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Redirecting cell-type specific cytokine responses with
engineered interleukin-4 superkines
Ilkka S. Junttila1,*,4,5, Remi J. Creusot2,*, Ignacio Moraga3,*, Darren L. Bates3,*, Michael T.
Wong2, Michael N. Alonso6, Megan M. Suhoski6, Patrick Lupardus3, Martin Meier-
Schellersheim7, Edgar G. Engleman6, Paul J. Utz2, C. Garrison Fathman2, William E. Paul1,
and K. Christopher Garcia3,+
1Laboratory of Immunology, National Institute of Allergy and Infectious Diseases, National
Institutes of Health, Bethesda, MD 20892 2Department of Medicine, Division of Immunology &
Rheumatology, Stanford University School of Medicine, Stanford, CA, 94305 3Howard Hughes
Medical Institute, Departments of Molecular and Cellular Physiology, Structural Biology, and
Program in Immunology, Stanford University School of Medicine, Stanford, CA, 94305 4School of
Medicine, University of Tampere, 33014, Tampere, Finland 5Fimlab Laboratories, Pirkanmaa
Hospital District, 33521, Tampere, Finland 6Department of Pathology, Stanford University School
of Medicine, Stanford, CA, 94305 7Laboratory of Systems Biology, National Institute of Allergy
and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892
Abstract
Cytokines dimerize their receptors, with binding of the “second chain” triggering signaling. In the
interleukin (IL)-4/13 system, different cell types express varying levels of alternative second
receptor chains (γc or IL-13Rα1), forming functionally distinct Type-I or Type-II complexes. We
manipulated the affinity and specificity of second chain recruitment by human IL-4. A Type-I
receptor-selective IL-4 ‘superkine’ with 3700-fold higher affinity for γc was 3-10 fold more
potent than wild-type IL-4. Conversely, a variant with high affinity for IL-13Rα1 more potently
activated cells expressing the Type-II receptor, and induced differentiation of dendritic cells from
monocytes, implicating the Type-II receptor in this process. Superkines exhibited signaling
advantages on cells with lower second chain levels. Comparative transcriptional analysis reveals
that the superkines induce largely redundant gene expression profiles. Variable second chain
levels can be exploited to redirect cytokines towards distinct cell subsets and elicit novel actions,
potentially improving the selectivity of cytokine therapy.
Cytokines regulate key cellular functions including differentiation, proliferation and
apoptosis/anti-apoptosis 1, principally through dimerization of receptor subunits, which
initiates intracellular JAK/STAT activation 2,3. Most cytokines mediate stimulation by first
+corresponding author: kcgarcia@stanford.edu.
*These authors contributed equally to this work
AUTHOR CONTRIBUTION STATEMENT:
KCG conceived project, designed approaches for engineering of IL-4 and initiated subsequent cellular and functional experiments.
DLB and PL performed protein engineering and biophysical experiments. ISJ, RJC, IM, and WEP designed and performed signaling
experiments. RJC, MMS, and IM performed transcriptional analysis and Luminex experiments. WEP, IJS and MMS performed
mathematical modeling using matlab. MTW, MNA, MMS and IM performed DC experiments. ISJ, RJC, IM, DLB, CGF, PJU, WEP
and KCG analyzed the data. PJU and EGE provided reagents and guidance for human primary cell experiments. ISJ, RJC, IM, WEP
and KCG wrote the manuscript.
COMPETING FINANCIAL INTERESTS STATEMENT
The authors have no competing financial interests.
NIH Public Access
Author Manuscript
Nat Chem Biol
. Author manuscript; available in PMC 2013 June 01.
Published in final edited form as:
Nat Chem Biol
. 2012 December ; 8(12): 990–998. doi:10.1038/nchembio.1096.
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interacting with a high affinity cytokine-binding chain (usually designated “α”) followed by
low affinity interaction with a receptor chain such as γc, gp130 or βc 4. The ultimate
potency of the cytokine at inducing signaling is determined by the efficiency, i.e. affinity, of
recruitment of the second chain 5,6. In many of these systems, different cell types express
different amounts of the first and second chain 7. Thus, manipulation of the binding
parameters for second chain recruitment could potentially skew the activity of a cytokine
towards certain cell types8, potentially making these new engineered cytokines more
specific and possibly less toxic, and therefore therapeutically advantageous.
IL-4 is a classical four α-helix bundle cytokine whose primary binding chain is IL-4Rα 9,10.
The IL-4 /IL-4Rα complex serves as a ligand for the second component of the IL-4 receptor,
which for the Type-I receptor is γc and for the Type-II receptor, IL-13Rα19. Formation of
the IL-4/IL-4Rα/γc or IL-4/IL-4Rα/IL-13Rα1 complex on the cell surface activates
intracellular signaling pathways including the Jak-STAT and the PI3K/Akt pathways 9,11.
Recent resolution of the crystal structures of extracellular domains of the IL-4-bound Type-I
and Type-II IL-4 receptors (Fig. 1a) showed that IL-4 sits between IL-4Rα and the second
receptor chain and is in direct contact with the second receptor chain through binding
surfaces on the D-helix of the cytokine 6. IL-4 binds to IL-4Rα with very high affinity (KD
= ~10−10 M) through a highly charged interface 12, while the subsequent binding of the
IL-4/IL-4Rα complex to either γc or IL-13Rα1 is of relatively low affinity 6,9,13,14. The
very high affinity of IL-4 for IL-4Rα means that in most instances the formation of the
signaling complex is largely determined by the expression level of the second chain(s)15.
The alternative second chains have different patterns of cellular expression with γc being
mainly expressed on hematopoietic cells and IL-13Rα1 mainly on non-hematopoietic cells.
Much of IL-4’s regulatory activity is mediated by B cells and T cells that mainly express
Type-I receptors whereas its effector functions, in which it mimics IL-13, are largely
mediated by cells that uniquely express the Type-II receptor and that also respond to IL-13.
Through its capacity to utilize both the Type-I and Type-II receptors, IL-4 is positioned to
play a central role in regulatory functions (i.e. Th2 differentiation, immunoglobulin class
switching, dendritic cell maturation, macrophage activation) as well as effector functions
(i.e. airway hypersensitivity and goblet cell metaplasia). However, these latter activities are
physiologically induced mainly by IL-13, which is made in far larger amounts than IL-4.
