BASIC RESEARCH www.jasn.org

Single-Cell RNA Sequencing Identifies Candidate Renal Resident Macrophage Gene Expression Signatures across Species

Kurt A. Zimmerman,1 Melissa R. Bentley,1 Jeremie M. Lever ,2 Zhang Li,1 David K. Crossman,3 Cheng Jack Song,1 Shanrun Liu,4 Michael R. Crowley,3 James F. George,5 Michal Mrug,2,6 and Bradley K. Yoder1

1Department of Cell, Developmental, and Integrative Biology, 2Division of Nephrology, Department of Medicine, 3Department of Genetics, 4Department of Biochemistry and Molecular Genetics, and 5Division of Cardiothoracic Surgery, Department of Surgery, University of Alabama at Birmingham, Birmingham, Alabama; and 6Department of Veterans Affairs Medical Center, Birmingham, Alabama

ABSTRACT Background Resident macrophages regulate homeostatic and disease processes in multiple tissues, in- cluding the kidney. Despite having well defined markers to identify these cells in mice, technical limita- tions have prevented identification of a similar cell type across species. The inability to identify resident macrophage populations across species hinders the translation of data obtained from animal model to human patients. Methods As an entry point to determine novel markers that could identify resident macrophages across species, we performed single-cell RNA sequencing (scRNAseq) analysis of all T and B cell–negative CD45+ innate immune cells in mouse, rat, pig, and human kidney tissue. Results We identified genes with enriched expression in mouse renal resident macrophages that were also present in candidate resident macrophage populations across species. Using the scRNAseq data, we defined a novel set of possible cell surface markers (Cd74 and Cd81) for these candidate kidney resident macrophages. We confirmed, using parabiosis and flow cytometry, that these proteins are indeed enriched in mouse resident macrophages. Flow cytometry data also indicated the existence of a defined population of innate immune cells in rat and human kidney tissue that coexpress CD74 and CD81, suggesting the presence of renal resident macrophages in multiple species. Conclusions Based on transcriptional signatures, our data indicate that there is a conserved population of innate immune cells across multiple species that have been defined as resident macrophages in the mouse. Further, we identified potential cell surface markers to allow for future identification and characterization of this candidate resident macrophage population in mouse, rat, and pig translational studies.

J Am Soc Nephrol 30: 767–781, 2019. doi: https://doi.org/10.1681/ASN.2018090931

Following the discoveryof mononuclear phagocytes 1 by Eli Metchnikoff, the innate immune system has Received September 14, 2018. Accepted February 19, 2019. received notoriety as the first line of defense against Published online ahead of print. Publication date available at foreign pathogens. The innate immune system con- www.jasn.org. sists of a complex array of cells, including neutro- phils, natural killer cells (NK cells), innate lymphoid Correspondence: Dr. Kurt A. Zimmerman (MCLM 689) or Dr. Bradley K. Yoder (THT 926A), Department of Cell, Developmental, and cells (ILCs), monocyte-derived macrophages, tissue Integrative Biology, University of Alabama at Birmingham, 1918 resident macrophages, and dendritic cells. University Blvd., Birmingham Al, 35294. Email: [email protected] Two major populations of macrophages are pre- or [email protected] sent within most solid tissues of mice and can be Copyright © 2019 by the American Society of Nephrology

J Am Soc Nephrol 30: 767–781, 2019 ISSN : 1046-6673/3005-767 767 BASIC RESEARCH www.jasn.org classified on the basis of ontological origin and the cell surface Significance Statement markers F4/80 and CD11b.2 Although multiple reports have identified well defined markers of resident macrophages Despite abundant research focused on understanding the impor- across tissues in the mouse, whether these cells are evolution- tance of mouse renal resident macrophages in homeostatic and fi arily conserved in higher mammalian species, including hu- disease settings, these ndings have unknown relevance to higher- order species, including humans, because markers to identify a mans, remains uncertain because of a lack of conservation similar population of cells across species are lacking. This hinders of markers between these species.3 For example, one of the translating data obtained in animal model systems to human pa- markers used to define tissue resident macrophages in mice tients. In this study, the authors used a single-cell RNA sequencing (adgre1, identified by the F4/80 antibody) is not expressed by approach, followed by validation using flow cytometry, to identify macrophage populations in human tissue.4,5 Further, recent novel markers of mouse resident macrophages and show that these markers also identify a population of macrophages in rat, pig, and literature highlights the fundamental importance of resident human kidney tissue. Over all, their findings serve as an entry point to macrophages in maintaining homeostasis and controlling dis- study candidate kidney resident macrophages across species. ease progression.6–10 Therefore, the inability to identify resi- dent macrophage populations across species is a major hurdle preventing translation of data obtained in animal model sys- approximately 2.5 g of kidney tissue containing both the cortex tems to human patients. In these studies, we address this issue and medulla was weighed. The kidney was minced with a sterile by using single-cell RNA sequencing (scRNAseq) to identify a razor blade and digested in 10 ml of RPMI 1640 containing set of genes whose expression is enriched in renal resident 1 mg/ml collagenase type I and 100 U/ml DNase I for 30 minutes macrophages of mice, and show that these genes are also at 37°C, with agitation. expressed in a distinct cluster of innate immune cells in multi- Pig Single-Cell Isolation ple species. On the basis of the scRNAseq data, we identified two A 6-month-old male pig (S. scrofa) was anesthetized with candidate cell surface markers that may define resident macro- combination of tiletamine and xylazine and the kidney was phage populations in mouse, rat, pig, and human kidney tissue. removed without perfusion. The kidney capsule was removed and approximately 2.5 g of kidney tissue containing cortex and medulla was weighed. The kidney was minced with a METHODS sterile razor blade and digested in 10 ml of RPMI 1640 con- taining 1 mg/ml collagenase type I and 100 U/ml DNase I for Animals 30 minutes at 37°C, with agitation. We purchased 8-week-old C57BL/6 male mice from the Jackson Laboratory (Bar Harbor, ME). We bred 3-month-old male Human Single-Cell Isolation Sprague–Dawley rats in house at University of Alabama at Remnant human kidney tissues were collected from surgical Birmingham (UAB). A 6-month-old male, uncastrated pig nephrectomies within 4 hours of resection, deidentified, and (Sus scrofa) was obtained from Synder Farms at 8–10 weeks analyzed according to a protocol approved by the Institutional of age and maintained at UAB. Animals were maintained in Review Board of UAB, as described previously.11 For scRNAseq, Association for Assessment and Accreditation of Laboratory normal kidney tissue was obtained from a 60-year-old white Animal Care International-accredited facilities in accordance male with normal serum creatinine (0.8–1.2 mg/dl) and an with Institutional Animal Care and Use Committee (IACUC) exophytic 3 cm lesion in the upper pole of the kidney. The regulations at UAB (approval numbers 10130 and 21072). validation of markers identified by scRNAseq (Figure 7) was performed on kidney tissues from three adult patients (average Mouse Single-Cell Isolation age 6368 years, two men and one woman, two white and one Eight-week-old male C57BL/6 wild-type mice were anesthe- black). In two cases, normal‐appearing tissue was collected from tized with avertin (2,2,2-tribromoethanol; catalog no. a kidney pole opposite to a well demarcated, relatively small, T48402; Sigma-Aldrich), opened, and perfused with 20 ml peripherally located mass; in one case, relatively unaffected tissue 13 Dulbecco’s-PBS (catalog no. 21–030-CV; Corning). The was collected from a patient with end-stage autosomal dominant kidney capsule was removed, kidneys (approximately 0.15 g) polycystic kidney disease. Remnant tissue was collected and were minced with a sterile razor blade, and digested in 1 ml processed within 4 hours of resection according to a protocol of RPMI 1640 containing 1 mg/ml collagenase type I (Sigma- approved by the Institutional Review Board of UAB. For isolation Aldrich) and 100 U/ml DNase I (Sigma-Aldrich) for 30 minutes of single cells, 2.5 g of tissue containing both the cortex and at 37°C, with agitation. For the 103 Genomics studies, three medulla were minced with a sterile razor blade and digested wild-type male kidneys were combined for sequencing. in 10 ml of RPMI 1640 containing 1 mg/ml collagenase type I and 100 U/ml DNase I for 30 minutes at 37°C, with agitation. Rat Single-Cell Isolation A 3-month-old male Sprague–Dawley rat was anesthe- Single-Cell Isolation and Flow Cytometry tized with carbon dioxide, opened, and perfused with 50 ml After digestion, kidney fragments were passed through a 13 Dulbecco’s-PBS. The kidney capsule was removed and 70-mmmeshfilter (Falcon; BD Biosciences), yielding single-cell

