Transcriptional Classification and Functional Characterization of Human Airway Macrophage and Dendritic Cell Subsets

This information is current as Vineet I. Patel, J. Leland Booth, Elizabeth S. Duggan, of September 24, 2021. Steven Cate, Vicky L. White, David Hutchings, Susan Kovats, Dennis M. Burian, Mikhail Dozmorov and Jordan P. Metcalf J Immunol published online 28 December 2016

http://www.jimmunol.org/content/early/2016/12/28/jimmun Downloaded from ol.1600777

Supplementary http://www.jimmunol.org/content/suppl/2016/12/28/jimmunol.160077 Material 7.DCSupplemental http://www.jimmunol.org/

Why The JI? Submit online.

• Rapid Reviews! 30 days* from submission to initial decision

• No Triage! Every submission reviewed by practicing scientists by guest on September 24, 2021 • Fast Publication! 4 weeks from acceptance to publication

*average

Subscription Information about subscribing to The Journal of is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts

The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published December 28, 2016, doi:10.4049/jimmunol.1600777 The Journal of Immunology

Transcriptional Classification and Functional Characterization of Human Airway Macrophage and Dendritic Cell Subsets

Vineet I. Patel,*,† J. Leland Booth,† Elizabeth S. Duggan,† Steven Cate,* Vicky L. White,‡ David Hutchings,x Susan Kovats,*,{ Dennis M. Burian,‡ Mikhail Dozmorov,‖ and Jordan P. Metcalf*,†

The respiratory system is a complex network of many cell types, including subsets of macrophages and dendritic cells that work together to maintain steady-state respiration. Owing to limitations in acquiring cells from healthy human lung, these subsets remain poorly characterized transcriptionally and phenotypically. We set out to systematically identify these subsets in human airways by developing a schema of isolating large numbers of cells by whole-lung bronchoalveolar lavage. Six subsets of phagocytic APC (HLA-DR+) were consistently observed. Aside from alveolar macrophages, subsets of +, BDCA12CD14+, BDCA1+CD14+, BDCA1+CD142,andBDCA12CD142 cells were identified. These subsets varied in their ability to internalize Escherichia coli, Staphylococcus aureus,andBacillus anthracis particles. Downloaded from All subsets were more efficient at internalizing S. aureus and B. anthracis compared with E. coli. Alveolar macrophages and CD14+ cells were overall more efficient at particle internalization compared with the four other populations. Subsets were further separated into two groups based on their inherent capacities to upregulate surface CD83, CD86, and CCR7 expression levels. Whole-genome transcriptional profiling revealed a clade of “true dendritic cells” consisting of Langerin+, BDCA1+CD14+,andBDCA1+CD142 cells. The dendritic cell clade was distinct from a macrophage/monocyte clade, as supported by higher mRNA expression levels of several dendritic cell–associated , including CD1, FLT3, CX3CR1,andCCR6. Each clade, and each member of both clades, was discerned by specific upregulated http://www.jimmunol.org/ genes, which can serve as markers for future studies in healthy and diseased states. The Journal of Immunology, 2017, 198: 000–000.

acrophages (Mf) and dendritic cells (DC) are mono- density of bacteria in the lower airways is several fold lower than nuclear phagocytes found in most human peripheral levels observed on the skin or in the intestinal tract (12), several M tissues, including the lung (1, 2). However, heterogeneity phyla have been identified in common between healthy donor co- clearly exists under both of these phagocyte categories (1, 3, 4). horts, including Firmicutes, Bacteroidetes, Proteobacteria, Fusobac- Additionally, the microenvironment of the lung airways, as opposed teria, and Actinobacteria (13). Resident airway cells must prevent

to the interstitial spaces, adds a level of complexity not seen else- overgrowth of these bacteria without triggering inflammatory re- by guest on September 24, 2021 where in the human body. Respiration occurs via an intricate system sponses. Bronchial and alveolar epithelial cells play a large role in of alveoli covered by a meshwork of thin-walled capillaries that al- promoting anti-inflammatory conditions in the steady-state via their lows diffusion of oxygen and carbon dioxide between inhaled air and constitutive production of IL-10 and TGF-b (14, 15). Under these the bloodstream. Given the delicate infrastructure of the respiratory tolerogenic conditions, inhaled particulates, pathogenic microbes, zone, inflammation in this region poses a serious threat to steady- nonpathogenic microbes, and dead cells must still be cleared to state respiration. Therefore, human lower airways must maintain an prevent respiratory obstruction and infection. DC and Mf serve this overall anti-inflammatory environment that directs tolerance to ev- purpose by internalizing, processing, and presenting encountered eryday airborne particulates, as well as to certain microbes. Recent Ags, thereby maintaining tolerance or modulating the precision, studies involving sequencing of 16S rRNA genes have shifted the strength, and direction of ensuing immune responses. paradigm of sterility in healthy lower airways toward the existence of The difficulty of acquiring human lung tissue has restricted a distinct resident bacterial microbiome (5–11). Although the overall investigation of rare resident phagocyte subsets. Some progress in

*Department of Microbiology and Immunology, University of Oklahoma Health data; V.I.P. and J.P.M. wrote the manuscript; and S.K., D.M.B., M.D., and J.P.M. Sciences Center, Oklahoma City, OK 73104; †Pulmonary and Critical Care Division, contributed to manuscript preparation. Department of Medicine, University of Oklahoma Health Sciences Center, Oklahoma The microarray data presented in this article have been submitted to Expression City, OK 73104; ‡Office of Aviation Medicine, Federal Aviation Administration, x { Omnibus (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE79706. Oklahoma City, OK 73169; Cherokee Healthcare Services, Catoosa, OK 74015; Ar- thritis and Clinical Immunology Research Program, Oklahoma Medical Research Address correspondence and reprint requests to Dr. Jordan P. Metcalf, Pulmonary and Foundation, Oklahoma City, OK 73104; and ‖Department of Biostatistics, Virginia Critical Care Division, Department of Medicine, University of Oklahoma Health Commonwealth University, Richmond, VA 23298 Sciences Center, 800 Research Parkway, RP-1, Suite 425, Oklahoma City, OK 73104. E-mail address: [email protected] ORCIDs: 0000-0001-5479-9952 (S.K.); 0000-0002-2664-4360 (D.M.B.); 0000- 0002-0086-8358 (M.D.). The online version of this article contains supplemental material. Received for publication May 2, 2016. Accepted for publication November 28, 2016. Abbreviations used in this article: AARP, airway- and alveolar-resident phagocyte; AF, autofluorescence; AM, alveolar macrophage; BAL, bronchoalveolar lavage; BALF, BAL This work was supported by funding from the Office of Aviation Medicine, Federal fluid; BDCA, blood dendritic cell Ag; DC, dendritic cell; DEG, differentially expressed Aviation Administration (to D.M.B.), Department of Veterans Affairs Grant 1 I01 gene; IRF, IFN regulatory factor; LC, Langerhans cell; Mf, macrophage; mo-DC, BX001937 (to J.P.M.), and by National Institutes of Health Grants AI062629 and monocyte-derived dendritic cell; MOI, multiplicity of infection; mo-Mf, monocyte- GM103648 (to J.P.M.) and HL119501 (to S.K.). derived macrophage; PC, principal component; PCA, principal component analysis; V.I.P. and J.P.M. conceived the study and designed experiments; J.L.B. and E.S.D. pDC, plasmacytoid DC; PI, phagocytic index; RPMI-10, RPMI 1640 with 10% FBS. provided technical assistance; S.C. performed HLA typing; V.L.W. and D.H. pro- vided microarray training; D.M.B. provided microarray reagents; V.I.P. conducted the Copyright Ó 2016 by The American Association of Immunologists, Inc. 0022-1767/16/$30.00 experiments and analyzed the data; V.I.P., D.M.B., and M.D. analyzed the microarray

www.jimmunol.org/cgi/doi/10.4049/jimmunol.1600777 2 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES identifying lung DC has been made by use of surgical resections (16– though several phagocyte subsets exist in the human lung, 19). Although resected tissue has the potential of yielding large cell phagocytes from the lower respiratory tract have not been sys- numbers by digestion, the procedure is harsh and results in con- tematically characterized or classified. Each of these subsets may tamination of lung-resident phagocytes with cells from pulmonary be functionally specialized, and therefore understanding an overall capillaries. In contrast, isolating cells directly from the airways is airway immune response in any diseased state first requires quick and bypasses the circulatory system. Studies have visualized identifying and classifying the potential contributing components. human DC in healthy airways from the bronchiolar to the alveolar Therefore, we developed techniques to isolate and preserve large epithelia (20, 21), although they did not distinguish between DC quantities of AARPs by BAL of functional (as measured by clinical subsets. Several groups have collected Mf andDCbybron- tests) whole human lungs. Subset composition and frequencies were choalveolar lavage (BAL) of volunteers, followed by varying de- comparable to those of healthy BAL volunteers. We reproducibly grees of subset discrimination (22–25). BAL Mf were first identified six AARP subsets based on surface marker expression. We separated from DC based solely on their high and low auto- tested these subsets for early functional responses based on their fluorescence (AF), respectively (25). These results suggested that ability to internalize bacterial particles, and subsequently to up- ∼95% of BAL cells were large alveolar Mf (AM), whereas cells of regulate markers of activation, maturation, and migration. These the lesser low AF fraction were mostly monocytic in appearance. results showed that AM, CD14+ DC, and CD142 DC were func- The blood DC Ags (BDCA) identify three specific subsets of DC tionally related to each other but separate from Langerin+, BDCA1+ in human blood after lineage exclusion (26). These markers, CD14+, and BDCA1+CD142 DC. This conclusion was supported BDCA-1 (CD1c), -2 (CD303), and -3 (CD141), were later tested for by transcriptional profiling of sorted cells, which split the former specificity to BAL cells (24). Tsoumakidou et al. (24) were able to “Mf-like” clade from the latter “true DC” clade. All airway subsets Downloaded from isolate small populations of BDCA-1+ and BDCA-3+ myeloid DC, were transcriptionally distant from monocyte-derived Mf (mo-Mf) as well as BDCA-2+ plasmacytoid DC (pDC) from BAL fluid and DC (mo-DC). Finally, we determined unique gene signatures (BALF). However, their studies revealed inherent limitations of cell that identified the Mf and DC clades, as well as each of the six collection by BAL. Finding healthy volunteers for BAL can be AARP subsets. time-consuming and costly, forcing researchers to turn to patients