Further, since IL-13 cannot bind to the Type-I receptor, which is dominantly expressed on
hematopoietic cells, it has little or no “regulatory” activity.
Pharmacologically, utilization of IL-4 to regulate lymphocyte differentiation is complicated
by its activity on non-hematopoietic cells through binding to the Type-II receptor and
consequent effector function. There have been previous efforts to engineer IL-4 analogs 16,
including the design of the antagonist Pitrakinra17. With the recent determination of the
three dimensional structures of the complete liganded Type-I and Type-II receptor ternary
complexes (Fig. 1a), we sought to engineer agonist IL-4 variants that would have altered
relative binding activities for the second chains of the Type-I and Type-II receptors. In
principle, these ‘superkines’ could have dose-dependent activities that allow optimal
regulatory function while having reduced side effects.
Here we decouple the pleiotropy of IL-4 signaling through the engineering of Type I and
Type II receptor-selective IL-4 superkines that exhibit cell-type specificity and novel
activities, such as specific induction of dendritic cell maturation with a Type II receptor-
specific superkine. Strikingly, the structure-activity relationships of these superkines do not
reveal a linear correlation between superkine potency and receptor affinity, and the highest
affinity superkines have a signaling advantage on cells with the lowest expression levels of
second chain receptor chains. Thus, we demonstrate that cytokine affinity can be ‘tuned’
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based on second receptor chain expression levels in order to selectively target desired cell
types and potentially improve the selectivity of cytokine therapy.
RESULTS
Development of high affinity IL-4 variants
We used two different approaches to engineer IL-4 for higher affinity binding to γc (Fig.
1b) or IL-13Rα1 (Fig. 1c): directed mutagenesis and
in vitro
evolution. To increase the
affinity of IL-4 for γc, we took a combinatorial library approach and used yeast surface
display 18 (Supplementary Results, Supplementary Fig. 1a). We produced C-terminally
biotinylated ectodomains of IL-4Rα, γc, and IL-13Rα1 for use as sorting reagents by
coupling to Streptavidin-phycoerythrin (PE). We found that IL-4 displayed on yeast bound
IL-4Rα with high affinity (Supplementary Fig. 1a) but did not bind to γc in the absence of
IL-4Rα (Supplementary Fig. 1a). In the presence of IL-4Rα, IL-4 on yeast binds to the γc
extracellular domain tetramer, indicating cooperative assembly of the heterodimeric receptor
complex (Supplementary Fig. 1a). The use of high avidity tetramers of γc was essential for
the detection of the initial weak γc binding in the early rounds of library sorting. To create a
library of D helix variants of IL-4, which is the principal γc-interacting helix of the cytokine
(Fig. 1b), we inspected the IL-4/γc interface in the crystal structure of the Type-I receptor
ternary complex. We created a focused library in which eight residues on the face of helix D
were randomized (Fig. 1b), resulting a yeast library with 2 × 108 variants. We carried out
selections by decorating the yeast library with IL-4Rα to create the IL-4/IL-4Rα site 2 on
the yeast and then sequentially enriched γc-binding yeast by decreasing the concentration of
tetrameric, and finally monomeric γc (Supplementary Fig. 1b). Sequencing the IL-4-
selected variants revealed two unique sequences, the ‘RQ’ and ‘RGA’ variants, in which
one, RGA, was highly enriched (Supplementary Table 1).
To increase the affinity of IL-4 for IL-13Rα1, we took a rational, structure-based approach,
rather than a combinatorial approach, based on inspection of the site 2 interfaces formed by
IL-4 and by IL-13 with IL-13Rα1 (Fig. 1c). IL-13 binds with much higher affinity to
IL-13Rα1 than does IL-4 (KD~30nM versus KD >1μM)6, so we aligned IL-4 with IL-13
from their structures in the two Type-II receptor ternary complexes (IL-4/IL-4Rα/IL-13Rα1
and IL-13/IL-4Rα/IL-13Rα1) to determine if we could “graft” important IL-13 receptor-
interacting residues into the corresponding positions seen in IL-4 (Fig. 1c). We noted that
three IL-4 D helix residues, Arg121, Tyr124, and Ser125, which form important contacts
with γc in the IL-4 Type-II receptor ternary complex, are substituted in IL-13 6. We
swapped these residues for their IL-13 positional equivalents (Fig. 1c) and made two IL-4
variants, a double mutant, Arg121Lys, Tyr124Phe, referred to as KF, and a triple mutant,
KFR, in which all three residues are swapped.
Second receptor binding characteristics of the mutants
We expressed recombinant IL-4 and the variants KF, KFR, RQ and RGA using baculovirus
and formed complexes with IL-4Rα in order to measure their binding affinities for
IL-13Rα1 and γc by surface plasmon resonance (SPR) (see Supplementary Table 1 and
Supplementary Fig. 2). The KD of WT IL-4/IL-4Rα for IL-13Rα1 and γc were 4200 nM
and 3300 nM, respectively. KF/IL-4Rα had greater affinity for binding to both IL-13Rα1
(KD = 250 nM), and γc (KD = 330 nM). The addition of the Ser125Arg mutation in KFR
resulted in a cytokine that had a 440-fold improvement over WT IL-4/IL-4Rα in affinity for
IL-13Rα1 (KD = 9.6 nM) but a decreased affinity for γc (KD = 6400 nM). In this respect,
the grafting was highly successful and resulted in a 3-log selectivity for IL-13Rα1 over γc.
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The RQ and RGA variants complexed to IL-4Rα exhibited substantially higher affinity
binding to γc (Supplementary Table 1, Supplementary Fig. 2). RQ/IL-4Rα showed a 36-
fold higher affinity for γc (KD = 91 nM) and RGA/IL-4Rα exhibited a 3700-fold higher
affinity (KD = 0.89 nM) than did IL-4/IL-4Rα. Both RQ and RGA superkines exhibited
substantially decreased binding to IL-13Rα1 (KD = 29,000 nM and 21,000 nM,
respectively), and would therefore be expected to exhibit negligible Type-II receptor
binding. The structure-based and
in vitro
evolution approaches have therefore yielded higher
affinity and receptor-selective IL-4 variants for functional testing. We refer to these
cytokines as IL-4 “superkines” and specifically to the RGA variant as “super-4”.
