| 
|
What is the Role of PulseNet? |
|
Why was PulseNet
developed? |
|
How does PulseNet work? |
|
Why is PulseNet important
to public health? |
|
What is the PFGE process? |
|
|
Advantages |
| |
|
Limitations of
PFGE and PulseNet |
|
How does subtyping
help in epidemiologic investigations? |
|
What makes
interlaboratory comparison of DNA patterns possible? |
|
What are the future
applications for PulseNet? |
 |
What
is the Role of PulseNet? |
|
Detect foodborne
disease case clusters by pulsed-field gel electrophoresis
(PFGE) |
|
Facilitate early
identification of common source outbreaks |
|
Assist epidemiologists
in investigating outbreaks |
|
|
Separate outbreak-associated
cases from other sporadic cases |
|
|
Assist in rapidly
identifying the source of outbreaks |
|
|
Act as a rapid
and effective means of communication between public
health laboratories |
|
Why
was PulseNet developed? |
| In 1993, a large
outbreak of foodborne illness caused by the bacterium
Escherichia coli O157:H7 occurred in the western
United States. In this outbreak, scientists at CDC performed
DNA "fingerprinting" by pulsed-field gel electrophoresis
(PFGE) and determined that the strain of E. coli
O157:H7 found in patients had the same PFGE pattern
as the strain found in hamburger patties served at a
large chain of regional fast food restaurants. Prompt
recognition of this outbreak and its cause may have
prevented an estimated 800 illnesses. As a result, CDC
developed standardized PFGE methods and in collaboration
with the Association
of Public Health Laboratories (APHL)*, created PulseNet
so that scientists at public health laboratories throughout
the country could rapidly compare the PFGE patterns
of bacteria isolated from ill persons and determine
whether they are similar. |
|
How
does PulseNet work? |
| 1 ) |
 PulseNet
participants perform DNA "fingerprinting"
by pulsed-field gel electrophoresis (PFGE) on disease-causing
bacteria isolated from humans and from suspected food
using standardized equipment and methods.
|
| 2) |
Once these PFGE
patterns are generated, they are entered into an electronic
database of DNA fingerprints at the state, local, or
federal laboratories. |
| 3a) |
The patterns
are then uploaded to the national database located at
CDC. |
| 3b) |
All participants
who are certified have a direct link to the national
database at CDC. |
| 4) |
Database managers
at CDC perform regular searches, looking for clusters
of patterns that are indistinguishable. The results
are reported back to the labs, the epidemiologists at
CDC and if relevant, to CDC Team, the PulseNet listserv. |
| 5) |
Laboratorians
perform regular searches on their local databases, looking
for clusters of patterns that are indistinguishable.
The results are reported to CDC, the state epidemiologists
and if relevant, to CDC Team, the PulseNet listserv. |
|
Why
is PulseNet important to public health? |
| PulseNet plays
a vital role in surveillance for and the investigation
of foodborne illness outbreaks that were previously
difficult to detect. Finding similar patterns through
PulseNet, scientists can determine whether an outbreak
is occurring, even if the affected persons are geographically
far apart. Outbreaks and their causes can be identified
in a matter of hours rather than days. |
|
What
is the PFGE process? |
|  DNA
macrorestriction analysis utilizes restriction enzymes
that cut genomic DNA infrequently and thus generates
a small number (usually 10-20) of restriction fragments.
These fragments are usually too large to separate
by conventional agarose gel electrophoresis. However,
these fragments can be effectively resolved by a process
termed pulsed-field gel electrophoresis (PFGE), developed
in 1984 to separate yeast chromosome-sized DNAs. PFGE
facilitates the differential migration of large DNA
fragments through agarose gels by constantly changing
the direction of the electrical field during electrophoresis.