who need the procedure for underlying medical conditions (22–24). Materials and Methods http://www.jimmunol.org/ Additionally, patient BAL does not always yield significant total Collection of BAL cells from volunteers cell numbers from which further analysis can be performed, with Human airway cells were obtained by bronchoscopy with signed informed 5 values as low as 7 3 10 prior to any enrichment (24). consent of subjects according to a protocol approved by the Oklahoma A gap in the characterization of human airway- and alveolar- University Health Sciences Center Institutional Review Board and the resident phagocytes (AARPs) has also come from the lack of Institutional Biosafety Committee. Volunteers were initially screened for recent or current use of immunosuppressive or anti-inflammatory medi- standardized markers that discriminate between cell types. Although cations. All volunteers were healthy nonsmoking subjects, aged 18–40 y BDCA markers identify known DC subsets in the blood, they do not (Supplemental Table I), with no history of or symptoms consistent with discriminate between all airway subsets. For example, multiple respiratory, cardiovascular, or autoimmune disease or recent infections. groups have identified a CD1a+ DC subset in BALF, suggested to be Current health status was verified by a complete physical examination by guest on September 24, 2021 a lung-equivalent of Langerhans cells (LC) (22, 25). However, in- focusing on the respiratory, cardiovascular, and gastrointestinal systems. For BAL, i.v. access was obtained prior to the procedure and vital signs depth flow cytometric surveys of extravascular phagocytes from were measured throughout. Airways were anesthetized with a combination whole human lungs have identified three cell subsets that expressed of nebulized and directly instilled topical lidocaine. Sedation was achieved BDCA1, two of which also expressed CD1a (27). Additionally, with i.v. midazolam and fentanyl. BAL was performed through the oral dermal Langerin+ DC were shown to be distinct from epidermal LC cavity of three separate bronchopulmonary segments (anterior segment of the right upper lobe, medial segment of the right middle lobe, and inferior in human skin, and equivalent Langerin+ DC (but not LC) were + lingular segment of the left upper lobe). For each segment, one 25-ml found in lung digestions (28). These Langerin DC in the lung were aliquot of sterile saline solution was instilled and the return discarded, prior 2 also BDCA1+, but they were separate from BDCA1+Langerin DC to collection of the return from instillation of four 30-ml aliquots of sterile and highly variable in their expression of CD1a (28). Thus, the use saline solution. Collections were pooled and viable cell counts were made of Langerin (CD207), in conjunction with CD1a and the BDCA by hemocytometer with trypan blue exclusion. Cells were centrifuged at 300 3 g for 10 min, the supernatant was aspirated, and the pellets were markers, for DC discrimination could identify the true scope of resuspended in 13 PBS at 1 3 106 cells/100 ml. Cells were stained for phagocyte subsets in the lung airways. viability using Zombie Aqua fixable viability dye (BioLegend) on ice Previous studies of human airways have likely excluded some following the manufacturer’s instructions, followed by 10 min FcR AARP subsets due to CD14 inclusion in lineage exclusion (22–24). blocking on ice with human TruStain FcX (BioLegend). Finally, cells were + stained with fluorescently labeled Abs (Supplemental Table II) for 20 min Whereas CD14 blood monocyte contamination is a concern when on ice. All samples were centrifuged at 300 3 g for 5 min and washed isolating cells by tissue digestion, BAL provides a methodology twice with 13 PBS-2. Samples were fixed with 2% paraformaldehyde that localizes the source of isolated CD14+ cells to the airways. prior to flow cytometry. Resident CD14+ cells, originally classified as DC (and described as such in our studies for consistency), have been identified in Lung cell isolation and preservation human dermis by several groups (29–33). This population tran- Whole human donor lungs were obtained through the International Institute scriptionally aligns closely with monocytes and dermal Mf rather for the Advancement of Medicine (Edison, NJ; http://www.iiam.org/), a than dermal DC (33). Indeed, resident populations of CD14+ and nonprofit division of the Musculoskeletal Transplant Foundation. Lungs BDCA1+CD14+ cells exist in lung digest preparations (18), and were deemed nontransplantable for reasons such as histocompatibility mismatching, lung size, uncertain drug usage, or prior incarceration. Our recent analysis of BALF from healthy volunteers has consistently criteria for lung acceptance included: 18–70 y of age, nonsmoking a + 2 identified both CD14 CD16 “classical monocytes” and a second minimum of 2 y, no history of lung disease, noncardiac death, a PaO2/FiO2 subset of CD14+CD16+ “intermediate monocytes” (34). In mice, ratio .200, and normal to minimal atelectasis based on chest x-ray results, monocytes in the steady-state enter the lung and migrate back to with no evidence of intercurrent infection (Supplemental Table I). Upon arrival, Wisconsin solution and residual blood was washed from the vas- draining LN without acquiring phenotypic characteristics of Mf + culature using sterile physiological saline (0.9% w/v). Saline was pumped (35). In humans, CD14 DC described previously may be the at low pressure (∼20 cm H2O) into the main bronchus to produce visible equivalent cell subset to these constant-turnover monocytes. Al- swelling of lobes. The resultant BAL collections were pooled, and cells The Journal of Immunology 3 were concentrated by centrifugation at 300 3 g for 10 min, resuspended to were sorted by FACS for AM and CD14+ DC into 13 PBS. Sorted 1 3 107 cells/ml in freeze medium (40% RPMI 1640, 50% FBS, and 10% populations were cytospun onto glass slides and sealed under glass DMSO) (36), frozen at a rate of ∼1˚C/min at 280˚C, and stored in liquid coverslips by ProLong Gold antifade reagent (Thermo Fisher Scientific). nitrogen vapor at 2190˚C. Microscopy was conducted using a Zeiss LSM 710 confocal microscope. Z-stacks were imaged for a minimum of 100 cells of each AARP subset HLA typing under 363 magnification. HLA-DR from FACS was used as a surface High-resolution HLA typing was performed, as previously described (37), stain for cells, whereas pHrodo signal was used to locate internalized S. aureus by sequence-based typing at the University of Oklahoma Health Science particles. Background fluorescence of particles was subtracted Center Clinical Laboratory Improvement Amendments/American Society prior to imaging. Cells were manually analyzed for particle positivity, and total particle numbers in positive cells were determined by visual for Histocompatibility and Immunogenetics–accredited HLA typing lab- counts. oratory using in-house methods. Briefly, genomic DNA was extracted from lung cells using a QIAamp DNA blood (Qiagen). After confirmation, Activation, maturation, and migration assays the PCR product was purified using an ExoSAP-IT kit (USB) and was sequenced using BigDye Terminator v3.1 (Applied Biosystems) chemistry. BAL cells were thawed and plated for 1 h at 37˚C as described above. After Dye removal was conducted by ethanol precipitation. Sequencing reactions 1 h, cells were exposed to an MOI of 1:1 and 10:1 of heat-killed E. coli were performed on a 3730 capillary electrophoresis DNA sequencer (0111:B4 strain; InvivoGen), heat-killed S. aureus (InvivoGen), and (Applied Biosystems). Four-digit HLA types were determined using the germination-null B. anthracis spores, with control wells receiving particle HLA typing program Assign sequence-based typing (Conexio Genomics). diluent. Exposure was conducted during 4 h (0 and 240 min) at 37˚C. The 0 h time point cells were harvested just prior to bacterial exposure. Cells FACS and flow cytometry were harvested at each time point, stained, and analyzed by flow cytom- etry. Abs used for measures of activation (CD83), maturation (CD86), and Cell sorting was performed on a BD FACSAria (BD Biosciences), whereas migration (CCR7) are indicated in Supplemental Table II. other data were acquired on a BD LSR II. All data were analyzed using Downloaded from FlowJo v10 software. mAbs and viability dyes used are listed in PBMC collection and monocyte enrichment Supplemental Table II. Cell gates were determined using fluorescence minus one controls for each stain, with the minus stain being filled with a Source material for all human blood cells was freshly collected buffy coats labeled isotype control to account for nonspecific binding. provided by the Oklahoma Blood Institute. Blood donors were in good health and negative for all infections tested for during standard donation. Preparation of Bacillus anthracis spores Age and smoking history were not available on blood donors. PBMC were immediately isolated by gradient centrifugation using Lymphoprep Starter culture of B. anthracis (Sterne strain 34F2 Δger) was provided by the (Stemcell Technologies) according to the manufacturer’s instructions. http://www.jimmunol.org/ laboratory of Dr. Philip Hanna (University of Michigan, Ann Arbor, MI). Spore Resulting PBMC were either resuspended in 13 PBS for subsequent stocks were created as previously described (38). Briefly, bacteria were grown staining and flow cytometry or in 13 PBS containing 0.5% BSA and 2 mM with continuous shaking in Luria–Bertani medium overnight at 37˚C. On the EDTA for monocyte enrichment. Positive selection of monocytes was next day, bacteria were streaked on AK agar sporulating dishes and incubated conducted using anti-CD14 MicroBeads along with MS separation col- for 3 wk at 30˚C. At time of harvest, each dish was washed by pipetting with umns (Miltenyi Biotec) following the manufacturer’s instructions. 5 ml of chilled, sterile, deionized water to dislodge spores. Spore collections were spun at 10,000 3 g for 10 min and resuspended in 1 ml of chilled water. Generation of mo-Mf and mo-DC Spore suspensions were heated at 65˚C for 60 min to kill any vegetative bac- teria. After heat treatment, spores were centrifuged for 10 min at 10,000 3 g, Monocytes isolated as described above were resuspended in RPMI-10 m m and the supernatant was discarded. Pellets were resuspended in 1 ml of chilled containing 100 IU/ml penicillin, 100 g/ml streptomycin, and 2.5 g/ml 3 6 by guest on September 24, 2021 water and centrifuged for 10 min at 10,000 3 g. The upper layer of resulting amphotericin B at 1 10 cells/ml. Medium contained 50 ng/ml GM-CSF f spore pellets was washed by pipette to remove contaminating bacterial cell for M differentiation or a combination of 50 ng/ml GM-CSF and 25 ng/ml debris. The supernatant and the top layer of the pellet were aspirated and IL-4 for DC differentiation (both from BioLegend). Cells were plated at discarded. The wash procedure was repeated a total of five times, with the final 37˚C for 6 d, with medium being replaced every 2 d. On the sixth day, half f spore preparations being resuspended in chilled, sterile, deionized water and the immature M and DC were harvested by repeated pipetting, centri- 3 3 6 m pooled. Spore counts were determined by hemocytometer and stocks were fuged at 300 g for 10 min, and resuspended at 1 10 cells/100 lin stored at 4˚C. All spores in experiments were harvested ,30 d prior to use. PBS-2. FcRs were blocked with human TruStain FcX (BioLegend) for 10 min on ice, followed by Ab staining for 20 min on ice. mAbs and vi- Particle internalization assays ability dyes used are listed in Supplemental Table II. Stained cells were washed twice with 13 PBS-2 and resuspended in PBS-2 for live cell Particles of pHrodo–Escherichia coli (K-12 strain) and pHrodo–Staphylococcus sorting. For maturation, remaining culture cells were exposed to LPS aureus (Wood strain without A) were prelabeled by the manufacturer, (Invivogen) at 1 mg/ml in fresh medium for 3 d. On the ninth day, mature whereas B. anthracis spores were manually labeled with a pHrodo red Mf and DC were harvested and stained for sorting by FACS. particle labeling kit for flow cytometry following the manufac- turer’s instructions (Thermo Fisher Scientific). Particle concentrations were RNA processing determined by resuspending an aliquot of particles in pH 4 buffer and counting by hemocytometer under a fluorescence microscope. Lung and monocyte-derived cell populations were sorted by FACS # 3 4 m Preserved BAL cells were rapidly thawed at 37˚C, resuspended in RPMI directly into QIAzol lysis reagent (Qiagen) at 5 10 cells/600 land 2 1640 with 10% FBS (RPMI-10), and centrifuged at 300 3 g for 10 min. frozen at 80˚C. When thawed, samples were purified using a QIAcube Supernatant was discarded and cell pellet depleted of dead/dying cells system in conjunction with miRNeasy mini kits (both from Qiagen) per using a dead cell removal kit (Miltenyi Biotec) in conjunction with MACS the manufacturer’s instructions. RNA yields and purities were deter- MS separation columns (Miltenyi Biotec) according to the manufacturer’s mined using NanoDrop 2000c (Thermo Scientific). RNA was reverse instructions. Viable cell counts were made by trypan blue exclusion and cells transcribed to cDNA and amplified using Ovation Pico WTA Systems V2 were resuspended in RPMI-10 containing 100 IU/ml penicillin, 100 mg/ml (NuGEN) following the manufacturer’s instructions. Final amplified streptomycin, and 2.5 mg/ml amphotericin B at 1 3 106 cells/ml. Cells were cDNA was purified using Agencourt RNAClean XP beads. Yields and m plated in tissue culture plates for 1 h at 37˚C. After 1 h, cells were exposed to purities were determined by NanoDrop. Based on these values, 5 gof multiplicities of infection (MOI) of 1:1 and 10:1 of bacterial particles labeled cDNA per sample was fragmented and biotinylated (Encore biotin with pHrodo red (in 50 ml of culture medium) during a 2-h time course module; NuGEN) following the manufacturer’s instructions for hybrid- (30, 60, and 120 min) at 37˚C. ization with microarrays. Hybridization cocktails were created using At each time point, cells were harvested by repeated pipetting, centrifuged components from the GeneChip hybridization, wash, and stain kit at 300 3 g for 5 min, and resuspended in 13 PBS at 1 3 106 cells/100 ml. (Affymetrix) and incubated on GeneChip U133 Plus 2.0 Cells were stained for viability and surface markers (Supplemental Table II) arrays (Affymetrix) for 18 h at 45˚C with rotation. Arrays were washed prior to flow cytometry as described for volunteer lavage cells. and stained using components of the GeneChip hybridization, wash, and stain Kit. Arrays were scanned using a GeneChip scanner 3000 7G Microscopy (Affymetrix). Fluorescence intensities were log2 RMA summarized to give values using Bioconductor v3.1 on R programming Cells were exposed to an MOI of 10:1 of pHrodo–S. aureus particles as language v3.2, with summarization specifically done with the affy described above over a 2-h time course (30, 60, and 120 min). Fixed cells v1.46.1 R package. 4 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES

Microarray analysis expressed high HLA-DR. In this fraction was a small subset of Langerin+ cells, further referenced as Langerin+ DC (subset 2). Because the microarray data were acquired in two separate batches, the batch + effect was removed with the “removeBatchEffect” function from limma Langerin DC had a lower cytoplasmic-to-nuclear ratio compared v3.26.5 R package. The principal component analysis (PCA) results were with AM, as well as unique membrane dendrites upon visualization. visualized using the scatterplot3d v0.3-36 R package. The correlogram of From the Langerin2 pool, we divided the remaining cells based on median-averaged cell type–specific gene expression profiles was created positivity for CD11c, CD14, and BDCA1 (CD1c). From the CD14+ using the “Euclidean” distance and “Ward.D” hierarchical clustering metric, + + + on top of which pairwise Pearson correlation coefficients were overlaid. The CD11c cells, a small group of BDCA1 CD14 DC (subset 3), + 2 dendrogram of cell type–specific gene expression profiles was created using along with a larger subset of CD14 BDCA1 DC (subset 4), was a Pearson correlation coefficient as the distance metric. seen. Both subsets had low cytoplasmic-to-nuclear ratios compa- For comparative analysis of genes defining cell type–specific gene rable to Langerin+ DC, and CD14+ DC specifically had bilobular signatures, pairwise differentially expressed genes (DEGs) were identified nuclei similar to monocytes. A similar division of the CD11c+ using limma v3.26.5 R package. Briefly, probes were filtered using the 2 + 2 “nsFilter” function with default settings from the genefilter v1.52.0 R CD14 pool revealed a small subset of BDCA1 CD14 DC (subset 2 2 package. The significant p values were adjusted for multiple testing using 5) and a larger subset of CD14 BDCA1 DC (subset 6). The the Benjamini–Hochberg procedure, and DEGs with adjusted p values of bilobular nuclei of CD14+ DC were the only visually distinguishing , 2 0.1 were reported. All data processing and analyses were carried out feature between these CD14 subsets and their CD14+ counter- using the R programming language v3.2.2 (http://www.r-project.org). + + DEG lists of lung AARP clades or subsets were used to identify enriched parts. Distinct populations of BDCA3 DC and CD123 pDC were canonical pathways by Ingenuity Pathway Analysis. Analysis criteria were not observed. BDCA3 expression was variable on a number of the restricted to specific tissues: dermis, epidermis, lung, lymph nodes, skin, described subsets (Fig. 1A), and thus we did not use it further as a and spleen. Filters were also placed on species to include only mouse, rat, defining marker of cells from whole-lung lavage. Downloaded from and human, and on cell types to include only data from bone marrow and Frequencies of the DC subsets were consistently very low (Fig. 1B), immune cells. Significant pathways were determined by a right-tailed Fisher + exact test with a = 0.05. as most of the AARPs are expected to be AM. CD14 DC showed the highest average frequency across the seven lungs (∼4.5%) versus Statistical analysis BDCA1+CD142 DC with the lowest average frequency (∼0.25%). All statistical analyses, except for those involving microarray data, were With the rarity of the lung DC subsets, we also tested whether AARP

performed using Prism 6.0 (GraphPad Software). Specific tests used are frequencies changed with time in culture (Fig. 1C). Such observa- http://www.jimmunol.org/ indicated where applicable with each figure and table. tions would indicate either death of specific subsets or the upregu- lation or downregulation of markers used to identify them. Langerin+, Results BDCA1+CD14+, and CD14+ DC frequencies significantly decreased Donor demographics show a diverse range of lung donors by4hinculture.Therefore,welimitedfurtherstudiesto4hto Pairs of functioning lungs (criteria described in Materials and include all DC subsets in our analyses. Methods) were obtained from seven donors ranging in age from 29 BAL of six healthy volunteers (Supplemental Table I) verified to 68 y of age. Although specific reasons for transplant rejection the residency and low frequencies of the five DC subsets in the were not available, acceptance of each pair of lungs was carefully small airways and alveolar spaces (Fig. 2A), with comparable by guest on September 24, 2021 determined based on PaO2/FiO2 ratios at the time of availability percentages to those measured by whole-lung lavage (Fig. 1B). In (some time prior to final readings) in conjunction with x-ray results an effort to delineate any additional phagocyte subsets found in (Supplemental Table I). No lungs from donors with more than normal airways, we also analyzed CD1a, BDCA3, and CLEC9A minimal atelectasis and/or infiltrates on chest x-rays were accepted. (CD370) expression on the five DC subsets from BAL of three Donors with any evidence of intercurrent infection were excluded. volunteers (Fig. 2B). CD1a has been used as a means of differ- Four of the lung donors were ex-smokers for at least 5 y prior to entiating DC subsets in combination with BDCA1 or Langerin by organ donation, and three donors had no history of smoking. Total several groups (25, 27, 28, 34). However, its coexpression had not cell yields by explant lavage did not correlate with history of been measured concurrently with both BDCA1 and Langerin on smoking. The average cell yield from lavage of a pair of lungs was airway cells. None of the five DC subsets uniformly expressed 5.43 3 109 total cells. As several studies have suggested that HLA CD1a (Fig. 2B, top). Additionally, CD1a was expressed over a type I (A, B, and C) and type II (DR, DQ, and DP) variants asso- spectrum from negative to positive rather than bimodal in these ciate with the pathogenesis of autoimmune disorders and infections categories, except on Langerin+ DC (Fig. 2C, left). Only ∼20% of 2 (39–42), we genotyped donor lungs for HLA alleles. High diversity CD14+ DC and 15% of CD14 DC expressed surface CD1a at all was observed in HLA variants at HLA-A, -B, and -C loci from all (Fig. 2B, top). In contrast, almost 60% of BDCA1+CD14+ and 2 seven donors, with only one donor carrying homozygosity. Diver- BDCA1+CD14 DC were positive for this marker. A distinctly sity was also high at class II loci, although homozygosity was more higher 75% of Langerin+ DC expressed CD1a, but a lesser fraction common (Supplemental Table I). These demographics suggest that of these CD1a+ cells was CD1aint. Overall, we determined that we acquired a broad sampling of the adult population in the areas of CD1a positivity did not correlate with the identity of any of the six age, gender, smoking history, and HLA class I and II genotypes. AARP subsets, and its expression was not used further to defini- tively separate additional subsets. High expression of BDCA3 and Six distinct AARP subsets are resident to human airways CLEC9A has been associated with identification of true cross- Flow cytometry of cells from whole-lung lavage revealed six presenting DC in human blood and peripheral tissues (43–46). AARP subsets after exclusion of dead and lineage+ (CD3, CD19, Expression of BDCA3 on fresh BAL cells from healthy volunteers CD20, and CD56) cells (Fig. 1A). APC status was confirmed by revealed that whereas most (∼75–100%) of the five DC subsets high surface expression of HLA-DR. AM were large, high com- did express this marker (Fig. 2B, middle), only 20–45% expressed plexity cells with high AF and expression of the integrin CD11c CLEC9A (Fig. 2B, bottom). Interestingly, surface expression of (subset 1). AM were identified after Diff-Quik staining based on both BDCA3 and CLEC9A was over a broad range, but distinct size and their high cytoplasmic-to-nuclear ratio. Initial discrimi- BDCA3hiCLEC9Ahi cells were only present as a small subgroup nation of large, high complexity cells from small, low complexity of the CD142 DC population (Fig. 2C). These results from vol- cells reduced the possibility that AM with changing AF would fall unteers suggested that BDCA3 and CLEC9A expression was not in the DC fraction. The small, low complexity, low AF cells also uniform and thus would not further discriminate the six subsets The Journal of Immunology 5 Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 1. Six AARP subsets are present in the human lower respiratory tract. (A) Flow cytometry of BAL cells from whole human lungs. The gating strategy used to identify six subsets (labeled 1–6 above) is shown. After exclusion of dead and lineage+ cells, only HLA-DRhi cells were analyzed further. In addition to large, high AF AM (subset 1), five distinct subsets of small, low AF cells, further designated as DC, were seen: subset 2, Langerin+; subset 3, BDCA1+CD14+; subset 4, CD14+,subset5,BDCA1+CD142; and subset 6, CD142 DC. Separate CD123+ pDC and BDCA3+ DC were not seen. Accompanying morphology of sort-purified lung subsets visualized by Diff-Quik staining is shown. Original magnification, 340 by phase-contrast microscopy. Representative plots from seven lung donors are shown. (B) Frequencies of lung DC subsets as percentages of total HLA-DR+ cells based on gating strategy. Composite data as mean 6 SEM from seven lung donors are shown. (C) Fold change in frequencies of lung subsets in relationship to time in culture (0, 4, and 8 h). Composite data as mean 6 SEM from three lung donors are shown. *p # 0.05, two-way repeated measures ANOVA with a Tukey multiple comparisons test. 6 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 2. Cell subsets isolated from whole-lung lavage are comparable to healthy volunteer populations. (A) Flow cytometric frequencies of DC subsets in BALF collected from three separate lung regions of healthy volunteers. Data are presented as percentages of total HLA-DR+ cells based on gating strategy shown in Fig. 1A. Composite data as mean 6 SEM from six volunteers are shown. (B) Percentages of each of the six lung AARP subsets positive for surface CD1a (top), BDCA3 (middle), and CLEC9A (bottom) expression. Composite data are expressed as mean 6 SEM from three BAL volunteers. (C) CD1a (left), BDCA3 (middle), and CLEC9A (right) positivity (gates shown) measured by flow cytometry of volunteer BALF. Representative plots from three volunteers are shown. Filled gray indicates isotype control. identified in whole-lung lavage, with the exception of a definite contain distinct populations of BDCA3+CD142 DC and CD123+ but quite scarce CD142BDCA3hiCLEC9Ahi population. pDC that were not present in BALF (Fig. 3A). In blood, most We also wanted to make sure our vigorous whole-lung lavage did (∼80%) of HLA-DR+ cells were monocytes (Fig. 3B). Collec- not cause blood DC to contaminate airway cells. Analysis of PBMC tively, these results suggest that six AARP subsets are commonly from three individuals (one male and two female), following the and reproducibly found in the human lower respiratory tract, and same gating strategy used to identify lung subsets (Fig. 1A), that our findings were not due to contamination from PBMC. revealed marked differences between lung and blood HLA-DR+ cell populations (Fig. 3). PBMC were frozen and thawed in the Lung DC subsets vary in internalization efficiency of bacterial same manner as BAL cells to discount the possibility that the pathogens method of preservation was eliminating susceptible cell types. We next looked for functional differences between the AARP PBMC lacked high AF cells and Langerin+ cells, but they did subsets, beginning with the ability to internalize bacterial particles. The Journal of Immunology 7

