From the Swiss Institute for Experimental Cancer
Research (ISREC) 1066 Epalinges, Switzerland,
Tularik Inc.,
South San Francisco, California 94080, ** Mount Sinai School of
Medicine, Immunobiology Center, New York, New York 10029-6574, and the
Institute for Microbiology,
Biochemistry and Genetics, University of Erlangen-Nürnberg,
D-91058 Erlangen, Germany
Received for publication, March 2, 2000, and in revised form, October 23, 2000
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ABSTRACT |
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STAT transcription factors are expressed in many
cell types and bind to similar sequences. However, different STAT gene
knock-outs show very distinct phenotypes. To determine whether
differences between the binding specificities of STAT proteins account
for these effects, we compared the sequences bound by STAT1, STAT5A, STAT5B, and STAT6. One sequence set was selected from random
oligonucleotides by recombinant STAT1, STAT5A, or STAT6. For another
set including many weak binding sites, we quantified the relative
affinities to STAT1, STAT5A, STAT5B, and STAT6. We compared the results
to the binding sites in natural STAT target genes identified by others. The experiments confirmed the similar specificity of different STAT proteins. Detailed analysis indicated that STAT5A specificity is
more similar to that of STAT6 than that of STAT1, as expected from the
evolutionary relationships. The preference of STAT6 for sites in which
the half-palindromes (TTC) are separated by four nucleotides
(N4) was confirmed, but analysis of weak binding
sites showed that STAT6 binds fairly well to N3 sites. As
previously reported, STAT1 and STAT5 prefer N3 sites;
however, STAT5A, but not STAT1, weakly binds N4 sites. None
of the STATs bound to half-palindromes. There were no specificity
differences between STAT5A and STAT5B.
STAT1 proteins were
discovered in the course of the analysis of interferon signaling
pathways (1, 2). Up to now seven mammalian genes coding for members of
this family of intracellular signaling proteins have been found. STAT
molecules are present as latent transcription factors in the cytoplasm.
Signaling by a large number of cytokine, growth factor, and hormone
receptors leads to activation of one or more STATs by JAK kinases or
intrinsic receptor tyrosine kinase activity. The interaction between
the SH2 domain present in all STATs and the STAT phosphotyrosine is the
basis for the formation of STAT dimers with 2-fold symmetry. The dimers
are transported into the nucleus where they bind to a palindromic DNA
motif present in cytokine-inducible genes (see Refs. 3 and 4 for
review). The same palindromic core motif, TTCN2-4GAA, has been found in sequences recognized
by all STATs.
Initially, the STAT signaling pathway was proposed to account for
specificity of cellular responses to different ligands, because STAT
molecules directly link the receptor to the regulatory elements in
responsive genes. However, it was soon found that the same STAT
molecule can be activated by different extracellular signals and that
many cytokine receptors can activate more than one STAT protein. In
view of this apparent promiscuity of receptor-STAT interactions, it was
surprising to find that targeted disruption of STAT genes in mice
resulted in very specific and distinct phenotypes. These results
suggest that in vivo, in contrast to cell culture systems,
an unknown number of receptors acts primarily through a single STAT
species. They leave open, however, the question of how STATs select
their target genes. The observation that the same STAT protein can
induce distinct genes in different cell types indicates that the
induction of these genes does not solely depend on the presence of
active STAT but may require the cooperation of other proteins (5) or
may be controlled by the state of the chromatin of a potential STAT
target gene (6). In some cell types different receptors activate
distinct STATs and induce expression of exclusive genes (7). In these
and in other cases, target gene selection may also be determined by the
capacity of different STATs to cooperate with distinct transcription
factors that bind to regulatory elements of particular genes. Finally, target gene selection by STATs may be determined by preferences in the
sequence specificity of different STAT dimers. Although the same
palindromic core is found in sequences bound by all STATs, previous work (164) has shown that STATs can be distinguished on
the basis of their sequence specificity. The most striking finding was
that STAT6 differs from the other members of the family in that it
prefers sites in which the two halves of the palindrome are separated
by four rather than three nucleotides (8)
(TTCN4GAA and
TTCN3GAA hereafter referred to as
N4 and N3 sites, respectively. We refer to this
distance Nx as spacer.) The observation that the fine
specificity for STAT1 and STAT3 is different when sites of low affinity
are taken into account (9) gave rise to the suggestion that natural
STAT responsive cis-acting elements may be weak affinity binding sites
that preferentially bind specific STATs. In some cases the specificity
of such sites may be increased by the arrangement in pairs that allow
the cooperative binding of two STAT dimers (10-13).
Until now, there have been relatively few studies (9, 14, 15) comparing
the sequence specificity of different STAT proteins, and in particular,
there are few data on the relative affinity of weak binding sites that
may be the physiological STAT targets. In the course of our previous
work (6), we identified two STAT-binding sites in the interleukin-2
responsive enhancer of the IL-2R Recombinant Proteins and Cell Extracts--
Preparation of
histidine-tagged recombinant human STAT1 and human STAT6 proteins from
insect have been described previously (8). The baculovirus expression
vector pVL1393 (PharMingen) was used. Recombinant human STAT5A was
prepared by the same method. Fig. 3A indicates that these
preparations contain no major impurities. Recombinant STAT5B was also
prepared using a baculovirus expression system. Briefly, rat STAT5B
cDNA (without a histidine tag) was cloned into pFastBac1, and virus
was produced in SF-21 cells. Subsequently, SF-21 cells were coinfected
with STAT5B and murine JAK2 encoding viruses. 60 h post-infection
protein extracts were purified by DNA affinity chromatography, using a
biotinylated oligo with tandem STAT-binding sites and magnetic beads,
according to Dreier et al. (16). SDS-polyacrylamide gel
electrophoresis analysis (not shown) indicates that, as expected, this
preparation is much less pure than that of the histidine-tagged
proteins. Extracts containing endogenous STAT1 were produced as
described previously (9) from BUD 8 fibroblasts.