Structural basis of IL-4 affinity enhancement for γc
We sought to understand whether the super-4 docking mode with the second chain, γc, was
perturbed relative to WT IL-4 since this issue is important in interpreting signaling activity
differences. We were able to crystallize the binary super-4/γc complex in the absence of
IL-4Rα and obtain a structure with a resolution of 3.25Å (Fig. 1d and e, Supplementary
Table 2, Supplementary Fig. 3). Superposition of the binary super-4/γc complex with the
ternary Type-I signaling complex showed no major perturbations in cytokine-receptor
orientation (Supplementary Fig. 3a-b). The position of γc bound to super-4 was essentially
identical to the IL-4Rα/γc heterodimer geometry as observed in the complexes formed with
WT IL-4. Therefore, any signaling changes we observe are very likely attributable to
increased affinity and not structural differences.
In the super-4/γc interface, side chain density was clear for super-4 helix D residues
117-127 (Supplementary Fig. 3c); these engage the γc binding site in a topologically similar
fashion to IL-4 with the γc hotspot residue Tyr124 occupying a central position (Fig. 1d). It
seems clear that an important mechanism underlying super-4’s enhanced affinity was the
replacement of Ser125 with Phe (Fig. 1e, left panel), which now inserts into a large
hydrophobic pocket of γc that was previously unoccupied, contributing an additional 52.5
Å2 of buried surface area (BSA) (Fig. 1e, right panel). The hydrophobic groove in γc
occupied by IL-4 Tyr124 gained a hydrogen bond from the Trp-N7 to a main chain carbonyl
of γc. Based on the structure and SPR data, we propose that the major affinity gains in
super-4 are derived from the Arg121Gln, Tyr124Trp, and Ser125Phe mutations. A detailed
comparison of amino acid interactions of IL-4 and super-4 with γc is presented in
Supplementary Table 3 and Supplementary Fig. 3d. We did not determine structure of the
KFR/IL-13Rα1 complex as the mechanism for affinity enhancement seems obvious from
the structure analysis and engineering strategy. The three side chains substituted on IL-4 D
helix would endow IL-4 with “IL-13 like” contacts.
Cell activation in response to IL-4 superkines
To study responses to IL-4 and its superkines, we used Ramos, HH, A549, and U937 cells.
We first measured the relative expression of mRNA (Supplementary Fig. 4a) and protein
(Supplementary Fig. 4b) levels of the Type-I and Type-II receptor chains on these cells.
Ramos cells have large amounts of IL-4Rα but their amounts of the Type-I receptor are
limited by relatively low expression of γc. HH cells, although having less IL-4Rα than
Ramos cells, have abundant γc. Both Ramos and HH cells have little or no IL-13Rα1. A549
cells have abundant Type-II receptor and little or no Type-I receptor. Finally, U937 cells
have substantial amounts of both Type-I and Type-II receptor chains.
We initially tested the stimulatory activity of IL-4, super-4 and KFR. We used Ramos cells
to study IL-4 responses dominated by the Type-I receptor complex (Supplementary Fig. 4).
Stimulating Ramos cells with 100 pg/ml (~7 pM) of either IL-4, super-4 or KFR for various
times, we found that the time course of stimulation of STAT6 phosphorylation by IL-4,
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super-4 and KFR is similar but super-4 induces substantially more phosphorylation than
does IL-4 or KFR at all time points measured (Fig. 2a); after 20 minute stimulation, the
mean MFI of STAT6 phosphorylation induced by super-4 is 19.6, by IL-4, 7.7 and by KFR,
5.4. In addition, dose/response experiments performed in Ramos cells with the three
cytokines showed that super-4 was 10 fold more potent that KFR, although the three
cytokines reach the same ‘plateau levels’ of STAT6 phosphorylation (Fig. 2b, Fig. 2c and
Supplementary Fig. 5). However, the relative advantage of super-4 over IL-4 was relatively
modest in comparison with the ~3700-fold difference in their solution equilibrium constants
for γc when complexed to IL-4Rα (Supplementary Table 1).
A549 cells principally utilize IL-13Rα1 as their second chain (Supplementary Fig. 4). KFR
was 3-10-fold more stimulatory than IL-4; super-4 was indistinguishable from IL-4 (Fig.
2d). Here again, while there was a qualitative agreement in that the highest affinity
superkine caused a better response but the degree of signaling advantage by the variants did
not mirror the absolute magnitudes of their solution affinity difference. In U937 monocytes,
which express both γc and IL-13Rα1, super-4 slightly outperformed IL-4 but generally the
differences between the superkines and IL-4 were modest (Fig. 2e).
To investigate whether the superior STAT6 activation by super-4 translates to the induction
of STAT6-dependent gene products, we measured CD23 protein expression19 in Ramos
cells that had been stimulated for 8 hours with either IL-4 or super-4. Super-4 was
significantly more potent in inducing CD23 than was IL-4 (Fig. 2f), but again, super-4
showed less of an advantage over IL-4 than might have been expected from its far greater
capacity, when complexed to IL-4Rα, to bind γc.
Primary human cell responses to IL-4 and superkines
We next studied STAT6 phosphorylation responses of human peripheral blood leukocytes
(PBL) using Phospho-Flow cytometry coupled with fluorescent cell barcoding. We first
measured IL-4Rα, γc and IL-13Rα1 expression in CD4 T cells, CD8 T cells, monocytes
and B cells from 5 healthy donors by flow cytometry. IL-4Rα expression was highest on B
cells while monocytes had intermediate expression and T cells had the least IL-4Rα (Fig.
2g). For γc, there was relatively little difference in expression between monocytes and CD4
T cells. B cells had slightly less γc and CD8 T cells had the lowest levels. As expected,
IL-13Rα1 expression was highest on monocytes, whereas B and T cells showed very low
expression of this chain. PBLs were either unstimulated or stimulated with IL-4 or the
various superkines for 15 minutes; STAT6 Tyr641 phosphorylation was measured by flow
cytometry. Super-4 induced stronger phosphorylation of STAT6 than IL-4 and much
stronger phosphorylation than KFR in CD4 and CD8 T cells (Fig. 2h and Supplementary
Fig. 6a-d). Monocytes showed little difference in their responses to IL-4, super-4 and KFR,
in keeping with their expression of both γc and IL-13Rα1.
