www.sciencemag.org/cgi/content/full/science.1251414/DC1

Supplementary Materials for

The Transcription Factor Gata6 Links Tissue Macrophage Phenotype and Proliferative Renewal

Marcela Rosas, Luke C. Davies, Peter J. Giles, Chia-Te Liao, Bashar Kharfan, Timothy C. Stone, Valerie B. O’Donnell, Donald J. Fraser, Simon A. Jones, Philip R. Taylor*

*Corresponding author. E-mail: taylorpr@cf.ac.uk

Published 24 April 2014 on Science Express

DOI: 10.1126/science.1251414

This PDF file includes:

Materials and Methods Figs. S1 to S11 Tables S1 to S7 References (25–37)

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Materials and Methods

Mice C57BL/6 mice were obtained from Harlan or Charles River Laboratories.

Lysozyme M Cre-recombinase ‘knock-in’ congenic mice on the C57BL/6 background (‘Lyz2Cre’, B6.129P2-Lyz2tm1(cre)Ifo/J)(13) and conditional ‘floxed’ Gata6 deficient mice (‘Gata6Fl’, Gata6tm2.1Sad/J) (12) were obtained from the Jackson Labs. All mice were sex-matched and between 6-12 weeks of age at the time of use, unless otherwise stated. Gata6-myeloid knockout (KOmye) mice (Lyz2+/CreGata6Fl/Fl), heterozygous KOmye mice (‘Het’, Lyz2+/CreGata6+/Fl) and ‘wild type’ (WT) littermates (Lyz2+/+Gata6Fl/Fl or Lyz2+/+Gata6+/Fl) were used in all experiments and were generated from crosses of two double heterozygous KO animals or crosses of KO animals and Lyz2+/+Gata6Fl/Fl mice, as appropriate. Lower levels of residual Gata6 truncated protein are known to be expressed from the Cre-deleted gene (12). 129S6 (CD45.2) and 129S6.CD45.1 congenic mice were bred in our own animal facilities.

Peritoneal cells were recovered by lavage with 5ml of ice-cold 5 mM EDTA in PBS. For study of peritonitis or genetically modified peritoneal cells, mice were first injected intraperitoneally at defined time points with zymosan particles (typically 2x106 particles unless indicated) in 100-300 µl of PBS or concentrated lentiviral particles in 100-300 µl of Aim V media (Life technologies). In select experiments, mice also received 1mg of 5-ethynyl-2'-deoxyuridine (EdU, Life Technologies) intraperitoneally.

All animal work was conducted in accordance with Institutional and UK Home Office guidelines.

Flow-cytometry and flow-cytometric cell sorting

Flow-cytometric staining (surface staining or after fixation and permeabilization) was conducted using our standard protocols (4, 6, 20, 23). For cell purifications for the peritonitis microarray study, lavages from mice were pooled, stained as detailed in Fig.1 and Table S1 and sorted on a MoFlo Legend (Beckman-Coulter) or FACSAria III (BD biosciences) for single events (via pulse width or FSCheight vs FSCarea respectively) with the defined flow-cytometric phenotype (Fig.1 and see below). Cell purities were verified flow-cytometrically and cellular morphologies after cytospin preparation were visualized on a Leica DMLB microscope (Leica) after using Microscopy Hemacolour stain (Merck) or on a Life Technologies Evos FL (Life Technologies) after fluorescent staining.

Analytical polychromatic flow-cytometry was conducted on the 3 laser CyAn ADP analyzer (Beckman-Coulter) and analyzed using Summit software v4.3 (Beckman-Coulter) and FlowJo v7.6.3 (TreeStar). Leukocytes in the blood and peritoneal cavity of naïve wild type animals were identified according to the criteria outlined in Table S2.

Antibodies

The following antibodies were used in this study: anti-Ly-6B.2-phycoerythrin (PE) (7/4 (4); AbD Serotec); anti-Ly-6G-PE-cyanine (Cy)7 (1A8; BD biosciences); anti-Ly-6C-Alexa Fluor (AF) 488 (ER-MP20, AbD Serotec); anti-Ki67-PE or FITC kit (including isotype controls) (B56, BD Biosciences); anti-Myc-tag-AF647 (9B11, NEB); anti-Tim4-PE (RMT4-54; eBiosciences); anti-F4/80-PE, -biotin or -AF405 (CL:A3-1; AbD

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Serotec); anti-MHCII (I-A/I-E)-Peridinin-chlorophyll-protein complex (PerCP)-Cy5.5 (M5/114.15.2, BioLegend) or -biotin (2G9, BD Biosciences); anti-IgM (II/41, eBioscience); anti-IgD-allophycocyanin (11-26c, eBioscience); anti-SIGNR1-AF647 (22D1; eBiosciences); anti-CRIg-biotin or FITC (MBI4; a gift from Dr. Claire Harris (Cardiff)); anti-ratCD2-AF488 or AF647 (Ox-34, AbD Serotec); anti-CD4-PE-Cy7 (RM4-5, eBioscience); anti-PIRA/B-PE (6C1, BD Biosciences); anti-CD5-biotin (57-7.3, BioLegend); anti-CD8-eFluor450 (53-6.7, eBioscience); anti-CD9-biotin (KMC8, BD Biosciences); anti-CD11b-allophycocyanin or -allophycocyanin-Cy7 (M1/70; BD biosciences) or –FITC (5C6, AbD Serotec); anti-CD11c-PE-Cy7 (HL3, BD biosciences) or –biotin (N418, AbD Serotec); anti-CD19-Pacific Blue/allophycocyanin (6D5, AbD Serotec or BioLegend); anti-CD23-PE (B3B4, eBioscience); anti-CD25-PE (PC61.5, eBioscience); anti-CD39-PE (24DMS1, eBioscience); anti-CD40-biotin (3/23, AbD Serotec); anti-CD43-FITC (eBioR2/60, eBioscience); anti-CD44-allophycocyanin (IM7, eBioscience); CD45.1-FITC (A20, Biolegend); CD45.2-allophycocyanin-Cy7 (104, BD Biosciences); anti-CD54-PE (3E2, BD Biosciences) and –biotin (YN1/1.7.4, Caltag Laboratories); anti-CD62L-FITC (MEL-14, BD Biosciences); anti-CD68-AF647 (FA-11, AbD Serotec); anti-CD73-biotin (TY/11.8, Biolegend); anti-CD80-biotin (16-10A1, BD Biosciences); anti-CD83-PE (Michel19, BD Biosciences); anti-CD93-PE (AA4.1, eBioscience); anti-CD107b-PE (M3/84, BD Biosciences); anti-CD172a-PE (p84, BD Biosciences); anti-CD204-biotin (2F8, AbD Serotec); polyclonal anti-human Gata6 (R&D systems). Streptavidin-PE-Texas red (BD Biosciences) and streptavidin-PerCP-Cy5.5 (eBioscience) were used to detect biotinylated primary antibodies.

The following isotype controls were also used: Rat IgG1-biotin (AbD Serotec); Rat IgG2a-biotin/PE (R35-95, BD Biosciences); Rat IgG2b-biotin (Homemade); Hamster IgG2a-biotin (B81-3, BD Biosciences); Hamster IgG1-biotin/PE (G235-G356, BD Biosciences); Rat IgG1-PE (R3-34, BD Biosciences); Rat IgG2b (A95-1, BD Biosciences); Rat IgG2a-AF647 (AbD Serotec); Hamster IgG-AF647 (eBio299Arm, eBioscience).

RNA extraction, Microarray analysis and RT-PCR

Peritonitis study – defining a peritoneal-resident MØ transcriptional profile: Peritonitis was induced as indicated above. These target cells were selected as they

represent an archetypal model of tissue-resident and inflammatory macrophages with distinct lineage origins (4, 6-8). The purification criteria are shown in Fig.S1A (see also Tables S1 and S2). The subsets of myeloid cells studied were purified from cells pooled from 5-15, 7 week old, female C57BL/6 mice. Total RNA, from 3 independent replicates per group, was extracted using Trizol (Invitrogen Life Technologies), according to the manufacturer’s instructions. The RNA was amplified and labeled using the GeneChip® Two-Cycle Target Labeling and Control Reagents from Affymetrix and hybridized to Affymetrix MOE430 2.0 GeneChips. All data passed the manufacturers QC thresholds and additional measure looking at RNA degradation localized scaling factor, and array correlation. Expression data were calculated using the MAS 5.0 algorithm and a target intensity (TGT) of 100 (GEO:GSE28621). Probesets were annotated using DAVID (25).

Differentially-expressed genes were identified using a one-way ANOVA with the P-values corrected for false discovery and multiple testing with the FDR methodology

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within the R environment. Confidence intervals for Pearson’s r values were computed using Fisher's z'. The values of Fisher's z' in the confidence interval were then converted back to Pearson's r values. To interrogate the functional significance of the transcriptional profiles we had identified, the probesets with ANOVA P values<0.001 were subject to K means clustering using Genesis (26).

Hierarchical clustering of those differentially-regulated probesets with an ANOVA P value of <1e–7 (FDR <1e–5%) (820 probesets) separated the 7 subsets broadly into a ‘monocytic-like’ and ‘macrophage-like’ groupings and emphasized the relationship between the 3 tissue-resident macrophage enriched populations (Fig.S1B). This was corroborated by a correlation in the expression of all measured transcripts between the resident macrophages and all other subsets (Fig.S1C). Probesets with ANOVA P values of <0.001 were subject to K means clustering using Genesis (26), generating 15 distinct gene expression clusters (Fig.S2). ‘Cluster 15’ was highly expressed only in the resident macrophage-enriched preparations. A summary of the genes and their functional activities that were enriched in the peritoneal-resident macrophage-restricted cluster 15 are summarized in Table S3). Within this cluster 215 individual probesets exhibit 10-fold higher expression than the mean expression observed in the ‘monocytic’ hierarchical cluster (identified in Fig.S1B above).

‘Cluster 15’was validated by its content of transcripts we and others have suggested to be restricted to peritoneal macrophages in C57BL/6 mice (namely: Cd209b (27), Visg4 (28) and Timd4 (6)) (Fig.S1D and Table S3A). However, Alox15, which is often associated with peritoneal-resident macrophages (16), but which we have found also expressed by recruited macrophages during inflammation (2), was excluded (Fig.S3). The Cluster was further validated, by assessment of the surface expression of Tim4, CRIg, Signr1 and CD73 (encoded by Nt5e and included in Cluster 15, Fig.S1D) in naïve mice (Fig.S1E) (obtaining similar results during experimental zymosan peritonitis, not shown). These studies confirmed the specificity of these markers for resident peritoneal macrophages in C57BL/6 mice.

