Results of our study also highlight an importance of development and implementation of quality assurance schemes for WGS. MIRU-VNTR genotyping is currently in routine use for prospective molecular epidemiology investigations in several
European countries and globally [3]. However, lack of discriminatory power and concerns regarding its cost-effectiveness and overall value in TB clinical and diagnostic management have been raised [6,15]. While WGS might address the issue of increased discriminatory power, the question of added value remains. WGS is a tool, which may provide answers to specific questions such as transmission chains and cross-border transmission and may evolve into a practical instrument used to cover the majority of laboratory diagnoses, including identification, provide indication of drug resistance testing and epidemiological typing. However, its impact in routine day-to-day public health and clinical investigations remains to be demonstrated. In the current review we established that WGS has a higher discriminatory power compared to conventional genotyping and is able to further divide false clusters potentially eliminating the need for unnecessary public health actions. WGS may also identify transmission events missed by conventional epidemiological investigations. The impact of WGS in resolving TB outbreaks, realtime TB epidemiology, and molecular surveillance is yet to be established. Future studies should be population-based including
Table 4 Study characteristics, results, outcomes and technical parameters proposed for inclusion in the WGS reports.
Parameters, outcomes, characteristics and other details
Study design and epidemiological data
Technical data
Conventional genotyping
Whole genome sequencing
- Study design (prospective/ retrospective, population-based, longitudinal, etc.) - Target populations, presence of high risk groups; - TB settings (low-, high, etc.) - Length of the study - Type of epidemiological data available and how it was collected - Number of transmission events identified using epidemiological investigations (confirmed/ unconfirmed)
- Hardware platform and chemistry used; - Length of reads; - Genome coverage and depth; - Bioinformatics analysis parameters and criteria for calling polymorphisms: Exclusion or inclusion of indels Exclusion or inclusion of SNPs in repetitive sequences, PE/ PPE, ESX and similar genes; Exclusion or inclusion of SNPs located within certain distance (e.g. 12 bp) Exclusion or inclusion of SNPs associated with drug resistance Minimum depth and consensus threshold for a valid call and whether these apply to each DNA strand
- Genotyping methodology used - VNTR profiles and lineages/ families assignation - Number of transmission events identified using genotyping and confirmed by epidemiological data; - Number of transmission events identified using genotyping and confirmed by WGS
- Criteria used to detect transmission using WGS (genetic distance between isolates in SNPs) - WGS sensitivity, specificity, PPV and NPV using epidemiological investigation data as a gold standard
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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TB isolates not related to outbreaks as well as full sets of epidemiological, genotyping and WGS data. Minimal reporting and quality criteria for WGS studies are imperative to ensure the highest level of evidence.
[17]
Acknowledgements Q2
This study has received funding from the European Centre for Disease Prevention and Control (ECDC) under the Grants 2009/004 and 2014/001. The funding body had no role in the study design or data analysis
Q3
Funding:
Q4
Competing interests:
[16]
[18]
[19]
None.
Ethical approval:
None declared. Not required.
Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.tube.2016.02.009
[20]
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[22]
[23]
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Contents lists available at ScienceDirect
Tuberculosis journal homepage: http://intl.elsevierhealth.com/journals/tube
REVIEW
Q10 Q9
Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review Vlad Nikolayevskyy a, b, *, 1, Katharina Kranzer a, c, d, 1, Stefan Niemann d, e, Francis Drobniewski a, b a
PHE National Mycobacterium Reference Unit, 2 Newark Street, E1 2AT London, United Kingdom Department of Medicine, Imperial College London, Du Cane Road, W12 0NN London, United Kingdom London School of Hygiene and Tropical Medicine, London, UK d National Reference Center for Mycobacteria, Forschungszentrum Borstel, Leibniz-Zentrum für Medizin und Biowissenschaften, D-23845 Borstel, Germany e German Center for Infection Research (DZIF), Partner Site Hamburg-Borstel-Lübeck, D-23845 Borstel, Germany b c
a r t i c l e i n f o
s u m m a r y
Article history: Received 22 November 2015 Received in revised form 22 February 2016 Accepted 29 February 2016
Contact tracing complemented with genotyping is considered an important means of understanding person-to-person transmission of tuberculosis (TB). It still remains unclear whether Whole Genome Sequencing (WGS) of Mycobacterium tuberculosis can rule in transmission and how it performs in different human populations, risk groups and across TB lineages. This systematic review aimed to determine the sensitivity and specificity of WGS for detection of recent transmission using conventional epidemiology as the gold standard and investigate if WGS identifies previously undetected transmission events. Systematic review was conducted according to the criteria of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses group. A compound search strategy was developed to identify all relevant studies published between 01/01/2005 and 30/11/2014 using three online databases. Publications satisfying specific criteria have been identified and data extracted. A total of 12 publications were included. We established that WGS has a higher discriminatory power compared to conventional genotyping and detects transmission events missed by epidemiological investigations. A cut-off value of <6 SNPs between isolates may predict recent transmission. None of the studies performed a head-to-head comparison between WGS and conventional genotyping using unselected prospectively collected isolates. Minimum reporting criteria for WGS studies have been proposed and quality control parameters considered. Crown Copyright © 2016 Published by Elsevier Ltd. All rights reserved.
