Strong Correlation Between Air-Liquid Interface Cultures and in Vivo Transcriptomics of Nasal Brush Biopsy

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Am J Physiol Lung Cell Mol Physiol 318: L1056–L1062, 2020. First published April 1, 2020; doi:10.1152/ajplung.00050.2020.

RAPID REPORT Translational Physiology

Strong correlation between air-liquid interface cultures and in vivo transcriptomics of nasal brush biopsy

X Baishakhi Ghosh,1 Bongsoo Park,1 Debarshi Bhowmik,2 Kristine Nishida,3 Molly Lauver,3 Nirupama Putcha,3 Peisong Gao,4 Murugappan Ramanathan, Jr.,5 Nadia Hansel,3 Shyam Biswal,1 and Venkataramana K. Sidhaye1,3 1Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; 2Department of Biology, Johns Hopkins University, Baltimore, Maryland; 3Department of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland; 4Division of Allergy and Clinical Immunology, Johns Hopkins School of Medicine, Baltimore, Maryland; and 5Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland Submitted 18 February 2020; accepted in ﬁnal form 24 March 2020

Ghosh B, Park B, Bhowmik D, Nishida K, Lauver M, Putcha N, RNA sequencing to determine the correlation between ALI- Gao P, Ramanathan M Jr, Hansel N, Biswal S, Sidhaye VK. cultured epithelial cells and epithelial cells obtained from nasal Strong correlation between air-liquid interface cultures and in vivo brushing and identify differences that may arise as a result of transcriptomics of nasal brush biopsy. Am J Physiol Lung Cell Mol redifferentiation. Physiol 318: L1056–L1062, 2020. First published April 1, 2020; doi:10.1152/ajplung.00050.2020.—Air-liquid interface (ALI) cultures METHODS are ex vivo models that are used extensively to study the epithelium of patients with chronic respiratory diseases. However, the in vitro Human subjects. Five former smokers with COPD were enrolled in conditions impose a milieu different from that encountered in the the study. The research protocol was approved by the Institutional patient in vivo, and the degree to which this alters gene expression Review Board of Johns Hopkins University, and all the patients gave remains unclear. In this study we employed RNA sequencing to signed informed consent. The diagnosis of COPD was established compare the transcriptome of fresh brushings of nasal epithelial cells using the Global Initiative for Chronic Obstructive Lung Disease with that of ALI-cultured epithelial cells from the same patients. We (GOLD)-2015 criteria, including Ն10-pack-yr smoking history, ratio observed a strong correlation between cells cultured at the ALI and of postbronchodilator forced expiratory volume in 1 s (FEV1)to Ͻ Ͻ cells obtained from the brushed nasal epithelia: 96% of expressed forced vital capacity 70%, and FEV1 80% predicted. Participants genes showed similar expression profiles, although there was greater were former smokers as defined by self-report of no smoking in the similarity between the brushed samples. We observed that while the last 6 mo and exhaled carbon monoxide Ͻ6 ppm. Demographic ALI model provides an excellent representation of the in vivo airway characteristics of patients with COPD are summarized in Table 1. No epithelial transcriptome for mechanistic studies, several pathways are known nasal or sinus comorbidities were observed in these patients affected by the change in milieu. with COPD. Sinonasal brushing sampling. Two samples were obtained from the air-liquid interface; cell culture; nasal brushing; nasal epithelia; inferior turbinate using a sterile cytology brush (Microvasive, Mil- transcriptome ford, MA); no topical anesthetic was used. The first brush head was ejected into a vial containing RNA stabilization reagent (RNAlater, Qiagen, MA) and stored at Ϫ80°C. The second brush head was suspended in 1ϫ Dulbecco’s phosphate-buffered saline (DPBS; BACKGROUND Thermo Fisher Scientific, CA) and immediately processed for cell culture. Air-liquid interface (ALI) cultures are ex vivo models used Culturing sinonasal epithelia at ALI. The cell suspension was extensively to study the epithelium of patients with allergies, centrifuged at 1,500 rpm for 10 min to remove 1ϫ DPBS. The pellet asthma, chronic obstructive pulmonary disease (COPD), and was resuspended in PneumaCult-Ex Plus medium (StemCell Tech- chronic rhinosinusitis (1, 3, 9, 11, 12). This model establishes nologies, Vancouver, BC, Canada) and amplified on rat tail collagen a differentiated epithelium, as seen in vivo, that is useful in I (Corning, NY)-coated flasks. Cells were passaged at 80–90% confluency. At subconfluency, cells were plated at 4 ϫ 105 per well performing mechanistic studies of respiratory epithelia, testing ␮ drug formulations, and studying the toxicity of inhaled sub- onto rat tail collagen I-coated 0.4- m-pore polyethylene terephthalate clear-membrane 12-mm-diameter Transwell inserts (Corning, NY) stances, both infectious and noninfectious, none of which can with PneumaCult-Ex Plus medium at ALI. At 100% confluency, the be performed in brushed cells. However, the in vitro conditions inserts were placed in basolateral PneumaCult-ALI medium (Stem- impose a milieu different from that encountered in the patient Cell Technologies). Cells were differentiated for 6 wk at ALI to obtain in vivo, and the degree to which this alters gene expression a fully differentiated pseudostratified epithelium. To ensure that the remains unclear. In this study we compared the transcriptome ALI cultures were fully differentiated, we confirmed that the mono- of fresh brushings of nasal epithelial cells with that of ALI- layer established a barrier as measured by transepithelial electrical cultured epithelial cells from the same patients. We employed resistance [380–600 ⍀·cm2 (average 470 ⍀·cm2)] and confirmed the presence of cilia by measuring the percentage of moving pixels [39–53% (average 45.37%)] and ciliary beat frequency [6.8–15.8 Hz Correspondence: V. K. Sidhaye ([email protected]). (average 8.95 Hz)] based on microscopy, as we reported previously

