The Journal of Immunology
Major Differences in the Responses of Primary Human
Leukocyte Subsets to IFN-b
Anette H. H. van Boxel-Dezaire,* Joana A. Zula,* Yaomin Xu,†Richard M. Ransohoff,‡
James W. Jacobberger,xand George R. Stark*
Treatment of cell lines with type I IFNs activates the formation of IFN-stimulated gene factor 3 (STAT1/STAT2/IFN regulatory
factor-9), which induces the expression of many genes. To study this response in primary cells, we treated fresh human blood with
IFN-b and used flow cytometry to analyze phosphorylated STAT1, STAT3, and STAT5 in CD4+and CD8+T cells, B cells, and
monocytes. The activation of STAT1 was remarkably different among these leukocyte subsets. In contrast to monocytes and CD4+
and CD8+T cells, few B cells activated STAT1 in response to IFN-b, a finding that could not be explained by decreased levels of
IFNAR2 or STAT1 or enhanced levels of suppressor of cytokine signaling 1 or relevant protein tyrosine phosphatases in B cells.
Microarray and real-time PCR analyses revealed the induction of STAT1-dependent proapoptotic mRNAs in monocytes but not in
B cells. These data show that IFN-stimulated gene factor 3 or STAT1 homodimers are not the main activators of gene expression
in primary B cells of healthy humans. Notably, in B cells and, especially in CD4+T cells, IFN-b activated STAT5 in addition to
STAT3, with biological effects often opposite from those driven by activated STAT1. These data help to explain why IFN-b increases
the survival of primary human B cells and CD4+T cells but enhances the apoptosis of monocytes, as well as to understand how
leukocyte subsets are differentially affected by endogenous type I IFNs during viral or bacterial infections and by type I IFN
treatment of patients with multiple sclerosis, hepatitis, or cancer.
II is IFN-g; and type III is IFN-l. IFN-a and -b use the IFNAR1
and IFNAR2c receptor subunits to signal (2), each of which binds
constitutively to a single member of the JAK family of kinases:
IFNAR1 to tyrosine kinase 2 and IFNAR2 to JAK1. Ligand bind-
ing induces the phosphorylation of JAK1, tyrosine kinase 2, intra-
cellular tyrosine residues of each receptor subunit, and STATs.
Activated STATs dimerize, dissociate from the receptor, and trans-
locate to the nucleus to induce the expression of IFN-stimulated
genes [ISGs (3)]. Current data suggest that IFN-stimulated gene
The Journal of Immunology, 2010, 185: 5888–5899.
nterferons are pleiotropic cytokines that play important roles
in infection and inflammation. Three classes of IFNs are known:
type I IFNs includes IFN-a, -b, -v, -t, -d, -k, and -ε (1); type
factor 3 (ISGF3) is the major transcription factor activated in re-
sponse to IFN-a/b (3, 4). ISGF3, a complex of phosphorylated
STAT1, STAT2, and unphosphorylated IFN regulatory factor
(IRF)-9, binds to the IFN-stimulated response element (ISRE)
present in the promoters of many ISGs. In response to type I IFNs,
activated STAT1 can also form homodimers that bind to gamma-
activated sequence (GAS) elements in some ISG promoters (3, 5).
It is becoming clear that, in addition to ISGF3 and STAT1
homodimers, other transcription factors play important roles as cy-
toplasmic messengers between the receptor and the nucleus (4),
helping to explain why type I IFNs, which were discovered on
the basis of their potent antiviral activities, are now known to act
much more broadly, as pleiotropic cytokines that regulate many
different cellular functions. For example, STAT3 is activated in
response to type I IFNs in most cell lines, forming STAT3 homo-
dimers or heterodimers with activated STAT1 (4). In contrast,
activation of STAT4 and STAT5 by IFN-a/b is found mostly in
NK and T cells (6–8). Interestingly, the activation of STAT6 in-
duced by type I IFNs has only been described in B cell lines
(9). STAT homo- and heterodimers bind to GAS elements in the
promoters of ISGs, but it is clear that different STAT dimers have
different preferences for specific GAS elements (5). The differ-
ential activation of STAT4, STAT5, and STAT6 in different cell
lines suggests the possibility of cell type-specific activation of
STATs by IFN-a/b in vivo. Of note, evidence for a cell type-
specific response to IFN-a was described with respect to differ-
ential ISG induction in human T cells and dendritic cells (10).
In this study, we investigated how primary human leukocytes
signal in response to IFN-b. Undiluted freshly drawn human whole
blood was stimulated with IFN-b in vitro to mimic the situation
in vivo as closely as possible. Because the activation of STATs
occurs only transiently, the isolation of many different leukocyte
subsets after stimulation of whole blood in combination with
Western blot analysis is not feasible because, by the time the
subsets could be isolated, the optimal time point for activation of
*Department of Molecular Genetics,†Statistical Genetics and Bioinformatics, De-
partment of Quantitative Health Sciences, and‡Department of Neurosciences, Neuro-
inflammation Research Center, Lerner Research Institute, Cleveland Clinic Foun-
dation, Cleveland, OH 44195; andxCase Comprehensive Cancer Center, Case West-
ern Reserve University, Cleveland, OH 44106
Received for publication July 21, 2009. Accepted for publication August 27, 2010.
This work was supported by Pilot Grant PP1086 and Career Transition Fellowship
Award TA3032A1/1 (to A.H.H.vB-D.) from the National Multiple Sclerosis Society
and by Grants P01 CA06220 (to G.R.S.) and P30 CA43703 (to Gene Expression and
Genotyping Facility of the Case Comprehensive Cancer Center) from the National
Institutes of Health.
The microarray data presented in this article have been deposited into National
Center for Biotechnology Information Gene Expression Omnibus (http://www.ncbi.
nlm.nih.gov/geo/query/acc.cgi?acc=GSE23307) under accession No. GSE23307.
Address correspondence and reprint requests to Dr. George R. Stark, Department of
Molecular Genetics, Lerner Research Institute, Mail Code NE20, Cleveland Clinic
The online version of this article contains supplemental material.
Abbreviations used in this paper: D-PBS, Dulbecco’s PBS; ETS, E–twenty-six; GAS,
gamma-activated sequence; HI, healthy individual; IRF, IFN regulatory factor; ISG,
IFN-stimulated gene; ISGF3, IFN-stimulated gene factor 3; ISRE, IFN-stimulated
response element; PY-STAT, phosphotyrosine-STAT; rtPCR, real-time PCR; SHP1,
Src homology region 2 domain-containing phosphatase 1; SOCS, suppressor of cy-
tokine signaling; TCP45, T cell protein tyrosine phosphatase of 45 kDa.
STATs would have passed. Therefore, we used a flow cytometry-
based technique that enables the detection of intracellular phos-
photyrosine-STAT (PY-STAT)1, STAT3, and STAT5 at the single-
cell level, allowing cells to be fixed at the optimal time for STAT
activation. IFN-b–induced activation of STAT1, STAT3, and STAT5
was chosen because these three transcription factors regulate cell
survival in opposite directions (11–13). Furthermore, this approach
allowed us to address whether differential activation of these STATs
might explain how IFN-b enhances the survival of mature B cells
and T cells (14–19) while increasing apoptosis in monocytes and
many cancer cell lines (20–23). Notably, we found that IFN-b in-
duced significant differences in the activation of STAT1 and STAT5
in different leukocyte subsets and that these differences are related
to the induction of pro- and antiapoptotic genes, respectively. Our
results provide important insights into the differential effects that
type I IFNs may have on leukocyte subsets during infection and
upon treatment of multiple sclerosis, hepatitis, and some cancers
with type I IFNs.
Materials and Methods
Cell culture and IFN-b stimulation
The HT cell line was acquired from the American Type Culture Collec-
tion (Manassas, VA) (CRL-2260, human B lymphoblast derived from a
patient with diffuse mixed lymphoma) and cultured in RPMI 1640 medium
supplemented with 2 mM L-glutamine, 1 mM sodium pyruvate, 4500 mg/l
glucose, and 10% FBS. This cell line was maintained in 10- or 15-cm
culture dishes and was always stimulated at a concentration of 1 3 106
cells/ml with IFN-b1a (Avonex, 30 mg/0.5 ml Prefilled Syringe, 12 3 106
IU/ml; Biogen Idec, Cambridge, MA). Stimulated cells were subsequently
fixed for flow-cytometry analysis or lysed for Western blot analysis.
Heparinized whole blood was obtained from healthy donors according to
an Institutional Review Board-approved protocol (Cleveland Clinic).
