
==== Front
Gastro Hep Adv
Gastro Hep Adv
Gastro Hep Advances
2772-5723
Elsevier

S2772-5723(24)00064-5
10.1016/j.gastha.2024.04.014
Original Research—Basic
Proteomic Differences in Colonic Epithelial Cells in Ulcerative Colitis Have an Epigenetic Basis
Jelinsky Scott scott.jelinsky@pfizer.com
1∗
Lee Isac 1
Monetti Mara 2†
Breitkopf Susanne 2‡
Martz Flora 3§
Kongala Ramya 3
Culver Jeffrey 2
Vo Vanessa 2¶
Xue Liang 4
Gieseck Richard III 1
Dickinson Caitlyn 1
Kasaian Marion 1
Lord James D. 3
1 Department of Inflammation and Immunology, Pfizer, Cambridge, Massachusetts
2 Internal Medicine Research Unit, Pfizer, Cambridge, Massachusetts
3 Translational Research Program, Benaroya Research Institute, Seattle, Washington
4 Machine Learning and Computational Sciences, Early Clinical Development, Pfizer, Cambridge, Massachusetts
∗ Correspondence: Address correspondence to: Scott Jelinsky, PhD, Department of Inflammation and Immunology, Pfizer, 1 Portland Street, Cambridge, Massachusetts 02139. scott.jelinsky@pfizer.com
† Proteomics Core, Memorial Sloan Kettering Cancer Center, New York, New York.

‡ Kymera Therapeutics, Watertown, Massachusetts.

§ Department of General Surgery, University of Washington, Seattle, Washington.

¶ Novartis Institute for Biomedical Research, Cambridge, Massachusetts.

09 5 2024
2024
09 5 2024
3 6 830841
9 10 2023
30 4 2024
© 2024 Published by Elsevier Inc. on behalf of the AGA Institute.
2024

https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Background and Aims

The colonic epithelium serves as both a barrier to lumenal contents and a gatekeeper of inflammatory responses. In ulcerative colitis (UC), epithelial dysfunction is a core feature, but little is known about the cellular changes that may underlie disease pathology. We therefore evaluated how the chromatin epigenetics and proteome of epithelial cells differs between health and UC.

Methods

We sorted live CD326+ epithelial cells from colon biopsies of healthy control (HC) screening colonoscopy recipients and from inflamed or uninflamed colon segments of UC patients on no biologic nor immunomodulator therapy (n = 5–7 subjects per group). Cell lysates were analyzed by proteomic evaluation and nuclei were analyzed for open chromatin with assay for transposase-accessible chromatin using sequencing.

Results

Proteins most highly elevated in inflamed UC biopsies relative to HC were those encoded by the HLA-DRA (P = 3.1 × 10−33) and CD74 (P = 1.6 × 10−27), genes associated with antigen presentation, and the antimicrobial dual oxidase 2 (DUOX2) (P = 3.2 × 10−28) and lipocalin-2 (P = 2.2 × 10−26) genes. Conversely, the water channel aquaporin 8 was strikingly less common with inflammation (P = 1.9 × 10−18). Assay for transposase-accessible chromatin using sequencing revealed more open chromatin around the aquaporin 8 gene in HCs (P = 2.0 × 10−2) and more around the DUOX2/DUOXA2 locus in inflamed UC colon (P = 5.7 × 10−4), suggesting an epigenetic basis for differential protein expression by epithelial cells in health and disease.

Conclusion

Numerous differences exist between the proteome and chromatin of colonic epithelial cells in UC patients and HCs, some of which correlate to suggest specific epigenetic mechanisms regulating the epithelial proteome.

Keywords

Proteomics
ATAC-Seq
DUOX2
AQP8
Abbreviations used in this paper

AGC automatic gain control

ATAC-Seq assay for transposase-accessible chromatin using sequencing

AQP aquaporin

BWA Burrows-Wheeler aligner

CE capillary electrophoresis

DUOX dual oxidase

FDR false discovery rate

HC healthy control

HPLC high pressure liquid chromatography

IBD inflammatory bowel disease

Ig immunoglobulin

IRB institutional review board

LC-MS liquid chromatography-mass spectrometry

LCN2 lipocalin-2

MHC major histocompatibility complex

PCR polymerase chain reaction

PSMB9 Proteasome subunit beta type-9

TAP transporter associated with antigen processing

TSS transcription start site

UC ulcerative colitis

UCIC UC inflamed

UCNC UC uninflamed
==== Body
pmcIntroduction

The gut epithelium is a single layer of cells separating the host from the external environment, supported by an interdigitating network of junctional proteins, and interacting with the underlying stromal layer to maintain polarity that supports secretory function. The epithelium is a dynamic structure, with stem cells localized to the base of crypts continuously undergoing maturation and functional specialization to maintain the integrity of the barrier, secretion of mucus and antimicrobial peptides, release of serotonin and other bioactive amines, and communication with immune cells. In inflammatory bowel disease (IBD), an escalating cycle of epithelial disruption and inflammation contributes to tissue damage and epithelial erosion.1 Agents targeting the inflammatory component are standard of care for IBD, but unmet need remains, with current treatments achieving remission in < 30% of patients vs placebo, and up to 40% of subjects showing partial response or loss of response over time.2

