Proof of concept of WGS based surveillance: meningococcal disease

Proof of concept of WGS based surveillance: meningococcal disease

Martin MaidenDepartment of Zoology

http://zoo-maidenlab.zoo.ox.ac.uk/@MaidenLab

… and our sponsors & collaborators

Population genomics: the gene-by-gene approach

Complete

Sequence

Annotation

Bacterial Isolate

Genome Sequence

Database

(BIGSDB)

Contigs

Gene sequencesProvenance/phenotyp

e information

Jolley, K. A. & Maiden, M. C. (2010). BIGSdb: Scalable analysis of bacterial

genome variation at the population level. BMC Bioinformatics 11, 595.

Data submitters:

currently >1300;

Data curators:

currently >90 MLST

schemes

Sequence

definitionsMLST, rMLST,

antigen genes, core

genome, pan-

genome

Gene A

Gene B

Gene C

Gene D

Allele1: TTTGATACTGTTGCCGAAGGTTT

Allele2: TTTGATACCGTTGCCGAAGGTTT

Allele3: TTTGATTCCGTTGCCGAAGGTTT

>750 citations

Isolate datasets

• provenance

• phenotype

• gene content

• allelic variation

• genomes

Linked to:

Population

annotation

• locus classification

• description

• biochemical

pathway

• Core + accessory

genome analysis

• Association studies

Comparative

genomics

PubMLST

1998*, 2003

Gene-by-gene

analysis using

reference genome or

defined loci

Molecular typing

Species identification

Epidemiology

Vaccine coverage/

impact

Linking genotype

to phenotype

Outbreak investigation

Population structure

>8000 unique visitors/month*http://mlst.zoo.ox.ac.uk

PubMLST RESTful API facilitates data exchange

• All data accessible

via JSON API

• Authenticated

(OAuth) access to

protected resources

• Data submission

available soon

http://rest.pubmlst.org

WGS determination, interpretation and dissemination pipeline

Isolate growth

DNA Extraction

Sequencing (Illumina)

de novo assembly(VELVET)

Database deposition (BIGSDB)

Autotagged, web accessible sequences

Bacterial cells

Purified DNA

Short-read sequences

Assembled contiguous

sequences

Phenotype & provenance

linkage and annotation

‘Plain language’

data Bratcher, H. B., Bennett, J. S. & Maiden, M. C. J.

(2012). Evolutionary and genomic insights into

meningococcal biology. Future Microbiology 7, 873-885.

Deposited

MLST

(7 loci)

16S rRNA

sequences

(1 locus)

Ribosomal MLST

(53 loci)

Strain

Lineage/

Clonal Complex

Species

Family

Order

Class

Phylum

Genus

Whole genome

MLST

(>500 loci)- Core genome

MLST

- Accessory

genome MLST

Hierarchical genome analysis

Clone

Meroclone

Maiden Maiden, M. C., van Rensburg, M. J., Bray, J. E., Earle, S. G., Ford, S. A., Jolley, K. A. & McCarthy, N. D. M.C.J. et al. 2013. MLST revisited: the gene-by-gene approach to bacterial genomics. Nat Rev Microbiol. 2013 Sep 2. doi: 10.1038/nrmicro3093.PMCID: PMC3980634

Neisseria structure and characterisation

Jolley, K. A., Brehony, C. & Maiden, M. C. (2007). Molecular typing of

meningococci: recommendations for target choice and nomenclature. FEMS

Microbiol Rev 31, 89-96.

Component Phenotypic Genotypic

Capsule Serogroup cps region

OMPS Serotype,Subtype, etc.

porA, porB, fetA, etc.

Housekeepinggenes

MLEE MLST

Ribosomes MALDITOF 16s rRNA,rMLST

Neisseria meningitidis B: P1.7,16: F3-3: ST-32 (cc32)

Validation of WGS pipeline• 108 diverse meningococcal isolates,

sequenced with 54bp Illuminareads.

• Assembled with VELVET and uploaded into BIGSDB.

• Comparison of 24 typing loci (total of 2592 loci) previously characterised by Sanger sequencing in all isolates.

• There were 34 (1.3%) allelic differences found in 20 of the de novo assembled genomes.

• 30 discrepancies (1.15%) attributable to Sanger sequence errors (mislabelling, editing errors).

• 4 discrepancies (0.15%) attributable to Velvet assembly. These were all in the same porA allele (a repeat sequence).

Bratcher, H. B., Corton, C., Jolley, K. A., Parkhill, J. & Maiden, M. C. (2014). A gene-by-

gene population genomics platform: de novo assembly, annotation and genealogical analysis of

108 representative Neisseria meningitidis genomes. BMC Genomics 15, 1138.

Genome and phenotype

• Whole genome MLST (wgMLST).

• Autotagger – runs regularly – tags all loci with known alleles (>2200 in Neisseria database.

• Each unique sequence given new allele number.

• Loci grouped into schemes.

• Linkage to phenotype & other information.

Jolley, K. A. & Maiden, M. C. (2013). Automated extraction of typing information for bacterial pathogens

from whole genome sequence data: Neisseria meningitidis as an exemplar. Euro Surveill 18 (4): 20379.

Meningitis Research Foundation Meningococcus Genome Library

• Charity funded.

