Design of ultrasensitive probes for human neutrophil
elastase through hybrid combinatorial substrate
Paulina Kasperkiewicza, Marcin Porebaa, Scott J. Snipasb, Heather Parkerc, Christine C. Winterbournc,
Guy S. Salvesenb,c,1, and Marcin Draga,b,1
aDivision of Bioorganic Chemistry, Faculty of Chemistry, Wroclaw University of Technology, Wroclaw 50-370, Poland;bProgram in Cell Death and Survival
Networks, Sanford-Burnham Medical Research Institute, La Jolla, CA 92024; andcCentre for Free Radical Research, Department of Pathology, University of
Otago Christchurch, Christchurch 8140, New Zealand
Edited* by Vishva M. Dixit, Genentech, San Francisco, CA, and approved January 15, 2014 (received for review October 1, 2013)
The exploration of protease substrate specificity is generally
restricted to naturally occurring amino acids, limiting the degree of
conformational space that can be surveyed. We substantially
enhanced this by incorporating 102 unnatural amino acids to
explore the S1–S4 pockets of human neutrophil elastase. This ap-
proach provides hybrid natural and unnatural amino acid sequen-
ces, and thus we termed it the Hybrid Combinatorial Substrate
Library. Library results were validated by the synthesis of individ-
ual tetrapeptide substrates, with the optimal substrate demon-
strating more than three orders of magnitude higher catalytic
efficiency than commonly used substrates of elastase. This optimal
substrate was converted to an activity-based probe that demon-
strated high selectivity and revealed the specific presence of active
elastase during the process of neutrophil extracellular trap forma-
tion. We propose that this approach can be successfully used for
any type of endopeptidase to deliver high activity and selectivity
in substrates and probes.
and cell cycle control being classic examples (1). Thus, mis-
regulation of proteolysis can be deleterious and accompanies
many human pathologies (2). The substrate specificity of pro-
teolytic enzymes is dictated by the sequence of their target
proteins, with proteinogenic (more frequently called natural)
amino acid sequences directing selectivity. Several methods have
been devised to define the optimal substrate specificity of pro-
teases; one of the most commonly used is the Positional Scan-
ning Substrate Combinatorial Library (PS-SCL) approach, in
which tetrapeptides coupled to fluorogenic leaving groups are
used to ascertain preferences (3–5). In this approach, only nat-
ural amino acids have previously been used, with the exception of
norleucine (used instead of methionine) (6, 7). Data obtained
using PS-SCL approaches have been used to design substrates,
inhibitors, or activity-based probes for several families of proteases
(3, 8, 9). However, restricting library design to natural amino acids
narrows the amount of chemical space that can be explored to
distinguish between closely related proteases of the same family.
To overcome these limitations, we designed a combinatorial
library of fluorogenic tetrapeptide substrates, exploring the pri-
mary specificity pockets of a protease [S1–S4 in the nomencla-
ture of Schechter and Berger (10) (Fig. 1)] by applying a pool of
102 unnatural amino acids (defined as those amino acids not
encoded in proteins) that are available in structurally different
forms. The power of this approach was demonstrated initially for
an individual fluorogenic substrates library screening of a family
of aminopeptidases (11). Using this approach, unnatural amino
acids were shown to be much better substrates in terms of
specificity and selectivity compared with natural ones (12, 13).
Demonstrating this in exopeptidases is relatively simple, as it only
includes screening of a single position. Endopeptidases provide a
greater challenge, as tetrapeptides are commonly used for sub-
strate specificity profiling, severely complicating the combinatorial
roteases play key roles in essentially all signaling pathways,
with infection and inflammation, apoptosis, blood clotting,
possibilities. Here we demonstrate a general approach for the syn-
thesis of combinatorial libraries containing unnatural amino acids,
with subsequent screening and analysis of large sublibraries. We
term this approach the Hybrid Combinatorial Substrate Library
(HyCoSuL). We demonstrate the utility of this approach in the
design of a highly selective substrate and activity-based probe.