Modeling of receptor assemblage
The notion that super-4 was only ~3-10-fold more potent at activating STAT6 while its three
dimensional equilibrium constant for γc was ~3700 higher than that of IL-4 left us
wondering how signal-inducing receptor formation is dictated by the expression of the
second chain. To address this question, we utilized a Matlab script slightly modified from
that used in our previous publication7 (see Supplementary Methods) to calculate the
assemblage of receptor complexes as a function of ligand concentration upon varying
second chain numbers and varying second chain equilibrium constants. This matrix takes
into account three parameters; the surface expression of IL-4Rα and γc receptor chains, the
alteration in 2-dimensional binding affinities of ligand-bound IL-4Rα towards the γc chain
and the ligand concentration. The calculation predicts the number of formed receptor
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complexes on cell surface and as such does not directly describe signaling particularly as it
assumes that the availability of intracellular signaling molecules (Jak1, Jak3, Tyk2 or
STAT6) does not limit the complex formation. Further, the calculation assumes that the
physical interaction between cell membrane and all the receptor chains involved is similar
and limits the free movement of the receptor chain equally on cell membrane.
Since the number of IL-4Rα chains on Ramos cells has been reported to be ~1500 20, we
determined the assemblage of receptors at this fixed IL-4Rα number. We used two
equilibrium binding constants previously measured for IFN alpha receptor as “surrogate”
values that roughly would be expected to correlate with Type-I and Type-II IL-4
receptors. 21. When γc number was set to 4500, there was a relatively modest effect of
increasing second chain Ka2 from 0.01 to 1.0 μm2. However, when γc number was set to
500, the increase in second chain Ka2 had a strong impact on the number of receptor chains
assembled (Fig. 3a). Thus, with a cytokine concentration of 100 pg/ml, the ratio of
assembled complexes for Ka2=1μm2 compared to Ka2=0.01μm2 was 6.7 when the number
of second chains was 4500 while that ratio was 34.5 when the γc number was set to 500. At
1000 pg/ml, the Ka2=1μm2 /Ka2=0.01μm2 ratio for 4500 γc molecules was 6.8 while it was
25.6 when the γc number was 500. Thus, increasing second chain Ka2 becomes more useful
when the second chain number is relatively low. This would effectively mean that a cell that
expresses low levels of γc or of IL-13Rα1 would most strongly benefit from enhanced
affinity for the second chain. Indeed, when we calculated the number of formed receptor
complexes at 100 pg/ml of ligand at only 167 γc receptor chains per cell, we found that the
WT IL-4, with 2-dimensional Ka2 of 0.01μm2 assembled very few signaling complexes, as
opposed to the 33 signaling complexes assembled by a superkine with a 100-fold higher 2-
dimensional Ka2 (Fig. 3b).
As IL-4 and super-4 stimulate similar plateau values for STAT6 phosphorylation (Fig. 2b),
we reasoned that assembling more signaling complexes than that induced by the lowest
ligand concentration giving maximal stimulation would not result in any further signaling.
As the plateau is achieved at 1,000 pg/ml of super-4 and 10,000 pg/ml of IL-4 in Ramos
cells (Fig. 2b) we calculated the number of assembled complexes to be 65 for a ligand that
had low affinity for the second chain (WT IL-4; 0.01 μm2) using an intermediate number of
γc chains (1500) at 10,000 pg/ml.
Altering second receptor chain expression levels
Our modeling predicts that an increase in γc expression would be expected to decrease the
advantage super-4 had over IL-4 and, conversely, limiting availability of γc would lead to
clearer differences between IL-4 and super-4. We studied the sensitivity to IL-4 and super-4
of the HH cell line, which had much higher expression of γc than Ramos cells
(Supplementary Fig. 4). Super-4 was not superior to IL-4 or KFR in inducing
phosphorylation of STAT6 in HH cells at concentrations ranging from 10 to 10,000 pg/ml
(Supplementary Fig. 6e).
An alternative test would be to diminish the accessibility of γc. For this purpose, we
stimulated Ramos cells with 100 pg/ml of IL-4 or the super-4 and KFR superkines in the
presence or absence of anti-γc, measured the phosphorylation of STAT6 by flow cytometry
and calculated the percentage decrease in STAT6 phosphorylation caused by anti-γc.
STAT6 phosphorylation induced by IL-4 was decreased 58% by 50 μg/ml of anti-γc
whereas for super-4, the decrease was only 12% (Fig. 3c). For KFR, the inhibition was
similar to that for IL-4. These results are consistent with the qualitative order of solution
KD’s of IL-4 and the superkines for binding to γc (super-4>IL-4=KFR, Supplementary
Table 1) and support the concept that increased affinity for the second chain results in
greater stimulatory discrimination when the second chain expression is low.
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In U937 cells, blocking γc would be predicted to diminish IL-4 responses whereas there
should be little impact on the activity of the KFR superkine because of its principal
utilization of the Type-II receptor. Indeed, blocking γc in U937 cells resulted in 44 %
reduction in STAT6 phosphorylation in response to IL-4 but only a 7% reduction in
response to KFR (Fig. 3c).
Immunomodulatory activities of IL-4 superkines
To study the functional specificity and immunomodulatory abilities of IL-4 and the
superkines, we performed a series of experiments involving CD4 T cells and monocytes
(Fig. 4). The combination of TGF-β and IL-4 promotes the differentiation of naïve human
CD4 T cells into Th9 cells 22. To test whether super-4 more potently induces Th9
differentiation than WT IL-4, naïve CD4+ CD45RA+ CD45RO−CD25− T cells were isolated
from human PBL and cultured with anti-CD3/anti-CD28-coated beads in the presence of
TGF-β and varying concentrations of IL-4, super-4 or KFR for 4 days. Priming with 10 or
100 μg/ml of super-4 resulted in a significantly higher percentage of cells that produced
IL-9 upon subsequent stimulation with PMA and ionomycin than did priming with the same
concentrations of IL-4 or KFR (Fig. 4a).
