UCSF Osher Center for Integrative Medicine

Mini Medical School for the Public

FALL 2013 – Tuesday Course Series VACCINES, ANTIBIOTICS, AND INFECTIONS:

GETTING YOUR QUESTIONS ANSWERED Date: Tuesday, November 5, 2013, 7:00 pm – 8:45 pm Topic: NEW GENOMIC TECHNOLOGIES FOR IDENTIFYING EMERGING OUTBREAK VIRUSES AND DIAGNOSING UNKNOWN INFECTIONS IN HOSPITALIZED PATIENTS Speaker: Charles Chiu, MD, PhD, Assistant Professor, Laboratory Medicine and Medicine, Division of Infectious Diseases; UCSF Director, UCSF-Abbott Viral Diagnostics and Discovery Center BIOGRAPHY: Charles Chiu, MD, PhD. is Associate Professor of Laboratory Medicine and Medicine / Infectious Diseases at UCSF, Director of the UCSF-Abbott Viral Diagnostics and Discovery Center (VDDC), Assistant Director of the UCSF Clinical Microbiology Laboratory, and a staff infectious diseases physician at UCSF. After undergraduate work at UC Berkeley, he received his PhD in biophysics and his MD at University of California, Los Angeles, and subsequently completed residency training in internal medicine and fellowship in infectious diseases at UCSF. Dr. Chiu is an expert in the development and validation of advanced genomic technologies – microarrays and next-generation sequencing (NGS) – for pathogen discovery and clinical diagnostic development, with over 50 patents and peer-reviewed publications on these topics. He has spoken at numerous national and international conferences on new diagnostic development for emerging viruses such as H7N9 influenza and MERS coronavirus, and is on an FDA-sponsored task force on genomic technologies for blood bank pathogen screening and outbreak surveillance. His research is supported by an NIH R01 grant, a California Discovery Grant, and a 7-year UCSF-Abbott Viral Discovery Award. BIBLIOGRAPHY: Chen EC, Yagi S, Kelly KR, Mendoza SP, Maninger N, Rosenthal A, Spinner A, Bales KL, Schnurr DP, Lerche NW, and Chiu CY. (2011) Cross-species transmission of a novel adenovirus associated with a fulminant pneumonia outbreak in a titi monkey colony. PloS Pathogens 7(7):e1002155. Chiu CY and Miller, SM. (2011) Microarrays and deep sequencing in clinical microbiology. Microbe, 6(1) (download from http://vddc.ucsf.edu)

UCSF Osher Center for Integrative Medicine

Mini Medical School for the Public Chiu CY (2013) Viral pathogen discovery. Current Opinion in Microbiology 16(4):468-478. Fournier PE, Drancourt M, Colson P, Rolain J-M, La Scola B, and Raoult D. (2013) Modern clinical microbiology: new challenges and solutions. 11:574-585. Greninger AL, Chen EC, Sittler T, Scheinerman A, Roubinian N, Yu G, Kim E, Pillai DR, Guyard C, Mazzulli T, Isa P, Arias CF, Hackett Jr. J, Schochetman G, Miller S, Tang P, and Chiu, CY. (2010) A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America. PloS ONE 5(10):e13381. Grard G, Fair JN, Lee D, Slikas E, Steffen I, Muyembe J-J, Sittler T, Veeraraghavan N, Ruby G, Wang C, Makuwa M, Mukendi EB, Mulembakani P, Mazet J, Rimoin A, Taylor T, Schneider BS, Simmons G, Delwart E, Wolfe ND, Chiu CY, and Leroy, E. (2012) A novel rhabdovirus associated with acute hemorrhagic fever in Central Africa. PloS Pathogens 8(9):e1002924.