Within 15 min after venipuncture, undiluted whole blood was stimulated in
6- or 10-cm culture dishes or 50-ml canonical tubes (BD Biosciences, San
Jose, CA) in vitro with recombinant human IFN-b1a (Biogen Idec), IFN-
a1 (3 3 103IU/ml), IFN-a2 (Intron A, 10 3 103IU/ml; Schering-Plough,
Kenilworth, NJ) or IFN-g (10 3 103IU/ml; Genentech, South San Fran-
cisco, CA), as indicated. For each staining, 130 ml of whole blood was
used. All in vitro stimulations were performed in an incubator at 37˚C
(Thermo Fisher Scientific, Asheville, NC); no cell clumping or adhesion to
tissue culture plates was observed. After stimulation, whole blood was
fixed and lysed for intracellular detection of PY-STATs.
Western blot analysis of HT cells and isolated leukocyte
After stimulation of HT cells with IFN-b1a or after leukocyte subsets were
purified from unstimulated whole blood, the cells were washed once with
PBS, and the cell pellets were lysed for 30 min at 4˚C in 250 ml (per 5 3
106cells) lysis buffer containing 50 mM HEPES (pH 7.9), 250 mM po-
tassium chloride, 0.1% Nonidet P-40, 10% glycerol, 0.1 mM EDTA, 10
mM sodium fluoride, 5 mM sodium orthovanadate, 1 mM phenylmethane-
sulfonyl fluoride, 20 mg/ml aprotinin, 20 mg/ml pepstatin, and 20 mg/ml
leupeptin. Cellular debris was pelleted by centrifugation at 13,000 3 g at
4˚C for 10 min. Cell extracts were fractionated by electrophoresis in 10 or
12% SDS-PAGE and transferred to polyvinylidene difluoride membranes
(Millipore, Bedford, MA). The following Abs were used: rabbit polyclonal
anti-SOCS1 and rabbit polyclonal anti–SH-PTP1 (clones H-93 and C-19,
respectively; Santa Cruz Biotechnology, Santa Cruz, CA), mouse mono-
clonal anti-T cell protein tyrosine phosphatase of 45 kDa (TCP45) (clone
CF4-1D; EMD Chemicals, Gibbstown, NJ), mouse monoclonal anti–N-
terminal STAT1 (clone 42, BD Biosciences), rabbit polyclonal anti–PY701-
STAT1, rabbit polyclonal anti–PY705-STAT3, rabbit polyclonal anti-STAT3,
rabbit polyclonal anti–PY694-STAT5, rabbit polyclonal anti-STAT5 (Cell
Signaling Technology, Beverly, MA), rabbit polyclonal anti–PY689-STAT2
and rabbit polyclonal anti-STAT2 (Upstate Biotechnology, Lake Placid,
NY), and mouse monoclonal anti–b-actin (clone AC-74; Sigma-Aldrich,
St. Louis, MO). HRP-coupled goat anti-rabbit or goat anti-mouse IgG
(Rockland Immunochemicals, Gilbertsville, PA) was used for visualiza-
tion, using the ECL (ECL Plus) Western blot analysis detection system
(PerkinElmer, Waltham, MA).
Intracellular detection of PY-STATs using flow cytometry
The published method of Chow et al. (24), which was developed to measure
intracellular phospho-ERK in whole blood cells, was adapted slightly
to measure the induction of phospho-STATs in human whole blood. A
number of commercially available anti-human CD3, CD4, CD8, CD19,
and CD14 Abs were screened. The best anti-CD3 and anti-CD14 clones
were those that performed optimally after fixation and erythrocyte lysis
but before methanol incubation. In contrast, the best anti-CD8, anti-CD4,
and anti-CD19 Abs performed best after methanol incubation. As pre-
viously published (25), IFN-b–induced phospho-STATs were optimally
detected in leukocytes that were permeabilized with 90% methanol (data
After stimulation with IFN-b1a in vitro or leaving cells untreated for the
same time period, whole blood or cell lines were fixed in 4 or 2% form-
aldehyde, respectively, by adding 10% prewarmed methanol-free formal-
dehyde (Polysciences, Warrington, PA), followed by incubation at 37˚C for
10 min. After fixation, cell lines were washed twice with 50 ml ice-cold
wash buffer (Dulbecco’s PBS [D-PBS], 5% FBS, 0.09% NaN3). Eryth-
rocytes were lysed by adding 0.12% Triton X-100 (0.1% Triton X-100 final
concentration; Pierce, Rockford, IL) dissolved in 13 D-PBS and in-
cubating for 30 min at room temperature with rocking. Lysed erythrocytes
were removed by washing three times with 50 ml ice-cold wash buffer,
followed by spinning at 300 3 g for 10 min at 4˚C. One hundred micro-
liters of fixed cells was subsequently added to each 5-ml Falcon FACS
tube (equivalent to 100 ml HT or 130 ml whole blood per tube), contain-
ing FITC- or Pacific blue-conjugated anti-CD3 (clone UCHT1; BD Bio-
sciences), anti–CD14-FITC (clone RM052; Beckman Coulter, Miami, FL),
or anti–CD14-AF700 (clone TU ¨K4, Invitrogen, Carlsbad, CA) Abs in the
amounts recommended by the manufacturers. Cells were incubated for 30
min at room temperature in the dark and washed twice: once with 2 ml ice-
cold wash buffer per tube and once with 2 ml ice-cold 13 D-PBS. While
vortexing at high speed, 1 ml 90% methanol in 13 D-PBS was added per
tube, and the mixture was incubated at 220˚C overnight. The next day,
the contents of each tube were washed twice with 2 ml wash buffer (with
spinning at 300 3 g, 4˚C). For the blocking step, the cell pellets were
resuspended in 50 ml wash buffer and incubated for 10 min at room
temperature in the dark. A combination of Abs directed against human
CD8 (clone B9.11, PE-Cy5 conjugated; Beckman Coulter), CD19 (clone
J4.119, PE-Cy5 or PE-Cy7 conjugated; Beckman Coulter), or CD4 (clone
13B8.20, PE-Cy5 conjugated; Beckman Coulter) and the following Alexa
Fluor 647- or PE-conjugated Abs against PY(701)-STAT1, PY(705)-
STAT3, or PY(694)-STAT5 (clones 4A, 4, and 47, respectively, BD Bio-
sciences) were added in amounts advised by the manufacturer, followed by
incubation at room temperature in the dark for 1 h. Anti-CD8 or anti-CD4
Abs were used; the alternative T cell subset was identified by selecting
the CD82CD3+or CD42CD3+population, respectively. To detect total
STAT1, cells were incubated with anti–STAT1-PE (N terminus of STAT1,
clone 1/Stat1; BD Biosciences) after permeabilization with 90% methanol.
To detect the activation of STAT2, rabbit polyclonal anti-PY(689)-STAT2
(Upstate Biotechnology) was added at 6.5 mg/ml. Experiments demon-
strating the specificity of this anti–PY-STAT2 Ab are shown in Supple-
mental Fig. 1A and 1B. For the fluorochrome-conjugated Abs, the last
wash step was performed with 3 ml wash buffer per tube (300 3 g; 10 min;
4˚C). To detect PY-STAT2, cells were incubated with 5 ml of a 1:10 di-
lution of goat anti-rabbit IgG-PE (Jackson ImmunoResearch Laboratories,
West Grove, PA) at room temperature for 30 min. After the final washing
step, each cell pellet was resuspended in 350 ml wash buffer and measured
on an LSRI or LSRII (both from BD Biosciences) flow cytometer. Samples
stained with a single color were used for compensation. Intact cells were
gated on forward and side scatter, and 50,000 cells were measured. Flow
data were analyzed with WinList (Verity Software House, Topsham, ME).
The percentage of IFN-b–induced phospho-STAT+cells was determined
by subtracting the percentage of positive cells in unstimulated cells, which
was set at ,2%. An example of an analysis is shown in Fig. 2.
Detection of IFNAR2 and caspase 3 activation by flow
Unstimulated and undiluted whole blood (150 ml) was incubated with
mouse anti–IFNAR2-PE (clone MMHAR-2; R&D Systems, Minneapolis,
MN) or control mIgG2a-PE (clone G155-178; BD Biosciences), as rec-
ommended by the manufacturer, in combination with the same anti-CD
Abs as mentioned above, for 30 min at 4˚C. Whole blood cells were
subsequently fixed, and erythrocytes were lysed as mentioned above, and
after the washing steps, the cell pellet was resuspended in 350 ml wash
buffer and measured on a LSRII (BD Biosciences) flow cytometer the
The Journal of Immunology 5889
To detect induction of apoptosis, whole blood that was diluted 1:3 with
plain RPMI 1640 was not stimulated or was stimulated with 2000 IU/ml
IFN-b for different time periods up to 48 h at 37˚C or was kept at 50˚C for
1 h (positive control). Cells were then washed one time with 25 ml 13
D-PBS, and whole blood was divided (150 ml/tube) and incubated with
the same anti-CD Abs as mentioned above for 30 min at 4˚C. Whole
blood cells were subsequently fixed, and erythrocytes were lysed as
mentioned above; after the washing steps, each pellet was eventually
resuspended in 100 ml Permeabilization Medium B (Invitrogen) and in-
cubated with 20 ml anti-activated caspase 3-PE Ab (0.25 mg) for 30 min at
room temperature. Finally, after each tube was washed with 3 ml stain
buffer, the cell pellet was resuspended in 350 ml stain buffer and measured
on a BD Biosciences LSR II flow cytometer the same day. Induction of
activated caspase 3 in leukocyte subsets by IFN-b was determined by
subtracting the percentage of caspase 3+cells in unstimulated cells from
those in IFN-b–stimulated cells.
