Global gas chromatography/time-of-flight mass spectrometry (GC/TOFMS)-based metabonomic profiling of lyophilized human feces

Evaluation of solutions for stabilizing feces in metabolomics studies using GC × GC-TOFMS

INTRODUCTION

Fecal metabolomics studies have garnered interest in recent years due to the potential for these samples to provide unique information about an individual. Stool is a dynamic mixture of human excrement, microbiota, and enzymes that yields a constantly changing metabolite profile. The main challenge in a fecal metabolomics study is ensuring that the metabolite profile changes as little as possible between sample collection and sample processing/analysis.

OBJECTIVES

This study aimed to evaluate the efficacy of five solutions in preserving human fecal metabolites over a seven-day storage period at ambient temperature, enabling at-home collection, cost-effective ambient transport and sample storage.

METHOD

Five solutions with varying chemical compositions were evaluated for their ability to stabilize fecal metabolites. Samples were stored at ambient temperature for seven days, and metabolites were analyzed using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOFMS). The stabilizing efficacy of the solutions was assessed using total useful peak area (TUPA), absolute relative change (ARC) and compound class-based analyses, comparing the initial, stabilized, and unstabilized samples.

RESULTS

Different solutions demonstrated varied efficiencies for different compound classes. Overall, the results indicated that the use of stabilization solutions significantly minimized changes in the fecal metabolite profile compared to unstabilized samples left at room temperature for one week.

CONCLUSION

This study demonstrates that stabilization solutions are effective in preserving fecal metabolites during storage at ambient temperature, supporting the feasibility of at-home sample collection.

Sample Preparation for Metabolomic Analysis in Exercise Physiology

Metabolomics investigates final and intermediate metabolic products in cells. Assessment of the human metabolome relies principally on the analysis of blood, urine, saliva, sweat, and feces. Tissue biopsy is employed less frequently. Understanding the metabolite composition of biosamples from athletes can significantly improve our knowledge of molecular processes associated with the efficiency of training and recovery. Such knowledge may also lead to new management opportunities. Successful execution of metabolomic studies requires simultaneous qualitative and quantitative analyses of numerous small biomolecules in samples under test. Unlike genomics and proteomics, which do not allow for direct assessment of enzymatic activity, metabolomics focuses on biochemical phenotypes, providing unique information about health and physiological features. Crucial factors in ensuring the efficacy of metabolomic analysis are the meticulous selection and pre-treatment of samples.

Anti-inflammatory mechanism of Houttuynia cordata polysaccharides against ulcerative colitis based on multi-omics conjoint analysis

The Houttuynia cordata polysaccharide (HCP) was extracted from the traditional Chinese medicine, Houttuynia cordata, known for its anti-inflammatory properties. It has an acidic heteropolysaccharide with a molecular weight of approximately 13.38 kDa, consisting of 7 monosaccharides such as galactose, galacturonic acid, and glucose. Mouse ulcerative colitis (UC) model experiments demonstrated its effective anti-inflammatory activity at concentrations of 100 mg/kg and 300 mg/kg respectively. The objective of this study was to investigate the mechanism of action underlying the therapeutic effects of HCP in UC through omics analysis method. A total of 724 different metabolites and 246 differential lipids were identified. Through metabolomic analysis, six metabolic pathways including the linoleic acid metabolic pathway, caffeine metabolic pathway, mannose and fructose metabolic pathways, methyl histidine metabolic pathway and fatty acid biosynthesis, which were significantly associated with colon-related diseases. Subsequently, lipidomics analysis revealed that the metabolic pathways of α-linolenic and linoleic acid, fatty acid biosynthesis, and glycerolipid metabolism exhibited significant associations with serum lipid metabolism. These findings suggested that HCP had potential therapeutic effects in treating UC.

First Insights into the Fecal Metabolome of Healthy, Free-Roaming Giraffes (Giraffa camelopardalis): An Untargeted GCxGC/TOF-MS Metabolomics Study

BACKGROUND/OBJECTIVES

This study provides the first insights to the fecal metabolome of the giraffe (Giraffa camelopardalis). By using untargeted metabolomics via gas chromatography time-of-flight mass spectrometry (GCxGC/TOF-MS), this study primarily aims to provide results of the impact that external stimuli, such as supplemental feeding (SF) practices, seasonal variation and sex, might have on the fecal metabolome composition of healthy, free-roaming giraffes.

METHODS

Untargeted GCxGC/TOF-MS analysis was applied to the feces collected from thirteen giraffes (six males and seven females) from six different locations within the central Free State Province of South Africa over a period of two years. Statistical analysis of the generated data was used to identify the metabolites that were significantly different between the giraffes located in environments that provided SF and others where the giraffes only fed on the natural available vegetation. The same metabolomics analysis was used to investigate metabolite concentrations that were significantly different between the wet and dry seasons for a single giraffe male provided with SF over the two-year period, as well as for age and sex differences.

RESULTS

A total of 2042 features were detected from 26 giraffe fecal samples. Clear variations between fecal metabolome profiles were confirmed, with higher levels of amino acid-related and carbohydrate-related metabolites for giraffes receiving SF. In addition, a separation between the obtained profiles of samples collected from a single adult male giraffe during the wet and dry seasons was identified. Differences, such as higher levels of carbohydrate-related metabolites and organic compounds during the wet season were noted. Distinct variations in profiles were also identified for the metabolites from fecal samples collected from the six males and seven females, with higher concentrations in carbohydrate-related metabolites and alkanes for female giraffes comparatively.

CONCLUSIONS

This is the first study to investigate the composition of the fecal metabolome of free-roaming giraffes, as well as the effects that external factors, such as environmental exposures, feeding practices, seasonal variations, age and sex, have on it. This novel use of fecal metabolomics assists in developing non-invasive techniques to determine giraffe populations' health that do not require additional stressors such as capture, restraint and blood collection. Ultimately, such non-invasive advances are beneficial towards the conservation of wildlife species on a larger scale.

The human volatilome meets cancer diagnostics: past, present, and future of noninvasive applications

BACKGROUND

Cancer is a significant public health problem, causing dozens of millions of deaths annually. New cancer screening programs are urgently needed for early cancer detection, as this approach can improve treatment outcomes and increase patient survival. The search for affordable, noninvasive, and highly accurate cancer detection methods revealed a valuable source of tumor-derived metabolites in the human metabolome through the exploration of volatile organic compounds (VOCs) in noninvasive biofluids.