DNA-binding Site Selection--
The STAT1 and STAT6-binding site
selection experiments that produced the data used in Fig. 2 have been
described previously (8, 9). The selection for STAT1-binding sites was
carried out on a pool of 76-base oligomers (26 random bases sandwiched between two constant 25-base regions containing primer recognition sites) with nuclear extract from interferon- Analysis of in Vitro Selected Binding Sites--
A hidden Markov
model (HMM) was chosen for a formal description of the binding
specificity of individual STAT proteins in the site-selection
experiments. The parameters of the STAT1-, STAT5-, and STAT6-specific
binding site models shown in Fig. 2 were obtained by training the same
initial model shown in Fig. 1 with the respective sequence sets. The
Baum-Welch algorithm as implemented in SAM software release
1.3.3 was chosen as training method for this purpose. All
oligonucleotides were presented in both orientations to the algorithm
taking into account the perfectly symmetric nature of the STAT dimer.
Competitors and Probes--
Oligonucleotides (see Table II for
upper strands) were purchased from Microsynth (Balgach, Switzerland) or
MWG Biotech (Ebersberg, Germany). Complementary oligonucleotides were
annealed by heating and slow cooling in 10 mM Tris (pH
7.4), 1 mM EDTA, 50 mM NaCl and kept at
Competition Assays--
Electrophoretic mobility shift assays
were carried out with the STAT1-responsive element of the
Fc-
The binding buffer for the bandshift reactions contained 10 mM Tris (pH 7.4), 1 mM EDTA, 140 mM
KCl, 10% glycerol, 1 mM dithiothreitol, 10 mM
sodium hydrogen phosphate, 4 mM urea, 0.1 mM
ATP, 20 mM spermine, 1 mg/ml bovine serum albumin, 5 mg/ml
poly(dI-dC).
To optimize binding conditions for recombinant STAT proteins, we
assessed several substances for their capacity to influence STAT-DNA
interactions. Among the compounds tested, the naturally occurring
polyanion spermine considerably increased recombinant STAT binding.
Maximal effects were obtained at the concentration specified above.
Note that spermine had no effect on the formation of STAT5 or STAT6
complexes using crude nuclear extracts from IL-2- or IL-4-stimulated
cells. Salt concentration was chosen to equal approximately the
intracellular concentrations.
For the competition experiments a constant amount of probe was mixed
with graded amounts of competitor, before addition of STAT protein. In
each experiment reactions with different concentrations of unlabeled
reference GRR oligonucleotide were included.
The following amounts of recombinant proteins were used: STAT5A, 15 ng/sample; STAT5B, 150 ng/sample; STAT6, 50 ng/sample; STAT1, 10 ng/sample. Binding reactions (22 µl) were incubated for 150 min at
29 °C and then loaded onto a running 4% nondenaturing polyacrylamide gel, which had been prerun at 4 °C for 30 min. The
binding reaction had reached equilibrium at the time of loading on the gel.
In Vitro Selection Experiments--
Data from binding site
selection experiments with human STAT1 and STAT6 have been partly
published previously, and we used the sequences derived from these
experiments for the analysis described here. For human STAT5A we
carried out a similar procedure, starting with randomized 14-mers
placed between PCR-priming sites. Three cycles of selection were
carried out by isolation of bound fragments from a bandshift procedure,
and the resulting sequences were cloned. 39 clones were subjected to
sequencing (for details see "Experimental Procedures").
These three oligonucleotide sequence sets constitute the raw data from
which the binding site models specific for the individual STAT family
member were generated and they are included as Supplemental Material.
Initial Assumptions, Choice of the Binding Site Model--
The
first critical step in the characterization of the binding specificity
of a transcription factor is the choice of the binding site model. As
mentioned, all STAT proteins are thought to recognize the same
palindromic core motif, TTCN2-4GAA (where Nx is
referred to as spacer). However, the specificities of individual STAT
proteins may differ in the following aspects: (i) differential
tolerance of specific mismatches in the core motif; (ii) preference of
certain bases at flanking positions; and (iii) preferences for
different spacer lengths between the core motif half-sites. In our
model, we included three flanking positions upstream and two flanking
positions downstream of the TTC half-site consensus triplet. The choice
of the length of the sequence analyzed was based on the most distal
contact observed in the co-crystal structure, the G-C base pair located
three positions upstream of the consensus triplet (21). The number of
two downstream positions is dictated by the maximal spacer length. Also
on the basis of crystallographic data, we assumed perfect dyad symmetry of the binding site, and we used each selected sequence in both orientations. Numerically, we express the position-specific base preferences and the spacer length preferences as percentages. Our
model thus contains 35 parameters, 4 × 8 relating to the
different bases at different half-site positions, and 3 to alternative
spacer lengths.
