High-performance liquid chromatography-based method to evaluate kinetics of glucosinolate hydrolysis by Sinapis alba myrosinase

Article abstract of DOI:10.1016/j.ab.2014.07.017

Isothiocyanates (ITCs) are one of several hydrolysis products of glucosinolates, plant secondary metabolites that are substrates for the thioglucohydrolase myrosinase. Recent pursuits toward the development of synthetic non-natural ITCs have consequently led to an exploration of generating these compounds from non-natural glucosinolate precursors. Evaluation of the myrosinase-dependent conversion of select non-natural glucosinolates to non-natural ITCs cannot be accomplished using established ultraviolet-visible (UV-Vis) spectroscopic methods. To overcome this limitation, an alternative high-performance liquid chromatography (HPLC)-based analytical approach was developed where initial reaction velocities were generated from nonlinear reaction progress curves. Validation of this HPLC method was accomplished through parallel evaluation of three glucosinolates with UV-Vis methodology. The results of this study demonstrate that kinetic data are consistent between both analytical methods and that the tested glucosinolates respond similarly to both Michaelis-Menten and specific activity analyses. Consequently, this work resulted in the complete kinetic characterization of three glucosinolates with Sinapis alba myrosinase, with results that were consistent with previous reports.

Full text of DOI:10.1016/j.ab.2014.07.017

Analytical Biochemistry 465 (2014) 105–113
Contents lists available at ScienceDirect
Analytical Biochemistry
journal homepage: www.elsevier.com/locate/yabio
High-performance liquid chromatography-based method to evaluate
kinetics of glucosinolate hydrolysis by Sinapis alba myrosinase
⇑
Kayla J. Vastenhout, Ruthellen H. Tornberg, Amanda L. Johnson, Michael W. Amolins, Jared R. Mays
Department of Chemistry, Augustana College, Sioux Falls, SD 57197, USA
a r t i c l e i n f o
a b s t r a c t
Article history:
Isothiocyanates (ITCs) are one of several hydrolysis products of glucosinolates, plant secondary metabolites
that are substrates for the thioglucohydrolase myrosinase. Recent pursuits toward the development of syn-
thetic non-natural ITCs have consequently led to an exploration of generating these compounds from non-
natural glucosinolate precursors. Evaluation of the myrosinase-dependent conversion of select non-natural
glucosinolates to non-natural ITCs cannot be accomplished using established ultraviolet–visible (UV–Vis)
spectroscopic methods. To overcome this limitation, an alternative high-performance liquid chromatogra-
phy (HPLC)-based analytical approach was developed where initial reaction velocities were generated from
nonlinear reaction progress curves. Validation of this HPLC method was accomplished through parallel
evaluation of three glucosinolates with UV–Vis methodology. The results of this study demonstrate that
kinetic data are consistent between both analytical methods and that the tested glucosinolates respond
similarly to both Michaelis–Menten and specific activity analyses. Consequently, this work resulted in
the complete kinetic characterization of three glucosinolates with Sinapis alba myrosinase, with results that
were consistent with previous reports.
Received 19 June 2014
Accepted 15 July 2014
Available online 25 July 2014
Keywords:
Glucosinolate
Isothiocyanate
Myrosinase
Michaelis–Menten
Progress curve
HPLC
Ó 2014 Elsevier Inc. All rights reserved.
Organic isothiocyanates (ITCs,1 3, Scheme 1) are a particularly
well-studied class of compounds that demonstrate several modes
of bioactivity relevant to improved human health. Many of the Bras-
sica vegetables—including broccoli, spinach, cabbage, cauliflower,
Brussels sprouts, kale, collard greens, pak choi, and kohlrabi—are rich
sources of ITCs with documented antioxidant [1–3], anti-inflamma-
tory [4–7], antibacterial [8–11], antifungal [12,13], and antitumor
[14–17] properties. The phytochemical origin of ITCs is dietary
glucosinolates (1), b-thioglucoside-N-hydroxysulfates biosynthe-
sized by plants from amino acids. More than 200 naturally occurring
glucosinolates have been identified, most of which are substrates of
the enzyme myrosinase (b-thioglucoside glucohydrolase, EC 3.2.3.1),
which is present in Brassica plants and whose mechanism follows
Michaelis–Menten kinetics [18]. Myrosinase catalyzes the hydrolysis
of the thioglucosidic linkage, evolving a molecule of D-glucose and an
unstable intermediate (2) that rapidly rearranges to a variety of
other organic functional groups [19]. At physiological pH and
temperature, 2 predominantly undergoes a Lossen rearrangement
to form an ITC (3) [19–21].
To maintain a consistent definition with non-natural ITCs, and
to differentiate between synthetic analogues of natural glucosino-
lates [22–24],
a
non-natural glucosinolate was defined as
a
b-thioglucoside-N-hydroxysulfate containing
a
side chain (R,
Scheme 1) not present in nature. Although select synthetic non-
natural ITCs have been shown to elicit improved activity profiles
versus their naturally occurring derivatives [25,26], few studies
have described the ability of non-natural glucosinolates to serve
as precursors for these non-natural ITCs. Investigators in a 2008
study hypothesized that myrosinase would be tolerant to the
structural changes of non-natural glucosinolates and would retain
its ability to hydrolyze their thioglucosidic linkages [26]. This
hypothesis was supported by results demonstrating that Sinapis
alba myrosinase catalyzed the hydrolysis of two non-natural gluc-
osinolates, resulting in evolution of their corresponding non-natu-
ral ITCs. More recently, a 2014 study described the hydrolysis
kinetics of five non-natural glucosinolates by S. alba myrosinase
[27].