GraphPad InStat 3 was used (GraphPad Software, La Jolla, CA). The
Friedman test, which is a nonparametric repeated-measures ANOVA for
paired samples test, was used to test whether the four blood cell subsets
(monocytes, B cells, and CD8+and CD4+T cells) differed with respect
to activation of STAT1, STAT3, and STAT5. When the Friedman test
showed a significant difference (p , 0.05), post hoc analysis was sub-
sequently performed using the Dunn test to detect which blood subsets
differed significantly from each other. When calculating the p values, the
Dunn test takes into account the number of comparisons one is making
(Bonferroni adjustment). The Pearson correlation test was used to de-
termine whether the percentages of PY-STAT+leukocyte subsets that
were induced after stimulation with IFN-b for 45 min correlated with the
percentage of activated caspase 3+subsets after longer periods of stim-
ulation with IFN-b. The coefficient of determination (R2) and the two-
tailed p values are shown (if significantly correlated).
Blood cell subset isolation, gene-array analysis, and real-time
Twenty-two milliliters of undiluted whole blood from each of two healthy
donors was stimulated with 2000 IU/ml IFN-b1a (Avonex, Biogen Idec) for
3 h, and 22 ml of blood was left unstimulated for 3 h. An aliquot of blood
was taken out after 45 min of stimulation with IFN-b to determine the
activation of STAT1, STAT3, and STAT5 by flow cytometry. Immediately
following stimulation for 3 h, 10 ml whole blood was incubated with 500
ml whole blood anti-CD14 or anti-CD19 microbeads (Miltenyi Biotec,
Auburn, CA) for 15 min at 4˚C to isolate monocytes and B cells, re-
spectively. After washing with cold running buffer (PBS, 2 mM EDTA,
0.5% BSA, 0.09% sodium azide; Miltenyi Biotec) to remove unbound
microbeads and after bringing the volume of the whole blood back to the
starting volume by adding cold running buffer, the cells of interest were
positively selected using the AutoMACS Pro Separator (Miltenyi Biotec)
and program posselWB. During the entire isolation procedure, the
blood cells were kept cold. The procedure is very fast (maximally 20 min),
which helps to preserve the quality of the RNA. The purity (90–99%) of
the positively selected fraction and the yield were excellent, because the
negative sorted fraction was totally depleted of each subset of interest.
Total RNAwas isolated from the isolated unstimulated (control) or IFN-b–
stimulated blood cell subset by dissolving the cells in TRIzol (Invitrogen;
1–10 3 106cells in 1 ml), following the protocol of the manufacturer. One
microgram of total RNA (100 ng is minimally needed) was sent to the
Cleveland Clinic Genomics Core. A single round of in vitro transcription
amplification was carried out using the Illumina RNA Amplification Kit
(Ambion, Austin, TX) to amplify mRNA and, thus, to obtain ample
amounts of cRNA to perform the whole human genome gene-expression
assay using the humanRef-8 v2 expression bead chips microarray (Illu-
mina, San Diego, CA), which has 22,184 transcript probes, representing
18,189 genes in total. The microarray data discussed in this publication
have been deposited in the National Center for Biotechnology Informa-
tion’s Gene Expression Omnibus and are accessible through GEO Series
accession number GSE23307. Expression data normalization and differ-
ential expression analysis were handled through the Illumina BeadStudio
Gene Expression module V3.2. The data were first normalized by using the
Illumina background normalization algorithm and then the differential-
expression analyses were performed using Illumina’s custom model.
Downstream data processing and reporting were handled in R packages
(http://www.r-project.org). Genes for downstream analyses were filtered to
include only those with both differential-expression analysis p values ,
0.001 and fold changes .2 compared with the unstimulated (control)
condition. Genes in this filtered list were further grouped into those that
were changed in all B cells and monocytes, those that were changed in
monocytes only, and those that were changed in B cells only (healthy
individual [HI] #1 and HI #2). The Gene Ontology Enrichment Analysis
Software Toolkit (available at http://omicslab.genetics.ac.cn/GOEAST/)
was used to sort these groups of genes according to gene ontology, par-
ticularly apoptosis, proliferation, and cell-cycle regulation.
Real-time PCR (rtPCR) was used to confirm changes in gene expression
obtained by microarray analysis. rtPCR was done with RNA isolated from
B cells and monocytes (present in whole blood of six healthy individuals,
and purification occurred after stimulation of whole blood, as mentioned
above), which were left untreated or were stimulated with 2000 IU/ml IFN-b
for 3 h. Thus, rtPCR was performed with 24 samples to detect changes
in seven mRNAs. The following seven TaqMan Gene Expression Assays
from Applied Biosystems (Foster City, CA) were used (gene, assay ID
number): BAK1, Hs00832876_g1; CASP3, Hs00263337_m1; CDKN1A,
Hs00355782_m1; BCL2L13, Hs00209789_m1; STK3, Hs00169491_m1;
IL2RA, Hs00907779_m1; and NAMPT, Hs00237184_m1. Two candidate
genes were chosen for endogenous control determination based on studies
about rtPCR performed with RNA from B cells and monocytes: eukaryotic
18S rRNA and HPRT1. An Applied Biosystems ABI 7900HT unit with
automation attachment was used for rtPCR. This unit is capable of col-
lecting spectral data at multiple points during a PCR run. To execute the
first step and make archive cDNA, 150 ng total RNA was reverse tran-
scribed in a 25-ml reaction using Applied Biosystems enzymes and re-
agents, in accordance with the manufacturer’s protocols. RNA samples
were accurately quantitated using an ND-1000 spectrophotometer (Nano-
drop Technologies, Wilmington, DE). The cDNA reaction from above was
diluted by a factor of 10. For the PCR step, 9 ml this diluted cDNA was
used for each of three replicate 15-ml reactions carried out in a 384-well
plate. Standard PCR conditions were used for the Applied Biosystems
assays: 50˚C for 2 min, 95˚C for 10 min, followed by 40 cycles of 95˚C
for 15 s alternating with 60˚C for 1 min each. The comparative cycle
threshold method was used for relative quantitation. 18S rRNA had very
little variation in expression across the sample sets; therefore, it was
chosen as the endogenous control. For rtPCR data analysis, RNA abun-
dance was normalized for each gene with respect to the endogenous
control in that sample (18S), and mean values for fold changes were cal-
culated for each gene (IFN-b stimulated over control treated). PCR con-
firmation of gene-expression array data required that the direction of the
change in expression had to be the same with rtPCR as with gene-
expression arrays and be increased $2-fold.
Exposure to low doses of IFN-b causes differential activation of
STAT1, STAT3, and STAT5 in primary human blood cell subsets
To verify Ab specificity, we compared our flow cytometry method
to Western blot analysis, using the human leukemic cell line HT,
which was stimulated with 1000 IU/ml of IFN-b (Fig. 1). The two
methods yielded the same overall pattern. Of note, the highest
percentage of PY-STAT+HT cells was found 30 min after stim-
ulation with IFN-b, as usually found in human cell lines. The
advantage of flow cytometry is that it reveals the percentage of
each cell subset in which a certain STAT is activated (Figs. 1, 2).
To begin to investigate how primary human monocytes, B cells,
and CD4+and CD8+T cells respond to IFN-b, we stimulated
undiluted whole blood samples from nine healthy individuals with
500 IU/ml of IFN-b for 25 min (Fig. 3A). We observed significant
differences in the fractions of leukocyte subsets in which STAT1
(p # 0.0001), STAT3 (p = 0.003), and STAT5 (p = 0.006) were
activated. Unexpectedly, remarkably few B cells and CD4+T cells
showed activation of STAT1 in comparison with monocytes. The
differences in activation of STAT3 were very similar to those seen
for the activation of STAT1; much fewer B cells and CD4+T cells
displayed activation of STAT3 compared with monocytes. Thus,
of the blood cell subsets investigated, the highest percentage of
PY-STAT1+and PY-STAT3+cells were found among monocytes,
whereas the percentages of CD8+T cells positive for PY-STAT1
and PY-STAT3 were intermediate (Fig. 3A). In contrast, many
more CD4+T cells than B cells showed activation of STAT5 when
whole blood was stimulated with 500 IU/ml IFN-b for 25 min.
