Systemic Responses of Mice to Dextran Sulfate Sodium-Induced Acute Ulcerative Colitis Using ¹H NMR Spectroscopy

The interplay between genetic mutation and environmental factors is believed to contribute to the etiology of inflammatory bowel disease (IBD). While focused attention has been paid to the aforementioned research, time-specific and organ-specific metabolic changes associated with IBD are still lacking. Here, we induced acute ulcerative colitis in mice by providing water containing 3% dextran sulfate sodium (DSS) for 7 days and investigated the metabolic changes of plasma, urine, and a range of biological tissues by employing a ¹H nuclear magnetic resonance (NMR)-based metabonomics approach with complementary information on serum clinical chemistry and histopathology. We found that DSS-induced acute ulcerative colitis leads to significant elevations in the levels of amino acids in plasma and decreased levels in the membrane-related metabolites and a range of nucleotides, nucleobases, and nucleosides in the colon. In addition, acute-colitis-induced elevations in the levels of nucleotides in the liver were observed, accompanied by reduced levels of glucose. DSS-induced acute colitis also resulted in increased levels of oxidized glutathione and attenuated levels of taurine in the spleen. Furthermore, acute colitis resulted in depletion in the levels of gut microbial cometabolites in urine along with an increase in citric acid cycle intermediates. These findings suggest that DSS-induced acute colitis causes a disturbance of lipid and energy metabolism, damage to the colon and liver, a promoted antioxidative and anti-inflammatory response, and perturbed gut microbiotal communities. The information obtained here provided details of the time-dependent and holistic metabolic changes in the development of the DSS-induced acute ulcerative colitis, which could be useful in discovery of novel therapeutic targets for management of IBD

O-PLS-DA comparison between plasma spectra from <i>K. pneumoniae</i> infected rats and corresponding controls and metabolite concentration changes relative to corresponding controls at different time points after <i>K. pneumoniae</i> infection.

<p>(A) Cross validated O-PLS-DA scores (left hand side) and coefficient plots (right hand side) generated from NMR spectral data of plasma of rats at 8 hours after <i>K. pneumoniae</i> infection (red dots), compared with those of non-infected (black squares). (B) a-c plots show metabolites changes in plasma. C_inf and C_con stand for the averaged concentration in the infection and control group, respectively.</p

Trajectories of plasma and urinary metabolic profiles of the control group and the infected group at different time intervals.

<p>Time-dependent trajectories of plasma (A, R²X = 0.928, Q² = 0.918) and urinary (B, R²X = 0.789, Q² = 0.614) metabolic profiles of the control group (black squares) and the infection group (red squares) from hour 0 to day 14. Bars denote the standard deviations of each group.</p

O-PLS-DA comparison between urine spectra from <i>K. pneumoniae</i> infected rats and corresponding controls and metabolite concentration changes relative to corresponding controls at different time points after <i>K. pneumoniae</i> infection.

<p>(A) Cross validated O-PLS-DA scores (left hand side) and coefficient plots (right hand side) generated from NMR spectral data of urine of rats at 8 hours after <i>K. pneumoniae</i> infection (red dots), compared with those of non-infected (black squares). (B) a-f plots show metabolites changes in urine. C_inf and C_con stand for the averaged concentration in the infection and control group, respectively.</p

O-PLS-DA Cross-validation Model Summary for Pair-wise Comparison between NMR Spectra of Plasma and Urine Obtained from <i>K. pneumoniae-</i>infected Rats Compared to Controls on Different Time Points^a.

a<p>Values are cumulative. One PLS component and one orthogonal component are calculated. The R²X value shows how much variation in the data set is explained by the model. The Q² value represents the predictability of the model.</p>b<p>All models have been validated using permutation tests (n = 200) and ANOVA of the cross-validated residuals (CV-ANOVA) tests. P-values are obtained from CV-ANOVA tests. The underlined values indicate valid models (p<0.05).</p

Schematic representation of the metabolites and metabolic pathways in <i>K. pneumoniae</i> bacteremia.

<p>The metabolites in red indicate the changes in plasma and those in blue indicate the changes in urine whereas those in black were not observed; the arrows pointing up and down denoted relative increase and decrease in the infected group compared with the controls.</p

¹H NMR spectra of plasma and urine from control and <i>K. pneumoniae</i> infected rats for 8 hours.