• Open access

• All available England and Wales (& soon Scotland) meningococcal isolates.

• Assembled & annotated contiguous sequence data.

http://www.meningitis.org/current-projects/genome

Isolates in the MRF Genome Library –England and Wales

0

100

200

300

400

500

600

Z

Y

X

W/Y

W

NG

E

C

B

A

National Surveillance: MRF-MGL 2010-2012

Hill, D.M.C., Lucidarme, J., Gray S.J., Newbold , L.S., Ure, R., Brehony, C., Harrison,

O.B., Bray, J.E., Jolley, K.A., Bratcher H.B.,, Parkhill, J., Tang, C.M., Borrow, R., and

Maiden, M.C.J. Genomic epidemiology of age-associated meningococcal lineages in national

surveillance: an observational cohort study. Lancet Infectious diseases, DOI:

http://dx.doi.org/10.1016/S1473-3099(15)00267-4

.

• A total of 923 isolates from England, Wales and Northern Ireland.

• 899 from England and Wales:

• Scanned at >2000 loci;

• 2-313 alleles/locus;

• 219 STs, 22 clonalcomplexes;

• 496 rSTs (ribosomal sequence types);

• Most isolates (78%) belonged to 6 clonalcomplexes.

http://dx.doi.org/10.1016/S1473-3099(15)00267-4

0

500

1000

1500

2000

2500

3000

1975 ~ 1985 ~ 1995 ~ 1999 2000 2001 ~ 2005 2006 2007 2008 2009 2010 2011 2012

41/44 269 11 32 8 213 23 167 174 22 Other UA NT

Retrospective epidemiology





http://dx.doi.org/10.1016/S1473-3099(15)00267-4

.

http://dx.doi.org/10.1016/S1473-3099(15)00267-4

Outbreak investigation

Mulhall, RM, Brehony, C, O’Connor, L, Bennett, D, Jolley, KA, Bray, J, Maiden, MCJ,

Cunney, R. Resolution of a protracted serogroup B meningococcal outbreak in a large extended

indigenous Irish Traveller Family in the Republic of Ireland during 2010 to 2013 using non-culture

PCR, WGS and publically accessible web-based tools. In preparation.

High resolution international epidemiology (W:cc11)

0

10

20

30

40

50

60

70

2005 2006 2007 2008 2009 2010 2011 2012 2013

n

year

W:cc11 England and Wales 2005 to 2013

Current UK

UK Hajj

UK1996 (n=3)1997 (n=2)1998 (n=2)

UK1975 (n=6)1987 (n=1)1989 (n=1)1990 (n=1)

UK1996 (n=2)1998 (n=1)

Argentina 2008-2012

Brazil 2008-2011

Current South Africa

Lucidarme, J., Hill, D.M., Bratcher, H.B., Gray S.J, du Plessis, M., Tsang, R.S.W., Vazquez, J.A., Taha, M.-K., Mehmet Ceyhan, Jamie Findlow J., Jolley, K.A., Maiden M.C.J., Borrow, R. (2015) Journal of Infection

0

10

20

30

40

50

60

70

80

90

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Nu

mb

er o

f C

ase

s

Year

N. meningitidis cases per year among inpatients in Bamako, Mali (2002-2012)

Group Ameningococcalcases

Group W135meningococcalcases

Protein vaccine antigens

0

10

20

30

40

50

60

70

80

90

100

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1300

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

Bexsero® MenBvac® MeNZB™ NonaMen rLP2086 VA-MENGOC-BC®

pe

rce

nta

ge

fre

qu

en

cy

Other

ST-60cc

ST-162cc

ST-11cc

ST-213cc

ST-32cc

ST-23cc

ST-269cc

ST-41/44cc

invasive isolate survey: proof of concept for WGS based surveillance

Epidemiological year 2011/2012

Dominique Caugant, Holly Bratcher, Carina Brehony, Martin Maiden, IBD-LabNet

799 representative IMD cases,15 countries

0

10

20

30

40

50

60

70

80

90

100

110

120

130

nu

mb

er

of

iso

late

s se

qu

en

ced

2011/12 2011 2012

Serogroup by country

0

25

50

75

100

125

150

175

200

225

250

nu

mb

er

of

iso

late

s

NovalueNG

Y

W

W/Y

X

E

C

B

Assembly statisticsContigs Total length Min Max Mean StdDev N50 L50 N90 L90 N95 L95 %GC

mean 466 2,143,632 208 61,050 5,211 8,306 53 15,048 187 3,529 240 1,708 52

max 1,061 2,354,459 277 252,479 16,881 33,939 185 63,436 620 21,987 756 16,002 52

min 128 2,011,908 200 19,580 1,999 2,174 10 3,531 31 951 36 549 51

Surveillance data coverage: 7 MLST loci

795 assigned MLST profiles

0

50

100

150

200

250

300

350

400

450

500

550

600

650

700

750

800

100 99.0-99.9 ≤99.9

nu

mb

er

of

iso

late

s

percent loci defined

4 missing ST profiles (0.5%)165-270 contigs / genome7 loci identified / isolate6 loci assigned / isolate