AIM OF REVIEW

This review discusses volatilomics-based approaches for cancer detection using noninvasive biomatrices (breath, saliva, skin secretions, urine, feces, and earwax). We presented the historical background, the latest approaches, and the required stages for clinical validation of volatilomics-based methods, which are still lacking in terms of making noninvasive methods available and widespread to the population. Furthermore, insights into the usefulness and challenges of volatilomics in clinical implementation steps for each biofluid are highlighted.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We outline the methodologies for using noninvasive biomatrices with up-and-coming clinical applications in cancer diagnostics. Several challenges and advantages associated with the use of each biomatrix are discussed, aiming at encouraging the scientific community to strengthen efforts toward the necessary steps to speed up the clinical translation of volatile-based cancer detection methods, as well as discussing in favor of (i) hybrid applications (i.e., using more than one biomatrix) to describe metabolite modulations that can be "cancer volatile fingerprints" and (ii) in multi-omics approaches integrating genomics, transcriptomics, and proteomics into the volatilomic data, which might be a breakthrough for diagnostic purposes, onco-pathway assessment, and biomarker validations.

Metabolomics-based analysis of the diatom Cheatoceros tenuissimus combining NMR and GC-MS techniques

Metabolomics, a recent addition to omics sciences, studies small molecules across plants, animals, humans, and marine organisms. Nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GC-MS) are widely used in those studies, including microalgae metabolomics. NMR is non-destructive and highly reproducible but has limited sensitivity, which could be supplemented by joining GC-MS analysis. Extracting metabolites from macromolecules requires optimization for trustworthy results. Different extraction methods yield distinct profiles, emphasizing the need for optimization. The results indicated that the optimized extraction procedure successfully identified NMR and GC-MS-based metabolites in MeOH, CHCl3, and H2O extraction solvents. The findings represented the spectral information related to carbohydrates, organic molecules, and amino acids from the water-soluble metabolites fraction and a series of fatty acid chains, lipids, and sterols from the lipid fraction. Our study underscores the benefit of combining NMR and GC-MS techniques to comprehensively understand microalgae metabolomes, including high and low metabolite concentrations and abundances.•In this study, we focused on optimizing the extraction procedure and combining NMR and GC-MS techniques to overcome the low NMR sensitivity and the different detected range limits of NMR and GC-MS.•We explored metabolome diversity in a tropical strain of the small cells' diatom Cheatoceros tenuissimus.

Microbiome metabolite quantification methods enabling insights into human health and disease

Many of the health-associated impacts of the microbiome are mediated by its chemical activity, producing and modifying small molecules (metabolites). Thus, microbiome metabolite quantification has a central role in efforts to elucidate and measure microbiome function. In this review, we cover general considerations when designing experiments to quantify microbiome metabolites, including sample preparation, data acquisition and data processing, since these are critical to downstream data quality. We then discuss data analysis and experimental steps to demonstrate that a given metabolite feature is of microbial origin. We further discuss techniques used to quantify common microbial metabolites, including short-chain fatty acids (SCFA), secondary bile acids (BAs), tryptophan derivatives, N-acyl amides and trimethylamine N-oxide (TMAO). Lastly, we conclude with challenges and future directions for the field.

Untargeted Metabolomic Profiling of Aqueous and Lyophilized Pooled Human Feces from Two Diet Cohorts Using Two-Dimensional Gas Chromatography Coupled with Time-of-Flight Mass Spectrometry

The metabolic profiles of human feces are influenced by various genetic and environmental factors, which makes feces an attractive biosample for numerous applications, including the early detection of gut diseases. However, feces is complex, heterogeneous, and dynamic with a significant live bacterial biomass. With such challenges, stool metabolomics has been understudied compared to other biospecimens, and there is a current lack of consensus on methods to collect, prepare, and analyze feces. One of the critical steps required to accelerate the field is having a metabolomics stool reference material available. Fecal samples are generally presented in two major forms: fecal water and lyophilized feces. In this study, two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) was used as an analytical platform to characterize pooled human feces, provided by the National Institute of Standards and Technology (NIST) as Research-Grade Test Materials. The collected fecal samples were derived from eight healthy individuals with two different diets: vegans and omnivores, matched by age, sex, and body mass index (BMI), and stored as fecal water and lyophilized feces. Various data analysis strategies were presented to determine the differences in the fecal metabolomic profiles. The results indicate that the sample storage condition has a major influence on the metabolic profiles of feces such that the impact from storage surpasses the metabolic differences from the diet types. The findings of the current study would contribute towards the development of a stool reference material.

Metabolite profiling analysis of hepatitis B virus-induced liver cirrhosis patients with minimal hepatic encephalopathy using gas chromatography-time-of-flight mass spectrometry and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry

This study used gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) and ultra-performance liquid chromatography-quadrupole TOFMS (UPLC-QTOFMS) metabonomic analytical techniques in combination with bioinformatics and pattern recognition analysis methods to analyze the serum metabolite profiling of hepatitis B virus (HBV)-induced liver cirrhosis patients with minimal hepatic encephalopathy (MHE), to find the specific biomarkers of MHE, to reveal the pathogenesis of MHE, and to determine a promising approach for early diagnosis of MHE. Serum samples of 100 normal controls (NC group), 29 HBV-induced liver cirrhosis patients with MHE (MHE group), and 24 HBV-induced liver cirrhosis patients without MHE [comprising 12 cases of compensated cirrhosis (CS group) and 12 cases of decompensated cirrhosis (DS group)] were collected and employed into GC-TOFMS and UPLC-QTOFMS platforms for serum metabolite detection; the outcome data were then analyzed using principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA). There were no significant differential metabolites between the NC group and the CS group. A series of key differential metabolites were detected. According to the variable influence in projection values and P-values, 60 small-molecule metabolites were considered to be dysregulated in the MHE group (compared to the NC group); 27 of these 60 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 4, marked in bold); 66 small-molecule metabolites were considered to be dysregulated in the DS group (compared to the NC group); 34 of these 66 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 5, marked in bold). According to the fold-change values, 9 of these 27 metabolites, namely valine, oxalic acid, erythro-sphingosine, 4,7,10,13,16,19-docosahexaenoic acid, isoleucine, allo-isoleucine, thyroxine, rac-octanoyl carnitine, and tocopherol (vitamin E), were downregulated in the MHE group (compared to the NC group); the other 18, namely adenine, glycochenodeoxycholic acid, fucose, allothreonine, glycohyocholic acid, glycoursodeoxycholic acid, tyrosine, taurocheno-deoxycholate, phenylalanine, 2-hydroxy-3-methyl-butanoic acid, hydroxyacetic acid, taurocholate, sorbitol, rhamnose, tauroursodeoxycholate, tolbutamide, pyroglutamic acid, and malic acid, were upregulated; 6 of these 34 metabolites were downregulated in the DS group (compared to the NC group), and the other 28 were upregulated, as shown in Table 5. (a) GC-TOFMS and UPLC-QTOFMS metabonomic analytical platforms can detect a range of metabolites in the serum; this might be of great help to study the pathogenesis of MHE and may provide a new approach for the early diagnosis of MHE. (b) Metabonomics analysis in combination with pattern recognition analysis might have great potential to distinguish the HBV-induced liver cirrhosis patients who have MHE from the normal healthy population and HBV-induced liver cirrhosis patients without MHE.