Keywords: Tuberculosis Epidemiology Transmission Next generation sequencing
1. Background Tuberculosis (TB) remains a serious public health problem killing more than 1.7 million people annually [1]. The varying impact of control measures in different settings highlights the need for better diagnostics, treatment, preventive strategies and improved understanding of transmission at the population level.
* Corresponding author. PHE National Mycobacterium Reference Unit, 2 Newark Street, E1 2AT London, United Kingdom. Tel.: þ44 207 3775895. E-mail address: [email protected] (V. Nikolayevskyy). 1 These authors contributed equally to the study.
Since the 1990s molecular epidemiological studies have provided valuable insights into the phylogeography of Mycobacterium tuberculosis complex (MTBC), its evolutionary pathways and population and nosocomial transmission helping to distinguish between reinfection and re-activation and detect laboratory crosscontamination [2e5]. Contact tracing complemented with MTBC genotyping is considered an important means of understanding person-to-person transmission. However, due to competing priorities and limited resources, nation-wide prospective genotyping has only been implemented in few high income countries such as the United Kingdom, the Netherlands, Finland and the United States [6e9]. It is less clear whether genotyping itself is cost-
http://dx.doi.org/10.1016/j.tube.2016.02.009 1472-9792/Crown Copyright © 2016 Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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effective and has any added value beyond contact tracing from an immediate public health point of view [6]. Over the past two decades, methods in MTBC genotyping have evolved from non-PCR based methods to more reproducible and less cumbersome methods such as spoligotyping and 24-lociMIRU-VNTR typing (Mycobacterial Interspersed Repetitive UnitsVariable Number of Tandem Repeats). These methods utilize variations in repetitive sequences in MTBC strains and produce results in digital format enabling portability of results and creation of national and international databases for routine and research purposes [10]. MIRU-VNTR genotyping using a standardised set of 24 loci is currently in use for routine MTBC genotyping in many European countries and globally [11,12]. Online analysis tools for lineages identification are available via online databases e.g. MIRUVNTRplus (www.miru-vntrplus.org) or SITVIT-WEB (www.pasteurguadeloupe.fr:8081/SITVIT_ONLINE/) [13]. Although introduction of MIRU-VNTR genotyping has significantly enhanced our knowledge in MTBC phylogeny and global transmission, its discriminatory power for prospective epidemiological investigations might be limited in some circumstances. It is an established method to rule out transmission in epidemiologically linked cases but ruling in transmission events is more problematic especially in endemic regions and/or where highly conserved genotypes (e.g. Beijing) prevail [14e16]. Although the VNTR molecular clock is considered to be relatively slow, there is some evidence suggesting that VNTR profiles evolve both within individuals and across transmission events as shown during longterm outbreaks [16,17]. High throughput whole genome sequencing (WGS) based on Next Generation Sequencing (NGS) technologies offers new opportunities both in research and public health including TB laboratory diagnosis and molecular epidemiology [2,5,18]. NGS allows sequencing nearly full genomes of multiple strains simultaneously saving time, simplifying the workflow and providing considerably more information compared to traditional methods with unprecedented accuracy [18,19]. WGS resequencing allows one to assemble a genome against a known reference and identify various polymorphisms, including SNPs and indels potentially important for epidemiology, diagnosis, drug resistance detection and phylogenetic investigations [2,20]. The past decade has seen a considerable expansion of sequencing capacity improving its availability for routine laboratories in high-income countries. Template amplification platforms with a variety of chemistries, both high-end and bench-top instruments are currently in use with single molecule sequencing technologies being under development [20,21]. Following the first outbreak investigation using WGS [22], several studies have shown the utility of WGS in the context of epidemiological investigations [16,23,24]. These studies suggest that WGS provides better discriminatory power than VNTR typing improving accuracy, resolving false clusters and, importantly, potentially saving money and resources of public health teams by preventing unnecessary actions [16]. The M. tuberculosis genome mutation rates were estimated at 0.5 single nucleotide polymorphisms (SNPs) per genome per year and a threshold of genetic distance of less than 6 SNP for strains from direct human to human transmission (suggesting recent transmission) was proposed [16,25]. Importantly, data obtained through WGS is of dual use also providing a crucial information on the mutations associated with drug resistance potentially making it a versatile tool in TB laboratory diagnosis [2,5,18]. It remains unclear whether WGS can more reliably rule in transmission and whether it is specific enough to identify cases truly involved in recent transmission chains. The value of classical genotyping techniques in TB-related epidemiological investigations