0102030405060708090

100110120130140150160170180190200210220230240250 unassigned

ST-92

ST-8

ST-750

ST-53

ST-226

ST-198

ST-116

ST-1117

ST-1

ST-364

ST-334

ST-254

ST-1157

ST-865

ST-461

ST-174

ST-162

ST-167

ST-35

ST-60

ST-22

ST-18

ST-103

ST-213

ST-23

ST-269

ST-11

ST-32

ST-41/44

Clonal complexes by country

Surveillance data coverage: PorA & FetA

0

50

100

150

200

250

300

350

400

450

500

550

600

650

700

750

800

100 66.7 33.3

nu

mb

er

of

iso

late

s

percent loci assigned (n=3)

21 partial antigen profiles (2.6%)216-677 contigs / genome1-2 loci assigned / isolate

14 no PorA VR1 allele12 no PorA VR2 allele

6 no FetA VR allele

Surveillance data coverage: 5 BAST loci

0

50

100

150

200

250

300

350

400

450

500

550

600

650

100 80-90 60-70 40-50

nu

mb

er

of

iso

late

s

percent loci defined

Over all 597 with partial profile (74.8%)

14 no PorA VR1 allele12 no PorA VR2 allele

130 no NadA peptide allele*3 no fHbp peptide allele

19 no NHBA peptide allele

44 only 2-3 loci identified (5.5%)average 495 contigs / genome

3 no PorA VR1 allele11 no PorA VR1, VR2 alleles

3 no fHbp/NadA peptide alleles19 no NHBA/NadA peptide alleles

Top 37 BAST profiles

0

1

2

3

4

5

6

7

8

9

10

11

No

val

ue 4

22

3 3

28

8

34

9

84

22

8 8

23

7

22

2

10

71

25

7

94

26

7

10

14

10

72 5

38

22

7

57

8

96

2

13

13

10

22

0

10

15

10

16

13

57

21

9

22

1

24

7

24

8

38

4

89

8

10

74

11

04

11

73

12

26

12

71

pe

rce

nt

of

iso

late

s

BAST profile (present in at least 3 isolates)

2011/12

2011

2012

BAST vaccine profile 1

fHbp_peptide: 1 | NHBA_peptide: 2 | NadA_peptide: 8 | PorA_VR1: 7-2 |

PorA_VR2: 4

Ribosomal (rMLST) data coverage798 assigned rMLST profiles

0

50

100

150

200

250

300

350

400

450

500

550

600

650

700

750

800

100 95.0-99.9 ≤99.9

nu

mb

er

of

iso

late

s

percent loci defined (n=51)

1 missing rST profile

(0.1%)

1061 contigs

50 loci identified

52 loci assigned

0

25

50

75

100

125

150

175

200

225

250

100 99.0-99.9 98.0-98.9 97.0-97.9 96.0-96.9 95.0-95.9 90.0-94.9 ≤89.9

nu

mb

er

of

gen

om

es

percent of cgMLST tagged (n=1605)

Core genome (cgMLST) locus coverage

177 (22.2%)

genomes

0

25

50

75

100

125

150

100 99.0-99.9 98.0-98.9 97.0-97.9 96.0-96.9 95.0-95.9 90.0-94.9 ≤89.9

nu

mb

er

of

iso

late

s

percent of tagged loci (n=1605)

(n=3)

cgMLST coverage: MRF-MGL 2013/2014

Scalable genomic epidemiology

Centuries+ decades years months weeks days hours

Evolution emergence epidemiology diagnosis

COLOMBIA 2004

(n=37)

Y

32%

B

51%

W-135

3%

C

14%

AFRICAN

MENINGITIS BELT

2003-2004

(n=501)

Other

1,2%

A

79%

W-135

20%

AUSTRALIA 2004

(n=361)

Other

7,2%

C

20%

A

0,3%

B

68%

W-135

3,3%

Y

2,2%

WESTERN

EUROPE 2002

(n=3,982)

A

0,1%

C

29%

Other

1,0%

B

64%

W-135

3,6%

Y

2,3%

RUSSIA 2002-2004

(n=1,899)

B

32%

A

36%C

22%

Other

10%

CHILE 2003

(n=193)

Other

5%

C

14%B

78%

W-135

1%

Y

2%

CANADA 2003*

(n=148)

W-135

7%

C

24%

B

43%

Other

1%

Y

25%

UNITED STATES 2003

(n=200)

Y

27%

C

21% B

44%

Other

6%W-135

2%

TAIWAN 2001

(n=43)

Y

19%

A

4,7%

W-135

41%

B

33%

C

2,3%

THAILAND 2001

(n=36)

Other

2%

B

81%

W-135

17%

SAUDI ARABIA

2002

(n=21)

B

10%

W-135

76%

A

14%

BRAZIL 2004

Sao Paulo state

(n=520)

B

36%

C

58%

Other

6%

NEW ZEALAND 2004

(n=252)

C

8%

Other

0,8%

B

87%

W-135

3,6%

Y

0,4%

SOUTH AFRICA 2003

(n=264)

Other

1%W-135

9%

B

29%

A

34%

C

11%

Y

16%

URUGUAY 2001

(n=53)

C

11%

B

83%

Other

6%

COLOMBIA 2004

(n=37)

Y

32%

B

51%

W-135

3%

C

14%

AFRICAN

MENINGITIS BELT

2003-2004

(n=501)

Other

1,2%

A

79%

W-135

20%

AUSTRALIA 2004

(n=361)

