Characterization of hematopoietic GATA transcription factor expression in mouse and human dendritic cells

Blood Cells, Molecules and Diseases 55 (2015) 293–303

Contents lists available at ScienceDirect

Blood Cells, Molecules and Diseases journal homepage: www.elsevier.com/locate/bcmd

Characterization of hematopoietic GATA transcription factor expression in mouse and human dendritic cells☆ Maaike R. Scheenstra a, Vishal Salunkhe a, Iris M. De Cuyper a, Mark Hoogenboezem b, Eveline Li a, Taco W. Kuijpers a,c, Timo K. van den Berg a, Laura Gutiérrez a,⁎ a b c

Department of Blood Cell Research, Sanquin Research and Landsteiner Laboratory, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands Department of Molecular Cell Biology, Sanquin Research and Landsteiner Laboratory, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands Department of Pediatric Hematology, Immunology and Infectious Diseases, Emma Children's Hospital, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

a r t i c l e

i n f o

Article history: Submitted 31 March 2015 Revised 10 July 2015 Accepted 11 July 2015 Available online 14 July 2015 Editor: Mohandas Narla Keywords: Dendritic cells Transcription factors GATA1 GATA2 GATA3 GATA switch PU.1

a b s t r a c t Dendritic cells (DCs) are key initiators and regulators of the immune response. The development of the DC lineage and their subsets requires an orchestrated regulation of their transcriptional program. Gata1, a transcription factor expressed in several hematopoietic cell lineages, has been recently reported to be required for mouse DC development and function. In humans, GATA1 is involved in the lineage separation between monocyte-derived DCs and Langerhans cells (LC) and loss of GATA1 results in differentiation arrest at the monocyte stage. The hematopoietic GATA factors (i.e. Gata1, Gata2, Gata3) are known to regulate each other's expression and to function consecutively throughout lineage commitment (so-called GATA switch). In humans, mutations in GATA2 are causative of MonoMAC disease, a human immunodeficiency syndrome characterized by loss of DCs, monocytes, B and NK cells. However, additional data on the expression of hematopoietic GATA factors in the DC lineage is missing. In this study, we have characterized the expression of hematopoietic GATA factors in murine and human DCs and their expression dynamics upon TLR stimulation. We found that all hematopoietic GATA factors are expressed in DCs, but identified species-specific differences in the relative expression of each GATA factor, and how their expression fluctuates upon stimulation. © 2015 Elsevier Inc. All rights reserved.

1. Introduction Dendritic cells (DCs) are key initiators and regulators of the immune system, both priming the immune response and inducing tolerance [1]. They are located both in lymphoid and non-lymphoid tissues, where they sample their environment continuously for self- and non-selfantigens [2, 3]. These “sampling” DCs are so-called immature DCs, and express a series of receptors that recognize pathogen-associated molecular patterns (PAMPs), including Toll-like receptors (TLRs). Upon PAMP

Abbreviations: DC, dendritic cell; LC, Langerhans cell; PAMP, pathogen-associated molecular pattern; TLR, Toll-like receptor; cDC, conventional dendritic cell; pDC, plasmacytoid dendritic cell; ssRNA, single stranded RNA; LPS, lipopolysaccharide; BMDC, bone marrow derived dendritic cell; GM-CSF, granulocyte-macrophage colonystimulating factor; Flt3L, FMS-like tyrosine kinase 3 ligand; PBMC, peripheral blood mononuclear cell; mo-DC, monocyte derived dendritic cell. ☆ Author's contributions: MS designed and performed experiments, analyzed the data, and wrote the manuscript. VS, IMDC, MH and EL performed experiments. TK and TB participated in discussions and revised the manuscript. LG designed experiments, contributed to data analysis and revised the manuscript. All authors reviewed and approved the final version. ⁎ Corresponding author at: Plesmanlaan 125; 1066 CX, Amsterdam, The Netherlands. E-mail address: [email protected] (L. Gutiérrez).

http://dx.doi.org/10.1016/j.bcmd.2015.07.006 1079-9796/© 2015 Elsevier Inc. All rights reserved.

recognition, DCs get activated, upregulate co-stimulatory molecule expression, migrate to the lymph nodes and present antigen-derived peptides to T-cells via MHC-I/II [4]. Two major types of DCs can be distinguished, namely conventional DC (cDC) and plasmacytoid DC (pDC) [5]. pDCs are mainly found in the blood stream. They are important mediators in the antiviral immunity by the large amounts of type-I interferon they produce upon TLR-7 (that recognizes ssRNA) or TLR-9 (that recognizes CpG-containing DNA) stimulation [6, 7]. cDCs are mainly resident tissue-dwelling or migratory and express TLR-2 (recognizing lipopeptides), TLR-4 (lipopolysaccharide (LPS)), TLR-5 (recognizing flagellin), TLR-6 (heterodimer with TLR-2), and TLR-9 (recognizing CpG-containing DNA), although they are recognized as potent bacterial responders [8, 9]. Under inflammatory conditions, yet another type of DC, so-called inflammatory DC, derives from circulating monocytes [5]. cDCs can be further subdivided into CD8a + cDCs and CD4 +|CD11b+ cDCs in the mouse, which are comparable to human cDCs recently subdivided as BDCA3+ and BDCA1+ respectively [10, 11]. CD8a+ cDCs highly express DEC205 and CD24, whereas CD11b+ cDCs are DEC205low and express high levels of Sirp-α [12–16]. Migratory cDCs can be distinguished from resident DCs in the lymph nodes by a higher MHC-II expression [4, 5, 14].

294

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

The development of DCs from hematopoietic progenitors is tightly regulated by transcriptional programs. Many transcription factors have been studied in depth by using genetically modified mice and reconstitution assays [17]. PU.1 [17–19], IRF-2 [20–23], IRF-4 [20–24], IRF-8 [20–22, 24], Batf3 [24], RelB [20, 21, 23], and E2-2 [25, 26] were all shown to be important in DC development, while some of them being required for a specific DC subset. Recently, Gata1 was described to be expressed in both cDCs and pDCs, and required for DC differentiation, survival and function [27]. Furthermore, previous studies showed that GATA1 is also essential for DC differentiation from human monocyte-derived DCs, since knockdown of GATA1 resulted in differentiation arrest at the monocyte stage, and also crucial for the LC–DC lineage bifurcation from monocytes [28]. Gata1 belongs to the GATA family of transcription factors, consisting of Gata1-6. Of these, Gata1, Gata2, and Gata3 are expressed in the hematopoietic system. All the GATA transcription factors are very similar to each other. They contain two conserved multifunctional zinc finger domains and recognize a common DNA binding motif WGATAR. The two zinc finger domains are involved in DNA-binding and protein–protein interactions. Gata1 is essential for the differentiation of erythrocytes, eosinophils and megakaryocytes [29], but seems to be dispensable for mast cell differentiation [30]. In humans, there are two isoforms of GATA1, i.e. full length GATA1 (GATA1-FL) and a short isoform (also known as GATA1s), both due to alternative splicing and translation [31]. Mutations in GATA1 exon 2 leading to the expression of Gata1s only, result in Diamond–Blackfan anemia [31–33]. Gata1 regulates genes related to cell differentiation, cell cycle and survival, such as the anti-apoptotic protein Bcl-XL [28, 34–37]. Importantly, it has been shown that Gata1 and PU.1 antagonize each other during erythroid (Gata1 dependent) or macrophage (PU.1 dependent) differentiation, while in other lineages they can co-exist [28]. Gata2 is important throughout the hematopoietic system. It regulates the self-renewal of multipotent progenitor cells and is involved in erythro- and megakaryopoiesis [29, 38]. Gata2 binds and regulates the PU.1 promoter directly [39]. Conditional expression of Gata2 in mouse embryonic stem cells resulted in a decrease of PU.1 and an increase of Gata1, which blocked macrophage differentiation [39]. In humans, heterozygous mutations in GATA2 are linked to the MonoMAC syndrome, which is characterized by the loss of DCs, monocytes, B and NK cells [40]. Gata3 is a critical regulator of cells that orchestrate both the innate and adaptive immunity. It regulates hematopoietic stem cell maintenance [41] and plays an essential role in the development and function of T cells [42] and NK cells [43]. GATA transcription factors are often expressed in an overlapping manner or replace each other during differentiation, a mechanism which is so-called the GATA switch [44, 45]. This is important for example in the erythrocyte/megakaryocyte lineage bifurcation point. Gata2 is expressed in common megakaryocyte/erythroid progenitors. Repression of Gata2 by Gata1 facilitates terminal differentiation of erythrocytes. However, if both Gata1 and Gata2 remain expressed, it leads to the differentiation of megakaryocytes [44, 46–48]. Until now, the expression of GATA factors other than Gata1 in DCs has not been explored. Considering the expression and need of Gata1 for DC differentiation, survival and activation, and taking into account the existence of GATA switches in other hematopoietic lineages, and the role of GATA2 in the development of MonoMAC disease, we decided to characterize in depth the expression of hematopoietic GATA factors in mouse and human DCs, either prospectively isolated or in vitro generated, and upon stimulation. 2. Materials and methods 2.1. Mice All mice were kept under pathogen-free conditions with free access to food and water, under the guidelines for animal experimentation

