1. Division of Tuberculosis Elimination
Making the journey from conventional genotyping to whole-genome sequencing for investigating TB transmission
Sarah Talarico, PhD, MPH
Surveillance, Epidemiology, and Outbreak Investigation Branch
and Laboratory Branch
California Tuberculosis Controllers Association Conference
March 12, 2019

2. Conflict of Interest
None to declare 2

3. Learning objectives
At the end of this presentation, participants will be able to describe
Key differences between conventional genotyping and WGS
What is being represented on a phylogenetic tree
How WGS is used to assess whether patients are potentially linked by recent transmission
Plans for the transition to using WGS as the standard method for TB genotyping 3

4. Why combine genotypic data with clinical and epidemiologic data to understand TB transmission?
Challenges to relying exclusively on epidemiologic investigation
Airborne transmission
Exposure in congregate settings
Long infectious periods
Patient recall may be incomplete or unreliable
Often in impoverished or marginalized communities
Genotypic data can provide additional, complementary information to aid detection and investigation of transmission
Genotyping identifies cases with genetically similar M. tuberculosis isolates that are more likely to be linked by transmission 4

5. Genotyping examines the DNA of M
Genotyping examines the DNA of M. tuberculosis isolates from TB patients
The M. tuberculosis bacteria from a TB patient is called the patient’s isolate
Bacteria, including M. tuberculosis, have DNA called a genome
DNA is made up of four different nucleotides (abbreviated A, T, C, and G)
The order of these nucleotides in the genome is the DNA sequence
The genome of M. tuberculosis is over 4.4 million nucleotides long 5

6. Genotyping can be used to identify TB patients who are more likely to be linked by recent transmission
Changes in the DNA (mutations) occur over time, so M. tuberculosis bacteria don’t all have the exact same DNA sequence
At the time of transmission, the person transmitting the infection and the person acquiring the infection will have M. tuberculosis with identical DNA sequence
Genotyping analyzes DNA to identify TB patients with similar M. tuberculosis genomes who are more likely to be linked by recent transmission 6

7. Detecting Clusters of Recent Transmission using Genotyping
2 or more isolates with the same genotype are clustered
Algorithms that consider time and space are used to identify clustered cases that may be due to recent transmission
CDC cluster detection methods
LLR cluster alerts: Unexpected increase in concentration of a genotype in a jurisdiction during a 3-year time period
Large outbreak surveillance: 10 or more cases in a 3-year period related by recent transmission 7

8. Conventional M. tuberculosis genotyping is based on only ~1% of the genome8

9. Conventional genotyping vs. Whole-genome sequencing (WGS)

10. Conventional genotyping
Coverage of the genome
Conventional genotyping
WGS
1% coverage
90% coverage
Adapted from: Guthrie JL, Gardy JL. Ann N Y Acad Sci Dec 23. doi: /nyas.13273 10

11. Types of genomic changes analyzed
Conventional genotyping
WGS
A T G G C G T C A C G G T C A G
ATGGCGTACG
ATGGCGTACG
ATGGCGTACG
Example: change between 3 and 2 repeat segments
Example: mutation that changes C to T in DNA sequence
A T G G C G T T A C G G T C A G
ATGGCGTACG
ATGGCGTACG
Gain or loss of segments of DNA sequence within certain repetitive regions
Single nucleotide polymorphisms (SNPs) throughout the genome 11

12. Whole-genome SNP analysis (wgSNP)
A T G G C G T C A C G G T C A G
A T G G C G T T A C G G T C A G
SNPs that differ between isolates in a cluster are identified
SNPs are mapped on to a phylogenetic tree to diagram the genetic relationship among isolates 12

13. Conventional genotyping
Results
Conventional genotyping
WGS
Cluster of isolates with GENType X
Phylogenetic tree of isolates in GENType X cluster
GENType
Isolates are clustered based on matching GENType
Phylogenetic tree
Isolates in a cluster may be further distinguished 13

14. WGS analysis: interpretation of the phylogenetic tree

15. Guide for interpreting the phylogenetic tree
Isolates are shown as circles (called nodes)
Isolates with the same genome type are displayed together in one node
Lines are proportional in length to the number of SNPs that differ between the isolates
Lines are labeled with the number of SNPs 15

16. Guide for interpreting the phylogenetic tree
MRCA = Most Recent Common Ancestor
Hypothetical genome type (not an actual isolate)
All isolates on the tree are descended from this hypothetical genome type
Serves as a reference point for examining the direction of genetic change
( ) 16