As a target protease, we selected human neutrophil elastase
(EC 188.8.131.52) (NE), a serine protease restricted to neutrophil
azurophil granules (14). NE is released by neutrophils during
inflammation, and its function is generally thought to be to de-
grade host tissue and destroy bacteria. Extended tissue destruction
is deleterious, and NE is also involved in the development of
chronic obstructive pulmonary diseases and in nonsmall-cell lung
cancer progression (15). NE belongs to one of the most in-
vestigated protease families and has very broad substrate speci-
ficity (16). This enzyme does not efficiently process substrates
based on natural amino acids, and there are no selective activity-
based probes for investigating NE in situ or ex vivo. Using
HyCoSuL, we set out to obtain highly efficient and selective
substrates for NE and convert these to activity-based probes for
HyCoSuL Libraries Synthesis Strategy. Our objective was to develop
selective substrates and probes based on the core tetrapeptide
scaffold sequence Ala-Ala-Pro-Val commonly used for NE (17).
The exploration of protease substrate specificity is generally
restricted to naturally occurring amino acids, limiting the de-
gree of conformational space that can be surveyed. We sub-
stantially enhanced this by incorporating 102 unnatural amino
acids to explore the S1–S4 pockets of human neutrophil elas-
tase. This approach provides hybrid natural and unnatural
amino acid sequences, and thus we termed it the Hybrid
Combinatorial Substrate Library. Using this approach, we have
designed an extremely active substrate of NE and subsequently
converted it into an ultrasensitive activity-based probe for
imaging active elastase during the process of neutrophil ex-
tracellular trap formation. Our study could have a substantial
effect on the design of substrates, inhibitors, and probes for
Author contributions: P.K., G.S.S., and M.D. designed research; P.K., M.P., S.J.S., H.P., G.S.S.,
and M.D. performed research; H.P. and C.C.W. contributed new reagents/analytic tools; P.K.,
M.P., S.J.S., H.P., C.C.W., G.S.S., and M.D. analyzed data; and P.K., G.S.S., and M.D. wrote
The authors declare no conflict of interest.
*This Direct Submission article had a prearranged editor.
1To whom correspondence may be addressed. E-mail: email@example.com or
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| February 18, 2014
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Strategically, we explored the P2, P3, and P4 subsites preferences
and followed-up by defining optimal occupancy in the key P1
position. Because of its convenience in solid-phase synthesis,
7-amino-4-carbamoylmethyl coumarin (ACC) was selected as the
reporting fluorophore (18). To explore the S2, S3, and S4
pockets, we designed three sublibraries and fixed the P1 position
as Ala (substituting Val, the preferred natural amino acid in this
position, because of a problem with complete substitution to
ACC fluorophore as a result of steric hindrance). Each library
contained fixed P2, P3, or P4 components with a natural or
unnatural amino acid and two components with isokinetic mix-
tures of natural amino acids (cysteine was omitted, Met was
substituted with Nle). This approach guaranteed selection of the
optimal residue occupancy (Fig. 1).
Each sublibrary contained 120 wells, with each well corre-
sponding to the amino acid being profiled. In each well, there
was a mixture of tetrapeptides composed of Ala fixed at P1, with
one amino acid fixed in a defined position (P4, P3, or P2) and the
remaining two positions composed of an equimolar mixture of
19 × 19 (361) tetrapeptidic substrates (Fig. 1). Unnatural amino
acids were selected to cover a broad range of chemical space.
They differed by side chain character (alkaline, acidic, neutral,
hydrophilic, hydrophobic), size (small, big), shape (bulky, branched,
unbranched), or stereoselectivity (D-amino acids). The free N
terminus was capped with an acetyl group. All sublibraries were
synthesized using standard solid-phase peptide synthesis proto-
cols on a semiautomatic FlexChem synthesizer (SciGene).