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New Genomic Technologies for Identifying Emerging Outbreak Viruses and Diagnosing Unknown Infections in

Hospitalized Patients

Charles Chiu, MD / PhD

Assistant Professor, Departments of Laboratory Medicine and Medicine / Infectious Diseases,

University of California San Francisco

Director, UCSF-Abbott Viral Diagnostics and Discovery Center

Associate Director, UCSF Clinical Microbiology Laboratory

Disclosures

• Abbott Diagnostics (research support for viral pathogen discovery)

• Amazon.Com (research support for cloud-computing analysis pipeline development)

• Rubicon Genomics (advisory board)

Summary of Talk

1. Case report a 14 year-old immunocompromised boy with an undiagnosed critical illness

2. Tools of the “microbe hunter” microarrays and next-generation sequencing (NGS)

3. The SURPI (“sequence-based ultra-rapid pathogen identification”) pipeline for NGS analysis

4. Investigation of an outbreak of pneumonia in a monkey colony at UC Davis, USA

5. Investigation of an unknown acute hemorrhagic fever outbreak in central Africa

6. Back to the case!

• 14 year-old boy with severe combined immunodeficiency (SCID) after 3 partially successful bone marrow transplants gets very sick

• Headache and fever progressed to coma and hydrocephalus, elevated cerebrospinal fluid pressure (CSF) in the head, a 4 month period

Case Report

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Brain MRI (magnetic resonance imaging)

• CSF: 125 white blood cells (18% neutrophils, 52% lymphocytes), 0 red blood cells, protein of 97 mg/dL, glucose of 24 mg/dL

• Exhaustive diagnostic workup including brain biopsy was unrevealing

• Multiple empiric antibiotic regimens without improvement

• Ultimately trialed on IV steroids for possible “neurosarcoidosis” but continued to deteriorate

Case Report (continued)

• Bacterial culture x 10 negative• BK virus PCR negative• West Nile virus PCR negative• California encephalitis PCR negative• Pan-bacterial 16S PCR x 3 negative• Viral culture x 2 negative• Aspergillus Ag negative• Mumps culture negative• Fungal culture x 3 negative• Human herpesvirus 7 negative• Acid-fast bacilli smear and culture negative• Cryptococcus antigen negative• Histoplasma antigen negative• Parvovirus B19 PCR negative• Enterovirus PCR negative• Blastomyces Ag negative• Adenovirus PCR negative• CMV PCR negative• HIV RNA negative• Influenza PCR negative• Rhinovirus PCR negative……….......

Partial List of Studies

All tests negative!

Many Acute Infectious Diseases Remain Undiagnosed

Pneumonia

15 – 25%unknown cause

60-80%unknown cause

Up to 50% unknown cause

Diarrheal Disease Meningitis / Encephalitis

Hemorrhagic Fever

~20% unknowncause

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Emergence of New Pathogens

MERS Coronavirus

2009 pH1N1 Influenza

AND

Avian H5N1 / H7N9

influenza

E. Coli O104:H4

Courtesy of David Rasko, University of Maryland

Courtesy of CDC

Courtesy of CDC

1. the “one bug, one test” paradigm in infectious diseases

2. pathogens (organisms, or microbes, that cause infectious disease) can be very different, or novel. Their DNA sequence can be highly divergent – differing significantly from any other sequence in existing reference databases

3. low sensitivity of existing tests in detecting organisms present at very low concentrations in clinical samples

Why Can’t We Diagnose More Infections?

Conventional Virus Detection Methods have Limitations

Virus Culture ElectronMicroscopy

Serology PCR

Direct AntigenDetection (DFA)

Viruses are Extremely Diverse

Anthony, et al. (2013), mBio

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DNA (Deoxyribonucleic Acid) – The Building Blocks of Life

Genomics the study of DNA (or RNA) sequences, including the “genomes” of microbes

Nearly All Microbes that Cause Infectious Diseases are Made of

DNA

Bacteria Viruses

Fungi Parasites

Prions

The Tools of the “Microbe Hunter”

Genomics

Next-GenerationSequencing (NGS)

Microarrays(Arrays)

Casting a Wide Net to Hunt Pathogens

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Microarrays – the “ViroChip”

• A pan-viral detection microarray developed at UCSF

• Viral sequence probes representing all viral species in GenBank

• Long, 70-nucleotide (“70mer” probes which can tolerate numerous mismatches and thus improve sensitivity for detection of divergent sequences

• 24-hr sample-to-answer turnaround time

• Used for discovery of novel viruses:

– SARS coronavirus (Wang, et al., PloS Biology 2003)

– Human cardioviruses (Chiu, et al., PNAS, 2008)

– Avian bornaviruses (Kistler, et al., Virol J., 2009)

• For diagnosis of respiratory and diarrheal viral infections, sensitivity of 85-90% and specificity of >99% relative to PCR (Chiu, et al., J Peds, 2008)

