•What do we need?

•Where do we stand currently?

•What are the stumbling blocks?

•Where can/should/will we be in 5 years?

New Technological Developments in Diagnostic

TestingCovering Infectious Diseases, UC Berkeley / October 2,

2003

•What do we need?

•Where do we stand currently?

•What are the stumbling blocks?

•Where can/should/will we be in 5 years?

New Technological Developments in Diagnostic

TestingCovering Infectious Diseases, UC Berkeley / October 2,

2003

The New Yorker, January 29, 2001

•What do we need? Environmental & Clinical:

Broad spectrum detection/dx tools Rapid, real-time (quantitative),

automated, (pt-of-care) monitoring

Standardized sampling methods Understanding of natural background

•Agent (variation: genetic, antigenic, geo, temp)

•Setting (related agents, non-biological issues)

current Dxapproaches

system indicators

difficulty in detection

opportunity for benefit

•What do we need?

•Where do we stand currently?

•What are the stumbling blocks?

•Where can/should/will we be in 5 years?

New Technological Developments in Diagnostic

TestingCovering Infectious Diseases, UC Berkeley / October 2,

2003

Current procedures and technologies

Detection Culture (reference, complete analysis) Immunoassays

Solid-phase, hand-held (“SMART”), FACS, ELISA Nucleic acids

Amplification: PCR, SDA…Capture: magnetic, Ab, electricalDetection: fluor, ECL, chromo, bDNA;

microarray, mass spectroscopy

(reliance on few antibodies!)

(reliance on type strains!)

Syndromes of suspected* microbial origin: success in achieving microbiological

diagnosis • pneumonia: ~50-70%• encephalitis: ~30%• sepsis: ~10%• acute diarrhea: ~20-50%

*suspected on basis of response to antibiotics, among other observations

Why might traditional approaches for pathogen identification have failed?

• Reliance on cultivation--insensitivity• Microbial phenotypic markers unreliable:

one can be mislead when one asks a microbe to perform in the laboratory!

• Serology delayed, or impossible• PCR not well deployed, problems with low

clinical sensitivity

•What do we need?

•Where do we stand currently?

•What are the stumbling blocks?

•Where can/should/will we be in 5 years?

New Technological Developments in Diagnostic

TestingCovering Infectious Diseases, UC Berkeley / October 2,

2003

Major challenges, obstacles

Diversity of potential agents(including bioengineered, chimeric organisms)

Variability, varying evenness of agents,in nature

Defining relationship between detected agentand disease risk

Complex biological background! Sampling, processing procedures

(standardization, calibration in real world)

The Tree of Life(based on rRNA sequences)

Bacteria

Eukarya

Archaea

Pace NR. A molecular view of microbial diversity and the biosphere. Science 1997; 276:734

The Tree of Life(based on rRNA sequences)

Bacteria

Eukarya

human-associated

Archaea

Pace NR. A molecular view of microbial diversity and the biosphere. Science 1997; 276:734

Bacteria

Emergence of infectious diseases

•Societal events: poverty, crowding, conflict, migration

•Globalization of food supply•Environmental changes•Human behavior: sexual, recreational,

diet, travel•Impaired host defenses, antibiotic use•Public health infrastructure

•Acquisition of toxins,adhesins

•Antigenic variation, e.g. new capsule

•Broadened host range•Improved growth

or transmissibility•Acquisition of drug R

What does it mean for an infectious disease to “emerge”?

• Evolution of new agent to cause disease

(evolution of virulence) • Previously-recognized agent causes disease

with new features (clinical, epidemiological, geographical, histological)

• Pre-existing, but previously-unrecognized

agent makes itself known (± new disease features)

Pathogen discovery: basicsPathogen discovery: basics

pathology

identification / relatedness

causation?

molecular signature

pathology

identification / relatedness

causation?

molecular signature

microbe

host

Pathogen discovery: basicsPathogen discovery: basics

Pathogen discovery: seeking molecular signatures

•broad range PCR•microbial/viral survey “phyloarray”•subtractive/comparative methods

• representational difference analysis• differential display

•expression or phage display library screening

(using host antisera or T-cells)•small molecule or protein detection (MS)

•host genome-wide transcript profiling (microarray, other)•host protein profiling (microarray, MS)

