In-situ generation of differential sensors that fingerprint kinases and the cellular response to their expression

Article abstract of DOI:10.1021/ja407397z

Mitogen-activated protein (MAP) kinases are responsible for many cellular functions, and their malfunction manifests itself in several human diseases. Usually, monitoring the phosphorylation states of MAP kinases in vitro requires the preparation and puri

Full text of DOI:10.1021/ja407397z

Article
pubs.acs.org/JACS
In-Situ Generation of Differential Sensors that Fingerprint Kinases
and the Cellular Response to Their Expression
Diana Zamora-Olivares,† Tamer S. Kaoud,‡,§ Kevin N. Dalby,*,‡ and Eric V. Anslyn*,†
†Department of Chemistry and Biochemistry and ‡Division of Medicinal Chemistry, The University of Texas at Austin, Austin, Texas
78712, United States
§Faculty of Pharmacy, Minia University, Minia, Egypt
S
* Supporting Information
ABSTRACT: Mitogen-activated protein (MAP) kinases are
responsible for many cellular functions, and their malfunction
manifests itself in several human diseases. Usually, monitoring
the phosphorylation states of MAP kinases in vitro requires the
preparation and purification of the proteins or Western
blotting. Herein, we report an array sensing approach for the
differentiation of MAP kinases and their phosphorylated
counterparts in vitro. This technique utilizes a library of
differential receptors created in situ containing peptides known
for affinity to MAP kinases, and a Zn(II)−dipicolylamine
complex that binds phosphate groups on proteins. An
indicator-displacement assay signals the binding of the individual receptors to the kinases, while chemometrics is used to
create a fingerprint for the kinases and their state of activity. For example, linear discriminant analysis correctly identified kinase
activity with a classification accuracy of 97.5% in vitro, while the cellular response to kinase expression was classified with 100%
accuracy.
Thr residues enhances the affinity of SOX with magnesium, and
as a result increases the fluorescence of SOX.14
INTRODUCTION
■
Protein phosphorylation is a pivotal post-translational mod-
ification that regulates intracellular signaling networks, gene
transcription, and cell growth in eukaryotic cells.1 The specific
phosphorylation of serine, threonine, and tyrosine residues
controls the enzymatic activity of a diverse range of kinases. For
example, the mitogen-activated protein (MAP) family of
kinases triggers key cell-signaling pathways, thus regulating a
variety of cellular responses, such as mitosis, cell differentiation,
the cell cycle, and apoptosis.2,3 Aberrant MAP kinase activity is
associated with human diseases, such as inflammatory response,
hematologic malignancies, and cancer.4,5 Of the MAP kinases,
several are associated with these disease states, including
extracellular signal-regulated kinases (ERK1/2), the c-Jun N-
terminal kinases (JNK1/2/3), and p38 MAPK α, β, γ, and δ.6
Simple and efficient protein phosphorylation detection
methods, as well as techniques to qualitatively assess cellular
changes in response to the phosphorylation, could serve as
tools to monitor cell status, kinase activity, and as screens for
potential inhibitors.2−6 While many approaches involve anti-
bodies and radioactivity-based assays,7 optical-based sensing
methods to detect phosphorylation events are advancing
rapidly.8−10 Efforts in this area have focused on the develop-
ment of receptors whose responses are sensitive, as well as
being functional in physiological environments.11,12 For
instance, the chelation-enhanced fluorescence strategy popu-
larized by Imperiali using a sulfonamido-oxine (SOX)
fluorophore is a leading approach.13 Phosphorylation of Ser/
Other groups are working to create supramolecular receptors
as kinase chemosensors.15,16 Hamachi and co-workers studied
chemosensor 1, which contains two units of zinc-dipicolylamine
Zn(DPA).17 In aqueous solution at neutral pH, the two
Zn(Dpa) moieties of 1 interact with various phosphopeptides
(Ka values ranging from 104 to 107 M−1),18 but not with their
nonphosphorylated counterparts. Additionally, the same group
designed a highly selective hybrid biosensor,19 where a similar
dinuclear zinc receptor was incorporated into the phosphopro-
tein binding site of M15C-WW mutant protein, allowing them
to monitor kinase-catalyzed phosphorylation.