17. Guide for interpreting the phylogenetic tree=
genetically distant isolates that are unlikely to be involved in recent transmission
In general, isolates that differ by 6 or more SNPs are considered genetically distant
Closely related isolates that may be involved in recent transmission
In general, isolates within 5 SNPs are considered closely related 17

18. Limitations of WGS analysis for understanding TB transmission
Recent transmission is easier to rule out than to confirm with WGS
Even isolates that are closely related or identical by WGS can be due to reactivation
This is because mutations may not occur as frequently during latent infection and therefore SNPs may not accumulate
A phylogenetic tree shows how isolates are genetically related to each other, but is not the same as a transmission diagram
WGS alone should not be used to infer direction of TB transmission
Important to consider if isolates may be missing from the analysis
Examples: Cases that are not yet diagnosed, not culture-confirmed, out-of-country, or have contaminated isolates
The phylogenetic tree should be used in conjunction with clinical and epidemiologic information to assess recent transmission and infer direction of TB transmission 18

19. Integration and visualization of WGS, clinical, and epidemiologic data
LITT algorithm (Logically Inferred Tuberculosis Transmission)
Automated integration of WGS, clinical, and epi data to identify and rank potential source cases
MicrobeTrace data visualization platform
Developed by Division of HIV/AIDS Prevention
Visualization of WGS, clinical ,and epi data together
Epi and transmission networks, timelines, phylogenetic trees, and maps ? 1 2 3
LITT algorithm
Surveillance data
Epi investigation data
WGS data ( 19

20. Transition to universal prospective WGS

21. Retrospective WGS of GENType clusters in the United States
D.C.
Number of isolates with whole-genome sequencing data*
>0 to 10
>10 to 20
>20
Puerto Rico
Guam
U.S. Virgin Islands
Marshall Islands
Fed. States of Micronesia
American Samoa
N. Mariana Islands
Republic of Palau
*N = 3,700 isolates, data current as of Aug. 2018
2012: first WGS of a GENType cluster
2014: WGS performed for all large outbreak alerts
2016: WGS expanded to include other select GENType clusters that could inform public health
WGS and phylogenetic analysis of >200 clusters nationally to date 21

22. Transition to universal prospective WGS
WGS of isolates from all new culture-confirmed cases of TB began in March 2018
GENType will continue to be analyzed during an initial 3 year transition period (2018 – 2020)
GENType will be reported in TB GIMS
Cluster alerts will be based on GENType
Still have some capacity to sequence isolates retrospectively
Isolates before March 2018: Retrospective WGS by request
Isolates after March 2018: Prospective WGS for all isolates 22

23. Transition to universal prospective WGS
In 2021, WGS will become the standard method for TB genotyping
wgMLST will replace GENType for defining TB clusters
wgMLST = whole-genome multi-locus sequence typing
wgMLST is a new genotyping scheme that uses WGS data
Conventional genotyping
wgMLST
24 Loci MIRU + Spoligotype
> 3,000 Loci
GENType
wgMLSType 23

24. Transition to universal prospective WGS
Step 1. Define a cluster
Step 2. Examine genetic relationship among isolates in the cluster
Currently: GENType
(conventional genotyping)
Starting 2021: wgMLSType
(WGS data)
wgSNP analysis 24

25. Analysis of clustering using WGS data: wgMLST vs. wgSNP
wgMLST
(whole-genome multi-locus sequence typing)
wgSNP
(whole-genome single nucleotide polymorphism)
Level of analysis
all isolates
isolates in a cluster
Use
assigning isolates to a wgMLSType that can be used for cluster alerting
examining genetic relationships among isolates in a cluster
Output
wgMLSType
(short string of numbers similar to a GENType)
phylogenetic tree 25

26. Universal prospective WGS began in 2018
TB Genotyping Methods and Data Flow (2018 – 2020) 26

27. wgMLSType will replace GENType for cluster alerting in 2021
TB Genotyping Methods and Data Flow (2021) 27

28. Summary
WGS can provide greater resolution than conventional genotyping for investigating recent TB transmission
Whole-genome SNP analysis is performed to produce a phylogenetic tree for examining genetic relationships between isolates in a genotype cluster
The phylogenetic tree should be interpreted in the context of epidemiologic and clinical data
Methods for integrating and visualizing WGS, epidemiologic, and clinical data to aid cluster investigations are being developed
We are transitioning to using WGS as the standard method for TB genotyping 28

29. Acknowledgements DTBE Applied Research Team
Jamie Posey
Lauren Cowan
DTBE Molecular Epi Activity
Ben Silk
Kala Marks Raz
Clint McDaniel
Kathryn Winglee
Association of Public Health Laboratories
Michigan State Public Health Laboratory 29