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Quantitative proteomic studies of the intestinal mucosa provide new insights into the molecular mechanism of ulcerative colitis

BMC Gastroenterology volume 25, Article number: 48 (2025) Cite this article

Abstract

Background

Differentiation between ulcerative colitis (UC) and other intestinal inflammatory diseases is difficult, and the precise etiology of UC is poorly understood. Thus, there is a need for novel diagnostic and prognostic biomarkers for UC.

Methods

Intestinal mucosal biopsy tissue specimens of inflamed (ulcerative colitis-inflamed, UC-I) and non-inflamed (ulcerative colitis-noninflamed, UC-N) tissue were obtained simultaneously during colonoscopy from newly diagnosed UC patients prior to any treatments. Label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) quantitative proteomics was used to detect proteomic differences between UC-I, UC-N, and normal control subjects (n = 5). Proteins with a fold-change > 1.5 and P < 0.05 between groups were considered to be differentially expressed (DEPs). Candidate biomarkers were further verified in 8 patients of each group by parallel reaction monitoring (PRM) (a prospective cohort, n = 8). Expression of TXNDC5 was quantified using immunohistochemistry (IHC).

Results

A total of 4,788 proteins were identified. Multiple upregulated pathways, including leukocyte trans-endothelial migration and natural killer (NK) cell-mediated cytotoxicity, were identified. Network analysis showed that proteins were involved in 4 pathways in UC-I and 3 pathways in UC-N tissues, and participated in protein-protein interactions. Increased expression of 9 DEPs, including TXNDC5, EPX, and ITGAM were detected in UC patients compared to normal control subjects. Subsequent verification of the 9 DEPs by PRM confirmed the reliability of the mass spectrometry data. TXNDC5 expression was significantly increased in UC.

Conclusions

The pathways, networks, and proteins identified in this study may provide new insights into the molecular pathogenesis of UC. Further studies are required to determine if the proteins identified may help in the diagnosis and treatment of UC.

Peer Review reports

Introduction

Ulcerative colitis (UC) is an immune-mediated chronic condition, and the prevalence is increasing globally [1]. The condition consists of life-long relapsing inflammation of the colon, and thus has a substantial impact on the physical and mental health of patients [2]. While there is no curative treatment, if not properly managed UC can result in serious complications such as intestinal hemorrhage and perforation, toxic megacolon, and colorectal cancer (CRC) [3]. Unfortunately, the precise cause and pathogenesis of UC is unclear [4], and the differential diagnosis of symptomatic patients is broad. Thus, novel biomarkers to establish a diagnosis of UC and predict a prognosis are needed.

Quantitative proteomics has been used in a number of diseases to identify diagnostic and prognostic biomarkers, and increase understanding of the disease pathophysiology. Over the past decade, only a few studies have used a proteomics approach to identify proteins and pathways that can help diagnose inflammatory bowel disease (IBD). Ning et al. identified differentially expressed proteins (DEPs) involved in the nicotinamide adenine dinucleotide (NAD) metabolism and signaling pathway between UC, Crohn’s disease (CD), and normal colon mucosa using tandem mass tag-(TMT)-based shotgun proteomics [5]. In another study, Lehmann et al. identified several disease specific marker proteins using a metaproteome approach to distinguish normal control subjects from patients with IBD [6]. These studies suggest that liquid chromatography tandem mass spectrometry (LC-MS/MS) has the potential to identify novel biomarkers for UC, and assist in understanding the underlying pathophysiology.

The purpose of this study was to use LC-MS/MS to identify proteomic differences between UC patients and healthy persons without IBD in order to identify novel proteins involved in the pathogenesis of UC.

Materials and methods

Study design

Intestinal mucosal biopsy tissue specimens of inflamed (ulcerative colitis-inflamed, UC-I) and non-inflamed (ulcerative colitis-noninflamed, UC-N) tissue were obtained simultaneously during colonoscopy from 5 newly diagnosed UC patients prior to any treatments, and from 5 normal control subjects without any evidence of IBD. The tissue specimens were subjected to LC-MS/MS quantitative proteomics analysis, then another 8 samples of each group were analyzed by parallel reaction monitoring (PRM) for further verification of the screened biomarkers. Finally, immunohistochemistry (IHC) for detection of TXNDC5 was conducted on tissue specimens from another 15 pairs of patients.

