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David Liu's group supercharged green fluorescent protein (left)
with a super positive (middle) and super negative (right)
charge.
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David Liu / Reprinted with permission from American Chemical
Society,J Am Chem Soc, 129:10110–2, 2007.
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One day in March of 2006, postdoc Mike Lawrence walked into David Liu's
laboratory at Harvard University in a slightly anxious mood. He'd been in the lab
for nine months with little to show in terms of good results, and he was hoping this
day might turn things around. He had taken on a bold new project with his labmate,
Kevin Phillips, to test whether changing the charge of surface residues on a
protein could reduce its propensity for aggregating.
Preventing aggregation could be appealing for a number of reasons:
understanding neurodegenerative diseases, extending the shelf life of
protein therapeutics, and producing better-behaving proteins for lab work
such as crystallography. In all of these examples, a protein's propensity for
aggregating can wreak havoc on attempts to control its behavior.
Instead of taking the route most scientists might take to avoid
aggregation – systematically changing just one amino acid at a time – Phillips
and Lawrence went to the extreme, creating a "supercharged" protein with 36
positive charges.
He and Phillips substituted neutral amino acids for positively charged
lysines or arginines – a whopping 29 of them. "Just the sheer number of changes
introduced into these proteins was pretty massive," says Liu, who was not aware
of the design of the project until the results came in. Lawrence and Phillips did
hedge their bets, however, creating proteins with random, smaller numbers of
mutations in addition to the fully supercharged mutant. (Most proteins fall
within the range of -10 to +10.) While scientists had predicted that surface
residues could tolerate change and still function properly, the numbers in mind
were closer to three or five changes, Liu says with a laugh, "not 30! We didn't
anticipate that one could make so many mutations without just obliterating the
function."
Such brazen science might usually win a researcher nothing more than
wasted time, but not this day. "I came in and looked at the colonies on the plate and
there were some green ones," Lawrence says, which meant that the green
fluorescent protein (GFP) he had supercharged was folding normally. "But the
more likely scenario was something went wrong," he says.
Lawrence sequenced the GFP from the colonies and, much to his surprise,
those with the glowing green proteins did indeed have all the charged mutations.
"It was a long shot," he says, but it worked, and he was excited to show his results
to Liu – who was also excited to see them. GFP with a super negative charge of -30
also glowed, and supercharging also prevented aggregation by the bacterial
proteins streptavidin and glutathione s-transferase (J Am Chem Soc,
129:10110–2, 2007). The study confirms earlier work showing that surface
charge can discourage aggregation. (J Biol Chem, 280:10607–13, 2005).
The scientists got the idea for supercharging after observing an
aggregating-prone protein evolve, to see how natural selection could solve the
problem of aggregation. Again and again, the solution seemed to be the same:
mutants with the highest charge on their surfaces showed the least aggregation.
While the idea of manipulating charge isn't new, it's "the large amount
of charge that's quite interesting," says Harvey Blanch at the University of
California, Berkeley. The reason supercharging works is pretty simple.
"Basically," says Blanch, "it's electrostatic propulsion between the
proteins": Positive charges on a protein's surface keep it at arm's length from
the positive charges on its neighbor.
The disadvantages to supercharging, at least in vitro, don't seem to be
too great. Lawrence says that the supercharged GFP required about 20% less
denaturing chemical to make it unfold, meaning the protein is slightly less
stable. The expression levels in bacteria were also lower for supercharged
proteins compared to protein with smaller changes in charge. Lawrence concedes
that it might be more practical to make just the number of changes necessary to
discourage aggregation. Additionally, in vivo, "the tendency to aggregate or
be recycled could be important," says Liu.
Fabrizio Chiti at the University of Florence, who published the 2005
paper with similar results, is interested in surface charge for algorithms he's
designing that can predict aggregation rates or aggregation-promoting
regions. "It's clear charge is an important factor," he says. Whether it is a
phenomenon that will work for all proteins remains to be seen. But Lawrence's
work supports his hunch, Chiti says: "I think it's a principle."