768 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 767–781, 2019 www.jasn.org BASIC RESEARCH suspensions. Cells were centrifuged at 1200 rpm (2203g) for Fluidigm C1 Sequencing 5 minutes at 4°C, resuspended in 5 ml red blood cell lysis buffer Fluidigm single-cell cDNA libraries were prepared according to and incubated at 37°C for 5 minutes. Cells were spun at 1200 rpm standard procedures outlined in Using C1 to Generate Single-Cell (2203g) for 5 minutes, resuspended in 1 ml Dulbecco’s-PBS cDNA Libraries for mRNA Sequencing (https://www.fluidigm.com/ containing 0.04% BSA (catalog no. BP1600–100; Fisher) and binaries/content/documents/fluidigm/resources/c1-mrna%E2% Fc blocking solution (dilution 1:200; catalog no. CUS-HB-197; 80%90seq-pr-100%E2%80%907168/c1-mrna%E2%80%90seq- BioXcell), and incubated for 30 minutes on ice. Cells were spun pr-100%E2%80%907168/fluidigm%3Afile). Briefly, sorted (2203g), washed with 0.04% BSA, and stained for 30 minutes macrophages were resuspended into a final concentration of at room temperature with the following antibodies, diluted 300–350 cells/mlinDulbecco’s-PBS and mixed with Fluidigm according to manufacturers’ recommendations: mouse: PE rat suspension reagent to reach 55% final buoyancy, as determined anti-mouse CD45 (catalog no. 12–0451, 30-F11; eBioscience), by pretesting. Six microliter of mixed cells were loaded into the BV786 hamster anti-mouse CD3e (catalog no. 564379, 145–2C11; Fluidigm C1 IFC plate for mRNA seq (10–17 mm capture site) BD Horizon), and PerCP-Cy5.5 rat anti-mouse B220 (catalog (PN 100–5760; Fluidigm). Captured single cells were confirmed no.561101, RA3–6B2; BD Biosciences); rat: PE anti-rat CD45 via brightfield microscopy. Next, lysis mix, transverse transcrip- (catalog no. 202207, OX-1; Biolegend), APC anti-rat CD3 (cat- tion mix, and preamplification mix were loaded into the C1 plate alog no. 201413, 1F4; Biolegend), and PE/Cy7 anti-rat CD45RA as instructed and single-cell preamplified cDNA libraries were (catalog no. 202315, OX-33; Biolegend); pig: mouse anti-pig generated by the C1 machine using the program “mRNA Seq: CD45 (catalog no. MCA1222GA; Bio-Rad), and Fitc mouse RTand Amp (17713/17723/17733) script.” Illumina sequenc- anti-human CD3e (catalog no. 556611; BD Biosciences), second- ing libraries were prepared from preamplified single-cell cDNA ary antibodies included Cy5 donkey anti-mouse IgG (catalog no. with Nextera XT DNA Sample Preparation Kit (PN FC-131– 715–175–151; Jackson Immunoresearch); and human: Pacific 1096; Illumina), following the sequential steps of tagmentation, Blue anti-human CD45 (catalog no. 304029, HI30; Biolegend), PCR amplification and pooling, and cleaning of the libraries. BV605 anti-human CD3 (catalog no. 317322, OKT3; Biolegend), The final constructed libraries were sequenced by an Illumina and Alexa Fluor 647 anti-human CD19 (catalog no. 302220, Nextseq machine with the minimum reads per cell set at 250,000. HIB19; Biolegend). All species were stained with a Fixable Aqua Dead Cell Stain (catalog no. L34957; Invitrogen). After addition of 103 Genomics primary antibody, cells were spun (2203g), washed in 0.04% BSA, 103 Chromium single-cell libraries were prepared according and resuspended in 1 ml of 0.04% BSA. Samples were taken to the to the standard protocol outlined in the manual. Briefly, sorted flow cytometry core and sorted using a Becton–Dickenson single-cell suspension, 103 barcoded gel beads, and oil were FACSAriaII. loaded into Chromium Single Cell A Chip to capture single cells in nanoliter-scale oil droplets by Chromium Controller Flow Cytometry Validation of Novel Resident and to generate Gel Bead-In-EMulsions (GEMs). Full-length Macrophage Markers cDNA libraries were prepared by incubation of GEMs in a After digestion, a single-cell suspension was generated as thermocycler machine. GEMs containing cDNAs were broken described above, blocked, washed, and stained with the fol- and all single-cell cDNA libraries were pooled together, lowing antibodies according to manufacturers’ recommen- cleaned using DynaBeads MyOne Silane beads (PN 37002D; dations: mouse: PE anti-mouse/rat CD81 (catalog no. 559519; Fisher), and preamplified by PCR to generate sufficient mass BD Biosciences), Fitc anti-mouse/rat/human C1Q (catalog no. for sequencing library construction. Sequencing libraries were MA1–40313; Invitrogen), Fitc anti-mouse CD74 (catalog no. constructed by following the steps cDNA fragmentation, 561941; BD Bioscience), and Alexa-647 conjugated anti- end repair and A-tailing, size selection by SPRIselect beads mouse Apoe (catalog no. NB110–6053155; Novus Biologicals); (PN B23318; Beckman Coulter), adaptor ligation, sample in- rat: PE anti-mouse/rat CD81 (catalog no. 559519), Fitc anti- dex PCR amplification, and repeat SPRIselect beads size selec- mouse/rat/human C1Q (catalog no. MA1–40313), Fitc anti-rat tion. The final constructed single-cell libraries were sequenced Cd74 (catalog no. 21419; Abcam); and human: Fitc anti-mouse/ by Illumina Nextseq machine with total reads per cell targeted, rat/human C1Q (catalog no. MA1–40313), Fitc anti-human for a minimum of 50,000. CD81 (catalog no. 551108; BD Pharmingen), Fitc anti-human CD74 (catalog no. 555540; BD Pharmingen), PE anti- Single-Cell Sequencing Data Processing human CD81 (catalog no. 561957; BD Bioscience), and PE For single cell RNA sequences generated from the Fluidigm anti-human CD74 (catalog no. 326807; Biolegend). After ad- platform, RSEM (version 1.2.31) was used to align the raw dition of primary antibody, cells were spun (2203g), washed in sequence reads obtained using STAR (version 2.5.3a) to the 0.04% BSA, and fixed for 30 minutes in 2% PFA at room tem- reference genome from Gencode.12,13 Transcript abundances perature. After 30 minutes, cells were spun (2203g), washed in represented as tags per million were then loaded into Fluidigm’s Dulbecco’s-PBS, and resuspended in Dulbecco’s-PBS. Samples R package, SINGuLAR (version 3.6.1), for differential gene were run on a Becton–Dickenson LSRII and analyzed using expression analysis. In brief, the function “identifyOutliers” in FlowJo software. SINGuLAR was used to identify outliers and remove them from

J Am Soc Nephrol 30: 767–781, 2019 Renal Resident Macrophages across Species 769 BASIC RESEARCH www.jasn.org downstream analysis. After the removal of outliers, the func- along the suture lines, taking care not to obstruct blood flow tion “autoAnalysis” was used to create the principal component to the distal extremities. Starting rostrally, interrupted sutures analysis (PCA), t-distributed stochastic neighbor embedding were used to attach the skin and muscular layers of the two (tSNE), hierarchical cluster, and correlation analysis of the mice. Working on the ventral side, continuous 3–0 absorbable gene clusters. Vicryl sutures through the skin and muscular layers were used, For 103 Genomics single cells, the 103 Genomics Cellranger followed by the same technique through the dorsal skin software (version 2.1.1), “mkfastq,” was used to create the fastq and muscular layer. Analgesia was maintained on all mice files from the sequencer. After fastq file generation, Cellranger according to IACUC guidelines. Topical antibiotics were applied “count” was used to align the raw sequence reads to the refer- to the surgical site upon completion of the procedure. Animals ence genome using STAR. The “count” software created were provided with water in a plastic dish on the floor of the three data files (barcodes.tsv, genes.tsv, matrix.mtx) from the cage as well as moistened chow and a gel food diet supplement “filtered_gene_bc_matrices” folder that were loaded into the daily for the duration of the experiment. Mouse weights were R package Seurat version 2.3.4,14 which allows for selection and monitored throughout the experiment. filtration of cells on the basis of quality control metrics, data normalization and scaling, and detection of highly variable Statistical Analyses genes. We followed the Seurat vignette (https://satijalab.org/ t test and one-way ANOVAwere used to analyze data. A value seurat/pbmc3k_tutorial.html) to create the Seurat data matrix was considered statistically significant if P,0.05. object.Inbrief,wekeptallgenesexpressedinmorethanthree cells and cells with at least 200 detected genes. Cells with mi- tochondrial gene percentages .5% and unique gene counts RESULTS .2500 or ,200 were discarded. The data were normalized using Seurat’s “NormalizeData” function, which uses a global- scRNAseq Reveals Distinct Clusters of Innate Immune scaling normalization method, LogNormalize, to normalize the Cells in the Mouse Kidney gene expression measurements for each cell to the total gene We sorted populations of immune cells (CD45+)fromthe expression. The result is multiplied by a scale factor of 1e4 and kidney, excluded lymphoid cells, and subjected the remaining the result is log-transformed. Highly variable genes were then cellstoscRNAsequsingthe103 Genomics platform identified using the function “FindVariableGenes” in Seurat. (Figure 1A). For this analysis, we excluded cells from both Genes were placed into 20 bins on the basis of their average the T cell (CD3e in mouse and pig, CD3 in rat and human) expression and removed using 0.0125 low cut-off, 3 high cut-off, andBcelllineage(B220inmouse,CD45RAinrat,CD19in and a z-score cut-off of 0.5. We also regressed out the variation human) using fluorescence-labeled antibodies that were com- arising from library size and percentage of mitochondrial genes mercially available. Using this approach, we analyzed 3013, 3935, using the function “ScaleData” in Seurat. We performed PCA of 4671, and 2868 single cells from mouse, rat, pig, and human kid- the variable genes as input and determined significant principal ney tissue, respectively (Supplemental Table 1). The mean reads components on the basis of the “JackStraw” function in Seurat. per cell were 80,508, 54,456, 61,638, and 112,080 for mouse, rat, The first 20 principal components were selected as input for pig, and human cells, respectively. Unbiased hierarchical clus- tSNE using the functions “FindClusters” and “RunTSNE” in Seurat. tering and heatmap analysis using Seurat shows a unique in- To identify differentially expressed genes (DEGs) in each cell nate immune cell landscape in each species with each color cluster, we used the function “FindAllMarkers” in Seurat on the representing a different cell population (Figure 1, B and C). normalized gene expression data. To understand the conservation of innate immune cells and All relevant data have been deposited in the Gene Expression to identify markers for these cells across species, we began by Omnibus under accession number GSE128993. defining cell populations from mouse scRNAseq data using canonical markers of innate immune cell populations derived Parabiosis from published literature and online databases.16 Lcn2 The parabiosis protocol was modified from the procedure encodes a 25 kD secreted protein that is produced by activated published by Kamran et al.15 Mice were anesthetized using neutrophils.17 Gzma is an effector molecule that is preferen- 1.5%–2.0% vol/vol isoflurane for induction and 1.0%–1.5% tially expressed by NK cells.18 Il7r is expressed by ILCs.19 vol/vol for maintenance. The surgical site, which was the en- Infiltrating (Cd11bhi,F4/80lo)andresident(Cd11blo,F4/80hi) tire flank region from rostral of the cervical spine to rostral of macrophages were originally identified on the basis of differen- the hip joint, as well as the involved extremities distally to the tial expression of CD11b (Itgam) and F4/80 (Adgre1).2 Follow- knee and elbow joints, was shaved. The mice were laid supine up studies indicate that CD64 (Fcgr1)20 and CCR2 (Ccr2)21 are and the site was disinfected with betadine followed by 70% additional markers of resident and infiltrating macrophages, ethanol. Incisions were made through the skin and muscular respectively. Snx22 and Batf3 are recently discovered genes that layer, starting from the elbow joint and extending down the can successfully distinguish dendritic cells from resident macro- flank to the knee joint. Nonabsorbable 3–0 interrupted sutures phages in the kidney.22 Using the indicated genes, we used tSNE were placed around the knee and elbow joints to prevent strain projections and violin plots to identify the following types of

