Download Substrate scope of the re-engineered enzyme, FucO D93

Substrate scope of the
re-engineered enzyme, FucO D93
Martin Friberg
Degree project in chemistry, Bachelor of science, 2015
Department of chemistry
Supervisor: Mikael Widersten
Abstract
In this report we take a deeper look at the engineered protein FucO D93
and its ability to efficiently catalyze the redox reactions of primary alcohols
and aldehydes. FucO is an enzyme native to E. coli where it catalyses the
reduction of lacaldehyde to (S )-1,2-propanediol. The D93 variant carries
a leucine to valine change at position 259, this mutation was introduced
to expand the substrate scope of the enzyme to include bulkier diols. It
was proven to work since the enzyme showed activity with 3-phenyl-(S )1,2-propanediol. In this study we examine the closely related compound
(S )-1-phenyl-1,2-ethanediol but find no activity. This further supports the
theory that the crowded active site of FucO is a major factor when it comes
to hindering the catalysis of bulkier substrates.
1
Contents
Abstract
1
Contents
2
1 Abbreviations
3
2 Introduction
2.1 Catalysis . . . . . . . .
2.2 Kinetics . . . . . . . .
2.3 Enzymes . . . . . . . .
2.4 Enzyme re-engineering
2.5 FucO . . . . . . . . . .
2.5.1 D93 . . . . . .
2.6 Aims . . . . . . . . . .
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3 Methods
3.1 Chemicals and reagents . . . . .
3.2 Expression . . . . . . . . . . . .
3.3 Purification . . . . . . . . . . .
3.4 Kinetic measurements . . . . .
3.5 Figure generation and software
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4 Results
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5 Discussion
16
References
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2
1
Abbreviations
Amp
FucO
IPTG
LA
OD600
NADH/NAD+
ON
SDS-PAGE
Wt
Ampicillin
Propane-1,2-diol oxidoreductase
Isopropyl β-D-1-thiogalactopyronoside
Lysogeny Agar
Optical density at 600 nm
Nicotinamide adenine dinucleotide
Over Night
Sodiumdodecylsulfate polyacrylamide gel electrophoresis
Wild type
3
2
Introduction
Environmental pollution is one of mankinds largest current problems. Though
it was ignored in the beginning, now many solutions are being proposed. One
such is the use of enzymes to make industrial production of chemicals safer
and more efficient. There are several properties of enzymes that makes them
interesting for use in large scale catalysis. First of all they are biodegradable
and easy to produce. Second they work in water solution, outside extreme pH
ranges and does not require the use of heavy metals. Last but not least enzymes are very specific, minimizing the need for protecting reactive groups
and even distinguishing between enantiomers. This said they seldom catalyze exactly the reactions that are interesting for the industry, thus a need
for custom designed enzymes arise. [7]
2.1
Catalysis
To fully grasp the potential of biocatalysis it is necessary to first go through
the basics of catalysis. Atkins and De Paulo [1] defines catalyst as follows
”A catalyst is a substance that accelerates a reaction but undergoes no net
chemical change”. This is done by lowering the activation energy of a reaction, either by stabilizing intermediates or by changing the reaction pathways
to avoid slow rate-limiting steps, see Fig 2.1. [1]
Catalysis is usually divided into two categories, homogeneous catalysis
and heterogeneous catalysis, depending on whether the catalyst is in the same
phase or not. For example the use of a strong acid to catalyse the formation
of an ester from a carboxylic acid and an alcohol would be homogeneous
catalysis since the reactants and the acid are all in solution. On the other
hand, the use of a metal to catalyze the hydrogenation of an alkene would
be heterogeneous catalysis since the alkene is in solution and the catalyst is
a solid surface to which the reactants, alkene and hydrogen, is adsorbed. [1]
It is important to note that even though the catalyst accelerates the
reaction it does not affect the equilibrium. Thus catalysis can never be used
to increase the amount of product obtained but only to decrease the time it
takes to obtain that product.