approved by the Animal Ethical Committee of the Netherlands Cancer Institute (NKI, Amsterdam, The Netherlands). 2.2. Human samples Blood was taken from healthy donors after informed consent was obtained as approved by our institution medical ethics committee and in accordance with the 1964 Declaration of Helsinki. 2.3. Mouse dendritic cell culture Bone marrow derived dendritic cells (BMDCs) were generated by culturing femoral and tibial bone marrow cells of male wild-type C57BL/6 mice (Jackson Laboratory, Bar Harbor, Main, USA). 2.3.1. GM-CSF cultures BMDCs were cultured at a density of 0.5 ∗ 106/ml in Gibco® RPMI 1640 (Life Technologies, Carlsbad, CA, USA) supplemented with 5% heat inactivated fetal calf serum, 1% penicillin/streptomycin, 5 μM 2-mercaptoethanol and 20 ng/ml GM-CSF (Peprotech, Rocky Hill, NJ, USA); when indicated, 25 ng/ml IL4 (eBioscience, San Diego, CA, USA) was added. 0.5 μg/ml LPS (Santa Cruz Biotechnology, Dallas, Texas, USA) was added to the cells at day 7, and harvested for analysis at day 10. 2.3.2. Flt3L cultures Red blood cells of the bone marrow were lysed with an isotonic ammoniumchloride buffer before culture. All cells of one femur and tibia were resuspended in 12 ml Gibco® RPMI 1640 supplemented with 10% heat inactivated fetal calf serum, 1% penicillin/streptomycin, 5 μM 2-mercaptoethanol and 200 ng/ml Flt3L (kind gift of B.N. Lambrecht, Ghent University) and cultured in a 6-well plate with 4 ml per well. 0.5 μg/ml LPS (Santa Cruz Biotechnology) or 2 μg/ml CpG-B ODN 1668 (Invivogen, Toulouse, France) was added at day 8 and the cells were harvested 24 h after stimulation for further analysis. 2.4. Human dendritic cell culture After isolating the peripheral blood mononuclear cell fraction by percoll gradient by centrifugation at 2070 RPM during 20 min, monocytes were positively selected with CD14+ MACS beads (Miltenyi Biotech, Auburn, CA, USA), following the manufacturer's guidelines. CD14+ cells were cultured in Gibco® RPMI 1640 supplemented with 10% heat inactivated fetal calf serum, 1% penicillin/streptomycin, 10 ng/ml GM-CSF (Peprotech) and 10 ng/ml IL4 (Peprotech). Cells were stimulated with 0.5 μg/ml LPS (Santa Cruz Biotechnology) at day 7 and collected at day 8. 2.5. Flow cytometry After harvesting cultured DCs either from mouse or human origin, cells were stained with antibody-cocktails, measured on a BD FACSCanto II flow cytometer (BD Bioscience, San Jose, CA, USA) and analyzed with FlowJo software (Ashland, OR, USA). For intracellular FACS, cells were fixed and permeabilized with the BD Cytofix/ Cytoperm™ Fixation/Permeabilization Solution Kit (BD-Bioscience) and stained according to manufacturer's guidelines (antibodies used are indicated in Table 1). 2.5.1. Prospective isolation of mouse splenic dendritic cell subtypes Spleen tissue was digested in Gibco® RPMI 1640 (Life Technologies), supplemented with 1.5 WU/ml Liberase TL (Roche diagnostics, Lewes, United Kingdom), 200 U/ml DNAse (Sigma Aldrich, Dorset United Kingdom), and 0.5 μg/ml Agrastat (Merck Sharp and Dohme, Haarlem, The Netherlands) for 45 min after which single cell suspensions were obtained by passing suspensions through a 40 μm filter (BD bioscience).

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

295

Table 1 Antibodies used. Reactivity

Antibody

Conjugate

Clone

Manufacturer

Use

Mouse Mouse Mouse Mouse Mouse Mouse Mouse Mouse Mouse Human Human Human Human Human Mouse/Human Mouse/Human Mouse/Human Mouse/Human Mouse/Human Mouse/Human Mouse/Human Mouse/Human – – – – – – – –

CD11c CD24 MHC-II CD40 CD86 Sirp-α B220 CD8a CD11b CD11c CD11b HLA-DR CD40 CD86 Gata1 Gata1 (N-terminus) Gata1 (C-terminus) Gata2 Gata3 PU.1 GAPDH Vinculin αRat IgG αGoat IgG αMouse IgG αRabbit IgG αRat IgG αGoat IgG αMouse IgG αRabbit IgG αMouse IgG

PE Pacific blue FITC FITC PerCP PerCP-eFluor710 Pacific blue PE-Cy7 APC-Cy7 PE APC-Cy7 FITC FITC PerCP – – – – – – – – AF488 AF488 AF488 AF488 HRP HRP HRP HRP IRDye 800CW

HL3 M1/69 M5/114.15.2 3/23 GL-1 P84 RA3-6B2 53-6.7 M1/70 S-HCL-3 ICRF44 G46-6 5C3 2331 (FUN-1) N6 ab11963 ab11852 H-116 14A9 T-21 6C5 V284 – – – – – – – –

BD-Pharmingen eBioscience eBioscience BD-Pharmingen BioLegend eBioscience eBioscience BD-Pharmingen BD-Pharmingen BD-Pharmingen BD-Pharmingen BD-Pharmingen BD-Pharmingen BD-Pharmingen Santa Cruz Abcam Abcam Santa Cruz Gift from Dr. D Kurek Santa Cruz Merck Millipore Life Technologies LifeTechnologies LifeTechnologies LifeTechnologies LifeTechnologies Dako ThermoFisher Amersham Amersham Li-Cor

FACS FACS FACS FACS FACS FACS FACS FACS FACS FACS FACS FACS FACS FACS FACS/WB WB WB FACS/WB FACS/WB FACS/WB WB WB FACS FACS FACS FACS WB WB WB WB WB

Red blood cells were lysed with an isotonic ammoniumchloride buffer. CD11c+ cells were selected using CD11c MACS beads (Miltenyi biotech). cDCs were then labeled (see Table 1) and sorted by flow cytometry (BD FACSAria III, BD bioscience) into CD11c+|MHCII+|CD11b+ and CD11c+|MHC-II+|CD8+ splenic DC subsets. Purity of 93.2%–98.7% was confirmed by analyzing the sorted fraction by flow cytometry. Sorted cells were further processed to isolate mRNA. 2.5.2. RNA isolation and quantitative q-PCR Total RNA was extracted from cultured DCs with Trizol (Life Technologies), or with QIAamp RNA blood Mini kit (Quiagen, Venlo, The Netherlands) from ex vivo isolated DCs. cDNA was synthesized with Superscript® III RT (Life Technologies). Custom-made primers were used to amplify desired transcripts with SYBR green as a detection method with the StepOnePlus™ Real time PCR system (Life Technologies). Custom made primers were used (Table 2). Input was normalized

using housekeeping genes (mouse: HPRT, UBC, and GAPDH; human: 18S and GAPDH) and relative expression was calculated using the cycle threshold value method (Ct) (relative expression = 2−ΔCt where ΔCt = Cttarget gene − average Cthousekeeping genes) [49]. 2.6. Protein extraction and Western blotting Cells were lysed with RIPA buffer (10 mM Tris–HCL pH 8, 1 mM EDTA, 0.5 mM EGTA, 140 mM NaCl, 1% TritonX100, 0.1% NaDOC, 0.1% SDS) for whole cell extracts and protein concentrations were measured with BCA Protein Assay Reagent (Thermo Scientific, Rockford, IL, USA). Equal protein levels were separated on a 10 or 12.5% SDS-polyacrylamide gel and transferred to a PVDF (Millipore, Billerica, MA, USA) or Whatman protran nitrocellulose membrane (GE Healthcare, Little Chalfont, United Kingdom). Membranes were first incubated with primary unlabeled antibodies and thereafter with

Table 2 Custom made primers.