Study of peritoneal-resident MØ Gata6-deficiency: Peritoneal macrophages (CD11bhighMHCIIlow/–) were pooled from 7 week old Gata6-

KO and WT mice (n=2-3/pool). Total RNA, from 3 independent replicates per group, was extracted using the RNeasy mini kit (Qiagen), according to the manufacturer’s instructions. The RNA was amplified and labeled using the GeneChip® Two-Cycle Target Labeling and Control Reagents from Affymetrix and hybridized to Affymetrix MOE430 2.0 GeneChips. All data passed the manufacturers QC thresholds and additional QC analysis looking at RNA degradation localized scaling factor, and array correlation. Expression data were calculated using the MAS 5.0 algorithm (GEO:GSE47049). Statistical significance differences between WT and Gata6-deficient cells were determined using an empirical bayesian statistic corrected for false discovery by the Benjamini-Hochberg procedure (29). Probesets were annotated using NetAffx Annotation (release 33, Affymetrix) and probe enrichment analyzed using DAVID (25) and transcriptional network analysis was conducted using Metacore (Thomson Reuters).

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Semi-quantitative and quantitative PCR studies For semi-quantitative analysis, cDNA was synthesized using the RETROscript kit

with random decamers (Ambion, Inc.,Austin, TX, USA), as described by the manufacturer. For quantitative analysis, RNA was extracted from cells using the RNeasy micro or mini kits (Qiagen). cDNA was synthesized using the Primer Design reverse transcription kit or Life Technologies high capacity cDNA reverse transcription kit and diluted to 5 ng/μl. Real-Time (RT) PCR amplification was performed with the SYBR Green JumpStart Taq ReadyMix without added MgCl2 (Sigma) using the ABI-7900HT fast RT-PCR system. Gata6 cycle threshold (Ct) values were normalized against the housekeeping gene Ywhaz and these values were expressed as a fold change. Primers (purchased from Sigma-Aldrich) used for RT-PCR (5’→3’) were: B2m, TGACCGGCTTGTATGCTATC and CAGTGTCAGCCAGGATATAG; Ahr, ATCGCCACTCAGAGACCAC and TGGATGAGGGCACTCATAAG; Ccnd2, TTACCTGGACCGTTTCTTGG and TGCTCAATGAAGTCGTGAGG; Ccr2, TGGCTGTGTTTGCCTCTCTA and CCTACAGCGAAACAGGGTGT; Cd209b, GCAGGAGAAGATCTACCAACA and AGGCCCGGGCTAGCCTTCAGTGCATGGGG; Ciita, TCTCCAGTGTCCTAATCTACCA and AGATGTGTCCTCTGTCTCATTT; Clec4n, CTGCCCAAATCACTGGAAGT and ATCATCGATCCATTGCCATT; Gata6, AAAGCTTGCTCCGGTAACAG and TCTCCCACTGCAGACATCAC; Gata6 (exon 2-3), GGTGCTCCACAGCTTACAGG and AGTGGCGTCTGGATGGAG Mrc1, ACGAGCCGAAGCTTAAGTCA and GCAATGGCCATAGAAAGGAA; Ptgs2, CCACTTCAAGGGAGTCTGGA and GAGAAGGCTTCCCAGCTTTT; Sell, CCATGAACTGGGAAAATGCT and CCTCCTTGGACTTCTTGTTGTT; Ywhaz, either TGCAAAAACAGCTTTCGATG and CCTGCTTCTGCTTCATCTCC or TTGAGCAGAAGACGGAAGGT and GAAGCATTGGGGATCAAGAA.

Peripheral blood counts

Total leukocyte, erythrocyte and platelet counts were determined as previously described (30) using counting beads (AbD Serotec) and 5 µM Draq5 (Biostatus) to identify nucleated leukocytes and FSC vs SSC profile to identify erythrocytes and platelets amongst the Draq5 negative/low cells.

For differential leukocyte counts, a 10 µl blood sample was added to 50 µl of blocking buffer (PBS supplemented with 0.5 % (w/v) BSA, 5 % (v/v) heat-inactivated rabbit serum, 2 mM sodium azide, 4 µg/ml 2.4G2) and incubated on ice for 30 minutes in 96 well plates. Antibodies (40 µl) were added for a further 30 minutes and then washed three times with ACK buffer (150mM NH4Cl, 10mM KHCO3, 0.1mM Na2EDTA - pH =7.2 to 7.4) to lyse erythrocytes. The leukocyte pellets were transfer into tubes with 1% formaldehyde for flow-cytometric analysis.

Preparation of lentiviral vectors and infectious lentiviral particles

The pHR’SIN-cPPT-SEW plasmid is previously described (31) and an eGFP deficient version (pHR’SIN-cPPT-SXW) was kindly provided by Dr. Paul Brennan (Cardiff). The ‘In-fusion’ cloning kit (Clontech) was used to modify these plasmids (see strategy in Table S4). Lentiviral particles were produced by transfecting HEK293T cells with lentiviral plasmid and helper constructs (pCMV-Δ8.91 (Gag/Pol, Tat and Rev) and

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pMD2.G (VSV-G coat)) using the Effectene transfection reagent (Qiagen). Lentivirus was concentrated using the Lenti-X concentrator kit (Clontech) with supernatants from HEK293T cells 48 hours after transfection. Lentiviral particles were resuspended in DPBS (Sigma) or Aim-V medium (Life Sciences) and stored at -80°C. For adoptive transfer experiments, bone-marrow macrophages were generated from 129S6.CD45.1 congenic mice in vitro as previously described with M-CSF (32). After 7 days, they were infected with lentiviral vectors and then subsequently (2 days later) transferred into the peritoneal cavity of naïve 129S6 mice. Infection rates of 40-70% were used for these adoptive transfer experiments with comparable infection within the same experiment.

Statistical analysis

One-way or Two-way ANOVAs (with or without Bonferroni post tests) and t-tests (paired or unpaired) were conducted using GraphPad Prism and the exact tests used are indicated within the appropriate text. Array data were analyzed as outlined above. Exact P values or the following abbreviations are used: * = P<0.05; ** = P<0.01; *** = P<0.001.

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Fig. S1. Definition of a peritoneal-resident macrophage-selective transcriptional profile and identification of Gata6. A. Representative flow-cytometric density plots showing the MoFlo acquisition data (left column) for the purification of bone marrow (BM)

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monocytes (Mo) and tissue-resident (Res) macrophages (MØ) from naïve mice and monocytes and macrophages 4hrs, 18hrs, 3 and 7 days after the induction of sterile peritonitis with zymosan (2x106 particles per mouse) (see Table S1 for further information). Purity was confirmed as >95% (middle column), except for day 7 Ly-6B+ macrophages, where purity was >90% and the major contaminant was Ly-6B– macrophages. Cytospin preparations were made from the purified cells and representative photomicrographs are shown (right column). The morphology of Ly-6B+ inflammatory (Inf) macrophages is shown elsewhere (8). Arrowheads (day 3 right column) denote the presence of zymosan particles within the macrophages and this was particularly evident in the cells purified from day 3 (19). All data shown is representative of cells pooled from C57BL/6 and purified on 3 completely separate occasions. B. For initial analysis those probesets with an ANOVA P value of 1e-7 (820 probesets) were clustered to identify basic group relationships. Hierarchical clustering was performed on log-transformed median-centered data using correlation as the distance metric and the data were represented as a dendrogram. Heatmap analysis of the same data readily highlighted the relationships shown in the dendrogram. C. Graphical representation of the relationships between all the groups as determined by the Pearson’s r2 values derived by comparison of all probesets between the individual groups. In all cases the 99% confidence intervals for these r2 values were <0.004 of the given value. D. Heatmap analysis of select peritoneal-resident macrophage-restricted transcripts, including the expression profile of 3 distinct Gata6 probesets. The expression of Gata6 was validated by semi-quantitative (sq) PCR. E. Flow-cytometric validation of the peritoneal macrophage-restricted transcriptional profile by selective detection of the protein products of proposed peritoneal macrophage-restricted transcripts on the surface of F4/80high peritoneal macrophages. Data are representative of one of two similar experiments with 5 female 7 week old, C57BL/6 mice. Flow-cytometry plots were gated on CD11b+F4/80+, macrophages and ‘dendritic cell-like’ cells after excluding eosinophils and doublets as previously described (6). The quadrants delineate the F4/80high expression associated with the predominant peritoneal macrophage population. This specificity was also confirmed during peritonitis in the presence of recruited inflammatory macrophages (not shown). F. Quantitative PCR analysis showing selectivity of Gata6 using peritoneal-resident and bone marrow derived macrophages. Data represents the mean±SEM of 3 independent samples per group. G. Quantitative PCR analysis of contemporary flow-cytometrically purified inflammatory recruited (F4/80+CD11b+Tim4–) and peritoneal-resident (F4/80highCD11bhighTim4+) macrophages isolated 48 hours after acute inflammation induced with zymosan (2x106 particles) and compared with peritoneal-resident macrophages from naïve animals. Data represents the mean±SEM of 2 independent samples per group. Abbreviations used in this figure: MØ, macrophage; Res, tissue-resident; Inf, inflammatory; Mo, monocyte.

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Fig. S2 Clustering of probesets by expression during inflammation. Regulated probesets (ANOVA P value <0.001; 8314 probesets) were clustered using Genesis. In all clusters populations are labeled as indicated in the lower right. One cluster of 896 probesets (cluster 15) described a transcriptional profile that was associated with 3 day post-inflammation macrophages (MØ), 7 day post-inflammation Ly-6B– macrophages and peritoneal-resident macrophages. These three populations are highly enriched in peritoneal-resident macrophages and hence cluster 15 represents a peritoneal-resident macrophage-selective transcriptional profile. BM, bone marrow; Mo, monocyte.

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Fig. S3 Validation of inflammation microarray data. Heatmap array data and cycle-restricted semi-quantitative (sq) RT-PCR validation of the expression of select transcripts from gene clusters preferentially expressed at time points throughout the time course of the inflammatory response. B) Table demonstrating detailed protein expression studies conducted by our laboratories showing a direct correlation with the array data. Genes were selected both because they represent individuals within clusters across the course of the inflammatory response and because their protein products have been studied in significant detail. In both (A) and (B) above, transcripts/probesets were selected to be representative of the phenotypes observed (and expected from previous studies) across the inflammatory response including monocyte related (e.g. Ly6c1, Ccr2 and Sell), activation/maturation-dependent (e.g. Ptgs2, Clec4n and Mrc1), general myeloid expressed (e.g. Clec7a and Csf2ra), macrophage maturation (Emr1, Itgam and Alox15), antigen presentation (Ciita) and tissue macrophage-associated (Vsig4 and Cd209b). References: 1.(5); 2.(33); 3.(34); 4.(4); 5.(23); 6.(3); 7.(35); 8.(36); 9.(2); 10.(27); 11.(28).