The preservation and restoration of the mucosal epithelium is a promising strategy for the development of novel IBD therapeutics,3 but mechanistic understanding of epithelial function has been challenging. Recent technical advances have allowed the first single-cell transcriptional analysis of isolated gut epithelial cells,4 but proteomic characterization has been more limited. In IBD, proteomics can inform on disease severity, progression, and treatment response, in relation to the degree of inflammation, tissue damage, and other correlates of histopathology.5,6 At the tissue level, proteomics has been instrumental in characterizing pathogenesis, providing evidence for disease-induced changes in mucus production,7 extracellular matrix,8,9 tissue repair,10,11 inflammation,5,10,12 autophagy,8 energy metabolism,9,13 unfolded protein response,9 and oxidative stress.13 Proteomic analysis targeted toward the epithelium may allow further characterization of the localization of response, and definition of the interplay between tissue damage and inflammation.

To date, the studies exploring protemics of enriched epithelium in IBD have all utilized surgical resections, rather than colonoscopic biopsies,6,8,10 which necessarily restricts ulcerative colitis (UC) subjects to patients with either malignancy or exhaustive medical treatment exposure and failure as an indication for surgery. Additionally, and in contrast to colonoscopies, bowel resections cannot be ethically performed on truly healthy human controls for comparison, necessitating the use of heterogeneous controls with other intestinal disease as an indication for surgery. Furthermore, much existing proteomic data on the colonic epithelium in IBD used chemically and mechanically dissociated epithelium, which would necessarily be contaminated with intraepithelial leukocytes and often some lamina propria cells. This is especially confounding when comparing profiles from inflamed and uninflamed regions of the gut, as intestinal inflammation is associated with immune infiltrate and epithelial erosion,14 making lymphoid contamination of the isolated epithelium even more likely. To avoid these caveats in the current study, we examine proteomics of sort-purified epithelial cells from colonoscopic biopsies obtained from healthy screening colonoscopy recipients, compared to those of the inflamed vs uninflamed colon segments of UC patients on no biologic or immunomodulator medication for their UC. Our findings reveal a unique profile of epithelial proteomic and epigenetic changes that differentiate the colonic epithelium of UC patients from that of healthy controls (HCs).

Materials and Methods

Subjects and Samples

Colon biopsies were obtained and cryopreserved from HC subjects undergoing screening colonoscopy, and from inflamed or uninflamed colon segments from UC patients on no biologic nor immunomodulator therapy (Table). Age of patients in each group was not statistically different (P = .87, P = .31 and P = .38 for healthy vs noninflamed, healthy vs inflamed and noninflamed vs inflamed respectively). All subjects provided written consent to participate as part of an instititional review board–approved biorepository program at the Benaroya Research Institute, in accordance with the Declaration of Helsinki.Table Patient Characteristics and Study Samples

Subject/biopsy	Age at draw	Gender	Race	Years of UC	Uceis score	UC medications	Patient type	Inflammation status	Anatomic location	Proteomics STUDY 1	Proteomics STUDY 2	ATAC-seq	
HC1	46	Female	Caucasian	n/a	n/a	n/a	Non-IBD	Uninflamed	Ascending colon	x	x	x	
HC2	52	Male	Declined	n/a	n/a	n/a	Non-IBD	Uninflamed	Ascending colon	x			
HC3	71	Female	Caucasian	n/a	n/a	n/a	Non-IBD	Uninflamed	Ascending colon	x		x	
HC4	61	Female	Caucasian	n/a	n/a	n/a	Non-IBD	Uninflamed	Ascending colon	x	x	x	
HC5	71	Female	Caucasian	n/a	n/a	n/a	Non-IBD	Uninflamed	Ascending colon	x	x		
HC6	56	Female	Caucasian	n/a	n/a	n/a	Non-IBD	Uninflamed	Ascending colon		x	x	
HC7	27	Female	Caucasian	n/a	n/a	n/a	Non-IBD	Uninflamed	Ascending colon		x	x	
UCNC1	49	Male	Caucasian	7.4	4	Mesalamine	UC	Uninflamed	Ascending colon	x	x	x	
UCNC2	47	Male	Asian	19.5	5	None	UC	Uninflamed	Ascending colon	x	x	x	
UCNC3	56	Male	Caucasian	37.9	0	None	UC	Uninflamed	Ascending colon	x	x	x	
UCNC4	78	Female	Caucasian	3.5	2	None	UC	Uninflamed	Ascending colon	x	x	x	
UCNC5	51	Male	African American	4	2	Balsalazide	UC	Uninflamed	Transverse colon	x		x	
UCNC6	22	Female	Asian	3.6	4	Mesalamine	UC	Uninflamed	Ascending colon		x	x	
UCIC1	25	Male	Asian, Caucasian	0	2	None	UC	Inflamed	Ascending colon	x	x	x	
UCIC2	55	Male	Caucasian	2.4	1	Mesalamine	UC	Inflamed	Ascending colon	x	x	x	
UCIC3	47	Male	Asian	19.5	3	None	UC	Inflamed	Descending colon	x	x	x	
UCIC4	35	Female	Caucasian	13.6	7	Mesalamine, budesonide	UC	Inflamed	Descending colon	x	x	x	
UCIC5	61	Male	Declined	2.7	5	Mesalamine	UC	Inflamed	Colon	x		x	
UCIC6	27	Male	Caucasian	0.5	3	None	UC	Inflamed	Ascending colon		x	x	
UCIC, ulcerative colitis inflamed; UCNC, ulcerative colitis uninflamed.