L1056 1040-0605/20 Copyright © 2020 the American Physiological Society http://www.ajplung.org Downloaded from journals.physiology.org/journal/ajplung at US EPA Main Lib (134.067.029.089) on January 7, 2021. CULTURED EPITHELIA REPRESENTS THE IN VIVO AIRWAY EPITHELIA L1057 Table 1. Demographic characteristics of recruited subjects

Patient No.

12345 Age, yr 62 68 61 79 75 Sex Female Male Female Male Female BMI, kg/m2 35.31 29.79 24.93 22.31 35.19 Postbronchodilator FVC, %predicted 84 77 59 99 79 FEV1, %predicted 36 65 36 57 58 FEV1/FVC 0.34 0.64 0.47 0.40 0.57

BMI, body mass index; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity.

(6, 7). These values are consistent with those reported by others in a few upregulated genes in brushed nasal epithelia [fatty acid-binding well-differentiated nasal epithelial culture (10, 11). protein 5 (FABP5), 2=-5=-oligoadenylate synthetase 1 (OAS1), and Total RNA preparation and sequencing. Total RNA was extracted aldehyde dehydrogenase 3 family member A1 (ALDH3A1)] and from ALI-cultured nasal epithelia and brushed nasal epithelia using cultured airway epithelia [ERBB receptor feedback inhibitor 1 (ER- the Invitrogen PureLink RNA Mini Kit (Thermo Fisher Scientific) RFI1), transglutaminase 2 (TGM2), and caveolin 1 (CAV1)]. Forward supplemented with the proteinase K (Qiagen, Germany) and RNase- primers, reverse primers, and product lengths for the genes are as free DNase set (Qiagen). follows: CTTCCCATCCCACTCCTGATG (forward), CCACAGCT- RNA quantity was assessed by VICTOR X2 fluorometry (Perkin GATGGCAGAAAA (reverse), and 83 bp for FABP1; AGGAA- Elmer, MA) using the Quant-iT RiboGreen RNA assay kit (Thermo AGGTGCTTCCGAGGTAG (forward), GGACTGAGGAAGACAA- Fisher Scientific). The integrity was checked by the Agilent Technol- CCAGGT (reverse), and 127 bp for OAS1; GGGAGAGGCTGTGT- ogies 4200 TapeStation System with an RNA integrity number Ն7. CAAAGG (forward), GCTCCGAGTGGATGTAGAGC (reverse), cDNA libraries were generated from 500 ng of total RNA using the and 334 bp for ALDH3A1; TGAGGAAGACCTACTGGAGCAG TruSeq Stranded Total RNA LT Sample Prep Kit (human/mouse/rat) (Illumina, CA). The quality of the cDNA library was assessed by (forward), GTATTAGGCGCTCCTGAGCAGA (reverse), and 111 bp Quant-iT PicoGreen dsDNA assay kit (Thermo Fisher Scientific, MA) for ERRFI1; TAAGAGATGCTGTGGAGGAG (forward), CGAGC- and D1000 screen tape analysis. CCTGGTAGATAAA (reverse), and 278 bp for TGM2; CCA- Quantitative RT-PCR. cDNA (500 ng/␮L) was obtained using a AGGAGATCGACCTGGTCAA (forward), GCCGTCAAAACTGT- high-capacity cDNA reverse transcription kit (Applied Biosystems, GTGTCCCT (reverse), and 113 bp for CAV1; and GTCTCCTCT- Thermo Fisher Scientific Baltics, Lithuania), and the absence of DNA GACTTCAACAGCG (forward), ACCACCCTGTTGCTGTAGC- contamination was verified by exclusion of RT from subsequent CAA (reverse), and 131 bp for GAPDH. PCRs. Each PCR was carried out as follows: initial denaturation at 94°C cDNA was subjected to PCR using SYBR green PCR master mix for 15 min, 45 cycles of 94°C for 35 s, 60°C for 1 min, and 72°C for (Applied Biosystems, Thermo Fisher Scientific, UK) to amplify the 1 min 15 s, followed by a final extension at 72°C for 2 min. Based on

