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Eyes for the invisible: microfluidic paper-based analytics (µPads) and
3rd - generation sequencing in clinical microbiology
John WA Rossen, PhD, MMM
Principle Investigator - Genomics for Infection Prevention
Head Molecular Unit
Department of Medical Microbiology, University of Groningen, University Medical
Center Groningen, Groningen, The Netherlands
Disclosure of speaker’s interests
(Potential) conflict of interest None
Potentially relevant company relationships in
connection with event
None
 Sponsorship or research funding
 Fee or other (financial) payment
 Shareholder
 Other relationship
· Interreg IVa-funded projects EurSafety
Heath-net (III-1-02=73) and SafeGuard
(III-2-03=025)
· None
· None
· None
Disclosure slide for speaker at further training events
Eyes for the invisible
A Dutch tradition?
Antoni van Leeuwenhoek (1632-1723)
Martinus Beijerinck (1851 - 1931)
Filtration experiments  Virus
Questions the patients have regarding
infections/infectious diseases
1. Did you prevent colonization and infection today?
2. Do I have an infection/ID and which one?
3. What is the optimal therapy?
Molecular Diagnostics – a powerful tool
• Detection (Real-time PCR/NASBA/LAMP)
– Unculturable micro-organisms
– Viral/bacterial load
– Therapeutic monitoring
• Typing (PCR, DNA arrays, Sequencing, AFLP)
– Surveillance of infectious diseases
– Outbreak investigation (epi-typing)
– Pathogenesis and course of infection (patho-typing)
• drug resistance (genes) and virulence genes
Does NGS fits it all?
Wet-lab technicians – practical work
Analysis performed by
• E-lab Technicians (Sigrid/Erwin)
• Master Kai Zhou teaches
Post-docs and PhDs
Amplicon-based approach
• Use of the Hospital Acquired Infections (HAI)
BioDetection approach for:
– rapid identification of negative clinical samples
– detection of microbes and resistance/virulence
genes
10
HAI BioDetection Kit (BioInnovation Solutions SA)
• amplicon-based NGS
• 298 probes (150-190 bp fragments sequenced)
= 144 PCRs
0 hour
Clinical sample
2 hours
DNA isolation
4.5 hours
Work flow
Sample prep (24)
10 hours
Template prep (12)
13.1 hours
Sequencing (12)
≈14 hours
Results (12)
Whole (full) genome sequencing
• Resolve resistance mechanisms
• Find virulence genes
• Outbreak investigation
Klebsiella pneumoniae KPC-outbreak
• KPC-KP ST258
• Hospital and nursing home (July – Dec 2013)
• 6 positive patients
• Extensive environmental contamination
Weterings et al., in revision
WGS and typing by a gene-by gene approach
Using Ridom’s Seqsphere
WGS
Resistance genes:
• Blakpc-2
• BlaSHV-12
ST 258 in Europe
(Curated) databases for early-warning required
Outbreak in a reha-center
• Between May and September 2012
• CTX-M-15 producing K. pneumoniae
• first occurred in a university hospital and later
spread to a nearby rehabilitation center
• sequence type (ST) known to be an epidemic
clone
• May 2013 - similar CTX-M-15 producing ST15 K.
pneumoniae isolated from a patient admitted to
the university hospital
Patient Referral Network in the Netherlands
Donker et al. Math Biol 2012
Prof H. Grundmann, UMCG
University Hospitals
Regional Centers
Local Hospital
Phylogenetic analysis of K.
pneumoniae isolates
Zhou et al., submitted
Combining data
• An epidemiological link was found between
the 2012 and 2013 isolates
• Supported by whole-genome sequencing
(WGS) only a few single-nucleotide
polymorphisms (SNPs) were detected
• WGS analysis of environmental isolates
indicates a possible role for the environment
in dissemination of outbreak clones.
The putative transmission chains of
the 2012 outbreak
Outbreaker (Jombart et al., 2014)Zhou et al., submitted
Outbreak clone specific Dx-test
Using BRIG to identify
variable regions
Designing primers to amplify
Unique marker
Screen patient isolates
The results of multiplex PCR specific to
the outbreak clone
Tailor-made diagnostics
(Unique gene analysis - UGA)
Classical
Screening DiagnosticOutbreak Typing Action
E. coli ESBL VRE KPN
Next Gen
NGS UGA
“Precision microbiology”
Conclusions
• WGS allows typing and molecular
characterization of the outbreak clone (AMR,
virulence)
• The outbreak-specific multiplex PCR facilitated
rapid patient screening procedures
• The study emphasizes the necessity of regional
collaborations for efficient infection control
measures and indicates the potential of WGS for
optimized outbreak management in hospital
settings
A certain microbe found = Infection?