IL-4, in combination with GM-CSF, induces the
in vitro
differentiation of dendritic cells
(DCs) from human monocytes 23. Highly purified monocytes were cultured with GM-CSF
alone or with varying concentrations of IL-4, super-4 or KFR. After 6 days, cells were
analyzed for cell surface expression of the DC-associated molecules DC-SIGN (CD209),
CD86 and HLA-DR. Strikingly, while IL-4 and KFR elicited monocyte differentiation into
DCs that expressed CD209, CD86 and HLA-DR (Fig. 4b and Supplementary Fig.7), super-4
failed to do so suggesting that such differentiation is mainly driven by signaling through the
Type-II IL-4 receptor complex, which is poorly engaged by super-4. Furthermore, super-4
was somewhat less effective than KFR or IL-4 in down-regulating CD14, a process also
associated with the differentiation of monocytes into DCs (Fig. 4c). Additionally, analysis of
further markers used to distinguish different DC subsets show that cells induced by GM-
CSF with or without super-4 are phenotypically identical (Supplementary Fig. 8), implying
that super-4-induced cells were incompletely differentiated rather than differentiated into a
distinct DC subset.
To confirm the relative roles of Type-I and Type-II IL-4 receptor complexes in DC
differentiation, we showed that anti-IL-4Rα, which would block both the Type-I and Type-
II receptors, diminished the expression of CD86 and CD209 in response to IL-4 and KFR
while anti-γc, which would only block the Type-I receptor failed to do so (Fig. 4d-f).
Super-4 caused very modest induction of these markers. Super-4-induced CD14 down-
regulation was partially inhibited by anti-IL-4Rα but not anti-γc. Thus, when γc was
blocked, IL-4 and KFR still induced the same level of DC maturation as in the control
condition (Fig. 4d-f), confirming that the Type-II IL-4 receptor complex plays an important
role in GM-CSF/IL-4-mediated DC differentiation.
Signaling profile of IL-4 and superkines in monocytes
Since IL-4 and the two superkines activated STAT6 to the same extent in monocytes
(Supplementary Fig. 6c), we sought to understand why super-4 was unable to induce DC
differentiation. Purified monocytes were treated with two doses of cytokines, one dose
corresponding to the pSTAT6 EC50 value (30pM) (Figure 5) and another dose
corresponding to saturation (50nM) (Supplementary Fig. 9). The levels of STAT6 and IRS1
phosphorylation as well as the downregulation of the γc and IL-13Rα1 receptors were
analyzed at the indicated times. At low doses, super-4 and KFR exhibited delayed activation
of STAT6 and IRS1 (Fig. 5a-b) when compared to IL-4. No significant internalization of
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either γc or IL-13Rα1 was observed (Figure 5c-d). At high doses, the three cytokines
induced the same kinetics profile of STAT6 and IRS1 activation (Supplementary Fig. 9a-b).
KFR exhibited stronger internalization of IL-13Rα1 at later times of stimulation
(Supplementary Figure 9c-d). Overall, these results show a lack of correlation between
surface receptor internalization and signaling activation. Moreover, the delayed kinetics of
signaling activation alone cannot explain the inefficiency of super-4 to induce DC
differentiation, suggesting that Type-II receptor specific signaling is required for DC
differentiation.
Gene expression profiling of IL-4 and superkines
To gain qualitative insights into the extent of redundancy of genetic programs induced by
IL-4 and superkines in differentiating DCs, we performed genome-wide analysis of gene
expression in response to WT IL-4 and the two superkines in monocytes treated
simultaneously with GM-CSF. Monocytes from 5 healthy donors were stimulated for six
hours with GM-CSF with or without IL-4, KFR or super-4 and RNA expression was
analyzed as described in Materials and Methods. As shown by scatter plot correlation, the
three cytokines induce the vast majority of genes to the same extent (Supplementary Figure
10a). However, interestingly, minor pockets of gene expression specificity can also be
observed between IL-4 and the two superkines. A considerable number of genes were
significantly induced by only one or two of the cytokines used. IL-4 regulated specifically
16 genes while super-4 and KFR regulated 72 and 45 respectively (Supplementary Figure
10b). The heatmap in Supplementary Figure 10c shows a representative set of cytokine-
selective genes where clear differences in the expression patterns induced by IL-4 and the
two superkines were observed. A more complete list of genes regulated differentially by
superkines and IL-4 in monocytes is presented in Supplementary Table 4. DC-specific genes
such as TPA1, HLA-DPA and CISH were clearly induced to a higher level by IL-4 and KFR
than by super-4, consistent with specific signals coming from the Type-II IL-4 receptor that
could bias the dendritic cell differentiation process induced by IL-4.
Cytokine secretion profiling of IL-4 and superkines
To further assess the functionality of the DCs induced by the engineered cytokines, we
compared the secretion patterns of cytokines, chemokines and growth factors by performing
a Luminex assay on supernatant of cells cultured for 8 days with or without LPS stimulation
during the last 24 hours (Fig. 6a). Among the 51 analytes, 20 showed no difference in
expression between treatments (superkines and LPS) (Fig. 6b) and 19 were up-regulated by
LPS (most notably IL-6, CCL3, CCL5, and CXCL1) without difference between IL-4 and
the superkines (Fig. 6c). The expression of the remaining 12 products discriminated the cells
induced by GM-CSF only or GM-CSF + super-4 from the DCs induced by GM-CSF + IL-4
or KFR (Fig. 6d and Supplementary Fig. 11). The former two subsets were very similar and
produced more G-CSF, HGF, IL-1α, IL-1β, IL-10, IL-12p40, LIF, TNFα, and less MCP3,
MIP1β, PDGF, TGFα than the latter two, also very similar, subsets. Most of the differences
were seen after LPS stimulation but some also existed in non-activated cells. Altogether,
these data demonstrate that super-4 had no effect over that of GM-CSF alone on monocytes,
while the addition of IL-4 or KFR led to phenotypically and functionally different DCs.
Thus, the engineered cytokines appear to possess new and distinct functional activities.
DISCUSSION
Many cytokines being developed in the pharmaceutical sector are associated with dose-
limiting toxicities or inadequate efficacy. One possibility for improving cytokines as
pharmacologic agents is to bias them for preferential activity on certain desired cell types.
Indeed, in a recent report by our lab, we succeeded in biasing the action of IL-2 to different
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leukocyte subsets by enhancing IL-2 affinity for IL-2Rβ 24. Cytokines that act through
heterodimeric receptor complexes, such as those in the γc, gp130 and βc families, are
particularly amenable to this approach given that the relative expression levels of the
specific α chains of their receptors and the shared “second” chains often vary on different
cell types.