Tissue sample collection

The Institutional Ethics Committees approved this study (registration ID: NFEC-202303-K29), and all enrolled subjects provided written informed consent. Tissue biopsy samples were obtained from the inflamed and non-inflamed areas of sigmoid colon in UC patients undergoing colonoscopy at Nanfang Hospital, Guangzhou, China. The recruited subjects were newly diagnosed with UC, and had not received any treatment for IBD. The presence of colonic inflammation was determined by endoscopic and histological examination of tissue specimens. The normal control subjects were persons receiving screening colonoscopies without a diagnosis of any known active or chronic intestinal pathology. Only non-inflamed biopsy tissue specimens of the sigmoid colon that exhibited macroscopically and histologically normal mucosa from the control subjects were used in the study. The tissue specimens were immediately frozen in liquid nitrogen for subsequent proteomic analysis. UC was diagnosed in accordance with general guidelines based on thorough clinical, endoscopic, and histological evaluation.

Protein extraction and trypsin digestion

The tissue samples in liquid nitrogen were ground into cell powder, and then lysis buffer (8 M urea, 1% protease inhibitor cocktail) was added, followed by sonication on ice 3 times. The remaining debris was removed by centrifugation at 12,000 ×g at 4 °C for 10 min. Finally, the supernatant was collected, and the protein concentration was measured with a Bicinchoninic Acid (BCA) kit. During digestion, the protein solution was reduced with 5 mM dithiothreitol for 30 min at 56 °C, and alkylated with 11 mM iodoacetamide for 15 min at room temperature in the dark.

The protein sample was then diluted by adding 100 mM TEAB to urea concentration < 2 M. Trypsin was added (1:50 trypsin: protein mass ratio) for overnight digestion, and the a 1:100 trypsin: protein mass ratio was used for a second digestion for 4 h. Finally, the peptides were desalted using a C18 SPE column.

LC-MS/MS analysis

The tryptic peptides were dissolved in solvent A (0.1% formic acid), directly loaded onto a home-made, reversed-phase analytical column (15 cm length, 75 μm internal diameter). Peptides were separated with a gradient of 6–23% solvent B (0.1% formic acid in 98% acetonitrile) over 26 min, 23–35% over 8 min, and increasing to 80% over 3 min, then holding at 80% for the last 3 min. The separation was performed at a constant flow rate of 400 nL/min using an EASY-nLC 1000 UPLC system.

The peptides were subjected to a nanospray ion (NSI) source, followed by MS/MS in a Q ExactiveTM Plus system (Thermo) coupled online to the UPLC. The electrospray voltage was 2.0 kV. Peptides were analyzed in the Orbitrap, with the m/z scan range from 350 to 1800 m/z. Peptides were selected using a NCE setting of 28, and 20 MS/MS scans were acquired per cycle. The dynamic exclusion was set to 15 s.

The MS/MS data were loaded into MaxQuant (version1.5.2.8), and searched against the human UniProt database. Trypsin/P was set with up to 4 missing cleavages. The mass tolerance was set to 20 ppm in the first search, and 5 ppm in the main search. Carbamidomethyl on Cys was set as a fixed modification, and acetylation modification and oxidation on Met were specified as variable modifications. The false detection rate (FDR) was adjusted to < 1%.

Bioinformatics analysis

The gene Ontology (GO) annotation proteome was derived from the UniProt-GOA database (http://www.ebi.ac.uk/GOA/). Proteins were classified by GO annotation based on 3 categories: biological process, cellular component, and molecular function. The identified proteins domain functional descriptions were annotated by InterProScan (a sequence analysis application) based on the protein sequence alignment method using the InterPro domain database.