770 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 767–781, 2019 www.jasn.org BASIC RESEARCH

A B 40

25 20

0 B cells 0 T cells 0 1 tSNE_2 tSNE_2 2 FACS 3 -25 4 5 -20 0 6 1 7 2 CD45+ 8 3 9 -50 -40 4 -20-40 0 20 -20 0 5025 tSNE_1 tSNE_1

40

20 20

Sequencing 0 0 tSNE_2 and tSNE_2 analysis -20 0 -20 0 1 1 2 2 3 3 4 4 -50 -25 025 -40 -20 0 20 C tSNE_1 tSNE_1 Mouse Rat

C1qa Blvra C1qb C1qc Mal Cd81 Apoe S100a4 Cd209a Clec10a Eno3 Cfp H2-Oa Napsa H2-DMb2 Gzma Ccl5 Nkg7 Ccl5 Nkg7 AW112010 Lgals1 Gzmm Chil3 Plac8 Gzmk Ms4a4c Ifitm3 Gzma Lyz2 Ear2 C1qc Fabp4 Pglyrp1 C1qa Cebpb Gngt2 C1qb Cd7 Xcl1 Tmem176b Cxcr6 Ccl4 RT1-Db1 Ccl3 Gata3 S100a9 Lztfl1 Ly6a AABR07034362.2 Ltb Phlda1 S100a8 Xcr1 Cxx1a Stfa2 Naaa Ppt1 Lrg1 Cst3 Ly6d Fcnb Cd79a Iglc2 Ifi30 Iglc1 Igkc Vim Retnlg Slpi Ccl2 S100a9 S100a8 AABR07065625.1 G0s2

Pig Human

CST3 GNLY

APOE NKG7

RNF128 CCL5

CXCL8 GZMB

PKIB CD69

HPGD S100A8

TBXAS1 S100A9

ADGRE5 LYZ

ENSSSCG00000030882 VCAN

ENSSSCG00000026653 S100A12

GNLY C1QC

CTSW RGS1

ENSSSCG00000033721 APOE

ENSSSCG00000029596 HLA-DPA1

CCL5 HLA-DPB1

LGALS3 LINC01272

ENSSSCG00000029414 MS4A7

S100A12 IFITM3

ENSSSCG00000033457 LST1

ENSSSCG00000039214 COTL1

MS4A1 CD1C

CD79B FCER1A

ENSSSCG00000025644 LMNA

ENSSSCG00000036224 HLA-DQA1

ENSSSCG00000037775 HLA-DQB1

Figure 1. scRNAseq identifies clusters of cells with unique gene expression patterns in the renal innate immune compartment. (A) Schematic of experimental design. (B) tSNE plot and (C) heatmap of innate immune cells in mouse, rat, pig, and human kidneys. The heatmap depicts the top five DEGs in each cluster of innate immune cells.

J Am Soc Nephrol 30: 767–781, 2019 Renal Resident Macrophages across Species 771 BASIC RESEARCH www.jasn.org innate immune cells in the mouse kidney: neutrophils (Lcn2+, (Figure 4, A–C). Our data indicate that 13 out of the top 20 Cluster 9, Figure 2A), NK cells (Gzma+, Cluster 2, Figure 2B), resident macrophage markers identified using 103 Genomics ILCs (Il7r+, Cluster 6, Figure 2C), infiltrating macrophages (Ccr2+, were also observed in resident macrophages using the Fluidigm Itgam+, Figure 2D), resident macrophages (Adgre1+, Fcgr1+, C1 platform. The number of reads per cell from Fluidigm Cluster 0, Figure 2E), dendritic cells (Snx22+, Batf3+,Clusters1 CI scRNAseq is shown in Supplemental Table 3. and 7, Figure 2F), and unknown (Cluster 5). Additional mark- ers including Plac8, Lyz2, and Cebpb were used to identify in- scRNAseq Reveals the Conservation of the Resident filtrating macrophages as clusters 3 and 4 (Figure 1).23 We also Macrophage Gene Expression Patterns across Species identified a small population of B cells (Cd79a+,Cluster8, Next, we assessed whether similar gene expression patterns Supplemental Figure 1) in our lineage-negative scRNAseq could be found in lineage negative CD45+ innate immune cells data, despite the use of a pan B cell marker (B220).24,25 isolated from rat, pig, and human kidneys. We began by choosing the top DEG used to unambiguously identify resi- Comparative Analysis Identifies Novel Genes Whose dent macrophages in the mouse (C1qc) and looked for the Expression Is Enriched in Infiltrating or Resident presence of this gene in scRNAseq data from each species. Macrophages Remarkably, tSNE projections and violin plots show the pres- Using the markers described above, we manually annotated ence of a unique cluster of cells with enriched expression of clusters of cells in the tSNE plots to reflect known innate im- C1qc in single-cell data from mouse, rat, pig, and human tissue mune cell populations that are present in the mouse kidney (Figure 5A). To test whether the candidate resident macro- (Figure 3A). Our results highlight the presence of distinct phage gene expression pattern exists across species, we clusters of neutrophils, NK cells, ILCs, infiltrating macro- searched for the presence of three other top DEGs that were phages, resident macrophages, and dendritic cells in the enriched in mouse resident macrophages (Cd81, Cd74, Apoe; mouse kidney. In this analysis, infiltrating macrophages Supplemental Table 2) in single-cell data from rat, pig, and were further subdivided into Ly6chi (Ly6c1, Ly6c2)andLy6clo human kidney tissue. tSNE projections and violin plots show (Cebpb, Nr4a1) subpopulations. Similarly, dendritic cells that each gene, including C1qc,isfoundinacommoncell were subdivided into cDC1 (Batf3, Irf8)andcDC2(Sirpa) cluster in each respective species (Figure 5, B–D). These data compartments. These data support recent findings show- indicate that the candidate resident macrophage gene ex- ing that resident macrophages and dendritic cells are unique pression pattern may be conserved in resident macrophages populations in the kidney as they cluster to distinct regions of across species. the tSNE plot.22 To determine if gene expression within other innate immune To identify novel markers of innate immune cells in the cell populations are conserved across species, we repeated this mouse kidney, we used Seurat to identify the top differentially analysis using a top DEG found in each innate immune cell expressed genes (DEGs) that are present in each cluster of cells population in the mouse. The gene that we selected to identify in Figure 3A. This approach identified a list of candidate genes each population of innate immune cells (Supplemental Table 2; whose expression was enriched in each innate immune com- red highlight) was chosen according to the calculated P value and partment in mice and comprised both known and unknown the presence of an orthologous gene in higher-order species. markers (Figure 3B, Supplemental Table 2). Using this unbi- tSNE projections show the presence of a unique cluster of cells ased approach, we were able to identify transcripts uniquely expressing the neutrophil (S100a8) and NK cell (Nkg7)specific expressed in Ly6chi (Chil3, Plac8) and Ly6clo (Fabp4, Ear2) in- marker in single-cell data from rat (Supplemental Figure 3, A filtrating macrophages as well as embryonic-derived resident and B), pig (Supplemental Figure 4, A and B), and human (C1qc, Cd81) macrophages (Figure 3C). (Supplemental Figure 5, A and B) kidney tissue. In contrast, the DEG used to identify Ly6chi (Irf7)andLy6clo (Cebpb) Fluidigm C1 scRNAseq of Infiltrating and Resident infiltrating macrophages and cDC1 (Naaa)andcDC2 Macrophages Using Conventional Flow Sorting (Clec10a) dendritic cells in mice could not distinguish be- Approaches (CD11b and F4/80) Confirms 103 tween these subtypes in rat (Supplemental Figure 3, C–E), Genomics Data pig (Supplemental Figure 4, C–E), or human kidney tissue To further validate the novel infiltrating and resident macro- (Supplemental Figure 5, C–E). phage markers identified by 103 Genomics, we used FACS to On the basis of gene expression profiles, additional DEGs to sort infiltrating (CD11bhi F4/80lo)andresident(CD11blo F4/80hi) identify each cell type (Supplemental Table 2), and other com- macrophage populations according to conventional markers mon lineage defining markers reported in the literature (CD14 (Supplemental Figure 2) and performed scRNAseq using for infiltrating macrophages in humans), we manually anno- Fluidigm C1 technology. PCA plots, violin plots, and heatmap tated clusters of cells into neutrophils, NK cells, infiltrating analysis of the C1 data show that infiltrating and resident macrophages, resident macrophages, and dendritic cells in macrophages express a unique gene signature and that each species (Figure 6A). In the rat, pig, and human, we de- several of the top DEGs between infiltrating and resident fined infiltrating macrophages as the cluster of cells that was (C1qa, Cd81, Apoe) macrophages match the 103 Genomics data negative for the neutrophil marker S100a8 and had enriched