Evaluation of fresh, frozen, and lyophilized fecal samples by SPME and derivatization methods using GC×GC-TOFMS

INTRODUCTION

Feces is a highly complex matrix containing thousands of metabolites. It also contains live bacteria and enzymes, and does not have a static chemistry. Consequently, proper control of pre-analytical parameters is critical to minimize unwanted variations in the samples. However, no consensus currently exists on how fecal samples should be stored/processed prior to analysis.

OBJECTIVE

The effects of sample handling conditions on fecal metabolite profiles and abundances were examined using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS).

METHODS

Solid-phase microextraction (SPME) and derivatization via trimethylsilylation (TMS) were employed as complementary techniques to evaluate fresh, frozen, and lyophilized fecal samples with expanded coverage of the fecal metabolome. The total number of detected peaks and the signal intensities were compared among the different handling conditions.

RESULTS

Our analysis revealed that the metabolic profiles of fecal samples depend greatly on sample handling and processing conditions, which had a more pronounced effect on results obtained by SPME than by TMS derivatization. Overall, lyophilization resulted in a greater amount of total and class-specific metabolites, which may be attributed to cell lysis and/or membrane disintegration.

CONCLUSIONS

A comprehensive comparison of the sample handling conditions provides a deeper understanding of the physicochemical changes that occur within the samples during freezing and lyophilization. Based on our results, snap-freezing at -80 °C would be preferred over lyophilization for handling samples in the field of fecal metabolomics as this imparts the least change from the fresh condition.

Metabonomics Study in Mice With Learning and Memory Impairment on the Intervention of Essential Oil Extracted From Cinnamomum camphora Chvar. Borneol

Our objective was to explore the mechanism of essential oil that was extracted from Cinnamomum camphora chvar. Borneol (Borneol essential oil) for improving learning and memory impairment in mice. Brain tissue and plasma samples of a normal group, a model group, a Borneol essential oil group and a reference group were detected using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) in order to find differential metabolites and analyze metabolic pathways. Results showed that there were 11 different metabolites --including glycine and azelaic acid --in plasma samples, and that there were 26 different metabolites--including adenine and aspartic acid --in brain tissue samples. These metabolites are involved in phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, alanine, aspartate and glutamate metabolism, arginine biosynthesis, beta-alanine metabolism, glyoxylate acid and dicarboxylate metabolism, and aminoacyl-tRNA biosynthesis. Thus, Borneol essential oil may improve learning and memory impairment by regulating amino acid metabolism and/or neurotransmitter changes.

Lizhong Decoction () Ameliorates Ulcerative Colitis in Mice via Regulation of Plasma and Urine Metabolic Profiling

OBJECTIVE

To elucidate the mechanism of Lizhong Decoction (LZD, ) in treating dextran sodium sulfate (DSS)-induced colitis in mice based on metabonomics.

METHODS

Thirty-six mice were randomly divided into 6 groups, including normal, model, low- (1.365 g/kg), medium- (4.095 g/kg) and high dose (12.285 g/kg) LZD and salazosulfadimidine (SASP) groups, 6 mice in each group. Colitis model mice were induced by DSS admistration for 7 days, and treated with low, medium and high dose LZD extract and positive drug SASP. Metabolic comparison of DSS-induced colitis and normal mice was investigated by using ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass (UPLC-Q-TOF/MS) combined with Metabolynx™ software.

RESULTS

The metabolic profiles of plasma and urine in colitis mice were distinctly ameliorated after LZD treatment (P<0.05). Potential biomarkers (9 in serum and 4 in urine) were screened and tentatively identified. The endogenous metabolites were mainly involved in primary bile acid, sphingolipid, linoleic acid, arachidonic acid, amino acids (alanine, aspartate, and glutamate), butanoate and glycerophospholipid metabolism in plasma, and terpenoid backbone biosynthesis, glycerophospholipid and tryptophan metabolism in urine. After LZD treatment, these markers notably restored to normal levels.

CONCLUSIONS

The study revealed the underlying mechanism of LZD on amelioration of ulcerative colitis based on metabonomics, which laid a foundation for further exploring the pathological and physiological mechanism, early diagnosis, and corresponding drug development of colitis.

Salvia miltiorrhiza and the Volatile of Dalbergia odorifera Attenuate Chronic Myocardial Ischemia Injury in a Pig Model: A Metabonomic Approach for the Mechanism Study

Salvia miltiorrhiza (SM) coupled with Dalbergia odorifera (DO) has been used to relieve cardiovascular diseases in China for many years. Our previous studies have integrated that SM—the volatile oil of DO (SM-DOO)—has a cardioprotective effect on chronic myocardial ischemia based on a pharmacological method, but the cardioprotective mechanism has not been elucidated completely in the metabonomic method. In the present study, a metabonomic method based on high-performance liquid chromatography time-of-flight mass spectrometry (HPLC-Q-TOF-MS) was performed to evaluate the effects of SM-DOO on chronic myocardial ischemia induced by an ameroid constrictor, which was placed on the left anterior descending coronary artery (LAD) of pigs. Pigs were divided into three groups: sham, model, and SM-DOO group. With multivariate analysis, a clear cluster among the different groups was obtained and the potential biomarkers were recognized. These biomarkers were mainly related to energy metabolism, glucose metabolism, and fatty acid metabolism. Furthermore, the protein expressions of phosphorylated AMP-activated protein kinase (p-AMPK) and glucose transporter-4 (GLUT4) were significantly upregulated by SM-DOO. The result indicated that SM-DOO could regulate the above biomarkers and metabolic pathways, especially energy metabolism and glucose metabolism. By analyzing and verifying the biomarkers and metabolic pathways, further understanding of the cardioprotective effect of SM-DOO with its mechanism was evaluated. Metabonomic is a reliable system biology approach for understanding the cardioprotective effects of SM-DOO on chronic myocardial ischemia and elucidating the mechanism underlying this protective effect.