Substrate Specificity Determination. Each of the P2, P3, and P4
sublibraries was screened at 50 μM final total substrate mixture
and 43 nM NE, and initial rates of substrate hydrolysis were
recorded as relative fluorescent units over time. The signals from
the two screens were combined and normalized by inclusion of at
least 3 reference substrate mixtures.
The preferred P2 substrate substituent is octahydro-1H-
indole-2-carboxylic acid (Oic), which is a Pro derivative with
an additional cyclohexyl ring (Fig. 2). The S2 subsite displays a
noticeable preference for bulky amino acid residues such as
Nle(O-Bzl), Lys(2-Cl-Z), Phe(3,4-F), dhPro, and hCit. Pro was
the best-recognized natural amino acid in P2, confirming a pre-
vious report (19).
In the P3 position, NE favored methionine dioxide [Met(O)2]
around five times more than Gln, which was the best-recognized
natural amino acid (Fig. 2). Methionine oxide was around five
times more weakly recognized compared with Met(O)2. Other
unnatural amino acids well-tolerated in the S3 pocket were
pentafluorinated phenylalanine and methyl, benzyl [Glu(O-Bzl)],
and cyclohexyl esters of glutamic acid. Several other natural and
unnatural amino acids were also recognized at P3.
Analysis of substrate specificity at the P4 position yields very
interesting observations. Hydrophobic unnatural amino acids with
very bulky side chains such as Bpa, Nle(O-Bzl), Oic, Glu(O-Bzl),
or Cha (Fig. 2) are preferred. However, hydrophilic (but also
bulky) Arg is the most preferred natural amino acid [around
60% activity of Glu(O-Bzl)]. Even better recognized is its de-
rivative ArgNO2. With the exception of some hydrolysis of D-Phg
at P2, D-amino acids were not selected at any position.
Preference in the P1 Position. To complete the definition of opti-
mal activity, we designed and screened a P1 library on the
scaffold of the commonly used tetrapeptidic sequence Ala-Ala-
Pro-Val (Fig. 1). In total, 45 individual substrate sequences with
the general formula Ac-Ala-Ala-Pro-P1-ACC (P1 is a natural or
unnatural amino acid) were synthesized using standard solid-
phase peptide synthesis, and each substrate was purified using
P1 substrate specificity analysis revealed that NE demon-
strates essentially exclusive selectivity for cleavage after small
aliphatic residues, primarily Val and Abu, with tolerance also for
Ala, Nva, Thr, and Ile (Fig. 2). Determination of second-order
rate constants (Table 1) demonstrates that the reference sub-
strate with Val in P1 is almost equal to Abu in terms of catalytic
efficiency and is around 5 times more active than with Ala.
Validation with Individual Tetrapeptide Sequences and Design of an
Optimal Substrate. To validate library screening data for each
sublibrary, we synthesized a selection of “good” and “bad” rep-
resentatives at each P2, P3, or P4 position and incorporated
them into the reference sequence Ac-Ala-Ala-Pro-Ala-ACC. All
individual sequences were synthesized by solid-phase methods,
and their experimental catalytic efficiency (kcat/Km) was de-
termined (SI Appendix, Tables S1, S2, and S3). The catalytic
rates confirmed the order of selectivity predicted in the library
screens, thereby validating the approach.
Finally, we selected the preferred P2, P3, and P4 substituents
recognized by NE and synthesized the optimal fluorogenic substrate
Ac-Nle(O-Bzl)-Met(O)2-Oic-Abu-ACC, containing the best un-
natural amino acid Abu in the P1 position (Fig. 3A). Determination
of catalytic efficiency revealed that this substrate is more than 7,000
times better hydrolyzed (kcat/Km= 4.79 × 107M−1·s−1) by NE than
the commonly used commercial peptide sequence based on the
Ala-Ala-Pro-Val specificity sequence (Ac-Ala-Ala-Pro-Val-ACC,
in our hands; kcat/Km= 5.81 × 103M−1·s−1) see also ref. 20.
screening, optimal substrate selection, and activ-
ity-based probe design. The substrate specificity of
NE, similar to that of many serine proteases, is
dominated by surface enzyme pockets (subsites
S4–S1) that occupy amino acid side chains P4–P1
(34). Preferred occupancy can be determined by
positional scanning of P4–P1 residues.