772 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 767–781, 2019 www.jasn.org BASIC RESEARCH

ABCNeutrophils NK Cells ILCs

Lcn2 Gzma II7r 25 25 25

0 0 0 tSNE_2 tSNE_2 tSNE_2

-25 -25 -25 3 3 5 4 2 3 2 2 1 1 1 0 -50 0 -50 -50 0 -40 -200 20 -40 -200 20 -40 -200 20 tSNE_1 tSNE_1 tSNE_1 Lcn2 Gzma II7r 6 3 3 4 2 2

2 1 1

0 0 0 Normalized Expression

0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9

DEFInf. MΦ Res. MΦ Dendritic Cells Itgam Adgre1 Snx22 25 25 25

0 0 0 tSNE_2 tSNE_2 tSNE_2 -25 -25 -25 2.5 3 2.0 1.5 1.5 2 1.0 1 1.0 0.5 0.5 0 -50 0.0 -50 -50 0.0 -40 -200 20 -40 -200 20 -40 -200 20 tSNE_1 tSNE_1 tSNE_1

Ccr2 Fcgr1 Batf3 25 25 25

0 0 0 tSNE_2 tSNE_2 tSNE_2 -25 -25 -25 3 3 2.5 2 2 2.0 1.5 1 1 1.0 0 0.5 -50 0 -50 -50 0.0 -40 -200 20 -40 -200 20 -40 -200 20 tSNE_1 tSNE_1 tSNE_1

Itgam Adgre1 2.0 Snx22 3 2 1.5

2 1.0 1 1 0.5

0 0 0.0 Normalized Expression 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9

Ccr2 Fcgr1 Batf3 3 3 2 2 2

1 1 1

0 0 0

Normalized Expression 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9

Figure 2. Canonical markers can be used to identify distinct clusters of innate immune cells in the mouse kidney. tSNE projections and accompanying violin plots depicting genes used to identify (A) neutrophils (Lcn2), (B) NK cells (Gzma), (C) ILCs (Il7r), (D) infiltrating macrophages (Itgam, Ccr2), (E) resident macrophages (Adgre1, Cd64), and (F) dendritic cells (Snx22, Batf3).

J Am Soc Nephrol 30: 767–781, 2019 Renal Resident Macrophages across Species 773 BASIC RESEARCH www.jasn.org

C1qa A B C1qb C1qc C181 Apoe Cd209a Clec10a Cfp 25 H2-Oa H2-DMb2 Gzma Nkg7 Ccl5 AW112010 Lgals1 Chil3 Plac8 Ms4a4c Ifitm3 Lyz2 Ear2 0 Fabp4 Pglyrp1 Cebpb Gngt2 Cd7 Xcl1 tSNE_2 Cxcr6 Ccl4 Ccl3 Gata3 Lztfl1 Ly6a Ltb Phlda1 -25 Xcr1 Cxx1a Naaa Ppt1 Cst3 Ly6d Cd79a Iglc2 Iglc1 Igkc Retnlg Slpi S100a9 -50 S100a8 G0s2 -40 -20 0 20 tSNE_1

C Ly6chi Inf. MΦ Ly6clo Inf. MФ Chil3 Plac8 Fabp4 Ear2 25 25 25 25

0 0 0 0 tSNE_2 tSNE_2 tSNE_2 tSNE_2 -25 -25 -25 -25 4 5 3 3 3 4 2 3 2 2 1 2 1 1 1 0 0 -50 -50 0 -50 0 -50 -40 -20 0 20 -40 -20 0 20 -40 -20 0 20 -40 -20 0 20 tSNE_1 tSNE_1 tSNE_1 tSNE_1 Chil3 Plac8 Fabp4 Ear2 5 4 4 3 3 3 3 2 2 2 2 1 1 1 1 Normalized Expression 0 0 0 0

Resident MФ C1qc Cd81 Resident MΦ 25 25 cDC2 DCs NK cells hi Φ 0 0 Ly6c Inf. M Ly6clo Inf. MΦ tSNE_2 tSNE_2 Unknown -25 -25 5 4 4 ILCs 3 3 2 2 cDC1 DCs 1 1 -50 0 -50 0 B cells -40 -20 0 20 -40 -20 0 20 tSNE_1 tSNE_1 Neutrophils C1qc Cd81 5 4 4

3 3

2 2

1 1 Normalized Expression 0 0

Figure 3. scRNAseq can be used to identify novel markers of innate immune cells in the mouse kidney. (A) Single cells from the mouse kidney were manually annotated according to expression of the canonical genes identified in Figure 2. (B) Heatmap identifying novel gene expression signatures in each innate immune compartment. A more detailed list of genes is included in Supplemental Table 2. (C) tSNE and violin plots depicting novel genes used to identify Ly6chi infiltrating macrophages (Chil3, Plac8), Ly6clo infiltrating macrophages (Fabp4, Ear2), and resident macrophages (C1qc, Cd81).

774 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 767–781, 2019 www.jasn.org BASIC RESEARCH

A PCA score plot B C1qb Cd81 C1qc C1qa AY036118 Cd72 Adgre1 Ms4a7 Lilra5 S100a6 20 15 15 Inf. MΦ 10 10 5 5 Φ 0 0 Res. M Apoe Hexb Lars2 Cdk6 Crip1 C3ar1 lfitm6 Plac8 S100a11 Vim 15 15 10 10 5 5 0 0 Maf Adap2 Gatm Cxcl16 Aft3 Napsa Ahnak Tmsb10 Casm1 Sdc4 15 15 10 10 10 5 5 0 0 Axl Pim1 S100a4 St3gal6 Adap2os Lcp1 Lsp1 Prdx5 Stab1 Fyb 15 15 10 10 5 5 0 0 Tmcc3 Slamf9 Plaur Notch2 Marcks Cx3cr1 Dusp3 Nupr1 Sub1 Nr4a1 15 15 0 10 10 5 5 0 0 Cd209a Kdm6b Sik1 Rab7b Cdkn1b Lgmn mt-Rnr1 Mrc1 Dnajc8 Gpr65

PC2 15 15 10 10 5 5 Expression (log2) 0 0 Creb5 Tgfbr1 Siglece Ctsc Gm26473 Ppp1r15a Btg1 Hpgds S100a10 Gpx1 15 15 10 10 -10 5 5 0 0 Scamp2 Arrb2 Srgn Rps10 Cd63 Cttnbp2nl BC035044 Pdcd4 Zfhx3 Selenop 15 15 10 10 5 5 0 0 Ear2Hnmpa1 Fh1 Oas2 Rgs10 Slco2b1 Adgre4 C5ar2 Btg2 Ccnd3 15 15 10 10 -20 5 5 0 0 SmpdI3a Scimp Ccl12 Gm20659 Ube2n-ps1 MUSG0000011 Slc9a9 Gusb Lgals3bp Son 15 15 10 10 5 5 0 0 Inf. MΦ Res. MΦ -30 -20 -10 0 10 20 30 PC1

C Inf. MΦ Res. MΦ

Apoe Fyb Adgre1 Ms4a7 Lgmn St3gal6 mt-Rnr1 Lep1 Lers2 Son Hexb Cdk6 Stab1 Cx3cr1 C3ar1 Scamp2 Oas2 Axl Gm26473 C5ar2 Gatm Scimp Selenop Lgals3bp Marcks Gusb Tmcc3 Slco2b1 Arrb2 Cd63 Hpgds ENSMUSG000 Clqb Cl81 Clqa C1qc AY036118 Cd72 Lilra5 Cxcl16 Sdc4 Cadm1 Maf Ccl12 Adap2 Adap2os Cttnbp2nl Gpr65 Slamf9 Rgs10 Ctsc Mrc1 Creb5 Zfhx3 Siglece Rab7b Tgfbr1 Slc9a9 Crip1 S100a11 Tmsb10 Hnmpa1 Napsa S100a4 Gpx1 Notch2 Vim Ahnak S100a6 Sub1 Lsp1 Srgn Cd209a S100a10 Fh1 BCO35044 Rps10 Ube2n-ps1 Ccnd3 Btg1 Pim1 Btg2 Cdkn1b 1fitm6 Kdm6b Nr4a1 Plaur Dusp3 Gm20659 Smpdl3a Atf3 Ppp1r15a Prdx5 Plac8 Adgre4 Sik1 Nupr1 Dnajc8 Ear2 Pdcd4