Metabolic profiles of oligosaccharides derived from four microbial polysaccharides by faecal inocula from type 2 diabetes patients

In vitro digestion of curdlan oligosaccharides (COSs), pullulan oligosaccharides (POSs), xanthan gum oligosaccharides (XGOSs) and gellan gum oligosaccharides (GGOSs) was investigated. These four oligosaccharides showed resistance to simulated saliva and gastric and small intestinal fluid. In further fermentation with faecal microbiota from healthy subjects and type 2 diabetes (T2D) patients, COS fermentation significantly increased the abundance of Bifidobacterium spp. and Lactobacillus spp. and the production of short-chain fatty acids in healthy and T2D groups. Digestion of XGOS enhanced the growth of the Clostridium leptum subgroup and significantly increased butyric acid production in healthy and T2D groups. Sole fermentation with COS, POS, XGOS and GGOS exhibited different metabolic profiles between healthy and T2D groups, and more small molecule polyols were produced in the T2D group than in the healthy group. This study provides a novel perspective on the reconstruction of gut microbiota and metabolism by POS, COS, GGOS and XGOS intervention.

The Multiomics Analyses of Fecal Matrix and Its Significance to Coeliac Disease Gut Profiling

Gastrointestinal (GIT) diseases have risen globally in recent years, and early detection of the host’s gut microbiota, typically through fecal material, has become a crucial component for rapid diagnosis of such diseases. Human fecal material is a complex substance composed of undigested macromolecules and particles, and the processing of such matter is a challenge due to the unstable nature of its products and the complexity of the matrix. The identification of these products can be used as an indication for present and future diseases; however, many researchers focus on one variable or marker looking for specific biomarkers of disease. Therefore, the combination of genomics, transcriptomics, proteomics and metabonomics can give a detailed and complete insight into the gut environment. The proper sample collection, sample preparation and accurate analytical methods play a crucial role in generating precise microbial data and hypotheses in gut microbiome research, as well as multivariate data analysis in determining the gut microbiome functionality in regard to diseases. This review summarizes fecal sample protocols involved in profiling coeliac disease.

Linking Gut Microbiome and Lipid Metabolism: Moving beyond Associations

Various studies aiming to elucidate the role of the gut microbiome-metabolome co-axis in health and disease have primarily focused on water-soluble polar metabolites, whilst non-polar microbial lipids have received less attention. The concept of microbiota-dependent lipid biotransformation is over a century old. However, only recently, several studies have shown how microbial lipids alter intestinal and circulating lipid concentrations in the host, thus impacting human lipid homeostasis. There is emerging evidence that gut microbial communities play a particularly significant role in the regulation of host cholesterol and sphingolipid homeostasis. Here, we review and discuss recent research focusing on microbe-host-lipid co-metabolism. We also discuss the interplay of human gut microbiota and molecular lipids entering host systemic circulation, and its role in health and disease.

A rapid GC method coupled with quadrupole or time of flight mass spectrometry for metabolomics analysis

Gas chromatography-mass spectrometry (GC-MS) is an ideal tool for analyzing the intermediates of tricarboxylic acid cycle and glycolysis, sugars, organic acids and amino acids, etc. High-throughput metabolomics methods are required by large-scale clinical researches, and time of flight mass spectrometry (TOF MS) having fast scanning rate is preferable for rapid GC. Quadrupole MS (qMS) instruments have 95% market share, and their potential in rapid metabolomics is worth being studied. In this work, a within 15-min GC program was established and matched by qMS scanning for plasma metabolome analysis after N-methyl-N-(trimethylsilyl)-trifluoroacetamide derivatization. Compared to the longer-time program GC-qMS method, the rapid GC-qMS method had nearly no metabolome information loss, and it had excellent profile performance in repeatability, intra-day and inter-day precision, sampling range, linearity and extraction recovery. Compared to TOF MS, qMS achieved similar results in investigating lung cancer serum metabolic disruptions. Partial least squares-discriminant analysis revealed that the two datasets acquired by qMS and TOF MS had very similar model parameters, and most of top ranked differential metabolites were the same. This study provides a rapid and economical GC-qMS metabolomics method for researchers. Still, MS having faster scanning rate and higher sensitivity are recommended, if possible, to detect more small peaks and some co-eluted peaks.

Sample pre-treatment procedures for the omics analysis of human gut microbiota: Turning points, tips and tricks for gene sequencing and metabolomics

The connection between gut microbiota and human health is becoming increasingly relevant and the number of groups working in this field is constantly growing. In this context, from high-throughput gene sequencing to metabolomics analysis, the omics technologies have contributed enormously to unveil the secret crosstalk between us and our microbes. All the omics technologies produce a great amount of information, and processing this information is time-consuming and expensive. For this reason, a correct experimental design and a careful pre-analytical planning are crucial. To study the human gut microbiota, faeces are the sample of choice. Faecal material is complex, and procedures for collecting and preserving faeces are not well-established. Furthermore, increasing evidence suggests that multiple confounding factors, such as antibiotics consumption, mode of delivery, diet, aging and several diseases and disorders can alter the composition and functionality of the microbiota. This review is focused on the discussion of critical general issues during the pre-analytical planning, from patient handling to faeces sampling, including collection procedures, transport, storage conditions and possible pre-treatments, which are critical for a successful research in omics with a special attention to metabolomics and gene sequencing. We also point out that the adoption of standard operating procedures in the field is needed to guarantee accuracy and reproducibility of results.

A Review of GC-Based Analysis of Non-Invasive Biomarkers of Colorectal Cancer and Related Pathways

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the world. In Europe, it is the second most common cause of cancer-related deaths. With the advent of metabolomics approaches, studies regarding the investigation of metabolite profiles related to CRC have been conducted, aiming to serve as a tool for early diagnosis. In order to provide further information about the current status of this field of research, 21 studies were systematically reviewed, regarding their main findings and analytical aspects. A special focus was given to the employment of matrices obtained non-invasively and the use of gas chromatography as the analytical platform. The relationship between the reported volatile and non-volatile biomarkers and CRC-related metabolic alterations was also explored, demonstrating that many of these metabolites are connected with biochemical pathways proven to be involved in carcinogenesis. The most commonly reported CRC indicators were hydrocarbons, aldehydes, amino acids and short-chain fatty acids. These potential biomarkers can be associated with both human and bacterial pathways and the analysis based on such species has the potential to be applied in the clinical practice as a low-cost screening method.