2.2
Kinetics
Kinetics is the study of reaction rates, the speed at which reactions proceed.
Usually defined as a product of the reactants to a power and a rate constant denoted k, Eq 1, the rate constant is specific for that reaction, at that
temperature and has to be experimentally determined.
4
Figure 1: This figure shows an energy coordination diagram for a hypothetical reaction with and without catalyst. As can be seen neither start nor finish
is affected by the catalyst but, the energy barrier in between is lowered.
v = k[A]a [B]b
(1)
The two most simple cases for this would be the 0th order reactions,
where the rate of the reaction is not dependent on any concentration, and
the 1st order reactions, where reaction rate is dependent on a single concentration raised to the power of 1. First order reactions are very simple to deal
with since they are linear, this is not the case for reactions of higher rates.
Therefore it is common to create a pseudo first order reaction when studying
reactions of higher order. By doing measurements with all reactants but one
in large excess the contribution of that chemical to the over all rate of the
reaction can be determined and if this process is repeated for all reactants
the rate law for the entire reaction can be approximated. To ensure that
5
depletion of reactants does not affect the reaction rate it is very common to
measure only the initial rate but with several different starting concentrations. This also allows the rate to be plotted as a function of concentrations
instead of time since start which is very helpful. [1]
That is the basics, but for reactions with several steps things quickly get a
bit complicated. To simplify these complex expressions something called the
steady-state approximation is used. The steady state approximation assumes
that after a short period of time the concentration of intermediates will stay
constant at a level where it is produced and consumed at the same rate. This
allows for considerable simplification of most reaction sequences. [1]
2.3
Enzymes
Enzymes are catalytically active proteins, they are not the only catalysts
within living things but by far the most common. The structural diversity
of enzymes allow them to catalyse a myriad of reactions as varied as the
fixation of atmospheric nitrogen into ammonia and the decomposition of
sugar to yield energy for our own cells. This in combination with the ability
of most enzymes to work well in water solutions, without strong acids or
bases, makes them powerful tools when looking for environmentally friendly
alternatives for mass production of chemicals. [9]
The catalytical part of a protein is called the active site. This is often
a pocket or fold in the enzyme where the microenvironment is strictly regulated. The amino acids that form the wall of the active site help to bind
the substrate and orient it correctly so that catalysis may take place. These
amino acids can also help with the catalysis by ensuring the pH is correct or
act as donors or acceptors for bonds or leaving groups. For some reactions
this is not enough, the enzyme needs some thing that helps it. This is called a
co-factor, some of the most common ones are NAD+ , NADH and a variation
of metal ions. [9]
Diving a bit deeper into the effect of structure, there are two models that
explain how the structure of the enzyme effect its catalytical efficiency and
selectivity. The first one is the ”lock and key” model, it was introduced in the
late 1800’s by Emil Fischer. His model states that if the enzyme is formed
so that the substrate fits perfectly then only the substrate will bind and be
catalysed. This model was considered good but there is a problem, if the
substrate fits perfectly into the enzyme there is nothing to help it transition
into the transition state and on to the product. Instead the idea was put forth
that the enzyme has some ability to bind the substrate but that the transition
state binds better. This would mean stabilization of the intermediate which
would lower the activation energy, thus catalysing the reaction. This is called
6
”induced fit” and is the leading theory at the moment. Together with the
effect of amino acid side chains in the active site the induced fit model forms
the current explanation of enzyme catalysis. [9]
The most common method to compare the efficiency of different enzymes
is through kinetic parameters, the most basic of which is the MichaelisMenten constant (Km ). The constant derives from the Michaelis-Menten
equation (Eq.2) where Vmax is the maximum rate at which the enzyme can
work, [S] is substrate concentration, Km the Michaelis-Menten constant, and
v0 the initial rate.
v0 =
Vmax [S]
Km + [S]
(2)
What Km really represent, is the substrate concentration at which the
enzyme works at half its theoretical maximum velocity, it is a measurement
of how well the enzyme binds the substrate. This is easy to measure and
calculate using initial rate experiments at different concentrations and plotting rate as a function of initial concentration to create a saturation curve.