• Automated interpretation using E-Predict (Urisman, et al., Genome Biology, 2006)

• Latest version: Version 5 – 60,000 probes, on commercial Agilent platform ($100 / array)

E-Predict – Detection of Viral Pathogens in Blood

Chikungunya Virus Hepatitis A Virus

Dengue Virus Type 1 Hepatitis B Virus

H1N1 (Human)ProbesH3N2 Probes

H1N1 (Swine)Probes

ViroChip Identification of 2009 Pandemic Influenza H1N1 Virus Microarray Analysis

of St. Jude Reference Strains

Blinded assignments:96% accuracy

# Host Subtype HA NA1 human H1N1 H1 N12 avian H1N1 H1 N13 human H1N1 H1 N14 human H1N1 H1 N15 human H2N2 H2 N26 avian H2N2 H2 N27 avian H3N8 H3 N88 horse H3N8 H3 N89 human H3N2 H3 N2

10 avian H4N6 H4 N611 avian H5 H5 -12 avian H6N5 H6 N513 avian H6N2 H6 N214 horse H7N7 H6 N715 avian H7N3 H7 -16 avian H8N4 H8 -17 avian H9N2 H8 N218 avian H10N7 H10 N719 avian H11N9 H11 N920 avian H12N5 H12 N521 avian H13N6 H13 N622 avian H14N5 H9 N523 avian H15N9 H15 N924 avian H16N3 H16 N325 human H1N1 H1 N126 avian H2N2 H2 N227 avian H5N3 H5 N328 avian H8N4 H8 -29 avian H6N5 H11 -30 avian H11N6 H11 -31 horse H7N7 H7 -32 avian H3N8 H3 -

• Combines 49,135 ViroChip probes 2,630 influenza sub-typing

probes• Applied to respiratory viral cohorts:

Simultaneously detect respiratory viral pathogens and subtype influenza

(with Dr. Carlos Arias, University of Cuernavaca, Mexico and Drs. Michael Shaw and Stephen Lindstrom, CDC)

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Microarray (“BloodChip”) Detection of

Babesia microti

• specific detection at dilutions down to 1 genome/mL

Next-Generation Sequencing (NGS) forPathogen Diagnosis / Discovery

• Random amplification of DNA followed by next-generation “deep” sequencing of clinical samples

• In principle, truly unbiased technology that does not target any specific pathogen

• can be used to detect and reconstruct the sequence of nearlyany and all pathogens including viruses, bacteria, fungi, and parasites

• Capacity ranging from 1 million (Roche 454 Jr) to 50 million (MiSeq) to ~1 billion (HiSeq) sequences, or reads per run

• Bar-coded primers to allow multiplexing of clinical samples per run to reduce costs

• Requires development Customized specimen preparation protocols novel bioinformatics analysis tools

Sample Prep

SpecimenProcessingEnrichment

Sequencing / Detection

Bioinformatics

842 reads

10.5 million sequences (reads)

A “Needle-in-a-Haystack” Problem Sequencing Instruments

Ion Torrent

Pacific Biosciences

Generation of 100k – 100 million reads in <24 hours

Illumina MiSeq

GS 454 Jr

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Source:  Wikipedia Source:  Nature 458, 719‐724 (2009)

Rate of DNA SequencingGenBank Size

N is growing at an exponential rate!

Bioinformatics Challenges

Filter

GenBank

Raw sequencing results file

“Preprocessing” (cleaning up reads)

Identifying “human background” reads

Computational subtraction of background reads

Identifying “pathogen-specific” reads

Assembling the genome

Detection and diagnosis

Identifying Pathogens by their Specific DNA Sequence

} computationalbottleneck

(days to weeks)

WebServer

Cloud Computing

(Amazon EC2)

Grids (UCSF QB3

Computational Cluster)

WEB

Clinical or Research Laboratory(single machine or small network)

A Scalable Computational Backbone is Required

How Long (and How Expensive) to Analyze 100 Million Sequences?