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Fig. S4 Peritoneal lymphocyte and peripheral blood counts in Gata6-KOmye mice. Quantification of peritoneal and peripheral blood cells demonstrates that myeloid deficiency of Gata6 results in no gross alterations in (A) peritoneal lymphocytes, (B) peripheral erythrocytes, platelets or leukocytes, or (C) the various blood leukocyte subsets. Cells were identified as described Table S2 and (30). Peritoneal data represents the mean±SEM of measurements from Gata6-KOmye mice (n=5♂/5♀) and their WT/Het littermates (n=9♂/7♀). Data were analyzed by two-way ANOVA (Int, Interaction statistic; Gata6, differences due to genotype; Sex, differences due to sex). Blood data represents the mean±SEM of measurements from Gata6-KOmye mice (n=5♂/4♀) and their WT/Het littermates (n=8♂/6♀). Data were pooled from two independent experiments.

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Cre-Myc trCD2 trCD2

12

Fig. S5 In vivo lentiviral modification of peritoneal-resident macrophages and lack of observable Cre-toxicity. A. Schematic representation of a series of lentiviral vectors based upon pHR’SIN-cPPT-SEW that were used in this study. The methods of production are detailed in the Materials and Methods and Table S4. B. Representative flow-cytometric analysis 7 days after in vivo i.p. infection with packaged lentiviral vector shows that highly efficient and selective (up to 90% infection of all peritoneal-resident macrophages (Res MØ) and few other leukocytes) can be readily achieved in vivo. The density plot is representative of many mice used throughout this study. The overlaid contour plot indicates the autofluorescence seen in a representative uninfected mouse. C. Infection of Gata6tm2.1Sad/J mice with lentiviral vector encoding a Myc-tagged Cre-recombinase (Cre-Myc) results in the progressive emergence of an F4/80low peritoneal macrophage phenotype. By day 7 (third panel), two very distinct peritoneal macrophage phenotypes were evident (F4/80highMyc– and F4/80lowMyc+). This did not occur after Cre delivery to wild type (129S6) mice (right panel). Data were compiled from initial experiments with at least 2 mice per time point. D. Co-infection with Cre and Gata6 expression viruses (right panel), resulted in the persistence of the F4/80high phenotype in Cre-Myc+ cells, which is shown graphically by the F4/80highCre-Myc+trCD2+ cells (white, right panel) in comparison to the F4/80lowCre-Myc+ trCD2+ cells seen when control virus was used (magenta, left panel). Data represents at least 3 mice per group from one of three similar experiments. E. Graphical representation of the phenotype conversion shown in (d) above from one of the three experiments. Data represents mean±SEM of 4 mice per group. The prevalence of F4/80highCre+ cells was compared between Gata6 reconstitution (+) and control virus (–) by Student’s t-test with the P value indicated. F. Representative flow-cytometry plot comparing F4/80 expression in Gata6tm2.1Sad/J peritoneal macrophages 7 days after infection with a Gata6-specific shRNA (indicated by expression of the truncated rat CD2 (trCD2) tag (left panel). Quantification from one of two experiments of the impact of Gata6 shRNA on F4/80 expression compared to non-silencing (Non-sil) shRNA (right panel). Data represents mean±SEM of n=3/group. These data (C-F) indicate that the results were not due to Cre-toxicity (15), since: i) it did not occur in WT animals that were similarly treated with Cre (C); ii) co-infection of Gata6tm2.1Sad/J mice with Gata6 and Cre expressing viral vectors prevented it (D, E); and iii) a similar effect could also be achieved by delivery of a Gata6 targeting shRNA (F).

13

A0.0001

0.1

1

0.001

0.01

0.001 10.01 0.1 10 100 1000

P-v

alue

Relative expression

749

107

Peritoneal Res MØ selective (here and Gautier et al. 2012)

Genes >2FC inGata6-KOmye

Genes <2FC in Gata 6-KOmye or ‘not signficantly’

alteredAnk Cxcl13

Aqp9 Edil3C230081A13Rik Ednrb

Cmah Fabp7Egln3 Hgd

F5 Lama3Fgfr1 LbpFlnb Lrg1

Garnl3 Mfsd6Ltbp1 Naip1Rai14 Nedd4Selp Vsig4

Serpinb2 Wnt2Stard13Tgfb2

Vmn2r261110032E23Rik

Up in KO MØDown in KO MØ

n.s. altered

Probes altered by Gata6-KO>2FC

Up>2FC Down

‘Not regulated'

All: 294 396 17758‘Gautier’: 7 49 107

χ2= 549.6, P<0.0001

B

Fig. S6 Derivation of a concise peritoneal macrophage-selective gene list from new and existing data. A. Analysis of Affymetrix MOE430 2.0 probes corresponding with peritoneal macrophage associated genes identified in another study (16), confirmed a significant enrichment (χ2 analysis below) of genes that were significantly 2-fold down-regulated in the absence of Gata6 (blue) compared to up-regulated (brown). B. Comparison of peritoneal-resident macrophage-selective genes identified in this study with those in (A) identifies a core gene profile that in addition to Gata6 is associated with peritoneal-resident macrophages and is selective both within the tissue and between tissues. Approximately 60% of these genes (blue and brown, as indicated) were significantly altered in expression in the absence of Gata6.

14

15

10

5

0

rCD2–rCD2+

Rel

ativ

e tis

sue

rete

ntio

n

Con

trol-t

rCD

2

Gat

a6-tr

CD

2

C

Two-way ANOVAInt: P=0.0055

CD11bF4

/80

Control-trCD2 Gata6-trCD2

CD

45.1

CD45.2F4

/80

F4/8

0trCD2 trCD2

A

B

Donor

Donor cells Donor cells

F4/80high cellsF4/80high cells

53% 95%

D1.0

0.8

0.4

0

F4/8

0 ex

pres

sion

(rela

tive

to R

es M

Ø)

Con

trol-t

rCD

2

Gat

a6-tr

CD

20.6

0.2

P<0.0001

Fig. S7 Enforced Gata6 expression promotes retention of bone marrow-derived macrophages in the peritoneum with an F4/80high phenotype. Bone marrow macrophages from 129S6.CD45.1 congenic mice were derived by 7 days of culture in M-CSF and then infected with lentiviral vectors encoding a self-cleaving Gata6-truncated rat CD2 (trCD2) fusion protein, or control-trCD2. Two days after lentiviral modification, cells were transferred intraperitoneally into naïve 129S6 mice (CD45.2). After a further 3 days, peritoneal cells were harvested and analyzed. A. Representative density plots showing

15

that donor macrophages could be identified amongst the F4/80+CD11b+ cells (indicated in left panel); separated from recipient cells by expression of the CD45 alloantigens (right panel). B. Representative density plots showing the F4/80 phenotype of the lentivirally modified cells (trCD2+) and their unmodified counterparts (trCD2–), when transduced with control-trCD2 (left) or Gata6-trCD2 (right). Gata6-transduction resulted in peritoneal retention of bone marrow-derived cells, which had acquired an F4/80high phenotype not present in the controls. Overlaid contour plots show for comparison the F4/80high phenotype of the endogenous recipient resident peritoneal macrophages. Percentages denote the proportion of transferred cells that are transduced at the time of analysis. C. Graphical representation of the data shown in (A-B) above. Data is expressed as ‘relative tissue retention’, where 1 denotes the mean number of non-transduced cells retained in control-trCD2-transduced bone marrow macrophage receiving mice. Approximately 10-fold more Gata6-transduced cells compared to the control cell types are present in the peritoneal cavity 3 days after adoptive transfer. D. Gata6-transduced bone marrow macrophages exhibit significantly increased F4/80 expression after transfer, which is approaching the levels seen on the recipients peritoneal macrophages (=1 on the relative scale). Data (A-D) represents the mean±SEM of 6 mice pooled from two similar experiments. Data were analyzed for statistically significant differences by Two-way ANOVA (C) and Student’s t-test (D).

16

15

10

0

5

% P

olyp

loid

y

******

P<0.0001

50 µm

50 µm

% P

olyp

loid

y

12

8

4

0

WT KO

***P<0.0001

% P

olyp

loid

y

20

15

5

0

10Two-way ANOVAInt: n.s.F4/80: p<0.0001***Sex: n.s.

F4/80lowF4/80high

Gata6-KOmye

A

C

B

D

Fig. S8 Polyploidy associated with Gata6-deficiency in tissue-resident macrophages. A. Graph showing the quantification of polyploidy in peritoneal macrophages of Gata6-KOmye and WT mice. Data were analyzed as indicated in Fig.4A are represented as mean±SEM and were analyzed by one-way ANOVA (P value as indicated) with Bonferroni post tests (***, P<0.001). Data is derived from one of two independent experiments (KOmye, n=5;‘Het’, n=4; WT, n=3). B. Examples of larger polyploid peritoneal macrophages within Gata6-KOmye mice observed on eosin and methylene blue stained cytospin preparations. Scale bar is as indicated. C. Examination of polyploidy within the same Gata6-KOmye mice between the bulk F4/80low peritoneal macrophages and the rare residual F4/80high WT macrophages. Data symbols represent individual mice with readings from the same mice connected by lines (n=5♂/4♀). Data were pooled from two similar experiments and analyzed by a Two-way ANOVA (with appropriate pairing of data from the same animals). Significant reductions in polyploidy were observed in the F4/80high peritoneal macrophages compared to the F4/80low cells. D. Quantification of polyploidy of pleural macrophages showed a marked increase in the polyploidy of F4/80low pleural macrophages from the Gata6-KOmye when compared to the F4/80high pleural macrophages of the WT mice. Data represents mean±SEM of mice pooled from two independent experiments (WT, n=12; Gata6-KOmye, n=8). Data were analyzed by Student’s t-test. Representative examples of multinucleate cells in the pleural lavage of Gata6-KOmye mice are also shown (right). Scale bar as indicated.