Though Km is useful it describes only half the problem, for example an enzyme can bind the substrate so tightly that it loses activity. This is called
a substrate trap and though showing a very ”good” Km they will function
poorly as catalysts. To avoid this problem one can use kcat . The turnover
number, kcat , is a measure of how many molecules a single enzyme can catalyse per unit of time. This constant is more intuitive, but also tells only half
the story. Unlike Km it says nothing about how much substrate you need to
reach maximum velocity, it can be argued that this is not essential for the
industry since reactants can be supplied in large excess it is however very
relevant in biological systems or when reactants are expensive. To sum up
this duality kcat /Km is often used, this ratio will rise if the substrate binds
well (low Km ) or the enzyme catalyses the reaction well (high kcat ), thus
being an excellent tool to estimate the over all efficiency of an enzyme. [9]
2.4
Enzyme re-engineering
Since enzymes are not well enough understood to be designed from the ground
up another technique for making synthetic enzymes is needed. This is usually
done by picking an enzyme that catalyses a reaction very similar to the
desired reaction and subjecting it to rounds of alternating mutagenesis and
selection. Mutagenesis can be either random or semi-rational, meaning you
can allow random mutation at any position or allow random mutation at set
position. The later is more common since computer methods and structure
analysis is getting better, this allows for better predictions of which positions
7
will matter and thus the generation of non-functional can be minimized and
thus screening time can be shaved of. Screening is the second half of the cycle;
the generated library is tested for desirable properties, most often increased
activity for a new substrate, any promising clones are sequenced and are used
as parents for the next cycle. This process can then be repeated until the
analysed enzyme have achieved the desired properties. [4, 8]
2.5
FucO
Propane-1,2-diol oxidoreductase (FucO), is a native enzyme to E. coli where
it is involved in fermentation of unusual sugars such as L-fucose. FucO catalyses the reduction L-lactaldehyde into (S )-1,2-propanediol using an Fe(II)
ion and NADH as cofactors, which allows for regeneration of NAD+ . [2, 3, 6]
Structures that use zinc as a co-factor instead of iron have been published,
Fig 2, it is a homodimer where each subunit has a molecular mass of 41kD.
Figure 2: a)The entire FucO protein (generated from PDB file 1RRM), the
two monomers are coloured differently. b)Close up of a single monomer with
the co-factors shown in blue and orange
2.5.1
D93
D93 is an engineered variant of FucO constructed by [4], it contains a leucin
to valine substitution at position 259 (L259V), Fig 3. It was created in an
attempt to make FucO catalyse bulkier substrates, as can be seen in the
figure below the change from leucin to valine shortens the side chain of the
amino acid leaving more space in the active site. [4]
8
Figure 3: Left: The active site of the wild-type enzyme (generated from
PDB file 2BL4). Right: The active site of D93, computer-modelled from the
same structure of wild type enzyme. Position 259 is coloured orange in both
pictures.
2.6
Aims
The aims of this study was to further investigate the effect of the L259V mutation on the ability of FucO to accept bulkier substrates. The first substrate
to be investigated was (S )-1-phenyl-1,2-ethanediol and further investigations
were performed to explain the results of this first test.
9
3
Methods
3.1
Chemicals and reagents
The following substrates were used, purity in brackets. 1-Propanol (unknown), propionaldehyde (97%), phenylacetaldehyde (≥ 90%), 2-phenylethanol (≥ 99%), (S )-1,2-propanediol (96%), (S )-1-phenyl-1,2-ethanediol
(99%), (R)-1-phenyl-1,2-ethanediol (99%). Substrates were prepared as 2
M stock solutions in buffer (pH 7 phosphate buffer for aldehydes and pH 10
glycine-NaOH buffer for alcohols). Phenylacetaldehyde and 2-phenylethanol
were dissolved in acetonitrile instead, since they show lower solubility in water.