Derivation of STAT1-, STAT5-, and STAT6-specific High Affinity
Binding Site Models from in Vitro Selected
Oligonucleotides--
Estimating the parameters of a binding site
model of the kind described above from in vitro selected
oligonucleotide sequences is not trivial because the oligonucleotides
are longer than the actual binding site, and the location of the
binding site within an oligonucleotide is not often not easy to
determine. A common approach in the analysis of such data is to
manually align putative binding regions according to some prior
knowledge and to tabulate the base frequencies observed in consecutive
columns of the multiple alignment. The drawbacks of such a method are
its lack of reproducibility and circularity. It will be unclear to what
extent such a manual alignment represents initial assumptions or the
true binding specificity of the protein used in the in vitro
selection experiment. This type of procedure is particularly
inappropriate in a case like ours where the goal of the analysis is to
reveal subtle differences in the binding preferences of members of the
same transcription factor family. Circular reasoning is a major problem
when dealing with spacer length variation. If, for instance, we align
STAT5-binding sites by making the assumption that STAT5 can only bind
to N3 sites, we would not find any N4 site in
the resulting multiple alignment, but this would reflect our initial
assumptions rather than an empirical finding. To make claims about
differences between binding specificities, especially with regard to
spacer length preferences of individual STAT family members, we have to
subject the in vitro selected oligonucleotide sets to
exactly the same procedure. This could be achieved by applying the same
ab initio method to all three data sets or by using a model
refinement procedure starting from the same general STAT-binding site
model. Since we do not know of any robust algorithm capable of finding
the optimal binding site model without using an initial assumption for
training sets of the size available to us, we chose the latter approach. The initial model used as common starting point is shown in
Fig. 1. We call it a hidden Markov model
(HMM), because we use an HMM training algorithm for parameter
estimation. Note that the initial model contains some
assumptions about a general STAT-binding site as indicated above but
leaves a great degree of flexibility. We seeded the model only with a
week preference for N3 spacers (50%) because we were
concerned that a stronger preference could mislead the refinement
process in the case of STAT6 that is expected to prefer N4
spacer sites. We chose the same initial preference for N2
spacers as for N4 spacers, primarily to control the
method.
For model refinement we used the Baum-Welch HMM training algorithm.
This method, in conjunction with the specific model architecture chosen, is equivalent to the Expectation Maximization algorithm introduced by Cardon and Stormo (22) for the analysis E. coli promoters. The method was chosen because promoter recognition by Escherichia coli RNA polymerase can be viewed as a
prototype of a protein-DNA interaction governed by a sequence motif
consisting of two conserved blocks separated by a spacer of variable
length. In simplified terms, the Baum-Welch algorithm is an iterative alignment procedure that works as follows. The initial model is used as
a guide to identify and align putative binding sites during the first
iteration. The base and spacer length frequencies of the resulting
multiple alignment define a new model that guides the alignment process
during the second iteration. One expects that each iteration results in
a model that gives a better fit to the training sequences. With
sufficiently large training sets, such an algorithm has a remarkable
capability of overcoming errors in the initial model. In our work this
is exemplified by the increase of the frequency of the N4
spacer class from 25 to 93% during the training with
STAT6-binding oligonucleotides. The simplified algorithm described
above corresponds to the "Viterbi training" variant of the
Baum-Welch algorithm which is more sophisticated in its original form
(for details see Ref. 23).
Comparison of STAT1, STAT5, and STAT6 High Affinity Binding Site
Models--
Like all other STATs, STAT5A shows a very strong
preference for sequences containing two palindromic half-sites
TTC ... GAA (24-26) (Fig. 2 and
numerical values in Table I). We use the
position notation proposed by Chen et al. (21) and
Becker et al. (27), i.e. position
Some of the variation between the matrices may be due to differences
between the conditions of the STAT5A and STAT6 selection experiments on
the one hand and the STAT1 selection on the other hand. However, the
results of the competition experiments described below reveal the same
preference patterns, which strongly suggest that they are not an
experimental artifact.
The hidden Markov modeling confirms the strong preference of STAT6 for
sites in which there are four nucleotides between the two halves of the
palindrome (TTCN4GAA), as is shown
in Fig. 2 and Table I. Nevertheless, STAT6 selected 7% N3
sites (TTCN3GAA), and below we
provide specific evidence that STAT6 can indeed bind to N3
sites. Like STAT1, STAT5A seems to select preferentially N3
sites, but the preference for such sites appears less absolute. Unlike
STAT5A or STAT6, STAT1 appears also to select some N2
sites. Among the oligonucleotides selected in vitro by STAT1
(see Supplemental Material), we found at least one candidate for such a
binding mode (CATCAC TTCCGGAA ATGGCGT).
Comparison of Low Affinity Binding Sites--
We wanted to
investigate whether the differences between the sequence
specificities of the various STAT proteins revealed by the
comparison of the selected high affinity binding sites also apply to
low affinity binding sites. For this purpose we tested the effect of
base changes on the affinities for STAT1, STAT5A and -B, and STAT6. We
used recombinant STAT proteins to avoid effects of unknown cellular
components on DNA binding. To determine relative affinities, we carried
out competition assays in which graded amounts of accurately quantified
double-stranded synthetic oligonucleotides were added as competitors to
a standard binding reaction between a STAT protein and a radioactive
reference probe (for an example see Fig.
