by author Bacterial typing - what methodology should I use? MTE Session ECCMID 2017 VIENNA, 25 APRIL 2017 L u í s a V i e i ra P e i xe

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1 Bacterial typing - what methodology should I use? MTE Session ECCMID 2017 VIENNA, 25 APRIL 2017 L u í s a V i e i ra P e i xe U C I B I R E Q U I M T E, F a c u l t y o f P h a r m a c y U n i v e r s i t y o f P o r t o P o r t o, P o r t u g a l

2 Typing clinical laboratory Overview of typing methods Potential of MALDI-TOF for typing clinically relevant species FT-IR ATR proficiency for typing several species Conclusions Overview

3 What is typing? Any method that can differentiate among related bacterial isolates or other infectious agents, but commonly Identifying different types of organisms within a species is called typing. Typing purpose: Evolution/structure of population Epidemiologic surveillance

4 Clinical Laboratory lobal surveillance Clinical Managment Typing Infection control Must have features Reliable Quick Lab Minimum sample preparation Analyzes data directly Automated

5 Biotyping Serotyping Phagetyping Low resolution Reproducibility Lack of reagents Antibiotyping Overview of Typing Methods DNA banding pattern (Rep-PCR; AFLP ) PFE DNA sequencing typing MLST ram + & ram - Portability Reproducibility Performance Reliable (clone) Quick (2-8 days) Medium-cost (10-40 Lab Minimum sample preparation Analyzes data directly- V Automated Non-ambiguity Portability Reproducibility Few species with MLST scheme MLST limitations

6 Bacterial typing - what methodology should I use? MTE Session ECCMID 2017 VIENNA, 25 APRIL 2017 F r é d é r i c L A U R E N T E S E M E S S I n s t i t u t e f o r I n f e c t i o u s A g e n t s, H o s p i c e s C i v i l s d e L y o n N a t i o n a l R e f e r e n c e C e n t r e f o r S t a p h y l o c o c c i I n t e r n a t i o n a l C e n t r e f o r I n f e c t i o l o g y R e s e a r c h, I n s e r m U , T e a m S t a p h y l o c o c c i p a t h o g e n e s i s F a c u l t y of P h a r m a c y, U n i v e r s i t y of L y o n L y o n, F r a n c e

7 Whole enome Sequencing (WS) and typing? I m a clinical microbiologist and not a bioinformatician like many of you! I m a good example of end-user! There are several more software/pipelines These are the ones I like/i know/i apply

8 WS and typing

9 WS and typing

10 Whole enome Sequencing around base pairs! WS and typing Sequence reads

11 SNP analysis WS and typing around base pairs! core genome Multi Locus Sequence Typing cgmlst

12 SNP analysis WS and typing around base pairs! core genome Multi Locus Sequence Typing cgmlst

13 Sequence reads Sequence reads mapping on reference genome Detection of Single Nucleotide Polymorphisms (SNP) SNP-based method and typing A A A A A A A A A A Reference genome T Reads from Strain X

14 Sequence reads Sequence reads mapping on reference genome Detection of Single Nucleotide Polymorphisms (SNP) SNP-based method and typing A A A A A A A A A A Reference genome Reads from Strain X To be performed for the XX clinical isolates T

15 SNP-based method and typing Non-informative/non-discriminative positions = CURED! Informative/discriminative position = CONSERVED!

16 Position on DNA eneration of a table/matrix including only the positions with 1 SNP in at least one of the strains Ref SNP-based method and typing 9 strains (1 per column) Intergenic sequences Intragenic sequences

17 SNP-based method and typing Alignment with all SNP (informative/discriminative positions) for the 9 clinical isolates! Phylogenetic tree (Maximum likelihood tree, Neighbour joining, ) of isolates constructed using XXXXX variable positions

18 SNP-based method and typing Alignment with all SNP (informative/discriminative positions) for the 9 clinical isolates! Phylogenetic tree (Maximum likelihood tree, Neighbour joining, ) of isolates constructed using XXXXX variable positions

19 Papers published Nice, easy, simple SNP-based method and typing Your set of data Assembly instructions, time, experience,

20 Sequence reads Sequence reads mapping on reference genome Detection of Single Nucleotide Polymorphisms (SNP) SNP-based method and typing Reference genome Reads from Strain X

21 Sequence reads Sequence reads mapping on reference genome Detection of Single Nucleotide Polymorphisms (SNP) SNP-based method and typing Default parameters versus fine tuning Reference genome Reads from Strain X

22 Sequence reads Quality control of the reads Sequence reads mapping on reference genome Detection of Single Nucleotide Polymorphisms (SNP) SNP-based method and typing Default parameters versus fine tuning Reference genome Reads from Strain X

23 position in the reads SNP-based method and typing Quality of sequencing for each position in the reads the higher value, the lower the probability of having a bad determination of the nucleic acid position in the reads

24 Quality of sequencing for each position in the reads the higher value, the lower the probability of having a bad determination of the nucleic acid Take into account all the size of the reads For the mapping of reads position in the reads SNP-based method and typing Exclude all the positions of the reads after position 120 for the mapping of reads position in the reads