FIGURE 3. Cell subsets in lung airways are markedly different from those in blood. (A) Flow cytometry of human PBMC obtained from freshly isolated buffy coats. Gating strategy is equivalent to that used in Fig. 1A for subset comparisons. After initial ex- clusion of dead and lineage+ cells, only Downloaded from HLA-DRhi cells were further analyzed. Representative plots from three blood donors are shown. (B) Frequencies of blood APC subsets as percentages (on logarithmic scale) of total HLA-DR+ cells based on gating strategy shown in (A). Composite data are expressed as http://www.jimmunol.org/ mean 6 SEM from three blood donors (one male, two female). by guest on September 24, 2021

Three different bacteria were tested at two different MOI during exposure, when AM exhibited significantly higher levels of in- a 2-h time course (Fig. 4): E. coli, S. aureus, and B. anthracis ternalization compared with CD142 DC. The lack of other dif- (spores). Each pathogen was labeled with the pH-sensitive dye ferences in internalization between subsets at early time points of pHrodo to discriminate internal from external particles. At a 1:1 10:1 E. coli exposure suggests that AM are not as efficient at ratio, we assumed that all cells were equally exposed to bacterial internalization of this bacterium as compared with S. aureus and particles. Interestingly, E. coli particles were not internalized as B. anthracis (Fig. 4B). By 120 min, E. coli internalization by AM efficiently as S. aureus or B. anthracis (Fig. 4A). AM did show was higher than that of all the DC subsets. However, CD142 DC significantly greater E. coli positivity compared with Langerin+, showed lower internalization than did other DC subsets as well, BDCA1+CD142, and CD142 DC, but this occurred only after including Langerin+, BDCA1+CD14+, and CD14+ DC. This pat- 120 min of exposure. At the lowest MOI of S. aureus and tern with AM versus CD142 DC held for 10:1 of S. aureus and B. anthracis, all subsets were better at internalization compared B. anthracis, except that it was more dramatic, appearing earlier with CD142 DC by 120 min of exposure. This observation was after exposure (30 min for B. anthracis and 60 min for S. aureus) true of AM, BDCA1+CD14+ DC, and CD14+ DC by 60 min of and with greater differences in values. Also at 10:1, internalization B. anthracis exposure, but not after S. aureus exposure. Overall, by CD14+ DC peaked with the second highest PI values after AM the efficiency of bacterial internalization at 1:1 was B. anthracis across all pathogens, although this occurrence was only significant spores . S. aureus . E. coli for all time points (Fig. 4A). at 120 min (Fig. 4B). Overall, the kinetics and magnitude of path- To tease out differences in internalization at a higher MOI of ogen internalization varied, with B. anthracis spores . S. aureus . 10:1 in the low frequency DC subsets, we calculated a variation of E. coli for all AARP subsets. standard phagocytic index (PI), based on flow cytometry. We We compared our measurement of the PI to the standard by calculated a flow cytometric PI by multiplying the percentage of a manual count, using AM and CD14+ DC exposed to 10:1 pHrodo– given subset positive for particles by the pHrodo median fluo- S. aureus (Fig. 4C). These subsets were chosen because of their rescence intensity of particle-positive cells (Fig. 4B, 4C). E. coli higher frequencies within the total lavage pool, and also our in- internalization at 10:1 was similar in all subsets until 60 min of terest in the greater internalization by CD14+ DC compared with 8 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 4. Lung AARP subsets vary in their ability to internalize different bacterial species. (A and B) Flow cytometry of internalization of pHrodo-labeled E. coli, S. aureus,andB. anthracis (spores) by lung AARP subsets. BAL cells were exposed to two different MOI (1:1 and 10:1) of bacteria during a 2-h time course (30, 60, and 120 min). Graphs represent mean 6 SEM from seven lung donors. *p # 0.05, **p # 0.01, ***p # 0.001, ****p # 0.0001, two-way repeated measures ANOVAwith a Tukey multiple comparisons test. (A) Percentage of six APC subsets positive for pHrodo signal after 1:1 MOI exposure. It was assumed that all cells were equally exposed to bacteria at this MOI. (B) Flow cytometric PI values, calculated as the percentage of a given subset positive for pHrodo signal multiplied by the median fluorescence intensity of the pHrodo-positive cells of that subset, after exposure to 10:1 of particles. (C)Com- parison of techniques for determining internalization using 10:1 exposure to pHrodo-labeled S. aureus, and analysis of AM and CD14+ DC from three lung donors. Left: Flow cytometry of pHrodo signal as described in (A)and(B) for the same three lung donors as in the center graph. Center: BAL cells were exposed to pHrodo–S. aureus during a 2-h time course (30, 60, and 120 min), followed by FACS of AM and CD14+ DC. Using confocal microscopy, a minimum of 100 cells of each subset were analyzed for particle positivity and numbers. PI values were calculated as the percentage of particle-positive cells multiplied by the average number of particles in positive cells. Right: Confocal microscopy maximum intensity projection of a CD14+ DC having internalized S. aureus. Blue indicates HLA-DR; red indicates pHrodo–S. aureus. Original magnification, 363. Ba, B. anthracis; Ec, E. coli; Sa, S. aureus. the other DC subsets (Fig. 4B). S. aureus was chosen because it metric PI is likely a measure of internalization and acidification fell in the middle of overall internalization between E. coli and rather than purely internalization, as is measured by manual counts. B. anthracis when comparing all AARP subsets (Fig. 4A, 4B). Overall, these results suggest that AM may be more efficient at Sorted AM and CD14+ DC were analyzed by confocal microscopy acidification but comparable to CD14+ DC in internalization. of a minimum of 100 cells of each subset (Fig. 4C, right). Al- + + + + 2 though comparable, CD14+ DC gave slightly higher average PI Langerin , BDCA1 CD14 , and BDCA1 CD14 DC values than did AM by manual counts (Fig. 4C, center). Looking intrinsically upregulate CD83, CD86, and CCR7 at the results of the same three lung donors by the flow cytometric Based on the early differences in internalization, we next deter- PI, AM average values were slightly higher than CD14+ DC mined whether certain subsets were prone to rapid activation (Fig. 4C, left). Because pHrodo is pH sensitive, the flow cyto- (CD83), maturation (CD86), or migration (CCR7). BAL cells were The Journal of Immunology 9 exposed to heat-killed E. coli or S. aureus, or germination-null CD14+ DC, and CD142 DC, did not spontaneously change during B. anthracis spores, thus eliminating confounding effects of ger- 4 h (Fig. 5B). Bacterial exposure caused no significant increases in mination, toxin production, or fixation. Exposure time was ex- CD86. CCR7 upregulation facilitates migration of peripheral tissue tended to 4 h to allow any early marker expression changes to DC to draining lymph nodes via afferent lymphatics (30). The time manifest. We began by measuring CD83, as it was assumed ac- frame in which human AARP subsets can upregulate CCR7 fol- tivation would occur prior to maturation and migration. The lowing pathogen exposure is unknown. The only significant in- most intriguing results were that Langerin+ DC, and especially creases in CCR7 caused by bacterial exposure were on Langerin+ BDCA1+CD142 DC, dramatically upregulated CD83 with time in DC after 10:1 exposure to S. aureus and B. anthracis (Fig. 5C). culture alone (Fig. 5A), suggesting these two subsets are sensitive This suggests a specific early migratory potential of Langerin+ DC to rapid activation due to minor perturbations. In comparison, by 4 h, but only when exposed to high pathogen doses (Fig. 5). As levels of CD83 on AM, CD14+ DC, and CD142 DC either with CD83 and CD86, Langerin+, BDCA1+CD14+, and BDCA1+ remained stable or only slightly increased in culture (Fig. 5A). CD142 DC subsets showed the greatest upregulation of CCR7 CD83 rarely increased in response to bacteria by 4 h exposure, with related to time in culture (Fig. 5), whereas AM, CD14+ DC, and the only significant increases in CD83 compared with no-exposure CD142 DC showed the least degree of variation. The former controls by BDCA1+CD142, Langerin+, and BDCA1+CD14+ DC grouping of AARP subsets by inherent CCR7 upregulation implied at 10:1 E. coli, S. aureus, and B. anthracis, respectively (Fig. 5A). that these three experience steady-state migration to regional Although we did not observe many changes in CD83 dependent on lymph nodes. The above results of CD83, CD86, and CCR7 to- pathogen exposure, we wanted to test whether maturation occurred gether suggested that Langerin+, BDCA1+CD14+, and BDCA1+ 2 in the absence of activation. As observed with CD83, BDCA1+ CD14 DC possessed an intrinsic sensitivity to activation, matu- Downloaded from CD142 DC spontaneously upregulated CD86 with increasing ration, and migration that grouped them separately from AM, culture time. Levels of CD86 on the other subsets, particularly AM, CD14+ DC, and CD142 DC. http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 5. Langerin+, BDCA1+CD14+, and BDCA1+CD142 DC upregulate CD83, CD86, and CCR7 with increasing time in culture. (A–C) Flow cytometry of subset activation, maturation, and migration potential as measured by change (Δ) in CD83, CD86, and CCR7 median fluorescence intensity of each subset compared with 0 h time. BAL cells were exposed to two MOI (1:1 and 10:1) of heat-killed E. coli, heat-killed S. aureus, and nongerminating B. anthracis spores for 4 h. Graphs represent mean 6 SEM from seven lung donors. Each donor’s cells were simultaneously exposed to the three types of particles, so no treatment (NT) control data points are equivalent across bacteria. *p # 0.05, **p # 0.01, ***p # 0.001, two-way repeated measures ANOVA with a Dunnett multiple comparisons test to NT values. (A) ΔCD83, (B) ΔCD86, (C) ΔCCR7. Ba, B. anthracis; Ec, E. coli; Sa, S. aureus. 10 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES

Transcriptional profiling delineates Mf and DC clades in the lung subsets. They also indicate that within AARP subsets, AM, CD14+ 2 f We next analyzed the steady-state AARP subsets for transcriptional DC, and CD14 DC form a transcriptional and functional M clade that can be separated from a DC clade of Langerin+, differences that could account for the bacterial internalization + + + 2 variations (Fig. 4) and the intrinsic propensities of certain DC BDCA1 CD14 , and BDCA1 CD14 DC. subsets for maturation and migration (Fig. 5). Previously, moDC We next determined whether these clades had core gene sig- f and mo-Mf have been standards for investigating phagocyte re- natures that could be tied to known properties of DC or M . Each sponses to various stimuli (47), largely due to the ease of isolating of the three subsets of each clade was compared with each of the three subsets of the second clade to elucidate genes with increased and differentiating human blood monocytes. Therefore, we also expression relative to the opposite clade (Fig. 6D). The Mf clade included transcriptomes of mo-DC and mo-Mf in analyses to had seven upregulated genes compared with the DC clade, establish the strength of these model cells in representing lung whereas the DC clade had 54 such genes compared with the Mf subsets. CD14+ monocytes from three male and three female clade (Fig. 6D). Among the genes up in the DC clade, we rec- blood donors were exposed to GM-CSF alone to generate mo-Mf, ognized several associated with Ag presentation and DC matura- or in combination with IL-4 to generate mo-DC. After 6 d in 2 2 tion, including CD1B, CD1C, CD1E, and CD86. Pathway analysis culture, CD14 DC-SIGN+ mo-DC and CD14+DC-SIGN mo- of DC clade-specific DEGs identified canonical pathways of DC Mf (Supplemental Fig. 1A) were purified by FACS, as described function, with the top three being DC maturation (p = 0.00178), previously (48). Cells were also tested for CD1a, which is lipid Ag presentation by CD1 (p = 0.00193), and phagosome expressed predominantly on DC. Based on the intrinsic upregu- formation (p = 0.00407). lation of CD83 and CD86 on some lung subsets (Fig. 5), To further examine the functional implications of the identified Downloaded from remaining monocyte-derived cells were matured with LPS for clades, we created an expression heat map of selected genes known to comparison. CD1a was selectively expressed on DC and increased relate to DC/Mf identity and function in human skin and lung significantly after LPS maturation (Supplemental Fig. 1B). CD80 (Fig. 7) (27, 33, 49). As suggested earlier (Fig. 6D), the CD1 mol- increased on both DC and Mf upon LPS maturation, although it ecules were highly expressed by members of the DC clade relative to was only significantly increased by Mf (Supplemental Fig. 1C). the Mf clade. Conversely, molecules known for their expression by CD86 significantly increased on both cell types after LPS expo- Mf,suchasMRC1, SIRPb1, NR1H3, CD36,andMARCO,wereall http://www.jimmunol.org/ sure (Supplemental Fig. 1D). CD83 also increased on both pop- elevated in the Mf clade, especially in AM and CD14+ DC. Sur- ulations after LPS exposure, although significance was only prisingly, levels of CD163 and CD209 were not useful in dis- f observed with M (Supplemental Fig. 1E). These results cumu- tinguishing lung Mf from lung DC, respectively. mRNA levels of latively demonstrated that we had derived distinct immature and these molecules could, however, separate mo-Mf from mo-DC. The f mature mo-DC and mo-M . transcription factor IFN regulatory factor (IRF)4 was specifically Transcriptomes of the six lung subsets, as well as those of upregulated in BDCA1+CD142 DC, which is vital for the equivalent f immature and mature mo-DC and mo-M , were compared by DC subset in human blood (49). Additionally, FLT3 was highly whole-genome transcriptional profiling (Fig. 6). PCA using the expressed by members of the DC clade, supporting the “true DC” first three PCs accounted for 62.26% of the total variation across nature of these three subsets (50). Along with high mRNA levels of by guest on September 24, 2021 all genes expressed (Fig. 6A). Three-dimensional distances were CD83, CD86,andCCR7, which agreed with our functional data greatest between monocyte-derived cells and the six AARP sub- (Fig. 5), we also measured high levels of CCR6 and CX3CR1 in the sets, with the exception of mature mo-DC along PC1. Immature DC clade. Both molecules were highly expressed by primary lung and mature mo-DC were relatively close together, as were im- DC subsets, but not by monocyte-derived phagocytes, verifying the f + mature and mature mo-M . Mo-DC did sort with Langerin , migratory potential of the peripheral DC subsets, as opposed to + + + 2 BDCA1 CD14 , and BDCA1 CD14 DC along PC2 and PC3, mo-DC and mo-Mf. We also analyzed DEGs from specific pairwise f + whereas mo-M sorted with AM and CD14 DC along these two subset comparisons to identify pathways that could be used to sep- + 2 PC. Within the lung subsets, AM, CD14 DC, and CD14 DC arate both closely and distantly related cell types. Our choices for + grouped together, especially along PC1 and PC3, whereas Langerin , pairwise comparisons related to current focus areas in tissue-resident + + + 2 BDCA1 CD14 , and BDCA1 CD14 DC grouped together along Mf and DC. The total number of DEGs in these comparisons agreed all three PC (Fig. 6A). These lung relationships agreed with our with their overall degree of relatedness, with AM versus BDCA1+ findings suggested by the varying levels of CD83, CD86, and CD142 DC showing the largest number of DEGs and BDCA1+ CCR7 (Fig. 5). Pearson correlation values were generally high CD142 DC versus Langerin+ DC showing the smallest number between lung subsets, with the lowest value of 0.83 occurring (Supplemental Fig. 2). + 2 between AM and BDCA1 CD14 DC, and the highest value of As CD14+ DC have been shown to relate closely to resident Mf + + 2 0.97 occurring between Langerin and BDCA1 CD14 DC in human skin (33), we examined the two equivalent subsets from + 2 (Fig. 6B). AM, CD14 DC, and CD14 DC were closely correlated the airways for canonical pathways that could differentiate them + + + in a range of 0.93–0.95. Similarly, Langerin ,BDCA1CD14 ,and (Table I). Interestingly, the top four in AM relative to CD14+ DC 2 BDCA1+CD14 DC yielded correlation coefficients in a highlighted degradation, whereas biosynthesis and fibrosis were range of 0.95–0.97. Comparing monocyte-derived cells to highlighted in CD14+ DC. Between comparisons that included lung subsets yielded much lower values, with the highest corre- members of the DC clade, upregulated pathways encompassed DC lation being between AM and immature mo-Mf, at 0.84 (Fig. 6B). maturation, phagosome formation, Ag presentation, and granulocyte/ Hierarchical clustering revealed that the monocyte-derived pop- agranulocyte adhesion and diapedesis. Within the DC clade, ulations clustered separately from the lung subsets by the greatest BDCA1+CD14+ DC showed specific upregulation of IL-17A sig- difference in relative heights (Fig. 6C). Within lung subsets, the naling pathways compared with both BDCA1+CD142 and Langerin+ closest relationship was between AM and CD14+ DC, which were DC (Table I). However, we realized that by including multiple spe- 2 then related to CD14 DC. The other grouping was between cies and tissue types in our pathway analyses, some of the canonical 2 Langerin+ and BDCA1+CD14 DC, which then related to pathways identified, such as “bile acid biosynthesis” and “patho- BDCA1+CD14+ DC (Fig. 6C). Collectively, these results imply genesis of multiple sclerosis,” would not have physiological rele- that mo-DC and mo-Mf are poor models for primary lung AARP vance to the human lung. Therefore, we also examined the specific The Journal of Immunology 11 Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 6. Lung subsets can be grouped into Mf and DC clades, which are highly divergent from monocyte-derived model APC. (A–C) Data shown are based on purified lung subsets (blue) and monocyte-derived APC (red). Data are composites of results from seven lung donors and six blood (monocyte) donors. Cells of the same type were not pooled prior to experiments. (A) PCA of gene expression by lung subsets, as well as immature and mature mo-DC and mo-Mf. Numbers in parentheses indicate level of variation encompassed by each of the first three PC. (B) Correlation matrix of lung subsets, and mo-DC and mo-Mf, based on all available gene probes. Values within grid indicate Pearson correlation coefficients, with perfect correlation being 1. (C) Hierarchical clustering of lung subsets, and mo-DC and mo-Mf, based on all available gene transcripts. (D) Venn diagram representing DEGs with in- creased expression between the lung Mf clade (blue) and DC clade (red) identified in (A)–(C). Overlapping regions represent the number of genes up- regulated by two or all three subsets of one clade when compared with all three subsets of the second clade. Lists are upregulated DEGs in common between all three subsets of the Mf clade relative to the DC clade (blue arrow), and the DC clade relative to the Mf clade (red arrow). Data are composites of results from seven lung donors. genes upregulated in the pairwise subset comparisons (Table I). system, histamine degradation, and oxidative ethanol degradation III. Several chemokines and chemokine receptors, cytokines and cyto- The other five AARP subsets did not have enough unique DEGs for kine receptors, TLRs, and Ag presentation molecules were regularly pathway analysis, but DEGs did provide insight into potential cel- identified in overlapping canonical pathways. These differences led lular functions. Of the 14 CD14+ DC DEGs, two peptidases, us to look for DEGs specifically upregulated in each AARP subset. ADAMTS2 and SERPINb2, had increased expression. Additionally, AMPH, involved in clathrin-mediated endocytosis, was also differ- Unique gene signatures identify lung AARP subsets entiallyexpressedbyCD14+ DC. Within the DC clade, very few Unique DEGs with increased expression were identified in each unique DEGs were found, reflecting the close relationships between AARP subset (Table II). AM gave the greatest number of DEGs these three subsets (Table II). Additionally, our high stringency of relative to the other five subsets, with 78. Analysis of AM DEGs identifying DEGs (specifically, removal of donor effects prior to demonstrated greatest upregulation of these five canonical path- subset comparisons) meant that the listed genes were upregulated in ways: PXR/RXR activation, retinol biosynthesis, complement the APC subsets in each of the seven donors. As confirmation of 12 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 7. The lung DC clade shows specialization for lipid Ag presentation, maturation, and migration. Heat map shows median gene expression by lung subsets, and immature and mature mo-DC and mo-Mf, of 44 selected genes known to relate to Mf and/or DC. Gene categories (left) include identification markers, transcription factors, markers of maturation and migration, and TLRs. Row scale (red–blue) across gene rows represents expression level after subtracting the average expression and dividing by the SD of that row. Data shown are based on purified lung subsets and monocyte-derived APC (blue–red cell type labels, respectively). Data are composites of results from seven lung donors and six blood (monocyte) donors. Cells of the same type were not pooled prior to experiments. our gating strategy, CD207 (LANGERIN) was the only DEG of AARP subsets may change prior to arrival of the lungs. However, 2 Langerin+ DC. In BDCA1+CD14 DC, five DEGs were identified, we do not think that any AARP subsets were lost completely in including four whose protein products localize to the plasma mem- our studies involving whole-lung BAL, as equivalent subsets were brane and thus could serve as additional markers for identifying this identified from BALF of healthy volunteers (Figs. 1, 2). Transit cell type: CNKSR3, HOMER2, P2RX5,andSLC7A11. Based on time of whole lungs varied depending on the source location, but these DEG lists, AM uniquely upregulate certain canonical path- in all cases, lungs were processed immediately upon arrival at our ways, whereas the other five subsets have increased expression of facilities. It is possible that the decreased frequencies of Langerin+, selected genes, some of whose function is yet unknown. BDCA1+CD14+, and CD14+ DC we observed in culture (Fig. 1C) related to the sensitivity of these specific subsets to the shock of Discussion lung harvest itself, transportation, or freezing/thawing after la- Our results demonstrate that at least six AARP subsets are present vage. Freshly isolated AM from BAL of healthy volunteers dis- in the human lower respiratory tract, and they show, to our play a proinflammatory profile at transcriptional and functional knowledge for the first time, that they associate with specific (based on cytokine production) levels, which decreases only after functional and transcriptional profiles. The rarity of primary DC in 24 h in culture (51). Thus, the AARP subsets are likely activated peripheral tissues has posed a restriction on their characterization. immediately after whole-lung lavage as well, which unfortunately Our method of whole-lung BAL and subsequent cell preservation prevents valid comparisons of steady-state cells before and after circumvents this issue, as rare DC subsets can be found at levels freezing. sufficient for repeated experiments. Another advantage of our The initial gating strategy (Fig. 1A) built on previous strategies technique is that airway cells are separated from interstitial DC of dividing tissue APC in human blood, skin, and lung (28, 33, 44, and Mf. We acknowledge that frequencies of some of the six 49). To our knowledge, our work is the first to apply this level of The Journal of Immunology 13

Table I. Top canonical pathways associated with pairwise comparisons of AARP subsets

AARP Subset Comparison Canonical Pathway Upregulated Genes p Valuea AM up versus CD14+ Choline degradation ALDHA1, CHDH 1.97 3 1024 Methylglyoxal degradation III AKR1B1, AKR1C3, AKR1C1/AKR1C2 2.16 3 1024 Bile acid biosynthesis, neutral AKR1C3, AKR1C1/AKR1C2, CYP27A1 4.16 3 1024 pathway Phenylethylamine degradation ALDH3A2, AOC3 5.84 3 1024 CD14+ up versus AM Pathogenesis of multiple sclerosis CCL4, CCR5, CXCL9, CXCL10 7.55 3 1026 IL-10 signaling CCR5, FCGR2A, FCGR2B, IL10, IL1R2, JAK1, 9.41 3 1025 NFKBIA Hepatic fibrosis/hepatic stellate cell CCR5, CXCL9, EDNRB, HGF, IL10, IL1R2, IL6R, 1.13 3 1024 activation SMAD3, TIMP1, TNFRSF1B, VEGFA Chondroitin sulfate biosynthesis CHST2, CHST15, CSGALNACT1, HS3ST3B1, 8.06 3 1024 XYLT1 AM up versus BDCA1+CD142 Heme degradation BLVRA, BLVRB, HMOX1, HMOX2 4.38 3 1025 LPS/IL-1–mediated inhibition of ABCA1, ABCC3, ABCG1, ACOX1, ACOX3, ACSL1, 4.51 3 1025 RXR function ALAS1, ALDH1A1, ALDH3A2, ALDH7A1, ALDH9A1, APOE, CAT, CD14, CPT2, FABP3, FABP4, FMO4, GSTO1, GSTT1, HS2ST1, IL1A, MGST1, MGST3, NR1H3, PAPSS2, PLTP, RXRA, SLC27A3, SULT1A1, SULT1C2, TLR4 Downloaded from Complement system C2, C1QA, C1QB, C1QC, C1S, C5AR1, CFB, CFD, 2.01 3 1024 CR1, SERPING1 Role of IL-17 in psoriasis CCL20, CXCL1, CXCL3, CXCL5, S100A8, S100A9 3.00 3 1024 BDCA1+CD142 up versus AM DC maturation CCR7, CD40, CD58, CD80, CD83, CD86, CD1A, 2.18 3 1029 CD1B, CD1C, CD1D, CREB5, FCGR2A, FCGR2B, FSCN1, HLA-DOA, HLA-DOB, HLA-DQA1, IL18, IL32, JAK2, LTB, LY75, MAP3K14, NFKB1, http://www.jimmunol.org/ NFKB2, PIK3CD, PIK3CG, PIK3R6, PLCB1, PLCG2, PLCL1, STAT4, TLR3, TNF, TNFRSF11B, TNFRSF1B Th cell differentiation BCL6, CD40, CD80, CD86, HLA-DOA, HLA-DOB, 3.20 3 1028 HLA-DQA1, ICOSLG/LOC102723996, IL18, IL18R1, IL21R, IL2RA, IL2RG, IL6R, STAT3, STAT4, TGFBR1, TNF, TNFRSF11B, TNFRSF1B Role of Mf, fibroblasts, and CCND1, CEBPD, CREB5, FZD1, GNAO1, GNAQ, 2.16 3 1027 endothelial cells in rheumatoid IL16, IL18, IL32, IL17RA, IL18R1, IL18RAP, IL1R1, arthritis IL1R2, IL1RL1, IL6R, IRAK2, JAK2, LTB,

MAP3K14, NFAT5, NFATC2, NFKB1, PDGFA, by guest on September 24, 2021 PIK3CD, PIK3CG, PIK3R6, PLCB1, PLCG2, PLCL1, PRKCA, PRKCB, PRKD3, SOCS1, STAT3, TCF3, TCF4, TLR1, TLR3, TLR6, TLR10, TNF, TNFRSF11B, TNFRSF1B, TRAF1, TRAF5, VEGFA, WNT5A TREM1 signaling CD40, CD83, CD86, CIITA, FCGR2B, IL18, 9.04 3 1027 IL1RL1, JAK2, LAT2, NFKB1, NFKB2, NLRP3, PLCG2, STAT3, TLR1, TLR3, TLR6, TLR10, TNF CD14+ up versus BDCA1+CD14+ Granulocyte adhesion and CCL7, CCL8, CCL18, CCL20, CXCL1, CXCL2, 2.21 3 1026 diapedesis FPR2, SDC3 Agranulocyte adhesion and CCL7, CCL8, CCL18, CCL20, CXCL1, CXCL2 2.49 3 1024 diapedesis Xenobiotic metabolism signaling ABCC3, ALDH1A1, CES1, CYP1B1, IL6, MAPK7, 3.46 3 1024 MGST1 Triacylglycerol biosynthesis ABHD5, DGAT2, PLPP3 5.59 3 1024 BDCA1+CD14+ up versus CD14+ Cyclins and cell cycle regulation CCNA2, CCNB1, CCNB2, CCND2, CDK1, CDK6, 2.32 3 1026 CDKN2C, HDAC9, PPP2R2B, TGFB2 Mitotic roles of polo-like kinase CCNB1, CCNB2, CDK1, CHEK2, KIF11, PLK4, 2.38 3 1026 PPP2R2B, PRC1, PTTG1 Phagosome formation FCER1A, FCGR2B, MRC2, PIK3C2B, PIK3CG, 1.65 3 1025 PRKCA, RHOF, RHOH, TLR3, TLR10 Allograft rejection signaling CD80, CD86, HLA-DOA, HLA-DPA1, HLA-DPB1, 7.17 3 1025 HLA-DQB2 BDCA1+CD14+ up versus Role of IL-17A in psoriasis CCL20, CXCL1, CXCL3, CXCL5, S100A8, S100A9 1.51 3 1028 BDCA1+CD142 Granulocyte adhesion and C5AR1, CCL2, CCL8, CCL20, CXCL1, CXCL3, 2.77 3 1026 diapedesis CXCL5, CXCL10, HRH1, ITGB3, MMP2, MMP19 Agranulocyte adhesion and C5AR1, CCL2, CCL8, CCL20, CXCL1, CXCL3, 3.63 3 1026 diapedesis CXCL5, CXCL10, FN1, HRH1, MMP2, MMP19 Complement system C1QA, C1QC, C3AR1, C5AR1, CR1 1.13 3 1024 BDCA1+CD142 up versus Tryptophan degradation to 2-amino- IDO1, IDO2 1.35 3 1023 BDCA1+CD14+ 3-carboxymuconate semialdehyde DC maturation CCR7, FSCN1, HLA-DOB, LTB, MAP3K14, 1.44 3 1023 TNFRSF11B (Table continues) 14 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES

Table I. (Continued)

AARP Subset Comparison Canonical Pathway Upregulated Genes p Valuea NAD biosynthesis II (from IDO1, IDO2 4.87 3 1023 tryptophan) OX40 signaling pathway HLA-DOB, TNFSF4, TRAF5 5.88 3 1023 Langerin+ up versus BDCA1+ Glutathione-mediated GSTM2, HPGDS 9.73 3 1024 CD14+ detoxification Ag presentation pathway HLA-DOB, HLA-DQB2 2.41 3 1023 Allograft rejection signaling HLA-DOB, HLA-DQB2 2.86 3 1023 OX40 signaling pathway HLA-DOB, HLA-DQB2 4.44 3 1023 BDCA1+CD14+ up versus Granulocyte adhesion and C5AR1, CCL20, CXCL1, CXCL2, CXCL10, 8.94 3 1029 Langerin+ diapedesis CXCL13, IL1RL1, ITGAM, ITGB3, MMP2, MMP7, SDC2 Role of IL-17A in psoriasis CCL20, CXCL1, S100A8, S100A9 3.72 3 1026 VDR/RXR activation CXCL10, HES1, HOXA10, IL1RL1, PDGFA, SPP1 4.82 3 1025 Agranulocyte adhesion and C5AR1, CCL20, CXCL1, CXCL2, CXCL10, 6.93 3 1025 diapedesis CXCL13, MMP2, MMP7 aThe p values are based on a right-tailed Fisher exact test, with significance criteria of a = 0.05. Downloaded from subset discrimination to human AARPs, and it complements re- our subsets by transcriptional profiling, this approach appears to cent work by Desch et al. (27) who separated extravascular lung have been appropriate. phagocytes based on BDCA1, CD1a, and CD206 expression. We observed BDCA3 expression on multiple phagocyte subsets Although we did examine expression of the nonclassical MHC (Fig. 1A), which is consistent with previous findings of BDCA3 class I molecule, CD1a, on the six AARP subsets from volunteer upregulation on BDCA1+ DC and pDC with increasing culture time

BAL (Fig. 2B, top), it was not used further as a subset-defining (25, 47). However, BDCA3 positivity was also observed on a large http://www.jimmunol.org/ marker. In human skin, CD1a has been observed at high levels on proportion of freshly isolated DC subsets from healthy volunteers epidermal LC, and thus it has been used interchangeably with (Fig. 2B, middle), suggesting that BDCA3 is not a specific marker Langerin expression to identify LC (32, 52, 53). However, in the for any of the subsets surveyed, irrespective of culturing. BDCA3hi dermis there is a separate population of CD1a+ DC that expresses CLEC9Ahi DC have been proposed as being a unique subset of lower levels of this marker compared with LC (31, 52). It was cross-presenting DC in humans (43–46). A much lower percentage surprising that we did not observe CD1a coexpression uniformly of our five DC subsets were CLEC9A+ (Fig. 2B, bottom) as com- on any of the subsets, including Langerin+ DC. Bigley et al. (28) pared with BDCA3+ (Fig. 2B, middle). More importantly, high observed that most (but not all) Langerin+BDCA1+ DC from lung expression of BDCA3 and CLEC9A was only observed on a small digestion were positive for CD1a, which is consistent with our fraction of the CD142 DC subset (Fig. 2C, right). These findings by guest on September 24, 2021 results (Fig. 2B, top), where ∼75% of Langerin+ DC were also suggest that steady-state airways house a small population of CD1a+. At the mRNA level, all the CD1 molecules were elevated BDCA3hiCLEC9AhiCD142 DC, which we would have grouped in members of the DC clade compared with the Mf clade, with within CD142 DC from whole-lung BAL. Future work may test highest levels in Langerin+ DC (Fig. 7). However, CD1a was not lung lavage cells for surface expression of the chemokine receptor bimodal in positivity on two of the three subsets on which it was XCR1, which has been identified as a conserved marker of cross- expressed (BDCA1+CD14+ and BDCA1+CD142 DC). Instead, presenting BDCA3+ DC in both mice and humans (54, 55). XCR1 expression was along a spectrum, which precluded separation mRNA levels were also relatively high in CD142 DC (Fig. 7), based on high, low, or intermediate levels (Fig. 2C, left). Langerin+ which would be explained by a small subset of BDCA3hiCLEC9Ahi DC did appear to contain a small CD1aint subset, separate from XCR1+ cells within the CD142 DC population. This cross- CD1a2/low cells (Fig. 2C, left). This Langerin+CD1aint DC subset presenting DC subset would express the transcription factor IRF8 may correspond to epidermal LC and warrants further investiga- (56, 57), as was observed under CD142 DC at the transcriptional tion with our model. High levels of BDCA1 have been seen on level (Fig. 7). These BDCA3hi DC can be distinctly separated from both LC and CD1a+ DC from skin (30, 32, 52). Therefore, had we BDCA1+CD142 DC, which are dependent on the transcription used CD1a as an additional marker on the other DC subsets, it factors FLT3 and IRF4 in human blood (49) and lung (Fig. 7). may have inappropriately split BDCA1+ DC subsets that we dis- Although Desch et al. (27) did not observe any extravascular lung criminated in this study. Desch et al. (27) recently examined cells that expressed CLEC9A when searching for true BDCA3+ DC, extravascular human lung subsets and noted two subsets of DC they did not compare their results to lavage cells of volunteers. that expressed BDCA1 and CD1a, with a third subset that only Conversely, we did not test our cells from whole lungs for surface expressed BDCA1. However, they did not measure Langerin ex- expression of CLEC9A. Some have hypothesized that pDC remain pression on any of their indicated subsets. BDCA1 is likely expressed in circulation and lymphoid tissues under steady-state conditions, on Langerin+ DC, but, importantly, Langerin is not expressed on the and only infiltrate the periphery after exposure to pathogens, par- two BDCA1+ DC subsets (Figs. 1A, 7). Attempting to compare results, ticularly viral pathogens (58). This could explain why we did not our studied BDCA1+CD14+ DC were likely divided into CD1a+ and observe pDC from lavage of whole lungs (Fig. 1A), whereas they CD1a2 monocyte-derived cells by Desch et al. (27). Additionally, were identified in blood samples using the same gating strategy although they investigated a BDCA1+CD142CD1a+ subset termed (Fig. 3). Although pDC have been isolated from BALF of healthy “pulmonary DC,” they did not characterize a BDCA1+CD142CD1a2 volunteers, their frequency was much lower than that of myeloid subset, which we did. For our studies, we did not want to have to DC (59). Our vigorous lavage thus may have diluted the already subjectively split AARP subsets based on nondiscrete differences small percentage of pDC below detectable limits. in the levels of expression of any markers, but rather only by Our gating strategy based on CD14 and BDCA1 expression has positivity or negativity. As we were able to separate and classify been similarly applied to human skin cells, with subsequent The Journal of Immunology 15

Table II. AARP subset-specific upregulated genes

AM CD14+ CD142 BDCA1+CD14+ Langerin+ BDCA1+CD142 ACACB KCNA3 ADAMTS2 DPP4 ANTXR1 CD207 CNKSR3 ACO1 KLHL29 AMPH FOXRED2 FLJ13224 ACP5 LGALS3BP CYP1B1 HOPX HOMER2 ALAS1 LINC00472 FCAR KIR2DL2 P2RX5 ALDH1A1 LINC00901 FCN1 LARGE SLC7A11 ALDH3A2 LOC101928716 GLT1D1 LOC284788 AMN LOC105369974 GPR27 MYLK ANOS1 LSAMP LILRA5 NR2F2 ARHGEF28 MDH1 LYVE1 OR9A1P ARV1 ME3 MCTP2 PRL ATP6AP1L MLPH OLIG1 RHOC C1QA MME PROK2 SFTPB C2 MOGAT1 RAI14 SRCIN1 CACNA1D MYO6 SERPINB2 SULF1 CAMP PAX8 TBX3 CD5L PHLDA3 TPSAB1/TPSB2 CEACAM21 PLA2G16 YWHAEP7 CES1 PNPLA3 ZNF595 CLDN7 PROS1 ZNF662 Downloaded from CORO2A PTGR1 CPE RDH10 DDO RMDN3 DEFB1 RND3 DYX1C1 S100A13 ECSCR SCCPDH EPB41L1 SCD http://www.jimmunol.org/ EPHX1 SEPT4 FABP4 SERPING1 FAM134B SLC19A3 FBXO10 SLC47A1 FHL1 SPARC FMNL2 SPOCD1 GATA3 STON1 GCHFR TFCP2L1 GPA33 TLCD2 HACD1 TPPP

HPGD TRHDE by guest on September 24, 2021 INHBA TUSC7 ITGB8 WDR49 identification of CD14+ DC and also a small population of man skin (61). Thus, our discrimination schema relating to human BDCA1+CD14+ cells (30–32, 52). The increased expression of AARP subsets is novel, and our findings are consistent with other CD1C,orBDCA1, in the DC clade (Fig. 6D) also agreed with our studies of similar cell types in human blood, skin, and lung. use of this surface marker for identification of the two BDCA1+ The finding that lung subsets are better at internalizing S. aureus DC subsets (Fig. 1A). Although we described five of the six and B. anthracis compared with E. coli (Fig. 4) is consistent with subsets as DC, our transcriptional profiling supports the work of work by others involving blood BDCA1+CD142 DC. Blood other groups (33, 49) that suggests CD14+ DC are more like BDCA1+CD142 DC phagocytose E. coli far less efficiently monocytes and Mf. This finding is also supported by histology compared with mo-DC, with only ∼25% positive for E. coli after (Fig. 1A), which showed CD14+ DC possessed a bilobed nucleus 1 h of incubation at a 50:1 MOI (62). Conversely, this DC subset is characteristically seen in human blood monocytes (60). Future ∼60% positive for S. aureus under similar culture conditions (63). work could compare transcriptional profiles of our CD14+ DC to The differences we observed likely relate to the varying mecha- profiles of CD14+ blood monocytes, as has been conducted with nisms of internalization for the three bacteria tested. Whereas CD14+ DC from human skin (33). Baharom et al. (34) have re- E. coli and S. aureus are predominantly extracellular pathogens, cently identified subsets of CD14+CD162 classical monocytes and B. anthracis spore internalization by phagocytes is thought to be CD14+CD16+ intermediate monocytes from BAL of healthy vol- required for germination in the lung (64, 65). Surface expression unteers. Both of these subsets were CD2062 (34), and our CD14+ of TLR-2 and, especially, TLR-4 is low on AM (66) and BDCA1+ DC also showed low relative mRNA expression of this marker CD142 blood DC (62) without stimulation, which agrees with our (Fig. 7). Our CD14+ DC are therefore likely to encompass both results if TLR-2 and, particularly, TLR-4 are major pattern rec- subsets of “tissue monocytes” found by Baharom et al. (34), and ognition receptors for E. coli internalization. Indeed, CD14+, they could be split further if we were to perform additional BDCA1+CD14+, and BDCA1+CD142 DC express comparably staining for surface CD206 and CD16. The functional importance elevated mRNA levels of TLR2, whereas AM and CD14+ DC of BDCA1+CD14+ DC has not been previously investigated in express higher levels of TLR4 (Fig. 7). These results suggest that human skin or lung, although upregulation of IL-17A signaling increasing E. coli internalization by these three subsets would pathways by this subset (Table I) indicates an area of future re- occur if longer time points had been examined. S. aureus recog- search. Finally, we propose that the CD142 DC we investigated, nition and subsequent uptake by phagocytes likely favors TLR-2, excluding a likely minor BDCA3hiCLEC9AhiXCR1+ subset, could possibly in combination with CD36 sensing of S. aureus diac- be equivalent to CD142CD1a2 cells previously observed in hu- ylglycerides (67, 68). We did observe CD36 mRNA to be elevated 16 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES in AM and CD14+ DC, which could partially explain the com- contributes to the differences we observed by flow cytometric PI paratively higher S. aureus internalization by these two subsets. In values. We can already infer that AM and CD14+ DC are more human dermis, a subset of CD14+ cells has been shown to express efficient at particle internalization (Fig. 4) compared with members TLR-2 without stimulation, whereas a second subset does not of the DC clade because they are slower to initiate maturation (29). The equivalent subsets in human airways are likely CD14+ pathways. Kiama et al. (78) have observed that immature mo-DC and BDCA1+CD14+ DC, respectively. B. anthracis spore inter- possess a much greater phagocytic potential of polystyrene beads nalization focuses on the integrin heterodimer CR3 (CD11b/CD18) compared with LPS-matured mo-DC, and that these mature mo-DC on the surface of phagocytes interacting with the spore surface were equally weak at phagocytosis compared with AM and blood protein BclA (69). Strength of internalization is further increased by monocytes. Thus, our AM, which were consistently highest in their inside-out signaling mediated by surface CD14 expression (70), and flow cytometric PI values (Fig. 4), were likely most efficient at also by the activation of complement components C1q and C3 (71). internalization/acidification but also slowest in their triggering of Future studies could focus on mRNA levels of pathogen-sensing maturation. Our observations of minimal CD83 and CD86 upregu- receptors similar to those we examined (Fig. 7), but after bacterial lation by AM and CD14+ DC (Fig. 5) suggest that these two subsets exposure. remain in an immature state longer, allowing uninhibited phagocy- The system we used, labeling bacteria with a pH-sensitive dye, tosis of bacterial particles compared with the quick-to-mature DC eliminates the measurement of particles that are only bound to the clade members. AARP surface but not internalized (72). However, it also intro- The upregulation of CD83, CD86, and CCR7 with time in culture duces the possibility that we collectively measured efficiency of was prominent in the DC clade but weak in the Mf clade (Fig. 5). internalization and acidification. Theoretically, a phagocyte con- These results were supported by increased mRNA expression of Downloaded from taining one highly acidified particle could contribute an equivalent these three molecules in the DC clade relative to the Mf clade fluorescence value as a cell with three internalized particles (Fig. 7), and they agree with studies that show dermal Mf and acidified to a lesser degree. Manual counting of internalized CD14+ DC do not express CCR7, even after stimulation, whereas S. aureus by confocal microscopy (Fig. 4C) supports this possi- dermal BDCA1+CD142 DC do (33). Such natural clade differences bility, as CD14+ DC showed slightly higher average PI values may be beneficial in minimizing the magnitude of potential proin-