Diagnostics today:
ID Species -> Clinical orientation
found in
blood/wound etc.
Resistance -> Therapy advice
Sub-/Genotype -> Infection prevention/Public Health
Pygocentrus nattereri (Piranha) Strepotoccus pyogenes (A-streptococcus)
?
Infectious Disease Staging/Therapy follow-up
by diagnostic gene expression profiling
Whole transcriptome sequencing
R
N
A
Metagenome sequencing
-> Collaborate with Pathology, Oncology, Genetics
Pharmacomicrobiomics
High-throughput sequencing for everyone ?
Phase 1: more is better
Phase 2: smaller is better
Phase 3: single-molecule
Phase 4: nanopores
“democratization” of next-generation sequencing
The MinION device is adaptable for DNA sequencing,
protein sensing and other nanopore sensing techniques
$ 1000
Costs of Sequencing and costs of data analysis
Sboner et al. (2011). Genome Biol. 12: 125 [PubMed].
Real Cost of Sequencing
Sboner et al. (2011). Genome Biol. 12: 125 [PubMed].
www.worldmapper.org
Mortality due to Infectious diseases
Microfluidics
smaller sample volume - increased speed and multiplexing possibilities
"The origins and the future of microfluidics" - G.M. Whitesides, Nature, 2006.
DOI:10.1038/nature05058
Microfluid-based point-of-care testing
Relevance of POCT
Clinic Relevance POCT Influence
Sepsis, Meningitis,
Pneumonia
High – specially in (N)ICUs Direct impact on clinical
outcome
Tuberculosis High for identifying drug-
resistant strains
Direct impact on clinical
outcome
Respiratory and GI-viruses Prevention of outbreaks
and ABS
Direct impact on
disease/patient
management
Antimicrobial resistance Monitoring emerging
resistance – outbreak
prevention
Direct impact on
disease/patient
management
STDs Low
POCT in resource-limited settings
• No costly laboratory based systems
• No need for well-trained technicians
• No need for good sample transport networks
• Self-contained quality control
• Fast – same day result
• Linked to a site where clinical decision making
is available at the same patient visit
New technological trends
• Smart Phone Diagnostics
• μPADs (micro-paper based analytical devices)
Partially from Martinez et al., Anal. Chem. (2010)
Strategy for performing inexpensive
bioassays in remote locations
Martinez et al., Anal. Chem. (2008)
Personalized Diagnostics using Nanocapsules
Courtesy : Mesa+ Nanolab, University of Twente, Netherlands
EHEC O157
please go to
your GP
From (molecular) microbiologist to nanobiologist ?
WGS
DNA Chips
Lab-on-a-chip
Doctor-on-a-chip
Nanotechnology
μPADs
Method centered diagnostics
CostTime
Quality
€-hour-systematic
100 h * 3€ = 1h * 300€
Cost
Prevention
Quality
Time
Therapy
Diagnostic
Patient-centered diagnostics
MMB mission
Protect patients against infections by
• Fast and precise Dx
• Advising in optimal treatment
• Obtain and share knowledge
 in the patient’s interest
Application of on-demand in-house developed and validated
diagnostics: personalized theragnostics
“Voici mon secret. Il est très simple: on ne voit bien qu'avec le cœur.
L'essentiel est invisible pour les yeux.”
Le Petit Prince (1943) by Antoine de Saint Exupéry
Translation: “Here is my secret. It is very simple: It is only with the heart
that one can see rightly; what is essential is invisible to the eye.”
ESCMID Postgraduate Technical Workshop
Capacity-building Workshop: rapid NGS for characterization
and typing of resistant gram negative bacilli
October 7th – 9th, 2015, UMCG Groningen, The Netherlands

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Rossen eccmid2015v1.5

  • 1. | 1 Eyes for the invisible: microfluidic paper-based analytics (µPads) and 3rd - generation sequencing in clinical microbiology John WA Rossen, PhD, MMM Principle Investigator - Genomics for Infection Prevention Head Molecular Unit Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
  • 2. Disclosure of speaker’s interests (Potential) conflict of interest None Potentially relevant company relationships in connection with event None  Sponsorship or research funding  Fee or other (financial) payment  Shareholder  Other relationship · Interreg IVa-funded projects EurSafety Heath-net (III-1-02=73) and SafeGuard (III-2-03=025) · None · None · None Disclosure slide for speaker at further training events
  • 3. Eyes for the invisible A Dutch tradition?
