Resequencing Microarray ...

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Resequencing Microarray ...

Rapid Laboratory Identification of Pathogens

by the Use of Resequencing Microarrays

Baochuan Lin

US Naval Research Laboratory

Washington DC.


Resequencing microarrays for broadrange

detection

• A tool that can test for hundreds of agents in parallel by directly

accessing sequence information

Microarray

hybridization

Base calling

algorithm

Search for matching

GenBank sequences

CACGAAGTCAGACCTGTTACAT

CCGGGTGCTTTCCTATAATGCA

Identification. May identify

pathogens present on the

microarray or close

neighbors up to 15%

divergence.

“Knowing what is not the cause is never as good as knowing what is!”


Background: Resequencing Microarray

CCTGGAATTCGCAGTACATGCCCCTACCTTTAGAGA…

Microprobe sets

T

G

T

C

Base 1 Base 2 Base 3 So on…

G

A

T

C

G

A

T

C

G

A

T

C

G

A

C

A


Background: Resequencing Microarray

A

C

G

T

Fluorescence Intensity Image


Respiratory Pathogens

Proof of Concept Microarray

Respiratory Pathogen Microarray v.1

240,000 features 30,000 bases

BioThreat

Pathogens

Target Identification

A/HA1 A/New Caledonia/20/99

A/NA1 A/New Caledonia/20/99

A/HA3 A/Wyoming/3/03

A/NA2 A/Wyoming/3/03

A/M A/Ann Arbor/6/60

B/HA B/Jilin/20/2003

B/NA B/Yamagata/1246/2003

B/M B/Ann Arbor/1/66 (cold-adapted)

B. Lin et al. (2006) Genome Res. 16: 527-

535


Pathogens Identified

Organism Culture (+) Ref © (+) RPM v.1 (+) Ref © (+)

RPM v.1 (-)

Adenovirus 2 8 9 0 1

Coronavirus 28* 29 24 6 2

Influenza A 176 263 269 1 7

Influenza B 28 41 46 1 6

PIV 1 0 0 1 0 1

PIV3 0 0 2 0 2

Rhinovirus 0 1 2 1 1

M. pneumoniae 0 2 3 0 1

S. pneumoniae 8 40 38 3 1

S. pyogenes 9 13 13 0 0

Negative 176 52 59 0 7

Ref © (-)

RPM v.1 (+)

Overall Microarray Result vs. Reference Methods* (Reference = Culture and/or RT/PCR)


(A) RPM v.1

97

68

55

95

51

63

Phylogenetic Analysis

66

74

A_Aichi_133_2005

NRL_AL_10078

NRL_AL_10337

NRL_AL_1123

NRL_KMB_MG08384

NRL_AL_15923

NRL_KMB_16236

NRL_KMB_10580

NRL_KMB_NN02972

NRL_AL_10425

A_Wisconsin_67_2005

A_NewYork_258_2005

NRL_AL_10091

NRL_AL_10026

NRL_KMB_NN08843

NRL_AL_10130

NRL_AL_15676

NRL_KMB_WR02927***

HA3 (A/Fujian/411/02 (H3N2))

A_Panama_2007_99

(B) De novo sequences

97

77

61

99

64

63

64

87

A_Aichi_133_2005

NRL_AL_10078

NRL_AL_10337

NRL_AL_1123

NRL_KMB_MG08384

NRL_AL_10425

NRL_AL_15923

NRL_KMB_10580

NRL_KMB_16236

NRL_KMB_NN02972

A_Wisconsin_67_2005

A_NewYork_258_2005

NRL_AL_10091

NRL_AL_10026

NRL_KMB_NN08843

NRL_AL_10130

NRL_AL_15676

NRL_KMB_WR02927***

HA3 (A/Fujian/411/02 (H3N2))

A_Panama_2007_99

Phylogenetic analysis of the hemagglutinin genes of 15 influenza A/H3N2 isolates in clinical

samples

Blue-highlighted are reference sequences: A/Fujian/411/02

A/New Yark_258_2005 is representative strain of A/California/7/2004: 2005-06 vaccine strain

A/Aichi_133_2005 is representative strain of A/Wellington/1/04

A/Wisconsin/67/2005: 2006-07 vaccine strain


Proof of Concept Microarray-RPM v.1

• RPM v.1, proof-of-concept microarray for the detection of more

than 20 common respiratory pathogens

• Only 1 out of 99 recognized strains of rhinovirus is represented

• Detection limits-10-10 3 genome copies per reaction

• Multiple pathogens could be identified in clinical samples in

approximately 8.5 hours

• Identifications were made at the strain, as well as species level.

