Transmission of Pathogens and Molecular Phylogenetics

WHO collaborating centre for Arbovirus and Hemorrhagic Fever Reference and Research

Transmission of pathogens and molecular phylogenetics: From surveillance typing to metagenomics Prof Dr Marion Koopmans, public health virology [email protected]; eLibrary @MarionKoopmans © by author ESCMID eLibrary © by author Research focus: getting ahead of the curve

ESCMIDKaresh et al., 2012 eLibrary © by author EID: the challenge

. Most EID come from animals, . Once introduced in people, many but prediction of transmissibility opportunities for transmission: and severity are challenging . WHEN it occurs, things can move extremely fast

ESCMIDWolfe et al., 2007; http://rambaut.github.io/EBOV_Visualization/Makona_1561_D3/; eLibrary Gytis et al., 2017 © by author Perspective: The use of pathogen genetic data that can inform (emerging) disease preparedness and response

. What pathogens to track and how to do that efficiently? . role of metagenomics?

. From genotype to phenotype: prediction of key parameters for hazard characterisation / decision making . Ability to infect humans and transmit between them . Ability to cause (severe) disease . Treatability . TrackingESCMID of sources and transmission eLibrary pathways © by author Choice of method and necessary resolution depends on question asked ICTV, increasingly uniform Family . Caliciviridae

Genus . Norovirus (vesi-, sapo, ea)

diagnosis

tracking outbreak Species . Genogroup I, II, III, IV, V, VI, VII X Subgroup . Genotype GII.4, 40 genotypes (X) … . GII4: antigenic variant Sydney X … . Sequence type, SNP’s X X Specialists > Wide ESCMID diversity eLibrary © by author Choice of method and necessary resolution depends on question asked

Family . Orthomyxoviridae

Genus . Influenza A - Toghoto

diagnosis

tracking outbreak

Species . Influenza A virus X Subgroup . Subtypes HA and NA X

… . antigenic variants, host variants X

X X … . Sequence , SNP’s ESCMID eLibrary © by author Choice of method and necessary resolution depends on question asked

Family . Filoviridae

tracking

diagnosis outbreak Genus . Ebola

Species . Reston, Zaire, etc X X Subgroup . Geographic lineages? (X) … . …..

… . Sequence type, SNP’s X X ESCMID eLibrary © by author Case: woman in her 20s, returning from travel to Surinam, with febrile illness and liver function abnormalities > is this an isolated case?

Background:

Expanding yellow fever outbreak in Brazil

Links with Brazil through illegal mining Wouthuyzen ESCMID-Bakker et al., 2017 eLibrary © by author 1. YFV related to Brazil sequences

2. Recent sequences are distinct > not related to outbreak ESCMID eLibrary © by author Case:

D1: School aged child, history of eczema Flu like symptoms in October 2016

D2: GP visit > antibiotics

D3: Rapid deterioration > admission to pediatric ICU Respiratory panel > Influenza A positive Species

D5: Further deterioration > referral for ECMO

D6: repeated sampling and subtyping > H1N1 Subtype Sequencing: swine influenza virus Variant (swine)

Fraaij ESCMIDet al., 2016 eLibrary © by author Immediate questions

. What is the source? Sequence type . Is it a fully swine virus or a recombinant? variant . Is it a single case?

visit of pig farm 2 days pre-illness onset, entered barn No earlier symptoms No others with symptoms Pigs sampled Fraaij ESCMIDet al., 2016 eLibrary © by author 1. Swine and human virus highly similar 2. All internal genes swine 3. Closest relatives NL viruses Does the sequence data provide definitive evidence?

 Importance of representative up to date reference database

 Understanding evolutionary rates ESCMID eLibrary © by author Using molecular diversity to estimate relatedness: the importance of understanding rates of change and a word of caution

Estimates of rate of change are diverse

Wide confidence intervals

> Impacts on resolution of sequence based linking

Aiewsakun ESCMIDand Katzourakis, 2016 eLibrary © by author Probability of identical sequences in unrelated cases by estimated rate of change (nt/site/yr)

0.01 0.001 0.01 0.001 60% potentially Almost falsely 30% linked potentially falsely linked

19.8 kb, eg Ebola 7.38 kb, eg norovirus http:// epidemic.bio.ed.ac.ukESCMID/viral_sequence_similarity eLibrary © by author Importance of adding metadata Genotype >

Genogroup >

GGII ~80% Seasonal HCAI Dominant Variant (GII.4) GGI ~20% More varied Food

Clarke et ESCMIDal, 2010; Verhoef et al., 2011; Kroneman et al., 2013,eLibrary van Beek et al, 2018 © by author Probability that 2 outbreaks are indicative of an common source event outbreak is greater for rare genotypes > Same level of genetic diversity leads to different conclusions based on epidemiology

Eg: 2 simultaneous G1P1 outbreaks: strong suspicion of food or environmental link

2 simultaneous GII4 outbreaks: link unlikely van BeekESCMID et al, Lancet Inf Dis, 2018 eLibrary © by author Effects of strain diversity of FB disease estimates from attribution analysis