Mouse Mouse Mouse Mouse Mouse Mouse Mouse Human Human Human Human Human Human Human Human Human Human

Gene

FW 3′-5′

Rev 3′-5′

Gata1 Gata2 Gata3 PU.1 GAPDH UBC HPRT GATA1 GATA1 ex I–II GATA1 ex II–II GATA1 ex III–IV GATA1 ex IV–VI GATA2 GATA3 PU.1 GAPDH 18S

CAGTCCTTTCTTCTCTCCCAC CCTGCGAGTCGAGATGGTTG GTCATCCCTGAGCCACATCT TCTTCACCTCGCCTGTCTT CCTGCCAAGTATGATGACAT AGGTCAAACAGGAAGACAGACGTA AGCCTAAGATGAGCGCAAGT AGATGAATGGGCAGAACAGG CACACTGAGCTTGCCACATC TGTCCTCCACACCAGAATCA CCAAGCTTCGTGGAACTCTC AGATGAATGGGCAGAACAGG CCCACCTACCCCTCCTATGT CTGGCCACAGTTGTTTGATG CACCTTCCAGTTCTCGTCCAA CTCTCTGCTCCTCCTGTTC GGAGAGGGAGCCTGAGAAAC

GCTCCACAGTTCACACACT CACCCCGCCGTATTGAATG AGGGCTCTGCCTCTCTAACC TCCAGTTCTCGTCCAAGCA GTCCTCAGTGTAGCCCAAG TCACACCCAAGAACAAGCACA ATGGCGACAGGACTAGAACA AGCGGAGCCACCACAGTA TCCCTGTAGTAGGCCAGTGC TCCCTGTAGTAGGCCAGTGC AGGCGTTGCATAGGTAGTGG AGCGGAGCCACCACAGTA GCCTTCTGAACAGGAACGAG TGCCCAGAACTGGTATTTCC CTTCTTCTTCACTTCTTGACCTC TGACTCCGACCTTCACCTTC GGGCCTCGAAAGAGTCCT

296

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

secondary antibodies labeled with HRP (see Table 1). HRP was activated with Amersham ECL Prime Western blotting detection reagent (GE Healthcare), exposed to Super RX films (Fujifilm, Tokyo, Japan) and developed in the medical film processor SRX-101A (Konic Minolta, Tokyo, Japan). Secondary antibodies with a fluorescent label (Licor, Lincoln, Nebraska, USA) were used, which were visualized with the Li-cor Odyssey Western Blot detection system (Westburg, Leusden, The Netherlands).

2.7. Statistical analysis Results are presented as the mean (+/− standard error of the mean (SEM)), unless otherwise stated. Statistical significance was assessed with a two-sided Student's t-test. *P ≤ 0.05, **P ≤ 0.01 and ***P ≤ 0.001

A

as calculated with GraphPad prism software, version 6.02 (San Diego, USA). 3. Results 3.1. Expression levels of GATA transcription factors in mouse BM-derived DCs in vitro To study the expression levels of the different GATA transcription factors in mouse DCs, two different culture methods were used. GMCSF BM-derived DCs resemble inflammatory DCs, which are derived from monocytes upon inflammation. Flt3L BM-derived DC cultures give rise to three DC subsets, pDCs, CD11b+ DCs and CD11b− DCs (equivalent to the CD8a+ DCs) [11] and therefore, resemble more closely the resident DC subtypes found in vivo.

MHC II

DCs

150

CD86

CD40

2000

40000

80000

***

***

***

1500

30000

60000

20000

MFI

MFI

%

MFI

100 1000

40000

50 500

10000 0

ST

0

LPS

B

ST

P=0.05 P=0.05

**

1500 500

2.5

***

***

ST

LPS

***

* **

400

**

300 200 100 0

Gata1

D Relative expression

**

2000

3.0 2.0 0.05 0.04 0.03 0.02 0.01 0.00

0

LPS

Protein expression 2500

3.5

2.0

ST

C

MFI

Relative expression

0

LPS

mRNA expression

4.0

20000

ST LPS

Gata2

Gata3

Gata1

PU.1

E

Fold induction

ST

Gata2

Gata3

PU.1

LPS Gata1

1.5

Gata2

1.0

Gata3

0.5

PU.1 GAPDH

0.0 Gata1

Gata2

Gata3

PU.1

Fig. 1. Expression levels of PU.1 and GATA transcription factors in mouse bone marrow derived GM-CSF DCs. A. Bar graphs representing the percentage of CD11c+|CD24+ GM-CSF DCs in culture (left) and the expression levels (mean fluorescence intensity, MFI) of MHC-II, CD40, and CD86, measured by flow cytometry in steady state and upon LPS stimulation. B. Bar graph representing mRNA qRT-PCR analysis of transcription factor expression in steady state GM-CSF DC cultures. C. Bar graph representing intracellular flow cytometry analysis of transcription factor protein expression levels (MFI) in steady state GM-CSF DC cultures. D. Bar graph representing fold induction of mRNA levels as measured by qRT-PCR of Gata1, Gata2, Gata3, and PU.1 upon LPS activation. E. Western blotting analysis of Gata1, Gata2, Gata3, and PU.1 transcription factors in steady state and upon LPS activation. At least three independent cultures were used for the analysis.

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

Mouse BMDCs cultured with GM-CSF (GM-CSF-DCs) resulted in a homogenous population of CD11chigh|CD24+ cells with a purity above 90% in all cultures (Fig. 1A). Cells were stimulated with LPS at day 7, and collected at day 10. To analyze whether the GM-CSF-DCs were properly activated, expression levels of MHC-II and their costimulatory molecules CD40 and CD86 were analyzed. All three markers showed a significant and substantial increase after LPS stimulation (Fig. 1A). Therefore we concluded that we had a representative culture of GM-CSF-DCs at steady state and upon stimulation for further analysis. Next we analyzed the mRNA expression levels of the GATA factors and PU.1 in steady state. PU.1 showed the highest expression levels. Amongst GATA factors, Gata1 and Gata3 had similar expression levels, whereas the expression of Gata2 was 4-fold higher (Fig. 1B). This was confirmed at the protein level by flow cytometry analysis of intracellular protein staining (Fig. 1C). As previously reported [18, 27], the expression levels of Gata1 increase upon LPS stimulation, whereas PU.1 levels decrease (Fig. 1D). We did not observe significant changes in the expression levels of Gata2 and Gata3 after stimulation (Fig. 1D). We confirmed these findings at the protein level by Western blotting, and showed that Gata1 increased with LPS stimulation and PU.1 decreased, while Gata2 and Gata3 remained unchanged (Fig. 1E). Mouse BMDCs cultured with Flt3L (Flt3L-DCs), resulted in three DC subtypes; pDCs, gated as B220+|CD11cint, and cDCs, gated as CD11c+ (Fig. 2A). cDCs were further subdivided into CD24+ or Sirp-α+ subsets