3B). For the latter we used
the GRR element of the Fc- Effect of Changing Spacer Length between Palindromic
Half-sites--
To investigate the role of the spacer of the
half-palindromes in the binding of different STATs to low affinity
binding sites, we added a base to the center of the N3
spaced palindrome of the distal STAT consensus site in the
IL-2-responsive enhancer of the murine IL-2R
Insertion of a C at position
It is an inherent characteristic of N4 sites that they
contain N3 spaced palindromes with more or less mismatches.
Thus the VII mIL-2rE site I-var1 sequence contains an N3
site with one mismatch (CAGTTTC
TT
Both STAT5A and STAT5B bound about 12 times better to the spacer N3
than to the spacer N4 sequence. STAT6 favored the spacer N4 site, but
binding was only 3 times stronger than to the spacer N3 site. The
affinity of STAT1 for the spacer N3 sequence was already very low, and
we could not detect significant binding to the N4 sites.
These data suggest that STAT5 can bind, albeit weakly, to
N4 spaced sites with two conserved TTC half-palindromes.
However, as any such site also contains an N3 spaced site
with two mismatches in one of the half-sites, we considered the
possibility that STAT5 does not bind to the N4 half-site
but rather to the N3-spaced half-site with two mismatches.
To test this, we introduced a mismatch into one of the conserved
N4-spaced half-sites of sequence spacer N4 that left the
N3-spaced half-sites with two mismatches unchanged (XI:
spacer N3/N4; GACAAA TTCGCGCGA
Of the 16 N4 spaced sequences tested (see Table II), STAT1
bound only one with detectable affinity. This sequence, the SIE element
of the c-fos promoter, contains one perfect half-site. In
addition it contains a half-site with one mismatch (XI: SIE, tccGTA
TTCCCGT Comparison with Natural Binding Sites in STAT-responsive
Genes--
We compared these spacer preferences with the configuration
of the natural sites described for STAT1, -5, and -6. Genes reported to
be activated by STAT3 and -4 were included for completeness. The
current literature was screened, and enhancer elements claimed to be
targets of STAT1, -3-6 listed in Table
III. The conditions for inclusion in the
table are outlined there. Table III also indicates whether data
derived from gene targeting, with
STAT-deficient cell lines, dominant negative STAT mutants, antisense
RNA, or electroporation of specific antibodies support a role for a
STAT protein. In the following the genes containing the enhancers
compiled in this fashion are referred to as STAT1- and
STAT3-6-activated genes, respectively. Note that in this
analysis, we relied on the published interpretations of the
experiments. The sequences in Table III were thus aligned as shown in
the original publications. Reanalysis of these sites by the same
HMM-based protocol as used for the in vitro selected
oligonucleotides was not possible because for many sites we were
lacking the experimental details delimiting the sequence range shown to
interact with the STAT protein.
All genes found to be activated STAT4 and STAT5 contained a palindrome
spaced by N3 (see Fig. 4 for
a graphic representation of the base frequency matrix derived from the
STAT-activated genes, the numerical values are presented in
Table IV). STAT1-activated genes also contained almost exclusively N3 sites, with the
exception of the 3'-interferon response region element of the
HLA-E gene, which is a half-site. Most of the STAT6 targets
were sites with N4 spacers, but some STAT6-responsive
enhancers did contain N3 sites. It was reported that one of
these sites conferred only a weak response to STAT6 (32). Among the
STAT3 targets, one canonical site with an N2 spacer could
be identified (CRP-APRE element of C-reactive protein), and there were
2 sites with a N4 spacer. We will address the question if
STAT1 can bind to sites with a N4 spacer below.
STATs Do Not Bind to Half-sites in Vitro--
In relation to these
experiments, the question arose whether STATs can bind with detectable
affinity to isolated half-sites. Since the binding site selection
experiments had indicated a strong preference for C at position STAT1 Is More Permissive for Mismatches in Position ±2 of the
Palindrome Than STAT5 and STAT6--
15 of the 26 elements of
"natural" STAT1-activated genes contained mismatches in the
palindromic sequence. All besides one sequence (3'-interferon response
region element of HLA-E gene) showed only a
substitution of a single base per palindromic half-site. In 10 cases
the substitution was in one half-site, and in the 4 other cases both
palindromic half-sites were mutated (cis-acting regions of genes
CD86 (both elements) and GBP-1, distal site of MIG). The most frequent substitution was TTC
The SIE element in the c-fos promoter (XI: SIE', tccGTA
TTCCCG
One of these (VIII, IL-4R) does contain a T at position +2. This
suggests that STAT1 binding to
TTCN3 Defined Bases Inside and Outside of the Palindrome Contribute
to STAT Binding Specificity--
After having analyzed effects of the
spacer and the sequence of the palindromic half-sites on STAT1, -5, and
-6 binding, we wanted to examine the role of the bases between the
half-sites and flanking the palindrome. In the site selection
experiment STAT1 selected very frequently a C in position
On the other hand, a T to C substitution at the same position next to a
half-site with one mismatch (reverse IV: mIL-2rE site II', CTCTC
TT
In the site selection experiments, there was a bias against C at
position The Specificities of STAT5A and STAT5B Are
Indistinguishable--
We investigated if weak affinity binding sites
can distinguish between STAT5A and STAT5B (33-35). The amino acid
sequences of these two proteins are 96% identical, and until now, to
our knowledge, no gene has been shown to be transactivated selectively by only one of the two STAT5 proteins. Nevertheless, analysis of mice
lacking STAT5A (36, 37), STAT5B (38), or both proteins (39) have
revealed that each has essential functions. Comparing the relative
affinity of these two proteins for 29 sequences (Table II), we found no
difference that was significantly greater than two. Thus, it seems
likely that the nonredundancy of STAT5A and STAT5B during development
is a reflection of nonoverlapping cell type-specific expression
of the two proteins or of their capacity to interact with different
proteins required for target gene activation rather than a result of
differences in DNA binding specificity. Our results are in agreement
with the findings of Soldaini et al. (28). Others have
reported that STAT5B binds much more strongly to the APRE element of
the rat Earlier work from many groups had shown that the sequence
specificity of different STAT proteins is very similar but not
identical. The experiments described here define more precisely and
quantify the specificity differences between STAT1, STAT5, and STAT6.