25 Quality of sequencing for each position in the reads the higher value, the lower the probability of having a bad determination of the nucleic acid Take into account all the size of the reads For the mapping of reads position in the reads SNP-based method and typing Exclude all the positions of the reads after position 120 for the mapping of reads position in the reads - C content : in agreement with the expected C of the species? (50% C for Staph aureus vs 30 expected) - Presence of adapters, Many parameters can be checked. for each isolate. and adapted for each isolate

26 Sequence reads Quality control of the reads Sequence reads mapping on reference genome Detection of Single Nucleotide Polymorphisms (SNP) SNP-based method and typing Default parameters versus fine tuning Reference genome Reads from Strain X

27 Sequence reads Quality control of the reads Cleaning/filtering Sequence reads mapping on reference genome Detection of Single Nucleotide Polymorphisms (SNP) SNP-based method and typing Default parameters versus fine tuning Reference genome Reads from Strain X

28 Sequence reads Quality control of the reads Cleaning/filtering Sequence reads mapping on reference genome Change the minimal coverage required? 5, 10, 30, Choose the reference genome ST5 clinical isolates vs ST5 or ST8 Quality of SNIP (75% vs 90%) Detection of Single Nucleotide Polymorphisms (SNP) SNP-based method and typing Default parameters versus fine tuning Reference genome Reads from Strain X

29 PRO cgmlst - large set of information : intragenic and intergenic information - genealogy/phylogeny/evolution/datation just closeness CON cgmlst - biased due to distinct same rates of mutations: intragenic and intergenic - just open source pipelines available (Nullarbor,.) need to be familiar with computer programming and use of code line! Some WS methods specifc to some pipelines one does not proceed blindly for interpretation Fine tuning : not for dummies SNP-based method and typing SNP analysis and typing???

30 enome wide comparison USA300 CA-MRSA highly prevalent in US 67 USA300 CA-MRSA strains reported in the last decade ( ) 431 ST8 MSSA and MRSA strains from the US [Uhleman et al. PNAS (2014) + Tewhey et al. BMC enomics (2012)] Red branches = US USA300-NA genomes Blue branches = FR USA300-NA genomes SNP-based method and typing NJ phylogenetic tree using SNP

31 enome wide comparison USA300 CA-MRSA highly prevalent in US 67 USA300 CA-MRSA strains reported in the last decade ( ) 431 ST8 MSSA and MRSA strains from the US [Uhleman et al. PNAS (2014) + Tewhey et al. BMC enomics (2012)] Red branches = US USA300-NA genomes Blue branches = FR USA300-NA genomes Strains isolated in France (blue) in the last decade are interleaved with USA300-NA strains from US (red) SNP-based method and typing USA300 clone in France: multiple introductions of USA300-NA lineage in the last decade as early as the onset of this lineage

32 enome wide comparison USA300 CA-MRSA highly prevalent in US 67 USA300 CA-MRSA strains reported in the last decade ( ) 431 ST8 MSSA and MRSA strains from the US [Uhleman et al. PNAS (2014) + Tewhey et al. BMC enomics (2012)] Red branches = US USA300-NA genomes Blue branches = FR USA300-NA genomes Strains isolated in France (blue) in the last decade are interleaved with USA300-NA strains from US (red) SNP-based method and typing Outbreak? USA300 clone in France: multiple introductions of USA300-NA lineage in the last decade as early as the onset of this lineage

33 USA300 CA-MRSA strains reported between in France SNP analysis 28 isolates from 1 outbreak in a Parisian long-term care facility (green) 3 strains isolated in Aubervilliers nearby Paris (red) 6 unlinked isolates from different parts of France SNP-based method and typing Minimum spanning tree based on SNP data. Circle sizes are a function of the number of strains with the same genotype. Dashed lines correspond to links with >25 SNPs; thin lines correspond to links with

34 USA300 CA-MRSA strains reported between in France SNP analysis 28 isolates from 1 outbreak in a Parisian long-term care facility (green) 3 strains isolated in Aubervilliers nearby Paris (red) 6 unlinked isolates from different parts of France SNP-based method and typing Minimum spanning tree based on SNP data. Circle sizes are a function of the number of strains with the same genotype. Dashed lines correspond to links with >25 SNPs; thin lines correspond to links with

35 Ancestral ACME - FluorS SNP-based method and typing Derived ACME + FluorR Derived ACME + FluorS Exploration of evolutionnary dynamic

36 MRSA ST22 WS SNP analysis

37 MRSA ST22 WS SNP analysis P15 vs p24 = 1 SNP

38 MRSA ST22 WS SNP analysis P15 vs p24 = 1 SNP Prove and track the transmission network and source

39 Disprove the transmission

40 SNP analysis WS and typing around base pairs! core genome Multi Locus Sequence Typing cgmlst

41 core genome MLST (cgmlst) and typing Sequence reads De novo assembly Blast against a predefined cgmlst scheme/database Allelic profiling gene-by-gene Blast