5890 IFN-b–INDUCED RESPONSES IN HUMAN BLOOD CELL SUBSETS
Exposure to low doses of IFN-b causes differential activation
of STAT1 and STAT5 in primary human blood cell subsets at
the optimal time for PY-STAT induction
Although 25 min of stimulation with IFN-b is optimal for STAT
activation in many cell lines, it is possible that this is not optimal
in CD4+T cells and B cells in whole blood. Therefore, blood sam-
ples from three healthy individuals were stimulated with 500 IU/
ml of IFN-b for various times, up to 75 min (Fig. 4). The greatest
activation of STAT3 and STAT5 was detected in all blood cell
subsets after 45 min of exposure to IFN-b; it declined gradually
thereafter. Optimal activation of STAT1 in CD8+T cells and
monocytes was also found after 45 min. Interestingly, although the
IFN-b–induced activation of STAT3 in CD4+T cells and B cells
was very low after 25 min (#15%), it increased by $ 1.8-fold
(between 22 and 32% on average) after 45 min. In contrast, the
activation of STAT1 in CD4+T cells, as well as B cells, remained
very low for the entire period tested (,10% positive cells).
Because the optimal time point for activation of STATs in whole
blood cells was 45 min, we tested whether the same significant
differences in PY-STAT1, PY-STAT3, and PY-STAT5 induction
whole blood from seven healthy subjects was stimulated with 500
IU/ml IFN-b for 45 min (Fig. 3B). There were significant differ-
ences in the fractions of blood cell subsets that showed activation of
STAT1 (p = 0.0005) andSTAT5 (p = 0.025). Thus,even after longer
stimulation with IFN-b, much fewer B cells and CD4+T cells
showed induction of PY-STAT1 than did monocytes, whereas more
CD4+T cells than CD8+T cells showed activation of STAT5 (Fig.
STAT3+cells, the difference, compared with B cells and CD4+
T cells, was no longer significant. Therefore, the activation of
STAT3 by IFN-b in CD4+T cells and B cells is delayed compared
with activation of STAT3 in CD8+T cells and monocytes, in par-
ticular after 25 min (Fig. 3A), but it eventually catches up after 45
min (Figs. 3A, 3B, 4).
Exposure to high-dose IFN-b also causes differential
activation of STAT1, STAT3, and STAT5 in primary human
blood cell subsets
Because the observed induction of PY-STATs at the optimal times
occurred in #50% of the cells after stimulation with 500 IU/ml
IFN-b, we explored whether stimulation with higher concentra-
show the same pattern. The leukemic human B cell line HTwas stimulated
with 1000 IU/ml of IFN-b1a. Cells were lysed and subjected to Western
blot analysis (A) or fixed and stained to determine the percentage of cells
with PY-STATs by flow cytometry (B).
Flow cytometric and Western blot analyses of PY-STATs
ml of IFN-b1a or was untreated for 45 min. After processing as described in Materials and Methods, the cells were analyzed by flow cytometry. CD14+
(monocytes) and CD4+/CD3+(CD4+T cells) were determined within the live gate. The percentages of IFN-b–induced PY-STAT+cells within each
leukocyte subset was determined by subtracting the percentages of positive unstimulated cells, which were set at ,2%.
Analysis of activation of STAT1 and STAT5 in human leukocytes. Undiluted whole blood from a healthy donor was stimulated with 500 IU/
The Journal of Immunology 5891
tions of IFN-b would yield a higher percentage of cells positive
for PY-STATs. We stimulated whole blood of three healthy indi-
viduals with increasing doses of IFN-b (up to 10,000 IU/ml) for
45 min (Fig. 5). At a concentration of 200 IU/ml, virtually no acti-
All four subsets responded with activation of STAT3 and STAT5 at
500 IU/ml, and more cells became positive at the higher concen-
trations. Furthermore, the activation of STAT1 by IFN-b was also
dose responsive in CD8+T cells and monocytes. Remarkably, it
was still observed that very few B cells and CD4+T cells (#10%)
showed activation of STAT1, even at the higher concentrations of
IFN-b (2,000–10,000 IU/ml).
To test whether the same differences in STAT1 and STAT5
activation could be observed with 2,000 IU/ml as with 500 IU/ml
IFN-b, whole blood from 20 healthy subjects was stimulated for
45 min with the higher concentration (Fig. 3C); 2,000 IU/ml was
used instead of 10,000 IU/ml because the activation of STAT1 in
monocytes and B cells was lower with the latter concentration
(Fig. 5). At 2000 IU/ml of IFN-b, there were significant differ-
ences in the fractions of blood cell subsets that showed activation
of STAT1 (p , 0.0001), STAT3 (p = 0.0026), and STAT5 (p ,
0.0001). Remarkably, in contrast to the lower dose, using this high
dose of IFN-b to stimulate whole blood of many donors also
revealed high numbers of PY-STAT1+CD4+T cells (Fig. 3C).
However, even at such a high concentration of IFN-b, much fewer
B cells than monocytes and CD4+and CD8+T cells activated
STAT1. Also, fewer B cells than monocytes activated STAT3 and
STAT5 (Fig. 3C). Of interest, the highest fraction of PY-STAT5+
cells was still found among the CD4+T cell subset (Fig. 3C).
In summary, irrespective of IFN-b concentration or stimulation
time, peripheral blood B cells do not show appreciable activation
of STAT1 in response to IFN-b, indicating that ISGF3 or STAT1
homodimers are not the main transcription factors driving ISG
induction in the majority of primary human B cells or in CD4+
T cells at lower IFN-b concentrations. In contrast, these subsets
show activation of STAT3 and STAT5, and the highest activation
of STAT5 occurs in CD4+T cells.
distinctive STAT-activation patterns in different leukocyte subsets. Un-
diluted whole blood of healthy donors was left untreated or was stimulated
with 500 IU/ml of IFN-b1a for 25 min (9 persons) (A) or 45 min (7
persons) (B) or with 2000 IU/ml IFN-b1a for 45 min (20 persons) (C), and
induction of PY-STAT1, PY-STAT3, and PY-STAT5 was determined. The
geometric means 6 SEM of the various donors are shown for the per-
centages of leukocyte subsets positive for each PY-STAT. The Friedman
test revealed significant differences in the activation of STATs among the
four leukocyte subsets. The Friedman test was followed by post hoc
analysis, revealing significant differences in STAT1, STAT3, or STAT5
activation between the subsets (indicated by arrows). pp , 0.05; ppp ,
0.01; pppp , 0.001.
In vitro stimulation of whole blood with IFN-b reveals
stimulation with IFN-b is optimal after 45 min. Undiluted whole blood
from three healthy donors was stimulated or not with 500 IU/ml IFN-b1a
for different time periods. The geometric means 6 SEM of the three do-
nors are shown for the percentages of leukocyte subsets positive for each
Activation of STATs in primary human blood cells after
5892IFN-b–INDUCED RESPONSES IN HUMAN BLOOD CELL SUBSETS
Differential activation of STAT1, STAT3, and STAT5 in
leukocyte subsets by IFN-b is associated with differences in
Activation of STAT1 usually leads to induction of cell-cycle arrest
and apoptosis, whereas enhanced survival and proliferation result
from PY-STAT3 and PY-STAT5 induction. Therefore, we explored
whether the differential activation of these STATs could be re-
sponsible for previously unexplained differences in induction of
apoptosis in the various primary human leukocyte subsets by IFN-
b. To this end, whole blood from four healthy subjects was
stimulated with IFN-b for 4, 6, 8, 10, 12, 24, or 48 h; apoptosis
induction in the various subsets was determined by the activation
of caspase 3 (Fig. 6A). Stimulation with IFN-b induced the greatest
apoptosis in monocytes, much less in CD8+T cells, and the least in
B cells and CD4+T cells (Fig. 6A), in agreement with previous
reports. Using the blood of the same donors, the induction of PY-
STAT1, PY-STAT3, and PY-STAT5 was also determined after stimu-
lation with IFN-b for 45 min in vitro. Interestingly, in none of the
leukocyte subsets did we observe a correlation between the total
percentages of PY-STAT1+cells after 45 min and the percentages of
activated caspase 3+cells at any of the later time points (data not
shown). This result might be explained by the fact that many of the
PY-STAT1+cells are actually doubly positive for PY-STAT3 and
PY-STAT5, resulting in opposing effects on apoptosis induction
at an individual cell level. Therefore, a double staining was also
performed with anti–PY-STAT1/PY-STAT3 or anti–PY-STAT1/PY-
STAT5 Abs to detect doubly positive cells after IFN-b stimula-
tion. Fig. 6B shows that the induction of PY-STAT1+/PY-STAT32,
PY-STAT1+/PY-STAT3+, PY-STAT12/PY-STAT3+, PY-STAT1+/PY-
STAT52, PY-STAT1+/PY-STAT5+, or PY-STAT12/PY-STAT5+pos-
itive cells among the four leukocyte subsets is strikingly different.
