GC/MS-based profiling of amino acids and TCA cycle-related molecules in ulcerative colitis

Inflammatory bowel disease as a model for translating the microbiome

The inflammatory bowel diseases (IBDs) are among the most closely studied chronic inflammatory disorders that involve environmental, host genetic, and commensal microbial factors. This combination of features has made IBD both an appropriate and a high-priority platform for translatable research in host-microbiome interactions. Decades of epidemiology have identified environmental risk factors, although most mechanisms of action remain unexplained. The genetic architecture of IBD has been carefully dissected in multiple large populations, identifying several responsible host epithelial and immune pathways but without yet a complete systems-level explanation. Most recently, the commensal gut microbiota have been found to be both ecologically and functionally perturbed during the disease, but with as-yet-unexplained heterogeneity among IBD subtypes and individual patients. IBD thus represents perhaps the most comprehensive current model for understanding the human microbiome's role in complex inflammatory disease. Here, we review the influences of the microbiota on IBD and its potential for translational medicine.

A novel gas chromatography mass spectrometry-based serum diagnostic and assessment approach to ulcerative colitis

BACKGROUND & AIMS

To improve the clinical course of ulcerative colitis (UC), more accurate serum diagnostic and assessment methods are required. We used serum metabolomics to develop diagnostic and assessment methods for UC.

METHODS

Sera from UC patients, Crohn's disease (CD) patients, and healthy volunteers (HV) were collected at multiple institutions. The UC and HV were randomly allocated to the training or validation set, and their serum metabolites were analyzed by gas chromatography mass spectrometry (GC/MS). Using the training set, diagnostic and assessment models for UC were established by multiple logistic regression analysis. Then, the models were assessed using the validation set. Additionally, to establish a diagnostic model for discriminating UC from CD, the CD patients' data were used.

RESULTS

The diagnostic model for discriminating UC from HV demonstrated an AUC of 0.988, 93.33% sensitivity, and 95.00% specificity in the training set and 95.00% sensitivity and 98.33% specificity in the validation set. Another model for discriminating UC from CD exhibited an AUC of 0.965, 85.00% sensitivity, and 97.44% specificity in the training set and 83.33% sensitivity in the validation set. The model for assessing UC showed an AUC of 0.967, 84.62% sensitivity, and 88.23% specificity in the training set and 84.62% sensitivity, 91.18% specificity, and a significant correlation with the clinical activity index (rs=0.7371, P<0.0001) in the validation set.

CONCLUSIONS

Our models demonstrated high performance and might lead to the development of a novel treatment selection method based on UC condition.

Laboratory evaluation and metabolomics in inflammatory bowel disease

Diagnosis and prognosis of inflammatory bowel disease (IBD) remain a challenge for physicians, and they are often based on history, clinical symptoms and endoscopic, histological, radiological and laboratory findings. Studies have shown that metabolomics may have important value in the diagnosis and prognosis of IBD. This paper will review the latest progress in laboratory evaluation and metabolomics in IBD.

Multi-omics analysis of inflammatory bowel disease

Crohn's disease and ulcerative colitis, known together as inflammatory bowel disease (IBD), are severe autoimmune disorders now causing gut inflammation and ulceration, among other symptoms, in up to 1 in 250 people worldwide. Incidence and prevalence of IBD have been increasing dramatically over the past several decades, although the causes for this increase are still unknown. IBD has both a complex genotype and a complex phenotype, and although it has received substantial attention from the medical research community over recent years, much of the etiology remains unexplained. Genome-wide association studies have identified a rich genetic signature of disease risk in patients with IBD, consisting of at least 163 genetic loci. Many of these loci contain genes directly involved in microbial handling, indicating that the genetic architecture of the disease has been driven by host-microbe interactions. In addition, systematic shifts in gut microbiome structure (enterotype) and function have been observed in patients with IBD. Furthermore, both the host genotype and enterotype are associated with aspects of the disease phenotype, including location of the disease. This provides strong evidence of interactions between host genotype and enterotype; however, there is a lack of published multi-omics data from IBD patients, and a lack of bioinformatics tools for modeling such systems. In this article we discuss, from a computational biologist's point of view, the potential benefits of and the challenges involved in designing and analyzing such multi-omics studies of IBD.