- Phylogenetic analysis of the hemagglutinin genes of

influenza A/H3N2 isolates showed similar results as

conventional sequencing

• No avian influenza (H5N1) was detected in clinical samples

• ~ 75% respiratory infections are caused by influenza during the

Flu season

• Picornaviruses, i.e. rhinoviruses, were not well-represented on

RPM v.1


RPM microarrays

RPM-Flu 3.1* RPM-TEI 1.0 #

Influenza A and more than 70 other

human respiratory pathogens

*Lin B. et al. (2009) J Clin Microbiol. 47(4):988-93

# Leski, TA et. al. (2009) PLoS ONE 4(8): e6569

Over 80 biothreat pathogens including

most of the priority A, B and C agents

plus near-neighbors from many

9


Adenovirus

Rhinovirus Commensal Bacteria

*

*

*

*

*

*

*

*

*

FRI

H-incoming

H-6 weeks

Survey of 202 samples from military

training sites

“Healthy” sampled at two time points

Febrile respiratory illness (FRI) for

comparison

---------------------------------------------------

1.“healthy” recruits - 40% rhinovirus

2. FRI causing agents

– site specific strains

– reduce appearance of rhinovirus

3. Commensal organisms - random strain distribution

4. Co-existence of multiple viral and bacterial

pathogens

5. All H. influenzae are nontypable, nonencapuslated

strains

6. S. pneumoniae belong to S. mitis group

7. N. meningitidis – serogroup C

Wang Z. et al. (2010) Microb. Ecol 59(4): 623 - 634


RPM-Flu 3.1

Influenza Viruses

• Surveying 41 avian influenza isolates from

Naval Medical Research Unit-3 (Cario, Egypt)

• 7 negative

• 24 avian H5N1 positive

• 4 H10N7 samples

• 2 H7N7 samples

• 75% of H5N1 is highly pathogenic

• Surveying 298 specimens from basic military

trainees

• Clinical sensitivity 96.8%

• Clinical specificity 100%

Lin B. et al. (2009) J Clin Microbiol. 47(4):988-93

Leski, TA et. al. (2009) PLoS ONE 4(8): e6569

Metzgar et al. (2010) PLoS ONE 5(2): e8995


Blinded

sample ID

RPM-Flu Assay

Identification

SEPRL reference strain

Unblinded Identification

USDA_1 A/H1N1 A/Turkey/Kansas/4880/80 (H1N1)

USDA_2 A/H2N8 A/Herring Gull/DE/677/88 (H2N8)

USDA_3 A/H3N2 A/turkey/MN/366767/2005 (H3N2) *

USDA_4 A/H4N6 A/Blue Winged Teal/OH/240B/88 (H4N6)

USDA_5 No detection of avian

influenza virus

No avianinfluenza virus,

inoculum failure

USDA_6 A/H7N2 A/quail/PA/20304/98 (H7N2)

USDA_7 A/H8N4 A/turkey/CO/169118-13/02 (H8N4) *

USDA_8 A/H11N9 Original inoculum as A/Chicken/NJ/12220/92 (H9N2) was found to be

coinfected with A/H11N9 strains

USDA_9 A/H10N7 A/quail/NJ/25254-22/95 (H10N7) *

USDA_10 A/H11N3 A/chicken/NJ/4645/96(H11N3) *

USDA_11 A/H12N5 A/duck/LA/188D/87 (H12N5)

USDA_12 A/H13N6 A/Gull/Maryland/1824/1978(H13N6)

USDA_13

No detection of avian

influenza virus

Detection of avian

metapneumovirus

No avian influenza virus

Avian metapneumovirus (Colorado strain)

USDA_14 A/H5N3 A/duck/Singapore/F119/97 (H5N3)

USDA_15 A/H7N3 A/chicken/Chile(F0)/176822/02 (H7N3)

USDA_16

No detection of avian

influenza virus

No avian influenza virus

Avian paramyxovirus type 1 (NDV)

USDA_17 A/H5N2 A/chicken/Mex/26654-1374/94 (H5N2)

USDA_18 A/H7N1 A/turkey/Italy/4580/99 (H7N1)

USDA_19 A/H7N3 A/chicken/Pakistan/1369-CR2/95 (H7N3)

USDA_20 A/H7N7 A/chicken/Victoria/85 (H7N7)

USDA_21 A/H14N5 A/mallard/Gurjev/263/82 (H14N5)

USDA_22 A/H15N9 A/Shearwater/W. Australia/2576/79 (H15N9)

USDA_23 A/H?/N4

No detection of HA sequence.