⇑
Corresponding author. Fax: +1 605 274 4492.
E-mail address: jmays@augie.edu (J.R. Mays).
Abbreviations used: ITC, isothiocyanate; UV–Vis, ultraviolet–visible; CE, capillary
Analysis of the myrosinase-catalyzed conversion of glucosino-
lates to ITCs traditionally has been conducted via ultraviolet–visi-
ble (UV–Vis) spectroscopy [28]. This method has been sufficient
for most natural glucosinolate/ITC pairs, whose absorbance scales
1
electrophoresis; HPLC, high-performance liquid chromatography; NMR, nuclear
magnetic resonance; TFA, trifluoroacetic acid.
http://dx.doi.org/10.1016/j.ab.2014.07.017
0003-2697/Ó 2014 Elsevier Inc. All rights reserved.

106
Glucosinolate hydrolysis kinetics using HPLC method / K.J. Vastenhout et al. / Anal. Biochem. 465 (2014) 105–113
Scheme 1. Enzymatic conversion of glucosinolates to isothiocyanates by myrosinase.
linearly with aqueous concentration. A recent study by Nehmé and
coworkers described a novel method to assess myrosinase kinetics
using capillary electrophoresis (CE) [27]. In this approach, partially
(<10%) completed reactions were electrophoretically separated
and analyzed for the presence of sulfate ion, the inorganic product
from the Lossen rearrangement of 2. Although the CE method pro-
vides robust data and offers the advantages of decreased reaction
volume, reduced enzyme use, and rapid (ꢀ10 min) data acquisition
for a single reaction timepoint, it is dependent on sulfate ion pro-
duction, an indirect measure of hydrolysis. Consequently, for stud-
ies seeking to simultaneously, directly, and differentially analyze
glucosinolate, ITC, and other possible hydrolysis products (e.g.,
nitriles, thiocyanates), the scope of the CE approach may be limited
in preference of a method that directly detects each analyte of
interest [29].
Unfortunately, neither of the reported approaches accommo-
dates the evaluation of glucosinolate/ITC pairs with limited aque-
ous solubility, such as the non-natural ITCs evaluated by Mays
[29]. In that report, both ITCs demonstrated poor aqueous solubil-
ity, precluding analysis of their evolution from non-natural gluco-
sinolates using UV–Vis spectroscopy. To circumvent this unforseen
incompatibility, an alternative high-performance liquid chroma-
tography (HPLC)-based method was employed where all compo-
Fig.1. Target glucosinolates and isothiocyanates.
without fitting an appropriate curve generated via nonlinear
regression [32–35]. Given these limitations, optimization and val-
idation of the HPLC method would be required to strengthen its
general ability to analyze the hydrolysis kinetics of non-natural
glucosinolates that are not amenable to other methods.
The central hypothesis of this work was that an efficient HPLC
assay could be developed to analyze myrosinase kinetics through
direct and concurrent detection of both non-natural glucosinolates
and non-natural ITCs. Unlike many similar approaches, this
method would generate V0 values from nonlinear reaction progress
curves, increasing its ability to analyze reactions beyond early
timepoints (>10% completion) or at sub-saturating conditions. Val-
idation of this HPLC approach would be completed through parallel
analysis using the established UV–Vis spectroscopy protocol, a fea-
ture that would facilitate the direct comparison of kinetic data
across glucosinolate analogues and the methodologies used to ana-
lyze them.
To test this hypothesis, three glucosinolates (4–6; see Fig. 1)
were selected to demonstrate applicability with glucosinolates of
commercial and synthetic origin bearing both natural and non-nat-
ural side chains. In addition, to ensure compatibility in both HPLC
and UV–Vis spectroscopy analysis methods for the purpose of val-
idation, all glucosinolates and resultant ITCs were required to have
absorbance that scales linearly with analytical concentrations in
aqueous buffer [26,29]. Sinigrin (4) was a commercially available
natural glucosinolate that doubled as the standard to calibrate
the specific activity of myrosinase [28]. Phenyl glucosinolate (5)
was a synthetic non-natural glucosinolate; the hydrolysis kinetics
for 5 has not been documented previously. Lastly, glucotropaeolin
(6) was a synthetically prepared natural glucosinolate whose
kinetics has been described in several accounts [36,37]. This article
describes the development and validation of an HPLC method to
analyze myrosinase-catalyzed conversion of glucosinolates to ITCs
nents in
a myrosinase-catalyzed hydrolysis reaction were
solubilized with CH3CN, chromatographically separated, and quan-
tified using HPLC [26]. There are many examples describing the use
of HPLC to assess reaction kinetics [30,31]. These approaches pro-
vide discontinuous data, sampled at regular intervals, from which
analyte concentrations can be determined over time. Although
authors rarely elaborate on the details of how initial reaction
velocities (V0 values) are obtained, it appears that most accounts
generate velocities from linear regression of concentration versus
time data, commonly known as a reaction progress curve. Often,
restraints are placed on the total percent progress of the reaction
to maintain saturation kinetics and linearity of the reaction
progress curve [27].