For instance, the percentage of PY-STAT1+/PY-STAT32cells is
highest in CD4+T cells, followed by CD8+T cells, and it is lowest
in B cells and monocytes (Fig. 6B). In contrast, the percentage of
PY-STAT1+/PY-STAT52cells is highest in CD8+T cells, followed
by CD4+T cells and monocytes, but again is lowest in B cells.
Remarkably, the generation of PY-STAT12/PY-STAT3+and PY-
STAT12/PY-STAT5+positive cells could only be observed in the
B cells subset (Fig. 6B), because in this subset IFN-b induced the
lowest percentage of PY-STAT1+cells. The monocyte subset showed
the highest amount of apoptosis induction by IFN-b; Fig. 6A illus-
trates that after 8 h of stimulation, significant apoptosis induction
could be observed for the first time in all four donors tested. Strik-
ingly, the generation of PY-STAT1+/PY-STAT32monocytes after 45
min correlated very significantly with the fraction of activated cas-
pase 3+monocytes after 8 h of IFN-b stimulation (p = 0.0008;
Fig. 6C). Of note, after 10 or 12 h of IFN-b stimulation, the number
of activated caspase 3+monocytes doubled or tripled, compared
with 8 h of stimulation (Fig. 6A), suggesting that apoptosis was
induced eventually, even in PY-STAT1+/PY-STAT3+or PY-STAT1+/
PY-STAT5+monocytes. None of the other subsets showed a corre-
lation between induction of PY-STAT1+/PY-STAT32or PY-STAT1+/
PY-STAT52after 45 min with apoptosis induction after 8 h (data not
shown), but this could be because individual donors showed varia-
tion in the B cell or CD4+or CD8+T cell subsets with respect to
significant activation of caspase 3. Therefore, the highest observed
activation of caspase 3 within the Tand B cell subsets offour healthy
subjects (based on Fig. 6A, CD4+T cells: at 6 h, 6 h, 10 h, and 12 h;
CD8+T cells: at 4 h, 6 h, 10 h, and 10 h; and B cells: at 10 h, 10 h,
12 h, and 12 h) was plotted against the percentage of PY-STAT1+/
PY-STAT32cells after 45 min, revealing a significant correlation
only within the CD8+T cell subset (Fig. 6C; p = 0.0357). Because
this subset has the highest percentage of PY-STAT1+/PY-STAT52
cells, many of the PY-STAT1+/PY-STAT32CD8+T cells are likely
to be PY-STAT1+/PY-STAT32/PY-STAT52and prone to apoptosis
induction. In contrast, CD4+T cells and B cells have the lowest per-
centages of PY-STAT1+/PY-STAT52cells and, consequently, pos-
sibly the lowest amount of apoptosis induction due to the antiapo-
ptotic effects in PY-STAT1+/PY-STAT5+cells.
Differential activation of STAT1 in primary human monocytes
and B cells is connected to differential induction of
apoptosis-promoting mRNAs by IFN-b
We investigated whether the observed differential activation of
STAT1 in B cells and monocytes would result in differences in
mRNAs. To this end, undiluted whole blood from two healthy
individuals was stimulated with 2000 IU/ml of IFN-b for 3 h, and
pure B cells and monocytes were isolated by using magnetically
labeled Abs. An aliquot of blood was taken out after 45 min of
stimulation with IFN-b to detect the activation of STAT1, STAT3,
and STAT5 by flow cytometry. Supplemental Fig. 2A shows the
whole blood cell subsets. Undiluted whole blood of three healthy donors
was stimulated or not with increasing concentrations of IFN-b1a for 45
min. PY-STAT1, PY-STAT3, and PY-STAT5 were determined in leukocyte
subsets as indicated. Geometric means 6 SEM of three healthy donors are
shown for the percentages of PY-STAT+blood cells.
Dose responses for stimulation of PY-STATs with IFN-b in
The Journal of Immunology 5893
expected differential activation of STATs in B cells and monocytes
from two healthy individuals. Remarkably, mRNA induction by
IFN-b was very different in primary human B cells and mono-
cytes. Three hours of stimulation with IFN-b caused 1462 mRNAs
to be up- or downregulated by $2-fold in monocytes or B cells
(836 upregulated, 626 downregulated). Fig. 7A shows the Venn
diagram of the 836 mRNAs that were increased by $2-fold in
monocytes and B cells in response to IFN-b. Remarkably, of the
mRNAs that changed in the monocytes of HI #1, 337 of 596
(57%) were increased in monocytes only, whereas 233 of 596
(39%) were shared between monocytes and B cells of HI #1, and
229 of 596 (38%) were shared with B cells of HI #2. In contrast,
the responses in B cells of HI #1 and HI #2 were very similar,
because 316 mRNAs of 405 (HI #1) or 410 (HI #2) were increased
by 2-fold (78 and 77%, respectively).
The mRNAs that increased by $2-fold in monocytes only
were sorted according to their ontology, using the Gene Ontology
Enrichment Analysis Software Toolkit program. The following
mRNAs, increased in monocytes only, are classified as inducers of
programmed cell death: CDKN1A, BAK1, BCL2L13, CASP3, and
STK3 (Table I); they are all known to be very potent apoptosis-
inducing proteins (26–29). The mRNA of CDKN1A (p21 or Cip1)
was increased 3-fold in monocytes, whereas the mRNA expression
in B cells of both healthy individuals remained unchanged. The
induction of p21 is dependent on binding of activated STAT1 to the
GAS element in the p21 promoter after IFN-g stimulation (27).
Likewise, increased expression of CASP3 is dependent on STAT1
activation (28). Although it has not been conclusively shown
that expression of BAK1, BCL2L13 (BCL-RAMBO), and STK3 are
dependent on the activation of STAT1 homodimers, this conclusion
is very likely to be correct because all of these mRNAs are induced
after IFN-g stimulation (29) (http://www.interferome.org).
After IFN-b stimulation, some mRNAs were induced $2-fold
in B cells and monocytes (TNFSF13B, IRF1, TNFSF10, FAS;
Table I). TNFS10 (TRAIL) and FAS cause apoptosis in cancer
cells but not necessarily in normal immune cells (30, 31). Remark-
ably, after sorting the mRNAs that were increased by $2-fold in
B cells only according to their ontology, we did not find any mRNA
to be related to apoptosis induction or cell-cycle arrest. In contrast,
IL2RA and PBEF1 are two mRNAs that were increased in primary
human B cells only (Table I), and TNFSF13B (BAFF) was in-
creased 3.5-fold more in B cells compared with monocytes (Table
I). These mRNAs are all related to increased survival and pro-
liferation (32–36). Of note, IL2RA and PBEF1 are induced by type I
IFNs only and not by IFN-g (http://www.interferome.org). In re-
sponse to IL-2 or IL-6, the mRNAs of IL2RA and PBEF1 are known
to be increased after binding of activated STAT5 or STAT3 (32, 35),
respectively, to the promoters. Because IL-10 increases the ex-
pression of TNFSF13B mRNA, the enhanced transcription is likely
dependent on PY-STAT3 binding to the TNFSF13B promoter (36).
Because only B cells show the formation of PY-STAT12/PY-
STAT3+and PY-STAT12/PY-STAT5+cells after stimulation with
from four healthy donors was stimulated or not with 2000 IU/ml IFN-b for varying times. Induction of activated caspase 3 in leukocyte subsets by IFN-b
was determined by subtracting the percentage of caspase 3+cells in unstimulated cells from those in IFN-b–stimulated cells; results are shown for in-
dividual donors. B, Undiluted whole blood from five healthy donors was stimulated or not with 2000 IU/ml IFN-b for 45 min. Geometric means 6 SD of
five donors are shown for PY-STAT1+/PY-STAT32, PY-STAT1+/PY-STAT3+, PY-STAT12/PY-STAT3+, PY-STAT1+/PY-STAT52, PY-STAT1+/PY-STAT5+,
and PY-STAT12/PY-STAT5+–positive subsets. C, Data from four healthy individuals (data of Fig. 6A and 6B combined) are depicted: induction of PY-
STAT32/PY-STAT1+-positive monocytes and CD8+T cells after stimulation with IFN-b for 45 min correlated with caspase 3 activation after 8 and 4–10 h,
Differences in activation of STAT1 in leukocyte subsets are associated with variation in induction of apoptosis. A, Undiluted whole blood
5894 IFN-b–INDUCED RESPONSES IN HUMAN BLOOD CELL SUBSETS
IFN-b (Fig. 6B), it is likely that activated STAT5 and STAT3 cause
the increases in IL-2RA, PBEF1, and BAFF in B cells only.