While the Hamachi and Imperiali detection systems
selectively bind to and signal phosphorylation, it is necessary
to synthesize a different receptor to be selective for each
phosphorylated target. Further, in some cases it may be
desirable to characterize an overall change in cell signaling
pathways, and the detection of a specific phosphorylation event
is not necessarily indicative of other cellular changes. To avoid
the tedious process of developing individual highly selective
receptors, the use of differential sensing techniques has been
growing in the supramolecular chemistry field. This sensing
protocol exploits the interactions between target analytes and a
library of cross-reactive receptors to create a response pattern
Received: July 18, 2013
Published: August 30, 2013
© 2013 American Chemical Society
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that is unique for individual analytes, or different mixtures
thereof.20,21 Using this approach, one obtains a distinct
fingerprint of composite signals produced by the sensor
elements, allowing for discrimination of different challenging
analytes.22 Our group,23 and others,24−27 have used differential
sensing for the analysis of various pure peptides and proteins.
For example, we recently reported a pattern-based approach to
discriminate phosphorylated tripeptides. A library of cross-
reactive receptors was derived from a tris(2-pyridylmethyl)-
amine unit conjugated to guanidinium ligands and random
tripeptides (2). Five different tripeptides, three metals, and
three indicators led to 45 receptors, imparting cross-reactivity
to the array, allowing chemometric-based differentiation of the
targets.28 Hence, as the next step in extending differential
sensing to the detection of post-translational modifications, we
envisioned that differential sensing could also be used to
pattern protein phosphorylation events, and thereby fingerprint
kinases in vitro. Furthermore, we also sought to challenge the
methodology with a real-life test and examine its utility in
complex mixtures, specifically cell extracts. In cell extracts, the
technique would necessarily be responding to changes in
distributions of protein modifications that result from activating
a kinase pathway.
Figure 1. Structure of the receptor library components: 4, Bis-
Zn(DPA) receptor; 5, DTT; and designed peptides 6 and 7 with
cysteine residues used to generate our in situ created cross-reactive
array for the discrimination of MAP kinases.
two peptides with known affinities to the MAP kinases. For
example, ERK-2 phosphorylates the transcription factor Ets-1 at
Thr-38 with high specificity.34 Residues 31−35 (PVDAC) are
in close proximity to the phosphorylation site of Ets-1.35
Hence, the PVDAC sequence, when incorporated into a
receptor library, was expected to impart cross-reactivity
between ERK-2 and other kinases. In addition, continuing
with this design strategy, we followed the lead of Dalby, who
reported the modular peptide substrate Sub-F, which is
phosphorylated by ERK-2 when docking with the F-recruit-
ment site (FRS) of this enzyme.36 The KALIC peptide derives
from a linker that separates the C-terminal WXWP binding
motif from the MAP kinase phosphorylation site of sub-F
peptide. Therefore, such a linker is expected to bind but have
low specificity. Lastly, dithiothreitol (DTT) was envisioned as a
linker that would add to two different scaffolds (3), resulting in
oligomerization, such as dimers, trimers, or even larger
receptors. When mixtures of three equivalents of these four
components are added to 3, a mixture of receptors is created.
By varying which components are combined together in the
individual wells of a multiwell plate, each well contains a unique
set of receptors, thereby creating the diversity and cross-
reactivity needed in a differential sensing scheme simply by
mixing the components.
