By: Frank Corden
As I was driving in this morning to the Hynes Convention
Center, I was thinking about how lucky we are to have an international meeting
of this caliber in Boston. I just love
BPI. It’s such a great mix of presentations; the breadth of discussions from
the applied science around cell engineering to the underlying business drivers
that will carry us into the next decade is amazing. The organizers successfully execute this
daunting task with seeming ease, though I’m sure in the background their little
duck feet are paddling away.
Those of you who know me have heard the story of how I
became a scientist. As a kid growing up
in the sixties and early seventies, my interests in science and technology were
birthed from watching Jacques Cousteau television specials and the race to the
moon. In the years since, I’ve had the
pleasure of seeing first hand that those fish on the coral reef are really all
those beautiful colors and that NASA used proven technology, kerosene and
liquid oxygen (aka Rocket Propellant No. 1) to get our astronauts into
space. Fortunately, my interest in all
cool things science hasn’t waned with age and that’s why I love BPI.
Yesterday afternoon, I was sitting in on the presentation “Raising
the Bar: Advanced Analytics in Upstream Bioprocess Development.” Much of the discussion focused on the use of
Liquid Chromatography coupled with Tandem Mass Spectroscopy (LC-MS/MS) to
identify and quantitate attributes of various cell culture processes. Without getting overly technical, the
technique can be used to map the amino acid sequence of a drug substance as
well as the pattern of added sugars (glycosylation) that are bound to an intact
monoclonal antibody molecule.
LC-MS/MS works by very accurately measuring the mass of the
peptide fragments created from the proteins in the sample during the sample
preparation process. By accurately
measuring the mass, the LC-MS/MS can identify the amino acid composition of
each fragment. This composition and the
mix of the fragments, especially unique fragments specific to the proteins of
interest, enable the instrumentation to identify with a very high certainty the
presence and relative concentration of different proteins in the sample.
In the data shown, the presenter, Chris Yu, demonstrated the
practical power of the LC-MS/MS method to characterize drug substance. Data showed that LC-MS/MS could identify and
quantitate host cell proteins and, further, could give positive confirmation of
glycosylation patterns. But what was
most interesting to me was a more basic discovery…
As part of the effort to characterize a particular drug
substance, the team identified a low percentage of peptides which differed from
the expected amino acid composition, often a swap between serine and
asparagine. Initially the thought was
that the DNA sequence for a fraction of the cells was different, as a result of
either spontaneous mutations or by misincorporation of the DNA sequence during
cell engineering. Surprising neither of
these possible errors was the root cause.
It turns out that there is a natural error rate for
misincorporation of amino acids into the primary sequence of proteins. The authors presented data that showed the
error rate was in the same range for both mammalian cells and E. coli. The error rate could also be influenced by
the relative availability of the amino acids in the cell culture. Restrict the availability of the intended
amino acid relative to the incorrect amino acid and you get higher
substitution. Provide a plentiful source
of the intended amino acid and the error rate decreases.
On reflection, it’s not surprising that some low level error
rate should be expected. After all,
these biological processes are driven by chemistry. You can have a preference for a given binding
affinity or reaction path, but it’s just a preference even when it’s a very
strong preference. As an analogy,
byproduct production in a chemical reaction is common and even if the reaction
is very strongly directed for a particular outcome, in all but the simplest
reactions, some byproducts are created. So,
you can view the amino acid substitutions as byproducts.
Whether the protein with the substitution is functionally
different than the desired product is unknown.
What we do know is that the LC-MS/MS can measure the error rate and that
process conditions affect the error rate. So if the error rate turns out to be
a critical quality attribute (CQA) of the protein that is the drug substance,
we can monitor it and control it.
Neither the deeper insight gained about misincorporation nor the
understanding of the ability to control the rate of amino acid substitution
would have occurred without the applied research of Dr. Yu’s team and the
advanced capabilities of the LC-MS/MS instruments.
Gaining that insight into how biology really works is the 21st
century equivalent of rocket science -
that’s why I love this meeting.
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