General scheme for HyCoSuL design,
Kasperkiewicz et al.PNAS
| February 18, 2014
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Selectivity of NE versus Proteinase 3. The most closely related
protease to NE is neutrophil proteinase 3 (PR3, also known as
myeloblastin), which is 54% identical, located primarily in neu-
trophils, and shares with NE a preference for Val in the P1 (21).
As a consequence, any attempt to devise specific substrates and
probes for the analysis of NE must take into account PR3. To
compare the two proteases, we obtained protease samples from
the same supplier, purified from normal human neutrophils,
determined their active site concentration by titration with 3,4-
dichloroisocoumarin to ensure equal and optimal protease ac-
tivity, and performed analysis with the optimal substrate Ac-Nle
(O-Bzl)-Met(O)2-Oic-Abu-ACC to determine kinetic parame-
ters. Because this substrate has a solubility limit of around 10 μM
in aqueous solution, we were limited to this concentration. In
addition, we shifted our assay buffer from a high-salt buffer (0.1 M
Hepes, 0.5 M NaCl at pH 7.5) used in library screening to a low-
structure Ac-P4-X-X-Ala-ACC, where P4 represents a natural or unnatural amino acid and X represents an isokinetic mixture of natural amino acids (Cys and
Met were omitted because of a problem with oxidation; Nle was used instead of Met). The P3 and P2 preferences were determined in a similar way. The P1
subsite preference was determined using individual substrate libraries of the general structure Ac-Ala-Ala-Pro-P1-ACC, where P1 is a natural or unnatural
amino acid. Abbreviated amino acid names (SI Appendix, Fig. S2) are shown on the x axis. The y axis displays the average relative activity expressed as
a percentage of the best amino acid. Error bars represent the SD (n = 3).
Preferences at the P4–P1 subsites of NE. The P4, subsite preference of NE was determined using combinatorial substrate libraries of the general
| www.pnas.org/cgi/doi/10.1073/pnas.1318548111 Kasperkiewicz et al.
salt buffer [50 mM Hepes, 0.1 M NaCl, 0.1% (vol/vol) Igepal
CA-630 (Sigma-Aldrich) at pH 7.4] in which we found PR3 and
NE to be optimally stable at 37 °C.
We readily observed substrate saturation with NE, but not
with PR3, and thus we were able to determine individual kcatand
Kmvalues for NE, but only the ratio kcat/Kmfor PR3 (SI Ap-
pendix, Fig. S1). The kcat/Kmvalue obtained for NE in low-salt
buffer was about fourfold higher than that obtained in high-salt
buffer, which is still in the same order of magnitude, More im-
portant, comparison of the kcat/Kmvalues (Table 2) demonstrates
that NE is 900-fold more efficient than PR3 in cleaving this
substrate. Moreover, the Kmfor NE is about 0.28 μM, whereas
for PR3 it must be above 10 μM, as we were unable to observe
deviation from linearity in the PR3 substrate velocity plot.
By way of validating the approach for developing optimal
substrates through HyCoSuL, we carried out a preliminary screen
using PR3 (SI Appendix, Fig. S3), which revealed an optimal sub-
strate Ac-Glu(O-Bzl)-Lys(Ac)-Hyp(Bzl)-Abu-ACC. This substrate
had a kcat/Kmof 7.9 × 104M−1·s−1and was 13-fold selective for
PR3 over NE. Further experiments would be required to enhance
the selectivity factor of substrates for PR3 compared with NE.
