Trinad Chakraborty Centre for Medical Microbiology and ... · Microbiology and Virology German...

Trinad ChakrabortyCentre for Medical Microbiology and

VirologyGerman Centre for

The changing face of clinical microbiology in the 21st century

Infect-ERA Young Scientists Networking Workshop, 14. October 2015, Budapest

Clinical microbiology

•diagnostics (clinical)- pathogenic bacteria

•surveillance & epidemiology – antibiotic resistance

•infection control- hygiene, antibiotic stewardship

Public Health- Microbiology

•Epidemiology

- relatedness to other strains

- transmission routes

- outbreak recognition

3

Conventional microbial diagnostics

Culture dependent

Requires viable microorganisms

Antibiotic susceptibility

Fastidous microorganisms

Non-culturable microorganisms

Microbiology diagnostic laboratory

5

Conventional workflow with cultured isolates

6

Staged strategy for the detection of microorganisms(low genome complexity-based)

Mass Tag PCR

Low-density-array PCR

DHPLC PCR

T-RFLP

FISH

Microarray

16S rRNA Phylogenetic Trees

Pulsed-Field Gel Electrophoresis (PFGE)

But….

•Current diagnostics take too long (>24h) – empiric

treatment usually starts before detection

•diagnostic is secondary (usually confirmatory), and not

a primary technique

•Too many procedures involved

•even for molecular diagnostics (PCR, PFGE, FISH, etc)

8

..and then there is the microbiome

~ 100 % Human

10 % human90 % microbial

Birth

Death

Increase in Microbiome content

n = 250 patients

Overview of the genera (n=39) detected:

Bacteria

Staphylococcus, Enterobacteriaceae,

Enterococcus, Peptostreptococcus,

Corynebacteria, Streptococcus,

Finegoldia, Lactobacillus, Lactococcus,

Leuconostoc, Mycobacterium, Pasteurella,

Fusobacterium, Bacteroides,

Anaerococcus, Granulicatella, Prevotella,

Haemophilus, Bifidobacterium,

Peptoniphilus, Helcococcus,

Carnobacterium, Stenoxybacter, Neisseria,

Arsenicicoccus, Actinomyces, Alcaligenes,

Micrococcus, Microbacterium, Kytococcus,

Bacillus, Paenibacillus, Kingella,

Streptomyces, Vagococcus

Fungi

Candida, Cryptococcus, Malassezia,

Saccharomyces

Diversity of the bacteria detected in the diabetic foot syndrome

S. aureus

S. epidermidis

P. aeruginosa

E. cloacae

E. faecalis

E. coli

P. mirabilis

Klebsiella sp.

majority ofstaphylococci

Phylogenetic tree and sequence type

Current diagnostic methods are…

•It is largely directed toward detecting pathogenic

bacteria e.g. EHEC, Mycobacteria, Salmonella, Listeria

etc.,

•However we are faced with low grade pathogens, e.g.

S. aureus, S. pneumoniae, E. coli, Acinetobacter etc.,

•Polymicrobial infections, co-infections

•Focus is often directed to multi-resistant bacteria

12

Consequences

•Complexity (mutual, benign, commensal, pathogen,

microbiome)

•Increase in antibiotic resistance

•Translational diagnostics – poorly developed

•Epidemiological chains fragmented (epidemiological

chains – one environment/one health)

13

Unifying approaches

•Simple, unifying technology•Rapid•Economically viable

•Genome-proteome-metabolome-based principles•Whole genome based analysis

Sequencing

Mass spectrometry

14

NGS Instrumentation

Giessen Machine Park

Roche 454 GS Junior

Ion Torrent PGM

Illumina MiSeq

PacBio RS II OxfordNanopore

Source : http://www.ncbi.nlm.nih.govhttp://www.ebi.ac.uk/uniprot/TrEMBLstats

http://www.ncbi.nlm.nih.gov/

http://www.ncbi.nlm.nih.gov/

Raw machine data~10 Gb

Formatted reads~1 Gb

Assembly~1 Gb

Genome Sequence< 10 Mb

Comparative Analysis

Results< 1 Mb

NGS - Data: Extracting meaningful results from a huge dataset

Bioinformatics

16

MDR-strain

Novel strain

Epidemiology

Relatedness

Long-term evolution

Colonization

Persistence

Resistence

Virulence

Transferability

Serotyping

MLST

PFGE

Serotype

Sequence type

PulseNet matching

Short-term evolution?