NADH and NAD+ were prepared from powder as 20 mM stock solution in
water. New stock was prepared each day since these molecules are unstable
if stored for prolonged time.
3.2
Expression
The E. coli strain XL1-Blue was used as host for expression. The protein
expression plasmid was pGTac:FucO-5H, it was prepared by Blikstad and
Widersten [3], it contains the FucO gene with an IPTG inducible promoter
and confers ampicillin resistance. The FucO gene also has C-terminal 5-His
tag for purification. Aliquots of 50 L competent cells were transformed with
2 L plasmid preparation ( 100 ng/ L) using electroporation, 12.5 kV/cm,
25 F. After electroporation the cells were removed from the electroporation
cuvette by suspension in 1 mL 2TY media. This mixture was then transferred
to a culture tube before incubation at 37
with shaking (200 rpm) for 1h.
The cells were diluted (100 , 10−2 , 10−4 , 10−6 ) and 100 L of each concentration
were plated on LA-plates with 100 g/mL Amp before incubation 37
over
night. Two single colonies were re-streaked on to either half of a new plate
and were left at 37
over night. The plate was then stored in the cold until
purification was started.
µ
µ
µ
µ
‰
µ
µ
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3.3
Purification
To start of purification a single colony was picked from a re-streaked plate
and inoculated into 2 mL 2TY media, grown at 37
with 200 rpm shaking
overnight. From this ON-culture, 350 L was transferred into an E-flask with
35 mL fresh 2TY + 100 g/mL Amp. This new subculture was incubated
at 30
with 200 rpm shaking over night.
‰
µ
µ
10
‰
To each of six 2-L E-flask was added the following: 0.5 L 2TY + 50
µg/mL Amp, 5 mL ON-culture, and FeCl to a final concentration of 100 µM.
These cultures were grown at 30 ‰ with 200 rpm shaking until OD = 0.4,
2
600
one E-flask was measured approximately every 30 min. When OD600 = 0.4
was reached, protein expression was induced by addition of IPTG to a final
concentration of 1 mM. The culture was left at 30
with 200 rpm shaking
overnight.
Cells were harvested by centrifugation at 4 , 3,825 g in a J-14 rotor,
for 15 min. The supernatant was discarded and the cells re-suspended in
just below 30 ml binding buffer (20 mM imidazole, 0.5 M NaCl, 20 mM
sodium-phosphate, pH 7.5) with added protease inhibitor cocktail (Roche).
The cells were then lysed using ultrasound (5·20 s pulses with 30 s pause in
between each pulse to avoid overheating). The cell lysate was transferred
into centrifuge tubes and cell debris was pelleted at 4 , 30,966 g for 30 min
in a JA20 rotor.
During centrifugation a nickel-IMAC column was prepared. Chelating
Sepharose was added to 2-3 cm in an empty PD-10 column and was washed
with at least 10 volumes of water. After this the beads were charged by addition of 0.1 M NiCl2 . This was repeated until flow-through kept its greenish
colour. The column was then washed with another 10 volumes of water.
After centrifugation the supernatant was collected and filtered through
two Kleenexr tissues into a 50 ml conical tube. The charged beads were
removed from the PD-10 column and were added to the same tube. This mix
was left for 45-60 in 4 , with mixing by inversion. The gel-sample mix was
then poured back onto the column and the flow-through was collected into
a clean conical tube. After this point, all eluent was collected manually as
1-1.5 mL fractions in Eppendorf tubes. Protein concentration was checked
using absorbance at 280 nm in a spectrophotometer. The column was washed
with binding buffer until no protein absorption was detected. The column
was then washed using wash buffer (60 mM imidazole, 0.5 M NaCl, 20 mM
sodium-phosphate, pH 7.5) until no protein was detected. Bound protein was
eluted in 6 fractions using elution buffer (300 mM imidazole, 0.5 M NaCl, 20
mM sodium-phosphate, pH 7.5) and the protein concentration was measured
for all fractions.