Fig. 1. Overall gene expression of nasal brushing (NBR) and cultured nasal epithelial (CU) samples. A and B: pair-wise sample (A) and pooled (B) correlation analysis using Pearson’s correlation analysis and log2-transformed count per million reads (CPM) between CU and NBR. C: principal component (PC) analysis of nasal brushing and cultured nasal epithelial cell samples using all genes expressed. Genes that were not expressed in all 5 samples were excluded. P Ͻ 0.05 was considered statistically signiﬁcant.

Patient No. CU vs. NBR Correlation, r Upregulation in CU (log2 FC Ͼ 2), TPM Upregulation in NBR (log2 FC ϽϪ2), TPM Less or No Signiﬁcant Change % Correlation 1 0.802 165 98 19,573 98.6 2 0.759 637 92 19,036 96.3 3 0.658 612 160 20,006 96.2 4 0.826 181 141 19,698 98.3 5 0.869 180 41 19,092 98.8 Union 1,149 396 CU, cultured epithelia; FC, fold change; NBR, nasal brushings; r, Pearson’s correlation coefﬁcient; TPM, transcripts per million (normalized data set).

the comparative CT method, gene expression levels were calculated; those directly harvested from the patient (Table 2). The repro- GAPDH was used as the housekeeping gene. ducibility and the potential outliers were identified by principal Gene expression analysis. For analysis of transcriptome data sets, component analysis (Fig. 1C), which showed three clusters, we built an index sequence for STAR using the human reference GENCODE v27 feature that includes protein-coding, as well as one around four of the brushed nasal biopsies, one encompass- noncoding, genes. Before sequence alignment, we applied TrimGalore ing three of the cultured cells, and another around the remain- (version 0.4.3) with the Cutadapt package (version 1.12) (5) to remove ing two cultured cells, suggesting close correlations between unnecessary genomic fragments (e.g., adapter dimers) and low-quality these groups. nucleotide sequences from the raw reads. Then we mapped adapter- A total of 117 ϫ 106 sequencing reads, with an average of trimmed sequencing reads to the human reference genome (GRCh38) 39 ϫ 106 reads per sample, were used. The genes with Ͼ1 using STAR aligner (2) and calculated the raw count using feature- count per million reads were considered for analysis. A gene- Counts (gene level) (4). Data availability. The data will be made available to qualified by-sample matrix of reading counts was analyzed using cus- investigators on request. tomized Python script to calculate transcripts per million, and the differentially expressed (Ͼ4-fold change) genes RESULTS (DEGs) were calculated. We validated the DEGs by RT- Pair-wise comparison (Fig. 1A, Table 2) and pooled sample PCR quantification of 3 upregulated genes randomly se- analysis (Fig. 1B) showed a strong correlation between cells lected from the list of top-10 upregulated genes in cultured cultured at ALI and cells from brushed biopsy of nasal epithe- epithelia and nasal brushing (Fig. 2, A and B). In addition, lia from the same patient. Overall, 96% of expressed genes to determine if cell types in the cultured cells differ from showed similar expression profiles in cells cultured in vitro and those in the nasal scrapings, we quantified the markers of

