In the previous tutorial, we talked about the ways in which biotechnology is revolutionizing
the production of important materials like plastics. Instead of having to perform chemical
reactions in the traditional way, like we do in a laboratory, we can refer to a catalog of
enzymes, and select a series of enzymes that catalyze a sequence of chemical reactions
which will transform some readily available starting material, often plant-based,
into an industrial material of our choosing. We can then encode those enzymes in a plasmid,
insert the plasmid into an appropriate microorganism,
and allow it to express the genes that result in the enzymes of interest. With these enzymes now
present inside the microorganism, it will rapidly generate mass quantities of the desired product,
in a way that has more in common with brewing beer than with traditional chemical manufacturing.
As far as industrial processes go, it’s cheap, it’s environmentally friendly, it’s everything we
want in new technology. So now let’s get a little bit more specific. Let’s examine the production
of a particular compound that is currently being optimized, as well as the challenges associated
with this process and its optimization. As we know, petroleum, or crude oil,
is pumped from the ground and refined so as to isolate individual organic components.
Some of these components are used to synthesize materials like plastics.
One such component is methyl methacrylate, an alpha-beta unsaturated methyl ester, abbreviated
as MMA. This compound can undergo polymerization to generate polymethyl methacrylate, or PMMA,
which is a durable transparent plastic also known by brand names like Plexiglas, Acrylite,
and others, though we can generally refer to it as acrylic plastic. This is a useful material in that
it acts as a lightweight and shatter-resistant alternative to glass, as well as an additive in
acrylic paints. However, this method of producing PMMA is non-sustainable. Extraction of petroleum
from the ground is harmful to the environment, as is indicated by the 1.8 billion metric tons
of carbon dioxide emission due to plastics production in 2015. Also, oil in the ground will
eventually run out, meaning this process can’t be carried out indefinitely. So what is the solution?
One solution is being developed by a protein engineering company named Arzeda,
and I reached out to project lead Aaron Korkegian, who was gracious enough to fill me in on some of
the details. As it happens, there is a compound named alpha-methylene gamma-butyrolactone,
or MBL, also known as Tulipalin A. It is named as such because it is produced in tulips.
This compound has properties that are extremely similar to those of
MMA. Like MMA, it can polymerize to form PMBL, which is also a transparent plastic.
But unlike PMMA, PMBL is more thermal and scratch resistant, which makes it more durable than PMMA,
so this is a more desirable process. The only problem is that it is not a major product of
tulips. The amount of tulips that would have to be grown to then harvest and purify an
amount of Tulipalin A that would be industrially useful is not even remotely practical. However,
given our new technique utilizing enzymes, we should be able to find a biological approach to
synthesizing this compound ourselves. After all, tulips use enzymes to make it, so why can’t we?
Ok, so let’s get to work. As per the scheme we outlined in the previous tutorial,
we can start with some biologically-derived sugars that are found in plants. Then we select
a fermentation host, which is some microorganism like yeast or a bacterial species. Then we have to
engineer a metabolic pathway. We need some number of enzyme-catalyzed reactions which will transform
that sugar, or more likely some metabolite the organism naturally generates from the sugar,
into mass quantities of Tulipalin A, which we can then purify and polymerize to make our plastics.
As we mentioned, these enzymes do not need to be native to this microorganism. They can
be any enzymes from any biological species, which can be referred to as source organisms.
In fact, they don’t even have to exist in nature at all, completely novel enzymes can be designed.
They just have to do the chemistry we are looking for, because we can insert the genes
that encode these enzymes into the host organism via a plasmid, and it will make those enzymes,
thereby promoting the relevant chemistry. Now of course, this task should not be portrayed
as trivial. In fact, it represents the bulk of the challenge. What is the sequence of enzymes
that will be successful? Finding the answer to this question would have been near-impossible just
a few decades ago. But thanks to advancements in computer science, many new avenues have opened up
for solving such a problem. Recent developments in computation have allowed us to take massive
enzyme databases and combine them with efficient algorithms which can search and identify potential
enzymatic pathways from any starting material to any potential product. It should be made clear
that although enzymes tend to have a highly specific substrate within biological systems,
when removed from their typical role in biosynthesis, they can technically operate on a
variety of molecules. Anything that fits into the active site and promotes the achievement of the
transition state for the enzymatic reaction will be a suitable substrate. This means that slight
structural variants of the natural substrate may be totally viable. For example, say there is an
enzyme class that is known to operate on phenol. It may be the case that some enzymes within that
class work just as well on 2-methylphenol, as it is possible that when inserting into the active
site, this additional methyl group can point outwards and not interfere with the chemistry.
By testing a wide variety of enzymes within that class, we may find some that function
on 2-methylphenol, even though they are only documented as working on phenol.
Therefore, this adds an element of testing for the researcher, as if we are set on this compound as
an intermediate in our pathway, we may need to screen a multitude of enzymes that are known to
operate on phenol and see how they work with this slightly altered substrate. For some of them the
methyl group will clash in the active site and it won’t work. For others there will be plenty
of space, and the reaction will proceed without a problem. Such an enzyme can be described as being
“promiscuous” between the substrates. Now imagine the multitude of potential
intermediates, and the ways in which they could resemble a known enzymatic substrate or another.