The role of gut microbiota (GM) and GM-related metabolites in diabetes and obesity. A review of analytical methods used to measure GM-related metabolites in fecal samples with a focus on metabolites' derivatization step

Disruption of gut microbiota (GM) composition is increasingly related to the pathogenesis of various metabolic diseases. Additionally, GM is responsible for the production and transformation of metabolites involved in the development of metabolic disorders, such as obesity and type 2 diabetes mellitus (T2DM). The current state of knowledge regarding the composition of GM and GM-related metabolites in relation to the progress and development of obesity and T2DM is presented in this review. To understand the relationships between GM-related metabolites and the development of metabolic disorders, their accurate qualitative and quantitative measurement in biological samples is needed. Feces represent a valuable biological matrix which composition may reflect the health status of the lower gastrointestinal tract and the whole organism. Mass spectrometry (MS), mainly in combination with gas chromatography (GC) or liquid chromatography (LC), is commonly used to measure fecal metabolites. However, profiling metabolites in such a complex matrix as feces is challenging from both analytical chemistry and biochemistry standpoints. Chemical derivatization is one of the most effective methods used to overcome these problems. In this review, we provide a comprehensive summary of the derivatization methods of GM-related metabolites prior to GC-MS or LC-MS analysis, which have been published in the last five years (2015-2020). Additionally, analytical methods used for the analysis of GM-related metabolites without the derivatization step are also presented.

Important Considerations for Sample Collection in Metabolomics Studies with a Special Focus on Applications to Liver Functions

Metabolomics has found numerous applications in the study of liver metabolism in health and disease. Metabolomics studies can be conducted in a variety of biological matrices ranging from easily accessible biofluids such as urine, blood or feces, to organs, tissues or even cells. Sample collection and storage are critical steps for which standard operating procedures must be followed. Inappropriate sample collection or storage can indeed result in high variability, interferences with instrumentation or degradation of metabolites. In this review, we will first highlight important general factors that should be considered when planning sample collection in the study design of metabolomic studies, such as nutritional status and circadian rhythm. Then, we will discuss in more detail the specific procedures that have been described for optimal pre-analytical handling of the most commonly used matrices (urine, blood, feces, tissues and cells).

Describing the fecal metabolome in cryogenically collected samples from healthy participants

The chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools. Frozen stool samples were collected from 10 healthy volunteers and cryogenically drilled in four areas along the specimen. Polar metabolites were analyzed using derivatization followed by two-dimensional gas chromatography and time of flight mass spectrometry. Lipids were detected using ultra high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry. 2326 metabolic features were detected. Out of a total of 298 metabolites that were annotated we report here 185 that showed a technical variation of x < 30%. These metabolites included amino acids, fatty acid derivatives, carboxylic acids and phenolic compounds. Lipids predominantly belonged to the groups of diacylglycerols, triacylglycerols and ceramides. Metabolites varied between sampling areas, some were broadly homogeneous, others varied 80%. A LASSO-computed network using metabolites present in all areas showed two main clusters describing the system, DAG lipids and phenyllactic acid. In feces from healthy participants, the main groups detected were phenolic compounds, ceramides, diacylglycerols and triacylglycerols.

Metabolomic profile of diabetic retinopathy: a GC-TOFMS-based approach using vitreous and aqueous humor

AIM

To identify the potential metabolite markers in diabetic retinopathy (DR) by using gas chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS).

METHODS

GC-TOFMS spectra were acquired from vitreous and aqueous humor (AH) samples of patients with DR and non-diabetic participants. Comparative analysis was used to elucidate the distinct metabolites of DR. Metabolic pathway was employed to explicate the metabolic reprogramming pathways involved in DR. Logistic regression and receiver-operating characteristic analyses were carried out to select and validate the biomarker metabolites and establish a therapeutic model.

RESULTS

Comparative analysis showed a clear separation between disease and control groups. Eight differentiating metabolites from AH and 15 differentiating metabolites from vitreous were highlighted. Out of these 23 metabolites, 11 novel metabolites have not been detected previously. Pathway analysis identified nine pathways (three in AH and six in vitreous) as the major disturbed pathways associated with DR. The abnormal of gluconeogenesis, ascorbate-aldarate metabolism, valine-leucine-isoleucine biosynthesis, and arginine-proline metabolism might weigh the most in the development of DR. The AUC of the logistic regression model established by D-2,3-Dihydroxypropanoic acid, isocitric acid, fructose 6-phosphate, and L-Lactic acid in AH was 0.965. The AUC established by pyroglutamic acid and pyruvic acid in vitreous was 0.951.

CONCLUSIONS

These findings have expanded our understanding of identified metabolites and revealed for the first time some novel metabolites in DR. These results may provide useful information to explore the mechanism and may eventually allow the development of metabolic biomarkers for prognosis and novel therapeutic strategies for the management of DR.

Freeze-drying enables homogeneous and stable sample preparation for determination of fecal short-chain fatty acids

BACKGROUND

The analysis methods for fecal short-chain fatty acids (SCFAs) have evolved considerably. Recently, the role of SCFAs in gastrointestinal physiology and their association with intestinal microbiota and disease were reported. However, the intra-fecal variability and storage stability of SCFAs have not been extensively investigated. The aim of this study was to understand the limitations of the measurement of SCFAs in crude feces and develop a useful pre-examination procedure using the freeze-drying technique.

METHODS

SCFAs in crude feces, obtained from healthy volunteers, and freeze-dried feces were determined by derivatization with isobutyl chloroformate, followed by liquid-liquid extraction with hexane, and separation and analysis using gas chromatography-mass spectrometry.

RESULTS

Among the SCFAS, the maximum intra-fecal variability was observed for iso-butyrate (coefficient of variation of 37.7%), but the freeze-drying procedure reduced this variability (coefficient of variation of 7.9%). Similar improvements were also observed for other SCFAs. Furthermore, significant decreases in the SCFA amounts were observed with storage at 4 °C for 24 h.

CONCLUSIONS

The freeze-drying procedure affords fecal SCFA stability, even with storage at room temperature for 3 d. The freeze-drying procedure allows reliable SCFA measurements without labour-intensive processes. Therefore, the freeze-drying procedure can be applied in basic, clinical, and epidemiological studies.