Other

7,2%

C

20%

A

0,3%

B

68%

W-135

3,3%

Y

2,2%

WESTERN

EUROPE 2002

(n=3,982)

A

0,1%

C

29%

Other

1,0%

B

64%

W-135

3,6%

Y

2,3%

RUSSIA 2002-2004

(n=1,899)

B

32%

A

36%C

22%

Other

10%

CHILE 2003

(n=193)

Other

5%

C

14%B

78%

W-135

1%

Y

2%

CANADA 2003*

(n=148)

W-135

7%

C

24%

B

43%

Other

1%

Y

25%

UNITED STATES 2003

(n=200)

Y

27%

C

21% B

44%

Other

6%W-135

2%

TAIWAN 2001

(n=43)

Y

19%

A

4,7%

W-135

41%

B

33%

C

2,3%

THAILAND 2001

(n=36)

Other

2%

B

81%

W-135

17%

SAUDI ARABIA

2002

(n=21)

B

10%

W-135

76%

A

14%

BRAZIL 2004

Sao Paulo state

(n=520)

B

36%

C

58%

Other

6%

NEW ZEALAND 2004

(n=252)

C

8%

Other

0,8%

B

87%

W-135

3,6%

Y

0,4%

SOUTH AFRICA 2003

(n=264)

Other

1%W-135

9%

B

29%

A

34%

C

11%

Y

16%

URUGUAY 2001

(n=53)

C

11%

B

83%

Other

6%

0.1

UK 1993

Case 1

Carrier 1

FAM18

USA

1983

Carrier 2

Carrier 3

Cases 3 & 6

Remote

cases 1 & 2

Carrier 4

Carrier 5

Contigs Total length Min Max Mean StdDev N50 L50 N90 L90 N95 L95 %GC

mean 306 2,133,479 209 88,174 7,847 12,456 33 22,789 117 5,194 151 2,688 52

max 612 2,278,600 273 258,183 19,478 32,854 80 64,227 289 16,887 370 9,336 52

min 109 2,026,649 200 30,309 3,499 4,877 12 7,569 35 1,670 44 942 51

MRF 2013/2014 assembly statistics

0

25

50

75

100

125

150

175

200

225

250

275

100 99.0-99.9 98.0-98.9 97.0-97.9 96.0-96.9 95.0-95.9 90.0-94.9 ≤89.9

nu

mb

ero

f is

ola

tes

percent of cgMLST tagged (n=1605)

Core genome data coverage: MRF 2014/2015

188 (24.7%) genomes

MRF 2014/2015 assembly statistics

H Bratcher, C Brehony, M Maiden, D Caugant . IDB-LabNet 2015

mean 323 2,126,265 202 80,153 6,900 10,841 35 19,614 126 4,366 162 2,215

max 516 2,278,600 273 219,677 18,381 28,710 67 58,245 236 15,605 305 9,336

min 116 2,037,538 200 34,143 4,184 5,990 13 8,869 43 1,992 53 1,065

Contigs Total length Min Max Mean StdDev N50 L50 N90 L90 N95 L95

Age association of meningococcal genotypes (MRF-MGL 2010-2012)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

<1 1-4 5-9 10-14 15-19 20-24 25-29 30-39 40-49 50-69 >70

Pro

po

rtio

n o

f ca

ses

Age category

Minor clonal complexes

ND

ST-174 complex

ST-461 complex

ST-162 complex

ST-22 complex

ST-23 complex/Cluster A3

ST-213 complex

ST-60 complex

ST-41/44 complex/Lineage 3

ST-269 complex

ST-32 complex/ET-5 complex

ST-11 complex/ET-37 complex





http://dx.doi.org/10.1016/S1473-3099(15)00267-4

.

http://dx.doi.org/10.1016/S1473-3099(15)00267-4

Population annotation

Harrison, O.B., Bray, J.A., Maiden, M.C., and Caugant, D.A. (2015) Genomic Analysis of the Evolution and Global Spread of Hyper-invasive Meningococcal Lineage 5. Ebiomedicine, 2(3), 234-243doi:10.1016/j.ebiom.2015.01.004.

Validation against four reference genomes

Isolate Loci present in draft genome

Identical loci Discrepantloci

Incomplete loci

Discrepantbases in annotated loci

Z2491 1872/1867 (99.8%)

1801 (96.2%) 19 (1%) 51 (2.7%) 32 (0.002%)

FAM18 1905/1914 (93.2%)

1775 (93.2%) 23 (1.2%) 107 (5.6%) 24 (0.001%)

G2136* 1897/1904 (99.6%)

1757 (92.6%) 47 (2.5%) 93 (4.9%) 90 (0.005%)

H44/76* 1967/1975 (99.2%)

1821 (92.6%) 49 (2.55) 97 (4.9%) 76 (0.004%)

Draft genomes generated by VELVET assembly of Illumina reads and deposited

in BIGSDB without further curation.

Annotations compared with GENOMECOMPARATOR.

* Finished genomes primarily generated with Roche 454 technology.