Here, guided by structures of IL-4 receptor complexes, we have altered the agonistic
properties of IL-4 in a way to redirect cell subset selectivity through engineering based on
the metric of differential second receptor chain expression level. While the signaling
experiments qualitatively confirmed the superiority of super-4 over IL-4 for a cell line
predominantly using the Type-I receptor (Ramos) and of KFR over IL-4 for a cell line
predominantly using the Type-II receptor (A549), the differences between IL-4 and super-4
on Ramos cells or IL-4 and KFR on A549 cells were much less dramatic than might have
been anticipated. These results could be accounted for in several ways. The measurement of
the equilibrium constant of the binding of soluble IL-4 (or superkine) complexed to IL-4Rα
to immobilized γc or IL-13Rα1 may overestimate the differences in the 2-dimensional
equilibrium constants among these proteins for second chain recruitment on the cell surface
when both ligand and receptor are membrane bound and have greater diffusion limits.
Another possibility is that the receptor heterodimers could exist, in a pre-associated form or
alternatively, localized in membrane compartments in close proximity, as seen for IL-2 25.
IL-4 is not currently in use as a therapeutic agent but it had been considered for such use in
the past and, if free of toxicity, might be considered for purposes such as directing CD4 T
cell differentiation during vaccination or altering an established pattern of differentiation in
view of the recent recognition of the plasticity of differentiated CD4 T cells 26. In the early
1990’s, clinical trials were performed in which IL-4 was administrated to cancer patients
with the hope of boosting T cell responses or of engaging the innate immune system.
However, intravenous administration of high dose (600 μg/m2/day) IL-4 resulted in a
vascular leak syndrome in two out of three patients in the study group 27. Other toxicities
were encountered in these studies and in preclinical analysis. The production of IL-4
superkines that cannot activate the Type-II receptor or in which activation of the Type-I
receptor can be achieved at substantially lower concentrations than activation of the Type-II
receptor might mitigate these problems, since most non-hematopoietic cells use only the
Type-II receptor and cells of the monocyte/ macrophage lineage tend to express similar
numbers of both receptors. Indeed, our observation that super-4 was relatively inefficient in
inducing DC differentiation favor this hypothesis and agrees with previous work describing
the requirement of Type-II IL-4 receptor for the surface expression of DC co-stimulatory
molecules in mouse bone-marrow precursor cells 28.
The use of IL-4 to redirect T cell differentiation from more inflammatory phenotypes (i.e.
Th1 or Th17) could be contemplated since CD4 T cells utilize the Type-I receptor virtually
exclusively. Our data strongly suggest that super-4 would have greater efficacy for this
purpose than IL-4 by combining a stronger activation of Type-I responses, which are
required for T cell effects, and by reducing the activation of Type-II responses including DC
differentiation. Indeed, super-4 more potently enhances TH9 differentiation, and may
provide greater clinical benefit than IL-4 in boosting Th9 immunity.
While delivery of IL-4 by various means generally has a beneficial outcome in several
preclinical models of autoimmunity such as the non-obese diabetic or the collagen-induced
arthritis mouse models, the interpretation of the mechanisms of action has been made
difficult by the pleiotropic nature of IL-4 binding. Thus, the use of receptor-selective
superkines in mouse models will help to both better delineate the mode of action of therapies
involving IL-4 and improve their efficacy 29,30.
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The development of superkines can be considered as proof of the feasibility of this approach
to achieve cell subset-specific cytokine effects. In principle, this approach can be attempted
with many different cytokines whose signaling is dependent on the biophysical parameters
of second chain recruitment.
METHODS
For Protein expression, yeast surface display, biophysical analysis and microarray analysis
see Supplemental Information.
Cell lines and stimulations with IL-4 and superkines
Ramos, U937, A549 and HH cells were grown in RPMI containing 10% FBS, penicillin/
streptomycin and l-glutamine (2mM) and maintained at 37°C with 5% CO2. Prior to
stimulation, cells were cultured overnight in growth medium containing 2% FBS
(“starved”). For γc-blocking experiments, overnight starved Ramos or U937 cells were
incubated for 1 hour at 37°C with blocking antibody (R&D). Various concentrations and
stimulation times of superkines are indicated in figures.
Flow cytometric stainings and antibodies
Cell surface expression of IL-4 receptor chains was performed after blocking Fc receptors I,
II and III. Antibodies to CD23 (ref. 555711), IL-4Rα (ref. 552178) and γc (ref. 555900)
antibodies were purchased from BD and for IL-13Rα1 (ref. FAB1462F) from R&D.
Intracellular pSTAT6 and pIRS-1 staining was performed after ice-cold methanol (90%)
permeabilization. Anti-pSTAT6 Ax488 (ref. 612600) and anti-pIRS-1 (ref. 558440)
antibodies were purchased from BD. The induction of STAT6 phosphorylation was
calculated by subtracting the Mean Fluorescence Intensity (MFI) of the stimulated sample
from unstimulated sample. For primary human cells, analysis of STAT6 activation was
performed as previously described 31. Briefly, PBMC samples from five donors were
purified and stimulated with increasing concentrations of the appropriate cytokine for 15
min. Samples were then fixed in PFA for 15 min at 37°C. Cells were pelleted, washed with
PBS, permeabilized with cold (4°C) methanol. Samples were then diluted with PBS to a
final concentration of 50% and fluorescently barcoded with DyLight 800 and Pacific Orange
dyes as previously described 31. After barcoding and combining, samples were stained for
one hour with CD19 PE (ref. 302209), CD4 Brilliant Violet (ref. 300531), CD14 PerCP-
Cy5.5 (ref. 325621), CD8 PE-Cy5 (ref. 301009) purchased from Biolegend and pSTAT6
Ax488. Analysis was performed on a BD Aria. Data analysis was performed in Cytobank
software. Log median fluorescence intensity values were plotted against cytokine
concentration to yield dose-response curves in cell subsets against pSTAT6.