Epithelial Cell Purification

Biopsies were thawed and homogenized by vigorous vortexing for 20–30 minutes at 37 °C in the presence of 150 U/mL collagenase (Gibco) in Roswell Park Memorial Institute medium supplemented with 1 mM calcium and 1 mM magnesium. Homogenized cells were then passed through a 100 μm filter and stained with a viability dye (LIVE/DEAD, Life Technologies) fluorophor-conjugated anti-CD45 (clone 2D1 BioLegend) and anti-CD326 (clone 9C4 BioLegend). Live epithelial cells were purified by fluorescence-activated cell sorting on a FACSAria Fusion (BD Biosciences) for CD326+, CD45− cells excluding viability dye. 1–2 × 105 sorted cells were pelleted and frozen for lysis and digestion for proteomic analysis, as below, while another 1.5 × 105 cells had their nuclei isolated, as below, for epigenetic analysis.

Lysis, Digestion, and Tandem Mass Tag Labeling for Proteomic Analyses

Epithelial cells (CD45−/CD326+) (STUDY 1; Table) from 5 human healthy colon or UC inflamed (5 donors) and uninflamed (5 donors) biopsies were lysed in 4% SDS/0.1 M Tris, pH 8.5 and precipitated in the presence of acetone at −20 °C overnight. Protein was reconstituted in 8 M urea. A second, overlapping set of epithelial cells (CD45−/CD326+) (STUDY 2; Table) was lysed in 8 M urea directly.

For both sets of samples (STUDY 1 and STUDY 2), protein disulfide bonds were reduced in the presence of dithiothreitol (5 mM final concentration), followed by alkylation in the presence of 2-iodoacetamide (10 mM final concentration). The urea concentration was then reduced to 1.5 M using 0.05 M ammonium bicarbonate, followed by digestion with trypsin (Pierce Biotechnology; 1:50 w/w) at 37 °C overnight.

Peptide digest was desalted by C18 Sep-Pak cartridge (Waters, Milford, MA). Desalted peptides were reconstituted in 50 mM 2-[4-(2-hydroxyethyl)piperazin-1-yl]ethanesulfonic acid prior to quantification by NanoDrop (Thermo Fisher Scientific, Waltham, MA). Peptides were labeled with TMTPro 16plex reagent (Thermo Fisher Scientific) according to the manufacturer’s instructions.

Off-Line Basic Reversed-Phase (High pH) High-Pressure Liquid Chromatography Fractionation and Liquid Chromatography-Mass Spectrometry/MS

TMT-labeled peptides were fractionated by offline reversed-phase high-pH fractionation using an Agilent 1200 High-Pressure Liquid Chromatography (Santa Clara, CA) and separated on an Agilent ZORBAX Extend-C18 column into a total of 12 fractions. Fractions were reconstituted in 5% Acetonitrile in 0.1% Formic Acid prior to injection onto an EasyNano 1200 LC. Peptides were separated on an EasySpray column (50 cm, ES903; Thermo Fisher Scientific). The LC was coupled to a Thermo QExactive-HF mass spectrometer. A ‘Top 10’ data-dependent acquisition method was employed with the instrument set in positive detection mode. For MS1, the resolution was set to 60,000, the scan range was set to 350–1800 m/z, and the automatic gain control target was set to 5e5, with a maximum IT of 50 ms. For MS2, the resolution was set to 60,000, the normalized capillary electrophoresis was set to 38, the isolation window was set to 0.7 m/z, the automatic gain control target was set to 1e5, and the maximum IT was set to 105 ms.

Proteomic Data Analysis and Normalization

All liquid chromatography-mass spectrometry/MS runs were analyzed using the Sequest algorithm (SEQUEST HT, Thermo Fisher Scientific) within Proteome Discoverer 2.4 (Thermo Fisher Scientific) against the UniProt human database. A 10 ppm MS1 error tolerance was used. Trypsin was set as the enzyme, allowing for 2 missed cleavages. A false discovery rate (FDR) level of 0.01 was used, with a reporter ion integration tolerance of 20 ppm for the most confident centroid in MS2. The MSstatsTMT workflow was applied for peptide quantification and normalization. Reporter abundances were based on signal intensities. Peptides were quantified by summing reporter ion intensity across all matching peptide-spectral, and then used to calculate protein abundance in each sample. The log2 peptide intensities are median normalized assuming equal input loading of all channels. Peptide intensities were summarized to protein intensities using Tukey's median polish algorithm.15