Global Z score

-2 -1 0 1 2

Figure 4. Fluidigm CI scRNAseq confirms several of the top DEGs in mouse resident macrophages. Mouse resident macrophages were flow-sorted using the canonical CD11b and F4/80 markers and RNAseq was performed using the Fluidigm CI platform. (A) PCA plot, (B) violin plot, and (C) heatmap identifying the top 100 DEGs between infiltrating and resident macrophages using Fluidigm C1 scRNAseq. expression of both the Ly6chi (Irf7) and Ly6clo (Cebpb) mouse tissue using this approach, despite recently published litera- infiltrating macrophage markers. Dendritic cells in the rat and ture identifying ILC2s in human kidney tissue.26 Therefore, we human were identified using Clec10a; however, the ortholog grouped clusters of cells into broad immune cell subtypes (i.e., of this gene is not present in pigs, thereby precluding us from infiltrating macrophage, dendritic cells) rather than subtypes, identifying dendritic cells in this species. Further, we were also in rat, pig, and human tissue. Of note, many of the canonical unable to identify ILCs (Cxcr6) in rat, pig, or human kidney markers used to identify macrophages in human samples (Cd68,

J Am Soc Nephrol 30: 767–781, 2019 Renal Resident Macrophages across Species 775 BASIC RESEARCH www.jasn.org

A 40 40 C1qc C1qc C1QC C1QC 25 20 20 20 0 0 0 0 tSNE_2 tSNE_2 tSNE_2 tSNE_2

-25 5 5 4 4 4 -20 4 3 3 -20 -20 3 3 2 2 2 2 1 1 1 1 -50 0 -40 0 0 0 -40 -20 0 20 -25 0 25 50 -25-50 0 25 -20-40 0 20 tSNE_1 tSNE_1 tSNE_1 tSNE_1

5 C1QC 4 C1QC C1qc 4 C1qc 4 4 3 3 3 2 2 2 2 1 1 1 Expression Normalized 0 0 0 0 0 1234 0 1234 0 1234

B 40 40 Cd81 Cd81 CD81 CD81 25 20 20 20 0 0 0 0 tSNE_2 tSNE_2 tSNE_2 tSNE_2 -25 4 3 -20 4 3 3 -20 -20 3 2 2 2 2 1 1 1 1 0 -50 -40 0 0 0 -40 -20 0 20 -25 0 25 50 -25-50 0 25 -20-40 0 20 tSNE_1 tSNE_1 tSNE_1 tSNE_1 5 Cd81 5 Cd81 CD81 3 CD81 4 3 4 3 2 3 2 2 2 1 1 1 1 Expression Normalized 0 0 0 0 0 1234 0 1234 0 1234 C Cd74 40 Cd7440 CD74 CD74 25 20 20 20 0 0 0 0 tSNE_2 tSNE_2 tSNE_2 -25 tSNE_2 6 6 -20 6 -20 6 4 -20 4 4 4 2 2 2 2 -50 0 -40 0 0 0 -40 -20 0 20 -25 0 25 50 -25-50 0 25 -20-40 0 20 tSNE_1 tSNE_1 tSNE_1 tSNE_1 8 Cd74 Cd74 CD74 CD74 6 6 6 6 4 4 4 4 2 2 2 2 Expression Normalized 0 0 0 0 0 1234 0 1234 0 1234

D Apoe 40 Apoe 40 APOE APOE 25 20 20 20 0 0 0 0 tSNE_2 tSNE_2 tSNE_2 -25 tSNE_2 6 5 5 4 -20 4 4 -20 -20 3 4 3 3 2 2 2 2 1 1 1 0 -50 0 -40 0 0 -40 -20 0 20 -25 0 25 50 -25-50 0 25 -20-40 0 20 tSNE_1 tSNE_1 tSNE_1 tSNE_1 Apoe Apoe APOE APOE 6 4 4 4 4 3 2 2 2 2 1 Expression Normalized 0 0 0 0 0 1234 0 1234 0 1234

Figure 5. scRNAseq data identifies a unique cluster of cells in multiple species that share the same gene expression pattern as mouse resident macrophages. (A–D) tSNE and violin plots showing the top DEGs (C1qc, Cd81, Cd74, Apoe) that were used to identify candidate resident macrophages in scRNAseq data from mouse, rat, pig, and human kidneys.

776 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 767–781, 2019 www.jasn.org BASIC RESEARCH

A 40

Resident MΦ 25 cDC2 DCs Φ 20 Infiltrating M NK cells NK cells hi Φ Ly6c Inf. M Resident MΦ Ly6clo Inf. MΦ 0 Neutrophils Unknown 0 Dendritic cells ILCs tSNE_2 tSNE_2 cDC1 DCs B cells -25 Neutrophils -20

-50 -40 -40 -20 0 20 -25 0 25 50 tSNE_1 tSNE_1

40

Infiltrating MΦ 20 Infiltrating MФ 20 NK cells NK cells Resident MΦ Resident MФ Neutrophils Neutrophils Unknown 0 Dendritic cells 0 tSNE_2 tSNE_2

-20 -20

-50 -250 25 -40-25 0 20 tSNE_1 tSNE_1 B CD68 CD163 CD14 FCGR3A

20 20 20 20

0 0 0 0 tSNE_2 tSNE_2 tSNE_2 tSNE_2

3 -20 3 -20 3 -20 3 -20 2 2 2 2 1 1 1 1 0 0 0 0 -40 -20 0 20 -40 -20 0 20 -40 -20 0 20 -40 -20 0 20 tSNE_1 tSNE_1 tSNE_1 tSNE_1

CD68 CD163 CD14 FCGR3A

3 4 4 3 3 3 2 2 2 2 1 1 1 1

Normalized Expression 0 0 0 0

Figure 6. scRNAseq identifies distinct renal innate immune cells. (A) tSNE plot of manually annotated mouse, rat, pig, and human innate immune compartments. (B) tSNE and violin plots showing expression of commonly used human macrophage markers (CD68, CD163, CD14, FCGR3A) in scRNAseq data from human kidney tissue.

Cd163, Cd14, Fcgr3a) were not specific to human renal macro- Novel Resident Macrophage Markers Identified by phage populations and could not separate human macrophages 103 Genomics Are Present at the Protein Level in a into infiltrating or resident macrophages (Figure 6B). Gene Population of Cells in Mouse, Rat, and Human expression patterns from 103 Genomics observed in human Kidney Tissue tissue were further confirmed using Fluidigm C1 technology We used our scRNAseq data to identify novel markers of (Supplemental Figure 6). mouse resident macrophages that may be present on candidate

J Am Soc Nephrol 30: 767–781, 2019 Renal Resident Macrophages across Species 777 BASIC RESEARCH www.jasn.org resident macrophages across species. Toconfirm that the novel is 2%–6%, similar to the percent chimerism observed using markers we identified were enriched in mouse renal resident canonical markers and in agreement with previous reports macrophages, we sorted single cells obtained from wild-type (Figure 8).20,28 In contrast, we observe 40%, 25%, 15%, and mouse kidneys and looked for the presence of our novel res- 25% chimerism in T/B cells, infiltrating macrophages, neu- ident macrophage markers (C1q, CD81, CD74, Apoe) in res- trophils, and NK cells, respectively. The level of chimerism ident macrophages that were gated based on the canonical is significantly higher in these populations compared with approach (CD11b, F4/80). As a control, we also analyzed ex- resident macrophages. pressionofthesemarkersininfiltrating macrophages.Analysis The low level of chimerism that we observe in neutrophils is of flow cytometry data shows that the number and mean likely due to the difficulty that these cells have in migrating fluorescence intensity of cells expressing C1q, CD81, and across the anastomotic vessels and their short lifespan.29 Anal- CD74 is enhanced in resident macrophages (CD11blo F4/80hi) ysis of percentage of chimerism of neutrophils in the blood compared with infiltrating macrophages (CD11bhi F4/80lo) confirms this idea and suggests that neutrophils in the kidney (Figure 7, A and B). Although the percentage of resident are fully exchanged with the peripheral blood (i.e., neutrophil macrophages expressing Apoe was slightly higher than the chimerism is approximately 15% in both the blood and kid- percentage of infiltrating macrophages expressing Apoe, the ney; Supplemental Figure 8). The level of chimerism observed mean fluorescence intensity (x-axis) was similar between in renal immune cell populations 8 weeks after parabiosis sur- the two groups, suggesting that it is not a good marker to gery in our study is similar to previously published studies in distinguish the two populations. Therefore, this marker was the kidney.28,30 Overall, our data validate that the population excluded in analysis of macrophage populations in higher- of cells we identify as candidate resident macrophages using order species. our novel markers are minimally replaced by cells from the On the basis of these data, we created a novel gating strategy peripheral blood in the mouse. to test whether CD74 and CD81 were able to identify resident macrophages in a mouse kidney (Supplemental Figure 7). These markers were chosen on the basis of antibody availabil- DISCUSSION ity and potential cell surface localization. In mice, the resident macrophages identified using the novel approach are almost Our findings shed light on the composition of the innate im- exclusively found in the resident macrophage gate using mune system in the kidney across multiple mammalian species CD11b and F4/80 (Supplemental Figure 7). We also identified using an unbiased lineage negative scRNAseq approach. The a population of CD74/CD81 double positive cells in kidney goal of this scRNAseq study was to determine a list of novel tissue from rat and human samples (Figure 7C, red circles). In candidate genes that were uniquely expressed in mouse resi- addition, we compared protein expression of C1q, CD81, and dent macrophages. Using this list of candidate genes, we CD74 in candidate resident macrophages (red) or nonresi- identified a unique cluster of cells in rat, pig, and human kidney dent (blue) macrophages identified using the Cd81 antibody. tissue that had enrichment of several of the same genes that Our data indicate that C1q, CD81, and CD74 protein expres- were identified in mouse resident macrophages. Further, we sion is enriched in CD81+ cells from mouse and rat tissue were able to use this list of genes to identify potential cell sur- (Figure 7, D and E). Of interest, although CD74 and CD81 face markers that could identify mouse resident macro- protein expression was enriched in human CD81+ cells, we phages and may be used to identify and characterize resident did not observe a similar enrichment C1q at the protein level macrophages in other species. in these cells (Figure 7, D and E), which may reflect the limited One of the key markers resulting from this study was number of patients analyzed or their disease state. Collec- C1q, whose expression was enriched at the RNA level in the tively, these data indicate that CD74 and CD81 can be used candidate resident macrophage populations across species. In- to identify a population of candidate resident macro- triguingly, scRNAseq data from other groups demonstrate the phages across multiple species, including mouse, rat, and presence of a unique cluster of cells that express C1q in mouse16 human tissue. and human31 kidney tissue. Park et al.16 performed scRNAseq of the mouse kidney and identified a distinct cluster of cells, Resident Macrophages Identified Using the Novel which they referred to as macrophages, that had enriched ex- Markers Have Minimal Exchange with the pression of C1qa and C1qb and comprised approximately 0.5% Peripheral Blood of total cells. Further, studies by Wu et al.31 identified a distinct To establish that the candidate resident macrophages iden- cluster of cells, which the authors referred to as monocytes, that tified using our novel approach demonstrate a lack of were isolated from human kidney allograft biopsy samples that exchange with the peripheral blood, a defining feature of had enriched expression of C1qa, C1qb, and C1qc. On the basis tissue resident macrophages,27 we applied the parabiosis of our data, we propose that the population of cells with en- model in CD45 congenic mice (CD45.2 and CD45.1). riched expression of C1q genes identified in each study is likely Our data indicate that the percent chimerism of candidate resident macrophages. Although C1q expression was enriched resident macrophages identified using our novel markers in a cluster of cells across species at the RNA level, we did not