Although the 2008 HPLC approach demonstrated the proof-of-
principle enzymatic conversion of non-natural glucosinolates to
non-natural ITCs, there were several aspects that devalue its gen-
eral utility [26]. Foremost, the solvent gradient and reequilibration
method were never optimized for rapid evaluation; each injection
required 1.5 h, and each reaction was conducted over 9 h. Over this
timeframe, significant ITC degradation was observed, limiting the
kinetic information that could be gained concerning the formation
of product. Consequently, the lengthy method, coupled with the
necessity to conduct replicate trials, led to analysis of only a single
initial concentration of substrate (glucosinolate) and enzyme
(myrosinase); the effects of variable substrate/enzyme concentra-
tion were not evaluated, precluding formal Michaelis–Menten
and specific activity analyses. Furthermore, all glucosinolates were
monitored at a single wavelength (227 nm); ideally, the use of a
diode array detector capable of simultaneously tracking several
discrete wavelengths should provide the opportunity to validate
kinetic data through standardization and analysis of several wave-
lengths in parallel. Lastly, and most critically, V0 values were esti-
mated from linear regression of nonlinear reaction progress curves
through
a parallel kinetic evaluation of three glucosinolate
substrates using HPLC and UV–Vis spectroscopy.
Materials and methods
General information
All reactions were carried out under nitrogen unless otherwise
indicated. All reagents were obtained from available commercial
sources and were used without further purification unless other-
wise noted. The silica gel used in flash chromatography was 60 Å

Glucosinolate hydrolysis kinetics using HPLC method / K.J. Vastenhout et al. / Anal. Biochem. 465 (2014) 105–113
107
and 230 to 400 mesh. Analytical thin-layer chromatography (TLC)
was performed on Uniplate 250- m silica gel plates with detection
ratio = 500.00, slope sensitivity = 0.751, peak width = 0.121, area
reject = 2.536, height reject = 0.176, and shoulders = off.
l
by UV light. Nuclear magnetic resonance (NMR) spectra were
acquired on a Jeol ECS-400 400-MHz NMR spectrometer with mul-
tinuclear capability and a 24-sample autosampler with solvent as
internal reference; the chemical shifts are reported in parts per
million (ppm) in d units. Infrared spectra were acquired on a Nico-
let Avatar Fourier transform infrared (FTIR) instrument. UV–Vis
spectroscopy experiments were conducted on a Shimadzu UV-
2450 spectrometer fitted with a TCC-240A temperature-controlled
cell chamber. HPLC experiments were conducted using an Agilent
1200 system with a degasser, photodiode array detector, and tem-
perature-controlled autosampler. High-resolution mass spectro-
scopic data were obtained at the Mass Spectrometry and
Analytical Proteomics Laboratory at the University of Kansas.
Regression analyses were completed using the GraphPad Prism 6
software suite.
HPLC kinetics assay
From standards of glucosinolates 4 to 6 and ITCs 7 to 9
(1000
lM in buffer A, 37 °C) were performed seven injection vol-
umes (1–100
ll) in triplicate. Standards were stabilized at 37 °C
in the autosampler for at least 15 min prior to injection; to main-
tain sample integrity, ITC standards were freshly prepared from
temperature-stabilized (37 °C) mixtures of buffer A and ITC stock
immediately prior to injection [26]. Chromatograms were cor-
rected for baseline drift through subtraction of a chromatogram
following injection of an equal volume of buffer A and were inde-
pendently analyzed at multiple wavelengths (4/7: 227, 235,
241 nm; 5/8: 235, 254, 265, 274 nm; 6/9: 227, 235, 241 nm). For
each compound, the baseline-corrected peak integration area
(mAU s) was linear between 0.25 and 12.50 nmol injected, with
linear correlation coefficients (r2) ranging from 0.9913 to 0.9997.
Hydrolysis reactions were performed in triplicate in an Agilent
screw cap vial. Each hydrolysis reaction contained glucosinolate
Preparation and characterization of ITCs and glucosinolates
The detailed experimental methods and spectral characteriza-
tion for glucosinolates 5 and 6 and ITCs 8 and 9 are provided as
supplementary data in the online supplementary material.
(1000–62.5 lM), myrosinase (4: 4.27 U; 5: 14.52 U; 6: 4.84 U),
and buffer A, with a total volume of 1.000 ml. Solutions of glucosin-
olate in buffer A were stabilized at 37 °C in the autosampler for at
least 15 min prior to the addition of enzyme. Reaction time was
measured from the addition of myrosinase to the times of injection
Calibration of myrosinase specific activity
The specific activity of commercial S. alba myrosinase (Sigma–
Aldrich, cat. no. T4528) was determined using the established
method [28]. Each final reaction mixture contained (À)-sinigrin
stock (10.0 mM in ddH2O, 50
in ddH2O, 0–6
A), with a total volume of 1.000 ml. Typical specific activity for
10 mg mlÀ1 myrosinase stock ranged from 0.5 to 1.1 U l À1
l
l), myrosinase stock (10 mg mlÀ1
ll), and 0.1 M phosphate buffer at pH 7.4 (buffer
l
.
