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Culture-Independent Identification

& Characterization of Infectious

Agents

Distribution Statement A: Approved for Public Release; Distribution is Unlimited

Jonathan Jacobs, PhD

Senior Advisor

Global Health Surveillance & Diagnostics

MRIGlobal

@bioinformer

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PanGIA Program – General Requirements and Approach

• Goals: Develop and Deploy a Sample to Sequence (S2S)

System for infectious disease:

– Provide unbiased detection of all pathogens

– Accept both clinical and environmental samples

– Modular system to allow incorporation of new emerging technologies

– Remote analysis and data compression

• Approach: Best-of-Breed evaluation of solutions and integration into workflow

– Forty-three (43) manual / automated components were evaluated to establish baseline workflow

– Custom bioinformatics analysis pipeline benchmarked against sixteen (16) analysis algorithm

– Integrated, hand-in-hand development of both wet-lab and bioinformatics methods

• Challenges

• Whole blood. High level of background host genetic material

• Environmental samples. Highly inhibited samples with complex

genetic material (swabs, soils, mosquitoes)

• Balancing analysis speed and hardware requirements with

information content and accuracy

Sample Prep

Bioinformatics

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PanGIA – Overview

• PanGIA (Pan-Genomics for Infectious Agents) is a

sample to sequence system capable of detecting

pathogens from clinical and environmental samples.

• Fully integrated End-to-End System:o Sample preparation

o Next-generation sequencing

o Bioinformatics analysis for unbiased pathogen detection (metagenomics)

• All COTS sample processing components

• Unbiased detection with streamlined workflow

• Platform agnostic modular system developed for sustainability

• “Push-button” bioinformatics analytical workflow using commodity hardwareo No Internet Connection Required

o Actionable results

o Built-in quality metrics

o High-confidence BSAT characterization

PanGIA is an end-to-end solution for unbiased detection of pathogens

o Gram ± bacteria o Fungal pathogens

o DNA / RNA viruses o Extracellular / Intracellular pathogens

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An Integrated Biosurveillance Pipeline

Sample Collection

Sample Prep

Next Generation Sequencing

Bioinformatics

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Actionable Reports

• Each process in the pipeline is developed independently (typically by vendors) ... but is dependent on each preceding process – Integration is not trivial, requires experience

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PanGIA Sample Prep Overview

• Workflow Components:

• Clinical and Environmental Workflows developed

– Whole blood

– Serum

– Plasma

– Forensic swabs.

Sample Pre-processing

Pre-lysis Host Depletion

Nucleic Acid Purification

Nucleic Acid Concentration

Whole Transcriptome Amplification

Library preparation

Sequencing

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Technologies for System Integration

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CITRATE EDTA mix

- Cynase NorgenPlasma /

Serum Prep

- RepliGSingle

Cell WTA

NexteraXT

Illumina MiSeq(2x75,2x150)

PanGIA

Example of workflow

for whole blood• Similar workflows have been established

for serum, plasma, forensic swabs and soil.

• Additional workflows will be developed in

FY18.

Sample Preprocessing

Pathogen Concentration

Pre-lysis Host Depletion

Nucleic Acid Purification

Post-purification

Host Depletion

Whole Transcriptome Amplification

Library Prep SequencingBioinformatics

AnalysisSummary Reporting

BD iMag Bead / BD FACSFocus

Sage Science Modified SageELF

BD CLiC

Sage Science Bump Array

SRI Sentinel System

Illumina MiSeq PanGIA*

GOTTCHA

KRAKEN

MetaPhlan2

PathoScope2

RealTime Genomics

CosmosID

OneCodex

SURPI

CLARK

Illumina NeoPrep

BD PPT

PAX Gene Blood RNA

TEMPUS Blood RNA

RNAGard Blood RNA

Citrate / K2 EDTA

InnovaPrepConcentrating Pipette

Acrodisk WBC Filter

Simple 5µm Filter Disk

MicroCon DNA Fast Flow column

PEPS6 Beads

BD Imag Beads

Cyanase

EL Buffer

Saponin

Simple Freeze/Thaw

OmniCleave

QiaAmp Circulating Nucleic Acid Kit

ViraPrep Mammal Kit

Norgen Circulating Nucleic Acid Kit

Norgen Preserved Blood RNA Kit

RNAGard Blood RNA

PAX Gene Blood RNA

E.Z.N.A. Blood RNA Midi Kit

Norgen Plasma/Serum Kit

QiaAmp DNA Blood Midi Kit

NEB Next MicrobiomeDNA Enrichment Kit

NEB Next rRNADepletion Kit

Illumina Ribo-Zero

Illumina Globin-Zero

Qiagen GeneReadsrRNA Depletion

Qiagen GeneReadsGlobin mRNA Removal

RepliG Single Cell WTA

Sigma Complete WTA

Illumina Nextera XT

Kapa HyperPlus

Rubicon PicoPlex

Technologies are compatible with the desired workflow and requirements.Evaluated technologies not optimal with sample workflow.

Technology not tested due to logistic incompatibilities or not yet available.Technology to be evaluated for this project.

kalisto

ConStrains

ReadScan

Sequedex

LMAT

PathoSphere

BioVelocityOxford Nanopore MinION

10 m 3 h2 h 6 h 10 h 22 h 24 h

Elapsed Time

PAN-0125

Illumina NextSeq

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PanGIA Implementation

• Minimal lab footprint

• No internet required.

