listeria monocytogenes from population structure to genomic epidemiology

Sylvain Brisse

Institut Pasteur, Microbial Evolutionary Genomics Unit

&

CNRS, UMR 3525, Paris, France

Listeria monocytogenes from population structure

to genomic epidemiology

Listeria monocytogenes is everywhere

• Severity of invasive forms (hospitalization rate around 100%)

• Mortality rate of 20 to 30 % (up to 45% in case of CNS infection)

• Incidence in France

• 4.9 cases / million (2009)

• Around 300 human cases/year

• Last large outbreak in 2003… but numerous small clusters

Listeria monocytogenes infections

• CNS infection

• Bacteremia

• Materno-neonatal infection

• Serotyping, PCR serogrouping

• Pulsed-field gel electrophoresis (PFGE)

• Ribotyping

• Amplified Fragment Length Polymorphism (AFLP)

• Multi-virulence sequence typing (MvLST)

• Multilocus VNTR Analysis (MLVA)

• Multilocus sequence typing (MLST)

ORF2819

lmo0737

1000

800 700 600 500 400 300

M 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

lmo1118

ORF2110

prs

Listeria monocytogenes: ‘classical’ strain typing methods

abcZ bglA cat dapE dat ldh lhkA

3 1 1 1 3 1 3

3 1 1 1 3 1 23

1 2 1 7 22 39 72

3 1 1 1 3 1 31

AllelesSequence type (ST)

1

1

2

3

3

•Allele• Sequence of one gene (lhkA, 480 bp)

MLST: Multilocus Sequence Typing

www.pasteur.fr/mlst

Currently:

~3,500 entries, 993 STs

Konstantinidis & Tiedje 2005

DNA-DNA

ANI

I

II

III

IV

4.99%

5.3%

7.57%

L. monocytogenes lineages ≈ 4 distinct genomic species

Average Nucleotide Identity

• 4 deep phylogenetic lineages

• 2 of them (LI and LII) = 99% of infections

CC7

CC9

CC1

CC6

CC2

CC3

CC4

4b

4b

1/2b

4b

4b

CC59

1/2b

1/2a

1/2a

1/2a

1/2c

CC5

CC87

1/2b

1/2b

L. monocytogenes: a few major clones

LII

LI

I

II

III

IV

Ragon et al. 2008

• Investigate international transmission of Lm strains

• Define population structure at improved resolution

• Enable epidemiological surveillance at global scale

Objectives

Develop a genome-wide MLST typing scheme to:

Core genome MLST

Step 1. Define core genome

Step 2. Define variation at

core genes1

1

2

3

3

Step 3. Define allelic profiles

Strain selection for genome sequencing

Core and pan-genome of L. monocytogenes

958 Lm isolates genome from 4 Public Health Agencies,

N50 > 20,000 nt

CDC, Atlanta 735

Public Health Agency of Canada 36

Statens Serum Institute 83

Institut Pasteur 104

Loci were eliminated if:

• Missing in > 5% genomes (33 loci)

• Paralogous locus > 60% nt identity resulting in wrong locus assignment (6 loci)

• Redundant with 7gMLST (4 loci)

Typeability validated on 650 prospective surveillance genomes from UK and F:

• Locus-level typeability was of 99.7% (1,742 ± 14.4)

Selection of 1,748 cgMLST loci

Robustness of cgMLST genotyping

• EGDe strain, sequenced by Sanger and Illumina (twice):

100% identity of 1,748 allele calls

• Most assemblers converge as long as coverage depth > 30X

core-genome genotyping (cgMLST) process

Contig 1 Contig 3Contig 2

Strain 1

Strain 2

Strain 3

Gene 1 …. Gene 1748

1748 core genes

BLAST

~5 days

~1 hour

914

15

3

9

10

4

1

12

1010

5

75

7

2

7

7

10

1

10

1

13

3

3

12

1

3

14

12

23

12

14

3

1

3

8

10

5

9

10

CC1

CC2

CC3

Lin. I, others

CC9

Lin. II, others

America (n = 77)

Europe (n = 156)

North Africa

(n = 33)

Asia / Middle

East / Oceania

(n = 30)

No significant Fst

MLST clones: Dispersal rate > evolutionary rate

Chenal-Francisque et al., 2011

Everything is Everywhere…at comparable frequency

Longevity of L. monocytogenes MLST clonal groups

Haase et al., Env. Microbiol. 2014

• Most intra-outbreak pairs < 7 mismatches

• 7 : best Dunn’s clustering index

Cut-off value to define cgMLST types (CT) : 7

Defining a threshold for cgMLST ‘types’

International cgMLST ‘types’

• No epidemiological link found upon retrospective analysis

• Long-term stability of CTs

• More precise definition of clustered cases

• More relevant epidemiological investigations

NRC

Core genome MLST discrimination >> PFGE

cgMLST types

• Listeria isolates sent to NRC

• ‘real-time’ genomic sequencing

• Detection of clusters

• Epidemiological investigation

• Remove contaminated productsSingle PFGE type

Listeria monocytogenes population structure

Lineage

Sublineage

cgMLST type

Most sublineages, but not CTs, have been sampled

Sublineages ~ clonal complexes

Transfer of MLST

nomenclature to

sublineages

Nomenclature proposal for L. monocytogenes strains

Lineage - Sublineage – ST – CgMLST type (CT)

LII – SL7 – ST7 – CT932

http://bigsdb.web.pasteur.fr/listeria

Public database for L. monocytogenes cgMLST nomenclature

BIGSdb: Bacterial Genomes Isolates Database

Jolley & Maiden 2010

Databases for genomic epidemiology & population biology

Isolates:

genomes and metadata

Local labs

Reference Centers

Public Private

Strain tracking

Resistome

Virulome

Population biology

Clie

nt

sid

eS

erv

er

sid

e

Public data

Curation

Genotype

nomenclature

database

• cgMLST is a robust approach for L. monocytogenes strain typing

• International transmission demonstrated both at evolutionary and

epidemiological timescales

• cgMLST is more discriminatory than PFGE

• Population structure allows defining nomenclature of sublineages

and CTs

• Public database available for sharing of genome sequences and

nomenclature

• Future needs:

- Ring trials / EQA studies

- Complementary approaches (SNP mapping) for fine scale

resolution

Conclusions

Biology of Infection Unit & National Reference Center for Listeria, Institut Pasteur

Hélène DIEYE, Morgane LAVINA, Pierre THOUVENOT, Alexandre LECLERCQ, Marc LECUIT

Microbial Evolutionary Genomics, Institut Pasteur

Alexandra MOURA, Elise LARSONNEUR, Mylène MAURY, Marie TOUCHON, Alexis CRISCUOLO, Eduardo ROCHA,

Sylvain BRISSE

Center for information Technology, Institut Pasteur

Louis JONES, Emmanuel QUEVILLON

Applied Maths, Belgium

Hannes POUSEELE, Bruno POT

CDC, Atlanta, USA

Peter GERNER-SMIDT, Cheryl TARR

Heather CARLETON, Lee KATZ, Zuzana

KUCEROVA, Steven STROIKA, John

BESSER

SSI, Denmark

Jonas LARSSON, Eva NIELSEN

Public Health England

Tim DALLMAN, Kathie GRANT

PHAC, CanadaAleisha REIMER, Matthew WALKER, Celine NADON

Oxford University, UKKeith JOLLEY

Funding:

Acknowledgements