As demonstrated previously (8), STAT6 differs from the other STATs in
its preference for sites in which the two palindromic halves are
separated by 4 rather than 3 nucleotides. Our results confirm earlier
findings of others (15, 30) that this preference is not absolute and
demonstrate that STAT6 can bind N3 sites. In the site
selection experiments STAT6 discriminated against N3 sites
no more than against single base changes in the core consensus region.
The ratio between N4 sites and N3 sites
selected by STAT6 (93:7) is the same as the ratio between sequences
containing T at position In general the differences suggested by the matrices derived from
the sites that were selected for high affinity binding (Fig. 2) are
consistent with the affinity differences of the various STAT proteins
for weaker binding sites. This indicates that the STAT-specific
differences between the high affinity matrices are not due to
variations in the site selection conditions.
There are two characteristics in which STAT1 differs from STAT5 and
STAT6, apart from its inability to bind N4 sites. One is
the preference for C at position The experiments reported here, together with previous studies
from other laboratories, reveal clear differences in the fine specificity of STAT proteins. The finding that these differences are
reflected among the natural target sites of different STATs indicates
that they do contribute to selective gene activation by these proteins.
They may account, for example, for the observation that in the same T
cell line the IL-2R
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ABSTRACT
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DISCUSSION
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gene, and we
showed that this enhancer responds to STAT5 but does not seem to
respond to STAT1 although the sites do bind STAT1 in vitro.
This led us to compare the fine specificities of STAT5 and STAT1. We
included STAT6 in this study, since the domain responsible for sequence
specificity is more similar to that of STAT5 than to the one of STAT1.
First we analyzed base frequency matrices obtained from the sequences
selected by STAT1, STAT5A, and STAT6 in binding site selection
experiments. The results revealed that apart from its preference for
N4 sites, STAT6 selected sites that resembled more the ones
selected by STAT5 than by STAT1. We compared these matrices to the
results from experiments in which we quantified the relative affinity
of a series of weak binding sites for STAT1, STAT5A and -B, and STAT6.
We found that the principles that govern STAT binding to high affinity
sequences equally apply to weak binding sites. Our results are in
reasonable agreement with the sequence pattern among the putative
target sites for various STAT proteins in cytokine-responsive genes. Thus, our results may be useful in predicting which STAT regulates expression of a gene that includes a STAT consensus site in its regulatory elements.
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-treated fibroblasts, according to Ref. 17. Bound oligonucleotides were precipitated with an
anti-STAT1 antibody and protein A-agarose and subsequently amplified by
PCR. Sequences were cloned after five rounds of selection amplification, and 52 clones were sequenced. The sequences of STAT5A-
and STAT6-binding sites were selected from a pool of 50-base oligonucleotides with 14 randomized positions as follows:
5'-GTCTGTCTGAGGTGAGATCTATN14ACAAGCTTGTCTAGCGACGTCGCG-3'. The constant regions 5' and 3' of the randomized positions
contained a SacI or a HindIII site, respectively,
which was used for subsequent cloning. The binding procedure was
carried out essentially as described (18), using recombinant STAT5 and
STAT6. Three rounds of selection by bandshift were performed. Bound
sequences were eluted, and 10 cycles of PCR amplification were used to
amplify the selected oligos for the second and third round using the
following conditions: 1 min at 94 °C, 1 min at 55 °C, and 30 s at 72 °C. PCRs were carried out in 50 µl according to the
specifications of the manufacturer (PerkinElmer Life Sciences), except
that dCTP was replaced by 3 × 10
5
µmol (3,000 Ci/mmol) of [
-32P]dCTP. After the third
mobility shift, the bound DNA was eluted, and a PCR with 20 cycles was
carried out in the absence of radioactive dCTP. The resulting fragments
were cloned and subjected to automated DNA sequencing from which 39 sequences (STAT5A) and 45 sequences (STAT6) were recovered.
80 °C. To control for completeness of annealing, 100 ng of
double-stranded oligonucleotide was fractionated on a nondenaturing
12% polyacrylamide gel that was stained with ethidium bromide after
the run. Oligonucleotide concentrations were verified by running
aliquots on a 12% polyacrylamide gel and comparing the ethidium
bromide signal with that of a titration series of the reference
competitor loaded on the same gel. Adjustments for the differences in
composition of the sequences were made. Serial 2-fold dilutions of the
stock solutions were used in the competition assays.
