WHEN a sudden outbreak of a strange
virus called Severe Acute Respiratory Syndrome (SARS) occurred
last year, the Centers for Disease Control and Prevention (CDC)
sought help from a team of Lawrence Livermore biologists, mathematicians,
and computer scientists. Within three hours of receiving the first
sequenced genome (genetic blueprint) of the virus from the CDC,
the Livermore team produced several candidate signatures of the
pathogen (disease-causing microbe). Signatures are specific regions
of DNA or RNA that uniquely identify a pathogen. The SARS case
was one of many in which the group has developed signatures using
a novel whole-genome analysis approach that is changing pathogen
team, part of the Laboratory’s Biology and Biotechnology
Research Program (BBRP), has been on the front lines of the nation’s
biodefense effort since 2001. Eleven computer scientists, biologists,
and mathematicians led by computer scientist Tom Slezak comprise
one of the largest pathogen bioinformatics groups. Their work spans
the full spectrum of effort, from identifying signature candidates
to developing DNA-based signatures and deploying validated assays
in the field. Team members have traveled throughout the nation,
often with only a few hours’ notice, to support the national
effort to defend against bioterrorism.
Biological weapons could include bacteria (anthrax, plague), DNA
viruses (smallpox), RNA viruses (ebola, SARS, foot-and-mouth disease),
fungi (soybean rust, corn rust), protozoa (giardiasis), and toxins
(ricin). Pathogens such as these and many others could be used
to sicken or kill urban populations, livestock, or crops. Early
detection and unmistakable identification are crucial to limiting
the potentially catastrophic human and economic costs of a bioattack.
Many types of signature requests are received by the team. One
request may be for all strains of a normally pathogenic species,
including its nonpathogenic and vaccine strains. Another request
may be for all of the pathogenic strains of a particular species.
Fulfilling these requests can be difficult because while there
may be hundreds of strains of a particular species, genomic sequences
may exist for only a few. Strains may also vary in pathogenicity,
and their genetic near-neighbors may or may not be virulent or
may affect hosts other than humans. In addition, RNA viruses have
extremely high mutation rates, so it may be difficult or impossible
to find adequate stable regions suitable for use as a signature.
The Livermore bioinformatics team has developed DNA-based signatures
of virtually every biothreat pathogen (the organisms identified
by the CDC as high-priority threat agents) for which adequate genomic
sequences are available as well as for several other human and
livestock pathogens. Signature requests come from agencies such
as the Department of Energy (DOE), the CDC’s Laboratory Response
Network and BioWatch Program, the Department of Agriculture, the
Food and Drug Administration, and the Department of Defense. Livermore
signatures are part of the nation’s public health system
and have been in use for homeland defense since fall 2001.
Sensors Sniff City
Air for Pathogens
specter of terrorists attacking American cities with
airborne pathogens has prompted federal agencies to
develop systems that continuously monitor the air for
nation’s first such monitoring
system is the Biological Aerosol Sentry
and Information System (BASIS). BASIS
was developed by a team of researchers
from Lawrence Livermore and Los Alamos
national laboratories and involved extensive
collaborations with emergency response,
public health, and law-enforcement agencies.
The system uses detection methods derived
from DNA-based signatures designed by
Livermore’s bioinformatics group.
BASIS was designed for the “detect
to treat” mission, identifying
a release quickly enough to permit effective
medical treatment of those exposed.
was called into service after the anthrax
attacks of October 2001. It was also
deployed to Salt Lake City, Utah, as
part of the overall security strategy
for the 2002 Winter Olympic Games. (See
S&TR, October 2003, BASIS
Counters Airborne Bioterrorism.) The
system was later deployed in Albuquerque
and in New
York City for the first anniversary of
the September 11 terrorist attacks.
air-monitoring units collect aerosol
samples at specific locations. A semi-automated
mobile field laboratory rapidly analyzes
DNA from the collected samples for evidence
of potentially lethal bacteria and viruses.
Safeguards built into the system ensure
sample integrity. Should a positive identification
be confirmed, the field laboratory immediately
notifies the appropriate response agencies.
late 2002, the U.S. Department of Homeland Security,
the Environmental Protection Agency,
and the Centers for Disease Control and Prevention
implemented the national BioWatch program.
BioWatch sensors resemble a phone booth
topped with an air intake and radio antenna.
Couriers collect air filters from the
sensors and deliver them to military
facilities or public health laboratories.
There, technicians use Livermore-developed
signatures to detect the presence of
target pathogens. If a pathogen were
detected, officials would examine wind
patterns in the area of the contaminated
sensor and take action to protect the
summer 2003, BioWatch sensors in Houston
detected fragments of Francisella
a bacterium found in rabbits, prairie
dogs, and rodents that can spread to
humans and cause tularemia. Health officials
concluded there had been no attack. Instead,
the sensor had detected tiny amounts
of F. tularensis naturally present in
the environment. Although F. tularensis was known to be endemic in Texas, this
was the first time it was detected in
an aerosol sample.
