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Chemical and cytokine features of innate immunity characterize serum and tissue profiles in inflammatory bowel disease

  1. Steven R. Tannenbauma,d
  1. aDepartment of Biological Engineering,
  2. dDepartment of Chemistry, and
  3. eDivision of Comparative Medicine, Massachusetts Institute of Technology, Cambridge, MA 02138;
  4. bDepartment of Biology, University of Konstanz, 78457 Konstanz, Germany; and
  5. cDepartment of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115

  1. Contributed by Gerald N. Wogan, January 3, 2013 (sent for review November 20, 2012)

  1. Fig. 1.
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    Fig. 1.

    5-Cl-dC was analyzed in human colon tissue derived from patients with IBD and compared with previously determined levels in mice (UC, n = 18; CD, n = 22, Rag2−/− H. hepaticus-infected mice, n = 12) (11). The 5-Cl-dC levels in Rag2−/− H. hepaticus-infected mice were significantly higher than those observed in IBD colon tissues (P < 0.0002). Statistical significance between groups was assessed by the Mann–Whitney U test and the line represents the mean value in each dataset.

  2. Fig. 2.
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    Fig. 2.

    Cl-Tyr and Nitro-Tyr were quantified in human tissues using stable isotope dilution LC-MS/MS analysis. (A and B) Quantitation of Cl-Tyr and Nitro-Tyr in IBD colon tissue (UC, n = 18; CD, n = 22). (C and D) Quantitation of Cl-Tyr and Nitro-Tyr in IBD and non-IBD serum (Control, n = 29; UC active, n = 38; UC inactive = 19; CD active, n = 42; CD inactive, n = 20). Cl-Tyr levels in both active UC (P value < 0.0001) and active CD (P value < 0.0001) serum samples were significantly higher than those observed in non-IBD control sera. Significant elevation in Cl-Tyr levels were also observed between UC active and UC inactive (P value = 0.0003), and CD active and CD inactive (P value < 0.0001) samples. A significant elevation was found in Nitro-Tyr levels between UC active and UC inactive (P value = 0.0038) samples. Statistical analysis for all panels is presented as box-and-whisker plots showing the median value (line), the interquartile range (box), and Tukey whiskers defining data within 1.5-fold of the interquartile range; all data outside the whiskers are presented as individual data points. Statistical significance between groups (two groups) was assessed by the Mann–Whitney U test.

  3. Fig. 3.
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    Fig. 3.

    Analysis of modified tyrosine residues following 10 and 20 wk postinfection with H. hepaticus or from sham-infected Rag2−/− mice. (A and B) Cl-Tyr levels in Rag2−/− mouse colon significantly increased at both 10 and 20 wk postinfection, and Nitro-Tyr levels in the Rag2−/− mouse colon significantly increased at 20 wk postinfection (10 wk +Hh or −Hh, n = 6; 20 wk +Hh or −Hh, n = 5). (C and D) Cl-Tyr analysis in Rag2−/− mouse serum demonstrated a significant increase in chlorination damage at 10 wk and a significant decrease at 20 wk (*), and Nitro-Tyr levels in Rag2−/− mouse serum increased at both 10 and 20 wk postinfection (10 wk +Hh or −Hh, n = 12; 20 wk +Hh, n = 13; 20 wk −Hh, n = 11). Statistical analysis performed as described in Fig. 2.

  4. Fig. 4.
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    Fig. 4.

    Acute-phase proteins were quantified in the serum of humans (A–E) and mice (F–K) by multiplex methodologies (Control, n = 29; UC, n = 20; CD, n = 20; 10 wk +Hh, n = 10; 10 wk −Hh, n = 11; 20 wk +Hh, n = 13; 20 wk −Hh, n = 12). Results were considered significant when P < 0.05. Statistical analysis performed as described in Fig. 2.

  5. Fig. 5.
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    Fig. 5.

    qPCR analysis of cytokine and chemokine transcripts in H. hepaticus-infected Rag2−/− mouse colon. (A) Gene-expression data for cytokines and chemokines in the Rag2−/− mouse colon at 10 and 20 wk postinfection. All inflammatory targets in this plot exhibited significant changes (P < 0.05) at least one time point (10 wk +Hh, n = 5; 10 wk −Hh, n = 5; 20 wk +Hh, n = 7; 20 wk −Hh, n = 5). A full list of the gene-expression data can be found in Table S3. Red circles denote inflammatory targets that were up-regulated at both time points; green circles denote inflammatory targets that were down-regulated at both time points; blue circles denote inflammatory targets that were differentially regulated. (B) Comparison of colon transcript levels and serum cytokine levels to highlight common and compartment-specific changes.

  6. Fig. 6.
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    Fig. 6.

    Multivariate modeling of UC serum analytes. Multivariate data analysis of serum analytes using partial least squares analysis to identify discriminatory features between UC patients (black squares, n = 20) and non-IBD controls (green squares, n = 29). (A) A 2D projection of the partial least-squares multivariate analysis, which produced separation of UC patients from non-IBD controls. The model produced R2Y = 0.87 (model fit) and Q2(cum) = 0.82 (model prediction). (B) List of the top VIPs (VIP > 1.0) in the dataset that were most influential on the data separation.

  7. Fig. 7.
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    Fig. 7.

    Multivariate modeling of CD serum analytes. Multivariate data analysis of serum analytes to identify discriminatory features between CD patients (red squares, n = 20) and non-IBD controls (green squares, n = 29). (A) A 2D projection of the partial least-squares multivariate analysis, which shows an overlapping distribution of CD patients and non-IBD controls. The model produced R2Y = 0.55 (model fit) and Q2(cum) = 0.15 (model prediction). (B) List of the top VIPs (VIP > 1.0) in the dataset that were most influential on the data separation.

  8. Fig. 8.
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    Fig. 8.

    Multivariate data analysis of serum analytes to identify discriminatory features between Rag2−/− H. hepaticus-infected mice and the uninfected controls. All infected (10 wk +Hh, black squares, n = 8; 20 wk +Hh, green squares, n = 10) and control mice (10 wk −Hh, red squares, n = 6; 20 wk −Hh, blue squares, n = 9) were pooled into two separate groups in this model. (A) A 2D projection of the partial least squares multivariate analysis, which produced clear separation of infected mice and uninfected controls. The model produced R2Y = 0.93 (model fit) and Q2(cum) = 0.91 (model prediction). (B) List of the top VIPs (VIP > 1.0) in the dataset that were most influential on the data separation.

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