Nucleus Isolation for Epigenetic Analyses

Cell suspensions were centrifuged at 300 × g for 5 minutes at 4 °C. Pellets were resuspended in PBS + 0.04% BSA for 1000 cells/μL cell suspension. Suspensions were centrifuged again, and supernatants were mixed with equal parts chilled Lysis Buffer (10 mM Tris-HCl, 10 mM NaCl, 3 mM MgCl2, 0.1% Tween-20, 0.1% IGEPAL, 0.01% Digitonin, 1% BSA in nuclease-free water). Suspensions were gently mixed and incubated on ice for 3–5 minutes. Wash Buffer (10 mM Tris-HCl, 10 mM NaCl, 3 mM MgCl2, 1% BSA, 0.1% Tween20 in nuclease-free water) was added without mixing. After centrifugation, chilled Diluted Nuclei Buffer (10X Genomics, Pleasanton, CA) was added to the pellet without mixing. After recentrifugation, nuclei pellets were resuspended in Freezing Buffer (40% glycerol, 5% Tris-HCl, 5 mM MgCl2, 0.1 mM ethylenediaminetetraacetic acid in water) and stored at −80 °C until shipment to Active Motif for assay for transposase-accessible chromatin using sequencing (ATAC-seq).

Epigenetic Analysis

Epigenetic analysis of open chromatin in purified nuclei was performed by Active Motif (Carlsbad, CA) using a standardized commercial ATAC-Seq protocol. Sequencing libraries were generated from tagmented DNA using standard library preparation protocols. Generated DNA libraries were purified using magnetic beads and amplified using polymerase chain reaction. After final polymerase chain reaction amplification, libraries were purified using Agencourt magnetic beads and assessed for quality by TapeStation and quantified with Qubit. Libraries were quantified with KAPA Library Quantification for Illumina platforms following the manufacturer’s instructions. Sequencing was performed on an Illumina NextSeq system using the following parameters: (a) paired end 42 bp reads (PE42) with 80% bases higher than Q30, (b) minimum of 30 million reads per sample.

Statistical Analysis

Protein expression differences were calculated using a limma R packages.16 Meta-Analysis was performed using the metafor R package (2.0) and effect sizes were calculated using a fixed effects model. ATAC-seq reads were aligned to hg38 genome using Burrows-Wheeler aligner mem with default settings.17 Peak calling was performed using MACS2,18 and differentially accessible peaks were found using DESeq2.19 Peaks were annotated based on the RefSeq database (hg38): peaks localized within ±2.5 kb of the transcription start site (TSS) of a protein-coding gene transcript were defined as promoter peaks with the gene of the nearest transcript as their target genes. All analyses were implemented in R version 3.6.2 and all visualizations were created using the ggplot2 R package version 3.3.6.

Pathway Analysis

Hypergeometric testing was used to assess the enrichment of specific pathways in the meta-analyzed protein expression data. Input regulated proteins (P < .05) were tested against pathways derived from Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), REACTOME or the Molecular Signatures Database (MSigDB) hallmark gene set collection. Significant regulated pathways were visualized using the TMOD package in R.

All authors had access to the study data and had reviewed and approved the final manuscript.

Results

Differentially Expressed Proteins

Differentially expressed proteins in freshly isolated CD326+, CD45-epithelial cells from inflamed and uninflamed colon were identified using mass spectrometry. In Study 1, cells were lysed in SDS, and proteins precipitated overnight in acetone, then reconstituted in urea prior to trypsin digestion and mass spectrometry. A total of 2939 distinct proteins were detected with 50 proteins differentially regulated (FDR < 0.05) between inflamed and uninflamed UC samples (N = 5 each), 582 proteins differentially regulated between inflamed UC and HC tissue (N = 5), and 0 proteins differentially expressed between uninflamed UC and HC biopsies. To improve protein detection in Study 2, the protein isolation protocol was optimized by lysing the cell pellets directly in urea prior to trypsin digestion, and a repeat proteomic analysis was performed on a separate set of samples from a partially overlapping cohort of subjects (Table). In Study 2, a total of 3715 distinct proteins was identified. Of these, 376 proteins were differentially regulated between inflamed and uninflamed, 451 proteins were differentially regulated between inflamed and healthy tissue and 1 protein was differentially expressed between uninflamed and healthy. Principal component analysis of the proteome profiles showed that samples from inflamed regions formed distinguishable clusters, while samples from uninflamed and normal regions co-clustered (Figure 1A and B). The expression patterns from the inflamed tissue were distinct from the expression patterns of healthy tissue, while the expression patterns of the uninflamed tissue were more similar to the pattern from healthy tissue (Figure 1C and D). To increase our sensitivity and overcome the variability between the different studies, a meta-analysis was performed on the proteins that were detected in both studies. An important benefit of meta-analysis is its capacity to merge data from multiple studies, leading to increased statistical power and improved precision in estimating the effect size. Consequently, this enhanced statistical power enables the detection of a greater number of differentially regulated proteins compared to what could be achieved through individual studies alone. Of the 2613 distinct proteins, 656 were differentially identified between inflamed and uninflamed UC, 791 between inflamed UC, and HC, and 3 between HC and uninflamed UC biopsies (Figure 1E–G and Table A1).Figure 1 Protein expression from inflamed and uninflamed epithelial tissue from IBD patients. (A and B) Principal Component Analysis (PCA) plot of protein expression data for inflamed, uninflamed, and healthy epithelial tissue from 2 independent studies (study 1 (A) and study 2 (B)). Each point represents a sample, and the colors indicate sample groupings. The first 2 principal components are shown on the x- and y-axes, respectively. (C and D) Heatmap of protein expression levels for the top differentially expressed proteins between inflamed, uninflamed, and healthy subjects. Rows correspond to proteins, and columns correspond to individual samples. Protein expression levels are represented by a color gradient from low (blue) to high (red). Scatterplot of change in protein expression levels for all proteins based on meta-analysis between the 2 studies for (E) inflamed and healthy subjects (F), inflamed and uninflamed subjects, and (G) uninflamed and healthy subjects. Each dot represents a protein, and the x- and y-axes show estimate and −log10 P value, determined by a moderated t-statistic as implemented in limma packages,16 respectively. Pathway analysis for protein expression. Dot plots of enrichment analysis for (H) Kegg pathways and (I) GO ontology. The color scale and dot size indicate the degree of enrichment based on hypergeometric test for proteins that are regulated (P < .05) in inflamed vs un inflamed (Inf vs Un), inflamed vs healthy (Inf vs H) and uninflamed vs healthy (Un vs H).