Limited characterization

Epidemiology

Relatedness

Long-term evolution

PCR-typing Resistance genes

Genome

sequencing

Bioinformatics

SRST ST-

Types

Phylogeny

SNP-Typing

Annotation

Comparative

genomics

Short-term evolution

Synteny and

horizontal

transfer events

Virulence

Factors

Drug resistance

Genomic islands

Plasmid type

Whole

Genome

based

approach

Current

approach

Analysis

17

Rapid growers: 1- 3 daysMycobacteria: 1- 3 weeks

What if ………….

Steps to genome-based diagnostics

1.NATURE REVIEWS GENETICS JANUARY 2014 VOLUME 15

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Annotation and AnalysisRAST MEGA CLC MAUVE GeCo

Sequencing and Analysis Pipeline

Next-Generation-Sequencing

IonTorrent PGM Illumina MiSeq

up to 4 Mill. Reads~200 bp

Up to 20 Mill. Reads2x300 bp

de novo Assembly

MIRA 4.0 CLC 6.5.1

10-200 Contigs

>= 1000 bp

Mapping of Contigs in MAUVE / Contiguator

Central Bioinformatics Databases- High quality data repository

19

Prokaryotic species identification using WGS Data

Larsen et al. 2014: modified

20

Diagnostic Report

21

A pathway to genome-based diagnostics

Strain selectio

n

Results Clinical Implications

Novel strain

EpidemiologyRelatednessLong-term evolution

ColonizationPersistenceResistenceVirulenceTransferability

Short-term evolution

Whole Genome Sequencing

Therapy

Diagnostics

Infection control

Antibiotic Stewardship

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Public Health Epidemiology

Blood

Liquor

Urine

Swabs

Sputum

SAMPLESC

om

plexity o

f sam

ples

Pure sample

Public health

Epidemiology

PUBLIC HEALTH EPIDEMIOLOGY

Biopsy

Stool

• • •

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Current initiatives in curbing the spread ofantibiotic resistance

European Commision 26-02-2015

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Background

26

MRE-Infektionen verursachen jährlich

8 Millionen zusätzliche Krankenhaustage und

kosten das US-Gesundheitssystem

30 Millionen $

“Antibiotic resistance is one of the most

pressing public health issues facing the world

today.”

US Präsident Obama

Hauptgrund für die Resistenzentwicklung ist

der unsachgemäße Gebrauch von

Antibiotika

In den letzten 25

Jahren wurden keine

neuen Antibiotika

entdeckt

“A post-antibiotic era means, in effect, an end to modern medicine

as we know it. Things as common as strep throat or a child’s scratched

knee could once again kill.”

WHO’s director-general Dr. Margaret Chan

Antibiotikaverbrauch in Deutschland (2011)

30%der Antibiotika-

Verordnungen sind fragwürdig

„One Health Konzept - An alles gemeinsam denken, und nicht in Schablonen – hier der Mensch, da das Tier.“

Bundeskanzlerin Angela Merkel

Antibiotikaresistenz ist ein

globales Problem

Economic costs

ESBL: total costs 1.04 Billion $/ Year

Carbapenemases:0.36 Billion $/ Year*BUT: virtually untreatable!

CDC* Calculated with ESBL prices

28

Antibiotic pipeline

http://www.davolterra.com/

New antibacterial agents approved by the FDA and EMA

29

Klebsiella pneumoniae carbapenemase

•KPC is a class A β-lactamase•Confers resistance to all β-lactams including extended-spectrum cephalosporins and carbapenems

•Occurs in Enterobacteriaceae•Common in Klebsiella pneumoniae•Also found in K. oxytoca, Citrobacter freundii, Enterobacter spp., Escherichia coli, Salmonella spp., Serratia spp.,

•Also reported for Pseudomonas

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Carbapenem resistance worldwide

Other carbapenemase types include VIM, OXA-48, or NDM. KPC=Klebsiella pneumoniae carbapenemase. Source: Munoz-Price LS et al. 2013, the lancet Infectious Diseases, Vol. 13, Sept. 2013

31

Anatomy of an Outbreak - Overview

•Location: a single hospital in Southern Hesse,

Germany

•Start: 2013-10-01

•End: 2014-09-30

•Largest accumulation of cases: May to July 2014

•Species: Enterobacteriaceae,

carrying Klebsiella-pneumoniae-Carbapenemase

(KPC-2)

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Bild durch Klicken auf Symbol hinzufügen




KPC-2 Outbreak - Epidemiology

33

Iso

late

Kalenderwoche

M. morganii

K. pneumoniae

E. coli

Enterobacter spp.

