Identification of novel serological biomarkers for inflammatory bowel disease using Escherichia coli proteome chip

Chien Sheng Chen, Sean Sullivan, Troy Anderson, Aik Choon Tan, Philip J. Alex, Steven R. Brant, Carmelo Cuffari, Theodore M Bayless, Monica V. Talor, C. Lynne Burek, Huan Wang, Richard Li, Lisa Datta, Yuqiong Wu, Raimond Winslow, Heng Zhu, Xuhang Li

Research output: Contribution to journalArticle

Abstract

Specific antimicrobial antibodies present in the sera of patients with inflammatory bowel disease (IBD) have been proven to be valuable serological biomarkers for diagnosis/prognosis of the disease. Herein we describe the use of a whole Escherichia coli proteome microarray as a novel high throughput proteomics approach to screen and identify new serological biomarkers for IBD. Each protein array, which contains 4,256 E. coli K12 proteins, was screened using individual serum from healthy controls (n = 39) and clinically well characterized patients with IBD (66 Crohn disease (CD) and 29 ulcerative colitis (UC)). Proteins that could be recognized by serum antibodies were visualized and quantified using Cy3-labeled goat anti-human antibodies. Surprisingly significance analysis of microarrays identified a total of 417 E. coli proteins that were differentially recognized by serum antibodies between healthy controls and CD or UC. Among those, 169 proteins were identified as highly immunogenic in healthy controls, 186 proteins were identified as highly immunogenic in CD, and only 19 were identified as highly immunogenic in UC. Using a supervised learning algorithm (k-top scoring pairs), we identified two sets of serum antibodies that were novel biomarkers for specifically distinguishing CD from healthy controls (accuracy, 86 ± 4%; p <0.01) and CD from UC (accuracy, 80 ± 2%; <0.01), respectively. The Set 1 antibodies recognized three pairs of E. coli proteins: Era versus YbaN, YhgN versus FocA, and GabT versus YcdG, and the Set 2 antibodies recognized YidX versus FrvX. The specificity and sensitivity of Set 1 antibodies were 81 ± 5 and 89 ± 3%, respectively, whereas those of Set 2 antibodies were 84 ± 1 and 70 ± 6%, respectively. Serum antibodies identified for distinguishing healthy controls versus UC were only marginal because their accuracy, specificity, and sensitivity were 66 ± 5, 69 ± 5, and 61 ± 7%, respectively (p <0.04). Taken together, we identified novel sets of serological biomarkers for diagnosis of CD versus healthy control and CD versus UC.

Original languageEnglish (US)
Pages (from-to)1765-1776
Number of pages12
JournalMolecular and Cellular Proteomics
Volume8
Issue number8
DOIs
StatePublished - 2009

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Biomarkers
Proteome
Inflammatory Bowel Diseases
Escherichia coli
Crohn Disease
Ulcerative Colitis
Antibodies
Serum
Escherichia coli Proteins
Microarrays
Proteins
Escherichia coli K12
Sensitivity and Specificity
Protein Array Analysis
Microarray Analysis
Goats
Proteomics
Supervised learning
Anti-Idiotypic Antibodies
Learning algorithms

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Analytical Chemistry

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Identification of novel serological biomarkers for inflammatory bowel disease using Escherichia coli proteome chip. / Chen, Chien Sheng; Sullivan, Sean; Anderson, Troy; Tan, Aik Choon; Alex, Philip J.; Brant, Steven R.; Cuffari, Carmelo; Bayless, Theodore M; Talor, Monica V.; Burek, C. Lynne; Wang, Huan; Li, Richard; Datta, Lisa; Wu, Yuqiong; Winslow, Raimond; Zhu, Heng; Li, Xuhang.

In: Molecular and Cellular Proteomics, Vol. 8, No. 8, 2009, p. 1765-1776.

Research output: Contribution to journalArticle

Chen, Chien Sheng ; Sullivan, Sean ; Anderson, Troy ; Tan, Aik Choon ; Alex, Philip J. ; Brant, Steven R. ; Cuffari, Carmelo ; Bayless, Theodore M ; Talor, Monica V. ; Burek, C. Lynne ; Wang, Huan ; Li, Richard ; Datta, Lisa ; Wu, Yuqiong ; Winslow, Raimond ; Zhu, Heng ; Li, Xuhang. / Identification of novel serological biomarkers for inflammatory bowel disease using Escherichia coli proteome chip. In: Molecular and Cellular Proteomics. 2009 ; Vol. 8, No. 8. pp. 1765-1776.
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abstract = "Specific antimicrobial antibodies present in the sera of patients with inflammatory bowel disease (IBD) have been proven to be valuable serological biomarkers for diagnosis/prognosis of the disease. Herein we describe the use of a whole Escherichia coli proteome microarray as a novel high throughput proteomics approach to screen and identify new serological biomarkers for IBD. Each protein array, which contains 4,256 E. coli K12 proteins, was screened using individual serum from healthy controls (n = 39) and clinically well characterized patients with IBD (66 Crohn disease (CD) and 29 ulcerative colitis (UC)). Proteins that could be recognized by serum antibodies were visualized and quantified using Cy3-labeled goat anti-human antibodies. Surprisingly significance analysis of microarrays identified a total of 417 E. coli proteins that were differentially recognized by serum antibodies between healthy controls and CD or UC. Among those, 169 proteins were identified as highly immunogenic in healthy controls, 186 proteins were identified as highly immunogenic in CD, and only 19 were identified as highly immunogenic in UC. Using a supervised learning algorithm (k-top scoring pairs), we identified two sets of serum antibodies that were novel biomarkers for specifically distinguishing CD from healthy controls (accuracy, 86 ± 4{\%}; p <0.01) and CD from UC (accuracy, 80 ± 2{\%}; <0.01), respectively. The Set 1 antibodies recognized three pairs of E. coli proteins: Era versus YbaN, YhgN versus FocA, and GabT versus YcdG, and the Set 2 antibodies recognized YidX versus FrvX. The specificity and sensitivity of Set 1 antibodies were 81 ± 5 and 89 ± 3{\%}, respectively, whereas those of Set 2 antibodies were 84 ± 1 and 70 ± 6{\%}, respectively. Serum antibodies identified for distinguishing healthy controls versus UC were only marginal because their accuracy, specificity, and sensitivity were 66 ± 5, 69 ± 5, and 61 ± 7{\%}, respectively (p <0.04). Taken together, we identified novel sets of serological biomarkers for diagnosis of CD versus healthy control and CD versus UC.",
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