Department of Homeland Security announced
that the incident marked the first time
the BioWatch network had detected such
a serious airborne threat, one that in
this case was naturally occurring. Tom
Slezak, leader of Livermore’s bioinformatics
group, notes that in more than 700,000
uses of Livermore-developed signatures,
the BASIS/ BioWatch network of sensors
has never raised a false-positive alarm,
that is, concluded that pathogens were
present when they were not.
Air samples are collected by this BASIS sensor installed
a New York Police station. (b) Another sensor resides
in a New York City borough neighborhood. (c) New York
City Department of Public Health officers accompany a
Department of Energy employee retrieving air samples
from a sensor located near the former World Trade Center.
Air samples are tested by Livermore technicians at a
Pipeline Called KPATH
Livermore’s signature pipeline, called KPATH, is used to
develop the signatures of bacterial and viral pathogens. This Livermore-designed
system is a fully automated DNA-based signature “pipeline,” able
to deliver signature candidates (spanning 200–300 base pairs
of DNA) in minutes to hours. In simplest terms, KPATH works by
comparing the genome of the target pathogen to a library of microbial
genomes, searching for those areas that are unique to the target
uses the software programs Multiple Genome Aligner (MGA) and Vmatch,
which were developed by collaborators in Germany. MGA
aligns the multiple genomes of a target pathogen, and Vmatch uses
efficient algorithms to quickly compare the genome of interest
with all other sequenced microbial genomes. “These software
tools allow the pathogen genomes themselves to show us which regions
of DNA are important,” Slezak says. The DNA regions that
are significant to the pathogen are conserved among all strains
of the pathogen sequenced to date and are unique when compared
to all other organisms sequenced to date. That is, they are present
in every strain of the pathogen and absent in all other organisms.
algorithms work by locating those portions of the genome that are
not unique and eliminating them from consideration. “In
this way,” says Slezak, “we define regions of apparent
uniqueness and mine them for candidate signatures.”
On the Road to KPATH:
A Short Timeline
2000, a crude test on Bacillus anthracis, the causative
agent of anthrax, demonstrated that a computer-based
approach to pathogen-signature development would work.
The test took summer student Marisa Lam several days
to process more than 4 billion bytes of information
from analysis of the B. anthracis genome. The roughly
4,000 resulting candidate signatures were narrowed
down to a handful and forwarded to the Centers for
Disease Control and Prevention (CDC) for formal validation.
These optimized signatures became the assays used for
the nation’s Biological Aerosol Sentry and Information
System (BASIS) and BioWatch environmental monitoring
networks. By comparison, earlier methods of signature
design had yielded zero successes among more than 1,000
candidates. Buoyed by this successful test, a team
led by computer scientist Tom Kuczmarski began work
on an automated signature pipeline.
February 2001, foot-and-mouth disease
was devastating the cattle and sheep
industry in the United Kingdom. The Livermore
team analyzed the tiny (8-kilobase) genome
of the foot-and-mouth disease virus (FMDV)
and found that viral genomes, although
tiny compared to the typically 3- to
5-megabase bacterial genomes, can be
troublesome to analyze because of their
high mutation rate. The team determined
that only one region of the FMDV genome
is capable of supporting a signature
assay. In the spring, the team began
collaborating with Sharon Hietala of
the University of California at Davis
to detect agricultural pathogens that
are common to California cattle and cause
symptoms that mimic those of FMDV.
computer scientist Tom Slezak was attending
a conference in Maryland when the September
11 terrorist attacks occurred. During
the five days it took him to return to
California, he conceived of a fully automated
system that would download all new and
updated genomic sequences weekly from
the major public databases. The system
would then compare those sequences with
the existing, fielded DNA-based signatures
to determine if any new sequences had
invalidated them. Slezak named the system
KPATH. “I was inspired by radio-station
call signals,” says Slezak. “KPATH,
all pathogens, all the time. Bringing
you the pathogen hits of the 50s, 60s,
and today.” To achieve the desired
speed and capacity, KPATH would require
a large server with multiple central-processing
units (CPU), a powerful database server,
and more advanced algorithms.
October 2001, when the anthrax attacks
occurred, BASIS was the only system in
the country capable of taking on pathogen
monitoring duties. “The anthrax
attacks resulted in the first real awareness
of bioterrorism by most of the U.S. general
public,” notes Slezak. A few months
later, BASIS also took on monitoring
duties at the 2002 Winter Olympic Games.