is well established while the role of WGS has not been accurately defined. Whether NGS genotyping has a variable performance in different human populations, risk groups and across TB lineages is yet to be investigated. To address these issues, we conducted a systematic review to determine the sensitivity and specificity of WGS for detection of recent transmission chains using conventional epidemiological data as a gold standard. We further investigated if WGS provides any additional information compared to classical genotyping and or conventional epidemiology with regards to identification of previously undetected transmission events and/or ruling out person-to-person transmission. 2. Methods This systematic review was conducted according to the criteria of the Preferred Reporting Items for Systematic Reviews and MetaAnalyses group [26]. The protocol was registered with PROSPERO (registration number CRD42015023675). 2.1. Inclusion and exclusion criteria Cross-sectional and cohort studies published between 1st January 2005 and 30th November 2014 were eligible for inclusion if they reported on individuals with culture positive TB disease. No geographical or language restriction was applied. Studies were included if WGS, molecular fingerprinting of M. tuberculosis complex isolates (IS6110 RFLP and/or multilocus VNTR typing) and conventional epidemiology data determining transmission chains, events and outbreaks were available. Review papers and studies with incomplete data sets were excluded. 2.2. Outcome measures The following types of outcome measures were recorded: - Number of transmission events detected by WGS and/or genotyping confirmed by conventional epidemiological data; - WGS performance characteristics (sensitivity, specificity, PPV, NPV) compared to conventional epidemiological data; - Number of subclusters/transmission chains identified using WGS within original RFLP- and/or VNTR-determined clusters.
2.3. Search strategy A compound search strategy was developed to identify all relevant studies regardless of language or publication status using MEDLINE (OVID), EMBASE (OVID), and Web of Science electronic databases (see Supplementary Tables 1 and 2). All references identified by the compound search strategy were imported into EndNote. Duplicates were removed. Titles and abstracts were examined in duplicate by two reviewers (VN and KK) and irrelevant studies were excluded. Full texts of all potentially relevant studies were obtained and inclusion criteria applied using a standardised eligibility form. Reference lists of all studies identified by the above methods and bibliographies of reviews and editorials were examined and additional references were identified satisfying original eligibility criteria [27]. Final agreement on study inclusion was determined through consensus between the two reviewers (VN and KK). 2.4. Data extraction and management Data extraction was performed independently, in duplicate, using a standardized data extraction form. The following data was
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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extracted: year, setting (country, city), duration of sampling, number of isolates included, risk group/population status and genetic lineages, primary and secondary (if available) genotyping method used, outcome measures. Additionally, relevant technical details such as WGS platform, SNPs genetic distances within epidemiologically linked and genotypically linked subjects, genome coverage/sequencing depth, quality control criteria and the exclusion/inclusion criteria which were applied to call polymorphisms were extracted. 2.5. Analysis A PRISMA diagram was constructed. The sensitivity and the specificity of MIRU-VNTR and WGS compared with conventional epidemiology were calculated using the following assumptions and definitions: - Number of links identified by genotyping: although some patients may be linked to more than one patient, and number of pairwise combinations within larger RFLP/VNTR clusters with identical profiles could be in theory hundreds or thousands, for the purposes of the current review we adopted a previously described approach [16], and assumed that the number of links identified by genotyping was equal to the number of strains within a cluster minus one and applied this definition to all studies for sensitivity and specificity calculations. - Number of links identified by WGS: unlike genotyping, WGS may allow to determine the direction of transmission. Even closely genomically related strains (i.e. within 0…5 SNPs genetic distance) may not represent actual direct transmission events. For the purposes of the current review, we assumed that any two strains within 5 SNP genetic distances (termed genomically linked) could be involved in direct transmission. Therefore in the current review the number of links identified by WGS is equal to the number of genomically linked strains. The number of transmission chains/subclusters identified using WGS within genotyping clusters was determined. 2.6. Quality assessment Currently there are no formally recognised criteria to assess the quality of WGS based studies. With regards to quality assessment of individual studies conventional criteria such as sampling frame and completeness were determined to assess selection bias. Reported quality criteria for the method itself, including genome coverage and sequencing depth, as well as specific cut-off values and reading consensus rates for valid SNP calls were derived from all studies. 3. Results
