Genomics links sporadic Salmonella Typhimurium Phage type 9 infections to a recurrent source of outbreak salmonellosis

Transcription

1 Genomics links sporadic Salmonella Typhimurium Phage type 9 infections to a recurrent source of outbreak salmonellosis Zoe Cutcher 1,2, Dieter Bulach 3, Glen Carter 3, Timothy P Stinear 3, Karolina Mercoulia 3, Mary Valcanis 3, Torsten Seemann 3, Nicola Stephens 1, Martyn D. Kirk 2, Benjamin P Howden 3, Marion Easton 1 1. Victorian Government Department of Health and Human Services 2. Australian National University 3. The University of Melbourne Research question How many sporadic Salmonella Typhimurium Phage Type 9 isolates could possibly be attributable to Farm A (or share a source with Farm A, eg grandparent stock) during ? Indistinguishable 1

2 Methods Reviewed MLVA patterns for historical STm9 isolates Identified predominant Farm A MLVA* pattern Categorised historical isolates into MLVA levels Sequenced 301 isolates 99 from Farm A 161 from a range of MLVA levels 41 from other outbreaks Examined SNPs^ between historic isolates and dominant Farm A clade, according to MLVA level Estimated number of historic isolates related to Farm A isolates, according to MLVA level * MLVA = multilocus variable-number tandem repeat analysis ^ SNPs = single nucleotide polymorphism Results Farm A predominant MLVA

3 Results Farm A predominant MLVA Results Farm A predominant MLVA Other 3

4 Results 176 outbreak cases associated with the farm during the 5 years Generally, 0-5 SNPs within an outbreak (up to 30 SNPs) Estimated relatedness of other isolates to Farm A clade. July 2009-June 2014 (n=1585) Estimated: 8% (125) other isolates <10 SNPS from Farm A clade 25% (398) other isolates <20 SNPs from Farm A clade 33% (518) other isolates < 30 SNPs from Farm A clade SNPs from Farm A clade: > 51 Acknowledgements Victorian Government Department of Health and Human Services Joy Gregory, Kaye Sturge, CDPC team Australian National University Katherine Glass Microbial Diagnostic Unit, The University of Melbourne Jessica Lynn Barnden Doherty Centre for Applied Microbial Genomics Anders desilva Victorian Government Department of Economic Development, Jobs, Transport and Resources Yonatan Segal 4

5 Methods Group Description # sequenced Farm A isolates Epidemiologically linked to Farm A 99 MLVA Level 1 Indistinguishable from predominant Farm A pattern MLVA Level repeat 1 (central) loci 22 MLVA Level repeat 2 (central) loci 22 MLVA Level 4 > 3 repeat 1 (central) loci 23 MLVA Level 5 > 3 repeat 2 (central) loci MLVA Level 6 Other outbreak Unrelated (3 central loci differ, or one of outer loci differ) Outbreaks with no known association with Farm A SNP* difference from dominant clade MLVA Level Sequenced isolates in MLVA level Total sporadic Sequenced isolates in MLVA-SNP Estimated sporadic isolates in isolates in MLVA category MLVA-SNP category level No No % 95% CI (%)** No No 95% CI s n p [=(n/s)x100] (d, e) t (p/100)*t ((d/100)*t, (e/100)*t) (12, 37) (23, 72) (1, 30) (1, 69) 0 SNPs (0, 0) (1, 31) 28 1 (0, 9) (0, 0) (0, 0) 0 SNPs subtotal 55 (25, 150) Cumulative total 55 (25, 150) (3, 22) (6, 43) (0, 0) 1-5 SNPs (0, 0) (0, 0) (0, 0) (0, 0) 1-5 SNPs subtotal 17 (6, 43) Cumulative total 72 (31, 193) (10, 35) (20, 68) (1, 30) (2, 69) 6-10 SNPs (0, 0) (2, 34) 28 3 (1, 10) (0, 0) (0, 0) 6-10 SNPs subtotal 53 (22, 147) Cumulative total 125 (53, 340) (28, 57) (55, 111) (29, 71) (67, 163) SNPs (33, 75) (42, 96) (7, 44) 28 5 (2, 12) (0, 0) (0, 0) (0, 0) SNPs subtotal 272 (166, 383) Cumulative total 397 (219, 722) (1, 2) (2, 4) (15, 55) (35, 127) SNPs (1, 30) (1, 38) (0, 0) (0, 0) (0, 26) (0, 214) (13, 50) (107, 412) SNPs subtotal 300 (131, 618) Cumulative total 817 (387, 1723) (0, 15) (0, 29) (1, 30) (2, 69) (6, 42) (8, 54) 5

6 Results: SNPs observed in Farm A and other outbreaks Results: SNP variation over time. Pairwise SNPs between Farm A isolates, 2010 versus

7 No. isolates 12-Jul-17 Results: Farm A MLVA patterns Farm A MLVA patterns according to outbreak OB1 OB2 OB4 OB5 OB6 OB7 OB8 OB9 OB10 OB11 OB12 Enviro Outbreak WGS Quality measures Core Genome = 90% of bp Quality > 99.9% accuracy (minimum phred quality score = 33) > 47 read depth Read length mode 151bp (range ) 7

8 Lit review: outbreaks Author Domivski et al 2014 Octavia et al 2015 Leekitcharoenphon et al 2014 Organism S. Typhimurium 135a No. clinical sequences 8 from 5 linked outbreaks No. environmental/ food sequences Interval Max SNP differences 2 3 yrs 22 Outbreak a 4 0? 0 Outbreak b 3 0? 5 S. Typhimurium 170 Outbreak days 31 Outbreak days 1 (or 5) S. Typhimurium Outbreak days 1 (or 21) Outbreak days 1 Outbreak days 2 18 from 6 outbreaks (phage U292, DT135, DT3, DT104, DT12, DT120) 0 few days to several months 30 (all <13 except except DT 12 = 30 SNPs) Inns et al 2015 S. Enteritidis 14b months 22 Results Lit review: temporal change Author Organism Sample Rate of change Hawkey 2013 S. Typhimurium 135a 8 isolates from 5 linked outbreaks, plus some sporadic cases with same MLVA 3-5 SNPs per year Octavia et al 2015 S. Typhimurium Isolates from 5 outbreaks 2-4 SNPs within 1 month 3-9 SNPs within 3 months 8

9 Single nucleotide polymporphisms (SNPs) SNP = nucleotides differ at one position in the genome SNPs develop over time through mutation Small number SNPs indicate related isolates Isolate 1 Isolate 2 Isolate 3 Results: Estimating SNPs from dominant Farm A clade Sporadic STm9 isolates according to MLVA level, July 2009 June 2014 (n=1584)* Level Sequenced Level 1 isolates (n=45): SNPs from dominant Farm A clade 0 SNPs: 22% Level Other SNPs: 9% 6-10 SNPs: 20% SNPs: 42% SNPs: 4% >51 SNPs: 2% Level Level 4 28 Level Level *2014/2015 isolates excluded due to genetic shift in Farm A isolate 9