Metabolomic Profile of Posner-Schlossman Syndrome: A Gas Chromatography Time-of-Flight Mass Spectrometry-Based Approach Using Aqueous Humor

The Posner-Schlossman syndrome (PSS) is a disease with clinically recurrent unilateral anterior uveitis with markedly elevated intraocular pressure (IOP) and subsequent progression to optic neuropathy. Retrospective studies have reported increased annual incidence of PSS, especially in China. While currently, the clinical management of PSS is still challenging. Metabolomics is considered to be a sensitive approach for the development of novel targeted therapeutics because of its direct elucidation of pathophysiological mechanisms. Therefore, we adopted gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) technology-based non-targeted metabolomics approach to measure comprehensive metabolic profiles of aqueous humor (AH) samples obtained from patients with PSS, with an aim to demonstrate the underlying pathophysiology, identify potential biomarkers specific to PSS, and develop effective treatment strategies. A comparative analysis was used to indicate the distinct metabolites of PSS. Pathway analysis was conducted using MetaboAnalyst 4.0 to explore the metabolic reprogramming pathways involved in PSS. Logistic regression and receiver-operating characteristic (ROC) analyses were employed to evaluate the diagnostic capability of selected metabolites. Comparative analysis revealed a clear separation between PSS and control groups. Fourteen novel differentiating metabolites from AH samples obtained from patients with PSS were highlighted. Pathway analysis identified 11 carbohydrate, amino acid metabolism and energy metabolism pathways as the major disturbed pathways associated with PSS. The abnormal lysine degradation metabolism, valine-leucine-isoleucine biosynthesis, and citrate circle were considered to weigh the most in the development of PSS. The ROC analysis implied that the combination of glycine and homogentisic acid could serve as potential biomarkers for the discrimination of control and PSS groups. In conclusion, these results revealed for the first time the identity of important metabolites and pathways contributing to the development/progression of PSS, enabled the better understanding of the mechanism of PSS, and might lead to the development of metabolic biomarkers and novel therapeutic strategies to restrict the development/progression of PSS.

Metabolomics-based approach to explore growth phase-dependent markers in cultured diatom Chaetoceros tenuissimus

Chaetoceros tenuissimus is a cosmopolitan marine diatom whose metabolism has been little investigated. In this study, we examined the alterations of the metabolite profile between different growth phases (exponential and stationary phase) in cultured C. tenuissimus and identified growth phase-dependent candidate marker metabolite. First, the preparation methodology was optimized, focusing on extraction solvent. Metabolites of the cultured diatom (exponential phase 2.4 × 10⁶ cells/mL, stationary phase 3.1 × 10⁶ cells/mL) were extracted using two solvents with different constituents (solvent 1, methanol:H₂O:chloroform = 5:2:2; solvent 2, methanol:ethanol:chloroform = 1:3:1). Gas chromatography mass spectrometry (GC/MS)-based metabolomics successfully detected 43 water-soluble metabolites in both solvents. The metabolic features were dependent on the growth phase: amino acid levels were higher in the exponential phase, whereas sugars and alcohols were more abundant in the stationary phase. Solvent 1 was superior in the recovery of the candidate metabolite that had a retention time of 18.13 min and predominantly contributed to discrimination between the growth phases; the metabolite level was higher in the stationary phase than in the exponential phase. The candidate metabolite was identified as mannonic acid by using GC/MS and liquid chromatography tandem mass spectrometry. Higher levels of mannonic acid during the stationary phase were also observed in other three diatom species. This study provides further insight into the use of metabolomics in the evaluation of physiological conditions of diatoms and suggests that mannonic acid content is a potential biomarker of the growth phase in cultured diatom cells.

Evaluating different extraction solvents for GC-MS based metabolomic analysis of the fecal metabolome of adult and baby giant pandas

The gut microbiome plays a fundamental role in host health and the fecal metabolome can be analysed to assess microbial activity and can be used as an intermediate phenotype monitoring the host-microbiome relationship. However, there is no established extraction protocol to study the fecal metabolome of giant pandas. The aim of this research is to optimize extraction of the fecal metabolome from adult and baby pandas for high throughput metabolomics analysis using gas chromatography-mass spectrometry (GC-MS). Fecal samples were collected from eight adult pandas and a pair of twin baby pandas. Six different extraction solvents were investigated and evaluated for their reproducibility, metabolite coverage, and extraction efficiency, particularly in relation to the biochemical compound classes such as amino acids, tricarboxylic acid (TCA) cycle intermediates, fatty acids, secondary metabolites, and vitamin and cofactors. Our GC-MS results demonstrated that the extraction solvents with isopropanol: acetonitrile: water (3:2:2 ratio) and 80% methanol were the most appropriate for studying the fecal metabolome of adult and baby giant pandas respectively. These extraction solvents can be used in future study protocols for the analysis of the fecal metabolome in giant pandas.

The unique composition of Indian gut microbiome, gene catalogue, and associated fecal metabolome deciphered using multi-omics approaches

BACKGROUND

Metagenomic studies carried out in the past decade have led to an enhanced understanding of the gut microbiome in human health; however, the Indian gut microbiome has not been well explored. We analyzed the gut microbiome of 110 healthy individuals from two distinct locations (North-Central and Southern) in India using multi-omics approaches, including 16S rRNA gene amplicon sequencing, whole-genome shotgun metagenomic sequencing, and metabolomic profiling of fecal and serum samples.

RESULTS

The gene catalogue established in this study emphasizes the uniqueness of the Indian gut microbiome in comparison to other populations. The gut microbiome of the cohort from North-Central India, which was primarily consuming a plant-based diet, was found to be associated with Prevotella and also showed an enrichment of branched chain amino acid (BCAA) and lipopolysaccharide biosynthesis pathways. In contrast, the gut microbiome of the cohort from Southern India, which was consuming an omnivorous diet, showed associations with Bacteroides, Ruminococcus, and Faecalibacterium and had an enrichment of short chain fatty acid biosynthesis pathway and BCAA transporters. This corroborated well with the metabolomics results, which showed higher concentration of BCAAs in the serum metabolome of the North-Central cohort and an association with Prevotella. In contrast, the concentration of BCAAs was found to be higher in the fecal metabolome of the Southern-India cohort and showed a positive correlation with the higher abundance of BCAA transporters.

CONCLUSIONS

The study reveals the unique composition of the Indian gut microbiome, establishes the Indian gut microbial gene catalogue, and compares it with the gut microbiome of other populations. The functional associations revealed using metagenomic and metabolomic approaches provide novel insights on the gut-microbe-metabolic axis, which will be useful for future epidemiological and translational researches.