Host as source of signature

Pathogen as source of signature

Pathogen discovery: seeking molecular signatures

•broad range PCR•microbial/viral survey “phyloarray”•subtractive/comparative methods

• representational difference analysis• differential display

•expression or phage display library screening

(using host antisera or T-cells)•small molecule or protein detection (MS)

•host genome-wide transcript profiling (microarray, other)•host protein profiling (microarray, MS)

Host as source of signature

Pathogen as source of signature

digest specimen, purify / concentrate DNA

broad range (bacterial) rDNA PCR

rRNA gene

conserved region

variable region

analyze sequence, infer phylogeny of putative organism(s)

build case for disease causation

Rhinosporidiosis

•slow-growing tumors of nasal mucosa, ocular conj.•southern India, Sri Lanka: prevalence 1-2% children

Rhinosporidium seeberi: a fungus?

sporangium

endospore

stain: PAS reagent

DiplomonadsMicrosporidiaTrichomonadsFlagellatesSlimemoldsAmoebidaCiliatesApicomplexansAlgaePlantsAcanthamoebaFungiAnimals0.10Eukaryaevolutionary distance

Perkinsus (Protozoan Oyster Parasite)

Sarcocystis (Coccidian Protozoan)

Xenopus (Frog)

Mytilus (Blue Mussel)Tripedalia (Jellyfish)

Microciona (Sponge)

Diaphanoeca (Choanoflagellate)

Rosette Agent

Rhinosporidium seeberiDermocystidium sp.

Dermocystidium salmonis

Psorospermium haeckelii

Ichthyophonus hoferi

Aspergillus

Chytridium (Chytrid)

Mucor (Bread Mold)

Acanthamoeba (Amoeba)

Zamia (Plant)

Porphyra (Red Algae)

Lagenidium (Oomycete)

Labyrinthuloides (Slime Net)

.10

Artemia (Brine Shrimp)

Animals

DRIPs

Fungi

ProtistsChlorophytes

Rhodophytes

Heterokonts

Apicomplexa

95

Other Animals

Jellyfish

Sponges

Choanoflagellates

DRIPs

Fungi

Plants Protists

0.1

DRIPs:• deepest branch of animals• aquatic parasites• hosts=fish…&

Rs in humans: water exposure

Bioterrorism: future considerations

• Mining nature (unconventional agents)• Improving upon nature

• Engineered pathogens: cloning ofknown virulence factors/”islands”, deletion of inhibitory factors, host modifying factors (eg, cytokines), shuffled “evolved” vir factors

• Novel agents (pathogenic proteins, bioregulators, chimeric agents)

Major challenges, obstacles

Diversity of potential agents(including bioengineered, chimeric organisms)

Variability, varying evenness of agents,in nature

Defining relationship between detected agentand disease risk

Complex biological background! Sampling, processing procedures

(standardization, calibration in real world)

4.3-6.2% healthy humans positive without history of

anthrax or anthrax exposure

Bacteria

Uncultivated TM7 in the human mouth

We know more about the tropical rain forest than we

do about the human endogenous microbial

flora!

Major challenges, obstacles

Diversity of potential agents(including bioengineered, chimeric organisms)

Variability, varying evenness of agents,in nature

Defining relationship between detected agentand disease risk

Complex biological background! Sampling, processing procedures

(standardization, calibration in real world)

The New Yorker, November 19, 2001

The realities of anthrax detection, 2001...

Lack of standardized collection methods Low specimen analysis through-put Inadequate laboratory surge capacity Slow turn-around, late in disease course Inadequate delivery and implementation of

state-of-the-art technologies in the field Data interpretation: negatives and positives

•What do we need?

•Where do we stand currently?

•What are the stumbling blocks?

•Where can/should/will we be in 5 years?