Design and Characteristics of Activity-Based Probes.The high degree
of selectivity of the optimal substrate Ac-Nle(O-Bzl)-Met(O)2-
Oic-Abu-ACC provides proof of concept that the peptidic
sequence recognition elements for NE can be used to convert
the optimal substrate to an activity-based probe for NE. This
compound was obtained using a mixed solid- and solution-
phase approach. First, we synthesized the tripeptidic sequence
Nle(O-Bzl)-Met(O)2-Oic, using chlorotrityl resin. The N terminus
of the peptide was first equipped with a polyethylene glycol linker
PEG (4), which was designed to improve solubility of the com-
pound and allow for separation of a biotin tag from the recog-
nition epitope. As an electrophilic warhead for the probe, we
selected a phosphonate,+H3N-Abu-PO3Ph2, which was obtained
according to the protocol described by Soroka and Goldeman
(22). Finally, biotin-PEG (4)-Nle(O-Bzl)-Met(O)2-Oic-COOH
was coupled to+H3N-Abu-PO3Ph2. After synthesis, Biotin-PEG
(4)-Nle(O-Bzl)-Met(O)2-Oic-Abu-PO3Ph2(Fig. 3B) was purified
using HPLC, and its identity was confirmed by mass spectrometry.
We determined the selectivity of PK101 for NE by calculating
apparent kobs(app)/I (second-order rate constants for inhibition)
under pseudo first-order conditions by varying probe concen-
trations at constant 10 μM optimal substrate concentration (23).
Because we had determined the Kmof the optimal substrate for
NE, we were able to calculate the exact kobs/I value for NE but
were only able to place an upper limit of the kobs/I value for PR3.
Comparison of the kobs/I values (Table 3) demonstrates that
PK101 inhibits NE 150-fold more rapidly than PR3, mirroring
the results with the optimal substrate.
Activity-Based Probe Labeling of NE. Armed with the information
that the probe-optimized PK101 inhibits NE at least 150-fold
more rapidly than PR3, we characterized the labeling by in-
cubating the probe with either NE or PR3 for 20 min at 37 °C in
low-salt buffer. We performed SDS/PAGE and dot blot analysis,
followed by transfer to nitrocellulose, visualizing protein with
fluorescent streptavidin (Fig. 4).
Each analysis revealed that the probe labels both NE and PR3,
with labeling of NE being more efficient. This is to be expected
from the calculated inhibition rates. We could have decreased
the incubation time to decrease PR3 binding, but this was not
practical, given the planned experiments with live neutrophils, so
we settled on 20 min incubation. Importantly, the competing
inhibitor MeOSuc-Ala-Ala-Pro-Val-CH2Cl almost completely
abrogated probe binding to NE, with almost no effect on PR3
binding under the conditions used. PK101 showed binding to
a pair of bands of ∼30 kDa in supernatants from neutrophils
treated to secrete granule contents, which would include NE
(Fig. 4D), indicating lack of off-target reactivity of the probe
under the conditions analyzed. These bands are typical of car-
bohydrate microheterogeneity of natural NE (24), and PK101
reactivity was largely competed by MeOSuc-Ala-Ala-Pro-Val-
CH2Cl, suggesting that the bands represent endogenous NE.
To test the specificity and utility of the biotinylated probe
PK101, we chose to examine the location and activity of NE in
neutrophil extracellular traps (NETs). These structures are
reported to neutralize pathogens via the action of antimicrobial
proteins bound to DNA that is extruded from neutrophils after
stimulation or pharmacologic treatment in a manner proposed to
be dependent on the activity of NE (25). NETs were formed
from freshly isolated human neutrophils on glass coverslips after
treatment with phorbol ester for 2.5 h at 37 °C in 5% (vol/vol)
CO2. Probe binding was detected by fluorescent streptavidin, and
general formula Ac-Ala-Ala-Pro-P1-ACC, where P1 is a natural or
unnatural amino acid selected for validation after library
Kinetic analysis of best tetrapeptide substrates of the
4920 ± 278
4892 ± 56
989 ± 36
Data represent the mean ± SD of three or more experiments.