Comprehensive analysis of pig feces metabolome by chromatographic techniques coupled to mass spectrometry in high resolution mode: Influence of sample preparation on the identification coverage

Pig feces is an interesting biological sample to be implemented in metabolomics experiments by virtue of the information that can be deduced from the interaction between host and microbiome. However, pig fecal samples have received scant attention, especially in untargeted metabolomic studies. In this research, an analytical strategy was planned to maximize the identification coverage of metabolites found in pig fecal samples. For this purpose, two complementary platforms such as LC-QTOF MS/MS and GC-TOF/MS were used. Concerning sample preparation six extractant solvents with different polarity grade were tested to evaluate the extraction performance and, in the particular case of GC-MS, two derivatization protocols were compared. A total number of 303 compounds by combination of all the extractants and analytical platforms were tentatively identified. The main identified families were amino acids, fatty acids and derivatives, carbohydrates and carboxylic acids. For GC-TOF/MS analysis, the recommended extractant is methanol, while methoxymation was required in the derivatization protocol since this step allows detecting the α-keto acids, which are direct markers of the microbiome status. Concerning LC-QTOF MS/MS analysis, a dual extraction approach with methanol (MeOH) or MeOH/water and ethyl acetate is proposed to enhance the detection of polar and non-polar metabolites.

Trial data of the anti-obesity potential of a high resistant starch diet for canines using Dodamssal rice and the identification of discriminating markers in feces for metabolic profiling

INTRODUCTION

Dodamssal rice (Oryza sativa L.) includes high levels of resistant starch (RS), which is a source of dietary fiber. Recently, there has been an increase in the prevalence of obesity in canines; however, the information regarding diet treatments for such a condition is inadequate.

OBJECTIVES

Targeted metabolic profiles in canine feces were performed to identify potential biomarkers of RS and demonstrate the effect and potential use of Dodamssal rice as an anti-obesity treatment.

METHODS

Study canines were divided into three groups and fed either a regular diet, high-fat diet (HFD), or high-fat diet with Dodamssal rice (DoHFD). Fecal metabolites were analyzed using gas chromatography time-of-flight mass spectrometry and a gas chromatography-flame ionization detector. Multivariate analyses were used to analyze and visualize the obtained data.

RESULTS

A total of 52 metabolites were detected in the canine feces. In addition, HFD group feces contained a significantly low level of C12:0. The DoHFD group feces had higher levels of 4-aminobutyric acid, glucose, and 3-hydroxybutyric acid compared to the other groups (p < 0.05).

CONCLUSION

For the first time, targeted metabolic profiling in the canine feces in response to three diets was performed. This metabolic profiling approach should be a useful tool to detect discriminating markers as well as assess the effect of diet compositions for anti-obesity treatment of canines. Furthermore, Dodamssal rice may possibly be used not only for canines, but also to treat obesity in other animals and humans.

Targeted UPLC-MS Metabolic Analysis of Human Faeces Reveals Novel Low-Invasive Candidate Markers for Colorectal Cancer

Low invasive tests with high sensitivity for colorectal cancer and advanced precancerous lesions will increase adherence rates, and improve clinical outcomes. We have performed an ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC-(TOF) MS)-based metabolomics study to identify faecal biomarkers for the detection of patients with advanced neoplasia. A cohort of 80 patients with advanced neoplasia (40 advanced adenomas and 40 colorectal cancers) and 49 healthy subjects were analysed in the study. We evaluated the faecal levels of 105 metabolites including glycerolipids, glycerophospholipids, sterol lipids and sphingolipids. We found 18 metabolites that were significantly altered in patients with advanced neoplasia compared to controls. The combinations of seven metabolites including ChoE(18:1), ChoE(18:2), ChoE(20:4), PE(16:0/18:1), SM(d18:1/23:0), SM(42:3) and TG(54:1), discriminated advanced neoplasia patients from healthy controls. These seven metabolites were employed to construct a predictive model that provides an area under the curve (AUC) median value of 0.821. The inclusion of faecal haemoglobin concentration in the metabolomics signature improved the predictive model to an AUC of 0.885. In silico gene expression analysis of tumour tissue supports our results and puts the differentially expressed metabolites into biological context, showing that glycerolipids and sphingolipids metabolism and GPI-anchor biosynthesis pathways may play a role in tumour progression.

Polysaccharides From Chrysanthemum morifolium Ramat Ameliorate Colitis Rats via Regulation of the Metabolic Profiling and NF-κ B/TLR4 and IL-6/JAK2/STAT3 Signaling Pathways

Studies have indicated that Chrysanthemum polysaccharides (CP) could prominently ameliorate colitis rats, but its possible mechanism remains unclear. In this study, the underlying mechanism of CP was explored by the metabolic profiling analysis and correlated signaling pathways. TNBS/ethanol induced colitis was used to investigate the intervention efficacy following oral administration of CP. The levels of cytokines such as TNF-α, IL-6, IFN-γ and IL-1β, and the activities of SOD, MPO, and MDA were determined. We also performed western-blot for p65, TLR4, p-JAK2, and STAT3 protein expression in the colon tissue to probe their mechanisms of correlated signaling pathways. What’s more, the metabolic changes in plasma and urine from colitis rats were investigated based on UPLC-Q-TOF/MS combined with Metabolynx^TM software. The potential biomarkers and metabolic pathways were also tentatively confirmed. The metabolic profiles of plasma and urine were clearly improved in model rats after oral administration of CP. Thirty-two (17 in serum and 15 in urine) potential biomarkers were identified. The endogenous metabolites were mainly involved in linoleic acid, retinol, arachidonic acid, glycerophospholipid and primary bile acid metabolism in plasma, and nicotinate and nicotinamide, ascorbate and aldarate, histidine and β-alanine metabolism in urine. After polysaccharides intervention, these markers turned back to normal level at some extent. Meanwhile, the elevated expression levels of pp65, TLR4, p-STAT3, and p-JAK2 were significantly decreased after treatment. Results suggested that CP would be a potential prebiotics for alleviation of TNBS-induced colitis. The study paved the way for the further exploration of the pathogenesis, early diagnosis and curative drug development of the colitis.

Preanalytical Processing and Biobanking Procedures of Biological Samples for Metabolomics Research: A White Paper, Community Perspective (for "Precision Medicine and Pharmacometabolomics Task Group"-The Metabolomics Society Initiative)

BACKGROUND

The metabolome of any given biological system contains a diverse range of low molecular weight molecules (metabolites), whose abundances can be affected by the timing and method of sample collection, storage, and handling. Thus, it is necessary to consider the requirements for preanalytical processes and biobanking in metabolomics research. Poor practice can create bias and have deleterious effects on the robustness and reproducibility of acquired data.