UV–Vis kinetics assay
Molar absorptivities (MÀ1 cmÀ1) of each analyte between 200
and 300 nm were determined from concentrations ranging from
1000 to 1.95
(1000–3.91
l
M. Each hydrolysis reaction contained glucosinolate
l
M), myrosinase (4: 4.27 U; 5: 14.52 U; 6: 4.84 U), and
buffer A, with a total volume of 1.000 ml. Solutions of glucosinolate
in buffer A were stabilized at 37 °C in a 10-mm quartz cuvette for
15 min prior to the addition of enzyme. The absorbance was mon-
itored at a single wavelength (4: 227, 235, 241 nm; 5: 235, 254,
265, 274 nm; 6: 227, 235, 241 nm) for 5 min. Linear changes in
absorbance versus time were converted to initial reaction veloci-
Fig.2. Representative baseline-corrected HPLC chromatograms following injection
of
4 (retention time = 2.16 min) and 7 (retention time = 5.10 min) (235 nm).
Chromatogram insets are provided for clarity; retention times not directly shown
were baseline (<1 mAU). Chromatograms: (a) 12.5 nmol injected; (b) 8.75 nmol
injected; (c) 6.25 nmol injected; (d) 3.75 nmol injected; (e) 2.50 nmol injected; (f)
1.25 nmol injected; (g) 0.25 nmol injected.
ties (l
M minÀ1) using the difference in molar absorptivity between
a glucosinolate and its ITC (De
, MÀ1 cmÀ1).
General HPLC method
HPLC analysis was conducted with a Zorbax Eclipse XDB–C18
guard column (4.6 Â 12.5 mm, 5 M) and a Zorbax Eclipse XDB–
C18 analytical column (4.6 Â 150 mm, 5 M), both at 25 °C, with
l
l
a flow rate of 1 ml minÀ1 (ddH2O with 0.1% [v/v] trifluoroacetic
acid [TFA] at pump A; HPLC-grade CH3CN with 0.1% [v/v] TFA at
pump B). A linear gradient method was used: pre-run equilibra-
tion, 3.0% pump B; 0.00 min, 3.0% pump B; 3.00 min, 3.0% pump
B; 8.00 min, 97.0% pump B; 8.01 min, 3.0% pump B; 13.00 min,
3.0% pump B. The autosampler was maintained at 37 °C. Following
injection, the needle was washed with CH3CN. The photodiode
array detector used a 4-nm slit width and was autobalanced pre-
run and post-run. Integration events were automated with the fol-
lowing features: tangent skim mode = standard, tail peak skim
height ratio = 0.00, front peak skim height ratio = 0.00, skim valley
ratio = 20.00, baseline correction = classical, peak-to-valley
Fig.3. Representative HPLC chromatograms for the conversion of 4 ([4]0 = 250
l
M,
retention time = 2.16 min) to 7 (retention time = 5.10 min) with [4]0 = 250
lM and
[Myr] = 4.27 U mlÀ1 (235 nm). Chromatogram insets are provided for clarity;
retention times not directly shown were baseline (<1 mAU). Reaction time was
measured from the addition of myrosinase to the times of injection (10 ll).
Chromatograms: (a) t = 1.05 min; (b) t = 15.82 min; (c) t = 30.62 min; (d) t = 45.42
min; (e) t = 60.22 min; (f) t = 75.07 min.

108
Glucosinolate hydrolysis kinetics using HPLC method / K.J. Vastenhout et al. / Anal. Biochem. 465 (2014) 105–113
Fig.4. Representative HPLC-generated reaction progress curves for the conversion of glucosinolates to ITC at 37 °C (235 nm). The concentration of myrosinase was constant
for a given substrate (4: 4.27 U mlÀ1; 5: 14.52 U mlÀ1; 6: 4.84 U mlÀ1). Peak areas were used to determine [Gluc] and [ITC] at each timepoint, and the data (n = 3) were fitted
to a reaction progress curve using nonlinear regression. The dotted line denotes the sum of [Gluc] + [ITC] at each timepoint, and its slope represents ITC loss over time.
Reaction progress curves for each [Gluc]0 – wavelength combination are available as supplementary material. Panels: (A) [4]0 = 1000
[6]0 = 1000 M; (D) [4]0 = 250 M; (E) [5]0 = 250 M; (F) [6]0 = 250 M; (G) [4]0 = 62.5 M; (H) [5]0 = 62.5 M; (I) [6]0 = 62.5 M.
lM; (B) [5]0 = 1000 lM; (C)
l
l
l
l
l
l
l
(10
75.07 min.
Analyte concentrations were calculated from the standard
ll), which occurred at 1.05, 15.82, 30.62, 45.42, 60.22, and
Results and discussion
Myrosinase kinetics assay (UV–Vis)
curves and were used to fit reaction progress curves via nonlinear
regression in GraphPad Prism 6.0. Glucosinolate reaction progress
curves ([Gluc]t) were fitted to a temporal closed-form solution of
the Michaelis–Menten equation incorporating the Lambert W(x)
UV–Vis spectroscopy was used to confirm that the absorbance
of all analytes scaled linearly with concentration in aqueous buffer,
to determine the specific activity of myrosinase, and to evaluate
hydrolysis kinetics; these methods were based on established pro-
tocols, with minor alterations to accommodate congruency with
the HPLC assay [28]. The wavelengths selected for kinetic analysis
corresponded to either a glucosinolate kmax, an ITC kmax, an
absorbance shoulder common to all glucosinolates (235 nm), or a
standard aromatic absorbance (254 nm). The specific activity of
myrosinase was determined spectrophotometrically at 227 nm
using 4 as substrate [26,28]. To maintain consistency with past
ˇ
function (Golicnik’s Eq. 11) [38]; ITC reaction progress curves
ˇ
([ITC]t) were similarly fitted (Golicnik’s Eq. 7) [38]. Initial variable
values for nonlinear regression were [Gluc]0 = 500 M, Km
1.0 M, and Vmax = 8.0
M minÀ1. In GraphPad Prism 6.0, the first
l
=
l
l
derivative of each reaction progress curve was generated with
smoothing (four neighbors on each side, second-order polynomial),
and initial reaction velocities (V0 values) were obtained from this
curve at t = 0 min.