Best matching record for

NA4 sequence is A/H8N4.

Surveying avian influenza

reference strains from USDA

(Athens, GA)

• The blue highlighted box

indicated that RPM

sequences match GenBank

sequences

• * Indicate that either HA or NA

or both sequences has not

been deposited in GenBank.


Zoonotic outbreak monitoring

• Monitoring outbreaks of infectious diseases among animals is

an important task in protecting of public health

– Zoonotic outbreaks frequently precede transmission to, and

outbreaks among humans

– Examples: influenza A (birds) 1 , Nipah virus (bats, pigs) 2 , Ebola

(non-human primates) 3

• Potential threat of avian influenza A*

– H5N1 influenza is still around (538 confirmed cases as of 3/2011)

– Case mortality rate – 58.9%

– Close contact with poultry is one of the risk factors

1Zimmer, S. M. et al. (2009) Historical perspective--Emergence of influenza A (H1N1) viruses. N Engl J Med, 361(3), 279-85

2Chua, K. B. et al. (2003) Nipah virus outbreak in Malaysia. J Clin Virol, 26(3), 265-75

3Gonzalez, J. P., et al. (2005) Ebola virus circulation in Africa( …). 13 Bull Soc Pathol Exot, 98(3), 210-7

*Van Kerkhove M.D. et al. (2011) Highly pathogenic avian influenza (H5N1) (…). PLoS One 6(1): e14582


Mercy Hospital Research Laboratory

• Challenges

– Unreliable power supply

• A hybrid system using solar

power, diesel generators and

municipal power was set up*

– Lack of expertise

• A team of highly motivated local

personnel was trained

– Communication systems

• Computer network linked to

Internet via satellite

– Climate

• Modified protocols and

equipment needed due to high

ambient temperatures

1Jacobus, H., et al., "Evaluating the impact of adding energy storage on the performance of a hybrid

power system", Energy Conversion and Management, 52(7), 2604-2610 (2011)

14


Collection of chicken samples

• Sample collection

– Samples from Bo farm experiencing an outbreak (34)

– Reference farms (68)

No. Farm location

Number of

samples

Sample

designations

1 Bo 34 B1-34 Sick

2 Hamilton 20 H1-20 All healthy

3 Hastings 8 HJ1-8 All healthy

4 Allen Town 16 A1-16 All healthy

Condition of chickens

5 Joe Town 12 J1-12 Some chickens sick

6 Wellington 12 W1-12 Some chickens sick


• Summary

– No influenza viruses

Microarray identification

– Most samples from Bo (outbreak location)

contained Klebsiella pneumoniae and

only one sample form all reference farms

contained this pathogen

– Staphylococcus methicillin resistance

genes (mecA) detected in Bo farm

samples

– Various Pseudomonas species present

throughout analyzed collection

– In half of the samples collected from

reference farms no pathogens were

detected

16

Farm Sample Most likely ID*

1

2

3

4

5

6

G1 K. pneumoniae, P. stutzeri

G2 K. pneumoniae, P. stutzeri

G11 no detection

G12 K. pneumoniae, P. aeruginosa, Staph. (mecA gene)

G13 K. pneumoniae, Pseudomonas

G14 K. pneumoniae, P. aeruginosa, Staph. (mecA gene)

G25 K. pneumoniae, Pseudomonas

G26 K. pneumoniae

G27 K. pneumoniae, P. putida

G28 K. pneumoniae, P. aeruginosa, Staph. (mecA gene)

H2 no detection

H3 no detection

H4 (P. aeruginosa or M. catarrhalis)

HJ5 (P. aeruginosa or M. catarrhalis)