RI gene (referred to as GRR (19)) as
a probe, which was end-labeled according to standard procedures (20)
with [
-32P]ATP (Amersham Pharmacia Biotech) and
purified on a 12% polyacrylamide gel. After precipitation, the probe
was resuspended in 10 mM Tris (pH 7.4), 1 mM
EDTA, 50 mM NaCl and kept at 4 °C. 30,000 cpm/sample were used per bandshift reaction.
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Fig. 1.
Analysis of in vitro
selected STAT1, STAT5A, and STAT6 sequences. A,
principle of the method and data flow. The individual protein-specific
models were obtained with an HMM training algorithm starting from the
same general STAT binding site model. The data flow diagram serves to
make clear that all three sequence sets were subjected to the same data
analysis procedure. We therefore claim that the differences between the
resulting STAT1-, STAT5-, and STAT6-specific models shown in Fig. 2 are
entirely data driven. B, initial model used in the model
building process. This HMM expresses our assumptions about a general
STAT protein-binding oligonucleotide. HMMs are probabilistic constructs
that define families of related sequences (23). The rectangular
boxes define the base frequencies at particular positions in the
model (the order is A, C, G, T from top to
bottom). The boxes numbered 7 to
1 and +1 to +7 correspond to
individual base positions. The half-sites are connected by three
alternative paths containing 0-, 1-, and 2-base positions,
respectively. The arrows pointing to the right from model
position
1 define the initial frequencies of the three spacer
classes. Note that the half-site regions are seeded with a moderate
preference for TTC and GAA (70% for the consensus base, 10% for each
mismatch). The boxes with loops at the beginning
and at the end of the model represent random sequences of the
oligonucleotides outside the binding regions. The trained models have
the same architecture as the input model but different parameter values
that are shown in Fig. 2 (numerical values are shown in Table I).
2 corresponds
to the C in TTC and +2 to the G in GAA. Unless otherwise specified, we
only refer to one half-site, implying that the complementary is true
for the other half-site. With regard to the central and the flanking
nucleotides, the matrix derived from the STAT5-selected sites resembles
very much the STAT6 matrix, whereas the STAT1 matrix is more loosely
related. Two differences are most striking. (i) Almost all
STAT1-selected sites have a C in position
1, whereas about 40% of
STAT5A- and STAT6-selected sites contain other nucleotides at this
position. Indeed, for STAT1 the requirement for a C at this position
appears to be even more stringent than that for C at position
2. (ii) STAT1 shows a strong preference for G or C at position 0, i.e. the center of the palindrome, whereas neither STAT5A
nor STAT6 strongly select specific nucleotides at this position.
Another interesting difference concerns nucleotide
7. STAT1 has a
preference for C at this position (57%), which translates into a
preference for G at position +7. This is in line with the crystal
structure of STAT1 bound to DNA that shows a contact of glutamate 421 with a guanosine at position +7 and the suggestion that this contact would be impossible with a thymidine at position +7 (21). It would be
interesting to know whether this contact could be observed in crystals
of STAT5A or STAT6 that show no preference for C at this position. Note
further that at position
5 C is strongly avoided by both STAT5A and
STAT6. STAT6, and to a lesser extent STAT5A, also select against C at
position
6. These results are in agreement with the recently
published data of Soldaini et al. (28).
View larger version (36K):
[in a new window]
Fig. 2.
High affinity binding site models for STAT1,
STAT5, and STAT6. The models were derived from primary data
(in vitro selected oligonucleotide sequences) using an HMM
training algorithm as described in the text and in Fig. 1. Only one
half-site is shown since we submitted each oligonucleotide in both
orientations to the data analysis procedure, and the result was
entirely symmetric. The position notation is shown in Fig. 1. The
spacer refers to the number x of nucleotides between the
canonical half-sites (TTCNxGAA). Spacer length frequencies are
the numbers associated with the three arrows pointing to the
right from box 1 of the trained models in Fig. 1.
Base frequency matrices of STAT half-sites derived from selection
experiments (see Fig. 2)
RI gene, as
it binds strongly to STAT1, -5, and -6 (12, 29, 30). Binding reactions
were carried out under conditions that had been optimized in
preliminary experiments (see "Experimental Procedures"). They were
fractionated on nondenaturing polyacrylamide gels. Autoradiographs of
the gels were used to determine the quantities of test and reference
competitor that reduced the amount of bound labeled probe to the same
level (see Fig. 3B). For example the affinity of STAT1 for
sequence II, spacer N3 was calculated in the following way (the roman
number in front of the sequence name designates the class of the
element in Table II for better
orientation). By using 5880 fmol of spacer N3 sequence and 35 fmol of
unlabeled GRR sequence, the shifted bands had the same intensity. The
adjacent bands served as control. We divided the amount of test
competitor by the amount of the reference competitor (5580 fmol/35
fmol = 168), and we rounded the final result to 170 times
reduction of affinity compared with the affinity of the reference
probe. In some instances, gels were also scanned with a PhosphorImager
to verify the accuracy of the results obtained by visual comparison and
to ascertain that the amount of probe added to each reaction and loaded
on the gel was constant. The complete results obtained with 40 sequences are reported in Table II, where they are expressed as the
fold reduction of affinity compared with that for the reference
probe.