New Technological Developments in Diagnostic

TestingCovering Infectious Diseases, UC Berkeley / October 2,

2003

Some “near-term” goals

Library of high-affinity binding reagents More sensitive binding detection Extensive database of sequences,

other signatures High-throughput labs, with surge capacity Standardized, automated specimen collection

and processing procedures, technologies

Further development of DNA microarray

approaches

•1600 unique 70-mers•~140 viral genomes•Sensitivity=~100 viral particles

“cold”RV-infected

Phyloarray v2:~10,000 rDNA oligo probes

Agilent: Theo Sana, Paul WolbertMike Eisen (LBL)Pat Brown (Stanford)

Unexplained Deaths Project

(CDC EIP)

Unexplained Deaths Project

(CDC EIP)

•Acute, life-threatening illness in ages 1-49,

previously healthy; all routine diagnostic tests (-); “enhanced passive surveillance”

•Seek patterns, clusters, clues; look forinfectious agents using molecular (research) tools

total pop = 7.78 million

Nikkari et al, Emerg Infect Dis 8:188-194, 2002; Hajjeh et al, Emerg Infect Dis 8:145-153, 2002

Unexplained Deaths Project

(CDC EIP)

Unexplained Deaths Project

(CDC EIP)

• 137 cases fit definition (5/95-12/98); ≥0.5/100,000• syndromes: neuro (29%), respiratory (27%),

cardiac (21%), multisystem (13%)

What are the causes of the unexplained cases?viruses, toxins, non-microbial processes,...specimen limitations

• 28% explained (serology; broad range PCR=8/46 cases)• Putative causative agents are all known agents

-broad range PCR: N. meningitidis, S. pneumoniae

Microbe (as target):• agent specificity (adjustable)• signatures more easily defined

Microbe or host: relative advantages

Host (as target):• agent need not be present• early diagnosis? • outcome predictions

Can one recognize and classify clinical (and pre-clinical) states of infection by examining host

gene response patterns?

Potential advantages: • broad range• early• microbe not required in specimen• prognostic value (& targets)

37,632 spots/elements~32,494 cDNAs~10,250 named genes; ~18,000 unique

genes

Alizadeh A et al., Cold Spring Harb Symp Quant Biol 64:71, 1999; Nature 403:503, 2000

Two-color, comparative hybridization format

Human cDNA microarray

transcriptional control

Comprehensive gene expression profiles integrate host genotype and environmental input

mRNA

gene

cDNA microarray procedures-1

(Relman & Brown)

cDNA microarray procedures-2

200 10000 50.00 5.644800 4800 1.00 0.009000 300 0.03 -4.91

Cy3 Cy5

Image analysisData filteringNormalization

R/G ratio represents relative abundance of transcripts

Cy5Cy3

Cy5Cy3

log2

Pattern recognition:• unsupervised (class discovery)-

clustering, SOM, SVD (PCA), ICA

• supervised (class prediction)-SAM, support vector machines, t/f-test (DLDA, ANOVA), modeling (waveform, periodicity) Experiments

Gen

es

clusterby

genes

clusterby

microbialstimuli

microbial stimuli

genes

2-Way Hierarchical Clustering Methodology

microbial stimuli microbial stimuli

• Variability--How noisy is the background?

Must each individual serve as his or her own control? Do patterns provide insight into physiology and “intrinsic-ness”?

• How well do blood cells “report” on local

processes? Other sources...?

Issues involving a complex background: gene expression

patterns from blood in healthy individuals

femalesmales 48 PBMC samples from 19 individuals

clustered on the basis of genes with intrinsic scores >2 SD from mean (340)(mean square pairwise difference between/ mean square pairwise difference within individuals)

Whitney A et al, PNAS 2003; 100:1896-1901

48 PBMC samples from 19 individuals clustered on the basis of genes with highest intrinsic scores (340)

Donor-intrinsic gene

expression

females

males

Whitney A et al, PNAS 2003; 100:1896-1901

Looking further into the future

Biosensors: remote (e.g. cells), endogenous (e.g. flora)

Hyperspectral imaging, analysis

Conclusions

Challenges associated with detection

and diagnosis are significant, but worthy of major investment

Current status: platforms are quite

promising; real-world issues still need further attention

Major pay-off may be achieved if we

embrace larger aspects of biology and disease, and anticipate future threats

Acknowledgements

StanfordPat BrownTrevor HastieAsh AlizadehJennifer BoldrickMary Brinig

Paul LeppCleber OuverneyStephen PopperKate RubinsAddie Whitney

CDCJim LeDuc Marc FisherPeter Dull

DukeBarth RellerChris WoodsDavid Murdoch