297

(equivalents to CD8a+ and CD11b+ subsets respectively [15]) (Fig. 2A). pDCs express TLR-7 and TLR-9 [6, 7], whereas cDCs express multiple TLRs, like TLR-2, TLR-4, TLR-5, TLR-6, and TLR-9 [8, 9]. The cultures were activated with either LPS (TLR4 ligand) or CpG-B (TLR9 ligand) and percentages of each DC subtype in the steady state or upon stimulation is depicted (Fig. 2A). DC activation was confirmed by the up-regulation of the surface expression of MHC-II. Both pDCs and cDCs increased MHC-II expression upon either stimulation, although cDCs displayed a stronger reaction upon LPS, whereas pDCs reacted stronger to CpG, as expected (Fig. 2B). RNA was isolated from the Flt3L cultures in the steady state condition and upon stimulation to analyze the expression of transcription factors. First, we compared the relative expression between the different transcription factors in the steady state condition. The expression level of PU.1 was the highest, as occurred with GM-CSF-derived DCs. Amongst GATA factors, Gata1 was expressed at a higher level than Gata2 and Gata3 (Fig. 2C). We next analyzed the effect of the two different stimuli, LPS and CpG-B on the expression levels of these factors. Gata1, Gata2, and Gata3 displayed the same pattern and the expression levels decreased with both stimuli compared to the steady state condition (Fig. 2D). In contrast, the levels of PU.1 increased after stimulation, especially after TLR9 stimulation, primarily targeting pDCs (Fig. 2D). This suggests essential differences in the expression and dynamics of the transcription factors analyzed, not only due to the steady state or

A

B

cDC gate

MHC II 80000

CD24

CD24 28.7

MFI

60000

pDC 9.96

B220

cDC pDC

Sirpa 52.2

40000

20000

cDC 64.2

0

CD11c

ST

Sirp-α

C

20

10 5

0 LPS CpG

D

20

0 ST

LPS CpG

50

0

150

100

50

0 CpG

LPS

****

CpG

****

0.06

**

0.04

**

0.02

LPS CpG

Gata1

Gata2

*

100

50

Gata3

PU.1

PU.1 **

150

0 ST

****

0.6 0.5 0.4

Gata3

** Relative expression

Relative expression

100

**

Steady state

0.00

ST

Gata2 150

**

LPS

40 20

LPS CpG

*

ST

60

0 ST

Gata1 150

30

10

0 ST

Relative expression

15

80

CpG

Sirp-α cDCs

Relative expression

40

40

Percentage

60

CD24 cDCs

Relative expression

20

Percentage

Percentage

80

pDCs

Percentage

cDCs

LPS

100

50

0 ST

LPS

CpG

ST

LPS

CpG

Fig. 2. Expression levels of PU.1 and GATA transcription factors in mouse bone marrow derived Flt3L DC cultures. A. Above, dot plots depicting representative Flt3L DC culture flow cytometry analysis. Left, dot plot depicting the gating and percentage of B220+|CD11cmid (pDCs) and B220-|CD11c+ (cDCs) as analyzed by flow cytometry. Right, dot plot depicting within the cDCs gate, the gating and percentages of cDC subtypes, namely CD24+ and Sirp-α+ (i.e. CD8+ and CD11b+ respectively). Below, bar graphs representing the percentage of each DC subtype in steady state and upon stimulation with either LPS or CpG from the total culture. B. MFI of MHC-II expression in steady state and upon TLR4 (LPS) or TLR9 (CpG-B) stimulation of both pDCs and cDCs as measured by flow cytometry. C. Bar graph representing mRNA qRT-PCR analysis of transcription factor expression in steady state Flt3L DC cultures. D. Bar graph representing the effect of TLR4 (LPS) or TLR9 (CpG-B) stimulation on transcription factor expression as measured by qRT-PCR in Flt3L DC cultures. At least three independent cultures were used for analysis.

298

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

subtypes. Gata2 and Gata3 showed higher expression levels in CD11b+ DCs compared to CD8a+ cDCs (Fig. 3C). Then we questioned what the relative expression to each other would be in ex vivo DCs and whether this was different between CD8a+ cDCs (Fig. 3D) and CD11b+ cDCs (Fig. 3E). PU.1 is expressed at the highest levels in both CD8+ and CD11b+ cDC subsets. Gata1, 2, and 3 did not differ significantly from each other in the CD8+ subset. In the CD11b+ subset there was a statistical difference in expression levels. Gata2 expression was higher compared to Gata1, but lower than Gata3, which showed the highest expression levels of the GATA factors in CD11b+ DCs (Fig. 3E). The expression level of Gata1 is higher compared to Gata2 and Gata3 in the Flt3L cultured cells compared to both ex vivo isolated splenic subsets. However, we cannot exclude that this difference found in the relative expression of Gata1 is influenced by pDCs still present in Flt3L cultures.

activated status of DCs, but also due to the culture method employed (i.e. mimicking splenic conventional DCs-Flt3L culture- or inflammatory DCs-GM-CSF culture-). 3.2. Expression levels in mouse ex vivo DCs Because the Flt3L culture system remains debatable as to how the cultured DCs compare to in vivo splenic DCs, we also directly analyzed ex vivo DCs isolated from mouse spleens in steady state condition. DCs were selected by the simultaneous expression of MHC-II+ and CD11c + , and subsequently sorted into two subtypes, namely CD8a+ cDCs and CD11b+ cDCs (Fig. 3A). The sorted fractions had a purity above 85% for each subset (Fig. 3A–B). The expression levels of the GATA transcription factors and PU.1 were analyzed at mRNA levels. Gata1 and PU.1 are expressed at similar levels in both

A

cell gate

B

MHC-II

SSC

DCs 94.9

Cells 74.2

FSC

CD8

CD11c

DC gate

DC gate CD11b 86.0

CD8a 97.9

CD8a 0.092

CD11b

CD11b

CD11b 0.122

CD11b CD8a

Gata1

Gata2 250 Relative expression

Relative expression

150

100

50

0

*

D Relative expression

C

CD8a

200 150 100 50 0

CD8

CD11b

CD8 0.5 0.4 0.3 0.2 0.020

****

0.015 0.010 0.005

CD11b

Gata1

E

200

0

Relative expression

Relative expression

Relative expression

400

100

50

0 CD8

CD11b

Gata2

Gata3

PU.1

CD11b

PU.1 150

**

****

0.000

CD8

Gata3 600

****

0.5 0.4 0.3 0.020

***

****

***

***

****

0.015

** 0.010 0.005 0.000

CD8

CD11b

Gata1

Gata2

Gata3

PU.1

Fig. 3. Expression levels of GATA transcription factors in isolated mouse splenic cDC subsets. A. Dot plots depicting the definition of splenic cDCs by flow cytometry (above): splenic cDCs were sorted as MHC-II+|CD11c +, and subsequently as CD11b+ (CD11b cDCs) or CD8+ (CD8 cDCs) subtypes. Below, dot plots of splenic cDC subtypes after sorting show N85% purity. B. Pictures of representative cytospins of sorted CD8+ and CD11b+ cDC subtypes, stained with May–Grünwald–Giemsa. C. Bar graphs representing mRNA qRT-PCR analysis of transcription factor expression in the two subtypes sorted, CD8+ and CD11b+ cDCs. D. Bar graph representing mRNA qRT-PCR analysis of the expression pattern of transcription factors in CD8+ cDCs. E. Bar graph representing mRNA qRT-PCR analysis of the expression pattern of transcription factors in CD11b+ cDCs. At least three independent samples were used for analysis.

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

human their levels seem to be regulated at the transition from monocyte to DCs, but are further not influenced by LPS stimulation. Furthermore, in humans, there are two isoforms of GATA1, the fulllength isoform which starts from the coding exon 2 (GATA1-FL), and GATA1s, which starts from the coding exon 3, skipping exon 2 [31]. Therefore, we analyzed the expression of the two GATA1 isoforms in monocytes and mo-DCs in steady state or with LPS stimulation. We used cDNA from DAMI cell line, a megakaryoblastic leukemia cell line, as control [50], that co-expresses both GATA1 isoforms. We designed primer combinations for RT-PCR either including or excluding exon 2. We could detect PCR products from both GATA1 isoforms in human monocytes and mo-DCs (Fig. 5A). However, analyzing quantitatively the relative expression of the two isoforms, we found that GATA1-FL is only 10–20% of GATA1-FL and GATA1s combined. This indicates that at mRNA level, mo-DCs contain higher levels of GATA1s (Fig. 5B). This led us to examine GATA1 isoform expression at the protein level, and for that we used antibodies that recognize either both isoforms (targeted against a C-terminus peptide of GATA1), or otherwise the long isoform only (targeted against an N-terminus peptide of GATA1). We could detect the long isoform of GATA1 in monocytes, and moDCs in steady state or cultured with LPS stimulation. GATA1 is a lowabundance transcription factor in these cells, as compared to DAMI cell line (used as control), and long exposure allowed us to detect also GATA1s in monocytes and mo-DCs stimulated with LPS (Fig. 5C). Western blotting results do not correlate to the quantification of the GATA1 isoforms at the mRNA level, either in monocytes, mo-DCs or DAMI control cell line.