17

high

low

F4/8

0

trCD2

0

50

100

150

h0

50

100

150

P<0.0001

F4/8

0low

F4/8

0high

F4/8

0low

F4/8

0high

P=0.0179

F4/8

0high

A B

Gata6-WTGata6-KOmyeN

ucle

ar G

ata6

(mea

n pi

xel in

tens

ity)

Nuc

lear

Gat

a6(m

ean

pixe

l inte

nsity

)

C

F

DF4

/80

CD73 CD24

high

low

CD9 Signr1

F4/8

0

high

low

high

low

high

low

–––

Gat

a6-K

Om

ye

Gat

a6-W

T

No

cDN

A

Gata6(exon 2-3)

Ywhaz300200100

300200100

Gata6-trCD2Control-trCD2

Lentivirus:

–––

E

–––

CD

73lo

w

CD

73hi

gh

No

cDN

A

Gata6(exon 2-3)

Ywhaz

300200100

300200100

–––

Gata6-KOmye

Fig. S9 F4/80high resident macrophages in Gata6-KOmye express normal Gata6 levels and are phenotypically normal. A-B. Nuclear Gata6 was quantified using Image J and

18

immunofluorescent images of Gata6 expression (see Fig.1) and expressed as mean pixel intensity after selecting the nuclear DAPI staining. A) Symbols denote individual macrophages from a representative Gata6-KOmye mouse. Red lines indicate the mean±SEM of the group. Data were analyzed by t-test. B) Symbols represent individual mice and the F4/80high and F4/80low macrophages from the same Gata6-KOmye mice are linked by lines. Red lines indicate the mean±SEM of the groups. Data were analyzed by paired t-test. A mean of 188±61 macrophages (mean±SEM) was quantified for each mouse. C. RNA was extracted from resident peritoneal macrophages of Gata6-WT and –KO mice, which had been purified by flow-cytometric sorting based on their CD11b+MHCIIlow/– phenotype, and analyzed by RT-PCR for the presence of exon 2 of Gata6. D. By flow-cytometry, F4/80high macrophages in Gata6-KOmye mice exhibit the CD73highCD24highCD9highSignr1high phenotype of WT resident macrophages (compare with Fig.2) distinct from the altered phenotype of the F4/80low Gata6-KOmye macrophages. Data is representative of 4 mice from one of two similar experiments. Plots are pre-gated on F4/80+CD11b+MHCIIlow/– macrophages. E. RNA was extracted from CD73high and CD73low resident peritoneal macrophages from Gata6-KOmye mice by flow-cytometric sorting based on their CD11b+MHCIIlow/– and respective CD73 phenotypes (see (D) above), and analyzed by RT-PCR for the presence of exon 2 of Gata6. F. Intraperitoneal infection of Gata6-KOmye mice with Gata6 expression lentivirus (detected via a self-cleaving truncated rat CD2 (rCD2)) results in the acquisition of an F4/80high phenotype in the transduced cells (density plot). A control rCD2 virus (overlaid contour plot), does not alter F4/80 expression, indicating that Gata6 transduction specifically rescues F4/80high expression on Gata6-KOmye macrophages. Plots (pre-gated on F4/80+CD11b+MHCIIlow/– macrophages) are representative of two experiments with 2-3 mice per group.

19

Eos

inop

hils

(x10

6 )

0.4

0

0.2

0.8

0.6

naive 4 48hours afterzymosan

Neu

troph

ils (x

106 ) 5

3

0

2

4

WTKOmye

naive 4 48hours afterzymosan

Two-way ANOVAInt: n.s.Gata6: n.s.Zymosan: p<0.0002***

1

Two-way ANOVAInt: n.s.Gata6: p=0.0010**Zymosan: p<0.0018**

Fig. S10 Normal inflammatory kinetics to mild zymosan peritonitis. Quantification of cell types present in the peritoneal cavity of naϊve mice and mice 4 and 48 hours after an intraperitoneal injection of zymosan (2×106 particles). The data shows that Gata6-KOmye mice exhibit a relatively normal inflammatory response based on the numbers of neutrophils (left panel), but maintain an elevated number of recruited eosinophils when compared to WT mice (right panel). Data shown is represented as mean±SEM and is pooled from two independent experiments in 7-9 week old female mice (n=5-11/group).

20

0

5

0

5

EGFP–

EGFP+

% S

G2M

shRNA:

0200400600800

100012001400

0

100

200

300

400

500

600

Gat

a6-W

TG

ata6

-KO

mye

Map3k81419208_at Map3k8

Exp

ress

ion

sign

al

0

50

100

150

200

250

300

BM

Mo

4hr M

o18

hr M

oMØ

3 da

y M

Ø7

day

Ly-6

B+M

Ø7

day

Ly-6

B–M

ØR

esid

ent M

Ø

Gata6 1425463_at

Exp

ress

ion

sign

al

20

15

10

0

5

Two-way ANOVAInt: P<0.0001

shRNA:

% K

i67hi

mito

tic

1.5

1.0

0.5

0

Two-way ANOVAInt: P=0.0317

A B

C

BM

Mo

4hr M

o18

hr M

oMØ

3 da

y M

Ø7

day

Ly-6

B+M

Ø7

day

Ly-6

B–M

ØR

esid

ent M

Ø

DeGFP–

eGFP+

Ki6

7

DNA

11%

15%

0.29%

0.56%

E

2515100 5 20

1.0

0.6

0.4

0

0.2

0.8

% K

i67hi

mito

tic

% SG2M

Control shRNAtransduced cellsMap3k8shRNA transduced cells

Fig. S11 In vivo shRNA knockdown of Map3k8 (Tumour progression locus 2, Tpl2) reduces the proliferative response of peritoneal-resident macrophages during inflammation. A. Map3k8 (Tpl2) clusters in our inflammatory monocyte/macrophage study in cluster 10 (see Fig.S2) and exhibits a significantly regulated expression pattern where it is

21

selectively low when Gata6 is highly expressed. Data shown represents the mean±SEM of biological triplicates analyzed by Affymetrix microarray (see Fig.S1). B. Map3k8 was examined in WT and Gata6-KOmye peritoneal macrophages. Gata6-deficient macrophages exhibited a significant (FDR corrected P=0.0216) 3-fold increase in Map3k8 expression. Data shown represents the mean±SEM of biological triplicates analyzed by Affymetrix microarray (see Fig.3). C. To assess the role of Map3k8 in macrophage proliferation in vivo, mice were intraperitoneally infected with shRNA encoding lentiviruses either targeted against Map3k8 or expressing a non-silencing control shRNA (Non. Sil.), using eGFP as a reporter (Fig.S5), 7 days prior to challenge intraperitoneally with zymosan (2x106 particles). Representative density plots (gated on F4/80high macrophages) are shown 48 hours after zymosan challenge, separating the eGFP+ (transduced) and eGFP– resident macrophages, from mice infected with the Map3k8 shRNA. Transgenic mice expressing low levels of eGFP in regulatory T cells driven by the Foxp3 promoter (37) were used in these studies. D. Graphical representation of the data shown in (C) above. Symbols represent individual mice pooled from two independent experiments with the paired data points (connected by lines) representing eGFP+ virally infected cells (containing shRNAs) or eGFP– uninfected cells within the same microenvironment. Resident peritoneal macrophages harbouring shRNA targeted to Map3k8 exhibited a reduced proliferative burst (6) during the recovery from zymosan peritonitis as measured by both the proportion of cells in SG2M phases of cell-cycle (left) and Ki67high4N DNA content stages of mitosis (right)(6). These data suggest that both Map3k8 expression is altered by the function of Gata6 and that Map3k8 expression promotes proliferation in normal resident peritoneal macrophages. Each symbol pair represents a single mouse and the data were assessed for significant differences by Two-way ANOVA analysis. E. Graph showing a correlation between the Ki67high, 4N DNA content (definitive mitotic events) with the calculated SG2M proportions. A significant linear correlation was observed (r2=0.648) and the slope was statistically non-zero (P=0.0002). Data shown represents the data points from the transduced macrophages shown in C-D above.

22

Cell type Abbrev. Purification Criteria Notes

Tissue-resident MØ Res MØ F4/80high,

CD11bhigh

By maintaining a high F4/80 cut-off combined with FSC/SSC and pulse-width gating we ensured minimal contamination with eosinophils or peritoneal dendritic cell-like cells (4, 5).

Bone marrow Mo BM Mo Ly-6Bhigh,

Ly-6G–

Ly-6Bhigh BM Mo were taken as a direct comparison to the inflammatory monocytes selected below (these cells co-express Ly-6C and are the major monocytic population in the BM) (4, 33)

Inflammatory Mo 4 hours

after zymosan 4hr Mo Ly-6Bhigh,

Ly-6G– also F4/80low, CD11b+, Ly-6C+ (4, 5, 34)

Inflammatory Mo/MØ 18 hours after zymosan

18hr Mo/MØ

Ly-6Bhigh/low, Ly-6G–

Also F4/80low/+, CD11b+. We have previously reported this flow-cytometric phenotype as a mixture with characteristics of inflammatory Mo merging into inflammatory MØ with loss of Ly-6B expression (and Ly-6C, not shown) and increases in FSC and surface F4/80. The flow-cytometric analysis is suggestive, but not proof, of an evolution of phenotype (4).

MØ 3 days after zymosan

3 day MØ

F4/80+/high, CD11b+/hi

These MØ isolated during the ‘resolution-phase’ of the acute inflammatory response have merging phenotype from F4/80+,CD11b+ to F4/80high, CD11bhigh (2, 35). We have recently demonstrated that the F4/80high, CD11bhigh cells are Res MØ restored during the resolution phase by local proliferation (6).

MØ 7 days after zymosan

7 day Ly-6B–

MØ

F4/80high, Ly-6B–

7 days after resolving zymosan peritonitis we have observed a predominance of MØ with F4/80high phenotype. These are primarily Ly-6B– and are primarily Res MØ (2, 4, 6).

Subset of MØ 7 days after

zymosan

7 day Ly-6B+

MØ

F4/80high, Ly-6B+

Whilst similar under basic analysis to their Ly-6B– counterparts, these cells have smaller FSC and indications that they may be less mature(4). We have recently demonstrated that these are bone-marrow-derived Inflammatory MØ with increased proliferative potential (8).

Table S1. Summary of purified peritonitis cell types used for Affymetrix transcriptional analysis. These included: i) Ly-6C+Ly-6B+ Inflammatory monocytes (Mo) present 4 hours after the induction of inflammation; ii) Ly-6B+/low ‘Inf monocytes and macrophages (MØ) present 18 hours after the induction of inflammation; iii) all macrophage populations present 3

23

days after induction of inflammation; iv) two subsets of macrophage present 7 days after the induction of inflammation (discriminated by expression of Ly-6B(4), these represent Ly-6B+ bone marrow-derived Inflammatory macrophages (8) and predominant Ly-6B– peritoneal-resident macrophages, recoverable after inflammation (6)). We purified Ly-6C+Ly-6B+ bone marrow (BM) monocytes and peritoneal-resident macrophages from naïve mice as reference cells. This approach ensured analysis of well-defined cells: the 4 and 18 hour time point samples were not mixed with residual recoverable resident macrophages and the other macrophage populations were not contaminated with inflammatory monocytes or MHCIIhigh ‘peritoneal dendritic cell-like’ cells and macrophages (2, 3)(Liao et al., in preparation).