RT-PCR
RNA was isolated from starved cells with RNeasy Kit (Qiagen). RNA was reverse-
transcribed to cDNA using SuperScript II First-Strand Synthesis System for RT-PCR
(Invitrogen). Quantitative PCR reactions were performed using a 7900HT sequence
detection system (Applied Biosystems). The primer/probe sets to detect IL-4Rα, IL-13Rα1
and γc (FAM-MGB probe), and TaqMan Ribosomal RNA Control Reagents for detecting
the 18S ribosomal RNA (VIC-MGB probe) were from Applied Biosystems. The mRNA
levels were normalized to 18S ribosomal RNA.
Th9 differentiation assay
Enriched CD4 T cells were prepared from buffy coats obtained from healthy donors
(Stanford Blood Center) using RosetteSep™ Human CD4+ T Cell Enrichment (Stem Cell
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Technologies) prior to density gradient centrifugation with Ficoll-Paque PLUS (GE
Healthcare). Naïve CD4+ CD45RA+ CD45RO− CD25− T cells were magnetically sorted
with Naïve CD4+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were cultured at 37°C in
48-well flat-bottomed plates (Falcon) in X-VIVO 15 media (Lonza) supplemented with 10%
Human Serum Type AB (Lonza), 100 units/ml penicillin/streptomycin, L-glutamine
(Invitrogen) and 50 μM β-mercaptoethanol (Sigma-Aldrich). Cells were cultured at 2.5×105
cells/mL with anti-CD3/CD28 coated beads (Invitrogen) at a 1:1 bead-to-cell ratio in the
presence of 5 ng/mL TGF-β (eBioscience) and the indicated concentrations of IL-4, super-4
or KFR. After 4 days in culture, beads were magnetically removed and cells were re-
stimulated with 25 ng/mL PMA and 750 ng/mL Ionomycin (Invitrogen) in the presence of
Brefeldin A (eBioscience) for 4 hours. Cells were then stained with a LIVE/DEAD Fixable
Aqua Dead Cell Stain Kit (Invitrogen), then fixed and permeablized (eBioscience) according
to manufacturer’s protocols. Subsequently, cells were stained with fluorescently labeled Abs
against IL-9 and Foxp3 (eBioscience). Labeled cells were acquired on a BD LSRII (BD
Bioscience), and data were analyzed on gated live single cells by FlowJo software
(Treestar).
Dendritic cells differentiation: phenotyping and cytokine profiling
CD14+ monocytes were isolated (>97% purity) from peripheral blood mononuclear cells
obtained from healthy blood donors (Stanford Blood Center) by density centrifugation using
a RosetteSep Human Monocyte Enrichment Cocktail (Stem Cell Technologies) followed by
magnetic separation with anti-CD14 conjugated microbeads (Miltenyi Biotec). 0.5-1×106
CD14+ monocytes were subsequently cultured with 50 ng/mL GM-CSF alone or with the
indicated concentrations of IL-4, KFR or super-4 in 12-well plates (Corning) containing
IMDM medium (Gibco) supplemented with 10% human AB serum, 100 U/mL penicillin,
100 μg/mL streptomycin, 2 mM L-glutamine, sodium pyruvate, non-essential amino acids
and 50 μM 2-ME. Fresh cytokines were added on days 2 and 4. Cells were processed on day
6-7 with 5 mM EDTA and subsequently stained with DAPI (Invitrogen), fluorescently
labeled antibodies against CD11c (ref. 561356), CD16 (ref. 560195), CD80 (ref. 555683),
CD86 (ref. 555660), CD209 (ref. 551265), HLA-DR (ref. 560944) (BD Biosciences), CD1a
(ref. 8017-0017-025), CD123 (ref. 48-1239-42) (eBioscience), CD1c (ref. 331514), CD40
(ref. 334312), CD14 (ref. 325619) (Biolegend), CD141 (ref. 130-090-513) and CD304 (ref.
130-090-9533) (Miltenyi Biotec), or appropriate isotype controls. Dendritic cell
differentiation was assessed by flow cytometry with a BD LSRII flow cytometer and the
mean fluorescent intensity (MFI) was determined on the FlowJo software (Treestar).
For Luminex cytokine profiling, culture supernatant was collected on day 8 (with or without
24h stimulation with 2 μg/ml LPS). Human 51-plex kits were purchased from Affymetrix
and used according to the manufacturer’s recommendations with modifications as described
below. Briefly, samples were mixed with antibody-linked polystyrene beads on 96-well
filter-bottom plates and incubated at room temperature for 2 h followed by overnight
incubation at 4°C. Plates were vacuum-filtered and washed twice with wash buffer, then
incubated with biotinylated detection antibody for 2 h at room temperature. Samples were
then filtered and washed twice as above and resuspended in streptavidin-PE. After
incubation for 40 minutes at room temperature, two additional vacuum washes were
performed, and the samples resuspended in Reading Buffer. Plates were read using a
Luminex 200 instrument with a lower bound of 100 beads per sample per cytokine. MFIs
were normalized to values from unstimulated cells cultured with GM-CSF only.
Supplementary Material
Refer to Web version on PubMed Central for supplementary material.
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Acknowledgments
The authors thank Dr. Josh Gregorio and Dr. Kipp Weiskopf for additional help and reagents, and the Stanford
Human Immune Monitoring Center. Supported by National Institute of Allergy and Infectious Diseases Division of
Intramural Research, (ISJ, WEP) and Finnish Medical Foundation (ISJ), the Howard Hughes Medical Institute
(KCG), NIH RO1-AI51321(KCG) and NIH UO1-DK078123 (CGF), and the Stanford Immunology Program
Training Grant (DLB).
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FIGURE 1. Structure-based engineering of IL-4 superkines
(a) Crystal structures of the IL-4 and IL-13 Type-I and Type-II ternary ectodomain
complexes 6. (b) and (c) The principal γc and IL-13Rα1 binding sites on the D-helices of
IL-4 and IL-13, respectively. In (b) the positions randomized in the IL-4 site 2 library are
shown, and in (c) a structural superposition of IL-4 and IL-13 in the receptor complexes
shows that positions 121, 124, and 125 of IL-4 superimpose closely on the analogous
positions of IL-13. In (c) IL-13 is in purple, and IL-4 is in light green, substituted residues
are in red. (d) Isolated view of the site 2 interfaces in the WT (left) and super-4 (right)
complexes with γc. The view shown is the ribbon representation of the A and D helices of
the cytokines, with γc-interacting side chains shown, projected onto the semi-transparent
molecular surface of γc. The interacting residues of γc underneath the surface are visible as
dark outlines on the surface. The area contacted by the respective cytokines on γc is
indicated in yellow on the surface, and the energetically critical Tyr103 of γc is colored red.