3 months18 days

24 hours 6 hours

For viral pathogen detection and discovery• 3 months on a single 16-core server• 1 week on our 96-core laboratory network (Chiu laboratory)• 12-24 hours on the UCSF computational cluster (700-1500 cores) • 6-12 hours on the Amazon EC2 cloud computing network (1000-5000 cores)

64 cores

Cloud ComputingCosts: $387.10 USD

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The SURPI Pipeline –Sequence Based

Ultra-Rapid PathogenIdentification

(Naccache, et al., 2013, submitted)

SURPI is fast

SURPI (SNAP) alignment to human nucleotide DB

Filter

GenBank

Raw sequencing results file

“Preprocessing” (cleaning up reads)

Identifying “human background” reads

Computational subtraction of background reads

Identifying “pathogen-specific” reads

Assembling the genome

Detection and diagnosis

Identifying Pathogens by their Specific DNA Sequence

} SURPI pipeline(10 min – 15 hours)

% of Sequencing Reads is Proportional to the Virus Concentration

Sensitivity down to 10 copies of virus per milliliter of clinical sample (e.g. blood)

(Samayoa, et al., 2012, Abstract #255048, AMP)

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315 μlsample input

Qiagen EZ1TM

RobotExtraction

<1 hour 1 hour

6-40 hours1-2 hours

2-4 hours

Serum, WB, Respiratory, CSFStool, Tissue, Bone Marrow

Analysis Pipeline and

Report Generation

10 min-6 hours

Pre-Treatment

Steps

NexteraXTTM or ThruPLEXTM

Library Prep and QC

RandonHexamer cDNA

SynthesisIlluminaMiSeqTM

TOTAL TURNAROUND TIME: 12 hours – 2 days

Samayoa, et al., manuscript in preparation

NGS Clinical Workflow for Pathogen IdentificationNGS-Based Identification and Genome

Assembly of Hantavirus

• NGS of a serum sample from a patient from California with hantavirus pulmonary syndrome

• 100% coverage of the genome

• Viral load in patient’s serum was 1x104

copies/mL

Naccache, et al. (2013) manuscript in preparation

Pathogen Discovery Flow Chart

Clinical Samples

Culture and Animal Modelof Infection

Characterize Epidemiology with PCR and Serology

Microarrays

NGS

Identification and Genome Sequencing

• Outbreak of fulminant pneumonia and hepatitis in an indoor pen of 68 titi monkeys (Callicebus cupreus)

• New World monkeys from South America, commonly used in social behavior studies

• High case fatality rate (83%)

• Conventional diagnostic testing for pathogens negative

Investigation of an Outbreak in a New World Monkey

Colony

Chen, et al. (2011) Plos Pathogens

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ViroChip Discovery of TitiMonkey Adenovirus

(TMAdV)

Transmission Electron Microscopy of Affected Lung

N. Lerche (California National Primate Research Center)

Revealing Adenoviral Particles…

N. Lerche (California National Primate Research Center)

Whole Genome Recovery of TMADV from Lung Tissue (~40 million

reads)

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TMAdV is a New Adenovirus

Species

– The scientist in closest contact with these animals was “sick” just prior or during the monkey outbreak – serum sample obtained for this individual

– Clinical signs and symptoms from scientist: fever / chills, headache, sore throat. Dry cough and chest pain when coughing or taking a deep breath. Symptoms lasted about 4 weeks.

– Family member also sick

Cross-Species Transmission of TMAdV

Scientist and family member were positive for exposure to TMAdV by antibody testing, suggesting cross-species

transmission of this virus

Unknown Hemorrhagic Fever in Central Africa

• An acute hemorrhagic fever outbreak in the heart of the African Congo

• Acute hemorrhagic fever1. Usually caused by viruses2. Occurs in tropical climates3. Commonly transmitted to humans by arthropods or

rodents4. Characterized by high fever, petechiae (red spots from

bleeding into the skin), internal bleeding, low blood pressure, and shock

• Village nearly inaccessible

Grard, et al. (2012), PloS Pathogens

Classification of the Four Viral Families Known to Cause Acute Hemorrhagic Fever

Arenaviridae Bunyaviridae Filoviridae Flaviviridae

Junin Crimean- Congo H.F.

Ebola Kyasanur Forest Disease

Machupo Hantavirus Marburg Omsk H.F.