The contour-clamped homogeneous electric field (CHEF)
gel electrophoresis method has become the method of
choice for resolving DNA macrorestriction fragments
of bacterial genomic DNA.
|
|
Advantages
of using PFGE |
| |
PFGE subtyping
has been successfully applied to the subtyping of many
pathogenic bacteria. PFGE has been repeatedly shown
to be more discriminating than methods such as ribotyping
for many bacteria. PFGE in the same basic format can
be applied as a universal generic method for subtyping
of bacteria. Only the choice of the restriction enzyme
and conditions for electrophoresis need to be optimized
for each species. DNA restriction patterns generated
by PFGE are stable and reproducible at the intra- and
inter-laboratory levels. In summary, PFGE is the method
of choice for epidemiologic subtyping of pathogenic
bacteria at the present time |
| |
|
Limitations
of the PFGE Method and Analysis and PulseNet |
| |
|
PFGE Method
and Analysis: |
| |
|
- |
Time consuming
|
| |
|
- |
Requires a high-level of
skill |
| |
|
- |
Does not work for everything
(i.e. clonal patterns) |
| |
|
- |
Pattern results vary from
person to person |
| |
|
- |
Can’t optimize separation
in every part of the gel at the same time |
| |
|
- |
Bands are bands, not sequences |
| |
|
- |
Don’t really know
if bands of same size are same pieces of DNA |
| |
|
- |
Bands are not independent |
| |
|
- |
Change in one restriction
site can mean more than one band change |
| |
|
- |
“Relatedness”
should be used as a guide, not true phylogenetic measure |
| |
|
- |
Some strains are untypable
by PFGE |
| |
|
|
|
| |
|
PulseNet: |
| |
|
- |
Competing priorities at
state and local public health laboratories |
| |
|
- |
Lack of resources at state,
local, and federal laboratories |
| |
|
- |
Lack of epidemiological
resources at the state, local, and federal levels |
|
How
does subtyping help in epidemiologic investigations? |
|
Identifies cases
within an outbreak |
|
|
Distinguishes
outbreak cases from concurrent sporadic cases |
|
|
Reduces misclassification |
|
Detects outbreaks
through surveillance |
|
|
Links apparently
sporadic cases |
|
|
- |
In which the cases are too
widely dispersed to detect |
|
|
- |
Organism too common to notice
small increase |
|
|
- |
Identifies related cases
and separates them from unrelated ones |
|
|
DNA “fingerprinting”
methods have greatly increased sensitivity of subtyping |
|
|
|
|
Food consumption
and practices have changed during the past 20 years
in the United States. We are observing a shift from
the typical point source, or “church supper”
outbreak, which is relatively easy to detect to the
more diffuse, widespread outbreaks that occur over
many communities with only a few illnesses in each
community.
For example, we have observed the establishment of
large food producing facilities that disseminate products
throughout the country. We have seen in a few outbreaks
that some low level contamination of food products
can occur, and the products are distributed among
many states. Only a few illnesses occur in each community,
and this new style of outbreak is often difficult
to detect. However, new laboratory and statistical
tools, such as PulseNet and the surveillance outbreak
detection algorithm (SODA), have had an impact on
our ability to identify and investigate these new
types of outbreaks |
|
What
makes interlaboratory comparison of DNA patterns possible? |
For PulseNet,
the quality and uniformity of the data is ensured
by the implementation of a quality assurance and quality
control (QA/QC) program. Here are components of the
QA/QC program that allow for the comparison of DNA
patterns across all labs: |
|
Standardized
protocols |
|
QA/QC Manual |
|
Same molecular
size standards |
|
Standardized
software used by all participants |
|
Standardized
nomenclature of PulseNet patterns |
|
Training workshops
(lab & software): most participating labs have attended
a week of combined laboratory and analysis software
training |
|
Certification:
all individuals who submit data must be certified by
stringent PulseNet standards |
|
Proficiency
testing: all certified individuals must participate
and pass annual proficiency testing in order to maintain
certification |
|
Annual update
meetings: provide a forum for the live exchange of information |
|
What
are future applications for PulseNet? |
|
Increase the
number of PulseNet participants |
|
Achieve real-time
subtyping and real-time communication |
|
|
Reduce the time
it takes for isolates to go from the clinical lab to
the state/local public health lab |
|
|
Reduce the time
for pulsed-field gel electrophoresis (PFGE) testing
of isolates |
|
|
Critical for
timely detection of clusters |
|
|
Increase the
level of communication between laboratorians and epidemiologists |
|
Improve bandmarking
among all labs |
|
Strengthen collaborations
with the food industry |
|
New subtyping
methodology |
|
|
Multiple-locus
variable-number tandem-repeats analysis (MLVA) |
|
|
Multiple-locus
sequence typing (MLST) |
|
