PulseNet Aotearoa New Zealand E. coli O157 & Campylobacter

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1 PulseNet Aotearoa New Zealand E. coli O157 & Campylobacter Angela Cornelius, Beth Robson, Carolyn Nicol, Phil Carter, Chris Pope, Brent Gilpin Institute of Environmental Science & Research, New Zealand Roger Cook NZ Food Safety Authority Specialist Science Solutions Manaaki Tangata Taiao Hoki protecting people and their environment through science

2 New Zealand 103,735 sq miles in size - Similar to California or Japan in size Population 4.0 million Dairy, meat exports - 40 million sheep - 10 million cattle - 90 million possum

3 The way the world really is.

4 PulseNet Aotearoa New Zealand Established PulseNet PFGE methodology for: - Campylobacter jejuni (2000 isolates) - E. coli (500 isolates) - Listeria monocytogenes (100 isolates) - Salmonella spp. (400 isolates) - Shigella Compatible with PulseNet USA, NOT equivalent.

5 USDA product testing - E. coli O157:H7 PFGE-XbaI PFGE-BlnI 1500 A B Key USDA_OB USDA_OB WA 9681 PFGE-XbaI-pattern EXHX EXHX EXHX PFGE-BlnI-pattern EXHA EXHA EXHA Meat Processor A Meat Processor B Supplier A Supplier B New Zealand Supplier C

6 Kristin Holt, USDA, FSIS Liaison to CDC Since a single establishment was identified as common to both facilities, we thought it would be of value to determine if the PFGE patterns and pattern combinations are found in New Zealand. I would appreciate your consideration of a query of the New Zealand PulseNet database to see if the patterns and pattern combinations are found there. FSIS is interested in knowing if the patterns have been identified in their database and, if so, additional information, such as data on the sample source (human, animal, env, food), relative frequency of the pattern(s), and spatial distribution of the pattern(s) would be of interest to us.

7 PulseNet USA WebBoard posting Date: Tuesday, April 04, :47 AM Hello, A 60-day search has identified a new multistate cluster of E. coli O157: H7 within the following states: NY(2), NYC(1), LAC(1), OH(1), and MI(1). USDA has an indistinguishable ground beef isolate from OR. The pattern combination is EXHX / EXHA which are both very common patterns (XbaI pattern frequency = 5.3%; BlnI pattern frequency = 4.2%; frequency of combination = 1.1%). A bundle file and spreadsheet of isolate information is attached. Please post any possible matches by 2 enzymes given the high commonality of these patterns. Thank you, Molly Joyner

8 NZ beef exports to USA USA 51% of total NZ beef exports Value of approximately 1 billion dollars

9 NZ E. coli databases Only XbaI Mostly pre-pulsenet methodology Mostly human isolates, incomplete other sources NZ Food Safety Authority funded investigation XbaI profiles human isolates (all human cases ), meat isolates (bobby calf sampling programme) BlnI profiles only on subset of isolates with similar XbaI profiles to US isolates.

10 Findings 12 human, 3 meat isolates same as US XbaI 74 - (This XbaI 5.9% of NZ isolates) All of have BlnI patterns different to US BlnI 569 No isolates with US XbaI pattern 1401 Two isolates with BlnI pattern 569 (different Xba) No evidence to suggest isolates came from NZ meat PFGE-XbaI PFGE-BlnI Key PFGE-XbaI-pattern PFGE-BlnI-pattern USDA_OB EXHX EXHA USDA_OB EXHX EXHA WA 9681 EXHX EXHA

11 PulseNet USA September update Between March and September isolates were uploaded with the PFGE pattern EXHX / EXHA different states, Canada Patients ages 2 86 No common source identified.

12 When are isolates the same? Tenover et al. (1995) - up to three bands different closely related, - up to six bands possibly related Tenover FC, Arbeit RD, Goering RV, Mickelsen PA, Murray BE, Persing DH, Swaminathan ESR 2007 B. (1995) J Clin Microbiol. 33(9):

13 Application to E. coli O157:H7 Tenover Criteria Developed on the basis of comparison of nosocomial pathogens, particularly in situations of ongoing transmission Assumptions: - all fragments are visible in a gel, - that the plasmid content is stable, and - that most mutations are point mutations. But - PFGE usually only resolves a limited number of bands. Theoretical digests E. coli O157 strains should generate 41 fragments with XbaI and fragments with BlnI. - Large megaplasmids are common in foodborne pathogens, if they are not in a linear conformation, their migration is unpredictable, may also be visible almost anywhere in the gel. - Kudva et al. (2002) demonstrated that PFGE diversity in E. coli O157 is primarily attributed to insertions and deletions, not to point mutations. Barrett TJ, Gerner-Smidt P, Swaminathan B. (2006). Foodborne Pathog Dis. 3(1):20-31.