Systems biology in inflammatory bowel diseases: ready for prime time

PURPOSE OF REVIEW

Ulcerative colitis and Crohn's disease are the two predominant types of inflammatory bowel disease (IBD), affecting over 1.4 million individuals in the United States. IBD results from complex interactions between pathogenic components, including genetic and epigenetic factors, the immune response, and the microbiome, through an unknown sequence of events. The purpose of this review is to describe a systems biology approach to IBD as a novel and exciting methodology aiming at developing novel IBD therapeutics based on the integration of molecular and cellular 'omics' data.

RECENT FINDINGS

Recent evidence suggested the presence of genetic, epigenetic, transcriptomic, proteomic, and metabolomic alterations in IBD patients. Furthermore, several studies have shown that different cell types including fibroblasts, epithelial, immune, and endothelial cells together with the intestinal microbiota are involved in IBD pathogenesis. Novel computational methodologies have been developed aiming to integrate high-throughput molecular data.

SUMMARY

A systems biology approach could potentially identify the central regulators (hubs) in the IBD interactome and improve our understanding of the molecular mechanisms involved in IBD pathogenesis. The future IBD therapeutics should be developed on the basis of targeting the central hubs in the IBD network.

Clinical significance of quantitative detection of serum tryptophan in patients with ulcerative colitis

AIM: To investigate the clinical significance of serum tryptophan in patients with ulcerative colitis (UC).

METHODS: Serum samples were obtained from 20 UC patients and 20 healthy volunteers. For each patient, serum samples were collected when the disease was active and inactive. The diagnosis for each patient was based on clinical symptoms, endoscopic, radiographic, and histological findings. The Montreal Classification was used for disease phenotyping. Disease activity was assessed by the modified Mayo score. Tryptophan in serum was measured by liquid chromatography tandem mass spectrometry (LC-MS/MS). Differences between different groups and the relationship between serum tryptophan and ESR/CRP in patients with active UC were analyzed.

RESULTS: Compared with patients with active UC, serum levels of tryptophan in patients with inactive UC and healthy volunteers were significantly lower (P < 0.05 for both), but there was no significant difference between patients with inactive UC and healthy volunteers. Serum tryptophan in active UC patients was inversely related to ESR (r = -0.502, P = 0.024) and CRP (r = -0.530, P = 0.016). After conventional treatment, the levels of serum tryptophan were significantly elevated (P < 0.05).

CONCLUSION: Tryptophan may play a key role in the occurrence and development of UC.

Metabolomics as a diagnostic tool in gastroenterology

Metabolomics has increasingly been applied in addition to other “omic” approaches in the study of the pathophysiology of different gastrointestinal diseases. Metabolites represent molecular readouts of the cell status reflecting a physiological phenotype. In addition, changes in metabolite concentrations induced by exogenous factors such as environmental and dietary factors which do not affect the genome, are taken into account. Metabolic reactions initiated by the host or gut microbiota can lead to “marker” metabolites present in different biological fluids that allow differentiation between health and disease. Several lines of evidence implicated the involvement of intestinal microbiota in the pathogenesis of inflammatory bowel disease (IBD). Also in irritable bowel syndrome (IBS), a role of an abnormal microbiota composition, so-called dysbiosis, is supported by experimental data. These compositional alterations could play a role in the aetiology of both diseases by altering the metabolic activities of the gut bacteria. Several studies have applied a metabolomic approach to identify these metabolite signatures. However, before translating a potential metabolite biomarker into clinical use, additional validation studies are required. This review summarizes contributions that metabolomics has made in IBD and IBS and presents potential future directions within the field.

Metabolomics: is it useful for inflammatory bowel diseases?