To confirm these microarray data from two healthy individuals,
the induction of specific mRNAs in monocytes and B cells after
3 h of stimulation with IFN-b was replicated in six healthy
individuals. After 45 min of stimulation, the activation of STAT1,
STAT3, and STAT5 showed the typical pattern (Supplemental Fig.
2B). Induction of BCL2L13 and IL2RA mRNA was not replicated
by rtPCR, but we confirmed increased BAK1, CASP3, CDKN1A,
and STK3 mRNAs (in monocytes only) and an increase in PBEF1
mRNA (in B cells only) after IFN-b stimulation (Fig. 7B). In
summary, the differential activation of STAT1 by IFN-b in pri-
mary human monocytes and B cells is associated with very sig-
nificant differences in mRNA induction. High activation of STAT1
in monocytes is related to an increase in the expression of potent
inducers of apoptosis, whereas poor STAT1 activation in B cells
could explain why the activation of STAT3 and STAT5 leads to
increased induction of certain proliferation-stimulating genes in
B cells only.
IFNAR2 and STAT1 levels are similarly expressed in primary
human leukocytes, and STAT2 is activated normally in B cells
To begin to understand the mechanism that causes few B cells to
activate STAT1 in response to IFN-b, we tested surface expression
of IFNAR2. IFNAR1 is crucial for ligand binding, but IFNAR2,
with its long cytoplasmic tail, possesses two conserved tyrosine
residues that are crucial for activation of STAT1, STAT2, and
STAT3 (1–4). IFNAR2 expression on leukocyte subsets present
in whole blood of six healthy individuals was studied by flow
cytometry. Fig. 8A shows that 100% of monocytes, B cells, and
CD4+and CD8+T cells expressed IFNAR2; therefore, lack of its
expression cannot be the reason why few B cells activated STAT1.
Although IFNAR2 expression was equal, the functionality of this
receptor chain might be different in B cells. We previously found
that the activation of STAT2 preceded the activation of STAT1 in
fibrosarcoma cells and that STAT2-null cells are severely ham-
pered in their ability to activate STAT1 (37). Fig. 8B shows the
percentage of cells positive for PY-STAT2 after stimulating whole
blood of six healthy individuals with 2000 IU/ml IFN-b for 45
min. Monocytes, B cells, and CD4+and CD8+T cells demon-
strated activation of STAT2 in response to IFN-b (Fig. 8B); there-
fore, failure to activate STAT2 is not the cause of low STAT1
activation in B cells. Another possible explanation for the very
low activation of STAT1 in B cells is that many fewer B cells
express STAT1 protein. We used flow cytometry to compare the
four different leukocyte subsets for the percentages of cells that
express total STAT1 (Fig. 8C), finding that all subsets were pos-
itive for STAT1. Although the percentages of total STAT1+B cells
were slightly lower compared with the other subsets, this differ-
ence cannot explain why usually ,15% of the B cells showed
activation of STAT1 in response to IFN-b. Finally, Western blot
analysis of total STAT1 expression in isolated monocytes, B cells,
and CD4+or CD8+T cells from two healthy individuals revealed
similar levels of STAT1 expression in all subsets (data not shown).
Types I and II IFNs induce similar amounts of PY-STAT1+
To test whether other type I IFNs and type II IFN also stimulate
few B cells to activate STAT1, undiluted whole blood of six
healthy subjects was stimulated with 2000 IU/ml IFN-g for 30 min
(the optimal time for activation of STATs by IFN-g; data not
shown), and 2000 IU/ml IFN-a1, IFN-a2b, or IFN-b for 45 min.
Fig. 9 shows that within all four leukocyte subsets tested (B cells,
monocytes, CD4+or CD8+T cells), all type I IFNs induced simi-
lar percentages of cells to activate STAT1. In B cells and mono-
cytes, type II IFN stimulated similar percentages of PY-STAT1+
cells as did type I IFNs (Fig. 9). Because T cells that produce IFN-
g, such as Th1 and Tc1 cells, are unresponsive to IFN-g due to
changed IFN-gR expression levels (38), CD4+and CD8+T cells
monocytes after in vitro stimulation with IFN-b. Undiluted whole blood
from two healthy donors was stimulated or not with 2000 IU/ml IFN-b1a
for 3 h. A, After 3 h, pure B cells and monocytes were isolated using
magnetically labeled Abs. RNA isolated from the purified subsets was used
for analysis of gene expression using microarray. The fold increase in
mRNA was calculated comparing expression in unstimulated subsets with
stimulated subsets. The Venn diagram shows increases in mRNA by $2-
fold and illustrates different mRNA-induction patterns in B cells (CD19)
and monocytes (CD14). B, Differences in expression of apoptosis-inducing
mRNAs (BAK1, CASP3, CDKN1A, STK3) and the survival-promoting
mRNA PBEF1 between B cells and monocytes after stimulation with IFN-
b, revealed by microarray analysis (Table I), was confirmed by rtPCR,
using mRNA isolated from purified monocytes and B cells, normalized
relative to 18S rRNA. The median fold changes in mRNA expression in
monocytes and B cells derived from six healthy subjects are shown for
stimulated subsets compared with control subsets.
Striking differences in gene induction in purified B cells and
B cells from two HIs after 3 h of stimulation with IFN-b
Fold increases of mRNAs in primary human monocytes and
aKnown STAT1-dependent gene.
bProbable STAT1-dependent gene.
cKnown STAT5-dependent gene.
dKnown STAT3-dependent gene.
eProbable STAT3-dependent gene.
The Journal of Immunology5895
generated lower amounts of PY-STAT1+cells in response to IFN-g
than in response to type I IFNs (Fig. 9). Remarkably, also on an
individual donor level, IFN-a1, -a2b, -b, and -g activated equal
percentages of PY-STAT1+B cells (Fig. 9). We found that only 7%
of healthy subjects (3 of 41) showed activation of STAT1 in .60%
of their B cells in response to IFN-b. As shown in Fig. 9, two
individuals had .60% of their B cells positive for PY-STAT1 in
response to IFN-a/b and IFN-g. The four individuals who showed
lower activation of STAT1 in B cells in response to IFN-b (i.e.,
∼10–20% of the cells positive for PY-STAT1) showed a similar
response after stimulation with IFN-a1, -a2b, and -g. Therefore, it
can be concluded that the same mechanism that influences the
activation of STAT1 in B cells after ligation of the type I IFNAR
also influences its activation by the IFN-gR.
Suppressor of cytokine signaling 1 (SOCS1), which diminishes
activation of STAT1 by the types I and II IFNRs by influencing the
activation of the JAKs (39), and Src homology region 2 domain-
containing phosphatase 1 (SHP1) and TCP45, two protein tyrosine
phosphatases known to decrease tyrosine phosphorylation of STAT1
(40, 41), are all candidates to explain the lack of PY-STAT1 induc-
tion in B cells by types I and II IFNs. We tested whether the ex-
pression of SOCS1, SHP1, and TCP45 was enhanced in B cells,
compared with other leukocyte subsets, in isolated monocytes,
B cells, and CD4+and CD8+T cells of one healthy individual, as
well as isolated monocytes and B cells from two other healthy
subjects. However, Western blot analysis showed no SOCS1 ex-
pression in any of the unstimulated subsets, whereas it did in an
IFN-g–stimulated monocytic cell line, and SHP1 and TCP45 were
expressed at similar levels in all subsets (data not shown).
Mechanistic aspects of differential STAT induction in response
The aims of this study were to investigate how certain primary
human blood cells signal in response to IFN-b and to explore
how such signals might be related to apoptosis or cell survival.
Nonimmune cells and cell lines have primarily been used to study
type I IFN signaling and to elucidate the mechanisms by which
these IFNs regulate transcription. We developed a flow cytometry-
based assay to detect, at the single-cell level, the activation of
specific STATs in primary human leukocytes. IFN-a/b–induced
activation of STAT1, which results mainly in the formation of the
ISGF3 complex, but also leads to the formation of STAT1 ho-
modimers in adherent and nonadherent cell lines, is a hallmark of
type I IFN signaling. The human leukemic B cell line HT and the
leukemic CD4+T cell line Jurkat form abundant amounts of
PY-STAT1 in response to IFN-b (Fig. 1; A.H.H. van Boxel-Dezaire
and G.R. Stark, unpublished data). Unexpectedly, we found that
only a small fraction of primary human B cells activated STAT1 in
response to IFN-b and that this activation was independent of the
concentration of IFN used (500–10,000 IU/ml) or the time of
stimulation (10–75 min; Fig. 4). We tested IFN-b–induced sig-
naling in 41 individuals. Although most of the time we saw that
a maximum of 25% of the B cells responded by activating STAT1,
in 7% of these individuals, we detected .65% of the B cells
positive for PY-STAT1 induction (3 of 41). It may be that these
persons have an underlying disease that has not been diagnosed or
that this response is normal during a subclinical virus infection.
