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Articles

Characterizing Targets in Model Organisms

Thu, 09/06/2007 - 6:57am

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Getting useful data from
model organisms is often laborious, but new strategies and technologies are
helping.

Alan Dove
Dove is a freelance writer based in New
York

On the long road from finding a new molecule in a cell to putting a
pill in a bottle, one of the main obstacles is validating the target in model
organisms. In essence, this

A high-resolution magnetic resonance imaging
(MRI) slice of a mouse showing internal structures for detailed phenotypic
mapping. Part of the Visible Mouse Project, the image’s resolution is more
than 10,000 times sharper than that of a routine clinical MRI scan.
(Source: Allan Johnson, PhD, Duke
University)

consists of
inactivating or stimulating the target in the cells of a live animal and seeing
whether that produces the desired effect. But in drug development, as in
marksmanship, seeing a target is the easy part—hitting it is hard.

Like
so much of modern drug development, the concept only sounds simple. Live animals
are far more difficult to control and study than individual cells, and even the
most straightforward questions about a target can be maddeningly difficult to
answer. Using a range of intriguing new technologies, though, several research
groups are starting to address some of the field's biggest
challenges.

Phenotypes are the central issue in target validation: What
is the model organism's normal biology and how does inactivating the target
change that? Unfortunately, although molecular biology revolutionized the way
researchers study genotypes, phenotyping remains a vague science where even
seemingly simple questions remain unanswered. Compounding the problem, advances
in medical imaging have enabled physicians to diagnose and study human diseases
in patients in unprecedented detail, creating a demand for drugs to treat
conditions that were previously not diagnosable. The technology for imaging
model organisms, however, has lagged far behind. Identifying an early-stage
tumor in a patient is important, but developing a new drug to treat it requires
seeing it in a mouse.

The simplest approach to the problem involves
applying clinical imaging techniques to model organisms, and indeed many
researchers have done just that, especially with magnetic resonance imaging
(MRI). "People do it routinely. They take their clinical MRI machine and they
put a mouse in there and then they try to make an image," says Allan Johnson,
PhD, director of the Center for In Vivo Microscopy at Duke University Medical
Center, Durham, N.C.

But producing an image is a far cry from obtaining
useful data. Just as digital cameras record fixed numbers of pixels, MRI
machines record fixed numbers of voxels, so scanning an animal thousands of
times smaller than a human yields an image with thousands of times less
resolution. In addition, the metabolism of a mouse is an order of magnitude
faster than that of a human. "So if you want to look at a mouse heart, you've
got to image it 10 times faster than if you were looking at a human heart, yet
your signal is 3,000 times weaker," says Johnson. Using conventional MRI, the
result is like a movie downloaded over a telephone modem. The technique can
reveal gross abnormalities from one animal to the next, but modern target
validation demands more detail.

To address this, Johnson and his
colleagues have steadily increased the bandwidth of the available imaging
systems. For MRI, this means combining stronger magnetic fields, more sensitive
receiver circuits, and more sophisticated image analysis software. Each
technical adaptation boosts the resolution a bit, while meticulous anesthesia
techniques keep the mouse still enough to scan. "You don't get that factor of
3,000-[fold improvement] by some magical little trick. You earn it," says
Johnson, who adds that "each phenotype is its own challenge."

Besides
imaging live animals, the new techniques can also be used on dead ones, a
strategy that is especially useful for characterizing structural phenotypes like
atherosclerosis or tumor size. Scanning a dead animal provides a reasonably
detailed three-dimensional map of the internal structures, which can then be
sectioned and studied microscopically for even greater resolution. Combining the
new tools may let drug developers study mice even more thoroughly than doctors
now study patients.

Other groups are also working on high-resolution
phenotyping, especially for mice. Major mouse breeding facilities are trying to
organize the flood of new data. Although phenotypic information is still far
less abundant than genotypic data, phenotypes based on images are much harder to
search and analyze than gene sequences, so the field may soon be facing a
bioinformatics bottleneck.

A clear advantage
Seeing tiny
changes inside a mouse is challenging, but in some other model organisms the
effects of inhibiting a target molecule are literally clearer. The worm

click the image to enlarge
An artist’s rendition of the process of
atherosclerotic plaque development showing the complex interactions of
multiple cell types. Medically important phenomena like this are often
difficult to replicate in model organisms. (Source: Bioseek
Inc.)

Caenorhabditis
elegans is the undisputed champion of biological transparency, providing
researchers with a detailed view of its innards throughout its life, along with
predictable genetics and easy culturing. Because many of the key signaling
pathways in human cells have homologs in worms, many drug developers already use
this model for initial target validation.

There is a lot of evolutionary
distance between worms and mice, though, so to test targets in a system with
intermediate complexity, some companies are turning to the zebrafish (Danio
rerio). The adult fish are opaque, but their eggs and embryos are
conveniently transparent, and some biotechnology companies have been working
hard to adapt this model for drug discovery. Researchers at Phylonix, Cambridge,
Mass., and Zygogen LLC, Atlanta, developed extensive sets of drug activity and
toxicological assays in the tiny fish. Both companies use fluorescent labels and
visual screens to score phenotypes, and the organism's transparency allows
screening for everything from liver toxicity to angiogenesis inhibition.
Conveniently, the eggs and embryos are small enough to fit in the wells of
96-well plates.