Phenotypic serogroup by country

0

25

50

75

100

125

150

175

200

225

250

nu

mb

er

of

iso

late

s

No value

NG

Y

W

W/Y

X

E

C

B

A

H Bratcher, C Brehony, M Maiden, D Caugant . IDB-LabNet 2015

Indexing the genome: Neiss loci

gene 122540..122974

/gene="rplK"

/locus_tag="NMC0119"

/db_xref="GeneID:4676186"

CDS 122540..122974

/gene="rplK"

/locus_tag="NMC0119"

/note="binds directly to 23S ribosomal RNA"

/codon_start=1

/transl_table=11

/product="50S ribosomal protein L11"

/protein_id="YP_974250.1"

/db_xref="GI:121634005"

/db_xref="GeneID:4676186"

/translation="MAKKIIGYIKLQIPAGKANPSPPVGPA

LGQRGLNIMEFCKAFNAATQGMEPGLPIPVVITAF

ADKSFTFVMKTPPASILLKKAAGLQKGSSNPLTNK

VGKLTRAQLEEIAKTKEPDLTAADLDAAVRTIAGS

ARSMGLDVEGVV“

Database: RefSeq

Entry: NC_008767

LinkDB: NC_008767

LOCUS NC_008767 2194961 bp DNA circular CON 10-

JUN-2013

DEFINITION Neisseria meningitidis FAM18 chromosome, complete

genome.

pubMLST.org/Neisseria

Sequence definition database

“LOCUS TAG IDENTIFIER”

NMC0119 (FAM18)

NMA0146 (020-06)

NGO1855 (FA 1090)

LOCUS “ALIASES” for

‘seed

sequences

’

Bacterial Isolate Genome Sequence Database (BIGSDB)

CCATCCCGTTGTCGAACAGCAGGTACGCCA

CTTCACCGCCAACCACACCGACCTTGACCAC

AAACACCGCCTCATGCTGCTCACCGGCCCC

AATATGGGCGGCAAATCCACCTACATGCGCAGGAACCCTCAAAGCCGTTTTCCCGGAAAACC

TATCCACAGCCGAACAGCTCCGCCAAGCCA

TTTTGCCCGAACCTTCCGTCTGGCTGAAAGA

CGGCAATGTCATCAACCACGGTTTTCATCCC

GAACTGGACGAATTGCGCCGCATTCAAAACC

ATGGCGACGAATTTTTGCTGGATTTGGAAGC

CAAGGAACGCGAACGTACCGGTTTGTCCAC

ACTTAAAGTCGAGTTCAACCGCGTTCACGGC

TTTTACATTGAATTGTCCAAAACCCAAGCCG

AACAAGCACCTGCCGACTACCAACGCCGGC

AAACCCTTAAAAACGCCGAACGCTTCATCAC

GCCGGAACTGAAAGCCTTTGAAGACAAAGT

GCTGACTGCTCAAGAGCAAGCCCTCGCCTT

AGAAAAACAACTCTTTGACGGCGTATTGAAA

AACCTTCAGACGGCATTGCCGCAGCTTCAAA

AAGCCGCCAAAGCCGCCGCCGCGCTGGAC

GTGTTGTCCACATTTTCAGCCTTGGCAAAAG

AGCGGAACTTCGTCCGCCCCGAGTTTGCCG

ACAAGTCGCGCTGATTGTTT





ACTATCCGGTTATCCACATCGAAAACGGCCG



AGGAACCCTCAAAGCCGTTTTCCCGGAAAAC

CTATCCACAGCCGAACAGCTCCGCCAAGCC

ATTTTGCCCGAACCTTCCGTCTGGCTGAAAG

ACGGCAATGTCATCAACCACGGTTTTCATCC

CGAACTGGACGAATTGCGCCGCATTCAAAAC

CATGGCGACGAATTTTTGCTGGATTTGGAAG

CCAAGGAACGCGAACGTACCGGTTTGTCCA

CACTTAAAGTCGAGTTCAACCGCGTTCACGG

CTTTTACATTGAATTGTCCAAAACCCAAGCC

GCCCCGAGTTTGCCGACTATCCGGTTATCCA

CATCGAAAACGGCCGCCATCCCGTTGTCGA

ACAGCAGGTACGCCACTTCACCGCCAACCA

CACCGACCTTGACCACAAACACCGCCTCATG

CTGCTCACCGGCCCCAATATGGGCGGCAAA

TCCACCTACATGCGCCAAGTCGCGCTGATTGTTT



ATTTTGCCCGAACCTTCCGTCTGGCTGAAAGACGGCAATGTCATCAACCACGGTTTTCATCC




CACTTAAAGTCGAGTTCAACCGCGTTCACGGCTTTTACATTGAATTGTCCAAAACCCAAGCC

GAACAAGCACCTGCCGACTACCAACGCCGG

CAAACCCTTAAAAACGCCGAACGCTTCATCA

CGCCGGAACTGAAAGCCTTTGAAGACAAAGT

GCTGACTGCTCAAGAGCAAGCCCTCGCCTTAGAAAAACAACTCTTTGACGGCGTATTGAAA



GTGTTGTCCACATTTTCAGCCTTGGCAAAAGAGCGGAACTTCGTCCGCCCCGAGTTTGCCG




AAACACCGCCTCATGCTGCTCACCGGCCCCAATATGGGCGGCAAATCCACCTACATGCGC

CAAGTCGCGCTGATTGTTT

abcZ

adk

aroE

fumC

gdh

pdhC

pgm

porA

porB

fetA

penA

rpoB

16S

Locus X

Locus Y

Sequence

bin

Jolley, K. A. & Maiden, M. C. (2010). BIGSdb:

Scalable analysis of bacterial genome variation at

the population level. BMC Bioinformatics 11, 595.