• Suitable for small clinical lab, portable

container lab, or remote field station

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Extraction WTA and Library Prep

Quantitation

SequencingBioinformatics

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Sample Prep Key Findings

With clinical samples, host

depletion is key to improved

detection

• Pre-lysis host depletion was

more effective than post-

purification host depletion (i.e.

rRNA depletion)

• Cyanase endonuclease was

optimal for digestion of free-

circulating nucleic acids

Sequencing library prep input is

1:1 ratio of sample WTA and

TNA

• TNA sample is concentrated,

half subjected to WTA, half

reserved for library prep

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PAN-0107

PAN-0128 + 129

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Sample Prep Key Findings

• Norgen Plasma/Serum RNA

Purification Midi Kit and Qiagen

QIAamp DNA Blood Midi Kit

performed similarly.

• MO BIO PowerMicrobiome RNA

Isolation outperformed all the

other kits for detection sensitivity

with environmental samples.

PAN-0059-60

PAN-0058/-0061/-0062/-0066

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Key Improvements

• Improved detection of DNA viruses

– Confirmed 1E2 pfu/ml Vaccinia from infected HeLa cells spiked into blood

• Optimization of pre-lysis host depletion method

– Incubation with Cyanase at room temperature, followed by Resin Inactivation

• Reduced sequencing time with 2 x 75 PE protocol vs. 2 x 150 PE

– No significant loss of detection sensitivity

PAN-0111

PAN-0154

PAN-0125

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LOD in Whole Blood

- S. aureus 1E3 cfu/ml

- V. cholera 1E2 cfu/ml

- Vaccinia MVA (pox virus) 1E2 pfu/ml

- VEEV (arbovirus) 1E2 pfu/ml

LOD in Forensic Swab

- B. anthracis (veg.) 1E3 cfu/ml

- V. cholera 1E3 cfu/ml

- Vaccinia MVA (pox virus) 1E2 pfu/ml

- VEEV (arbovirus) 1E3 pfu/ml

LODs are generally

between 1E2 – 1E3

cfu/pfu per ml

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Addition of BSAT Pipeline Eliminates False-Positives

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1

10

100

1000

10000

100000

1000000

Log#m

appe

dread

s

Spikelevels(cfu/ml)forB.anthracisinforensicswabs

w/o BSAT

with BSAT

• BSAT pipeline is currently being validated on multiple Tier 1 Select Agents;

• Fully integrated and validated into PanGIA by August, 2018.

• Readily adaptable to any pathogen of interest and/or for rapid AMR detection

B. anthracis in forensic swabs

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Sample Preparation Workflow and Optimization

• Baseline workflow

established during the

Base Year based on

literature review.

• Option Year 1 focused on

improvements &

optimization

• Modifications to the

workflow resulted in

– Improved senstitivity

– Reduction turnaround

time to <24 hours

– Reduction in cost per

sample to

~$240/sample

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PanGIA: Pan-Genomics for Infectious Agents

KEY Advantages/Differentiators

• Uses read-mapping approach to a custom database: (RefSeq + IMG + your favorite strains)

• All the advantages of read-mapping, while still fast and tuned to overcome multi-mapped

reads

• Confidence scores

• Comparative analysis to control samples

• Developed hand-in-hand with laboratory methods

• Easy, intuitive graphical user interface

• No Internet Required

• Runs on commodity hardware

• Open-Source, dockerized, and easy to implement

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Performance vs. best in class tools: In silico data

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Performance vs. best in class tools: In silico data

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Performance on commodity hardware (8 cores)

0

0.2

0.4

0.6

0.8

1

1.2

1 2 3 4 5

Ho

urs

Walltime (Hours)

Series1 Series2

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PanGIA GOTTCHA Kraken Kaiju Metaphlan2

CLINICAL

ENVIRONMENTAL

WALLTIME (h)

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CLINICAL

ENVIRONMENTAL

PanGIA GOTTCHA Kraken Kaiju Metaphlan2

MEMORY USAGE (GB)

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PanGIA Hardware

• No Internet Required (but cloud version available)

• Very small hardware footprint and requirement

• A “BackPacker’s Bioinformatics Brick”

• Intel NUC ‘Skull Canyon’ SBC

– 32 GB of RAM

– 2TB Solid State Drive

– Quadcore i7 CPU

– Wifi / 4G / LTE Connectivity

– No moving parts

• Analysis is typically under 15m per sample on this system

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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PanGIA User Interface

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FY18 Development Efforts

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• Development of optimized methods for additional matrices for both clinical and environmental workflows

• Further optimization of existing workflow

– Evaluate post-purification host depletion technologies, potential for automation, investigation of new sample prep technologies

• Implementation of end to end Quality Control guidelines

– Process controls spiked with PhiX, MS2, and synthetic xenoDNA/RNA

– Lot# control, metadata tracking

• Optimization and integration of BSAT characterization pipeline

• User-defined / custom databases

Additional matrices

include nasopharyngeal

swabs, serum, soil and

surface water

2017 – 2018 OCONUS Deployment

• Update system based on

OCONUS feedback

• Integrate automated

technologies

• Integration with other

sequencing devices

Clinical, BSV, Food Safety

Partner Labs Wanted

jjacobs@mriglobal.org

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Patrick Chain, PhD

Karen Davenport, PhD

Paul Li, PhD

Chenchui Gao, PhD

Tom Slezak

Marissa Torres

Cleveland Clinic

Gary Procop, MD

Laura Strawn, PhD

Steve Rideout, PhD

Thank you!

Jonathan Jacobs, PhD

Richard Winegar, PhD

JR Aspinwall

Joseph Russell, PhD

Kyle Parker

Jennifer Stone

John Bagnoli

Dave Yarmosh

Brittney Campos

Benjamin Pinsky, MD PhD

Trish Simner, PhD

Matthew Robinson, MD

DOD SPONSORS

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Defense Threat Reduction

Agency (DTRA)

Joint Science &

Technology Office

(JSTO J9)