2. Determination of the Optimal Ratio of Fluorophore
to Receptor. For the creation of an optical-signaling protocol
that reports the binding of the suite of receptors to the kinases,
we turned to indicator displacement assays (IDAs). In an IDA,
the receptor interacts with the indicator through noncovalent
interactions, and the indicator is displaced from the receptor
when it is replaced by the analyte, inducing a signal
modulation.37 IDAs have several advantages when using
differential sensing: (1) fluorescent indicators can be easily
incorporated to impart optical signal changes, (2) they are
modular, meaning that different combinations of receptors and
RESULTS AND DISCUSSION
■
1. Design Criteria. To pattern kinases and cellular
responses to their activation we first considered the use of
library 2. However, the synthetic complexity of 2 is daunting,
and hence we set another goal, that of creating a general
method by which a suite of receptors could be generated simply
by mixing components in situ. The conjugate addition reaction
of thiols to different conjugate acceptors caught our attention
because of its recent use for drug discovery.29 The reaction,
which takes place rapidly in water at room temperature,30,31
involves the 1,4-addition of sulfhydryl groups to an enone. For
our purposes the differential receptor library was based on the
functionalization of 1,3,5-triacryloylhexahydro-1,3,5-triazine (3)
which has been shown by Son (eq 1), to be an attractive
conjugate acceptor scaffold for creating tripodal systems.32
To pursue our objectives, specific components of the tripodal
receptor library were chosen. First, we created component 4
(Figure 1). This compound carries a nucleophilic thiol for use
in eq 1, as well as Hamachi’s proven phosphate binding bis-
Zn(DPA) unit (the synthesis of 4 is described in detail in the
Supporting Information). Second, because our group has
previously shown that peptides provide differential binding
toward different analytes,33 we synthesized by SPPS techniques
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indicators are created simply by mixing, (3) the receptor-
indicator stoichiometries can be adjusted to optimize the
optical response and the threshold concentration for signal-
ing,38 and (4) one avoids the synthesis of several indicator-
linked receptors.39 To signal peptide and protein binding
events to our receptors, the coumarin-based indicator 8 was
chosen because of its high solubility under physiological
conditions, and previous binding studies with zinc coordination
compounds.40,41
Information) which determined the ratio of ZnR-10 to
indicator to be used in the following binding assays with
peptides and proteins.
3. Indicator Displacement Assay Using a Phosphory-
lated Peptide. To prove our principle for sensing protein
phosphorylation, we first targeted a specific phosphorylated
peptide. We synthesized sub-F peptide (YAEPLTPRILAKWE-
WPA), which is a substrate for ERK-2. The phosphorylation
conditions and characterization of sub-F peptide is described in
the Supporting Information. In our first IDA, we prepared a 1:2
receptor−indicator complex (ZnR-10:8) in aqueous solution at
pH = 7.4 (50 mM HEPES, 10 mM NaCl). Then, in separate
experiments fluorescent titrations between peptides with ZnR-
10−indicator complex were done. Individual solutions of 36.6
μM ZnR-10 and 100 μM 8 in HEPES buffer were titrated with
aliquots of 1.92 mM phosphorylated peptide solution and 1.92
mM nonphosphorylated peptide solution, which also contained
the receptor−indicator complex. Only the phosphorylated
peptide (Figure 4A) was able to displace the indicator, which
resulted in the restoration of the emission intensity at the λmax
of 8 (see Figure S4 Supporting Information).
To test our IDA strategy, and to probe for any differential
interactions of our general receptor design with phosphopro-
teins, receptor ZnR-10 was synthesized (Figure 2). This
Figure 2. Chemical structures of coumarin-based indicator 8 and bis-
Zn(DPA) chemosensors ZnR-9, ZnR-10, and ZnR-11.
Figure 4. Increase in the fluorescence intensity due to displacement of
the coumarin indicator. (A) Addition of sub-F phosphorylated peptide
(0−1.37 mM) to ZnR-10 (36.6 μM) and 8 (100 μM) in 50 mM
HEPES buffer, 10 mM NaCl pH = 7.4, λex = 347 nm. (B) Addition of
phosphorylated ERK-1 (0−3.8 μM) to ZnR-10 (36.6 μM) and 8 (100
μM) in 50 mM HEPES, 10 mM NaCl pH = 7.4, λex 347 nm.