The reality of the matter is that it will almost never be the case that each intermediate in some
desired pathway lines up flawlessly with the precise structures that are documented as
known substrates for enzymes in a catalog. We just need them to be close enough that
the chemistry may work the same way. So when building the pathway, for each step,
it may be necessary to select hundreds or even thousands of different enzymes that each carry
out the transformation you are looking for, but on a substrate that is similar to what you’ve got.
Again, say we have 2-methylphenol. Enzymes that are documented to promote the desired reaction
on phenol could be tested, as could any number of other untested proteins with sequence identities
close to these known ones. Or perhaps activity on 2-methylphenol is also documented for a particular
enzyme, but the activity is poor. Then perhaps the structure of the enzyme can be modified,
again driven by computational design. We can model the active site and predict where that
additional methyl group must be sitting, such that it interferes with the activity.
Perhaps we can see that there is a bit of space for the methyl group, but one amino
acid in particular seems to be getting in the way, perhaps due to a bulky side chain. We can
swap that residue out for a different one with a smaller side chain, and this singular modification
may result in a hundred-fold better reactivity. In fact, such modifications may result in the
enzyme preferring the novel substrate over the native one. And it doesn’t have to be just
one residue. Our developing understanding of protein structure and function relationships
also allows for more aggressive designs that change twenty to thirty residues at once,
thereby significantly influencing enzyme activity, selectivity, and expression.
So as you can see, designing the pathway is a mountain of work. The possibilities
are staggering, given how many enzymes there are, and the wide range of substrates they
could potentially act upon, particularly once enzyme modification is taken into account.
But one way or another, the pathway is planned with specific reactions in mind,
like for example, the reduction of an aldehyde to an alcohol. For each step, some number of enzymes
which perform that reaction on substrates similar to yours are screened meticulously, and options
that work for each step are either identified or designed. This process continues until the whole
pathway is covered. Pathways with fewer steps are preferred, and once a pathway is selected,
each enzyme is tested individually to ensure that it can perform the transformation intended for it.
To confirm their activity, the enzymes first have to be generated. This entails identifying
DNA sequences that encode each enzyme, and then optimizing them for expression within the host
organism. There are many ways we can do this, and one example involves codon-optimizing for
the intended host organism, like perhaps E. coli. What this means is that since multiple codons can
code for the same amino acid residue, as we recall from learning about transcription and translation,
there is significant variability that is possible in the DNA sequence without altering the resulting
protein. But certain sequences may be preferential over others in a particular host organism for
subtle reasons, such as the ratios of specific tRNA production in that host. Essentially,
in a particular organism, some codons are used frequently, and some very infrequently.
So if introducing a gene that contains many instances of the codons that are almost never
used, the necessary tRNA molecules may not be available and gene expression becomes difficult.
Once this is finalized, each enzyme can then be individually expressed and purified,
and the desired reaction is tested in vitro to confirm that the intended chemistry is occurring.
Thousands of different variants of a given enzyme or enzyme expression system can be
screened all at once in massive screening sets so that quantitative data on their ability to
promote the desired reaction can be gathered quickly and efficiently. Once enzymes have been
identified that can conduct the desired series of reactions, their properties can be further
optimized by computational design. This entails using computers to get ideas about how we might be
able to modify an enzyme so as to improve reaction rates, stability at a certain temperature,
binding affinity, or selectivity. In other words, we can use our growing
knowledge of the relationship between enzyme structure and function to tweak the enzymes
so as to improve their activity on the desired substrate, and therefore their ability to generate
the desired product. These novel designs can again be converted into corresponding DNA sequences
for expression and testing, and this process can be repeated, with further refinement each time.
Once the activity of the complete enzymatic pathway is confirmed in vitro, their genes can be
assembled together on an operon, and transformed into the manufacturing host for further testing.
What this means is that because the genes are part of the same operon, all the enzymes
will be expressed by the microorganism at once, in a singular act of transcription.
After the initial test, further refinement and iteration will typically be required to tune
the expression of each enzyme in the context of the overall efficiency of the pathway.
This could involve modifying the individual ribosomal binding site sequences in front of each
enzyme sequence in order to adjust the translation initiation rate separately for each enzyme, so as
to modify the relative rates of enzyme production. Additional work may also be required to engineer
the host organism to better push carbon flow into the desired product and away from other existing
metabolic processes to increase the yield of the target. Once the numbers look good, scale up can
occur sequentially with further refinement, until in the long run, the large-scale process
just looks pretty much like a vat of beer brewing, and is essentially just as simple to execute.
Though this technology is in its budding stages, it promises to completely change the way
entire industries operate. Whether aiming for a target molecule like Tulipalin A or any other,
the better these designer organisms become, the closer we can get to supplanting current
manufacturing techniques, thereby leading to more diverse products that can be produced
not only cheaply and efficiently, but from simple plant-based starting materials which
are grown from nothing but sunlight, water, and air. Any reaction can be run in the same vat
with precisely the same materials, all that changes is the specific engineered microorganism
that is employed. This means we don’t need a variety of expensive industrial machinery,
there are no significant reagent expenses, nor any reagent waste. Scaling up in this case just means
buying a bigger vat. And again, the whole process is carbon-capturing,
or at the very least carbon-neutral, rather than carbon-releasing. It’s as clean and sustainable as
manufacturing can get, and with companies like Arzeda leading the way, it’s only a matter of
time before we begin to see the societal ramifications of these daring innovations.