778 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 767–781, 2019 www.jasn.org BASIC RESEARCH

A Φ Φ B FMO Res. M Inf. M **** C1q CD81 CD74 Apoe **** **** 15 100 **** 5 Inf 10 10 50 15 4 8.0 40 10 10 10 6.0 30 103 50 4.0 20 5.0 Cell number CD11b 5.0 0 Res. % of parent 2.0 10 3 -10 0 0 0 0 0 4 4 5 3 3 4 5 4 5 3 3 4 5 C1Q+ CD81+ CD74+ Apoe+ 3 3 4 5 -10 010 10 -10 010 10 10 0 10 10 -10 0 10 10 10 -10 010 10 10 Res. Inf. Res. Inf. Res. Inf. Res. Inf. F4/80 C1q CD81 CD74 Apoe

C D C1q CD81 CD74

5 50 25 10 60 40 20 104 40 30 15 20 10 0 20 10 5.0 0 0 0 3 0-10 103 104 105 010104 105 01104 5 -103 0 103 104 05

105 150 60 80 104 100 60 40

103 40 CD74 50 20 0 20 Cell number -103 0 0 0 3 3 4 5 -10 0 10 10 10 -103 0 103 104 105 3 0-10 103 104 105 3 0-10 103 104 105

105 12 10 20 4 9.0 8.0 10 15 6.0 3 6.0 10 10 4.0 0 3.0 2.0 5.0 -103 0 0 0 3 3 4 5 -10 0 10 10 10 -103 0 103 104 105 -103 0 103 104 105 -103 0 103 104 105

CD81 Expression

E Mouse Rat Human **** **** **** 100 100 **** 150 80 80 * 100 60 60 50 40 40 % of parent % of parent 20 20 % of parent 0

0 0 -50 C1Q CD74 C1Q CD74 C1Q CD74

CD81+ Residents CD81- Non-Residents

Figure 7. Genes identified by scRNAseq are enriched in mouse resident macrophages at the protein level. (A) Representative his- tograms depicting C1q, CD81, CD74, and Apoe expression in mouse infiltrating and resident macrophages that were gated on CD11b and F/480 (Supplemental Figure 2). FMO, fluorescence minus one antibody of interest; Inf., Infiltrating macrophage; Res., resident macrophage. (B) Quantification of the percentage of resident and infiltrating macrophages that express each marker. Data are shown as mean6SEM; ****P,0.001. (C) Representative flow cytometry plots showing expression of CD81 and CD74 in innate immune cells from mouse, rat, and human kidney tissue. (D) Representative histograms depicting protein expression of C1q, CD81, and CD74 in can- didate resident (red) and nonresident macrophages (blue) identified using the CD81 antibody. (E) Quantification of the percentage of 2 CD81+ candidate resident macrophages and CD81 nonresident macrophages that express C1q and CD74 in mouse, rat, and human kidney tissue. Each point represents an individual kidney sample that was harvested from mice, rats, or humans. Data are shown as mean6SEM. *P,0.01; ****P,0.001. mouse n=5, rat n=3 or 6, and human n=3.

J Am Soc Nephrol 30: 767–781, 2019 Renal Resident Macrophages across Species 779 BASIC RESEARCH www.jasn.org

60 ** C.J. Song, Z. Li., J.M. Lever, S. Liu, M.R. Crowley, and D.K. Crossman **** performed experiments. B.K. Yoder, M. Mrug, and J.F. George pro- **** vided resources. M.R. Bentley and K.A. Zimmerman made the figures. **** K.A. Zimmerman and B.K. Yoder drafted the manuscript. All authors 40 approved the final version. This project was funded by Polycystic Kidney Disease Research Foundation grant 214g16a (to B.K. Yoder), University of Alabama

% Chimerism 20 at Birmingham (UAB) School of Medicine AMC21 grant (to B.K. NS Yoder, M. Mrug, and J.F. George), National Institutes of Health (NIH) T32 training grant in Basic Immunology and Immunologic disease 2T32AI007051-38 (to K.A. Zimmerman), F31DK115169 (to 0 J.M. Lever) NIH grants R01 DK115752 (to B.K. Yoder) and R01 DK097423 (to M. Mrug), and grant 1-I01-BX002298 from the Office

B/T Cells NK Cells of Research and Development, Medical Research Service, Department Infiltrating Neutrophil of Veterans Affairs (to M. Mrug). The following NIH-funded cores Resident (novel) provided services for this project: UAB Hepato/Renal Fibrocystic Resident (canonical) Disease Core Center (P30-DK074038), UAB-University of California- Figure 8. Candidate resident macrophages identified using novel San Diego O’Brien Center for AKI Research (P30-DK079337), and markers have minimal exchange with the peripheral blood. Quanti- the UAB Comprehensive Flow Cytometry Core (P30-AR048311 and fication showing the percent chimerism of B/T cells, resident mac- P30-AI027767). Additional services were provided by the UAB com- rophages (canonical markers), resident macrophages (novel markers), parative pathology laboratory and UAB Heflin Genomic Core. infiltrating macrophages, neutrophils, and NK cells. Each dot repre- sents data collected from a single kidney harvested from individual mice. **P,0.01; ****P,0.001. B/T cells, B and T cells; Resident DISCLOSURES (Canonical), resident macrophages identified using CD11b and M. Mrug has received research/clinical trial support from and has consulted F4/80; Resident (Novel), resident macrophages identified using for Otsuka and Sanofi-Genzyme not related to this project. CD81 and C1q; Infiltrating, infiltrating macrophages. observe a corresponding enrichment of C1q at the protein SUPPLEMENTAL MATERIAL level in candidate resident macrophages isolated from hu- man kidney tissue. This discrepancy may be because of a This article contains the following supplemental material online at divergence in C1q protein expression between species, the http://jasn.asnjournals.org/lookup/suppl/doi: 10.1681/ASN.2018090931/-/ limited number of kidneys that were analyzed, the disease DCSupplemental. state of the kidney tissue, or a lack of a reliable antibody to Supplemental Table 1. Number of cells, genes, and reads in single- detect human C1q. cell data from mouse, rat, pig, and human kidneys. Although these studies suggest that resident macrophages Supplemental Table 2. Top DEGs in mouse innate immune cell exist in the kidney of multiple species, whether CD81/CD74 populations. double positive cells share a gene expression signature across Supplemental Table 3. Number of reads in individual cells from mouse Fluidigm C1 scRNAseq data. species is unknown, nor is it knownwhether candidate resident + macrophages maintain a functional equivalency across species Supplemental Figure 1. scRNAseq revealsthe presence of CD79a B during homeostatic and disease processes. Overall, this study cells in mouse kidney tissue. provides an optimistic outlook for the potential translatability Supplemental Figure 2. Gating strategy used in Fluidigm C1 studies fi of kidney resident macrophage studies in mouse and provides a to identify in ltrating and resident macrophages on the basis of ca- template for future comparative immunologic studies in res- nonical markers. ident macrophages across tissues and species. Supplemental Figure 3. scRNAseq reveals the presence of distinct clusters of innate immune cells in rat kidney tissue. Supplemental Figure 4. scRNAseq reveals the presence of distinct ACKNOWLEDGMENTS clusters of innate immune cells in pig kidney tissue. Supplemental Figure 5. scRNAseq reveals the presence of distinct We would like to thank members of the Yoder laboratory for helpful clusters of innate immune cells in human kidney tissue. suggestions during these studies. Wewould also like to thank Julie Hill, Supplemental Figure 6. Fluidigm C1 scRNAseq of single cells from Wenguang Feng, and Darvi Sergio for help with sample acquisition. human kidney tissue. K.A. Zimmerman and B.K. Yoder conceptualized the ideas. K.A. Supplemental Figure 7. Gating strategy used to identify candidate Zimmerman, C.J. Song, and D.K. Crossman collected data. K.A. resident macrophages on the basis of novel markers. Zimmerman and D.K. Crossman analyzed data. B.K. Yoder, M. Mrug Supplemental Figure 8. Chimerism of blood-derived cells in mouse and J.F. George obtained funding. K.A. Zimmerman, M.R. Bentley, parabiosis studies.