Fig. 2. Validation of total RNA sequencing data and quantiﬁcation of cell population makers. A and B: expression of 3 signiﬁcantly upregulated genes in cultured nasal epithelial (CU) and nasal brushing (NBR) samples was validated using RT-quantitative PCR. C–F: relative expression of basal cell (CD109, KRT5, KRT14, KRT17, TP63), goblet cell (MUC2, MUC5B, MUC16, TFF1, TFF3), ciliated cell (TUB1A, CROCC, PDGFRA, ACTG1, CALM3), and Clara cell (SCGB1A1) genes. Data are represented in scatter plots with median for 5 donors.

Table 3. Pathway analysis of differentially expressed genes in cultured nasal epithelia vs. nasal brushings

Pathway (Identifiers Found) Ratio P Value* Pathways with genes with increased expression in NBR vs. CU Formation of the cornified envelope 0.01 2.81E-10 (KRT13, SPRR3, SPRR2A, CSTA, SPRR2A) Keratinization 0.016 1.97E-08 (KRT13, SPRR3, SPRR2A, CSTA, SPRR1A) tRNA processing in the mitochondrion 0.003 2.57E-07 (MT-TP, MT-TL1, MT-TT, MT-TW, MT-TS1) Nuclear receptor transcription pathway 0.006 1.30E-04 (NR3C2) tRNA processing 0.013 2.06E-04 (MT-TP, MT-TL1, MT-TT, MT-TW, MT-TS1) rRNA processing in the mitochondrion 0.003 2.42E-04 (MT-TL1, MT-TT, MT-TW) Thyroxine biosynthesis 0.002 3.00E-03 (DU0X2) Developmental biology 0.084 8.23E-03 (KRT13, SPRR3, SPRR2A, CSTA, SPRR1A) MyD88 deficiency (TLR5, MYD88) 0 8.90E-03 Pathways with genes with decreased expression in NBR vs. CU ECM organization 0.023 4.62E-11 (FBLN1, LAMC2, LAMA3, COL7A1, SERPINE1, LAMB3, ITGB4, TGFB2, ITGA3, ITGB6, ITGB6, ITGAV, TNC, FN1, LTBP2, COL1A1, CAPN13, COL17A1, SPARC, MMP13, HSPG2, THBS1, ICAM1) Type I hemidesmosome assembly 0.001 1.38E-8 (LAMC2, KRT17, LAMA3, KRT13, LAMB3, COL17A1, ITGB4) Laminin interactions 0.002 1.66E-8 (LAMC2, LAMA3, COL7A1, LAMB3, ITGB4, ITGA3, ITGAV, HSPG2) Non-integrin membrane-ECM interactions 0.004 1.88E-8 (LAMC2, KRT17, LAMA3, KRT13, LAMB3, COL17A1, ITGB4) FOXO-mediated transcription of cell cycle genes 0.002 1.29E-8 (TNC, FN1, LAMA3, SERPINE 1, COL1A1, SPARC, TGFB2, ITGB6, ITGAV, HSPG2) ECM proteoglycans 0.005 2.01E-7 (CDKN1A, CAV1, GADD45A) Integrin-cell surface interactions 0.006 4.33E-7 (TNC, FN1, COL7A1, COL1A1, ITGA3, ITGB6, ITGAV, HSPG2, THBS1, ICAM1) Assembly of collagen fibrils and other multimeric structures 0.005 5.09E-7 (TNC, LAMC2, LAMA3, COL7A1, LAMB3, COL1A1, COL17A1, ITGB4, MMP13) Anchoring fibril formation 0.001 2.53E-6 (LAMC2, LAMA3, COL7A1, LAMB4, COL1A1) MET promotes cell motility 0.003 3.74E-6 (FN1, LAMC2, LAMA3, LAMB3, COL1A1, TNS3, ITGA3) Syndecan interactions 0.002 3.78E-6 (TNC, FN1, COL1A1, ITGB4, ITGAV, THBS1) MET activates PTK2 signaling 0.002 6.59E-6 (FN1, LAMC2, LAMA3, LAMA3, LAMB3, COL1A1, ITGA3) Cell junction organization 0.007 7.8E-6 (FLNA, LAMC2, KRT17, LAMA3, KRT13, LAMB3, COL17A1, ITGB4, CDH3) Degradation of the ECM 0.01 8.28E-6 (TNC, FN1, LAMC2, LAMA3, COL7A1, LAMB3, COL1A1, CAPN13, COL17A1, MMP13, HSPG2) Collagen formation 0.007 1.72E-5 (TNC, LAMC2, LAMA3, COL7A1, LAMB3, COL1A1, COL17A1, ITGB4, MMP13) Molecules associated with elastic fibers 0.003 1.73E-5 (FN1, FBLN1, LTBP2, TGFB2, ITGB6, ITGAV) Cellular senescence 0.014 2.52E-5 (FLNA, CDKN1A, CDKN2A, IGFBP7, JUN, HES4) TP53 regulates transcription of cell cycle genes 0.005 3.9E-5 (PLK2, CDKN1A, GADD45A) IL-4 and IL-13 signaling 0.015 4.41E-5 (VIM, FN1, CDKN1A, SAA1, CCND1, ICAM1) Transcriptional regulation by RUNX3 0.008 4.55E-5 (CDKN1A, CDKN2A, CTGF, CCND1) Functional pathway analysis was carried out on differentially expressed genes from all 5 patients with chronic obstructive pulmonary disease. Ratio refers to percentage of total genes in the pathway. CU, cultured epithelia; ECM, extracellular matrix; MET, mesenchymal-epithelial transition factor; NBR, nasal brushing; PTK2, protein tyrosine kinase 2; RUNX3, runt-related transcription factor 3. *P < 0.01 after Benjamini-Hochberg multiple test correction.