3
M. africanum isolates were sequenced. Two studies conducted social network analysis [22,29]. Only one study was conducted in a high TB incidence setting in China [29], the others were conducted in the Netherlands (n ¼ 3), United Kingdom (n ¼ 3), Germany (n ¼ 2), Canada (n ¼ 2), and USA (n ¼ 1). Methods used for genotyping varied across studies. PCR-based methods (MIRU-VNTR typing and spoligotyping) and non PCR-based methods (IS6110 RFLP) were utilised in 5 and 4 studies, respectively. In three studies both PCR- and non-PCR based methods were used in parallel. In a proportion of studies non-standard and/or incomplete sets of VNTR loci (12, 15, or 16 loci plus hypervariable loci) were used [16,29,31,36]. 3.3. Study design, human populations and M. tuberculosis genetic lineages In all but one study [35], historical TB outbreaks were analysed. In five studies genotyped isolates belonged to long-term TB outbreaks lasting from 18 months to 17 years confined to specific geographical settings (towns, provinces or metropolitan areas). One population-based study conducted in the UK utilised a nondiscriminatory sampling strategy and WGS was performed on strains isolated from patients with and without confirmed epidemiological links [35]. In the majority of studies (n ¼ 10) selection of MTBC isolates for sequencing was based on availability of conventional genotyping results so only strains clustered using molecular genotyping methods (IS6110 RFLP and/or multilocus VNTR) and therefore considered part of TB outbreaks were sequenced; no strains outside those clusters were included. The total number of IS6110 RFLP or multilocus VNTR clusters within a given study varied from 1 to 42; in two studies original clusters formed by a primary genotyping method were further split into smaller groups using secondary methods [32,33]. Information on M. tuberculosis genetic groups and lineages was derived from VNTR genotyping, spoligotyping and/or WGS data and reported in nine studies. Two more studies reported VNTR codes, but those could not be unambiguously assigned to any known family using international databases [22,32]. Two studies included exclusively East Asian (Beijing family) strains (N ¼ 34) [29,37], three more studies e Euro-American (Haarlem family) strains (N ¼ 121) [24,31,33], and two small studies included a total of three EuroAmerican strains belonging to the T family [23,30]. Two larger studies included strains from all major lineages (N ¼ 416) [16,28]. None of the studies specifically focused on high-risk groups; some studies included high-risk, foreign-born patients or ethnic minorities. Individuals belonging to high-risk groups such as the homeless, recreational drug users, and people living with HIV comprised over 60% of individuals in two Canadian studies [22,32]. The studies conducted in the UK and Germany included a significant (although unspecified) proportion of foreign-born individuals.
3.1. Study selection A total of 2085 publications were identified; 59 studies were selected for full text review, 47 of those were excluded leaving 12 studies being included in the current systematic review [16,22e24,28e35]. PRISMA diagram is depicted on Figure 1. 3.2. General characteristics of included studies
Q1
The characteristics of included studies and relevant outcome data are summarised in Tables 1 and 2. WGS data was available for 1088 MTBC isolates. The number of isolates included in each study varied from 2 to 390. All but one report included M. tuberculosis isolates only; in one study [16] a small number of M. bovis and
3.4. Relevant technical data, quality control and polymorphisms calling criteria WGS is a novel method that has emerged over the last few years. Commercial kits covering all stages of analysis are not available so ‘wet’ laboratory technology and data processing pipelines have not been fully standardised. Data summarizing the technical details are presented in Table 3. All studies reported the sequencing chemistry platform and hardware used for sample analysis. Two studies used 454 technology, and the rest used various versions of Illumina including GeneAnalyser (n ¼ 2), Hi Seq (n ¼ 3), and MiSeq (n ¼ 2). Genome coverage and average sequencing depth were reported in 8 of the
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
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Figure 1. PRISMA study selection flow diagram.