A dashed oval encircles a region of the interface shown from the side in panel (e). In (e) a
close-up is shown of interface packing and shape complementarity in super-4 (right) versus
IL-4 (left).
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FIGURE 2. Effect of IL-4 superkines on intracellular signaling
(a) Overnight starved Ramos cells were unstimulated or stimulated for indicated times with
100 pg/ml of IL-4, super-4 or KFR. The cells were then fixed, permeabilized and stained
with antibody against phosphorylated STAT6. (b-e) Ramos cells (b), Ramos cell starved
overnight (c), A549 cells (d) and U937 cells (e) were stimulated for 15 minutes with
increasing amounts of IL-4, super-4 and KFR, the analysis was then performed as in Figure
3a. (f) Ramos cells were stimulated for 8 hours either with IL-4 or super-4 as indicated,
followed by surface staining of CD23. Means and SEMs from three independent
experiments are shown for all experiments. (g) Expression of IL-4 Type-I and Type-II
receptor chains on human PBLs from five donors. For the measurement of IL-4Rα, γc and
IL-13Rα1 expression, B and T cells were gated by cell surface markers (CD19, CD4, CD8),
while monocytes were identified as CD14+ cells. Appropriate isotype controls served as
negative control. (h) Normalized pSTAT6 EC50 values obtained based on sigmoidal dose-
response curves of IL-4 and the superkines (Supplementary Fig.6). pSTAT6 EC50 values
from IL-4 wt were normalized to 1 and the EC50 values of the super-4 and KFR were
calculated accordingly, means and SD are presented. Paired T-test was used to determine
significant changes. In all the experiments, asterisk represent significant p values (p<0.05)
obtained from the Paired T-test analysis.
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FIGURE 3. Modeling of receptor assemblage in response to varying number of second chains
A Matlab algorithm was used to calculate assemblage of IL-4 receptors on cell surfaces
expressing only the Type-I IL-4 receptor. (a) IL-4Rα number was set to 1500. Second chain
number was raised from 500 to 4500 and 2-dimensional equilibrium constant (Ka2) of
IL-4Rα complexes for second chain were over a range from 0.01μm2 to 1μm2 as indicated.
The ratio of assembled chains of highest (1.0 μm2) versus lowest (0.01 μm2) second chain
Ka2 values was calculated for 100 and 1000 pg/ml at 500, 1500 and 4500 γc molecules per
cell. (b) IL-4Rα number was set to 1500. 2-D equilibrium constant was varied from 1μm2 to
0.01μm2 and second chain number from 167 to 4500 per cell. Complexes assembled with
167 γc chains per cell at 100 and 1000 pg/ml of IL-4 or superkines at 2-D equilibrium
constants of 1.0 μm2, 0.1 μm2 or 0.01 μm2 are shown. (c) Phosphorylation of STAT6 in
Ramos and U937 cells in response to super-4, IL-4 and KFR in the presence of anti-γc
antibody (0, 5, or 50 μg/ml). Response in the absence of anti-γc was normalized to 100%
and responses in the presence of anti-γc expressed as in relation to the normalized value.
Data (mean and SEM) are from three independent experiments.
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FIGURE 4. Functional activities exhibited by IL-4 and superkines
(a) Human naïve CD4+ CD45RA+ CD45RO− CD25− T cells were cultured with anti-CD3/
anti-CD28-coated beads in the presence of TGF-β and the indicated concentrations of IL-4,
super-4 or KFR. Cells were subsequently analyzed for intracellular expression of IL-9. Data
(mean and SEM) are from 3 independent experiments with >4 donors. (b,c) CD14+
monocytes were isolated (>97% purity) from peripheral blood mononuclear cells obtained
from healthy blood donors and cultured with 50 ng/mL GM-CSF alone or with the indicated
concentrations of IL-4, KFR or super-4. Cells were subsequently stained with DAPI,
fluorescently labeled isotype control mAbs, or mAbs against HLA-DR (b) and CD14 (c).
Data (mean and SEM) are from 3 donors. (d,f) CD14+ monocytes were isolated (>97%
purity) and cultured with 50 ng/mL GM-CSF and 2 μg/ml of IL-4, KFR or super-4 in the
presence of the indicated antibodies. Cells were processed and subsequently stained with
DAPI, fluorescently labeled isotype control mAbs, or mAbs against CD209 (d), CD86 (e)
and CD14 (f). Data (mean and SEM) are from 3 donors. Paired T-test was used to determine
significant changes.
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FIGURE 5. Signaling and internalization kinetics of IL-4 and the two superkines in monocytes
CD14+ monocytes (>97% pure) were stimulated with 30pM of IL-4, super-4 or KFR for the
indicated times. (a,b) Kinetics of STAT6 (a) and IRS1 phosphorylation (b) were measured
by flow cytometry using phospho-specific antibodies coupled to fluorescence dyes. (c,d)
Surface IL-13Rα1 (c) and γc internalization (d) was assayed by flow cytometry using
receptor chain specific antibodies fluorescently labeled. In both cases data (mean and SEM)
are from 4 healthy donors.
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FIGURE 6. Distinct patterns of cytokine secretion induced by IL-4 and the two superkines in
immature and LPS-matured DCs
Purified monocytes from 3 healthy donors were cultured for 7 days with GM-CSF (50 ng/
ml) alone or combined with IL-4, KFR or super-4 (20 ng/ml), then stimulated (or not) with
LPS (2 μg/ml) for another 24 hours. Culture supernatant was assessed by Luminex for
relative amounts of 51 cytokines, chemokines and growth factors (listed by the heatmap (a)).
(b-d) The panels on the right of the heatmap are representative examples of products whose
secretion was either (b) unchanged (n=19), (c) increased by LPS stimulation only (n=20), or
(d) modulated by superkines in the presence or absence of LPS (n=12). Data represent mean
and SD from 3 healthy donors (normalized to GM-CSF alone group). Paired T-test was used
to determine significant changes, *p<0.05).
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