Pathway (Identifiers Found) Ratio P Value* Pathways with genes with increased expression in CU2 and CU3 ECM organization 0.023 1.11E-16 (TIMP2, COL6A6, COL6A3, COL6A1, COLA1, COL4A1, COL4A2, ADAM12, DST, TEX10, COL18A1, SPARC. KALRN, COL16A1, LOXL1, LOXL2, HTRA1, LAMC1, PLOD3, LAMC2, PLOD2, PLOD1, P4HA2, SERPINE1, COL12A1, SDC2, PLCD3, FBN1, MFAP2, PMP2, FMNL1, BMP1, CRTAP, SERPINH1, LAMB1, COL5A2, MMP2, ITGA11, COL5A1, LAMB3, ITGA1) Collagen formation 0.007 5.57E-14 (SERPINH1, COL6A6, COL6A3, COL6A1, COL5A2, COL4A1, COL4A2, LAMB3, P3H2, P3H1, DST, PXDN, COL18A1, COL1A1, COL3A1, COL16A1, COL1A2, LOXL1, LOXL2, PLOD3, LAMC2, PLOD2, PLOD1, LAMA3, LOX, P4HA2, COL12A1, PLEC, COL27A1, FMNL1, BMP1, CRTAP) Non-integrin membrane-ECM interactions 0.004 1.06E-12 (LAMC1, SERPINH1, LAMB1, LAMC2, LAMA3, COL5A2, LAMA4, COL4A1, COL4A2, ITGB1, COL5A1, SDC2, LAMB3, DDR2, ITGA2, ITGB5, FN1, PDGFA, PDGFB, COL1A1, ACTN1, COL3A1, COL1A2, THBS1) Assembly of collagen fibrils and other multimeric structures 0.005 4.52E-11 (COL6A6, LAMC2, COL6A3, COL6A1, LAMA3, LOX, COL5A2, COL4A1, COL12A1, COL4A2, COL5A1, LAMB3, PLEC, DST, PXDN, COL18A1, COL1A1, COL27A1, COL3A1, BMP1, COL1A2, LOXL1, LOXL2) Collagen biosynthesis and modifying enzymes 0.005 1.04E-10 (SERPINH1, PLOD3, COL6A6, PLOD2, COL6A1, COL5A2, P4HA2, COL4A1, COL12A1, COL4A2, COL5A1, P3H2, P3H1, COL18A1, COL1A1, COL27A1, COL3A1, COL16A1, FMNL1, BMP1, COL1A2, CRTAP) Degradation of the ECM 0.01 1.64E-10 (TIMP2, LAMB1, COL6A6, COL6A3, COLA1, COL5A2, MMP2, COL4A1, COL4A2, COL5A1, LAMB3, A2M, FN1, MAN1A1, CTSK, TEX10, COL18A1, COL1A1, MMP12, MMP14, KALRN, COL3A1, COL16A1, COL1A2, MYH9, HTRA1, LAMC1, LAMC2, LAMA3, COL12A1, FBN1, ADAMTS1, CLSTN3, BMP1) ECM proteoglycans 0.005 5.48E-09 (LAMC1, LAMB1, COL6A6, COL6A3, COL6A1, LAMA3, COL5A2, LAMA4, COL4A1, SERPINE1, COL4A2, ITGB1, COL5A1, ITGA2, VCAN, ITGB5, ITGB6, SRGAP2, FN1, COL1A1, SPARC, COL3A1, COL1A2) Integrin-cell surface interactions 0.006 5.72E-09 (COL6A6, COL6A3, COL6A1, COL5A2, ITGA11, COL4A1, COL4A2, ITGA11, COL4A1, COL4A2, ITGB1, COL5A1, ITGA1, ITGA2, ITGB5, ITGA4, ITGA5, ITGB6, FBN1, FN1, COL18A1, COL1A1, COL3A1, COL16A1, COL1A2, THBS1) MET activates PTK2 signaling 0.002 6.03E-09 (LAMC1, LAMB1, LAMC2, LAMA3, COL5A2, LAMA4, ITGB1, COL5A1, LAMB3, ITGA2, FN1, COL1A1, COL27A1, COL3A1, COL1A2) Axon