June 2002, supplemental funding was obtained
from the Department of Energy to
purchase a 24-CPU server, an 8-CPU database machine,
and a 3-terabyte file server and to hire six summer
students to help build KPATH. The team also adopted
the new Multiple Genome Aligner (MGA) program, which
was developed by collaborators in Germany to dramatically
speed up signature development.
fall 2002, three of the team’s
summer students who had graduated—Clinton
Torres, Jason Smith, and Lam—were
hired to complete the KPATH system. Meanwhile,
Kuczmarski and Shea Gardner handled the
constant demands for new pathogen signatures
using the original pipeline.
December 2002, Livermore’s smallpox
and related signatures were evaluated
by the CDC. A year earlier, Livermore
had anticipated the need for smallpox
assays and had developed candidate signatures.
Just after KPATH signatures passed extensive
testing in January 2003, the CDC requested
that the team process several new smallpox
and near-neighbor genomes in anticipation
of world events.
March 2003, the CDC requested assistance
in analyzing the newly sequenced Severe
Acute Respiratory Syndrome (SARS) virus.
The Livermore team processed both a Canadian
genome and a CDC genome and returned
a set of signature candidates within
three hours. The U.S. Army later tested
these signatures, and the CDC is considering
several for validation.
presents a special situation,” says
Slezak. “We don’t really
know what near-neighbor species are like,
so it is very hard to be sure which signatures
will work when near-neighbor viruses
are eventually discovered. At this time,
77 percent of the genome appears to be
highly unique, but this clearly will
not be the case once other related organisms
are discovered and sequenced. However,
the automated KPATH approach will be
capable of capitalizing on new data,
and within 30 minutes we should be able
to know which regions of SARS still appear
to be unique and therefore which signatures
will continue to work.”
June 2003, an unexpected outbreak of
monkeypox in the U.S. occurred as a result
of exotic animals being imported from
Africa as household pets. Ironically,
although the team had developed candidate
signatures of monkeypox in 2002, the
CDC had not tested these because monkeypox
had never occurred in the Western Hemisphere.
Following the U.S. outbreak, the CDC
supplied Livermore with sequenced monkeypox
from both a human and a prairie dog.
The genomes, which turned out to be identical,
were used by the Livermore team to refine
the monkeypox signatures.
naturally occurring situations provide
us with real-life training experiences
for rapid emergency response,” says
Slezak. “It is a distinct honor
that our team has earned the privilege
of being the bioinformatics team assisting
the CDC on major pathogen emergencies.”
signature development team includes (from left) Nisha
Mulakken, Carol Zhou, Adam Zemla, Ed Miller, Tom Slezak,
Tom Kuczmarski, Jason Smith, Marisa Lam, Clinton Torres,
Shea Gardner, Mark Wagner, and Beth Vitalis. The Livermore
team collectively has expertise in biology, mathematics,
systems science, and computer science.
signatures must then be verified in the laboratory. “It’s
a long path from candidate signature to validated assay,” notes
Slezak. Hundreds of thousands of candidate signatures are computationally
screened. Wet-chemistry procedures reduce that number to hundreds
and then dozens. Much of the laboratory testing takes place at
the CDC and other organizations that are certified to work with
virulent pathogens. Once a signature is verified, the final step
is optimizing the signature for a specific detection chemistry
or instrument using a specific protocol. When that process is complete,
the signature is called an assay.
of KPATH’s important features is that it automatically
downloads newly sequenced pathogen genomes from all major public
databases, and all validated and fielded assays are verified weekly
as the new sequence data are acquired. “As known strains
evolve and new strains are discovered and their genomes sequenced,
some of the ‘unique’ regions will erode,” says
Slezak. “We’ll then need to refine the signature.”
Livermore researchers try to sleep
on a U.S. Air Force C-130 transport plane on their way
to deploy a pathogen-detection system.
Olympic Games Motivate
early 2000, the DOE’s Chemical and Biological National
Security Program (CBNP) began a national pathogen-detection effort
following the announcement by then-Secretary Richardson that DOE
would be providing biosecurity at the 2002 Winter Olympic Games
in Salt Lake City, Utah. Lawrence Livermore was assigned the task
of developing reliable and validated assays for a number of the
most likely bioterrorism agents.
bioinformatics team reasoned that a whole-genome analysis approach—that
is, comparing a target pathogen genome against all other sequenced
microbial genomes—would reveal which regions of the DNA were
unique. They also believed the process could be automated to get
results more quickly. Until the Livermore approach, signature design
was a time-consuming, expensive process done largely by hand and
guided heavily by intuition. Analysis was generally limited to
sequences from a few genes thought to be important. Traditional
approaches to DNA-based signature development started with the
assumption that a particular gene was vital to an organism’s
virulence, host range, or other factor. The resulting assay would
then be tested with the available strain. This approach would at
times yield good results, but it frequently resulted in failure.