Enrichment analysis utilizing KEGG pathways revealed that the proteome of inflamed UC epithelial cells exhibited significant enrichment in pathways related to oxidative phosphorylation, antigen processing and presentation, and several pathways associated with energy metabolism. Furthermore, when GO pathways were employed for enrichment analysis, oxidation/reduction processes, oxidoreductase activity, and oxidative phosphorylation were identified as prominent terms, along with various cellular metabolic pathways. Notably, several pathways that were found to be enriched in the proteomes of inflamed vs uninflamed cells were also enriched in the proteomes of inflamed vs healthy cells, as shown in Figure 1H and I.

Differentially Accessible Chromatin

To investigate a potential epigenetic cause for differential protein expression in diseased vs healthy epithelium, differences in accessible chromatin between epithelial cell sources were evaluated by ATAC-seq. Across all samples, we observed a total of 54,904 accessibility peaks, with 43,413 peaks from HCs, 39,964 from uninflamed UC, and 43,929 from inflamed UC. To infer gene activity from chromatin accessibility, we calculated the promoter chromatin accessibility for each gene, as the average signal in peaks within ±2.5 kb of the TSS. Principal component analysis was conducted on the promoter activities, and the results indicated that, similar to protein expression, the inflamed UC samples formed a distinct cluster on PC1, while HC and uninflamed UC samples clustered together (Figure 2A). In addition, the peaks that were more open in inflamed tissue were more closed in the healthy and uninflamed tissue (Figure 2B).Figure 2 ATACseq profiles of inflamed and uninflamed epithelia from IBD patients. (A) Principal Component Analysis (PCA) plot of ATAC-seq peaks in inflamed, uninflamed, healthy epithelial tissue. Each point represents a sample, and the colors indicate sample groupings. The first 2 principal components are shown on the x- and y-axes, respectively. (B) Heatmap of ATAC-seq peaks for the top differentially accessible peaks between inflamed, uninflamed, and healthy subjects. Rows correspond to peaks, and columns correspond to individual samples. Red indicates a more accessible peak and blue indicates a less accessible peak. (CDE)Volcano plot showing change in peaks accessibility for all detected peaks between (C) inflamed and healthy subjects (D), inflamed and uninflamed subjects and (E) uninflamed and healthy subjects. Each dot represents a peak, and the x- and y-axes show the difference in peak accessibility and the negative logarithm of the P value as determined by the Wald test as implemented in the r packages DESeq218,19 respectively.

We identified 411 genes with differentially accessible promoters (FDR < 0.05) between inflamed UC and HC biopsies, 23 genes between inflamed and uninflamed UC, and 1 gene between uninflamed UC and HC samples (Figure 2C–E and Table A1).

Additionally, we observed a specific open chromatin locus at chr15:45,114,200 near the dual oxidase 2 (DUOX2) and DUOXA2 genes. This region was open in epithelial cells from all inflamed UC biopsies and 2 of 6 uninflamed UC biopsies, but not in any from HCs. This suggests that this region may contain a crucial regulatory element driving the expression of DUOX2 and DUOXA2 genes, and hence production of H2O2 reactive oxygen species, in UC.

Correlations Between Proteomic and Epigenetic Differences

To determine whether open chromatin regions correlate with disease-associated protein expression, we integrated our ATAC-seq data with our proteomic data on epithelial cells sorted from the same biopsies. Out of the 376 differentially expressed proteins between inflamed and healthy in Study 2, we identified 361 proteins with open chromatin peaks upstream of their protomer, 28 of which had statistically different peak sizes. For proteins that were differentially expressed and had open chromatin peaks within their promotor region (2.5 kb upstream and downstream of TSS) we calculated the correlation between differences in promoter accessibility and differences in protein expression between sample types. This correlation was strong between inflamed UC and HCs (Figure 3A, R2 = 0.565 (Spearman)), and between inflamed and uninflamed UC (Figure 3B, R2 = 0.558 (Spearman)), indicating that proteins with increased expression in inflamed tissue tended to have an increased amount of open chromatin in the promoter for their gene, while proteins with decreased expression in inflamed tissues tended to have a decreased amount of open chromatin. We did not observe any correlation in the uninflamed UC vs HC comparison due to a few differentially expressed proteins (Figure 3C).Figure 3 Correlation of protein expression and ATAC-seq peaks in epithelia of ID patients. Scatterplot of protein expression difference from study 2 and ATAC-seq peak accessibility differences in: (A) inflamed vs healthy, (B) inflamed vs uninflamed, and (C) uninflamed vs healthy epithelial tissue from IBD patients. Each dot represents a distinct protein. The x-axis shows the change in protein expression levels, while the y-axis shows the change in ATAC-seq peak accessibility. Correlations were determined by Pearson correlation coefficient method.