3.3. Human monocytes and monocyte-derived dendritic cells The similarities and differences between mouse and human DCs, for example in surface marker expression and cytokine production, are many [7], but relatively little is known about the expression of GATA factors in human DCs. Monocytes were cultured with GM-CSF and IL4 to generate monocyte derived DCs (mo-DCs), activated with LPS at day 7 and harvested at day 8. The culture status and DC activation upon LPS was confirmed by flow cytometry. The culture was very homogenous, with a purity of CD11c+|CD11b+ cells above 95% in all cultures. Activation of mo-DCs was analyzed by the expression of HLA-DR, and the co-stimulatory molecules CD40 and CD86 (Fig. 4A). All three markers increased significantly after LPS activation. Since it has been recently shown that GATA1 expression is upregulated in mo-DCs compared to monocytes [28], we included monocytes in our characterization. In monocytes, PU.1 was the highest in expression compared to either of the three GATA factors analyzed. The three GATA factors were expressed at similar levels amongst themselves (Fig. 4B). The relative RNA-levels in steady state mo-DCs (Fig. 4C) displayed a different pattern compared to monocytes. GATA1 levels strongly increased, as expected [28]. GATA2 had the lowest expression levels of all these transcription factors tested. GATA3 and PU.1 were expressed at similar levels, but still lower compared to GATA1. Next we analyzed the influence of differentiation and LPS activation on the expression of the single factors (Fig. 4D). GATA1 was significantly upregulated during the differentiation towards mo-DCs, however, LPS activation did not influence its expression further. The levels of GATA2 and PU.1 decreased during mo-DC differentiation, and LPS activation did not influence the expression further. The levels of GATA3 remained stable during the differentiation from monocytes, to mo-DCs and also after LPS stimulation. This suggests a different behavior of the transcription factor dynamics upon stimulation between mouse and human GM-CSF-derived or the so-called inflammatory DCs, since in mouse GM-CSF-derived DCs, Gata1 and PU.1 levels are influenced by LPS stimulation, while in

3.4. IL4 influences the balance of GATA factors in mouse DCs To culture human monocyte-derived DCs, IL4 is required in addition to GM-CSF, whereas GM-CSF alone gives rise to monocyte derived macrophages. IL4 induces GATA1 expression in mo-DCs, which is required for monocytes to differentiate into mo-DCs and loss of GATA1 results in differentiation arrest at the monocyte stage in these culture

A

B CD40 3

ST

C 0.25

LPS

1

0

LPS

Relative expression

**

0.10 0.05

Gata1

** 1.0

0.5

0.0

Gata1 Gata2 Gata3

ST

0.8 0.6 0.4

*

*

*

0.05 0.04 0.03 0.02 0.01 0.00

LPS

Gata1 Gata2 Gata3

PU.1

D

Steady state

0.15

0.00

5

0

ST

1.5

0.20

10

Monocytes

PU.1

M

ST LPS

Gata2

4 3 2 1 0

Gata3 2.5

M

ST LPS

2.0

**

40

1.5 1.0

20

0.5 0.0

PU.1 60

Relative expression

0.0

***

2

Relative expression

0.5

** Relative MFI

1.0

15

Relative expression

1.5

CD86 Relative expression

HLA-DR *** Relative MFI

Relative MFI

2.0

Relative expression

299

M

ST LPS

0

M

ST LPS

Fig. 4. Expression levels of GATA transcription factors in human monocytes and mo-DCs. A. Bar graphs representing the MFI expression levels of HLA-DR, CD40, and CD86 in human monocyte derived DCs (CD11b+|CD11c+) upon LPS stimulation, as measured by flow cytometry analysis. B. Bar graph representing mRNA qRT-PCR analysis of transcription factor expression in freshly isolated monocytes. C. Bar graph representing mRNA qRT-PCR analysis of transcription factor expression in monocyte-derived DCs in steady state condition. D. Bar graphs representing mRNA qRT-PCR analysis of the expression levels of each transcription factor of study on freshly isolated monocytes, and on GM-CSF/IL4 steady state and LPS-stimulated DC cultures. At least three independent cultures were used for analysis.

300

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

A

7.75 kb

I

Mo

m

DC ST

DC LPS

II

III

IV

V

VI

Dami m

m

Ex I-II Ex IV-VI GAPDH

B RFE setting L+S to 100

100 80

Mo

m

60

DC ST

DC LPS Ex II

40

Ex III-IV 20

GAPDH 0 Mo

DC ST

DC LPS

FL+S (Ex III-IV) FL (Ex II)

C

DAMI

Ex II

Ex III-IV

* GATA1-FL * * GATA1s

*

GAPDH

DC Dami Mo ST LPS (ab11852) (long exposure)

* GATA1-FL * * GATA1s * GATA1-FL * * GATA1s

(short exposure)

VINCULIN

Dami

m

Dami

DC Dami Mo ST LPS (ab11852) * * *

m

DC Dami Mo ST LPS

DC Mo ST LPS GATA1-FL * (ab11963) VINCULIN

GATA1-FL * (N6) GAPDH

Fig. 5. Expression of both GATA1 isoforms in human monocytes and mo-DCs. A. RT-PCR analysis of GATA1 isoform expression in human monocytes and mo-DCs in steady state and upon LPS stimulation, using DAMI cell line as control. Primer location is indicated in the scheme, and allowed us to discern between full length (GATA1-FL) and GATA1s isoforms. Gel pictures show amplification products. “m”, marker. B. Bar graph representing the relative fold enrichment (RFE) of GATA1-FL (FL) alone compared to GATA1-FL and GATA1s together (FL + S) as measured by qRT-PCR. Gel pictures show amplification products. FL + S was set to 100%. C. Western blotting analysis of GATA1 isoform expression in monocytes and mo-DCs in steady state and upon LPS stimulation, using DAMI cell line as control. Ab11852 recognizes both GATA1-FL and GATA1s isoforms, while ab11963 and N6 recognize only GATA1-FL. VINCULIN or GAPDH were used as loading controls.

conditions [28]. Therefore, we wondered whether we could further induce Gata1 expression in mouse GM-DCs when IL4 was added to the culture. For this purpose, mouse bone marrow was cultured with GMCSF with or without addition of IL4. The culture phenotype and activation upon stimulation were analyzed by flow cytometry. Addition of

IL4 resulted in the same percentage of CD11chigh|CD24+ cells as in the culture with only GM-CSF (Fig. 6A), however it did impact the maturation status of DCs. Expression of the activation markers, MHC-II, CD86 and CD40 (Fig. 6A) were already much higher in steady state condition and only CD40 increased after LPS activation, in the presence of IL4. The

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

MHC II *

% DCs 50000

150

**

***

* MFI

% 50

***

40000

1000

30000 20000

** ***

*

40000

100

CD86 60000

MFI

*

CD40 1500

MFI

A

301

20000

500

10000 0

0

ST

0

0

ST

LPS

ST

LPS

ST

LPS

LPS

B Gata2

100 50

100

50

ST

*

*

100 50

**

***

G2

G3

PU.1

G1

G2

ST

LPS

G3

PU.1

LPS

GM-CSF GM-CSF IL4

2.0 1.5 1.0 0.5 0.0

G1

50

Fold induction with LPS

Fold induction

P=0.06

***

***

100

2.5

*

n.s.

