ON THE eve of a major conference on the safety of genetically modified food
and crops, two research teams have put forward their vision of how scientists
can ensure that transgenic plants and animals don’t run riot when released into
the environment.
“At the moment, the environment is being used as an open air laboratory,”
says Adrian Bebb of Friends of the Earth in Britain. There is no agreed way to
evaluate the dangers of GMOs before field trials are carried out. Once an
organism has been released, it could be too late.
Now William Muir and his colleague Richard Howard at Purdue University in
Indiana have developed a way to spot rogue GM organisms long before they are
released into the environment.
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The technique could do for GMOs what clinical trials do for drugs.
“Pharmaceuticals companies have to ensure that their drugs are safe for human
consumption,” says Muir. “Agricultural companies should have to ensure that
their organisms are safe for the environment.”
His plea comes as delegates from OECD countries, the UN Food and Agriculture
Organization and the World Health Organization prepare to meet in Bangkok on 10
July to thrash out a consensus on the science behind GMOs and the public’s
concerns. Muir and Howard hope their method will win enough support from
scientists and regulators to be adopted worldwide.
It is based on taking the results of extensive lab tests and feeding them
into a computer model. This, they say, can predict whether a foreign gene would
spread if a GM organism escaped or was released into the wild. So far Muir and
Howard have only tried their model on fish, but in a paper published this week
in The American Naturalist (vol 158, p 1), they say the same principle
would work for any animal or plant species.
The model would give scientists common ground—something they can agree
on, says Muir. “Once scientists are able to agree, that makes something much
more acceptable to the public.”
Environmentalists have given the idea a cautious welcome. “It would help,”
says Bebb. “I do think there’s a need for research like this before experiments
come out of the lab.”
Sue Mayer of GeneWatch UK agrees. “Models are extremely useful and they can
really pick up what things are sensitive to. They are bound to make you feel
that there has been rigorous investigation before you go to the next step.” But
models are only ever as good as the data you put in, she warns.
But what will the biotech companies think? “I suspect that industry would
baulk at such a thorough approach,” says Peter Kareiva, a senior ecologist at
the US National Marine Fisheries Service. It could take up to five years to get
enough data on GM salmon strains for the model to work, for example. But Mayer
says that firms won’t have a choice if regulators deem such tests
appropriate.
To develop their model, Muir and Howard identified six aspects of the life
history of fish that affect their “fitness”—the number of offspring they
produce. These include how many fish survive to adulthood, the age at which they
sexually mature and the number of eggs females produce. Then they developed a
computer model based on these six traits that predicts how any modified strain
would fare against the wild-type fish.
The researchers applied their model to a strain of Japanese
ricefish, or medaka, to which they had added the gene for human growth hormone.
They counted and measured separate populations of modified and unmodified fish
for around two years to see how they compared.
The modified fish were less likely to survive to adulthood, but they reached
sexual maturity earlier and the females laid more eggs. Attempting to predict
how these effects balance out would be extremely difficult, but the computer
model can work it out.
Muir and Howard found that even though the modified fish were more likely to
die young, they would still take over the natural population if released into
the wild—so this should never be done. “There’s an assumption that if
juvenile viability is lower, then the gene won’t spread,” says Muir. “That’s the
common misconception that everybody’s been working with. But we’ve shown that
there are several other factors that can offset this.”
“It is a sensible approach,” says James Bullock of the Centre for Ecology and
Hydrology in Dorset. “Modelling and lab-based stuff only give a limited picture,
but it gives you an idea of what may happen.”
If anything, the model should overestimate the risks of GMOs in
the wild, says Muir. “We consider the lab to be more benign and hospitable than
nature,” he says. “So if in the lab, transgenic organisms are not found to be a
risk when they are given a beneficial environment, we feel confident that in
nature there will be even less of a risk.”
But John Beringer, former head of Britain’s Advisory Committee
on Releases to the Environment, disagrees. “I don’t believe that we know enough
about fitness for that to be valid,” he says. “We don’t know which
characteristics are important because environments change so much.”
While Muir is working out the risks of foreign genes spreading in
the wild, Bullock is trying to estimate the consequences of such contamination.
He’s using a technique called matrix modelling to combine data obtained from
natural plants in the wild and from related GM crop species in the lab. This
model predicts whether wild plants that gain foreign genes from their GM
relatives would be likely to invade habitats at the expense of native strains.
“We’re saying: what if gene flow has already happened, what would be the
consequences of that?”
He is measuring life-cycle traits such as seed germination, seed production
and the survival rate of native plants in different habitats in the wild. His
model uses these to calculate how fast their populations are increasing. He then
does the same for GM plants grown in the lab. From this, he hopes to be able to
tell whether a foreign gene will make wild plants more invasive or not.
Bullock hasn’t published his results yet, and acknowledges that modelling
can’t give definite answers. But his initial results indicate that GM oilseed
rape could affect its wild turnip relatives. In one worst-case scenario, a
population of turnips could increase hugely at the expense of other species if
it took up an oilseed rape gene that boosts seed production, he says.
The results could be used to help decide which GM plants are safe enough for
field trials, Bullock says. “If you then put a plant into the wild, you could be
fairly sure what the problems are likely to be.”
The researchers accept that modelling environmental effects doesn’t take into
account other factors, such as ethical considerations, possible threats to human
health and the potential benefits of the modified animals and plants. But Muir
says he hopes his work will help make biotechnology more acceptable.
ATTEMPTS to check whether genetically modified crops and foods could produce
unexpected health effects in people are coming up with promising results.
Regulators currently test GM plants for known allergens. They also look to
see if there are any large differences in the composition of a GM plant compared
with its conventional cousins—a concept called “sustainable equivalence”.
But critics say this isn’t enough.
So researchers are devising ways to check for subtle differences between the
plants that might make them dangerous. Mike Gasson of the Institute of Food
Research in Norwich is heading a three-year pilot project that is profiling the
metabolism and proteins produced by conventional and GM tomato and tobacco
plants.
So far they have examined the protein profiles of several conventional tomato
varieties. “The results so far have been quite encouraging,” he says. “They look
more or less identical, so if GM did produce something weird, we’d pick it
ܱ.”
Differences in the metabolism of the conventional varieties that Gasson has
found could give a baseline against which GM crops could be judged. “The idea
would be to have a database setting out the normal range of variation,” he
says.
The researchers also found differences between the metabolism of conventional
tobacco and a GM variety. But they expected that, as they had inserted a gene
into one set of plants that disrupts growth.
Scientists elsewhere in Europe are working on similar projects. Collaborators
are profiling messenger RNAs for example, which serve as markers for genes that
are switched on. Encouraged by Gasson’s results, Britain’s Food Standards Agency
is planning to invest an extra £6 million in more research. “We thought
we’d take it forward, and we’re drawing up contracts now,” says a spokeswoman.
Andy Coghlan