receptor was used to model the behavior of all receptors in the
array; it carries two of the bis-Zn(DPA) units and one
underivatized site. First, fluorescence titrations in HEPES buffer
were performed to optimize the correct receptor-to-indicator
ratio. To study the binding of indicator 8 to ZnR-10, 750 μL of
100 μM 8 in HEPES buffer in a septum-capped glass cuvette
(Starna cells) was titrated with aliquots of at least 5 μL, using a
100 μL Hamilton microsyringe, of a solution of 250 μM ZnR-
10 and 100 μM 8 in HEPES buffer. The spectra at 357 to 644
nm were recorded after each addition with an excitation
wavelength of 347 nm. The fluorescence values at the
maximum wavelength (475 nm) were obtained after each
aliquot. The addition of receptor ZnR-10 into a solution of 8
resulted in a concentration-dependent quenching of the
fluorescence emission of 8 (Figure 3), and a 1:2 receptor−
indicator binding stoichiometry was found. The change in
fluorescent intensity at 475 nm was plotted against an
increasing concentration of host (see Figure S3B Supporting
4. In Vitro Differentiation of Active and Inactive MAP
Isoform Kinases. Because it was found that chemosensor
ZnR-10 can differentiate between phosphorylated and non-
phosphorylated peptides, we anticipated a similar distinction
between active and inactive kinases. In separate experiments,
phosphorylated ERK-1 and its inactive form were titrated into a
1:2 receptor−indicator complex solution. A significant increase
in the fluorescence intensity was observed upon the addition of
active ERK-1 (Figure 4B), compared with the nonphosphory-
lated analogue. The detection limit and limit of quantitation
were 14 2.3 nM and 46 7.5 nM of phosphorylated ERK-1,
respectively (see Supporting Information). Despite an increase
in the fluorescence intensity observed in both cases (see Figure
S5 Supporting Information), there was a large enough and
reproducible difference to encourage us to continue. Hence,
our third and final test prior to creating the array was to analyze
the response to a different MAP kinase. Starting with ERK-2, an
isoform of ERK-1 with 84% identity at the amino acid level,42
we found that the inactive ERK-2 induces a fluorescence
response similar to that of active ERK-2 (Figure S6 Supporting
Information). Although the response of this single receptor to
active and inactive ERK-2 are similar, the isotherms are
different from those of ERK-1, and potentially other receptors
that result from our in situ generated array would be able to
differentiate these two ERK-2 species. Hence, these preliminary
results showed that this single receptor−indicator system is not
Figure 3. The indicator is added to a solution of receptor ZnR-10, the
host−indicator complex is formed quenching the fluorescence
emission of 8. The addition of ZnR-10 (0−82 μM) to 8 (100 μM)
in 50 mM HEPES buffer, 10 mM NaCl pH = 7.4, λex = 347 nm.
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Figure 5. LDA score plots and loading plots of the response from the sensing array showing in vitro differentiation of active and inactive MAP
kinases. (A) LDA score plot and (B) loading plot of the fluorescence response pattern of phosphorylated MAP kinases (ERK-1, ERK-2, JNK-3, and
p38γ) at 4 μM concentration with 100% jack-knife analysis. (C) LDA score plot and (D) loading plot of the fluorescence response pattern of
○
△
phosphorylated ( ) and nonphosphorylated ( ) kinases (ERK-1, ERK-2, JNK-3, and p38γ) at 4 μM concentration with 93.5% jack-knife analysis.
Vectors on the loading plots represent individual host contribution on the array represented by host number.
only capable of distinguishing active and inactive kinases, but it
can also differentiate between close isoforms, and it led
credence to the notion that a series of such receptors may lead
to a reliable method to classify kinases and their active/inactive
forms.
(refer to Table S3 in the Supporting Information). Aliquots of
each host solution were loaded into a 384-well plate (32 μL
Costar black polystyrene microplate), followed by indicator
aliquots according to the number of bis-Zn(DPA) moieties
present in each receptor. The final concentrations of indicator
were 57 μM of 8 to hosts H1-4, 100 μM of 8 to hosts H5 and
H6, and 124 μM of 8 to host H7 in HEPES buffer. Finally,
respective aliquots of phosphorylated and nonphosphorylated
kinases ERK-1, ERK-2, JNK-3, and p38γ were added to each set
of host-indicator solutions, so that the final protein
concentrations were 4 μM (four replicates each).
Changes in the emission data at the λmax of 8 at pH = 7.4
(475 nm) for each ensemble of the sensor array upon addition
of each kinase were recorded using a microplate reader (Biotek
Synergy 2). The data generated (4 replicates × 7 hosts × 8
kinases) were analyzed with the program XLSTAT using linear
discriminant analysis (LDA). This chemometric analytical
technique simplifies the data set obtained from the sensing
array, allowing for differentiation and classification of the
response pattern. LDA maximizes the distance between analyte
groups while minimizing the distance within an analyte group.44
A series of LDA tests were set up with purified and single
proteins. First, using the four phosphorylated kinases (ERK-1,
ERK-2, JNK-3, and p38γ), the resulting score plot (Figure 5A)
shows excellent differentiation along the F1 and F2 axes, and
good clustering of the experimental replicates at the given
5. Sensing Ensemble Construction and Fingerprint of
MAP Kinases. To evaluate the ability of the in situ generated
cross-reactive receptors to discriminate ERK-1/2, JNK-3 and
p38γ kinases, we prepared a 384-well plate with receptor−
indicator combinations. To generate the sensing ensemble, bis-
(DPA) receptors R-9, R-10, and R-11 were synthesized (see
Supporting Information) and used to create seven different
combinations of hosts (see Table S3 in the Supporting
Information). Host H1 contains R-9 (57 μM); hosts H2 and
H3 contain receptor R-9 (57 μM) which was stirred separately
with one equivalent (per free vinyl group) of the correspondent
peptide PVDAC or KALIC (57 μM), and DTT (57 μM).