PURPOSE OF REVIEW

The assessment of metabolite profiles in biofluids has become a powerful method for the detection of biomarker molecules and disease mechanisms. This review outlines the recent advances in the use of metabolomic techniques to study inflammatory bowel diseases (IBDs).

RECENT FINDINGS

The last few years have seen an increase in the studies of experimental and human IBD focusing on the search for small metabolites, such as amino acids, bases, and tricarboxylic acid cycle intermediates. Experimental methods for the screening of metabolites in serum, urine, fecal extracts, and colon tissue include H NMR spectroscopy, gas chromatography-mass spectrometry, and liquid chromatography methods. Several studies demonstrate that IBD patients and healthy individuals, as well as the IBD subtypes, can be distinguished using metabolic profiling. Metabolomic data of fecal extracts and urine have revealed disruptions in bacterial populations, findings that are indicative of a possible involvement of the microbiome in the development of IBDs.

SUMMARY

Metabolites from biofluids can be detected in IBDs by different experimental methods that allow successful separation of IBD subtypes from healthy cohorts. Knowledge of a unique metabolomic fingerprint in IBDs could be useful for diagnosis, treatment, and detection of disease mechanisms.

Proteomics and metabolomics in inflammatory bowel disease

Genome-wide studies in inflammatory bowel disease (IBD) have allowed us to understand Crohn's disease and ulcerative colitis as forms of related autoinflammatory disorders that arise from a multitude of pathogenic origins. Proteomics and metabolomics are the offspring of genomics that possess unprecedented possibilities to characterize unknown pathogenic pathways. It has been about a decade since proteomics was first applied to IBD, and 5 years for metabolomics. These techniques have yielded novel and potentially important findings, but turning these results into beneficial patient outcomes remains challenging. This review recounts the history and context of clinical IBD developments before and after proteomics and metabolomics IBD in this field, discusses the challenges in consolidating high complexity data with physiological understanding, and provides an outlook on the emerging principles that will help interface the bioanalytical laboratory with IBD prognosis.

An alternative derivatization method for the analysis of amino acids in cerebrospinal fluid by gas chromatography-mass spectrometry

The determination of the concentrations of l-amino acids in cerebrospinal fluid (CSF) has been used to gain biochemical insight into central nervous system disorders. This paper describes a microwave-assisted derivatization (MAD) method using N,O-bis-(trimethylsilyl)trifluoroacetamide (BSTFA) as a derivatizing agent for determining the concentrations of l-amino acids in human CSF by gas chromatography with mass spectrometry (GC/MS). The experimental design used to optimize the conditions showed that the optimal derivatization time was 3min with a microwave power of 210W. The method showed good performance for the validation parameters. The sensitivity was very good, with limits of detection (LODs) ranging from 0.01μmolL(-1) to 4.24μmolL(-1) and limits of quantification (LOQs) ranging from 0.02 to 7.07μmolL(-1). The precision, measured using the relative standard deviation (RSD), ranged from 4.12 to 15.59% for intra-day analyses and from 6.36 to 18.71% for inter-day analyses. The coefficients of determination (R(2)) were above 0.990 for all amino acids. The optimized and validated method was applied to the determination of amino acid concentrations in human CSF.

A novel serum metabolomics-based diagnostic approach to pancreatic cancer

BACKGROUND

To improve the prognosis of patients with pancreatic cancer, more accurate serum diagnostic methods are required. We used serum metabolomics as a diagnostic method for pancreatic cancer.

METHODS

Sera from patients with pancreatic cancer, healthy volunteers, and chronic pancreatitis were collected at multiple institutions. The pancreatic cancer and healthy volunteers were randomly allocated to the training or the validation set. All of the chronic pancreatitis cases were included in the validation set. In each study, the subjects' serum metabolites were analyzed by gas chromatography mass spectrometry (GC/MS) and a data processing system using an in-house library. The diagnostic model constructed via multiple logistic regression analysis in the training set study was evaluated on the basis of its sensitivity and specificity, and the results were confirmed by the validation set study.