12 studies and varied from 88.5% to 99.2% and from 50.9 to 174, respectively. Principal QC criteria applied at analytical stages included minimum depth for valid single nucleotide polymorphisms (SNP) call, minimum consensus rate for valid call and exclusion of certain types of polymorphisms depending on their nature and location. SNPs associated with drug resistance and indels were not included in any studies while SNPs located in repetitive and high GC-rich regions (including PE/PPE and ESX genes) were included in one study [22], and not reported in two. Exclusion criteria and rules applied to polymorphisms located within 12 bp of each other, as well as information on whether DNA was extracted from single colonies, was not systematically reported. Minimum depth for valid
SNP call and minimum consensus rate for valid SNP calls were reported in 5 and 8 studies and ranged from 10 to 20 and from 75% to 90%, respectively. There was no clarity whether these criteria were applied to each DNA strand separately. 3.5. Genetic distances between M. tuberculosis strains isolated from patients with confirmed epidemiological links Genetic distances between strains isolated from patients with confirmed epidemiological links were reported in all but two studies and ranged from 0 to 1746; in the majority of studies (N ¼ 7), they did not exceed 5 SNPs. There was a total of 23 epidemiological links (7.4% of the total number of transmission
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
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Table 1 General characteristics of the studies. Publication
Primary genotyping method used
Epi data
Country
Settings
Risk groups
M. tuberculosis lineages
Duration of sampling (longest time interval(s) between isolates within suspected outbreaks)
Schurch et al., 2010a Schurch et al., 2010b
Contact tracing, interviews Contact tracing, interviews
Netherlands Netherlands
Low incidence Low incidence
Not reported Not reported
Not reported Not reported
13 years 13 years
Gardy et al., 2011
IS6110 RFLP IS6110 RFLP, 24 VNTR, spoligotyping 24 VNTR
Canada
Low incidence
No HIV infected
Not reported
30 months
Bryant et al., 2013
IS6110 RFLP
Contact tracing, interviews, social network analysis Contact tracing, interviews, stone-in-the-pond principle
Netherlands
Low incidence
Not reported
16 years
Luo et al., 2013
16 þ 2 VNTR, 6 SNPs
Contact tracing, interviews, social network analysis
China
High incidence
Not reported
Kato-Maeda et al., 2013
Contact tracing, interviews
USA
Low incidence
Roetzer et al., 2013
IS6110 RFLP, 12 VNTR, spoligotyping IS6110 RFLP
Contact tracing, interviews
Germany
Low incidence
Euro-American (Haarlem family)
13 years
Torok et al., 2013
24 VNTR
Contact tracing, interviews
United Kingdom
Low incidence
15 or 24 VNTR
Contact tracing, interviews
United Kingdom
Low incidence
Kohl et al., 2014
IS6110 RFLP, spoligotyping 24 VNTR, spoligotyping
Contact tracing, interviews
Germany
Low incidence
Not reported
Contact tracing, interviews
Canada
Low incidence
17 years
e
Contact tracing, interviews
United Kingdom
Low incidence
Outbreak associated with high risk populations (homeless/HIV infected and drug abusers) Not reported
East Asian (Beijing family) All major lineages, M. bovis and M. africanum Euro-American (Haarlem family) Not reported
e
Walker et al., 2013
Foreign-born individuals, ethnic minority Outbreak associated with high risk populations (homeless and alcohol abusers) Foreign-born individuals Not reported
Euro-American, East Asian, East-African Indian, Indo-Oceanic East Asian (Beijing family modern sublineage) Euro-American (Haarlem family)
All major lineages
e
Q8
Mehaffy et al., 2014
Walker et al., 2014
events across all studies) where genetic distances between isolates were over 12 SNPs; eighteen of those (>100 SNPs, exact distances not specified) occurred in a Chinese study where epidemiological investigations were challenging [29]. Applying more stringent criteria for epidemiological linkage (<6 SNPs) only marginally increased the proportion of genomically unconfirmed links (29 links, 9.4%). 3.6. Sensitivity and specificity of WGS and genotyping using epidemiological data as a gold standard Performance characteristics of WGS and genotyping (sensitivity, specificity, PPV and NPV) were not systematically reported in the reviewed papers and were calculated as described in the Methods section. All studies reporting conventional genotyping data selected isolates on the basis that they were indistinguishable by IS6110 RFLP and/or VNTR typing so sensitivity and specificity of conventional genotyping data could not be determined. The only study performing non-discriminatory testing reported on WGS data only and did not include any genotyping data [35]. WGS performance characteristics had to be interpreted in the context of the sampling frame. Within VNTR/RFLP clusters, nearly all transmission events identified by conventional epidemiology were confirmed by WGS resulting in high sensitivity (100% in 8 out of 12 studies). Data to calculate specificity was available in five