C. amalonaticus

K. oxytoca

C. freundii

Introduction Control

Measures in the

Kitchen

Modified Carstens 2015





Isolates sequenced

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Whole Genome Sequencing :

24 Bacterial Patient Isolates during Outbreak

1 Patient-Isolate before Outbreak

12 Environmental Isolates





Antibiotic Resistance Genes in Sequenced Isolates

35

Ma

cro

lid

e

Lin

co

sa

mid

e

Rifa

mp

icin

Ph

en

ico

l

Te

tra

cyclin

Fo

sfo

mycin

Isolate

aa

c(6

')Ib

-cr

str

A

str

B

aa

dA

1

aa

dA

4

aa

c(3

)-IId

bla

KP

C2

bla

TE

M-1

B

bla

OX

A-1

bla

CM

Y-4

8

/65

/68

/76

/84

bla

CM

Y-4

9

bla

SH

V-1

1

bla

OX

A-9

bla

OX

Y-5

-1

bla

AC

T-1

4

aa

c(6

')Ib

-cr

Qn

rB4

9

oq

xA

+o

qxB

Qn

rB1

Qn

rB1

9

Qn

rB3

8

Qn

rS1

mp

h(A

)

AR

R-3

ca

t B

3

su

l1

su

l2

tet(

B)

dfr

A1

; d

frA

14

dfr

A1

8

fosA

CA_13304 N

CB_13142 N

CF_08698 N

CF_11993 N

CF_12637 N

CF_12908 N

CF_13014 N

CF_13066 N

CF_13069 N

CF_13141 N

CF_13143 N

CF_13479 N

CF_14650 N

CF_14655 N

CF_16178 N

CF_16680 N

CK_13481 N

EC_11992 N

EC_12632 N

EC_13177 N

EC_13848 N

EC_16154_2 N

EC_16155 N

EC_16156 N

EA_12869 N

EA_13139 N

EA_16186 N

Enc_16154_1 N

KO_13047 N

KO_13048 N

KO_13137a N

KO_14641 N

KO_14657 N

KO_16162 N

KP_13205 N

KP_13846 N

KP_11394 FIB

Aminoglycoside

Tri

me

tho

pri

m

KP

C-2

en

co

din

g In

c g

rou

p

Betalactame

Su

lph

on

am

ide

Fluorquinolone





Plasmids present in isolates

36

LR CA

13304

CF

12908

EC

11992

1EC

6155

KP

11394

LM CF

14650

CF

11993

CF

16178

EA

16186

KO

14641

KP

13846

CK

13481

Plasmid diversity

37

same patient

same patient

same patient

21 53 4

aac(3)-IId

blaTEM-1B

blaKPC-2

Regions deleted:1.+2. orf3. StrA, StrB4. dfrA18, sul1, QnrB495. mph(A), sul1, ARR3, catB3, blaOXA1, aac(6’)Ib-cr





A transmissible IncN-plasmid harbouring KPC-2 and 17 other resistance genes

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Dynamic MDR Region

Unique

Segment

From the environment to clinic

Citrobacter freundii



Klebsiella pneumoniae

Klebsiella oxytoca

Enterobacter aerogenes

Escherichia coli

Escherichia coli

Klebsiella oxytoca

Enterobacter spp.

Environment Hospital

Klebsiella oxytoca

Vectors of transmission

Klebsiella oxytoca

Klebsiella oxytoca

Klebsiella oxytoca

Citrobacter spp.

C. freundii

C. freundii

C. freundii

39

Contaminated water as outbreak source

40





How is DNA-transferred?