compared with AM, as opposed to the opposite observation using flammatory responses in human airways. Anatomically, Mf clade http://www.jimmunol.org/ flow cytometry. CD14+ DC may in fact be better at phagocytosis members likely have temporal and spatial advantages of acquiring compared with AM (Fig. 4C, middle), at least of S. aureus par- inhaled particulates over DC clade members, due to their greater ticles, but AM surpass CD14+ DC in their acidification efficiency numbers along alveoli (Fig. 1A, 1B). This suggests that the Mf clade (based on time and level of acidification). Mf are generally ac- can “soak up” most inhaled particles without phagocyte activation. If cepted as poor APC that rapidly acidify phagosomes and totally particle overflow occurs due to Mf clade saturation, DC clade proteolytically degrade ingested material via lysosomal fusion. members are then exposed, but to relatively few particles. Lower DC are inefficient at phagosomal acidification and proteolytic exposure allows the DC clade to then upregulate CD83, CD86, and degradation, thus producing immunogenic peptides of lengths CCR7 in a controlled manner and initiate highly regulated immune suitable for Ag loading and presentation (73). In fact, DC may responses (which would not occur if exposure occurred quickly at by guest on September 24, 2021 actively slow acidification of phagosomes through recruitment of extremely high dosages). Such sequestration of Ags has been shown the NADPH oxidase NOX2 and subsequent production of reactive to take place in a rat model of bacterial inhalation (79), and we oxygen species (74). Members of the DC clade we propose suggest the same order of events occurs in human airways. (Fig. 6D) may be fair at internalization of the tested particles but In human dermis, a lesser subset of CD14+ cells has been shown be poor at acidification following early phagosome formation, as to naturally express CD83, but also to have decreased TLR-2 has been shown to occur at the lysosomal level within immature levels (29). We contend that BDCA1+CD14+ DC are the airway DC (75). In Mf, immediately after phagosome formation, endo- equivalent of these CD83+CD14+TLR-2lo dermal cells, whereas somal fusion leads to insertion of vacuolar H(+)-ATPases into the CD14+ DC are equivalent to CD832CD14+TLR-2med dermal cells phagosomal membrane. Activity of the V-ATPase increases with a higher capacity for TLR-2–dependent bacterial internali- sharply early after internalization of bacteria by Mf, thereby zation. Surface levels of CD83 and CD86 on BDCA1+CD142 DC dropping phagosomal pH from physiological 7.4 to below 6.0 from blood are known to increase in response to S. aureus expo- within 20 min (76, 77). The close transcriptional relationship we sure, but after 12 h of coincubation (63). identified between AM and CD14+ DC (Fig. 6) may relate in part Our transcriptional profiling suggests that lung AARP subsets to their higher efficiency of phagosomal acidification. The ex- can be grouped into Mf and DC clades, but that immature or ception to the Mf versus DC clade separation based on acidifi- mature mo-DC and mo-Mf are poor models for both clades. cation would be CD142 DC, which relate to AM and CD14+ DC, Comparing relative mRNA expression of the chemokine receptors yet show poor ability to internalize and acidify bacteria (Fig. 4A, CCR6 and CX3CR1 provides specific examples of genes that are 4B). One possibility is that CD142 DC are not specialized for highly expressed by the DC clade compared with both the Mf internalization at all, and that BDCA3hiCLEC9AhiCD142 DC clade and monocyte-derived phagocytes (Fig. 7) (80). The tyrosine within this population are responsible for the low levels of inter- kinase FLT3 is also specifically elevated in the DC clade, which nalization seen. We observed a large separation between CD142 DC agrees with work by Waskow et al. (50) that highlights its im- and the other two members of the Mf clade along PC2 of our PCA portance in murine peripheral DC development. Others have (Fig. 6A), which could represent the variable of internalization/ shown that mo-DC differ considerably from lymph node–resident acidification. Supporting the idea of variations in acidification po- DC at the transcriptional level (81), whereas more recent work has tential between subsets is the observation that resting CD14+ DC grouped these in vitro cells closely with human inflammatory DC and, especially, AM express higher mRNA levels of the lysosomal that drive a Th17 response (82). Pathways upregulated specifically LAMP1 and LAMP2 compared with the other four lung by AM, such as PXR/RXR activation and the complement system, subsets (Fig. 7). If it were practical, we would isolate enough cells of agree with human dermal studies by McGovern et al. (33) that all the AARP subsets to perform manual counts of particle inter- suggest that both pathways are upregulated in dermal Mf.The nalization, and thus determine the extent to which acidification overall close relatedness we observed between AM and CD14+ DC The Journal of Immunology 17 was also observed in comparisons of skin-equivalent subsets by The small number of specific upregulated genes identified be- this group. For example, we identified LYVE1 as a unique gene tween members of the DC clade (as opposed to the much larger with increased expression in CD14+ DC (Table II), as was seen in number of upregulated genes of all its members compared with the dermal Mf and CD14+ DC. Our identification of NR1H3 (liver Mf clade) points to the close relationships between the “true DC” X receptor a) as an upregulated gene by the Mf clade agrees with subsets (Figs. 6, 7, Table II). It may also point toward plasticity its specificity to Mf in other human tissues (33) and also provides between these DC subsets according to the constant changes oc- a potential target for modulation of Mf activity in inflammatory curring in the microenvironment of the airways. Indeed, others diseases (83). Interestingly, the BDCA1+CD14+ DC subset we have recently determined that dermal and lung Langerin+ DC can analyzed does not have a definite counterpart in the blood or skin. express BDCA1, and also that blood BDCA1+ DC can be induced We suspected that expression of CD14 by this population would to express Langerin when cultured with TGF-b (28). This cyto- mean a close transcriptional relationship with CD14+ DC. How- kine has been measured at high concentrations in human BALF ever, BDCA1+CD14+ DC actually grouped in the DC clade along (91) and is likely produced by epithelial cells along the airways with Langerin+ and BDCA1+CD142 DC (Fig. 6). A possible (92) to maintain an anti-inflammatory environment in response to functionality of BDCA1+CD14+ DC compared with the other two regularly inhaled particulates. We recognize that the stringency of true DC subsets may relate to IL-17A signaling (Table I), and our comparisons may be eliminating some genes that are indeed should be a focus of future research. BDCA1 expression alone upregulated by specific members of the DC clade in the steady- does not correlate with expression of the transcription factor IRF4, state. In our transcriptional analyses, we removed donor effects, so as IRF4 was relatively elevated in BDCA1+CD142 DC only that the DEGs identified had to be statistically upregulated in

(Fig. 7). Although IRF4 has been implicated in directing Th17 subsets of all seven donors. Had we collected samples from ad- Downloaded from immune responses by human BDCA1+CD142 DC (49), this ob- ditional donors, we may have been able to test for outlier profiles servation does not preclude the possibility that BDCA1+CD14+ and identify more subset-specific DEGs, especially for the DC DC stimulate Th17 responses through an alternate pathway that clade members. This idea is supported by our relative expression does not involve IRF4. In comparison with CD14+ DC, BDCA1+ comparisons (Fig. 7), in which certain genes such as CD1A, CD14+ DC have upregulation of pathways related to the cell cycle SIRPb1, NR1H3, XCR1, CD11C, IRF4, and IRF8 were clearly

and mitosis (Table I), and thus they may have the ability to self- elevated in one specific APC subset relative to the other five http://www.jimmunol.org/ renew in steady-state tissue, as has been suggested for LC in subsets. These genes likely did not appear in the subset-specific human skin (84, 85). Importantly, pathways upregulated by the DEG lists (Table II) because in at least one donor, they were not DC clade were functionally expected of DC, including DC mat- upregulated. In contrast, the results of Fig. 7 are not filtered by uration and lipid Ag presentation by CD1. As an example, the certain expression criteria or significance values, and thus they can chemokine receptor CX3CR1, which was uniquely upregulated by mask a single donor outlier. Comparison of the relative expression the DC clade (Fig. 6D), is also highly expressed by resident renal levels may actually be more relevant for functionally differenti- BDCA1+ DC (86). Overall, Langerin+, BDCA1+CD14+, and ating the AARP subsets, because we chose the genes to analyze BDCA1+CD142 DC are the “true DC” of the human airways that based on existing literature of DC and Mf. can be separated transcriptionally from AM, CD14+BDCA12 DC, Microenvironmental differences between sites such as the skin by guest on September 24, 2021 and CD142 BDCA12 DC of the Mf clade. and lung preclude complete overlap between gene signatures of We identified several upregulated genes in AM that relate to equivalent cell types. One avenue of future investigation would be to canonical degradation pathways (Tables I, II). These results agree identify equivalent airway subsets between humans and mice by with the notion that Mf specialize in rapid, complete proteolytic transcriptional profiling. Others have taken a similar path comparing degradation, whereas DC favor a delayed and incomplete process human blood and skin BDCA1+ and BDCA3+ DC to mouse to generate immunogenic peptides (75, 87). Other pathways up- lymphoid-resident and nonlymphoid DC subsets (44, 49, 81). We regulated specifically by AM, such as PXR/RXR activation and propose taking this a step further by comparing human airway cells the complement system, agree with recent human skin studies that to those of the mouse airways to allow microenvironmental dif- suggest that both pathways are upregulated in dermal Mf and ferences to be accounted for between species. Our identified gene CD14+ cells (33). It is no surprise that AM yielded the greatest signatures of the Mf and DC clades, along with individual subset number of DEGs compared with the other APC subsets (Table II), signatures, also provide means of further characterizing these cells as they likely self-renew in the lung tissue (88), as opposed to functionally based on protein expression of these DEGs. steady-state replenishment from circulation. In contrast, CD14+ DC, at least in the skin, have been transcriptionally classified as a Acknowledgments transient population whose precursors are blood monocytes (33, We thank the following persons from the Oklahoma Medical Research + 44). Had we further separated our CD14 DC based on CD16 Foundation for their assistance: Jacob Bass and Dr. Diana Hamilton at 2 positivity, CD14+CD16 cells may have appeared more distantly the Flow Cytometry Core Facility and Ben Fowler and Julie Crane at the related to AM than CD14+CD16+ cells. It is possible that the Imaging Core Facility. We thank Dr. Philip Hanna (University of Michigan, CD14+CD162 cells, resembling “classical monocytes” (34), reg- Ann Arbor, MI) for providing ger-null B. anthracis. We thank Dr. K. Mark ularly transit to the airways and back to draining lymph node Coggeshall for his intellectual input. without phenotypic transformation characteristic of Mf or DC. Such an occurrence has been observed in a murine model (35) and Disclosures theoretically could occur in humans as well. In contrast, a CD14+ The authors have no financial conflicts of interest. CD16+ monocytic subset in the airways may differentiate from + f CD16 interstitial M , but in the process of crossing the alveolar References epithelium lose their expression of CD206 (89, 90). Indeed, rel- 1. Krombach, F., J. T. Gerlach, C. Padovan, A. Burges, J. Behr, T. Beinert, and ative mRNA levels suggested that CD206 was highest in AM and C. Vogelmeier. 1996. Characterization and quantification of alveolar monocyte- comparatively much lower in the other five APC subsets (Fig. 7). like cells in human chronic inflammatory lung disease. Eur. Respir. J. 9: 984–991. + 2. Sertl, K., T. Takemura, E. Tschachler, V. J. Ferrans, M. A. Kaliner, and However, CD16 mRNA, although highest in our CD14 DC, was E. M. Shevach. 1986. Dendritic cells with antigen-presenting capability reside in + + 2 also relatively elevated in BDCA1 CD14 DC and CD14 DC. airway epithelium, lung parenchyma, and visceral pleura. J. Exp. Med. 163: 436–451. 18 HUMAN AIRWAY AND ALVEOLAR PHAGOCYTE PROFILES

3. Demedts, I. K., K. R. Bracke, T. Maes, G. F. Joos, and G. G. Brusselle. 2006. of mononuclear phagocytes in nondiseased human lung and lung-draining lymph Different roles for human lung dendritic cell subsets in pulmonary immune nodes. Am. J. Respir. Crit. Care Med. 193: 614–626. defense mechanisms. Am. J. Respir. Cell Mol. Biol. 35: 387–393. 28. Bigley, V., N. McGovern, P. Milne, R. Dickinson, S. Pagan, S. Cookson, 4. Gant, V. A., and A. S. Hamblin. 1985. Human bronchoalveolar macrophage M. Haniffa, and M. Collin. 2015. Langerin-expressing dendritic cells in human heterogeneity demonstrated by histochemistry, surface markers and phagocyto- tissues are related to CD1c+ dendritic cells and distinct from Langerhans cells sis. Clin. Exp. Immunol. 60: 539–545. and CD141high XCR1+ dendritic cells. J. Leukoc. Biol. 97: 627–634. 5. Cabrera-Rubio, R.,M.Garcia-Nu´n˜ez, L. Seto´,J.M.Anto´,A.Moya, 29. Angel, C. E., A. Lala, C.-J. J. Chen, S. G. Edgar, L. L. Ostrovsky, and E. Monso´, and A. Mira. 2012. Microbiome diversity in the bronchial tracts of P. R. Dunbar. 2007. CD14+ antigen-presenting cells in human dermis are less patients with chronic obstructive pulmonary disease. J. Clin. Microbiol. 50: mature than their CD1a+ counterparts. Int. Immunol. 19: 1271–1279. 3562–3568. 30. Angel, C. E., E. George, A. E. S. Brooks, L. L. Ostrovsky, T. L. H. Brown, and 6. Charlson, E. S., K. Bittinger, A. R. Haas, A. S. Fitzgerald, I. Frank, A. Yadav, P. R. Dunbar. 2006. Cutting edge: CD1a+ antigen-presenting cells in human F. D. Bushman, and R. G. Collman. 2011. Topographical continuity of bacterial dermis respond rapidly to CCR7 ligands. J. Immunol. 176: 5730–5734. populations in the healthy human respiratory tract. Am. J. Respir. Crit. Care Med. 31. Haniffa, M., F. Ginhoux, X.-N. Wang, V. Bigley, M. Abel, I. Dimmick, 184: 957–963. S. Bullock, M. Grisotto, T. Booth, P. Taub, et al. 2009. Differential rates of re- 7. Charlson, E. S., K. Bittinger, J. Chen,J.M.Diamond,H.Li,R.G.Collman,and placement of human dermal dendritic cells and macrophages during hemato- F. D. Bushman. 2012. Assessing bacterial populations in the lung by replicate poietic stem cell transplantation. J. Exp. Med. 206: 371–385. analysis of samples from the upper and lower respiratory tracts. PLoS One 7: e42786. 32. Klechevsky, E., R. Morita, M. Liu, Y. Cao, S. Coquery, L. Thompson-Snipes, 8. Dickson, R. P., J. R. Erb-Downward, H. C. Prescott, F. J. Martinez, F. Briere, D. Chaussabel, G. Zurawski, A. K. Palucka, et al. 2008. Functional J. L. Curtis, V. N. Lama, and G. B. Huffnagle. 2014. Analysis of culture- specializations of human epidermal Langerhans cells and CD14+ dermal den- dependent versus culture-independent techniques for identification of bacteria dritic cells. Immunity 29: 497–510. in clinically obtained bronchoalveolar lavage fluid. J. Clin. Microbiol. 52: 33. McGovern, N., A. Schlitzer, M. Gunawan, L. Jardine, A. Shin, E. Poyner, K. Green, 3605–3613. R. Dickinson, X.-N. Wang, D. Low, et al. 2014. Human dermal CD14+ cells are a 9. Dickson, R. P., J. R. Erb-Downward, C. M. Freeman, L. McCloskey, J. M. Beck, transient population of monocyte-derived macrophages. [Published erratum appears in G. B. Huffnagle, and J. L. Curtis. 2015. Spatial variation in the healthy human 2015 Immunity 42: 391.] Immunity 41: 465–477. lung microbiome and the adapted island model of lung biogeography. Ann. Am. 34. Baharom, F., S. Thomas, G. Rankin, R. Lepzien, J. Pourazar, A. F. Behndig, Thorac. Soc. 12: 821–830. C. Ahlm, A. Blomberg, and A. Smed-So¨rensen. 2016. Dendritic cells and Downloaded from 10. Erb-Downward, J. R., D. L. Thompson, M. K. Han, C. M. Freeman, monocytes with distinct inflammatory responses reside in lung mucosa of L. McCloskey, L. A. Schmidt, V. B. Young, G. B. Toews, J. L. Curtis, healthy humans. J. Immunol. 196: 4498–4509. B. Sundaram, et al. 2011. Analysis of the lung microbiome in the “healthy” 35. Jakubzick, C., E. L. Gautier, S. L. Gibbings, D. K. Sojka, A. Schlitzer, smoker and in COPD. PLoS One 6: e16384. T. E. Johnson, S. Ivanov, Q. Duan, S. Bala, T. Condon, et al. 2013. Minimal 11. Morris, A., J. M. Beck, P. D. Schloss, T. B. Campbell, K. Crothers, J. L. Curtis, differentiation of classical monocytes as they survey steady-state tissues and S. C. Flores, A. P. Fontenot, E. Ghedin, L. Huang, et al; Lung HIV Microbiome transport antigen to lymph nodes. Immunity 39: 599–610. Project. 2013. Comparison of the respiratory microbiome in healthy nonsmokers 36. Lewalle, P., R. Rouas, F. Lehmann, and P. Martiat. 2000. Freezing of dendritic