Sabia Rift Valley fever Yellow Fever

Guanarito Dengue

Lassa

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Viral Hemorrhagic Fever Viruses in Africa

Grard, et al. (2012), PloS Pathogens

Outbreak PatientsOutbreakPatients

Grard, et al. (2012), PloS Pathogens

De Novo Genome Assembly of a Novel Rhabdovirus. Bas-Congo virus (BASV)

Grard, et al. (2012), PloS Pathogens

Rhabdoviruses

1. bullet-shaped” RNA viruses rabies is the most well-known

example

2. Infect more than 175 viruses of vertebrates, insects, and plants

3. Have not been previously linked to hemorrhagic fever in

humans

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Phylogeny ofthe BASV

Rhabdovirus

Grard, et al. (2012), PloS Pathogens

Viral Hemorrhagic Septicemia (VHS) Virusis a Rhabdovirus of the Genus Novirhabdovirus

BASV is Structurally Similar to Rhabdoviruses in the Ephemerovirus and Tibrogargan Groups

Neutralizing Antibody Titers in BASV Infection(Index Patient and Close Contacts)

Patient #3

Nurse ofPatient #3

Grard, et al. (2012), PloSPathogens

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Model of BASV Outbreak Transmission

Grard, et al. (2012), PloS Pathogens

14 year‐old boy with a critical illness  clinical laboratory workflow

Back to the Case…

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VDDC 183, Leptospira borgpetersenii Chromosome 1, 1e-10

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VDDC 183, Leptospira borgpetersenii Chromosome 2, 1e-10

NGS (48 hr turnaround time) of CSF detected 1,438 reads from the Leptospira genus – diagnosis of leptospirosis infection

Results Leptospirosis – Overview

• Most widespread zoonosis throughout the world; re-emerging in the US

• Bacterial spirochete

• Transmitted in the urine of chronically infected carrier animals

• Rats are universal reservoirs, although farm animals and livestock (cattle) can also harbor the infection

Levitt, et al, 2001, Clin Microbiol Rev

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Leptospirosis – Transmission• Infection occurs when spirochetes in contaminated water or

soil enter microabrasions on the skin or intact mucous membranes

• Outbreaks have occurred among white-water rafters (MMWR, 1997,46(25):577-579; Agampodi, et al., 2013 Epidemiol Infect); water sports and recreation (74/639 triathletes in 1998 races in Wisconsin and Illinois, large outbreak in US; Morgan, 2002, CID 2002;34:1593-9).

• Incubation period ~10 days (range 4-19 days); peak incidence in during the summer

• The particular strain infecting this patient was negative by conventional antibody and PCR testing

• Steroids discontinue and IV penicillin initiated

• Dramatic response improvement in symptoms (seizures), CSF profile, brain scanning

• Discharged to home 2 weeks later

• Leptospira exposure is believed to have occurred during a missionary trip to Puerto Rico in 2012 or Florida in 2013

Back to the CaseSummary

• Microarrays and next-generation sequencing (NGS) are promising

strategy for pathogen detection and discovery in clinical and public

health settings

• The power of the technology lies in the ability to test for and

characterize up all potential pathogens simultaneously

• These approaches are critical because of the need for highly sensitive,

broad-spectrum diagnostics in the clinical laboratory and the high

sequence diversity of viruses in particular

• New pipelines in development can greatly improve computational

turnaround time and make these technologies accessible for hospital /

clinical laboratories without bioinformatics expertise

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Acknowledgements

UCSF Chiu Lab and VDDCErik Samayoa, BSEunice Chen, BSSamia Naccache, PhDJerome Bouquet, PhDDeanna Lee, PhDGuixia Yu, BSScot Federman, BSDaniel Wilkerson, BSSneha Somasekar, BSSteve Miller, MD/PhD

FundingNational Institutes of Health R01Abbott Viral Discovery AwardAmazon.Com EC2 GrantUC Discovery Grant

Abbott DiagnosticsJohn Hackett, PhDGerald Schochetman, PhD

Blood Systems Research InstituteEric Delwart, PhDGraham Simmons, PhD

Metabiota/PREDICTJoseph Fair, PhDBrad Schneider,PhDJonna Mazet, DVM, PhD

UCSF DeRisi LaboratoryMichael Wilson, MDJoseph DeRisi, PhD

University of WisconsinJames Gern, MDSheryl Henderson, MD/PhDChristine Seroogy, MD

California Department of Public HealthShigeo Yagi, PhDSharon Messenger, PhD