For even easier processing of fish eggs or any other
model system smaller than about a millimeter in diameter, companies are
increasingly turning to large-particle flow cytometry, a technique being
pioneered by researchers at Union Biometrica Inc., Holliston, Mass. Like an
ordinary flow cytometer, the system rapidly sorts particles from a mixed
solution into individual wells while providing quick measurements of each
specimen's fluorescence or light-scattering characteristics.

Union
Biometrica's system permits these analyses on samples that would clog an
ordinary flow cytometer. Though it was initially applied to C. elegans,
the large-particle sorter has now been adapted to handle everything from small
plant seeds to whole fruit fly and fish embryos. "We've seen a number of
different groups that are using C. elegans, we've seen quite a few using
Drosophila, and more recently . . . zebrafish. I think there's a kind of
popularity right now for using zebrafish for toxicology studies," says Rock
Pulak, director of biology at Union Biometrica. The system might also be useful
for sorting clusters of human embryonic stem cells, embryoid bodies, and complex
primary cell cultures. High-throughput systems based on these types of cellular
aggregations could become especially useful as drug developers try to bridge the
gap between nonhuman model organisms and humans.

Researchers usually turn
to automated techniques simply to accelerate their current research, Pulak says
that increasing the throughput of an animal assay can also enable entirely new
types of studies. For example, many mutant animal strains develop particular
disease phenotypes, but the genes that contribute to the disease remain unknown.
With a high-throughput animal-handling system, a researcher could screen an
entire library of inhibitory RNA molecules against the animal's expressed genes
to find the ones that ameliorate the phenotype. "Any RNA interference [RNAi]
that would come up in such a screen is almost immediately identifying a [drug]
target," says Pulak.

RNAi precision
Of course, Pulak is not
the first to suggest using RNAi technology to accelerate drug discovery. Indeed,
the very existence of RNAi and its ability to do researchers'

Virtual Biology Monitors
Regulation
There are seldom good explanations for compounds that
look wonderful in animal tests but turn out to be costly failures in
humans, especially since most of our understanding of drug metabolism
comes from the same animal systems that failed to predict the problem.
Because clinical trials are so expensive, the gap between humans and model
organisms remains one of the greatest risks in drug development. "When you
start comparing the biology of animals and people, certainly while core
pathways and mechanisms might be conserved . . . what turns out to be
critically different is the regulation," says Ellen Berg, PhD, chief
scientific officer of Bioseek Inc., Burlingame, Calif. To address that
problem, Bioseek is turning humans into model
organisms—virtually.

With complex mixtures of primary human cells
from blood and tissue samples, Berg and her colleagues are creating
miniature versions of specific biological environments. One system
incorporates endothelial cells, B cells, T cells, monocytes, and other
components of a blood vessel. The culture responds appropriately to
changes, such as the addition of inflammatory and anti-inflammatory
signals.

By combining the primary cell cultures with a
sophisticated gene expression profiling algorithm, the company can map the
responses that human cells exhibit to different drugs. Comparing known and
novel drugs in multiple systems produces an impressively accurate
two-dimensional diagram of relationships; drugs that are near each other
in the diagram tend to have very similar effects and side effects in real
humans. There are shortcomings, however: "What you do miss is certainly
the whole physiology, the fact that organ systems are talking to one
another."

bidding still strikes many
biologists as an uncommonly generous gift from nature. Though RNA researchers
are still teasing out the mechanistic details (see "Opening a Portal: The
Strange New World of MicroRNA," Genomics & Proteomics, June 2005,
page 14), stopping the expression of individual proteins with RNAi already forms
the backbone of many target discovery and validation efforts.

The
precision of RNAi-based techniques is impressive, but there are still drawbacks.
One limitation is that complex organisms have complex physiology, and the
dynamics of artificial RNAi metabolism are still murky. Even if the inhibitors
can be stabilized and delivered efficiently to model animals, there are some
tissues, especially in the central nervous system, that remain difficult for any
noninvasive technique to penetrate.

Because many of the most promising
drug targets are proteins the RNAs code for, RNAi and other techniques to stop
gene expression, such as conditional gene deletion, are also one step removed
from the real target. What target validation really needs is a way to
selectively inactivate proteins in intact tissues. By cleverly exploiting
physical chemistry, Kimberly Hamad-Schifferli, PhD, and her colleagues at the
Massachusetts Institute of Technology (MIT), Cambridge, Mass., are trying to
develop just such a tool.

The technique entails attaching iron or iron
alloy particles a few nanometers in size to the biomolecule of interest. "Then
we just set it in a magnetic field [which] will heat the nanoparticle," says
Hamad-Schifferli, an assistant professor of mechanical engineering. The hot
nanoparticle heats the protein, denaturing and inactivating it, while other
proteins that are not attached to nanoparticles remain unaffected. Having tested
the approach on purified proteins, the investigators are now hoping to apply it
to intact cells and eventually to tissues.

Remote-control switches for
natural proteins would be wonderful, but a more likely application in drug
development would be to attach the nanoparticles to artificial molecules that
bind particular targets. Once the drug is bound to its target in a model system,
either the drug or the target might then be activated or inactivated at will.
The idea is elegant, but the implementation will take a lot of work, a situation
that remains painfully familiar to drug developers. No matter what model
organism a researcher uses, progressing from a promising target to a worthwhile
drug is still an arduous process. With a few new tools and a bit of luck,
though, drug developers may eventually be able to hit the
bull's-eye.

Topics

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