Hosts H4 and H5 contain receptor R-10 (39 μM) and Host H6
contains receptor R-10 (39 μM) and DTT (39 μM). Host H7
contains receptor R-11 (35 μM). The order of addition of each
of the reagents was important because of the known
coordination interactions between sulfhydryl groups and Zn2+
metal ions.43 Therefore, zinc nitrate was the last reagent added
in appropriate equivalents according to the number of DPA
moieties present in each receptor where the final concentration
was 114 μM, 155 μM, and 213 μM according to each host
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Figure 6. LDA score plots and loading plots of the response from the sensing array showing differentiation of HEK293T cell lysates with differing
kinase expression. (A,C) LDA score plots and (B,D) loading plots of the fluorescence response pattern of different sets of stimulated and untreated
HEK293T cell lysates with 100% jack-knife analysis: control lysate (CL), induced/overexpressed (ERK+), overexpressed (ERK-), JNK induced with
anisomycin (Ansio), ERK induction with EGF (EGF).
concentration. The active kinases are organized along the F1
axes by emission modulation of the sensing ensemble, where
isoform ERK-2 is located into the left quadrant and ERK-1 is
located into the right one. The kinases are classified into
respective sets with 100% accuracy according to a jack-knife
analysis.45 Next, using the same conditions we sought to test
the capability of our sensing ensemble to discriminate
phosphorylated and nonphosphorylated kinases (ERK-1,
ERK-2, JNK-3, and p38γ). Similar to the previous study, each
active and inactive kinase produced a distinctive fluorescence
pattern, but with a lower accuracy, 93.5% via a jack-knife
(Figure 5C). Although inactive p38γ overlaps with active ERK-
2, we can clearly distinguish that the active/inactive p38γ and
ERK-2 proteins are located on opposite sides of the left
quadrant. It is also observed that ERK-1/ERK-2 kinases, which
have very similar structures, are classified in opposite areas
along F1. Furthermore, the phosphorylated isoforms are
significantly differentiated from the nonphosphorylated ones,
and within themselves, along both F1 and F2 axes. Finally,
active and inactive JNK-3 kinases are clearly classified and
located on the top right quadrant. A general trend was found,
where the active kinases are located on the right side and the
inactive ones are located on the left side, except the ERK-2
isoform.
plot (Figure 5A,C). A loading plot can be generated along with
the LDA score plot, and it gives vectors that represent the host
contribution to the differentiation of the kinases (Figure 5B,D).
According to both loading plots, hosts H-1, H-5, H-6, and H-
7 which contain single receptors ZnR-9, ZnR-10, ZnR-10, with
DTT and ZnR-11 vary significantly in response to both active
and inactive kinases, whereas hosts H-2, H-3, and H-4 which
contain ZnR-9 with peptides and DTT did not contribute
significantly. This result suggests that different extents of bis-
Zn(DPA) moieties on the receptors are responsible to
maximize the differential binding between active and inactive
kinases.
6. Fingerprint of Cell Lysates with Different Cellular
Response. After the successful in vitro differentiation of
purified active and inactive kinases using LDA of the signals
from our array, we explored whether the system could be used
to differentiate kinase activity in a complex mixture. To prove
the discriminatory properties of our system, we assessed
whether the differential receptor library could differentiate
HEK293T cells that have differing kinase expression and
activity. Because our approach necessarily responds to all
phosphorylated proteins, the pattern that arises is a qualitative
differentiation of distributions of proteins that change due to a
specific profile of kinase activity. For example, differences in the
cell line generated by stimulation with anisomycin, epidermal
growth factor (EGF), and/or overexpression of ERK-1, would
all be reflective of changes resulting from activation of specific
It was found that the protein kinases located on the right side
of the score plot displaced indicator 8 in the array to a higher
extent than those kinases located on the left side of the score
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pathways. Anisomycin has been reported to activate both JNK
and p38 MAPK pathways,46 and EGF was reported to induce
ERK and to a lesser extent the JNK pathway.47
cell lysates in vitro at neutral aqueous conditions using
chemometric analysis. In this manner, a new pattern
recognition approach was derived to target this class of analyte.