PK101. (A) Optimal substrate. (B) Activity-based probe derived from the opti-
mal substrate. In the case of the probe PK101, enzyme inhibition is likely via
attack of the serine nucleophile on the phosphorous of the probe, with release
of a phenoxy group and formation of a highly stable, covalent intermediate
complex, as previously discussed for this type of electrophilic warhead (35).
Structure of the optimized NE substrate and activity-based probe
Comparison of specificity constants for NE and PR3,
Km, μMkcat/Km, M−1·s−1
4.79 (±0.12) × 107
5.4 (±0.1) × 104
Data represent the mean and SD of three or more experiments. ND, not
able to determine.
Kasperkiewicz et al.PNAS
| February 18, 2014
| vol. 111
| no. 7
NET formation was detected by propidium iodide (PI) staining
of extruded DNA (Fig. 5).
PK101 labeled material that was noticeably competed away
with MeOSuc-Ala-Ala-Pro-Val-CH2Cl, indicating that pro-
teolytic activity was present in punctate areas associated pri-
marily in a perinuclear location. These are likely to be azurophil
granules, the primary storage location of NE and PR3. NETs
also contain PR3, but in lower abundance than NE (26). Because
staining was substantially competed by MeOSuc-Ala-Ala-Pro-
Val-CH2Cl, the majority of staining was caused by NE. Under
the conditions used, although NET formation (revealed by
string-like PI staining) is readily apparent, very little active NE is
associated with the NETs. At first glance, this seems surprising,
as it has been shown that NE is extruded together with nuclear
material during NET formation (27). However, the advantage of
using an activity-based probe is that it reveals the location of
active, not just total, enzyme. Therefore, it appears NE associ-
ated with NETS is either not active in this location or is present
only in a very low amount in the two individuals examined.
Proteases define one of the largest groups of enzymes, and it has
proven difficult to selectively measure their activity in biological
samples because of the presence of multiple family members
with overlapping specificity (1, 19, 28). To overcome this prob-
lem, substantial effort has been exerted by many groups over the
years to understand the principles of recognition of natural and
artificial substrates and to leverage this information to produce
definitive diagnostic tools for in vivo and in vitro work. HyCoSuL
provides a powerful tool in this quest, as it is based on classic and
groundbreaking conventional positional scanning substrate li-
brary principles (6) but explores far more chemical space. Our
objective was to create the very best NE substrate, not the most
selective one. In doing so, we achieved the most sensitive sub-
strate yet reported for NE, with a specificity constant of 4.79 ×
107M−1·s−1, about 100-fold more sensitive than the previous
champion NE substrate Abz-Ala-Pro-Glu-Glu-Ile/Met-Arg-Arg-Gln-
EDDnp [a fluorescence-quenched peptide where Abz is ortho-
aminobenzoic acid and EDDnp is N-(2, 4-dinitrophenyl)ethylene-
diamine] (17). Interestingly, our optimal peptide has about the
same degree of selectivity for human NE as Abz-APEEI/MRRQ-
EDDnp. Importantly, our substrate can be converted to an ac-
tivity-based probe, whereas the former champion cannot. One
could imagine gaining even more selectivity for NE over PR3 by
screening for subsite preferences of PR3, using HyCoSuL, and
selecting ratio preferences that would substantially enhance the
current selectivity ratio of 150 described by our PK101 probe, al-
though this may take a hit in terms of absolute sensitivity for NE.
This strategy seems not to be needed in the case of NE and PR3 but
could become useful in situations in which more proteases with
with a range of PK101 concentrations, denatured in SDS sample buffer, and
analyzed by dot blot (A) or SDS/PAGE followed by transfer (B and C). One
sample was preincubated under the same conditions with 10 mM MeOSuc-
Ala-Ala-Pro-Val-CH2Cl for 30 min to decrease probe binding (first samples in
each column). (D) Supernatants from formyl-Met-Leu-Phe neutrophils were col-
lected by centrifugation and treated with the indicated concentrations of PK101.
Blots were developed with labeled streptavidin and imaged by fluorescence or
bioluminescence scanning, as described in SI Appendix, Materials and Methods.