RESULTS

In the training set study, which included 43 patients with pancreatic cancer and 42 healthy volunteers, the model possessed high sensitivity (86.0%) and specificity (88.1%) for pancreatic cancer. The use of the model was confirmed in the validation set study, which included 42 pancreatic cancer, 41 healthy volunteers, and 23 chronic pancreatitis; that is, it displayed high sensitivity (71.4%) and specificity (78.1%); and furthermore, it displayed higher sensitivity (77.8%) in resectable pancreatic cancer and lower false-positive rate (17.4%) in chronic pancreatitis than conventional markers.

CONCLUSIONS

Our model possessed higher accuracy than conventional tumor markers at detecting the resectable patients with pancreatic cancer in cohort including patients with chronic pancreatitis.

IMPACT

It is a promising method for improving the prognosis of pancreatic cancer via its early detection and accurate discrimination from chronic pancreatitis.

1H NMR-based spectroscopy detects metabolic alterations in serum of patients with early-stage ulcerative colitis

Ulcerative colitis (UC) has seriously impaired the health of citizens. Accurate diagnosis of UC at an early stage is crucial to improve the efficiency of treatment and prognosis. In this study, proton nuclear magnetic resonance (1H NMR)-based metabolomic analysis was performed on serum samples collected from active UC patients (n=20) and healthy controls (n=19), respectively. The obtained spectral profiles were subjected to multivariate data analysis. Our results showed that consistent metabolic alterations were present between the two groups. Compared to healthy controls, UC patients displayed increased 3-hydroxybutyrate, β-glucose, α-glucose, and phenylalanine, but decreased lipid in serum. These findings highlight the possibilities of NMR-based metabolomics as a non-invasive diagnostic tool for UC.

GC/MS-based metabolomic analysis of cerebrospinal fluid (CSF) from glioma patients

Metabolomics has recently undergone rapid development; however, metabolomic analysis in cerebrospinal fluid (CSF) is not a common practice. We analyzed the metabolite profiles of preoperative CSF samples from 32 patients with histologically confirmed glioma using gas chromatography/mass spectrometry (GC/MS). We assessed how alterations in the metabolite levels were related to the World Health Organization (WHO) tumor grades, tumor location, gadolinium enhancement on magnetic resonance imaging (MRI), and the isocitrate dehydrogenase (IDH) mutation status. Sixty-one metabolites were identified in the CSF from glioma patients using targeted, quantitative and non-targeted, semi-quantitative analysis. The citric and isocitric acid levels were significantly higher in the glioblastoma (GBM) samples than in the grades I-II and grade III glioma samples. In addition, the lactic and 2-aminopimelic acid levels were relatively higher in the GBM samples than in the grades I-II glioma samples. The CSF levels of the citric, isocitric, and lactic acids were significantly higher in grade I-III gliomas with mutant IDH than in those with wild-type IDH. The tumor location and enhancement obtained using MRI did not significantly affect the metabolite profiles. Higher CSF levels of lactic acid were statistically associated with a poorer prognosis in grades III-IV malignant gliomas. Our study suggests that the metabolomic analysis of CSF from glioma patients may be useful for predicting the glioma grade, metabolic state, and prognosis of gliomas.

Metabolic phenotyping in clinical and surgical environments

Metabolic phenotyping involves the comprehensive analysis of biological fluids or tissue samples. This analysis allows biochemical classification of a person's physiological or pathological states that relate to disease diagnosis or prognosis at the individual level and to disease risk factors at the population level. These approaches are currently being implemented in hospital environments and in regional phenotyping centres worldwide. The ultimate aim of such work is to generate information on patient biology using techniques such as patient stratification to better inform clinicians on factors that will enhance diagnosis or the choice of therapy. There have been many reports of direct applications of metabolic phenotyping in a clinical setting.