2 0.05 0.04 0.03 0.02 0.01 0.00

*

0

ST

D

4 3

**

150

LPS

mRNA expression 5

150

0

ST

LPS

C 6

200

0

0

Relative expression

**

PU.1

250

Relative expression

P=0.05

150

Gata3

150

Relative expression

*

Relative expression

Relative expression

Gata1 200

Gata1

Gata2

Gata3

PU.1

Fig. 6. IL4 induces Gata3 and inhibits Gata2 in mouse GM-CSF DCs. A. Bar graphs representing the percentage of CD11c+|CD24+ GM-CSF DCs (black bars) and GM-CSF/IL4 DCs (gray bars) in culture and the expression of activation markers MHC-II, CD40, and CD86, measured by flow cytometry. B. Bar graphs representing mRNA qRT-PCR analysis of transcription factor expression in GM-CSF DCs (black bars) and GM-CSF/IL4 DCs (gray bars) in steady state and after activation with LPS. C. Bar graph representing mRNA qRT-PCR analysis of the expression pattern of transcription factors in steady state GM-CSF DCs (black bars) and GM-CSF/IL4 DCs (gray bars) cultures. D. Bar graph representing the fold induction of mRNA levels of transcription factors as measured by qRT-PCR after LPS stimulation of GM-CSF DCs (black bars) and GM-CSF/IL4 DCs (gray bars) cultures. At least three independent cultures were used for analysis.

levels of CD86 and MHC-II remained similar or decreased respectively after activation (Fig. 6A). The transcript levels of Gata1 and PU.1 were not affected by IL4 addition, and increased and decreased respectively after activation with LPS in both culture conditions (Fig. 6B–D). However, Gata2 and Gata3 expression levels were affected by IL4 addition. Levels of Gata2 decreased significantly in steady state and increased slightly after LPS stimulation, but remained repressed by IL4 (Fig. 6B– D). Gata3 on the other hand was induced by IL4, and increased even more after LPS stimulation (Fig. 6B–D). 4. Discussion This study provides, for the first time, a systematic description of GATA transcription factor expression in mouse and human DCs. We found all three hematopoietic GATA transcription factors present in all DCs subtypes analyzed, of both murine and human origin. PU.1, a well-known transcription factor in DCs and antagonist of Gata1, was expressed a ten-fold higher in murine DCs, both cultured and freshly isolated, but expressed at similar levels in human monocyte-derived DCs. Major differences in the different DCs analyzed were the expression levels and pattern of the three GATA transcription factors, especially of Gata3. GATA transcription factors play distinct yet essential roles in

the hematopoietic system [51]. In addition to erythropoiesis and megakaryopoiesis [29], Gata1 was found to be important in the development of dendritic cells in mouse [27] and human [28]. In humans, loss of function mutations of GATA2 resulted in loss of DCs, monocytes, B-cells and NK-cells [40]. However, additional data regarding the expression of GATA3 in DCs was missing. We characterized different mouse in vitro DC culture protocols and compared it to freshly isolated murine splenic DC subtypes and human monocyte-derived DC cultures. In both mouse BM-derived DC cultures (GM-CSF or Flt3L) the expression levels of PU.1 was about a tenfold higher compared to the GATA transcription factors, which is comparable to the findings in freshly isolated splenic DC subtypes. However, major differences between the two culture protocols and ex vivo DCs, were found with respect to the three GATA transcription factors. Expression of Gata3 was the highest of the GATA factors in freshly isolated murine splenic DCs, especially in the CD11b+ cDC subset. However, we did not observed induction of GATA3 in neither of the two murine DC culture methods, nor in the human monocyte derived DCs; rather we saw downregulation of Gata3 upon LPS stimulation in FLt3L-derived mouse cultures. Until now, Gata3 was mainly described in T-cells, were it induces CD4 expression through Runx3 [52]. Expression of Gata3 has not been described in DCs before, however, ablation

302

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303

of Runx3 was shown to result in a decrease of the splenic CD11b+ cDC subset [53]. Therefore, we hypothesize that Gata3 is required for the induction of Runx3 in dendritic cells and thereby for the differentiation of the splenic CD11b+ cDC subset. Because it was previously reported that IL4 induces Gata3 expression in T-cells [52], and because IL4 is required for the differentiation of human monocyte-derived DCs [28], we also studied the effect of adding IL4 to murine GM-CSF-derived cultures. In concordance with this notion, expression of Gata3 was induced in the cultures supplemented with IL4, however not to the expression levels that were observed in freshly isolated splenic DCs. Therefore, we hypothesize that in vitro cultured DCs might be more comparable to the in vivo situation if we can find a way to properly induce Gata3 expression levels in DCs. In humans, there are two isoforms of GATA1, i.e. GATA1-FL and GATA1s, depending on translation starting on exon 2 or 3 [31]. Both isoforms are equally expressed in eosinophils, but previous studies pointed out the undetectable levels of GATA1 in mo-DCs, being GATA1s detected only in mature mo-DCs [54]. Diamond–Blackfan patients have a mutated Gata1 gene, resulting in loss of Gata1-FL, although GATA1s is normally expressed. The expression of only GATA1s was insufficient for proper erythropoiesis [31–33]. In addition, mutations in exon 2 of GATA1 of patients with Down syndrome are causative of transient myeloproliferative disorder (TMD) [55]. Therefore, we analyzed the expression of both GATA1-FL and GATA1s in monocyte-derived DCs. We found that the expression of GATA1s mRNA is more abundant in monocytes and mo-DCs, both in steady state and after LPS stimulation. However, when analyzing isoform expression at the protein level, we readily detected GATA1-FL (although being a low-abundance transcription factor when compared to DAMI cell line), while GATA1s was only detected in monocytes and LPS-stimulated DCs after long exposure of the Western blot developing film. However, it would be interesting to analyze the expression of GATA1-FL and GATA1s not only in monocytes and mo-DCs, but also in prospectively isolated DC subtypes, and in the context of GATA1 exon2 mutations. We cannot discard that expression of only GATA1s would be sufficient for the monocyte/DC lineage to develop and function properly in the context of GATA1 mutations affecting the expression of the GATA1-FL isoform, i.e. Diamond–Blackfan anemia and Down Syndrome. Mutations in the GATA2 gene have been recently linked to the human immunodeficiency syndrome MonoMAC, which is characterized by loss of DCs, monocytes, B-cells and NK-cells [40]. We found expression of GATA2 in both monocytes as in monocyte-derived DCs. Although the GATA2 expression levels in monocytes are more variable amongst donors, in all cases expression levels decreased upon DC differentiation. In addition, in murine GM-CSF BM-derived DCs, in which DC differentiation is assumed to go through the monocytic pathway, Gata2 is the highest in expression amongst the GATA factors. This suggests an important, and yet unanticipated, role for GATA2 in the development of monocytes towards inflammatory dendritic cells. Lastly, we questioned whether a GATA switch was present in DC differentiation or activation, as was observed to play a determinant role in other lineages, like the erythroid or megakaryocytic [44, 47, 48]. In human primary cultures, we observed a clear shift in the expression level balance between GATA1 and GATA2 in the differentiation from monocytes towards monocyte-derived DCs. Levels of GATA1 were strongly induced, and GATA2, although not significant by the donordependent variation noted in monocytes, decreased in all cases in monocyte-derived DCs. Taken together with the MonoMAC syndrome, this might indicate that GATA2 expression is required to induce GATA1 expression for the DC differentiation at the monocyte precursor stage. These results are also suggestive of a GATA switch playing a role in human inflammatory DC differentiation from circulating monocytes. In both of the mouse DC culture protocols, we did not observe a clear GATA factor expression level alternating shifts that could suggest the presence of a GATA switch, although we examined expression level changes upon DC stimulation. DC stimulation does influence the expression of all