CONTENT

This review presents both current practice and latest evidence on preanalytical processes and biobanking of samples intended for metabolomics measurement of common biofluids and tissues. It highlights areas requiring more validation and research and provides some evidence-based guidelines on best practices.

SUMMARY

Although many researchers and biobanking personnel are familiar with the necessity of standardizing sample collection procedures at the axiomatic level (e.g., fasting status, time of day, "time to freezer," sample volume), other less obvious factors can also negatively affect the validity of a study, such as vial size, material and batch, centrifuge speeds, storage temperature, time and conditions, and even environmental changes in the collection room. Any biobank or research study should establish and follow a well-defined and validated protocol for the collection of samples for metabolomics research. This protocol should be fully documented in any resulting study and should involve all stakeholders in its design. The use of samples that have been collected using standardized and validated protocols is a prerequisite to enable robust biological interpretation unhindered by unnecessary preanalytical factors that may complicate data analysis and interpretation.

Gut metabolome meets microbiome: A methodological perspective to understand the relationship between host and microbe

It is well established that gut microbes and their metabolic products regulate host metabolism. The interactions between the host and its gut microbiota are highly dynamic and complex. In this review we present and discuss the metabolomic strategies to study the gut microbial ecosystem. We highlight the metabolic profiling approaches to study faecal samples aimed at deciphering the metabolic product derived from gut microbiota. We also discuss how metabolomics data can be integrated with metagenomics data derived from gut microbiota and how such approaches may lead to better understanding of the microbial functions. Finally, the emerging approaches of genome-scale metabolic modelling to study microbial co-metabolism and host-microbe interactions are highlighted.

Exploring the human microbiome from multiple perspectives: factors altering its composition and function

Our microbiota presents peculiarities and characteristics that may be altered by multiple factors. The degree and consequences of these alterations depend on the nature, strength and duration of the perturbations as well as the structure and stability of each microbiota. The aim of this review is to sketch a very broad picture of the factors commonly influencing different body sites, and which have been associated with alterations in the human microbiota in terms of composition and function. To do so, first, a graphical representation of bacterial, fungal and archaeal genera reveals possible associations among genera affected by different factors. Then, the revision of sequence-based predictions provides associations with functions that become part of the active metabolism. Finally, examination of microbial metabolite contents and fluxes reveals whether metabolic alterations are a reflection of the differences observed at the level of population structure, and in the last step, link microorganisms to functions under perturbations that differ in nature and aetiology. The utilisation of complementary technologies and methods, with a special focus on metabolomics research, is thoroughly discussed to obtain a global picture of microbiota composition and microbiome function and to convey the urgent need for the standardisation of protocols.

American Ginseng Attenuates Colitis-Associated Colon Carcinogenesis in Mice: Impact on Gut Microbiota and Metabolomics

Inflammatory bowel disease is a risk factor for colorectal cancer initiation and development. In this study, the effects of American ginseng on chemically induced colitis and colon carcinogenesis were evaluated using an azoxymethane (AOM)/dextran sulfate sodium (DSS) mouse model. During the acute phase on day 15, the oral administration of ginseng (15 and 30 mg/kg/day) significantly suppressed AOM/DSS-induced colitis, as demonstrated by the disease activity index and colon tissue histology. During the chronic phase in week 13, AOM/DSS-induced tumor multiplicity was significantly suppressed by ginseng. Ginseng significantly attenuated the increase of inflammatory cytokines, such as IL1α, IL1β, IL6, G-CSF, and GM-CSF. Serum metabolomics data in the PCA plots showed good separation between the AOM/DSS model and ginseng-treated mice, and the most important endogenous metabolite changes were identified. The 16S rRNA data showed that after AOM/DSS, the microbiome community in the model group was obviously changed, and ginseng inhibited these changes. Fecal metabolomics analysis supported these findings. In conclusion, oral ginseng significantly decreased AOM/DSS-induced colitis and colon carcinogenesis by inhibiting inflammatory cytokines and restoring the metabolomics and microbiota profiles accordingly. Selective endogenous small molecules could be used as biomarkers to elucidate the effects of ginseng treatment. Cancer Prev Res; 9(10); 803-11. ©2016 AACR.

Sample preparation optimization in fecal metabolic profiling

Metabolomic analysis of feces can provide useful insight on the metabolic status, the health/disease state of the human/animal and the symbiosis with the gut microbiome. As a result, recently there is increased interest on the application of holistic analysis of feces for biomarker discovery. For metabolomics applications, the sample preparation process used prior to the analysis of fecal samples is of high importance, as it greatly affects the obtained metabolic profile, especially since feces, as matrix are diversifying in their physicochemical characteristics and molecular content. However there is still little information in the literature and lack of a universal approach on sample treatment for fecal metabolic profiling. The scope of the present work was to study the conditions for sample preparation of rat feces with the ultimate goal of the acquisition of comprehensive metabolic profiles either untargeted by NMR spectroscopy and GC-MS or targeted by HILIC-MS/MS. A fecal sample pooled from male and female Wistar rats was extracted under various conditions by modifying the pH value, the nature of the organic solvent and the sample weight to solvent volume ratio. It was found that the 1/2 (w_f/v_s) ratio provided the highest number of metabolites under neutral and basic conditions in both untargeted profiling techniques. Concerning LC-MS profiles, neutral acetonitrile and propanol provided higher signals and wide metabolite coverage, though extraction efficiency is metabolite dependent.

A GC-MS Based Metabonomics Study of Rheumatoid Arthritis and the Interventional Effects of the Simiaowan in Rats

Simiaowan (SMW) is a famous Chinese prescription widely used in clinical treatment of rheumatoid arthritis (RA). The aim of the present study is to determine novel biomarkers to increase the current understanding of RA mechanisms, as well as the underlying therapeutic mechanism of SMW, in RA-model rats. Plasma extracts from control, RA model, and SMW-treated rats were analyzed by gas chromatography coupled with mass spectrometry (GC-MS). An orthogonal partial least-square discriminant analysis (OPLS-DA) model was created to detect metabolites that were expressed in significantly different amounts between the RA model and the control rats and investigate the therapeutic effect of SMW. Metabonomics may prove to be a valuable tool for determining the efficacy of complex traditional prescriptions.