14 Barrett et al. (2006) recommendations When any differences in PFGE patterns are observable, the patterns should be reported as different. Patterns that are indistinguishable should be reported as such, not as identical. Interpretation of patterns requires adherence to the following steps: 1. The gel must be of sufficient quality to be properly interpreted. 2. The diversity of the organism under consideration must be considered. Even in an organism with high diversity, some clonal populations may exist. 3. The outbreak setting should be considered. More variability is likely in ongoing transmission than a suspected point source. 4. The most important factor is how the laboratory data fit with the epidemiologic and environmental information. PFGE results alone cannot establish an epidemiological connection between isolates. Barrett TJ, Gerner-Smidt P, Swaminathan B. (2006). Foodborne Pathog Dis. 3(1):20-31.

15 Comparison US NZ isolates Similar profiles Stable over at least 3 years Indistinguishable XbaI pattern They are different 2 band differences BlnI

16 Dangers of PFGE databases? Inappropriate comparison of genotypes Used to restrict trade? Used to restrict movement of people? f d b A c e g h j m A l k i

17 Potential research questions? Are bacterial pathogens separated or restricted by geographical boundaries? Are the same strains found worldwide or do the microbial strains in different countries form distinct groupings of isolates? If strains form distinct country clusters, can the movement of these strains be followed or mapped? Is this movement a consequence of human movement, transport of contaminated food or livestock, or are wild animals or birds responsible for movement. How stable in time are bacterial pathogens in one region? Over what time periods do subtypes change and can these be predicted or measured?

18 1 st step - PFGE comparisons Comparison of the common profiles in the PulseNet databases to map the distribution of common clones.

19 Importance of two enzymes Dice (Opt:1.00%) (Tol 1.5%-1.5%) Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100.0%] Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100.0%] PFGE-Sm PFGE-SmaI PFGE-SmaI Kb Kb E E A B C D E F G H I J K L M Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100.0%] PFGE-Kp PFGE-Kp PFGE-KpnI PFGE-KpnI Kb Kb E E Campylobacter PFGE A B C D E F G H I J K L M

20 Importance of two E enzymes F Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100.0%] Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100. PFGE-Sm PFGE-SmaI Kb C D G H I J K E L M N O PFGE-Kp PFGE-KpnI Kb C D E F G H I J K E L M N O Campylobacter PFGE

21 Importance of two E enzymes F Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100.0%] Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100. PFGE-Sm PFGE-SmaI Kb C D G H I J K E L M N O PFGE-Kp PFGE-KpnI Kb C D E F G H I J K E L M N O Campylobacter PFGE

22 Importance of two E enzymes F Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100.0%] Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100. PFGE-Sm PFGE-SmaI Kb C D G H I J K E L M N O PFGE-Kp PFGE-KpnI Kb C D E F G H I J K E L M N O Campylobacter PFGE

23 Importance of two E enzymes F Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100.0%] Dice (Opt:1.00%) (Tol 1.5%-1.5%) (H>0.0% S>0.0%) [0.0%-100. PFGE-Sm PFGE-SmaI Kb C D G H I J K E L M N O PFGE-Kp PFGE-KpnI Kb C D E F G H I J K E L M N O Campylobacter PFGE

24 Favourite notified diseases in NZ 2006 Disease Cases Rate 100,000 Campylobacteriosis Salmonellosis Giardiasis Cryptosporidiosis Yersiniosis Shigellosis VTEC/STEC (O157) Listeriosis

25 Incidence of campylobacteriosis in selected countries Country Rate (per 100,000) New Zealand (2006) 422 USA (2002) 13 Australia (2004) 117 England and Wales (2001) 108 Denmark (2002) 82

26 Jul-06 NZ Rate of Campylobacteriosis Campylobactoriosis rate in New Zealand July Rate per 100,

27 Notified cases campylobacteriosis Campylobacter PFGE clusters observed Number of cases Week Tested Sporadic cases

28 PFGE cluster definition Indistinguishable SmaI pattern Indistinguishable KpnI pattern (same Penner serotype)

29 Temporal clustering of subtypes Campylobacter PFGE clusters observed Number of cases Week Tested Unique A B D E F G M H I J K L N O P Q R S T U V X Y AA BB CC DD EE

30 Spatial clustering of subtypes Spring 2002 (77 cases)

31 Spatial clustering of subtypes Autumn 2003 (106 cases)

32 U cluster 18 cases 4 University of Canterbury students

33 With subtyping Campylobacter Subtype U Yes No University Canterbury Student Yes No Odds Ratio = 55 95% CI = 3 to 1075

34 Without subtyping... Campylobacter University Canterbury Student Yes No Yes No

35 Estimate only based on population of 10,000 University students in local poulation of 450,000 Without subtyping... Campylobacter Yes No University Canterbury Student Yes No Odds Ratio = 2 95% CI = 0.4 to 11

36 Health Research Council Proposal Genotype within a week of isolation in clinical lab every case from Canterbury over two 1 month periods (500 human cases) Extensive food sampling (1000 samples) Intensive reiterative epidemiological investigation - Case:case analysis - Exposure rate analysis Additional environmental sampling Identify mechanisms of transmission - Restaurants, foods, practices in home or industry

37 Campy & PulseNet I believe PulseNet philosophy is entirely applicable to campylobacteriosis Multi-state outbreaks are happening all the time Just not being recognised Therefore you need to genotype every isolate!!! With PFGE that s not practical Therefore we need cheaper and easier methodology that is suited to high throughput. Need high throughput epidemiology tools! Campy - The outbreak bug to rule them all

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