The ability of this sensing ensemble to differentiate cells that
have been induced with different stimulants increases our
expectation for the ability of this array to differentiate between
different types of cells, such as cells from diseased and
nondiseased tissues or even cells from different organs.
Before array analysis, Western blot (WB) on lysates was
performed to confirm the anticipated changes in these kinases
(see Figure S12 Supporting Information). The WBs showed an
increased activation/phosphorylation of JNK and p38 in the
cells that were stimulated with anisomycin if compared to the
untreated ones (control cells). Further, the ERK activation/
phosphorylation pathway was confirmed to be increased in cells
stimulated with EGF when compared to the control. Two other
sets of lysates contained HEK293T cells that have ERK1-WT
overexpressed, while one of them was also stimulated with
EGF. WB analysis showed that overexpressed ERK-1 was
partially phosphorylated. However, induction of the cells with
EGF significantly increased its phosphorylation.
Cell lysate expression, purification, and activation, are
described in the Supporting Information. HEK293T cell lysates
were prepared in CytoBuster Protein Extraction Reagent
(EMD-Biosciences) after washing in PBS (Invitrogen). The
lysates were cleared by centrifugation, and ATP was washed
away using Amicon Ultra 0.5 mL Centrifugal Filters. Bradford
analysis (Bio-Rad) was used to measure the protein
concentration. Discrimination of cell lysates was obtained at
total protein concentration according to Supporting Informa-
tion, Table S4. For the detection, 6 μL of cell lysate was added
to the same sensing ensemble and same data analysis was
followed.
The LDA score plot (Figure 6A) of the fluorescence data
showed excellent differentiation between the cells overexpress-
ing ERK-1 (ERK-), cells overexpressing ERK-1 and induced by
EGF (ERK+), and control cells along the F1 and F2 axes, and
good clustering of the replicates. This result suggests that the
variation of the responses is dependent on protein and
phospho-protein identity. Furthermore, the LDA score plot
(Figure 6C) of the fluorescence data also showed excellent
discrimination of the cells that have ERK induced by EGF
(EGF), which are separated along the second principal
component (F2) from the cells that have JNK/p38 induced
by anisomycin, and separated from the control cells along the
first principal component (F1). This differentiation suggests
that the sensing array is able to detect subtle changes in
phosphoproteins when cells are stimulated with different
activators. These cell extracts are classified into respective sets
with 100% accuracy according to a jack-knife analysis. Another
general trend was found (Figure 6A,C), where the induced
and/or overexpressed cell lysates are located on the right side
of the score plot and the control lysates are located on the left
side.
ASSOCIATED CONTENT
* Supporting Information
■
S
Detail synthetic procedures, product characterization, and
experimental details. This material is available free of charge
via the Internet at http://pubs.acs.org.
AUTHOR INFORMATION
Corresponding Author
anslyn@austin.utexas.edu; kinases@me.com
■
Notes
The authors declare no competing financial interest.
ACKNOWLEDGMENTS
■
This work was supported by NSF Grant CHE-1212971 and the
Welch Foundation (F-1151) to Dr. Eric V. Anslyn. We also
acknowledge CONACYT fellowship 212537 to Diana Zamora-
Olivares. Tamer S. Kaoud is supported by a postdoctoral
trainee fellowship from Cancer Prevention Research Institute of
Texas (CPRIT). This research was also supported by the grants
from the Welch Foundation (F-1390) and NIH (GM059802
and CA167505) to Dr. Kevin Dalby.
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̈
NOTE ADDED AFTER ASAP PUBLICATION
■
Due to a production error, the fluorophore sulfonamido-oxine
(SOX) was misrepresented as -oxime. The corrected version
was reposted on September 20, 2013.
14820
dx.doi.org/10.1021/ja407397z | J. Am. Chem. Soc. 2013, 135, 14814−14820