The elution fractions with the highest measured concentrations were pooled
to a total volume of 2.5 ml, this was called the Peak elution. The highest
remaining fractions were also pooled to a total volume of 2.5 and called Side
elution. These two fractions were desalted (one at a time) using a PD-10
column and 0.1 M phosphate buffer (pH = 7.4). For every wash step the
fraction with the highest absorbance was saved together with a sample from
‰
‰
‰
‰
11
the original flowthrough and the two elution samples.
SDS-PAGE was used to assess the purity of the elution fractions and to
check other fractions for loss of product. First a separation gel was cast (12
% (w/v) acrylamide, pH 8.8). It was left to polymerize for 30 min with a
layer of water on top to create an even edge and prevent drying. On top
of this gel was cast a stacking gel (4 % /w/v) acrylamide, pH 6.5) with a
10-well comb inserted into it. This was also left to set for 30 minutes. In
the meantime the samples and a protein size ladder were diluted in H2 O to a
final volume of 10 L and suitable concentrations. The samples were mixed
1:1 with loading dye and was heated at 95 for 5 min. After polymerization
and removal of the comb the wells were washed carefully with H2 O. The gel
was then put into the electrophoresis machine, buffer was added, and the
samples loaded. The gel was run at 200 V for 40 min.
The gel was put in staining solution (PhastaGelr Blue R) and microwaved until boiling, left with gentle stirring for 10 minutes. The staining
solution was removed and the procedure repeated thrice with destaining solution.
µ
3.4
‰
Kinetic measurements
Kinetic measurements were done for both the reduction of aldehyde and
the oxidation of alcohols, both reactions were measured using the change
of NADH at 340 nm in a spectrophotometer (UV-1700 PharmaSpec, Shimadzu). For the oxidation reaction 20 L NAD+ (20 mM), 20 L enzyme
solution, and substrate (1-20 L) was added to a final volume of 1 ml in pH
10 glycine-NaOH buffer in a 1 cm quartz cuvette. For the reduction reaction,
20 L NADH (20 mM), 20 L enzyme solution, and substrate (1-20 L) was
added to a final volume of 1 ml in pH 7 phosphate buffer in a 0.5 cm quartz
cuvette. Measurements were done over 1-2 min and in triplicates. Raw data
was obtained as ∆Abs/min and can be found in Appendix 1. The raw data
was transformed to s−1 by division with the extinction coefficient for NADH
( = 6.22mM−1 cm−1 ), 60 (converting minutes to seconds), and the enzyme
concentration (c = 20 M , described below) to give Vmax = kcat . Vmax , KM ,
and kcat /KM were calculated using SimFit programs mmfit and rffit.
Enzyme concentration was measured using a spectrum (400 nm-200 nm),
Protein absorbtion was calculated from the peak at 280 nm after being corrected for noise using the absorbance at 400 nm. This corrected value was
divided by the extinction coefficient of FucO ( = 41mM −1 cm−1 ) to give the
concentration of enzyme.
µ
µ
µ
µ
µ
µ
µ
12
3.5
Figure generation and software
All figures in this report are generated by the author. Imaging was done using
paint.NET by dotPDN LLC, protein images were generated using PyMOL
0.99rc6 (DeLano Scientific, LLC) and original files were imported using the
PDB loading service plug in. Molecular formulas were drawn using Marvin
sketch 15.5.18 (ChemAxon), saturation curves were done using simfit program simplot, Figure 4 is a photocopy of the SDS-PAGE gel and last of all
the entire report was written using LATEX.