24

Blood Phenotype

Monocytes F4/80+CD11b+SSClow Neutrophils Ly-6G+CD11b+ Eosinophils F4/80+CD11b+SSChigh

B cells CD19+ CD4 T cells CD4+ CD8 T cells CD8+

Peritoneal Cavity Phenotype Res MØ F4/80highCD11bhighTim4high

‘DC-like' cells F4/80intCD11bintMHCIIhighCD19– Eosinophils F4/80+CD11b+SSChigh B1a B cell SSClowCD19+CD23–CD5+IgMhigh B1b B cell SSClowCD19+CD23–CD5–IgMhigh B2 B cell SSClowCD19+CD23+CD5–IgDhigh

CD4 T cell CD4+ CD8 T cell CD8+

Table S2. Summary of surface phenotypes used to identify leukocytes in the blood and peritoneal cavity of wild type mice. MØ, macrophage; Res, resident; DC, dendritic cell.

1

ProbeID ANOVA P value Gene Title Gene Symbol

Fold increase

over ‘monocytes’

Pearson’s r2

1419137_at 0.0000000133 SH3/ankyrin domain gene 3 Shank3 226.18 0.9428

1438227_at 0.0000000080 src homology 2 domain-containing transforming protein E She 149.84 0.9798

1423250_a_at 0.0000017988 transforming growth factor, beta 2 Tgfb2 125.29 0.9639

1455318_at 0.0000000001 T-cell immunoglobulin and mucin domain containing 4 Timd4 125.21 0.9836

1459679_s_at 0.0000051365 myosin IB Myo1b 117.32 0.9132 1438303_at 0.0000022254 transforming growth factor, beta 2 Tgfb2 105.74 0.9344 1451019_at 0.0000024604 cathepsin F Ctsf 104.35 0.9699

1447547_at 0.0000000026 latent transforming growth factor beta binding protein 1 Ltbp1 104.16 0.9659

1450923_at 0.0000000921 transforming growth factor, beta 2 Tgfb2 97.22 0.9774 1450062_a_at 0.0000009874 melanoma antigen, family D, 1 Maged1 94.02 0.9626 1449425_at 0.0000000423 wingless-related MMTV integration site 2 Wnt2 92.27 0.9681 1433553_at 0.0000019114 GTPase activating RANGAP domain-like 3 Garnl3 88.46 0.9698

1416514_a_at 0.0000275210 fascin homolog 1, actin bundling protein (Strongylocentrotus purpuratus) Fscn1 86.87 0.8518

1451651_at 0.0000000830 similar to V-set and immunoglobulin domain containing 4 /// V-set and immunoglobulin

domain containing 4

LOC100044885 /// Vsig4 81.52 0.9743

1424155_at 0.0000056691 fatty acid binding protein 4, adipocyte Fabp4 79.94 0.9202

1448870_at 0.0000000001 latent transforming growth factor beta binding protein 1 Ltbp1 78.30 0.9869

1450922_a_at 0.0000001317 transforming growth factor, beta 2 Tgfb2 73.99 0.9737 1417023_a_at 0.0000007002 fatty acid binding protein 4, adipocyte Fabp4 72.32 0.9809 1455393_at 0.0000003751 Ceruloplasmin Cp 69.31 0.9498

2

1417494_a_at 0.0000001631 Ceruloplasmin Cp 69.18 0.9716 1425809_at 0.0000009086 fatty acid binding protein 4, adipocyte Fabp4 63.31 0.9242

1451789_a_at 0.0000010969 receptor-like tyrosine kinase Ryk 61.07 0.9450 1448859_at 0.0000650457 chemokine (C-X-C motif) ligand 13 Cxcl13 60.74 0.9248 1430637_at 0.0000078542 RIKEN cDNA 2210016H18 gene 2210016H18Rik 60.47 0.9527 1449906_at 0.0000612458 selectin, platelet Selp 60.16 0.9422

1424769_s_at 0.0000000504 caldesmon 1 Cald1 59.35 0.9775 1440156_s_at 0.0000043602 --- --- 58.92 0.9260 1448823_at 0.0000010856 chemokine (C-X-C motif) ligand 12 Cxcl12 58.44 0.9675 1458739_at 0.0000020600 --- --- 58.29 0.9563 1421430_at 0.0000012732 RAD51-like 1 (S. cerevisiae) Rad51l1 57.78 0.9748 1448873_at 0.0000005059 Occluding Ocln 56.41 0.9663 1448816_at 4.57444E-11 prostaglandin I2 (prostacyclin) synthase Ptgis 52.41 0.9953 1448734_at 0.0000028607 Ceruloplasmin Cp 51.72 0.9527

1448269_a_at 0.0000062178 kelch-like 13 (Drosophila) Klhl13 50.97 0.9641 1417495_x_at 0.0000006331 Ceruloplasmin Cp 50.15 0.9627 1426388_s_at 0.0000003708 receptor-like tyrosine kinase Ryk 49.80 0.9747 1460003_at 0.0000004311 expressed sequence AI956758 AI956758 48.35 0.9790 1445421_at 0.0000002488 --- --- 46.90 0.9871

1451263_a_at 0.0000025875 fatty acid binding protein 4, adipocyte Fabp4 44.87 0.9393

1424939_at 0.0000068691 ankyrin repeat, SAM and basic leucine zipper domain containing 1 Asz1 43.81 0.9196

Table S3A. Selection of probesets from the peritoneal-resident macrophage cluster 15. This list is ranked based on fold difference from the mean of the monocytic hierarchical cluster (top 40 probesets are shown). Also shown is the correlation (r2) value of the probeset expression to the mean of cluster 15.

3

GOTERM_BP_FAT Count % Fold

Enrichment P value Benjamini GO:0032101~regulation of response to external stimulus 14 2.18 4.33 0.00001940 0.04143797 GO:0016192~vesicle-mediated transport 33 5.14 2.25 0.00002765 0.02969958 GO:0042592~homeostatic process 38 5.92 2.07 0.00003703 0.02656443 GO:0007155~cell adhesion 37 5.76 2.10 0.00003746 0.02021926 GO:0022610~biological adhesion 37 5.76 2.10 0.00003821 0.01653085 GO:0050727~regulation of inflammatory response 10 1.56 5.58 0.00006363 0.02286480 GO:0007033~vacuole organization 8 1.25 7.49 0.00007319 0.02254670 GO:0006575~cellular amino acid derivative metabolic process 15 2.34 3.39 0.00013774 0.03685719 GO:0016477~cell migration 20 3.12 2.65 0.00020469 0.04839858 GO:0019725~cellular homeostasis 25 3.89 2.32 0.00021147 0.04507976 GO:0009611~response to wounding 25 3.89 2.29 0.00025101 0.04855715 GO:0048584~positive regulation of response to stimulus 17 2.65 2.91 0.00025329 0.04499675 GO:0010324~membrane invagination 17 2.65 2.88 0.00028597 0.04685122 GO:0006897~endocytosis 17 2.65 2.88 0.00028597 0.04685122 GO:0006875~cellular metal ion homeostasis 12 1.87 3.82 0.00029145 0.04439455 GO:0050900~leukocyte migration 8 1.25 5.92 0.00034379 0.04876676

Table S3B. Enrichment of GOTERM_BP_FAT terms in cluster 15 peritoneal-resident macrophage-restricted genes.

4

KEGG_PATHWAY Term Count % Fold

Enrichment P value mmu04142:Lysosome 28 4.36 5.79 8.38668E-14 mmu00531:Glycosaminoglycan degradation 7 1.09 7.50 0.00023159 mmu00511:Other glycan degradation 6 0.93 9.23 0.00031350 mmu00600:Sphingolipid metabolism 8 1.25 4.69 0.00129672 mmu00520:Amino sugar and nucleotide sugar metabolism 8 1.25 4.48 0.00171961 mmu04916:Melanogenesis 10 1.56 2.46 0.01920689 mmu00604:Glycosphingolipid biosynthesis 4 0.62 6.57 0.02070477 mmu04610:Complement and coagulation cascades 8 1.25 2.63 0.03105749 mmu04310:Wnt signaling pathway 12 1.87 1.98 0.03814234 mmu04530:Tight junction 11 1.71 2.01 0.04593380 mmu04670:Leukocyte transendothelial migration 10 1.56 2.07 0.05080710 mmu04640:Hematopoietic cell lineage 8 1.25 2.35 0.05242838 mmu04510:Focal adhesion 14 2.18 1.74 0.05684247 mmu04350:TGF-beta signaling pathway 8 1.25 2.26 0.06120244 mmu05200:Pathways in cancer 20 3.12 1.52 0.06245113 mmu05414:Dilated cardiomyopathy 8 1.25 2.14 0.07771714 mmu04520:Adherens junction 7 1.09 2.27 0.08585107

Table S3C. Enrichment of KEGG pathway terms in cluster 15 peritoneal-resident macrophage-restricted genes.