standardization methods,
De
227 = 6458 MÀ1 cmÀ1 was used to cal-
culate initial reaction velocities and one unit of myrosinase was
defined as the amount of enzyme able to hydrolyze 1 nmol of 4
per minute at pH 7.4 and 37 °C when the initial concentration of
Michaelis–Menten analysis
Velocity data generated by both UV–Vis and HPLC methods
were fitted to the Michaelis–Menten equation using nonlinear
regression in GraphPad Prism 6.0 [38]. Initial variable values for
4 ([4]0) was 250 lM [28].
Initial reaction velocities for the myrosinase-catalyzed conver-
sion of glucosinolates to ITCs were determined using a modifica-
tion of the established UV–Vis protocol [26,28]. Reaction
nonlinear regression were Km = 1.0 lM and Vmax = 1.0 l ;
M minÀ1
Km was restrained to ensure that the converged value was greater
than zero. Best-fit values for Km and Vmax were reported with cor-
relation coefficients (r2, range = 0.9588–0.9990).
velocities (V0 values,
absorbance versus time using the difference in the molar
l
M minÀ1) were calculated from plots of

Glucosinolate hydrolysis kinetics using HPLC method / K.J. Vastenhout et al. / Anal. Biochem. 465 (2014) 105–113
109
Fig.5. Enzyme dependence on HPLC reaction progress curves for [Gluc]t and [ITC]t at 37 °C ([Gluc]0 = 250 lM, 235 nm). Peak areas were used to determine [Gluc] and [ITC] at
each timepoint, and the data (n = 3) were fitted to a reaction progress curve using nonlinear regression. Progress curves for other wavelength–substrate combinations are
available as supplementary material. Panels: (A) [4]t; (B) [7]t; (C) [5]t; (D) [8]t; (E) [6]t; (F) [9]t.
absorptivity between ITC and glucosinolate (
D
e
=
e
(ITC) À e(glucosino-
data analysis was limited to glucosinolates and the ITCs, which
appeared to be the only detectable hydrolysis product.
late)); these velocities are available as supplementary material.
The V0 values were relatively consistent between wavelengths for
a given initial concentration of glucosinolate ([Gluc]0) and, as
expected, V0 values were proportional to [Gluc]0. A second set of
A challenge in developing an HPLC method to simultaneously
evaluate glucosinolates and ITCs was the diverse polarity of these
substances and finding a solvent gradient that provided resolution
with minimal compromise to efficiency. Maintaining an isocratic
polar mobile phase for 3 min provided sufficient resolution of gluc-
osinolates from the void volume, after which a gradient to nonpo-
lar mobile phase over 5 min resulted in elution of ITCs. Although a
steeper gradient would have decreased total time per injection,
inconsistent mixing of rapidly changing elution solvents had a neg-
ative impact on the ability to apply a consistent and reproducible
baseline correction. The described 8-min method provided repro-
ducible retention times for glucosinolates between 1.90 and
3.32 min and for ITCs between 5.12 and 5.73 min (Fig. 2); a 5-
min reequilibration of initial mobile phase and the unavoidable
autosampler–computer lag between injections kept the total time
per injection under 15 min, a significant improvement over previ-
ous HPLC methods [26]. Chromatograms generated throughout an
enzyme-catalyzed transformation provided the ability to observe
hydrolysis of glucosinolate and formation of ITC (Fig. 3).
kinetic studies was conducted with constant [Gluc]0 (250 lM)
using four relative concentrations of myrosinase [Myr]: 100, 67,
33, and 0% of a maximum (4: 3.33 U mlÀ1; 5: 14.52 U mlÀ1; 6:
4.84 U mlÀ1). These V0 data (see Table SD-3 in supplementary
material) were also proportional to [Myr]; in the absence of myro-
sinase, the V0 was minimal.
Myrosinase kinetics assay (HPLC)
Parallel kinetic analysis was conducted using a reverse-phase
HPLC method that incorporated several improvements over prior
HPLC methodology [26]. A distinct advantage of using HPLC to ana-
lyze reaction kinetics was its ability to chromatographically sepa-
rate reactant (glucosinolate) and product (ITC) and to
independently and directly quantify their concentrations versus
time. Early in method development, other low-percentage gluco-
sinolate hydrolysis products (e.g., nitrile, thiocyanates) and ITC-
derived amines (via hydrolysis) were analyzed using the HPLC
method with the expectation that they may be observed as minor
products during kinetic analysis (data not shown). Surprisingly,
peaks corresponding to these other potential products were not
observed in hydrolysis chromatograms; consequently, subsequent
Although linear regression directly provided V0 using UV–Vis
spectroscopy, HPLC-generated [Gluc]t and [ITC]t plots were nonlin-
ear and V0 values were determined through implementation of
reaction progress curves [32–34], where rates of glucosinolate
hydrolysis (
obtained from their slopes at t = 0 min (see Tables SD-5 and SD-6 in
D[Gluc] Dt D[ITC]obs Dt
À1) and ITC formation ( À1) were

110
Glucosinolate hydrolysis kinetics using HPLC method / K.J. Vastenhout et al. / Anal. Biochem. 465 (2014) 105–113
ˇ
employing the Lambert W(x) function (Golicnik’s Eq. 11) [38].