guidance 0.04 7.77E-09 (COL6A6, COL6A3, COL6A1, COL4A1, COL4A2, TNS1, TUBB6, CAP1, MYO5A, ABL2, GRB10, MYO5A, ABL2, GRB10, MYO9B, PSMD2, TPRA1, DLG1, KALRN, PPFIBP1, LAMC1, SLIT2, FAP, ABLIM3, SDC2, DPYSL2, SEMA5A, SPTBN1, FGFR1, LIMK1, MAPK11, EFNA1, LAMB1, FLNB, KIF3C, COL5A2, MMP2, COL5A1, ITGA1, ITGA2, ITGA5, SRGAP2, PDLIM7) Elastic fiber formation 0.003 1.89E-08 (LOX, COL4A1, ITGB1, EFEMP2, ITGB5, ITGA5, ITGB6, PLCD3, FBN1, FN1, LTBP2, MFAP2, BMP2, LTBP1, LOXL1, LOXL2) Regulation of IGF transport and uptake by IGFBPs 0.009 4.59E-08 (TIMP2, LAMB1, MMP2, COL4A1, LIMS1, FAM20C, FN1, APOE, CDH2, PAPPA, SPARC, LTBP1, LAMC1, CSF1, LOX, SDC2, VCAN, RCN1, LGALS1, GAS6, FBN1, MELTF, IGFBP6, CLSTN3, IGFBP4, EVA1A, CALU, FSTL3, FSTL1) MET promotes cell motility 0.003 8.24E-08 (LAMC1, LAMB1, LAMC2, LAMA3, COL5A2, LAMA4, ITGB1, COL5A1, LAMB3, ITGA2, TNS4, FN1, COL1A1, COL27A1, COL3A1, COL1A2) Collagen degradation 0.005 2.62E-07 (COL6A6, COL6A3, COL6A1, COL5A2, MMP2, COL4A1, COL12A1, COL4A2, COL5A1, CTSK, COL18A1, COL1A1, MMP12, MMP14, KALRN, COL3A1, COL16A1, COL1A2) Collagen chain trimerization 0.003 3.50E-07 (COL6A6, COL6A3, COLA1, COL5A2, COL4A1, COL12A1, COL4A2 COL5A1, COL18A1, COLA1, COL27A1, COL3A1, COL16A1, COL1A2) Posttranslational protein phosphorylation 0.008 4.20E-07 (TIMP2, LAMB2, COL4A1, LIMS1, FAM20C, FN1, APOE, CDH2, SPARC, LTBP1, LAMC1, CSF1, LOX, SDC2, VCAN, RCN1, LGALS1, GAS6, FBN1, MELTF, IGFBP4, EVA1A, CALU, FSTL3, FSTL1) Syndecan interactions 0.002 7.15E-07 (FN1, COL5A2, ITGB1, COL5A1, SDC2, COL1A1, ACTN1, ITGA2, COL3A1, COL1A2, ITGB5, THBS1) Signaling by receptor tyrosine kinases 0.038 7.62E-07 (SPRY2, COL6A6, COL6A3, COL6A1, COL4A1, COL4A2, TNS4, ADAM12, GRB10, APOE, SPARC, KALRN, LAMC1, ITPR2, LAMC2, PTPRK, ITPR3, AXL, SPTBN1, FGFR1, MAPK11, NEDD4, RALA, VEGFA, CAV1, LAMB1, FLNB, COL5A2, SPHK1, COL5A1, LAMB3, ITGA2, PAG1, RAB11FIP5, FN1, ANOS1, COL1A1, COL3A1, COL1A2, DNM1) Signaling by PDGF 0.005 1.39E-06 (COL6A6, COL6A3, COL6A1, COL5A2, COL4A1, COL4A2, COL5A1, RASA1, NT5DC2, PDGFC, PLAT, PDGFA, PDGFB, COL3A1, THBS3, THBS1) Laminin interactions 0.002 1.42E-6 (LAMC1, LAMB1, LAMC2, LAMA3, LAMA4, COL4A1, COL4A2, ITGB1, LAMB3, COL18A1, ITGA1, ITGA2) Continued