GATA factors examined, especially Gata1 in GM-CSF-derived cultures (upregulated) and Gata1-3 in FLt3L-derived cultures (all downregulated). However, we cannot exclude that GATA factors might regulate each other during mouse dendritic cell differentiation from precursor stages. Here we studied the expression of GATA factors and PU.1 comparing mouse and human DCs. In both species, two subsets of cDCs have been described. CD8+ and CD11b+ in mouse and CD141+ (BDCA3+) and CD1c+ (BDCA1+) in human respectively [10, 11]. However, the in vivo cDC development of human DCs is less well understood than that of mouse cDC development. In vitro human cDCs are often cultured from monocytes in the presence of GM-CSF/IL4, however, these monocytederived DCs, or inflammatory DCs, also relate to activated monocytes [56]. Recently, a new culture method was described using human CD34+ hematopoietic stem cells cultured with Flt3L, SCF and GM-CSF on stromal cells, which gave rise to, amongst other cell types, the two major DC types (which include pDCs and both subsets of cDCs) [57], which were closely related to the in vivo subsets [57, 58]. Therefore, it might be interesting to study the expression of GATA1-3 and PU.1 also from freshly isolated human DCs and compare these to the mouse ex vivo DC subsets. In conclusion, we found PU.1 expression to be the highest in all mouse DC culture methods and also in the freshly isolated splenic DC subsets. The main difference in expression levels of the GATA factors between freshly isolated splenic DC subsets and cultured BM derived DCs is the “failed” induction of Gata3 in culture. We found that IL4 slightly induced Gata3 expression in culture, although not to comparable levels as ex vivo. In human monocyte derived DC cultures, we observed a potential GATA1–GATA2 GATA switch in the differentiation from monocytes towards DCs, although not after activation. However, the specific function and/or redundancy of GATA factors (especially of GATA2 and GATA3) in human ex vivo DCs remains to be elucidated. Acknowledgments This work was supported by a VENI grant from the Netherlands Scientific Organization (NWO) to LG (VENI 863.09.012). References [1] S.H. Naik, Generation of large numbers of pro-DCs and pre-DCs in vitro, Methods Mol. Biol. 595 (2010) 177–186. [2] F. Geissmann, The origin of dendritic cells, Nat. Immunol. 8 (6) (2007) 558–560. [3] F. Geissmann, C. Auffray, R. Palframan, C. Wirrig, A. Ciocca, L. Campisi, et al., Blood monocytes: distinct subsets, how they relate to dendritic cells, and their possible roles in the regulation of T-cell responses, Immunol. Cell Biol. 86 (5) (2008) 398–408. [4] J.A. Villadangos, P. Schnorrer, Intrinsic and cooperative antigen-presenting functions of dendritic-cell subsets in vivo, Nat. Rev. Immunol. 7 (7) (2007) 543–555. [5] K. Shortman, S.H. Naik, Steady-state and inflammatory dendritic-cell development, Nat. Rev. Immunol. 7 (1) (2007) 19–30. [6] M. Gilliet, W. Cao, Y.J. Liu, Plasmacytoid dendritic cells: sensing nucleic acids in viral infection and autoimmune diseases, Nat. Rev. Immunol. 8 (8) (2008) 594–606. [7] K. Shortman, Y.J. Liu, Mouse and human dendritic cell subtypes, Nat. Rev. Immunol. 2 (3) (2002) 151–161. [8] T. Kawai, S. Akira, The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors, Nat. Immunol. 11 (5) (2010) 373–384. [9] T. Liu, T. Matsuguchi, N. Tsuboi, T. Yajima, Y. Yoshikai, Differences in expression of toll-like receptors and their reactivities in dendritic cells in BALB/c and C57BL/6 mice, Infect. Immun. 70 (12) (2002) 6638–6645. [10] M. Haniffa, A. Shin, V. Bigley, N. McGovern, P. Teo, P. See, et al., Human tissues contain CD141hi cross-presenting dendritic cells with functional homology to mouse CD103+ nonlymphoid dendritic cells, Immunity 37 (1) (2012) 60–73. [11] S.H. Naik, Demystifying the development of dendritic cell subtypes, a little, Immunol. Cell Biol. 86 (5) (2008) 439–452. [12] D. Dudziak, A.O. Kamphorst, G.F. Heidkamp, V.R. Buchholz, C. Trumpfheller, S. Yamazaki, et al., Differential antigen processing by dendritic cell subsets in vivo, Science 315 (5808) (2007) 107–111. [13] M.H. Lahoud, A.I. Proietto, K.H. Gartlan, S. Kitsoulis, J. Curtis, J. Wettenhall, et al., Signal regulatory protein molecules are differentially expressed by CD8− dendritic cells, J. Immunol. 177 (1) (2006) 372–382. [14] K. Liu, M.C. Nussenzweig, Origin and development of dendritic cells, Immunol. Rev. 234 (1) (2010) 45–54.

M.R. Scheenstra et al. / Blood Cells, Molecules and Diseases 55 (2015) 293–303 [15] S.H. Naik, D. Metcalf, A. van Nieuwenhuijze, I. Wicks, L. Wu, M. O'Keeffe, et al., Intrasplenic steady-state dendritic cell precursors that are distinct from monocytes, Nat. Immunol. 7 (6) (2006) 663–671. [16] D. Vremec, J. Pooley, H. Hochrein, L. Wu, K. Shortman, CD4 and CD8 expression by dendritic cell subtypes in mouse thymus and spleen, J. Immunol. 164 (6) (2000) 2978–2986. [17] F. Geissmann, M.G. Manz, S. Jung, M.H. Sieweke, M. Merad, K. Ley, Development of monocytes, macrophages, and dendritic cells, Science 327 (5966) (2010) 656–661. [18] S. Carotta, A. Dakic, A. D'Amico, S.H. Pang, K.T. Greig, S.L. Nutt, et al., The transcription factor PU.1 controls dendritic cell development and Flt3 cytokine receptor expression in a dose-dependent manner, Immunity 32 (5) (2010) 628–641. [19] S.L. Nutt, D. Metcalf, A. D'Amico, M. Polli, L. Wu, Dynamic regulation of PU.1 expression in multipotent hematopoietic progenitors, J. Exp. Med. 201 (2) (2005) 221–231. [20] E. Ichikawa, S. Hida, Y. Omatsu, S. Shimoyama, K. Takahara, S. Miyagawa, et al., Defective development of splenic and epidermal CD4+ dendritic cells in mice deficient for IFN regulatory factor-2, Proc. Natl. Acad. Sci. U. S. A. 101 (11) (2004) 3909–3914. [21] S. Suzuki, K. Honma, T. Matsuyama, K. Suzuki, K. Toriyama, I. Akitoyo, et al., Critical roles of interferon regulatory factor 4 in CD11bhighCD8alpha− dendritic cell development, Proc. Natl. Acad. Sci. U. S. A. 101 (24) (2004) 8981–8986. [22] T. Tamura, P. Tailor, K. Yamaoka, H.J. Kong, H. Tsujimura, J.J. O'Shea, et al., IFN regulatory factor-4 and -8 govern dendritic cell subset development and their functional diversity, J. Immunol. 174 (5) (2005) 2573–2581. [23] L. Wu, A. D'Amico, K.D. Winkel, M. Suter, D. Lo, K. Shortman, RelB is essential for the development of myeloid-related CD8alpha− dendritic cells but not of lymphoidrelated CD8alpha+ dendritic cells, Immunity 9 (6) (1998) 839–847. [24] K. Hildner, B.T. Edelson, W.E. Purtha, M. Diamond, H. Matsushita, M. Kohyama, et al., Batf3 deficiency reveals a critical role for CD8alpha+ dendritic cells in cytotoxic T cell immunity, Science 322 (5904) (2008) 1097–1100. [25] B. Cisse, M.L. Caton, M. Lehner, T. Maeda, S. Scheu, R. Locksley, et al., Transcription factor E2-2 is an essential and specific regulator of plasmacytoid dendritic cell development, Cell 135 (1) (2008) 37–48. [26] H.S. Ghosh, B. Cisse, A. Bunin, K.L. Lewis, B. Reizis, Continuous expression of the transcription factor e2-2 maintains the cell fate of mature plasmacytoid dendritic cells, Immunity 33 (6) (2010) 905–916. [27] L. Gutierrez, T. Nikolic, T.B. van Dijk, H. Hammad, N. Vos, M. Willart, et al., Gata1 regulates dendritic-cell development and survival, Blood 110 (6) (2007) 1933–1941. [28] F. Gobel, S. Taschner, J. Jurkin, S. Konradi, C. Vaculik, S. Richter, et al., Reciprocal role of GATA-1 and vitamin D receptor in human myeloid dendritic cell differentiation, Blood 114 (18) (2009) 3813–3821. [29] H. Kaneko, R. Shimizu, M. Yamamoto, GATA factor switching during erythroid differentiation, Curr. Opin. Hematol. 17 (3) (2010) 163–168. [30] K. Ohneda, T. Moriguchi, S. Ohmori, Y. Ishijima, H. Satoh, S. Philipsen, et al., Transcription factor GATA1 is dispensable for mast cell differentiation in adult mice, Mol. Cell. Biol. 34 (10) (2014) 1812–1826. [31] S. Parrella, A. Aspesi, P. Quarello, E. Garelli, E. Pavesi, A. Carando, et al., Loss of GATA-1 full length as a cause of Diamond–Blackfan anemia phenotype, Pediatr. Blood Cancer 61 (7) (2014) 1319–1321. [32] V.G. Sankaran, R. Ghazvinian, R. Do, P. Thiru, J.A. Vergilio, A.H. Beggs, et al., Exome sequencing identifies GATA1 mutations resulting in Diamond–Blackfan anemia, J. Clin. Invest. 122 (7) (2012) 2439–2443. [33] L.S. Ludwig, H.T. Gazda, J.C. Eng, S.W. Eichhorn, P. Thiru, R. Ghazvinian, et al., Altered translation of GATA1 in Diamond–Blackfan anemia, Nat. Med. 20 (7) (2014) 748–753. [34] J.T. Caldwell, H. Edwards, A.A. Dombkowski, S.A. Buck, L.H. Matherly, Y. Ge, et al., Overexpression of GATA1 confers resistance to chemotherapy in acute megakaryocytic leukemia, PLoS One 8 (7) (2013) e68601. [35] L. Pevny, C.S. Lin, V. D'Agati, M.C. Simon, S.H. Orkin, F. Costantini, Development of hematopoietic cells lacking transcription factor GATA-1, Development 121 (1) (1995) 163–172. [36] H. Tanaka, I. Matsumura, K. Nakajima, H. Daino, J. Sonoyama, H. Yoshida, et al., GATA-1 blocks IL-6-induced macrophage differentiation and apoptosis through the sustained expression of cyclin D1 and bcl-2 in a murine myeloid cell line M1, Blood 95 (4) (2000) 1264–1273.