HJ6 no detection

HJ7 Pseudomonas

A1 no detection

A2 P. putida

A16 no detection

J2 P. aeruginosa, E. sakazakii

J7 no detection

J10 no detection

W3 K. pneumoniae

W4 P. aeruginosa

W6 (Pseudomonas or Moraxella or Methylobacillus)


1. Bacillus cereus

2. Brucella melitensis (F6145)

3. Brucella abortus (RB51)

4. Burkholderia mallei (Glanders)

5. Burkholderia pseudomallei (Meliodosis)

6. Clostridium perfringens

7. Chlamydia psittaci

8. Coxiella burnetii

9. Cryptosporidium parvum

10. Rickettsia prowazekii

11. Rickettsia typhi

12. Rickettsia tsutsugamushi

13. Bartonella quintana

14. Campylobacter jejuni

15. Salmonella typhi

16. Salmonella enterica

17. Leptospira interrogans

18. Mycobacterium tuberculosis

19. Seoul virus

20. Toscana virus

21. Punta Roro virus

22. Sin Nombre virus

23. O'nyong-nyong virus

24. Variola major virus

25. Human herpesvirus

26. Foot and mouth disease virus

27. Morbillivirus (Rinderpest)

28. Clostridium perfringens

29. Ricinus communis

30. Staphylococcus aureus

31. Clostridium tetani

32. E. coli 0157:H7

33. Vibrio cholerae

34. Arabidopsis thaliana TIM

35. Arabidopsis thaliana NAC1

36. Control

“RPM-TEI” Chip

Development and validation funded by Office of Naval

Research

• Design to address the need for

pathogen surveillance for US naval

operation

• Provide solution for “…rapid

detection of possible bioweapons.

… immediate identification of

epidemiological pathogens (viruses

or bacteria) that could adversely

affect the health of the entire MEF.

…provide an untapped source of

intelligence and forensics that is

not readily available.”

• Organisms lists includes pathogens

endemic to the Africa (i.e. Lassa

viruses, Ebola viruses), South

America (hemorrhagic fever

viruses)


Organism Taxon Concentration ID Result

Ebola Zaire

0.0001 – 1 ng Zaire Ebola virus strain Zaire 1995

0.00001 ng No detection

Ebola Reston 0.001 – 1 ng Reston Ebola virus strain Pennsylvania

Ebola Ivory Coast 0.1 ng Cotê d'Ivoire Ebola virus

Ebola Zaire strain

Mayinga

Filoviridae

0.1 ng Zaire Ebola virus strain Mayinga

Marburg Ravn 0.1 ng Lake Victoria Marburg virus - Ravn

Marburg Musoke 0.1 ng No detection

Marburg Ci67 0.1 ng Marburg virus strain

M/Germany/Marburg/1967/Ratayczak

Lassa Josiah

0.01 – 1 ng Lassa virus strain Josiah

Lassa Z148 0.001 – 1 ng Lassa virus strain Z148

Lassa Acar 0.1 ng Lassa virus

Lassa Weller 0.1 ng Lassa virus strain Weller

Lassa Pinneo 0.1 ng

0.1 ng

Lassa virus

Machupo Carvallo

Machupo Chicava

Guanarito

INH95551

Arenaviridae

0.1 ng

0.1 ng

Machupo virus strain Carvallo

Machupo virus strain Chicava

Guanarito virus strain INH-95551

Junin Rumero 0.1 ng Junin virus strain Rumero

CCHFV 10200

Buniaviridae

(Nairovirus)

0.1 ng Crimean-Congo hemorrhagic fever virus

strain IbAr10200

Rift Valley Fever Buniaviridae 0.1 ng Rift Valley fever virus

Sandfly Sicilian (Phlebovirus) 0.1 ng Sicilian sandfly fever virus

Sandfly Naples

0.1 ng Sandfly fever Naples virus strain NAMRU

840055

Toscana 0.1 ng Toscana virus

Punta Toro 0.1 ng No detection

Seoul Buniaviridae 0.1 ng Seoul virus strain 80-39

Hantaan (Hantavirus) 0.1 ng No detection

Puumala 0.1 ng No detection

Sin Nombre

0.1 ng Pulmonary syndrome hantavirus (Convict

Creek 107)

• Detection limits for most

pathogen at 1x10 4 genome

copies with a few exception, i.e.

nipah virus.