Nevertheless, despite individual variations, we found that many
fewer B cells showed activation of STAT1 compared with mono-
cytes and CD4+and CD8+T cells after stimulation with 2000 IU/ml
IFN-b (Fig. 3C). To begin to understand the mechanism, we studied
IFNAR expression and found that 100% of primary human B cells,
differences in IFNAR2 expression levels, STAT2 activation, or STAT1
levels. A, Surface IFNAR2 expression was determined on monocytes, B
cells, CD4+T cells, and CD8+T cells present in unstimulated whole blood
of six healthy individuals. B, Activation of STAT2 in leukocyte subsets was
determined by stimulating undiluted whole blood of six healthy donors
with 2000 IU/ml of IFN-b1a or not for 45 min. C, STAT1 expression was
determined in monocytes, B cells, CD4+T cells, and CD8+T cells present
in unstimulated blood of four healthy subjects. Geometric means 6 SEM
for the percentages of leukocyte subsets that are positive for surface
IFNAR2 (A), PY-STAT2 (B), or intracellular STAT1 (C) are shown.
Differences in STAT1 activation cannot be explained by
IFN-g, IFN-a1, IFN-a2b, and IFN-b. Undiluted whole blood from six
healthy subjects was stimulated for 30 min with 2000 IU/ml IFN-g or for
45 min with 2000 IU/ml IFN-a1, IFN-a2b, or IFN-b (optimal time points
for activation of STATs). Activation of STAT1 was determined in the
various leukocyte subsets for all six healthy subjects individually as the
percentages of PY-STAT1+subsets.
Similar activation of STAT1 in B cells after stimulation with
5896 IFN-b–INDUCED RESPONSES IN HUMAN BLOOD CELL SUBSETS
monocytes, and CD4+and CD8+T cells expressed the IFNAR2
chain (Fig. 8A), which has a long cytoplasmic tail containing two
conserved tyrosine residues that are crucial for activation of STAT1,
STAT2, and STAT3 (1–4). Although IFNAR2 expression was found
to be equal, the functionality of this receptor chain could still be
different in B cells. An explanation for the low activation of STAT1
could be decreased activation of STAT2, because activation of
STAT1 depends on the activation of STAT2 in fibrosarcoma cells
and primary fibroblasts (37, 42). However, STAT2-deficient peri-
toneal macrophages retained the ability to activate STAT1, high-
lighting intriguing differences in the ability of the IFNAR to activate
STAT1 in fibroblasts and monocytic cells (42). Nothing is known
about this function of the IFNAR in other leukocyte subsets, but we
found low activation of STAT1 in primary human B cells at every
IFN-b concentration and in CD4+T cells at lower IFN-b concen-
trations, despite normal activation of STAT2. At the optimal time
point for IFN-b–induced STAT activation, we found the highest
activation of STAT5 in primary human CD4+T cells and we also
found activation of STAT5 and STAT3 in primary human B cells,
suggesting that the type I IFNR is functional in B cells.
It will be important to investigate whether low STAT1 activation
is an intrinsic property of mature B cells and CD4+T cells or
whether it is a result of other factors present in whole blood.
Notably, our results comparing IFN-a1, IFN-a2b, and IFN-g with
IFN-b showed very similar low activation of STAT1 in B cells
(Fig. 9), suggesting that the same mechanism is involved. By
influencing activation of the JAKs, SOCS1 can diminish the ac-
tivation of STAT1 by the types I and II IFNRs (39). SHP1 and
TCP45 are protein tyrosine phosphatases that decrease tyrosine
phosphorylation of STAT1 (40, 41). Although SOCS1, SHP1, and
TCP45 are excellent candidates to explain the lack of PY-STAT1
induction in B cells by types I and II IFNs, we could not find
evidence of their enhanced protein expression in B cells only.
Based on our experiments, we propose that physical properties of
STAT1 protein itself are altered or that a selective negative reg-
ulator of STAT1 tyrosine phosphorylation is present in the ma-
jority of B cells. B cells are a heterogeneous population, and it
will be important to characterize the minor fractions that show
activation of STAT1 by studying the expression of CD markers,
chemokine receptors, and adhesion molecules. Perhaps the STAT1-
activating cells are immature, because type I IFNs inhibit B and
T cell lymphopoiesis (43). In contrast, IFN-a induces STAT1-
dependent proliferation in dormant hematopoietic stem cells (44),
suggesting that the response to type I IFNs may change during the
maturation of leukocyte subsets. Future experiments could address
this issue by analyzing subsets separated on the basis of lineage
and differentiation markers expressed on their surfaces.
Biological consequences of differential STAT activation
Type I IFNs cause apoptosis in many cancer cell lines and are
used to treat several types of tumors (22, 23). Similarly, type I
IFNs induce apoptosis in primary monocytes (20, 21) but, in con-
trast, increase the survival and proliferation of primary B cells and
T cells (14–19). In agreement, we found the highest activation of
caspase 3, a hallmark of apoptosis induction, in monocytes, fol-
lowed by CD8+T cells, and the least amount in CD4+T cells and
B cells after stimulation with IFN-b. Interestingly, during virus
infection of mice, only CD8+T cells with low STAT1 activation
proliferate in response to type I IFNs, as a result of lower STAT1
protein expression (45). The apoptosis-inducing capacity of type I
IFNs is largely attributed to the activation of STAT1 (11, 46),
whereas the activation of STAT3 and STAT5 by type I IFNs is
related to survival and proliferation (12, 13, 47). By performing
double staining of IFN-b–stimulated cells with anti–PY-STAT1/
PY-STAT3 or anti–PY-STAT1/PY-STAT5 Abs, we were able to
detect the activation of STAT1/STAT3 and STAT1/STAT5 to-
gether, in individual cells. Notably, the percentage of PY-STAT1+/
PY-STAT3–monocytes found in response to IFN-b after 45 min
correlated significantly with the percentage of activated caspase 3+
monocytes after 8 h (Fig. 6C). Enhanced STAT3 protein levels in
monocytes have been demonstrated to suppress DNA binding of
STAT1 homodimers by sequestering STAT1 into STAT1/STAT3
heterodimers (48). Therefore, it is to be expected that the PY-
STAT1+/PY-STAT32monocytes would become apoptotic first and
that PY-STAT1+/PY-STAT3+monocytes are protected from apo-
ptosis induction only if PY-STAT3 levels are high enough to se-
quester activated STAT1. However, after longer stimulation with
IFN-b (.10 h), the percentage of apoptotic cells is doubled or
tripled compared with the percentage at 8 h, indicating that even
PY-STAT1+/PY-STAT3+monocytes eventually die. Very few B cells
are PY-STAT1+/PY-STAT32and, because STAT1 activation is so
low in these cells, it is more likely that enhanced PY-STAT3 levels
could suppress DNA binding of STAT1 homodimers by sequester-
ing STAT1 into STAT1/STAT3 heterodimers in PY-STAT1+/PY-
STAT3+B cells than in monocytes (48). It is interesting that CD4+
T cells that show the highest percentage of PY-STAT1+/PY-STAT32
cells in response to IFN-b after 45 min display the lowest apoptosis
induction, along with B cells (Fig. 6A, 6B). Both leukocyte subsets
have very low numbers of PY-STAT1+/PY-STAT52cells and sig-
nificant numbers of PY-STAT1+/PY-STAT5+cells, suggesting that
the activation of STAT5 in the majority of CD4+T cells and B cells
protects against apoptosis induction. Indeed, the antiapoptotic and
mitogenic properties of type I IFNs in mouse T cells are dependent
on the activation of STAT3 and STAT5 (47). Strangely, despite the
fact that monocytes also generate very high numbers of PY-STAT1+/
PY-STAT5+cells in response to IFN-b, they are the most sensitive to
apoptosis induction. This disparity between monocytes, B cells, and
CD4+T cells might be explained by the fact that our anti–PY-STAT5
Ab recognizes activated STAT5A and STAT5B, and human mono-
cytic cells activate only STAT5A (49), in contrast to human T cells,
which activate STAT5A and STAT5B in response to type I IFNs (8).