View larger version (44K):
[in a new window]
Fig. 3.
A, characterization of recombinant STAT.
Histidine-tagged proteins were produced in insect cells as described
previously. Cells were coinfected with two baculovirus samples, one
encoding JAK2 tyrosine kinase and the other a STAT protein. Tagged
proteins were purified by Ni2+ affinity and analyzed by
SDS-polyacrylamide gel electrophoresis. 500 ng of each protein were
loaded on the gel and stained with Coomassie Brilliant Blue.
Numbers on the side refer to molecular weight standards. We
do not know why STAT5A migrates as a doublet; the upper band
does not represent the phosphorylated portion. B,
experimental procedure for the determination of relative affinities of
STAT proteins. Different amounts of carefully quantified reference or
test competitor were added to bandshift reactions containing a constant
amount of STAT protein and labeled reference probe (see "Experimental
Procedures"). Reactions loaded onto the same gel were compared by
assessment of the resulting autoradiographs. This allows one to
determine with an accuracy of less than 2-fold the amount of test
competitor required to reduce the signal due to the shifted probe to
the same level as a given quantity of reference competitor.
Comparison of the affinities of different DNA sequences for STAT1,
STAT5A, STAT5B and STAT6
response region of the
Fc-
RI gene (19, 41); mIL-2rE site I/II, distal/proximal
GAS element of mouse IL-2R
gene (42); hIL-2rE site I/II,
distal/proximal GAS element of human IL-2R
gene (43, 44);
APRE, acute phase response element of rat
2-macroglobulin gene (45);
, GLS of human
Ig heavy chain germ line gene (46); IL-4R, STAT6-binding
site of human IL-4R gene (30); SIE, sis-inducible element of
human c-fos gene (47); N3-selected, sequence selected in
random selection experiment with STAT5A; N4 artificial 1-3, artificial
N4 sequence 1-3; N4-selected, sequence selected in random selection
experiment with STAT6; N3 artificial 1, artificial N3 sequence 1;
half-site 1-5, artificial half-sites. The sequences designed to test
effect of specific base changes and spacer length are as follows:
spacer N3, reference sequence (N3 spaced palindrome); spacer
cttc, A
C change at position
5; spacer ttcc, G
C change at
position
1; spacer N4, conversion to N4 site by insertion of
a base (see text); spacer N3/N4, A
T change at position 4 (see
text); spacer half, mutation in one side of the palindrome to create a
half-site (see text); no STAT1-2, sequences without STAT-binding
element nor half-sites; suffix var-1, -2... denominates sequence
variations of the original
sites.
gene (III, mIL-2rE site I; ... GTTTC
TTCTGAGAA GTACCA; half-sites of core palindrome
are underlined) (see Table II for complete results).
1 (VII: mIL-2rE site I-var1:
... GTTTC TTCCTGAGAA
GTACC ... ; inserted bases are in italics) resulted in an 8-fold
reduction of STAT5A binding, whereas insertion of a C at position
0
(VII: mIL-2rE site I-var2; ... GTTTC
TTCTCGAGAA GTACC ... ) reduced
binding more than 20 times. This difference is presumably due to the
fact that insertion of a C at position
1 gives rise to a half-site
TTCC, characteristic for high affinity binding
sites. Surprisingly, neither insertion significantly improved STAT6
affinity. In III, mIL-2rE site I the N3 site overlaps with an N4 site (CAGT TTCTTCTGA
5 and +5, respectively. It is possible that STAT6 binds to
this element that is destroyed by the insertions in the mIL-2rE site I variants.
C mutation that induces a second mismatch in the
N4 spaced palindrome (tccGTA
TTCCCGT
A that creates an N3 site with one instead of two
mismatches (tccGTA TTCCCG
Cis-acting elements of STAT-responsive genes
View larger version (25K):
[in a new window]
Fig. 4.
Base frequencies by position derived from
manual alignment of the half-sites of the STAT-responsive elements
described in the literature. The number of half-sites
analyzed was 52 for STAT1, 48 for STAT3, 6 for STAT4, 62 for STAT5, and
22 for STAT6 (for numerical values see Table IV, for full sequences see
Table III).
Base frequency matrices of STAT half-sites of cis-acting elements of
STAT-responsive genes (see Fig. 4 and Table III)
1 for
all proteins tested, and STAT1 had, in addition, selected C or G at
position 0, we reasoned that TTCCC would be an optimal half-site. We
designed an oligonucleotide with this motif, but without a second
half-site (XII: spacer-half, GACAAA TTCCCCAGCTTTGG). This
oligonucleotide did not compete for binding to any of the four STAT
proteins analyzed. Thus, it appears that these STATs cannot bind with
significant affinity to isolated half-sites.
TTA (see
Table III). In contrast to STAT1, the 11 cis-acting elements of
STAT6-activated genes all contained perfect palindromes besides
one (mCD23a STAT6 site). For STAT5 the situation was more complex; all
22 STAT5-activated genes contained one cis-acting element with a
perfect palindrome, but in three of the six genes regulated by more
than one binding site for STAT5, one of the elements contains a TAA
half-site (instead of GAA). These differences suggest that STAT1 is
more permissive for mismatches in vivo. This is consistent
with our in vitro measurements of relative affinity, as
illustrated by the following. Sequence IV, mIL-2rE site II ( ...