Locus

definitions

tables:

annotation

source Locus Allele Provenance

abcZ 2 Country UK

adk 3 Year 2013

aroE 4 serogroup B

gdh 8 Disease carrier

pdhC 4 Age 23

pgm 6 Source Swab

... etc... ... etc ...

Acknowledgements

Julia BennettWT

Carly Bliss

Holly BratcherWT

James BrayWT

Carina BrehonyWT

Marianne Clemence

Ali Cody

Fran Colles

Kanny DialloWTF

Sarah Earle

Suzanne Ford

Odile HarrisonWT

Sofia Hauck

Dorothea Hill

Lisa Rebbets

Melissa Jansen van Rensburg

Keith JolleyWT

Jasna Kovac

Jenny MacLennanWT

Noel McCarthyWTF

Maddi Pearce

Samuel SheppardWTF

Helen Strain

Eleanor Watkins

Helen Wimalarathna

Population genomics: the gene-by-gene approach

Complete Sequence

Annotation

Bacterial Isolate Genome Sequence Database (BIGSDB)

Contigs

Gene sequencesProvenance/phenotype information

Jolley, K. A. & Maiden, M. C. (2010). BIGSdb: Scalable analysis of bacterial genome variation at


Bacterial typing requirements

1. Universal, in that they are applicable to all bacteria.

2. Natural, reflecting genealogical relationships while retaining the capacity to describe closely related organisms with distinct properties.

3. Understandable, so that the output and the process by which the system has been arrived at are transparent, easily interpreted and reproducible, and where possible the system should be backwards compatible with previous approaches.

4. Expandable, to account for the incompleteness of our knowledge of diversity, and flexible enough to accommodate changes in this knowledge.


5. Portable, because methods need to be easily carried out in any laboratory and the data need to be freely exchanged by the use of generic methodologies, reagents and bioinformatics pipelines

6. Technology independent, so that the data used are independent of the means of their collection (this means that schemes adopted now need to retain their validity as data improve)

7. Readily available to the entire community


8. Scalable, so that methods are sufficiently fast and inexpensive to be useable in real time for large or small numbers of isolates (this scalability is especially important for clinical applications and large-scale bacterial population analyses)

9. Accommodate a wide range of variation so that they can encompass both close and distant genealogical relationships

10. Broadly accepted by those who use them and open to contributions from members of the community.

Bacterial typing methods

• Universal, in that they are applicable to all bacteria

• Natural, reflecting genealogical relationships while retaining the capacity to describe closely related organisms with distinct properties

• Understandable, so that the output and the process by which the system has been arrived at are transparent, easily interpreted and reproducible, and where possible the system should be backwards compatible with previous approaches

• Expandable, to account for the incompleteness of our knowledge of diversity, and flexible enough to accommodate changes in this knowledge

• Portable, because methods need to be easily carried out in any laboratory and the data need to be freely exchanged by the use of generic methodologies, reagents and bioinformatics pipelines

• Technology independent, so that the data used are independent of the means of their collection (this means that schemes adopted now need to retain their validity as data improve)

• Readily available to the entire community

• Scalable, so that methods are sufficiently fast and inexpensive to be useable in real time for large or small numbers of isolates (this scalability is especially important for clinical applications and large-scale bacterial population analyses)

• Able to accommodate a wide range of variation so that they can encompass both close and distant genealogical relationships

• Broadly accepted by those who use them and open to contributions from members of the community.

cnl meningococci & other species

Claus, H., Maiden, M. C., Maag, R., Frosch, M. & Vogel, U. (2002). Many carried meningococci lack the genes required for capsule synthesis and transport. Microbiology 148, 1813-1819.Harrison, O. B., Claus, H., Jiang, Y., Bennett, J. S., Bratcher, H. B., Jolley, K. A., Corton, C., Care, R., Poolman, J. T., Zollinger, W. D., Frasch, C. E., Stephens, D. S., Feavers, I., Frosch, M., Parkhill, J., Vogel, U., Quail, M. A., Bentley, S. D. & Maiden, M. C. J. (2013). Description and Nomenclature of Neisseria meningitidis Capsule Locus. Emerging Infectious Diseases 19, 566-573.

First generation genomics:single locus typing and MLST

aroE

gdh

pgm

adkpdhC

fumC

porA

fetA

abcZ

Maiden, MCJ, Bygraves, JA, Feil, E, Morelli, G, Russell, JE, Urwin, R, Zhang, Q, Zhou, J, Zurth, K,

Caugant, DA, Feavers, IM, Achtman, M & Spratt, BG. 1998. Multilocus sequence typing: a portable

approach to the identification of clones within populations of pathogenic microorganisms. Proc Natl Acad

Sci USA 95, 3140-3145.

Maiden, MC. 2006. Multilocus Sequence Typing of Bacteria. Annu Rev Microbiol 60, 561-588.

Jolley KA, Brehony C, Maiden MC. 2007. Molecular typing of meningococci: recommendations for target

choice and nomenclature. FEMS Microbiol Rev 31, 89-96.