4
Results
First the enzyme was purified using a nickel column. Two samples were
created, the first one by pooling the most concentrated elution fractions, the
second sample using the most concentrated fractions that remained after the
first pool. The first sample was named ”Peak elution” and the second ”Side
elution”, both samples were desalted and the concentration was checked at
280 nm using a spectrophotometer, Table 1.
Table 1: Concentration of pooled elution fraction
Sample
Peak elution
Side elution
Concentration (mM)
0.3122
0.0317
The purity was checked using SDS-PAGE, Fig 4. Both samples were
deemed pure and concentrated enough to use. The ”Side elution” was used
for all measurements since the more concentrated ”Peak elution” could be
sent for crystallization studies.
To start of the kinetic studies, the activity with 1-propanol was measured
to see if the enzyme was active and comparable to previous studies, Table
2. After this the substrates in Fig 5 were measured in turn. The choice of
alcohols are motivated in the discussion.
13
Figure 4: SDS-PAGE to test purity. The samples are 1) Flow-through 2) 1st
Fraction, 1st wash 3) 27th Fraction, 1st wash 4) 4th Fraction, 2nd wash L)
Protein size ladder 5) Side elution 6) Peak elution
Table 2: Kinetic properties of FucO for all measured substrates
Substrate
kcat
(s−1 )
Alcohols
1-Propanol
(S)-1,2-Propanediol
2-Phenylethanol
(S)-1-Phenyl-1,2Propanediol
(R)-1-Phenyl-1,2Propanediol
Aldehydes
Propionaldehyde
Phenylacetaldehyde
KM
(mM )
kcat /KM
(s−1 M −1 )
ref. kc at/KM
(s−1 M −1 )
0.58(3.5 · 10−2 )
7.7(2.0) 76(17)
110 [5]
0.63(8.5 · 10−2 )
32(14)
27(8.5)
77 [5]
2.4 · 10−3 (4.9 · 10−4 ) 11(4.5) 0.23(0.050) This work
NDA
NDA
NDA
This work
NDA
NDA
NDA
9.0(0.47)
SNR
5.6(1.1) 1700(270)
SNR
130(8.5)
This work
This work
13 [5]
After each value is given the Standard Error in parenthesis, NDA = No Detected Activity, SNR = Saturation
Not Reached
14
Figure 5: Tested substrates and their structural similarity. All substrates are
essentially mono- or 1,2-di-substituted ethanol or acetaldehyde derivatives.
At first no activity could be detected for 2-phenylethanol but a second try
was done using concentrated peak fraction and 5 min measuring time. Using
this new approach a saturation curve was done and all kinetic parameters
calculated.
In a continued effort to visualize the results of this study a thermodynamic
cycle was created by first calculating ∆∆G, using Eq. 3, for three of the
derivatives as compared to 1-propanol. And then plotting the information in
Fig. 6.
∆∆G = −RT ln
(kcat /Km )1−propanol
(kcat /Km )derivative
15
(3)
Figure 6: Thermodynamic cycle for 1-phenyl-S-2,3-propanediol. Numbers
given are ∆∆G as compared to 1-propanol.
5
Discussion
In the SDS-PAGE you can clearly see a band corresponding to FucO at
around 41 kD for both the peak and tail elution. There is also a rather
large band at the same height for the second wash (sample 4, Fig4). This
seem to indicate that the His tag does not bind as strongly to the matrix as
expected and that the protein is partly washed away at 60 mM imidazole.
It was already know that the protein binds poorer than usual which is the
reasoning behind using 60 mM imidazole instead of the usual 100 mM for
washing.
After the first trial using 1-propanol it was found that the activity of
the purified FucO was comparable to previously published data, Table 2.
Next were the 1-phenyl-1,2-ethanediols, these were the primary interest for
this study. They are interesting because the enzyme shows activity with 1phenyl-S-2,3-propanediol but is believed to suffer from structural restraints
in the active site. Since the phenyl ring of 1-phenyl-1,2-ethanediol can’t
rotate freely around the chiral coal it is believed to be bulkier and harder
to catalyse than the phenylpropanediol. This theory was further supported
since no activity was detected for either phenyldiol. After this discovery S1,2-propanediol was tested, this is the same alcohol with a methyl substituent
instead of the phenyl ring, activity was observed which suggests that this
reduction of size does indeed allow the substrate to catalyzed.