The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate protein pathways. Then, Wolfpsort, a subcellular localization predication software, was used to predict subcellular localization. Finally, all differentially expressed protein database accessions or sequences were searched against the STRING database (version 11.0) for protein-protein interactions.

Immunohistochemistry (IHC)

Colon mucosal biopsy specimens were obtained from another 15 patients with active UC who had undergone colonoscopy examination at Nanfang Hospital, Guangzhou, China. These patients were diagnosed by certified hospital gastroenterologists. IHC staining for TXNDC5 (Catalog number 19834-1-AP, Proteintech) was performed on paraffin-embedded sections of tissue. Tissues were cut into 4µm-thick sections, followed by deparaffinization and subsequent hydration. The sections were incubated with primary antibody for human TXNDC5 overnight at 4°C, followed by incubation with anti-IgG at 37°C for 1 h. The samples were visualized with 3,3’-diaminobenzidine (DAB), and observed under an optical microscope.

Statistical analysis

All statistical analyses were performed using SPSS version 24.0 software (SPSS, Inc., Chicago, IL, USA). Analysis of variance (ANOVA), the K independent samples test, or the independent samples t-test were used for comparisons where appropriate. A value of P < 0.05 was considered statistically significant.

Results

Descriptive characteristics

Biopsy tissue specimens from inflamed and non-inflamed areas of the sigmoid colon were obtained from 26 patients undergoing diagnostic colonoscopy. A summary of the patient characteristics is shown in Table 1. The average age of the control subjects (n = 13, sum of discovery cohort and validation cohort) was 42.4 ± 7.1 years (range, 32–52 years), and of patients with UC (n = 13) was 43.8 ± 7.9 years (range, 31–55 years) (P > 0.05). There was no sex imbalance between normal controls and patients with UC, and 46.2% of patients with UC exhibited pancolitis.

Table 1 Patient characteristics
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Proteomics analysis

Analysis of the global proteome was performed using LC-MS/MS on UC-I, UC-N, and colonic mucosa tissue specimens from normal control subjects to determine the proteomic signature of the intestinal mucosa (Fig. 1).

Fig. 1
figure 1

Study design. (1) Differentially expressed proteins (DEPs) and candidate prognostic biomarkers differentiating ulcerative colitis (UC) from normal subjects were identified with tandem mass proteomics. (2) The candidate biomarkers were preliminarily validated in 3 groups of samples by parallel reaction monitoring (PRM)

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A total of 4,788 proteins were identified (Fig. 2A). Principal component analysis (PCA) showed a distinct separation of normal control and UC proteomes based on the combination of PC1 and PC2 (Fig. 2B). As shown in Fig. 2C, Pearson correlation analysis showed a positive correlation among UC-I, UC-N, and colon tissue from normal control subjects. Using a FDR filter under 0.05 with a difference of 1.5-fold, we identified 1,052 DEPs between UC-I and normal control mucosa, and 366 DEPs between UC-N and normal control mucosa. A total of 588 DEPs were identified between UC-I and UC-N mucosa (Fig. 2D and F). Finally, 511 upregulated proteins and 541 downregulated proteins were identified between UC-I and normal control mucosa (Fig. 2D).

Fig. 2
figure 2

Proteome bioinformatics analysis of human colon tissue. A Venn diagram of proteins identified by mass proteomics, from which 4,788 co-expressed proteins were used for downstream analysis. B Principal component analysis (PCA) of proteomics data showing separation of ulcerative colitis (UC) colon proteomes (UC-I, green; UC-N, blue) from controls (red). The points represent biological replicates (n = 5). C Heatmap of Pearson correlation coefficients for proteomics data (red, high correlation; blue, high negative correlation; white, lack of correlation). D-F) Volcano map of the 1,052 DEPs of UC-I compared to healthy controls; 366 DEPS of UC-N compared to healthy controls; and 588 DEPs between UC-I and UC-N (DEPs, differentially expressed proteins; UC-I, ulcerative colitis-inflamed, UN-N, ulcerative colitis-noninflamed.)