Reactivity of PK101 with NE and PR3. Purified NE or PR3 was treated
PR3, using 10 μM Ac-Nle(O-Bzl)-Met(O)2-Oic-Abu-ACC as
Comparison of inhibition rate constants for NE and
kobs(app)/I [M−1·s−1]Km, μMkobs/I, M−1·s−1
3.9 (±0.1) x 105
9.3 × 104
1.4 (±0.1) × 107
9.3 × 104
Data represent the mean and SD of three or more experiments with the
exception of PR3, which was analyzed once.
was triggered with phorbol ester, followed by 20 min of treatment with
40 nM PK101. It was briefly washed, fixed, and incubated with fluorescent
streptavidin to visualize the probe, and PI was used to visualize DNA. (A) No
probe. (B) Probe added. (C) Samples treated with 10 mM MeOSuc-Ala-Ala-
Pro-Val-CH2Cl for 30 min before addition of probe. (A–C) Imaged using a 20×
objective; two overlaid images from the same experiment are seen in D and
E with a 40× objective. Representative images of 4 experiments using 2
different donors. NET formation is visible as PI-stained strings and dispersed
nuclear material, and PK101 labeling is visible as punctate staining associ-
ated with cellular material, but not with NETs. NETs treated with PK101 fol-
lowed by anti(NE) antiserum and imaged using a 40× objective are shown in F.
The total NE antigen parallels PI binding, demonstrating that NETS are deco-
rate with NE, but the overlaid image demonstrates than most of the NE on
NETs is not active but is concentrated in the cell-associated punctate structures.
Imaging of neutrophils and NETs treated with PK101. NET formation
| www.pnas.org/cgi/doi/10.1073/pnas.1318548111Kasperkiewicz et al.
overlapping specificities need to be deconvoluted (e.g., caspases Download full-text
The conversion from a HyCoSuL-derived optimal substrate to
an activity-based probe that preserves a similar ability to dis-
criminate between NE and PR3 as the parent substrate has
provided us with an important tool. With it we defined the lo-
cation of active NE during NET formation, revealing the utility
of this approach in dissecting biological events and as a potential
biomarker. As pointed out earlier, in the case of proteases, which
are usually stored in inactive forms until required, it is not the
presence of protein that defines a biological event, it is the
presence of active protein (29, 30). Thus, it comes as somewhat
of a surprise that active NE revealed by PK101 is largely absent
from NETs and is highly enriched in granular structures (Fig. 5 F
and G), whereas NE antigen itself is readily found in NETs (Fig.
5H; ref. 31) and is reported to be the most abundant nonhistone
protein present in NETs (26). Our data imply that NETs may be
decorated with inactive NE. A recent report suggests that NE
activity in NETs may vary considerably between donors (32), and
at this time, we have only imaged NETs from three donors, with
equivalent results. Not only is NE present on NETs but its activity
is required for chromatin decondensation, leading to NET for-
mation in response to phorbol ester and microbial stimuli (33).
Signaling leading to NET formation, however, is dependent on the
stimulus (25). PK101 provides an ideal tool to test the hypothesis
that NE is required for NET formation by these and other stimuli
in vitro and in vivo (33) and may form the basis of a sensitive and
selective biomarker for defining the role of NE and neutrophils in
innate immunity pathology.
Synthesis of the HyCoSuL library and individual substrates was carried out
using solid phase strategies. The activity-based probe was synthesized using
combined solid phase and solution phase strategies. Biochemical assays were
performed with purified natural enzymes, and in situ activity-based probe
labeling was carried out using freshly-isolated human donor neutrophils. For
additional information please see SI Appendix, Materials and Methods.
ACKNOWLEDGMENTS. The M.D. laboratory is supported by the Foundation
for Polish Science. The C.C.W. laboratory is supported by the Health Research
Council of New Zealand. The G.S.S. laboratory is supported by National
Institutes of Health Grants R01GM09040 and R01CA163743.
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| vol. 111
| no. 7