Pathway (Identiﬁers Found) Ratio P Value* Pathways with genes with increased expression in CU1, CU3, and CU5 Neutrophil degranulation 0.033 9.92E-4 (ANK3, PRKCD, NAPRT, CYBB, VAMP8, CD55, GSTK1, LRRC6, TUBB4B, S100P, LRG1, CD14, SELL, IDH, SERPINB3, SVIP, RIPOR2, CST3, HPSE, MGST1, CD9, ATP10B, SLCO4C1, FASN, FCGR2A, CSTB, LCN2, DEGS2, TACC2, NFASC, SERPINA1, CRACR2A, IQGAP2, STOM, METTL7A, CTSC, ALDH3B2, PLAC8, CEACAM6, CTSD) Termination of O-glycan biosynthesis 0.002 1.37E-3 (MUC13, MUC15, MUC16, RPIA, MUC1, MUC2, ST6GAL1, ST6GALNAC4, MUC5B, MUC5AC) Defective GALNT12 causes CRCS1 0.001 2.02E-3 (MUC13, MUC15, MUC16, GLANT12, MUC1, MUC2, MUC5, MUC5AC) Metal sequestration by antimicrobial compounds 0.001 3.62E-3 (S100A7, S100A8, S100A9, TF. LCN2, LTF) O-linked glycosylation of mucins 0.005 3.96E-3 (MUC13, MUC15, MUC16, RPIA, MUC1, MUC2, CHST4, ST6GALNAC4, GALNT6, GCNT3, B3GNT6, B3GNT3, GALNT12, GALNT14, ST6GAL1, MUC5B, MUC5AC) ERBB2 activates PTK6 signaling 0.001 4.39E-3 (NRG4, ERBB4, ERBB3, BTC) Fatty acids 0.002 5.74E-3 (CYP4B1, CYP2A13, RRAGD, CYP4F3, CYP2J2, CYP2F1, CYP4F12, SORL1, CYP4F11) ERBB2 regulates cell motility 0.001 5.84E-3 (NRG4, ERBB4, ERBB3, BTC) Defective GALNT3 causes familial hyperphosphatemic tumoral calcinosis 0.001 7.62E-3 (MUC13, MUC15M MUC16, MUC1, MUC2, MUC5B, MUC5AC) SHC1 events in ERBB2 signaling 0.001 9.77E-3 (MITF, NRG4, ERBB4, BTC) Defective GALNT3 causes familial C1GALT1C1 causes TNPS 0.001 9.77E-3 (MUC13, MUC15, MUC16, MUC1, MUC2, MUC5B, MUC5AC) GRB2 events in ERBB2 signaling 0.001 9.77E-3 (MITF, NRG4, ERBB4, BTC) Ratio refers to percentage of the total genes in the pathway. CRCS1, colorectal cancer 1; CU, cultured epithelia; ECM, extracellular matrix; GALNT12, polypeptide N-acetylgalactosaminyltransferase 12; IGF, insulin-like growth factor; IGFBPs, IGF-binding proteins; MET, mesenchymal-epithelial transition factor; NBR, nasal brushing; PDGF, platelet-derived growth factor; PTK2, protein tyrosine kinase 2; TNPS, Tn polyagglutination syndrome. *P < 0.01 after Benjamini-Hochberg multiple test correction.

