Presented by: Najmeh Parhizgari PhD student of medical virology at TUMS Insights to Genetic Characterization Tools for Epidemiological Tracking of Francisella.

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Presentation transcript:

Presented by: Najmeh Parhizgari PhD student of medical virology at TUMS Insights to Genetic Characterization Tools for Epidemiological Tracking of Francisella tularensis in Sweden

Introduction 1

Introduction FF rancisella tularensis H ighly virulent F acultative intracellular pathogen T ularaemia in humans and animals TT ransmission A rthropod bites (Vector Born Disease) I nhalation of contaminated dust I ngestion of contaminated food or water 2

 Main form of disease  Ulceroglandular tularemia  Glandular tularemia  Oculoglandular tularemia  Oropharyngeal tularemia  Pneumonic tularemia  Typhoidal tularemia 3

Introduction  F. tularensis subspecies: – tularensis – holarctica – mediasiatica – novicida  Difference in : Virulence Geographic distribution Host/vector associations Genetic diversity Type A Tularemia Type B Tularemia 4

High-resolution molecular methods Pulsed-field gel electrophoresis (PFGE) Multi-locus variable-number of tandem repeat (VNTR) analysis (MLVA) canonical Single Nucleotide Polymorphism (canSNP) Insertion-deletion markers (INDELs) Whole genome microarrays 5

Evaluate canSNPs, MLVA, and PmeI-PFGE for practical uses in epidemiological investigation 6

Method Geomapping g Genotyping tools: canSNP MLVA PFGE Clinical samples 7

 F. tularensis subspecies holarctica  From 1994 to 2010  Diverse regions in Sweden  Three ulceroglandular tularaemia  One hundred twenty four cultured samples 8

Genotyping tools  canSNP:  Using 26 assays  MLVA:  Ft-M3, Ft-M6, Ft-M20, Ft-M22 and Ft-M24  PFGE:  PmeI 9 GTTT_^AAAC

Results 10

11 MLVA canSNPPFGE n:97, B12 n:24, B7/8 Tul-I Tul-II Tul-III Type 1 Type 2 Type 3 M22 M24 canSNP, MLVA, and PFGE were in general agreement when classifying samples into major groups

12 MLVA

Pulsed- Field Gel Electrophoresis (PFGE) patterns 13

14 canSNP

15 Geographic distribution of SNP groups A highly complex geographic pattern among the phylogroups exists at a national and regional scale in Sweden

Relationships among groups Discrimination among samples within the same phylogroup canSNP MLVA 16

Discussion 17

18 Complex phylogeographic pattern of tularemia distribution in Sweden poses a great challenge to accurately identify a source and place of infection for any given F. tularensis specimen Discussion All phylogroups identified in Sweden have also been found in distant nations abroad, except B.22, which is restricted to Sweden The broad distribution of closely related phylogroups is central to the argument that F. tularensis is a rapidly dispersed organism Despite the phylogeographic complexity, patterns emerge that suggest the possibility of identifying SNP markers that could be meaningfully linked to geographic regions or at least narrow the geographic range of possible places This B.22 SNP was highly specific to FSC200 genome. All other phylogroups are defined by SNPs discovered from genomes found in other nations (USA, Russia, and Hungary) The striking genetic similarity suggests that they all recently emerged from a common ancestor. The temporal pattern rules out a single outbreak season and provides insight into the stability of this genotype. The results of the present study indicate that SNP typing schemes, designed from geographically informative SNPs, combined with a MLVA typing scheme have the potential to be used as a standalone typing method in outbreak investigations whole-genome sequencing (WGS) would be the most appropriate tool for effectively linking specific genetic type to geography

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