Sarah Talarico, PhD, MPH Surveillance, Epidemiology, and Outbreak Investigation Branch

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. 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 genome 8

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

10. Coverage of the genome Conventional genotyping WGS 1% coverage 90% coverage Adapted from: Guthrie JL, Gardy JL. Ann N Y Acad Sci. 2016 Dec 23. doi: 10.1111/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 Single nucleotide polymorphisms (SNPs) throughout the genome Gain or loss of segments of DNA sequence within certain repetitive regions 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. Results Conventional genotyping WGS Cluster of isolates with GENType X Phylogenetic tree of isolates in GENType X cluster Phylogenetic tree Isolates in a cluster may be further distinguished GENType Isolates are clustered based on matching GENType 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 • 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 Surveillance data Epi investigation data WGS data 2 1 3 (http://bit.ly/microbetrace) 19

20. Transition to universal prospective WGS

21. Retrospective WGS of GENType clusters in the United States 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 clustersnationally to date D.C. Puerto Rico Guam U.S. Virgin Islands Marshall Islands Fed. States of Micronesia American Samoa Number of isolates with whole-genome sequencing data* N. Mariana Islands Republic of Palau 0 >0 to 10 >10 to 20 >20 21 *N = 3,700 isolates, data current as of Aug. 2018

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 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