303

[37] D.J. Whyatt, A. Karis, I.C. Harkes, A. Verkerk, N. Gillemans, A.G. Elefanty, et al., The level of the tissue-specific factor GATA-1 affects the cell-cycle machinery, Genes Funct. 1 (1) (1997) 11–24. [38] C. Vicente, A. Conchillo, M.A. Garcia-Sanchez, M.D. Odero, The role of the GATA2 transcription factor in normal and malignant hematopoiesis, Crit. Rev. Oncol. Hematol. 82 (1) (2012) 1–17. [39] K. Kitajima, M. Tanaka, J. Zheng, H. Yen, A. Sato, D. Sugiyama, et al., Redirecting differentiation of hematopoietic progenitors by a transcription factor, GATA-2, Blood 107 (5) (2006) 1857–1863. [40] R.E. Dickinson, H. Griffin, V. Bigley, L.N. Reynard, R. Hussain, M. Haniffa, et al., Exome sequencing identifies GATA-2 mutation as the cause of dendritic cell, monocyte, B and NK lymphoid deficiency, Blood 118 (10) (2011) 2656–2658. [41] C.J. Ku, T. Hosoya, I. Maillard, J.D. Engel, GATA-3 regulates hematopoietic stem cell maintenance and cell-cycle entry, Blood 119 (10) (2012) 2242–2251. [42] I.C. Ho, T.S. Tai, S.Y. Pai, GATA3 and the T-cell lineage: essential functions before and after T-helper-2-cell differentiation, Nat. Rev. Immunol. 9 (2) (2009) 125–135. [43] S.I. Samson, O. Richard, M. Tavian, T. Ranson, C.A. Vosshenrich, F. Colucci, et al., GATA-3 promotes maturation, IFN-gamma production, and liver-specific homing of NK cells, Immunity 19 (5) (2003) 701–711. [44] E.H. Bresnick, H.Y. Lee, T. Fujiwara, K.D. Johnson, S. Keles, GATA switches as developmental drivers, J. Biol. Chem. 285 (41) (2010) 31087–31093. [45] S. Pal, A.B. Cantor, K.D. Johnson, T.B. Moran, M.E. Boyer, S.H. Orkin, et al., Coregulator-dependent facilitation of chromatin occupancy by GATA-1, Proc. Natl. Acad. Sci. U. S. A. 101 (4) (2004) 980–985. [46] A.D. Friedman, Transcriptional control of granulocyte and monocyte development, Oncogene 26 (47) (2007) 6816–6828. [47] J.A. Grass, M.E. Boyer, S. Pal, J. Wu, M.J. Weiss, E.H. Bresnick, GATA-1-dependent transcriptional repression of GATA-2 via disruption of positive autoregulation and domain-wide chromatin remodeling, Proc. Natl. Acad. Sci. U. S. A. 100 (15) (2003) 8811–8816. [48] M. Pimkin, A.V. Kossenkov, T. Mishra, C.S. Morrissey, W. Wu, C.A. Keller, et al., Divergent functions of hematopoietic transcription factors in lineage priming and differentiation during erythro-megakaryopoiesis, Genome Res. 24 (12) (2014) 1932–1944. [49] T.D. Schmittgen, K.J. Livak, Analyzing real-time PCR data by the comparative C(T) method, Nat. Protoc. 3 (6) (2008) 1101–1108. [50] S.M. Greenberg, D.S. Rosenthal, T.A. Greeley, R. Tantravahi, R.I. Handin, Characterization of a new megakaryocytic cell line: the Dami cell, Blood 72 (6) (1988) 1968–1977. [51] R.S. Viger, S.M. Guittot, M. Anttonen, D.B. Wilson, M. Heikinheimo, Role of the GATA family of transcription factors in endocrine development, function, and disease, Mol. Endocrinol. 22 (4) (2008) 781–798. [52] Y.Y. Wan, GATA3: a master of many trades in immune regulation, Trends Immunol. 35 (6) (2014) 233–242. [53] J. Dicken, A. Mildner, D. Leshkowitz, I.P. Touw, S. Hantisteanu, S. Jung, et al., Transcriptional reprogramming of CD11b+ Esam(hi) dendritic cell identity and function by loss of Runx3, PLoS One 8 (10) (2013) e77490. [54] C. Halsey, M. Docherty, M. McNeill, D. Gilchrist, M. Le Brocq, B. Gibson, et al., The GATA1s isoform is normally down-regulated during terminal haematopoietic differentiation and over-expression leads to failure to repress MYB, CCND2 and SKI during erythroid differentiation of K562 cells, J. Hematol. Oncol. 5 (2012) 45. [55] G. Xu, M. Nagano, R. Kanezaki, T. Toki, Y. Hayashi, T. Taketani, et al., Frequent mutations in the GATA-1 gene in the transient myeloproliferative disorder of Down syndrome, Blood 102 (8) (2003) 2960–2968. [56] S.H. Robbins, T. Walzer, D. Dembele, C. Thibault, A. Defays, G. Bessou, et al., Novel insights into the relationships between dendritic cell subsets in human and mouse revealed by genome-wide expression profiling, Genome Biol. 9 (1) (2008) R17. [57] J. Lee, G. Breton, T.Y. Oliveira, Y.J. Zhou, A. Aljoufi, S. Puhr, et al., Restricted dendritic cell and monocyte progenitors in human cord blood and bone marrow, J. Exp. Med. 212 (3) (2015) 385–399. [58] G. Breton, J. Lee, Y.J. Zhou, J.J. Schreiber, T. Keler, S. Puhr, et al., Circulating precursors of human CD1c+ and CD141+ dendritic cells, J. Exp. Med. 212 (3) (2015) 401–413.