• Testing clinical isolates of Lassa

viruses and Ebola viruses at

USAMRIID – excellent sensitivity

and specificity.

• No detection of Puumala virus is

expected

• No detection of Marburg Musoke,

Hantaan viruses, and Punta Roro

– template issue


Environmental Samples

• Soil samples: Surface soil, maximum depth of 2

centimeters, were collected from 5 points at each

location

• 1 center point and four ordinal positions (north,

south, east and west compass point) 50 meters

from the center.

• Mixed and multistage sieving process using

standard sized sieves

• 500 mg of particles smaller than 25 mm was

used for nucleic acid extraction

• Airborne particulate samples: 24 hours with

Deployable Particulate Sampler System

• Flow rate of 10 liter per minute

• 2.0 mm pore size PTFE filters

• 2.5 by 2.5 centimeter squares were used for

nucleic acid extraction.


Collection Sites

Kuwait

Iraq


Sample Location Organisms

Identified

Iraq Mycobacterium

Bacillus*

Brucella*

Kuwait Mycobacterium

Coxiella burnetii #

Brucella

Clostridium

perfringens @

* These microbes were only detected in 1 location, @

Clostridium perfringens was detected in 2 locations,

# Coxiella burnetii was detected in 3 locations.

RPM Results

• These samples were also tested with

RPM-Flu – no positive identification

• Soil and air filter samples showed

consistent results.

• Omnipresence of Mycobacterium spp.

• Brucella spp., C. burnetii, and C.

perfringens, were also detected -

infections or respiratory illness, known

for their resistance to drying and ability

to be spread over long distances.


Conclusions

• Provide sequence information which allows

– phylogenetic classification of target pathogens

– tracking genetic variation of the organisms

– “Near-Neighbor discrimination”

• A modern, broad-spectrum infectious disease surveillance

solution

– RPM not only rapidly confirm the presence and absence of suspected

pathogen, but enables simultaneous detection of pathogens that were not

expected

• Excellent candidate for the next generation of pathogen

detection tools

– In some situations use of more complex and expensive broad-range

detection methods is more cost-effective and less logistically

challenging than using a large number of simple assays


Infectious Disease/Pathogen Detection

and Identification Assays in Development

◆ In collaboration with the Institute for Viral Disease Control and Prevention (Chinese

National CDC)

◆ Four individual assays for the detection and identification of:

◆ Respiratory pathogens

◆ Gastrointestinal pathogens

◆ Hemorrhagic Fever pathogens

◆ Encephalitis and Meningitis pathogens

◆ In collaboration with UC San Francisco and Lawrence Berkeley National Lab

◆ Sepsis bacterial pathogens with associated antibiotic resistance

◆ In collaboration with FDA/CBER

◆ Two individual assays for the detection and identification of:

◆ Blood-borne pathogens, viral, bacteria, and eukaryotic

◆ Human retroviral genomics for detection and tracking of emergent variants

◆ In collaboration with the NIH Clinical Center and NCI

◆ Pathogens associated with respiratory infections in immunocompromised patients

◆ Funded by USDA/CREES under a Phase I SBIR

◆ Detection and identification of swine infectious disease pathogens


Acknowledgements

NRL

• Anthony Malanoski

• Tomasz Leski

• Joseph Smith

• Zheng Wang

• Kate Blaney*

• Adam Ligler*

• Carolyn Meador*

• Nina Long

• Joel Schnur

• Gary Vora

• David Stenger

Field Deployable Preventive

Medicine Units

• Lt Amy Mocatelli

• HM2 Carl Druhl

• Richard Ankney

• LT Edward Benchoff

• LT Steward Bullock

• HM2 Reatha Candler

• HM2 Robin Lenon

• Mercy Hospital

– Rashid Ansumana

– David Jimmy

– Umaru Bangura

• NAMRU#2

– Michael Gregory

• NAMRU#3

– Samuel Yingst

– Marshall Monteville

– Magdi Saad

• USAMRIID

– Sofi Ibrahim

• USDA

– David Swayne

– Colleen Thomas

• Tessarae

– Clark Tibbetts

– Klaus Schafer

– Matt Lorrence

– Brian Weslowski

– Lisa Borsuk

– Agnieszka Lichanska

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