42 ene 1 ene 2 ène 3 Strain A allele n AATTTTAA 1 ATTTTCCC 1 TTTTTTA 1 cgmlst and typing Strain B allele n AATTTTAA 1 ATTTTCCT 2 TTTTTTAA 2 Strain C allele n ATTTTAA 1 ATTTTCCT 2 CTTTATTT 3 Alllelic profiling Distance matrix computed based on allelic profiling Strain D allele n ATTTTAA 1 ATTTTCC 3 CTTTTTTA 4

43 Distance matrix computed Minimun Spanning Tree (MST) or Neighbour joining tree 1851 core genes analyzed 9 clinical CC30 S. aureus isolates 1 CC30 MRSA strain of collection (MRSA252) 1 Refrence starin MSSA 476 Number of distinct alleles on branches cgmlst and typing

44 wgmlst = cgmlst + accessory genes wgmlst and typing Minimun spanning tree (MST) or Neighbour joining tree

45 Papers published Nice, easy, simple cgmlst and typing Your set of data Assembly instructions, time, experience,

46 Sequence reads Quality control of the reads Cleaning/filtering De novo assembly Blast against a predefined cgmlst scheme/database Allelic profiling gene-by-gene cgmlst and typing Blast

47 Sequence reads Quality control of the reads Cleaning/filtering De novo assembly % to perform blast Blast against a predefined cgmlst scheme/database Allelic profiling gene-by-gene cgmlst and typing Blast

48 Sequence reads Quality control of the reads Cleaning/filtering De novo assembly % to perform blast Blast against a predefined cgmlst scheme/database Missing results? Allelic profiling gene-by-gene cgmlst and typing Blast

49 Open-source software Commercial software RIDOM SEQSPHERE+ cgmlst for typing with client server solutions from assembly to allele calling and visualization for core genome MLST (MLST+/ cgmlst) APPLIED MATHS - BIONUMERICS Commercial software with client server solutions from assembly to allele calling and visualization for whole genome MLST (wgmlst)

50 PRO cgmlst - attenuation of gene replacement/recombination : 1 to 20 or 50 SNP = change of 1 allele - easier to standardize - only focuse on genes CON cgmlst. = coding regions = high positive pressure of selection. same rates of mutations. attenuation of gene replacement/recombination : 1 to 20 or 50 SNP = change of 1 allele - reduction of information cgmlst and typing - No more genealogy/phylogeny/evolution/datation just closeness

51 cgmlst and typing MRSA cases in two intensive care units (ICUs) over the course of 4 weeks Clonal relationship of t001 isolates. A phylogenetic dendrogram(upma)was generated for all spa type t001 isolates basedonthe allelic profiles of 1,714cgMLST target genes

52 cgmlst and typing MRSA cases in two intensive care units (ICUs) over the course of 4 weeks Clonal relationship of t001 isolates. A phylogenetic dendrogram(upma)was generated for all spa type t001 isolates basedonthe allelic profiles of 1,714cgMLST target genes

53 Isolates tested 106 isolates from ESLI Panel Typing 229 isolates (195 from 5 STs) SNP-based method Core genome MLST (cgmlst) 50 core genes 100 core genes 500 core genes 1455 core genes 1521 core genes David et al. JCM 2016 Extended MLST schemes On the behalf of EWLI - ESLI the European Legionnaires' Disease Surveillance Network (ELDSNet) and can now be accessed from this link: ELDSNet incremental database requiring to include systematically the same core genes

54 n = 335 isolates Method Typability Typability cgmlst (50 genes) cgmlst (100 genes) cgmlst (500 genes) cgmlst (1455 genes) cgmlst (1521 genes) SNP-based David et al. JCM 2016 Typability decreases as the number of genes increases

55 Method David et al. JCM 2016 Typability using 79 epidemiologically unrelated isolates from the typing panel cgmlst (50 genes) cgmlst (100 genes) cgmlst (500 genes) cgmlst (1455 genes) cgmlst (1521 genes) SNP-based Index of discrimination 0.99 High discriminatory

56 Conclusion 50-gene cgmlst achieves high discrimination (D=0.990) whilst maintaining good epidemiological concordance David et al. JCM 2016

57 cgws and typing WS for all MDR isolates belonging to MRSA, VRE, MDR E. coli, MDR P. aeruginosa 645 isolates : cgws Turn Around Time (TAT), cost,

58 cgws and typing WS for all MDR isolates belonging to MRSA, VRE, MDR E. coli, MDR P. aeruginosa 645 isolates : cgws Turn Around Time (TAT), cost, Cost per isolate: ( 130,000) Avoided costs : 200,000.

59 Conclusion Calibrate the tools for your bacteria, i.e. species or sub species Diversity over time within patients Between sites diversity Between patients diversity Within household diversity... Between lineages within a given species WS not required all the time : agr typing for S. aureus ex : agr typing using 1 PCR = agr1, agr2, agr3, agr4 Cost and type requires for results : in my hospital : 1 WS run for S. aureus per month!!!! not for dummies. at the moment