To further investigate the interplay of size and free rotation in 1-phenyl1,2-ethanediol catalysis, a close relative was investigated. 2-phenylethanol
16
lacks the secondary alcohol and thus the chiral center, this should allow the
phenyl ring to move more freely in the active site. Since it is know that
the corresponding aldehyde (Phenylaceticaldehyde) is catalyzed one would
expect the reverse reaction to also happen. This proved to be the case,
to visualize the interplay of the Phenyl ring and the secondary alcohol a
thermodynamic cycle was created (Fig 6). This figure tells us that the phenyl
ring causes an increase in ∆G that is more than twice the increase from
adding the secondary hydroxyl group, thus it seems that the phenyl ring is
the primary cause for the loss of activity.
It is however worth noting that 3-phenyl-(S )-1,2-propanediol is a substrate to the enzyme and this molecule carries a phenyl ring at the end just
like 1-phenyl-1,2-ethanediol. Why this is can not be explained by this study,
it is possible that the extra coal of the propane chain allows the molecule to
be arranged to fit into the active site. It would have been interesting to search
for activity with the aldehyde corresponding to (S )-1-phenyl-1,2-ethanediol
sice this activity is usually higher. However the chemical could not be found
at any company and thus could not be measured.
To investigate this deeper one would need to go on to computer modelling,
however finding out why something does not work is often more complicated
than finding out how it works. Docking studies might be used to get an
understanding of how the molecule fits, or rather does not fit in the active
site, one must however be somewhat careful since these methods are still a
bit primitive.
To sum up, a deeper investigation into the substrate scope of FucO D93
was conducted within this study. It was found that although activity for
3-phenyl-(S )-1,2-propanediol was confirmed in a previous study [5], (S )-1phenyl-1,2-ethanediol is not catalysed by the enzyme. The exact explanation
was not found but it is probable that it is due to the steric phenyl group not
fitting in the crowded active site of FucO.
17
References
[1] Peter Atkins and Julio De Paulo.
[2] L Baldom and J Aguliar. Metabolism of l-fucose and l-rhamnose in Exherichia coli : Aerobic-anaerobic regulation of l-lactaldehyde dissimilation. Journal of Bacteriology, 1988.
[3] Cecilia Blikstad and Mickael Widersten. Functional characterization of
stereospecific diol dehydrogenasse, fuco, from Escherichia coli : Substrate
specificity, ph dependence, kinetic isotope effects and influence of solvent
viscosity. Journal of Molecular Catalysis B: Enzymatic, 2010.
[4] Cecilia Blikstad, Kathe M. Dahlstrom, Tiina A. Salminen, and Mikael
Widersten. Stereoselective oxidation of aryl-substituted vicinal diols into
chiral α-hydroxy aldehydes by re-engineered propanediol oxidoreductase.
ACS Catalysis, 2013.
[5] Cecilia Blikstad, Kthe M. Dahlstrm, Tina A. Salminen, and Widersten
Widersten. Effects on substrate scope and selectivity in offspring to an
enzyme subjected to directed evolution. FEBS Journal, 2013.
[6] G. T. Cocks, J. Aguilar, and E. C. C. Lin. Evolution of l-1,2-propanediol
catabolism in Escherichia coli by recruitment of enzymes for l-fucose and
l-lactate metabolism. Journal of bacteriology, 1974.
[7] Maria Gavrilescu and Yusuf Chisti. Biotechnology-a sustainable alternative for chemical industry. Biotechnology Advances, 2005.
[8] Moore JC and Arnold FH. Directed evolution of a para-nitrobenzyl esterase for aqueous-organic solvents. Nature biotechnology, 1996.