In accordance with the above-mentioned data, when monocytes
and B cells were compared for proapoptotic mRNA induction by
IFN-b, we only found enhancement of CDKN1A, BAK1, CASP3,
and STK3 mRNA in monocytes (Fig. 7B, Table I). Evidence that
the induction of these mRNAs depends upon phosphorylated
STAT1 homodimers is as follows. First, IFN-g does not induce
CDKN1A (or p21) in STAT1-deficient U3A fibrosarcoma cells, but
it does enhance p21 expression in U3A cells in which STAT1 has
been reintroduced (27), and enhancement of CASP3 expression is
dependent on PY-STAT1 formation (28). Second, because BAK1
expression is induced directly in HT-29 cells by IFN-g (29), its
induction probably depends on the formation of STAT1 homo-
dimers. Finally, because types I and II IFNs enhance STK3 ex-
pression (http://www.interferome.org), it is likely that the induc-
tion of this mRNA occurs through activation of STAT1. p21,
BAK1, CASP3, and STK3 are known to be involved at different
stages of the intrinsic apoptotic pathway. For instance, increased
p21 leads to cell-cycle arrest in the G1 phase of fibrosarcoma and
Burkitt’s lymphoma cells, and the induction of G1 arrest in Bur-
kitt’s B cell lymphoma by type I IFNs is followed by induction of
apoptosis (26). BAK1 is a member of the BCL-2 family of proa-
poptotic proteins that, upon activation by IFN-a, forms oligomers or
heterodimers that interact with the mitochondria, leading to the
release of cytochrome c and apoptosis induction (50, 51). Notably, it
was shown that apoptosis induction through activation of STAT1 is
mediated by activation of the effector caspase 3, among others (46).
Interestingly, STK3 is a direct substrate of caspase 3 and, following
The Journal of Immunology5897
cleavage, translocates to the nucleus and induces chromatin con-
densation, followed by internucleosomal DNA fragmentation (52,
53). However, increased levels of STK3 can also accelerate apo-
ptosis induction through the activation of caspase 3 (52).
Induction by IFN-b of CDKN1A, BAK1, CASP3, and STK3 all
involved in the intrinsic apoptotic pathway, seems to occur only in
monocytes, whereas the induction of certain proapoptotic genes
was not found in B cells exclusively. Nevertheless, in monocytes
and B cells, TRAIL mRNA was increased by 7–24-fold after
IFN-b stimulation (Table I). Although TRAIL expression induces
apoptosis in tumor- and virus-infected cells, it exhibits no ap-
parent adverse affect on normal cells (30, 54). Moreover, TRAIL
engagement on T cells can even lead to increased proliferation,
but it is not known whether this is also true for B cells (55).
However, the expression of TRAIL on monocytic cells might still
have inhibitory effects, because the rapid maturation of monocytes
into short-lived dendritic cells by IFN-b is associated with TRAIL
expression (21). TRAIL induction by IFN-b in fibrosarcoma cells
is dependent on ISGF3 binding to the ISRE element in the pro-
moter (56). The fact that our data suggest that TRAIL mRNAwas
increased in B cells by IFN-b, despite low activation of STAT1,
could be explained by the binding of STAT2dimer/IRF-9 or
STAT2/STAT6/IRF-9 to the ISRE (4, 5), because primary human
B cells can activate STAT2 and STAT6 (Fig. 8B). Alternatively,
formation of STAT3, STAT5, or STAT6 homodimers (5) in re-
sponse to IFN-b could be responsible for the observed increase in
IRF-1 in primary human B cells (Table I) and IRF1 dimers could
subsequently bind to the ISRE in the TRAIL promoter (57). In
addition to TRAIL induction, we found that, in monocytes and
B cells, the mRNA for the death receptor FAS was increased by 3–
4-fold (Table I). Upon FASL binding, the extrinsic apoptosis path-
way could be triggered by recruitment of FAS-associated death
domain protein, activation of caspase 8, and cleavage of the proa-
poptotic BCL-2 family member Bid (31, 50). However, we did not
observe any simultaneous increase in FASL mRNA expression in
B cells or monocytes. Of note, FAS also has nonapoptotic functions
(31), because individuals with homozygous caspase-8 reduction-
of-function mutations display defects in FAS signaling and im-
paired proliferation of B, T, and NK cells (58).
Very low percentages of PY-STAT1+/PY-STAT32and PY-STAT1+/
PY-STAT52were observed in B cells, the only leukocyte subset in
which the PY-STAT12/PY-STAT3+and PY-STAT12/PY-STAT5+
combinations were induced upon IFN-b stimulation (Fig. 6B). These
findings together are likely to be responsible for decreased induction
of apoptosis and increased induction of the PY-STAT3– or PY-
STAT5–dependent mRNAs that are responsible for increased survival
and proliferation. Notably, the probable PY-STAT3–dependent BAFF
(36), which our preliminary data suggest to be increased 3.5-fold
more in B cells compared with monocytes (Table I), was shown to
overcome any negative effects from FAS signaling and increase the
survival of B cells (59). Another activated STAT3-dependent mRNA
(35), PBEF1, increased in B cells only (Fig. 7B, Table I) and not in
monocytes in response to IFN-b. Notably, PBEF1 inhibits the in-
duction of apoptosis in neutrophils and epithelial cells by reducing
the activity of caspases 3 and 8 (34). In addition, PBEF1 synergizes
with IL-7 in pre-B cell colony formation (33). We did not observe
increased BCL2 or BCL2L1 expression, which was previously sug-
gested to be the antiapoptotic mechanism of IFN-b in B cells (15).
The promoters of BCL2 and BCL2L1 are typical targets of acti-
vated STAT5 in response to several growth factors, and the STAT5-
dependent induction of resistance to apoptosis functions through
these proteins (13). Because we studied only early mRNA tran-
scription in response to IFN-b, the induction of BCL2 and BCL2L1
mRNA in B cells might need .3 h of stimulation with IFN-b. We
propose that the low activation of STAT1 and much higher activa-
tion of STAT3 and STAT5 and, consequently, the absence of in-
duction of genes participating sequentially in the intrinsic apoptosis-
induction pathway (as observed in monocytes) are important me-
chanisms to enable primary human B cells to survive in response to
IFN-b. More in-depth studies using Chip assays to determine the
residence of specific STATs on specific promoters are necessary to
understand in detail how STAT1, STAT3, and STAT5 activated by
IFN-a/b exert their proapoptotic and mitogenic effects in specific
immune subsets. In addition, it will be vital to unravel the mecha-
nism of low STAT1 activation in the great majority of primary hu-
man B cells.
Although to enable survival, few B cells activate STAT1 in re-
sponse to types I and II IFNs, it is nevertheless important that the
antiviral effects of IFNs are preserved. mRNAs derived from virus-
responsive genes, such as MX1, OAS, EIF2AK2, ISG15, IFI44, and
IFITM3, increased $2-fold in B cells and monocytes in response to
IFN-b (data not shown). It seems that only the promoter of MX1
harbors a classical ISRE element (57), and increased MX1 tran-
scription in B cells, despite low STAT1 activation by IFN-b, could
be the result of activation of similar transcription factor com-
plexes as mentioned above for TRAIL. All of the other typical
virus-responsive genes are suggested to belong to a new subtype of
ISRE termed “E–twenty-six (ETS)/IRF response elements,” which
can bind IRF dimers (similar to classic ISRE) or an ETS/IRF dimer
(57). Because B cells express IRF4, IRF8, PU.1, and other ETS
family members (57), an IRF/ETS dimer might bind to these
promoters in primary B cells after IFN-b stimulation. Therefore,
the inability of most B cells to activate STAT1 does not lead to
a deficient antiviral response in B cells, but the mechanism has still
to be elucidated. These results have important implications for
understanding more fully the influence of IFN-a/b on leukocyte
subsets during virus infection in humans, as well as the effects of
treatment with IFN-a/b on these subsets in patients with multiple
sclerosis, hepatitis, or cancer.
We thank Dr. Ian M. Kerr for many helpful suggestions and Dr. Ganes
C. Sen for critically reviewing this manuscript. In addition, we thank Mike
Sramkoski (Case Comprehensive Cancer Center Flow Cytometry Core,
Case Western Reserve University) and Cathy Shemo and Sage O’Bryant
(Flow Cytometry Core, Lerner Research Institute of the Cleveland Clinic)
for advice and technical assistance. We thank Dr. Pieter Faber (Genomics
Core Facility, Cleveland Clinic) for microarray analyses. Moreover, we
thank Vai Pathak and Dr. Patrick Leahy (Gene Expression and Genotyping
Core Facility, Case Comprehensive Cancer Center, Case Western Reserve
University) for assistance with the rtPCR experiments. Finally, we thank
Drs. Thomas Hamilton and Ernest Borden (Department of Immunology
and Taussig Cancer Institute and Cleveland Clinic, respectively) for their
kind gifts of human rIFN-g, rIFN-a1, and rIFN-a2b.
The authors have no financial conflicts of interest.
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