Among the proteins differentially expressed between inflamed and uninflamed tissue, DUOX2 and aquaporin 8 (AQP8) also showed some of the highest epigenetic differences and had strong peak signals (Figure 4). A significant increase in DUOX2 protein and decrease in AQP8 protein in inflamed tissue relative to uninflamed correlated with increased accessibility in the DUOX2 promoter and decreased accessibility in the AQP8 promoter in inflamed tissue by ATACseq (Figure 4).Figure 4 Chromatin accessibility and protein expression for DUOX2 and AQP8. (A and B) Protein expression and ATAC-seq peak accessibility for DUOX2 and AQP8 in inflamed and uninflamed epithelial from IBD subjects. (C and D) Genome browser view of DUOX2 and AQP8 showing open chromatin regions align with promoter start sites for DUOX2 and AQP8. Genome browser views consist of a combination of multiple individual samples.

Additional proteins that were significantly elevated in inflamed UC as compared to uninflamed UC or biopsies from healthy subjects included several involved in inflammation or antigen presentation. Lipocalin 2, an antimicrobial protein of the innate immune system encoded by the lipocalin-2 (LCN2) gene, was increased in epithelial cells from inflamed biopsies (P = 2.2 × 10−26 vs HC, P = 8.7 × 10−15 vs uninflamed UC; Table A1) which showed correspondingly more open chromatin near the LCN2 promoter (P = 6.6 × 10−7) (Figure 5A). Similarly, for the antigen-presenting major histocompatibility complex (MHC) class II protein HLA-DRA (Figure 5B) and its chaperone, CD74 (Figure 5C), protein levels were significantly higher in inflamed than uninflamed UC biopsies (P = 8.2 × 10−20 for HLA-DRA, and P = 2.3 × 10−19 for CD74) or HC biopsies (P = 3.1 × 10−33 for HLA-DRA, and P = 1.6 × 10−27 for CD74; Table A1). In both cases, promoter accessibility for these genes was increased in accordance with the higher protein expression in the inflamed epithelium (P = 1.4 × 10−4 for HLA-DRA, and P = 2.8 × 10−4 for CD74) (Figure 5B and C). Levels of other proteins involved in antigen processing and presentation, such as the proteasome protein encoded by the proteasome subunit beta type-9 (PSMB9) gene and the MHC class I peptide transporters transporter associated with antigen processing (TAP-1 and TAP-2), were also significantly higher in inflamed UC than HC epithelium (P = 6.2 × 10−23 for PSMB9, P = 2.0 × 10−6 for TAP1, and P = 5.6 × 10−4 for TAP2; Figure 5D–F and Table A1). However, in contrast to LCN2, HLA-DRA, and CD74, there was no correlation between inflammation and the accessibility of chromatin near the PSMB9 or TAP1 and TAP2 genes (Figure 5D–F).Figure 5 Comparison of protein expression and ATAC-peak accessibility. Expression of protein and ATAC-seq peak accessibility in inflamed, uninflamed, and healthy epithelia tissue from the gut for (A) LCN2, (B) HLA_DRA, (C) CD74, (D) PSMB9, (E) TAP1 and (F) TAP2.

In the absence of inflammation, differences in protein expression between uninflamed UC and HC epithelial cells were much more modest. However, IgA was the most differentially associated with uninflamed UC biopsies relative to HCs (IGHA1; P = 5.2 × 10−4; Table A1). Likewise, IgG1 was among the proteins most strongly associated with inflamed UC biopsies compared to HCs (IGHG1; P = 2.0 × 10−16; Table A1). Unsurprisingly, neither IGHA1 nor IGHG1 was detected in the chromatin analysis by ATAC-seq, as antibodies are exclusively made by B cells, not epithelial cells.

Determination of Cell Type-Specific Protein Expression

We aimed to determine the cell type-selective expression of the proteins we identified as regulated. To accomplish this, we utilized a publicly available single-cell RNA sequencing dataset.4 This data confirmed that the expression of DUOX2 mRNA is restricted to epithelial populations from inflamed sites (Figure 6) with significantly reduced expression in noninflamed sites and very low expression in healthy sites. In contrast, and consistent with the proteomics data, AQP8 demonstrated high mRNA expression in healthy and noninflamed sites (Figure 6). For both DUOX2 and AQP8, mRNA expression was primarily seen in mature enterocytes, suggesting that these are the predominant epithelial cell type we purified, although AQP8 mRNA is also expressed fairly well by immature enterocyte populations, raising the possibility that a greater fraction of these immature cells could exist in our uninflamed biopsies to contribute to them having more AQP8 and less DUOX2 protein in our data. There was little to no expression of either protein’s mRNA in immune cells or stromal cells (data not shown) to suggest such cells could be contaminating our data.Figure 6 Single-cell expression of DUOX2 from IBD subjects. Single-cell expression from epithelial cell compartment derived from Smillie et al.4 Dot intensity represents the average expression level, and the size of dots represents the percentage of cells expressing the gene of interest.