780 Journal of the American Society of Nephrology J Am Soc Nephrol 30: 767–781, 2019 www.jasn.org BASIC RESEARCH

REFERENCES 18. Bezman NA, Kim CC, Sun JC, Min-Oo G, Hendricks DW, Kamimura Y, et al.: Immunological Genome Project Consortium: Molecular defi- 1. Metchnikoff E: Untersuchungen uber die intracellulare Verdauung bei nition of the identity and activation of natural killer cells. Nat Immunol 13: Wirbellosen Thieren. Arbeit Zoologischen Instituten. Universitat Wien 1000–1009, 2012 5: 141–168, 1883 19. Kang J, Coles M: IL-7: The global builder of the innate lymphoid network 2. Schulz C, Gomez Perdiguero E, Chorro L, Szabo-Rogers H, Cagnard N, and beyond, one niche at a time. Semin Immunol 24: 190–197, 2012 Kierdorf K, et al.: A lineage of myeloid cells independent of Myb and 20. Stamatiades EG, Tremblay ME, Bohm M, Crozet L, Bisht K, Kao D, et al.: hematopoietic stem cells. Science 336: 86–90, 2012 Immune monitoring of trans-endothelial transport by kidney-resident 3. Mass E, Ballesteros I, Farlik M, Halbritter F, Günther P, Crozet L, et al.: macrophages. Cell 166: 991–1003, 2016 Specification of tissue-resident macrophages during organogenesis. 21. Braga TT, Correa-Costa M, Silva RC, Cruz MC, Hiyane MI, da Silva JS, Science 353: aaf4238, 2016 et al.: CCR2 contributes to the recruitment of monocytes and leads to 4. Hamann J, Koning N, Pouwels W, Ulfman LH, van Eijk M, Stacey M, kidney inflammation and fibrosis development. Inflammopharmacology et al.: EMR1, the human homolog of F4/80, is an eosinophil-specific 26: 403–411, 2018 receptor. Eur J Immunol 37: 2797–2802, 2007 22. Brähler S, Zinselmeyer BH, Raju S, Nitschke M, Suleiman H, Saunders 5. Reynolds G, Haniffa M: Human and mouse mononuclear phagocyte BT, et al.: Opposing roles of dendritic cell subsets in experimental GN. networks: A tale of two species? Front Immunol 6: 330, 2015 JAmSocNephrol29: 138–154, 2018 6. Hulsmans M, Clauss S, Xiao L, Aguirre AD, King KR, Hanley A, et al.: 23. Huber R, Pietsch D, Panterodt T, Brand K: Regulation of C/EBPb and Macrophages facilitate electrical conduction in the heart. Cell 169: resulting functions in cells of the monocytic lineage. Cell Signal 24: 510–522.e20, 2017 1287–1296, 2012 7. Paolicelli RC, Bolasco G, Pagani F, Maggi L, Scianni M, Panzanelli P, 24. Hardy RR, Hayakawa K: B cell development pathways. Annu Rev Immunol et al.: Synaptic pruning by microglia is necessary for normal brain de- 19: 595–621, 2001 velopment. Science 333: 1456–1458, 2011 25. Chu PG, Arber DA: CD79: A review. Appl Immunohistochem Mol 8. Keren-Shaul H, Spinrad A, Weiner A, Matcovitch-Natan O, Dvir-Szternfeld Morphol 9: 97–106, 2001 R, Ulland TK, et al.: A unique microglia type Associated with restricting 26. Riedel JH, Becker M, Kopp K, Düster M, Brix SR, Meyer-Schwesinger C, developmentofalzheimer’sdisease.Cell 169: 1276–1290.e17, 2017 et al.: IL-33-mediated expansion of type 2 innate lymphoid cells pro- 9. Munro DAD, Hughes J: The origins and functions of tissue-resident tects from progressive glomerulosclerosis. JAmSocNephrol28: macrophages in kidney development. Front Physiol 8: 837, 2017 2068–2080, 2017 10. Berry MR, Mathews RJ, Ferdinand JR, Jing C, Loudon KW, Wlodek E, 27. Hashimoto D, Chow A, Noizat C, Teo P, Beasley MB, Leboeuf M, et al.: et al.: Renal sodium gradient orchestrates a dynamic antibacterial de- Tissue-resident macrophages self-maintain locally throughout adult life fense zone. Cell 170: 860–874.e19, 2017 with minimal contribution from circulating monocytes. Immunity 38: 11. Zimmerman KA, Gonzalez NM, Chumley P, Chacana T, Harrington LE, 792–804, 2013 Yoder BK, et al.: Urinary T cells correlate with rate of renal function loss 28. Lever JM, Yang Z, Boddu R, Adedoyin OO, Guo L, Joseph R, et al.: in autosomal dominant polycystic kidney disease. Physiol Rep 7: Parabiosis reveals leukocyte dynamics in the kidney. Lab Invest 98: e13951, 2019 391–402, 2018 12. Li B, Dewey CN: RSEM: Accurate transcript quantification from 29. Gibney BC, Chamoto K, Lee GS, Simpson DC, Miele LF, Tsuda A, et al.: RNA-Seq data with or without a reference genome. BMC Bioinformatics Cross-circulation and cell distribution kinetics in parabiotic mice. J Cell 12: 323, 2011 Physiol 227: 821–828, 2012 13. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al.: STAR: 30. Puranik AS, Leaf IA, Jensen MA, Hedayat AF, Saad A, Kim KW, et al.: Ultrafast universal RNA-seq aligner. Bioinformatics 29: 15–21, 2013 Kidney-resident macrophages promote a proangiogenic environment 14. Butler A, Hoffman P, Smibert P, Papalexi E, Satija R: Integrating single- in the normal and chronically ischemic mouse kidney. Sci Rep 8: 13948, cell transcriptomic data across different conditions, technologies, and 2018 species. Nat Biotechnol 36: 411–420, 2018 31. Wu H, Malone AF, Donnelly EL, Kirita Y, Uchimura K, Ramakrishnan SM, 15. Kamran P, Sereti KI, Zhao P, Ali SR, Weissman IL, Ardehali R: Parabiosis et al.: Single-cell transcriptomics of a human kidney allograft biopsy in mice: A detailed protocol. J Vis Exp (80): 50556, 2013 specimen defines a diverse inflammatory response. J Am Soc Nephrol 16. Park J, Shrestha R, Qiu C, Kondo A, Huang S, Werth M, et al.: Single-cell 29: 2069–2080, 2018 transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 360: 758–763, 2018 17. Kjeldsen L, Cowland JB, Borregaard N: Human neutrophil gelatinase- associated lipocalin and homologous proteins in rat and mouse. Biochim See related editorial, “How to Find a Resident Kidney Macrophage: the Single- Biophys Acta 1482: 272–283, 2000 Cell Sequencing Solution,” on pages 715–716.

J Am Soc Nephrol 30: 767–781, 2019 Renal Resident Macrophages across Species 781 Supplemental Material

Table S1-S3

Figure S1-8

Supplementary Table 1 Species # of cells % of reads mapped to genome Mean reads/cell Median genes/cell Total genes detected Mouse 3013 78.1 80508 952 15380 Rat 3935 82.5 54456 1113 14944 Pig 4671 90.9 61638 1065 14589 Human 2868 91.7 112080 878 17658