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The DEPs were divided into 6 clusters by analysis of the expression trends of the proteins in the different groups. The proteins in the first cluster first increased, and then decreased slowly during the development of UC, while proteins in the second cluster increased and then continuously decreased. Proteins in cluster 3 consistently increased in UC tissue, while those in cluster 4 first slowly declined and then increased in UC tissue. Proteins in cluster 5 continuously declined, and proteins in cluster 6 first decreased and then slowly increased during the development of UC (Fig. 3).

Fig. 3
figure 3

Cluster analysis of expression patterns of differentially expressed proteins (DEPs). Proteins were divided into 6 clusters by the changing trends of protein expression

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Subcellular localization in the cytoplasm accounted for approximately 30% of DEPs in the UC-I group and the UC-N group compared with the normal control group (Fig. 4A and B). Similarly, 156 (26.53%) of the DEPs between the UC-I group and the UC-N group were distributed in the cytoplasm (Fig. 4C). To further elucidate the features and functions of these proteins, GO analyses were performed for the 511 upregulated proteins in the UC-I group compared to the normal control group. As shown in Figs. 4F and 175 proteins were involved in the GO biological process category “signaling”. Additionally, 170 proteins were involved in “immune system process”.

Fig. 4
figure 4

Cluster heatmap analysis and functions of differentially expressed proteins (DEPs). A-C) Subcellular distribution of DEPs of the UC-I, UC-N, and normal control groups. D) KEGG enrichment analysis for all DEPs identified from the 3 groups. E) GO cellular components for all DEPs identified from the 3 groups. F) GO analyses of upregulated proteins in the UC-I compared to the normal control group

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KEGG pathway enrichment analysis was used to compare the UC-I, UC-N, and normal control groups. As shown in Fig. 4D, there was significant enrichment in leukocyte trans-endothelial migration and natural killer (NK) cell-mediated cytotoxicity in the UC-I group, and the UC-N group exhibited changes in regulation of lipolysis in adipocytes and the PI3K-Akt signaling pathway.

GO enrichment analysis of the cellular component category revealed that compared to the normal control group, DEPs of the UC-I group were primarily related to the cell membrane region, transmembrane transporter complex, protein complex involved in cell adhesion, and the integrin complex. DEPs between the UC-I group and UC-N group were mainly distributed in the endoplasmic reticulum (ER) and mitochondrial matrix (Fig. 4E).

To gain insights into the biological processes and protein interaction networks involved in UC, we used the STRING (v.11.0) online database with a high confidence score (> 0.7) and Cytoscape software to construct PPI (protein-protein interactions) networks (Fig. 5). Comparison of the UC-I and normal control group revealed 90 DEPs (62 upregulated and 28 downregulated) in PPI networks containing 4 major subgroups (Fig. 5A). The leukocyte trans-endothelial migration, NK cell-mediated cytotoxicity, protein processing in the ER, and the PPAR signaling pathway shared strong connections with each other, indicating the vital importance of screening for key candidate proteins. In the UC-I and UC-N groups, 3 major PPI networks were identified (cell adhesion molecules, protein processing in the ER, and PPAR signaling pathway), and formed a larger network with connecting DEPs. Notably, most of the proteins in the PPAR signaling pathway subgroup were downregulated (Fig. 5B).

Fig. 5
figure 5

Protein-protein interaction (PPI) networks of differentially expressed proteins (DEPs) from: (A) UC-I compared to healthy control group; (B) UC-I compared to UC-N group. DEPs from the 3 groups were mapped using STRING (v.11.0) and Cytoscape (3.4.0) to clearly show the PPI. Node colors represent changes in protein expression (red = upregulated, green = downregulated)

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Of the upregulated candidate proteins, 9 proteins with the greatest expression were further validated by PRM. As shown in Fig. 6A, the levels of the 9 proteins were increased with upregulated colitis disease severity than normal (all, P < 0.05). Notably, TXNDC5, EPX, and ITGAM expressions were the most important for differentiating UC from normal control tissue (all, P < 0.05). The heatmap of these 9 proteins confirmed the aforementioned results (Fig. 6B).