• Neisseria seven-locus ST summarises 3284bp.

• That is 0.15% of the 2.18Mbp genome.

• 11,001 STs in PubMLSTdatabase (September 2014).

• 469-750 alleles per locus.

• Many polymorphisms per locus.

GENOMECOMPARATOR: gene-by-gene analysis

GENOMECOMPARATOR: rapid comparative genomics

Jolley, K. A., Hill, D. M., Bratcher, H. B., Harrison, O. B., Feavers, I. M., Parkhill, J. &

Maiden, M. C. (2012). Resolution of a meningococcal disease outbreak from whole genome

sequence data with rapid web-based analysis methods. J Clin Microbiol. 50(9):3046-53.

SPLITSTREE 4.0

NEIGHBORNET

Ribosomal multi-locus sequence typing, rMLST

Jolley, K. A., Bliss, C. M., Bennett, J. S., Bratcher, H. B., Brehony, C. M., Colles, F. M., Wimalarathna, H. M., Harrison, O. B., Sheppard, S. K., Cody, A. J. & Maiden, M. C. (2012). Ribosomal Multi-Locus Sequence Typing: universal characterisation of bacteria from domain to strain. Microbiology 158, 1005-1015.

• Isolate characterisation from ‘domain to strain.

• Indexes the 53 ribosomal genes.• PubMLST.org/rMLST, provides a look-up table

available on the web.• Ribosomal sequence types, rSTs related to

appropriate nomenclatures, October 2014:• 99,996 genome sequences;• 977 genera;• 2,531 unique species ;• rSTs defined for 6 groups, Neisseria and

Campylobacter to clonal complex level.

Meningococcal genealogies: cgMLST, rMLST, & MLST

Bratcher, H.B., Maiden, M.C. Unpublished.

Lineage 5: 40 years of global disease and reverse vaccinology

1,886 (95%) core loci

52 (3%) accessory

Harrison, O. B., Bray, J. E., Maiden, M. C. J. & Caugant, D. A. Genomic Analysis of the Evolution and

Global Spread of Hyper-invasive Meningococcal Lineage 5. EBioMedicine.

Harrison, O.B., Hill, D.M., Maiden, M.C.J. unpublished.

Variability across the lineage 5 (ST-32 complex) genome

229 loci identical

1,600 loci p-distance values below

0.002

Harrison, O.B., Bray, J.A., Maiden, M.C., and Caugant, D.A. (2015)

Genomic Analysis of the Evolution and Global Spread of Hyper-

invasive Meningococcal Lineage 5. Ebiomedicine, 2(3), 234-243

doi:10.1016/j.ebiom.2015.01.004.

Meningitis Research Foundation Meningococcus Genome Library

• Charity funded.

• Open access

• All available England and Wales (& soon Scotland) meningococcal isolates.

• Assembled & annotated contiguous sequence data.

http://www.meningitis.org/current-projects/genome

MRF-MGL isolates 2010-2012• A total of 923 isolates from

England, Wales and Northern Ireland.

• 899 from England and Wales:

• Scanned at >1600 loci;

• 2-313 alleles/locus;

• 219 STs, 22 clonalcomplexes;

• 496 rSTs (ribosomal sequence types);

• Most isolates (78%) belonged to 6 clonalcomplexes.

ST-41/44 complex

237 isolates

ST-269 complex

171 isolatesST-11 complex, 59 isolates

ST-213 complex

75 isolates

ST-23 complex

120 isolates

ST-32 complex

42 isolates

0

500

1000

1500

2000

2500

3000

1975 ~ 1985 ~ 1995 ~ 1999 2000 2001 ~ 2005 2006 2007 2008 2009 2010 2011 2012

41/44 269 11 32 8 213 23 167 174 22 Other UA NT

Meningococcal clonal complexes and disease: England and Wales


O.B., Bray, J.E., Jolley, K.A., Bratcher H.B.,, Parkhill, J., Tang, C.M.,, Borrow, R., and


surveillance: an observational cohort study. Submitted.

2015 vaccine introductions

MRF-MGL isolates:genogroups by epidemiological year

0

100

200

300

400

500

600

07/2010-06/2011 07/2011-06/2012 07/2012-06/2013 07/2013-06/2014 07/2014-06/2015

Nu

mb

er

of

iso

late

s

Epidemiological Year

Y

X

W/Y

W

NG

E

C

B

A

Vaccine antigens exact peptide matches in MRF MGL

0

10

20

30

40

50

60

70

80

90

100

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1300

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

all g

en

ogr

ou

ps

gen

ogr

ou

p B

on

ly

Bexsero® MenBvac® MeNZB™ NonaMen rLP2086 VA-MENGOC-BC®

pe

rce

nta

ge

fre

qu

en

cy

Other

ST-60cc

ST-162cc

ST-11cc

ST-213cc

ST-32cc

ST-23cc

ST-269cc

ST-41/44cc

0

5

10

15

20

25

<1 1 2 3

4-6

7-9

10

-12

13

-15

16

-18

19

-21

22

-24

25

-27

28

-30

31

-33

34

-36

37

-39

40

-43

44

-46

47

-49

50

-52

53

-55

56

-58

59

-61

62

-64

65

-67

68

-70

71

-73

74

-76

77

-79

80

-82

83

-85

86

-88

89

-91

92

-94

95

-97

>9

7

NK

Pro

po

rtio

n o

f IM

D C

ase

s Ep

ide

mio

logi

cal

Ye

ar (

%)

Patient Age (Years)

2010/11

2011/12

0

1

2

3

4

5

6

7

8

9

<1 1-3 4-6 7-9 10-11P

rop

ort

ion

of

Cas

es

Epid

em

iolo

gica

l Ye

ar (

%)

Patient Age (Months)

Age distribution of isolates in meningococcal genome library

Contiguous sequences (contigs.)