[9] David L. Nelson and Michael M. Cox.
18
Appendix
1-Propanol
Saturation curve 1-propanol
0.70
0.60
v (1/s)
0.50
0.40
0.30
0.20
0.10
0.00
0.0
20.0
40.0
60.0
80.0
[S] (mM)
[S](mM)
2
2
2
5
5
5
10
10
10
20
20
20
40
40
40
60
60
1/s
0.048826962
0.1037572943
0.0793438133
0.1800494224
0.1739460522
0.1281707753
0.3448404192
0.3845123258
0.3723055853
0.5737168036
0.4699595093
0.4180808622
0.4913213052
0.5004763606
0.5004763606
0.6408538764
0.6622156723
19
100.0
120.0
60
80
80
80
120
120
120
0.5157347862
0.3845123258
0.4241842325
0.4760628796
0.460804454
0.4760628796
0.6011819698
20
(S)-1,2-Propanediol
Saturation curve (S)-1,2-propanediol
0.70
0.60
v (1/s)
0.50
0.40
0.30
0.20
0.10
0.00
0.0
50.0
100.0
[S] (mM)
[S](mM)
1
1
1
5
5
5
20
20
20
40
40
40
60
60
60
80
80
80
120
1/s
0.0305168513
0.0213617959
0.0213617959
0.1037572943
0.0671370728
0.1007056091
0.1281707753
0.1678426819
0.1800494224
0.3600988448
0.2685482911
0.2777033464
0.5004763606
0.3906156961
0.5493033226
0.5737168036
0.6347505061
0.5462516375
0.5737168036
21
150.0
200.0
120
120
160
160
160
0.631698821
0.4943729904
0.3845123258
0.36315053
0.3570471597
22
2-Phenylethanol
Saturation curve 2-phenylethanol
2.0
×10
-3
v (1/s)
1.5
1.0
0.5
0.0
0.0
5.0
10.0
[S] (mM)
[S](mM)
2
2
2
4
4
4
7.5
7.5
7.5
10
10
10
20
20
20
1/s
0.000329582
0.0003845123
0.000494373
0.0006042337
0.0003845123
0.000494373
0.0009338156
0.0007140943
0.0012084673
0.0015380493
0.001153537
0.0015380493
0.0017028403
0.0014281886
0.001318328
23
15.0
20.0
(S )1-Phenyl-1,2-propanediol
[S](mM)
40
40
40
40
10
10
10
10
2
2
2
δAbs/min
0.0007
0.0001
0.0019
0.0029
0.0011
0.0001
0.0012
0.0011
0.0020
0.0001
0.0014
(R)1-Phenyl-1,2-propanediol
[S](mM)
4
4
20
20
20
20
40
40
40
40
δAbs/min
0.0017
0.0005
0.0004
0.0084
0.0004
0.0003
0.0004
0.0002
0.0008
0.0016
24
Propionaldehyde
Saturation curve propionaldehyde
10.0
8.0
v (1/s)
6.0
4.0
2.0
0.0
0.0
10.0
20.0
30.0
40.0
[S] (mM)
[S](mM)
1
1
1
2.5
2.5
2.5
5
5
5
20
20
20
40
40
40
60
60
1/s
1.5014290818
1.2450875313
1.3183279743
2.4596582113
2.4840716923
2.404727879
4.0770513279
4.1258782899
3.9793974038
8.2517565797
7.4278015958
8.1541026557
7.2996308205
8.8804037156
8.7095093486
7.214183637
6.5489162796
25
50.0
60.0
Phenylacetaldehyde
[S](mM)
0.4
0.4
0.4
2
2
2
4
4
4
6
6
6
10
1/s
0.1892044778
0.1892044778
0.1098606645
0.3356853638
0.2441348101
0.2807550316
0.3295819936
0.4760628796
0.4394426581
0.5615100631
0.7995415029
0.7568179112
1.5746695248
26