Fig. 6
figure 6

Relative expressions of 9 candidate biomarkers detected by PRM based on mass spectrometry of intestinal mucosa tissue specimens to distinguish patients with UC from normal control subjects (A, scatter plot; B, heatmap). *P < 0.05, **P < 0.01, ***P < 0.001. (CYBB, cytochrome b; ITGAM, integrin alpha-M; HLA-C, HLA class I histocompatibility antigen C; TXNDC5, thioredoxin domain-containing protein 5; IFI16, gamma-interferon-inducible protein 16; RNF213, E3 ubiquitin-protein ligase; PML, protein PML; EPX, eosinophil peroxidase; GBP1, guanylate-binding protein 1)

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We then analyzed TXNDC5 protein expression in colon specimens from patients with UC. TXNDC5 protein expression was higher in patients with UC than in controls, confirmed by IHC (Fig. 7).

Fig. 7
figure 7

TXNDC5 is upregulated in patients with ulcerative colitis (UC). (A) Expression of TXNDC5 by immunohistochemical (IHC) staining (original magnification, ×100 and ×400). (B) IHC staining of TXNDC5 in epithelial cells was scored from colon tissue specimens from patients with UC and normal control subjects (n = 15)

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Discussion

IBD is characterized by changes in the levels of acute-phase response markers such as C-reactive protein (CRP) and fecal calprotectin (FC), which can be detected in the serum or stool, and an altered erythrocyte sedimentation rate (ESR) [7]. CRP and ESR have been reported to be able to distinguish IBD from normal persons, but the difference between CD and UC is heterogenic [7, 8]. Several antibodies including perinuclear anti-neutrophil cytoplasmic antibody (pANCA) and anti-Saccharomyces cerevisiae antibody (ASCA) are characteristically present in patients with IBD; however, poor sensitivity limits their clinical use in differentiating UC from CD [9, 10]. Therefore, there is a need for novel biomarkers for the early diagnosis and prediction of prognosis of IBD.

The pathogenesis of UC is complex and not completely understood, and typical findings are alterations in the gut microbiota and the activation of different immune cell types [11,12,13]. In recent years, proteomics has been used to identify accurate biomarkers for the diagnosis and treatment of IBD by analyzing and characterizing large amounts of data, and many studies have focused on proteomic changes in IBD [14,15,16]. In this study label-free LC-MS/MS proteomics was used to identify DEPs in patients with UC in order to find novel candidate biomarkers.

We identified 4,788 DEPs between UC-I, UC-N, and normal colonic tissue. The results showed that the leukocyte trans-endothelial migration pathway and the NK cell-mediated cytotoxicity pathway were upregulated in UC. It is well known that recruitment of leukocytes from the circulation to the intestine is an essential process in UC and CD [17,18,19], and is now being examined as a potential target for therapy. The success of vedolizumab (anti-α4β7) for the treatment of UC has proven that the leukocyte trans-endothelial migration pathway plays an important role in UC progression [20]. Previous study using a dextran sodium sulfate (DSS)-induced colitis model demonstrated that the NK cell-mediated cytotoxicity pathway is involved in the development of UC [21].

We observed that a negative enrichment of proteins was involved in the PPAR signaling pathway in UC-I colon tissue, which is consistent with previous reports [22,23,24,25]. PPARγ is highly expressed in intestinal epithelial cells and macrophages, and plays a critical role in the mucosal immune response [23]. The expression of PPARγ was downregulated in the colonic mucosa of patients with UC compared with normal controls [24]. Notably, a study using a murine DSS-induced colitis model showed a loss of PPARγ expression in macrophages [25]. Our study also showed that protein processing in the ER is highly activated in UC, which is in agreement with the results of numerous studies that have found excessive epithelial ER stress contributes to the pathogenesis of UC by promoting inflammatory cytokines, activating epithelial cell autophagy, and initiating intestinal inflammation [26,27,28,29].