1

Starting Plasmid Restriction New Plasmid Primer Pairs / Synthetic templates

SXW

Xho I

GATA6 PCR F: GGATCCCGGGCTCGAGCCACCATGTACCAGACCCTCGCC

PCR R: TACCAGGCCTCTCGAGTCAGGCCAGGGCCAGAGCA

GATA6-Myc

PCR F: GGATCCCGGGCTCGAGCCACCATGTACCAGACCCTCGCC PCR R: TACCAGGCCTCTCGAGTTACAGATCTTCTTCAGAAATAAGTTTTTGTTCGGCCAGGGCCAGAGC

Cre-Myc PCR F: GGATCCCGGGCTCGAGCCACCATGTCCAATTTACTGACC

PCR R: TACCAGGCCTCTCGAGTCACAAGTCTTCTTC

Mlu I T2A-rCD2 Intermediate

PCR F: : GCCTGGTACCACGCGTCTCGAGAGCGGCAGCGG

PCR R: TCGCGGCCGCACGCGTTTACCGTTTTTTCCTCTTGCA

T2A-rCD2 Intermediate

Xho I

T2A-rCD2 F: GGATCCCGGGCTCGACCACCATGCTCGAGAGCGGCAGC

R: GCTGCCGCTCTCGAGCATGGTGGTCGAGCCCGGGATCC

T2A-rCD2

Gata6-T2A-rCD2

PCR F: GGATCCCGGGCTCGACCACCATGTACCAGACCCTC

PCR R: CGCTGCCGCTCTCGAGGGCCAGGGCCAGAGC

Cre-rCD2 PCR F: GCTTGATATCGAATTCGATCCGACGCCGCCATCTCT

PCR R: GGGGCTGCAGGAATTCGTTTAAACAAGGCTTTTCTCCAAGGG

SEW/T2A-rCD2 Eco RI U6 (eGFP/U6

T2A-rCD2) PCR F: GCTTGATATCGAATTCGATCCGACGCCGCCATCTCT

PCR R: GGGGCTGCAGGAATTCGTTTAAACAAGGCTTTTCTCCAAGGG

U6 (eGFP/U6 T2A-rCD2) Pme I

ICAM-1 shRNA (eGFP)

F: AGAAAAGCCTTGTTTGACGCTGACTTCATTCTCTATTCTCGAGAATAGAGAATGAAGTCAGCGTCTTTTTCGTTTAAACGAATTCCTGCA R: TGCAGGAATTCGTTTAAACGAAAAAGACGCTGACTTCATTCTCTATTCTCGAGAATAGAGAATGAAGTCAGCGTCAAACAAGGCTTTTCT

Non-Silencing shRNA

(eGFP/T2A-rCD2)

F: AGAAAAGCCTTGTTTGTCTCGCTTGGGCGAGAGTAAGTAGTGAAGCCACAGATGTACTTACTCTCGCCCAAGCGAGACTTTTTCGTTTAAACGAATTCCTGCA R: TGCAGGAATTCGTTTAAACGAAAAAGTCTCGCTTGGGCGAGAGTAAGTACATCTGTGGCTTCACTACTTACTCTCGCCCAAGCGAGACAAACAAGGCTTTTCT

Non-Silencing shRNA-2 (eGFP)

F: AGAAAAGCCTTGTTTGTCCTAAGGTTAAGTCGCCCTCGCTCGAGCGAGGGCGACTTAACCTTAGGACTTTTTGTTTAAACGAATTCCTGCA R: TGCAGGAATTCGTTTAAACAAAAAGTCCTAAGGTTAAGTCGCCCTCGCTCGAGCGAGGGCGACTTAACCTTAGGACAAACAAGGCTTTTCT

Gata6 shRNA (T2A-rCD2)

F: AGAAAAGCCTTGTTTGCCACTACCTTATGGCGTAGAACTCGAGTTCTACGCCATAAGGTAGTGGCTTTTTGTTTAAACGAATTCCTGCA R: TGCAGGAATTCGTTTAAACAAAAAGCCACTACCTTATGGCGTAGAACTCGAGTTCTACGCCATAAGGTAGTGGCAAACAAGGCTTTTCT

Map3k8 shRNA

(eGFP)

F: AGAAAAGCCTTGTTTGCGTGCAAACTGATCCCTATACTCGAGTATAGGGATCAGTTTGCACGCTTTTTGTTTAAACGAATTCCTGCA R: TGCAGGAATTCGTTTAAACAAAAAGCGTGCAAACTGATCCCTATACTCGAGTATAGGGATCAGTTTGCACGCAAACAAGGCTTTTCT

2

Table S4. Lentiviral Vectors. Summary of the construction of recombinant lentiviral vectors detailing original plasmid, restriction site used, the name of the new plasmid and the PCR primers or synthetic inserts used for In-fusion cloning. Starting plasmids were cut with the indicated restriction enzyme. Inserts were produced by either annealing synthetic templates (F/R), or via PCR amplification using primers (PCR F/PCR R). The ‘In-Fusion’ reaction was used to recombine cut vectors and inserts to form chimeric plasmids. All restriction enzymes were from New England Biolabs or Roche.

1

GOTERM_BP_FAT Count % Fold

Enrichment P value Benjamini GO:0034329~cell junction assembly 7 1.36 12.83 1.13E-05 0.02373886 GO:0009611~response to wounding 25 4.85 2.77 1.25E-05 0.01318413 GO:0007044~cell-substrate junction assembly 6 1.17 16.50 1.87E-05 0.01317578 GO:0042127~regulation of cell proliferation 32 6.21 2.29 2.70E-05 0.01422099 GO:0045859~regulation of protein kinase activity 17 3.30 3.52 2.72E-05 0.01148526 GO:0043549~regulation of kinase activity 17 3.30 3.41 4.01E-05 0.01410258 GO:0007155~cell adhesion 32 6.21 2.20 6.01E-05 0.01808602 GO:0051338~regulation of transferase activity 17 3.30 3.29 6.18E-05 0.01627452 GO:0022610~biological adhesion 32 6.21 2.19 6.24E-05 0.01462971 GO:0007507~heart development 18 3.50 3.11 7.14E-05 0.01504914 GO:0034330~cell junction organization 7 1.36 8.42 1.48E-04 0.02826378 GO:0042060~wound healing 12 2.33 4.12 1.53E-04 0.02674057 GO:0008284~positive regulation of cell proliferation 20 3.88 2.71 1.56E-04 0.02511784 GO:0016044~membrane organization 19 3.69 2.69 2.64E-04 0.03927954 GO:0007160~cell-matrix adhesion 8 1.56 6.16 2.82E-04 0.03922184 GO:0043405~regulation of MAP kinase activity 10 1.94 4.58 3.16E-04 0.04106203 GO:0010324~membrane invagination 15 2.91 3.07 3.90E-04 0.04756683 GO:0006897~endocytosis 15 2.91 3.07 3.90E-04 0.04756683

Table S5A. Enrichment of GOTERM_BP_FAT terms associated with probesets significantly altered in expression (>2-fold change) between wild type and Gata6-deficient resident peritoneal macrophages.

2

KEGG_PATHWAY Term Count % Fold

Enrichment P value Benjamini mmu04640:Hematopoietic cell lineage 11 2.14 4.25 2.21E-04 0.029142 mmu04510:Focal adhesion 17 3.30 2.78 3.39E-04 0.022451

Table S5B. Enrichment of KEGG pathway terms associated with probesets significantly altered in expression (>2-fold change) between wild type and Gata6-deficient resident peritoneal macrophages.

1

Peritoneal macrophage specific (Gautier et al., 2012)

Resident macrophage

restricted (Clust 15)

Affymetrix 430 2.0 Probes

FC in Gata6-KO

EmpBayes BH-P value

Serpinb2 YES 1419082_at -6.27 0.002235693 Serpinb8 NO 1422776_at 1.51 0.065436366

NO 1458882_at 1.29 0.015746727 Sell NO 1419480_at 3.43 0.201487075

NO 1419480_at 3.43 0.201487075 Selp YES 1420558_at -9.95 0.001927449

YES 1449906_at -12.72 0.031414093 YES 1440173_x_at -7.56 0.006255059

F5 YES 1418907_at -3.50 0.019384311 YES 1449269_at -4.28 0.043101983

Mfsd6 YES 1424463_at 1.04 0.532934648 Fn1 NO 1426642_at -1.17 0.383680203

NO 1437218_at -2.27 0.028620353 Pam NO 1418908_at -1.35 0.417271843

NO 1447421_at 1.21 0.776089064 Rgs18 NO 1420398_at -2.12 0.056955831

NO 1449856_at -2.51 0.039776348 Prg4 NO 1449824_at -1.26 0.129804363

Tgfb2 YES 1450923_at -3.76 0.010883382 YES 1450922_a_at -4.58 0.020062755 YES 1423250_a_at -4.06 0.010473847 YES 1438303_at -4.69 0.005537398

Fabp7 YES 1450779_at -1.32 0.369334156 Prtn3 NO 1419669_at -1.39 0.725426723 Hal NO 1418645_at 2.44 0.094246957

9130014G24Rik NO 1445639_at -2.05 0.249810303 Arg1 NO 1419549_at 2.10 0.118269173 Lyz1 NO 1436996_x_at 1.19 0.303589673

NO 1439426_x_at 1.88 0.04503016

NO 1450822_at -1.24 0.071643234 Gas7 NO 1417859_at 1.55 0.110266419 Mgl1 NO 1419605_at 2.33 0.045227919

Atp2a3 NO 1421129_a_at -3.73 0.009344189 Slfn1 NO 1418612_at 1.21 0.651282598 Slfn4 NO 1427102_at 1.79 0.026880187 Acaca NO 1427595_at 1.03 0.978856496

NO 1434185_at -1.92 0.028997632 Alox15 NO 1420338_at -2.33 0.027355937

2

Icam2 NO 1448862_at -1.48 0.096148813 Fam20a NO 1433653_at -1.28 0.13176481 Abca6 NO 1453817_at -3.68 0.048199807 Egln3 YES 1418649_at -11.92 0.00599968

YES 1418648_at -5.38 0.01870309 NO 1425918_at -1.16 0.845232733

Cmah YES 1421214_at 1.69 0.087379576 YES 1436039_at 1.84 0.118380258 YES 1428043_a_at 2.01 0.059977737

NO 1440458_at -1.26 0.692264781

NO 1440517_x_at 1.52 0.01870309

NO 1447502_at 6.90 0.039516339 Edil3 YES 1433474_at -1.62 0.166356697

NO 1425622_at -1.24 0.690743306 F13a1 NO 1448929_at 6.40 0.002614878 Naip1 YES 1425298_a_at -1.86 0.026790027 Flnb YES 1426750_at -3.14 0.084738982

NO 1442107_at -3.88 0.033258734

NO 1445534_at -4.56 0.025037927

NO 1458226_at -2.54 0.091901043 Rarb NO 1454906_at -1.53 0.036330697 Ednrb YES 1426314_at 1.31 0.323266249

NO 1423594_a_at 1.05 0.807272056

NO 1437347_at -1.03 0.859957273 Ank YES 1450627_at -2.51 0.007694574

Rai14 YES 1417400_at -2.84 0.011229636 NO 1417401_at -2.26 0.217603339

Itgb7 NO 1418741_at -3.63 0.02702612 Hgd YES 1452986_at -10.21 0.146733725

Retnla NO 1449015_at 2.89 0.032742527 Gbe NO 1420654_a_at -1.42 0.284199281

Ltbp1 YES 1448870_at -17.21 0.005432193 YES 1447547_at -20.79 0.003993917 YES 1419786_at -12.37 0.015997876 NO 1440678_at -5.65 0.021284981

C4b NO 1418021_at -1.50 0.12877106 Lrg1 YES 1417290_at -1.36 0.437418845

Emilin2 NO 1435264_at -1.38 0.189847263 Xdh NO 1451006_at 1.02 0.924129373

Gata6 YES 1443081_at -2.35 0.036807186 YES 1425464_at -1.82 0.057677463 YES 1425463_at -1.01 0.979309647