  • 4. Antoni van Leeuwenhoek (1632-1723) Martinus Beijerinck (1851 - 1931) Filtration experiments  Virus
  • 5. Questions the patients have regarding infections/infectious diseases 1. Did you prevent colonization and infection today? 2. Do I have an infection/ID and which one? 3. What is the optimal therapy?
  • 6. Molecular Diagnostics – a powerful tool • Detection (Real-time PCR/NASBA/LAMP) – Unculturable micro-organisms – Viral/bacterial load – Therapeutic monitoring • Typing (PCR, DNA arrays, Sequencing, AFLP) – Surveillance of infectious diseases – Outbreak investigation (epi-typing) – Pathogenesis and course of infection (patho-typing) • drug resistance (genes) and virulence genes
  • 7. Does NGS fits it all?
  • 8. Wet-lab technicians – practical work
  • 9. Analysis performed by • E-lab Technicians (Sigrid/Erwin) • Master Kai Zhou teaches Post-docs and PhDs
  • 10. Amplicon-based approach • Use of the Hospital Acquired Infections (HAI) BioDetection approach for: – rapid identification of negative clinical samples – detection of microbes and resistance/virulence genes 10
  • 11. HAI BioDetection Kit (BioInnovation Solutions SA) • amplicon-based NGS • 298 probes (150-190 bp fragments sequenced) = 144 PCRs
  • 12. 0 hour Clinical sample 2 hours DNA isolation 4.5 hours Work flow Sample prep (24) 10 hours Template prep (12) 13.1 hours Sequencing (12) ≈14 hours Results (12)
  • 13. Whole (full) genome sequencing • Resolve resistance mechanisms • Find virulence genes • Outbreak investigation
  • 14. Klebsiella pneumoniae KPC-outbreak • KPC-KP ST258 • Hospital and nursing home (July – Dec 2013) • 6 positive patients • Extensive environmental contamination
  • 15. Weterings et al., in revision WGS and typing by a gene-by gene approach Using Ridom’s Seqsphere WGS Resistance genes: • Blakpc-2 • BlaSHV-12
  • 16. ST 258 in Europe (Curated) databases for early-warning required
  • 17. Outbreak in a reha-center • Between May and September 2012 • CTX-M-15 producing K. pneumoniae • first occurred in a university hospital and later spread to a nearby rehabilitation center • sequence type (ST) known to be an epidemic clone • May 2013 - similar CTX-M-15 producing ST15 K. pneumoniae isolated from a patient admitted to the university hospital
  • 18. Patient Referral Network in the Netherlands Donker et al. Math Biol 2012 Prof H. Grundmann, UMCG University Hospitals Regional Centers Local Hospital
  • 19. Phylogenetic analysis of K. pneumoniae isolates Zhou et al., submitted
  • 20. Combining data • An epidemiological link was found between the 2012 and 2013 isolates • Supported by whole-genome sequencing (WGS) only a few single-nucleotide polymorphisms (SNPs) were detected • WGS analysis of environmental isolates indicates a possible role for the environment in dissemination of outbreak clones.
  • 21. The putative transmission chains of the 2012 outbreak Outbreaker (Jombart et al., 2014)Zhou et al., submitted
  • 22. Outbreak clone specific Dx-test Using BRIG to identify variable regions Designing primers to amplify Unique marker Screen patient isolates
  • 23. The results of multiplex PCR specific to the outbreak clone
  • 24. Tailor-made diagnostics (Unique gene analysis - UGA) Classical Screening DiagnosticOutbreak Typing Action E. coli ESBL VRE KPN Next Gen NGS UGA “Precision microbiology”
  • 25. Conclusions • WGS allows typing and molecular characterization of the outbreak clone (AMR, virulence) • The outbreak-specific multiplex PCR facilitated rapid patient screening procedures • The study emphasizes the necessity of regional collaborations for efficient infection control measures and indicates the potential of WGS for optimized outbreak management in hospital settings
  • 26. A certain microbe found = Infection? Diagnostics today: ID Species -> Clinical orientation found in blood/wound etc. Resistance -> Therapy advice Sub-/Genotype -> Infection prevention/Public Health Pygocentrus nattereri (Piranha) Strepotoccus pyogenes (A-streptococcus) ?