Discussion

Our unique epithelial-specific dataset addressed changes in protein expression that distinguish healthy donor colonic epithelium and the uninflamed and inflamed colonic epithelia of UC patients. These proteomic changes may underlie pathogenic changes in UC, encompassing epithelial erosion and depletion of the mucus barrier, leading to bacterial translocation, inflammation, and tissue damage. Along with this, epithelial-based repair mechanisms including antimicrobial responses and antigen presentation may distinguish inflamed and uninflamed sites.

Our analysis showed that the proteomic profile of UC inflamed biopsies segregated from those of all uninflamed biopsies, while the uninflamed profiles from UC patients clustered with proteomics of biopsies from healthy subjects. Transcriptomic analysis of IBD colonic epithelium isolated from biopsies by laser capture microdissection has shown a similar clustering pattern, with uninflamed profiles overlapping with the healthy transcriptome.20 In contrast, we found several hundred proteins were differentially expressed in inflamed UC biopsies as compared to biopsies from HCs. Those most increased with inflammation tended to be involved with oxidative stress, antimicrobial responses, and antigen presentation. We explored the epigenetic basis of key proteomic changes and found that open chromatin near the promoters of some but not all of the genes encoding these proteins correlates with their expression.

The water channel protein AQP8 was significantly higher in uninflamed than inflamed colonic epithelial cells. In the small and large intestines, AQP8 is localized to the apical surface of mucosal epithelial cells,21 and allows bidirectional transport of water and H2O2.22 Reduced AQP8 expression has been linked with collagenous colitis23 and bile acid diarrhea,24 and has been noted in active UC,21,25, 26, 27 Crohn’s disease (CD),26,27 and mouse models of colitis.26,27 Under conditions of hypoxia or ER stress, the activity of AQP8 to transport H2O2 and water is impaired,28 and downregulation of AQP8 expression has been suggested as a defense mechanism against severe oxidative stress.27

Consistent with the oxidative stress response, DUOX proteins were among the most strongly and significantly elevated proteins in inflamed colonic epithelial cells of UC. DUOX2 is a hydrogen peroxide-generating enzyme involved in antimicrobial defense at the mucosal surface. The Ca2+-dependent nicotinamide adenine dinucleotide phosphate, reduced form oxidase encoded by DUOX2, along with its maturation partner encoded by DUOXA2, mediates the production of epithelial H2O2.29 We found the products of both DUOX2 and DUOXA2 genes to be more common in inflamed colon epithelial cells, consistent with single cell transcriptomic studies revealing enhanced expression of DUOX2 and DUOXA2 in inflamed epithelial cells of UC.4,30 DUOX2/DUOXA2 is localized to epithelial crypts on the apical surface,31 and is known to be upregulated in UC,32 CD,30 very early onset IBD,33 and mouse models of IBD.34 Under homeostatic conditions, epithelial H2O2 plays a protective role, to drive innate immune responses and maintain antimicrobial immunity.29,33 Under conditions of disease, excessive generation of reactive oxygen species from DUOX2 activation can promote tissue inflammation.31,33,35

The major strength of our study is a parallel whole-genome survey of open chromatin performed by ATAC-seq, in conjunction with a proteomic analysis of epithelial cells purified from inflamed vs uninflamed colonic biopsies from UC patients vs HCs. This analysis revealed an epigenetic basis for some of their most significant differences in protein expression, including AQP8 and dual oxidase 2 (DUOX2 and DUOXA2). The hypoxia-inducible transcription factor, HIF-1α, is a modulator of AQP8 in hepatocytes,36 and was one of several transcription factor binding motifs identified in epithelial cells (data not shown). Gut epithelial expression of DUOX2 is induced by gut microbiota, downstream of inflammatory signals including NF-kB, MyD88, and p38.37

Gut microbiota also stimulates release of lipocalin 2, a validated fecal biomarker of intestinal inflammation that plays a key antimicrobial function in the gut.38 Lipocalin 2 was highly increased in the proteome of inflamed biopsies, consistent with the prominent induction of LCN2 transcript in UC,25 and elevated expression of LCN2 in proteomic analysis of unfractionated UC mucosal biopsies.9 LCN2 can be produced by intestinal epithelial cells in addition to neutrophils.39 In accordance with this, we detected LCN2 in our sample of enriched epithelial cells, in the absence of neutrophil markers such as calprotectin. Although LCN is considered to be primarily neutrophil-derived with epithelial cells and monocytes contributing lesser amounts,39 it was one of the most highly induced proteins in the inflamed UC epithelial dataset, and ATAC-seq showed enhanced chromatin accessibility. These observations suggest that epithelial cells may be a more robust source of lipocalin than previously appreciated. Interestingly, epithelial expression of LCN2 can be induced by oxidative stress,40 suggesting a common mechanism with observed changes in DUOX2/DUOXA2.