3

Lama3 YES 1427512_a_at -3.69 0.064713207 Gypc NO 1423878_at 1.15 0.392458946 Klf9 NO 1422264_s_at 1.11 0.676038037

NO 1428288_at -1.09 0.642963641

NO 1428289_at -1.02 0.945868758

NO 1436763_a_at -1.19 0.658733037

NO 1456341_a_at 1.09 0.689291591 Thbs1 NO 1421811_at -3.34 0.023052176

NO 1460302_at -6.55 0.010879221 Lbp YES 1448550_at 1.15 0.833144746

St8sia6 NO 1438566_at 1.12 0.717885964

NO 1456147_at 1.14 0.726998567

NO 1456440_s_at 1.21 0.631319112 Garnl3 YES 1433553_at -24.59 0.030531238

NO 1458891_at -7.92 0.032077621 Sestd1 NO 1429114_at 1.57 0.026956651

NO 1455549_at -1.19 0.445534012 Hdc NO 1451796_s_at -85.98 0.032552539 Cd93 NO 1419589_at -6.05 0.001548345

NO 1441907_s_at -3.77 0.041929286

NO 1449521_at -4.41 0.010473847

NO 1456046_at -5.25 0.001927449 1110032E23Rik YES 1416805_at -7.81 0.00288313

S100a4 NO 1424542_at 1.09 0.834857404 S100a6 NO 1421375_a_at -1.08 0.84642396 Gbp1 NO 1420549_at -6.49 0.004449599 Ecm1 NO 1448613_at -1.73 0.051712926

Slc44a1 NO 1423865_at -1.02 0.966748415

NO 1433645_at -1.53 0.058302441

Padi4 NO 1422760_at 1.21 0.274482365 Car6 NO 1421001_a_at -2.32 0.097242095 Pf4 NO 1448995_at -1.04 0.850281412

Cxcl13 YES 1417851_at -5.27 0.103957444 YES 1448859_at -6.05 0.094194897

Fam20c NO 1417688_at -1.12 0.532436254

NO 1443827_x_at 1.05 0.854401368

NO 1457648_x_at 1.10 0.528239047 Hpse NO 1433930_at 5.16 0.018046675 Ccl24 NO 1450488_at 1.51 0.061175978

Stard13 YES 1452604_at -11.92 0.027015077 Clec4d NO 1420804_s_at 1.00 0.993118787 Wnt2 YES 1449425_at -1.94 0.018046675

4

Clec4e NO 1420330_at -2.45 0.046240292 NO 1420331_at -2.20 0.147385472

Vmn2r26 YES 1421719_at -13.48 0.015517229 Ifitm2 NO 1417460_at 1.27 0.027152006 Pde2a NO 1447707_s_at 1.04 0.676744783

NO 1447708_x_at 1.30 0.067014723

NO 1452202_at -1.14 0.602096888 Apoc2 NO 1418069_at -7.96 0.215892602 Bcam NO 1424791_a_at 1.47 0.120066482

Atp1a3 NO 1427481_a_at 1.45 0.227360936 Saa3 NO 1450826_a_at 1.13 0.554081238

Gprc5b NO 1424613_at 2.19 0.030518198 NO 1451411_at 2.36 0.017464374

Adam8 NO 1416871_at -4.50 0.040667997 Ifitm6 NO 1440865_at 1.03 0.874962906 Fgfr1 YES 1425911_a_at -2.24 0.108923257

YES 1436551_at -2.49 0.036595133 YES 1424050_s_at -2.31 0.023052176

Efnb2 NO 1419638_at -1.99 0.046791887

NO 1419639_at -2.07 0.056377944

NO 1449548_at 1.00 0.998259893 Msr1 NO 1422062_at -1.00 0.985050089

NO 1425434_a_at 1.20 0.490385565

NO 1425435_at 1.19 0.28623758

NO 1448061_at -1.14 0.251492687 Hp NO 1448881_at -6.01 0.01775889

Calml4 NO 1424713_at 1.40 0.156573374 Aldh1a2 NO 1422789_at 1.17 0.461118621 Nedd4 YES 1450431_a_at -1.77 0.221670247

YES 1451109_a_at -1.39 0.212326214 Mst1r NO 1420461_at -5.70 0.054521762 S1pr5 NO 1449365_at -1.72 0.12909727 Zbtb16 NO 1419874_x_at -4.14 0.04722295

NO 1439163_at -3.73 0.064540133 C230081A13Rik YES 1435580_at -2.46 0.025858179

YES 1439104_at -1.98 0.031060745 NO 1442072_at -1.51 0.495678191

Aqp9 YES 1421605_a_at -1.92 0.237850692 YES 1424011_at -4.52 0.019878563

Vsig4 YES 1451651_at -1.70 0.128339823

5

Table S6. Alterations in peritoneal-resident macrophage-selective transcripts caused by Gata6 deficiency. Examination of the genes identified by Gautier et al. (16) as peritoneal macrophage specific, identification of probes in the Affymetrix 430 2.0 Arrays and whether or not these probes were identified in our Res MØ-restricted profile (shaded green). The alteration in mean gene expression between wild type and Gata6-KOmye CD11bhighMHCIIlow/– macrophages is shown along with the empirical Bayesian Benjamini-Hochberg corrected P value corresponding with that probeset (blue indicates significantly down regulated and red indicated significantly upregulated in Gata6-deficient peritoneal macrophages). Gata6 (red shading) is in both profiles and shows only relatively minor alteration most-likely due to the discrete conditional deletion of a single exon (12).

6

No Key network

objects GO Processes Total

nodes Seed nodes

p-value zScore gScore

1 CREB1 positive regulation of biological process (45.7%), regulation of response to stimulus (37.1%), positive regulation of cellular process (41.1%), negative

regulation of cellular process (39.1%), regulation of signaling (31.8%)

166 165 0.00e+00 144.34 144.34

2 c-Myc positive regulation of biological process (59.0%), positive regulation of cellular process (53.3%), multicellular organismal development (59.8%), system

development (54.9%), negative regulation of cellular process (50.0%)

127 126 2.48e-271 125.98 125.98

3 GCR-alpha positive regulation of biological process (65.3%), positive regulation of cellular process (60.2%), regulation of response to stimulus (52.0%), regulation of signal

transduction (43.9%), cellular response to chemical stimulus (43.9%)

101 100 7.37e-214 112.09 112.09

4 ESR1 (nuclear) multicellular organismal development (70.6%), positive regulation of biological process (67.1%), negative regulation of cellular process (61.2%), positive

regulation of cellular process (62.4%), regulation of signal transduction (49.4%)

89 88 1.38e-187 105.07 105.07

5 SP1 positive regulation of biological process (70.2%), positive regulation of cellular process (63.1%), response to wounding (38.1%), single-multicellular organism

process (78.6%), response to organic substance (51.2%)

84 83 1.10e-176 102.00 102.00

6 p53 positive regulation of biological process (65.4%), positive regulation of cellular process (60.5%), negative regulation of cellular process (58.0%), regulation of

cell proliferation (38.3%), positive regulation of macromolecule metabolic process (45.7%)

83 82 1.65e-174 101.38 101.38

7 Oct-3/4 positive regulation of biological process (68.1%), multicellular organismal development (71.0%), organ development (56.5%), developmental process

(72.5%), positive regulation of cellular process (62.3%)

74 73 5.79e-155 95.57 95.57

8 RelA (p65 NF-kB subunit)

immune system process (54.9%), positive regulation of biological process (71.8%), multicellular organismal development (73.2%), positive regulation of cellular process (64.8%), positive regulation of response to stimulus (43.7%)

72 71 1.24e-150 94.24 94.24

9 C/EBPbeta positive regulation of biological process (79.7%), positive regulation of cellular process (75.4%), regulation of cell proliferation (47.8%), positive regulation of

cell proliferation (36.2%), multicellular organismal development (72.5%)

72 71 1.24e-150 94.24 94.24

10 Androgen receptor (AR)

regulation of cell proliferation (43.9%), multicellular organismal development (71.2%), regulation of phosphorylation (36.4%), developmental process

(72.7%), cell differentiation (57.6%)

68 67 5.55e-142 91.50 91.50

11 HIF1A multicellular organismal development (83.6%), developmental process (83.6%), system development (75.4%), positive regulation of biological process (75.4%),

anatomical structure development (75.4%)

64 63 2.39e-133 88.68 88.68

12 c-Jun negative regulation of cellular process (71.4%), positive regulation of biological process (76.2%), developmental process (81.0%), negative regulation of

biological process (71.4%), positive regulation of cellular process (69.8%)

64 63 2.39e-133 88.68 88.68

Table S7. Table showing the top 12 scoring (by the number of pathways) transcriptional networks derived from the differentially regulated genes between Gata6-deficient and wild type macrophages identified by MetacoreTM analysis. The analysis is consistent with a complex transcriptional control of resident macrophage biology.

References and Notes 1. L. C. Davies, S. J. Jenkins, J. E. Allen, P. R. Taylor, Tissue-resident macrophages. Nat.

Immunol. 14, 986–995 (2013). doi:10.1038/ni.2705 Medline

2. V. Dioszeghy, M. Rosas, B. H. Maskrey, C. Colmont, N. Topley, P. Chaitidis, H. Kühn, S. A. Jones, P. R. Taylor, V. B. O’Donnell, 12/15-Lipoxygenase regulates the inflammatory response to bacterial products in vivo. J. Immunol. 181, 6514–6524 (2008). Medline

3. M. Rosas, S. Gordon, P. R. Taylor, Characterisation of the expression and function of the GM-CSF receptor alpha-chain in mice. Eur. J. Immunol. 37, 2518–2528 (2007). doi:10.1002/eji.200636892 Medline

4. M. Rosas, B. Thomas, M. Stacey, S. Gordon, P. R. Taylor, The myeloid 7/4-antigen defines recently generated inflammatory macrophages and is synonymous with Ly-6B. J. Leukoc. Biol. 88, 169–180 (2010). doi:10.1189/jlb.0809548 Medline

5. P. R. Taylor, G. D. Brown, A. B. Geldhof, L. Martinez-Pomares, S. Gordon, Pattern recognition receptors and differentiation antigens define murine myeloid cell heterogeneity ex vivo. Eur. J. Immunol. 33, 2090–2097 (2003). doi:10.1002/eji.200324003 Medline

6. L. C. Davies, M. Rosas, P. J. Smith, D. J. Fraser, S. A. Jones, P. R. Taylor, A quantifiable proliferative burst of tissue macrophages restores homeostatic macrophage populations after acute inflammation. Eur. J. Immunol. 41, 2155–2164 (2011). doi:10.1002/eji.201141817 Medline

7. S. Yona, K. W. Kim, Y. Wolf, A. Mildner, D. Varol, M. Breker, D. Strauss-Ayali, S. Viukov, M. Guilliams, A. Misharin, D. A. Hume, H. Perlman, B. Malissen, E. Zelzer, S. Jung, Fate mapping reveals origins and dynamics of monocytes and tissue macrophages under homeostasis. Immunity 38, 79–91 (2013). doi:10.1016/j.immuni.2012.12.001 Medline

8. L. C. Davies, M. Rosas, S. J. Jenkins, C. T. Liao, M. J. Scurr, F. Brombacher, D. J. Fraser, J. E. Allen, S. A. Jones, P. R. Taylor, Distinct bone marrow-derived and tissue-resident macrophage lineages proliferate at key stages during inflammation. Nat Commun 4, 1886 (2013). doi:10.1038/ncomms2877 Medline

9. M. Koutsourakis, A. Langeveld, R. Patient, R. Beddington, F. Grosveld, The transcription factor GATA6 is essential for early extraembryonic development. Development 126, 723 (1999).