ACAT TTCTGA
7 in the site selection experiment (Fig. 2). Note that the
TTCN3
1 (Fig. 2).
Comparing two N3 sequences with conserved half-sites (II:
spacer N3, GACAAA TTCGCCGAA TTTGG, and
II: spacer ttcc, GACAAA TTCCCCGAA
TTTGG) (substituted bases are underlined), we found that substituting a
C for a G at position
1 indeed resulted in a very strong increase in
the affinity for STAT1 but barely had any effect on the affinities of
STAT5 or STAT6.
1 does improve the
affinity of a TTC half-site for STAT1 but not for STAT5 or STAT6, it
should be noted that among natural STAT targets TTCC is as
frequent in the STAT5 as among the STAT1-responsive elements.
5 in the STAT5- and STAT6-specific high affinity binding
site models, whereas STAT1 showed no such bias. We did not observe any
impact of base changes at this position in lower affinity sites.
Substitution of A by C in two weak binding sites (II: spacer N3,
GACAAA TTCGCCGAA TTTGG
versus II: spacer cttc, GACAAC
TTCGCCGAA TTTGG, and reverse IV: hIL-2rE site
II, CTCTA TT
5.
2-macroglobulin promoter than STAT5A (40).
They showed that this is due to a single amino acid difference at
position 433 between STAT5A (glutamine) and STAT5B (glycine). The
significance of their finding is unclear since all of the human, mouse,
or rat STAT5A and STAT5B data base entries predict a glutamine at this position.
DISCUSSION
TOP
ABSTRACT
INTRODUCTION
EXPERIMENTAL PROCEDURES
RESULTS
DISCUSSION
REFERENCES
4 and those with other nucleotides at this
position. With regard to STAT5 we show here that this protein can bind
N4 sites but that its affinity for N3 sites is
much higher. STAT1 appears incapable of recognizing N4
sites. On the other hand, the site selection experiments suggest that
STAT1 but not STAT5 is capable of binding to N2 sites.
Previous experiments indicate that STAT3 may also bind to
N2 sites (15). STAT1 also shows a stronger preference than
STAT5 and STAT6 for C at position
1. Indeed among the 40 sequences
tested in our experiments, the relative affinity of any sequence
without a C in position
1 was at least 50 times lower than that of
the reference probe. In this and in other more subtle aspects, STAT5
and STAT6 are more similar to each other than to STAT1 (see below),
reflecting, presumably, the closer similarity of the STAT5 and STAT6
DNA binding domains.
7. The crystal structure of the
STAT1-DNA complex suggests that the interaction between Glu-421 and the
C at this position is a structural correlate of this preference (see
Supplemental Material). It has not been found in STAT3 crystals, and it
will be interesting to observe whether is also absent in STAT5 and
STAT6 crystals. The other STAT1-specific feature is the capacity of
this protein to bind palindromes with one TTA half-site that are much
less well recognized by STAT5 or STAT6. This difference might be
explained by the fact that the asparagine in STAT1 which makes contacts
with positions 1-3 of the binding site is replaced by a histidine in
STAT5 and STAT6 (see Supplemental Material). A combination of these
STAT1 characteristics may be responsible for the apparently greater
tolerance of this protein for mismatches in the canonical palindrome.
gene is induced by IL-2 whereas the
IL-4R gene responds to IL-4 (7). On the other hand, the
example of the different phenotypes of STAT5A- and of STAT5B-deficient mice reveals that other mechanisms, such as cell type-specific expression of receptors and signaling proteins, protein-protein interactions, and regulation of the chromatin conformation of target
genes contribute to STAT target selection. To determine the relative
importance of these mechanisms will require quite complex experiments.
![]() |
ACKNOWLEDGEMENTS |
---|
The computational analysis of the in vitro selected sequences was performed with resources maintained at the Swiss Institute of Bioinformatics. We thank C. Rusterholz and P. Corthésy-Henrioud for help with the gel-shift experiments and advice; S. Cherpillod for help with the preparation of the manuscript; and F. Guilleux and O. Hagenbüchle for DNA probes. We also thank W. Meyer, F. Meylan, V. Imbert, C. Saner, O. Zilian, and F. Radtke for very useful suggestions and support.
![]() |
FOOTNOTES |
---|
* This work was supported in part by research grants from the Swiss National Science Foundation (to M. N.) and from the Deutsche Forschungsgemeinschaft Grant DFG SFB 473, project B6 (to G. Fey at the University Erlangen-Nürnberg).The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
The on-line version of this article (available at
http://www.jbc.org) contains sequences selected by STAT1,
STAT5A, and STAT6, and Fig. 5.
§ Present address Universität Heidelberg, Im Neuenheimer Feld 346, D-69120 Heidelberg, Germany.
¶ To whom correspondence should be addressed. Tel.: 41-21-692-58-92; Fax: 41-21-652-6933; E-mail: markus.nabholz@isrec.unil.ch.
§§ Present address: NanoTools GmbH, Tscheulinstrasse 21, D-79331 Teningen, Germany.
Published, JBC Papers in Press, October 26, 2000, DOI 10.1074/jbc.M001748200
![]() |
ABBREVIATIONS |
---|
The abbreviations used are: STAT, signal transducer and activator of transcription; PCR, polymerase chain reaction; IFN, interferon; IL, interleukin; oligos, oligonucleotides; HMM, hidden Markov model.
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