Systematically collected data

Comparison sequence diversity in food sources and in human disease

Great fluctuations in estimated foodborne illness

> Genotyping is indicative but not proof

ESCMIDVerhoef et al., 2015 eLibrary © by author Importance of platform choice, quality control, and workflow Transplant patients with chronic norovirus WGS,

Standard reference set of commercial workflow Reference from first sample from patient specialised workflow Suggested between- patient transmissions

No evidence for between- patient transmissions Van Beek ESCMIDet al., 2017 eLibrary © by author COllaborative Management Platform for detection and Analyses of (Re-) emerging and foodborne outbreaks in Europe

Developing an enabling system and tools for collaborative preparedness and outbreak research

1.Protocols, standards 2. Across Pathogens (bacteria, viruses, parasites) 3. Across Sectors (clinical public health, academia) 4. Across Domains: a.o. medical, veterinary 5. Open source solutions 6. Agreed mechanisms and platforms for sharing 7. FAIR, Nagoya protocol

Aarestrup and Koopmans, 2016; Alleweld et al., 2017This project has received funding from the European Union’s Horizon 2020 ESCMID eLibraryresearch and innovation programme under grant agreement No 643476. © by author Pandemic Zoonosis “Reservoir”

H5N1 Influenza H6N1 viruses B? C? H7N2 H1N1 H7N3 H2N2 H7N7 H3N2 H7N9 pH1N1 H9N2 H10N7 H10N8 Intermediate hosts H3N2v H1N1v H1N2v We need knowledge of what makes flu virus transmissible (between humans or animals) ESCMIDFriedl et al., Eurosurveillance eLibrary 2014; Herfst & Fouchier, Eurosurveillance 2014 © by author Ongoing zoonotic influenza outbreaks in SE Asia

H5Nx infections Limited human to human spread

Few mutations can change that

Current Case fatality rate H7N9 infections >25%

Mandatory lock-up based on wild bird surveillance NL, UK, DE

ESCMIDLycett et al., 2016 eLibrary © by author Comparison of platforms and workflows, 3 reference centers substantial differences in SNP calls

> concluding on chain of transmission based on shared sequence data ESCMID needs to be done with caution eLibrary © by author A massive outbreak of neuroinvasive mosquito-borne disease in birds

Zoonotic, identified in European blood donors

Same mosquito as West nile

Heralding change in ecology of these viruses in ESCMIDnorthern Europe? eLibrary © by author Minion considered to be “noisy” for viral WGS Validation of WGS by comparison to Sanger, Ion Torrent, Illumina consensus Coverage: 100x (1) 100x (2) 1000x (1) 1000x (2) 3000 20x 81% 21x 86% Coverage of 100x 22x 84% 23x 85% results in a 24x 87% reliable 25x 93% consensus 26x 84% 27x 94% sequence 28x 90% 29x 97% 50x 98% 98% 98.6% (2959/3000) 70x 100% 99% 99.6% 75x 100% 100% 99.4% 99.7% 100x 100% 100% 99.9% 100% 100% 105x 100% 100% 110x 100% 115x 100% 130x 100% 150x 100% 200xESCMID 100%eLibrary © by author At least two lineages Suggests one is exotic, one is enzootic What does that mean for human health risk?

Blue = Owl Africa 3 lineage Red = Blackbird Green = Mosquito Light blue = Pigeon

Europe 3 lineage Engel etESCMID al., 2016; Reusken et al., in preparation eLibrary © by author Exploring metagenomics for combined detection and typing, and visualization of information for clinicians

0.1

EV-D68 (JX101846) 98

92 EV-D68 (JX070222)

EV-D68 (KF726085)

85 EV-D68 (EF107098)

EV-D68 (AB601882) 99 EV-D68 (AB601883)

EV-D68 (AY426531)

E1000586 100 100 E1000268 100 EV-D70 (D00820) 99

EV-D70 (NC_001430) 100 EV-D70 (DQ201177)

EV-D94 (DQ916376) 100 EV-D94 (EF107097) . Diarrheal pathogens . OtherESCMID viruses present, con-infections, eLibrary discovery © by author Metagenomics

• Catch all technology • Sample dependent • Explosion of protocols and tools • Hard to choose for clinical/public health applications

> In depth review of metagenomics workflows

. Use of sequence based techniques for outbreak detection, case linking, source tracking is complex . Need for validation of platforms, workflows for specific questions . Control runs . Curated databases . reproducibility . For outbreak questions, always compare with samples from unrelated cases . No universal solution across virus families at present . Link with good metadata is essential . Fast developing platforms ESCMID eLibrary © by author ESCMID eLibrary © by author WHO collaborating centre for Arbovirus and Hemorrhagic Fever Reference and Research

Strategic academic partnership One Health, WUR, UU, AMC, LU, LUMC, KNAW, director EID theme National contact point (MOH appointed) for emerging viral diseases BSL4, EU health threat unit

Coordinator of European network for imported viral diseases for ECDC (BSL3 and 4)

COllaborative Management Platform for detection and Analyses of (Re-) emerging and foodborne outbreaks in Europe BIG DATA, BIOINFORMATCIS ESCMID eLibrarywww.erasmusmc.nl/viroscience/ © by author