10. A. C. Laverriere, C. MacNeill, C. Mueller, R. E. Poelmann, J. B. Burch, T. Evans, GATA-4/5/6, a subfamily of three transcription factors transcribed in developing heart and gut. J. Biol. Chem. 269, 23177–23184 (1994). Medline

11. R. Zhao, A. J. Watt, J. Li, J. Luebke-Wheeler, E. E. Morrisey, S. A. Duncan, GATA6 is essential for embryonic development of the liver but dispensable for early heart formation. Mol. Cell. Biol. 25, 2622–2631 (2005). doi:10.1128/MCB.25.7.2622-2631.2005 Medline

12. C. P. Sodhi, J. Li, S. A. Duncan, Generation of mice harbouring a conditional loss-of-function allele of Gata6. BMC Dev. Biol. 6, 19 (2006). doi:10.1186/1471-213X-6-19 Medline

13. B. E. Clausen, C. Burkhardt, W. Reith, R. Renkawitz, I. Förster, Conditional gene targeting in macrophages and granulocytes using LysMcre mice. Transgenic Res. 8, 265–277 (1999). doi:10.1023/A:1008942828960 Medline

14. Information on materials and methods is available as supplementary material on Science Online.

15. M. Schmidt-Supprian, K. Rajewsky, Vagaries of conditional gene targeting. Nat. Immunol. 8, 665–668 (2007). doi:10.1038/ni0707-665 Medline

16. E. L. Gautier, T. Shay, J. Miller, M. Greter, C. Jakubzick, S. Ivanov, J. Helft, A. Chow, K. G. Elpek, S. Gordonov, A. R. Mazloom, A. Ma’ayan, W. J. Chua, T. H. Hansen, S. J. Turley, M. Merad, G. J. Randolph, E. L. Gautier, C. Jakubzick, G. J. Randolph, A. J. Best, J. Knell, A. Goldrath, J. Miller, B. Brown, M. Merad, V. Jojic, D. Koller, N. Cohen, P. Brennan, M. Brenner, T. Shay, A. Regev, A. Fletcher, K. Elpek, A. Bellemare-Pelletier, D. Malhotra, S. Turley, R. Jianu, D. Laidlaw, J. Collins, K. Narayan, K. Sylvia, J. Kang, R. Gazit, B. S. Garrison, D. J. Rossi, F. Kim, T. N. Rao, A. Wagers, S. A. Shinton, R. R. Hardy, P. Monach, N. A. Bezman, J. C. Sun, C. C. Kim, L. L. Lanier, T. Heng, T. Kreslavsky, M. Painter, J. Ericson, S. Davis, D. Mathis, C. Benoist; Immunological Genome Consortium, Gene-expression profiles and transcriptional regulatory pathways that underlie the identity and diversity of mouse tissue macrophages. Nat. Immunol. 13, 1118–1128 (2012). doi:10.1038/ni.2419 Medline

17. D. Hashimoto, A. Chow, C. Noizat, P. Teo, M. B. Beasley, M. Leboeuf, C. D. Becker, P. See, J. Price, D. Lucas, M. Greter, A. Mortha, S. W. Boyer, E. C. Forsberg, M. Tanaka, N. van Rooijen, A. García-Sastre, E. R. Stanley, F. Ginhoux, P. S. Frenette, M. Merad, Tissue-resident macrophages self-maintain locally throughout adult life with minimal contribution from circulating monocytes. Immunity 38, 792–804 (2013). doi:10.1016/j.immuni.2013.04.004 Medline

18. C. D. Capo-chichi, K. Q. Cai, J. R. Testa, A. K. Godwin, X. X. Xu, Loss of GATA6 leads to nuclear deformation and aneuploidy in ovarian cancer. Mol. Cell. Biol. 29, 4766–4777 (2009). doi:10.1128/MCB.00087-09 Medline

19. J. U. McDonald, M. Rosas, G. D. Brown, S. A. Jones, P. R. Taylor, Differential dependencies of monocytes and neutrophils on dectin-1, dectin-2 and complement for the recognition of fungal particles in inflammation. PLoS ONE 7, e45781 (2012). doi:10.1371/journal.pone.0045781 Medline

20. M. Rosas, K. Liddiard, M. Kimberg, I. Faro-Trindade, J. U. McDonald, D. L. Williams, G. D. Brown, P. R. Taylor, The induction of inflammation by dectin-1 in vivo is dependent on myeloid cell programming and the progression of phagocytosis. J. Immunol. 181, 3549–3557 (2008). Medline

21. S. C. Mullaly, P. Kubes, Mast cell-expressed complement receptor, not TLR2, is the main detector of zymosan in peritonitis. Eur. J. Immunol. 37, 224–234 (2007). doi:10.1002/eji.200636405 Medline

22. J. C. Pfau, J. C. Schneider, A. J. Archer, J. Sentissi, F. J. Leyva, J. Cramton, Environmental oxygen tension affects phenotype in cultured bone marrow-derived macrophages. Am. J. Physiol. Lung Cell. Mol. Physiol. 286, L354–L362 (2004). doi:10.1152/ajplung.00380.2002 Medline

23. P. R. Taylor, G. D. Brown, D. M. Reid, J. A. Willment, L. Martinez-Pomares, S. Gordon, S. Y. Wong, The beta-glucan receptor, dectin-1, is predominantly expressed on the surface of cells of the monocyte/macrophage and neutrophil lineages. J. Immunol. 169, 3876–3882 (2002). Medline

24. S. Gordon, Z. Cohn, Macrophage-melanocyte heterokaryons. II. The activation of macrophage DNA synthesis. Studies with inhibitors of RNA synthesis. J. Exp. Med. 133, 321–338 (1971). doi:10.1084/jem.133.2.321 Medline

25. G. Dennis Jr., B. T. Sherman, D. A. Hosack, J. Yang, W. Gao, H. C. Lane, R. A. Lempicki, DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 4, P3 (2003). doi:10.1186/gb-2003-4-5-p3 Medline

26. A. Sturn, J. Quackenbush, Z. Trajanoski, Genesis: Cluster analysis of microarray data. Bioinformatics 18, 207–208 (2002). doi:10.1093/bioinformatics/18.1.207 Medline

27. P. R. Taylor, G. D. Brown, J. Herre, D. L. Williams, J. A. Willment, S. Gordon, The role of SIGNR1 and the beta-glucan receptor (dectin-1) in the nonopsonic recognition of yeast by specific macrophages. J. Immunol. 172, 1157–1162 (2004). Medline

28. N. N. Gorgani, J. Q. He, K. J. Katschke Jr., K. Y. Helmy, H. Xi, M. Steffek, P. E. Hass, M. van Lookeren Campagne, Complement receptor of the Ig superfamily enhances complement-mediated phagocytosis in a subpopulation of tissue resident macrophages. J. Immunol. 181, 7902–7908 (2008). Medline

29. Y. Benjamini, Y. Hochberg, Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc., B 57, 289 (1995).

30. P. R. Taylor, D. Heydeck, G. W. Jones, G. Krönke, C. D. Funk, S. Knapper, D. Adams, H. Kühn, V. B. O’Donnell, Development of myeloproliferative disease in 12/15-lipoxygenase deficiency. Blood 119, 6173–6174, author reply 6174–6175 (2012). doi:10.1182/blood-2012-02-410928 Medline

31. C. Demaison, K. Parsley, G. Brouns, M. Scherr, K. Battmer, C. Kinnon, M. Grez, A. J. Thrasher, High-level transduction and gene expression in hematopoietic repopulating cells using a human immunodeficiency virus type 1-based lentiviral vector containing an internal spleen focus forming virus promoter. Hum. Gene Ther. 13, 803–813 (2002). doi:10.1089/10430340252898984 Medline

32. M. Rosas, F. Osorio, M. J. Robinson, L. C. Davies, N. Dierkes, S. A. Jones, C. Reis e Sousa, P. R. Taylor, Hoxb8 conditionally immortalised macrophage lines model inflammatory monocytic cells with important similarity to dendritic cells. Eur. J. Immunol. 41, 356–365 (2011). doi:10.1002/eji.201040962 Medline

33. F. Geissmann, S. Jung, D. R. Littman, Blood monocytes consist of two principal subsets with distinct migratory properties. Immunity 19, 71–82 (2003). doi:10.1016/S1074-7613(03)00174-2 Medline

34. R. B. Henderson, J. A. Hobbs, M. Mathies, N. Hogg, Rapid recruitment of inflammatory monocytes is independent of neutrophil migration. Blood 102, 328–335 (2003). doi:10.1182/blood-2002-10-3228 Medline

35. P. R. Taylor, D. M. Reid, S. E. Heinsbroek, G. D. Brown, S. Gordon, S. Y. Wong, Dectin-2 is predominantly myeloid restricted and exhibits unique activation-dependent expression on maturing inflammatory monocytes elicited in vivo. Eur. J. Immunol. 35, 2163–2174 (2005). doi:10.1002/eji.200425785 Medline

36. L. Martinez-Pomares, D. M. Reid, G. D. Brown, P. R. Taylor, R. J. Stillion, S. A. Linehan, S. Zamze, S. Gordon, S. Y. Wong, Analysis of mannose receptor regulation by IL-4, IL-10, and proteolytic processing using novel monoclonal antibodies. J. Leukoc. Biol. 73, 604–613 (2003). doi:10.1189/jlb.0902450 Medline

37. J. M. Kim, J. P. Rasmussen, A. Y. Rudensky, Regulatory T cells prevent catastrophic autoimmunity throughout the lifespan of mice. Nat. Immunol. 8, 191–197 (2007). doi:10.1038/ni1428 Medline