Data sources

First generation ‘Next generation’

Archival

Short-read

sequence

data

DNA

Sequence on

preferred platform

(e.g. Illumina)

Bacteria

l isolate

Complete, assembled closed

genomes with annotation, available

from public databases (e.g. IMGD)

Clinical

specimen

TGGAGCAGATCGAGGAGAGCGAGTTCGACGC







TGGAGCAGATCGAGGAGAGCGAGTTCGACGCTGGAGCAGATCGAGGAGAGCGAGTTCGACGC

Assemble with

preferred software

(e.g. VELVET)

wgMLST ST-32 complex isolates

2063 CDS, 1,894 present in all isolates

Harrison, O.B. Maiden M.C., Caugant, D.A. Unpublished,

Rapid automated genome assembly

506 IsolatesIllumina Genome Analyzer GAIIxRead Lengths: 100 NucleotidesAverage Input FASTQ Filesize: 586MB

(258 million nucleotides)Average Number of Reads: 2.58 millionK-mer Range: 21-99

Median Final K-mer: 81Median N50: 37,503Average Number of Contigs: 209Average Program Time: 22 mins 31 secsTotal Program Time: 58 hours

Filesize (MB)

Pro

gram

Tim

e (h

h:m

m:s

s) Total AutoAssembler.pl Program Time Using 10 Threads Per Assembly

James Bray, unpublished

BIGSDB automated annotation

MLST definitions CCATCCCGTTGTCGAACAGCAGGTACGCCA


AAACACCGCCTCATGCTGCTCACCGGCCCC

AATATGGGCGGCAAATCCACCTACATGCGCAGGAACCCTCAAAGCCGTTTTCCCGGAAAACC

TATCCACAGCCGAACAGCTCCGCCAAGCCA

TTTTGCCCGAACCTTCCGTCTGGCTGAAAGA

CGGCAATGTCATCAACCACGGTTTTCATCCC

GAACTGGACGAATTGCGCCGCATTCAAAACC

ATGGCGACGAATTTTTGCTGGATTTGGAAGC

CAAGGAACGCGAACGTACCGGTTTGTCCAC

ACTTAAAGTCGAGTTCAACCGCGTTCACGGC

TTTTACATTGAATTGTCCAAAACCCAAGCCG

AACAAGCACCTGCCGACTACCAACGCCGGC

AAACCCTTAAAAACGCCGAACGCTTCATCAC

GCCGGAACTGAAAGCCTTTGAAGACAAAGT

GCTGACTGCTCAAGAGCAAGCCCTCGCCTT

AGAAAAACAACTCTTTGACGGCGTATTGAAA





ACAAGTCGCGCTGATTGTTT










ATTTTGCCCGAACCTTCCGTCTGGCTGAAAG

ACGGCAATGTCATCAACCACGGTTTTCATCC




CACTTAAAGTCGAGTTCAACCGCGTTCACGG

CTTTTACATTGAATTGTCCAAAACCCAAGCC

GCCCCGAGTTTGCCGACTATCCGGTTATCCA

CATCGAAAACGGCCGCCATCCCGTTGTCGA

ACAGCAGGTACGCCACTTCACCGCCAACCA

CACCGACCTTGACCACAAACACCGCCTCATG

CTGCTCACCGGCCCCAATATGGGCGGCAAA

TCCACCTACATGCGCCAAGTCGCGCTGATTGTTT



ATTTTGCCCGAACCTTCCGTCTGGCTGAAAGACGGCAATGTCATCAACCACGGTTTTCATCC




CACTTAAAGTCGAGTTCAACCGCGTTCACGGCTTTTACATTGAATTGTCCAAAACCCAAGCC

GAACAAGCACCTGCCGACTACCAACGCCGG

CAAACCCTTAAAAACGCCGAACGCTTCATCA

CGCCGGAACTGAAAGCCTTTGAAGACAAAGT

GCTGACTGCTCAAGAGCAAGCCCTCGCCTTAGAAAAACAACTCTTTGACGGCGTATTGAAA



GTGTTGTCCACATTTTCAGCCTTGGCAAAAGAGCGGAACTTCGTCCGCCCCGAGTTTGCCG




AAACACCGCCTCATGCTGCTCACCGGCCCCAATATGGGCGGCAAATCCACCTACATGCGC

CAAGTCGCGCTGATTGTTT

abcZ

adk

aroE

fumC

gdh

pdhC

pgm

porA

porB

fetA

penA

rpoB

16S

Locus X

Locus Y

MLST definitions

database

External

definitions

databases

Sequence

bin

Jolley, K. A. & Maiden, M. C. (2010). BIGSdb:

Scalable analysis of bacterial genome variation at


Health & Medicine

Proof of concept of WGS based surveillance: meningococcal disease