18 months
22 months
12 years
10 years
studies [16,24,29,32,35]. Within RFLP/VNTR-defined clusters, WGS identified a significant number of isolates with less than 5 SNP difference (suggesting transmission) despite non-established epidemiological links resulting in specificity ranging from 17 to 95% using conventional epidemiology as a gold standard. 100% sensitivity rates were reported for different lineages including East Asian (Beijing family) and Euro-American (Haarlem family). Two studies did not stratify transmission events by lineage [16,28]. 3.7. Identification of transmission chains using WGS and overall comparison with conventional genotyping WGS had a higher discriminatory power compared to IS6110 RFLP and/or VNTR to identify separate transmission chains within RFLP/VNTR clusters. WGS allowed the identification of two independent transmission chains within two clusters defined by indistinguishable IS6110 RFLP/VNTR profiles in Canada. These results were in agreement with contact tracing data and geographical distribution of isolates [22,32,33]. One of the subclusters identified using WGS in the Canadian study was comprised of strains harbouring a 15 kB deletion which was not detected by MIRU-VNTR typing [32]. In another study conducted in Germany two additional clusters were identified within a cluster defined by IS6110 RFLP [33]. In a small study conducted in the UK WGS allowed the identification of a previously missed transmission event [37].
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
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Table 2 Principal findings. Publication
No of isolates sequenced
Schurch et al., 2010a Schurch et al., 2010b
3 (One RFLP cluster) 2 (One RFLP/VNTR/spoligo cluster)
Gardy et al., 2011
No of epi links
No of links identified by WGS (<6 SNPs genetic distance)
No of links identified by genotyping*
2 1
2 1
2 1
36 (One VNTR/RFLP cluster)
19
e
35
Bryant et al., 2013
199 (42 RFLP clusters)
97
149y,¶
Luo et al., 2013
32 (3 16VNTR clusters)
24
Kato-Maeda et al., 2013
9 (One genotyping cluster)
Roetzer et al., 2013
Torok et al., 2013 Walker et al., 2013
Kohl et al., 2014 Mehaffy et al., 2014
Walker et al., 2014
No of links identified by WGS (<6 SNPs genetic distance) and confirmed by epidemiology 2 1 e
157
89¶
10
29
10
7
10
8
7
86 (One RFLP cluster; VNTR further subdivided into five groups) 2 (One 24 VNTR cluster)
31
85
85
31
0
1
1
217 from 168 patients within 11 VNTR clusters (6…47 cases) 26 (One RFLP/spoligo cluster)
69
142
157
69
14
22
25
14
18
39
55
18
28x
26¶
56 (One VNTR/spoligo genotyping cluster further split into three “pseudo clusters” using RFLP) 247
e
11
WGS sensitivityz and specificity (<6 SNPs genetic distance) 100% 100% e e e 91.8% e 100% 95.0% 100% e 100% e e e 100.0% 17.0% 100% 27.2% 100% 29.2% 78.5% 93.5%
*
Number of links identified by genotyping ¼ number of strains within an RFLP/VNTR cluster minus one. Values calculated using the data available in the publications and Supplementary data. In all but one study (Walker et al., 2014), only isolates clustered based on genotypical investigations (VNTR and/or RFLP) were included which introduced significant bias into calculations of WGS sensitivity and made impossible to calculate genotyping sensitivities and specificities x Including 12 culture-negative cases and two isolates with no WGS data ¶ Identified using <12 SNPs criteria y z
Overall, in most studies only a proportion of strains within clusters defined by indistinguishable IS6110 RFLP and/or VNTR were genomically linked (using both <6 and <12 SNP criteria). This confirms the limited discriminatory power of conventional genotyping methods for prospective epidemiological investigations. 