and smokers. Am. J. Respir. Crit. Care Med. 187: 1067–1075. cells, generated from cryopreserved leukaphereses, does not influence their http://www.jimmunol.org/ 12. Hilty, M., C. Burke, H. Pedro, P. Cardenas, A. Bush, C. Bossley, J. Davies, ability to induce antigen-specific immune responses or functionally react to A. Ervine, L. Poulter, L. Pachter, et al. 2010. Disordered microbial communities maturation stimuli. J. Immunol. Methods 240: 69–78. in asthmatic airways. PLoS One 5: e8578. 37. Lanteri, M. C., Z. Kaidarova, T. Peterson, S. Cate, B. Custer, S. Wu, 13. Adami, A. J., and J. L. Cervantes. 2015. The microbiome at the pulmonary al- M. Agapova, J. P. Law, T. Bielawny, F. Plummer, et al. 2011. Association be- veolar niche and its role in Mycobacterium tuberculosis infection. Tuberculosis tween HLA class I and class II alleles and the outcome of West Nile virus in- (Edinb.) 95: 651–658. fection: an exploratory study. PLoS One 6: e22948. 14. Bonfield, T. L., M. W. Konstan, P. Burfeind, J. R. Panuska, J. B. Hilliard, and 38. Chakrabarty, K., W. Wu, J. L. Booth, E. S. Duggan, N. N. Nagle, M. Berger. 1995. Normal bronchial epithelial cells constitutively produce the K. M. Coggeshall, and J. P. Metcalf. 2007. Human lung innate immune response anti-inflammatory cytokine interleukin-10, which is downregulated in cystic fi- to Bacillus anthracis spore infection. Infect. Immun. 75: 3729–3738. brosis. Am. J. Respir. Cell Mol. Biol. 13: 257–261. 39. Johar, A. S., C. Mastronardi, A. Rojas-Villarraga, H. R. Patel, A. Chuah, 15. Mayer, A. K., H. Bartz, F. Fey, L. M. Schmidt, and A. H. Dalpke. 2008. Airway K. Peng, A. Higgins, P. Milburn, S. Palmer, M. F. Silva-Lara, et al. 2015. Novel epithelial cells modify immune responses by inducing an anti-inflammatory and rare functional genomic variants in multiple autoimmune syndrome and by guest on September 24, 2021 microenvironment. Eur. J. Immunol. 38: 1689–1699. Sjo¨gren’s syndrome. J. Transl. Med. 13: 173. 16. Cochand, L., P. Isler, F. Songeon, and L. P. Nicod. 1999. Human lung dendritic 40. Long, A. E., K. M. Gillespie, R. J. Aitken, J. C. Goode, P. J. Bingley, and cells have an immature phenotype with efficient mannose receptors. Am. J. A. J. K. Williams. 2013. Humoral responses to islet antigen-2 and zinc trans- Respir. Cell Mol. Biol. 21: 547–554. porter 8 are attenuated in patients carrying HLA-A*24 alleles at the onset of type 17. Nicod, L. P., M. F. Lipscomb, J. C. Weissler, and G. B. Toews. 1989. Mono- 1 diabetes. Diabetes 62: 2067–2071. nuclear cells from human lung parenchyma support antigen-induced 41. O’Hanlon, T. P., D. M. Carrick, I. N. Targoff, F. C. Arnett, J. D. Reveille, T lymphocyte proliferation. J. Leukoc. Biol. 45: 336–344. M. Carrington, X. Gao, C. V. Oddis, P. A. Morel, J. D. Malley, et al. 2006. 18. Demedts, I. K., G. G. Brusselle, K. Y. Vermaelen, and R. A. Pauwels. 2005. Immunogenetic risk and protective factors for the idiopathic inflammatory my- Identification and characterization of human pulmonary dendritic cells. Am. J. opathies: distinct HLA-A, -B, -Cw, -DRB1, and -DQA1 allelic profiles distin- Respir. Cell Mol. Biol. 32: 177–184. guish European American patients with different myositis autoantibodies. 19. Masten, B. J., G. K. Olson, C. A. Tarleton, C. Rund, M. Schuyler, Medicine (Baltimore) 85: 111–127. R. Mehran, T. Archibeque, and M. F. Lipscomb. 2006. Characterization of 42. Sveinbjornsson, G., D. F. Gudbjartsson, B. V. Halldorsson, K. G. Kristinsson, myeloid and plasmacytoid dendritic cells in human lung. J. Immunol. 177: M. Gottfredsson, J. C. Barrett, L. J. Gudmundsson, K. Blondal, A. Gylfason, 7784–7793. S. A. Gudjonsson, et al. 2016. HLA class II sequence variants influence tuber- 20. Todate, A., K. Chida, T. Suda, S. Imokawa, J. Sato, K. Ide, T. Tsuchiya, N. Inui, culosis risk in populations of European ancestry. Nat. Genet. 48: 318–322. Y. Nakamura, K. Asada, et al. 2000. Increased numbers of dendritic cells in the 43. Jongbloed, S. L., A. J. Kassianos, K. J. McDonald, G. J. Clark, X. Ju, C. E. Angel, bronchiolar tissues of diffuse panbronchiolitis. Am. J. Respir. Crit. Care Med. C.-J. J. Chen, P. R. Dunbar, R. B. Wadley, V. Jeet, et al. 2010. Human CD141+ 162: 148–153. (BDCA-3)+ dendritic cells (DCs) represent a unique myeloid DC subset that cross- 21. Veres, T. Z., S. Rochlitzer, M. Shevchenko, B. Fuchs, F. Prenzler, C. Nassenstein, presents necrotic cell antigens. J. Exp. Med. 207: 1247–1260. A. Fischer, L. Welker, O. Holz, M. Muller,€ et al. 2007. Spatial interactions be- 44. Haniffa, M., A. Shin, V. Bigley, N. McGovern, P. Teo, P. See, P. S. Wasan, tween dendritic cells and sensory nerves in allergic airway inflammation. Am. J. X.-N. Wang, F. Malinarich, B. Malleret, et al. 2012. Human tissues contain Respir. Cell Mol. Biol. 37: 553–561. CD141hi cross-presenting dendritic cells with functional homology to mouse 22. Bratke, K., M. Lommatzsch, P. Julius, M. Kuepper, H.-D. Kleine, W. Luttmann, CD103+ nonlymphoid dendritic cells. Immunity 37: 60–73. and J. Christian Virchow. 2007. Dendritic cell subsets in human bronchoalveolar 45. Huysamen, C., J. A. Willment, K. M. Dennehy, and G. D. Brown. 2008. lavage fluid after segmental allergen challenge. Thorax 62: 168–175. CLEC9A is a novel activation C-type lectin-like receptor expressed on BDCA3+ 23. Ten Berge, B., F. Muskens, A. Kleinjan, H. Hammad, H. C. Hoogsteden, dendritic cells and a subset of monocytes. J. Biol. Chem. 283: 16693–16701. B. N. Lambrecht, and B. Van den Blink. 2009. A novel method for isolating 46. Sancho, D., O. P. Joffre, A. M. Keller, N. C. Rogers, D. Martı´nez, P. Hernanz-Falco´n, dendritic cells from human bronchoalveolar lavage fluid. J. Immunol. Methods I. Rosewell, and C. Reis e Sousa. 2009. Identification of a dendritic cell receptor that 351: 13–23. couples sensing of necrosis to immunity. Nature 458: 899–903. 24. Tsoumakidou, M., N. Tzanakis, H. A. Papadaki, H. Koutala, and N. M. Siafakas. 47. MacDonald, K. P. A., D. J. Munster, G. J. Clark, A. Dzionek, J. Schmitz, and 2006. Isolation of myeloid and plasmacytoid dendritic cells from human bron- D. N. J. Hart. 2002. Characterization of human blood dendritic cell subsets. choalveolar lavage fluid. Immunol. Cell Biol. 84: 267–273. Blood 100: 4512–4520. 25. van Haarst, J. M., H. C. Hoogsteden, H. J. de Wit, G. T. Verhoeven, 48. Tserel, L., T. Runnel, K. Kisand, M. Pihlap, L. Bakhoff, R. Kolde, H. Peterson, C. E. Havenith, and H. A. Drexhage. 1994. Dendritic cells and their precursors J. Vilo, P. Peterson, and A. Rebane. 2011. MicroRNA expression profiles of isolated from human bronchoalveolar lavage: immunocytologic and functional human blood monocyte-derived dendritic cells and macrophages reveal miR-511 properties. Am. J. Respir. Cell Mol. Biol. 11: 344–350. as putative positive regulator of Toll-like receptor 4. J. Biol. Chem. 286: 26487– 26. Dzionek, A., A. Fuchs, P. Schmidt, S. Cremer, M. Zysk, S. Miltenyi, D. W. Buck, 26495. and J. Schmitz. 2000. BDCA-2, BDCA-3, and BDCA-4: three markers for distinct 49. Schlitzer, A., N. McGovern, P. Teo, T. Zelante, K. Atarashi, D. Low, A. W. subsets of dendritic cells in human peripheral blood. J. Immunol. 165: 6037–6046. S. Ho, P. See, A. Shin, P. S. Wasan, et al. 2013. IRF4 transcription factor- 27. Desch, A. N., S. L. Gibbings, R. Goyal, R. Kolde, J. Bednarek, T. Bruno, dependent CD11b+ dendritic cells in human and mouse control mucosal IL-17 J. E. Slansky, J. Jacobelli, R. Mason, Y. Ito, et al. 2016. Flow cytometric analysis cytokine responses. Immunity 38: 970–983. The Journal of Immunology 19

50. Waskow, C., K. Liu, G. Darrasse-Je`ze, P. Guermonprez, F. Ginhoux, M. Merad, 72. Neaga, A., J. Lefor, K. E. Lich, S. F. Liparoto, and Y. Q. Xiao. 2013. Devel- T. Shengelia, K. Yao, and M. Nussenzweig. 2008. The receptor tyrosine kinase opment and validation of a flow cytometric method to evaluate phagocytosis of Flt3 is required for dendritic cell development in peripheral lymphoid tissues. pHrodo™ BioParticlesÒ by granulocytes in multiple species. J. Immunol. Nat. Immunol. 9: 676–683. Methods 390: 9–17. 51. Tomlinson, G. S., H. Booth, S. J. Petit, E. Potton, G. J. Towers, R. F. Miller, 73. Lennon-Dume´nil, A.-M., A. H. Bakker, R. Maehr, E. Fiebiger, H. S. Overkleeft, B. M. Chain, and M. Noursadeghi. 2012. Adherent human alveolar macrophages M. Rosemblatt, H. L. Ploegh, and C. Lagaudrie`re-Gesbert. 2002. Analysis of exhibit a transient pro-inflammatory profile that confounds responses to innate protease activity in live antigen-presenting cells shows regulation of the phag- immune stimulation. PLoS One 7: e40348. osomal proteolytic contents during dendritic cell activation. J. Exp. Med. 196: 52. Nestle, F. O., X. G. Zheng, C. B. Thompson, L. A. Turka, and B. J. Nickoloff. 529–540. 1993. Characterization of dermal dendritic cells obtained from normal human 74. Jancic, C., A. Savina, C. Wasmeier, T. Tolmachova, J. El-Benna, P. M.-C. Dang, skin reveals phenotypic and functionally distinctive subsets. J. Immunol. 151: S. Pascolo, M.-A. Gougerot-Pocidalo, G. Raposo, M. C. Seabra, and 6535–6545. S. Amigorena. 2007. Rab27a regulates phagosomal pH and NADPH oxidase 53. Lenz, A., M. Heine, G. Schuler, and N. Romani. 1993. Human and murine recruitment to dendritic cell phagosomes. Nat. Cell Biol. 9: 367–378. dermis contain dendritic cells. Isolation by means of a novel method and phe- 75. Trombetta, E. S., M. Ebersold, W. Garrett, M. Pypaert, and I. Mellman. 2003. notypical and functional characterization. J. Clin. Invest. 92: 2587–2596. Activation of lysosomal function during dendritic cell maturation. Science 299: 54. Crozat, K., R. Guiton, V. Contreras, V. Feuillet, C.-A. Dutertre, E. Ventre, T.-P. Vu 1400–1403. Manh, T. Baranek, A. K. Storset, J. Marvel, et al. 2010. The XC chemokine re- 76. Lukacs, G. L., O. D. Rotstein, and S. Grinstein. 1991. Determinants of the phag- ceptor 1 is a conserved selective marker of mammalian cells homologous to mouse osomal pH in macrophages. In situ assessment of vacuolar H(+)-ATPase activity, CD8a+ dendritic cells. J. Exp. Med. 207: 1283–1292. counterion conductance, and H+ “leak”. J. Biol. Chem. 266: 24540–24548. 55. Bachem, A., S. Guttler,€ E. Hartung, F. Ebstein, M. Schaefer, A. Tannert, 77. Lukacs, G. L., O. D. Rotstein, and S. Grinstein. 1990. Phagosomal acidification A. Salama, K. Movassaghi, C. Opitz, H. W. Mages, et al. 2010. Superior antigen is mediated by a vacuolar-type H(+)-ATPase in murine macrophages. J. Biol. cross-presentation and XCR1 expression define human CD11c+CD141+ cells as Chem. 265: 21099–21107. homologues of mouse CD8+ dendritic cells. J. Exp. Med. 207: 1273–1281. 78. Kiama, S. G., L. Cochand, L. Karlsson, L. P. Nicod, and P. Gehr. 2001. Eval- 56. Crozat, K., R. Guiton, M. Guilliams, S. Henri, T. Baranek, I. Schwartz-Cornil, uation of phagocytic activity in human monocyte-derived dendritic cells. B. Malissen, and M. Dalod. 2010. Comparative genomics as a tool to reveal J. Aerosol Med. 14: 289–299. functional equivalences between human and mouse dendritic cell subsets. 79. MacLean, J. A., W. Xia, C. E. Pinto, L. Zhao, H. W. Liu, and R. L. Kradin. 1996. Downloaded from Immunol. Rev. 234: 177–198. Sequestration of inhaled particulate antigens by lung phagocytes. A mechanism 57. Salem, S., D. Langlais, F. Lefebvre, G. Bourque, V. Bigley, M. Haniffa, for the effective inhibition of pulmonary cell-mediated immunity. Am. J. Pathol. J.-L. Casanova, D. Burk, A. Berghuis, K. M. Butler, et al. 2014. Func- 148: 657–666. tional characterization of the human dendritic cell immunodeficiency associated 80. Greaves, D. R., W. Wang, D. J. Dairaghi, M. C. Dieu, B. Saint-Vis, K. Franz- with the IRF8(K108E) mutation. Blood 124: 1894–1904. Bacon, D. Rossi, C. Caux, T. McClanahan, S. Gordon, et al. 1997. CCR6, a CC 58. Cox, K., M. North, M. Burke, H. Singhal, S. Renton, N. Aqel, S. Islam, and chemokine receptor that interacts with macrophage inflammatory protein 3a and S. C. Knight. 2005. Plasmacytoid dendritic cells (PDC) are the major DC subset is highly expressed in human dendritic cells. J. Exp. Med. 186: 837–844.