Representative progress curves monitored at 235 nm for the con-
version of 4 to 7, 5 to 8, and 6 to 9 are provided (Fig. 4); progress
curves for all other substrate/wavelength combinations are avail-
able as supplementary material. Reaction progress curves to
describe [ITC]t (Fig. 4, dashed lines) were generated using an alter-
ˇ
nate approximation of the Michaelis–Menten equation (Golicnik’s
Eq. 7) [38]. The W(x) approximation did not provide consistent
[ITC]t progress curves that fit the data, likely due to complications
arising from the competing rate of ITC loss (D[ITC]loss Dt
À1) [26].
Despite the reduction in total reaction time from 9 h [26] to
75 min, appreciable ITC loss was still observed; this effect was par-
ticularly noticeable at low [Gluc]0 where negative
D[ITC]obs D
tÀ1
were observed at reaction times following complete consumption
of glucosinolate. As documented previously, HPLC chromatograms
did not indicate the presence of any noticeable degradation prod-
ucts [21,39–41] and additional evidence toward rationalizing this
loss was not identified. To explore this phenomenon, the sum of
[Gluc] + [ITC] at each timepoint (Fig. 4, dotted lines) was calculated
as a representation of the detectable concentration balance of each
transformation. Given the 1:1 reaction stoichiometry, this sum
should equal [Gluc]0 at all points; however, this sum decreases
over time, representing a net rate of detectable ITC loss. Further
experimentation will be required to rationalize this observed loss
and will be reported in due course.
HPLC-monitored hydrolysis reactions were also conducted to
test the effect of [Myr] on V0 with regard to both
and [ITC]obs D
À1. To maintain consistency with the correspond-
ing UV–Vis spectroscopy experiments, substrate concentration was
constant ([Gluc]0 = 250 M) and the same relative array of [Myr]
D[Gluc] D
tÀ1
D
t
l
was used (100, 67, 33, and 0% of maximum; 4: 3.33 U mlÀ1; 5:
14.52 U mlÀ1; 6: 4.84 U mlÀ1). Representative progress curves at
235 nm are depicted in Fig. 5; progress curves for all other sub-
strate/wavelength combinations are available as supplementary
material. As before, both [Gluc]t and [ITC]t data demonstrate that
[Myr] was proportional to V0 (see supplementary material); in
the absence of myrosinase, the detectable [Gluc]t and [ITC]t did
not change over time.
Fig.6. Michaelis–Menten plots for V0 versus [Gluc]0 data from UV–Vis and HPLC
methods (37 °C, 235 nm). The concentration of myrosinase was constant for a given
substrate (4: 4.27 U mlÀ1; 5: 14.52 U mlÀ1; 6: 4.84 U mlÀ1). Michaelis–Menten plots
for other wavelength–substrate combinations are available as supplementary
material. Panels: (A) 4 to 7; (B) 5 to 8; (C) 6 to 9.
Comparison of UV–Vis and HPLC methods
supplementary material). Reaction progress curves to describe
[Gluc]t were generated using nonlinear regression with a closed-
Myrosinase follows the Michaelis–Menten mechanism [28],
where V0 is dependent on [Gluc]0, the Michaelis–Menten constant
(Km), and the maximum velocity (Vmax) [38]. Using nonlinear
ˇ
form solution of the Michaelis–Menten equation (Golicnik’s Eq. 3)
Table 1
Michaelis–Menten kinetic constants for the action of Sinapis alba myrosinase on glucosinolates.
Entry
k (nm)
Km
(
lM)
Vmax
(
l
M minÀ1
)
Vmax [Myr]À1 (minÀ1
)
Relative rate (%)
UV–Vis
HPLC
233 41
142
147 27
168 17
UV–Vis
HPLC
UV–Vis
HPLC
UV–Vis
HPLC
4 to 7
227
198 29
132 10
122 19
149 21
8.16 0.67
7.29 022
8.14 0.48
7.94 0.48
8.78 0.57
7.38 0.13
7.68 0.45
7.88 0.26
1.91a
1.71
1.91
1.86
2.06
1.73
1.80
1.85
100
89
100
97
108
90
94
235
241
Pooled
8
97
5 to 8
6 to 9
235
254
265
274
569 117
3185 3061
2070 329
1822 211
1709 302
1187 155
1136 115
1204 170
1108 120
1157 70
6.84 0.88
20.10 17.09
15.03 1.75
14.10 1.16
13.33 1.72
10.87 0.90
10.24 0.87
10.86 0.97
10.45 0.70
10.60 0.40
0.47
1.38
1.04
0.97
0.92
0.75
0.71
0.75
0.72
0.73
25
72
54
51
48
39
37
39
38
38
Pooled
227
235
241
Pooled
97.8 7.6
82.6 4.5
57.8 5.0
72.0 5.7
83.9 8.7
84.6 17.4
105.2 9.0
90.6 6.8
7.16 0.25
6.29 0.14
5.79 0.15
6.15 0.18
5.83 0.15
5.90 0.31
6.10 0.14
5.93 0.12
1.48
1.30
1.20
1.27
1.20
1.22
1.26
1.23
77
68
63
66
63
64
66
64
Note. Results were independently evaluated using both UV–Vis spectroscopy and HPLC methods at multiple wavelengths; regression analysis of pooled wavelength data for
each glucosinolate/ITC pair are also included. The Michaelis–Menten constant standard error (Km, lM) and maximum velocity standard error (Vmax, l
M minÀ1) are shown.