4. Discussion Previous studies indicated that WGS sequencing provides a higher discrimination of clinical MTBC isolates compared to classical genotyping e.g. based on MIRU-VNTR typing but this has not been investigated systematically to date. By performing a systematic analysis of 12 studies, this review confirms the notion that WGS has a higher discriminatory power and is able to subdivide clusters defined by classical genotyping. Studies included in this review have shown that the proposed cut-off value of <6 SNPs could be used for identification of isolates involved in direct human-tohuman TB transmission [16]. No study has yet performed a head-to-head comparison between WGS and conventional genotyping using unselected prospectively collected isolates. All studies except one included in this review have used a selective sampling strategy, where isolates found to be identical by conventional genotypic methods were then retested using WGS. It was therefore impossible to evaluate sensitivity and specificity of different genotyping methods compared to conventional epidemiological investigations. Performance characteristics of WGS described in this review are subject to selection bias due to the particular strategies used in the original studies. Hence, sensitivity and specificity estimates need to be
interpreted with caution, and should be confirmed in future studies utilising non-discriminatory sampling of specimens. Overall sensitivity of WGS to identify epidemiologically linked isolates was high. WGS allowed one to distinguish between isolates sharing identical genotyping patterns potentially separating transmission chains within RFLP/VNTR clusters. WGS identified false clustering ruling out false transmission events. Some studies showed that WGS was in better agreement with contact tracing data and geographical distribution of isolates. Specificity of WGS for detection of recent transmission chains using conventional epidemiology as a gold standard varied across studies (17.0e95.0%). A high number of “false positive” results might raise concerns about its applicability to ruling in transmission; however, these results may actually represent transmission events missed by conventional epidemiology or linked to other problems with the conventional epidemiology data collection, interpretation and quality. Conventional epidemiology is an imperfect gold standard itself especially in high TB incidence settings and is influenced by the method used and resources available [29,38]. This review has several strengths and limitations. The review used an extensive search strategy applying international criteria of the Preferred Reporting Items for Systematic Reviews and MetaAnalyses group. Due to heterogeneity of data a meta-analysis was not possible and lack of internationally agreed quality criteria for WGS studies in the context of TB epidemiology and laboratory diagnosis made quality assessment challenging. Limitations of studies included in this review included the retrospective nature of the study design, selection bias, small sample sizes in some studies,
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
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Table 3 WGS technical data. Publication
WGS genome WGS average Platform/methodology used coverage depth
PE/PPE/PGRS Minimum Minimum and repetitive depth for consensus valid call rate threshold sequences for valid call
No of SNPs between isolates with confirmed epi links, range
No of SNPs between isolates clustered using genotyping
Schurch et al., 2010a Schurch et al., 2010b Gardy et al., 2011 Bryant et al., 2013
95.4% 97.0% 99.2% 95.6%
50.9 e 174 100
e e Included Excluded
e e e e
e e 70% 75% on each strand
4 4 e 0…149 SNP
Luo et al., 2013 Kato-Maeda et al., 2013 Roetzer et al., 2013 Torok et al., 2013 Walker et al., 2013
e 95.7% 96.4% e 88.5%
100 Illumina HiSeq 300 bp reads 73 Illumina GA 36 bp reads e 454 (one strain) and Illumina 82 to 102 Illumina MiSeq 150 bp reads e Illumina HiSeq 75 bp reads
Excluded Excluded Excluded e Excluded
10 12 10 e e
e 85% 80% 75% 75%
>100 0…2 0…3 n/a 0…5
Kohl et al., 2014 Mehaffy et al., 2014 Walker et al., 2014
e e 92%
84 e 106
Excluded Excluded Excluded
10 20 e
75% 75% 90%
0…5 0…4 0…1746
8 4 204 95% of RFLP-linked isolates had SNP distances <11 SNPs 108 7 85 0 0…150 (up to two mismatches in VNTR clusters) 322 81 n/a
454 Platform 454 Platform 250 bp reads Illumina 50 bp reads Illumina GAIIx 76e108 bp reads
Illumina MiSeq Illumina Illumina HiSeq