(4, 5) and ingenuity pathways analysis in samples from all five exposures that occur in the nose from the shear effects of patients with COPD to summarize the functional class and respiration to the various stimuli that are in the air and 2) the pathway of DEGs (Table 3). Analysis of the functional cate- difference in the matrix on which cultured cells are grown. gories of differentially expressed genes revealed that pathways However, despite these concerns, ALI cultures are used rou- involved in the cornified epithelium are activated in squamous tinely to test physiologic and pathologic responses of differen- or flattened epithelium (Table 3, increased expression pathway tiated epithelium to infectious and noninfectious particles and data). In addition, pathways involved in nuclear receptor and to perform other toxicology studies. To determine the extent to tRNA processing were highly expressed in fresh nasal brush- which the ALI cultures are representative of a given individual, ings (Table 3, increased expression pathway data), whereas we compared the transcriptomics of nasal epithelial cells of a pathways involved in the extracellular matrix and genes in- given patient directly extracted from the nose with those grown volved in interactions with the extracellular matrix were highly and differentiated in vitro before RNA extraction. Such an expressed in cultured nasal epithelia (Table 3, decreased ex- analysis can provide a better assessment of which pathways pression pathway data). We also performed pathway analysis in cultured cells are highly representative of pathways in the of DEGs among different clusters observed in principal com- nasal epithelium and which pathways may require additional ponent analysis of cultured epithelia (Fig. 1C). The cluster of correlation. It is important to recognize that the samples cultured nasal epithelia, i.e., CU2 and CU3, showed an in- were collected from diseased (i.e., COPD) patients, and we crease in pathways involved in collagen-related extracellular have evidence that cells derived from patients with COPD matrix organization (Table 4) and the cluster CU1, CU4, and behave differently and have significant differences in gene CU5 showed an increase in pathways involved in innate expression compared with cells derived from normal pa- immunity (Table 4), although the available clinical data do not tients (6, 7). However, since the source of the comparators provide a rationale for these findings. is the same disease condition, it is unlikely that it would affect the interpretation. DISCUSSION There is, in fact, a high degree of correlation in the tran- Although ALI cultures are used routinely for studies, the scriptome between collected nasal brushings and cells that are degree to which these in vitro cultures are representative of cultured and then allowed to differentiate in vitro. Interest- cells in patient airways remains in question. This has been an ingly, pair-wise comparison of specific cell types between the ongoing concern, as these cells are grown in a different cultured cells and nasal brushings showed similar numbers of environment, in terms of 1) the lack of physical and chemical ciliated, goblet, Clara, and basal cells, although there were

AJP-Lung Cell Mol Physiol • doi:10.1152/ajplung.00050.2020 • www.ajplung.org Downloaded from journals.physiology.org/journal/ajplung at US EPA Main Lib (134.067.029.089) on January 7, 2021. L1062 CULTURED EPITHELIA REPRESENTS THE IN VIVO AIRWAY EPITHELIA some differences in specific marker expression and a large prepared figures; B.G. drafted manuscript; B.G., M.R., N.N.H., S.B., and degree of variability. V.K.S. edited and revised manuscript; P.G., M.R., N.N.H., S.B., and V.K.S. Based on principal component analysis, the transcriptomics approved final version of manuscript. of nasal brushings are more closely clustered, indicating that, ultimately, these samples are more tightly correlated. The REFERENCES cultured cells form separate clusters, suggesting more variabil- 1. Den Beste KA, Hoddeson EK, Parkos CA, Nusrat A, Wise SK. ity in their transcriptome. 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