Our results showed significantly increased TXNDC5, EPX, and ITGAM protein levels in patients with UC, which have been rarely reported before. TXNDC5 is abundantly expressed in endothelial cells and fibroblasts [30], and abnormally expressed TXNDC5 has been implicated in various diseases such as rheumatoid arthritis (RA) [31], cancer [32], and organ fibrosis [33]. Shih et al. reported that TXNDC5 facilitates cardiac fibrosis by promoting extracellular matrix (ECM) protein folding, and enhancing the c-Jun N-terminal kinase (JNK) signaling pathway [34]. In addition, an identical role of TXNDC5 in the transforming growth factor (TGF)-β pathway in pulmonary and renal fibrosis has been confirmed by several studies [35, 36]. Intestinal fibro-stenosis is one of the most common and serious complications in the late stage of IBD, including UC [37]. Epithelial-to-mesenchymal transition (EMT) has been identified as a pathogenic mechanism of UC-related intestinal fibrosis [38]. The TGF-β pathway plays a central regulatory role in intestinal fibrosis progression through the SMAD dependent pathway [39, 40]. Our study confirmed the increased expression of TXNDC5 in UC, which is consistent with the results previously reported by Nowak JK et al. [41]. Taken together, the aforementioned results suggest that our finding of upregulation of TXNDC5 in the mucosa of patients with UC may reflect a mechanism of fibrosis that has not been previously identified. To our knowledge, there has been little study on the role of TXNDC5 in UC related-fibrosis.

Conclusions

In summary, the present study identified proteins and signaling pathways that were significantly different between patients with UC and normal controls using LC-MS/MS quantitative proteomics. Of the proteins identified, the expressions of TXNDC5, EPX, and ITGAM were further validated, specially TXNDC5. The results of this study provide novel insights into the molecular mechanism of UC, and the proteins identified have the potential to be developed into novel markers for the diagnosis and treatment of UC.

Data availability

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the iProX partner repository with the dataset identifier PXD040747. iProX: pinkmoon，xj330748.

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Acknowledgements

The authors would like to thank Wenfeng Shao for support of this work.

Funding

This study was supported by the National Natural Science Foundation of China (No. 81700489), Natural Science Foundation of Guangdong Province (No. 2017A030313578, No. 2020A1515110036), Science and Technology Project of Guangzhou (No. 201707010276) and Director Foundation of Nanfang Hospital (No. 2023A044).

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Author notes

  1. Yandong Guo and Dahal Pabitra contributed equally to this work.

Authors and Affiliations

  1. Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China

    Yandong Guo, Dahal Pabitra, Lei Pan, Lanbo Gong, Aimin Li, Side Liu & Jing Xiong

  2. Guangdong Provincial Key Laboratory of Gastroenterology, Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong Province, China

    Jing Xiong

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  1. Yandong Guo
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  4. Lanbo Gong
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  5. Aimin Li
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  6. Side Liu
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Contributions

Original draft of the manuscript: Yandong Guo. Review and editing of the manuscript: Dahal Pabitra. Sample collection: Lei Pan. Interpretation of the results: Lanbo Gong, Aimin Li, Side Liu. Conception and design of the study: Jing Xiong. All authors approve the final draft of the manuscript and provide consent for publication.

Corresponding author

Correspondence to Jing Xiong.

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Ethics approval and consent to participate

The study was approved by the Ethics Committee of Nanfang Hospital, Southern Medical University, and written informed consent was obtained from each patient (registration ID: NFEC-202303-K29). All the procedures were carried out in accordance with the Declaration of Helsinki.

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All authors approve the final draft of the manuscript and provide consent for publication.

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The authors declare no competing interests.

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Guo, Y., Pabitra, D., Pan, L. et al. Quantitative proteomic studies of the intestinal mucosa provide new insights into the molecular mechanism of ulcerative colitis. BMC Gastroenterol 25, 48 (2025). https://doi.org/10.1186/s12876-025-03647-y

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Keywords

BMC Gastroenterology

ISSN: 1471-230X

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