lack of data related to specific M. tuberculosis lineages and populations such as high risk groups. This review was unable to assess the difference of performance of WGS for different lineages of M. tuberculosis, as only few studies stratified their analysis by lineage. In future studies using WGS methodology are likely to become prolific. Developing minimal criteria for reporting and assessment of quality is important as such criteria have been agreed for other studies such as observational studies and clinical trials [39,40]. We take the opportunity to introduce minimum list of technical parameters, as well as outcomes and performance characteristics for studies using WGS technology that should be included in future reports to ensure comparability of studies and improve quality (Table 4). Consensus on cut-off values and thresholds for certain technical parameters including minimum depth for a valid SNP call and criteria for minor alleles is yet to be reached and applied in future studies. Results of our study also highlight an importance of development and implementation of quality assurance schemes for WGS. MIRU-VNTR genotyping is currently in routine use for prospective molecular epidemiology investigations in several
European countries and globally [3]. However, lack of discriminatory power and concerns regarding its cost-effectiveness and overall value in TB clinical and diagnostic management have been raised [6,15]. While WGS might address the issue of increased discriminatory power, the question of added value remains. WGS is a tool, which may provide answers to specific questions such as transmission chains and cross-border transmission and may evolve into a practical instrument used to cover the majority of laboratory diagnoses, including identification, provide indication of drug resistance testing and epidemiological typing. However, its impact in routine day-to-day public health and clinical investigations remains to be demonstrated. In the current review we established that WGS has a higher discriminatory power compared to conventional genotyping and is able to further divide false clusters potentially eliminating the need for unnecessary public health actions. WGS may also identify transmission events missed by conventional epidemiological investigations. The impact of WGS in resolving TB outbreaks, realtime TB epidemiology, and molecular surveillance is yet to be established. Future studies should be population-based including
Table 4 Study characteristics, results, outcomes and technical parameters proposed for inclusion in the WGS reports.
Parameters, outcomes, characteristics and other details
Study design and epidemiological data
Technical data
Conventional genotyping
Whole genome sequencing
- Study design (prospective/ retrospective, population-based, longitudinal, etc.) - Target populations, presence of high risk groups; - TB settings (low-, high, etc.) - Length of the study - Type of epidemiological data available and how it was collected - Number of transmission events identified using epidemiological investigations (confirmed/ unconfirmed)
- Hardware platform and chemistry used; - Length of reads; - Genome coverage and depth; - Bioinformatics analysis parameters and criteria for calling polymorphisms: Exclusion or inclusion of indels Exclusion or inclusion of SNPs in repetitive sequences, PE/ PPE, ESX and similar genes; Exclusion or inclusion of SNPs located within certain distance (e.g. 12 bp) Exclusion or inclusion of SNPs associated with drug resistance Minimum depth and consensus threshold for a valid call and whether these apply to each DNA strand
- Genotyping methodology used - VNTR profiles and lineages/ families assignation - Number of transmission events identified using genotyping and confirmed by epidemiological data; - Number of transmission events identified using genotyping and confirmed by WGS
- Criteria used to detect transmission using WGS (genetic distance between isolates in SNPs) - WGS sensitivity, specificity, PPV and NPV using epidemiological investigation data as a gold standard
Please cite this article in press as: Nikolayevskyy V, et al., Whole genome sequencing of Mycobacterium tuberculosis for detection of recent transmission and tracing outbreaks: A systematic review, Tuberculosis (2016), http://dx.doi.org/10.1016/j.tube.2016.02.009
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TB isolates not related to outbreaks as well as full sets of epidemiological, genotyping and WGS data. Minimal reporting and quality criteria for WGS studies are imperative to ensure the highest level of evidence.
[17]
Acknowledgements Q2
This study has received funding from the European Centre for Disease Prevention and Control (ECDC) under the Grants 2009/004 and 2014/001. The funding body had no role in the study design or data analysis
Q3
Funding:
Q4
Competing interests:
[16]
[18]
[19]
None.
Ethical approval:
None declared. Not required.
Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.tube.2016.02.009
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[21]
[22]
[23]
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Q5
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