Calculated Vmax values were normalized to the concentration of myrosinase ([Myr], U mlÀ1) to yield normalized rate constants (minÀ1) and relative percentage rates versus 4
(UV–Vis, 227 nm).
a
Point of reference for the relative maximum rates of hydrolysis.

Glucosinolate hydrolysis kinetics using HPLC method / K.J. Vastenhout et al. / Anal. Biochem. 465 (2014) 105–113
111
Table 2
Specific activities (V0, minÀ1) for the hydrolysis of glucosinolates ([Gluc]0 = 250
lM) by Sinapis alba myrosinase determined in parallel using UV–Vis spectroscopy and HPLC
methods.
Entry
k (nm)
V0 [Myr]À1 (minÀ1
)
Relative specific activity (%)
UV–Vis
HPLC–[Gluc]t
HPLC–[ITC]t
UV–Vis
HPLC–[Gluc]t
HPLC–[ITC]t
4 to 7
227
235
241
0.94 0.04a
1.02 0.02
1.20 0.05
0.92 0.01
1.00 0.08
1.08 0.02
1.04 0.06
1.04 0.02
0.98 0.02
100
109
128
98
106
115
111
111
104
5 to 8
6 to 9
235
254
265
274
0.14 0.01
0.10 0.00
0.11 0.00
0.12 0.01
0.12 0.00
0.13 0.00
0.13 0.01
0.13 0.00
0.10 0.00
0.11 0.00
0.11 0.00
0.11 0.00
15
11
12
13
13
14
14
14
11
12
12
12
227
235
241
1.00 0.02
0.98 0.03
0.98 0.07
0.88 0.02
0.88 0.01
0.88 0.01
0.76 0.05
0.86 0.00
0.78 0.05
106
104
104
94
94
94
81
91
83
Note. HPLC data for [Gluc]t (HPLC–[Gluc]t) and [ITC]t (HPLC–[ITC]t) were independently tracked. Specific activities were normalized to the specific activity of 4 (UV–Vis,
227 nm).
a
Point of reference for relative specific activities at [Gluc]0 = 250 lM.
regression, Michaelis–Menten curves were independently gener-
ated for each wavelength–glucosinolate–method combination
[32]. Representative Michaelis–Menten plots for the hydrolysis of
4 to 6 (235 nm) generated from both UV–Vis and HPLC experi-
ments are depicted in Fig. 6; analogous plots for other wavelengths
are available as supplementary material. Despite the different lim-
its of sensitivity for the analytical range between UV–Vis spectros-
copy and HPLC, the Michaelis–Menten curves from the two
methods are consistent with one another; each Michaelis–Menten
directly compare the catalytic efficiency of substrates independent
of the differences in intrinsic activity for enzyme stocks that were
used. Unsurprisingly, 4 demonstrated a relative maximum velocity
of 89 to 108% versus itself as standard. Similarly, based on the more
consistent HPLC data, the catalytic rates of hydrolysis of 5 and 6
appear to be 37 to 39% and 63 to 66% the rate for 4, respectively;
previous accounts have described the relative maximum velocity
of 6 versus 4 as 34% [37] and 63% [36].
Analysis of specific activity plots allowed comparison of three
methods of detection: UV–Vis spectroscopy and HPLC (independent
V0 from both [Gluc]t and [ITC]t); representative plots conducted at
235 nm are depicted in Fig. 7. A linear correlation (r2 > 0.9884)
was observed between V0 and [Myr], including data derived from
curve was fit with
a high correlation coefficient (UV–Vis:
r2 > 0.9890; HPLC: r2 > 0.9588; see Table 2). Converged Km and Vmax
values across independently monitored wavelengths for a given
substrate were congruent; when independently–monitored wave-
length V0 and [Gluc]0 data were treated as separate trials, pooled
per substrate, and subjected to Michaelis–Menten analysis (see
supplementary material), a similar high correlation coefficient
(UV–Vis: r2 > 0.9716; HPLC: r2 > 0.9723) was observed. This com-
parison suggests that kinetic analysis of glucosinolates can be con-
[ITC]t whose observed velocities were affected
cific activities of each substrate ([Gluc]0 = 250
specific activities versus the standard ([4]0 = 250
D
l
[ITC]loss D
M) and normalized
M, 227 nm) are
t
À1. Spe-
l
provided in Table 2. Specific activities were consistent for each
glucosinolate across both the method of detection and the wave-
length monitored. Although a direct proportionality between nor-
malized specific activities and normalized maximum rates
(Table 1) was impossible due to the mathematical contributions
of Km, the normalized specific activities demonstrate similar rela-
tive velocity trends versus the normalized Vmax; normalized specific
activities of 4 were nearly 100% versus itself, those of 5 were
approximately an order of magnitude less than 4, and those of 6
were 60 to 80% lower compared with 4.