Computational support for diagnostic development was rare. “The
time was ripe for radical changes in this field,” says Slezak.
There are two major ways to detect
pathogen signatures. One involves finding specific regions
of DNA (or RNA) that uniquely identify a pathogen. The
other (still under development) involves finding specific
regions of a unique protein whose production is specified
by that pathogen’s DNA (or RNA).
August 2000, the team began building a set of tools that would
accomplish these goals. Slezak says, “We used techniques
and mindsets from our many years of experience working on the Human
Genome Project (HGP).” Slezak formerly led Livermore’s
HGP bioinformatics effort and later the Joint Genome Institute’s
informatics effort. BBRP scientist Paula McCready led Livermore’s
HGP sequencing effort for several years and was the first leader
of the sequencing effort at DOE’s Joint Genome Institute.
concept of an automated signature-design system began with a crude
algorithm and a proof-of-principle test that took about
one week. The goal was to develop a signature for Bacillus
the bacterium that causes anthrax. When the test proved successful,
Slezak began to search for more efficient algorithms.
“In October 2000,” says Slezak, “we
began building a preliminary pipeline based on this approach with
from the Laboratory Directed Research and Development Program.
In May 2002, we were funded by DOE to build the current KPATH pipeline.
We continued to use the first pipeline until about January 2003,
when KPATH was shown to be functionally equivalent and much faster.”
DNA-based signatures are often the
part of a pathogen’s genome that reflects the code
of a particular protein or enzyme unique to the pathogen.
This model depicts one such pathogen protein. Blue represents
the part of the protein that is conserved (present) in
all strains of the pathogen’s DNA. Red represents
the portion of the protein that is unique to the target
strain. Green depicts the most highly conserved portion
across multiple organisms. The DNA-based signature of this
target strain, therefore, combines those portions of DNA
that code for both the blue and red regions.
New Features on the Horizon
bioinformatics team is developing additional features for KPATH,
including the capability to generate multiple types of signatures
to support different detection chemistries and machines, better
algorithms to improve processing efficiencies, and improved capabilities
for developing signatures of RNA viral genomes. Signature development
of RNA viruses is particularly difficult because they mutate so
rapidly. To overcome this difficulty, the team is building a pipeline
of protein signatures—the other major approach to pathogen
signatures are commonly used in diagnostic kits, such as commercially
available home-use pregnancy tests. Slezak notes that
the sequence of amino acids that make up a protein tends to be
conserved (unchanged) because altering the protein sequence is
likely to change the protein’s shape, which in turn would
alter its function. Using this approach, the team has found conserved
and unique signature regions in the glycoprotein of the West Nile
virus (an RNA virus) and has mapped these regions to three-dimensional
protein structure models created by Livermore mathematician Adam
Zemla. Antibodies derived from these regions are being tested at
the University of California at Davis to verify that the identified
regions are indeed unique.
KPATH uses computers and efficient
algorithms to compare genomes and identify those portions
that are unique to a particular pathogen or family of related
pathogens. (a) A small part of the genome (50 DNA bases
out of 8,000) of six strains of a pathogen are aligned
and arranged in five columns for comparison. (The letters
T, C, A, and G represent thymine, cytosine, adenine, and
guanine, the four nucleic acids that make up all DNA.)
The stars are a rough visual indicator of the degree of
similarity or “consensus” among the six strains
in each column. (b) A “consensus genome” is
derived from those regions that are common to the six strains,
indicated by the upper case letters. (c) The consensus
region is mined to obtain a unique signature of the pathogen,
which corresponds to the colored sequence.
team also plans to develop fungi signatures. However, fungal DNA
is more difficult to analyze than bacterial DNA because of
the larger genome size of fungi. Because of funding constraints,
only a few fungi genomes have been sequenced. As a result, it is
difficult to know what genomic regions are common to fungi and
thus are not useful for signatures.
ongoing task for the team is building and maintaining relationships
with partners in various agencies and universities. Slezak explains, “Much
of the data we need are not in the public domain.”
the meantime, researchers worldwide are regularly publishing the
sequences of new and updated genomes. As additional pathogens
are sequenced, the Livermore team will continue to provide rapid
computational analysis and develop DNA-based and protein signatures
to help thwart bioterrorists.
Key Words: BASIS, bioinformatics, bioterrorism, BioWatch, Centers
for Disease Control and Prevention (CDC), DNA, foot-and-mouth
disease, Human Genome Project, KPATH, microbe, pathogen, protein
signature, RNA, Severe Acute Respiratory Syndrome (SARS), smallpox.
For further information contact Thomas Slezak
(925) 422-5746 (email@example.com).
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