Other notable differences in proteins quantitated between inflamed UC biopsies and HCs included HLA-DRA and CD74, involved in antigen presentation. Elevated HLA-DRA is a hallmark of the inflamed epithelium in IBD,41 and can be up-regulated by epithelial cells upon exposure to interferon gamma.42 CD74 functions as the invariant chain and chaperone for MHC class II, and are the receptor for the cytokine migration inhibitory factor. Functionally, it has been linked to mucosal healing in IBD, promoting intestinal epithelial regeneration and repair.43 Current findings point to a role for chromatin remodeling in promoting the expression of HLA-DRA and CD74.

In accordance with this, several proteins associated with antigen processing and presentation were induced in UC. Proteasome subunit beta type 9 (PSMB9; LMP2), is a component of the 20S proteasome that degrades endogenous proteins. Peptides generated by the 20S proteasome are transported by the ER-resident TAP1/TAP2 complex, for loading onto MHC class I molecules. TAP1, TAP2, and PSMB9 proteins were all increased in UC inflamed tissues compared to tissues from HCs, and PSMB9 was also elevated in UC uninflamed tissues compared to healthy. Interestingly, PSMB9 (LMP2) and TAP1 share a bidirectional promoter.44 Although PSMB9, TAP1, and TAP2 proteins were all increased in inflamed tissues, ATAC-seq findings do not indicate increased accessibility of the promoter region.

Surprisingly, antibodies were observed to be among the proteins most differentially present on epithelial cells from UC patients relative to HCs. IgA (IGHA1) was the most so on epithelial cells from uninflamed UC biopsies and IgG1 (IGHG1) was among the most enriched proteins of inflamed UC biopsies relative to HC samples (Table A1). While IgA-producing B cells are more common than IgG-producing ones in normal colon, this ratio shifts to favor IgG in UC, particularly as it gets more inflamed.45 Because the current study was an analysis of isolated epithelial cells, lacking any B cells that can produce immunoglobins, and because open chromatin corresponding to IGHA1 or IGHG1 was not detected, the source of this protein is presumably antibodies bound to epithelial cells. Open chromatin near the FCGR1A and FCGR1B genes encoding Fc receptors for IgG were identified by ATAC-seq, but were not modulated by inflammation, and no protein for IgG receptors was identified in the epithelial cell proteome, regardless of inflammation. If UC epithelial cells are not using Fc receptors to preferentially bind these antibodies, they may be the targets of autoantibodies, suggesting a role for the humoral immune system in the pathogenesis of UC. Indeed, high serum titers of both IgA and IgG autoantibodies specific for integrin αVβ6, which is expressed on the surface of epithelial cells, have recently been very strongly correlated with the diagnosis of UC,46 even predating its onset by as much as a decade.47

Taken together, our findings are consistent with oxidative stress at the colonic epithelium in UC driving antimicrobial responses, induction of antigen processing and presentation, and tissue damage. Our analysis indicates that changes in chromatin accessibility modulate the expression of AQP8, DUOX2/DUOXA2, LCN2, HLA-DRA, CD74, and other key proteins at sites of colonic inflammation, but do not account for all of the protein modulation in the colon. Additional factors, which may include protein stabilization, hydrolyzing enzymes, or post-transcriptional modifications, could contribute to shifts in the proteome associated with active UC. By defining epithelial-associated changes, the current proteomics and ATAC-seq databases may help to define mechanisms underlying damage and repair in UC.

Supplementary Materials

Table A1

Acknowledgments:

The authors thank Kassidy Benoscek (BRI), for supervising subject recruitment, and Adam Woijno (BRI), for assistance with cell sorting. The authors thank Dr Monica Schenone (Pfizer) for helpful discussions and review of the manuscript, and Lawrence Weissbach (Pfizer) for project management.

Authors' Contributions:

Study Concept and Design: James Lord, Scott Jelinsky, Isac Lee, Mara Monetti, Marion Kasaian, Caitlyn Dickinson, Richard Gieseck III. Acquisition of Data: Suzanne Breitkopf, Mara Monetti, Jeffrey Culver, Flora Martz, Ramya Kongala, Vanessa Vo. Analysis and Interpretation of Data: Scott Jelinsky, Isac Lee, James Lord, Liang Xue, Mara Monetti, Jeffrey Culver, Suzanne Breitkopf. Drafting of Manuscript: Scott Jelinsky, James Lord, Marion Kasaian, Isac Lee. Manuscript Review and Editing: Jeffrey Culver, Caitlyn Dickinson, Liang Xue, Richard Gieseck III. Project Administration: Caitlyn Dickinson, Marion Kasaian.

Conflicts of Interest: These authors disclose the following: Scott Jelinsky, Isac Lee, Mara Monetti PhD, Susanne Breitkopf, Jeffrey Culver, Vanessa Vo, Liang Xue, Richard Gieseck III, Caitlyn Dickinson, and Marion Kasaian were shareholders and employees of Pfizer Inc at the time of this research. The remaining author disclose no conflicts.

Funding: This study was funded through a collaborative research agreement between by 10.13039/100004319 Pfizer Inc and the Benaroya Research Institute.

Ethical Statement: This study was approved by the Benaroya Research Institute Institutional Review Board.

Data Transparency Statement: All relevant data are within the manuscript and its Supporting Information files.

Reporting Guidelines: None.

Material associated with this article can be found, in the online version, at https://doi.org/10.1016/j.gastha.2024.04.014.
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