Both UV–Vis and HPLC methods of kinetic analysis offer advan-
tages and disadvantages with regard to each other. Advantages of
UV–Vis spectroscopy include its ease of use, the general availability
of analytical-grade instrumentation, and the rapid rate of data
acquisition. However, elucidation of kinetic parameters requires
either prior knowledge of the UV–Vis properties of all reactants
and products or purified samples for standardization; in cases
where the products are unknown, unavailable, or formed in a com-
plex mixture, accurate kinetic analysis would be limited. Further-
ducted at
a variety of wavelengths without compromising
experimental results, supporting the hypothesis that both analyti-
cal methods provide data of equivalent quality and precision.
These studies provided a complete comprehensive kinetic char-
acterization of glucosinolates 4 to 6 with S. alba myrosinase.
Although 4 has been used as a substrate for myrosinase in several
studies, variances in the organismal source of myrosinase, isozyme,
level of purity and the resultant effects on intrinsic activity, pH,
and temperature limit the ability for direct comparison with
known standard values [42]. In this study, the Km of 4 ranged from
122 to 233
alba) [26], 359
brassicae) [36]. For 5, the UV–Vis-derived Km showed greater vari-
ance (Km = 569–3185 M) and the HPLC data were much more
consistent (Km = 1108–1204 M); this study represents the first
documented Km for non-natural glucosinolate 5. Glucosinolate 6
demonstrated a Km range of 57 to 105 M, supportive of previous
accounts: Km = 161 M (B. brassicae) [37], Km = 520 M (B. brassi-
cae) [36], and Km = 125 M (S. alba) [27]. Structurally, the combina-
lM and was supportive of prior findings: 117
lM (S.
lM (Brevicoryne brassicae) [37], and 410
lM (B.
l
l
l
l
l
more, in relation to a key premise of this work, UV–Vis
l
spectroscopy might not be amenable for direct detection of gluco-
sinolate/ITC pairs whose absorbance does not scale linearly with
concentration in aqueous buffer. By comparison, advantages of
the HPLC approach lie in its ability to chromatographically sepa-
rate and independently evaluate substrates and products, its abil-
ity to incorporate elements of automation, and its ability to
accommodate glucosinolate/ITC systems with limited aqueous sol-
ubility. In contrast, limitations of the HPLC method may include
accessibility to instrumentation, increased cost of materials (e.g.,
elution solvents), and the length of time required to generate data;
tion of conformational flexibility in the side chain in 4 and 6 and
the reduced steric impact near the thiohydroximate may provide
lower Km versus the rigid phenyl group in 5.
Rather than determining kcat, which is heavily influenced by the
purity and intrinsic activity of enzyme, Vmax
(l
M minÀ1) was nor-
malized to [Myr], expressed in terms of its specific activity (U l À1
l
).
Because the specific activity of each enzyme stock was determined
prior to kinetic analysis and was based on a common standard
([4]0 = 250 lM, 227 nm), normalization provided the ability to

112
Glucosinolate hydrolysis kinetics using HPLC method / K.J. Vastenhout et al. / Anal. Biochem. 465 (2014) 105–113
continued use of the described HPLC kinetics approach for the
evaluation of glucosinolate hydrolysis.
Outside the realm of myrosinase kinetic evaluation, the broader
impact of this work lies both in the described HPLC method and the
application of nonlinear reaction progress curves to elucidate V0.
Using a multistep mobile phase gradient provides the opportunity
to reproducibly resolve analytes with varied physical properties
with moderate injection efficiency (ꢀ15 min per injection). At sub-
strate concentrations below enzyme saturation, HPLC reaction pro-
gress plots become increasingly nonlinear. Fitting this type of data
to an appropriate nonlinear curve, such as the solution to the
Michaelis–Menten equation used in this account, would provide
the flexibility to evaluate V0 under a wider array of experimental
conditions. Furthermore, as others have described [32,43], with
enough data points it may be feasible to calculate Michaelis–
Menten kinetic parameters directly from nonlinear analysis of a
single initial concentration of substrate, a feature that would
undoubtedly provide substantial time and cost savings when
evaluating enzyme kinetics.
Acknowledgments
This research was supported by an Institutional Development
Award (IDeA) from the National Institute of General Medical
Sciences of the National Institutes of Health under grant
P20GM103443. The content is solely the responsibility of the
authors and does not necessarily represent the official views of
the National Institutes of Health. This research was also supported
by the Sanford Program for Undergraduate Research. We extend
our thanks to Brandon Gustafson, the faculty and staff in the
Department of Chemistry at Augustana College, and the Mass
Spectrometry and Analytical Proteomics Laboratory at the
University of Kansas.
Appendix A. Supplementary data
Fig.7. Specific activity plots from UV–Vis and HPLC methods (37 °C, [Gluc]0 = 250 -
l
M). HPLC data for [Gluc]t (HPLC–[Gluc]t) and [ITC]t (HPLC–[ITC]t) were indepen-
Supplementary data associated with this article can be found, in
the online version, at http://dx.doi.org/10.1016/j.ab.2014.07.017.
dently tracked. Plots for other wavelength–substrate combinations are available as
supplementary material. Panels: (A) 4 to 7; (B) 5 to 8; (C) 6 to 9.
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throughout the 1350 min of automated instrument use (94% time
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