  • 27. Infectious Disease Staging/Therapy follow-up by diagnostic gene expression profiling Whole transcriptome sequencing R N A Metagenome sequencing -> Collaborate with Pathology, Oncology, Genetics Pharmacomicrobiomics
  • 28. High-throughput sequencing for everyone ? Phase 1: more is better Phase 2: smaller is better Phase 3: single-molecule Phase 4: nanopores “democratization” of next-generation sequencing
  • 29. The MinION device is adaptable for DNA sequencing, protein sensing and other nanopore sensing techniques $ 1000
  • 30. Costs of Sequencing and costs of data analysis Sboner et al. (2011). Genome Biol. 12: 125 [PubMed].
  • 31. Real Cost of Sequencing Sboner et al. (2011). Genome Biol. 12: 125 [PubMed].
  • 33. Microfluidics smaller sample volume - increased speed and multiplexing possibilities "The origins and the future of microfluidics" - G.M. Whitesides, Nature, 2006. DOI:10.1038/nature05058
  • 35. Relevance of POCT Clinic Relevance POCT Influence Sepsis, Meningitis, Pneumonia High – specially in (N)ICUs Direct impact on clinical outcome Tuberculosis High for identifying drug- resistant strains Direct impact on clinical outcome Respiratory and GI-viruses Prevention of outbreaks and ABS Direct impact on disease/patient management Antimicrobial resistance Monitoring emerging resistance – outbreak prevention Direct impact on disease/patient management STDs Low
  • 36. POCT in resource-limited settings • No costly laboratory based systems • No need for well-trained technicians • No need for good sample transport networks • Self-contained quality control • Fast – same day result • Linked to a site where clinical decision making is available at the same patient visit
  • 37. New technological trends • Smart Phone Diagnostics • μPADs (micro-paper based analytical devices) Partially from Martinez et al., Anal. Chem. (2010)
  • 38. Strategy for performing inexpensive bioassays in remote locations Martinez et al., Anal. Chem. (2008)
  • 39. Personalized Diagnostics using Nanocapsules Courtesy : Mesa+ Nanolab, University of Twente, Netherlands EHEC O157 please go to your GP
  • 40. From (molecular) microbiologist to nanobiologist ? WGS DNA Chips Lab-on-a-chip Doctor-on-a-chip Nanotechnology μPADs
  • 42. Cost Prevention Quality Time Therapy Diagnostic Patient-centered diagnostics MMB mission Protect patients against infections by • Fast and precise Dx • Advising in optimal treatment • Obtain and share knowledge  in the patient’s interest Application of on-demand in-house developed and validated diagnostics: personalized theragnostics
  • 43. “Voici mon secret. Il est très simple: on ne voit bien qu'avec le cœur. L'essentiel est invisible pour les yeux.” Le Petit Prince (1943) by Antoine de Saint Exupéry Translation: “Here is my secret. It is very simple: It is only with the heart that one can see rightly; what is essential is invisible to the eye.”
  • 44. ESCMID Postgraduate Technical Workshop Capacity-building Workshop: rapid NGS for characterization and typing of resistant gram negative bacilli October 7th – 9th, 2015, UMCG Groningen, The Netherlands

Editor's Notes

  1. A maximum likelihood tree was constructed based on the alignments of a 4.4Mb genome, defined as the core genome in this study. The tree was rooted on the isolate KP-21F. The outbreak clones are shown as a red triangle. The non-outbreak isolates of this study are indicated as a blue dot, and the others, retrieved from GenBank, are indicated as black dots. The numbers represent the percentage of bootstrap support (> 90). The inset shows the close-up phylogenetic tree of isolates from each outbreak. The outbreak isolates of patients are shown as red (2012) and yellow (2013) dots, and the environment isolates are shown as green dots. The number of SNPs is indicated on the branches.
  2. The transmission route was predicted with patient trace data combined with genetic data. Nodes with numbers represent patients, and arrows indicated a possible transmission event from one patient to another. The blue arrows represent a transmission even between patients predicted by both epidemiological data and genetic data, and the red arrows indicate the equally parsimonious transmission link which cannot be resolved by neither epidemiological data nor genetic data