Serum metabolomics in a Helicobacter hepaticus mouse model of inflammatory bowel disease reveal important changes in the microbiome, serum peptides, and intermediary metabolism

Inflammatory bowel disease (IBD) is a chronic relapsing inflammatory disorder of the bowel. The etiology remains unknown, but IBD is immune-driven and multiple factors including genetic, environmental, and microbiological components play a role. Recombinase-activating gene-2-deficient (Rag2(-/-)) mice infected with Helicobacter hepaticus (H. hepaticus) have been developed as an animal model to imitate naturally occurring inflammatory events and associated key features of chronic inflammatory responses in humans. In this study, we have combined mass spectrometry-based metabolomics and peptidomics to analyze serum samples of Rag2(-/-) mice infected with H. hepaticus. Metabolomics profiling revealed that H. hepaticus infection dramatically changed numerous metabolite pathways, including tryptophan metabolism, glycerophospholipids, methionine-homocysteine cycle, citrate cycle, fatty acid metabolism and purine metabolism, with the majority of metabolites being down-regulated. In particular, there were notable effects of gut microflora on the blood metabolites in infected animals. In addition, the peptidomics approach identified a number of peptides, originating from proteins, including fibrinogen, complement C4, and alpha-2-macroglobulin, with diverse biological functions with potentially important implications for the progress of IBD. In summary, the strategy of integrating a relevant animal model and sensitive mass spectrometry-based profiling may offer a new perspective to explore biomarkers and provide mechanistic insights into IBD.

Regulation of the metabolite profile by an APC gene mutation in colorectal cancer

Mutation of the APC gene occurs during the early stages of colorectal cancer development. To obtain new insights into the mechanisms underlying the aberrant activation of the Wnt pathway that accompanies APC mutation, we carried out a gas chromatography-mass spectrometry-based semiquantitative metabolome analysis. In vitro experiments comparing SW480 cells expressing normal APC and truncated APC indicated that the levels of metabolites involved in the latter stages of the intracellular tricarboxylic acid cycle, including succinic acid, fumaric acid, and malic acid, were significantly higher in the SW480 cells expressing the truncated APC. In an in vivo study, we found that the levels of most amino acids were higher in the non-polyp tissues of APC(min/+) mice than in the normal tissues of the control mice and the polyp tissues of APC(min/+) mice. Ribitol, the levels of which were decreased in the polyp lesions of the APC(min/+) mice and the SW480 cells expressing the truncated APC, reduced the growth of SW480 cells with the APC mutation, but did not affect the growth of SW480 transfectants expressing full-length APC. The level of sarcosine was found to be significantly higher in the polyp tissues of APC(min/+) mice than in their non-polyp tissues and the normal tissues of the control mice, and the treatment of SW480 cells with 50 μM sarcosine resulted in a significant increase in their growth rate. These findings suggest that APC mutation causes changes in energetic metabolite pathways and that these alterations might be involved in the development of colorectal cancer.

Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography-mass spectrometry

Recently, metabolome analysis has been increasingly applied to biomarker detection and disease diagnosis in medical studies. Metabolome analysis is a strategy for studying the characteristics and interactions of low molecular weight metabolites under a specific set of conditions and is performed using mass spectrometry and nuclear magnetic resonance spectroscopy. There is a strong possibility that changes in metabolite levels reflect the functional status of a cell because alterations in their levels occur downstream of DNA, RNA, and protein. Therefore, the metabolite profile of a cell is more likely to represent the current status of a cell than DNA, RNA, or protein. Thus, owing to the rapid development of mass spectrometry analytical techniques metabolome analysis is becoming an important experimental method in life sciences including the medical field. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry, and matrix assisted laser desorption ionization-mass spectrometry. Then, the findings of studies about GC-MS-based metabolome analysis of gastroenterological diseases are summarized, and our research results are also introduced. Finally, we discuss the realization of disease diagnosis by metabolome analysis. The development of metabolome analysis using mass spectrometry will aid the discovery of novel biomarkers, hopefully leading to the early detection of various diseases.