Supplementary Table 2

Cell Type Gene P value Cell Type Gene P value Resident macrophages C1qa 0.00E+00 Unknown Cd7 2.06E-179 Resident macrophages C1qb 0.00E+00 Unknown Xcl1 4.04E-179 Resident macrophages C1qc 0.00E+00 Unknown Cxcr6 3.33E-120 Resident macrophages Cd81 0.00E+00 Unknown Trbc2 8.37E-104 Resident macrophages Apoe 0.00E+00 Unknown Gimap4 4.19E-103 Resident macrophages H2-Eb1 0.00E+00 Unknown Gimap6 2.55E-79 Resident macrophages Ctss 0.00E+00 Unknown Ltb 1.36E-76 Resident macrophages Ms4a7 7.14E-240 Unknown Trbc1 3.35E-70 Resident macrophages Cd74 3.25E-229 Unknown Ccl4 1.03E-07 Resident macrophages Mmp12 1.48E-135 Unknown Ccl3 9.89E-04 cDC2 DCs Cd209a 0.00E+00 Innate Lymphoid Cells Gata3 2.94E-279 cDC2 DCs Clec10a 1.12E-274 Innate Lymphoid Cells Cxcr6 6.75E-200 cDC2 DCs Tnip3 2.53E-210 Innate Lymphoid Cells Lztfl1 9.02E-150 cDC2 DCs Cfp 8.55E-188 Innate Lymphoid Cells Ly6a 2.01E-121 cDC2 DCs H2-Oa 4.82E-186 Innate Lymphoid Cells Skap1 1.66E-113 cDC2 DCs H2-DMb2 1.42E-146 Innate Lymphoid Cells Ltb 6.25E-99 cDC2 DCs S100a6 6.01E-125 Innate Lymphoid Cells Hs3st1 3.74E-89 cDC2 DCs Napsa 1.67E-123 Innate Lymphoid Cells Phlda1 3.44E-87 cDC2 DCs Tnfsf9 2.13E-112 Innate Lymphoid Cells Lmo4 2.29E-35 cDC2 DCs Socs3 8.42E-69 Innate Lymphoid Cells Junb 8.94E-29 NK cells Gzma 0.00E+00 cDC1 DCs Xcr1 0.00E+00 NK cells Nkg7 0.00E+00 cDC1 DCs Ifi205 4.49E-219 NK cells Gzmb 0.00E+00 cDC1 DCs Cd24a 6.31E-214 NK cells Klre1 0.00E+00 cDC1 DCs Cxx1b 5.95E-160 NK cells Klra8 0.00E+00 cDC1 DCs Cxx1a 7.09E-150 NK cells Klra4 2.76E-302 cDC1 DCs Tnni2 3.39E-122 NK cells Klra9 1.27E-297 cDC1 DCs Naaa 4.87E-96 NK cells Ccl5 6.02E-284 cDC1 DCs Ppt1 9.94E-58 NK cells AW112010 2.24E-199 cDC1 DCs Cst3 1.01E-51 NK cells Lgals1 1.74E-190 cDC1 DCs Irf8 9.37E-51 Ly6chi macrophages Chil3 4.23E-160 B cells Ly6d 0.00E+00 Ly6chi macrophages Plac8 2.50E-138 B cells Cd79a 0.00E+00 Ly6chi macrophages Ms4a4c 5.04E-127 B cells Iglc3 0.00E+00 Ly6chi macrophages Lyz1 2.13E-118 B cells Ms4a1 0.00E+00 Ly6chi macrophages Ly6c2 3.23E-111 B cells Ebf1 0.00E+00 Ly6chi macrophages Ms4a6c 2.64E-89 B cells Iglc2 3.04E-153 Ly6chi macrophages Ifitm3 1.09E-77 B cells Iglc1 7.77E-150 Ly6chi macrophages Lyz2 4.71E-77 B cells Cd79b 5.07E-90 Ly6chi macrophages Irf7 1.35E-67 B cells Ighm 2.80E-39 Ly6chi macrophages Gbp2 1.89E-60 B cells Igkc 3.51E-39 Ly6clo macrophages Ear2 4.26E-255 Neutrophils Retnlg 0.00E+00 Ly6clo macrophages Fabp4 9.84E-246 Neutrophils Slpi 6.02E-283 Ly6clo macrophages Eno3 8.06E-228 Neutrophils S100a9 3.84E-209 Ly6clo macrophages Treml4 1.63E-216 Neutrophils S100a8 1.07E-206 Ly6clo macrophages Pglyrp1 8.26E-167 Neutrophils Hp 1.90E-144 Ly6clo macrophages Cebpb 7.06E-130 Neutrophils G0s2 7.00E-124 Ly6clo macrophages Msrb1 6.57E-127 Neutrophils Cxcl2 4.22E-116 Ly6clo macrophages Nr4a1 6.65E-126 Neutrophils Msrb1 1.36E-57 Ly6clo macrophages Gngt2 1.72E-117 Neutrophils Il1b 3.03E-47 Ly6clo macrophages Smpdl3a 1.50E-115 Neutrophils S100a11 2.10E-38 Supplementary Table 3 Infiltrating macrophage Resident macrophage Cell number Reads Cell number Reads R1_C12 1,492,862 R2_C03 2,134,946 R1_C15 2,227,789 R2_C05 2,303,807 R1_C16 6,460,052 R2_C06 738,061 R1_C23 1,050,069 R2_C10 159,872 R1_C24 2,596,836 R2_C12 253,938 R1_C25 3,425,398 R2_C13 3,578,235 R1_C32 3,406,075 R2_C14 2,304,633 R1_C34 3,262,353 R2_C21 2,807,416 R1_C38 1,247,509 R2_C23 3,143,572 R1_C40 258,583 R2_C28 1,657,015 R1_C52 3,180,335 R2_C30 1,896,495 R1_C53 1,822,262 R2_C32 476,005 R1_C54 2,280,668 R2_C34 4,799,911 R1_C55 2,294,715 R2_C36 4,347,918 R1_C56 3,071,868 R2_C39 1,542,320 R1_C58 4,297,437 R2_C42 2,068,422 R1_C60 3,016,114 R2_C46 1,865,383 R1_C63 3,895,750 R2_C47 1,067,191 R1_C65 1,038,025 R2_C53 91,473 R1_C69 653,524 R2_C55 4,186,470 R1_C70 4,737,539 R2_C56 2,602,547 R1_C71 2,564,324 R2_C60 183,934 R1_C77 216,424 R2_C61 4,719,640 R1_C78 2,581,007 R2_C64 1,628,547 R1_C81 9,560 R2_C73 1,259,852 R1_C83 3,635,582 R2_C74 3,947,573 R1_C84 2,171,672 R2_C78 4,059,899 R1_C85 644,928 R2_C79 1,172,156 R1_C87 2,828,777 R2_C80 1,811,933 R1_C90 3,485,523 R2_C81 206,613 R1_C91 1,703,711 R2_C82 6,985,563 R1_C93 941,270 R2_C84 2,860,895 R1_C95 2,109,498 R2_C90 1,543,593 R2_C91 2,093,469 R2_C92 2,839,715 R2_C93 2,515,540

Figure S1. tSNE projection and violin plot showing expression of Cd79a in mouse renal innate immune cells.

Figure S2 Gating strategy used to isolate infiltrating and resident macrophages based on the canonical Cd11b and F/480 approach. Infiltrating and resident macrophages were collected and subjected to C1 Fluidigm single cell RNA sequencing.

Figure S3 tSNE projections and violin plots showing a top DEG that was used to identify (A) neutrophils (S100a8), (B) NK cells (Nkg7), (C) innate lymphoid cells (ILCs, Cxcr6), (D) infiltrating macrophages (Irf7, Cebpb), (E) and dendritic cells (Naaa, Clec10a) in single cell data from a rat kidney.

Figure S4 tSNE projections and violin plots showing a top DEG that was used to identify (A) neutrophils (S100A8), (B) NK cells (NKG7), (C) innate lymphoid cells (ILCs, CXCR6), (D) infiltrating macrophages (IRF7, CEBPB), and (E) dendritic cells (NAAA) in single cell data from a pig kidney. Unfortunately, the Clec10a orthologue has not been identified in the pig.

Figure S5 tSNE projections and violin plots showing a top DEG that was used to identify (A) neutrophils (S100A8), (B) NK cells (NKG7), (C) innate lymphoid cells (ILCs, CXCR6), (D) infiltrating macrophages (IRF7, CEBPB), (E) and dendritic cells (NAAA, CLEC10A) in single cell data from a human kidney.

Figure S6 Heat map of top 100 DEGs in lineage negative CD45+ innate immune cells from human kidney tissue identified using Fluidigm C1 single cell RNA sequencing.

Figure S7 Gating strategy used to identify resident macrophages in multiple species using CD74 and CD81 antibodies. Figure S8 Quantification of the percent chimerism of B/T cells, infiltrating monocytes/macrophages, and neutrophils in the blood of mice undergoing parabiosis. ****

P<0.0001.

FSC-H Figure S2. Figure S1. Cd79a FSC- A

FSC-A CD45 Normalized Expression 0 Cd79a 1 2

FSC-A 3 4 5 Live/Dead 6 7 8 9

GR-1 F4/80

Cd11b Infiltrating F4/80 Resident Figure S3

0 1 2 3 4

S100a8 Nkg7 Cxcr6 A (Neutrophils) B (NK Cells) C (ILCs) Normalized Expression 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4

D Irf7 E Cebpb F Naaa G Clec10a (Infltrating MФ) (Infltrating MФ) (Dendritic Cells) (Dendritic Cells) Normalized Expression 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 Figure S4 Pig

0 1 2 3 4

S100A8 NKG7 CXCR6 A (Neutrophils) B (NK Cells) C (ILCs) Normalized Expression 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4

IRF7 CEBPB NAAA D (Infltrating MФ) E (Infltrating MФ) F (Dendritic Cells) Normalized Expression 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 Figure S5

Human

0 1 2 3 4

S100A8 NKG7 CXCR6 A B (Neutrophils) (NK Cells) C (ILCs) Normalized Expression 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4

IRF7 CEBPB NAAA ClEC10A D (Infltrating MФ) E (Infltrating MФ) F (Dendritic Cells) G (Dendritic Cells) Normalized Expression

0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 Figure S6

RPS14 RPL3 RPS19 RPL30 RPS15 RPL41 ENSG00000279483 PFDN5 TMSB10 RPL23A RPL32 RPL31 RPL8 RPL35 RPL38 B2M TMSB4X EIF1 RPS27 RPL18A DDX5 RPL17 RPL23 RPL13A SAT1 FOS PABPC1 CD52 ALDOA EEF1B2 CASP1 RPL21 RPL21P16 RPL37A UBB HNRNPA2B1 RPL9P9 S100A11 HSPA8 RPL27A RPS16 SERF2 RPL19 H3F3AP4 RPS23 RPL11 HSPE1 RPL27 EEF1A1 RPL10 IFITM2 RPS3A RPS18 RPS29 RPS27A ARHGDIB HSP90AB1 DUSP1 TYROBP RPS10 UBC ARPC2 YWHAZ FCER1G NKG7 CD247 GNLY PLAC8 CX3CR1 FGFBP2 CCL4 CCL5 PRF1 GZMB RPS11 DBI BRD2 CST7 CD74 RGS2 FTH1 LYZ HLA-DRA NFKBIZ FTL S100A6 S100A8 S100A9 IFI30 ENSG00000278217 HSPH1 DNAJB1 RPL26 LST1 ATP10D OLIG1 TCP1 FPR1 EIF5 ZFAND2A

S100A8+ NKG7+ NK Cells Neutrophils S100A11+ Mac. Inf. Figure S7 FSC-H FSC- A

FSC-A CD45

FSC-A Live/Dead

FSC-A B/T cells

CD11b CD74 F4/80 CD81 Figure S8

Blood **** 6 0

4 0

2 0

% Chimerism

0

B/ T Cells Infltrating Neutrophil