<p>Typical 500 MHz ¹H (CPMG) NMR spectra of plasma obtained from a non-infected SD rat (P_A) and a rat infected with <i>K. pneumoniae</i> for 8 hours (P_B). The region of δ 5.0–9.0 in the blood plasma spectra was vertically expanded 16 times compared with the region of δ 0.5–4.5; Representative 600 MHZ ¹H NMR spectra of urine samples obtained from a non-infected SD rat (U_A) and a rat infected with <i>K. pneumoniae</i> for 8 hours (U_B). The spectral region, δ 6.2–9.5, was vertically expanded 4 times compared with the region of δ 0.5–4.4. Key: 1,lipoprotein; 2,valine; 3,leucine; 4,isoleucine; 5,creatine; 6,<i>N</i>-acetyl glycoprotein; 7,<i>O</i>-acetyl glycoprotein; 8,alanine; 9,lactate; 10,acetoacetate; 11,α-glucose; 12,acetate; 13,pyruvate; 14,dihydrothymine; 15,threonine; 16,unsaturated fatty acid; 17,choline; 18,phosphorylcholine; 19,glycerophosphocholine; 20,lysine; 21,citrate; 22,_D-3-hydroxybutyrate; 23,glutamine; 24,glutamate; 25,histidine; 26,phenylalanine; 27,tyrosine; 28,formate; 29,trimethylamine; 30,urea; 31,triglyceride; 32,arginine; 33,ω-3 fatty acid; 34,poly unsaturated fatty acid; 35,glucose and amino acids α-CH resonances; 36,2-oxoglutarate; 37,creatinine; 38,hippurate; 39,1-methylnicotimamide; 40,acetamide; 41,fumarate; 42,phenylacetylglycine; 43,cis-aconitate; 44,pantothenic acid; 45,succinate; 46,<i>N</i>-methylnicotinate; 47,malate; 48,indoxyl sulfate; 49,dimethylamine; 50,glycine; 51,isovalerate; 52,2-(4-hydroxyphenyl)propanoic acid; 53,2,3-dihydroxybutyrate; 54,4-cresol glucuronide; 55,dimethylglycine; 56,taurine; 57,hypotaurine; 58,4-deoxyerythronate; 59,trimethylamine <i>N</i>-oxide.</p

Bacterial counts, procalcitonin, white blood cell count and C-reactive protein in blood stream obtained from <i>K.</i><i>pneumoniae-</i>infected rats compared to controls^a.

a<p>Bacterial counts data are represented as median (range); Procalcitonin, white blood cell count and C-reactive protein are represented as mean ± SD. *p<0.05, **p<0.01.</p

sj-docx-1-try-10.1177_11786469231182508 – Supplemental material for Endogenous Tryptophan-Derived Ah Receptor Ligands are Dissociated from CYP1A1/1B1-Dependent Negative-Feedback

Supplemental material, sj-docx-1-try-10.1177_11786469231182508 for Endogenous Tryptophan-Derived Ah Receptor Ligands are Dissociated from CYP1A1/1B1-Dependent Negative-Feedback by Fangcong Dong, Andrew J Annalora, Iain A Murray, Yuan Tian, Craig B Marcus, Andrew D Patterson and Gary H Perdew in International Journal of Tryptophan Research</p

Microbiota Metabolism Promotes Synthesis of the Human Ah Receptor Agonist 2,8-Dihydroxyquinoline

The aryl hydrocarbon receptor (AHR) is a major regulator of immune function within the gastrointestinal tract. Resident microbiota are capable of influencing AHR-dependent signaling pathways via production of an array of bioactive molecules that act as AHR agonists, such as indole or indole-3-aldehyde. Bacteria produce a number of quinoline derivatives, of which some function as quorum-sensing molecules. Thus, we screened relevant hydroxyquinoline derivatives for AHR activity using AHR responsive reporter cell lines. 2,8-Dihydroxyquinoline (2,8-DHQ) was identified as a species-specific AHR agonist that exhibits full AHR agonist activity in human cell lines, but only induces modest AHR activity in mouse cells. Additional dihydroxylated quinolines tested failed to activate the human AHR. Nanomolar concentrations of 2,8-DHQ significantly induced CYP1A1 expression and, upon cotreatment with cytokines, synergistically induced IL6 expression. Ligand binding competition studies subsequently confirmed 2,8-DHQ to be a human AHR ligand. Several dihydroxyquinolines were detected in human fecal samples, with concentrations of 2,8-DHQ ranging between 0 and 3.4 pmol/mg feces. Additionally, in mice the microbiota was necessary for the presence of DHQ in cecal contents. These results suggest that microbiota-derived 2,8-DHQ would contribute to AHR activation in the human gut, and thus participate in the protective and homeostatic effects observed with gastrointestinal AHR activation