41

Conjugation Transformation

Transduction

Downloaded from Wikipedia





Citrobacter freundii produce Outer Membrane Vesicles (OMVs)

The Functions of Outer Membrane Vesicles

Microbe-microbe interactions

Virulence factor delivery

Contain DNA

Bacterialpqs

Elimination of unwanted proteins, metabolites

Stimulation of adaptive immune

response

Stimulation of innate immune

responseBiofilm formation

250 -130 -

95 -72 -

55 -

36 -

28 -

17 -

10 -

kDa M WC OMVs

Fig. Transmission electron micrograph and protein profiles of C. freundii’s OMVs. (A) Negative-staining TEM of OMVs.(B) CBB-stained SDS-PAGE of whole-cell lysates (WC) and OMVs. Molecular weight standards are indicated on the left(kDa)

BA

Analysis of the vesicular proteins by SDS-PAGE and TEM

44

OMV´s induce host cell responses

Rapamycin E. coli MG1665 hlyF induced OMVs

C. freundii‘s OMVs E. coli MG1655 OMVs

A

Fig. (A) Autophagosome formation (green punctate structures) in HeLa cells expressing GFP-LC3 after treatment with Rapamycin, C. freundii’sOMVs and hlyF induced OMVs. (B) Immunoblot of UPR indicators including phosphorylated eIF2a and total eIF2a, in lysates of HeLa cellsuntreated (N) or treated with Citrobacter’s OMVs. As positive controls, HeLa cells were treated with 5 µM thapsigargin. GAPDH is shown as aloading control.

eIF2α-p51

eIF2α

38kDa

38kDa

N 0 2 4 6 24 Time [h]

Thapsigargin eIF2α-p51

B

Induction of ER stress

GAPDH37kDa

45





Can vesicle DNA transferred?

46

+ =

?

plasmid DNA

M 1 2 3 4 5 6 M

48,5 -

97,0 -

145,5 -

194,0 -

242,5 -291,0 -

Fig. S1-linearized plasmids visualized on a PFGE gel. The lanes 1 - E. coliJ53, 2 - 5 - OMVs transformed E. coli J53, 6 – C. freundii

Fig. PCR detected KPC-2 gene transferred byC. freundii NRZ 08698 vesicles to recipient J53 cells.

N POMVs

transformants kbp

OMV-mediated DNA transfer

47





Overcoming distance

48

µm mm

Genome annotation

Genome-sequencedatabase

Genome-sequenc.

Quality control

Genomeassembly

Genome orientation

Comparative Genomics

Plasmid/Phage-sequence-database

Virulence-gene-database

Antibiotic-resistance-database

MLST 7 /31 House-keeping gene Phylogeny

Core genome MLST

ReadXplorer

AAI/ANI

Molecular Epidemiology Platform

Number of SNPs

SNP Phylogeny

GIS

Epidemiology

Diagnostic, Epidemiology, therapy-recommendations, Vaccines

16S rRNAphylogeny

Conclusion

•Diagnostic microbiology is poised for revolutionary

changes

•Medium- to high-throughput –omics technologies

•Development of Point-of-Care diagnostics

•Evidence-based treatments

•and…. there is still a lot to develop and learn

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Acknowledgment

•Institute of Medical Microbiology, Justus-Liebig-University Giessen, Germany

–Dr. Can Imirzalioglu–Dr. Linda Falgenhauer–Dr. Yancheng Yao–Dr. Moritz Fritzenwanker–Dr. Torsten Hain–Dr. Judith Schmiedel –Dr. Swapnil Doijad–Hiren Ghosh–Konrad Gwozdzinski–Christina Gerstmann–David Dippel–Rolf Hilker

RESET

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Microbiology diagnostic laboratory

•Detection – grow isolate from specimen

•Identification – identify species

•Susceptibility – antimicrobial testing

•Epidemiology – Public Health

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Signature

Gram-

Gene list

Patient

PMN

Monocytes

Gram+Gram-

Signature

Gram+

Therapy

Gene list

Gram+Gene list

Gram-

TRANSKRIPTOME

DIAGNOSTICS

From bench to bedside and back

Host-pathogen-interaction

= „Battle of the Genomes“

Macrophage T-cell Bacteria3 000 – 6 000 genes

~30 000 genes

Expression profiles in acute respiratory infections

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Nanostove® detection• Turn-around time in about 15 minutes• 5x faster than competitors• Ease-of-use• Near-patient testing• Less sample preparation• Simple cartridge for each panel assay

Point-of-care detection of antibiotic-resistance genes

Trinad Chakraborty Centre for Medical Microbiology and ... · Microbiology and Virology German...

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