innately producing cytokines in human lymph nodes. J. Leukoc. Biol. 78: 1142–1152. 81. Robbins, S. H., T. Walzer, D. Dembe´le´, C. Thibault, A. Defays, G. Bessou, http://www.jimmunol.org/ 59. Ten Berge, B., A. Kleinjan, F. Muskens, H. Hammad, H. C. Hoogsteden, H. Xu, E. Vivier, M. Sellars, P. Pierre, et al. 2008. Novel insights into the re- R. W. Hendriks, B. N. Lambrecht, and B. Van den Blink. 2012. Evidence for lationships between dendritic cell subsets in human and mouse revealed by local dendritic cell activation in pulmonary sarcoidosis. Respir. Res. 13: 33. genome-wide expression profiling. Genome Biol. 9: R17. 60. Geissmann, F., S. Jung, and D. R. Littman. 2003. Blood monocytes consist of 82. Segura, E., M. Touzot, A. Bohineust, A. Cappuccio, G. Chiocchia, A. Hosmalin, two principal subsets with distinct migratory properties. Immunity 19: 71–82. M. Dalod, V. Soumelis, and S. Amigorena. 2013. Human inflammatory dendritic 61. Segura, E., J. Valladeau-Guilemond, M.-H. Donnadieu, X. Sastre-Garau, cells induce Th17 cell differentiation. Immunity 38: 336–348. V. Soumelis, and S. Amigorena. 2012. Characterization of resident and migra- 83. Asquith, D. L., L. E. Ballantine, J. S. Nijjar, M. K. Makdasy, S. Patel, tory dendritic cells in human lymph nodes. J. Exp. Med. 209: 653–660. P. B. Wright, J. H. Reilly, S. Kerr, M. Kurowska-Stolarska, J. A. Gracie, and 62. Kassianos, A. J., M. Y. Hardy, X. Ju, D. Vijayan, Y. Ding, A. J. E. Vulink, I. B. McInnes. 2013. The liver X receptor pathway is highly upregulated in K. J. McDonald, S. L. Jongbloed, R. B. Wadley, C. Wells, et al. 2012. Human rheumatoid arthritis synovial macrophages and potentiates TLR-driven cytokine CD1c (BDCA-1)+ myeloid dendritic cells secrete IL-10 and display an immuno- release. Ann. Rheum. Dis. 72: 2024–2031.

regulatory phenotype and function in response to Escherichia coli. Eur. J. 84. Bigley, V., M. Haniffa, S. Doulatov, X.-N. Wang, R. Dickinson, N. McGovern, by guest on September 24, 2021 Immunol. 42: 1512–1522. L. Jardine, S. Pagan, I. Dimmick, I. Chua, et al. 2011. The human syndrome of 63. Jin, J.-O., W. Zhang, J.-Y. Du, and Q. Yu. 2014. BDCA1-positive dendritic cells dendritic cell, monocyte, B and NK lymphoid deficiency. J. Exp. Med. 208: 227–234. (DCs) represent a unique human myeloid DC subset that induces innate and 85. Kanitakis, J., E. Morelon, P. Petruzzo, L. Badet, and J.-M. Dubernard. 2011. adaptive immune responses to Staphylococcus aureus infection. Infect. Immun. Self-renewal capacity of human epidermal Langerhans cells: observations made 82: 4466–4476. on a composite tissue allograft. Exp. Dermatol. 20: 145–146. 64. Brittingham, K. C., G. Ruthel, R. G. Panchal, C. L. Fuller, W. J. Ribot, 86. Kassianos, A. J., X. Wang, S. Sampangi, S. Afrin, R. Wilkinson, and H. Healy. T. A. Hoover, H. A. Young, A. O. Anderson, and S. Bavari. 2005. Dendritic cells 2015. Fractalkine-CX3CR1-dependent recruitment and retention of human endocytose Bacillus anthracis spores: implications for anthrax pathogenesis. CD1c+ myeloid dendritic cells by in vitro-activated proximal tubular epithelial J. Immunol. 174: 5545–5552. cells. Kidney Int. 87: 1153–1163. 65. Guidi-Rontani, C., M. Weber-Levy, E. Labruye`re, and M. Mock. 1999. Germi- 87. Delamarre, L., M. Pack, H. Chang, I. Mellman, and E. S. Trombetta. 2005. nation of Bacillus anthracis spores within alveolar macrophages. Mol. Micro- Differential lysosomal proteolysis in antigen-presenting cells determines antigen biol. 31: 9–17. fate. Science 307: 1630–1634. 66. Juarez, E., C. Nun˜ez, E. Sada, J. J. Ellner, S. K. Schwander, and M. Torres. 2010. 88. Hashimoto, D., A. Chow, C. Noizat, P. Teo, M. B. Beasley, M. Leboeuf, Differential expression of Toll-like receptors on human alveolar macrophages C. D. Becker, P. See, J. Price, D. Lucas, et al. 2013. Tissue-resident macrophages and autologous peripheral monocytes. Respir. Res. 11: 2. self-maintain locally throughout adult life with minimal contribution from cir- 67. Hoebe, K., P. Georgel, S. Rutschmann, X. Du, S. Mudd, K. Crozat, S. Sovath, culating monocytes. Immunity 38: 792–804. L. Shamel, T. Hartung, U. Za¨hringer, and B. Beutler. 2005. CD36 is a sensor of 89. Yu, Y.-R. A., D. F. Hotten, Y. Malakhau, E. Volker, A. J. Ghio, P. W. Noble, diacylglycerides. Nature 433: 523–527. M. Kraft, J. W. Hollingsworth, M. D. Gunn, and R. M. Tighe. 2016. Flow 68. Takeuchi, O., K. Hoshino, and S. Akira. 2000. Cutting edge: TLR2-deficient and cytometric analysis of myeloid cells in human blood, bronchoalveolar lavage, MyD88-deficient mice are highly susceptible to Staphylococcus aureus infec- and lung tissues. Am. J. Respir. Cell Mol. Biol. 54: 13–24. tion. J. Immunol. 165: 5392–5396. 90. Bharat, A., S. M. Bhorade, L. Morales-Nebreda, A. C. McQuattie-Pimentel, 69. Oliva, C. R., M. K. Swiecki, C. E. Griguer, M. W. Lisanby, D. C. Bullard, S. Soberanes, K. Ridge, M. M. DeCamp, K. K. Mestan, H. Perlman, G. R. C. L. Turnbough, Jr., and J. F. Kearney. 2008. The integrin Mac-1 (CR3) me- S. Budinger, and A. V. Misharin. 2016. Flow cytometry reveals similarities between diates internalization and directs Bacillus anthracis spores into professional lung macrophages in humans and mice. Am. J. Respir. Cell Mol. Biol. 54: 147–149. phagocytes. Proc. Natl. Acad. Sci. USA 105: 1261–1266. 91.Yamauchi,K.,Y.Martinet,P.Basset,G.A.Fells,andR.G.Crystal.1988. 70. Oliva, C., C. L. Turnbough, Jr., and J. F. Kearney. 2009. CD14-Mac-1 interac- High levels of transforming growth factor-b are present in the epithelial lining tions in Bacillus anthracis spore internalization by macrophages. Proc. Natl. fluid of the normal human lower respiratory tract. Am. Rev. Respir. Dis. 137: Acad. Sci. USA 106: 13957–13962. 1360–1363. 71. Gu, C., S. A. Jenkins, Q. Xue, and Y. Xu. 2012. Activation of the classical 92. Magnan, A., I. Frachon, B. Rain, M. Peuchmaur, G. Monti, B. Lenot, M. Fattal, complement pathway by Bacillus anthracis is the primary mechanism for spore G. Simonneau, P. Galanaud, and D. Emilie. 1994. Transforming growth factor phagocytosis and involves the spore surface protein BclA. J. Immunol. 188: beta in normal human lung: preferential location in bronchial epithelial cells. 4421–4431. Thorax 49: 789–792. Supplemental Data

Supplemental Table I. Lung Cell Donor Demographics

Lung Donor Demographics Donor Peak Final Chest X-Ray # Age Gender PaO2/FiO2 PaO2/FiO2 Results Smoking History Normal except for scattered areas of nodularity within 1 29 Male 438.0 438.0 Never smoked. right lung suggestive of bronchiolitis. Normal except for right basilar atelectasis or infiltrate. Ex-smoker for 13 yrs. 2 68 Female 341.0 320.0 Prior <1 ppd for 39 yrs. Normal except for stable left basilar infiltrate with Never smoked. 3 57 Male 540.3 382.5 layering pleural effusion and stable right mild basilar

infiltrate. Normal except for stable right pleural effusion and Ex-smoker for 11 yrs. 4 35 Male 363.0 261.7 volume loss in right lung base. Prior 2 cpd for 7 yrs. Normal except for persistent pneumomediastinum, and Ex-smoker for 5 yrs. 5 52 Female 244.0 138.6 persistent soft tissue gas in the neck and left chest wall. Prior 1 ppw for 16 yrs. Normal except for mild bilateral parahilar and basilar Ex-smoker for 16 yrs. 6 34 Male 329.0 321.0 infiltrates. Prior 0.5 ppd for 4 yrs. Normal except for increasing retro cardiac density, 7 48 Male 344.0 242.5 blunting in the region of the left costophrenic angle, and Never smoked. exclusion of the right costophrenic angle. Lung Donor Cell Yields and HLA Types Donor HLA Class I-Type HLA Class II-Type Cell Yield # A B C DRB1 DRA DQB1 DQA1 DPB1 DPA1 02:01 44:03 03:03 15:03 01:01 05:02 01:02 04:02G 02:02 1 5.62 x 109 68:02 58:02 06:02 16:02 01:01 06:02 01:02 85:01G 03:01 11:01 40:02 02:02 13:01 01:01 06:03 01:03 01:01G 02:01 2 4.08 x 109 32:01 51:01 07:01 13:01 01:01 06:03 01:03 05:01G 02:02 29:02 53:01 04:01 13:01 01:01 06:02 01:02 01:01G 01:03 3 4.61 x 109 33:03 78:01 16:01 15:03 01:01 06:04 01:03 04:02G 02:02 02:01 18:01 02:02 01:02 01:01 05:01 01:01 01:01G 02:01 4 6.02 x 109 36:01 53:01 04:01 11:01 01:01 06:02 01:02 17:01G 02:02 01:01 13:02 06:02 07:01 01:01 02:02 02:01 02:01G 01:03 5 3.36 x 109 68:01 44:02 07:04 11:01 01:01 03:01 05:05 03:01G 01:03 02:01 07:02 04:01 13:01 01:01 06:02 01:02 02:01G 01:03 6 7.30 x 109 02:01 35:01 07:02 15:01 01:01 06:09 01:02 04:01G 01:03 01:01 08:01 04:01 03:01 01:01 02:01 01:02 04:01G 01:03 7 7.01 x 109 02:01 35:01 07:01 15:01 01:01 06:02 05:01 04:02G 01:03 Bronchoscopy Volunteer Demographics Donor # Age Gender Smoking History Cell Yield 1 28 Male Never smoked 17.60 x 106 2 34 Female Ex-smoker for 5 yrs. Prior 5 cpd for 15 yrs. 24.96 x 106 3 26 Male Never smoked 5.26 x 106 4 39 Female Never smoked 3.56 x 106 5 30 Female Ex-smoker for 7 yrs. Prior 1 ppw for 5 yrs. 3.52 x 106 6 21 Male Never smoked 8.27 x 106 a PaO2/FiO2 = partial pressure arterial oxygen / fraction of inspired oxygen. b ppd, ppw, cpd = packs per day, packs per week, cigarettes per day. c HLA, human leukocyte antigen. d G in DPB1 column indicates only typing of exon 2 was performed.

Supplemental Table II. Antibodies and viability dyes used for FACS and flow cytometry

General Assay Lung Microscopy Functional Monocyte- Lung & Marker Dye Clone Company Live Sorting Lung FC derived Blood Sorting Analyses Cells Cell ID Viability Zombie n/a BioLegend - + + - + Aqua Viability Propidium n/a BioLegend + - - + - Iodide CD3 PE-Cy5 HIT3a BioLegend + + + - + CD19 PE-Cy5 HIB19 BioLegend + + + - + CD20 PE-Cy5 2H7 BioLegend + + + - + CD56 PE-Cy5 HCD56 BioLegend + + + - + HLA-DR Pacific L243 BioLegend + + + - + Blue CD11c PE-Cy7 3.9 BioLegend + + + - + Langerin APC 10E2 BioLegend + + + - + CD14 AF700 HCD14 BioLegend + + + + + BDCA1 PE L161 BioLegend + - - - + BDCA1 PerCP- L161 BioLegend - + + - - Cy5.5 BDCA3 PerCP- M80 BioLegend - - - - + Cy5.5 BDCA3 BV605 M80 BioLegend - - - - + CLEC9A PE 8F9 BioLegend - - - - + CD123 BV605 6H6 BioLegend - - - - + CD83 PE HB15e BioLegend - - + + - CD86 PE-Cy5 IT2.2 BioLegend - - - + - CD86 BV605 IT2.2 BioLegend - - + - - CCR7 APC-Cy7 G043H7 BioLegend - - + - - DC- FITC 9E9A8 BioLegend - - - + - SIGN CD1a APC-Cy7 HI149 BioLegend - - - + + CD80 APC 2D10 BioLegend - - - + -

Supplemental Figure 1. Distinct populations of monocyte-derived DC and MΦ can be generated, which increase in their expression of standard activation and maturation markers upon exposure to LPS. (A) Flow cytometry of monocytes purified from freshly isolated buffy coats and exposed to either GM-CSF alone, or GM-CSF and IL-4 for 6 days in culture. Plots represent gating strategy used to identify and sort monocyte-derived DC (mo-DC) and MΦ (mo-MΦ) on day 6 post culture. After initial exclusion of dead cells, mo-DC were identified as DC-SIGN+ CD14- cells, while mo-MΦ were identified as DC-SIGN- CD14+ cells. Representative plots from treated monocytes from 6 different blood donors are shown. (B-E) Flow cytometry of mo-DC and mo-MΦ sorted at day 6 post-culture (immature, blue) or at day 9 post- culture following 3 days of LPS exposure (mature, red). Flow cytometry plots are representative of 6 sets of mo-DC and mo-MΦ from different blood donors, and are compared to isotype controls (gray) for the surface markers indicated. Right: Composite graphs with mean + SEM of median fluorescence intensities of the markers indicated from 6 sets of donor monocytes. *p ≤ 0.05, One- tailed Wilcoxon matched-pairs signed test. (B) MFI of CD1a. (C) MFI of CD80. (D) MFI of CD86. (E) MFI of CD83.

Cell-to-cell DEGs Supplemental Figure 2. Closely-related subsets within the MΦ and DC clades can be separated by upregulated DEGs. 246 DEG Numbers of upregulated DEGs between specific pairwise comparisons of lung APC subsets. Comparisons include members from within the AM CD14+ MΦ (blue and blue arrows) and DC (red and red arrows) clades and between the two clades. DEGs were used for pathway analyses represented in 251 DEG Table I.

1367 DEG

AM BDCA1+ CD14-

1346 DEG

84 DEG

CD14+ BDCA1+ CD14+

312 DEG

16 DEG

BDCA1+ Langerin+ CD14-

5 DEG

137 DEG

BDCA1+ BDCA1+ CD14- CD14+

231 DEG

38 DEG

BDCA1+ Langerin+ CD14+

140 DEG